1
|
Zhang YR, Wu BS, Chen SD, Yang L, Deng YT, Guo Y, Wu XR, Liu WS, Kang JJ, Feng JF, Cheng W, Yu JT. Whole exome sequencing analyses identified novel genes for Alzheimer's disease and related dementia. Alzheimers Dement 2024. [PMID: 39129223 DOI: 10.1002/alz.14181] [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: 05/21/2024] [Revised: 07/11/2024] [Accepted: 07/16/2024] [Indexed: 08/13/2024]
Abstract
INTRODUCTION The heritability of Alzheimer's disease (AD) is estimated to be 58%-79%. However, known genes can only partially explain the heritability. METHODS Here, we conducted gene-based exome-wide association study (ExWAS) of rare variants and single-variant ExWAS of common variants, utilizing data of 54,569 clinically diagnosed/proxy AD and related dementia (ADRD) and 295,421 controls from the UK Biobank. RESULTS Gene-based ExWAS identified 11 genes predicting a higher ADRD risk, including five novel ones, namely FRMD8, DDX1, DNMT3L, MORC1, and TGM2, along with six previously reported ones, SORL1, GRN, PSEN1, ABCA7, GBA, and ADAM10. Single-variant ExWAS identified two ADRD-associated novel genes, SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-β process pathways, microglia, and brain regions like hippocampus. The druggability evidence suggests that DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets. DISCUSSION Our study contributes to the current body of evidence on the genetic etiology of ADRD. HIGHLIGHTS Gene-based analyses of rare variants identified five novel genes for Alzheimer's disease and related dementia (ADRD), including FRMD8, DDX1, DNMT3L, MORC1, and TGM2. Single-variant analyses of common variants identified two novel genes for ADRD, including SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-β process pathways, microglia, and brain regions like hippocampus. DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets.
Collapse
Affiliation(s)
- Ya-Ru Zhang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yue-Ting Deng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yu Guo
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xin-Rui Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei-Shi Liu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ju-Jiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| |
Collapse
|
2
|
Yang L, Ou YN, Wu BS, Liu WS, Deng YT, He XY, Chen YL, Kang J, Fei CJ, Zhu Y, Tan L, Dong Q, Feng J, Cheng W, Yu JT. Large-scale whole-exome sequencing analyses identified protein-coding variants associated with immune-mediated diseases in 350,770 adults. Nat Commun 2024; 15:5924. [PMID: 39009607 PMCID: PMC11250857 DOI: 10.1038/s41467-024-49782-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 06/18/2024] [Indexed: 07/17/2024] Open
Abstract
The genetic contribution of protein-coding variants to immune-mediated diseases (IMDs) remains underexplored. Through whole exome sequencing of 40 IMDs in 350,770 UK Biobank participants, we identified 162 unique genes in 35 IMDs, among which 124 were novel genes. Several genes, including FLG which is associated with atopic dermatitis and asthma, showed converging evidence from both rare and common variants. 91 genes exerted significant effects on longitudinal outcomes (interquartile range of Hazard Ratio: 1.12-5.89). Mendelian randomization identified five causal genes, of which four were approved drug targets (CDSN, DDR1, LTA, and IL18BP). Proteomic analysis indicated that mutations associated with specific IMDs might also affect protein expression in other IMDs. For example, DXO (celiac disease-related gene) and PSMB9 (alopecia areata-related gene) could modulate CDSN (autoimmune hypothyroidism-, psoriasis-, asthma-, and Graves' disease-related gene) expression. Identified genes predominantly impact immune and biochemical processes, and can be clustered into pathways of immune-related, urate metabolism, and antigen processing. Our findings identified protein-coding variants which are the key to IMDs pathogenesis and provided new insights into tailored innovative therapies.
Collapse
Affiliation(s)
- Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Wei-Shi Liu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Yue-Ting Deng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Xiao-Yu He
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Yi-Lin Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200443, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Chen-Jie Fei
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Ying Zhu
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, 200032, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Qiang Dong
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200443, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200443, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
| |
Collapse
|
3
|
Kang J, Deng YT, Wu BS, Liu WS, Li ZY, Xiang S, Yang L, You J, Gong X, Jia T, Yu JT, Cheng W, Feng J. Whole exome sequencing analysis identifies genes for alcohol consumption. Nat Commun 2024; 15:5777. [PMID: 38982111 PMCID: PMC11233704 DOI: 10.1038/s41467-024-50132-3] [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: 05/15/2023] [Accepted: 06/26/2024] [Indexed: 07/11/2024] Open
Abstract
Alcohol consumption is a heritable behavior seriously endangers human health. However, genetic studies on alcohol consumption primarily focuses on common variants, while insights from rare coding variants are lacking. Here we leverage whole exome sequencing data across 304,119 white British individuals from UK Biobank to identify protein-coding variants associated with alcohol consumption. Twenty-five variants are associated with alcohol consumption through single variant analysis and thirteen genes through gene-based analysis, ten of which have not been reported previously. Notably, the two unreported alcohol consumption-related genes GIGYF1 and ANKRD12 show enrichment in brain function-related pathways including glial cell differentiation and are strongly expressed in the cerebellum. Phenome-wide association analyses reveal that alcohol consumption-related genes are associated with brain white matter integrity and risk of digestive and neuropsychiatric diseases. In summary, this study enhances the comprehension of the genetic architecture of alcohol consumption and implies biological mechanisms underlying alcohol-related adverse outcomes.
Collapse
Affiliation(s)
- Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China
| | - Yue-Ting Deng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China
| | - Wei-Shi Liu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China
| | - Ze-Yu Li
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China
| | - Jia You
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China
| | - Xiaohong Gong
- School of Life Sciences, Fudan University, Shanghai, 200433, China
| | - Tianye Jia
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- School of Psychology, University of Southampton, Southampton, UK
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China.
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China.
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200433, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Zhejiang, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, 200433, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, 200433, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Zhejiang, China.
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK.
| |
Collapse
|
4
|
Gong W, Fu Y, Wu BS, Du J, Yang L, Zhang YR, Chen SD, Kang J, Mao Y, Dong Q, Tan L, Feng J, Cheng W, Yu JT. Whole-exome sequencing identifies protein-coding variants associated with brain iron in 29,828 individuals. Nat Commun 2024; 15:5540. [PMID: 38956042 PMCID: PMC11219919 DOI: 10.1038/s41467-024-49702-2] [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: 04/12/2024] [Accepted: 06/16/2024] [Indexed: 07/04/2024] Open
Abstract
Iron plays a fundamental role in multiple brain disorders. However, the genetic underpinnings of brain iron and its implications for these disorders are still lacking. Here, we conduct an exome-wide association analysis of brain iron, measured by quantitative susceptibility mapping technique, across 26 brain regions among 26,789 UK Biobank participants. We find 36 genes linked to brain iron, with 29 not being previously reported, and 16 of them can be replicated in an independent dataset with 3,039 subjects. Many of these genes are involved in iron transport and homeostasis, such as FTH1 and MLX. Several genes, while not previously connected to brain iron, are associated with iron-related brain disorders like Parkinson's (STAB1, KCNA10), Alzheimer's (SHANK1), and depression (GFAP). Mendelian randomization analysis reveals six causal relationships from regional brain iron to brain disorders, such as from the hippocampus to depression and from the substantia nigra to Parkinson's. These insights advance our understanding of the genetic architecture of brain iron and offer potential therapeutic targets for brain disorders.
Collapse
Affiliation(s)
- Weikang Gong
- School of Data Science, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK.
