1
|
Bonk S, Eszlari N, Kirchner K, Gezsi A, Garvert L, Kuokkanen M, Cano I, Grabe HJ, Antal P, Juhasz G, Van der Auwera S. Impact of gene-by-trauma interaction in MDD-related multimorbidity clusters. J Affect Disord 2024; 359:382-391. [PMID: 38806065 DOI: 10.1016/j.jad.2024.05.126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 05/23/2024] [Accepted: 05/24/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) is considerably heterogeneous in terms of comorbidities, which may hamper the disentanglement of its biological mechanism. In a previous study, we classified the lifetime trajectories of MDD-related multimorbidities into seven distinct clusters, each characterized by unique genetic and environmental risk-factor profiles. The current objective was to investigate genome-wide gene-by-environment (G × E) interactions with childhood trauma burden, within the context of these clusters. METHODS We analyzed 77,519 participants and 6,266,189 single-nucleotide polymorphisms (SNPs) of the UK Biobank database. Childhood trauma burden was assessed using the Childhood Trauma Screener (CTS). For each cluster, Plink 2.0 was used to calculate SNP × CTS interaction effects on the participants' cluster membership probabilities. We especially focused on the effects of 31 candidate genes and associated SNPs selected from previous G × E studies for childhood maltreatment's association with depression. RESULTS At SNP-level, only the high-multimorbidity Cluster 6 revealed a genome-wide significant SNP rs145772219. At gene-level, MPST and PRH2 were genome-wide significant for the low-multimorbidity Clusters 1 and 3, respectively. Regarding candidate SNPs for G × E interactions, individual SNP results could be replicated for specific clusters. The candidate genes CREB1, DBH, and MTHFR (Cluster 5) as well as TPH1 (Cluster 6) survived multiple testing correction. LIMITATIONS CTS is a short retrospective self-reported measurement. Clusters could be influenced by genetics of individual disorders. CONCLUSIONS The first G × E GWAS for MDD-related multimorbidity trajectories successfully replicated findings from previous G × E studies related to depression, and revealed risk clusters for the contribution of childhood trauma.
Collapse
Affiliation(s)
- Sarah Bonk
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Nora Eszlari
- Department of Pharmacodynamics, Faculty of Pharmaceutical Sciences, Semmelweis University, Nagyvárad tér 4., H-1089 Budapest, Hungary; NAP3.0-SE Neuropsychopharmacology Research Group, Hungarian Brain Research Program, Semmelweis University, Üllői út 26., H-1085 Budapest, Hungary
| | - Kevin Kirchner
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Andras Gezsi
- Department of Measurement and Information Systems, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Linda Garvert
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Mikko Kuokkanen
- Department of Public Health and Welfare, Finnish Health and Welfare Institute. Biomedicum 1, Haartmaninkatu 8, 00290 Helsinki, Finland; Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine at University of Texas Rio Grande Valley, Brownsville, TX, United States; Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Finland
| | - Isaac Cano
- Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Villarroel 170, Barcelona 08036. Spain
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany; German Centre for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, 17475 Greifswald, Germany
| | - Peter Antal
- Department of Measurement and Information Systems, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Gabriella Juhasz
- Department of Pharmacodynamics, Faculty of Pharmaceutical Sciences, Semmelweis University, Nagyvárad tér 4., H-1089 Budapest, Hungary; NAP3.0-SE Neuropsychopharmacology Research Group, Hungarian Brain Research Program, Semmelweis University, Üllői út 26., H-1085 Budapest, Hungary
| | - Sandra Van der Auwera
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany; German Centre for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, 17475 Greifswald, Germany.
| |
Collapse
|
2
|
Qiao G, Xu P, Guo T, He X, Yue Y, Yang B. Genome-wide detection of structural variation in some sheep breeds using whole-genome long-read sequencing data. J Anim Breed Genet 2024; 141:403-414. [PMID: 38247268 DOI: 10.1111/jbg.12846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/21/2023] [Accepted: 12/29/2023] [Indexed: 01/23/2024]
Abstract
Genomic structural variants (SVs) constitute a significant proportion of genetic variation in the genome. The rapid development of long-reads sequencing has facilitated the detection of long-fragment SVs. There is no published study to detect SVs using long-read data from sheep. We applied a long-read mapping approach to detect SVs and characterized a total of 30,771 insertions, deletions, inversions and translocations. We identified 716, 916, 842 and 303 specific SVs in Southdown sheep, Alpine merino sheep, Qilian White Tibetan sheep and Oula sheep, respectively. We annotated these SVs and found that these SV-related genes were primarily enriched in the well-established pathways involved in the regulation of the immune system, growth and development and environmental adaptability. We detected and annotated SVs based on NGS resequencing data to validate the accuracy based on third-generation detection. Moreover, five candidate SVs were verified using the PCR method in 50 sheep. Our study is the first to use a long-reads sequencing approach to construct a novel structural variation map in sheep. We have completed a preliminary exploration of the potential effects of SVs on sheep.
Collapse
Affiliation(s)
- Guoyan Qiao
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Lanzhou, China
- College of Ecological Agriculture and Animal Husbandry, Qinghai Communications Technical College, Xining, China
| | - Pan Xu
- State Key Laboratory of Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, China
| | - Tingting Guo
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Lanzhou, China
| | - Xue He
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Lanzhou, China
| | - Yaojing Yue
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Lanzhou, China
| | - Bohui Yang
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Lanzhou, China
| |
Collapse
|
3
|
Brasher MS, Grotzinger AD, Friedman NP, Smolker HR, Evans LM. Disentangling differing relationships between internalizing disorders and alcohol use. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32975. [PMID: 38375614 PMCID: PMC11147714 DOI: 10.1002/ajmg.b.32975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 12/14/2023] [Accepted: 02/08/2024] [Indexed: 02/21/2024]
Abstract
Both internalizing disorders and alcohol use have dramatic, wide-spread implications for global health. Previous work has established common phenotypic comorbidity among these disorders, as well as shared genetic variation underlying them both. We used genomic structural equation modeling to investigate the shared genetics of internalizing, externalizing, and alcohol use traits, as well as to explore whether specific domains of internalizing symptoms mediate the contrasting relationships with problematic alcohol use compared to alcohol consumption. We also examined patterns of genetic correlations between similar traits within additional Finnish and East Asian ancestry groups. When the shared genetic influence of externalizing psychopathology was accounted for, the genetic effect of internalizing traits on alcohol use was reduced, suggesting the important role of common genetic factors underlying multiple psychiatric disorders and their genetic influences on comorbidity of internalizing and alcohol use traits. Individual internalizing domains had contrasting effects on frequency of alcohol consumption, which demonstrate the complex system of pleiotropy that exists, even within similar disorders, and can be missed when evaluating only relationships among formal diagnoses. Future work must consider the broad effects of shared psychopathology along with the fine-scale effects of heterogeneity within disorders to more fully understand the biology underlying complex traits.
Collapse
Affiliation(s)
- Maizy S Brasher
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Ecology and Evolutionary Biology, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Andrew D Grotzinger
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Psychology and Neuroscience, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Naomi P Friedman
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Psychology and Neuroscience, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Harry R Smolker
- Institute of Cognitive Science, University of Colorado Boulder, Boulder, Colorado, USA
| | - Luke M Evans
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Ecology and Evolutionary Biology, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| |
Collapse
|
4
|
Paradis H, Werdyani S, Zhai G, Gendron RL, Tabrizchi R, McGovern M, Jumper JM, Brinton D, Good WV. Genetic Variants of the Beta-Adrenergic Receptor Pathways as Both Risk and Protective Factors for Retinopathy of Prematurity. Am J Ophthalmol 2024; 263:179-187. [PMID: 38224928 DOI: 10.1016/j.ajo.2023.12.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 12/21/2023] [Accepted: 12/28/2023] [Indexed: 01/17/2024]
Abstract
PURPOSE There is strong evidence that genetic factors influence retinopathy of prematurity (ROP), a neovascular eye disease. It has been previously suggested that polymorphisms in the genes involved in β-adrenergic receptor (ADRβ) pathways could protect against ROP. Antagonists for the ADRβ are actively tested in clinical trials for ROP treatment, but not without controversy and safety concerns. This study was designed to assess whether genetic variations in components of the ADRβ signaling pathways associate with risk of developing ROP. DESIGN An observational case-control targeted genetic analysis. METHODS A study was carried out in premature participants with (n = 30) or without (n = 34) ROP and full-term controls (n = 20), who were divided into a discovery cohort and a validation cohort. ROP was defined using International Classification of Retinopathy of Prematurity criteria (ICROP). Targeted sequencing of 20 genes in the ADRβ pathways was performed in the discovery cohort. Polymerase chain reaction (PCR)/restriction enzyme analysis for some of the discovered ROP-associated variants was performed for validation of the results using the validation cohort. RESULTS The discovery cohort revealed 543 bi-allelic variants within 20 genes of the ADRβ pathways. Ten single-nucleotide variants (SNVs) in 5 genes including protein kinase A regulatory subunit 1α (PRKAR1A), rap guanine exchange factor 3 (RAPGEF3), adenylyl cyclase 4 (ADCY4), ADCY7, and ADCY9 were associated with ROP (P < .05). The most significant SNV was found in PRKAR1A (P = .001). Multiple variants located in the 3'-untranslated region (3'UTR) of RAPGEF3 were also associated with ROP (P < .05). PCR/restriction enzyme analysis of the 3'UTR of RAPGEF3 methodologically validated these findings. CONCLUSION SNVs in PRKAR1A may represent protective factors whereas SNVs in RAPGEF3 may represent risk factors for ROP. PRKAR1α has previously been implicated in retinal vascular development whereas the RAPGEF3 product has a role in the maintenance of vascular barrier function, 2 processes important in ROP. Multicenter validation of these newly discovered risk factors could lead to valuable tools for predicting and preventing the development of severe ROP.
Collapse
Affiliation(s)
- Hélène Paradis
- From the Division of BioMedical Sciences (H.P., S.W., G.Z., R.L.G., R.T.), Faculty of Medicine, Memorial University, St. John's, Newfoundland, Canada
| | - Salem Werdyani
- From the Division of BioMedical Sciences (H.P., S.W., G.Z., R.L.G., R.T.), Faculty of Medicine, Memorial University, St. John's, Newfoundland, Canada
| | - Guangju Zhai
- From the Division of BioMedical Sciences (H.P., S.W., G.Z., R.L.G., R.T.), Faculty of Medicine, Memorial University, St. John's, Newfoundland, Canada
| | - Robert L Gendron
- From the Division of BioMedical Sciences (H.P., S.W., G.Z., R.L.G., R.T.), Faculty of Medicine, Memorial University, St. John's, Newfoundland, Canada
| | - Reza Tabrizchi
- From the Division of BioMedical Sciences (H.P., S.W., G.Z., R.L.G., R.T.), Faculty of Medicine, Memorial University, St. John's, Newfoundland, Canada
| | - Margaret McGovern
- Smith Kettlewell Eye Research Institute (M.M., W.V.G.), San Francisco, California, USA
| | | | - Daniel Brinton
- East Bay Retina Consultants, Inc. (D.B.), Oakland, California, USA
| | - William V Good
- Smith Kettlewell Eye Research Institute (M.M., W.V.G.), San Francisco, California, USA.
| |
Collapse
|
5
|
Yaacov O, Mathiyalagan P, Berk-Rauch HE, Ganesh SK, Zhu L, Hoffmann TJ, Iribarren C, Risch N, Lee D, Chakravarti A. Identification of the Molecular Components of Enhancer-Mediated Gene Expression Variation in Multiple Tissues Regulating Blood Pressure. Hypertension 2024; 81:1500-1510. [PMID: 38747164 PMCID: PMC11168860 DOI: 10.1161/hypertensionaha.123.22538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 04/24/2024] [Indexed: 06/14/2024]
Abstract
BACKGROUND Inter-individual variation in blood pressure (BP) arises in part from sequence variants within enhancers modulating the expression of causal genes. We propose that these genes, active in tissues relevant to BP physiology, can be identified from tissue-level epigenomic data and genotypes of BP-phenotyped individuals. METHODS We used chromatin accessibility data from the heart, adrenal, kidney, and artery to identify cis-regulatory elements (CREs) in these tissues and estimate the impact of common human single-nucleotide variants within these CREs on gene expression, using machine learning methods. To identify causal genes, we performed a gene-wise association test. We conducted analyses in 2 separate large-scale cohorts: 77 822 individuals from the Genetic Epidemiology Research on Adult Health and Aging and 315 270 individuals from the UK Biobank. RESULTS We identified 309, 259, 331, and 367 genes (false discovery rate <0.05) for diastolic BP and 191, 184, 204, and 204 genes for systolic BP in the artery, kidney, heart, and adrenal, respectively, in Genetic Epidemiology Research on Adult Health and Aging; 50% to 70% of these genes were replicated in the UK Biobank, significantly higher than the 12% to 15% expected by chance (P<0.0001). These results enabled tissue expression prediction of these 988 to 2875 putative BP genes in individuals of both cohorts to construct an expression polygenic score. This score explained ≈27% of the reported single-nucleotide variant heritability, substantially higher than expected from prior studies. CONCLUSIONS Our work demonstrates the power of tissue-restricted comprehensive CRE analysis, followed by CRE-based expression prediction, for understanding BP regulation in relevant tissues and provides dual-modality supporting evidence, CRE and expression, for the causality genes.
Collapse
Affiliation(s)
- Or Yaacov
- Center for Human Genetics and Genomics, NYU Grossman School of Medicine, New York, NY, USA
| | - Prabhu Mathiyalagan
- Center for Human Genetics and Genomics, NYU Grossman School of Medicine, New York, NY, USA
- Benthos Prime Central, Houston, TX, USA
| | - Hanna E. Berk-Rauch
- Center for Human Genetics and Genomics, NYU Grossman School of Medicine, New York, NY, USA
| | - Santhi K. Ganesh
- Department of Internal Medicine & Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Luke Zhu
- Center for Human Genetics and Genomics, NYU Grossman School of Medicine, New York, NY, USA
| | - Thomas J. Hoffmann
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Carlos Iribarren
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Neil Risch
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Dongwon Lee
- Department of Pediatrics, Division of Nephrology, Boston Children’s Hospital, Boston & Harvard Medical School, Boston, MA, USA
| | - Aravinda Chakravarti
- Center for Human Genetics and Genomics, NYU Grossman School of Medicine, New York, NY, USA
| |
Collapse
|
6
|
Song H, Dong T, Wang W, Jiang B, Yan X, Geng C, Bai S, Xu S, Hu H. Cost-effective genomic prediction of critical economic traits in sturgeons through low-coverage sequencing. Genomics 2024; 116:110874. [PMID: 38839024 DOI: 10.1016/j.ygeno.2024.110874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 05/27/2024] [Accepted: 06/01/2024] [Indexed: 06/07/2024]
Abstract
Low-coverage whole-genome sequencing (LCS) offers a cost-effective alternative for sturgeon breeding, especially given the lack of SNP chips and the high costs associated with whole-genome sequencing. In this study, the efficiency of LCS for genotype imputation and genomic prediction was assessed in 643 sequenced Russian sturgeons (∼13.68×). The results showed that using BaseVar+STITCH at a sequencing depth of 2× with a sample size larger than 300 resulted in the highest genotyping accuracy. In addition, when the sequencing depth reached 0.5× and SNP density was reduced to 50 K through linkage disequilibrium pruning, the prediction accuracy was comparable to that of whole sequencing depth. Furthermore, an incremental feature selection method has the potential to improve prediction accuracy. This study suggests that the combination of LCS and imputation can be a cost-effective strategy, contributing to the genetic improvement of economic traits and promoting genetic gains in aquaculture species.
Collapse
Affiliation(s)
- Hailiang Song
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China; Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China; National Innovation Center for Digital Seed Industry, Beijing 100097, China
| | - Tian Dong
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China; Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China; National Innovation Center for Digital Seed Industry, Beijing 100097, China
| | - Wei Wang
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China; Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China; National Innovation Center for Digital Seed Industry, Beijing 100097, China
| | - Boyun Jiang
- Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China; Hangzhou Qiandaohu Xunlong Sci-tech Co., Ltd., Hangzhou 311799, China.
| | - Xiaoyu Yan
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China; Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China; National Innovation Center for Digital Seed Industry, Beijing 100097, China
| | - Chenfan Geng
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China; Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China; National Innovation Center for Digital Seed Industry, Beijing 100097, China
| | - Song Bai
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China; Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China; National Innovation Center for Digital Seed Industry, Beijing 100097, China
| | - Shijian Xu
- Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China; Hangzhou Qiandaohu Xunlong Sci-tech Co., Ltd., Hangzhou 311799, China.
| | - Hongxia Hu
- Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China; Key Laboratory of Sturgeon Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Hangzhou 311799, China; National Innovation Center for Digital Seed Industry, Beijing 100097, China.
| |
Collapse
|
7
|
Monjaraz-Ruedas R, Starrett J, Leavitt D, Hedin M. Broken Ring Speciation in California Mygalomorph Spiders (Nemesiidae, Calisoga). Am Nat 2024; 204:55-72. [PMID: 38857341 DOI: 10.1086/730262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024]
Abstract
AbstractIdealized ring species, with approximately continuous gene flow around a geographic barrier but singular reproductive isolation at a ring terminus, are rare in nature. A broken ring species model preserves the geographic setting and fundamental features of an idealized model but accommodates varying degrees of gene flow restriction over complex landscapes through evolutionary time. Here we examine broken ring species dynamics in Calisoga spiders, which, like the classic ring species Ensatina salamanders, are distributed around the Central Valley of California. Using nuclear and mitogenomic data, we test key predictions of common ancestry, ringlike biogeography, biogeographic timing, population connectivity, and terminal overlap. We show that a ring complex of populations shares a single common ancestor, and from an ancestral area in the Sierra Nevada mountains, two distributional and phylogenomic arms encircle the Central Valley. Isolation by distance occurs along these distributional arms, although gene flow restriction is also evident. Where divergent lineages meet in the South Coast Ranges, we find rare lineage sympatry, without evidence for nuclear gene flow and with clear evidence for morphological and ecological divergence. We discuss general insights provided by broken ring species and how such a model could be explored and extended in other systems and future studies.
