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Pang T, Ding N, Zhao Y, Zhao J, Yang L, Chang S. Novel genetic loci of inhibitory control in ADHD and healthy children and genetic correlations with ADHD. Prog Neuropsychopharmacol Biol Psychiatry 2024; 132:110988. [PMID: 38430954 DOI: 10.1016/j.pnpbp.2024.110988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 11/26/2023] [Accepted: 02/28/2024] [Indexed: 03/05/2024]
Abstract
Cumulative evidence has showed the deficits of inhibitory control in patients with attention deficit hyperactivity disorder (ADHD), which is considered as an endophenotype of ADHD. Genetic study of inhibitory control could advance gene discovery and further facilitate the understanding of ADHD genetic basis, but the studies were limited in both the general population and ADHD patients. To reveal genetic risk variants of inhibitory control and its potential genetic relationship with ADHD, we conducted genome-wide association studies (GWAS) on inhibitory control using three datasets, which included 783 and 957 ADHD patients and 1350 healthy children. Subsequently, we employed polygenic risk scores (PRS) to explore the association of inhibitory control with ADHD and related psychiatric disorders. Firstly, we identified three significant loci for inhibitory control in the healthy dataset, two loci in the case dataset, and one locus in the meta-analysis of three datasets. Besides, we found more risk genes and variants by applying transcriptome-wide association study (TWAS) and conditional FDR method. Then, we constructed a network by connecting the genes identified in our study, leading to the identification of several vital genes. Lastly, we identified a potential relationship between inhibitory control and ADHD and autism by PRS analysis and found the direct and mediated contribution of the identified genetic loci on ADHD symptoms by mediation analysis. In conclusion, we revealed some genetic risk variants associated with inhibitory control and elucidated the benefit of inhibitory control as an endophenotype, providing valuable insights into the mechanisms underlying ADHD.
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Affiliation(s)
- Tao Pang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Ning Ding
- School of Psychology, Shaanxi Normal University and Shaanxi Provincial Key Research Center of Child Mental and Behavioral Health, Xi'an, China
| | - Yilu Zhao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Jingjing Zhao
- School of Psychology, Shaanxi Normal University and Shaanxi Provincial Key Research Center of Child Mental and Behavioral Health, Xi'an, China.
| | - Li Yang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.
| | - Suhua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences, Peking University, Beijing 100191, China.
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Xiang X, Wang D, Leng J, Li N, Wei C. Association of adiponectin and its receptor gene polymorphisms with the risk of coronary heart disease in northern Guangxi. Cytokine 2024; 178:156567. [PMID: 38489870 DOI: 10.1016/j.cyto.2024.156567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 02/06/2024] [Accepted: 03/01/2024] [Indexed: 03/17/2024]
Abstract
OBJECTIVE To investigate the association of circulating adiponectin (APN) level and single nucleotide polymorphisms (rs1501299 and rs266729) of the APN gene in the coronary heart disease (CHD) population of Northern Guangxi Province. METHODS Two hundred and sixty-three CHD patients and 235 healthy controls from our hospital from August 2018 to October 2020 were included in this study. ELISA was used to determine the serum APN concentration. PCR-RFLP and direct DNA sequencing were used to analyze the genotypes of APN gene rs1501299 G/T and rs266729 C/G single-nucleotide loci, their distribution differences between the two groups were compared and their correlation with APN concentration was analyzed. RESULTS The serum APN concentration in the CHD group was significantly lower than the control group (14.40(1.42-52.26) μg/mL vs. 29.40 (3.18-90.31) μg/mL, P < 0.001). There were statistically significant differences in the rs266729 genotype of APN single nucleotide locus between the two groups (P < 0.001). The dominant model and recessive model of rs266729 genotype showed that mutant homozygous GG genotype carriers significantly increased the risk of CHD in comparison with C allele carriers (CG + CC) (OR = 2.156, 95 %CI: 1.004-4.631, P = 0.049), and this effect was still significant after adjusting gender and age (OR = 2.695, 95 %CI 1.110-6.540, P = 0.028). In both the dominant and recessive models for rs1501299, ORs before and after adjustment for age and sex revealed no significant association with CHD, with ORs of 0.765 (95 % CI: 0.537-1.091, P = 0.139) and 0.718 (95 % CI: 0.466-1.106, P = 0.133) in the Dominant model, and ORs of 0.960 (95 % CI: 0.442-2.087, P = 0.918) and 0.613 (95 % CI: 0.239-1.570, P = 0.308) in the Recessive model, respectively. No statistically significant differences in APN concentrations across genotypes in both groups (P > 0.05), with chi-square values of 1.633 (control group) and 0.823 (CHD group) for rs1501299, and 1.354 (control group) and 0.618 (CHD group) for rs266729. CONCLUSIONS APN gene of rs266729 C/G single-nucleotide loci gene mutation can significantly increase the risk of CHD. There was no significant correlation between rs1501299 G/T single-nucleotide loci and CHD in Northern Guangxi populations.
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Affiliation(s)
- Xiaohua Xiang
- Department of Laboratory Medicine, Shenzhen Guangming District People's Hospital, Shenzhen 518106, Guangdong Province, China; Department of Laboratory Medicine, The Second Affiliated Hospital of Guilin Medical University, Guilin 541199, Guangxi Province, China.
| | - Di Wang
- Department of Laboratory Medicine, The Second Affiliated Hospital of Guilin Medical University, Guilin 541199, Guangxi Province, China
| | - Jun Leng
- Department of Laboratory Medicine, The Second Affiliated Hospital of Guilin Medical University, Guilin 541199, Guangxi Province, China
| | - Ning Li
- Department of Laboratory Medicine, The Second Affiliated Hospital of Guilin Medical University, Guilin 541199, Guangxi Province, China
| | - Chuandong Wei
- Department of Laboratory Medicine, The Second Affiliated Hospital of Guilin Medical University, Guilin 541199, Guangxi Province, China.
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Pisanu C, Congiu D, Meloni A, Paribello P, Patrinos GP, Severino G, Ardau R, Chillotti C, Manchia M, Squassina A. Dissecting the genetic overlap between severe mental disorders and markers of cellular aging: Identification of pleiotropic genes and druggable targets. Neuropsychopharmacology 2024; 49:1033-1041. [PMID: 38402365 DOI: 10.1038/s41386-024-01822-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 01/17/2024] [Accepted: 02/04/2024] [Indexed: 02/26/2024]
Abstract
Patients with severe mental disorders such as bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) show a substantial reduction in life expectancy, increased incidence of comorbid medical conditions commonly observed with advanced age and alterations of aging hallmarks. While severe mental disorders are heritable, the extent to which genetic predisposition might contribute to accelerated cellular aging is not known. We used bivariate causal mixture models to quantify the trait-specific and shared architecture of mental disorders and 2 aging hallmarks (leukocyte telomere length [LTL] and mitochondrial DNA copy number), and the conjunctional false discovery rate method to detect shared genetic loci. We integrated gene expression data from brain regions from GTEx and used different tools to functionally annotate identified loci and investigate their druggability. Aging hallmarks showed low polygenicity compared with severe mental disorders. We observed a significant negative global genetic correlation between MDD and LTL (rg = -0.14, p = 6.5E-10), and no significant results for other severe mental disorders or for mtDNA-cn. However, conditional QQ plots and bivariate causal mixture models pointed to significant pleiotropy among all severe mental disorders and aging hallmarks. We identified genetic variants significantly shared between LTL and BD (n = 17), SCZ (n = 55) or MDD (n = 19), or mtDNA-cn and BD (n = 4), SCZ (n = 12) or MDD (n = 1), with mixed direction of effects. The exonic rs7909129 variant in the SORCS3 gene, encoding a member of the retromer complex involved in protein trafficking and intracellular/intercellular signaling, was associated with shorter LTL and increased predisposition to all severe mental disorders. Genetic variants underlying risk of SCZ or MDD and shorter LTL modulate expression of several druggable genes in different brain regions. Genistein, a phytoestrogen with anti-inflammatory and antioxidant effects, was an upstream regulator of 2 genes modulated by variants associated with risk of MDD and shorter LTL. While our results suggest that shared heritability might play a limited role in contributing to accelerated cellular aging in severe mental disorders, we identified shared genetic determinants and prioritized different druggable targets and compounds.
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Affiliation(s)
- Claudia Pisanu
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy.
| | - Donatella Congiu
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Anna Meloni
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Pasquale Paribello
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - George P Patrinos
- Laboratory of Pharmacogenomics and Individualized Therapy, School of Health Sciences, Department of Pharmacy, University of Patras, Patras, Greece
- College of Medicine and Health Sciences, Department of Genetics and Genomics, United Arab Emirates University, Al‑Ain, Abu Dhabi, UAE
- Zayed Center for Health Sciences, United Arab Emirates University, Al‑Ain, Abu Dhabi, UAE
| | - Giovanni Severino
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Raffaella Ardau
- Unit of Clinical Pharmacology, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Caterina Chillotti
- Unit of Clinical Pharmacology, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Mirko Manchia
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
- Department of Pharmacology, Dalhousie University, Halifax, NS, Canada
| | - Alessio Squassina
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy.
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Liu H, Wang X, Feng H, Zhou S, Pan J, Ouyang C, Hu X. Obstructive sleep apnea and mental disorders: a bidirectional mendelian randomization study. BMC Psychiatry 2024; 24:304. [PMID: 38654235 DOI: 10.1186/s12888-024-05754-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 04/09/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Previous studies have reported associations between obstructive sleep apnea (OSA) and several mental disorders. However, further research is required to determine whether these associations are causal. Therefore, we evaluated the bidirectional causality between the genetic liability for OSA and nine mental disorders by using Mendelian randomization (MR). METHOD We performed two-sample bidirectional MR of genetic variants for OSA and nine mental disorders. Summary statistics on OSA and the nine mental disorders were extracted from the FinnGen study and the Psychiatric Genomics Consortium. The primary analytical approach for estimating causal effects was the inverse-variance weighted (IVW), with the weighted median and MR Egger as complementary methods. The MR Egger intercept test, Cochran's Q test, Rucker's Q test, and the MR pleiotropy residual sum and outlier (MR-PRESSO) test were used for sensitivity analyses. RESULT MR analyses showed that genetic liability for major depressive disorder (MDD) was associated with an increased risk of OSA (odds ratio [OR] per unit increase in the risk of MDD, 1.29; 95% CI, 1.11-1.49; P < 0.001). In addition, genetic liability for OSA may be associated with an increased risk of attention-deficit/hyperactivity disorder (ADHD) (OR = 1.26; 95% CI, 1.02-1.56; p = 0.032). There was no evidence that OSA is associated with other mental disorders. CONCLUSION Our study indicated that genetic liability for MDD is associated with an increased risk of OSA without a bidirectional relationship. Additionally, there was suggestive evidence that genetic liability for OSA may have a causal effect on ADHD. These findings have implications for prevention and intervention strategies targeting OSA and ADHD. Further research is needed to investigate the biological mechanisms underlying our findings and the relationship between OSA and other mental disorders.
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Affiliation(s)
- Heming Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, No.199, Donggang West Road, Chengguan District, 730000, Lanzhou, Gansu Province, China
| | - Xuemei Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, No.199, Donggang West Road, Chengguan District, 730000, Lanzhou, Gansu Province, China
| | - Hu Feng
- Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, No.199, Donggang West Road, Chengguan District, 730000, Lanzhou, Gansu Province, China
| | - Shengze Zhou
- Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, No.199, Donggang West Road, Chengguan District, 730000, Lanzhou, Gansu Province, China
| | - Jinhua Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, No.199, Donggang West Road, Chengguan District, 730000, Lanzhou, Gansu Province, China
| | - Changping Ouyang
- Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, No.199, Donggang West Road, Chengguan District, 730000, Lanzhou, Gansu Province, China
| | - Xiaobin Hu
- Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, No.199, Donggang West Road, Chengguan District, 730000, Lanzhou, Gansu Province, China.
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Jakwerth CA, Weckmann M, Illi S, Charles H, Zissler UM, Oelsner M, Guerth F, Omony J, Nemani SSP, Grychtol R, Dittrich AM, Skevaki C, Foth S, Weber S, Alejandre Alcazar MA, van Koningsbruggen-Rietschel S, Brock R, Blau S, Hansen G, Bahmer T, Rabe KF, Brinkmann F, Kopp MV, Chaker AM, Schaub B, von Mutius E, Schmidt-Weber CB. 17q21 Variants Disturb Mucosal Host Defense in Childhood Asthma. Am J Respir Crit Care Med 2024; 209:947-959. [PMID: 38064241 DOI: 10.1164/rccm.202305-0934oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 12/07/2023] [Indexed: 03/13/2024] Open
Abstract
Rationale: The strongest genetic risk factor for childhood-onset asthma, the 17q21 locus, is associated with increased viral susceptibility and disease-promoting processes.Objectives: To identify biological targets underlying the escalated viral susceptibility associated with the clinical phenotype mediated by the 17q21 locus.Methods: Genome-wide transcriptome analysis of nasal brush samples from 261 children (78 healthy, 79 with wheezing at preschool age, 104 asthmatic) within the ALLIANCE (All-Age-Asthma) cohort, with a median age of 10.0 (range, 1.0-20.0) years, was conducted to explore the impact of their 17q21 genotype (SNP rs72163891). Concurrently, nasal secretions from the same patients and visits were collected, and high-sensitivity mesoscale technology was employed to measure IFN protein levels.Measurements and Main Results: This study revealed that the 17q21 risk allele induces a genotype- and asthma/wheeze phenotype-dependent enhancement of mucosal GSDMB expression as the only relevant 17q21-encoded gene in children with preschool wheeze. Increased GSDMB expression correlated with the activation of a type-1 proinflammatory, cell-lytic immune, and natural killer signature, encompassing key genes linked to an IFN type-2-signature (IFNG, CXCL9, CXCL10, KLRC1, CD8A, GZMA). Conversely, there was a reduction in IFN type 1 and type 3 expression signatures at the mRNA and protein levels.Conclusions: This study demonstrates a novel disease-driving mechanism induced by the 17q21 risk allele. Increased mucosal GSDMB expression is associated with a cell-lytic immune response coupled with compromised airway immunocompetence. These findings suggest that GSDMB-related airway cell death and perturbations in the mucosal IFN signature account for the increased vulnerability of 17q21 risk allele carriers to respiratory viral infections during early life, opening new options for future biological interventions.The All-Age-Asthma (ALLIANCE) cohort is registered at www.clinicaltrials.gov (pediatric arm, NCT02496468).
