1
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Cui L, Zhang Y, Dong T, Xu L. Causal associations between childhood obesity and delayed puberty or height: a bidirectional two-sample Mendelian randomization study. J Pediatr Endocrinol Metab 2025; 38:359-366. [PMID: 39878765 DOI: 10.1515/jpem-2024-0438] [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: 09/10/2024] [Accepted: 01/16/2025] [Indexed: 01/31/2025]
Abstract
OBJECTIVES Childhood obesity is thought to influence pubertal development, according to observational studies. However, the exact causal relationship remains unclear due to the complexity of factors affecting pubertal development. METHODS To explore the association between exposure (childhood obesity) and outcome (delayed puberty, height), we utilized various methods, including inverse-variance weighted (IVW), weighted median, weighted mode, and MR Egger regression. Additionally, sensitivity analyses were conducted using MR-Egger, MR-PRESSO, Cochran's Q, and leave-one-out techniques to ensure the robustness of the results. Additionally, reverse MR analysis was conducted to explore potential reverse causation. RESULTS The IVW analysis revealed no significant genetic causal link between childhood obesity and delayed puberty or height (all p>0.05). In the reverse analysis, height had a causal association with childhood obesity (OR=0.85, 95 % CI=0.76-0.96). The Cochran's Q test highlighted heterogeneity in the results concerning childhood obesity and height (p<0.05). But the MR-Egger intercept and MR-PRESSO test confirmed no impact the results pleiotropic bias, supported by leave-one-out sensitivity analysis. CONCLUSIONS Our study found no significant genetic causal association between childhood obesity and delayed puberty or height. However, height was causally associated with childhood obesity. Future research should utilize advanced analytical methods to better understand the determinants of pubertal development.
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Affiliation(s)
- Lulu Cui
- Department of Pediatric Endocrinology, School of Medicine, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Zhang
- Department of Pediatric Endocrinology, School of Medicine, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Ting Dong
- Department of Pediatric Endocrinology, School of Medicine, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Liya Xu
- Department of Pediatric Endocrinology, School of Medicine, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China
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2
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Ahi EP, Panda B, Primmer CR. The hippo pathway: a molecular bridge between environmental cues and pace of life. BMC Ecol Evol 2025; 25:35. [PMID: 40275190 PMCID: PMC12020181 DOI: 10.1186/s12862-025-02378-8] [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: 12/30/2024] [Accepted: 04/14/2025] [Indexed: 04/26/2025] Open
Abstract
The pace of life (POL) is shaped by a complex interplay between genetic and environmental factors, influencing growth, maturation, and lifespan across species. The Hippo signaling pathway, a key regulator of organ size and cellular homeostasis, has emerged as a central integrator of environmental cues that modulate POL traits. In this review, we explore how the Hippo pathway links environmental factors-such as temperature fluctuations and dietary energy availability-to molecular mechanisms governing metabolic balance, hormonal signaling, and reproductive timing. Specifically, we highlight the regulatory interactions between the Hippo pathway and metabolic sensors (AMPK, mTOR, SIRT1 and DLK1-Notch), as well as hormonal signals (IGF-1, kisspeptin, leptin, cortisol, thyroid and sex steroids), which together orchestrate key life-history traits, including growth rates, lifespan and sexual maturation, with a particular emphasis on their role in reproductive timing. Furthermore, we consider its role as a potential coordinator of POL-related molecular processes, such as telomere dynamics and epigenetic mechanisms, within a broader regulatory network. By integrating insights from molecular biology and eco-evolutionary perspectives, we propose future directions to dissect the Hippo pathway's role in POL regulation across taxa. Understanding these interactions will provide new perspectives on how organisms adaptively adjust life-history strategies in response to environmental variability.
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Affiliation(s)
- Ehsan Pashay Ahi
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Viikinkaari 9, 00014, Helsinki, Finland.
| | - Bineet Panda
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Viikinkaari 9, 00014, Helsinki, Finland
| | - Craig R Primmer
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Viikinkaari 9, 00014, Helsinki, Finland
- Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
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3
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Richardson TG, Urquijo H, Howe LJ, Hawkes G, DePaolo J, Damrauer SM, Frayling TM, Davey Smith G. Effects of childhood and adult height on later life cardiovascular disease risk estimated through Mendelian randomization. Eur J Epidemiol 2025; 40:167-176. [PMID: 40106116 PMCID: PMC12018521 DOI: 10.1007/s10654-025-01203-2] [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: 04/11/2024] [Accepted: 01/18/2025] [Indexed: 03/22/2025]
Abstract
Taller individuals are at elevated and protected risk of various cardiovascular disease endpoints. Whether this is due to a direct consequence of their height during childhood, a long-term effect of remaining tall throughout the lifecourse, or confounding by other factors, is unknown. We sought to address this by harnessing human genetic data from the UK Biobank to separate the independent effects of childhood and adulthood height using an approach known as lifecourse Mendelian randomization (MR). Protective effects of taller childhood height on risk of later life coronary artery disease (OR = 0.78 per change in height category, 95% CI = 0.70 to 0.86, P = 4 × 10- 10) and stroke (OR = 0.93, 95% CI = 0.86 to 1.00, P = 0.03) using data from large-scale consortia were found using a univariable model, although evidence of these effects attenuated in a multivariable setting upon accounting for adulthood height. In contrast, direct effects of taller childhood height on increased risk of later life atrial fibrillation (OR = 1.61, 95% CI = 1.42 to 1.79, P = 5 × 10- 7) and thoracic aortic aneurysm (OR = 1.55, 95% CI = 1.16 to 1.95, P = 0.03) were found even after accounting for adulthood height. Evidence for both of these direct effects was replicated in the Million Veterans Program. The protective effect of childhood height on risk of coronary artery disease and stroke can be largely explained by taller children typically becoming taller individuals in later life. Conversely, the independent effect of childhood height on increased risk of atrial fibrillation and thoracic aortic aneurysm may point towards developmental mechanisms in early life which confer a lifelong risk on these disease outcomes.
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Affiliation(s)
- Tom G Richardson
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK.
| | - Helena Urquijo
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Laurence J Howe
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Gareth Hawkes
- Genetics of Complex Traits, College of Biomedical Sciences, University of Exeter Medical School, University of Exeter, Exeter, Devon, UK
| | - John DePaolo
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Scott M Damrauer
- Division of Vascular Surgery, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Cardiovascular Institute, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
| | - Timothy M Frayling
- Department of Genetic Medicine and Development, Faculty of Medicine, CMU, Geneva, Suisse
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- NIHR Bristol Biomedical Research Centre Bristol, University Hospitals Bristol and Weston NHS Foundation Trust, University of Bristol, Bristol, UK
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4
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Calcaterra V, Tiranini L, Magenes VC, Rossi V, Cucinella L, Nappi RE, Zuccotti G. Impact of Obesity on Pubertal Timing and Male Fertility. J Clin Med 2025; 14:783. [PMID: 39941454 PMCID: PMC11818283 DOI: 10.3390/jcm14030783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2024] [Revised: 01/20/2025] [Accepted: 01/24/2025] [Indexed: 02/16/2025] Open
Abstract
Childhood obesity has profound effects on puberty in boys and girls, altering its timing, progression, and associated hormonal changes. Also, later male fertility could be impaired by childhood and pubertal obesity in light of the impact of inflammatory markers on semen quality. The aim of this narrative review is to explore the intricate relationship between childhood obesity and its impact on pubertal development and fertility, with a specific focus on boys. Such a relationship between obesity and pubertal timing in males is highly influenced by metabolic, hormonal, genetic, epigenetic, and environmental factors. While many studies suggest that obesity accelerates pubertal onset in boys, some studies do not confirm these findings, especially in cases of severe obesity. In fact, delayed puberty has also been reported in certain instances. Obesity influences fertility through different central and peripheral processes, including an altered endocrine milieu, inflammatory environment, and epigenetic modifications that alter semen quality and vitality, leading to subfertility or infertility. The early identification and management of potential issues associated with obesity are crucial for ensuring optimal reproductive health in adulthood. Further research is essential to clarify these associations and to develop targeted interventions aimed at preventing the negative health outcomes associated with obesity-related disruptions in puberty and fertility.
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Affiliation(s)
- Valeria Calcaterra
- Department of Internal Medicine and Therapeutics, University of Pavia, 27100 Pavia, Italy
- Pediatric Department, Buzzi Children’s Hospital, 20154 Milano, Italy; (V.C.M.); (V.R.); (G.Z.)
| | - Lara Tiranini
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy; (L.T.); (L.C.); (R.E.N.)
| | | | - Virginia Rossi
- Pediatric Department, Buzzi Children’s Hospital, 20154 Milano, Italy; (V.C.M.); (V.R.); (G.Z.)
| | - Laura Cucinella
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy; (L.T.); (L.C.); (R.E.N.)
- Research Center for Reproductive Medicine, Gynecological Endocrinology and Menopause, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Rossella Elena Nappi
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy; (L.T.); (L.C.); (R.E.N.)
- Research Center for Reproductive Medicine, Gynecological Endocrinology and Menopause, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Gianvincenzo Zuccotti
- Pediatric Department, Buzzi Children’s Hospital, 20154 Milano, Italy; (V.C.M.); (V.R.); (G.Z.)
- Department of Biomedical and Clinical Science, University of Milano, 20157 Milano, Italy
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5
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Zhou S, Xu Y, Xiong J, Cheng G. Cross-trait multivariate GWAS confirms health implications of pubertal timing. Nat Commun 2025; 16:799. [PMID: 39824883 PMCID: PMC11742396 DOI: 10.1038/s41467-025-56191-4] [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: 06/11/2024] [Accepted: 01/07/2025] [Indexed: 01/20/2025] Open
Abstract
Pubertal timing is highly variable and is associated with long-term health outcomes. Phenotypes associated with pubertal timing include age at menarche, age at voice break, age at first facial hair and growth spurt, and pubertal timing seems to have a shared genetic architecture between the sexes. However, puberty phenotypes have primarily been assessed separately, failing to account for shared genetics, which limits the reliability of the purported health implications. Here, we model the common genetic architecture for puberty timing using a multivariate GWAS, with an effective population of 514,750 European participants. We find 266 independent variants in 197 loci, including 18 novel variants. Transcriptomic, proteome imputation and fine-mapping analyses reveal genes causal for pubertal timing, including KDM4C, LEPR, CCNC, ACP1, and PCSK1. Linkage disequilibrium score regression and Mendelian randomisation analysis establish causal associations between earlier puberty and both accelerated ageing and the risk of developing cardiovascular disease and osteoporosis. We find that alanine aminotransferase, glycated haemoglobin, high-density lipoprotein cholesterol and Parabacteroides levels are mediators of these relationships, and establish that controlling oily fish and retinol intake may be beneficial for promoting healthy pubertal development.
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Affiliation(s)
- Siquan Zhou
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Laboratory of Molecular Translational Medicine, Center for Translational Medicine, West China Second University Hospital, Sichuan University, Chengdu, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Maternal & Child Nutrition Center, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Yujie Xu
- Laboratory of Molecular Translational Medicine, Center for Translational Medicine, West China Second University Hospital, Sichuan University, Chengdu, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Maternal & Child Nutrition Center, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Jingyuan Xiong
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
- Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Sichuan University, Chengdu, China.
| | - Guo Cheng
- Laboratory of Molecular Translational Medicine, Center for Translational Medicine, West China Second University Hospital, Sichuan University, Chengdu, China.
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Maternal & Child Nutrition Center, West China Second University Hospital, Sichuan University, Chengdu, China.
- Children's Medicine Key Laboratory of Sichuan Province, Sichuan University, Chengdu, China.
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6
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Zhang B, Zhu G, Wu J, Xie H, Cui J, Qian W, Yi Q, Pan F, Fang F, Ling Y, Zhang Y, Li Y, Liu Y. Transcriptome and DNA methylation analysis of the goat pineal gland during puberty. Sci Rep 2025; 15:2269. [PMID: 39824948 PMCID: PMC11742059 DOI: 10.1038/s41598-024-84559-x] [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: 07/17/2024] [Accepted: 12/24/2024] [Indexed: 01/20/2025] Open
Abstract
Previous studies have confirmed that methylation regulates gene transcription in the hypothalamus-pituitary-gonadal axis during puberty initiation, but little is known about the regulation of DNA methylation on gene expression in the pineal gland. To screen pineal gland candidate genes related to the onset of goat puberty and regulated by genome methylation, we collected pineal glands from prepubertal and pubertal female goats, then, determined the DNA methylation profile by whole genome bisulfite sequencing and the transcriptome by RNA sequencing on Illumina HiSeqTM2500. We analyzed differentially expressed genes between the Pre group and Pub group using the DESeq2 software (version 1.20.0), and applied the Benjamini and Hochberg method for adjusting P-values. Genes with a P-value less than 0.05 and an absolute log2 fold change greater than 0 were considered differentially expressed genes. Results showed that there was no significant difference in the whole-genome methylation level of the pineal gland between prepubertal and pubertal goats, but the methylation pattern changed significantly, indicating that genomic DNA methylation of the pineal gland might play a role in regulating the initiation of goat puberty. Changes in DNA methylation patterns affected some pineal gland transcriptomes, while the transcriptional level of most genes remained unaffected by DNA methylation differences. Genes regulated by DNA methylation regulates genes primarily involved in metabolic processes, oxidative phosphorylation, and signaling pathways related to thermogenesis. Methylation significantly regulated the expression of genes such as ATP5F1D, CACNB2, and PTEN, while genes like LIN28B, GIP, OPN1SW, and DCC showed the most notable fold changes, which may indicate their involvement in the onset of puberty.
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Affiliation(s)
- Bochao Zhang
- College of Veterinary Medicine, Anhui Agricultural University, Hefei, Anhui, China
| | - Genbao Zhu
- College of Veterinary Medicine, Anhui Agricultural University, Hefei, Anhui, China
- AnhuiWanbei Electricity Group General Hospital, Suzhou, Anhui, China
| | - Jianling Wu
- College of Veterinary Medicine, Anhui Agricultural University, Hefei, Anhui, China
- HefeiTiangang Immune Medicine Co., Ltd, Hefei, Anhui, China
| | - Huihui Xie
- College of Veterinary Medicine, Anhui Agricultural University, Hefei, Anhui, China
| | - Jiankun Cui
- College of Veterinary Medicine, Anhui Agricultural University, Hefei, Anhui, China
| | - Wei Qian
- College of Veterinary Medicine, Anhui Agricultural University, Hefei, Anhui, China
| | - Qing Yi
- College of Veterinary Medicine, Anhui Agricultural University, Hefei, Anhui, China
| | - Fuqiang Pan
- College of Veterinary Medicine, Anhui Agricultural University, Hefei, Anhui, China
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, Jiangsu, China
| | - Fugui Fang
- College of Veterinary Medicine, Anhui Agricultural University, Hefei, Anhui, China
- Anhui Provincial Key Laboratory of Local Livestock and Poultry Genetic Resource Conservation and Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui, China
- Linquan County Modern Agriculture Technology Cooperation and Extension Service Center, Linquan, Anhui, China
| | - Yinghui Ling
- College of Animal Science and Technology, Anhui Agricultural University, 130 Changjiang West Road, Hefei, 230036, Anhui, China
- Anhui Provincial Key Laboratory of Local Livestock and Poultry Genetic Resource Conservation and Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui, China
- Linquan County Modern Agriculture Technology Cooperation and Extension Service Center, Linquan, Anhui, China
| | - Yunhai Zhang
- College of Animal Science and Technology, Anhui Agricultural University, 130 Changjiang West Road, Hefei, 230036, Anhui, China
- Anhui Provincial Key Laboratory of Local Livestock and Poultry Genetic Resource Conservation and Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui, China
- Linquan County Modern Agriculture Technology Cooperation and Extension Service Center, Linquan, Anhui, China
| | - Yunsheng Li
- College of Animal Science and Technology, Anhui Agricultural University, 130 Changjiang West Road, Hefei, 230036, Anhui, China.
- Anhui Provincial Key Laboratory of Local Livestock and Poultry Genetic Resource Conservation and Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui, China.
- Linquan County Modern Agriculture Technology Cooperation and Extension Service Center, Linquan, Anhui, China.
| | - Ya Liu
- College of Veterinary Medicine, Anhui Agricultural University, Hefei, Anhui, China.
- College of Animal Science and Technology, Anhui Agricultural University, 130 Changjiang West Road, Hefei, 230036, Anhui, China.
- Anhui Provincial Key Laboratory of Local Livestock and Poultry Genetic Resource Conservation and Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui, China.
- Linquan County Modern Agriculture Technology Cooperation and Extension Service Center, Linquan, Anhui, China.
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7
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Strobel MR, Zhou Y, Qiu L, Hofer AM, Chen X. Temporal ablation of the ciliary protein IFT88 alters normal brainwave patterns. Sci Rep 2025; 15:347. [PMID: 39747370 PMCID: PMC11697071 DOI: 10.1038/s41598-024-83432-1] [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: 04/16/2024] [Accepted: 12/16/2024] [Indexed: 01/04/2025] Open
Abstract
The primary cilium is a hair-like organelle that hosts molecular machinery for various developmental and homeostatic signaling pathways. Its alteration can cause rare ciliopathies such as the Bardet-Biedl and Joubert syndromes, but is also linked to Alzheimer's disease, clinical depression, and autism spectrum disorder. These afflictions are caused by disturbances in a wide variety of genes but a common phenotype amongst them is cognitive impairment. While cilia-mediated neural function has been widely examined in early neurodevelopment, their function in the adult brain is not well understood. To help elucidate the role of cilia in neural activity, we temporally induced the ablation of IFT88, a gene encoding the intraflagellar transport 88 protein which is neccessary for ciliogenesis, in adult mice before performing memory-related behavioral assays and electroencephalogram/electromyogram (EEG/EMG) recordings. Inducible IFT88 KO mice exhibited severe learning deficits in trace fear conditioning and Morris water maze tests. They had strongly affected brainwave activity both under isoflurane induced anesthesia and during normal activity. And additionally, inducible IFT88 KO mice had altered sleep architecture and attenuated phase-amplitude coupling, a process that underlies learning and memory formation. These results highlight the growing significance of primary cilia for healthy neural function in the adult brain.
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Affiliation(s)
- Matthew R Strobel
- Department of Molecular, Cellular, and Biomedical Sciences, College of Life Sciences and Agriculture, University of New Hampshire, Durham, NH, 03824, USA.