Collapse
|
8
|
Crouse JJ, Park SH, Byrne EM, Mitchell BL, Chan K, Scott J, Medland SE, Martin NG, Wray NR, Hickie IB. Evening Chronotypes With Depression Report Poorer Outcomes of Selective Serotonin Reuptake Inhibitors: A Survey-Based Study of Self-Ratings. Biol Psychiatry 2024; 96:4-14. [PMID: 38185236 DOI: 10.1016/j.biopsych.2023.12.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 12/20/2023] [Accepted: 12/28/2023] [Indexed: 01/09/2024]
Abstract
BACKGROUND Preliminary evidence suggests that evening chronotype is related to poorer efficacy of selective serotonin reuptake inhibitors. It is unknown whether this is specific to particular medications, self-rated chronotype, or efficacy. METHODS In the Australian Genetics of Depression Study (n = 15,108; 75% women; 18-90 years; 68% with ≥1 other lifetime diagnosis), a survey recorded experiences with 10 antidepressants, and the reduced Morningness-Eveningness Questionnaire was used to estimate chronotype. A chronotype polygenic score was calculated. Age- and sex-adjusted regression models (Bonferroni-corrected) estimated associations among antidepressant variables (how well the antidepressant worked [efficacy], duration of symptom improvement, side effects, discontinuation due to side effects) and self-rated and genetic chronotypes. RESULTS The chronotype polygenic score explained 4% of the variance in self-rated chronotype (r = 0.21). Higher self-rated eveningness was associated with poorer efficacy of escitalopram (odds ratio [OR] = 1.04; 95% CI, 1.02 to 1.06; p = .000035), citalopram (OR = 1.03; 95% CI, 1.01 to 1.05; p = .004), fluoxetine (OR = 1.03; 95% CI, 1.01 to 1.05; p = .001), sertraline (OR = 1.02; 95% CI, 1.01 to 1.04; p = .0008), and desvenlafaxine (OR = 1.03; 95% CI, 1.01 to 1.05; p = .004), and a profile of increased side effects (80% of those recorded; ORs = 0.93-0.98), with difficulty getting to sleep the most common. Self-rated chronotype was unrelated to duration of improvement or discontinuation. The chronotype polygenic score was only associated with suicidal thoughts and attempted suicide (self-reported). While our measures are imperfect, and not of circadian phase under controlled conditions, the model coefficients suggest that dysregulation of the phenotypic chronotype relative to its genetic proxy drove relationships with antidepressant outcomes. CONCLUSIONS The idea that variation in circadian factors influences response to antidepressants was supported and encourages exploration of circadian mechanisms of depressive disorders and antidepressant treatments.
Collapse
Affiliation(s)
- Jacob J Crouse
- Brain and Mind Centre, the University of Sydney, Sydney, New South Wales, Australia.
| | - Shin Ho Park
- Brain and Mind Centre, the University of Sydney, Sydney, New South Wales, Australia
| | - Enda M Byrne
- Institute for Molecular Bioscience, the University of Queensland, Brisbane, Queensland, Australia; Child Health Research Centre, the University of Queensland, Brisbane, Queensland, Australia
| | - Brittany L Mitchell
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Karina Chan
- Brain and Mind Centre, the University of Sydney, Sydney, New South Wales, Australia
| | - Jan Scott
- Brain and Mind Centre, the University of Sydney, Sydney, New South Wales, Australia; Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Sarah E Medland
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, the University of Queensland, Brisbane, Queensland, Australia; Department of Psychiatry, University of Oxford, Oxford, United Kingdom; Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Ian B Hickie
- Brain and Mind Centre, the University of Sydney, Sydney, New South Wales, Australia
| |
Collapse
|
9
|
Nothdurfter D, Jawinski P, Markett S. White Matter Tract Integrity Is Reduced in Depression and in Individuals With Genetic Liability to Depression. Biol Psychiatry 2024; 95:1063-1071. [PMID: 38103877 DOI: 10.1016/j.biopsych.2023.11.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 11/06/2023] [Accepted: 11/26/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND While major depression has been linked to changes in white matter architecture, it remains unclear whether risk factors for depression are directly associated with these alterations. We reexamined white matter fiber tracts in individuals with depressive symptoms and investigated the connection between genetic and environmental risk for depression and structural changes in the brain. METHODS We included 19,183 participants from the UK Biobank imaging cohort, with depression status and adverse life experience based on questionnaire data and genetic liability for depression quantified by polygenic scores. The integrity of 27 white matter tracts was assessed using mean fractional anisotropy derived from diffusion magnetic resonance imaging. RESULTS White matter integrity was reduced, particularly in thalamic and intracortical fiber tracts, in individuals with depressive symptoms, independent of current symptom status. In a group of healthy individuals without depression, increasing genetic risk and increasing environmental risk were associated with reduced integrity in relevant fiber tracts, particularly in thalamic radiations. This association was stronger than expected based on statistical dependencies between samples, as confirmed by subsequent in silico simulations and permutation tests. CONCLUSIONS White matter alterations in thalamic and association tracts are associated with depressive symptoms and genetic risk for depression in unaffected individuals, suggesting an intermediate phenotype at the brain level.
Collapse
Affiliation(s)
- David Nothdurfter
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Philippe Jawinski
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Sebastian Markett
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.
| |
Collapse
|
10
|
Huang L, Tang S, Rietkerk J, Appadurai V, Krebs MD, Schork AJ, Werge T, Zuber V, Kendler K, Cai N. Polygenic Analyses Show Important Differences Between Major Depressive Disorder Symptoms Measured Using Various Instruments. Biol Psychiatry 2024; 95:1110-1121. [PMID: 38056704 PMCID: PMC11139567 DOI: 10.1016/j.biopsych.2023.11.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 11/06/2023] [Accepted: 11/26/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND Symptoms of major depressive disorder (MDD) are commonly assessed using self-rating instruments like the Patient Health Questionnaire-9 (PHQ-9) (current symptoms) and the Composite International Diagnostic Interview Short-Form (CIDI-SF) (worst-episode symptoms). We performed a systematic comparison between them for their genetic architecture and utility in investigating MDD heterogeneity. METHODS Using data from the UK Biobank (n = 41,948-109,417), we assessed the single nucleotide polymorphism heritability and genetic correlation (rg) of both sets of MDD symptoms. We further compared their rg with non-MDD traits and used Mendelian randomization to assess whether either set of symptoms has more genetic sharing with non-MDD traits. We also assessed how specific each set of symptoms is to MDD using the metric polygenic risk score pleiotropy. Finally, we used genomic structural equation modeling to identify factors that explain the genetic covariance between each set of symptoms. RESULTS Corresponding symptoms reported through the PHQ-9 and CIDI-SF have low to moderate genetic correlations (rg = 0.43-0.87), and this cannot be fully attributed to different severity thresholds or the use of a skip structure in the CIDI-SF. Both Mendelian randomization and polygenic risk score pleiotropy analyses showed that PHQ-9 symptoms are more associated with traits that reflect general dysphoria, whereas the skip structure in the CIDI-SF allows for the identification of heterogeneity among likely MDD cases. Finally, the 2 sets of symptoms showed different factor structures in genomic structural equation modeling, reflective of their genetic differences. CONCLUSIONS MDD symptoms assessed using the PHQ-9 and CIDI-SF are not interchangeable; the former better indexes general dysphoria, while the latter is more informative about within-MDD heterogeneity.
Collapse
Affiliation(s)
- Lianyun Huang
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany; Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany; School of Medicine, Technical University of Munich, Munich, Germany
| | - Sonja Tang
- School of Public Health, Imperial College London, London, United Kingdom; MRC Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Jolien Rietkerk
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany; Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany; School of Medicine, Technical University of Munich, Munich, Germany
| | - Vivek Appadurai
- Institute of Biological Psychiatry, Mental Health Center, Sct Hans, Copenhagen University Hospital, Mental Health Services CPH, Copenhagen, Denmark
| | - Morten Dybdahl Krebs
- Institute of Biological Psychiatry, Mental Health Center, Sct Hans, Copenhagen University Hospital, Mental Health Services CPH, Copenhagen, Denmark
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center, Sct Hans, Copenhagen University Hospital, Mental Health Services CPH, Copenhagen, Denmark; Neurogenomics Division, The Translational Genomics Research Institute, Phoenix, Arizona; Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center, Sct Hans, Copenhagen University Hospital, Mental Health Services CPH, Copenhagen, Denmark; Lundbeck Foundation GeoGenetics Centre, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Verena Zuber
- School of Public Health, Imperial College London, London, United Kingdom; MRC Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Kenneth Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
| | - Na Cai
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany; Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany; School of Medicine, Technical University of Munich, Munich, Germany.
| |
Collapse
|
11
|
Chen Z, Chen L, Tan J, Mao Y, Hao M, Li Y, Wang Y, Li J, Wang J, Jin L, Zheng HX. Natural selection shaped the protective effect of the mtDNA lineage against obesity in Han Chinese populations. J Genet Genomics 2024:S1673-8527(24)00129-2. [PMID: 38880354 DOI: 10.1016/j.jgg.2024.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 06/06/2024] [Accepted: 06/06/2024] [Indexed: 06/18/2024]
Abstract
Mitochondria play a key role in lipid metabolism, and mitochondrial DNA (mtDNA) mutations are thus considered to affect obesity susceptibility by altering oxidative phosphorylation and mitochondrial function. In this study, we investigated mtDNA variants that may affect obesity risk in 2,877 Han Chinese individuals from three independent populations. The association analysis of 16 basal mtDNA haplogroups with body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) revealed that only haplogroup M7 was significantly negatively correlated with all three adiposity-related anthropometric traits in the overall cohort (P=0.003 for BMI, P=1×10-5 for WC, P=0.005 for WHR), which was verified by the analysis of a single population, i.e., the Zhengzhou population. Furthermore, subhaplogroup analysis suggested that M7b1a1 was the most likely haplogroup associated with a decreased obesity risk, and the variation T12811C (causing Y159H in ND5) harbored in M7b1a1 may be the most likely candidate for altering mitochondrial function. Specifically, we found that proportionally more nonsynonymous mutations accumulated in M7b1a1 carriers, indicating that M7b1a1 was either under positive selection or subject to a relaxation of selective constraints. We also found that nuclear variants, especially in DACT2 and PIEZO1, may functionally interact with M7b1a1.
Collapse
Affiliation(s)
- Ziwei Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Center for Evolutionary Biology, Fudan University, Shanghai, China
| | - Lu Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Jingze Tan
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Center for Evolutionary Biology, Fudan University, Shanghai, China
| | - Yizhen Mao
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, China
| | - Meng Hao
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Center for Evolutionary Biology, Fudan University, Shanghai, China
| | - Yi Li
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Center for Evolutionary Biology, Fudan University, Shanghai, China
| | - Yi Wang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Center for Evolutionary Biology, Fudan University, Shanghai, China; Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Jinxi Li
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Center for Evolutionary Biology, Fudan University, Shanghai, China
| | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Center for Evolutionary Biology, Fudan University, Shanghai, China; Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China; Research Unit of Dissecting Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai, China.
| | - Li Jin
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Center for Evolutionary Biology, Fudan University, Shanghai, China; Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China; Research Unit of Dissecting Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai, China.
| | - Hong-Xiang Zheng
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute and Center for Evolutionary Biology, Fudan University, Shanghai, China; Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China.
| |
Collapse
|
12
|
Bolognini D, Halgren AS, Lou RN, Raveane A, Rocha J, Guarracino A, Soranzo N, Chin J, Garrison E, Sudmant PH. Global diversity, recurrent evolution, and recent selection on amylase structural haplotypes in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.07.579378. [PMID: 38370750 PMCID: PMC10871346 DOI: 10.1101/2024.02.07.579378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
The adoption of agriculture, first documented ~12,000 years ago in the Fertile Crescent, triggered a rapid shift toward starch-rich diets in human populations. Amylase genes facilitate starch digestion and increased salivary amylase copy number has been observed in some modern human populations with high starch intake, though evidence of recent selection is lacking. Here, using 52 long-read diploid assemblies and short read data from ~5,600 contemporary and ancient humans, we resolve the diversity, evolutionary history, and selective impact of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in populations with agricultural subsistence compared to fishing, hunting, and pastoral groups. We identify 28 distinct amylase structural architectures and demonstrate that nearly identical structures have arisen recurrently on different haplotype backgrounds throughout recent human history. AMY1 and AMY2A genes each exhibit multiple duplications/deletions with mutation rates >10,000-fold the SNP mutation rate, whereas AMY2B gene duplications share a single origin. Using a pangenome graph-based approach to infer structural haplotypes across thousands of humans, we identify extensively duplicated haplotypes present at higher frequencies in modern day populations with traditionally agricultural diets. Leveraging 533 ancient human genomes we find that duplication-containing haplotypes (i.e. haplotypes with more amylase gene copies than the ancestral haplotype) have increased in frequency more than seven-fold over the last 12,000 years providing evidence for recent selection in West Eurasians. Together, our study highlights the potential impacts of the agricultural revolution on human genomes and the importance of long-read sequencing in identifying signatures of selection at structurally complex loci.
Collapse
|
13
|
Reich P, Möller S, Stock KF, Nolte W, von Depka Prondzinski M, Reents R, Kalm E, Kühn C, Thaller G, Falker-Gieske C, Tetens J. Genomic analyses of withers height and linear conformation traits in German Warmblood horses using imputed sequence-level genotypes. Genet Sel Evol 2024; 56:45. [PMID: 38872118 PMCID: PMC11177368 DOI: 10.1186/s12711-024-00914-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 05/30/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND Body conformation, including withers height, is a major selection criterion in horse breeding and is associated with other important traits, such as health and performance. However, little is known about the genomic background of equine conformation. Therefore, the aim of this study was to use imputed sequence-level genotypes from up to 4891 German Warmblood horses to identify genomic regions associated with withers height and linear conformation traits. Furthermore, the traits were genetically characterised and putative causal variants for withers height were detected. RESULTS A genome-wide association study (GWAS) for withers height confirmed the presence of a previously known quantitative trait locus (QTL) on Equus caballus (ECA) chromosome 3 close to the LCORL/NCAPG locus, which explained 16% of the phenotypic variance for withers height. An additional significant association signal was detected on ECA1. Further investigations of the region on ECA3 identified a few promising candidate causal variants for withers height, including a nonsense mutation in the coding sequence of the LCORL gene. The estimated heritability for withers height was 0.53 and ranged from 0 to 0.34 for the conformation traits. GWAS identified significantly associated variants for more than half of the investigated conformation traits, among which 13 showed a peak on ECA3 in the same region as withers height. Genetic parameter estimation revealed high genetic correlations between these traits and withers height for the QTL on ECA3. CONCLUSIONS The use of imputed sequence-level genotypes from a large study cohort led to the discovery of novel QTL associated with conformation traits in German Warmblood horses. The results indicate the high relevance of the QTL on ECA3 for various conformation traits, including withers height, and contribute to deciphering causal mutations for body size in horses.
Collapse
Affiliation(s)
- Paula Reich
- Department of Animal Sciences, Georg-August-University Göttingen, 37077, Göttingen, Germany.
- Center for Integrated Breeding Research (CiBreed), Georg-August-University Göttingen, 37075, Göttingen, Germany.
| | - Sandra Möller
- Department of Animal Sciences, Georg-August-University Göttingen, 37077, Göttingen, Germany
| | - Kathrin F Stock
- IT Solutions for Animal Production (vit), 27283, Verden, Germany
| | - Wietje Nolte
- Saxon State Office for Environment, Agriculture and Geology, 01468, Moritzburg, Germany
| | | | - Reinhard Reents
- IT Solutions for Animal Production (vit), 27283, Verden, Germany
| | - Ernst Kalm
- Institute of Animal Breeding and Husbandry, Kiel University, 24098, Kiel, Germany
| | - Christa Kühn
- Institute of Genome Biology, Research Institute for Farm Animal Biology (FBN), 18196, Dummerstorf, Germany
- Faculty of Agricultural and Environmental Sciences, University of Rostock, 18059, Rostock, Germany
- Friedrich-Loeffler-Institute, 17493, Greifswald - Riems Island, Germany
| | - Georg Thaller
- Institute of Animal Breeding and Husbandry, Kiel University, 24098, Kiel, Germany
| | - Clemens Falker-Gieske
- Department of Animal Sciences, Georg-August-University Göttingen, 37077, Göttingen, Germany
- Center for Integrated Breeding Research (CiBreed), Georg-August-University Göttingen, 37075, Göttingen, Germany
| | - Jens Tetens
- Department of Animal Sciences, Georg-August-University Göttingen, 37077, Göttingen, Germany
- Center for Integrated Breeding Research (CiBreed), Georg-August-University Göttingen, 37075, Göttingen, Germany
| |
Collapse
|
14
|
Lucas SE, Yang T, Wimberly CE, Parmar KV, Hansen HM, de Smith AJ, Morimoto LM, Metayer C, Ostrom QT, Eward WC, Graves LA, Wagner LM, Wiemels JL, Spector LG, Walsh KM. Genetic variation near GRB10 associated with bone growth and osteosarcoma risk in canine and human populations. Cancer Epidemiol 2024:102599. [PMID: 38871555 DOI: 10.1016/j.canep.2024.102599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 06/06/2024] [Accepted: 06/07/2024] [Indexed: 06/15/2024]
Abstract
BACKGROUND Canine and human osteosarcoma are similar in clinical presentation and tumor genomics. Giant breed dogs experience elevated osteosarcoma incidence, and taller stature remains a consistent risk factor for human osteosarcoma. Whether evolutionarily conserved genes contribute to both human and canine osteosarcoma predisposition merits evaluation. METHODS A multi-center sample of childhood osteosarcoma patients and controls underwent genome-wide genotyping and imputation. Ancestry-adjusted SNP associations were calculated within each dataset using logistic regression, then meta-analyzed across the three datasets, totaling 1091 patients and 3026 controls. Ten regions previously associated with canine osteosarcoma risk were mapped to the human genome, spanning ∼6 Mb. We prioritized association testing of 5985 human SNPs mapping to candidate osteosarcoma risk regions detected in Irish wolfhounds, the largest dog breed studied. Secondary analyses explored 6289 additional human SNPs mapping to candidate osteosarcoma risk regions identified in Rottweilers and greyhounds. RESULTS Fourteen SNPs were associated with human osteosarcoma risk after adjustment for multiple comparisons, all within a 42 kb region of human Chromosome 7p12.1. The lead variant was rs17454681 (OR=1.25, 95 %CI: 1.12-1.39; P=4.1×10-5), and independent risk variants were not observed in conditional analyses. While the associated region spanned 2.1 Mb and contained eight genes in Irish wolfhounds, associations were localized to a 50-fold smaller region of the human genome and strongly implicate GRB10 (growth factor receptor-bound protein 10) in canine and human osteosarcoma predisposition. PheWAS analysis in UK Biobank data identified noteworthy associations of the rs17454681 risk allele with varied measures of height and pubertal timing. CONCLUSIONS Our comparative oncology analysis identified a novel human osteosarcoma risk allele near GRB10, a growth inhibitor that suppresses activated receptor tyrosine kinases including IGF1R, PDGFRB, and EGFR. Epidemiologists may benefit from leveraging cross-species comparisons to identify haplotypes in highly susceptible but genetically homogenous populations of domesticated animals, then fine-mapping these associations in diverse human populations.