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Affiliation(s)
- Constanze A Jakwerth
- Center of Allergy and Environment (ZAUM), Technical University and Helmholtz Center Munich, Munich, Germany
- Member of the German Center for Lung Research (DZL), Germany
| | - Markus Weckmann
- Member of the German Center for Lung Research (DZL), Germany
- Division of Epigenetics in Chronic Lung Disease, Priority Area Chronic Lung Diseases, Research Center Borstel-Leibniz Lung Center, Borstel, Germany
- Department of Pediatric Pneumology and Allergology, University Medical Center Schleswig-Holstein, Lübeck, Germany
- Airway Research Center North, Borstel, Lübeck, Kiel, Grosshansdorf, Germany
| | - Sabina Illi
- Member of the German Center for Lung Research (DZL), Germany
- Institute for Asthma and Allergy Prevention, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany
- Comprehensive Pneumology Center-Munich, Munich, Germany
| | - Helen Charles
- Center of Allergy and Environment (ZAUM), Technical University and Helmholtz Center Munich, Munich, Germany
- Member of the German Center for Lung Research (DZL), Germany
| | - Ulrich M Zissler
- Center of Allergy and Environment (ZAUM), Technical University and Helmholtz Center Munich, Munich, Germany
- Member of the German Center for Lung Research (DZL), Germany
| | - Madlen Oelsner
- Center of Allergy and Environment (ZAUM), Technical University and Helmholtz Center Munich, Munich, Germany
- Member of the German Center for Lung Research (DZL), Germany
| | - Ferdinand Guerth
- Center of Allergy and Environment (ZAUM), Technical University and Helmholtz Center Munich, Munich, Germany
- Member of the German Center for Lung Research (DZL), Germany
| | - Jimmy Omony
- Member of the German Center for Lung Research (DZL), Germany
- Institute for Asthma and Allergy Prevention, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany
- Comprehensive Pneumology Center-Munich, Munich, Germany
| | - Sai Sneha Priya Nemani
- Member of the German Center for Lung Research (DZL), Germany
- Department of Pediatric Pneumology and Allergology, University Medical Center Schleswig-Holstein, Lübeck, Germany
- Airway Research Center North, Borstel, Lübeck, Kiel, Grosshansdorf, Germany
| | - Ruth Grychtol
- Member of the German Center for Lung Research (DZL), Germany
- Department of Pediatric Pneumology, Allergology and Neonatology, Hannover Medical School, Hanover, Germany
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover, Hanover, Germany
| | - Anna-Maria Dittrich
- Member of the German Center for Lung Research (DZL), Germany
- Department of Pediatric Pneumology, Allergology and Neonatology, Hannover Medical School, Hanover, Germany
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover, Hanover, Germany
| | - Chrysanthi Skevaki
- Member of the German Center for Lung Research (DZL), Germany
- Institute of Laboratory Medicine and Pathobiochemistry, Molecular Diagnostics and
| | - Svenja Foth
- Member of the German Center for Lung Research (DZL), Germany
- Universities of Giessen and Marburg Lung Center, Philipps University Marburg and University Children's Hospital Marburg, University of Marburg, Marburg, Germany
| | - Stefanie Weber
- Member of the German Center for Lung Research (DZL), Germany
- Universities of Giessen and Marburg Lung Center, Philipps University Marburg and University Children's Hospital Marburg, University of Marburg, Marburg, Germany
| | - Miguel A Alejandre Alcazar
- Member of the German Center for Lung Research (DZL), Germany
- Institute for Lung Health and Cardio-Pulmonary Institute, Universities of Giessen and Marburg Lung Center, Giessen, Germany
- Translational Experimental Pediatrics, Experimental Pulmonology, Department of Pediatrics
- Center for Molecular Medicine Cologne and Cologne Excellence Cluster on Stress Responses in Aging-associated Diseases, and
- Pediatric Pulmonology and Allergology, Department of Pediatrics, Faculty of Medicine, University of Cologne and University Hospital Cologne, Cologne, Germany; and
| | - Silke van Koningsbruggen-Rietschel
- Member of the German Center for Lung Research (DZL), Germany
- Pediatric Pulmonology and Allergology, Department of Pediatrics, Faculty of Medicine, University of Cologne and University Hospital Cologne, Cologne, Germany; and
| | - Robert Brock
- Member of the German Center for Lung Research (DZL), Germany
- Pediatric Pulmonology and Allergology, Department of Pediatrics, Faculty of Medicine, University of Cologne and University Hospital Cologne, Cologne, Germany; and
| | - Samira Blau
- Member of the German Center for Lung Research (DZL), Germany
- Pediatric Pulmonology and Allergology, Department of Pediatrics, Faculty of Medicine, University of Cologne and University Hospital Cologne, Cologne, Germany; and
| | - Gesine Hansen
- Member of the German Center for Lung Research (DZL), Germany
- Department of Pediatric Pneumology, Allergology and Neonatology, Hannover Medical School, Hanover, Germany
- Biomedical Research in Endstage and Obstructive Lung Disease Hannover, Hanover, Germany
- Cluster of Excellence 2115 (RESIST), Hannover Medical School, Hanover, Germany
| | - Thomas Bahmer
- Member of the German Center for Lung Research (DZL), Germany
- Airway Research Center North, Borstel, Lübeck, Kiel, Grosshansdorf, Germany
- Internal Medicine Department I, University Hospital Schleswig-Holstein-Campus Kiel, Kiel, Germany
| | - Klaus F Rabe
- Member of the German Center for Lung Research (DZL), Germany
- Airway Research Center North, Borstel, Lübeck, Kiel, Grosshansdorf, Germany
- LungenClinic Grosshansdorf GmbH and Medical Clinics, Christian Albrechts University, Kiel, Germany
| | - Folke Brinkmann
- Member of the German Center for Lung Research (DZL), Germany
- Division of Epigenetics in Chronic Lung Disease, Priority Area Chronic Lung Diseases, Research Center Borstel-Leibniz Lung Center, Borstel, Germany
- Department of Pediatric Pneumology and Allergology, University Medical Center Schleswig-Holstein, Lübeck, Germany
- Airway Research Center North, Borstel, Lübeck, Kiel, Grosshansdorf, Germany
| | - Matthias Volkmar Kopp
- Department of Pediatric Pneumology and Allergology, University Medical Center Schleswig-Holstein, Lübeck, Germany
- Pediatric Respiratory Medicine, Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Airway Research Center North, Borstel, Lübeck, Kiel, Grosshansdorf, Germany
| | - Adam M Chaker
- Center of Allergy and Environment (ZAUM), Technical University and Helmholtz Center Munich, Munich, Germany
- Department of Otorhinolaryngology and Head and Neck Surgery, Medical School, Technical University of Munich, Munich, Germany
| | - Bianca Schaub
- Member of the German Center for Lung Research (DZL), Germany
- Dr. von Hauner Children's Hospital, Ludwig Maximilians University, Munich, Germany
- Comprehensive Pneumology Center-Munich, Munich, Germany
| | - Erika von Mutius
- Member of the German Center for Lung Research (DZL), Germany
- Institute for Asthma and Allergy Prevention, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany
- Dr. von Hauner Children's Hospital, Ludwig Maximilians University, Munich, Germany
| | - Carsten B Schmidt-Weber
- Center of Allergy and Environment (ZAUM), Technical University and Helmholtz Center Munich, Munich, Germany
- Member of the German Center for Lung Research (DZL), Germany
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Lin L, Ma Y, Li Z, Liu L, Hu Q, Zhou L. Genetic susceptibility of urolithiasis: comprehensive results from genome-wide analysis. World J Urol 2024; 42:230. [PMID: 38607442 DOI: 10.1007/s00345-024-04937-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 03/20/2024] [Indexed: 04/13/2024] Open
Abstract
BACKGROUND The pathogenesis of urolithiasis is multi-factorial and genetic factors have been shown to play a significant role in the development of urolithiasis. We tried to apply genome-wide Mendelian randomization (MR) analysis and figure out reliable gene susceptibility of urolithiasis from the largest samples to date in two independent genome-wide association studies (GWAS) database of European ancestry. METHODS We extracted summary statistics of expression quantitative trait locus (eQTL) from eQTLGen consortium. Urolithiasis phenotype information was obtained from both FinnGen Biobank and UK Biobank. Multiple two-sample MR analysis with a Bonferroni-corrected P threshold (P < 2.5e-06) was conducted. The primary endpoint was the causal effect calculated by random-effect inverse variance weighted (IVW) method. Sensitivity analysis, volcano plots, scatter plots, and regional plots were also performed and visualized. RESULTS After multiple MR tests between 19942 eQTLs and urolithiasis phenotype from both cohorts, 30 common eQTLs with consistent effect size direction were found to be causally associated with urolithiasis risk. Finally only one gene (LMAN2) was simultaneously identified among all top significant eQTLs from both FinnGen Biobank (beta = 0.6758, se = 0.0327, P = 6.775e-95) and UK Biobank (beta = 0.0044, se = 0.0009, P = 2.417e-06). We also found that LMAN2 was with the largest beta effect size on urolithiasis phenotype from the two cohorts. CONCLUSION We for the first time implemented genome-wide MR analysis to investigate the genetic susceptibility of urolithiasis in general population of European ancestry. Our results provided novel insights into common genetic variants of urinary stone disease, which was of great help to subsequent researches.
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Affiliation(s)
- Lede Lin
- Department of Urology and Institute of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yucheng Ma
- Department of Urology and Institute of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhen Li
- Department of Urology, Hunan Provincial People's Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China
| | - Linhu Liu
- Department of Urology and Institute of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qibo Hu
- Department of Urology and Institute of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Liang Zhou
- Department of Urology and Institute of Urology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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Avery CN, Russell ND, Steely CJ, Hersh AO, Bohnsack JF, Prahalad S, Jorde LB. Shared genomic segments analysis identifies MHC class I and class III molecules as genetic risk factors for juvenile idiopathic arthritis. HGG Adv 2024; 5:100277. [PMID: 38369753 PMCID: PMC10918567 DOI: 10.1016/j.xhgg.2024.100277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 02/13/2024] [Accepted: 02/13/2024] [Indexed: 02/20/2024] Open
Abstract
Juvenile idiopathic arthritis (JIA) is a complex rheumatic disease encompassing several clinically defined subtypes of varying severity. The etiology of JIA remains largely unknown, but genome-wide association studies (GWASs) have identified up to 22 genes associated with JIA susceptibility, including a well-established association with HLA-DRB1. Continued investigation of heritable risk factors has been hindered by disease heterogeneity and low disease prevalence. In this study, we utilized shared genomic segments (SGS) analysis on whole-genome sequencing of 40 cases from 12 multi-generational pedigrees significantly enriched for JIA. Subsets of cases are connected by a common ancestor in large extended pedigrees, increasing the power to identify disease-associated loci. SGS analysis identifies genomic segments shared among disease cases that are likely identical by descent and anchored by a disease locus. This approach revealed statistically significant signals for major histocompatibility complex (MHC) class I and class III alleles, particularly HLA-A∗02:01, which was observed at a high frequency among cases. Furthermore, we identified an additional risk locus at 12q23.2-23.3, containing genes primarily expressed by naive B cells, natural killer cells, and monocytes. The recognition of additional risk beyond HLA-DRB1 provides a new perspective on immune cell dynamics in JIA. These findings contribute to our understanding of JIA and may guide future research and therapeutic strategies.
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Affiliation(s)
- Cecile N Avery
- Department of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA.
| | - Nicole D Russell
- Department of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA
| | - Cody J Steely
- Department of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA
| | - Aimee O Hersh
- Department of Pediatrics, University of Utah, Salt Lake City, UT 84112, USA
| | - John F Bohnsack
- Department of Pediatrics, University of Utah, Salt Lake City, UT 84112, USA
| | - Sampath Prahalad
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30307, USA
| | - Lynn B Jorde
- Department of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA.
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8
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de Smith AJ, Wahlster L, Jeon S, Kachuri L, Black S, Langie J, Cato LD, Nakatsuka N, Chan TF, Xia G, Mazumder S, Yang W, Gazal S, Eng C, Hu D, Burchard EG, Ziv E, Metayer C, Mancuso N, Yang JJ, Ma X, Wiemels JL, Yu F, Chiang CWK, Sankaran VG. A noncoding regulatory variant in IKZF1 increases acute lymphoblastic leukemia risk in Hispanic/Latino children. Cell Genom 2024; 4:100526. [PMID: 38537633 PMCID: PMC11019360 DOI: 10.1016/j.xgen.2024.100526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 12/11/2023] [Accepted: 02/27/2024] [Indexed: 04/04/2024]
Abstract
Hispanic/Latino children have the highest risk of acute lymphoblastic leukemia (ALL) in the US compared to other racial/ethnic groups, yet the basis of this remains incompletely understood. Through genetic fine-mapping analyses, we identified a new independent childhood ALL risk signal near IKZF1 in self-reported Hispanic/Latino individuals, but not in non-Hispanic White individuals, with an effect size of ∼1.44 (95% confidence interval = 1.33-1.55) and a risk allele frequency of ∼18% in Hispanic/Latino populations and <0.5% in European populations. This risk allele was positively associated with Indigenous American ancestry, showed evidence of selection in human history, and was associated with reduced IKZF1 expression. We identified a putative causal variant in a downstream enhancer that is most active in pro-B cells and interacts with the IKZF1 promoter. This variant disrupts IKZF1 autoregulation at this enhancer and results in reduced enhancer activity in B cell progenitors. Our study reveals a genetic basis for the increased ALL risk in Hispanic/Latino children.
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Affiliation(s)
- Adam J de Smith
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA.
| | - Lara Wahlster
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Soyoung Jeon
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Linda Kachuri
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Susan Black
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jalen Langie
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Liam D Cato
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Tsz-Fung Chan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Guangze Xia
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
| | - Soumyaa Mazumder
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Wenjian Yang
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Steven Gazal
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Celeste Eng
- Department of Medicine, Institute for Human Genetics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Bioengineering and Biotherapeutic Sciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Donglei Hu
- Department of Medicine, Institute for Human Genetics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Esteban González Burchard
- Department of Medicine, Institute for Human Genetics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Bioengineering and Biotherapeutic Sciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Elad Ziv
- Department of Medicine, Institute for Human Genetics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Catherine Metayer
- School of Public Health, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Jun J Yang
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Xiaomei Ma
- Yale School of Public Health, New Haven, CT 06520, USA
| | - Joseph L Wiemels
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Fulong Yu
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangzhou, China
| | - Charleston W K Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA; USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
| | - Vijay G Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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Rajan KB, Mcaninch EA, Wilson RS, Dhana A, Evans-Lacko S, Evans DA. Statin Initiation and Risk of Incident Alzheimer Disease and Cognitive Decline in Genetically Susceptible Older Adults. Neurology 2024; 102:e209168. [PMID: 38447103 DOI: 10.1212/wnl.0000000000209168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 01/08/2024] [Indexed: 03/08/2024] Open
Abstract
BACKGROUND AND OBJECTIVES The association of statin initiation with incident Alzheimer disease (AD) dementia and cognitive decline by the APOE ε4 allele is unknown. Our objective was to examine whether the association of statin initiation with incident AD dementia and cognitive decline differs by the APOE ε4 allele. METHODS This population-based longitudinal cohort study was conducted in 4 urban communities in Chicago, IL, United States, consisting of 4,807 participants. Statin initiation is based on the inspection of medications during home assessments. Clinical diagnosis for incident AD used the NINCDS-ADRDA criteria, and longitudinal measurements of global cognition consisted of episodic memory, perceptual speed, and the Mini-Mental State Examination tests. RESULTS The study participants had a mean age of 72 years, consisting of 63% female individuals and 61% non-Hispanic Black individuals. During the study period, 1,470 (31%) participants reported statin initiation. In a covariate-adjusted competing risk model, statin initiation was associated with a reduced risk of incident clinical AD [hazard ratio (HR) 0.81 (95% CI 0.70-0.94)] compared with nonusers. This association was statistically significantly lower (p interaction = 0.015) among participants with the APOE ε4 allele [HR 0.60 (95% CI 0.49-0.74)] compared with those without the APOE ε4 allele [HR 0.96 (95% CI 0.82-1.12)]. The annual decline in global cognition (β = 0.021, 95% CI 0.007-0.034) and episodic memory (β = 0.020, 95% CI 0.007-0.033) was also substantially slower among participants with the APOE ε4 allele after statin initiation compared with nonusers. However, the association of statin initiation with cognitive decline was not significant among those without the APOE ε4 allele. DISCUSSION Our findings suggest that statins might be associated with a lower risk of incident AD among individuals with the APOE ε4 allele. The benefits of statin therapy need further consideration in randomized clinical trials, especially among those with the APOE ε4 allele. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that among those aged 65 years or older, statin initiation was associated with a reduced risk of Alzheimer disease, especially in the presence of an APOE-e4 allele.
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Affiliation(s)
- Kumar B Rajan
- From the Rush Institute for Healthy Aging (K.B.R., A.D., D.A.E.), Department of Internal Medicine, Rush University Medical Center, Chicago, IL; Division of Endocrinology (E.A.M.), Gerontology and Metabolism, Stanford University Medical Center, CA; Rush Alzheimer's Disease Center (R.S.W.), Rush University Medical Center, Chicago, IL; and Care Policy and Evaluation Centre (S.E.-L.), London School of Economics and Political Science, United Kingdom
| | - Elizabeth A Mcaninch
- From the Rush Institute for Healthy Aging (K.B.R., A.D., D.A.E.), Department of Internal Medicine, Rush University Medical Center, Chicago, IL; Division of Endocrinology (E.A.M.), Gerontology and Metabolism, Stanford University Medical Center, CA; Rush Alzheimer's Disease Center (R.S.W.), Rush University Medical Center, Chicago, IL; and Care Policy and Evaluation Centre (S.E.-L.), London School of Economics and Political Science, United Kingdom
| | - Robert S Wilson
- From the Rush Institute for Healthy Aging (K.B.R., A.D., D.A.E.), Department of Internal Medicine, Rush University Medical Center, Chicago, IL; Division of Endocrinology (E.A.M.), Gerontology and Metabolism, Stanford University Medical Center, CA; Rush Alzheimer's Disease Center (R.S.W.), Rush University Medical Center, Chicago, IL; and Care Policy and Evaluation Centre (S.E.-L.), London School of Economics and Political Science, United Kingdom
| | - Anisa Dhana
- From the Rush Institute for Healthy Aging (K.B.R., A.D., D.A.E.), Department of Internal Medicine, Rush University Medical Center, Chicago, IL; Division of Endocrinology (E.A.M.), Gerontology and Metabolism, Stanford University Medical Center, CA; Rush Alzheimer's Disease Center (R.S.W.), Rush University Medical Center, Chicago, IL; and Care Policy and Evaluation Centre (S.E.-L.), London School of Economics and Political Science, United Kingdom
| | - Sara Evans-Lacko
- From the Rush Institute for Healthy Aging (K.B.R., A.D., D.A.E.), Department of Internal Medicine, Rush University Medical Center, Chicago, IL; Division of Endocrinology (E.A.M.), Gerontology and Metabolism, Stanford University Medical Center, CA; Rush Alzheimer's Disease Center (R.S.W.), Rush University Medical Center, Chicago, IL; and Care Policy and Evaluation Centre (S.E.-L.), London School of Economics and Political Science, United Kingdom
| | - Denis A Evans
- From the Rush Institute for Healthy Aging (K.B.R., A.D., D.A.E.), Department of Internal Medicine, Rush University Medical Center, Chicago, IL; Division of Endocrinology (E.A.M.), Gerontology and Metabolism, Stanford University Medical Center, CA; Rush Alzheimer's Disease Center (R.S.W.), Rush University Medical Center, Chicago, IL; and Care Policy and Evaluation Centre (S.E.-L.), London School of Economics and Political Science, United Kingdom
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10
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Sun X, Qian Y, Cheng W, Ye D, Liu B, Zhou D, Wen C, Andreassen OA, Mao Y. Characterizing the polygenic overlap and shared loci between rheumatoid arthritis and cardiovascular diseases. BMC Med 2024; 22:152. [PMID: 38589871 PMCID: PMC11003061 DOI: 10.1186/s12916-024-03376-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 03/26/2024] [Indexed: 04/10/2024] Open
Abstract
BACKGROUND Despite substantial research revealing that patients with rheumatoid arthritis (RA) have excessive morbidity and mortality of cardiovascular disease (CVD), the mechanism underlying this association has not been fully known. This study aims to systematically investigate the phenotypic and genetic correlation between RA and CVD. METHODS Based on UK Biobank, we conducted two cohort studies to evaluate the phenotypic relationships between RA and CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), and stroke. Next, we used linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and bivariate causal mixture model (MiXeR) methods to examine the genetic correlation and polygenic overlap between RA and CVD, using genome-wide association summary statistics. Furthermore, we explored specific shared genetic loci by conjunctional false discovery rate analysis and association analysis based on subsets. RESULTS Compared with the general population, RA patients showed a higher incidence of CVD (hazard ratio [HR] = 1.21, 95% confidence interval [CI]: 1.15-1.28). We observed positive genetic correlations of RA with AF and stroke, and a mixture of negative and positive local genetic correlations underlying the global genetic correlation for CAD and HF, with 13 ~ 33% of shared genetic variants for these trait pairs. We further identified 23 pleiotropic loci associated with RA and at least one CVD, including one novel locus (rs7098414, TSPAN14, 10q23.1). Genes mapped to these shared loci were enriched in immune and inflammatory-related pathways, and modifiable risk factors, such as high diastolic blood pressure. CONCLUSIONS This study revealed the shared genetic architecture of RA and CVD, which may facilitate drug target identification and improved clinical management.