- Department of Surgery, VA Boston Healthcare System, Harvard Medical School, Brigham and Women's Hospital, 1400 VFW Parkway, West Roxbury, MA, 02132, USA.
| | - Yuxin Zhou
- Department of Molecular, Cellular, and Biomedical Sciences, College of Life Sciences and Agriculture, University of New Hampshire, Durham, NH, 03824, USA
| | - Liyan Qiu
- Department of Molecular, Cellular, and Biomedical Sciences, College of Life Sciences and Agriculture, University of New Hampshire, Durham, NH, 03824, USA
| | - Aldebaran M Hofer
- Department of Surgery, VA Boston Healthcare System, Harvard Medical School, Brigham and Women's Hospital, 1400 VFW Parkway, West Roxbury, MA, 02132, USA
| | - Xuanmao Chen
- Department of Molecular, Cellular, and Biomedical Sciences, College of Life Sciences and Agriculture, University of New Hampshire, Durham, NH, 03824, USA.
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8
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Chun D, Chung T, Kang J, Ko T, Rhie YJ, Kim J. Height estimation in children and adolescents using body composition big data: Machine-learning and explainable artificial intelligence approach. Digit Health 2025; 11:20552076251331879. [PMID: 40162169 PMCID: PMC11951887 DOI: 10.1177/20552076251331879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2024] [Accepted: 03/17/2025] [Indexed: 04/02/2025] Open
Abstract
Objective To develop an accurate and interpretable height estimation model for children and adolescents using body composition variables and explainable artificial intelligence approaches. Methods A light gradient boosting method was employed on a dataset of 278,301 measurements from 54,374 children and adolescents aged 6-18 years. The model incorporated anthropometric and body composition measures. Model interpretability was enhanced through feature importance analysis, Shapley additive explanations, partial dependence plots, and accumulated local effects. Results The models achieved high accuracy with mean absolute percentage errors of 1.64% and 1.63% for boys and girls, respectively. Soft lean mass (SLM), body fat mass percentage (BFMP), skeletal muscle mass, and skeletal muscle mass percentage were consistently identified as key factors influencing height estimation. Analysis revealed a positive correlation between SLM and estimated height, while BFMP exhibited an inverse relationship with height projections. Conclusion These findings provide valuable insights into the relationship between body composition and height, underlining the potential of body composition variables as accurate height predictors in children and adolescents. The model's interpretability and accuracy make it a promising tool for pediatric growth assessment and monitoring.
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Affiliation(s)
- Dohyun Chun
- College of Business Administration, Kangwon National University, Chuncheon, Gangwon-do, Korea
- Research Team, The Global Prediction Co., Ltd, Gwangmyeong, Gyeonggi-do, Korea
| | - Taesung Chung
- Quality Management Team, The Global Prediction Co., Ltd, Gwangmyeong, Gyeonggi-do, Korea
| | - Jongho Kang
- Research Team, The Global Prediction Co., Ltd, Gwangmyeong, Gyeonggi-do, Korea
- College of Business Administration, Chonnam National University, Gwangju, Korea
| | - Taehoon Ko
- Department of Medical Informatics, The Catholic University of Korea, Seoul, Korea
| | - Young-Jun Rhie
- Department of Pediatrics, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Gyeonggi-do, Korea
| | - Jihun Kim
- Research Team, The Global Prediction Co., Ltd, Gwangmyeong, Gyeonggi-do, Korea
- College of Humanities & Social Sciences Convergence, Yonsei University, Wonju, Gangwon-do, Korea
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9
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Strobel MR, Zhou Y, Qiu L, Hofer AM, Chen X. Temporal Ablation of the Ciliary Protein IFT88 Alters Normal Brainwave Patterns. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.03.587983. [PMID: 38617207 PMCID: PMC11014598 DOI: 10.1101/2024.04.03.587983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
The primary cilium is a hair-like organelle that hosts molecular machinery for various developmental and homeostatic signaling pathways. Its alteration can cause rare ciliopathies such as the Bardet-Biedl and Joubert syndromes, but is also linked to Alzheimer's disease, clinical depression, and autism spectrum disorder. These afflictions are caused by disturbances in a wide variety of genes but a common phenotype amongst them is cognitive impairment. While cilia-mediated neural function has been widely examined in early neurodevelopment, their function in the adult brain is not well understood. To help elucidate the role of cilia in neural activity, we temporally induced the ablation of IFT88, a gene encoding the intraflagellar transport 88 protein which is neccessary for ciliogenesis, in adult mice before performing memory-related behavioral assays and electroencephalogram/electromyogram (EEG/EMG) recordings. Inducible IFT88 KO mice exhibited severe learning deficits in trace fear conditioning and Morris water maze tests. They had strongly affected brainwave activity both under isoflurane induced anesthesia and during normal activity. And additionally, inducible IFT88 KO mice had altered sleep architecture and attenuated phase-amplitude coupling, a process that underlies learning and memory formation. These results highlight the growing significance of primary cilia for healthy neural function in the adult brain.
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Affiliation(s)
- Matthew R. Strobel
- Department of Molecular, Cellular, and Biomedical Sciences, College of Life Sciences and Agriculture, University of New Hampshire, Durham, NH 03824, USA
- Harvard Medical School and the VA Boston Healthcare System and the Department of Surgery, Brigham and Women’s Hospital, 1400 VFW Parkway, West Roxbury, MA 02132, USA
| | - Yuxin Zhou
- Department of Molecular, Cellular, and Biomedical Sciences, College of Life Sciences and Agriculture, University of New Hampshire, Durham, NH 03824, USA
| | - Liyan Qiu
- Department of Molecular, Cellular, and Biomedical Sciences, College of Life Sciences and Agriculture, University of New Hampshire, Durham, NH 03824, USA
| | - Aldebaran M. Hofer
- Harvard Medical School and the VA Boston Healthcare System and the Department of Surgery, Brigham and Women’s Hospital, 1400 VFW Parkway, West Roxbury, MA 02132, USA
| | - Xuanmao Chen
- Department of Molecular, Cellular, and Biomedical Sciences, College of Life Sciences and Agriculture, University of New Hampshire, Durham, NH 03824, USA
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10
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He Q, Liu H, Lu L, Zhang Q, Wang Q, Wang B, Wu X, Guan L, Mao J, Xue Y, Zhang C, Cao X, He Y, Peng X, Peng H, Zhao K, Li H, Jin X, Zhao L, Zhang J, Wang T. A genome-wide association study of neonatal metabolites. CELL GENOMICS 2024; 4:100668. [PMID: 39389019 PMCID: PMC11602626 DOI: 10.1016/j.xgen.2024.100668] [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: 03/09/2023] [Revised: 12/16/2023] [Accepted: 09/11/2024] [Indexed: 10/12/2024]
Abstract
Genetic factors significantly influence the concentration of metabolites in adults. Nevertheless, the genetic influence on neonatal metabolites remains uncertain. To bridge this gap, we employed genotype imputation techniques on large-scale low-pass genome data obtained from non-invasive prenatal testing. Subsequently, we conducted association studies on a total of 75 metabolic components in neonates. The study identified 19 previously reported associations and 11 novel associations between single-nucleotide polymorphisms and metabolic components. These associations were initially found in the discovery cohort (8,744 participants) and subsequently confirmed in a replication cohort (19,041 participants). The average heritability of metabolic components was estimated to be 76.2%, with a range of 69%-78.8%. These findings offer valuable insights into the genetic architecture of neonatal metabolism.
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Affiliation(s)
- Quanze He
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China; Suzhou Municipal Hospital, Suzhou Jiangsu 215000, China
| | - Hankui Liu
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang 050035, China; BGI Genomics, Shenzhen 518083, China
| | - Lu Lu
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China
| | - Qin Zhang
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China
| | - Qi Wang
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China
| | - Benjing Wang
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China
| | - Xiaojuan Wu
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China
| | - Liping Guan
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang 050035, China; BGI Genomics, Shenzhen 518083, China
| | - Jun Mao
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China
| | - Ying Xue
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China
| | - Chunhua Zhang
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China
| | - Xinye Cao
- Clinical Medicine Department, Xinjiang Medical University, Urumqi, Xinjiang Province 830054, China
| | - Yuxing He
- Clinical Medicine Department, Xinjiang Medical University, Urumqi, Xinjiang Province 830054, China
| | - Xiangwen Peng
- Changsha Hospital for Maternal and Child Health Care of Hunan Normal University, Changsha, Hunan Province 431005, China
| | | | - Kangrong Zhao
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China
| | - Hong Li
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China
| | - Xin Jin
- BGI Research, Shenzhen 518083, China; The Innovation Centre of Ministry of Education for Development and Diseases, School of Medicine, South China University of Technology, Guangzhou 510006, China; Shanxi Medical University-BGI Collaborative Center for Future Medicine, Shanxi Medical University, Taiyuan 030001, China; Shenzhen Key Laboratory of Transomics Biotechnologies, BGI Research, Shenzhen 518083, China.
| | - Lijian Zhao
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang 050035, China; BGI Genomics, Shenzhen 518083, China; Medical Technology College, Hebei Medical University, Shijiazhuang 050000, China.
| | - Jianguo Zhang
- Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang 050035, China; BGI Research, Shenzhen 518083, China; School of Public Health, Hebei Medical University, Shijiazhuang 050000, China.
| | - Ting Wang
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China; Suzhou Municipal Hospital, Suzhou Jiangsu 215000, China.
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Gianferante DM, Moore A, Spector LG, Wheeler W, Yang T, Hubbard A, Gorlick R, Patiño-Garcia A, Lecanda F, Flanagan AM, Amary F, Andrulis IL, Wunder JS, Thomas DM, Ballinger ML, Serra M, Hattinger C, Demerath E, Johnson W, Birmann BM, De Vivo I, Giles G, Teras LR, Arslan A, Vermeulen R, Sample J, Freedman ND, Huang WY, Chanock SJ, Savage SA, Berndt SI, Mirabello L. Genetically inferred birthweight, height, and puberty timing and risk of osteosarcoma. Cancer Epidemiol 2024; 92:102432. [PMID: 37596165 PMCID: PMC10869637 DOI: 10.1016/j.canep.2023.102432] [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: 05/04/2023] [Accepted: 07/14/2023] [Indexed: 08/20/2023]
Abstract
INTRODUCTION Several studies have linked increased risk of osteosarcoma with tall stature, high birthweight, and early puberty, although evidence is inconsistent. We used genetic risk scores (GRS) based on established genetic loci for these traits and evaluated associations between genetically inferred birthweight, height, and puberty timing with osteosarcoma. METHODS Using genotype data from two genome-wide association studies, totaling 1039 cases and 2923 controls of European ancestry, association analyses were conducted using logistic regression for each study and meta-analyzed to estimate pooled odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup analyses were conducted by case diagnosis age, metastasis status, tumor location, tumor histology, and presence of a known pathogenic variant in a cancer susceptibility gene. RESULTS Genetically inferred higher birthweight was associated with an increased risk of osteosarcoma (OR =1.59, 95% CI 1.07-2.38, P = 0.02). This association was strongest in cases without metastatic disease (OR =2.46, 95% CI 1.44-4.19, P = 9.5 ×10-04). Although there was no overall association between osteosarcoma and genetically inferred taller stature (OR=1.06, 95% CI 0.96-1.17, P = 0.28), the GRS for taller stature was associated with an increased risk of osteosarcoma in 154 cases with a known pathogenic cancer susceptibility gene variant (OR=1.29, 95% CI 1.03-1.63, P = 0.03). There were no significant associations between the GRS for puberty timing and osteosarcoma. CONCLUSION A genetic propensity to higher birthweight was associated with increased osteosarcoma risk, suggesting that shared genetic factors or biological pathways that affect birthweight may contribute to osteosarcoma pathogenesis.
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Affiliation(s)
| | - Amy Moore
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Rockville, MD, USA
| | - Logan G Spector
- Department of Pediatrics, University of Minnesota, Minneapolis, MN 55455, USA
| | | | - Tianzhong Yang
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Aubrey Hubbard
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Rockville, MD, USA
| | - Richard Gorlick
- University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ana Patiño-Garcia
- Department of Pediatrics and Solid Tumor Division CIMA, IdiSNA, Clínica Universidad de Navarra, Pamplona, Spain
| | - Fernando Lecanda
- Center for Applied Medical Research (CIMA)-University of Navarra, IdiSNA, and CIBERONC, Pamplona, Spain
| | - Adrienne M Flanagan
- UCL Cancer Institute, Huntley Street, London WC1E 6BT, UK; Royal National Orthopaedic Hospital NHS Trust, Stanmore, Middlesex HA7 4LP, UK
| | - Fernanda Amary
- Royal National Orthopaedic Hospital NHS Trust, Stanmore, Middlesex HA7 4LP, UK
| | - Irene L Andrulis
- Litwin Centre for Cancer Genetics, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Jay S Wunder
- Litwin Centre for Cancer Genetics, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
| | - David M Thomas
- Garvan Institute of Medical Research, Darlinghurst, NSW, Australia; St Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Mandy L Ballinger
- Garvan Institute of Medical Research, Darlinghurst, NSW, Australia; St Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Massimo Serra
- Laboratory of Experimental Oncology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy; IRCCS Istituto Ortopedico Rizzoli, Osteoncology, Bone and Soft Tissue Sarcomas and Innovative Therapies, Pharmacogenomics and Pharmacogenetics Research Unit, Bologna, Italy
| | - Claudia Hattinger
- Laboratory of Experimental Oncology, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy; IRCCS Istituto Ortopedico Rizzoli, Osteoncology, Bone and Soft Tissue Sarcomas and Innovative Therapies, Pharmacogenomics and Pharmacogenetics Research Unit, Bologna, Italy
| | - Ellen Demerath
- Division of Epidemiology and Clinical Research, School of Public Health, UMN, USA
| | - Will Johnson
- School of Sport, Exercise, and Health Sciences, University of Loughborough, UK
| | - Brenda M Birmann
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Immaculata De Vivo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Graham Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Lauren R Teras
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Alan Arslan
- Department of Obstetrics and Gynecology, New York School of Medicine, New York, NY, USA; Department of Population Health, New York University School of Medicine, New York, NY, USA
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jeannette Sample
- Department of Pediatrics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Neal D Freedman
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Rockville, MD, USA
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Rockville, MD, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Rockville, MD, USA
| | - Sharon A Savage
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Rockville, MD, USA
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Rockville, MD, USA
| | - Lisa Mirabello
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Rockville, MD, USA.
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12
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Lukusa MT, Yang CY, Tsai MC. Mendelian randomization analysis on the impacts of age at menarche on adult height: A Taiwanese population study. Pediatr Neonatol 2024:S1875-9572(24)00158-X. [PMID: 39278795 DOI: 10.1016/j.pedneo.2024.04.012] [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] [Received: 10/05/2023] [Revised: 03/30/2024] [Accepted: 04/29/2024] [Indexed: 09/18/2024] Open
Abstract
BACKGROUNDS Ample evidence supports potential influence of age at menarche (AM) on adult height (AH), but multiple confounders may affect causal estimates. To address this issue, the Mendelian randomization (MR) analysis was used to explore the causal impacts of AM on AH. METHODS Using data (n = 57,349) from the publicly accessible Taiwan Biobank and randomly splitting them into 2 equal-size subsets, we identified single nucleotide polymorphisms (SNPs) significantly associated with AM in the exploration subset and used these SNPs as instrumental variables to estimate the effects of instruments on AH in the validation subset based on two stage least squares (2SLS) regression. In addition, three more summary statistics-based approaches, namely inverse variance weighted (IVW), MR-Egger, and weighted median (WM) analyses, were used to verify the findings. We also performed heterogeneity and sensitivity analyses to evaluate the robustness of the results. RESULTS We identified 4 leading SNPs associated with AM at the genome-wide significant level, whereas rs9409082 may exert some pleiotropic effects on AH. After eliminating rs9409082, the 2SLS analysis indicated that one year delay in genetically determined AM predicted 1.5 cm height gain in adulthood (β = 1.508, 95% confidence interval [0.852, 2.163]). The causal relationship was also supported by WM (β = 1.183, [0.329, 2.038]) and IVW (β = 1.493, [0.523, 2.463]) methods. CONCLUSIONS Evidence from the present MR study supports a causal relationship between later AM and taller AH.
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Affiliation(s)
- Martin Tshishimbi Lukusa
- Institute of Data Science, College of Management, National Cheng Kung University, Tainan, Taiwan; Department of Statistics, College of Management, National Cheng Kung University, Tainan, Taiwan; Department of Statistics, College of Business, Feng Chia University, Taichung, Taiwan
| | - Cheng-Yi Yang
- Department of Statistics, College of Management, National Cheng Kung University, Tainan, Taiwan; Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | - Meng-Che Tsai
- Division of Genetics, Endocrinology, and Metabolism, Department of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Genomic Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Medical Humanities and Social Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
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13
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M JN, Bharadwaj D. The complex web of obesity: from genetics to precision medicine. Expert Rev Endocrinol Metab 2024; 19:403-418. [PMID: 38869356 DOI: 10.1080/17446651.2024.2365785] [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: 11/06/2023] [Accepted: 06/05/2024] [Indexed: 06/14/2024]
Abstract
INTRODUCTION Obesity is a growing public health concern affecting both children and adults. Since it involves both genetic and environmental components, the management of obesity requires both, an understanding of the underlying genetics and changes in lifestyle. The knowledge of obesity genetics will enable the possibility of precision medicine in anti-obesity medications. AREAS COVERED Here, we explore health complications and the prevalence of obesity. We discuss disruptions in energy balance as a symptom of obesity, examining evolutionary theories, its multi-factorial origins, and heritability. Additionally, we discuss monogenic and polygenic obesity, the converging biological pathways, potential pharmacogenomics applications, and existing anti-obesity medications - specifically focussing on the leptin-melanocortin and incretin pathways. Comparisons between childhood and adult obesity genetics are made, along with insights into structural variants, epigenetic changes, and environmental influences on epigenetic signatures. EXPERT OPINION With recent advancements in anti-obesity drugs, genetic studies pinpoint new targets and allow for repurposing existing drugs. This creates opportunities for genotype-informed treatment options. Also, lifestyle interventions can help in the prevention and treatment of obesity by altering the epigenetic signatures. The comparison of genetic architecture in adults and children revealed a significant overlap. However, more robust studies with diverse ethnic representation is required in childhood obesity.