Collapse
Affiliation(s)
- Sydney E Lucas
- Preston Robert Tisch Brain Tumor Center, Department of Neurosurgery, Duke University, Durham, NC, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Tianzhong Yang
- Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, USA; Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Courtney E Wimberly
- Preston Robert Tisch Brain Tumor Center, Department of Neurosurgery, Duke University, Durham, NC, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Kajal V Parmar
- Preston Robert Tisch Brain Tumor Center, Department of Neurosurgery, Duke University, Durham, NC, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Helen M Hansen
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Adam J de Smith
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Libby M Morimoto
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Catherine Metayer
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Quinn T Ostrom
- Preston Robert Tisch Brain Tumor Center, Department of Neurosurgery, Duke University, Durham, NC, USA; Duke Cancer Institute, Duke University, Durham, NC, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - William C Eward
- Duke Cancer Institute, Duke University, Durham, NC, USA; Department of Orthopaedic Surgery, Duke University, Durham, NC, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Laurie A Graves
- Department of Pediatrics, Duke University, Durham, NC, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Lars M Wagner
- Duke Cancer Institute, Duke University, Durham, NC, USA; Department of Pediatrics, Duke University, Durham, NC, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Joseph L Wiemels
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Logan G Spector
- Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA
| | - Kyle M Walsh
- Preston Robert Tisch Brain Tumor Center, Department of Neurosurgery, Duke University, Durham, NC, USA; Duke Cancer Institute, Duke University, Durham, NC, USA; Department of Pediatrics, Duke University, Durham, NC, USA; Division of Pediatric Hematology/Oncology, Duke University Medical Center, Durham, NC, USA.
| |
Collapse
|
15
|
Herrera-Rivero M, Adli M, Akiyama K, Akula N, Amare AT, Ardau R, Arias B, Aubry JM, Backlund L, Bellivier F, Benabarre A, Bengesser S, Bhattacharjee AK, Biernacka JM, Birner A, Cearns M, Cervantes P, Chen HC, Chillotti C, Cichon S, Clark SR, Colom F, Cruceanu C, Czerski PM, Dalkner N, Degenhardt F, Del Zompo M, DePaulo JR, Etain B, Falkai P, Ferensztajn-Rochowiak E, Forstner AJ, Frank J, Frisén L, Frye MA, Fullerton JM, Gallo C, Gard S, Garnham JS, Goes FS, Grigoroiu-Serbanescu M, Grof P, Hashimoto R, Hasler R, Hauser J, Heilbronner U, Herms S, Hoffmann P, Hou L, Hsu YH, Jamain S, Jiménez E, Kahn JP, Kassem L, Kato T, Kelsoe J, Kittel-Schneider S, Kuo PH, Kusumi I, König B, Laje G, Landén M, Lavebratt C, Leboyer M, Leckband SG, Maj M, Manchia M, Marie-Claire C, Martinsson L, McCarthy MJ, McElroy SL, Millischer V, Mitjans M, Mondimore FM, Monteleone P, Nievergelt CM, Novák T, Nöthen MM, O'Donovan C, Ozaki N, Papiol S, Pfennig A, Pisanu C, Potash JB, Reif A, Reininghaus E, Richard-Lepouriel H, Roberts G, Rouleau GA, Rybakowski JK, Schalling M, Schofield PR, Schubert KO, Schulte EC, Schweizer BW, Severino G, Shekhtman T, Shilling PD, Shimoda K, Simhandl C, Slaney CM, Squassina A, Stamm T, Stopkova P, Streit F, Tekola-Ayele F, Thalamuthu A, Tortorella A, Turecki G, Veeh J, Vieta E, Viswanath B, Witt SH, Zandi PP, Alda M, Bauer M, McMahon FJ, Mitchell PB, Rietschel M, Schulze TG, Baune BT. Exploring the genetics of lithium response in bipolar disorders. Int J Bipolar Disord 2024; 12:20. [PMID: 38865039 PMCID: PMC11169116 DOI: 10.1186/s40345-024-00341-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 05/02/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N = 2064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. RESULTS We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. CONCLUSIONS Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.
Collapse
Affiliation(s)
- Marisol Herrera-Rivero
- Department of Psychiatry, University of Münster and Joint Institute for Individualisation in a Changing Environment (JICE), University of Münster and Bielefeld University, Albert-Schweitzer-Campus 1, Building A9, 48149, Münster, Germany
| | - Mazda Adli
- Department of Psychiatry and Psychotherapy, Charité, Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
- Fliedner Klinik Berlin, Berlin, Germany
| | - Kazufumi Akiyama
- Department of Biological Psychiatry and Neuroscience, Dokkyo Medical University School of Medicine, Mibu, Japan
| | - Nirmala Akula
- Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Department of Health & Human Services, Baltimore, USA
| | - Azmeraw T Amare
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia
| | - Raffaella Ardau
- Unit of Clinical Pharmacology, Hospital University Agency of Cagliari, Cagliari, Italy
| | - Bárbara Arias
- Unitat de Zoologia i Antropologia Biològica (Dpt. Biologia Evolutiva, Ecologia i Ciències Ambientals), Facultat de Biologia and Institut de Biomedicina (IBUB), University of Barcelona, CIBERSAM, Barcelona, Spain
| | - Jean-Michel Aubry
- Department of Psychiatry, Division of Psychiatric Specialities, Geneva University Hospitals, Geneva, Switzerland
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Lena Backlund
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine at Karolinska University Hospital, Karolinska Institute, Stockholm, Sweden
| | - Frank Bellivier
- Département de Psychiatrie et de Médecine Addictologique, INSERM UMR-S 1144, Université Paris Cité, AP-HP, Groupe Hospitalier Saint-Louis-Lariboisière, F. Widal, Paris, France
| | - Antonio Benabarre
- Bipolar Disorder Program, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Spain
| | - Susanne Bengesser
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Graz, Austria
| | | | - Joanna M Biernacka
- Department of Health Sciences Research, Mayo Clinic, Rochester, USA
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, USA
| | - Armin Birner
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Graz, Austria
| | - Micah Cearns
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia
| | - Pablo Cervantes
- The Neuromodulation Unit, McGill University Health Centre, Montreal, Canada
| | - Hsi-Chung Chen
- Department of Psychiatry & Center of Sleep Disorders, National Taiwan University Hospital, Taipei, Taiwan
| | - Caterina Chillotti
- Unit of Clinical Pharmacology, Hospital University Agency of Cagliari, Cagliari, Italy
| | - Sven Cichon
- Human Genomics Research Group, Department of Biomedicine, University Hospital Basel, Basel, Switzerland
- Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - Scott R Clark
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia
| | - Francesc Colom
- Mental Health Research Group, IMIM-Hospital del Mar, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Cristiana Cruceanu
- Douglas Mental Health University Institute, McGill University, Montreal, Canada
| | - Piotr M Czerski
- Psychiatric Genetic Unit, Poznan University of Medical Sciences, Poznań, Poland
| | - Nina Dalkner
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Graz, Austria
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Maria Del Zompo
- Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - J Raymond DePaulo
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, USA
| | - Bruno Etain
- Département de Psychiatrie et de Médecine Addictologique, INSERM UMR-S 1144, Université Paris Cité, AP-HP, Groupe Hospitalier Saint-Louis-Lariboisière, F. Widal, Paris, France
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University Munich, Munich, Germany
| | | | - Andreas J Forstner
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Louise Frisén
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Mark A Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, USA
| | - Janice M Fullerton
- Neuroscience Research, Australia and School of Biomedical Sciences, University of New South Wales, Sydney, Australia
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, San Martín de Porres, Peru
| | - Sébastien Gard
- Service de Psychiatrie, Hôpital Charles Perrens, Bordeaux, France
| | - Julie S Garnham
- Department of Psychiatry, Dalhousie University, Halifax, Canada
| | - Fernando S Goes
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, USA
| | - Maria Grigoroiu-Serbanescu
- Biometric Psychiatric Genetics Research Unit, Alexandru Obregia Clinical Psychiatric Hospital, Bucharest, Romania
| | - Paul Grof
- Mood Disorders Center of Ottawa, Ottawa, Canada
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Roland Hasler
- Department of Psychiatry, Division of Psychiatric Specialities, Geneva University Hospitals, Geneva, Switzerland
| | - Joanna Hauser
- Psychiatric Genetic Unit, Poznan University of Medical Sciences, Poznań, Poland
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Stefan Herms
- Human Genomics Research Group, Department of Biomedicine, University Hospital Basel, Basel, Switzerland
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Per Hoffmann
- Human Genomics Research Group, Department of Biomedicine, University Hospital Basel, Basel, Switzerland
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Liping Hou
- Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Department of Health & Human Services, Baltimore, USA
| | - Yi-Hsiang Hsu
- Program for Quantitative Genomics, Harvard School of Public Health and HSL Institute for Aging Research, Harvard Medical School, Boston, USA
| | - Stephane Jamain
- Univ. Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France
| | - Esther Jiménez
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, ISCIII, Barcelona, Spain
| | - Jean-Pierre Kahn
- Service de Psychiatrie et Psychologie Clinique, Centre Psychothérapique de Nancy - Université, Nancy, France
| | - Layla Kassem
- Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Department of Health & Human Services, Baltimore, USA
| | - Tadafumi Kato
- Department of Psychiatry & Behavioral Science, Graduate School of Medicine, Juntendo University, Tokyo, Japan
| | - John Kelsoe
- Department of Psychiatry, University of California San Diego, San Diego, USA
| | - Sarah Kittel-Schneider
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Würzburg, Würzburg, Germany
| | - Po-Hsiu Kuo
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Ichiro Kusumi
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Barbara König
- Department of Psychiatry and Psychotherapeutic Medicine, Landesklinikum Neunkirchen, Neunkirchen, Austria
| | - Gonzalo Laje
- Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Department of Health & Human Services, Baltimore, USA
| | - Mikael Landén
- Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the Gothenburg University, Gothenburg, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Catharina Lavebratt
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine at Karolinska University Hospital, Karolinska Institute, Stockholm, Sweden
| | - Marion Leboyer
- Univ. Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, AP-HP, Mondor University Hospital, DMU Impact, Fondation FondaMental, Créteil, France
| | - Susan G Leckband
- Office of Mental Health, VA San Diego Healthcare System, California, USA
| | - Mario Maj
- Department of Psychiatry, University of Campania 'Luigi Vanvitelli', Caserta, Italy
| | - Mirko Manchia
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Department of Pharmacology, Dalhousie University, Halifax, Canada
| | - Cynthia Marie-Claire
- Université Paris Cité, Inserm UMR-S 1144, Optimisation Thérapeutique en Neuropsychopharmacologie, 75006, Paris, France
| | - Lina Martinsson
- Department of Clinical Neurosciences, Karolinska Institutet, Stockholm, Sweden
| | - Michael J McCarthy
- Department of Psychiatry, University of California San Diego, San Diego, USA
- Department of Psychiatry, VA San Diego Healthcare System, San Diego, CA, USA
| | - Susan L McElroy
- Department of Psychiatry, Lindner Center of Hope/University of Cincinnati, Cincinnati, USA
| | - Vincent Millischer
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine at Karolinska University Hospital, Karolinska Institute, Stockholm, Sweden
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
| | - Marina Mitjans
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, Institut de Biomedicina de La Universitat de Barcelona (IBUB), University of Barcelona, Barcelona, Spain
| | - Francis M Mondimore
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, USA
| | - Palmiero Monteleone
- Department of Medicine, Surgery and Dentistry 'Scuola Medica Salernitana', University of Salerno, Baronissi, Italy
| | | | - Tomas Novák
- National Institute of Mental Health, Klecany, Czech Republic
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | | | - Norio Ozaki
- Department of Psychiatry & Department of Child and Adolescent Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Sergi Papiol
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University Munich, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Andrea Pfennig
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Medical Faculty, Technische Universität Dresden, Dresden, Germany
| | - Claudia Pisanu
- Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - James B Potash
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, USA
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt, Germany
| | - Eva Reininghaus
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Graz, Austria
| | - Hélène Richard-Lepouriel
- Department of Psychiatry, Division of Psychiatric Specialities, Geneva University Hospitals, Geneva, Switzerland
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Gloria Roberts
- School of Psychiatry, University of New South Wales, Sydney, Australia
| | - Guy A Rouleau
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Janusz K Rybakowski
- Department of Adult Psychiatry, Poznan University of Medical Sciences, Poznań, Poland
| | - Martin Schalling
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine at Karolinska University Hospital, Karolinska Institute, Stockholm, Sweden
| | - Peter R Schofield
- Neuroscience Research, Australia and School of Biomedical Sciences, University of New South Wales, Sydney, Australia
| | - Klaus Oliver Schubert
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, Australia
- Northern Adelaide Local Health Network, Mental Health Services, Adelaide, Australia
| | - Eva C Schulte
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University Munich, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Medical Faculty University of Bonn, Bonn, Germany
| | - Barbara W Schweizer
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, USA
| | - Giovanni Severino
- Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Tatyana Shekhtman
- Department of Psychiatry, University of California San Diego, San Diego, USA
| | - Paul D Shilling
- Department of Psychiatry, University of California San Diego, San Diego, USA
| | - Katzutaka Shimoda
- Department of Psychiatry, Dokkyo Medical University School of Medicine, Mibu, Japan
| | - Christian Simhandl
- Medical Faculty, Bipolar Center Wiener Neustadt, Sigmund Freud University, Vienna, Austria
| | - Claire M Slaney
- Department of Psychiatry, Dalhousie University, Halifax, Canada
| | - Alessio Squassina
- Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Thomas Stamm
- Department of Psychiatry and Psychotherapy, Charité, Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Pavla Stopkova
- National Institute of Mental Health, Klecany, Czech Republic
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, USA
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
| | | | - Gustavo Turecki
- Douglas Mental Health University Institute, McGill University, Montreal, Canada
| | - Julia Veeh
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt, Germany
| | - Eduard Vieta
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, ISCIII, Barcelona, Spain
| | - Biju Viswanath
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, 560029, India
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Peter P Zandi
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, Canada
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Medical Faculty, Technische Universität Dresden, Dresden, Germany
| | - Francis J McMahon
- Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Department of Health & Human Services, Baltimore, USA
| | - Philip B Mitchell
- School of Psychiatry, University of New South Wales, Sydney, Australia
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Thomas G Schulze
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, USA
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, Norton College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster and Joint Institute for Individualisation in a Changing Environment (JICE), University of Münster and Bielefeld University, Albert-Schweitzer-Campus 1, Building A9, 48149, Münster, Germany.
- Department of Psychiatry, Melbourne Medical School, University of Melbourne and The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia.
| |
Collapse
|
16
|
Jermy B, Läll K, Wolford BN, Wang Y, Zguro K, Cheng Y, Kanai M, Kanoni S, Yang Z, Hartonen T, Monti R, Wanner J, Youssef O, Lippert C, van Heel D, Okada Y, McCartney DL, Hayward C, Marioni RE, Furini S, Renieri A, Martin AR, Neale BM, Hveem K, Mägi R, Palotie A, Heyne H, Mars N, Ganna A, Ripatti S. A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk. Nat Commun 2024; 15:5007. [PMID: 38866767 PMCID: PMC11169548 DOI: 10.1038/s41467-024-48938-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 05/17/2024] [Indexed: 06/14/2024] Open
Abstract
Polygenic scores (PGSs) offer the ability to predict genetic risk for complex diseases across the life course; a key benefit over short-term prediction models. To produce risk estimates relevant to clinical and public health decision-making, it is important to account for varying effects due to age and sex. Here, we develop a novel framework to estimate country-, age-, and sex-specific estimates of cumulative incidence stratified by PGS for 18 high-burden diseases. We integrate PGS associations from seven studies in four countries (N = 1,197,129) with disease incidences from the Global Burden of Disease. PGS has a significant sex-specific effect for asthma, hip osteoarthritis, gout, coronary heart disease and type 2 diabetes (T2D), with all but T2D exhibiting a larger effect in men. PGS has a larger effect in younger individuals for 13 diseases, with effects decreasing linearly with age. We show for breast cancer that, relative to individuals in the bottom 20% of polygenic risk, the top 5% attain an absolute risk for screening eligibility 16.3 years earlier. Our framework increases the generalizability of results from biobank studies and the accuracy of absolute risk estimates by appropriately accounting for age- and sex-specific PGS effects. Our results highlight the potential of PGS as a screening tool which may assist in the early prevention of common diseases.
Collapse
Affiliation(s)
- Bradley Jermy
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Brooke N Wolford
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ying Wang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kristina Zguro
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
| | - Yipeng Cheng
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Zhiyu Yang
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Tuomo Hartonen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Remo Monti
- Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
| | - Julian Wanner
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
| | - Omar Youssef
- Helsinki Biobank, Hospital District of Helsinki and Uusimaa (HUS), Helsinki, Finland
- Pathology Department, University of Helsinki, Helsinki, Finland
| | - Christoph Lippert
- Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
- Hasso Plattner Institute for Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - David van Heel
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Yukinori Okada
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Simone Furini
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
- Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy
| | - Alessandra Renieri
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
- Medical Genetics, University of Siena, Siena, Italy
- Genetica Medica, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Alicia R Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Henrike Heyne
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
- Hasso Plattner Institute for Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nina Mars
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland.
- Massachusetts General Hospital, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland.