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, 266071, Qingdao, China
| | - Bang-Sheng Wu
- School of Data Science, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA, 02138, USA
| | - Liu Yang
- School of Data Science, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Ya-Ru Zhang
- School of Data Science, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- School of Data Science, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - JuJiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 200433, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, 200433, Shanghai, China
| | - Ying Mao
- School of Data Science, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Qiang Dong
- School of Data Science, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, 266071, Qingdao, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 200433, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, 200433, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Wei Cheng
- School of Data Science, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 200433, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, 200433, Shanghai, China.
| | - Jin-Tai Yu
- School of Data Science, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
| |
Collapse
|
5
|
Tabet DR, Kuang D, Lancaster MC, Li R, Liu K, Weile J, Coté AG, Wu Y, Hegele RA, Roden DM, Roth FP. Benchmarking computational variant effect predictors by their ability to infer human traits. Genome Biol 2024; 25:172. [PMID: 38951922 PMCID: PMC11218265 DOI: 10.1186/s13059-024-03314-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 06/17/2024] [Indexed: 07/03/2024] Open
Abstract
BACKGROUND Computational variant effect predictors offer a scalable and increasingly reliable means of interpreting human genetic variation, but concerns of circularity and bias have limited previous methods for evaluating and comparing predictors. Population-level cohorts of genotyped and phenotyped participants that have not been used in predictor training can facilitate an unbiased benchmarking of available methods. Using a curated set of human gene-trait associations with a reported rare-variant burden association, we evaluate the correlations of 24 computational variant effect predictors with associated human traits in the UK Biobank and All of Us cohorts. RESULTS AlphaMissense outperformed all other predictors in inferring human traits based on rare missense variants in UK Biobank and All of Us participants. The overall rankings of computational variant effect predictors in these two cohorts showed a significant positive correlation. CONCLUSION We describe a method to assess computational variant effect predictors that sidesteps the limitations of previous evaluations. This approach is generalizable to future predictors and could continue to inform predictor choice for personal and clinical genetics.
Collapse
Affiliation(s)
- Daniel R Tabet
- Donnelly Centre, University of Toronto, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Da Kuang
- Donnelly Centre, University of Toronto, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Megan C Lancaster
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Roujia Li
- Donnelly Centre, University of Toronto, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Karen Liu
- Donnelly Centre, University of Toronto, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Jochen Weile
- Donnelly Centre, University of Toronto, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Atina G Coté
- Donnelly Centre, University of Toronto, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Yingzhou Wu
- Donnelly Centre, University of Toronto, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Robert A Hegele
- Department of Medicine, Department of Biochemistry, Schulich School of Medicine and Dentistry, Robarts Research Institute, Western University, London, ON, Canada
| | - Dan M Roden
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pharmacology, Vanderbilt University Medical Centre, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Frederick P Roth
- Donnelly Centre, University of Toronto, Toronto, ON, Canada.
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
- Department of Computer Science, University of Toronto, Toronto, ON, Canada.
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada.
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| |
Collapse
|
6
|
Zhang DD, He XY, Yang L, Wu BS, Fu Y, Liu WS, Guo Y, Fei CJ, Kang JJ, Feng JF, Cheng W, Tan L, Yu JT. Exome sequencing identifies novel genetic variants associated with varicose veins. PLoS Genet 2024; 20:e1011339. [PMID: 38980841 PMCID: PMC11233024 DOI: 10.1371/journal.pgen.1011339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 06/13/2024] [Indexed: 07/11/2024] Open
Abstract
BACKGROUND Varicose veins (VV) are one of the common human diseases, but the role of genetics in its development is not fully understood. METHODS We conducted an exome-wide association study of VV using whole-exome sequencing data from the UK Biobank, and focused on common and rare variants using single-variant association analysis and gene-level collapsing analysis. FINDINGS A total of 13,823,269 autosomal genetic variants were obtained after quality control. We identified 36 VV-related independent common variants mapping to 34 genes by single-variant analysis and three rare variant genes (PIEZO1, ECE1, FBLN7) by collapsing analysis, and most associations between genes and VV were replicated in FinnGen. PIEZO1 was the closest gene associated with VV (P = 5.05 × 10-31), and it was found to reach exome-wide significance in both single-variant and collapsing analyses. Two novel rare variant genes (ECE1 and METTL21A) associated with VV were identified, of which METTL21A was associated only with females. The pleiotropic effects of VV-related genes suggested that body size, inflammation, and pulmonary function are strongly associated with the development of VV. CONCLUSIONS Our findings highlight the importance of causal genes for VV and provide new directions for treatment.
Collapse
Affiliation(s)
- Dan-Dan Zhang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xiao-Yu He
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Wei-Shi Liu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yu Guo
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Chen-Jie Fei
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ju-Jiao Kang
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, United Kingdom
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, United Kingdom
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| |
Collapse
|
7
|
Paludan-Müller C, Vad OB, Stampe NK, Diederichsen SZ, Andreasen L, Monfort LM, Fosbøl EL, Køber L, Torp-Pedersen C, Svendsen JH, Olesen MS. Atrial fibrillation: age at diagnosis, incident cardiovascular events, and mortality. Eur Heart J 2024; 45:2119-2129. [PMID: 38592444 PMCID: PMC11212824 DOI: 10.1093/eurheartj/ehae216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 02/19/2024] [Accepted: 03/20/2024] [Indexed: 04/10/2024] Open
Abstract
BACKGROUND AND AIMS Patients with atrial fibrillation (AF) are at increased risks of cardiovascular diseases and mortality, but risks according to age at diagnosis have not been reported. This study investigated age-specific risks of outcomes among patients with AF and the background population. METHODS This nationwide population-based cohort study included patients with AF and controls without outcomes by the application of exposure density matching on the basis of sex, year of birth, and index date. The absolute risks and hazard rates were stratified by age groups and assessed using competing risk survival analyses and Cox regression models, respectively. The expected differences in residual life years among participants were estimated. RESULTS The study included 216 579 AF patients from year 2000 to 2020 and 866 316 controls. The mean follow-up time was 7.9 years. Comparing AF patients with matched controls, the hazard ratios among individuals ≤50 years was 8.90 [95% confidence interval (CI), 7.17-11.0] for cardiomyopathy, 8.64 (95% CI, 7.74-9.64) for heart failure, 2.18 (95% CI, 1.89-2.52) for ischaemic stroke, and 2.74 (95% CI, 2.53-2.96) for mortality. The expected average loss of life years among individuals ≤50 years was 9.2 years (95% CI, 9.0-9.3) years. The estimates decreased with older age. CONCLUSIONS The findings show that earlier diagnosis of AF is associated with a higher hazard ratio of subsequent myocardial disease and shorter life expectancy. Further studies are needed to determine causality and whether AF could be used as a risk marker among particularly younger patients.
Collapse
Affiliation(s)
- Christian Paludan-Müller
- Department of Cardiology, The Heart Center, Copenhagen University Hospital—Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen O, Denmark
| | - Oliver B Vad
- Department of Cardiology, The Heart Center, Copenhagen University Hospital—Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen O, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niels K Stampe
- Department of Cardiology, The Heart Center, Copenhagen University Hospital—Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen O, Denmark
| | - Søren Z Diederichsen
- Department of Cardiology, The Heart Center, Copenhagen University Hospital—Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen O, Denmark
| | - Laura Andreasen
- Department of Cardiology, The Heart Center, Copenhagen University Hospital—Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen O, Denmark
| | - Laia M Monfort
- Department of Cardiology, The Heart Center, Copenhagen University Hospital—Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen O, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Emil L Fosbøl
- Department of Cardiology, The Heart Center, Copenhagen University Hospital—Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen O, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lars Køber
- Department of Cardiology, The Heart Center, Copenhagen University Hospital—Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen O, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christian Torp-Pedersen
- Department of Cardiology, Copenhagen University Hospital—North Zealand Hospital, Hillerød, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jesper H Svendsen
- Department of Cardiology, The Heart Center, Copenhagen University Hospital—Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen O, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Morten S Olesen
- Department of Cardiology, The Heart Center, Copenhagen University Hospital—Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen O, Denmark
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
8
|
Antikainen AA, Haukka JK, Kumar A, Syreeni A, Hägg-Holmberg S, Ylinen A, Kilpeläinen E, Kytölä A, Palotie A, Putaala J, Thorn LM, Harjutsalo V, Groop PH, Sandholm N. Whole-genome sequencing identifies variants in ANK1, LRRN1, HAS1, and other genes and regulatory regions for stroke in type 1 diabetes. Sci Rep 2024; 14:13453. [PMID: 38862513 PMCID: PMC11166668 DOI: 10.1038/s41598-024-61840-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 05/10/2024] [Indexed: 06/13/2024] Open
Abstract
Individuals with type 1 diabetes (T1D) carry a markedly increased risk of stroke, with distinct clinical and neuroimaging characteristics as compared to those without diabetes. Using whole-exome or whole-genome sequencing of 1,051 individuals with T1D, we aimed to find rare and low-frequency genomic variants associated with stroke in T1D. We analysed the genome comprehensively with single-variant analyses, gene aggregate analyses, and aggregate analyses on genomic windows, enhancers and promoters. In addition, we attempted replication in T1D using a genome-wide association study (N = 3,945) and direct genotyping (N = 3,263), and in the general population from the large-scale population-wide FinnGen project and UK Biobank summary statistics. We identified a rare missense variant on SREBF1 exome-wide significantly associated with stroke (rs114001633, p.Pro227Leu, p-value = 7.30 × 10-8), which replicated for hemorrhagic stroke in T1D. Using gene aggregate analysis, we identified exome-wide significant genes: ANK1 and LRRN1 displayed replication evidence in T1D, and LRRN1, HAS1 and UACA in the general population (UK Biobank). Furthermore, we performed sliding-window analyses and identified 14 genome-wide significant windows for stroke on 4q33-34.1, of which two replicated in T1D, and a suggestive genomic window on LINC01500, which replicated in T1D. Finally, we identified a suggestively stroke-associated TRPM2-AS promoter (p-value = 5.78 × 10-6) with borderline significant replication in T1D, which we validated with an in vitro cell-based assay. Due to the rarity of the identified genetic variants, future replication of the genomic regions represented here is required with sequencing of individuals with T1D. Nevertheless, we here report the first genome-wide analysis on stroke in individuals with diabetes.