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Affiliation(s)
- Xiaohui Sun
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Yu Qian
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
- School of Life Sciences, Westlake University, Hangzhou, 310024, China
| | - Weiqiu Cheng
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, 0407, Norway
| | - Ding Ye
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Bin Liu
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Dan Zhou
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chengping Wen
- College of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, 0407, Norway.
| | - Yingying Mao
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
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11
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Sun Y, Zhou Y, Yu B, Zhang K, Wang B, Tan X, Lu Y, Wang N. Frailty, genetic predisposition, and incident atrial fibrillation. Eur Heart J 2024; 45:1281-1283. [PMID: 38442287 DOI: 10.1093/eurheartj/ehae130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 01/13/2024] [Accepted: 02/15/2024] [Indexed: 03/07/2024] Open
Affiliation(s)
- Ying Sun
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China
| | - Yinuo Zhou
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China
| | - Bowei Yu
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China
| | - Kun Zhang
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China
| | - Bin Wang
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China
| | - Xiao Tan
- Department of Big Data in Health Science, Zhejiang University, Hangzhou, China
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Yingli Lu
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China
| | - Ningjian Wang
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China
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12
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Spindler J, Koller S, Graf U, Berger W, Gerth-Kahlert C, Blaser F. Macular Corneal Dystrophy - Molecular Genetics as the Key in Treatment-Refractory Keratopathy. Klin Monbl Augenheilkd 2024; 241:398-401. [PMID: 38653268 DOI: 10.1055/a-2219-8288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2024]
Affiliation(s)
- Jan Spindler
- Department of Ophthalmology, University Hospital Zurich, Zurich, Switzerland
| | - Samuel Koller
- Institute of Medical Molecular Genetics, University of Zurich, Schlieren, Switzerland
| | - Urs Graf
- Institute of Medical Molecular Genetics, University of Zurich, Schlieren, Switzerland
- Aktuelle Adresse: Labordiagnostic St. Gallen West AG, 9015 St. Gallen
| | - Wolfgang Berger
- Institute of Medical Molecular Genetics, University of Zurich, Schlieren, Switzerland
- Zurich Center for Integrative Human Physiology (ZIHP), University of Zurich, Zurich, Switzerland
- Zentrum für Neurowissenschaften (ZNZ), University and ETH Zurich, Zurich, Switzerland
| | | | - Frank Blaser
- Department of Ophthalmology, University Hospital Zurich, Zurich, Switzerland
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13
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Yeh PK, An YC, Hung KS, Yang FC. Influences of Genetic and Environmental Factors on Chronic Migraine: A Narrative Review. Curr Pain Headache Rep 2024; 28:169-180. [PMID: 38363449 DOI: 10.1007/s11916-024-01228-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/07/2024] [Indexed: 02/17/2024]
Abstract
PURPOSE OF REVIEW In this narrative review, we aim to summarize recent insights into the complex interplay between environmental and genetic factors affecting the etiology, development, and progression of chronic migraine (CM). RECENT FINDINGS Environmental factors such as stress, sleep dysfunction, fasting, hormonal changes, weather patterns, dietary compounds, and sensory stimuli are critical triggers that can contribute to the evolution of episodic migraine into CM. These triggers are particularly influential in genetically predisposed individuals. Concurrently, genome-wide association studies (GWAS) have revealed over 100 genetic loci linked to migraine, emphasizing a significant genetic basis for migraine susceptibility. In CM, environmental and genetic factors are of equal importance and contribute to the pathophysiology of the condition. Understanding the bidirectional interactions between these elements is crucial for advancing therapeutic approaches and preventive strategies. This balanced perspective encourages continued research into the complex gene-environment nexus to improve our understanding and management of CM.
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Affiliation(s)
- Po-Kuan Yeh
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Section 2, Cheng-Kung Road, Neihu 114, No. 325, Taipei, Taiwan
- Department of Psychiatry, Tri-Service General Hospital, National Defense Medical Center, Beitou Branch, Taipei, Taiwan
| | - Yu-Chin An
- Department of Emergency Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Kuo-Sheng Hung
- Center for Precision Medicine and Genomics, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Fu-Chi Yang
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Section 2, Cheng-Kung Road, Neihu 114, No. 325, Taipei, Taiwan.
- Center for Precision Medicine and Genomics, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
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14
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Sakaue S, Weinand K, Isaac S, Dey KK, Jagadeesh K, Kanai M, Watts GFM, Zhu Z, Brenner MB, McDavid A, Donlin LT, Wei K, Price AL, Raychaudhuri S. Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles. Nat Genet 2024; 56:615-626. [PMID: 38594305 DOI: 10.1038/s41588-024-01682-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 02/07/2024] [Indexed: 04/11/2024]
Abstract
Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining noncoding variant function.
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Affiliation(s)
- Saori Sakaue
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kathryn Weinand
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Shakson Isaac
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Kushal K Dey
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Karthik Jagadeesh
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Masahiro Kanai
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Gerald F M Watts
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Zhu Zhu
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael B Brenner
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrew McDavid
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA
| | - Laura T Donlin
- Hospital for Special Surgery, New York, NY, USA
- Weill Cornell Medicine, New York, NY, USA
| | - Kevin Wei
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alkes L Price
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Soumya Raychaudhuri
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
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15
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Nicolas G. Recent advances in Alzheimer disease genetics. Curr Opin Neurol 2024; 37:154-165. [PMID: 38235704 DOI: 10.1097/wco.0000000000001242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
PURPOSE OF REVIEW Genetics studies provide important insights into Alzheimer disease (AD) etiology and mechanisms. Critical advances have been made recently, mainly thanks to the access to novel techniques and larger studies. RECENT FINDINGS In monogenic AD, progress has been made with a better understanding of the mechanisms associated with pathogenic variants and the input of clinical studies in presymptomatic individuals. In complex AD, increasing sample sizes in both DNA chip-based (genome-wide association studies, GWAS) and exome/genome sequencing case-control studies unveiled novel common and rare risk factors, while the understanding of their combined effect starts to suggest the existence of rare families with oligogenic inheritance of early-onset, nonmonogenic, AD. SUMMARY Most genetic risk factors with a known consequence designate the aggregation of the Aβ peptide as a core etiological factor in complex AD thus confirming that the research based on monogenic AD - where the amyloid cascade seems more straightforward - is relevant to complex AD as well. Novel mechanistic insights and risk factor studies unveiling novel factors and attempting to combine the effect of common and rare variants will offer promising perspectives for future AD prevention, at least regarding early-onset AD, and probably in case of later onset as well.
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Affiliation(s)
- Gaël Nicolas
- Univ Rouen Normandie, Normandie Univ, Inserm U1245 and CHU Rouen, Department of Genetics and CNRMAJ, F-76000 Rouen, France
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16
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Reynoso A, Torricelli R, Jacobs BM, Shi J, Aslibekyan S, Norcliffe-Kaufmann L, Noyce AJ, Heilbron K. Gene-Environment Interactions for Parkinson's Disease. Ann Neurol 2024; 95:677-687. [PMID: 38113326 DOI: 10.1002/ana.26852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 12/06/2023] [Accepted: 12/06/2023] [Indexed: 12/21/2023]
Abstract
OBJECTIVE Parkinson's disease (PD) is a neurodegenerative disorder with complex etiology. Multiple genetic and environmental factors have been associated with PD, but most PD risk remains unexplained. The aim of this study was to test for statistical interactions between PD-related genetic and environmental exposures in the 23andMe, Inc. research dataset. METHODS Using a validated PD polygenic risk score and common PD-associated variants in the GBA gene, we explored interactions between genetic susceptibility factors and 7 lifestyle and environmental factors: body mass index (BMI), type 2 diabetes (T2D), tobacco use, caffeine consumption, pesticide exposure, head injury, and physical activity (PA). RESULTS We observed that T2D, as well as higher BMI, caffeine consumption, and tobacco use, were associated with lower odds of PD, whereas head injury, pesticide exposure, GBA carrier status, and PD polygenic risk score were associated with higher odds. No significant association was observed between PA and PD. In interaction analyses, we found statistical evidence for an interaction between polygenic risk of PD and the following environmental/lifestyle factors: T2D (p = 6.502 × 10-8), PA (p = 8.745 × 10-5), BMI (p = 4.314 × 10-4), and tobacco use (p = 2.236 × 10-3). Although BMI and tobacco use were associated with lower odds of PD regardless of the extent of individual genetic liability, the direction of the relationship between odds of PD and T2D, as well as PD and PA, varied depending on polygenic risk score. INTERPRETATION We provide preliminary evidence that associations between some environmental and lifestyle factors and PD may be modified by genotype. ANN NEUROL 2024;95:677-687.
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Affiliation(s)
| | - Roberta Torricelli
- Center for Preventive Neurology, Wolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Benjamin Meir Jacobs
- Center for Preventive Neurology, Wolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | | | | | | | - Alastair J Noyce
- Center for Preventive Neurology, Wolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Karl Heilbron
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Berlin, Germany
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
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17
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Zhang H, Chang Y, Li Y, Wei J, Ma X, Zhou W, Zang X, Jin T, Wu S. Effects of CASZ1, WNT2B and PTPRG SNPs on stroke susceptibility in the Chinese Han population. Eur J Clin Invest 2024; 54:e14144. [PMID: 38059696 DOI: 10.1111/eci.14144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 10/20/2023] [Accepted: 11/19/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND Stroke is an important cause of death and disability worldwide, ranking second in the cause of death, and it is thought to be related to genetic factors. The purpose of our study is to investigate the association between CASZ1, WNT2B and PTPRG single nucleotide polymorphisms (SNPs) and stroke risk in the Chinese population. METHODS We recruited 1418 volunteers, comprised of 710 stroke cases and 708 controls in this study. We used MassARRAY iPLEX GOLD method to genotype the three SNPs on CASZ1, WNT2B and PTPRG. Logistic regression was used to analyse the association between these SNPs and stroke, and odds ratios (ORs) and 95% confidence intervals (CIs) were then calculated. What's more, the interactions among SNPs were predicted by multi-factor dimensionality reduction (MDR) analysis. RESULTS This research demonstrated that CASZ1 rs880315 and PTPRG rs704341 were associated with reduced stroke susceptibility. More precisely, CASZ1 rs880315 was associated with reduced stroke susceptibility in people aged ≤64 years and women. PTPRG rs704341 was associated with reduced stroke susceptibility in people aged >64 years, women, non-smokers and non-drinkers. Conversely, WNT2B rs12037987 was related to elevated stroke susceptibility in people aged >64 years, women and non-smokers. In addition, CASZ1 rs880315, WNT2B rs12037987 and PTPRG rs704341 had a strong redundancy relationship. CONCLUSION Our study concludes that CASZ1 rs880315, WNT2B rs12037987 and PTPRG rs704341 are associated with stroke, and the study provides a basis for assessing genetic variants associated with stroke risk in the Han Chinese population.
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Affiliation(s)
- Huan Zhang
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
- Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), School of Life Sciences, Ministry of Education, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
- Department of Neurology, The First Hospital of Xi'an, The First Affiliated Hospital of Northwest University, Xi'an, Shaanxi, China
| | - Yanting Chang
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
- Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), School of Life Sciences, Ministry of Education, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
- Department of Neurology, The First Hospital of Xi'an, The First Affiliated Hospital of Northwest University, Xi'an, Shaanxi, China
| | - Yujie Li
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
- Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), School of Life Sciences, Ministry of Education, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
| | - Jie Wei
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
- Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), School of Life Sciences, Ministry of Education, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
| | - Xiaoya Ma
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
- Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), School of Life Sciences, Ministry of Education, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
| | - Wenqian Zhou
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
- Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), School of Life Sciences, Ministry of Education, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
| | - Xufeng Zang
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
- Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), School of Life Sciences, Ministry of Education, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
| | - Tianbo Jin
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
- Key Laboratory of Resource Biology and Biotechnology in Western China (Northwest University), School of Life Sciences, Ministry of Education, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
| | - Songdi Wu
- College of Life Science, Northwest University, Xi'an, Shaanxi, China
- Department of Neurology, The First Hospital of Xi'an, The First Affiliated Hospital of Northwest University, Xi'an, Shaanxi, China
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18
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Ayari F, Chaaben AB, Abaza H, Mihoub O, Ouni N, Boukouaci W, Kharrat M, Leboyer M, Guemira F, Tamouza R, Mankai A. Association between genetic variants of TLR2, TLR4, TLR9 and schizophrenia. Encephale 2024; 50:178-184. [PMID: 37718198 DOI: 10.1016/j.encep.2023.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 05/23/2023] [Accepted: 05/23/2023] [Indexed: 09/19/2023]
Abstract
BACKGROUND AND STUDY AIM Schizophrenia (SZ) is a multifactorial disorder involving complex interactions between genetic and environmental factors, where immune dysfunction plays a key etiopathogenic role. In order to explore the control of innate immune responses in SZ, we aimed to investigate the potential association between twelve TLR2, TLR4 and TLR9 variants (TLR2: rs4696480T>A, rs3804099T>C, rs3804100T>C; TLR4: rs1927914G>A, rs10759932T>C, rs4986790A>G, rs4986791T>C, rs11536889G>C, rs11536891T>C; TLR9: rs187084A>G, rs352139T>C and rs352140C>T) and SZ susceptibility in a Tunisian population. PATIENTS AND METHODS This study included 150 patients and 201 healthy controls with no history of psychiatric illness. Genotyping was done using a TaqMan SNP genotyping assay. We also assessed a haplotype analysis for TLR2, TLR4 and TLR9 variants with SZ using Haploview 4.2 Software. RESULTS We found that the AA genotype of the TLR2 rs4696480T>A variant was significantly associated with an increased risk of SZ (46% vs. 31%, P=4.7×10-3, OR=1.87 and 95% CI [1.18-2.97]). The frequency of the TA genotype was significantly higher in the control group than in SZ patients (27% vs. 43%, P=2.1×10-3) and may be associated with protection against SZ (OR=0.49 and 95% CI [0.30-0.80]). Whereas, the TLR9 rs187084-GG genotype was higher in the control group compared to patients (16% vs. 5%, P=1.6×10-3) and would present protection against SZ (OR=0.28, CI=[0.10-0.68]). The ACT haplotype of the TLR2 and the ACC haplotype of the TLR9 gene were identified as a risk haplotypes for SZ (P=0.04, OR=9.30, 95% CI=[1.11-77.71]; P=3×10-4, OR=6.05, 95% CI=[2.29-15.98], respectively). CONCLUSION The results indicate that TLR2 and TLR9 genetic diversity may play a role in genetic vulnerability to SZ. However, including more patients and evaluation of TLR2 and TLR9 expression are recommended.
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Affiliation(s)
- Fayza Ayari
- Clinical Biology Department, Salah Azaiz Institute, Tunis, Tunisia; Faculty of Sciences of Tunis, University Tunis El Manar, Tunis, Tunisia.
| | - Arij Ben Chaaben
- Biology Department, Higher School of Health Sciences and Techniques, Tunis El Manar University, Tunis, Tunisia; Human Genetic Laboratory (LR99E510), Faculty of Medicine, University of Tunis El Manar, Tunis, Tunisia
| | - Hajer Abaza
- Research Unit 03/04 Schizophrenia and Department of Psychiatry F, Razi Hospital, Manouba, Tunisia
| | - Ons Mihoub
- Human Genetic Laboratory (LR99E510), Faculty of Medicine, University of Tunis El Manar, Tunis, Tunisia
| | - Nesrine Ouni
- Clinical Biology Department, Salah Azaiz Institute, Tunis, Tunisia; Faculty of Sciences of Tunis, University Tunis El Manar, Tunis, Tunisia
| | - Wahid Boukouaci
- Université Paris Est Creteil (UPEC), INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, 94010 Creteil, France
| | - Maher Kharrat
- Human Genetic Laboratory (LR99E510), Faculty of Medicine, University of Tunis El Manar, Tunis, Tunisia
| | - Marion Leboyer
- Université Paris Est Creteil (UPEC), INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, 94010 Creteil, France
| | - Fethi Guemira
- Clinical Biology Department, Salah Azaiz Institute, Tunis, Tunisia
| | - Ryad Tamouza
- Université Paris Est Creteil (UPEC), INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, 94010 Creteil, France
| | - Amani Mankai
- Biology Department, Higher School of Health Sciences and Techniques, Tunis El Manar University, Tunis, Tunisia; Research Unit "Obesity: etiopathology and treatment, UR18ES01", National Institute of Nutrition and Food Technology, Tunis, Tunisia
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19
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Dey S, Debnath M, Yelamanchi R, Mullapudi T, Kuniyil AP, Kamble N, Holla VV, Mahale RR, Pal PK, Yadav R. Novel Insights into the Genetic Basis of Progressive Supranuclear Palsy in Asian-Indian Population. Mov Disord 2024; 39:753-755. [PMID: 38314938 DOI: 10.1002/mds.29740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 01/04/2024] [Accepted: 01/16/2024] [Indexed: 02/07/2024] Open
Affiliation(s)
- Saikat Dey
- Department of Human Genetics, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Monojit Debnath
- Department of Human Genetics, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Ramchandra Yelamanchi
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Thrinath Mullapudi
- Department of Human Genetics, National Institute of Mental Health and Neurosciences, Bangalore, India
| | | | - Nitish Kamble
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Vikram V Holla
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Rohan R Mahale
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Pramod Kumar Pal
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Ravi Yadav
- Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore, India
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20
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Zhu L, Zhang X, Guan Y, Zhu Y, Zhou Q, Liu B, Ren H, Yang X. Meta-analysis of the association of prosaposin polymorphisms rs4747203 and rs885828 with risk of Parkinson's disease. Acta Neurol Belg 2024; 124:573-580. [PMID: 38206457 DOI: 10.1007/s13760-023-02446-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 11/27/2023] [Indexed: 01/12/2024]
Abstract
BACKGROUND Previous research has established a connection between polymorphisms rs4747203 and rs885828 in the prosaposin (PSAP) gene and an increased risk of Parkinson's disease (PD). However, other studies have found no significant difference in risk compared to the general population. METHODS To evaluate the current evidence linking rs4747203 and rs885828 to PD risk, we conducted a comprehensive search of PubMed, the Web of Science, Embase, and the Cochrane Library for relevant studies up until May 2023. In addition, we analyzed data from the publicly available "PD Variant Browser". We performed a meta-analysis using Stata 17.0 to synthesize the findings from the selected studies. RESULTS Our meta-analysis, which included data from six published studies and the public database, revealed no significant association between PD risk and either rs4747203 [OR (95% CI) = 0.99 (0.93-1.05), I2 = 90.3%, P = 0.635] or rs885828 [OR (95% CI) = 1.01 (0.95-1.07), I2 = 90.7%, P = 0.773]. These results remained consistent when examining subgroups of individuals within or outside of Asia. CONCLUSION The available evidence does not support an association between the genotype at rs4747203 or rs885828 and the risk of PD.