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Affiliation(s)
- Janaki Nair M
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
| | - Dwaipayan Bharadwaj
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
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Hu X, Cai M, Xiao J, Wan X, Wang Z, Zhao H, Yang C. Benchmarking Mendelian randomization methods for causal inference using genome-wide association study summary statistics. Am J Hum Genet 2024; 111:1717-1735. [PMID: 39059387 PMCID: PMC11339627 DOI: 10.1016/j.ajhg.2024.06.016] [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: 01/31/2024] [Revised: 06/26/2024] [Accepted: 06/26/2024] [Indexed: 07/28/2024] Open
Abstract
Mendelian randomization (MR), which utilizes genetic variants as instrumental variables (IVs), has gained popularity as a method for causal inference between phenotypes using genetic data. While efforts have been made to relax IV assumptions and develop new methods for causal inference in the presence of invalid IVs due to confounding, the reliability of MR methods in real-world applications remains uncertain. Instead of using simulated datasets, we conducted a benchmark study evaluating 16 two-sample summary-level MR methods using real-world genetic datasets to provide guidelines for the best practices. Our study focused on the following crucial aspects: type I error control in the presence of various confounding scenarios (e.g., population stratification, pleiotropy, and family-level confounders like assortative mating), the accuracy of causal effect estimates, replicability, and power. By comprehensively evaluating the performance of compared methods over one thousand exposure-outcome trait pairs, our study not only provides valuable insights into the performance and limitations of the compared methods but also offers practical guidance for researchers to choose appropriate MR methods for causal inference.
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Affiliation(s)
- Xianghong Hu
- School of Mathematical Sciences, Institute of Statistical Sciences, Shenzhen University, Shenzhen 518060, China; Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China; Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China
| | - Mingxuan Cai
- Department of Biostatistics, City University of Hong Kong, Hong Kong, China
| | - Jiashun Xiao
- Shenzhen Research Institute of Big Data, Shenzhen 518172, China
| | - Xiaomeng Wan
- Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China; Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China
| | - Zhiwei Wang
- Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China; Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.
| | - Can Yang
- Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China; Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China; Big Data Bio-Intelligence Lab, The Hong Kong University of Science and Technology, Hong Kong SAR, China.
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Aykanat T, Jacobsen JA, Hindar K. Ontogenetic variation in the marine foraging of Atlantic salmon functionally links genomic diversity with a major life history polymorphism. Mol Ecol 2024; 33:e17465. [PMID: 38994907 DOI: 10.1111/mec.17465] [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: 03/07/2024] [Revised: 06/26/2024] [Accepted: 07/01/2024] [Indexed: 07/13/2024]
Abstract
The ecological role of heritable phenotypic variation in free-living populations remains largely unknown. Knowledge of the genetic basis of functional ecological processes can link genomic and phenotypic diversity, providing insight into polymorphism evolution and how populations respond to environmental changes. By quantifying the marine diet of Atlantic salmon, we assessed how foraging behaviour changes along the ontogeny, and in relation to genetic variation in two loci with major effects on age at maturity (six6 and vgll3). We used a two-component, zero-inflated negative binomial model to simultaneously quantify foraging frequency and foraging outcome, separately for fish and crustaceans diets. We found that older salmon forage for both prey types more actively (as evidenced by increased foraging frequency), but with a decreased efficiency (as evidenced by fewer prey in the diet), suggesting an age-dependent shift in foraging dynamics. The vgll3 locus was linked to age-dependent changes in foraging behaviour: Younger salmon with vgll3LL (the genotype associated with late maturation) tended to forage crustaceans more often than those with vgll3EE (the genotype associated with early maturation), whereas the pattern was reversed in older salmon. Vgll3 LL genotype was also linked to a marginal increase in fish acquisition, especially in younger salmon, while six6 was not a factor explaining the diet variation. Our results suggest a functional role for marine feeding behaviour linking genomic diversity at vgll3 with age at maturity among salmon, with potential age-dependent trade-offs maintaining the genetic variation. A shared genetic basis between dietary ecology and age at maturity likely subjects Atlantic salmon populations to evolution induced by bottom-up changes in marine productivity.
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Affiliation(s)
- Tutku Aykanat
- Organismal and Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
| | | | - Kjetil Hindar
- Norwegian Institute for Nature Research (NINA), Trondheim, Norway
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16
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Wang Y, Ren J, Luo B. The association between dietary, physical activity and the DNA methylation of PPARGC1A, HLA-DQA1 and ADCY3 in pregnant women with gestational diabetes mellitus: a nest case-control study. BMC Pregnancy Childbirth 2024; 24:503. [PMID: 39060963 PMCID: PMC11282794 DOI: 10.1186/s12884-024-06673-y] [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: 09/13/2023] [Accepted: 07/02/2024] [Indexed: 07/28/2024] Open
Abstract
BACKGROUND Gestational diabetes mellitus (GDM) is associated with DNA methylation and lifestyle. The effects of DNA methylation on GDM, and the interaction between DNA methylation and lifestyle factors are not well elucidated. The objective of this study was to explore the association between GDM, DNA methylation and lifestyle factors. METHODS A nest case-control design was performed. Sociodemographic data, dietary intake and daily physical activity information of pregnant women were collected. Bisulfate pyrosequencing was used to detect the DNA methylation level of PPARGC1A, HLA-DQA1, and ADCY3 genes. The differences of DNA methylation levels between the GDM group and the control group were compared. The correlation between clinical characteristics, dietary, physical activity and DNA methylation level was analyzed. RESULTS A total of 253 pregnant women were enrolled, of which, 60 participants (GDM: 30; control: 30) were included in the final analysis. There were no significant differences in DNA methylation levels of six methylated sites between the two groups in this study (P > 0.05). Daily intake of potato and poultry were associated with DNA methylation level of the CpG 1 site of the ADCY3 gene in all participants and the control group (P < 0.05). Duration of folic acid intake before pregnancy was correlated with the methylation level of the CpG 1 site of the ADCY3 gene in all participants (r = 0.341, P = 0.04) and the control group (r = 0.431, P = 0.025). Daily oil intake was correlated with the methylation level of CpG 2 (r = 0.627, P = 0.016) and CpG 3 (r = 0.563, P = 0.036) of PPARGC1A in the GDM group. CONCLUSION The association between the DNA methylation levels and GDM wasn't validated. There were associations between dietary and DNA methylation in pregnant women. A large-sample-sized and longitudinal study is warranted to further investigate the impacts of lifestyle on DNA methylation.
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Affiliation(s)
- Yan Wang
- Department of Reproductive Medicine Nursing, West China Second University Hospital, Sichuan University, Chengdu, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
| | - Jianhua Ren
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
- Department of Obstetrics and Gynecology Nursing, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Biru Luo
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China.
- Department of Nursing, West China Second University Hospital, Sichuan University, Chengdu, China.
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Ramírez-Luzuriaga MJ, Kobes S, Hsueh WC, Baier LJ, Hanson RL. Novel signals and polygenic score for height are associated with pubertal growth traits in Southwestern American Indians. Hum Mol Genet 2024; 33:981-990. [PMID: 38483351 PMCID: PMC11466845 DOI: 10.1093/hmg/ddae030] [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: 10/13/2023] [Revised: 02/02/2024] [Accepted: 02/16/2024] [Indexed: 05/20/2024] Open
Abstract
Most genetic variants associated with adult height have been identified through large genome-wide association studies (GWASs) in European-ancestry cohorts. However, it is unclear how these variants influence linear growth during adolescence. This study uses anthropometric and genotypic data from a longitudinal study conducted in an American Indian community in Arizona between 1965-2007. Growth parameters (i.e. height, velocity, and timing of growth spurt) were derived from the Preece-Baines growth model, a parametric growth curve fitted to longitudinal height data, in 787 participants with height measurements spanning the whole period of growth. Heritability estimates suggested that genetic factors could explain 25% to 71% of the variance of pubertal growth traits. We performed a GWAS of growth parameters, testing their associations with 5 077 595 imputed or directly genotyped variants. Six variants associated with height at peak velocity (P < 5 × 10-8, adjusted for sex, birth year and principal components). Implicated genes include NUDT3, previously associated with adult height, and PACSIN1. Two novel variants associated with duration of growth spurt (P < 5 × 10-8) in LOC105375344, an uncharacterized gene with unknown function. We finally examined the association of growth parameters with a polygenic score for height derived from 9557 single nucleotide polymorphisms (SNPs) identified in the GIANT meta-analysis for which genotypic data were available for the American Indian study population. Height polygenic score was correlated with the magnitude and velocity of height growth that occurred before and at the peak of the adolescent growth spurt, indicating overlapping genetic architecture, with no influence on the timing of adolescent growth.
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Affiliation(s)
- Maria J Ramírez-Luzuriaga
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 1550 E indian School Rd, Phoenix, AZ 85014, United States
| | - Sayuko Kobes
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 1550 E indian School Rd, Phoenix, AZ 85014, United States
| | - Wen-Chi Hsueh
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 1550 E indian School Rd, Phoenix, AZ 85014, United States
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 1550 E indian School Rd, Phoenix, AZ 85014, United States
| | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 1550 E indian School Rd, Phoenix, AZ 85014, United States
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18
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Passero K, Noll JG, Verma SS, Selin C, Hall MA. Longitudinal method comparison: modeling polygenic risk for post-traumatic stress disorder over time in individuals of African and European ancestry. Front Genet 2024; 15:1203577. [PMID: 38818035 PMCID: PMC11137250 DOI: 10.3389/fgene.2024.1203577] [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: 04/11/2023] [Accepted: 04/15/2024] [Indexed: 06/01/2024] Open
Abstract
Cross-sectional data allow the investigation of how genetics influence health at a single time point, but to understand how the genome impacts phenotype development, one must use repeated measures data. Ignoring the dependency inherent in repeated measures can exacerbate false positives and requires the utilization of methods other than general or generalized linear models. Many methods can accommodate longitudinal data, including the commonly used linear mixed model and generalized estimating equation, as well as the less popular fixed-effects model, cluster-robust standard error adjustment, and aggregate regression. We simulated longitudinal data and applied these five methods alongside naïve linear regression, which ignored the dependency and served as a baseline, to compare their power, false positive rate, estimation accuracy, and precision. The results showed that the naïve linear regression and fixed-effects models incurred high false positive rates when analyzing a predictor that is fixed over time, making them unviable for studying time-invariant genetic effects. The linear mixed models maintained low false positive rates and unbiased estimation. The generalized estimating equation was similar to the former in terms of power and estimation, but it had increased false positives when the sample size was low, as did cluster-robust standard error adjustment. Aggregate regression produced biased estimates when predictor effects varied over time. To show how the method choice affects downstream results, we performed longitudinal analyses in an adolescent cohort of African and European ancestry. We examined how developing post-traumatic stress symptoms were predicted by polygenic risk, traumatic events, exposure to sexual abuse, and income using four approaches-linear mixed models, generalized estimating equations, cluster-robust standard error adjustment, and aggregate regression. While the directions of effect were generally consistent, coefficient magnitudes and statistical significance differed across methods. Our in-depth comparison of longitudinal methods showed that linear mixed models and generalized estimating equations were applicable in most scenarios requiring longitudinal modeling, but no approach produced identical results even if fit to the same data. Since result discrepancies can result from methodological choices, it is crucial that researchers determine their model a priori, refrain from testing multiple approaches to obtain favorable results, and utilize as similar as possible methods when seeking to replicate results.
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Affiliation(s)
- Kristin Passero
- Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
| | - Jennie G. Noll
- Department of Psychology, Mount Hope Family Center, University of Rochester, Rochester, NY, United States
| | - Shefali Setia Verma
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Claire Selin
- Center for Childhood Deafness, Language, and Learning, Boys Town National Research Hospital, Omaha, NE, United States
| | - Molly A. Hall
- Department of Genetics and Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, United States
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Kess T, Lehnert SJ, Bentzen P, Duffy S, Messmer A, Dempson JB, Newport J, Whidden C, Robertson MJ, Chaput G, Breau C, April J, Gillis C, Kent M, Nugent CM, Bradbury IR. Variable parallelism in the genomic basis of age at maturity across spatial scales in Atlantic Salmon. Ecol Evol 2024; 14:e11068. [PMID: 38584771 PMCID: PMC10995719 DOI: 10.1002/ece3.11068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Accepted: 01/31/2024] [Indexed: 04/09/2024] Open
Abstract
Complex traits often exhibit complex underlying genetic architectures resulting from a combination of evolution from standing variation, hard and soft sweeps, and alleles of varying effect size. Increasingly, studies implicate both large-effect loci and polygenic patterns underpinning adaptation, but the extent that common genetic architectures are utilized during repeated adaptation is not well understood. Sea age or age at maturation represents a significant life history trait in Atlantic Salmon (Salmo salar), the genetic basis of which has been studied extensively in European Atlantic populations, with repeated identification of large-effect loci. However, the genetic basis of sea age within North American Atlantic Salmon populations remains unclear, as does the potential for a parallel trans-Atlantic genomic basis to sea age. Here, we used a large single-nucleotide polymorphism (SNP) array and low-coverage whole-genome resequencing to explore the genomic basis of sea age variation in North American Atlantic Salmon. We found significant associations at the gene and SNP level with a large-effect locus (vgll3) previously identified in European populations, indicating genetic parallelism, but found that this pattern varied based on both sex and geographic region. We also identified nonrepeated sets of highly predictive loci associated with sea age among populations and sexes within North America, indicating polygenicity and low rates of genomic parallelism. Despite low genome-wide parallelism, we uncovered a set of conserved molecular pathways associated with sea age that were consistently enriched among comparisons, including calcium signaling, MapK signaling, focal adhesion, and phosphatidylinositol signaling. Together, our results indicate parallelism of the molecular basis of sea age in North American Atlantic Salmon across large-effect genes and molecular pathways despite population-specific patterns of polygenicity. These findings reveal roles for both contingency and repeated adaptation at the molecular level in the evolution of life history variation.
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Affiliation(s)
- Tony Kess
- Northwest Atlantic Fisheries CentreFisheries and Oceans CanadaSt. John'sNewfoundland and LabradorCanada
| | - Sarah J. Lehnert
- Northwest Atlantic Fisheries CentreFisheries and Oceans CanadaSt. John'sNewfoundland and LabradorCanada
| | - Paul Bentzen
- Department of BiologyDalhousie UniversityHalifaxNova ScotiaCanada
| | - Steven Duffy
- Northwest Atlantic Fisheries CentreFisheries and Oceans CanadaSt. John'sNewfoundland and LabradorCanada
| | - Amber Messmer
- Northwest Atlantic Fisheries CentreFisheries and Oceans CanadaSt. John'sNewfoundland and LabradorCanada
| | - J. Brian Dempson
- Northwest Atlantic Fisheries CentreFisheries and Oceans CanadaSt. John'sNewfoundland and LabradorCanada
| | - Jason Newport
- Marine Environmental Research Infrastructure for Data Integration and Application NetworkHalifaxNova ScotiaCanada
| | | | - Martha J. Robertson
- Northwest Atlantic Fisheries CentreFisheries and Oceans CanadaSt. John'sNewfoundland and LabradorCanada
| | - Gerald Chaput
- Fisheries and Oceans CanadaGulf Fisheries CentreMonctonNew BrunswickCanada
| | - Cindy Breau
- Fisheries and Oceans CanadaGulf Fisheries CentreMonctonNew BrunswickCanada
| | - Julien April
- Ministère des Forêts de la Faune et des ParcsQuebecQuebecCanada
| | - Carole‐Anne Gillis
- Gespe'gewa'gi, Mi'gma'qi, ListugujGespe'gewa'gi Institute of Natural UnderstandingQuebecQuebecCanada
| | - Matthew Kent
- Centre for Integrative GeneticsNorwegian University of Life SciencesÅsNorway
| | - Cameron M. Nugent
- Northwest Atlantic Fisheries CentreFisheries and Oceans CanadaSt. John'sNewfoundland and LabradorCanada
| | - Ian R. Bradbury
- Northwest Atlantic Fisheries CentreFisheries and Oceans CanadaSt. John'sNewfoundland and LabradorCanada
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Chorlian DB, Kamarajan C, Meyers JL, Pandey AK, Zhang J, Kinreich S, Porjesz B. Non-linear development of EEG coherence in adolescents and young adults shown by the analysis of neurophysiological trajectories and their covariance. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.13.584867. [PMID: 38559025 PMCID: PMC10980032 DOI: 10.1101/2024.03.13.584867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
To contribute to the understanding of changes in the factors governing the development of neural connectivity, the developmental structure of EEG coherence in adolescents and young adults was analyzed using the means, variances, and covariances of high alpha frequency band coherence measures from a set of 27 coherence pairs obtained from a sample of 1426 participants from the COGA study with 5006 observations over ages 12 through 31. Means and covariances were calculated at 96 age centers by a LOESS method. In the current study, trajectories of covariance matrices considered as individual units were determined by tensorial analysis: calculation of Riemannian geodesic (non-Euclidean) distances between matrices and application of both linear and non-linear dimension reduction techniques to these distances. Results were evaluated by bootstrap methods. Mean coherence trajectories for males and females were very similar, showing a steady upward trend from ages 12 to 20 which diminishes gradually from 20 to 25 and reaches stability from 25 to 31. In contrast, the individual covariance trajectories of males and female differed, with the male covariance levels becoming greater than that of females during the developmental process. Tensorial determination of the distances from the initial covariance matrix of subsequent covariance matrices to age 20 had the same trajectory as the mean coherence values. Tensorial determination of the trajectories of the covariance matrices of males and females based on their all pairs geodesic distances revealed a non-linear pattern in the multi-dimensional space of each of the trajectories: A steady increase in one dimension is accompanied by deviations from it peaking at age 20 which have both transient and lasting effects. There is a precise temporal parallelism of this pattern of covariance in males and females, while there is a consistent distance between the male and female covariance structures throughout the developmental process. Between region differences (anterior-posterior) within each sex are greater than between sex differences within regions. Examining development using multiple methods provides unique insight into the developmental process.