- Massachusetts General Hospital, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Public Health, University of Helsinki, Helsinki, Finland.
| |
Collapse
|
17
|
Rodriguez-Algarra F, Evans DM, Rakyan VK. Ribosomal DNA copy number variation associates with hematological profiles and renal function in the UK Biobank. CELL GENOMICS 2024; 4:100562. [PMID: 38749448 DOI: 10.1016/j.xgen.2024.100562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 11/19/2023] [Accepted: 04/21/2024] [Indexed: 06/15/2024]
Abstract
The phenotypic impact of genetic variation of repetitive features in the human genome is currently understudied. One such feature is the multi-copy 47S ribosomal DNA (rDNA) that codes for rRNA components of the ribosome. Here, we present an analysis of rDNA copy number (CN) variation in the UK Biobank (UKB). From the first release of UKB whole-genome sequencing (WGS) data, a discovery analysis in White British individuals reveals that rDNA CN associates with altered counts of specific blood cell subtypes, such as neutrophils, and with the estimated glomerular filtration rate, a marker of kidney function. Similar trends are observed in other ancestries. A range of analyses argue against reverse causality or common confounder effects, and all core results replicate in the second UKB WGS release. Our work demonstrates that rDNA CN is a genetic influence on trait variance in humans.
Collapse
Affiliation(s)
| | - David M Evans
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia; Frazer Institute, The University of Queensland, Brisbane, QLD 4102, Australia; MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
| | - Vardhman K Rakyan
- The Blizard Institute, School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK.
| |
Collapse
|
18
|
Taylor AJ, Yahara K, Pascoe B, Ko S, Mageiros L, Mourkas E, Calland JK, Puranen S, Hitchings MD, Jolley KA, Kobras CM, Bayliss S, Williams NJ, van Vliet AHM, Parkhill J, Maiden MCJ, Corander J, Hurst LD, Falush D, Keim P, Didelot X, Kelly DJ, Sheppard SK. Epistasis, core-genome disharmony, and adaptation in recombining bacteria. mBio 2024; 15:e0058124. [PMID: 38683013 DOI: 10.1128/mbio.00581-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 03/26/2024] [Indexed: 05/01/2024] Open
Abstract
Recombination of short DNA fragments via horizontal gene transfer (HGT) can introduce beneficial alleles, create genomic disharmony through negative epistasis, and create adaptive gene combinations through positive epistasis. For non-core (accessory) genes, the negative epistatic cost is likely to be minimal because the incoming genes have not co-evolved with the recipient genome and are frequently observed as tightly linked cassettes with major effects. By contrast, interspecific recombination in the core genome is expected to be rare because disruptive allelic replacement is likely to introduce negative epistasis. Why then is homologous recombination common in the core of bacterial genomes? To understand this enigma, we take advantage of an exceptional model system, the common enteric pathogens Campylobacter jejuni and C. coli that are known for very high magnitude interspecies gene flow in the core genome. As expected, HGT does indeed disrupt co-adapted allele pairings, indirect evidence of negative epistasis. However, multiple HGT events enable recovery of the genome's co-adaption between introgressing alleles, even in core metabolism genes (e.g., formate dehydrogenase). These findings demonstrate that, even for complex traits, genetic coalitions can be decoupled, transferred, and independently reinstated in a new genetic background-facilitating transition between fitness peaks. In this example, the two-step recombinational process is associated with C. coli that are adapted to the agricultural niche.IMPORTANCEGenetic exchange among bacteria shapes the microbial world. From the acquisition of antimicrobial resistance genes to fundamental questions about the nature of bacterial species, this powerful evolutionary force has preoccupied scientists for decades. However, the mixing of genes between species rests on a paradox: 0n one hand, promoting adaptation by conferring novel functionality; on the other, potentially introducing disharmonious gene combinations (negative epistasis) that will be selected against. Taking an interdisciplinary approach to analyze natural populations of the enteric bacteria Campylobacter, an ideal example of long-range admixture, we demonstrate that genes can independently transfer across species boundaries and rejoin in functional networks in a recipient genome. The positive impact of two-gene interactions appears to be adaptive by expanding metabolic capacity and facilitating niche shifts through interspecific hybridization. This challenges conventional ideas and highlights the possibility of multiple-step evolution of multi-gene traits by interspecific introgression.
Collapse
Affiliation(s)
- Aidan J Taylor
- School of Biological Sciences, University of Reading, Reading, United Kingdom
| | - Koji Yahara
- Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo, Japan
| | - Ben Pascoe
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | - Seungwon Ko
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | - Leonardos Mageiros
- Swansea University Medical School, Institute of Life Science, Swansea, United Kingdom
- The Department of Biology and Biochemistry, University of Bath, Bath, United Kingdom
| | | | - Jessica K Calland
- Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway
| | - Santeri Puranen
- Department of Mathematics and Statistics, Helsinki Institute for Information Technology, University of Helsinki, Helsinki, Finland
| | - Matthew D Hitchings
- Swansea University Medical School, Institute of Life Science, Swansea, United Kingdom
| | - Keith A Jolley
- Department of Biology, University of Oxford, Oxford, United Kingdom
| | - Carolin M Kobras
- Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
| | - Sion Bayliss
- Bristol Veterinary School, University of Bristol, Bristol, United Kingdom
| | - Nicola J Williams
- Department of Epidemiology and Population Health, Institute of Infection and Global Health, University of Liverpool, Leahurst Campus, Wirral, United Kingdom
| | | | - Julian Parkhill
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | | | - Jukka Corander
- Department of Mathematics and Statistics, Helsinki Institute for Information Technology, University of Helsinki, Helsinki, Finland
- Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
- Parasites and Microbes, Wellcome Sanger Institute, Cambridge, United Kingdom
| | - Laurence D Hurst
- The Department of Biology and Biochemistry, University of Bath, Bath, United Kingdom
| | - Daniel Falush
- The Centre for Microbes, Development and Health, Institut Pasteur of Shanghai, Shanghai, China
| | - Paul Keim
- Department of Biology, University of Oxford, Oxford, United Kingdom
- The Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, USA
- Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona, USA
| | - Xavier Didelot
- Department of Statistics, School of Life Sciences, University of Warwick, Coventry, United Kingdom
| | - David J Kelly
- School of Biosciences, University of Sheffield, Sheffield, United Kingdom
| | | |
Collapse
|
19
|
Chen T, Pham G, Fox L, Adler N, Wang X, Zhang J, Byun J, Han Y, Saunders GRB, Liu D, Bray MJ, Ramsey AT, McKay J, Bierut L, Amos CI, Hung RJ, Lin X, Zhang H, Chen LS. Genomic Insights for Personalized Care: Motivating At-Risk Individuals Toward Evidence-Based Health Practices. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.19.24304556. [PMID: 38562690 PMCID: PMC10984046 DOI: 10.1101/2024.03.19.24304556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Background Lung cancer and tobacco use pose significant global health challenges, necessitating a comprehensive translational roadmap for improved prevention strategies. Polygenic risk scores (PRSs) are powerful tools for patient risk stratification but have not yet been widely used in primary care for lung cancer, particularly in diverse patient populations. Methods We propose the GREAT care paradigm, which employs PRSs to stratify disease risk and personalize interventions. We developed PRSs using large-scale multi-ancestry genome-wide association studies and standardized PRS distributions across all ancestries. We applied our PRSs to 796 individuals from the GISC Trial, 350,154 from UK Biobank (UKBB), and 210,826 from All of Us Research Program (AoU), totaling 561,776 individuals of diverse ancestry. Results Significant odds ratios (ORs) for lung cancer and difficulty quitting smoking were observed in both UKBB and AoU. For lung cancer, the ORs for individuals in the highest risk group (top 20% versus bottom 20%) were 1.85 (95% CI: 1.58 - 2.18) in UKBB and 2.39 (95% CI: 1.93 - 2.97) in AoU. For difficulty quitting smoking, the ORs (top 33% versus bottom 33%) were 1.36 (95% CI: 1.32 - 1.41) in UKBB and 1.32 (95% CI: 1.28 - 1.36) in AoU. Conclusion Our PRS-based intervention model leverages large-scale genetic data for robust risk assessment across populations. This model will be evaluated in two cluster-randomized clinical trials aimed at motivating health behavior changes in high-risk patients of diverse ancestry. This pioneering approach integrates genomic insights into primary care, promising improved outcomes in cancer prevention and tobacco treatment.
Collapse
|
20
|
Gelernter J, Levey DF, Galimberti M, Harrington K, Zhou H, Adhikari K, Gupta P, Gaziano JM, Eliott D, Stein MB. Genome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations. CELL GENOMICS 2024; 4:100582. [PMID: 38870908 DOI: 10.1016/j.xgen.2024.100582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 02/20/2024] [Accepted: 05/10/2024] [Indexed: 06/15/2024]
Abstract
Epiretinal membrane (ERM) is a common retinal condition characterized by the presence of fibrocellular tissue on the retinal surface, often with visual distortion and loss of visual acuity. We studied European American (EUR), African American (AFR), and Latino (admixed American, AMR) ERM participants in the Million Veteran Program (MVP) for genome-wide association analysis-a total of 38,232 case individuals and 557,988 control individuals. We completed a genome-wide association study (GWAS) in each population separately, and then results were meta-analyzed. Genome-wide significant (GWS) associations were observed in all three populations studied: 31 risk loci in EUR subjects, 3 in AFR, and 2 in AMR, with 48 in trans-ancestry meta-analysis. Many results replicated in the FinnGen sample. Several GWS variants associate to alterations in gene expression in the macula. ERM showed significant genetic correlation to multiple traits. Pathway enrichment analyses implicated collagen and collagen-adjacent mechanisms, among others. This well-powered ERM GWAS identified novel genetic associations that point to biological mechanisms for ERM.
Collapse
Affiliation(s)
- Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA; Departments of Genetics and Neuroscience, Yale School of Medicine, New Haven, CT, USA.
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Marco Galimberti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Kelly Harrington
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA; Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Keyrun Adhikari
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Priya Gupta
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - J Michael Gaziano
- Department of Medicine, Harvard Medical School, Boston, MA, USA; Department of Medicine, Divisions of Aging and Preventative Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dean Eliott
- Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Murray B Stein
- University of California, San Diego, La Jolla, CA, USA; VA San Diego Healthcare System, San Diego, CA, USA
| |
Collapse
|
21
|
Jonsson L, Hörbeck E, Primerano A, Song J, Karlsson R, Smedler E, Gordon-Smith K, Jones L, Craddock N, Jones I, Sullivan PF, Pålsson E, Di Florio A, Sparding T, Landén M. Association of Occupational Dysfunction and Hospital Admissions With Different Polygenic Profiles in Bipolar Disorder. Am J Psychiatry 2024:appiajp20230073. [PMID: 38859703 DOI: 10.1176/appi.ajp.20230073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/12/2024]
Abstract
OBJECTIVE Many but not all persons with bipolar disorder require hospital care because of severe mood episodes. Likewise, some but not all patients experience long-term occupational dysfunction that extends beyond acute mood episodes. It is not known whether these dissimilar outcomes of bipolar disorder are driven by different polygenic profiles. Here, polygenic scores (PGSs) for major psychiatric disorders and educational attainment were assessed for associations with occupational functioning and psychiatric hospital admissions in bipolar disorder. METHODS A total of 4,782 patients with bipolar disorder and 2,963 control subjects were genotyped and linked to Swedish national registers. Longitudinal measures from at least 10 years of registry data were used to derive percentage of years without employment, percentage of years with long-term sick leave, and mean number of psychiatric hospital admissions per year. Ordinal regression was used to test associations between outcomes and PGSs for bipolar disorder, schizophrenia, major depressive disorder, attention deficit hyperactivity disorder (ADHD), and educational attainment. Replication analyses of hospital admissions were conducted with data from the Bipolar Disorder Research Network cohort (N=4,219). RESULTS Long-term sick leave and unemployment in bipolar disorder were significantly associated with PGSs for schizophrenia, ADHD, major depressive disorder, and educational attainment, but not with the PGS for bipolar disorder. By contrast, the number of hospital admissions per year was associated with higher PGSs for bipolar disorder and schizophrenia, but not with the other PGSs. CONCLUSIONS Bipolar disorder severity (indexed by hospital admissions) was associated with a different polygenic profile than long-term occupational dysfunction. These findings have clinical implications, suggesting that mitigating occupational dysfunction requires interventions other than those deployed to prevent mood episodes.
Collapse
Affiliation(s)
- Lina Jonsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Elin Hörbeck
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Amedeo Primerano
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Jie Song
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Robert Karlsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Erik Smedler
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Katherine Gordon-Smith
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Lisa Jones
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Nicholas Craddock
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Ian Jones
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Patrick F Sullivan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Erik Pålsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Arianna Di Florio
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Timea Sparding
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| | - Mikael Landén
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden (Jonsson, Hörbeck, Smedler, Pålsson, Sparding, Landén); National Centre for Mental Health, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, U.K. (Primerano, Craddock, I. Jones, Di Florio); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Song, Karlsson, Sullivan, Landén); Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China (Song); Department of Psychological Medicine, University of Worcester, Worcester, U.K. (Gordon-Smith, L. Jones); Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill (Sullivan)
| |
Collapse
|
22
|
Yuan H, Liu Z, Chen M, Xu Q, Jiang Y, Zhang T, Suo C, Chen X. Protein truncating variants in mitochondrial-related nuclear genes and the risk of chronic liver disease. BMC Med 2024; 22:239. [PMID: 38862964 PMCID: PMC11167739 DOI: 10.1186/s12916-024-03466-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 06/05/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND Mitochondrial (MT) dysfunction is a hallmark of liver diseases. However, the effects of functional variants such as protein truncating variants (PTVs) in MT-related genes on the risk of liver diseases have not been extensively explored. METHODS We extracted 60,928 PTVs across 2466 MT-related nucleus genes using whole-exome sequencing data obtained from 442,603 participants in the UK Biobank. We examined their associations with liver dysfunction that represented by the liver-related biomarkers and the risks of chronic liver diseases and liver-related mortality. RESULTS 96.10% of the total participants carried at least one PTV. We identified 866 PTVs that were positively associated with liver dysfunction at the threshold of P value < 8.21e - 07. The coding genes of these PTVs were mainly enriched in pathways related to lipid, fatty acid, amino acid, and carbohydrate metabolisms. The 866 PTVs were presented in 1.07% (4721) of participants. Compared with participants who did not carry any of the PTVs, the carriers had a 5.33-fold (95% CI 4.15-6.85), 2.82-fold (1.69-4.72), and 4.41-fold (3.04-6.41) increased risk for fibrosis and cirrhosis of liver, liver cancer, and liver disease-related mortality, respectively. These adverse effects were consistent across subgroups based on age, sex, body mass index, smoking status, and presence of hypertension, diabetes, dyslipidemia, and metabolic syndrome. CONCLUSIONS Our findings revealed a significant impact of PTVs in MT-related genes on liver disease risk, highlighting the importance of these variants in identifying populations at risk of liver diseases and facilitating early clinical interventions.
Collapse
Affiliation(s)
- Huangbo Yuan
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and School of Life Sciences, Fudan University, No. 2005 Songhu Road, Shanghai, 200438, China
| | - Zhenqiu Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and School of Life Sciences, Fudan University, No. 2005 Songhu Road, Shanghai, 200438, China
| | - Mingyang Chen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and School of Life Sciences, Fudan University, No. 2005 Songhu Road, Shanghai, 200438, China
| | - Qiaoyi Xu
- Department of Epidemiology, School of Public Health, Fudan University, No. 130 Dongan Road, Shanghai, 200032, China
| | - Yanfeng Jiang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and School of Life Sciences, Fudan University, No. 2005 Songhu Road, Shanghai, 200438, China
- Fudan University Taizhou Institute of Health Sciences, Taizhou, China
| | - Tiejun Zhang
- Department of Epidemiology, School of Public Health, Fudan University, No. 130 Dongan Road, Shanghai, 200032, China
- Fudan University Taizhou Institute of Health Sciences, Taizhou, China
| | - Chen Suo
- Department of Epidemiology, School of Public Health, Fudan University, No. 130 Dongan Road, Shanghai, 200032, China.
- Fudan University Taizhou Institute of Health Sciences, Taizhou, China.
| | - Xingdong Chen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and School of Life Sciences, Fudan University, No. 2005 Songhu Road, Shanghai, 200438, China.
- Fudan University Taizhou Institute of Health Sciences, Taizhou, China.
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
- Yiwu Research Institute of Fudan University, Yiwu, China.
| |
Collapse
|
23
|
Petrazzini BO, Forrest IS, Rocheleau G, Vy HMT, Márquez-Luna C, Duffy Á, Chen R, Park JK, Gibson K, Goonewardena SN, Malick WA, Rosenson RS, Jordan DM, Do R. Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease. Nat Genet 2024:10.1038/s41588-024-01791-x. [PMID: 38862854 DOI: 10.1038/s41588-024-01791-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 05/08/2024] [Indexed: 06/13/2024]
Abstract
Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk factors and pathogenic processes. An in silico score for CAD built using machine learning and clinical data in electronic health records captures disease progression, severity and underdiagnosis on this spectrum and could enhance genetic discovery efforts for CAD. Here we tested associations of rare and ultrarare coding variants with the in silico score for CAD in the UK Biobank, All of Us Research Program and BioMe Biobank. We identified associations in 17 genes; of these, 14 show at least moderate levels of prior genetic, biological and/or clinical support for CAD. We also observed an excess of ultrarare coding variants in 321 aggregated CAD genes, suggesting more ultrarare variant associations await discovery. These results expand our understanding of the genetic etiology of CAD and illustrate how digital markers can enhance genetic association investigations for complex diseases.