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Affiliation(s)
- Liuhui Zhu
- Department of Geriatric Neurology, First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, People's Republic of China
- Joint Institute of Smoking and Health, Kunming, 650106, Yunnan, China
| | - Xinyue Zhang
- Department of Geriatric Neurology, First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, People's Republic of China
| | - Ying Guan
- Joint Institute of Smoking and Health, Kunming, 650106, Yunnan, China
| | - Yongyun Zhu
- Department of Geriatric Neurology, First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, People's Republic of China
| | - Qian Zhou
- Department of Geriatric Neurology, First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, People's Republic of China
| | - Bin Liu
- Department of Geriatric Neurology, First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, People's Republic of China
| | - Hui Ren
- Department of Geriatric Neurology, First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, People's Republic of China
| | - Xinglong Yang
- Department of Geriatric Neurology, First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, People's Republic of China.
- Joint Institute of Smoking and Health, Kunming, 650106, Yunnan, China.
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21
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Smith K, Deutsch AJ, McGrail C, Kim H, Hsu S, Huerta-Chagoya A, Mandla R, Schroeder PH, Westerman KE, Szczerbinski L, Majarian TD, Kaur V, Williamson A, Zaitlen N, Claussnitzer M, Florez JC, Manning AK, Mercader JM, Gaulton KJ, Udler MS. Multi-ancestry polygenic mechanisms of type 2 diabetes. Nat Med 2024; 30:1065-1074. [PMID: 38443691 DOI: 10.1038/s41591-024-02865-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 02/06/2024] [Indexed: 03/07/2024]
Abstract
Type 2 diabetes (T2D) is a multifactorial disease with substantial genetic risk, for which the underlying biological mechanisms are not fully understood. In this study, we identified multi-ancestry T2D genetic clusters by analyzing genetic data from diverse populations in 37 published T2D genome-wide association studies representing more than 1.4 million individuals. We implemented soft clustering with 650 T2D-associated genetic variants and 110 T2D-related traits, capturing known and novel T2D clusters with distinct cardiometabolic trait associations across two independent biobanks representing diverse genetic ancestral populations (African, n = 21,906; Admixed American, n = 14,410; East Asian, n =2,422; European, n = 90,093; and South Asian, n = 1,262). The 12 genetic clusters were enriched for specific single-cell regulatory regions. Several of the polygenic scores derived from the clusters differed in distribution among ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a body mass index (BMI) of 30 kg m-2 in the European subpopulation and 24.2 (22.9-25.5) kg m-2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg m-2 in the East Asian group. Thus, these multi-ancestry T2D genetic clusters encompass a broader range of biological mechanisms and provide preliminary insights to explain ancestry-associated differences in T2D risk profiles.
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Affiliation(s)
- Kirk Smith
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Aaron J Deutsch
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Carolyn McGrail
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
| | - Hyunkyung Kim
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Committee on Genetics, Genomics and Systems Biology, University of Chicago, Chicago, IL, USA
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Sarah Hsu
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Alicia Huerta-Chagoya
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ravi Mandla
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Philip H Schroeder
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kenneth E Westerman
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Lukasz Szczerbinski
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, Bialystok, Poland
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Timothy D Majarian
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
- Vertex Pharmaceuticals, Boston, MA, USA
| | - Varinderpal Kaur
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alice Williamson
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Noah Zaitlen
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Melina Claussnitzer
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jose C Florez
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Alisa K Manning
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Josep M Mercader
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kyle J Gaulton
- Department of Pediatrics, University of California, San Diego, San Diego, CA, USA
| | - Miriam S Udler
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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22
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Ouyang D, Liang Y, Wang J, Li L, Ai N, Feng J, Lu S, Liao S, Liu X, Xie S. HGCLAMIR: Hypergraph contrastive learning with attention mechanism and integrated multi-view representation for predicting miRNA-disease associations. PLoS Comput Biol 2024; 20:e1011927. [PMID: 38652712 PMCID: PMC11037542 DOI: 10.1371/journal.pcbi.1011927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 02/19/2024] [Indexed: 04/25/2024] Open
Abstract
Existing studies have shown that the abnormal expression of microRNAs (miRNAs) usually leads to the occurrence and development of human diseases. Identifying disease-related miRNAs contributes to studying the pathogenesis of diseases at the molecular level. As traditional biological experiments are time-consuming and expensive, computational methods have been used as an effective complement to infer the potential associations between miRNAs and diseases. However, most of the existing computational methods still face three main challenges: (i) learning of high-order relations; (ii) insufficient representation learning ability; (iii) importance learning and integration of multi-view embedding representation. To this end, we developed a HyperGraph Contrastive Learning with view-aware Attention Mechanism and Integrated multi-view Representation (HGCLAMIR) model to discover potential miRNA-disease associations. First, hypergraph convolutional network (HGCN) was utilized to capture high-order complex relations from hypergraphs related to miRNAs and diseases. Then, we combined HGCN with contrastive learning to improve and enhance the embedded representation learning ability of HGCN. Moreover, we introduced view-aware attention mechanism to adaptively weight the embedded representations of different views, thereby obtaining the importance of multi-view latent representations. Next, we innovatively proposed integrated representation learning to integrate the embedded representation information of multiple views for obtaining more reasonable embedding information. Finally, the integrated representation information was fed into a neural network-based matrix completion method to perform miRNA-disease association prediction. Experimental results on the cross-validation set and independent test set indicated that HGCLAMIR can achieve better prediction performance than other baseline models. Furthermore, the results of case studies and enrichment analysis further demonstrated the accuracy of HGCLAMIR and unconfirmed potential associations had biological significance.
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Affiliation(s)
- Dong Ouyang
- Peng Cheng Laboratory, Shenzhen, China
- School of Biomedical Engineering, Guangdong Medical University, Dongguan, China
| | - Yong Liang
- Peng Cheng Laboratory, Shenzhen, China
- Pazhou Laboratory (Huangpu), Guangzhou, China
| | - Jinfeng Wang
- College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China
| | - Le Li
- School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China
| | - Ning Ai
- School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China
| | - Junning Feng
- School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China
| | - Shanghui Lu
- School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China
| | - Shuilin Liao
- School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China
| | - Xiaoying Liu
- Computer Engineering Technical College, Guangdong Polytechnic of Science and Technology, Zhuhai, China
| | - Shengli Xie
- Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing, Guangzhou, China
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23
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Segura AG, Serna EDL, Sugranyes G, Baeza I, Valli I, Martínez-Serrano I, Díaz-Caneja CM, Andreu-Bernabeu Á, Moreno DM, Gassó P, Rodríguez N, Martínez-Pinteño A, Prohens L, Torrent C, García-Rizo C, Mas S, Castro-Fornieles J. Polygenic risk scores mediating functioning outcomes through cognitive and clinical features in youth at family risk and controls. Eur Neuropsychopharmacol 2024; 81:28-37. [PMID: 38310718 DOI: 10.1016/j.euroneuro.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 01/23/2024] [Accepted: 01/26/2024] [Indexed: 02/06/2024]
Abstract
Schizophrenia and bipolar disorder exhibit substantial clinical overlap, particularly in individuals at familial high risk, who frequently present sub-threshold symptoms before the onset of illness. Severe mental disorders are highly polygenic traits, but their impact on the stages preceding the manifestation of mental disorders remains relatively unexplored. Our study aimed to examine the influence of polygenic risk scores (PRS) on sub-clinical outcomes over a 2-year period in youth at familial high risk for schizophrenia and bipolar disorder and controls. The sample included 222 children and adolescents, comprising offspring of parents with schizophrenia (n = 38), bipolar disorder (n = 80), and community controls (n = 104). We calculated PRS for psychiatric disorders, neuroticism and cognition using the PRS-CS method. Linear mixed-effects models were employed to investigate the association between PRS and cognition, symptom severity and functioning. Mediation analyses were conducted to explore whether clinical features acted as intermediaries in the impact of PRS on functioning outcomes. SZoff exhibited elevated PRS for schizophrenia. In the entire sample, PRS for depression, neuroticism, and cognitive traits showed associations with sub-clinical features. The effect of PRS for neuroticism and general intelligence on functioning outcomes were mediated by cognition and symptoms severity, respectively. This study delves into the interplay among genetics, the emergence of sub-clinical symptoms and functioning outcomes, providing novel evidence on mechanisms underpinning the continuum from sub-threshold features to the onset of mental disorders. The findings underscore the interplay of genetics, cognition, and clinical features, providing insights for personalized early interventions.
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Affiliation(s)
- Alex G Segura
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Elena de la Serna
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Gisela Sugranyes
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Inmaculada Baeza
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Isabel Valli
- Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Irene Martínez-Serrano
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Covadonga M Díaz-Caneja
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Álvaro Andreu-Bernabeu
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Dolores M Moreno
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Adolescent Inpatient Unit, Department of Psychiatry, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Psychiatry Department, Universidad Complutense de Madrid, Madrid, Spain
| | - Patricia Gassó
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Natalia Rodríguez
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Albert Martínez-Pinteño
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Llucia Prohens
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Carla Torrent
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Barcelona Bipolar Disorders Program, Clinical Institute of Neuroscience, Hospital Clinic, University of Barcelona, Fundació Clinic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Clemente García-Rizo
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Barcelona Clinic Schizophrenia Unit, Institute of Neuroscience, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
| | - Sergi Mas
- Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
| | - Josefina Castro-Fornieles
- Child and Adolescent Psychiatry and Psychology Department, 2021SGR01319, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Child and Adolescent Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
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24
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Follett J, Guenther D, Xoi L, Amouri R, Ben Sassi S, Hentati F, Farrer MJ. Genetic Modifiers of LRRK2 Parkinson's Disease: A Replication Study in Arab-Berbers. Mov Disord 2024; 39:751-753. [PMID: 38291980 DOI: 10.1002/mds.29735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 01/16/2024] [Indexed: 02/01/2024] Open
Affiliation(s)
- Jordan Follett
- Department of Neurology, University of Florida, Gainesville, Florida, USA
| | - Dylan Guenther
- Department of Neurology, University of Florida, Gainesville, Florida, USA
| | - Leyna Xoi
- Department of Neurology, University of Florida, Gainesville, Florida, USA
| | - Rim Amouri
- Mongi Ben Hamida National Institute of Neurology, La Rabta, Tunisia
| | - Samia Ben Sassi
- Mongi Ben Hamida National Institute of Neurology, La Rabta, Tunisia
| | - Faycel Hentati
- Mongi Ben Hamida National Institute of Neurology, La Rabta, Tunisia
| | - Matthew J Farrer
- Department of Neurology, University of Florida, Gainesville, Florida, USA
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25
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Xin Y, Yuan T, Wang J. The causal relationship between atopic dermatitis and brain cancer: A bidirectional Mendelian randomization study. Skin Res Technol 2024; 30:e13715. [PMID: 38646850 PMCID: PMC11033834 DOI: 10.1111/srt.13715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 04/08/2024] [Indexed: 04/23/2024]
Abstract
BACKGROUND Atopic dermatitis ranks among the prevalent skin disorders. Research has indicated a potential association with brain cancer. Yet, establishing a direct causal relationship between atopic dermatitis and brain cancer continues to be challenging. MATERIALS AND METHODS We extracted single nucleotide polymorphisms (SNPs) significantly associated with atopic dermatitis (sample size = 382 254) at a genome-wide level from a large Finnish Genome-Wide Association Study (GWAS) dataset (n cases = 15 208, n controls = 367 046). Summary data for 372 622 cases of brain cancer (n cases = 606, n controls = 372 016) were obtained via the IEU Open GWAS database. We employed the Inverse Variance Weighted (IVW) method as our primary analytical approach for Mendelian Randomization (MR) analysis. Additionally, heterogeneity was measured using Cochran's Q value, and horizontal pleiotropy was evaluated using MR-Egger 、Mendelian Randomization Pleiotropy RESidual Sum and Outlier and leave-one-out analyses. RESULTS The risk of brain cancer increases with the presence of atopic dermatitis, as evidenced by the odds ratios (ORs) and 95% confidence intervals (CIs),(OR = 1.0005; 95% CI = 1.0001, 1.0009; p = 0.0096). However, when conducting the analysis in reverse, no significant link was observed. CONCLUSION The findings from our study indicate a causative link between atopic dermatitis and brain cancer, highlighting the importance of conducting broader clinical investigations into their potential association going forward.
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Affiliation(s)
- Yu Xin
- Department of DermatologyYijishan Hospital Affiliated With Wannan Medical CollegeWuhuAnhui ProvinceChina
| | - Tao Yuan
- Department of DermatologyYijishan Hospital Affiliated With Wannan Medical CollegeWuhuAnhui ProvinceChina
| | - Jun Wang
- Department of DermatologyYijishan Hospital Affiliated With Wannan Medical CollegeWuhuAnhui ProvinceChina
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Bi W, Li J, Xiong M, Nasifu L, Tan M, Tai P, Jin Q, Zhang L, Zhu C, He B. EGR3 Polymorphism Is a Potential Susceptibility Factor of Schizophrenia Risk in a Chinese Population. Genet Test Mol Biomarkers 2024; 28:144-150. [PMID: 38657122 DOI: 10.1089/gtmb.2023.0562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2024] Open
Abstract
Objective: The purpose of this study was to evaluate the association between the single nucleotide polymorphisms (SNPs) (EGR3 rs1996147; EGR4 rs3813226, rs6747506; ERBB3 rs2292238; and ERBB4 rs707284, rs7560730) and the risk of schizophrenia (SZ) in a Chinese population. Materials and Methods: We conducted a case-control study, including 248 patients with SZ and 236 healthy controls matched for age and sex. The Mass-array platform was used to detect all the genotypes of the SNPs. Results: The results revealed that the EGR3 rs1996147 AA genotype was associated with borderline decreased SZ risk (AA vs. GG: adjusted OR = 0.43, 95% CI: 0.18-1.02, p = 0.06). However, no significant correlation was found between the other SNPs and overall SZ risk. Subgroup analysis also failed to show any significant association between all SNPs and the risk of SZ. Conclusion: In summary, this study revealed that the EGR3 rs1996147 AA genotype was associated with a borderline risk for SZ.
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Affiliation(s)
- Wen Bi
- Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Jingjing Li
- Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Mengqiu Xiong
- Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Lubanga Nasifu
- Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- Department of Biology, Muni University, Arua, Uganda
| | - Mingjuan Tan
- Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Ping Tai
- Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Qing Jin
- Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Lingyun Zhang
- Department of Laboratory Medicine, Zutangshan Hospital, Nanjing, China
| | - Chengbin Zhu
- Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Bangshun He
- Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
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27
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Ojo OO, Bandres-Ciga S, Makarious MB, Crea PW, Hernandez DG, Houlden H, Rizig M, Singleton AB, Noyce AJ, Nalls MA, Blauwendraat C, Okubadejo NU. GBA1 rs3115534 Is Associated with REM Sleep Behavior Disorder in Parkinson's Disease in Nigerians. Mov Disord 2024; 39:728-733. [PMID: 38390630 DOI: 10.1002/mds.29753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 01/25/2024] [Accepted: 02/06/2024] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND Rapid eye movement (REM) sleep behavior disorder (RBD) is an early feature of Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Damaging coding variants in Glucocerebrosidase (GBA1) are a genetic risk factor for RBD. Recently, a population-specific non-coding risk variant (rs3115534) was found to be associated with PD risk and earlier onset in individuals of African ancestry. OBJECTIVES We aimed to investigate whether the GBA1 rs3115534 PD risk variant is associated with RBD in persons with PD. METHODS We studied 709 persons with PD and 776 neurologically healthy controls from Nigeria. All DNA samples were genotyped and imputed, and the GBA1 rs3115534 risk variant was extracted. The RBD screening questionnaire (RBDSQ) was used to assess symptoms of possible RBD. RESULTS RBD was present in 200 PD (28.2%) and 51 (6.6%) controls. We identified that the non-coding GBA1 rs3115534 risk variant is associated with possible RBD in individuals of Nigerian origin (β, 0.3640; standard error [SE], 0.103, P = 4.093e-04), as well as in all samples after adjusting for PD status (β, 0.2542; SE, 0.108; P = 0.019) suggesting that although non-coding, this variant may have the same downstream consequences as GBA1 coding variants. CONCLUSIONS Our results indicate that the non-coding GBA1 rs3115534 risk variant is associated with an increasing number of RBD symptoms in persons with PD of Nigerian origin. Further research is needed to assess if this variant is also associated with polysomnography-defined RBD and with RBD symptoms in DLB. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Oluwadamilola Omolara Ojo
- College of Medicine, University of Lagos, Idi-Araba, Lagos State, Nigeria
- Lagos University Teaching Hospital, Idi-Araba, Lagos State, Nigeria
| | - Sara Bandres-Ciga
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
- UCL Movement Disorders Centre, University College London, London, United Kingdom
| | - Peter Wild Crea
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
- UCL Movement Disorders Centre, University College London, London, United Kingdom
| | - Dena G Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Henry Houlden
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Mie Rizig
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Andrew B Singleton
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Alastair J Noyce
- Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London, United Kingdom
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
- DataTecnica LLC, Washington, District of Columbia, USA
| | - Cornelis Blauwendraat
- Center for Alzheimer's and Related Dementias, National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Njideka Ulunma Okubadejo
- College of Medicine, University of Lagos, Idi-Araba, Lagos State, Nigeria
- Lagos University Teaching Hospital, Idi-Araba, Lagos State, Nigeria
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28
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Gupta P, Sambyal V, Bali JS, Guleria K, Uppal MS, Sudan M. miR-107 and miR-126 and Risk of Breast Cancer: A Case-Control Study. Genet Test Mol Biomarkers 2024; 28:165-168. [PMID: 38487920 DOI: 10.1089/gtmb.2023.0606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2024] Open
Abstract
Background: Micro RNAs are new diagnostic markers and therapeutic targets in breast cancer research. miR-107 and miR-126 have been reported to be linked with the pathogenesis of breast cancer. The present study investigates the levels of expression of miR-107 and miR-126 in patients with breast cancer to find their correlation with the risk of breast cancer in Amritsar, Punjab, Northwest India. Material and Methods: In total, 200 subjects, 100 patients with breast cancer and 100 controls, were enrolled to screen the expression of miR-107 and miR-126 using quantitative reverse transcription polymerase chain reaction (RT-PCR) technique. The Livak method (2-ΔΔCt) was used to calculate the fold change of the expression of micro RNAs. Student t-test was used to calculate the significant change in the expression of miRNAs in patients as compared with controls. Spearman rank correlation coefficient and ROC were conducted. The value of p < 0.05 was considered to indicate a statistically significant difference. Results: miR-107 was downregulated in patients with breast cancer as compared with controls (fold change = 0.467; p = 0.114) but not statistically significant. The expression of miR-126 was found to be 5.37 times elevated in patients with breast cancer, specifically in stage I and stage III patients (p = 0.009), compared with controls, which may indicate its oncogenic activity. The ROC analyses revealed that miR-126 could be a potential diagnostic marker. In conclusion oncogenic behavior of miR-126 is suggestive of its role in pathogenesis in patients with breast cancer.