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21
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Marceau K, Loviska AM, Horvath G, Knopik VS. Interactions Between Genetic, Prenatal Substance Use, Puberty, and Parenting are Less Important for Understanding Adolescents' Internalizing, Externalizing, and Substance Use than Developmental Cascades in Multifactorial Models. Behav Genet 2024; 54:181-195. [PMID: 37840057 PMCID: PMC11373084 DOI: 10.1007/s10519-023-10164-9] [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: 01/24/2023] [Accepted: 10/03/2023] [Indexed: 10/17/2023]
Abstract
This study tested interactions among puberty-related genetic risk, prenatal substance use, harsh discipline, and pubertal timing for the severity and directionality (i.e., differentiation) of externalizing and internalizing problems and adolescent substance use. This is a companion paper to Marceau et al. (2021) which examined the same influences in developmental cascade models. Data were from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort (n = 4504 White boys, n = 4287 White girls assessed from the prenatal period through 18.5 years). We hypothesized generally that later predictors would strengthen the influence of puberty-related genetic risk, prenatal substance use exposure, and pubertal risk on psychopathology and substance use (two-way interactions), and that later predictors would strengthen the interactions of earlier influences on psychopathology and substance use (three-way interactions). Interactions were sparse. Although all fourteen interactions showed that later influences can exacerbate or trigger the effects of earlier ones, they often were not in the expected direction. The most robust moderator was parental discipline, and differing and synergistic effects of biological and socially-relevant aspects of puberty were found. In all, the influences examined here operate more robustly in developmental cascades than in interaction with each other for the development of psychopathology and transitions to substance use.
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Affiliation(s)
- Kristine Marceau
- Purdue University, 225 Hanley Hall, 1202 Mitch Daniels Blvd, West Lafayette, IN, 47907, USA.
| | - Amy M Loviska
- Purdue University, 225 Hanley Hall, 1202 Mitch Daniels Blvd, West Lafayette, IN, 47907, USA
| | - Gregor Horvath
- Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
| | - Valerie S Knopik
- Purdue University, 225 Hanley Hall, 1202 Mitch Daniels Blvd, West Lafayette, IN, 47907, USA
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22
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Reshetnikov E, Churnosova M, Reshetnikova Y, Stepanov V, Bocharova A, Serebrova V, Trifonova E, Ponomarenko I, Sorokina I, Efremova O, Orlova V, Batlutskaya I, Ponomarenko M, Churnosov V, Aristova I, Polonikov A, Churnosov M. Maternal Age at Menarche Genes Determines Fetal Growth Restriction Risk. Int J Mol Sci 2024; 25:2647. [PMID: 38473894 PMCID: PMC10932237 DOI: 10.3390/ijms25052647] [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: 12/27/2023] [Revised: 02/06/2024] [Accepted: 02/14/2024] [Indexed: 03/14/2024] Open
Abstract
We aimed to explore the potential link of maternal age at menarche (mAAM) gene polymorphisms with risk of the fetal growth restriction (FGR). This case (FGR)-control (FGR free) study included 904 women (273 FGR and 631 control) in the third trimester of gestation examined/treated in the Departments of Obstetrics. For single nucleotide polymorphism (SNP) multiplex genotyping, 50 candidate loci of mAAM were chosen. The relationship of mAAM SNPs and FGR was appreciated by regression procedures (logistic/model-based multifactor dimensionality reduction [MB-MDR]) with subsequent in silico assessment of the assumed functionality pithy of FGR-related loci. Three mAAM-appertain loci were FGR-linked to genes such as KISS1 (rs7538038) (effect allele G-odds ratio (OR)allelic = 0.63/pperm = 0.0003; ORadditive = 0.61/pperm = 0.001; ORdominant = 0.56/pperm = 0.001), NKX2-1 (rs999460) (effect allele A-ORallelic = 1.37/pperm = 0.003; ORadditive = 1.45/pperm = 0.002; ORrecessive = 2.41/pperm = 0.0002), GPRC5B (rs12444979) (effect allele T-ORallelic = 1.67/pperm = 0.0003; ORdominant = 1.59/pperm = 0.011; ORadditive = 1.56/pperm = 0.009). The haplotype ACA FSHB gene (rs555621*rs11031010*rs1782507) was FRG-correlated (OR = 0.71/pperm = 0.05). Ten FGR-implicated interworking models were founded for 13 SNPs (pperm ≤ 0.001). The rs999460 NKX2-1 and rs12444979 GPRC5B interplays significantly influenced the FGR risk (these SNPs were present in 50% of models). FGR-related mAAM-appertain 15 polymorphic variants and 350 linked SNPs were functionally momentous in relation to 39 genes participating in the regulation of hormone levels, the ovulation cycle process, male gonad development and vitamin D metabolism. Thus, this study showed, for the first time, that the mAAM-appertain genes determine FGR risk.
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Affiliation(s)
- Evgeny Reshetnikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
| | - Maria Churnosova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
| | - Yuliya Reshetnikova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
| | - Vadim Stepanov
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia; (V.S.); (A.B.); (V.S.); (E.T.)
| | - Anna Bocharova
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia; (V.S.); (A.B.); (V.S.); (E.T.)
| | - Victoria Serebrova
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia; (V.S.); (A.B.); (V.S.); (E.T.)
| | - Ekaterina Trifonova
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia; (V.S.); (A.B.); (V.S.); (E.T.)
| | - Irina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
| | - Inna Sorokina
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
| | - Olga Efremova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
| | - Valentina Orlova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
| | - Irina Batlutskaya
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
| | - Marina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
| | - Vladimir Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
| | - Inna Aristova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
| | - Alexey Polonikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
- Department of Biology, Medical Genetics and Ecology and Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (E.R.); (M.C.); (Y.R.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (I.A.); (A.P.)
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23
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Li T, Jin M, Wang H, Zhang W, Yuan Z, Wei C. Whole-Genome Scanning for Selection Signatures Reveals Candidate Genes Associated with Growth and Tail Length in Sheep. Animals (Basel) 2024; 14:687. [PMID: 38473071 DOI: 10.3390/ani14050687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 02/10/2024] [Accepted: 02/18/2024] [Indexed: 03/14/2024] Open
Abstract
Compared to Chinese indigenous sheep, Western sheep have rapid growth rate, larger physique, and higher meat yield. These excellent Western sheep were introduced into China for crossbreeding to expedite the enhancement of production performance and mutton quality in local breeds. Here, we investigated population genetic structure and genome-wide selection signatures among the Chinese indigenous sheep and the introduced sheep based on whole-genome resequencing data. The PCA, N-J tree and ADMIXTURE results showed significant genetic difference between Chinese indigenous sheep and introduced sheep. The nucleotide diversity (π) and linkage disequilibrium (LD) decay results indicated that the genomic diversity of introduced breeds were lower. Then, Fst & π ratio, XP-EHH, and de-correlated composite of multiple signals (DCMS) methods were used to detect the selection signals. The results showed that we identified important candidate genes related to growth rate and body size in the introduced breeds. Selected genes with stronger selection signatures are associated with growth rate (CRADD), embryonic development (BVES, LIN28B, and WNT11), body size (HMGA2, MSRB3, and PTCH1), muscle development and fat metabolism (MSTN, PDE3A, LGALS12, GGPS1, and SAR1B), wool color (ASIP), and hair development (KRT71, KRT74, and IRF2BP2). Thus, these genes have the potential to serve as candidate genes for enhancing the growth traits of Chinese indigenous sheep. We also identified tail-length trait-related candidate genes (HOXB13, LIN28A, PAX3, and VEGFA) in Chinese long-tailed breeds. Among these genes, HOXB13 is the main candidate gene for sheep tail length phenotype. LIN28A, PAX3, and VEGFA are related to embryonic development and angiogenesis, so these genes may be candidate genes for sheep tail type traits. This study will serve as a foundation for further genetic improvement of Chinese indigenous sheep and as a reference for studies related to growth and development of sheep.
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Affiliation(s)
- Taotao Li
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Meilin Jin
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Huihua Wang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Wentao Zhang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Zehu Yuan
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education, Yangzhou University, Yangzhou 225009, China
| | - Caihong Wei
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
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24
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Bradfield JP, Kember RL, Ulrich A, Balkhiyarova Z, Alyass A, Aris IM, Bell JA, Broadaway KA, Chen Z, Chai JF, Davies NM, Fernandez-Orth D, Bustamante M, Fore R, Ganguli A, Heiskala A, Hottenga JJ, Íñiguez C, Kobes S, Leinonen J, Lowry E, Lyytikainen LP, Mahajan A, Pitkänen N, Schnurr TM, Have CT, Strachan DP, Thiering E, Vogelezang S, Wade KH, Wang CA, Wong A, Holm LA, Chesi A, Choong C, Cruz M, Elliott P, Franks S, Frithioff-Bøjsøe C, Gauderman WJ, Glessner JT, Gilsanz V, Griesman K, Hanson RL, Kaakinen M, Kalkwarf H, Kelly A, Kindler J, Kähönen M, Lanca C, Lappe J, Lee NR, McCormack S, Mentch FD, Mitchell JA, Mononen N, Niinikoski H, Oken E, Pahkala K, Sim X, Teo YY, Baier LJ, van Beijsterveldt T, Adair LS, Boomsma DI, de Geus E, Guxens M, Eriksson JG, Felix JF, Gilliland FD, Biobank PM, Hansen T, Hardy R, Hivert MF, Holm JC, Jaddoe VWV, Järvelin MR, Lehtimäki T, Mackey DA, Meyre D, Mohlke KL, Mykkänen J, Oberfield S, Pennell CE, Perry JRB, Raitakari O, Rivadeneira F, Saw SM, Sebert S, Shepherd JA, Standl M, Sørensen TIA, Timpson NJ, Torrent M, Willemsen G, Hypponen E, Power C, McCarthy MI, Freathy RM, Widén E, et alBradfield JP, Kember RL, Ulrich A, Balkhiyarova Z, Alyass A, Aris IM, Bell JA, Broadaway KA, Chen Z, Chai JF, Davies NM, Fernandez-Orth D, Bustamante M, Fore R, Ganguli A, Heiskala A, Hottenga JJ, Íñiguez C, Kobes S, Leinonen J, Lowry E, Lyytikainen LP, Mahajan A, Pitkänen N, Schnurr TM, Have CT, Strachan DP, Thiering E, Vogelezang S, Wade KH, Wang CA, Wong A, Holm LA, Chesi A, Choong C, Cruz M, Elliott P, Franks S, Frithioff-Bøjsøe C, Gauderman WJ, Glessner JT, Gilsanz V, Griesman K, Hanson RL, Kaakinen M, Kalkwarf H, Kelly A, Kindler J, Kähönen M, Lanca C, Lappe J, Lee NR, McCormack S, Mentch FD, Mitchell JA, Mononen N, Niinikoski H, Oken E, Pahkala K, Sim X, Teo YY, Baier LJ, van Beijsterveldt T, Adair LS, Boomsma DI, de Geus E, Guxens M, Eriksson JG, Felix JF, Gilliland FD, Biobank PM, Hansen T, Hardy R, Hivert MF, Holm JC, Jaddoe VWV, Järvelin MR, Lehtimäki T, Mackey DA, Meyre D, Mohlke KL, Mykkänen J, Oberfield S, Pennell CE, Perry JRB, Raitakari O, Rivadeneira F, Saw SM, Sebert S, Shepherd JA, Standl M, Sørensen TIA, Timpson NJ, Torrent M, Willemsen G, Hypponen E, Power C, McCarthy MI, Freathy RM, Widén E, Hakonarson H, Prokopenko I, Voight BF, Zemel BS, Grant SFA, Cousminer DL. Trans-ancestral genome-wide association study of longitudinal pubertal height growth and shared heritability with adult health outcomes. Genome Biol 2024; 25:22. [PMID: 38229171 PMCID: PMC10790528 DOI: 10.1186/s13059-023-03136-z] [Show More Authors] [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: 02/19/2023] [Accepted: 11/30/2023] [Indexed: 01/18/2024] Open
Abstract
BACKGROUND Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analyses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank. RESULTS Large-scale growth modeling enables an unprecedented view of adolescent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide significant loci and leverage trans-ancestry data to perform fine-mapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with different growth trajectories correlated with different outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fibrillation. CONCLUSION We report novel genetic associations with the tempo of pubertal growth and find that genetic determinants of growth are correlated with reproductive, glycemic, respiratory, and cardiac traits in adulthood. These results aid in identifying specific growth trajectories impacting lifelong health and show that there may not be a single "optimal" pubertal growth pattern.
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Affiliation(s)
- Jonathan P Bradfield
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Rachel L Kember
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Anna Ulrich
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Zhanna Balkhiyarova
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK
| | - Akram Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Joshua A Bell
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Zhanghua Chen
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90032, USA
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Neil M Davies
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Ruby Fore
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Amitavo Ganguli
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Anni Heiskala
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Carmen Íñiguez
- Department of Statistics and Computational Research, Universitat de València, Valencia, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain
| | - Sayuko Kobes
- Phoenix Epidemiology and Clinical Research Center, NIDDK, NIH, Bethesda, USA
| | - Jaakko Leinonen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Estelle Lowry
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Leo-Pekka Lyytikainen
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, 33521, Tampere, Finland
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Theresia M Schnurr
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Christian Theil Have
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - David P Strachan
- Population Health Research Institute, St George's, University of London, Cranmer Terrace, London, SW17 0RE, UK
| | - Elisabeth Thiering
- Institute of Epidemiology, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
- Division of Metabolic and Nutritional Medicine, Dr. Von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany
| | - Suzanne Vogelezang
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Kaitlin H Wade
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Carol A Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, University of Newcastle, Callaghan, NSW, 2308, Australia
- Hunter Medical Research Institute, Newcastle, NSW, 2305, Australia
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Louise Aas Holm
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, The Children's Obesity Clinic, Copenhagen University Hospital Holbæk, Holbæk, Denmark
| | - Alessandra Chesi
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Catherine Choong
- Faculty of Health and Medical Sciences, University of Western Australia, Perth, WA, Australia
| | - Miguel Cruz
- Unidad de Investigación Médica en Bioquímica, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Paul Elliott
- MRC Centre for Environment and Health, School of Public Health, Faculty of Medicine, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Steve Franks
- Institute of Reproductive & Developmental Biology, Imperial College London, London, UK
| | - Christine Frithioff-Bøjsøe
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, The Children's Obesity Clinic, Copenhagen University Hospital Holbæk, Holbæk, Denmark
| | - W James Gauderman
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90032, USA
| | - Joseph T Glessner
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Vicente Gilsanz
- Center for Endocrinology, Diabetes & Metabolism, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | | | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Center, NIDDK, NIH, Bethesda, USA
| | - Marika Kaakinen
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- Institute of Reproductive & Developmental Biology, Imperial College London, London, UK
| | - Heidi Kalkwarf
- Department of Pediatrics, Cincinnati Children's Hospital, University of Cincinnati, Cincinnati, OH, USA
| | - Andrea Kelly
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Endocrinology & Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Joseph Kindler
- College of Family and Consumer Sciences, University of Georgia, Athens, GA, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, 33521, Tampere, Finland
| | - Carla Lanca
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Joan Lappe
- Department of Medicine and College of Nursing, Creighton University School of Medicine, Omaha, NB, USA
| | - Nanette R Lee
- USC-Office of Population Studies Foundation, Inc, University of San Carlos, Cebu, Philippines
| | - Shana McCormack
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Endocrinology & Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Frank D Mentch
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Jonathan A Mitchell
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Gastroenterology, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Nina Mononen
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center - Tampere, Tampere University, 33014, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, 33520, Tampere, Finland
| | - Harri Niinikoski
- Department of Pediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland
- Department of Physiology, University of Turku, Turku, Finland
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
- Department of Nutrition, Harvard T.H Chan School of Public Health, Boston, MA, 02115, USA
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Paavo Nurmi Centre, Unit for Health and Physical Activity, University of Turku, Turku, Finland
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Center, NIDDK, NIH, Bethesda, USA
| | - Toos van Beijsterveldt
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Linda S Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
| | - Eco de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Mònica Guxens
- ISGlobal, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Johan G Eriksson
- Institute of Clinical Medicine Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
- Department of Obstetrics & Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Frank D Gilliland
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90032, USA
| | | | - Torben Hansen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Rebecca Hardy
- Cohort and Longitudinal Studies Enhancement Resources (CLOSER), UCL Institute of Education, London, UK
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Jens-Christian Holm
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Pediatrics, The Children's Obesity Clinic, Copenhagen University Hospital Holbæk, Holbæk, Denmark
- The Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
- Unit of Primary Health Care, Oulu University Hospital, OYS, Kajaanintie 50, 90220, Oulu, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center - Tampere, Tampere University, 33014, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, 33520, Tampere, Finland
| | - David A Mackey
- Lions Eye Institute, Centre for Ophthalmology and Visual Science, Centre for Eye Research Australia, University of Western Australia, Perth, WA, Australia
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
- Inserm UMR_S1256 Nutrition-Genetics-Environmental Risk Exposure, University of Lorraine, Nancy, France
- Department of Biochemistry-Molecular Biology-Nutrition, University Hospital Centre of Nancy, Nancy, France
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Juha Mykkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Sharon Oberfield
- Division of Pediatric Endocrinology, Columbia University Medical Center, New York, NY, USA
| | - Craig E Pennell
- School of Medicine and Public Health, Faculty of Medicine and Health, University of Newcastle, Callaghan, NSW, 2308, Australia
- Hunter Medical Research Institute, Newcastle, NSW, 2305, Australia
- Department of Maternity and Gynaecology, John Hunter Hospital, Newcastle, NSW, 2305, Australia
| | - John R B Perry
- Metabolic Research Laboratory, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
- MRC Epidemiology Unit, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Seang-Mei Saw
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
| | - John A Shepherd
- Department of Epidemiology and Population Science, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Marie Standl
- Institute of Epidemiology, Helmholtz Zentrum München- German Research Center for Environmental Health, Neuherberg, Germany
| | - Thorkild I A Sørensen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Maties Torrent
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Fundació Institut d'Investigació Sanitària Illes Balears - IdISBa, Palma, Spain
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Elina Hypponen
- UCL Great Ormond Street Institute of Child Health, London, UK
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Chris Power
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Current Address: Genentech, 1 DNA Way, San Francisco, CA, 94080, USA
| | - Rachel M Freathy
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, EX2 5DW, UK
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Inga Prokopenko
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK
- UMR 8199 - EGID, Institut Pasteur de Lille, CNRS, University of Lille, 59000, Lille, France
| | - Benjamin F Voight
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Babette S Zemel
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Division of Gastroenterology, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Struan F A Grant
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
- Division of Endocrinology & Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
| | - Diana L Cousminer
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Currently Employed By GlaxoSmithKline, 1250 S Collegeville Rd, Collegeville, PA, 19426, USA.