Collapse
Affiliation(s)
- Ben Omega Petrazzini
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Iain S Forrest
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ghislain Rocheleau
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ha My T Vy
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Carla Márquez-Luna
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Áine Duffy
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert Chen
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joshua K Park
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kyle Gibson
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sascha N Goonewardena
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Division of Cardiovascular Medicine, VA Ann Arbor Health System, Ann Arbor, MI, USA
| | - Waqas A Malick
- Metabolism and Lipids Program, Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert S Rosenson
- Metabolism and Lipids Program, Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daniel M Jordan
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Center for Genomic Data Analytics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| |
Collapse
|
24
|
Cañadas-Garre M, Baños-Jaime B, Maqueda JJ, Smyth LJ, Cappa R, Skelly R, Hill C, Brennan EP, Doyle R, Godson C, Maxwell AP, McKnight AJ. Genetic variants affecting mitochondrial function provide further insights for kidney disease. BMC Genomics 2024; 25:576. [PMID: 38858654 PMCID: PMC11163707 DOI: 10.1186/s12864-024-10449-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 05/24/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) is a complex disorder that has become a high prevalence global health problem, with diabetes being its predominant pathophysiologic driver. Autosomal genetic variation only explains some of the predisposition to kidney disease. Variations in the mitochondrial genome (mtDNA) and nuclear-encoded mitochondrial genes (NEMG) are implicated in susceptibility to kidney disease and CKD progression, but they have not been thoroughly explored. Our aim was to investigate the association of variation in both mtDNA and NEMG with CKD (and related traits), with a particular focus on diabetes. METHODS We used the UK Biobank (UKB) and UK-ROI, an independent collection of individuals with type 1 diabetes mellitus (T1DM) patients. RESULTS Fourteen mitochondrial variants were associated with estimated glomerular filtration rate (eGFR) in UKB. Mitochondrial variants and haplogroups U, H and J were associated with eGFR and serum variables. Mitochondrial haplogroup H was associated with all the serum variables regardless of the presence of diabetes. Mitochondrial haplogroup X was associated with end-stage kidney disease (ESKD) in UKB. We confirmed the influence of several known NEMG on kidney disease and function and found novel associations for SLC39A13, CFL1, ACP2 or ATP5G1 with serum variables and kidney damage, and for SLC4A1, NUP210 and MYH14 with ESKD. The G allele of TBC1D32-rs113987180 was associated with higher risk of ESKD in patients with diabetes (OR:9.879; CI95%:4.440-21.980; P = 2.0E-08). In UK-ROI, AGXT2-rs71615838 and SURF1-rs183853102 were associated with diabetic nephropathies, and TFB1M-rs869120 with eGFR. CONCLUSIONS We identified novel variants both in mtDNA and NEMG which may explain some of the missing heritability for CKD and kidney phenotypes. We confirmed the role of MT-ND5 and mitochondrial haplogroup H on renal disease (serum variables), and identified the MT-ND5-rs41535848G variant, along with mitochondrial haplogroup X, associated with higher risk of ESKD. Despite most of the associations were independent of diabetes, we also showed potential roles for NEMG in T1DM.
Collapse
Affiliation(s)
- Marisa Cañadas-Garre
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK.
- Genomic Oncology Area, Centre for Genomics and Oncological Research: Pfizer, GENYO, University of Granada-Andalusian Regional Government, PTS Granada. Avenida de La Ilustración 114, 18016, Granada, Spain.
- Hematology Department, Hospital Universitario Virgen de Las Nieves, Avenida de Las Fuerzas Armadas 2, 18014, Granada, Spain.
- Instituto de Investigación Biosanitaria de Granada (Ibs.GRANADA), Avda. de Madrid, 15, 18012, Granada, Spain.
| | - Blanca Baños-Jaime
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
- Instituto de Investigaciones Químicas (IIQ), Centro de Investigaciones Científicas Isla de La Cartuja (cicCartuja), Consejo Superior de Investigaciones Científicas (CSIC), Universidad de Sevilla, Avda. Américo Vespucio 49, 41092, Seville, Spain
| | - Joaquín J Maqueda
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
- Experimental Oncology Laboratory, IRCCS Rizzoli Orthopaedic Institute, 40136, Bologna, Italy
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, 40126, Bologna, Italy
| | - Laura J Smyth
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Ruaidhri Cappa
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Ryan Skelly
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Claire Hill
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| | - Eoin P Brennan
- UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- School of Medicine, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Ross Doyle
- UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- School of Medicine, University College Dublin, Dublin, D04 V1W8, Ireland
- Mater Misericordiae University Hospital, Eccles St, Dublin, D07 R2WY, Ireland
| | - Catherine Godson
- UCD Diabetes Complications Research Centre, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- School of Medicine, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Alexander P Maxwell
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
- Regional Nephrology Unit, Belfast City Hospital, Level 11Lisburn Road, Belfast, BT9 7AB, UK
| | - Amy Jayne McKnight
- Molecular Epidemiology and Public Health Research Group, Centre for Public Health,, Queen's University Belfast, Institute for Clinical Sciences A, Royal Victoria Hospital, Belfast, BT12 6BA, UK
| |
Collapse
|
25
|
McVey DG, Andreadi C, Gong P, Stanczyk PJ, Solomon CU, Turner L, Yan L, Chen R, Cao J, Nelson CP, Thompson JR, Yu H, Webb TR, Samani NJ, Ye S. Genetic influence on vascular smooth muscle cell apoptosis. Cell Death Dis 2024; 15:402. [PMID: 38851795 PMCID: PMC11162461 DOI: 10.1038/s41419-024-06799-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 05/27/2024] [Accepted: 05/31/2024] [Indexed: 06/10/2024]
Abstract
Vascular smooth muscle cell (VSMC) proliferation, migration, and apoptosis play important roles in many physiological processes and pathological conditions. To identify genetic influences on VSMC behavior, we measured these traits and undertook genome-wide association studies in primary umbilical artery-derived VSMCs from >2000 individuals. Although there were no genome-wide significant associations for VSMC proliferation or migration, genetic variants at two genomic loci (7p15.3 and 7q32.3) showed highly significant associations with VSMC apoptosis (P = 1.95 × 10-13 and P = 7.47 × 10-9, respectively). The lead variant at the 7p51.3 locus was associated with increased expression of the GSDME and PALS2 genes in VSMCs. Knockdown of GSDME or PALS2 in VSMCs attenuated apoptotic cell death. A protein co-immunoprecipitation assay indicated that GSDME complexed with PALS2. PALS2 knockdown attenuated activated caspase-3 and GSDME fragmentation, whilst GSDME knockdown also reduced activated caspase-3. These findings provide new insights into the genetic regulation of VSMC apoptosis, with potential utility for therapeutic development.
Collapse
Affiliation(s)
- David G McVey
- Department of Cardiovascular Sciences and National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Catherine Andreadi
- Department of Cardiovascular Sciences and National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Peng Gong
- Department of Cardiovascular Sciences and National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Paulina J Stanczyk
- Department of Cardiovascular Sciences and National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Charles U Solomon
- Department of Cardiovascular Sciences and National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Lenka Turner
- Department of Cardiovascular Sciences and National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Liu Yan
- Cardiovascular-Metabolic Disease Translational Research Programme, Yong Loo Lin School of Medicine, National University of, Singapore, Singapore
| | - Runji Chen
- Shantou University Medical College, Shantou, China
| | - Junjun Cao
- Shantou University Medical College, Shantou, China
| | - Christopher P Nelson
- Department of Cardiovascular Sciences and National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - John R Thompson
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Haojie Yu
- Cardiovascular-Metabolic Disease Translational Research Programme, Yong Loo Lin School of Medicine, National University of, Singapore, Singapore
| | - Tom R Webb
- Department of Cardiovascular Sciences and National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Nilesh J Samani
- Department of Cardiovascular Sciences and National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Shu Ye
- Department of Cardiovascular Sciences and National Institute for Health Research Leicester Biomedical Research Centre, University of Leicester, Leicester, UK.
- Cardiovascular-Metabolic Disease Translational Research Programme, Yong Loo Lin School of Medicine, National University of, Singapore, Singapore.
- Shantou University Medical College, Shantou, China.
| |
Collapse
|
26
|
Fabbri C, Lewis CM, Serretti A. Polygenic risk scores for mood and related disorders and environmental factors: Interaction effects on wellbeing in the UK biobank. Prog Neuropsychopharmacol Biol Psychiatry 2024; 132:110972. [PMID: 38367896 DOI: 10.1016/j.pnpbp.2024.110972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 12/15/2023] [Accepted: 02/14/2024] [Indexed: 02/19/2024]
Abstract
Mood disorders have a genetic and environmental component and interactions (GxE) on the risk of psychiatric diseases have been investigated. The same GxE interactions may affect wellbeing measures, which go beyond categorical diagnoses and reflect the health-disease continuum. We evaluated GxE effects in the UK Biobank, considering as outcomes subjective wellbeing (feeling good and functioning well) and objective measures (education and income). We estimated the polygenic risk scores (PRSs) of major depressive disorder, bipolar disorder, schizophrenia, and attention deficit hyperactivity disorder. Stressful/traumatic events during adulthood or childhood were considered as E variables, as well as social support. The addition of the PRSxE interaction to PRS and E variables was tested in linear or multinomial regression models, adjusting for confounders. We included 33 k-380 k participants, depending on the variables considered. Most PRSs and E factors showed additive effects on outcomes, with effect sizes generally 3-5 times larger for E variables than PRSs. We found some interaction effects, particularly when considering recent stress, history of a long illness/disability/infirmity, and social support. Higher PRSs increased the negative effects of stress on wellbeing, but they also increased the positive effects of social support, with interaction effects particularly for the outcomes health satisfaction, loneliness, and income (p < Bonferroni corrected threshold of 1.92e-4). PRSxE terms usually added ∼0.01-0.02% variance explained to the corresponding additive model. PRSxE effects on wellbeing involve both positive and negative E factors. Despite small variance explained at the population level, preventive/therapeutic interventions that modify E factors could be beneficial at the individual level.
Collapse
Affiliation(s)
- Chiara Fabbri
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Alessandro Serretti
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy; Department of Medicine and Surgery, Kore University of Enna, Enna, Italy
| |
Collapse
|
27
|
Xiao Q, Mao X, Ploner A, Grassmann F, Rodriguez J, Eriksson M, Hall P, Czene K. Cancer risks among first-degree relatives of women with a genetic predisposition to breast cancer. J Natl Cancer Inst 2024; 116:911-919. [PMID: 38366028 PMCID: PMC11160497 DOI: 10.1093/jnci/djae030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 01/23/2024] [Accepted: 02/05/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Associations between germline alterations in women and cancer risks among their relatives are largely unknown. METHODS We identified women from 2 Swedish cohorts Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) and prevalent KARMA (pKARMA), including 28 362 women with genotyping data and 13 226 with sequencing data. Using Swedish Multi-Generation Register, we linked these women to 133 389 first-degree relatives. Associations between protein-truncating variants in 8 risk genes and breast cancer polygenic risk score in index women and cancer risks among their relatives were modeled via Cox regression. RESULTS Female relatives of index women who were protein-truncating variant carriers in any of the 8 risk genes had an increased breast cancer risk compared with those of noncarriers (hazard ratio [HR] = 1.85, 95% confidence interval [CI] = 1.52 to 2.27), with the strongest association found for protein-truncating variants in BRCA1 and 2. These relatives had a statistically higher risk of early onset than late-onset breast cancer (P = .001). Elevated breast cancer risk was also observed in female relatives of index women with higher polygenic risk score (HR per SD = 1.28, 95% CI = 1.23 to 1.32). The estimated lifetime risk was 22.3% for female relatives of protein-truncating variant carriers and 14.4% for those related to women in the top polygenic risk score quartile. Moreover, relatives of index women with protein-truncating variant presence (HR = 1.30, 95% CI = 1.06 to 1.59) or higher polygenic risk score (HR per SD = 1.04, 95% CI = 1.01 to 1.07) were also at higher risk of nonbreast hereditary breast and ovary cancer syndrome-related cancers. CONCLUSIONS Protein-truncating variants of risk genes and higher polygenic risk score in index women are associated with an increased risk of breast and other hereditary breast and ovary syndrome-related cancers among relatives.
Collapse
Affiliation(s)
- Qingyang Xiao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Xinhe Mao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Alexander Ploner
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Felix Grassmann
- Institute for Clinical Research and Systems Medicine, Health and Medical University, Potsdam, Germany
| | - Juan Rodriguez
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| |
Collapse
|
28
|
She CH, Tsang HW, Yang X, Tsao SS, Tang CS, Chan SH, Kwan MY, Chua GT, Yang W, Ip P. Genome-wide association study of BNT162b2 vaccine-related myocarditis identifies potential predisposing functional areas in Hong Kong adolescents. BMC Genom Data 2024; 25:51. [PMID: 38844841 PMCID: PMC11155081 DOI: 10.1186/s12863-024-01238-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 05/27/2024] [Indexed: 06/09/2024] Open
Abstract
Vaccine-related myocarditis associated with the BNT162b2 vaccine is a rare complication, with a higher risk observed in male adolescents. However, the contribution of genetic factors to this condition remains uncertain. In this study, we conducted a comprehensive genetic association analysis in a cohort of 43 Hong Kong Chinese adolescents who were diagnosed with myocarditis shortly after receiving the BNT162b2 mRNA COVID-19 vaccine. A comparison of whole-genome sequencing data was performed between the confirmed myocarditis cases and a control group of 481 healthy individuals. To narrow down potential genomic regions of interest, we employed a novel clustering approach called ClusterAnalyzer, which prioritised 2,182 genomic regions overlapping with 1,499 genes for further investigation. Our pathway analysis revealed significant enrichment of these genes in functions related to cardiac conduction, ion channel activity, plasma membrane adhesion, and axonogenesis. These findings suggest a potential genetic predisposition in these specific functional areas that may contribute to the observed side effect of the vaccine. Nevertheless, further validation through larger-scale studies is imperative to confirm these findings. Given the increasing prominence of mRNA vaccines as a promising strategy for disease prevention and treatment, understanding the genetic factors associated with vaccine-related myocarditis assumes paramount importance. Our study provides valuable insights that significantly advance our understanding in this regard and serve as a valuable foundation for future research endeavours in this field.
Collapse
Affiliation(s)
- Chun Hing She
- Department of Paediatrics and Adolescent Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Hing Wai Tsang
- Department of Paediatrics and Adolescent Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Xingtian Yang
- Department of Paediatrics and Adolescent Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Sabrina Sl Tsao
- Department of Paediatrics and Adolescent Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Clara Sm Tang
- Department of Surgery, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Sophelia Hs Chan
- Department of Paediatrics and Adolescent Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Mike Yw Kwan
- Department of Paediatrics and Adolescent Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Gilbert T Chua
- Department of Paediatrics and Adolescent Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Wanling Yang
- Department of Paediatrics and Adolescent Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
| | - Patrick Ip
- Department of Paediatrics and Adolescent Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.
| |
Collapse
|
29
|
Yang J, Wang DF, Huang JH, Zhu QH, Luo LY, Lu R, Xie XL, Salehian-Dehkordi H, Esmailizadeh A, Liu GE, Li MH. Structural variant landscapes reveal convergent signatures of evolution in sheep and goats. Genome Biol 2024; 25:148. [PMID: 38845023 PMCID: PMC11155191 DOI: 10.1186/s13059-024-03288-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 05/21/2024] [Indexed: 06/10/2024] Open
Abstract
BACKGROUND Sheep and goats have undergone domestication and improvement to produce similar phenotypes, which have been greatly impacted by structural variants (SVs). Here, we report a high-quality chromosome-level reference genome of Asiatic mouflon, and implement a comprehensive analysis of SVs in 897 genomes of worldwide wild and domestic populations of sheep and goats to reveal genetic signatures underlying convergent evolution. RESULTS We characterize the SV landscapes in terms of genetic diversity, chromosomal distribution and their links with genes, QTLs and transposable elements, and examine their impacts on regulatory elements. We identify several novel SVs and annotate corresponding genes (e.g., BMPR1B, BMPR2, RALYL, COL21A1, and LRP1B) associated with important production traits such as fertility, meat and milk production, and wool/hair fineness. We detect signatures of selection involving the parallel evolution of orthologous SV-associated genes during domestication, local environmental adaptation, and improvement. In particular, we find that fecundity traits experienced convergent selection targeting the gene BMPR1B, with the DEL00067921 deletion explaining ~10.4% of the phenotypic variation observed in goats. CONCLUSIONS Our results provide new insights into the convergent evolution of SVs and serve as a rich resource for the future improvement of sheep, goats, and related livestock.
Collapse
Affiliation(s)
- Ji Yang
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Dong-Feng Wang
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Jia-Hui Huang
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Qiang-Hui Zhu
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Ling-Yun Luo
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Ran Lu
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xing-Long Xie
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Hosein Salehian-Dehkordi
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, 76169-133, Iran
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, MD, 20705, USA
| | - Meng-Hua Li
- State Key Laboratory of Animal Biotech Breeding, China Agricultural University, Beijing, 100193, China.
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
| |
Collapse
|
30
|
Han L, Zeng Y, Huang T, Jia J. Exercise may delay cognitive decline in Chinese older adults: a causal inference for ordered multi-categorical exposures with a Mendelian randomization approach. Sci Rep 2024; 14:13007. [PMID: 38844511 PMCID: PMC11156672 DOI: 10.1038/s41598-024-59326-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Accepted: 04/09/2024] [Indexed: 06/09/2024] Open
Abstract
The cognitive problems are prominent in the context of global aging, and the traditional Mendelian randomization method is not applicable to ordered multi-categorical exposures. Therefore, we aimed to address this issue through the development of a method and to investigate the causal inference of cognitive-related lifestyle factors. The study sample was derived from the Chinese Longitudinal Healthy Longevity Survey, which included 897 older adults aged 65 + . This study used genome-wide association analysis to screen genetic loci as instrumental variables and innovatively combined maximum likelihood estimation to infer causal associations between ordered multi-categorical exposures (diet, exercise, etc.) and continuous outcomes (cognitive level). The causal inference method for ordered multi-categorical exposures developed in this study was simple, easy to implement, and able to effectively and reliably discover the potential causal associations between variables. Through this method, we found a potential positive causal association between exercise status and cognitive level in Chinese older adults ( β ^ = 1.883, 95%CI 0.182-3.512), in which there was no horizontal pleiotropy (p = 0.370). The study provided a causal inference method applicable to ordered multi-categorical exposures, that addressed the limitations of the traditional Mendelian randomization method.
Collapse
Affiliation(s)
- Lizhen Han
- Center for Clinical and Epidemiologic Research, Beijing An Zhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, 100029, China
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, 100191, China
- Center for Study of Aging and Human Development and Geriatrics Division, School of Medicine, Duke University, Durham, NC, USA
| | - Tao Huang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
- Center for Intelligent Public Health, Academy for Artificial Intelligence, Peking University, Beijing, 100871, China.
| | - Jinzhu Jia
- Department of Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing, 100191, China.