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Affiliation(s)
- Priyanka Gupta
- Department of Human Genetics, Human Cytogenetics Laboratory, Guru Nanak Dev University, Amritsar, Punjab, India
| | - Vasudha Sambyal
- Department of Human Genetics, Human Cytogenetics Laboratory, Guru Nanak Dev University, Amritsar, Punjab, India
| | - Jagmohan Singh Bali
- Department of Human Genetics, Human Cytogenetics Laboratory, Guru Nanak Dev University, Amritsar, Punjab, India
| | - Kamlesh Guleria
- Department of Human Genetics, Human Cytogenetics Laboratory, Guru Nanak Dev University, Amritsar, Punjab, India
| | - Manjit Singh Uppal
- Department of Surgery, Sri Guru Ram Das Institute of Medical Sciences and Research, Amritsar, Punjab, India
| | - Meena Sudan
- Department of Radiotherapy, Sri Guru Ram Das Institute of Medical Sciences and Research, Amritsar, Punjab, India
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Shah Y, Kulm S, Nauseef JT, Chen Z, Elemento O, Kensler KH, Sharaf RN. Benchmarking multi-ancestry prostate cancer polygenic risk scores in a real-world cohort. PLoS Comput Biol 2024; 20:e1011990. [PMID: 38598551 PMCID: PMC11034641 DOI: 10.1371/journal.pcbi.1011990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 04/22/2024] [Accepted: 03/11/2024] [Indexed: 04/12/2024] Open
Abstract
Prostate cancer is a heritable disease with ancestry-biased incidence and mortality. Polygenic risk scores (PRSs) offer promising advancements in predicting disease risk, including prostate cancer. While their accuracy continues to improve, research aimed at enhancing their effectiveness within African and Asian populations remains key for equitable use. Recent algorithmic developments for PRS derivation have resulted in improved pan-ancestral risk prediction for several diseases. In this study, we benchmark the predictive power of six widely used PRS derivation algorithms, including four of which adjust for ancestry, against prostate cancer cases and controls from the UK Biobank and All of Us cohorts. We find modest improvement in discriminatory ability when compared with a simple method that prioritizes variants, clumping, and published polygenic risk scores. Our findings underscore the importance of improving upon risk prediction algorithms and the sampling of diverse cohorts.
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Affiliation(s)
- Yajas Shah
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York City, New York, United States of America
| | - Scott Kulm
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York City, New York, United States of America
| | - Jones T. Nauseef
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Medicine—Hematology and Medical Oncology, Weill Cornell Medicine, New York City, New York, United States of America
| | - Zhengming Chen
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, New York, United States of America
| | - Olivier Elemento
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York City, New York, United States of America
| | - Kevin H. Kensler
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, New York, United States of America
| | - Ravi N. Sharaf
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Medicine–Gastroenterology and Hepatology, Weill Cornell Medicine, New York City, New York, United States of America
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30
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Shi W, Zhang Q, Lu Y, Liu J, Ma X, Xie Z, Zhang G, Chang M, Tian Y. Association of single nucleotide polymorphisms in ITLN1 gene with ischemic stroke risk in Xi'an population, Shaanxi province. PeerJ 2024; 12:e16934. [PMID: 38529304 PMCID: PMC10962333 DOI: 10.7717/peerj.16934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 01/22/2024] [Indexed: 03/27/2024] Open
Abstract
Background Ischemic stroke (IS) is the main cause of death and adult disability. However, the pathogenesis of this complicated disease is unknown. The present study aimed to assess the relationship between ITLN1 single nucleotide polymorphisms (SNPs) and the susceptibility to IS in Xi'an population, Shaanxi province. Methods In this study, we designed polymerase chain reaction (PCR) primers located at -3,308 bp upstream of the transcription initiation site within promoter region of the ITLN1 gene. The target fragment was amplified by PCR and identified by agarose gel electrophoresis. Sanger sequencing was then performed in the samples extracted from a cohort comprising 1,272 participants (636 controls and 636 cases), and the obtained sequences were compared with the reference sequences available on the National Center for Biotechnology Information (NCBI) website to detect SNPs in the ITLN1 gene promoter region. Logistic regression analysis was employed to assess the relationship between ITLN1 polymorphisms and IS risk, with adjustments for age and gender. Significant positive results were tested by false-positive report probability (FPRP) and false discovery rate (FDR). The interaction among noteworthy SNPs and their predictive relationship with IS risk were explored using the Multi-Factor Dimensionality Reduction (MDR) software. Results The results of Sanger sequencing were compared with the reference sequences on the NCBI website, and we found 14 SNPs in ITLN1 gene promoter satisfied Hardy-Weinberg equilibrium (HWE). Logistic regression analysis showed that ITLN1 was associated with a decreased risk of IS (rs6427553: Homozygous C/C: adjusted OR: 0.69, 95% CI [0.48-0.97]; Log-additive: adjusted OR: 0.83, 95% CI [0.70-0.98]; rs7411035: Homozygous G/G: adjusted OR: 0.66, 95% CI [0.47-0.94]; Dominant G/T-G/G: adjusted OR: 0.78, 95% CI [0.62-0.98]; Log-additive: adjusted OR: 0.81, 95% CI [0.69-0.96]; rs4656958: Heterozygous G/A: adjusted OR: 0.74, 95% CI [0.59-0.94]; Homozygous A/A: adjusted OR: 0.51, 95% CI [0.31-0.84]; Dominant G/A-A/A: adjusted OR: 0.71, 95% CI [0.57-0.89]; Recessive A/A: adjusted OR: 0.59, 95% CI [0.36-0.96]; Log-additive: adjusted OR: 0.73, 95% CI [0.61-0.88]), especially in people aged less than 60 years and males. Conclusions In short, our study revealed a correlation between ITLN1 variants (rs6427553, rs7411035 and rs4656958) and IS risk in Xi'an population, Shaanxi province, laying a foundation for ITLN1 gene as a potential biomarker for predicting susceptibility to IS.
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Affiliation(s)
- Wenzhen Shi
- Clinical Medical Research Center, Xi’an Key Laboratory of Cardiovascular and Cerebrovascular Diseases, the Affiliated Hospital of Northwest University, Xi’an No.3 Hospital, Xi’an, China
| | - Qi Zhang
- Clinical Medical Research Center, Xi’an Key Laboratory of Cardiovascular and Cerebrovascular Diseases, the Affiliated Hospital of Northwest University, Xi’an No.3 Hospital, Xi’an, China
| | - Ying Lu
- Department of Neurology, the Affiliated Hospital of Northwest University, Xi’an No.3 Hospital, Xi’an, China
| | - Jie Liu
- Clinical Medical Research Center, Xi’an Key Laboratory of Cardiovascular and Cerebrovascular Diseases, the Affiliated Hospital of Northwest University, Xi’an No.3 Hospital, Xi’an, China
| | - Xiaojuan Ma
- Clinical Medical Research Center, Xi’an Key Laboratory of Cardiovascular and Cerebrovascular Diseases, the Affiliated Hospital of Northwest University, Xi’an No.3 Hospital, Xi’an, China
| | - Zhen Xie
- Xi’an Key Laboratory of Cardiovascular and Cerebrovascular Diseases, The College of Life Sciences and Medicine, Northwest University, Xi’an, China
| | - Gejuan Zhang
- Department of Neurology, the Affiliated Hospital of Northwest University, Xi’an No.3 Hospital, Xi’an, China
| | - Mingze Chang
- Department of Neurology, the Affiliated Hospital of Northwest University, Xi’an No.3 Hospital, Xi’an, China
| | - Ye Tian
- Department of Neurology, the Affiliated Hospital of Northwest University, Xi’an No.3 Hospital, Xi’an, China
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Rui Y, Zhou J, Zhen X, Zhang J, Liu S, Gao Y. TBX5 genetic variants and SCD-CAD susceptibility: insights from Chinese Han cohorts. PeerJ 2024; 12:e17139. [PMID: 38525280 PMCID: PMC10959103 DOI: 10.7717/peerj.17139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 02/28/2024] [Indexed: 03/26/2024] Open
Abstract
Background The prevention and prediction of sudden cardiac death (SCD) present persistent challenges, prompting exploration into common genetic variations for potential insights. T-box 5 (TBX5), a critical cardiac transcription factor, plays a pivotal role in cardiovascular development and function. This study systematically examined variants within the 500-bp region downstream of the TBX5 gene, focusing on their potential impact on susceptibility to SCD associated with coronary artery disease (SCD-CAD) in four different Chinese Han populations. Methods In a comprehensive case-control analysis, we explored the association between rs11278315 and SCD-CAD susceptibility using a cohort of 553 controls and 201 SCD-CAD cases. Dual luciferase reporter assays and genotype-phenotype correlation studies using human cardiac tissue samples as well as integrated in silicon analysis were applied to explore the underlining mechanism. Result Binary logistic regression results underscored a significantly reduced risk of SCD-CAD in individuals harboring the deletion allele (odds ratio = 0.70, 95% CI [0.55-0.88], p = 0.0019). Consistent with the lower transcriptional activity of the deletion allele observed in dual luciferase reporter assays, genotype-phenotype correlation studies on human cardiac tissue samples affirmed lower expression levels associated with the deletion allele at both mRNA and protein levels. Furthermore, our investigation revealed intriguing insights into the role of rs11278315 in TBX5 alternative splicing, which may contribute to alterations in its ultimate functional effects, as suggested by sQTL analysis. Gene ontology analysis and functional annotation further underscored the potential involvement of TBX5 in alternative splicing and cardiac-related transcriptional regulation. Conclusions In summary, our current dataset points to a plausible correlation between rs11278315 and susceptibility to SCD-CAD, emphasizing the potential of rs11278315 as a genetic risk marker for aiding in molecular diagnosis and risk stratification of SCD-CAD.
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Affiliation(s)
- Yukun Rui
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
| | - Ju Zhou
- Medical College of Soochow University, Suzhou, China
| | - Xiaoyuan Zhen
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
| | - Jianhua Zhang
- Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Sciences, Ministry of Justice, Shanghai, China
| | - Shiquan Liu
- Institute of Evidence Law and Forensic Science, China University of Political Science and Law, Beijing, China
| | - Yuzhen Gao
- Department of Forensic Medicine, Medical College of Soochow University, Suzhou, China
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Khalil MMIM, Monir Mansour M, Bakrey Hamed Ata M, Elaskary SA, Genena SESR. Toll-like receptor 7 and tumor necrosis factor alpha polymorphisms in Egyptian patients with autoimmune thyroid diseases. J Immunoassay Immunochem 2024; 45:93-111. [PMID: 38174954 DOI: 10.1080/15321819.2023.2294298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Hashimoto's thyroiditis (HT) and Graves' disease (GD) susceptibility depends on a complex interaction between environmental and genetic factors. Genes for tumor necrosis factor alpha (TNF-α) and toll-like receptors (TLRs) have been incorporated into the pathophysiology of autoimmune disorders. Our aim is to assess the association between TLR7 (rs179009) and TNF-α (rs1800629) polymorphisms and susceptibility to autoimmune thyroid disorders. One-hundred ninety-nine individuals, divided into 68 HT patients in group I, 57 GD patients in group II, and 74 age- and gender-matched healthy subjects in group III, underwent laboratory investigations, including the detection of TLR7 and TNF-α polymorphisms using real-time PCR technique. TLR7 (rs179009) genotypes, A/G and G/G, were significantly more prevalent in HT patients (group I) compared to normal controls. Meanwhile, TNF-α (rs1800629) genotypes in GD patients (group II) showed a six fold increase in the risk of the disease in the G/A and A/A genotypes. Our findings propose the fact that the polymorphisms of TLR7 (rs179009) play a role in the susceptibility and the development of Hashimoto's thyroiditis, whereas TNF-α (rs1800629) polymorphisms play a role in the susceptibility and development of Graves' disease.
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Affiliation(s)
| | - Manal Monir Mansour
- Department of Clinical Pathology, Faculty of Medicine, Menoufia University Menoufia Governorate, Shebein-El-Kom, Egypt
| | - Moustafa Bakrey Hamed Ata
- Department of Internal Medicine, Faculty of Medicine, Menoufia University Menoufia Governorate, Shebein-El-Kom, Egypt
| | - Shymaa Abdelsattar Elaskary
- Department of Medical Microbiology and Immunology, Faculty of Medicine, Menoufia University Menoufia Governorate, Shebein-El-Kom, Egypt
| | - Shaimaa El Sayed Ramadan Genena
- Department of Medical Biochemistry and Molecular Biology, Faculty of Medicine, Menoufia University, Shebein-El-Kom, Egypt
- Medical Microbiology and Immunology, Faculty of Medicine, King Abdulaziz University, Rabigh, Saudi Arabia
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Pan C, Cheng S, Liu L, Chen Y, Meng P, Yang X, Li C, Zhang J, Zhang Z, Zhang H, Cheng B, Wen Y, Jia Y, Zhang F. Identification of novel rare variants for anxiety: an exome-wide association study in the UK Biobank. Prog Neuropsychopharmacol Biol Psychiatry 2024; 130:110928. [PMID: 38154517 DOI: 10.1016/j.pnpbp.2023.110928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 11/19/2023] [Accepted: 12/23/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND Rare variants are believed to play a substantial role in the genetic architecture of mental disorders, particularly in coding regions. However, limited evidence supports the impact of rare variants on anxiety. METHODS Using whole-exome sequencing data from 200,643 participants in the UK Biobank, we investigated the contribution of rare variants to anxiety. Firstly, we computed genetic risk score (GRS) of anxiety utilizing genotype data and summary data from a genome-wide association study (GWAS) on anxiety disorder. Subsequently, we identified individuals within the lowest 50% GRS, a subgroup more likely to carry pathogenic rare variants. Within this subgroup, we classified individuals with the highest 10% 7-item Generalized Anxiety Disorder scale (GAD-7) score as cases (N = 1869), and those with the lowest 10% GAD-7 score were designated as controls (N = 1869). Finally, we conducted gene-based burden tests and single-variant association analyses to assess the relationship between rare variants and anxiety. RESULTS Totally, 47,800 variants with MAF ≤0.01 were annotated as non-benign coding variants, consisting of 42,698 nonsynonymous SNVs, 489 nonframeshift substitution, 236 frameshift substitution, 617 stop-gain and 40 stop-loss variants. After variation aggregation, 5066 genes were included in gene-based association analysis. Totally, 11 candidate genes were detected in burden test, such as RNF123 (PBonferroni adjusted = 3.40 × 10-6), MOAP1(PBonferroni adjusted = 4.35 × 10-4), CCDC110 (PBonferroni adjusted = 5.83 × 10-4). Single-variant test detected 9 rare variants, such as rs35726701(RNF123)(PBonferroni adjusted = 3.16 × 10-10) and rs16942615(CAMTA2) (PBonferroni adjusted = 4.04 × 10-4). Notably, RNF123, CCDC110, DNAH2, and CSKMT gene were identified in both tests. CONCLUSIONS Our study identified novel candidate genes for anxiety in protein-coding regions, revealing the contribution of rare variants to anxiety.
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Affiliation(s)
- Chuyu Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Yujing Chen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Chun'e Li
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Jingxi Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Zhen Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Huijie Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, P. R. China.
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Liang Y, Deng MG, Jian Q, Liu M, Fang K, Chen S. Maternal history of Alzheimer's disease predisposes to altered serum cholesterol levels in adult offspring. J Neurochem 2024; 168:303-311. [PMID: 38316937 DOI: 10.1111/jnc.16056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Revised: 01/08/2024] [Accepted: 01/08/2024] [Indexed: 02/07/2024]
Abstract
Controversial findings regarding the association between serum cholesterol levels and Alzheimer's disease (AD) have been identified through observational studies. The genetic basis shared by both factors and the causality between them remain largely unknown. The objective of this study is to examine the causal impact of maternal history of AD on changes in serum cholesterol levels in adult offspring. By retrieving genetic variants from summary statistics of large-scale genome-wide association study of maternal history of AD (European-based: Ncase = 27 696, Ncontrol = 260 980). The causal association between genetically predicted maternal history of AD and changes in serum cholesterol levels in adult offspring was examined using the two-sample Mendelian randomization (MR) method. Causal impact estimates were calculated using single-nucleotide polymorphisms in both univariable MR (UMR) and multivariable MR (MVMR) analyses. Additionally, other approaches, such as Cochran's Q test and leave-one-out variant analysis, were employed to correct for potential biases. The results of UMR presented that genetically predicted maternal history of AD was positively associated with hypercholesterolemia (OR = 1.014; 95% CI: 1.009-1.018; p < 0.001), total cholesterol (OR = 1.29; 95% CI: 1.134-1.466; p < 0.001) and low-density lipoprotein (OR = 1.525; 95% CI: 1.272-1.828; p < 0.001) among adult offspring. Genetic predisposition for maternal history of AD to be negatively associated with high-density lipoprotein (OR = 0.889; 95% CI: 0.861-0.917; p < 0.001). The MVMR analysis remained robust and significant after adjusting for diabetes and obesity in offspring. Sufficient evidence was provided in this study to support the putative causal impact of maternal history of AD on the change of serum cholesterol profile in adult offspring. In clinical practice, priority should be given to the detection and monitoring of cholesterol levels in individuals with a maternal history of AD, particularly in the early stages.