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25
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Ghanbari F, Otomo N, Gamache I, Iwami T, Koike Y, Khanshour AM, Ikegawa S, Wise CA, Terao C, Manousaki D. Interrogating Causal Effects of Body Composition and Puberty-Related Risk Factors on Adolescent Idiopathic Scoliosis: A Two-Sample Mendelian Randomization Study. JBMR Plus 2023; 7:e10830. [PMID: 38130750 PMCID: PMC10731118 DOI: 10.1002/jbm4.10830] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 09/18/2023] [Accepted: 09/20/2023] [Indexed: 12/23/2023] Open
Abstract
Adolescent idiopathic scoliosis (AIS) is the most common form of pediatric musculoskeletal disorder. Observational studies have pointed to several risk factors for AIS, but almost no evidence exists to support their causal association with AIS. Here, we applied Mendelian randomization (MR), known to limit bias from confounding and reverse causation, to investigate causal associations between body composition and puberty-related exposures and AIS risk in Europeans and Asians. For our two-sample MR studies, we used single nucleotide polymorphisms (SNPs) associated with body mass index (BMI), waist-hip ratio, lean mass, childhood obesity, bone mineral density (BMD), 25-hydroxyvitamin D (25OHD), age at menarche, and pubertal growth in large European genome-wide association studies (GWAS), and with adult osteoporosis risk and age of menarche in Biobank Japan. We extracted estimates of the aforementioned SNPs on AIS risk from the European or Asian subsets of the largest multiancestry AIS GWAS (N = 7956 cases/88,459 controls). The results of our inverse variance-weighted (IVW) MR estimates suggest no causal association between the aforementioned risk factors and risk of AIS. Pleiotropy-sensitive MR methods yielded similar results. However, restricting our analysis to European females with AIS, we observed a causal association between estimated BMD and the risk of AIS (IVW odds ratio for AIS = 0.1, 95% confidence interval 0.01 to 0.7, p = 0.02 per SD increase in estimated BMD), but this association was no longer significant after adjusting for BMI, body fat mass, and 25OHD and remained significant after adjusting for age at menarche in multivariable MR. In conclusion, we demonstrated a protective causal effect of BMD on AIS risk in females of European ancestry, but this effect was modified by BMI, body fat mass, and 25OHD levels. Future MR studies using larger AIS GWAS are needed to investigate small effects of the aforementioned exposures on AIS. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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Affiliation(s)
- Faegheh Ghanbari
- Research Center of the Sainte‐Justine University HospitalUniversity of MontrealMontrealQuebecCanada
| | - Nao Otomo
- Laboratory for Statistical and Translational GeneticsRIKEN Center for Integrative Medical Sciences, RIKENYokohamaJapan
- Department of Orthopedic SurgeryKeio University School of MedicineTokyoJapan
| | - Isabel Gamache
- Research Center of the Sainte‐Justine University HospitalUniversity of MontrealMontrealQuebecCanada
| | - Takuro Iwami
- Laboratory for Statistical and Translational GeneticsRIKEN Center for Integrative Medical Sciences, RIKENYokohamaJapan
- Department of Orthopedic SurgeryKeio University School of MedicineTokyoJapan
| | - Yoshinao Koike
- Laboratory for Statistical and Translational GeneticsRIKEN Center for Integrative Medical Sciences, RIKENYokohamaJapan
- Department of Orthopedic SurgeryHokkaido University Graduate School of MedicineSapporoJapan
| | - Anas M. Khanshour
- Scottish Rite for Children Center for Pediatric Bone Biology and Translational ResearchDallasTexasUSA
| | - Shiro Ikegawa
- Laboratory for Statistical and Translational GeneticsRIKEN Center for Integrative Medical Sciences, RIKENYokohamaJapan
| | - Carol A. Wise
- Scottish Rite for Children Center for Pediatric Bone Biology and Translational ResearchDallasTexasUSA
- McDermott Center for Human Growth & DevelopmentUniversity of Texas Southwestern Medical CenterDallasTexasUSA
| | - Chikashi Terao
- Laboratory for Statistical and Translational GeneticsRIKEN Center for Integrative Medical Sciences, RIKENYokohamaJapan
| | - Despoina Manousaki
- Research Center of the Sainte‐Justine University HospitalUniversity of MontrealMontrealQuebecCanada
- Department of PediatricsUniversity of MontrealMontrealCanada
- Department of Biochemistry and Molecular MedicineUniversity of MontrealMontrealQuebecCanada
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26
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Moulistanos A, Nikolaou T, Sismanoglou S, Gkagkavouzis K, Karaiskou N, Antonopoulou E, Triantafyllidis A, Papakostas S. Investigating the role of genetic variation in vgll3 and six6 in the domestication of gilthead seabream ( Sparus aurata Linnaeus) and European seabass ( Dicentrarchus labrax Linnaeus). Ecol Evol 2023; 13:e10727. [PMID: 38020694 PMCID: PMC10654472 DOI: 10.1002/ece3.10727] [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: 10/04/2023] [Revised: 10/27/2023] [Accepted: 10/27/2023] [Indexed: 12/01/2023] Open
Abstract
Gene function conservation is crucial in molecular ecology, especially for key traits like growth and maturation in teleost fish. The vgll3 and six6 genes are known to influence age-at-maturity in Atlantic salmon, but their impact on other fish species is poorly understood. Here, we investigated the association of vgll3 and six6 in the domestication of gilthead seabream and European seabass, both undergoing selective breeding for growth-related traits in the Mediterranean. We analysed two different sets of samples using two different genotyping approaches. The first dataset comprised farmed and wild populations from Greece, genotyped for SNPs within the two genes ('gene-level genotyping'). The second dataset examined 300-600 k SNPs located in the chromosomes of the two genes, derived from a meta-analysis of a Pool-Seq experiment involving farmed and wild populations distributed widely across the Mediterranean ('chromosome-level genotyping'). The gene-level analysis revealed a statistically significant allele frequency differences between farmed and wild populations on both genes in each species. This finding was partially supported by the chromosome-level analysis, identifying highly differentiated regions may be involved in the domestication process at varying distances from the candidate genes. Noteworthy genomic features were found, such as a CpG island in gilthead seabream and novel candidate genes in European seabass, warranting further investigation. These findings support a putative role of vgll3 and six6 in the maturation and growth of gilthead seabream and European seabass, emphasizing the need for further research on their conserved function.
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Affiliation(s)
- Aristotelis Moulistanos
- Department of Genetics, Development & Molecular Biology, School of Biology, Faculty of ScienceAristotle University of ThessalonikiThessalonikiGreece
- Genomics and Epigenomics Translational Research (GENeTres)Center for Interdisciplinary Research and Innovation (CIRI‐AUTH), Balkan CenterThessalonikiGreece
| | - Theopisti Nikolaou
- Department of Genetics, Development & Molecular Biology, School of Biology, Faculty of ScienceAristotle University of ThessalonikiThessalonikiGreece
| | - Smaragda Sismanoglou
- Department of Genetics, Development & Molecular Biology, School of Biology, Faculty of ScienceAristotle University of ThessalonikiThessalonikiGreece
| | - Konstantinos Gkagkavouzis
- Department of Genetics, Development & Molecular Biology, School of Biology, Faculty of ScienceAristotle University of ThessalonikiThessalonikiGreece
- Genomics and Epigenomics Translational Research (GENeTres)Center for Interdisciplinary Research and Innovation (CIRI‐AUTH), Balkan CenterThessalonikiGreece
| | - Nikoleta Karaiskou
- Department of Genetics, Development & Molecular Biology, School of Biology, Faculty of ScienceAristotle University of ThessalonikiThessalonikiGreece
- Genomics and Epigenomics Translational Research (GENeTres)Center for Interdisciplinary Research and Innovation (CIRI‐AUTH), Balkan CenterThessalonikiGreece
| | - Efthimia Antonopoulou
- Department of Zoology, School of BiologyAristotle University of ThessalonikiThessalonikiGreece
| | - Alexandros Triantafyllidis
- Department of Genetics, Development & Molecular Biology, School of Biology, Faculty of ScienceAristotle University of ThessalonikiThessalonikiGreece
- Genomics and Epigenomics Translational Research (GENeTres)Center for Interdisciplinary Research and Innovation (CIRI‐AUTH), Balkan CenterThessalonikiGreece
| | - Spiros Papakostas
- Department of Science and TechnologyInternational Hellenic UniversityThessalonikiGreece
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27
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Reshetnikova Y, Churnosova M, Stepanov V, Bocharova A, Serebrova V, Trifonova E, Ponomarenko I, Sorokina I, Efremova O, Orlova V, Batlutskaya I, Ponomarenko M, Churnosov V, Eliseeva N, Aristova I, Polonikov A, Reshetnikov E, Churnosov M. Maternal Age at Menarche Gene Polymorphisms Are Associated with Offspring Birth Weight. Life (Basel) 2023; 13:1525. [PMID: 37511900 PMCID: PMC10381708 DOI: 10.3390/life13071525] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/29/2023] [Accepted: 07/05/2023] [Indexed: 07/30/2023] Open
Abstract
In this study, the association between maternal age at menarche (AAM)-related polymorphisms and offspring birth weight (BW) was studied. The work was performed on a sample of 716 pregnant women and their newborns. All pregnant women underwent genotyping of 50 SNPs of AAM candidate genes. Regression methods (linear and Model-Based Multifactor Dimensionality Reduction (MB-MDR)) with permutation procedures (the indicator pperm was calculated) were used to identify the correlation between SNPs and newborn weight (transformed BW values were analyzed) and in silico bioinformatic examination was applied to assess the intended functionality of BW-associated loci. Four AAM-related genetic variants were BW-associated including genes such as POMC (rs7589318) (βadditive = 0.202/pperm = 0.015), KDM3B (rs757647) (βrecessive = 0.323/pperm = 0.005), INHBA (rs1079866) (βadditive = 0.110/pperm = 0.014) and NKX2-1 (rs999460) (βrecessive = -0.176/pperm = 0.015). Ten BW-significant models of interSNPs interactions (pperm ≤ 0.001) were identified for 20 polymorphisms. SNPs rs7538038 KISS1, rs713586 RBJ, rs12324955 FTO and rs713586 RBJ-rs12324955 FTO two-locus interaction were included in the largest number of BW-associated models (30% models each). BW-associated AAM-linked 22 SNPs and 350 proxy loci were functionally related to 49 genes relevant to pathways such as the hormone biosynthesis/process and female/male gonad development. In conclusion, maternal AMM-related genes polymorphism is associated with the offspring BW.
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Affiliation(s)
- Yuliya Reshetnikova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Maria Churnosova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Vadim Stepanov
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia; (V.S.); (A.B.); (V.S.); (E.T.)
| | - Anna Bocharova
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia; (V.S.); (A.B.); (V.S.); (E.T.)
| | - Victoria Serebrova
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia; (V.S.); (A.B.); (V.S.); (E.T.)
| | - Ekaterina Trifonova
- Research Institute for Medical Genetics, Tomsk National Research Medical Center of the Russian Academy of Sciences, 634050 Tomsk, Russia; (V.S.); (A.B.); (V.S.); (E.T.)
| | - Irina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Inna Sorokina
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Olga Efremova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Valentina Orlova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Irina Batlutskaya
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Marina Ponomarenko
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Vladimir Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Natalya Eliseeva
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Inna Aristova
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Alexey Polonikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
- Department of Biology, Medical Genetics and Ecology and Research Institute for Genetic and Molecular Epidemiology, Kursk State Medical University, 305041 Kursk, Russia
| | - Evgeny Reshetnikov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
| | - Mikhail Churnosov
- Department of Medical Biological Disciplines, Belgorod State National Research University, 308015 Belgorod, Russia; (Y.R.); (M.C.); (I.P.); (I.S.); (O.E.); (V.O.); (I.B.); (M.P.); (V.C.); (N.E.); (I.A.); (A.P.); (E.R.)
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28
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Chorlian DB, Meyers JL, Manz N, Zhang J, Kamarajan C, Pandey A, Wang JC, Plawecki M, Edenberg H, Goate A, Tischfield J, Porjesz B. Genetic influences vary by age and sex: Trajectories of the association of cholinergic system variants and theta band event related oscillations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.27.530318. [PMID: 36909650 PMCID: PMC10002625 DOI: 10.1101/2023.02.27.530318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
To characterize systemic changes in genetic effects on brain development, the age variation of the associations of cholinergic genetic variants and theta band event-related oscillations (EROs) was studied in a sample of 2140 adolescents and young adults, ages 12 to 25 from the COGA prospective study. The theta band EROs were elicited in visual and auditory oddball (target detection) tasks and measured by EEG recording. Associations were found to vary with age, sex, task modality (auditory or visual), and scalp locality. Seven of the twenty-one muscarinic and nicotinic cholinergic SNPs studied in the analysis, from CHRM2, CHRNA3, CHRNA5, and CHRNB4, had significant effects on theta band EROs with considerable age spans for some sex-modality combination. No SNP-age-modality combination had significant effects in the same direction for males and females. Results suggest that nicotinic receptor associations are stronger before age 18, while muscarinic receptor associations are stronger after age 18.
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29
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Wang K. Support Interval for Two-Sample Summary Data-Based Mendelian Randomization. Genes (Basel) 2023; 14:211. [PMID: 36672952 PMCID: PMC9859138 DOI: 10.3390/genes14010211] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 12/31/2022] [Accepted: 01/04/2023] [Indexed: 01/18/2023] Open
Abstract
The summary-data-based Mendelian randomization (SMR) method is gaining popularity in estimating the causal effect of an exposure on an outcome. In practice, the instrument SNP is often selected from the genome-wide association study (GWAS) on the exposure but no correction is made for such selection in downstream analysis, leading to a biased estimate of the effect size and invalid inference. We address this issue by using the likelihood derived from the sampling distribution of the estimated SNP effects in the exposure GWAS and the outcome GWAS. This likelihood takes into account how the instrument SNPs are selected. Since the effective sample size is 1, the asymptotic theory does not apply. We use a support for a profile likelihood as an interval estimate of the causal effect. Simulation studies indicate that this support has robust coverage while the confidence interval implied by the SMR method has lower-than-nominal coverage. Furthermore, the variance of the two-stage least squares estimate of the causal effect is shown to be the same as the variance used for SMR for one-sample data when there is no selection.
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Affiliation(s)
- Kai Wang
- Department of Biostatistics, University of Iowa, 145 N Riverside Dr., Iowa City, IA 52242, USA
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30
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Wijesena HR, Nonneman DJ, Snelling WM, Rohrer GA, Keel BN, Lents CA. gBLUP-GWAS identifies candidate genes, signaling pathways, and putative functional polymorphisms for age at puberty in gilts. J Anim Sci 2023; 101:skad063. [PMID: 36848325 PMCID: PMC10016198 DOI: 10.1093/jas/skad063] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 02/27/2023] [Indexed: 03/01/2023] Open
Abstract
Successful development of replacement gilts determines their reproductive longevity and lifetime productivity. Selection for reproductive longevity is challenging due to low heritability and expression late in life. In pigs, age at puberty is the earliest known indicator for reproductive longevity and gilts that reach puberty earlier have a greater probability of producing more lifetime litters. Failure of gilts to reach puberty and display a pubertal estrus is a major reason for early removal of replacement gilts. To identify genomic sources of variation in age at puberty for improving genetic selection for early age at puberty and related traits, gilts (n = 4,986) from a multigeneration population representing commercially available maternal genetic lines were used for a genomic best linear unbiased prediction-based genome-wide association. Twenty-one genome-wide significant single nucleotide polymorphisms (SNP) located on Sus scrofa chromosomes (SSC) 1, 2, 9, and 14 were identified with additive effects ranging from -1.61 to 1.92 d (P < 0.0001 to 0.0671). Novel candidate genes and signaling pathways were identified for age at puberty. The locus on SSC9 (83.7 to 86.7 Mb) was characterized by long range linkage disequilibrium and harbors the AHR transcription factor gene. A second candidate gene on SSC2 (82.7 Mb), ANKRA2, is a corepressor for AHR, suggesting a possible involvement of AHR signaling in regulating pubertal onset in pigs. Putative functional SNP associated with age at puberty in the AHR and ANKRA2 genes were identified. Combined analysis of these SNP showed that an increase in the number of favorable alleles reduced pubertal age by 5.84 ± 1.65 d (P < 0.001). Candidate genes for age at puberty showed pleiotropic effects with other fertility functions such as gonadotropin secretion (FOXD1), follicular development (BMP4), pregnancy (LIF), and litter size (MEF2C). Several candidate genes and signaling pathways identified in this study play a physiological role in the hypothalamic-pituitary-gonadal axis and mechanisms permitting puberty onset. Variants located in or near these genes require further characterization to identify their impact on pubertal onset in gilts. Because age at puberty is an indicator of future reproductive success, these SNP are expected to improve genomic predictions for component traits of sow fertility and lifetime productivity expressed later in life.
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Affiliation(s)
| | - Dan J Nonneman
- Genetics and Animal Breeding Research Unit, USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, USA
| | - Warren M Snelling
- Genetics and Animal Breeding Research Unit, USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, USA
| | - Gary A Rohrer
- Genetics and Animal Breeding Research Unit, USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, USA
| | - Brittney N Keel
- Genetics and Animal Breeding Research Unit, USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, USA
| | - Clay A Lents
- LivestockBio-systems Research Unit, Clay Center, NE, USA
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31
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Saavedra JM, Prentice AM. Nutrition in school-age children: a rationale for revisiting priorities. Nutr Rev 2022:6811793. [PMID: 36346900 DOI: 10.1093/nutrit/nuac089] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Middle childhood and early adolescence have received disproportionately low levels of scientific attention relative to other life stages, especially as related to nutrition and health. This is partly due to the justified emphasis on the first 1000 days of life, and the idea that early deficits and consequences may not be fully reversible. In addition, these stages of life may superficially appear less "eventful" than infancy or late adolescence. Finally, there has been historical ambiguity and inconsistency in terminology, depending on whether viewing "childhood" through physiologic, social, legal, or other lenses. Nevertheless, this age bracket, which encompasses most of the primary education and basic schooling years for most individuals, is marked by significant changes, inflection points, and sexually driven divergence in somatic and brain growth and development trajectories. These constitute transformative changes, and thus middle childhood and early adolescence represents a major and last opportunity to influence long-term health and productivity. This review highlights the specificities of growth and development in school age, with a focus on middle childhood and early adolescence (5 years-15 years of age, for the purposes of this review), the role of nutrition, the short- and long-term consequences of inadequate nutrition, and the current global status of nutrition in this age group. Adequate attention and emphasis on nutrition in the school-age years is critical: (a) for maintaining an adequate course of somatic and cognitive development, (b) for taking advantage of this last major opportunity to correct deficits of undernutrition and "catch-up" to normal life course development, and (c) for addressing the nutritional inadequacies and mitigating the longer-term consequences of overnutrition. This review summarizes and provides a rationale for prioritizing nutrition in school-age children, and for the need to revisit priorities and focus on this part of the life cycle to maximize individuals' potential and their contribution to society.