- Center for Statistical Science, Peking University, Beijing, 100871, China.
| |
Collapse
|
31
|
Grunin M, Triffon D, Beykin G, Rahmani E, Schweiger R, Tiosano L, Khateb S, Hagbi-Levi S, Rinsky B, Munitz R, Winkler TW, Heid IM, Halperin E, Carmi S, Chowers I. Genome wide association study and genomic risk prediction of age related macular degeneration in Israel. Sci Rep 2024; 14:13034. [PMID: 38844476 PMCID: PMC11156861 DOI: 10.1038/s41598-024-63065-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 05/24/2024] [Indexed: 06/09/2024] Open
Abstract
The risk of developing age-related macular degeneration (AMD) is influenced by genetic background. In 2016, the International AMD Genomics Consortium (IAMDGC) identified 52 risk variants in 34 loci, and a polygenic risk score (PRS) from these variants was associated with AMD. The Israeli population has a unique genetic composition: Ashkenazi Jewish (AJ), Jewish non-Ashkenazi, and Arab sub-populations. We aimed to perform a genome-wide association study (GWAS) for AMD in Israel, and to evaluate PRSs for AMD. Our discovery set recruited 403 AMD patients and 256 controls at Hadassah Medical Center. We genotyped individuals via custom exome chip. We imputed non-typed variants using cosmopolitan and AJ reference panels. We recruited additional 155 cases and 69 controls for validation. To evaluate predictive power of PRSs for AMD, we used IAMDGC summary-statistics excluding our study and developed PRSs via clumping/thresholding or LDpred2. In our discovery set, 31/34 loci reported by IAMDGC were AMD-associated (P < 0.05). Of those, all effects were directionally consistent with IAMDGC and 11 loci had a P-value under Bonferroni-corrected threshold (0.05/34 = 0.0015). At a 5 × 10-5 threshold, we discovered four suggestive associations in FAM189A1, IGDCC4, C7orf50, and CNTNAP4. Only the FAM189A1 variant was AMD-associated in the replication cohort after Bonferroni-correction. A prediction model including LDpred2-based PRS + covariates had an AUC of 0.82 (95% CI 0.79-0.85) and performed better than covariates-only model (P = 5.1 × 10-9). Therefore, previously reported AMD-associated loci were nominally associated with AMD in Israel. A PRS developed based on a large international study is predictive in Israeli populations.
Collapse
Affiliation(s)
- Michelle Grunin
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, POB 12271, 9112102, Jerusalem, Israel
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Daria Triffon
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, POB 12271, 9112102, Jerusalem, Israel
| | - Gala Beykin
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Elior Rahmani
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Regev Schweiger
- Molecular Microbiology and Biotechnology, Tel Aviv University, Tel Aviv, Israel
- Department of Genetics, University of Cambridge, CB21TN, Cambridge, UK
| | - Liran Tiosano
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Samer Khateb
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Shira Hagbi-Levi
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Batya Rinsky
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Refael Munitz
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Eran Halperin
- Molecular Microbiology and Biotechnology, Tel Aviv University, Tel Aviv, Israel
- Department of Anesthesiology, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, POB 12271, 9112102, Jerusalem, Israel.
| | - Itay Chowers
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel.
| |
Collapse
|
32
|
Xu ZM, Gnouamozi GE, Rüeger S, Shea PR, Buti M, Chan HL, Marcellin P, Lawless D, Naret O, Zeller M, Schneuing A, Scheck A, Junier T, Moradpour D, Podlaha O, Suri V, Gaggar A, Subramanian M, Correia B, Gfeller D, Urban S, Fellay J. Joint host-pathogen genomic analysis identifies hepatitis B virus mutations associated with human NTCP and HLA class I variation. Am J Hum Genet 2024; 111:1018-1034. [PMID: 38749427 PMCID: PMC11179264 DOI: 10.1016/j.ajhg.2024.04.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 04/17/2024] [Accepted: 04/18/2024] [Indexed: 06/09/2024] Open
Abstract
Evolutionary changes in the hepatitis B virus (HBV) genome could reflect its adaptation to host-induced selective pressure. Leveraging paired human exome and ultra-deep HBV genome-sequencing data from 567 affected individuals with chronic hepatitis B, we comprehensively searched for the signatures of this evolutionary process by conducting "genome-to-genome" association tests between all human genetic variants and viral mutations. We identified significant associations between an East Asian-specific missense variant in the gene encoding the HBV entry receptor NTCP (rs2296651, NTCP S267F) and mutations within the receptor-binding region of HBV preS1. Through in silico modeling and in vitro preS1-NTCP binding assays, we observed that the associated HBV mutations are in proximity to the NTCP variant when bound and together partially increase binding affinity to NTCP S267F. Furthermore, we identified significant associations between HLA-A variation and viral mutations in HLA-A-restricted T cell epitopes. We used in silico binding prediction tools to evaluate the impact of the associated HBV mutations on HLA presentation and observed that mutations that result in weaker binding affinities to their cognate HLA alleles were enriched. Overall, our results suggest the emergence of HBV escape mutations that might alter the interaction between HBV PreS1 and its cellular receptor NTCP during viral entry into hepatocytes and confirm the role of HLA class I restriction in inducing HBV epitope variations.
Collapse
Affiliation(s)
- Zhi Ming Xu
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Gnimah Eva Gnouamozi
- Department of Infectious Diseases, Molecular Virology, University Hospital Heidelberg, Heidelberg, Germany
| | - Sina Rüeger
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Patrick R Shea
- Institute for Genomic Medicine, Columbia University, New York, NY, USA
| | - Maria Buti
- Liver Unit, Hospital Universitario Vall d'Hebron and CIBEREHD del Instituto Carlos III, Barcelona, Spain
| | - Henry Ly Chan
- The Chinese University of Hong Kong, Hong Kong, China
| | | | - Dylan Lawless
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Olivier Naret
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Matthias Zeller
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Arne Schneuing
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Andreas Scheck
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Thomas Junier
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Darius Moradpour
- Division of Gastroenterology and Hepatology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | | | | | | | - Bruno Correia
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - David Gfeller
- Department of Oncology UNIL-CHUV, Lausanne University Hospital, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Stephan Urban
- Department of Infectious Diseases, Molecular Virology, University Hospital Heidelberg, Heidelberg, Germany; German Center for Infection Research (DZIF), Partner Site Heidelberg, Heidelberg, Germany
| | - Jacques Fellay
- School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; Precision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
| |
Collapse
|
33
|
Reeve MP, Vehviläinen M, Luo S, Ritari J, Karjalainen J, Gracia-Tabuenca J, Mehtonen J, Padmanabhuni SS, Kolosov N, Artomov M, Siirtola H, Olilla HM, Graham D, Partanen J, Xavier RJ, Daly MJ, Ripatti S, Salo T, Siponen M. Oral and non-oral lichen planus show genetic heterogeneity and differential risk for autoimmune disease and oral cancer. Am J Hum Genet 2024; 111:1047-1060. [PMID: 38776927 PMCID: PMC11179409 DOI: 10.1016/j.ajhg.2024.04.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 04/23/2024] [Accepted: 04/25/2024] [Indexed: 05/25/2024] Open
Abstract
Lichen planus (LP) is a T-cell-mediated inflammatory disease affecting squamous epithelia in many parts of the body, most often the skin and oral mucosa. Cutaneous LP is usually transient and oral LP (OLP) is most often chronic, so we performed a large-scale genetic and epidemiological study of LP to address whether the oral and non-oral subgroups have shared or distinct underlying pathologies and their overlap with autoimmune disease. Using lifelong records covering diagnoses, procedures, and clinic identity from 473,580 individuals in the FinnGen study, genome-wide association analyses were conducted on carefully constructed subcategories of OLP (n = 3,323) and non-oral LP (n = 4,356) and on the combined group. We identified 15 genome-wide significant associations in FinnGen and an additional 12 when meta-analyzed with UKBB (27 independent associations at 25 distinct genomic locations), most of which are shared between oral and non-oral LP. Many associations coincide with known autoimmune disease loci, consistent with the epidemiologic enrichment of LP with hypothyroidism and other autoimmune diseases. Notably, a third of the FinnGen associations demonstrate significant differences between OLP and non-OLP. We also observed a 13.6-fold risk for tongue cancer and an elevated risk for other oral cancers in OLP, in agreement with earlier reports that connect LP with higher cancer incidence. In addition to a large-scale dissection of LP genetics and comorbidities, our study demonstrates the use of comprehensive, multidimensional health registry data to address outstanding clinical questions and reveal underlying biological mechanisms in common but understudied diseases.
Collapse
Affiliation(s)
- Mary Pat Reeve
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Mari Vehviläinen
- Department of Oral and Maxillofacial Diseases, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Shuang Luo
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Jarmo Ritari
- Finnish Red Cross Blood Service, Helsinki, Finland
| | - Juha Karjalainen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Javier Gracia-Tabuenca
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Juha Mehtonen
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Shanmukha Sampath Padmanabhuni
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Nikita Kolosov
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA; Ohio State University College of Medicine, Columbus, OH, USA
| | - Mykyta Artomov
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA; Ohio State University College of Medicine, Columbus, OH, USA
| | - Harri Siirtola
- TAUCHI Research Center, Tampere University, Tampere, Finland
| | - Hanna M Olilla
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Daniel Graham
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Ramnik J Xavier
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Mark J Daly
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Analytical and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Tuula Salo
- Research Unit of Population Health, Department of Oral Pathology, University of Oulu and Oulu University Hospital, Oulu, Finland; Medical Research Center, Oulu University Hospital, Oulu, Finland; Department of Oral and Maxillofacial Diseases, and Translational Immunology Program (TRIMM), University of Helsinki, Helsinki, Finland
| | - Maria Siponen
- Institute of Dentistry, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland; Odontology Education Unit, and Oral and Maxillofacial Diseases Clinic, Kuopio University Hospital, Kuopio, Finland
| |
Collapse
|
34
|
Fiscus CJ, Herniter IA, Tchamba M, Paliwal R, Muñoz-Amatriaín M, Roberts PA, Abberton M, Alaba O, Close TJ, Oyatomi O, Koenig D. The pattern of genetic variability in a core collection of 2,021 cowpea accessions. G3 (BETHESDA, MD.) 2024; 14:jkae071. [PMID: 38708794 DOI: 10.1093/g3journal/jkae071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 03/18/2024] [Indexed: 05/07/2024]
Abstract
Cowpea is a highly drought-adapted leguminous crop with great promise for improving agricultural sustainability and food security. Here, we report analyses derived from array-based genotyping of 2,021 accessions constituting a core subset of the world's largest cowpea collection, held at the International Institute of Tropical Agriculture (IITA) in Ibadan, Nigeria. We used this dataset to examine genetic variation and population structure in worldwide cowpea. We confirm that the primary pattern of population structure is two geographically defined subpopulations originating in West and East Africa, respectively, and that population structure is associated with shifts in phenotypic distribution. Furthermore, we establish the cowpea core collection as a resource for genome-wide association studies by mapping the genetic basis of several phenotypes, with a focus on seed coat pigmentation patterning and color. We anticipate that the genotyped IITA Cowpea Core Collection will serve as a powerful tool for mapping complex traits, facilitating the acceleration of breeding programs to enhance the resilience of this crop in the face of rapid global climate change.
Collapse
Affiliation(s)
- Christopher J Fiscus
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
| | - Ira A Herniter
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
| | - Marimagne Tchamba
- International Institute of Tropical Agriculture (IITA), Ibadan 200001, Nigeria
| | - Rajneesh Paliwal
- International Institute of Tropical Agriculture (IITA), Ibadan 200001, Nigeria
| | | | - Philip A Roberts
- Department of Nematology, University of California, Riverside, Riverside, CA 92521, USA
| | - Michael Abberton
- International Institute of Tropical Agriculture (IITA), Ibadan 200001, Nigeria
| | - Oluwafemi Alaba
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
| | - Timothy J Close
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
- Institute for Integrative Genome Biology, University of California, Riverside, Riverside, CA 92521, USA
| | - Olaniyi Oyatomi
- International Institute of Tropical Agriculture (IITA), Ibadan 200001, Nigeria
| | - Daniel Koenig
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA
- Institute for Integrative Genome Biology, University of California, Riverside, Riverside, CA 92521, USA
| |
Collapse
|
35
|
Murgiano L, Banjeree E, O'Connor C, Miyadera K, Werner P, Niggel JK, Aguirre GD, Casal ML. A naturally occurring canine model of syndromic congenital microphthalmia. G3 (BETHESDA, MD.) 2024; 14:jkae067. [PMID: 38682429 DOI: 10.1093/g3journal/jkae067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 03/13/2024] [Indexed: 05/01/2024]
Abstract
In humans, the prevalence of congenital microphthalmia is estimated to be 0.2-3.0 for every 10,000 individuals, with nonocular involvement reported in ∼80% of cases. Inherited eye diseases have been widely and descriptively characterized in dogs, and canine models of ocular diseases have played an essential role in unraveling the pathophysiology and development of new therapies. A naturally occurring canine model of a syndromic disorder characterized by microphthalmia was discovered in the Portuguese water dog. As nonocular findings included tooth enamel malformations, stunted growth, anemia, and thrombocytopenia, we hence termed this disorder Canine Congenital Microphthalmos with Hematopoietic Defects. Genome-wide association study and homozygosity mapping detected a 2 Mb candidate region on canine chromosome 4. Whole-genome sequencing and mapping against the Canfam4 reference revealed a Short interspersed element insertion in exon 2 of the DNAJC1 gene (g.74,274,883ins[T70]TGCTGCTTGGATT). Subsequent real-time PCR-based mass genotyping of a larger Portuguese water dog population found that the homozygous mutant genotype was perfectly associated with the Canine Congenital Microphthalmos with Hematopoietic Defects phenotype. Biallelic variants in DNAJC21 are mostly found to be associated with bone marrow failure syndrome type 3, with a phenotype that has a certain degree of overlap with Fanconi anemia, dyskeratosis congenita, Shwachman-Diamond syndrome, Diamond-Blackfan anemia, and reports of individuals showing thrombocytopenia, microdontia, and microphthalmia. We, therefore, propose Canine Congenital Microphthalmos with Hematopoietic Defects as a naturally occurring model for DNAJC21-associated syndromes.
Collapse
Affiliation(s)
- Leonardo Murgiano
- Department of Clinical Sciences & Advanced Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Sylvia M. Van Sloun Laboratory for Canine Genomic Analysis, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Esha Banjeree
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Cynthia O'Connor
- Section of Medical Genetics, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- East Bridgewater Veterinary Hospitla, East Bridgewater, MA 02333, USA
| | - Keiko Miyadera
- Department of Clinical Sciences & Advanced Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Petra Werner
- Section of Medical Genetics, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Genetic Diagnostic Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jessica K Niggel
- Department of Clinical Sciences & Advanced Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Sylvia M. Van Sloun Laboratory for Canine Genomic Analysis, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Gustavo D Aguirre
- Department of Clinical Sciences & Advanced Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Sylvia M. Van Sloun Laboratory for Canine Genomic Analysis, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Margret L Casal
- Department of Clinical Sciences & Advanced Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Section of Medical Genetics, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| |
Collapse
|
36
|
Cruchaga C, Bradley J, Western D, Wang C, Fonseca ELD, Neupane A, Kurup J, Ray NI, Jean-Francois M, Gorijala P, Bergmann K, Budde J, Martin E, Pericak-Vance M, Cuccaro M, Kunkle B, Morris J, Holtzman D, Perrin R, Naj A, Haines J, Schellenberg G, Fernandez V, Reitz C, Beecham G, Consortium ADG, Adrc CFAJKADRC. Novel early-onset Alzheimer-associated genes influence risk through dysregulation of glutamate, immune activation, and intracell signaling pathways. RESEARCH SQUARE 2024:rs.3.rs-4480585. [PMID: 38883718 PMCID: PMC11177996 DOI: 10.21203/rs.3.rs-4480585/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Alzheimer Disease (AD) is a highly polygenic disease that presents with relatively earlier onset (≤70yo; EOAD) in about 5% of cases. Around 90% of these EOAD cases remain unexplained by pathogenic mutations. Using data from EOAD cases and controls, we performed a genome-wide association study (GWAS) and trans-ancestry meta-analysis on non-Hispanic Whites (NHW, NCase=6,282, NControl=13,386), African Americans (AA NCase=782, NControl=3,663) and East Asians (NCase=375, NControl=838 CO). We identified eight novel significant loci: six in the ancestry-specific analyses and two in the trans-ancestry analysis. By integrating gene-based analysis, eQTL, pQTL and functional annotations, we nominate four novel genes that are involved in microglia activation, glutamate production, and signaling pathways. These results indicate that EOAD, although sharing many genes with LOAD, harbors unique genes and pathways that could be used to create better prediction models or target identification for this type of AD.
Collapse
|
37
|
Larsson MNA, Morell Miranda P, Pan L, Başak Vural K, Kaptan D, Rodrigues Soares AE, Kivikero H, Kantanen J, Somel M, Özer F, Johansson AM, Storå J, Günther T. Ancient Sheep Genomes Reveal Four Millennia of North European Short-Tailed Sheep in the Baltic Sea Region. Genome Biol Evol 2024; 16:evae114. [PMID: 38795367 PMCID: PMC11162877 DOI: 10.1093/gbe/evae114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 04/24/2024] [Accepted: 05/21/2024] [Indexed: 05/27/2024] Open
Abstract
Sheep are among the earliest domesticated livestock species, with a wide variety of breeds present today. However, it remains unclear how far back this diversity goes, with formal documentation only dating back a few centuries. North European short-tailed (NEST) breeds are often assumed to be among the oldest domestic sheep populations, even thought to represent relicts of the earliest sheep expansions during the Neolithic period reaching Scandinavia <6,000 years ago. This study sequenced the genomes (up to 11.6X) of five sheep remains from the Baltic islands of Gotland and Åland, dating from the Late Neolithic (∼4,100 cal BP) to historical times (∼1,600 CE). Our findings indicate that these ancient sheep largely possessed the genetic characteristics of modern NEST breeds, suggesting a substantial degree of long-term continuity of this sheep type in the Baltic Sea region. Despite the wide temporal spread, population genetic analyses show high levels of affinity between the ancient genomes and they also exhibit relatively high genetic diversity when compared to modern NEST breeds, implying a loss of diversity in most breeds during the last centuries associated with breed formation and recent bottlenecks. Our results shed light on the development of breeds in Northern Europe specifically as well as the development of genetic diversity in sheep breeds, and their expansion from the domestication center in general.