Collapse
Affiliation(s)
- Anni A Antikainen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jani K Haukka
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Anmol Kumar
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Anna Syreeni
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Stefanie Hägg-Holmberg
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Anni Ylinen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Elina Kilpeläinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Anastasia Kytölä
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jukka Putaala
- Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Lena M Thorn
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Valma Harjutsalo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, Australia.
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland.
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
| |
Collapse
|
9
|
Butnariu LI, Bizim DA, Oltean C, Rusu C, Pânzaru MC, Păduraru G, Gimiga N, Ghiga G, Moisă ȘM, Țarcă E, Starcea IM, Popa S, Trandafir LM. The Importance of Molecular Genetic Testing for Precision Diagnostics, Management, and Genetic Counseling in MODY Patients. Int J Mol Sci 2024; 25:6318. [PMID: 38928025 PMCID: PMC11204182 DOI: 10.3390/ijms25126318] [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: 05/10/2024] [Revised: 05/31/2024] [Accepted: 06/05/2024] [Indexed: 06/28/2024] Open
Abstract
Maturity-onset diabetes of the young (MODY) is part of the heterogeneous group of monogenic diabetes (MD) characterized by the non-immune dysfunction of pancreatic β-cells. The diagnosis of MODY still remains a challenge for clinicians, with many cases being misdiagnosed as type 1 or type 2 diabetes mellitus (T1DM/T2DM), and over 80% of cases remaining undiagnosed. With the introduction of modern technologies, important progress has been made in deciphering the molecular mechanisms and heterogeneous etiology of MD, including MODY. The aim of our study was to identify genetic variants associated with MODY in a group of patients with early-onset diabetes/prediabetes in whom a form of MD was clinically suspected. Genetic testing, based on next-generation sequencing (NGS) technology, was carried out either in a targeted manner, using gene panels for monogenic diabetes, or by analyzing the entire exome (whole-exome sequencing). GKC-MODY 2 was the most frequently detected variant, but rare forms of KCNJ11-MODY 13, specifically, HNF4A-MODY 1, were also identified. We have emphasized the importance of genetic testing for early diagnosis, MODY subtype differentiation, and genetic counseling. We presented the genotype-phenotype correlations, especially related to the clinical evolution and personalized therapy, also emphasizing the particularities of each patient in the family context.
Collapse
Affiliation(s)
- Lăcrămioara Ionela Butnariu
- Department of Medical Genetics, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (C.R.); (S.P.)
| | - Delia Andreia Bizim
- Department of Diabetes, Saint Mary’s Emergency Children Hospital, 700309 Iasi, Romania; (D.A.B.); (C.O.)
| | - Carmen Oltean
- Department of Diabetes, Saint Mary’s Emergency Children Hospital, 700309 Iasi, Romania; (D.A.B.); (C.O.)
| | - Cristina Rusu
- Department of Medical Genetics, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (C.R.); (S.P.)
| | - Monica Cristina Pânzaru
- Department of Medical Genetics, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (C.R.); (S.P.)
| | - Gabriela Păduraru
- Department of Mother and Child, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (G.P.); (N.G.); (G.G.); (Ș.M.M.); (I.M.S.); (L.M.T.)
| | - Nicoleta Gimiga
- Department of Mother and Child, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (G.P.); (N.G.); (G.G.); (Ș.M.M.); (I.M.S.); (L.M.T.)
| | - Gabriela Ghiga
- Department of Mother and Child, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (G.P.); (N.G.); (G.G.); (Ș.M.M.); (I.M.S.); (L.M.T.)
| | - Ștefana Maria Moisă
- Department of Mother and Child, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (G.P.); (N.G.); (G.G.); (Ș.M.M.); (I.M.S.); (L.M.T.)
| | - Elena Țarcă
- Department of Surgery II—Pediatric Surgery, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania;
| | - Iuliana Magdalena Starcea
- Department of Mother and Child, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (G.P.); (N.G.); (G.G.); (Ș.M.M.); (I.M.S.); (L.M.T.)
| | - Setalia Popa
- Department of Medical Genetics, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (C.R.); (S.P.)
| | - Laura Mihaela Trandafir
- Department of Mother and Child, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (G.P.); (N.G.); (G.G.); (Ș.M.M.); (I.M.S.); (L.M.T.)
| |
Collapse
|
10
|
Ryu J, Rämö JT, Jurgens SJ, Niiranen T, Sanna-Cherchi S, Bauer KA, Haj A, Choi SH, Palotie A, Daly M, Ellinor PT, Bendapudi PK. Thrombosis risk in single- and double-heterozygous carriers of factor V Leiden and prothrombin G20210A in FinnGen and the UK Biobank. Blood 2024; 143:2425-2432. [PMID: 38498041 DOI: 10.1182/blood.2023023326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 02/22/2024] [Accepted: 02/23/2024] [Indexed: 03/19/2024] Open
Abstract
ABSTRACT The factor V Leiden (FVL; rs6025) and prothrombin G20210A (PTGM; rs1799963) polymorphisms are 2 of the most well-studied genetic risk factors for venous thromboembolism (VTE). However, double heterozygosity (DH) for FVL and PTGM remains poorly understood, with previous studies showing marked disagreement regarding thrombosis risk conferred by the DH genotype. Using multidimensional data from the UK Biobank (UKB) and FinnGen biorepositories, we evaluated the clinical impact of DH carrier status across 937 939 individuals. We found that 662 participants (0.07%) were DH carriers. After adjustment for age, sex, and ancestry, DH individuals experienced a markedly elevated risk of VTE compared with wild-type individuals (odds ratio [OR] = 5.24; 95% confidence interval [CI], 4.01-6.84; P = 4.8 × 10-34), which approximated the risk conferred by FVL homozygosity. A secondary analysis restricted to UKB participants (N = 445 144) found that effect size estimates for the DH genotype remained largely unchanged (OR = 4.53; 95% CI, 3.42-5.90; P < 1 × 10-16) after adjustment for commonly cited VTE risk factors, such as body mass index, blood type, and markers of inflammation. In contrast, the DH genotype was not associated with a significantly higher risk of any arterial thrombosis phenotype, including stroke, myocardial infarction, and peripheral artery disease. In summary, we leveraged population-scale genomic data sets to conduct, to our knowledge, the largest study to date on the DH genotype and were able to establish far more precise effect size estimates than previously possible. Our findings indicate that the DH genotype may occur as frequently as FVL homozygosity and may confer a similarly increased risk of VTE.