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Affiliation(s)
- Jose M Saavedra
- with the Division of Gastroenterology and Nutrition, Johns Hopkins University School of Medicine, Baltimore, USA
| | - Andrew M Prentice
- is with the MRC Unit, The Gambia and MRC International Nutrition Group, London School of Hygiene & Tropical Medicine, London, UK
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32
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Niemelä PT, Klemme I, Karvonen A, Hyvärinen P, Debes PV, Erkinaro J, Sinclair-Waters M, Pritchard VL, Härkönen LS, Primmer CR. Life-history genotype explains variation in migration activity in Atlantic salmon ( Salmo salar). Proc Biol Sci 2022; 289:20220851. [PMID: 35858058 PMCID: PMC9277231 DOI: 10.1098/rspb.2022.0851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
One of the most well-known life-history continuums is the fast-slow axis, where 'fast' individuals mature earlier than 'slow' individuals. 'Fast' individuals are predicted to be more active than 'slow' individuals because high activity is required to maintain a fast life-history strategy. Recent meta-analyses revealed mixed evidence for such integration. Here, we test whether known life-history genotypes differ in activity expression by using Atlantic salmon (Salmo salar) as a model. In salmon, variation in Vgll3, a transcription cofactor, explains approximately 40% of variation in maturation timing. We predicted that the allele related to early maturation (vgll3*E) would be associated with higher activity. We used an automated surveillance system to follow approximately 1900 juveniles including both migrants and non-migrants (i.e. smolt and parr fish, respectively) in semi-natural conditions over 31 days (approx. 580 000 activity measurements). In migrants, but not in non-migrants, vgll3 explained variation in activity according to our prediction in a sex-dependent manner. Specifically, in females the vgll3*E allele was related to increasing activity, whereas in males the vgll3*L allele (later maturation allele) was related to increasing activity. These sex-dependent effects might be a mechanism maintaining within-population genetic life-history variation.
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Affiliation(s)
- Petri T. Niemelä
- Organismal and Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
| | - Ines Klemme
- Department of Biological and Environmental Science, University of Jyvaskyla, PO Box 35, 40014 Jyvaskyla, Finland
| | - Anssi Karvonen
- Department of Biological and Environmental Science, University of Jyvaskyla, PO Box 35, 40014 Jyvaskyla, Finland
| | - Pekka Hyvärinen
- Natural Resources Institute Finland (Luke), Migratory fish and regulated rivers, Manamansalontie 90, 88300 Paltamo, Finland
| | - Paul V. Debes
- Organismal and Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland,Institue of Biotechnology, Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Helsinki, Finland,Department of Aquaculture and Fish Biology, Hólar University, Háeyri 1, 550 Sauðárkrókur, Hólar, Iceland
| | - Jaakko Erkinaro
- Natural Resources Institute Finland (Luke), Migratory fish and regulated rivers, Paavo Havaksen tie 3, 90570 Oulu, Finland
| | - Marion Sinclair-Waters
- Organismal and Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
| | - Victoria L. Pritchard
- Organismal and Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland,Rivers and Lochs Institute, Inverness College, University of the Highlands and Islands, Inverness, UK
| | - Laura S. Härkönen
- Natural Resources Institute Finland (Luke), Migratory fish and regulated rivers, Manamansalontie 90, 88300 Paltamo, Finland,Natural Resources Institute Finland (Luke), Migratory fish and regulated rivers, Paavo Havaksen tie 3, 90570 Oulu, Finland
| | - Craig R. Primmer
- Organismal and Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland,Institue of Biotechnology, Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Helsinki, Finland
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33
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Østvold AC, Grundt K, Wiese C. NUCKS1 is a highly modified, chromatin-associated protein involved in a diverse set of biological and pathophysiological processes. Biochem J 2022; 479:1205-1220. [PMID: 35695515 PMCID: PMC10016235 DOI: 10.1042/bcj20220075] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/17/2022] [Accepted: 05/26/2022] [Indexed: 11/17/2022]
Abstract
The Nuclear Casein and Cyclin-dependent Kinase Substrate 1 (NUCKS1) protein is highly conserved in vertebrates, predominantly localized to the nucleus and one of the most heavily modified proteins in the human proteome. NUCKS1 expression is high in stem cells and the brain, developmentally regulated in mice and associated with several diverse malignancies in humans, including cancer, metabolic syndrome and Parkinson's disease. NUCKS1 function has been linked to modulating chromatin architecture and transcription, DNA repair and cell cycle regulation. In this review, we summarize and discuss the published information on NUCKS1 and highlight the questions that remain to be addressed to better understand the complex biology of this multifaceted protein.
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Affiliation(s)
- Anne Carine Østvold
- Institute of Basic Medical Science, Dept. of Biochemistry, University of Oslo, P.O box 1110 Blindern, 0317 Oslo, Norway
| | - Kirsten Grundt
- Institute of Basic Medical Science, Dept. of Biochemistry, University of Oslo, P.O box 1110 Blindern, 0317 Oslo, Norway
| | - Claudia Wiese
- Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, Colorado 80523, USA
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34
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Nguyen LT, Lau LY, Fortes MRS. Proteomic Analysis of Hypothalamus and Pituitary Gland in Pre and Postpubertal Brahman Heifers. Front Genet 2022; 13:935433. [PMID: 35774501 PMCID: PMC9237413 DOI: 10.3389/fgene.2022.935433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 05/25/2022] [Indexed: 11/28/2022] Open
Abstract
The hypothalamus and the pituitary gland are directly involved in the complex systemic changes that drive the onset of puberty in cattle. Here, we applied integrated bioinformatics to elucidate the critical proteins underlying puberty and uncover potential molecular mechanisms from the hypothalamus and pituitary gland of prepubertal (n = 6) and postpubertal (n = 6) cattle. Proteomic analysis in the hypothalamus and pituitary gland revealed 275 and 186 differentially abundant (DA) proteins, respectively (adjusted p-value < 0.01). The proteome profiles found herein were integrated with previously acquired transcriptome profiles. These transcriptomic studies used the same tissues harvested from the same heifers at pre- and post-puberty. This comparison detected a small number of matched transcripts and protein changes at puberty in each tissue, suggesting the need for multiple omics analyses for interpreting complex biological systems. In the hypothalamus, upregulated DA proteins at post-puberty were enriched in pathways related to puberty, including GnRH, calcium and oxytocin signalling pathways, whereas downregulated proteins were observed in the estrogen signalling pathway, axon guidance and GABAergic synapse. Additionally, this study revealed that ribosomal pathway proteins in the pituitary were involved in the pubertal development of mammals. The reported molecules and derived protein-protein networks are a starting point for future experimental approaches that might dissect with more detail the role of each molecule to provide new insights into the mechanisms of puberty onset in cattle.
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Affiliation(s)
- Loan To Nguyen
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Australia
- *Correspondence: Loan To Nguyen,
| | - Li Yieng Lau
- Agency of Science, Technology and Research, Singapore, Singapore
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35
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Silventoinen K, Jelenkovic A, Palviainen T, Dunkel L, Kaprio J. The Association Between Puberty Timing and Body Mass Index in a Longitudinal Setting: The Contribution of Genetic Factors. Behav Genet 2022; 52:186-194. [PMID: 35381915 PMCID: PMC9135891 DOI: 10.1007/s10519-022-10100-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 03/17/2022] [Indexed: 12/11/2022]
Abstract
We analyzed the contribution of genetic factors on the association between puberty timing and body mass index (BMI) using longitudinal data and two approaches: (i) genetic twin design and (ii) polygenic scores (PGS) of obesity indices. Our data were derived from Finnish cohorts: 9080 twins had information on puberty timing and BMI and 2468 twins also had genetic data. Early puberty timing was moderately associated with higher BMI in childhood in both boys and girls; in adulthood these correlations were weaker and largely disappeared after adjusting for childhood BMI. The largest proportion of these correlations was attributable to genetic factors. The higher PGSs of BMI and waist circumference were associated with earlier timing of puberty in girls, whereas weaker associations were found in boys. Early puberty is not an independent risk factor for adult obesity but rather reflects the association between puberty timing and childhood BMI contributed by genetic predisposition.
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Affiliation(s)
- Karri Silventoinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, P.O. Box 18, 00014, Helsinki, Finland.
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
| | - Aline Jelenkovic
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Bilbao, Spain
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Leo Dunkel
- Barts & the London Medical School, William Harvey Research Institute, London, UK
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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36
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Zhou J, Zhang F, Zhang S, Li P, Qin X, Yang M, Teng Y, Huang K. Maternal pre-pregnancy body mass index, gestational weight gain, and pubertal timing in daughters: A systematic review and meta-analysis of cohort studies. Obes Rev 2022; 23:e13418. [PMID: 35014751 DOI: 10.1111/obr.13418] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 12/10/2021] [Accepted: 12/18/2021] [Indexed: 11/30/2022]
Abstract
The timing of daughter's puberty onset is constantly earlier. It is still unclear about the maternal pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) as important prenatal factors that may affect offspring's onset of puberty. Thus, we evaluated the association among maternal pre-pregnancy BMI, GWG, and daughters' early pubertal development based on the existing literature. Literature review was conducted in different databases, including Web of Science, Pubmed, Wiley, ScienceDirect, Web of Science, and Chinese National Knowledge Infrastructure databases up to June 2021. We selected random effects model or fixed effects model for meta-analysis according to the I2 statistics value to obtain the summary measurement. A total of 12 cohort studies were included. Compared to maternal pre-pregnancy normal weight, maternal pre-pregnancy overall overweight/obesity (RR = 1.24; 95% CI 1.17 to 1.32), obesity (RR = 1.35; 95% CI 1.23 to 1.48), and overweight (RR = 1.17; 95% CI 1.09 to 1.26) were significantly associated with the increased risk of earlier timing of pubertal onset in daughters. Daughters born of mothers with pre-pregnancy overall overweight/obesity, obesity, and overweight had earlier pubertal onset compared to those born of mothers with normal weight ([mean difference = -3.03, 95% CI: -3.97 to -2.10], [mean difference = -3.50, 95% CI: -5.38 to -1.62], and [mean difference = -2.89, 95% CI: -4.07 to -1.71], respectively). The effects were also significant in the assessed three milestones (menarche, breast development, and pubic hair development). Maternal excessive GWG increased the risk of early pubertal timing in daughters (RR = 1.19; 95% CI 1.09 to 1.30).
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Affiliation(s)
- Jixing Zhou
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.,Key Laboratory of Population Health Across Life Cycle (AHMU), MOE, Hefei, China.,Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, China.,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China
| | - Fu Zhang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.,Key Laboratory of Population Health Across Life Cycle (AHMU), MOE, Hefei, China.,Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, China.,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China
| | - Shanshan Zhang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.,Key Laboratory of Population Health Across Life Cycle (AHMU), MOE, Hefei, China.,Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, China.,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China
| | - Peixuan Li
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.,Key Laboratory of Population Health Across Life Cycle (AHMU), MOE, Hefei, China.,Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, China.,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China
| | - Xiaoyun Qin
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.,Key Laboratory of Population Health Across Life Cycle (AHMU), MOE, Hefei, China.,Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, China.,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China
| | - Mengting Yang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.,Key Laboratory of Population Health Across Life Cycle (AHMU), MOE, Hefei, China.,Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, China.,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China
| | - Yuzhu Teng
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.,Key Laboratory of Population Health Across Life Cycle (AHMU), MOE, Hefei, China.,Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, China.,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China
| | - Kun Huang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, China.,Key Laboratory of Population Health Across Life Cycle (AHMU), MOE, Hefei, China.,Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Hefei, China.,NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China.,Scientific Research Center in Preventive Medicine, School of Public Health, Anhui Medical University, Hefei, China
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37
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Jo EJ, Han S, Wang K. Estimation of Causal Effect of Age at Menarche on Pubertal Height Growth Using Mendelian Randomization. Genes (Basel) 2022; 13:genes13040710. [PMID: 35456516 PMCID: PMC9029282 DOI: 10.3390/genes13040710] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/14/2022] [Accepted: 04/14/2022] [Indexed: 01/27/2023] Open
Abstract
We use Mendelian randomization to estimate the causal effect of age at menarche on late pubertal height growth and total pubertal height growth. The instrument SNPs selected from the exposure genome-wide association study (GWAS) are validated in additional population-matched exposure GWASs. Based on the inverse variance weighting method, there is a positive causal relationship of age at menarche on late pubertal growth (β^=0.56, 95% CI: (0.34, 0.78), p=3.16×10−7) and on total pubertal growth (β^=0.36, 95% CI: (0.14, 0.58), p=1.30×10−3). If the instrument SNPs are not validated in additional exposure GWASs, the estimated effect on late pubertal height growth increases by 3.6% to β^=0.58 (95% CI: (0.42, 0.73), p=4.38×10−13) while the estimates on total pubertal height growth increases by 41.7% to β^=0.51 (95% CI: (0.35, 0.67), p=2.96×10−11).
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Affiliation(s)
- Eun Jae Jo
- Department of Biostatistics, University of Iowa, Iowa City, IA 52242, USA;
| | - Shizhong Han
- Lieber Institute for Brain Development, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA;
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Kai Wang
- Department of Biostatistics, University of Iowa, Iowa City, IA 52242, USA;
- Correspondence:
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Fernández-Rhodes L, Graff M, Buchanan VL, Justice AE, Highland HM, Guo X, Zhu W, Chen HH, Young KL, Adhikari K, Palmer ND, Below JE, Bradfield J, Pereira AC, Glover L, Kim D, Lilly AG, Shrestha P, Thomas AG, Zhang X, Chen M, Chiang CW, Pulit S, Horimoto A, Krieger JE, Guindo-Martínez M, Preuss M, Schumann C, Smit RA, Torres-Mejía G, Acuña-Alonzo V, Bedoya G, Bortolini MC, Canizales-Quinteros S, Gallo C, González-José R, Poletti G, Rothhammer F, Hakonarson H, Igo R, Adler SG, Iyengar SK, Nicholas SB, Gogarten SM, Isasi CR, Papnicolaou G, Stilp AM, Qi Q, Kho M, Smith JA, Langefeld CD, Wagenknecht L, Mckean-Cowdin R, Gao XR, Nousome D, Conti DV, Feng Y, Allison MA, Arzumanyan Z, Buchanan TA, Ida Chen YD, Genter PM, Goodarzi MO, Hai Y, Hsueh W, Ipp E, Kandeel FR, Lam K, Li X, Nadler JL, Raffel LJ, Roll K, Sandow K, Tan J, Taylor KD, Xiang AH, Yao J, Audirac-Chalifour A, de Jesus Peralta Romero J, Hartwig F, Horta B, Blangero J, Curran JE, Duggirala R, Lehman DE, Puppala S, Fejerman L, John EM, Aguilar-Salinas C, Burtt NP, Florez JC, García-Ortíz H, González-Villalpando C, Mercader J, Orozco L, Tusié-Luna T, Blanco E, Gahagan S, Cox NJ, Hanis C, et alFernández-Rhodes L, Graff M, Buchanan VL, Justice AE, Highland HM, Guo X, Zhu W, Chen HH, Young KL, Adhikari K, Palmer ND, Below JE, Bradfield J, Pereira AC, Glover L, Kim D, Lilly AG, Shrestha P, Thomas AG, Zhang X, Chen M, Chiang CW, Pulit S, Horimoto A, Krieger JE, Guindo-Martínez M, Preuss M, Schumann C, Smit RA, Torres-Mejía G, Acuña-Alonzo V, Bedoya G, Bortolini MC, Canizales-Quinteros S, Gallo C, González-José R, Poletti G, Rothhammer F, Hakonarson H, Igo R, Adler SG, Iyengar SK, Nicholas SB, Gogarten SM, Isasi CR, Papnicolaou G, Stilp AM, Qi Q, Kho M, Smith JA, Langefeld CD, Wagenknecht L, Mckean-Cowdin R, Gao XR, Nousome D, Conti DV, Feng Y, Allison MA, Arzumanyan Z, Buchanan TA, Ida Chen YD, Genter PM, Goodarzi MO, Hai Y, Hsueh W, Ipp E, Kandeel FR, Lam K, Li X, Nadler JL, Raffel LJ, Roll K, Sandow K, Tan J, Taylor KD, Xiang AH, Yao J, Audirac-Chalifour A, de Jesus Peralta Romero J, Hartwig F, Horta B, Blangero J, Curran JE, Duggirala R, Lehman DE, Puppala S, Fejerman L, John EM, Aguilar-Salinas C, Burtt NP, Florez JC, García-Ortíz H, González-Villalpando C, Mercader J, Orozco L, Tusié-Luna T, Blanco E, Gahagan S, Cox NJ, Hanis C, Butte NF, Cole SA, Comuzzie AG, Voruganti VS, Rohde R, Wang Y, Sofer T, Ziv E, Grant SF, Ruiz-Linares A, Rotter JI, Haiman CA, Parra EJ, Cruz M, Loos RJ, North KE. Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium. HGG ADVANCES 2022; 3:100099. [PMID: 35399580 PMCID: PMC8990175 DOI: 10.1016/j.xhgg.2022.100099] [Show More Authors] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 03/06/2022] [Indexed: 02/05/2023] Open
Abstract
Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.