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Affiliation(s)
- Yuehui Liang
- School of Public Health, Wuhan University, Wuhan, China
| | - Ming-Gang Deng
- Department of Psychiatry, Wuhan Mental Health Centre, Wuhan, China
- Department of Psychiatry, Wuhan Hospital for Psychotherapy, Wuhan, China
| | - Qinghong Jian
- The Affiliated Stomatology Hospital of Southwest Medical University, Luzhou, China
| | - Mingwei Liu
- School of Public Health, Wuhan University, Wuhan, China
- Julius Global Health, The Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Kui Fang
- Department of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Shuai Chen
- School of Public Health, Wuhan University, Wuhan, China
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Jacobs MF, Goldman JW, Austin S, Koeppe ES, Murad AM, Koschmann CJ, Chinnaiyan AM, Mody RJ. Family Recall of and Response to Germline Pathologic Variants Found on Paired Tumor-Germline Sequencing in Pediatric Oncology. JCO Precis Oncol 2024; 8:e2300539. [PMID: 38484211 PMCID: PMC10954074 DOI: 10.1200/po.23.00539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 12/19/2023] [Accepted: 01/09/2024] [Indexed: 03/19/2024] Open
Abstract
PURPOSE Paired tumor-germline sequencing can identify somatic variants for targeted therapy and germline pathogenic variants (GPVs) causative of hereditary cancer/tumor predisposition syndromes. It is unknown how patients/families in pediatric oncology use information about an identified GPV. We assessed recall of germline results and actions taken on the basis of findings. METHODS We completed phone surveys with patients (and/or their parent) with GPVs identified via a single academic medical center's paired tumor-germline sequencing study. Seven hundred forty pediatric (aged 0-25 years) oncology patients were enrolled in this sequencing study between May 2012 and August 2021. Ninety-six participants (13.0%) had at least one GPV identified and were therefore eligible for this survey. The parent/guardian (for patients younger than 18 years or deceased patients) or patients themselves (if 18 years or older) were contacted. Survey topics included germline result recall, experience with genetic counseling, changes to patient's cancer treatment/screening, sharing of results with family members, and lifestyle changes. RESULTS Fifty-three surveys (response rate, 55.2%) were completed between October 2021 and June 2022. Thirty-seven (69.8%) respondents correctly recalled the identified GPV. Discussing results with a genetic counselor (P = .0001), having a GPV related to the cancer/tumor diagnosis (P = .002), and non-Hispanic White race/ethnicity (P = .02) were associated with accurate recall. Twenty-five respondents (47.2%) reported a change in the child's cancer treatment and/or screening recommendations, 17 respondents (32.1%) made a lifestyle change on the basis of the results, and 44 respondents (83.0%) shared results with at least one family member. CONCLUSION While most respondents remembered that a GPV was identified in the patient, some did not recall having a GPV found, and others recalled germline findings incorrectly. Future work may determine patient/family preferences for timing/method of result return to optimize patient recall and use of germline results.
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Affiliation(s)
- Michelle F. Jacobs
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI
| | | | - Sarah Austin
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI
| | - Erika S. Koeppe
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI
| | | | | | - Arul M. Chinnaiyan
- Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI
| | - Rajen J. Mody
- Department of Pediatrics, University of Michigan, Ann Arbor, MI
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Dai J, Jiang H, Cheng Z, Li Y, Tang X. Genetic polymorphism of KIAA1217 is functionally associated with lumbar disc herniation in the Chinese population. Neurochirurgie 2024; 70:101538. [PMID: 38311218 DOI: 10.1016/j.neuchi.2024.101538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/24/2024] [Accepted: 01/25/2024] [Indexed: 02/10/2024]
Abstract
BACKGROUND Genetic polymorphism of KIAA1217 has been reported to be associated with lumbar disc herniation (LDH) in different populations such as Japanese population and Finnish population. This study aimed to explore whether the genetic polymorphism of KIAA1217 is functionally associated with LDH in Chinese population. METHODS SNP rs16924573 of KIAA1217 was genotyped in 1272 patients and 1248 healthy controls. The mRNA expression of KIAA1217 in the intervertebral disc was analyzed for 84 patients and 32 controls. The differences of genotype and allele distributions between LDH patients and healthy controls were evaluated using the Chi-square test. One-way ANOVA test was used to compare the relationship between genotypes and tissue expression of KIAA1217. RESULTS Patients were found to have significantly higher frequency of genotype GG of rs16924573 than the controls (64.2% vs. 52.8%, p<0.001). The frequency of allele G was remarkably higher in the patients than in the controls (79.8% vs. 73.2%, p<0.001), with an OR of 1.45 (95% confidential interval=1.27-1.66). Compared with the controls, LDH patients were observed to have significantly decreased expression of KIAA1217. Patients with genotype GG had remarkably lower mRNA expression of KIAA1217 than those with genotype AG or AA (p=0.01). CONCLUSIONS SNP rs16924573 of KIAA1217 could be functionally associated with LDH in the Chinese population. More in vivo and vitro experiments need to be carried out to further clarify the regulatory mechanism of functional variants in KIAA1217.
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Affiliation(s)
- Jian Dai
- Department of Orthopaedics, Huai'an First People's Hospital, Nanjing Medical University, Huai'an, Jiangsu 223300, People's Republic of China
| | - Haitao Jiang
- Department of Orthopaedics, Huai'an First People's Hospital, Nanjing Medical University, Huai'an, Jiangsu 223300, People's Republic of China
| | - Zhang Cheng
- Department of Orthopaedics, Huai'an First People's Hospital, Nanjing Medical University, Huai'an, Jiangsu 223300, People's Republic of China
| | - Yao Li
- Department of Orthopaedics, Huai'an First People's Hospital, Nanjing Medical University, Huai'an, Jiangsu 223300, People's Republic of China
| | - Xiaoming Tang
- Department of Orthopaedics, Huai'an First People's Hospital, Nanjing Medical University, Huai'an, Jiangsu 223300, People's Republic of China.
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Govahi Kakhki F, Sargazi S, Montazerifar F, Majidpour M, Karajibani A, Karajibani M, Ghasemi M. IGF2BP2 and IGFBP3 Genotypes, Haplotypes, and Genetic Models Studies in Polycystic Ovary Syndrome. J Clin Lab Anal 2024; 38:e25021. [PMID: 38468402 PMCID: PMC10959184 DOI: 10.1002/jcla.25021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 01/20/2024] [Accepted: 02/15/2024] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND Insulin resistance has been correlated with the genetic diversity within the insulin-like binding proteins genes. Moreover, insulin resistance is one of the key characteristics of the widespread reproductive endocrine condition known as polycystic ovarian syndrome (PCOS). Hence, this study is aimed to determine the association between IGFBP3 and IGF2BP2 gene variants and PCOS risk. METHODS A total of 300 subjects (150 PCOS cases diagnosed based on Rotterdam ESHRE/ASRM consensus criteria and 150 healthy subjects) were recruited in this case-control cross-sectional study. Tetra-primer amplification refractory mutation system polymerase chain reaction (ARMS-PCR) was used for genotyping rs11705701, whereas genotyping of rs1470579 and rs2854744 was done employing PCR-restriction fragment length polymorphism (PCR-RFLP) technique. RESULTS The CC and AA+AC genotypes of rs1470579 conferred an increased risk of PCOS in our population. Regarding the rs2854744, an increased risk of PCOS was observed under the codominant homozygous (TT vs. GG) model by 2.54 fold. The C allele of rs1470579 and T allele of rs2854744 enhanced PCOS risk by 1.97 and 1.46 folds, respectively. Haplotype analysis showed that the Ars1470579Ars11705701 haplotype conferred a decreased risk of PCOS (odds ratio = 0.53, 95% confidence interval = 0.34-0.83, p = 0.006). The AC/GG/GT, AA/GA/GT, AC/GA/GG, and AC/GA/GT genotype combinations of rs1470579/rs11705701/rs2854744 were associated with a decreased risk of the disease. CONCLUSIONS IGF2BP2 rs1470579 and IGFBP3 rs2854744 enhanced PCOS susceptibility in a Southeastern Iranian population. Further investigation involving larger cohorts representing diverse ethnic backgrounds is needed to confirm the current findings.
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Affiliation(s)
- Fatemeh Govahi Kakhki
- Department of Nutrition, School of MedicineZahedan University of Medical SciencesZahedanIran
| | - Saman Sargazi
- Cellular and Molecular Research Center, Research Institute of Cellular and Molecular Sciences in Infectious DiseasesZahedan University of Medical SciencesZahedanIran
- Department of Clinical Biochemistry, School of MedicineZahedan University of Medical SciencesZahedanIran
| | - Farzaneh Montazerifar
- Department of Nutrition, School of MedicineZahedan University of Medical SciencesZahedanIran
- Pregnancy Health Research CenterZahedan University of Medical SciencesZahedanIran
| | - Mahdi Majidpour
- Clinical Immunology Research Center, Zahedan University of Medical SciencesZahedanIran
| | - Atena Karajibani
- Department of BiologyUniversity of Sistan and BaluchestanZahedanIran
| | - Mansour Karajibani
- Department of Nutrition, School of MedicineZahedan University of Medical SciencesZahedanIran
- Health Promotion Research CenterZahedan University of Medical SciencesZahedanIran
| | - Marzieh Ghasemi
- Pregnancy Health Research CenterZahedan University of Medical SciencesZahedanIran
- Moloud Infertility Center, Ali Ibn Abitaleb HospitalZahedan University of Medical SciencesZahedanIran
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Zhu H, Choi J, Kui N, Yang T, Wei P, Li D, Sun R. Identification of Pancreatic Cancer Germline Risk Variants With Effects That Are Modified by Smoking. JCO Precis Oncol 2024; 8:e2300355. [PMID: 38564682 DOI: 10.1200/po.23.00355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 12/08/2023] [Accepted: 02/08/2024] [Indexed: 04/04/2024] Open
Abstract
PURPOSE Pancreatic cancer (PC) is a deadly disease most often diagnosed in late stages. Identification of high-risk subjects could both contribute to preventative measures and help diagnose the disease at earlier timepoints. However, known risk factors, assessed independently, are currently insufficient for accurately stratifying patients. We use large-scale data from the UK Biobank (UKB) to identify genetic variant-smoking interaction effects and show their importance in risk assessment. METHODS We draw data from 15,086,830 genetic variants and 315,512 individuals in the UKB. There are 765 cases of PC. Crucially, robust resampling corrections are used to overcome well-known challenges in hypothesis testing for interactions. Replication analysis is conducted in two independent cohorts totaling 793 cases and 570 controls. Integration of functional annotation data and construction of polygenic risk scores (PRS) demonstrate the additional insight provided by interaction effects. RESULTS We identify the genome-wide significant variant rs77196339 on chromosome 2 (per minor allele odds ratio in never-smokers, 2.31 [95% CI, 1.69 to 3.15]; per minor allele odds ratio in ever-smokers, 0.53 [95% CI, 0.30 to 0.91]; P = 3.54 × 10-8) as well as eight other loci with suggestive evidence of interaction effects (P < 5 × 10-6). The rs77196339 region association is validated (P < .05) in the replication sample. PRS incorporating interaction effects show improved discriminatory ability over PRS of main effects alone. CONCLUSION This study of genome-wide germline variants identified smoking to modify the effect of rs77196339 on PC risk. Interactions between known risk factors can provide critical information for identifying high-risk subjects, given the relative inadequacy of models considering only main effects, as demonstrated in PRS. Further studies are necessary to advance toward comprehensive risk prediction approaches for PC.
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Affiliation(s)
- Huili Zhu
- Section of Hematology and Oncology, Department of Medicine, Baylor College of Medicine, Houston, TX
| | - Jaihee Choi
- Department of Statistics, Rice University, Houston, TX
| | - Naishu Kui
- Department of Biostatistics, University of Texas School of Public Health, Houston, TX
| | - Tianzhong Yang
- Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Peng Wei
- Department of Biostatistics, Division of Basic Science, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Ryan Sun
- Department of Biostatistics, Division of Basic Science, The University of Texas MD Anderson Cancer Center, Houston, TX
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Tang F, Yang L, Yang W, Li C, Zhang J, Liu J. The genetic susceptibility analysis of TAAR1 rs8192620 to methamphetamine and heroin abuse and its role in impulsivity. Eur Arch Psychiatry Clin Neurosci 2024; 274:453-459. [PMID: 37145176 DOI: 10.1007/s00406-023-01613-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Accepted: 04/16/2023] [Indexed: 05/06/2023]
Abstract
Abnormal genetic polymorphism of trace amine-associated receptor 1 (TAAR1) rs8192620 site has been confirmed to induce methamphetamine (MA) use and drug craving. However, the genetic susceptibility difference between MA addicts and heroin addicts is unknown. This study evaluated genetic heterogeneity of TAAR1 rs8192620 between MA and heroin addicts and elucidated whether rs8192620 genotypes associated with discrepancy in emotional impulsivity, which would help to instruct individualized treatment in addiction via acting on TAAR1 and evaluate risk of varied drug addiction. Participants consisting of gender-matched 63 MA and 71 heroin abusers were enrolled in the study. Due to mixed drug usage in some MA addicts, MA users were further subdivided into 41 only-MA (only MA taking) and 22 mixed-drug (Magu composed of about 20% MA and 70% caffeine) abusers. Via inter-individual single nucleotide polymorphism (SNP) analysis and two-sample t tests, respectively, the genotypic and Barratt Impulsiveness Scale-11 (BIS-11) scores differences between groups were completed. With following genotypic stratification, the differences in BIS-11 scores between groups were analyzed through two-sample t test. Individual SNP analysis showed significant differences in alleles distribution of rs8192620 between MA and heroin subjects (p = 0.019), even after Bonferroni correction. The TT homozygotes of rs8192620 dominated in MA participants, while C-containing genotypes in heroin (p = 0.026). There was no association of genotypes of TAAR1 rs8192620 with addicts' impulsivity. Our research indicates that the TAAR1 gene polymorphism might mediate the susceptibility discrepancy between MA and heroin abuse.
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Affiliation(s)
- Fei Tang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Longtao Yang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Wenhan Yang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Cong Li
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jun Zhang
- Hunan Judicial Police Academy, Changsha, China
| | - Jun Liu
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China.
- Clinical Research Center for Medical Imaging in Hunan Province, Changsha, China.
- Department of Radiology Quality Control Center in Hunan Province, Changsha, China.
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Yang ML, Xu C, Gupte T, Hoffmann TJ, Iribarren C, Zhou X, Ganesh SK. Sex-specific genetic architecture of blood pressure. Nat Med 2024; 30:818-828. [PMID: 38459180 DOI: 10.1038/s41591-024-02858-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 02/05/2024] [Indexed: 03/10/2024]
Abstract
The genetic and genomic basis of sex differences in blood pressure (BP) traits remain unstudied at scale. Here, we conducted sex-stratified and combined-sex genome-wide association studies of BP traits using the UK Biobank resource, identifying 1,346 previously reported and 29 new BP trait-associated loci. Among associated loci, 412 were female-specific (Pfemale ≤ 5 × 10-8; Pmale > 5 × 10-8) and 142 were male-specific (Pmale ≤ 5 × 10-8; Pfemale > 5 × 10-8); these sex-specific loci were enriched for hormone-related transcription factors, in particular, estrogen receptor 1. Analyses of gene-by-sex interactions and sexually dimorphic effects identified four genomic regions, showing female-specific associations with diastolic BP or pulse pressure, including the chromosome 13q34-COL4A1/COL4A2 locus. Notably, female-specific pulse pressure-associated loci exhibited enriched acetylated histone H3 Lys27 modifications in arterial tissues and a female-specific association with fibromuscular dysplasia, a female-biased vascular disease; colocalization signals included Chr13q34: COL4A1/COL4A2, Chr9p21: CDKN2B-AS1 and Chr4q32.1: MAP9 regions. Sex-specific and sex-biased polygenic associations of BP traits were associated with multiple cardiovascular traits. These findings suggest potentially clinically significant and BP sex-specific pleiotropic effects on cardiovascular diseases.
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Affiliation(s)
- Min-Lee Yang
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Chang Xu
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Trisha Gupte
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Thomas J Hoffmann
- Department of Epidemiology & Biostatistics, and Institute for Human Genetics, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - Xiang Zhou
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Santhi K Ganesh
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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Rezqallah A, Torres-Esquius S, Llop-Guevara A, Cruellas M, Martinez MT, Romey M, Denkert C, Serra V, Chirivella I, Balmaña J. Two Germline Pathogenic Variants in Cancer Susceptibility Genes and Their Null Implication in Breast Cancer Pathogenesis: The Importance of Tumoral Homologous Recombination Deficiency Testing. JCO Precis Oncol 2024; 8:e2300446. [PMID: 38513169 DOI: 10.1200/po.23.00446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 12/28/2023] [Accepted: 01/22/2024] [Indexed: 03/23/2024] Open
Abstract
Homologous recombination proficiency in patients with breast cancer despite germline PALB2/RAD51C pathogenic variants.