Collapse
Affiliation(s)
- Justine Ryu
- Department of Medicine, Section of Hematology, Yale School of Medicine, New Haven, CT
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Joel T Rämö
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Cardiology Division, Massachusetts General Hospital, Boston, MA
| | - Sean J Jurgens
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Cardiology Division, Massachusetts General Hospital, Boston, MA
- Department of Experimental Cardiology, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Teemu Niiranen
- Department of Internal Medicine, University of Turku, Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Turku, Finland
| | | | - Kenneth A Bauer
- Harvard Medical School, Boston, MA
- Division of Hemostasis and Thrombosis, Beth Israel Deaconess Medical Center, Boston, MA
| | - Amelia Haj
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Harvard Medical School, Boston, MA
- Department of Pathology, Massachusetts General Hospital, Boston, MA
| | - Seung Hoan Choi
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Aarno Palotie
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Cardiology Division, Massachusetts General Hospital, Boston, MA
| | - Mark Daly
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Cardiology Division, Massachusetts General Hospital, Boston, MA
| | - Patrick T Ellinor
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Cardiology Division, Massachusetts General Hospital, Boston, MA
- Harvard Medical School, Boston, MA
| | - Pavan K Bendapudi
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA
- Harvard Medical School, Boston, MA
- Division of Hemostasis and Thrombosis, Beth Israel Deaconess Medical Center, Boston, MA
- Division of Hematology and Blood Transfusion Service, Massachusetts General Hospital, Boston, MA
| |
Collapse
|
11
|
Deng YT, Wu BS, Yang L, He XY, Kang JJ, Liu WS, Li ZY, Wu XR, Zhang YR, Chen SD, Ge YJ, Huang YY, Feng JF, Zhu Y, Dong Q, Mao Y, Cheng W, Yu JT. Large-scale whole-exome sequencing of neuropsychiatric diseases and traits in 350,770 adults. Nat Hum Behav 2024; 8:1194-1208. [PMID: 38589703 DOI: 10.1038/s41562-024-01861-4] [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: 10/06/2023] [Accepted: 03/11/2024] [Indexed: 04/10/2024]
Abstract
While numerous genomic loci have been identified for neuropsychiatric conditions, the contribution of protein-coding variants has yet to be determined. Here we conducted a large-scale whole-exome-sequencing study to interrogate the impact of protein-coding variants on 46 neuropsychiatric diseases and 23 traits in 350,770 adults from the UK Biobank. Twenty new genes were associated with neuropsychiatric diseases through coding variants, among which 16 genes had impacts on the longitudinal risks of diseases. Thirty new genes were associated with neuropsychiatric traits, with SYNGAP1 showing pleiotropic effects across cognitive function domains. Pairwise estimation of genetic correlations at the coding-variant level highlighted shared genetic associations among pairs of neurodegenerative diseases and mental disorders. Lastly, a comprehensive multi-omics analysis suggested that alterations in brain structures, blood proteins and inflammation potentially contribute to the gene-phenotype linkages. Overall, our findings characterized a compendium of protein-coding variants for future research on the biology and therapeutics of neuropsychiatric phenotypes.
Collapse
Affiliation(s)
- Yue-Ting Deng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiao-Yu He
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ju-Jiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Wei-Shi Liu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ze-Yu Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Xin-Rui Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ya-Ru Zhang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi-Jun Ge
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yu-Yuan Huang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Ying Zhu
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Qiang Dong
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital Fudan University, Shanghai, China
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Zhejiang, China.
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
| |
Collapse
|
12
|
da Fonseca ACP, Assis ISDS, Salum KCR, Palhinha L, Abreu GDM, Zembrzuski VM, Campos Junior M, Nogueira-Neto JF, Cambraia A, Souza Junior MLF, Maya-Monteiro CM, Cabello PH, Bozza PT, Carneiro JRI. Genetic variants in DBC1, SIRT1, UCP2 and ADRB2 as potential biomarkers for severe obesity and metabolic complications. Front Genet 2024; 15:1363417. [PMID: 38841722 PMCID: PMC11151296 DOI: 10.3389/fgene.2024.1363417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 05/01/2024] [Indexed: 06/07/2024] Open
Abstract
Introduction Obesity is a multifactorial disease associated with the development of many comorbidities. This disease is associated with several metabolic alterations; however, it has been shown that some individuals with obesity do not exhibit metabolic syndrome. Adipose tissue neutralizes the detrimental effects of circulating fatty acids, ectopic deposition, and inflammation, among others, through its esterification into neutral lipids that are stored in the adipocyte. However, when the adipocyte is overloaded, i.e., its expansion capacity is exceeded, this protection is lost, resulting in fatty acid toxicity with ectopic fat accumulation in peripheral tissues and inflammation. In this line, this study aimed to investigate whether polymorphisms in genes that control adipose tissue fat storage capacity are potential biomarkers for severe obesity susceptibility and also metabolic complications. Methods This study enrolled 305 individuals with severe obesity (cases, BMI≥35 kg/m2) and 196 individuals with normal weight (controls, 18.5≤BMI≤24.9 kg/m2). Demographic, anthropometric, biochemical, and blood pressure variables were collected from the participants. Plasma levels of leptin, resistin, MCP1, and PAI1 were measured by Bio-Plex 200 Multiplexing Analyzer System. Genomic DNA was extracted and variants in DBC1 (rs17060940), SIRT1 (rs7895833 and rs1467568), UCP2 (rs660339), PPARG (rs1801282) and ADRB2 (rs1042713 and rs1042714) genes were genotyped by PCR allelic discrimination using TaqMan® assays. Results Our findings indicated that SIRT1 rs7895833 polymorphism was a risk factor for severe obesity development in the overdominant model. SIRT1 rs1467568 and UCP2 rs660339 were associated with anthropometric traits. SIRT1 rs1467568 G allele was related to lower medians of body adipose index and hip circumference, while the UCP2 rs660339 AA genotype was associate with increased body mass index. Additionally, DBC1 rs17060940 influenced glycated hemoglobin. Regarding metabolic alterations, 27% of individuals with obesity presented balanced metabolic status in our cohort. Furthermore, SIRT1 rs1467568 AG genotype increased 2.5 times the risk of developing metabolic alterations. No statistically significant results were observed with Peroxisome Proliferator-Activated Receptor Gama and ADRB2 polymorphisms. Discussion/Conclusion This study revealed that SIRT1 rs7895833 and rs1467568 are potential biomarkers for severe obesity susceptibility and the development of unbalanced metabolic status in obesity, respectively. UCP2 rs660339 and DBC1 rs17060940 also showed a significant role in obesity related-traits.