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Affiliation(s)
- Lindsay Fernández-Rhodes
- Department of Biobehavioral Health, Pennsylvania State University, 219 Biobehavioral Health Building, University Park, PA 16802, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Victoria L. Buchanan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Anne E. Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biomedical and Translational Informatics, Geisinger Health System, Danville, PA 17822, USA
| | - Heather M. Highland
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Wanying Zhu
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Hung-Hsin Chen
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Kristin L. Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, MK7 6AA Milton Keynes, UK
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Jennifer E. Below
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jonathan Bradfield
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Alexandre C. Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - LáShauntá Glover
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Daeeun Kim
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Adam G. Lilly
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Poojan Shrestha
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Alvin G. Thomas
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Xinruo Zhang
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Minhui Chen
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Charleston W.K. Chiang
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90007, USA
| | - Sara Pulit
- Vertex Pharmaceuticals, W2 6BD Oxford, UK
| | - Andrea Horimoto
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - Jose E. Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - Marta Guindo-Martínez
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- The Novo Nordisk Center for Basic Metabolic Research, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Michael Preuss
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Claudia Schumann
- Hasso Plattner Institute, University of Potsdam, Digital Health Center, 14482 Potsdam, Germany
| | - Roelof A.J. Smit
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gabriela Torres-Mejía
- Department of Research in Cardiovascular Diseases, Diabetes Mellitus, and Cancer, Population Health Research Center, National Institute of Public Health, Cuernavaca, Morelos 62100, Mexico
| | | | - Gabriel Bedoya
- Molecular Genetics Investigation Group, University of Antioquia, Medellín 1226, Colombia
| | - Maria-Cátira Bortolini
- Department of Genetics, Federal University of Rio Grande do Sul, Porto Alegre 90040-060, Brazil
| | - Samuel Canizales-Quinteros
- Population Genomics Applied to Health Unit, The National Institute of Genomic Medicine and the Faculty of Chemistry at the National Autonomous University of Mexico, Mexico City 04510, Mexico
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | - Rolando González-José
- Patagonian Institute of the Social and Human Sciences, Patagonian National Center, Puerto Madryn U9120, Argentina
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | | | - Hakon Hakonarson
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Robert Igo
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Sharon G. Adler
- Division of Nephrology and Hypertension, Harbor-University of California Los Angeles Medical Center, Torrance, CA 90502, USA
| | - Sudha K. Iyengar
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Susanne B. Nicholas
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, CA 90095, USA
| | | | - Carmen R. Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | | | - Adrienne M. Stilp
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Carl D. Langefeld
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Lynne Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Roberta Mckean-Cowdin
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Xiaoyi Raymond Gao
- Department of Ophthalmology and Visual Sciences, Department of Biomedical Informatics, Division of Human Genetics, The Ohio State University, Columbus, OH 43210, USA
| | - Darryl Nousome
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - David V. Conti
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Ye Feng
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Matthew A. Allison
- Department of Family Medicine, University of California, San Diego, CA 92161, USA
| | - Zorayr Arzumanyan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Thomas A. Buchanan
- Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Pauline M. Genter
- Department of Medicine, Division of Endocrinology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Yang Hai
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Willa Hsueh
- Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA
| | - Eli Ipp
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, CA 90095, USA
- Department of Medicine, Division of Endocrinology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Fouad R. Kandeel
- Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Kelvin Lam
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Xiaohui Li
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Jerry L. Nadler
- Department of Pharmacology at New York Medical College School of Medicine, Valhalla, NY 10595, USA
| | - Leslie J. Raffel
- Division of Genetic and Genomic Medicine, Department of Pediatrics, University of California, Irvine, CA 92697, USA
| | - Kathryn Roll
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Kevin Sandow
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Anny H. Xiang
- Research and Evaluation Branch, Kaiser Permanente of Southern California, Pasadena, CA 91101, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Astride Audirac-Chalifour
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Jose de Jesus Peralta Romero
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Fernando Hartwig
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas 96010-610, Brazil
| | - Bernando Horta
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas 96010-610, Brazil
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Donna E. Lehman
- Department of Medicine, School of Medicine, University of Texas Health San Antonio, San Antonio, TX 78229, USA
| | - Sobha Puppala
- Department of Internal Medicine, Section of Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27109, USA
| | - Laura Fejerman
- Department of Public Health Sciences, School of Medicine, and the Comprehensive Cancer Center, University of California Davis, Davis, CA 95616, USA
| | - Esther M. John
- Departments of Epidemiology & Population Health and Medicine-Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Carlos Aguilar-Salinas
- Division of Nutrition, Salvador Zubirán National Institute of Health Sciences and Nutrition, Mexico City 14080, Mexico
| | - Noël P. Burtt
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Jose C. Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Humberto García-Ortíz
- Laboratory of Immunogenomics and Metabolic Diseases, National Institute of Genomic Medicine, Mexico City 14610, Mexico
| | - Clicerio González-Villalpando
- Center for Diabetes Studies, Research Unit for Diabetes and Cardiovascular Risk, Center for Population Health Studies, National Institute of Public Health, Mexico City 14080, Mexico
| | - Josep Mercader
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Lorena Orozco
- Laboratory of Immunogenomics and Metabolic Diseases, National Institute of Genomic Medicine, Mexico City 14610, Mexico
| | - Teresa Tusié-Luna
- Molecular Biology and Medical Genomics Unity, Institute of Biomedical Research, The National Autonomous University of Mexico and the Salvador Zubirán National Institute of Health Sciences and Nutrition, Mexico City 14080, Mexico
| | - Estela Blanco
- Center for Community Health, Division of Academic General Pediatrics, University of California at San Diego, San Diego, CA 92093, USA
| | - Sheila Gahagan
- Center for Community Health, Division of Academic General Pediatrics, University of California at San Diego, San Diego, CA 92093, USA
| | - Nancy J. Cox
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Craig Hanis
- University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Nancy F. Butte
- United States Department of Agriculture, Agricultural Research Service, The Children’s Nutrition Research Center, and the Department Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Shelley A. Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | | | - V. Saroja Voruganti
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
| | - Rebecca Rohde
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yujie Wang
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tamar Sofer
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Elad Ziv
- Division of General Internal Medicine, Department of Medicine, Helen Diller Family Comprehensive Cancer Center, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94115, USA
| | - Struan F.A. Grant
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Andres Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai 200438, China
- Department of Genetics, Evolution and Environment, and Genetics Institute of the University College London, London WC1E 6BT, UK
- Laboratory of Biocultural Anthropology, Law, Ethics, and Health, Aix-Marseille University, Marseille 13385, France
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Esteban J. Parra
- Department of Anthropology, University of Toronto- Mississauga, Mississauga, ON L5L 1C6, Canada
| | - Miguel Cruz
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Ruth J.F. Loos
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kari E. North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
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Kovács I, Kovács K, Gerván P, Utczás K, Oláh G, Tróznai Z, Berencsi A, Szakács H, Gombos F. Ultrasonic bone age fractionates cognitive abilities in adolescence. Sci Rep 2022; 12:5311. [PMID: 35351941 PMCID: PMC8964807 DOI: 10.1038/s41598-022-09329-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 03/22/2022] [Indexed: 12/12/2022] Open
Abstract
Adolescent development is not only shaped by the mere passing of time and accumulating experience, but it also depends on pubertal timing and the cascade of maturational processes orchestrated by gonadal hormones. Although individual variability in puberty onset confounds adolescent studies, it has not been efficiently controlled for. Here we introduce ultrasonic bone age assessment to estimate biological maturity and disentangle the independent effects of chronological and biological age on adolescent cognitive abilities. Comparing cognitive performance of female participants with different skeletal maturity we uncover the impact of biological age on both IQ and specific abilities. We find that biological age has a selective effect on abilities: more mature individuals within the same age group have higher working memory capacity and processing speed, while those with higher chronological age have better verbal abilities, independently of their maturity. Based on our findings, bone age is a promising biomarker of adolescent maturity.
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Affiliation(s)
- Ilona Kovács
- Laboratory for Psychological Research, Pázmány Péter Catholic University, 1 Mikszáth sq., 1088, Budapest, Hungary. .,Adolescent Development Research Group, Hungarian Academy of Sciences-Pázmány Péter Catholic University, 1088, Budapest, Hungary. .,Institute of Cognitive Neuroscience and Psychology, Res. Centre for Natural Sciences, 1117, Budapest, Hungary.
| | - Kristóf Kovács
- Institute of Psychology, ELTE Eötvös Loránd University, 1075, Budapest, Hungary
| | - Patrícia Gerván
- Laboratory for Psychological Research, Pázmány Péter Catholic University, 1 Mikszáth sq., 1088, Budapest, Hungary.,Adolescent Development Research Group, Hungarian Academy of Sciences-Pázmány Péter Catholic University, 1088, Budapest, Hungary
| | - Katinka Utczás
- Research Centre for Sport Physiology, University of Physical Education, 1123, Budapest, Hungary
| | - Gyöngyi Oláh
- Laboratory for Psychological Research, Pázmány Péter Catholic University, 1 Mikszáth sq., 1088, Budapest, Hungary.,Adolescent Development Research Group, Hungarian Academy of Sciences-Pázmány Péter Catholic University, 1088, Budapest, Hungary
| | - Zsófia Tróznai
- Research Centre for Sport Physiology, University of Physical Education, 1123, Budapest, Hungary
| | - Andrea Berencsi
- Institute for the Methodology of Special Needs Education and Rehabilitation, Bárczi Gusztáv Faculty of Special Needs Education, Eötvös Loránd University, 1097, Budapest, Hungary
| | - Hanna Szakács
- Laboratory for Psychological Research, Pázmány Péter Catholic University, 1 Mikszáth sq., 1088, Budapest, Hungary
| | - Ferenc Gombos
- Laboratory for Psychological Research, Pázmány Péter Catholic University, 1 Mikszáth sq., 1088, Budapest, Hungary.,Adolescent Development Research Group, Hungarian Academy of Sciences-Pázmány Péter Catholic University, 1088, Budapest, Hungary
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Li S, Li S, Su S, Zhang H, Shen J, Wen Y. Gene Region Association Analysis of Longitudinal Quantitative Traits Based on a Function-On-Function Regression Model. Front Genet 2022; 13:781740. [PMID: 35265102 PMCID: PMC8899465 DOI: 10.3389/fgene.2022.781740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 01/04/2022] [Indexed: 11/13/2022] Open
Abstract
In the process of growth and development in life, gene expressions that control quantitative traits will turn on or off with time. Studies of longitudinal traits are of great significance in revealing the genetic mechanism of biological development. With the development of ultra-high-density sequencing technology, the associated analysis has tremendous challenges to statistical methods. In this paper, a longitudinal functional data association test (LFDAT) method is proposed based on the function-on-function regression model. LFDAT can simultaneously treat phenotypic traits and marker information as continuum variables and analyze the association of longitudinal quantitative traits and gene regions. Simulation studies showed that: 1) LFDAT performs well for both linkage equilibrium simulation and linkage disequilibrium simulation, 2) LFDAT has better performance for gene regions (include common variants, low-frequency variants, rare variants and mixture), and 3) LFDAT can accurately identify gene switching in the growth and development stage. The longitudinal data of the Oryza sativa projected shoot area is analyzed by LFDAT. It showed that there is the advantage of quick calculations. Further, an association analysis was conducted between longitudinal traits and gene regions by integrating the micro effects of multiple related variants and using the information of the entire gene region. LFDAT provides a feasible method for studying the formation and expression of longitudinal traits.
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Affiliation(s)
- Shijing Li
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China.,> Institute of Statistics and Application, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Shiqin Li
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Shaoqiang Su
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Hui Zhang
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China.,> Institute of Statistics and Application, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Jiayu Shen
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China.,> Institute of Statistics and Application, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Yongxian Wen
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, China.,> Institute of Statistics and Application, Fujian Agriculture and Forestry University, Fuzhou, China
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Lu M, Feng R, Qin Y, Deng H, Lian B, Yin C, Xiao Y. Identifying Environmental Endocrine Disruptors Associated With the Age at Menarche by Integrating a Transcriptome-Wide Association Study With Chemical-Gene-Interaction Analysis. Front Endocrinol (Lausanne) 2022; 13:836527. [PMID: 35282430 PMCID: PMC8907571 DOI: 10.3389/fendo.2022.836527] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 02/03/2022] [Indexed: 11/28/2022] Open
Abstract
Menarche is the first occurrence of menstrual bleeding and one of the most important events of female puberty. Alarmingly, over the last several decades, the mean age at menarche (AAM) has decreased. Environmental endocrine disruptors (EEDs) are chemicals that may interfere with the endocrine system, resulting in adverse developmental, immunological, neurological, and reproductive effects in humans. Thus, the effects of EEDs on fertility and reproduction are growing concerns in modern societies. In this study, we aimed to determine the influence of genetic and environmental factors on AAM. We used data from an AAM genome-wide association study of 329,345 women to conduct a transcriptome-wide association study (TWAS) with FUSION software. As references, we determined the gene-expression levels in the hypothalamus, pituitary gland, ovaries, uterus, and whole blood. We performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the significantly dysregulated genes identified by the TWAS. Using the STRING database, we also generated a protein-protein-interaction network to analyze common AAM-specific genes identified by the TWAS with different tissues. We performed chemical-related gene set enrichment analysis (CGSEA) and identified significant TWAS genes to uncover relationships between different chemicals and AAM. The TWAS identified 9,848 genes; among these, 1580 genes were significant (P < 0.05), and 11 genes were significant among the hypothalamus, pituitary, ovary, uterus, and whole blood. CGSEA identified 1,634 chemicals, including 120 chemicals significantly correlated with AAM. In summary, we performed a TWAS (for genetic factors) and CGSEA (for environmental factors) focusing on AAM and identified several AAM-associated genes and EEDs. The results of this study expand our understanding of genetic and environmental factors related to the onset of female puberty.
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Affiliation(s)
- Mengnan Lu
- Department of Pediatrics, The Second Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, China
| | - Ruoyang Feng
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiao Tong University, Xi'an, China
| | - Yujie Qin
- Department of Pediatrics, The Second Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, China
| | - Hongyang Deng
- Department of Pediatrics, The Second Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, China
| | - Biyao Lian
- Department of Pediatrics, The Second Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, China
| | - Chunyan Yin
- Department of Pediatrics, The Second Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, China
| | - Yanfeng Xiao
- Department of Pediatrics, The Second Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, China
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42
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Chan II, Kwok MK, Schooling CM. Timing of Pubertal Development and Midlife Blood Pressure in Men and Women: A Mendelian Randomization Study. J Clin Endocrinol Metab 2022; 107:e386-e393. [PMID: 34343299 DOI: 10.1210/clinem/dgab561] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Observational studies suggest earlier puberty is associated with higher adulthood blood pressure (BP), but these findings have not been replicated using Mendelian randomization (MR). We examined this question sex-specifically using larger genome-wide association studies (GWAS) with more extensive measures of pubertal timing. METHODS We obtained genetic instruments proxying pubertal maturation (age at menarche [AAM] or voice breaking [AVB]) from the largest published GWAS. We applied them to summary sex-specific genetic associations with systolic and diastolic BP z-scores, and self-reported hypertension in women (n = 194 174) and men (n = 167 020) from the UK Biobank, using inverse-variance weighted meta-analysis. We conducted sensitivity analyses using other MR methods, including multivariable MR adjusted for childhood obesity proxied by body mass index (BMI). We used late pubertal growth as a validation outcome. RESULTS AAM (beta per 1-year later = -0.030 [95% confidence interval, -0.055 to -0.005] and AVB (beta -0.058 [95% CI, -0.100 to -0.015]) were inversely associated with systolic BP independent of childhood BMI, as were diastolic BP (-0.035 [95% CI, -0.060 to -0.009] for AAM and -0.046 [95% CI, -0.089 to -0.004] for AVB) and self-reported hypertension (odds ratio 0.89 [95% CI, 0.84-0.95] for AAM and 0.87 [95% CI, 0.79-0.96] for AVB). AAM and AVB were positively associated with late pubertal growth, as expected. The results were robust to sensitivity analysis using other MR methods. CONCLUSION Timing of pubertal maturation was associated with adulthood BP independent of childhood BMI, highlighting the role of pubertal maturation timing in midlife BP.
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Affiliation(s)
- Io Ieong Chan
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Man Ki Kwok
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - C Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- Graduate School of Public Health and Health Policy, City University of New York, NY 10027, USA
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Pahl MC, Doege CA, Hodge KM, Littleton SH, Leonard ME, Lu S, Rausch R, Pippin JA, De Rosa MC, Basak A, Bradfield JP, Hammond RK, Boehm K, Berkowitz RI, Lasconi C, Su C, Chesi A, Johnson ME, Wells AD, Voight BF, Leibel RL, Cousminer DL, Grant SFA. Cis-regulatory architecture of human ESC-derived hypothalamic neuron differentiation aids in variant-to-gene mapping of relevant complex traits. Nat Commun 2021; 12:6749. [PMID: 34799566 PMCID: PMC8604959 DOI: 10.1038/s41467-021-27001-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 10/27/2021] [Indexed: 11/09/2022] Open
Abstract
The hypothalamus regulates metabolic homeostasis by influencing behavior and endocrine systems. Given its role governing key traits, such as body weight and reproductive timing, understanding the genetic regulation of hypothalamic development and function could yield insights into disease pathogenesis. However, given its inaccessibility, studying human hypothalamic gene regulation has proven challenging. To address this gap, we generate a high-resolution chromatin architecture atlas of an established embryonic stem cell derived hypothalamic-like neuron model across three stages of in vitro differentiation. We profile accessible chromatin and identify physical contacts between gene promoters and putative cis-regulatory elements to characterize global regulatory landscape changes during hypothalamic differentiation. Next, we integrate these data with GWAS loci for various complex traits, identifying multiple candidate effector genes. Our results reveal common target genes for these traits, potentially affecting core developmental pathways. Our atlas will enable future efforts to determine hypothalamic mechanisms influencing disease susceptibility.