Collapse
Affiliation(s)
- Martin N A Larsson
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Pedro Morell Miranda
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Li Pan
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Kıvılcım Başak Vural
- Department of Biological Sciences, Middle East Technical University, Ankara, Turkey
| | - Damla Kaptan
- Department of Biological Sciences, Middle East Technical University, Ankara, Turkey
| | | | - Hanna Kivikero
- Department of Culture, University of Helsinki, Helsinki, Finland
| | - Juha Kantanen
- Natural Resources Institute Finland, Jokioinen, Finland
| | - Mehmet Somel
- Department of Biological Sciences, Middle East Technical University, Ankara, Turkey
| | - Füsun Özer
- Department of Anthropology, Hacettepe University, Ankara, Turkey
| | - Anna M Johansson
- Department of Animal Biosciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Jan Storå
- Osteoarchaeological Research Laboratory, Stockholm University, Stockholm, Sweden
| | - Torsten Günther
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| |
Collapse
|
38
|
Skytte Af Sätra J, Garkava-Gustavsson L, Ingvarsson PK. Why we thrive beneath a northern sky - genomic signals of selection in apple for adaptation to northern Sweden. Heredity (Edinb) 2024:10.1038/s41437-024-00693-2. [PMID: 38834867 DOI: 10.1038/s41437-024-00693-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 05/16/2024] [Accepted: 05/16/2024] [Indexed: 06/06/2024] Open
Abstract
Good understanding of the genomic regions underlying adaptation of apple to boreal climates is needed to facilitate efficient breeding of locally adapted apple cultivars. Proper infrastructure for phenotyping and evaluation is essential for identification of traits responsible for adaptation, and dissection of their genetic composition. However, such infrastructure is costly and currently not available for the boreal zone of northern Sweden. Therefore, we used historical pomological data on climate adaptation of 59 apple cultivars and whole genome sequencing to identify genomic regions that have undergone historical selection among apple cultivars recommended for cultivation in northern Sweden. We found the apple collection to be composed of two ancestral groups that are largely concordant with the grouping into 'hardy' and 'not hardy' cultivars based on the pomological literature. Using a number of genome-wide scans for signals of selection, we obtained strong evidence of positive selection at a genomic region around 29 MbHFTH1 of chromosome 1 among apple cultivars in the 'hardy' group. Using phased genotypic data from the 20 K apple Infinium® SNP array, we identified haplotypes associated with the two cultivar groups and traced transmission of these haplotypes through the pedigrees of some apple cultivars. This demonstrates that historical data from pomological literature can be analyzed by population genomic approaches as a step towards revealing the genomic control of a key property for a horticultural niche market. Such knowledge is needed to facilitate efficient breeding strategies for development of locally adapted apple cultivars in the future. The current study illustrates the response to a very strong selective pressure imposed on tree crops by climatic factors, and the importance of genetic research on this topic and feasibility of breeding efforts in the light of the ongoing climate change.
Collapse
Affiliation(s)
- J Skytte Af Sätra
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden.
| | - L Garkava-Gustavsson
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - P K Ingvarsson
- Department of Plant Biology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| |
Collapse
|
39
|
Samarasinghe SR, Lee SB, Corpas M, Fatumo S, Guchelaar HJ, Nagaraj SH. Mapping the Pharmacogenetic Landscape in a Ugandan Population: Implications for Personalized Medicine in an Underrepresented Population. Clin Pharmacol Ther 2024. [PMID: 38837390 DOI: 10.1002/cpt.3309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/27/2024] [Indexed: 06/07/2024]
Abstract
Africans are extremely underrepresented in global genomic research. African populations face high burdens of communicable and non-communicable diseases and experience widespread polypharmacy. As population-specific genetic studies are crucial to understanding unique genetic profiles and optimizing treatments to reduce medication-related complications in this diverse population, the present study aims to characterize the pharmacogenomics profile of a rural Ugandan population. We analyzed low-pass whole genome sequencing data from 1998 Ugandans to investigate 18 clinically actionable pharmacogenes in this population. We utilized PyPGx to identify star alleles (haplotype patterns) and compared allele frequencies across populations using the Pharmacogenomics Knowledgebase PharmGKB. Clinical interpretations of the identified alleles were conducted following established dosing guidelines. Over 99% of participants displayed actionable phenotypes across the 18 pharmacogenes, averaging 3.5 actionable genotypes per individual. Several variant alleles known to affect drug metabolism (i.e., CYP3A5*1, CYP2B6*9, CYP3A5*6, CYP2D6*17, CYP2D6*29, and TMPT*3C)-which are generally more prevalent in African individuals-were notably enriched in the Ugandan cohort, beyond reported frequencies in other African peoples. More than half of the cohort exhibited a predicted impaired drug response associated with CFTR, IFNL3, CYP2B6, and CYP2C19, and approximately 31% predicted altered CYP2D6 metabolism. Potentially impaired CYP2C9, SLCO1B1, TPMT, and DPYD metabolic phenotypes were also enriched in Ugandans compared with other African populations. Ugandans exhibit distinct allele profiles that could impact drug efficacy and safety. Our findings have important implications for pharmacogenomics in Uganda, particularly with respect to the treatment of prevalent communicable and non-communicable diseases, and they emphasize the potential of pharmacogenomics-guided therapies to optimize healthcare outcomes and precision medicine in Uganda.
Collapse
Affiliation(s)
- Sumudu Rangika Samarasinghe
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Queensland, Australia
| | | | - Manuel Corpas
- College of Liberal Arts and Sciences, University of Westminster, London, UK
| | - Segun Fatumo
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Shivashankar H Nagaraj
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Queensland, Australia
- Translational Research Institute, Queensland University of Technology, Brisbane, Queensland, Australia
| |
Collapse
|
40
|
Johnson MB, Ogishi M, Domingo-Vila C, De Franco E, Wakeling MN, Imane Z, Resnick B, Williams E, Galão RP, Caswell R, Russ-Silsby J, Seeleuthner Y, Rinchai D, Fagniez I, Benson B, Dufort MJ, Speake C, Smithmyer ME, Hudson M, Dobbs R, Quandt Z, Hattersley AT, Zhang P, Boisson-Dupuis S, Anderson MS, Casanova JL, Tree TI, Oram RA. Human inherited PD-L1 deficiency is clinically and immunologically less severe than PD-1 deficiency. J Exp Med 2024; 221:e20231704. [PMID: 38634869 PMCID: PMC11032109 DOI: 10.1084/jem.20231704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 01/16/2024] [Accepted: 03/13/2024] [Indexed: 04/19/2024] Open
Abstract
We previously reported two siblings with inherited PD-1 deficiency who died from autoimmune pneumonitis at 3 and 11 years of age after developing other autoimmune manifestations, including type 1 diabetes (T1D). We report here two siblings, aged 10 and 11 years, with neonatal-onset T1D (diagnosed at the ages of 1 day and 7 wk), who are homozygous for a splice-site variant of CD274 (encoding PD-L1). This variant results in the exclusive expression of an alternative, loss-of-function PD-L1 protein isoform in overexpression experiments and in the patients' primary leukocytes. Surprisingly, cytometric immunophenotyping and single-cell RNA sequencing analysis on blood leukocytes showed largely normal development and transcriptional profiles across lymphoid and myeloid subsets in the PD-L1-deficient siblings, contrasting with the extensive dysregulation of both lymphoid and myeloid leukocyte compartments in PD-1 deficiency. Our findings suggest that PD-1 and PD-L1 are essential for preventing early-onset T1D but that, unlike PD-1 deficiency, PD-L1 deficiency does not lead to fatal autoimmunity with extensive leukocytic dysregulation.
Collapse
Affiliation(s)
- Matthew B. Johnson
- Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Masato Ogishi
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Clara Domingo-Vila
- Department of Immunobiology, School of Immunology and Microbial Sciences, Kings College London, London, UK
| | - Elisa De Franco
- Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Matthew N. Wakeling
- Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Zineb Imane
- Faculty of Medicine and Pharmacy, Mohammed 5 University of Rabat, Rabat, Morocco
| | - Brittany Resnick
- National Institute for Health and Care Research Exeter Clinical Research Facility, Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Evangelia Williams
- Department of Immunobiology, School of Immunology and Microbial Sciences, Kings College London, London, UK
| | - Rui Pedro Galão
- Department of Infectious Diseases, School of Immunobiology and Microbial Sciences, Kings College London, London, UK
| | - Richard Caswell
- Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - James Russ-Silsby
- Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Yoann Seeleuthner
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France
- Imagine Institute, Paris Cité University, Paris, France
| | - Darawan Rinchai
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Iris Fagniez
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Basilin Benson
- Center for Systems Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - Matthew J. Dufort
- Center for Systems Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - Cate Speake
- Center for Interventional Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - Megan E. Smithmyer
- Center for Interventional Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - Michelle Hudson
- Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
- National Institute for Health and Care Research Exeter Clinical Research Facility, Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Rebecca Dobbs
- Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
- National Institute for Health and Care Research Exeter Clinical Research Facility, Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Zoe Quandt
- Endocrine Division, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- Diabetes Center, University of California San Francisco, San Francisco, CA, USA
| | - Andrew T. Hattersley
- Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Peng Zhang
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
| | - Stephanie Boisson-Dupuis
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France
- Imagine Institute, Paris Cité University, Paris, France
| | - Mark S. Anderson
- Endocrine Division, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- Diabetes Center, University of California San Francisco, San Francisco, CA, USA
| | - Jean-Laurent Casanova
- St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY, USA
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, INSERM U1163, Paris, France
- Imagine Institute, Paris Cité University, Paris, France
- Department of Pediatrics, Necker Hospital for Sick Children, Paris, France
- Howard Hughes Medical Institute, New York, NY, USA
| | - Timothy I. Tree
- Department of Immunobiology, School of Immunology and Microbial Sciences, Kings College London, London, UK
| | - Richard A. Oram
- Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| |
Collapse
|
41
|
Smelik M, Zhao Y, Li X, Loscalzo J, Sysoev O, Mahmud F, Mansour Aly D, Benson M. An interactive atlas of genomic, proteomic, and metabolomic biomarkers promotes the potential of proteins to predict complex diseases. Sci Rep 2024; 14:12710. [PMID: 38830935 PMCID: PMC11148091 DOI: 10.1038/s41598-024-63399-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 05/28/2024] [Indexed: 06/05/2024] Open
Abstract
Multiomics analyses have identified multiple potential biomarkers of the incidence and prevalence of complex diseases. However, it is not known which type of biomarker is optimal for clinical purposes. Here, we make a systematic comparison of 90 million genetic variants, 1453 proteins, and 325 metabolites from 500,000 individuals with complex diseases from the UK Biobank. A machine learning pipeline consisting of data cleaning, data imputation, feature selection, and model training using cross-validation and comparison of the results on holdout test sets showed that proteins were most predictive, followed by metabolites, and genetic variants. Only five proteins per disease resulted in median (min-max) areas under the receiver operating characteristic curves for incidence of 0.79 (0.65-0.86) and 0.84 (0.70-0.91) for prevalence. In summary, our work suggests the potential of predicting complex diseases based on a limited number of proteins. We provide an interactive atlas (macd.shinyapps.io/ShinyApp/) to find genomic, proteomic, or metabolomic biomarkers for different complex diseases.
Collapse
Affiliation(s)
- Martin Smelik
- Medical Digital Twin Research Group, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institute, Stockholm, Sweden
| | - Yelin Zhao
- Medical Digital Twin Research Group, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institute, Stockholm, Sweden
| | - Xinxiu Li
- Medical Digital Twin Research Group, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institute, Stockholm, Sweden
| | - Joseph Loscalzo
- Division of Cardiovascular Medicine, Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Oleg Sysoev
- Division of Statistics and Machine Learning, Department of Computer and Information Science, Linköping University, Linköping, Sweden
| | - Firoj Mahmud
- Medical Digital Twin Research Group, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institute, Stockholm, Sweden
| | - Dina Mansour Aly
- Medical Digital Twin Research Group, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institute, Stockholm, Sweden
| | - Mikael Benson
- Medical Digital Twin Research Group, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institute, Stockholm, Sweden.
| |
Collapse
|
42
|
Krug A, Stein F, David FS, Schmitt S, Brosch K, Pfarr JK, Ringwald KG, Meller T, Thomas-Odenthal F, Meinert S, Thiel K, Winter A, Waltemate L, Lemke H, Grotegerd D, Opel N, Repple J, Hahn T, Streit F, Witt SH, Rietschel M, Andlauer TFM, Nöthen MM, Philipsen A, Nenadić I, Dannlowski U, Kircher T, Forstner AJ. Factor analysis of lifetime psychopathology and its brain morphometric and genetic correlates in a transdiagnostic sample. Transl Psychiatry 2024; 14:235. [PMID: 38830892 PMCID: PMC11148082 DOI: 10.1038/s41398-024-02936-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 05/16/2024] [Accepted: 05/16/2024] [Indexed: 06/05/2024] Open
Abstract
There is a lack of knowledge regarding the relationship between proneness to dimensional psychopathological syndromes and the underlying pathogenesis across major psychiatric disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizoaffective Disorder (SZA), and Schizophrenia (SZ). Lifetime psychopathology was assessed using the OPerational CRITeria (OPCRIT) system in 1,038 patients meeting DSM-IV-TR criteria for MDD, BD, SZ, or SZA. The cohort was split into two samples for exploratory and confirmatory factor analyses. All patients were scanned with 3-T MRI, and data was analyzed with the CAT-12 toolbox in SPM12. Psychopathological factor scores were correlated with gray matter volume (GMV) and cortical thickness (CT). Finally, factor scores were used for exploratory genetic analyses including genome-wide association studies (GWAS) and polygenic risk score (PRS) association analyses. Three factors (paranoid-hallucinatory syndrome, PHS; mania, MA; depression, DEP) were identified and cross-validated. PHS was negatively correlated with four GMV clusters comprising parts of the hippocampus, amygdala, angular, middle occipital, and middle frontal gyri. PHS was also negatively associated with the bilateral superior temporal, left parietal operculum, and right angular gyrus CT. No significant brain correlates were observed for the two other psychopathological factors. We identified genome-wide significant associations for MA and DEP. PRS for MDD and SZ showed a positive effect on PHS, while PRS for BD showed a positive effect on all three factors. This study investigated the relationship of lifetime psychopathological factors and brain morphometric and genetic markers. Results highlight the need for dimensional approaches, overcoming the limitations of the current psychiatric nosology.
Collapse
Affiliation(s)
- Axel Krug
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany.
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany.
| | - Friederike S David
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Simon Schmitt
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Kai G Ringwald
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lena Waltemate
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- German Centre for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Jena, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Frankfurt, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Hector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159, Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159, Mannheim, Germany
| | - Till F M Andlauer
- Department of Neurology, Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Alexandra Philipsen
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- Centre for Human Genetics, University of Marburg, Marburg, Germany
| |
Collapse
|
43
|
Nguyen KT, Xu H, Gaynor B, Adebamowo SN, McArdle PF, O'Connor T, Worrall B, Malik R, Boncoraglio GB, Zand R, Kittner SJ, Mitchell BD. The Impact of Conventional Stroke Risk Factors on Early and Late Onset Ischemic Stroke: a Mendelian Randomization Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.31.24308308. [PMID: 38853993 PMCID: PMC11160856 DOI: 10.1101/2024.05.31.24308308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Objective Although stroke incidence is decreasing in older ages, it is increasing in young adults. While these divergent trends in stroke incidence are at least partially attributable to diverging prevalence trends in stoke risk factors, age-dependent differences in the impact of stroke risk factors on stroke may also contribute. To address this issue, we utilized Mendelian Randomization (MR) to assess differences in the association of stroke risk factors between early onset ischemic stroke (EOS) and late onset ischemic stroke (LOS). Methods We employed a two-sample MR design with inverse variance weighting as the primary method of analysis. Using large publicly available genome-wide association summary results, we calculated MR estimates for conventional stroke risk factors (body mass index, total, HDL-and LDL-cholesterol, triglycerides, type 2 diabetes, systolic and diastolic blood pressure, and smoking) in EOS cases (onset 18-59 years, n = 6,728) and controls from the Early Onset Stroke Consortium and in LOS cases (onset ≥ 60 years, n = 9,272) and controls from the Stroke Genetics Network. We then compared odds ratios between EOS and LOS, stratified by TOAST subtypes, to determine if any differences observed between effect sizes could be attributed to differences in the distribution of stroke subtypes. Results EOS was significantly associated with all risk factors except for total cholesterol levels, and LOS was associated with all risk factors except for triglyceride and total cholesterol levels. The associations of BMI, DBP, SBP, and HDL-cholesterol were significantly stronger in EOS than LOS (all p < 0.004). The differential distribution of stroke subtypes could not explain the difference in effect size observed between EOS and LOS. Conclusion These results suggest that interventions targeted at lowering body mass index and blood pressure may be particularly important for reducing stroke risk in young adults.
Collapse
|
44
|
Asiimwe IG, Walker L, Sofat R, Jorgensen AL, Pirmohamed M. Genetic Determinants of Thiazide-Induced Hyperuricemia, Hyperglycemia, and Urinary Electrolyte Disturbances - A Genome-Wide Evaluation of the UK Biobank. Clin Pharmacol Ther 2024; 115:1408-1417. [PMID: 38425181 DOI: 10.1002/cpt.3229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 02/12/2024] [Indexed: 03/02/2024]
Abstract
Thiazide diuretics, widely used in hypertension, cause a variety of adverse reactions, including hyperglycemia, hyperuricemia, and electrolyte abnormalities. In this study, we aimed to identify genetic variants that interact with thiazide-use to increase the risk of these adverse reactions. Using UK Biobank data, we first performed genomewide variance quantitative trait locus (vQTL) analysis of ~ 6.2 million SNPs on 95,493 unrelated hypertensive White British participants (24,313 on self-reported bendroflumethiazide treatment at recruitment) for 2 blood (glucose and urate) and 2 urine (potassium and sodium) biomarkers. Second, we conducted direct gene-environment interaction (GEI) tests on the significant (P < 2.5 × 10-9) vQTLs, included a second UK Biobank cohort comprising 13,647 unrelated hypertensive White British participants (3,478 on thiazides other than bendroflumethiazide) and set significance at P = 0.05 divided by the number of vQTL SNPs tested for GEIs. The vQTL analysis identified eight statistically significant SNPs for blood glucose (5 SNPs) and serum urate (3 SNPs), with none being identified for the urinary biomarkers. Two of the SNPs (1 glucose SNP: CDKAL1 intron rs35612982, GEI P = 6.24 × 10-3; and 1 serum urate SNP: SLC2A9 intron rs938564, GEI P = 4.51 × 10-4) demonstrated significant GEI effects in the first, but not the second, cohort. Both genes are biologically plausible candidates, with the SLC2A9-mediated interaction having been previously reported. In conclusion, we used a two-stage approach to detect two biologically plausible genetic loci that can interact with thiazides to increase the risk of thiazide-associated biochemical abnormalities. Understanding how environmental exposures (including medications such as thiazides) and genetics interact, is an important step toward precision medicine and improved patient outcomes.