Collapse
Affiliation(s)
- Ana Carolina Proença da Fonseca
- Laboratory of Immunopharmacology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
- Human Genetics Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
- Genetics Laboratory, Grande Rio University/AFYA, Rio de Janeiro, Brazil
- Postgraduate Program in Translational Biomedicine, Grande Rio University/AFYA, Rio de Janeiro, Brazil
| | - Izadora Sthephanie da Silva Assis
- Laboratory of Immunopharmacology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
- Human Genetics Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Kaio Cezar Rodrigues Salum
- Laboratory of Immunopharmacology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
- Human Genetics Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
- Clementino Fraga Filho University Hospital, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Lohanna Palhinha
- Laboratory of Immunopharmacology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Gabriella de Medeiros Abreu
- Human Genetics Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
- Josué de Castro Nutrition Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Mario Campos Junior
- Human Genetics Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | | | - Amanda Cambraia
- Human Genetics Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | | | | | - Pedro Hernán Cabello
- Human Genetics Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Patrícia Torres Bozza
- Laboratory of Immunopharmacology, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - João Regis Ivar Carneiro
- Clementino Fraga Filho University Hospital, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| |
Collapse
|
13
|
Teng Y, Du T, Feng S, Tian R, Liu Y, Guo J, Wang L, Zhang Z, Luan X, He S, Zhuang S, Wang Y, Zhang S, Chen S, Liu Z, Zhang S. The spectrum of rare monogenic diseases in patients with premature coronary artery disease. Chin Med J (Engl) 2024; 137:1246-1248. [PMID: 38297435 PMCID: PMC11101226 DOI: 10.1097/cm9.0000000000002996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Indexed: 02/02/2024] Open
Affiliation(s)
- Yaqun Teng
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- Department of Internal Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- Department of Basic Medical Sciences, Tsinghua University School of Medicine, Beijing 100084, China
| | - Tian Du
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- Department of Basic Medical Sciences, Tsinghua University School of Medicine, Beijing 100084, China
- Department of Breast Oncology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong 510060, China
| | - Siqin Feng
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- Department of Internal Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Ran Tian
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Yaping Liu
- McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Jian Guo
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Lei Wang
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Zhiyu Zhang
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- Department of Internal Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Xiaodong Luan
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- Department of Basic Medical Sciences, Tsinghua University School of Medicine, Beijing 100084, China
- Tsinghua University-Peking University Joint Center for Life Sciences, Beijing 100084, China
| | - Shan He
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- Department of Internal Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Shengsheng Zhuang
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Yifei Wang
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- Department of Basic Medical Sciences, Tsinghua University School of Medicine, Beijing 100084, China
- Department of Cardiology, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing 102218, China
| | - Shuyuan Zhang
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Shi Chen
- Department of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, Peking Union Medical College Hospital, Chinese Research Center for Behavior Medicine in Growth and Development, Beijing 100730, China
| | - Zhenyu Liu
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Shuyang Zhang
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare disease, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
- Department of Basic Medical Sciences, Tsinghua University School of Medicine, Beijing 100084, China
- Tsinghua University-Peking University Joint Center for Life Sciences, Beijing 100084, China
| |
Collapse
|
14
|
Guo H, Urban AE, Wong WH. Prioritizing disease-related rare variants by integrating gene expression data. RESEARCH SQUARE 2024:rs.3.rs-4355589. [PMID: 38766095 PMCID: PMC11100897 DOI: 10.21203/rs.3.rs-4355589/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Rare variants, comprising a vast majority of human genetic variations, are likely to have more deleterious impact on human diseases compared to common variants. Here we present carrier statistic, a statistical framework to prioritize disease-related rare variants by integrating gene expression data. By quantifying the impact of rare variants on gene expression, carrier statistic can prioritize those rare variants that have large functional consequence in the diseased patients. Through simulation studies and analyzing real multi-omics dataset, we demonstrated that carrier statistic is applicable in studies with limited sample size (a few hundreds) and achieves substantially higher sensitivity than existing rare variants association methods. Application to Alzheimer's disease reveals 16 rare variants within 15 genes with extreme carrier statistics. We also found strong excess of rare variants among the top prioritized genes in diseased patients compared to that in healthy individuals. The carrier statistic method can be applied to various rare variant types and is adaptable to other omics data modalities, offering a powerful tool for investigating the molecular mechanisms underlying complex diseases.
Collapse
|
15
|
Baudic M, Murata H, Bosada FM, Melo US, Aizawa T, Lindenbaum P, van der Maarel LE, Guedon A, Baron E, Fremy E, Foucal A, Ishikawa T, Ushinohama H, Jurgens SJ, Choi SH, Kyndt F, Le Scouarnec S, Wakker V, Thollet A, Rajalu A, Takaki T, Ohno S, Shimizu W, Horie M, Kimura T, Ellinor PT, Petit F, Dulac Y, Bru P, Boland A, Deleuze JF, Redon R, Le Marec H, Le Tourneau T, Gourraud JB, Yoshida Y, Makita N, Vieyres C, Makiyama T, Mundlos S, Christoffels VM, Probst V, Schott JJ, Barc J. TAD boundary deletion causes PITX2-related cardiac electrical and structural defects. Nat Commun 2024; 15:3380. [PMID: 38643172 PMCID: PMC11032321 DOI: 10.1038/s41467-024-47739-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: 02/17/2023] [Accepted: 04/08/2024] [Indexed: 04/22/2024] Open
Abstract
While 3D chromatin organization in topologically associating domains (TADs) and loops mediating regulatory element-promoter interactions is crucial for tissue-specific gene regulation, the extent of their involvement in human Mendelian disease is largely unknown. Here, we identify 7 families presenting a new cardiac entity associated with a heterozygous deletion of 2 CTCF binding sites on 4q25, inducing TAD fusion and chromatin conformation remodeling. The CTCF binding sites are located in a gene desert at 1 Mb from the Paired-like homeodomain transcription factor 2 gene (PITX2). By introducing the ortholog of the human deletion in the mouse genome, we recapitulate the patient phenotype and characterize an opposite dysregulation of PITX2 expression in the sinoatrial node (ectopic activation) and ventricle (reduction), respectively. Chromatin conformation assay performed in human induced pluripotent stem cell-derived cardiomyocytes harboring the minimal deletion identified in family#1 reveals a conformation remodeling and fusion of TADs. We conclude that TAD remodeling mediated by deletion of CTCF binding sites causes a new autosomal dominant Mendelian cardiac disorder.
Collapse
Affiliation(s)
- Manon Baudic
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Hiroshige Murata
- The Department of Cardiovascular Medicine, Nippon Medical School Hospital, Tokyo, Japan
| | - Fernanda M Bosada
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ, Amsterdam, The Netherlands
| | - Uirá Souto Melo
- Max Planck Institute for Molecular Genetics, RG Development and Disease, 13353, Berlin, Germany
| | - Takanori Aizawa
- Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Pierre Lindenbaum
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Lieve E van der Maarel
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam Reproduction and Development, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ, Amsterdam, The Netherlands
| | - Amaury Guedon
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Estelle Baron
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Enora Fremy
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Adrien Foucal
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Taisuke Ishikawa
- Omics Research Center, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Hiroya Ushinohama
- Department of Cardiology, Fukuoka Children's Hospital, Fukuoka, Japan
| | - Sean J Jurgens
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Experimental Cardiology, Heart Center, Amsterdam Cardiovascular Sciences, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands
| | - Seung Hoan Choi
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Florence Kyndt
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Solena Le Scouarnec
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Vincent Wakker
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ, Amsterdam, The Netherlands
| | - Aurélie Thollet
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Annabelle Rajalu
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Tadashi Takaki
- Department of Cell Growth and Differentiation, Center for iPS Cell Research and Application, Kyoto University, Kyoto, Japan
- Takeda-CiRA Joint Program for iPS Cell Applications, Fujisawa, Japan
- Department of Pancreatic Islet Cell Transplantation, National Center for Global Health and Medicine, Tokyo, Japan
| | - Seiko Ohno
- Department of Bioscience and Genetics, National Cerebral and Cardiovascular Center Research Institute, Suita, Japan
| | - Wataru Shimizu
- The Department of Cardiovascular Medicine, Nippon Medical School Hospital, Tokyo, Japan
| | - Minoru Horie
- Department of Cardiovascular Medicine, Shiga University of Medical Science, Ohtsu, Japan
| | - Takeshi Kimura
- Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Patrick T Ellinor
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Florence Petit
- Service de Génétique Clinique, CHU Lille, Hôpital Jeanne de Flandre, F-59000, Lille, France
- University of Lille, EA 7364-RADEME, F-59000, Lille, France
| | - Yves Dulac
- Unité de Cardiologie Pédiatrique, Hôpital des Enfants, F-31000, Toulouse, France
| | - Paul Bru
- Service de Cardiologie, GH La Rochelle, F-17019, La Rochelle, France
| | - Anne Boland
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine (CNRGH), 91057, Evry, France
| | - Jean-François Deleuze
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine (CNRGH), 91057, Evry, France
| | - Richard Redon
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Hervé Le Marec
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Thierry Le Tourneau
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
| | - Jean-Baptiste Gourraud
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart: ERN GUARD-Heart, Amsterdam, The Netherlands
| | - Yoshinori Yoshida
- Department of Cell Growth and Differentiation, Center for iPS Cell Research and Application, Kyoto University, Kyoto, Japan
| | - Naomasa Makita
- Omics Research Center, National Cerebral and Cardiovascular Center, Suita, Japan
- Department of Cardiology, Sapporo Teishinkai Hospital, Sapporo, Japan
| | - Claude Vieyres
- Cabinet Cardiologique, Clinique St. Joseph, F-16000, Angoulême, France
| | - Takeru Makiyama
- Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
- Department of Community Medicine Supporting System, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Stephan Mundlos
- Max Planck Institute for Molecular Genetics, RG Development and Disease, 13353, Berlin, Germany
| | - Vincent M Christoffels
- Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam Reproduction and Development, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ, Amsterdam, The Netherlands
| | - Vincent Probst
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart: ERN GUARD-Heart, Amsterdam, The Netherlands
| | - Jean-Jacques Schott
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France.