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Affiliation(s)
- Alejandra Rezqallah
- Hereditary Cancer Genetics Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - Sara Torres-Esquius
- Hereditary Cancer Genetics Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - Alba Llop-Guevara
- Experimental Therapeutics Group, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Mara Cruellas
- Medical Oncology Department, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - María T Martinez
- Medical Oncology Department, INCLIVA Biomedical Research Institute, Hospital Clínico de València, University of Valencia, Valencia, Spain
| | - Marcel Romey
- Institute of Pathology, Universitätsklinikum Marburg, Marburg, Germany
| | - Carsten Denkert
- Institute of Pathology, Universitätsklinikum Marburg, Marburg, Germany
| | - Violeta Serra
- Experimental Therapeutics Group, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Isabel Chirivella
- Medical Oncology Department, INCLIVA Biomedical Research Institute, Hospital Clínico de València, University of Valencia, Valencia, Spain
| | - Judith Balmaña
- Hereditary Cancer Genetics Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
- Medical Oncology Department, Hospital Universitari Vall d'Hebron, Barcelona, Spain
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Wang T, Yan Z, Zhang Y, Lou Z, Zheng X, Mai D, Wang Y, Shang X, Xiao B, Peng J, Chen J. postGWAS: A web server for deciphering the causality post the genome-wide association studies. Comput Biol Med 2024; 171:108108. [PMID: 38359659 DOI: 10.1016/j.compbiomed.2024.108108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 01/23/2024] [Accepted: 02/04/2024] [Indexed: 02/17/2024]
Abstract
While genome-wide association studies (GWAS) have unequivocally identified vast disease susceptibility variants, a majority of them are situated in non-coding regions and are in high linkage disequilibrium (LD). To pave the way of translating GWAS signals to clinical drug targets, it is essential to identify the underlying causal variants and further causal genes. To this end, a myriad of post-GWAS methods have been devised, each grounded in distinct principles including fine-mapping, co-localization, and transcriptome-wide association study (TWAS) techniques. Yet, no platform currently exists that seamlessly integrates these diverse post-GWAS methodologies. In this work, we present a user-friendly web server for post-GWAS analysis, that seamlessly integrates 9 distinct methods with 12 models, categorized by fine-mapping, colocalization, and TWAS. The server mainly helps users decipher the causality hindered by complex GWAS signals, including casual variants and casual genes, without the burden of computational skills and complex environment configuration, and provides a convenient platform for post-GWAS analysis, result visualization, facilitating the understanding and interpretation of the genome-wide association studies. The postGWAS server is available at http://g2g.biographml.com/.
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Affiliation(s)
- Tao Wang
- School of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China; Key Laboratory of Big Data Storage and Management, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi'an, 710072, China
| | - Zhihao Yan
- School of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China; Key Laboratory of Big Data Storage and Management, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi'an, 710072, China
| | - Yiming Zhang
- School of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Zhuofei Lou
- School of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Xiaozhu Zheng
- Department of Anesthesiology, The People's Hospital of Yubei District, Chongqing, 401120, China
| | - DuoDuo Mai
- School of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China; Key Laboratory of Big Data Storage and Management, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi'an, 710072, China
| | - Yongtian Wang
- School of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China; Key Laboratory of Big Data Storage and Management, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi'an, 710072, China
| | - Xuequn Shang
- School of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China; Key Laboratory of Big Data Storage and Management, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi'an, 710072, China
| | - Bing Xiao
- School of Automation, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Jiajie Peng
- School of Computer Science, Northwestern Polytechnical University, Xi'an, 710072, China; Key Laboratory of Big Data Storage and Management, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi'an, 710072, China
| | - Jing Chen
- School of Computer Science and Engineering, Xi'an University of Technology, Xi'an, 710048, China.
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Schwabe I, Jović M, Rimfeld K, Allegrini AG, van den Berg SM. Genotype-Environment Interaction in ADHD: Genetic Predisposition Determines the Extent to Which Environmental Influences Explain Variability in the Symptom Dimensions Hyperactivity and Inattention. Behav Genet 2024; 54:169-180. [PMID: 38270759 PMCID: PMC10861382 DOI: 10.1007/s10519-023-10168-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 11/22/2023] [Indexed: 01/26/2024]
Abstract
Although earlier research has shown that individual differences on the spectrum of attention deficit hyperactivity disorder (ADHD) are highly heritable, emerging evidence suggests that symptoms are associated with complex interactions between genes and environmental influences. This study investigated whether a genetic predisposition [Note that the term 'genetic predisposition' was used in this manuscript to refer to an estimate based on twin modeling (an individual's score on the latent trait that resembles additive genetic influences) in the particular population being examined.] for the symptom dimensions hyperactivity and inattention determines the extent to which unique-environmental influences explain variability in these symptoms. To this purpose, we analysed a sample drawn from the Twins Early Development Study (TEDS) that consisted of item-level scores of 2168 16-year-old twin pairs who completed both the Strengths and Difficulties Questionnaire (SDQ; Goodman, in J Child Psychol Psychiatry 38:581-586, 1997) and the Strength and Weaknesses of ADHD Symptoms and Normal Behavior (SWAN; Swanson, in Paper presented at the meeting of the American Psychological Association, Los Angeles, 1981) questionnaire. To maximize the psychometric information to measure ADHD symptoms, psychometric analyses were performed to investigate whether the items from the two questionnaires could be combined to form two longer subscales. In the estimation of genotype-environment interaction, we corrected for error variance heterogeneity in the measurement of ADHD symptoms through the application of item response theory (IRT) measurement models. A positive interaction was found for both hyperactivity (e.g., [Formula: see text] = 2.20 with 95% highest posterior density interval equal to [1.79;2.65] and effect size equal to 3.00) and inattention (e.g., [Formula: see text] = 2.16 with 95% highest posterior density interval equal to [1.56;2.79] and effect size equal to 3.07). These results indicate that unique-environmental influences were more important in creating individual differences in both hyperactivity and inattention for twins with a genetic predisposition for these symptoms than for twins without such a predisposition.
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Affiliation(s)
- Inga Schwabe
- Department of Methodology and Statistics, Tilburg University, Tilburg, The Netherlands.
| | - Miljan Jović
- Department of Cognition, Data and Education (CODE), University of Twente, Enschede, The Netherlands
| | - Kaili Rimfeld
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychology, Royal Holloway, University of London, Egham, UK
| | - Andrea G Allegrini
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Division of Psychology and Language Sciences, Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Stéphanie M van den Berg
- Department of Cognition, Data and Education (CODE), University of Twente, Enschede, The Netherlands
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Bick AG, Metcalf GA, Mayo KR, Lichtenstein L, Rura S, Carroll RJ, Musick A, Linder JE, Jordan IK, Nagar SD, Sharma S, Meller R, Basford M, Boerwinkle E, Cicek MS, Doheny KF, Eichler EE, Gabriel S, Gibbs RA, Glazer D, Harris PA, Jarvik GP, Philippakis A, Rehm HL, Roden DM, Thibodeau SN, Topper S, Blegen AL, Wirkus SJ, Wagner VA, Meyer JG, Cicek MS, Muzny DM, Venner E, Mawhinney MZ, Griffith SML, Hsu E, Ling H, Adams MK, Walker K, Hu J, Doddapaneni H, Kovar CL, Murugan M, Dugan S, Khan Z, Boerwinkle E, Lennon NJ, Austin-Tse C, Banks E, Gatzen M, Gupta N, Henricks E, Larsson K, McDonough S, Harrison SM, Kachulis C, Lebo MS, Neben CL, Steeves M, Zhou AY, Smith JD, Frazar CD, Davis CP, Patterson KE, Wheeler MM, McGee S, Lockwood CM, Shirts BH, Pritchard CC, Murray ML, Vasta V, Leistritz D, Richardson MA, Buchan JG, Radhakrishnan A, Krumm N, Ehmen BW, Schwartz S, Aster MMT, Cibulskis K, Haessly A, Asch R, Cremer A, Degatano K, Shergill A, Gauthier LD, Lee SK, Hatcher A, Grant GB, Brandt GR, Covarrubias M, Banks E, Able A, Green AE, Carroll RJ, Zhang J, Condon HR, Wang Y, Dillon MK, Albach CH, Baalawi W, Choi SH, Wang X, Rosenthal EA, Ramirez AH, Lim S, Nambiar S, Ozenberger B, Wise AL, Lunt C, Ginsburg GS, Denny JC. Genomic data in the All of Us Research Program. Nature 2024; 627:340-346. [PMID: 38374255 PMCID: PMC10937371 DOI: 10.1038/s41586-023-06957-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 12/08/2023] [Indexed: 02/21/2024]
Abstract
Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics1-4. The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health5,6. Here we describe the programme's genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all.
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Jegodzinski L, Gebauer J. [Tumor predisposition in endocrinology - from MEN to FIPA]. Dtsch Med Wochenschr 2024; 149:283-289. [PMID: 38412983 DOI: 10.1055/a-2131-2450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
Understanding genetic predisposition has a significant impact on the management of patients with endocrine tumours, including therapy, early detection and prevention. These tumours, which develop as part of a familial predisposition, often manifest early in life and frequently affect several endocrine organs. In the following article, both common syndromes, such as multiple endocrine neoplasia (MEN) syndromes, and rare syndromes, such as familial isolated pituitary adenoma (FIPA), are presented based on their indicator diseases.
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Affiliation(s)
- Lina Jegodzinski
- Medizinische Klinik 1, Bereich Endokrinologie und Diabetologie, Universitätsklinikum Schleswig Holstein, Campus Lübeck, Lübeck
| | - Judith Gebauer
- Medizinische Klinik 1, Bereich Endokrinologie und Diabetologie, Universitätsklinikum Schleswig Holstein, Campus Lübeck, Lübeck
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Torrey EF. Did the human genome project affect research on Schizophrenia? Psychiatry Res 2024; 333:115691. [PMID: 38219345 DOI: 10.1016/j.psychres.2023.115691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 12/15/2023] [Accepted: 12/21/2023] [Indexed: 01/16/2024]
Abstract
The Human Genome Project was undertaken primarily to discover genetic causes and better treatments for human diseases. Schizophrenia was targeted since three of the project`s principal architects had a personal interest and also because, based on family, adoption, and twin studies, schizophrenia was widely believed to be a genetic disorder. Extensive studies using linkage analysis, candidate genes, genome wide association studies [GWAS], copy number variants, exome sequencing and other approaches have failed to identify causal genes. Instead, they identified almost 300 single nucleotide polymorphisms [SNPs] associated with altered risks of developing schizophrenia as well as some rare variants associated with increased risk in a small number of individuals. Risk genes play a role in the clinical expression of most diseases but do not cause the disease in the absence of other factors. Increasingly, observers question whether schizophrenia is strictly a genetic disorder. Beginning in 1996 NIMH began shifting its research resources from clinical studies to basic research based on the promise of the Human Genome Project. Consequently, three decades later NIMH's genetics investment has yielded almost nothing clinically useful for individuals currently affected. It is time to review NIMH`s schizophrenia research portfolio.
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Gowtham P, Girigoswami K, Thirumalai A, Harini K, Pallavi P, Girigoswami A. Association of TIMP2 418 G/C and MMP Gene Polymorphism with Risk of Urinary Cancers: Systematic Review and Meta-analysis. Genet Test Mol Biomarkers 2024; 28:83-90. [PMID: 38478803 DOI: 10.1089/gtmb.2023.0457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/10/2024] Open
Abstract
Aim: The matrix metalloproteinases (MMPs) inhibit tissue inhibitors of metalloproteinases (TIMPs), playing a notable role in various biological processes, and mutations in TIMP2 genes impact a variety of urinary cancers. In this study, we analyze and evaluate the potential involvement of the TIMP2 418 G/C and MMP gene polymorphism in the etiology of urinary cancer. Methodology: For suitable case-control studies, a literature search was undertaken from various database sources such as PubMed, EMBASE, and Google Scholar. Incorporated into the analysis were case-control or cohort studies that documented the correlation between TIMP2 418 G/C and urological cancers. MetaGenyo served as the tool for conducting the meta-analysis, employing a fixed-effects model. The collective odds ratios, along with their corresponding 95% confidence intervals, were calculated and presented to assess the robustness of the observed associations. Results: A total of seven studies involving controls and cases out of recorded 1265 controls and 1154 cases were analyzed to ascertain the significant association of the TIMP2 gene with urologic cancer. No statistically significant correlation was observed between allelic, recessive, dominant, and overdominant models for the genetic variant under investigation. A 95% confidence interval (CI) and odds ratio (OR) were computed for each model, considering p-values <0.05. The OR and 95% CI for the allelic model were 0.99 and 0.77-1.27, respectively, whereas the respective values were 1.00 and 0.76-1.32 for the recessive model. In the dominant contrast model, OR and 95% CI were 1.09 and 0.62-1.90, while the same were 0.93 and 0.77-1.12 for the overdominant model. A funnel plot was used to reanalyze and detect the results as statically satisfactory. Conclusions: As a result of the data obtained, the TIMP2 gene polymorphism does not correlate statistically with cancer risk. The significance of this finding can only be confirmed using a large population, extensive epidemiological research, a comprehensive survey, and a better understanding of the molecular pathways associated.
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Affiliation(s)
- Pemula Gowtham
- Medical Bionanotechnology, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute (CHRI), Chettinad Academy of Research and Education (CARE), Chennai, India
| | - Koyeli Girigoswami
- Medical Bionanotechnology, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute (CHRI), Chettinad Academy of Research and Education (CARE), Chennai, India
| | - Anbazhagan Thirumalai
- Medical Bionanotechnology, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute (CHRI), Chettinad Academy of Research and Education (CARE), Chennai, India
| | - Karthick Harini
- Medical Bionanotechnology, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute (CHRI), Chettinad Academy of Research and Education (CARE), Chennai, India
| | - Pragya Pallavi
- Medical Bionanotechnology, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute (CHRI), Chettinad Academy of Research and Education (CARE), Chennai, India
| | - Agnishwar Girigoswami
- Medical Bionanotechnology, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute (CHRI), Chettinad Academy of Research and Education (CARE), Chennai, India
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Constantinides C, Baltramonaityte V, Caramaschi D, Han LKM, Lancaster TM, Zammit S, Freeman TP, Walton E. Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study. Cortex 2024; 172:1-13. [PMID: 38154374 DOI: 10.1016/j.cortex.2023.11.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 09/22/2023] [Accepted: 11/23/2023] [Indexed: 12/30/2023]
Abstract
Neuroimaging studies consistently show advanced brain age in schizophrenia, suggesting that brain structure is often 'older' than expected at a given chronological age. Whether advanced brain age is linked to genetic liability for schizophrenia remains unclear. In this pre-registered secondary data analysis, we utilised a recall-by-genotype approach applied to a population-based subsample from the Avon Longitudinal Study of Parents and Children to assess brain age differences between young adults aged 21-24 years with relatively high (n = 96) and low (n = 93) polygenic risk for schizophrenia (SCZ-PRS). A global index of brain age (or brain-predicted age) was estimated using a publicly available machine learning model previously trained on a combination of region-wise gray-matter measures, including cortical thickness, surface area and subcortical volumes derived from T1-weighted magnetic resonance imaging (MRI) scans. We found no difference in mean brain-PAD (the difference between brain-predicted age and chronological age) between the high- and low-SCZ-PRS groups, controlling for the effects of sex and age at time of scanning (b = -.21; 95% CI -2.00, 1.58; p = .82; Cohen's d = -.034; partial R2 = .00029). These findings do not support an association between SCZ-PRS and brain-PAD based on global age-related structural brain patterns, suggesting that brain age may not be a vulnerability marker of common genetic risk for SCZ. Future studies with larger samples and multimodal brain age measures could further investigate global or localised effects of SCZ-PRS.
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Affiliation(s)
| | | | - Doretta Caramaschi
- Department of Psychology, Faculty of Health and Life Sciences, University of Exeter, UK
| | - Laura K M Han
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia; Orygen, Parkville, Australia
| | | | - Stanley Zammit
- Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom P Freeman
- Addiction and Mental Health Group (AIM), Department of Psychology, University of Bath, UK
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49
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Tamman AJF, Koller D, Nagamatsu S, Cabrera-Mendoza B, Abdallah C, Krystal JH, Gelernter J, Montalvo-Ortiz JL, Polimanti R, Pietrzak RH. Psychosocial moderators of polygenic risk scores of inflammatory biomarkers in relation to GrimAge. Neuropsychopharmacology 2024; 49:699-708. [PMID: 37848731 PMCID: PMC10876568 DOI: 10.1038/s41386-023-01747-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 08/25/2023] [Accepted: 09/25/2023] [Indexed: 10/19/2023]
Abstract
GrimAge acceleration has previously predicted age-related morbidities and mortality. In the current study, we sought to examine how GrimAge is associated with genetic predisposition for systemic inflammation and whether psychosocial factors moderate this association. Military veterans from the National Health and Resilience in Veterans study, which surveyed a nationally representative sample of European American male veterans, provided saliva samples for genotyping (N = 1135). We derived polygenic risk scores (PRS) from the UK Biobank as markers of genetic predisposition to inflammation. Results revealed that PRS for three inflammatory PRS markers-HDL (lower), apolipoprotein B (lower), and gamma-glutamyl transferase (higher)-were associated with accelerated GrimAge. Additionally, these PRS interacted with a range of potentially modifiable psychosocial variables, such as exercise and gratitude, previously identified as associated with accelerated GrimAge. Using gene enrichment, we identified anti-inflammatory and antihistamine drugs that perturbate pathways of genes highly represented in the inflammatory PRS, laying the groundwork for future work to evaluate the potential of these drugs in mitigating epigenetic aging.