Collapse
Affiliation(s)
- Innocent G Asiimwe
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Lauren Walker
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Reecha Sofat
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Andrea L Jorgensen
- Department of Health Data Science, Institute of Population Health Sciences, University of Liverpool, Liverpool, UK
| | - Munir Pirmohamed
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| |
Collapse
|
45
|
Zhang X, Yang F, Zhu T, Zhao X, Zhang J, Wen J, Zhang Y, Wang G, Ren X, Chen A, Wang X, Wang L, Lv X, Yang W, Qu C, Wang H, Ning Z, Qu L. Whole genome resequencing reveals genomic regions related to red plumage in ducks. Poult Sci 2024; 103:103694. [PMID: 38663207 PMCID: PMC11068611 DOI: 10.1016/j.psj.2024.103694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 03/15/2024] [Accepted: 03/25/2024] [Indexed: 05/07/2024] Open
Abstract
Plumage color is a characteristic trait of ducks that originates as a result of natural and artificial selection. As a conspicuous phenotypic feature, it is a breed characteristic. Previous studies have identified some genes associated with the formation of black and white plumage in ducks. However, studies on the genetic basis underlying the red plumage phenotype in ducks are limited. Here, genome-wide association analysis (GWAS) and selection signal detection (Fst, θπ ratio, and cross-population composite likelihood ratio [XP-CLR]) were conducted to identify candidate regions and genes underlying duck plumage color phenotype. Selection signal detection revealed 29 overlapping genes (including ENPP1 and ULK1) significantly associated with red plumage color in Ji'an Red ducks. ENSAPLG00000012679, ESRRG, and SPATA5 were identified as candidate genes associated with red plumage using GWAS. Selection signal detection revealed that 19 overlapping genes (including GMDS, PDIA6, and ODC1) significantly correlated with light brown plumage in Brown Tsaiya ducks. GWAS to narrow down the significant regions further revealed nine candidate genes (AKT1, ATP6V1C2, GMDS, LRP4, MAML3, PDIA6, PLD5, TMEM63B, and TSPAN8). Notably, in Brown Tsaiya ducks, GMDS, ODC1, and PDIA6 exhibit significantly differentiated allele frequencies among other feather-colored ducks, while in Ji'an Red ducks, ENSAPLG00000012679 has different allele frequency distributions compared with that in other feather-colored ducks. This study offers new insights into the variation and selection of the red plumage phenotype using GWAS and selective signals.
Collapse
Affiliation(s)
- Xinye Zhang
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Fangxi Yang
- Beijing Nankou Duck Breeding Technology Co., Ltd., Beijing, China
| | - Tao Zhu
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiurong Zhao
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Jinxin Zhang
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Junhui Wen
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Yalan Zhang
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Gang Wang
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xufang Ren
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Anqi Chen
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xue Wang
- VVBK Animal Medical Diagnostic Technology (Beijing) Co., Ltd, Daxing District, Beijing, China
| | - Liang Wang
- Beijing Municipal General Station of Animal Science, Beijing, China
| | - Xueze Lv
- Beijing Municipal General Station of Animal Science, Beijing, China
| | - Weifang Yang
- Beijing Municipal General Station of Animal Science, Beijing, China
| | - Changqing Qu
- Engineering Technology Research Center of Anti-aging Chinese Herbal Medicine of Anhui Province, Fuyang Normal University, Fuyang, China
| | - Huie Wang
- College of Animal Science, Tarim University, Xinjiang, China
| | - Zhonghua Ning
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Lujiang Qu
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.
| |
Collapse
|
46
|
Powell NR, Shugg T, Leighty J, Martin M, Kreutz RP, Eadon MT, Lai D, Lu T, Skaar TC. Analysis of the combined effect of rs699 and rs5051 on angiotensinogen expression and hypertension. Chronic Dis Transl Med 2024; 10:102-117. [PMID: 38872760 PMCID: PMC11166681 DOI: 10.1002/cdt3.103] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 10/23/2023] [Accepted: 11/06/2023] [Indexed: 06/15/2024] Open
Abstract
Background Hypertension (HTN) involves genetic variability in the renin-angiotensin system and influences antihypertensive response. We previously reported that angiotensinogen (AGT) messenger RNA (mRNA) is endogenously bound by miR-122-5p and rs699 A > G decreases reporter mRNA in the microRNA functional-assay PASSPORT-seq. The AGT promoter variant rs5051 C > T is in linkage disequilibrium (LD) with rs699 A > G and increases AGT transcription. The independent effect of these variants is understudied due to their LD therefore we aimed to test the hypothesis that increased AGT by rs5051 C > T counterbalances AGT decreased by rs699 A > G, and when these variants occur independently, it translates to HTN-related phenotypes. Methods We used in silico, in vitro, in vivo, and retrospective models to test this hypothesis. Results In silico, rs699 A > G is predicted to increase miR-122-5p binding affinity by 3%. Mir-eCLIP results show rs699 is 40-45 nucleotides from the strongest microRNA-binding site in the AGT mRNA. Unexpectedly, rs699 A > G increases AGT mRNA in an AGT-plasmid-cDNA HepG2 expression model. Genotype-Tissue Expression (GTEx) and UK Biobank analyses demonstrate liver AGT expression and HTN phenotypes are not different when rs699 A > G occurs independently from rs5051 C > T. However, GTEx and the in vitro experiments suggest rs699 A > G confers cell-type-specific effects on AGT mRNA abundance, and suggest paracrine renal renin-angiotensin-system perturbations could mediate the rs699 A > G associations with HTN. Conclusions We found that rs5051 C > T and rs699 A > G significantly associate with systolic blood pressure in Black participants in the UK Biobank, demonstrating a fourfold larger effect than in White participants. Further studies are warranted to determine if altered antihypertensive response in Black individuals might be due to rs5051 C > T or rs699 A > G. Studies like this will help clinicians move beyond the use of race as a surrogate for genotype.
Collapse
Affiliation(s)
- Nicholas R. Powell
- Division of Clinical Pharmacology, Department of MedicineSchool of Medicine, Indiana UniversityIndianapolisIndianaUSA
| | - Tyler Shugg
- Division of Clinical Pharmacology, Department of MedicineSchool of Medicine, Indiana UniversityIndianapolisIndianaUSA
| | - Jacob Leighty
- Division of Clinical Pharmacology, Department of MedicineSchool of Medicine, Indiana UniversityIndianapolisIndianaUSA
| | - Matthew Martin
- Department of Pharmacology and ToxicologySchool of Medicine, Indiana UniversityIndianapolisIndianaUSA
| | - Rolf P. Kreutz
- Department of CardiologySchool of Medicine, Krannert Institute of Cardiology, Indiana UniversityIndianapolisIndianaUSA
| | - Michael T. Eadon
- Division of Nephrology, Department of MedicineSchool of Medicine, Indiana UniversityIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsSchool of Medicine, Indiana UniversityIndianapolisIndianaUSA
| | - Dongbing Lai
- Department of Medical and Molecular GeneticsSchool of Medicine, Indiana UniversityIndianapolisIndianaUSA
| | - Tao Lu
- Department of Pharmacology and ToxicologySchool of Medicine, Indiana UniversityIndianapolisIndianaUSA
| | - Todd C. Skaar
- Division of Clinical Pharmacology, Department of MedicineSchool of Medicine, Indiana UniversityIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsSchool of Medicine, Indiana UniversityIndianapolisIndianaUSA
| |
Collapse
|
47
|
Zhao H, Guo X, Wang W, Wang Z, Rawson P, Wilbur A, Hare M. Consequences of domestication in eastern oyster: Insights from whole genomic analyses. Evol Appl 2024; 17:e13710. [PMID: 38817396 PMCID: PMC11134191 DOI: 10.1111/eva.13710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 04/02/2024] [Accepted: 05/01/2024] [Indexed: 06/01/2024] Open
Abstract
Selective breeding for production traits has yielded relatively rapid successes with high-fecundity aquaculture species. Discovering the genetic changes associated with selection is an important goal for understanding adaptation and can also facilitate better predictions about the likely fitness of selected strains if they escape aquaculture farms. Here, we hypothesize domestication as a genetic change induced by inadvertent selection in culture. Our premise is that standardized culture protocols generate parallel domestication effects across independent strains. Using eastern oyster as a model and a newly developed 600K SNP array, this study tested for parallel domestication effects in multiple independent selection lines compared with their progenitor wild populations. A single contrast was made between pooled selected strains (1-17 generations in culture) and all wild progenitor samples combined. Population structure analysis indicated rank order levels of differentiation as [wild - wild] < [wild - cultured] < [cultured - cultured]. A genome scan for parallel adaptation to the captive environment applied two methodologically distinct outlier tests to the wild versus selected strain contrast and identified a total of 1174 candidate SNPs. Contrasting wild versus selected strains revealed the early evolutionary consequences of domestication in terms of genomic differentiation, standing genetic diversity, effective population size, relatedness, runs of homozygosity profiles, and genome-wide linkage disequilibrium patterns. Random Forest was used to identify 37 outlier SNPs that had the greatest discriminatory power between bulked wild and selected oysters. The outlier SNPs were in genes enriched for cytoskeletal functions, hinting at possible traits under inadvertent selection during larval culture or pediveliger setting at high density. This study documents rapid genomic changes stemming from hatchery-based cultivation of eastern oysters, identifies candidate loci responding to domestication in parallel among independent aquaculture strains, and provides potentially useful genomic resources for monitoring interbreeding between farm and wild oysters.
Collapse
Affiliation(s)
- Honggang Zhao
- Department of Natural Resources & the EnvironmentCornell UniversityIthacaNew YorkUSA
- Present address:
Center for Aquaculture TechnologySan DiegoCaliforniaUSA
| | - Ximing Guo
- Haskin Shellfish Research LaboratoryRutgers UniversityPort NorrisNew JerseyUSA
| | - Wenlu Wang
- Department of Computer SciencesTexas A&M University‐Corpus ChristiCorpus ChristiTexasUSA
| | - Zhenwei Wang
- Haskin Shellfish Research LaboratoryRutgers UniversityPort NorrisNew JerseyUSA
| | - Paul Rawson
- School of Marine SciencesUniversity of MaineOronoMaineUSA
| | - Ami Wilbur
- Shellfish Research Hatchery, Center for Marine ScienceUniversity of North Carolina WilmingtonWilmingtonNorth CarolinaUSA
| | - Matthew Hare
- Department of Natural Resources & the EnvironmentCornell UniversityIthacaNew YorkUSA
| |
Collapse
|
48
|
Curtis D, Amos W. The human genome harbours widespread exclusive yin yang haplotypes. Eur J Hum Genet 2024; 32:691-696. [PMID: 37308599 PMCID: PMC11153572 DOI: 10.1038/s41431-023-01399-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/28/2023] [Accepted: 05/23/2023] [Indexed: 06/14/2023] Open
Abstract
There have been reports of examples of exclusive yin yang haplotypes, differing at every locus, but there has been no systematic search for them. Unphased whole genome sequence data for 2504 unrelated 1000 Genomes subjects was searched for chains of SNPs having global minor allele frequency (MAF) > =0.1 made up of at least 20 SNPs in complete linkage disequilibrium with each other and with no pair being separated by more than 9 other SNPs. The global distribution of these haplotypes was investigated, along with their ancestral origins and associations with genes and phenotypes. A number of previously unrecognised repeats were noted, flagged by all or most subjects being called as heterozygotes, and these were discarded. There were 5114 exclusive yin yang haplotypes each consisting of on average 34.8 SNPs, each spanning on average 15.7 kb and cumulatively covering 80 Mb. Although for some haplotypes the MAF varied markedly between populations the average global fixation index was similar to that for SNPs elsewhere in the genome and there was no evidence of enrichment for genes or gene ontologies. For all but 92 haplotypes there were partial forms present in the chimpanzee and/or Neanderthal genome, indicating that they had been formed in a gradual process but that intermediate haplotypes were now absent from modern humans. Exclusive yin yang haplotypes cover over 2% of the human genome. The mechanisms accounting for their formation and preservation are unclear. They may serve as useful markers of the dispersal of chromosomal regions through human history.
Collapse
Affiliation(s)
- David Curtis
- UCL Genetics Institute, UCL, Darwin Building, Gower Street, London, WC1E 6BT, UK.
| | - William Amos
- Department of Zoology, Downing Street, Cambridge, CB2 3EJ, UK
| |
Collapse
|
49
|
Liu J, Wang Y, Zhao Y, Pan H, Liu Z, Xu Q, Lu S, Jiang H, Wang J, Sun Q, Tan J, Yan X, Li J, Tang B, Guo J. Comprehensive variant analysis of phospholipase A2 superfamily genes in large Chinese Parkinson' s disease cohorts. Mech Ageing Dev 2024; 219:111940. [PMID: 38750970 DOI: 10.1016/j.mad.2024.111940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/31/2024] [Accepted: 05/10/2024] [Indexed: 05/19/2024]
Abstract
To clarify the genetic role of phospholipase A2 (PLA2) genes in Parkinson's disease (PD), we performed a genetic association study in large Chinese population cohorts using next-generation sequencing. In this study, we analyzed both rare and common variants of 38 phospholipase A2 genes in two large cohorts. We detected 1558 and 1115 rare variants in these two cohorts, respectively. In both cohorts, we observed suggestive associations between specific subgroups and the risk of PD. At the single-gene level, several genes (PLA2G2D, PLA2G12A, PLA2G12B, PLA2G4F, PNPLA1, PNPLA3, PNPLA7, PLA2G7, PLA2G15, PLAAT5, and ABHD12) are suggestively associated with PD. Meanwhile, 364 and 2261 common variants were identified in two cohorts, respectively. Our study has expanded the genetic spectrum of the PLA2 family genes and suggested potential pathogenetic roles of PLA2 superfamily in PD.
Collapse
Affiliation(s)
- Jiabin Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yige Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yuwen Zhao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Hongxu Pan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zhenhua Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China; Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Qian Xu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Shen Lu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Hong Jiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Junling Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Qiying Sun
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jieqiong Tan
- Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Xinxiang Yan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jinchen Li
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China; Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China; Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Jifeng Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, Hunan, China; Centre for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China; Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China.
| |
Collapse
|
50
|
Jung ES, Ellinghaus D, Degenhardt F, Meguro A, Khor SS, Mucha S, Wendorff M, Juzenas S, Mizuki N, Tokunaga K, Kim SW, Lee MG, Schreiber S, Kim WH, Franke A, Cheon JH. Genome-wide association analysis reveals the associations of NPHP4, TYW1-AUTS2 and SEMA6D for Behçet's disease and HLA-B*46:01 for its intestinal involvement. Dig Liver Dis 2024; 56:994-1001. [PMID: 37977914 DOI: 10.1016/j.dld.2023.10.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 10/29/2023] [Accepted: 10/30/2023] [Indexed: 11/19/2023]
Abstract
BACKGROUND Intestinal involvement in Behçet's disease (BD) is associated with poor prognosis and is more prevalent in East Asian than in Mediterranean populations. Identifying the genetic causes of intestinal BD is important for understanding the pathogenesis and for appropriate treatment of BD patients. METHODS We performed genome-wide association studies (GWAS) and imputation/replication genotyping of human leukocyte antigen (HLA) alleles for 1,689 Korean and Turkish patients with BD (including 379 patients with intestinal BD) and 2,327 healthy controls, followed by replication using 593 Japanese patients with BD (101 patients with intestinal BD) and 737 healthy controls. Stratified cross-phenotype analyses were performed for 1) overall BD, 2) intestinal BD, and 3) intestinal BD without association of overall BD. RESULTS We identified three novel genome-wide significant susceptibility loci including NPHP4 (rs74566205; P=1.36 × 10-8), TYW1-AUTS2 (rs60021986; P=1.14 × 10-9), and SEMA6D (rs4143322; P=5.54 × 10-9) for overall BD, and a new association with HLA-B*46:01 for intestinal BD (P=1.67 × 10-8) but not for BD without intestinal involvement. HLA peptide binding analysis revealed that Mycobacterial peptides, have a stronger binding affinity to HLA-B*46:01 compared to the known risk allele HLA-B*51:01. CONCLUSIONS HLA-B*46:01 is associated with the development of intestinal BD; NPHP4, TYW1-AUTS2, and SEMA6D are susceptibility loci for overall BD.
Collapse
Affiliation(s)
- Eun Suk Jung
- Department of Internal Medicine and Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, South Korea; Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Kiel, Germany
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Kiel, Germany.
| | - Frauke Degenhardt
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Akira Meguro
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, Yokohama, Japan
| | - Seik-Soon Khor
- Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, Japan
| | - Sören Mucha
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Mareike Wendorff
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Simonas Juzenas
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Kiel, Germany; Institute of Biotechnology, Life Science Centre, Vilnius University, Vilnius, Lithuania
| | - Nobuhisa Mizuki
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, Yokohama, Japan
| | - Katsushi Tokunaga
- Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, Japan
| | - Seung Won Kim
- Department of Internal Medicine and Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, South Korea
| | - Min Goo Lee
- Department of Pharmacology, Brain Korea 21 PLUS Project for Medical Sciences, Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Won Ho Kim
- Department of Internal Medicine and Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, South Korea
| | - Andre Franke
- Institute of Clinical Molecular Biology, Kiel University and University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Jae Hee Cheon
- Department of Internal Medicine and Institute of Gastroenterology, Yonsei University College of Medicine, Seoul, South Korea.
| |
Collapse
|