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart: ERN GUARD-Heart, Amsterdam, The Netherlands.
| | - Julien Barc
- Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du Thorax, F-44000, Nantes, France.
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart: ERN GUARD-Heart, Amsterdam, The Netherlands.
| |
Collapse
|
16
|
Fitzsimmons L, Beaulieu-Jones B, Kobren SN. Phenotypic overlap between rare disease patients and variant carriers in a large population cohort informs biological mechanisms. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.18.24305861. [PMID: 38699301 PMCID: PMC11064998 DOI: 10.1101/2024.04.18.24305861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
The biological mechanisms giving rise to the extreme symptoms exhibited by rare disease patients are complex, heterogenous, and difficult to discern. Understanding these mechanisms is critical for developing treatments that address the underlying causes of diseases rather than merely the presenting symptoms. Moreover, the same dysfunctional biological mechanisms implicated in rare recessive diseases may also lead to milder and potentially preventable symptoms in carriers in the general population. Seizures are a common, extreme phenotype that can result from diverse and often elusive biological pathways in patients with ultrarare or undiagnosed disorders. In this pilot study, we present an approach to understand the biological pathways leading to seizures in patients from the Undiagnosed Diseases Network (UDN) by analyzing aggregated genotype and phenotype data from the UK Biobank (UKB). Specifically, we look for enriched phenotypes across UKB participants who harbor rare variants in the same gene known or suspected to be causally implicated in a UDN patient's recessively manifesting disorder. Analyzing these milder but related associated phenotypes in UKB participants can provide insight into the disease-causing molecular mechanisms at play in the rare disease UDN patient. We present six vignettes of undiagnosed patients experiencing seizures as part of their recessive genetic condition, and we discuss the potential mechanisms underlying the spectrum of symptoms associated with UKB participants to the severe presentations exhibited by UDN patients. We find that in our set of rare disease patients, seizures may result from diverse, multi-step pathways that involve multiple body systems. Analyses of large-scale population cohorts such as the UKB can be a critical tool to further our understanding of rare diseases in general.
Collapse
|
17
|
Liu X, Koyama S, Tomizuka K, Takata S, Ishikawa Y, Ito S, Kosugi S, Suzuki K, Hikino K, Koido M, Koike Y, Horikoshi M, Gakuhari T, Ikegawa S, Matsuda K, Momozawa Y, Ito K, Kamatani Y, Terao C. Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing. SCIENCE ADVANCES 2024; 10:eadi8419. [PMID: 38630824 PMCID: PMC11023554 DOI: 10.1126/sciadv.adi8419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 03/07/2024] [Indexed: 04/19/2024]
Abstract
We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.
Collapse
Affiliation(s)
- Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Sadaaki Takata
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Faculty of Medicine, Shimane University, Izumo, Japan
| | - Shunichi Kosugi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kunihiko Suzuki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Keiko Hikino
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masaru Koido
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoshinao Koike
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Takashi Gakuhari
- Institute for the Study of Ancient Civilizations and Cultural Resources, College of Human and Social Sciences, Kanazawa University, Kanazawa, Japan
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
| | - Kochi Matsuda
- Laboratory of Genome Technology, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| |
Collapse
|
18
|
Wang L, Kranzler HR, Gelernter J, Zhou H. Multi-ancestry Whole-exome Sequencing Study of Alcohol Use Disorder in Two Cohorts. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.05.24305412. [PMID: 38645055 PMCID: PMC11030482 DOI: 10.1101/2024.04.05.24305412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. There has been substantial progress in identifying genetic variants underlying AUD. However, there are few whole-exome sequencing (WES) studies of AUD. We analyzed WES of 4,530 samples from the Yale-Penn cohort and 469,835 samples from the UK Biobank (UKB). After quality control, 1,420 AUD cases and 619 controls of European ancestry (EUR) and 1,142 cases and 608 controls of African ancestry (AFR) from Yale-Penn were retained for subsequent analyses. WES data from 415,617 EUR samples (12,861 cases), 6,142 AFR samples (130 cases) and 4,607 South Asian (SAS) samples (130 cases) from UKB were also analyzed. Single-variant association analysis identified the well-known functional variant rs1229984 in ADH1B ( P =4.88×10 -31 ) and several other common variants in ADH1C . Gene-based tests identified ADH1B ( P =1.00×10 -31 ), ADH1C ( P =5.23×10 -7 ), CNST ( P =1.19×10 -6 ), and IFIT5 (3.74×10 -6 ). This study extends our understanding of the genetic basis of AUD.
Collapse
|
19
|
Wen Y, Chen YQ, Konrad RJ. Angiopoietin-like protein 8: a multifaceted protein instrumental in regulating triglyceride metabolism. Curr Opin Lipidol 2024; 35:58-65. [PMID: 37962908 DOI: 10.1097/mol.0000000000000910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
PURPOSE OF REVIEW The angiopoietin-like (ANGPTL) proteins ANGPTL3 and ANGPTL4 are critical lipoprotein lipase (LPL) inhibitors. This review discusses the unique ability of the insulin-responsive protein ANGPTL8 to regulate triglyceride (TG) metabolism by forming ANGPTL3/8 and ANGPTL4/8 complexes that control tissue-specific LPL activities. RECENT FINDINGS After feeding, ANGPTL4/8 acts locally in adipose tissue, has decreased LPL-inhibitory activity compared to ANGPTL4, and binds tissue plasminogen activator (tPA) and plasminogen to generate plasmin, which cleaves ANGPTL4/8 and other LPL inhibitors. This enables LPL to be fully active postprandially to promote efficient fatty acid (FA) uptake and minimize ectopic fat deposition. In contrast, liver-derived ANGPTL3/8 acts in an endocrine manner, has markedly increased LPL-inhibitory activity compared to ANGPTL3, and potently inhibits LPL in oxidative tissues to direct TG toward adipose tissue for storage. Circulating ANGPTL3/8 levels are strongly correlated with serum TG, and the ANGPTL3/8 LPL-inhibitory epitope is blocked by the TG-lowering protein apolipoprotein A5 (ApoA5). SUMMARY ANGPTL8 plays a crucial role in TG metabolism by forming ANGPTL3/8 and ANGPTL4/8 complexes that differentially modulate LPL activities in oxidative and adipose tissues respectively. Selective ANGPTL8 inhibition in the context of the ANGPTL3/8 complex has the potential to be a promising strategy for treating dyslipidemia.
Collapse
Affiliation(s)
- Yi Wen
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana, USA
| | | | | |
Collapse
|
20
|
He XY, Wu BS, Yang L, Guo Y, Deng YT, Li ZY, Fei CJ, Liu WS, Ge YJ, Kang J, Feng J, Cheng W, Dong Q, Yu JT. Genetic associations of protein-coding variants in venous thromboembolism. Nat Commun 2024; 15:2819. [PMID: 38561338 PMCID: PMC10984941 DOI: 10.1038/s41467-024-47178-8] [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: 07/12/2023] [Accepted: 03/19/2024] [Indexed: 04/04/2024] Open
Abstract
Previous genetic studies of venous thromboembolism (VTE) have been largely limited to common variants, leaving the genetic determinants relatively incomplete. We performed an exome-wide association study of VTE among 14,723 cases and 334,315 controls. Fourteen known and four novel genes (SRSF6, PHPT1, CGN, and MAP3K2) were identified through protein-coding variants, with broad replication in the FinnGen cohort. Most genes we discovered exhibited the potential to predict future VTE events in longitudinal analysis. Notably, we provide evidence for the additive contribution of rare coding variants to known genome-wide polygenic risk in shaping VTE risk. The identified genes were enriched in pathways affecting coagulation and platelet activation, along with liver-specific expression. The pleiotropic effects of these genes indicated the potential involvement of coagulation factors, blood cell traits, liver function, and immunometabolic processes in VTE pathogenesis. In conclusion, our study unveils the valuable contribution of protein-coding variants in VTE etiology and sheds new light on its risk stratification.