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Affiliation(s)
- Amanda J F Tamman
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA.
| | - Dora Koller
- Division of Human Genetics, Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Sheila Nagamatsu
- Division of Human Genetics, Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Brenda Cabrera-Mendoza
- Division of Human Genetics, Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Chadi Abdallah
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - John H Krystal
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- U.S. Department of Veterans Affairs National Center for Posttraumatic Stress Disorder, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, CT, USA
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- U.S. Department of Veterans Affairs National Center for Posttraumatic Stress Disorder, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, CT, USA
| | - Janitza L Montalvo-Ortiz
- Division of Human Genetics, Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- U.S. Department of Veterans Affairs National Center for Posttraumatic Stress Disorder, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, CT, USA
| | - Renato Polimanti
- Division of Human Genetics, Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Robert H Pietrzak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- U.S. Department of Veterans Affairs National Center for Posttraumatic Stress Disorder, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, CT, USA
- Department of Social and Behavioral Sciences, Yale School of Public Health, New Haven, CT, USA
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50
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Suzuki K, Hatzikotoulas K, Southam L, Taylor HJ, Yin X, Lorenz KM, Mandla R, Huerta-Chagoya A, Melloni GEM, Kanoni S, Rayner NW, Bocher O, Arruda AL, Sonehara K, Namba S, Lee SSK, Preuss MH, Petty LE, Schroeder P, Vanderwerff B, Kals M, Bragg F, Lin K, Guo X, Zhang W, Yao J, Kim YJ, Graff M, Takeuchi F, Nano J, Lamri A, Nakatochi M, Moon S, Scott RA, Cook JP, Lee JJ, Pan I, Taliun D, Parra EJ, Chai JF, Bielak LF, Tabara Y, Hai Y, Thorleifsson G, Grarup N, Sofer T, Wuttke M, Sarnowski C, Gieger C, Nousome D, Trompet S, Kwak SH, Long J, Sun M, Tong L, Chen WM, Nongmaithem SS, Noordam R, Lim VJY, Tam CHT, Joo YY, Chen CH, Raffield LM, Prins BP, Nicolas A, Yanek LR, Chen G, Brody JA, Kabagambe E, An P, Xiang AH, Choi HS, Cade BE, Tan J, Broadaway KA, Williamson A, Kamali Z, Cui J, Thangam M, Adair LS, Adeyemo A, Aguilar-Salinas CA, Ahluwalia TS, Anand SS, Bertoni A, Bork-Jensen J, Brandslund I, Buchanan TA, Burant CF, Butterworth AS, Canouil M, Chan JCN, Chang LC, Chee ML, Chen J, Chen SH, Chen YT, Chen Z, Chuang LM, Cushman M, Danesh J, Das SK, de Silva HJ, Dedoussis G, Dimitrov L, Doumatey AP, Du S, Duan Q, Eckardt KU, Emery LS, Evans DS, Evans MK, Fischer K, Floyd JS, Ford I, Franco OH, Frayling TM, Freedman BI, Genter P, Gerstein HC, Giedraitis V, González-Villalpando C, González-Villalpando ME, Gordon-Larsen P, Gross M, Guare LA, Hackinger S, Hakaste L, Han S, Hattersley AT, Herder C, Horikoshi M, Howard AG, Hsueh W, Huang M, Huang W, Hung YJ, Hwang MY, Hwu CM, Ichihara S, Ikram MA, Ingelsson M, Islam MT, Isono M, Jang HM, Jasmine F, Jiang G, Jonas JB, Jørgensen T, Kamanu FK, Kandeel FR, Kasturiratne A, Katsuya T, Kaur V, Kawaguchi T, Keaton JM, Kho AN, Khor CC, Kibriya MG, Kim DH, Kronenberg F, Kuusisto J, Läll K, Lange LA, Lee KM, Lee MS, Lee NR, Leong A, Li L, Li Y, Li-Gao R, Ligthart S, Lindgren CM, Linneberg A, Liu CT, Liu J, Locke AE, Louie T, Luan J, Luk AO, Luo X, Lv J, Lynch JA, Lyssenko V, Maeda S, Mamakou V, Mansuri SR, Matsuda K, Meitinger T, Melander O, Metspalu A, Mo H, Morris AD, Moura FA, Nadler JL, Nalls MA, Nayak U, Ntalla I, Okada Y, Orozco L, Patel SR, Patil S, Pei P, Pereira MA, Peters A, Pirie FJ, Polikowsky HG, Porneala B, Prasad G, Rasmussen-Torvik LJ, Reiner AP, Roden M, Rohde R, Roll K, Sabanayagam C, Sandow K, Sankareswaran A, Sattar N, Schönherr S, Shahriar M, Shen B, Shi J, Shin DM, Shojima N, Smith JA, So WY, Stančáková A, Steinthorsdottir V, Stilp AM, Strauch K, Taylor KD, Thorand B, Thorsteinsdottir U, Tomlinson B, Tran TC, Tsai FJ, Tuomilehto J, Tusie-Luna T, Udler MS, Valladares-Salgado A, van Dam RM, van Klinken JB, Varma R, Wacher-Rodarte N, Wheeler E, Wickremasinghe AR, van Dijk KW, Witte DR, Yajnik CS, Yamamoto K, Yamamoto K, Yoon K, Yu C, Yuan JM, Yusuf S, Zawistowski M, Zhang L, Zheng W, Raffel LJ, Igase M, Ipp E, Redline S, Cho YS, Lind L, Province MA, Fornage M, Hanis CL, Ingelsson E, Zonderman AB, Psaty BM, Wang YX, Rotimi CN, Becker DM, Matsuda F, Liu Y, Yokota M, Kardia SLR, Peyser PA, Pankow JS, Engert JC, Bonnefond A, Froguel P, Wilson JG, Sheu WHH, Wu JY, Hayes MG, Ma RCW, Wong TY, Mook-Kanamori DO, Tuomi T, Chandak GR, Collins FS, Bharadwaj D, Paré G, Sale MM, Ahsan H, Motala AA, Shu XO, Park KS, Jukema JW, Cruz M, Chen YDI, Rich SS, McKean-Cowdin R, Grallert H, Cheng CY, Ghanbari M, Tai ES, Dupuis J, Kato N, Laakso M, Köttgen A, Koh WP, Bowden DW, Palmer CNA, Kooner JS, Kooperberg C, Liu S, North KE, Saleheen D, Hansen T, Pedersen O, Wareham NJ, Lee J, Kim BJ, Millwood IY, Walters RG, Stefansson K, Ahlqvist E, Goodarzi MO, Mohlke KL, Langenberg C, Haiman CA, Loos RJF, Florez JC, Rader DJ, Ritchie MD, Zöllner S, Mägi R, Marston NA, Ruff CT, van Heel DA, Finer S, Denny JC, Yamauchi T, Kadowaki T, Chambers JC, Ng MCY, Sim X, Below JE, Tsao PS, Chang KM, McCarthy MI, Meigs JB, Mahajan A, Spracklen CN, Mercader JM, Boehnke M, Rotter JI, Vujkovic M, Voight BF, Morris AP, Zeggini E. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. Nature 2024; 627:347-357. [PMID: 38374256 PMCID: PMC10937372 DOI: 10.1038/s41586-024-07019-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 01/03/2024] [Indexed: 02/21/2024]
Abstract
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.
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Affiliation(s)
- Ken Suzuki
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Konstantinos Hatzikotoulas
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
| | - Lorraine Southam
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Henry J Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Xianyong Yin
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Kim M Lorenz
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ravi Mandla
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alicia Huerta-Chagoya
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Giorgio E M Melloni
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Nigel W Rayner
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ozvan Bocher
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ana Luiza Arruda
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Graduate School of Experimental Medicine, Technical University of Munich, Munich, Germany
- Munich School for Data Science, Helmholtz Munich, Neuherberg, Germany
| | - Kyuto Sonehara
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Simon S K Lee
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael H Preuss
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lauren E Petty
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Philip Schroeder
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Brett Vanderwerff
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Mart Kals
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Fiona Bragg
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London NorthWest Healthcare NHS Trust, London, UK
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Young Jin Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Jana Nano
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Amel Lamri
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Sanghoon Moon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | - Robert A Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - James P Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Jung-Jin Lee
- Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ian Pan
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
| | - Daniel Taliun
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Esteban J Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, Ontario, Canada
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yang Hai
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tamar Sofer
- Department of Biostatistics, Harvard University, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard University, Boston, MA, USA
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Chloé Sarnowski
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Darryl Nousome
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Soo-Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Meng Sun
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Lin Tong
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, University of Chicago, Chicago, IL, USA
| | - Wei-Min Chen
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Suraj S Nongmaithem
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Victor J Y Lim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Claudia H T Tam
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Chinese University of Hong Kong, Hong Kong, China
| | - Yoonjung Yoonie Joo
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, South Korea
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Chien-Hsiun Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bram Peter Prins
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Aude Nicolas
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Lisa R Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Edmond Kabagambe
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Academics, Ochsner Health, New Orleans, LA, USA
| | - Ping An
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Anny H Xiang
- Department of Research and Evaluation, Division of Biostatistics Research, Kaiser Permanente of Southern California, Pasadena, CA, USA
| | - Hyeok Sun Choi
- Department of Biomedical Science, Hallym University, Chuncheon, South Korea
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jingyi Tan
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - K Alaine Broadaway
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Alice Williamson
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Metabolic Research Laboratories, Wellcome Trust-Medical Research Council Institute of Metabolic Science, Department of Clinical Biochemistry, University of Cambridge, Cambridge, UK
| | - Zoha Kamali
- Department of Epidemiology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Jinrui Cui
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Manonanthini Thangam
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Linda S Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Carlos A Aguilar-Salinas
- Unidad de Investigación en Enfermedades Metabólicas and Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Sonia S Anand
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Alain Bertoni
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ivan Brandslund
- Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
- Department of Clinical Biochemistry, Vejle Hospital, Vejle, Denmark
| | - Thomas A Buchanan
- Department of Medicine, Division of Endocrinology and Diabetes, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Charles F Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus, University of Cambridge, Hinxton, UK
- National Institute for Health and Care Research (NIHR) Blood and Transplant Unit (BTRU) in Donor Health and Behaviour, Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Mickaël Canouil
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Hong Kong, China
| | - Li-Ching Chang
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Miao-Li Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Ji Chen
- Exeter Centre of Excellence in Diabetes (ExCEeD), Exeter Medical School, University of Exeter, Exeter, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Shyh-Huei Chen
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Yuan-Tsong Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Lee-Ming Chuang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | - Mary Cushman
- Department of Medicine, University of Vermont, Colchester, VT, USA
| | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus, University of Cambridge, Hinxton, UK
- National Institute for Health and Care Research (NIHR) Blood and Transplant Unit (BTRU) in Donor Health and Behaviour, Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Swapan K Das
- Section of Endocrinology and Metabolism, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - George Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece
| | - Latchezar Dimitrov
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Shufa Du
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Qing Duan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Leslie S Emery
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Krista Fischer
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - Oscar H Franco
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Barry I Freedman
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Pauline Genter
- Department of Medicine, Division of Endocrinology and Metabolism, Lundquist Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Hertzel C Gerstein
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Vilmantas Giedraitis
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Clicerio González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico
| | - Maria Elena González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Lindsay A Guare
- Genomics and Computational Biology Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sophie Hackinger
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Liisa Hakaste
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
| | - Sohee Han
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | | | - Christian Herder
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Annie-Green Howard
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Willa Hsueh
- Department of Internal Medicine, Diabetes and Metabolism Research Center, Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Mengna Huang
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
- Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
| | - Wei Huang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China
| | - Yi-Jen Hung
- Division of Endocrine and Metabolism, Tri-Service General Hospital Songshan Branch, Taipei, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
| | - Mi Yeong Hwang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Sahoko Ichihara
- Department of Environmental and Preventive Medicine, Jichi Medical University School of Medicine, Shimotsuke, Japan
| | - Mohammad Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Martin Ingelsson
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | | | - Masato Isono
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Hye-Mi Jang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Farzana Jasmine
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, University of Chicago, Chicago, IL, USA
| | - Guozhi Jiang
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Chinese University of Hong Kong, Hong Kong, China
| | - Jost B Jonas
- Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland
| | - Torben Jørgensen
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Medicine, Aalborg University, Aalborg, Denmark
| | - Frederick K Kamanu
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Fouad R Kandeel
- Department of Clinical Diabetes, Endocrinology and Metabolism, Department of Translational Research and Cellular Therapeutics, City of Hope, Duarte, CA, USA
| | | | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Geriatric and General Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Varinderpal Kaur
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Jacob M Keaton
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Abel N Kho
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Health Information Partnerships, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Muhammad G Kibriya
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, University of Chicago, Chicago, IL, USA
| | - Duk-Hwan Kim
- Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon, South Korea
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Leslie A Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Kyung Min Lee
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Myung-Shik Lee
- Soochunhyang Institute of Medi-bio Science and Division of Endocrinology, Department of Internal Medicine, Soochunhyang University College of Medicine, Cheonan, South Korea
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Nanette R Lee
- USC-Office of Population Studies Foundation, University of San Carlos, Cebu City, Philippines
| | - Aaron Leong
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Symen Ligthart
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Cecilia M Lindgren
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Adam E Locke
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Department of Medicine, Division of Genomics and Bioinformatics, Washington University School of Medicine, St Louis, MO, USA
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Tin Louie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Andrea O Luk
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Chinese University of Hong Kong, Hong Kong, China
| | - Xi Luo
- Department of Biostatistics and Data Science, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Julie A Lynch
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden
- Department of Clinical Science, Center for Diabetes Research, University of Bergen, Bergen, Norway
| | - Shiro Maeda
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Nishihara, Japan
| | - Vasiliki Mamakou
- Dromokaiteio Psychiatric Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Sohail Rafik Mansuri
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Koichi Matsuda
- Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technical University Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Olle Melander
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Huan Mo
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Andrew D Morris
- Usher Institute to the Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Filipe A Moura
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jerry L Nadler
- Department of Medicine and Pharmacology, New York Medical College, Valhalla, NY, USA
| | - Michael A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Uma Nayak
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Ioanna Ntalla
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita, Japan
| | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Sanjay R Patel
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Snehal Patil
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Mark A Pereira
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Fraser J Pirie
- Department of Diabetes and Endocrinology, Nelson R. Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Hannah G Polikowsky
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bianca Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Gauri Prasad
- Academy of Scientific and Innovative Research, CSIR-Human Resource Development Campus, Ghaziabad, India
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Michael Roden
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Rebecca Rohde
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Katheryn Roll
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Kevin Sandow
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Alagu Sankareswaran
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Naveed Sattar
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Mohammad Shahriar
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, University of Chicago, Chicago, IL, USA
| | - Botong Shen
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Jinxiu Shi
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China
| | - Dong Mun Shin
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Nobuhiro Shojima
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Wing Yee So
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Hong Kong, China
| | - Alena Stančáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | | | - Adrienne M Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Biostatistics, Epidemiology, and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Chair of Genetic Epidemiology, Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Unnur Thorsteinsdottir
- deCODE Genetics, Amgen, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Brian Tomlinson
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Faculty of Medicine, Macau University of Science and Technology, Macau, China
| | - Tam C Tran
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Fuu-Jen Tsai
- Department of Medical Genetics and Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Jaakko Tuomilehto
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- National School of Public Health, Madrid, Spain
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Teresa Tusie-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
- Departamento de Medicina Genómica y Toxiología Ambiental, Instituto de Investigaciones Biomédicas, UNAM, Mexico City, Mexico
| | - Miriam S Udler
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Adan Valladares-Salgado
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jan B van Klinken
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Clinical Chemistry, Laboratory of Genetic Metabolic Disease, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Rohit Varma
- Southern California Eye Institute, CHA Hollywood Presbyterian Hospital, Los Angeles, CA, USA
| | - Niels Wacher-Rodarte
- Unidad de Investigación Médica en Epidemiologia Clinica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | | | - Ko Willems van Dijk
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
| | - Daniel R Witte
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
| | - Chittaranjan S Yajnik
- Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
| | - Ken Yamamoto
- Department of Medical Biochemistry, Kurume University School of Medicine, Kurume, Japan
| | - Kenichi Yamamoto
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Department of Pediatrics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Kyungheon Yoon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Salim Yusuf
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Matthew Zawistowski
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Liang Zhang
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Leslie J Raffel
- Department of Pediatrics, Division of Genetic and Genomic Medicine, UCI Irvine School of Medicine, Irvine, CA, USA
| | - Michiya Igase
- Department of Anti-Aging Medicine, Ehime University Graduate School of Medicine, Touon, Japan
| | - Eli Ipp
- Department of Medicine, Division of Endocrinology and Metabolism, Lundquist Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Yoon Shin Cho
- Department of Biomedical Science, Hallym University, Chuncheon, South Korea
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Michael A Province
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Craig L Hanis
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Erik Ingelsson
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ya-Xing Wang
- Beijing Institute of Ophthalmology, Ophthalmology and Visual Sciences Key Laboratory, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Diane M Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Medicine, Division of Cardiology, Duke University School of Medicine, Durham, NC, USA
| | | | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - James C Engert
- Department of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Amélie Bonnefond
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Philippe Froguel
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - James G Wilson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Wayne H H Sheu
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Division of Endocrinology and Metabolism, Department of Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Jer-Yuarn Wu
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - M Geoffrey Hayes
- Division of Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Anthropology, Northwestern University, Evanston, IL, USA
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Hong Kong, China
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Tiinamaija Tuomi
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- Department of Endocrinology, Helsinki University Hospital, Helsinki, Finland
| | - Giriraj R Chandak
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
- Science and Engineering Research Board (SERB), Department of Science and Technology, Ministry of Science and Technology, Government of India, New Delhi, India
| | - Francis S Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Dwaipayan Bharadwaj
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
| | - Guillaume Paré
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Michèle M Sale
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Habibul Ahsan
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, University of Chicago, Chicago, IL, USA
| | - Ayesha A Motala
- Department of Diabetes and Endocrinology, Nelson R. Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kyong-Soo Park
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Netherlands Heart Institute, Utrecht, The Netherlands
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Roberta McKean-Cowdin
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Josee Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Woon-Puay Koh
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Donald W Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Colin N A Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, University of Dundee, Dundee, UK
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London NorthWest Healthcare NHS Trust, London, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | | | - Simin Liu
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
- Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
- Department of Medicine, Brown University Alpert School of Medicine, Providence, RI, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Danish Saleheen
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
- Center for Non-Communicable Diseases, Karachi, Pakistan
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Juyoung Lee
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Bong-Jo Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Kari Stefansson
- deCODE Genetics, Amgen, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Emma Ahlqvist
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Mark O Goodarzi
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité-Universitätsmedizin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Mindich Child Health and Development Institute, Ichan School of Medicine at Mount Sinai, New York, NY, USA
| | - Jose C Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Daniel J Rader
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Translational Medicine and Therapeutics, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Center for Precision Medicine, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sebastian Zöllner
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Nicholas A Marston
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christian T Ruff
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Sarah Finer
- Institute for Population Health Sciences, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Joshua C Denny
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Toshimasa Yamauchi
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Takashi Kadowaki
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Toranomon Hospital, Tokyo, Japan
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London NorthWest Healthcare NHS Trust, London, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Maggie C Y Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jennifer E Below
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Philip S Tsao
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - James B Meigs
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - Cassandra N Spracklen
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Josep M Mercader
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK.
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- TUM School of Medicine and Health, Technical University of Munich and Klinikum Rechts der Isar, Munich, Germany.
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