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Affiliation(s)
- Matthew C Pahl
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Claudia A Doege
- Department of Pathology, Naomi Berrie Diabetes Center, Columbia Stem Cell Initiative, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Kenyaita M Hodge
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Sheridan H Littleton
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Michelle E Leonard
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Sumei Lu
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Rick Rausch
- Department of Pediatrics, Naomi Berrie Diabetes Center, Columbia Stem Cell Initiative, Columbia University, Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - James A Pippin
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Maria Caterina De Rosa
- Department of Pediatrics, Naomi Berrie Diabetes Center, Columbia Stem Cell Initiative, Columbia University, Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Alisha Basak
- Department of Pediatrics, Naomi Berrie Diabetes Center, Columbia Stem Cell Initiative, Columbia University, Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Jonathan P Bradfield
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Reza K Hammond
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Keith Boehm
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Robert I Berkowitz
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Chiara Lasconi
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Chun Su
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Matthew E Johnson
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Andrew D Wells
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Benjamin F Voight
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Rudolph L Leibel
- Division of Molecular Genetics (Pediatrics) and the Naomi Berrie Diabetes Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Diana L Cousminer
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA
- GSK, Human Genetics and Computational Biology, 1250 South Collegeville Road, Collegeville, PA, 19426, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Genetics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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Grgic O, Gazzara MR, Chesi A, Medina-Gomez C, Cousminer DL, Mitchell JA, Prijatelj V, de Vries J, Shevroja E, McCormack SE, Kalkwarf HJ, Lappe JM, Gilsanz V, Oberfield SE, Shepherd JA, Kelly A, Mahboubi S, Faucz FR, Feelders RA, de Jong FH, Uitterlinden AG, Visser JA, Ghanem LR, Wolvius EB, Hofland LJ, Stratakis CA, Zemel BS, Barash Y, Grant SFA, Rivadeneira F. CYP11B1 variants influence skeletal maturation via alternative splicing. Commun Biol 2021; 4:1274. [PMID: 34754074 PMCID: PMC8578655 DOI: 10.1038/s42003-021-02774-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 09/24/2021] [Indexed: 12/13/2022] Open
Abstract
We performed genome-wide association study meta-analysis to identify genetic determinants of skeletal age (SA) deviating in multiple growth disorders. The joint meta-analysis (N = 4557) in two multiethnic cohorts of school-aged children identified one locus, CYP11B1 (expression confined to the adrenal gland), robustly associated with SA (rs6471570-A; β = 0.14; P = 6.2 × 10-12). rs6410 (a synonymous variant in the first exon of CYP11B1 in high LD with rs6471570), was prioritized for functional follow-up being second most significant and the one closest to the first intron-exon boundary. In 208 adrenal RNA-seq samples from GTEx, C-allele of rs6410 was associated with intron 3 retention (P = 8.11 × 10-40), exon 4 inclusion (P = 4.29 × 10-34), and decreased exon 3 and 5 splicing (P = 7.85 × 10-43), replicated using RT-PCR in 15 adrenal samples. As CYP11B1 encodes 11-β-hydroxylase, involved in adrenal glucocorticoid and mineralocorticoid biosynthesis, our findings highlight the role of adrenal steroidogenesis in SA in healthy children, suggesting alternative splicing as a likely underlying mechanism.
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Affiliation(s)
- Olja Grgic
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Department of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Matthew R Gazzara
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, 2615 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, 2615 Civic Center Boulevard, Philadelphia, PA, 19104, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, USA
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Diana L Cousminer
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, 2615 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, USA
| | - Jonathan A Mitchell
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Division of Gastroenterology, Hepatology, and Nutrition, The Children's Hospital of Philadelphia, 3401 Civic Center Boulevard Philadelphia, Philadelphia, PA, 19104, USA
| | - Vid Prijatelj
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Department of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Jard de Vries
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Enisa Shevroja
- Bone and Joint Department, Center of Bone Diseases, Lausanne University Hospital, Rue du Bugnon 46, 1011, Lausanne, Switzerland
| | - Shana E McCormack
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard Philadelphia, Philadelphia, PA, 19104, USA
| | - Heidi J Kalkwarf
- Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, 3333 Burnet Ave, Cincinnati, OH, 45229, USA
| | - Joan M Lappe
- Division of Endocrinology, Creighton University, 2500 California Plaza, Omaha, NE, 68178, USA
| | - Vicente Gilsanz
- Division of Orthopedic Surgery, Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, 1975 Zonal Ave, Los Angeles, CA, 90033, USA
- Department of Radiology, Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, 1975 Zonal Ave, Los Angeles, CA, 90033, USA
| | - Sharon E Oberfield
- Division of Pediatric Endocrinology, Morgan Stanley Children's Hospital, Columbia University Irving Medical Center, 622 West 168th Street, PH17 W 307, New York, NY, 10032, USA
| | - John A Shepherd
- Cancer Epidemiology, University of Hawai'i Cancer Center, 701 Ilalo St, Honolulu, HI, 96813, USA
| | - Andrea Kelly
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard Philadelphia, Philadelphia, PA, 19104, USA
| | - Soroosh Mahboubi
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, USA
| | - Fabio R Faucz
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, 6710 Rockledge Dr, Bethesda, MD, 20817, USA
| | - Richard A Feelders
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Frank H de Jong
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Andre G Uitterlinden
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Jenny A Visser
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Louis R Ghanem
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Division of Gastroenterology, Hepatology, and Nutrition, The Children's Hospital of Philadelphia, 3401 Civic Center Boulevard Philadelphia, Philadelphia, PA, 19104, USA
| | - Eppo B Wolvius
- Department of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Leo J Hofland
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Constantine A Stratakis
- Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, 6710 Rockledge Dr, Bethesda, MD, 20817, USA
| | - Babette S Zemel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Division of Gastroenterology, Hepatology, and Nutrition, The Children's Hospital of Philadelphia, 3401 Civic Center Boulevard Philadelphia, Philadelphia, PA, 19104, USA
| | - Yoseph Barash
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, 2615 Civic Center Boulevard, Philadelphia, PA, 19104, USA
| | - Struan F A Grant
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, 2615 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard Philadelphia, Philadelphia, PA, 19104, USA
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
- Department of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
- The Generation R Study, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
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Sinclair-Waters M, Piavchenko N, Ruokolainen A, Aykanat T, Erkinaro J, Primmer CR. Refining the genomic location of single nucleotide polymorphism variation affecting Atlantic salmon maturation timing at a key large-effect locus. Mol Ecol 2021; 31:562-570. [PMID: 34716945 DOI: 10.1111/mec.16256] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Revised: 10/22/2021] [Accepted: 10/25/2021] [Indexed: 12/14/2022]
Abstract
Efforts to understand the genetic underpinnings of phenotypic variation are becoming more and more frequent in molecular ecology. Such efforts often lead to the identification of candidate regions showing signals of association and/or selection. These regions may contain multiple genes and therefore validation of which genes are actually responsible for the signal is required. In Atlantic salmon (Salmo salar), a large-effect locus for maturation timing, an ecologically important trait, occurs in a genomic region including two genes, vgll3 and akap11, but data for clearly determining which of the genes (or both) contribute to the association have been lacking. Here, we take advantage of natural recombination events detected between the two candidate genes in a salmon broodstock to reduce linkage disequilibrium at the locus, thus enabling delineation of the influence of variation at these two genes on early maturation. By rearing 5,895 males to maturation age, of which 81% had recombinant vgll3/akap11 allelic combinations, we found that vgll3 single nucleotide polymorphism (SNP) variation was strongly associated with early maturation, whereas there was little or no association between akap11 SNP variation and early maturation. These findings provide strong evidence supporting vgll3 as the primary candidate gene in the chromosome 25 locus for influencing early maturation. This will help guide future research for understanding the genetic processes controlling early maturation. This also exemplifies the utility of natural recombinants to more precisely map causal variation underlying ecologically important phenotypic diversity.
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Affiliation(s)
- Marion Sinclair-Waters
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.,Institute of Biotechnology, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
| | - Nikolai Piavchenko
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.,Institute of Biotechnology, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
| | - Annukka Ruokolainen
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.,Institute of Biotechnology, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
| | - Tutku Aykanat
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.,Institute of Biotechnology, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
| | | | - Craig R Primmer
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.,Institute of Biotechnology, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
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Predicting physiological aging rates from a range of quantitative traits using machine learning. Aging (Albany NY) 2021; 13:23471-23516. [PMID: 34718232 PMCID: PMC8580337 DOI: 10.18632/aging.203660] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 09/29/2021] [Indexed: 11/25/2022]
Abstract
It is widely thought that individuals age at different rates. A method that measures “physiological age” or physiological aging rate independent of chronological age could therefore help elucidate mechanisms of aging and inform an individual’s risk of morbidity and mortality. Here we present machine learning frameworks for inferring individual physiological age from a broad range of biochemical and physiological traits including blood phenotypes (e.g., high-density lipoprotein), cardiovascular functions (e.g., pulse wave velocity) and psychological traits (e.g., neuroticism) as main groups in two population cohorts SardiNIA (~6,100 participants) and InCHIANTI (~1,400 participants). The inferred physiological age was highly correlated with chronological age (R2 > 0.8). We further defined an individual’s physiological aging rate (PAR) as the ratio of the predicted physiological age to the chronological age. Notably, PAR was a significant predictor of survival, indicating an effect of aging rate on mortality. Our trait-based PAR was correlated with DNA methylation-based epigenetic aging score (r = 0.6), suggesting that both scores capture a common aging process. PAR was also substantially heritable (h2~0.3), and a subsequent genome-wide association study of PAR identified significant associations with two genetic loci, one of which is implicated in telomerase activity. Our findings support PAR as a proxy for an underlying whole-body aging mechanism. PAR may thus be useful to evaluate the efficacy of treatments that target aging-related deficits and controllable epidemiological factors.
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Debes PV, Piavchenko N, Ruokolainen A, Ovaskainen O, Moustakas-Verho JE, Parre N, Aykanat T, Erkinaro J, Primmer CR. Polygenic and major-locus contributions to sexual maturation timing in Atlantic salmon. Mol Ecol 2021; 30:4505-4519. [PMID: 34228841 DOI: 10.1111/mec.16062] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 06/16/2021] [Accepted: 07/01/2021] [Indexed: 12/13/2022]
Abstract
Sexual maturation timing is a life-history trait central to the balance between mortality and reproduction. Maturation may be triggered when an underlying compound trait, called liability, exceeds a threshold. In many different species and especially fishes, this liability is approximated by growth and body condition. However, environmental vs. genetic contributions either directly or via growth and body condition to maturation timing remain unclear. Uncertainty exists also because the maturation process can reverse this causality and itself affect growth and body condition. In addition, disentangling the contributions of polygenic and major loci can be important. In many fishes, males mature before females, enabling the study of associations between male maturation and maturation-unbiased female liability traits. Using 40 Atlantic salmon families, longitudinal common-garden experimentation, and quantitative genetic analyses, we disentangled environmental from polygenic and major locus (vgll3) effects on male maturation, and sex-specific growth and condition. We detected polygenic heritabilities for maturation, growth, and body condition, and vgll3 effects on maturation and body condition but not on growth. Longitudinal patterns for sex-specific phenotypic liability, and for genetic variances and correlations between sexes suggested that early growth and condition indeed positively affected maturation initiation. However, towards spawning time, causality appeared reversed for males whereby maturation affected growth negatively and condition positively via both the environmental and genetic effects. Altogether, the results indicate that growth and condition are useful traits to study liability for maturation initiation, but only until maturation alters their expression, and that vgll3 contributes to maturation initiation via condition.
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Affiliation(s)
- Paul V Debes
- Organismal & Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences / Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE, University of Helsinki, Helsinki, Finland
| | - Nikolai Piavchenko
- Organismal & Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences / Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE, University of Helsinki, Helsinki, Finland
| | - Annukka Ruokolainen
- Organismal & Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences / Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE, University of Helsinki, Helsinki, Finland
| | - Outi Ovaskainen
- Organismal & Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences / Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE, University of Helsinki, Helsinki, Finland
| | - Jacqueline E Moustakas-Verho
- Organismal & Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences / Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE, University of Helsinki, Helsinki, Finland
| | - Noora Parre
- Organismal & Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences / Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE, University of Helsinki, Helsinki, Finland
| | - Tutku Aykanat
- Organismal & Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences / Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE, University of Helsinki, Helsinki, Finland
| | | | - Craig R Primmer
- Organismal & Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences / Institute of Biotechnology, Helsinki Institute of Life Science (HiLIFE, University of Helsinki, Helsinki, Finland
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陈 曼, 杨 招, 苏 彬, 李 艳, 高 迪, 马 莹, 马 涛, 董 彦, 马 军. [Analysis on the law of height growth spurt in adolescence of children and adolescents in Zhongshan City]. BEIJING DA XUE XUE BAO. YI XUE BAN = JOURNAL OF PEKING UNIVERSITY. HEALTH SCIENCES 2021; 53:506-510. [PMID: 34145852 PMCID: PMC8220054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Indexed: 08/13/2024]
Abstract
OBJECTIVE To analyze the characteristics of the age at peak height velocity and peak height velocity of primary and middle school students in Zhongshan City, Guangdong Province, and to explore the law of the sudden increase in adolescent height in this area, and to understand the law of height growth spurt in adolescence by longitudinal tracking of the height of children and adolescents in Zhong-shan City. METHODS Based on the physical examination database of primary and middle school students in Zhongshan City, Guangdong Province from 2005 to 2016, individuals who had been continuously tracked for more than 6 times were selected as research samples. SITAR model was used to fit the height data of the sample population, and the age at peak height velocity and peak height velocity were calcula-ted. RESULTS A total of 49 579 subjects were included in this study, including 26 524 boys and 26 008 urban students. The median follow-up ages of boys and girls were 7.74 and 7.72 years, respectively. The boy's height spurt peak age was (12.72±0.89) years, and later than the girls at the age of (10.98±0.95) years (t=207.639, P < 0.001), the boy's height spurt peak velocity of (10.12±1.49) cm/year, higher than the girls of (8.35±1.12) cm/year (t=150.826, P < 0.001). The gender differences of height spurt peak age and height spurt peak speed in urban and rural students were consistent with the whole sample. The height surge peak age of urban male students was earlier than that of rural male students, and the height surge peak speed of urban female students was lower than that of rural female students. CONCLUSION The peak age of the surge of girls was earlier than that of boys, but the peak rate of the surge of girls was lower than that of boys, the peak age of urban students was earlier than that of rural students, but the peak rate of urban boys was lower than that of rural boys in Guangdong Province.
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Affiliation(s)
- 曼曼 陈
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 招庚 杨
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 彬彬 苏
- 北京大学人口研究所,北京 100871Institute of Population Research, Peking University, Beijing 100871, China
| | - 艳辉 李
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 迪 高
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 莹 马
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 涛 马
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 彦会 董
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 军 马
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
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49
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陈 曼, 杨 招, 苏 彬, 李 艳, 高 迪, 马 莹, 马 涛, 董 彦, 马 军. [Analysis on the law of height growth spurt in adolescence of children and adolescents in Zhongshan City]. BEIJING DA XUE XUE BAO. YI XUE BAN = JOURNAL OF PEKING UNIVERSITY. HEALTH SCIENCES 2021; 53:506-510. [PMID: 34145852 PMCID: PMC8220054 DOI: 10.19723/j.issn.1671-167x.2021.03.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Indexed: 06/12/2023]
Abstract
OBJECTIVE To analyze the characteristics of the age at peak height velocity and peak height velocity of primary and middle school students in Zhongshan City, Guangdong Province, and to explore the law of the sudden increase in adolescent height in this area, and to understand the law of height growth spurt in adolescence by longitudinal tracking of the height of children and adolescents in Zhong-shan City. METHODS Based on the physical examination database of primary and middle school students in Zhongshan City, Guangdong Province from 2005 to 2016, individuals who had been continuously tracked for more than 6 times were selected as research samples. SITAR model was used to fit the height data of the sample population, and the age at peak height velocity and peak height velocity were calcula-ted. RESULTS A total of 49 579 subjects were included in this study, including 26 524 boys and 26 008 urban students. The median follow-up ages of boys and girls were 7.74 and 7.72 years, respectively. The boy's height spurt peak age was (12.72±0.89) years, and later than the girls at the age of (10.98±0.95) years (t=207.639, P < 0.001), the boy's height spurt peak velocity of (10.12±1.49) cm/year, higher than the girls of (8.35±1.12) cm/year (t=150.826, P < 0.001). The gender differences of height spurt peak age and height spurt peak speed in urban and rural students were consistent with the whole sample. The height surge peak age of urban male students was earlier than that of rural male students, and the height surge peak speed of urban female students was lower than that of rural female students. CONCLUSION The peak age of the surge of girls was earlier than that of boys, but the peak rate of the surge of girls was lower than that of boys, the peak age of urban students was earlier than that of rural students, but the peak rate of urban boys was lower than that of rural boys in Guangdong Province.
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Affiliation(s)
- 曼曼 陈
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 招庚 杨
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 彬彬 苏
- 北京大学人口研究所,北京 100871Institute of Population Research, Peking University, Beijing 100871, China
| | - 艳辉 李
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 迪 高
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 莹 马
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 涛 马
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 彦会 董
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
| | - 军 马
- 北京大学公共卫生学院,北京大学儿童青少年卫生研究所,北京 100191Institute of Child and Adolescent Health, Peking University School of Public Health, Beijing 100191, China
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50
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Chiou J, Geusz RJ, Okino ML, Han JY, Miller M, Melton R, Beebe E, Benaglio P, Huang S, Korgaonkar K, Heller S, Kleger A, Preissl S, Gorkin DU, Sander M, Gaulton KJ. Interpreting type 1 diabetes risk with genetics and single-cell epigenomics. Nature 2021; 594:398-402. [PMID: 34012112 PMCID: PMC10560508 DOI: 10.1038/s41586-021-03552-w] [Citation(s) in RCA: 218] [Impact Index Per Article: 54.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2020] [Accepted: 04/14/2021] [Indexed: 02/04/2023]
Abstract
Genetic risk variants that have been identified in genome-wide association studies of complex diseases are primarily non-coding1. Translating these risk variants into mechanistic insights requires detailed maps of gene regulation in disease-relevant cell types2. Here we combined two approaches: a genome-wide association study of type 1 diabetes (T1D) using 520,580 samples, and the identification of candidate cis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cells using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) of 131,554 nuclei. Risk variants for T1D were enriched in cCREs that were active in T cells and other cell types, including acinar and ductal cells of the exocrine pancreas. Risk variants at multiple T1D signals overlapped with exocrine-specific cCREs that were linked to genes with exocrine-specific expression. At the CFTR locus, the T1D risk variant rs7795896 mapped to a ductal-specific cCRE that regulated CFTR; the risk allele reduced transcription factor binding, enhancer activity and CFTR expression in ductal cells. These findings support a role for the exocrine pancreas in the pathogenesis of T1D and highlight the power of large-scale genome-wide association studies and single-cell epigenomics for understanding the cellular origins of complex disease.
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Affiliation(s)
- Joshua Chiou
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA.
- Internal Medicine Research Unit, Pfizer Worldwide Research, Cambridge, MA, USA.
| | - Ryan J Geusz
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Mei-Lin Okino
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Jee Yun Han
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Michael Miller
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Rebecca Melton
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Elisha Beebe
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Paola Benaglio
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Serina Huang
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Katha Korgaonkar
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Sandra Heller
- Department of Internal Medicine I, Ulm University, Ulm, Germany
| | | | - Sebastian Preissl
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - David U Gorkin
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Biology, Emory University, Atlanta, GA, USA
| | - Maike Sander
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Kyle J Gaulton
- Department of Pediatrics, Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
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