Collapse
Affiliation(s)
- Xiao-Yu He
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yu Guo
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yue-Ting Deng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ze-Yu Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Chen-Jie Fei
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei-Shi Liu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi-Jun Ge
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
| | - Qiang Dong
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
| |
Collapse
|
21
|
Guo H, Urban AE, Wong WH. Prioritizing disease-related rare variants by integrating gene expression data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.19.585836. [PMID: 38562756 PMCID: PMC10983955 DOI: 10.1101/2024.03.19.585836] [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
Rare variants, comprising a vast majority of human genetic variations, are likely to have more deleterious impact on human diseases compared to common variants. Here we present carrier statistic, a statistical framework to prioritize disease-related rare variants by integrating gene expression data. By quantifying the impact of rare variants on gene expression, carrier statistic can prioritize those rare variants that have large functional consequence in the diseased patients. Through simulation studies and analyzing real multi-omics dataset, we demonstrated that carrier statistic is applicable in studies with limited sample size (a few hundreds) and achieves substantially higher sensitivity than existing rare variants association methods. Application to Alzheimer's disease reveals 16 rare variants within 15 genes with extreme carrier statistics. The carrier statistic method can be applied to various rare variant types and is adaptable to other omics data modalities, offering a powerful tool for investigating the molecular mechanisms underlying complex diseases.
Collapse
Affiliation(s)
- Hanmin Guo
- Department of Statistics, Stanford University, Stanford, California 94305, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Alexander Eckehart Urban
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Wing Hung Wong
- Department of Statistics, Stanford University, Stanford, California 94305, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California 94305, USA
| |
Collapse
|
22
|
Schuermans A, Vlasschaert C, Nauffal V, Cho SMJ, Uddin MM, Nakao T, Niroula A, Klarqvist MDR, Weeks LD, Lin AE, Saadatagah S, Lannery K, Wong M, Hornsby W, Lubitz SA, Ballantyne C, Jaiswal S, Libby P, Ebert BL, Bick AG, Ellinor PT, Natarajan P, Honigberg MC. Clonal haematopoiesis of indeterminate potential predicts incident cardiac arrhythmias. Eur Heart J 2024; 45:791-805. [PMID: 37952204 PMCID: PMC10919923 DOI: 10.1093/eurheartj/ehad670] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 09/07/2023] [Accepted: 09/26/2023] [Indexed: 11/14/2023] Open
Abstract
BACKGROUND AND AIMS Clonal haematopoiesis of indeterminate potential (CHIP), the age-related expansion of blood cells with preleukemic mutations, is associated with atherosclerotic cardiovascular disease and heart failure. This study aimed to test the association of CHIP with new-onset arrhythmias. METHODS UK Biobank participants without prevalent arrhythmias were included. Co-primary study outcomes were supraventricular arrhythmias, bradyarrhythmias, and ventricular arrhythmias. Secondary outcomes were cardiac arrest, atrial fibrillation, and any arrhythmia. Associations of any CHIP [variant allele fraction (VAF) ≥ 2%], large CHIP (VAF ≥10%), and gene-specific CHIP subtypes with incident arrhythmias were evaluated using multivariable-adjusted Cox regression. Associations of CHIP with myocardial interstitial fibrosis [T1 measured using cardiac magnetic resonance (CMR)] were also tested. RESULTS This study included 410 702 participants [CHIP: n = 13 892 (3.4%); large CHIP: n = 9191 (2.2%)]. Any and large CHIP were associated with multi-variable-adjusted hazard ratios of 1.11 [95% confidence interval (CI) 1.04-1.18; P = .001] and 1.13 (95% CI 1.05-1.22; P = .001) for supraventricular arrhythmias, 1.09 (95% CI 1.01-1.19; P = .031) and 1.13 (95% CI 1.03-1.25; P = .011) for bradyarrhythmias, and 1.16 (95% CI, 1.00-1.34; P = .049) and 1.22 (95% CI 1.03-1.45; P = .021) for ventricular arrhythmias, respectively. Associations were independent of coronary artery disease and heart failure. Associations were also heterogeneous across arrhythmia subtypes and strongest for cardiac arrest. Gene-specific analyses revealed an increased risk of arrhythmias across driver genes other than DNMT3A. Large CHIP was associated with 1.31-fold odds (95% CI 1.07-1.59; P = .009) of being in the top quintile of myocardial fibrosis by CMR. CONCLUSIONS CHIP may represent a novel risk factor for incident arrhythmias, indicating a potential target for modulation towards arrhythmia prevention and treatment.
Collapse
Affiliation(s)
- Art Schuermans
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | | | - Victor Nauffal
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - So Mi Jemma Cho
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Integrative Research Center for Cerebrovascular and Cardiovascular Diseases, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Md Mesbah Uddin
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
| | - Tetsushi Nakao
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Abhishek Niroula
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Laboratory Medicine, Lund University, Lund, Sweden
| | | | - Lachelle D Weeks
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Amy E Lin
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | - Kim Lannery
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
| | - Megan Wong
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
| | - Whitney Hornsby
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
| | - Steven A Lubitz
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
| | | | - Siddhartha Jaiswal
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Peter Libby
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Benjamin L Ebert
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA, USA
| | - Alexander G Bick
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Patrick T Ellinor
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
| | - Pradeep Natarajan
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
| | - Michael C Honigberg
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, 75 Ames St., Cambridge, MA 02142, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St., Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
| |
Collapse
|
23
|
Fei CJ, Li ZY, Ning J, Yang L, Wu BS, Kang JJ, Liu WS, He XY, You J, Chen SD, Yu H, Huang ZL, Feng JF, Yu JT, Cheng W. Exome sequencing identifies genes associated with sleep-related traits. Nat Hum Behav 2024; 8:576-589. [PMID: 38177695 DOI: 10.1038/s41562-023-01785-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 11/15/2023] [Indexed: 01/06/2024]
Abstract
Sleep is vital for human health and has a moderate heritability. Previous genome-wide association studies have limitations in capturing the role of rare genetic variants in sleep-related traits. Here we conducted a large-scale exome-wide association study of eight sleep-related traits (sleep duration, insomnia symptoms, chronotype, daytime sleepiness, daytime napping, ease of getting up in the morning, snoring and sleep apnoea) among 450,000 participants from UK Biobank. We identified 22 new genes associated with chronotype (ADGRL4, COL6A3, CLK4 and KRTAP3-3), daytime sleepiness (ST3GAL1 and ANKRD12), daytime napping (PLEKHM1, ANKRD12 and ZBTB21), snoring (WDR59) and sleep apnoea (13 genes). Notably, 20 of these genes were confirmed to be significantly associated with sleep disorders in the FinnGen cohort. Enrichment analysis revealed that these discovered genes were enriched in circadian rhythm and central nervous system neurons. Phenotypic association analysis showed that ANKRD12 was associated with cognition and inflammatory traits. Our results demonstrate the value of large-scale whole-exome analysis in understanding the genetic architecture of sleep-related traits and potential biological mechanisms.
Collapse
Affiliation(s)
- Chen-Jie Fei
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ze-Yu Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Jing Ning
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ju-Jiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Wei-Shi Liu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiao-Yu He
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jia You
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Huan Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhi-Li Huang
- Department of Pharmacology, School of Basic Medical Sciences, State Key Laboratory of Medical Neurobiology, Institutes of Brain Science and Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
| |
Collapse
|
24
|
Rowley AM, Yao G, Andrews L, Bedermann A, Biddulph R, Bingham R, Brady JJ, Buxton R, Cecconie T, Cooper R, Csakai A, Gao EN, Grenier-Davies MC, Lawler M, Lian Y, Macina J, Macphee C, Marcaurelle L, Martin J, McCormick P, Pindoria R, Rauch M, Rocque W, Shen Y, Shewchuk LM, Squire M, Stebbeds W, Tear W, Wang X, Ward P, Xiao S. Discovery and SAR Study of Boronic Acid-Based Selective PDE3B Inhibitors from a Novel DNA-Encoded Library. J Med Chem 2024; 67:2049-2065. [PMID: 38284310 DOI: 10.1021/acs.jmedchem.3c01562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
Human genetic evidence shows that PDE3B is associated with metabolic and dyslipidemia phenotypes. A number of PDE3 family selective inhibitors have been approved by the FDA for various indications; however, given the undesirable proarrhythmic effects in the heart, selectivity for PDE3B inhibition over closely related family members (such as PDE3A; 48% identity) is a critical consideration for development of PDE3B therapeutics. Selectivity for PDE3B over PDE3A may be achieved in a variety of ways, including properties intrinsic to the compound or tissue-selective targeting. The high (>95%) active site homology between PDE3A and B represents a massive obstacle for obtaining selectivity at the active site; however, utilization of libraries with high molecular diversity in high throughput screens may uncover selective chemical matter. Herein, we employed a DNA-encoded library screen to identify PDE3B-selective inhibitors and identified potent and selective boronic acid compounds bound at the active site.
Collapse
Affiliation(s)
- Ann M Rowley
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Gang Yao
- GSK, Encoded Library Technologies, NCE Molecular Discovery, 200 Cambridge Park Drive, Cambridge, Massachusetts 02140, United States
| | - Logan Andrews
- 23andMe Inc, Therapeutics, 349 Oyster Point Boulevard, South San Francisco, California 94080, United States
| | - Aaron Bedermann
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Ross Biddulph
- GSK Medicines Research Centre, Gunnels Wood Road, Stevenage SG1 2NY, Hertfordshire, U.K
| | - Ryan Bingham
- GSK Medicines Research Centre, Gunnels Wood Road, Stevenage SG1 2NY, Hertfordshire, U.K
| | - Jennifer J Brady
- 23andMe Inc, Therapeutics, 349 Oyster Point Boulevard, South San Francisco, California 94080, United States
| | - Rachel Buxton
- GSK Medicines Research Centre, Gunnels Wood Road, Stevenage SG1 2NY, Hertfordshire, U.K
| | - Ted Cecconie
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Rona Cooper
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Adam Csakai
- GSK, Encoded Library Technologies, NCE Molecular Discovery, 200 Cambridge Park Drive, Cambridge, Massachusetts 02140, United States
| | - Enoch N Gao
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Melissa C Grenier-Davies
- GSK, Encoded Library Technologies, NCE Molecular Discovery, 200 Cambridge Park Drive, Cambridge, Massachusetts 02140, United States
| | - Meghan Lawler
- GSK, Encoded Library Technologies, NCE Molecular Discovery, 200 Cambridge Park Drive, Cambridge, Massachusetts 02140, United States
| | - Yiqian Lian
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Justyna Macina
- GSK Medicines Research Centre, Gunnels Wood Road, Stevenage SG1 2NY, Hertfordshire, U.K
| | - Colin Macphee
- GSK Medicines Research Centre, Gunnels Wood Road, Stevenage SG1 2NY, Hertfordshire, U.K
| | - Lisa Marcaurelle
- GSK, Encoded Library Technologies, NCE Molecular Discovery, 200 Cambridge Park Drive, Cambridge, Massachusetts 02140, United States
| | - John Martin
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Patricia McCormick
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Rekha Pindoria
- GSK Medicines Research Centre, Gunnels Wood Road, Stevenage SG1 2NY, Hertfordshire, U.K
| | - Martin Rauch
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Warren Rocque
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Yingnian Shen
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Lisa M Shewchuk
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Michael Squire
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Will Stebbeds
- GSK Medicines Research Centre, Gunnels Wood Road, Stevenage SG1 2NY, Hertfordshire, U.K
| | - Westley Tear
- GSK, Encoded Library Technologies, NCE Molecular Discovery, 200 Cambridge Park Drive, Cambridge, Massachusetts 02140, United States
| | - Xin Wang
- 23andMe Inc, Therapeutics, 349 Oyster Point Boulevard, South San Francisco, California 94080, United States
| | - Paris Ward
- GSK, 1250 South Collegeville Road, Collegeville, Pennsylvania 19426, United States
| | - Shouhua Xiao
- 23andMe Inc, Therapeutics, 349 Oyster Point Boulevard, South San Francisco, California 94080, United States
| |
Collapse
|
25
|
Colvin A, Youssef S, Noh H, Wright J, Jumonville G, LaRow Brown K, Tatonetti NP, Milner JD, Weng C, Bordone LA, Petukhova L. Inborn Errors of Immunity Contribute to the Burden of Skin Disease and Create Opportunities for Improving the Practice of Dermatology. J Invest Dermatol 2024; 144:307-315.e1. [PMID: 37716649 DOI: 10.1016/j.jid.2023.08.018] [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: 06/28/2023] [Revised: 07/31/2023] [Accepted: 08/01/2023] [Indexed: 09/18/2023]
Abstract
Opportunities to improve the clinical management of skin disease are being created by advances in genomic medicine. Large-scale sequencing increasingly challenges notions about single-gene disorders. It is now apparent that monogenic etiologies make appreciable contributions to the population burden of disease and that they are underrecognized in clinical practice. A genetic diagnosis informs on molecular pathology and may direct targeted treatments and tailored prevention strategies for patients and family members. It also generates knowledge about disease pathogenesis and management that is relevant to patients without rare pathogenic variants. Inborn errors of immunity are a large class of monogenic etiologies that have been well-studied and contribute to the population burden of inflammatory diseases. To further delineate the contributions of inborn errors of immunity to the pathogenesis of skin disease, we performed a set of analyses that identified 316 inborn errors of immunity associated with skin pathologies, including common skin diseases. These data suggest that clinical sequencing is underutilized in dermatology. We next use these data to derive a network that illuminates the molecular relationships of these disorders and suggests an underlying etiological organization to immune-mediated skin disease. Our results motivate the further development of a molecularly derived and data-driven reorganization of clinical diagnoses of skin disease.
Collapse
Affiliation(s)
- Annelise Colvin
- Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Soundos Youssef
- Department of Pediatrics and Adolescent Medicine, American University of Beirut Medical Center, Beirut, Lebanon
| | - Heeju Noh
- Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Julia Wright
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Ghislaine Jumonville
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Kathleen LaRow Brown
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Nicholas P Tatonetti
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA; Department of Computational Biomedicine, Cedars-Sinai Medical Center, West Hollywood, California, USA; Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Joshua D Milner
- Department of Pediatrics, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Lindsey A Bordone
- Department of Dermatology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Lynn Petukhova
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA; Department of Dermatology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA.
| |
Collapse
|
26
|
Chen SD, You J, Zhang W, Wu BS, Ge YJ, Xiang ST, Du J, Kuo K, Banaschewski T, Barker GJ, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Martinot MLP, Artiges E, Nees F, Orfanos DP, Lemaitre H, Paus T, Poustka L, Hohmann S, Millenet S, Baeuchl C, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Feng JF, Dong Q, Cheng W, Yu JT. The genetic architecture of the human hypothalamus and its involvement in neuropsychiatric behaviours and disorders. Nat Hum Behav 2024:10.1038/s41562-023-01792-6. [PMID: 38182882 DOI: 10.1038/s41562-023-01792-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 11/20/2023] [Indexed: 01/07/2024]
Abstract
Despite its crucial role in the regulation of vital metabolic and neurological functions, the genetic architecture of the hypothalamus remains unknown. Here we conducted multivariate genome-wide association studies (GWAS) using hypothalamic imaging data from 32,956 individuals to uncover the genetic underpinnings of the hypothalamus and its involvement in neuropsychiatric traits. There were 23 significant loci associated with the whole hypothalamus and its subunits, with functional enrichment for genes involved in intracellular trafficking systems and metabolic processes of steroid-related compounds. The hypothalamus exhibited substantial genetic associations with limbic system structures and neuropsychiatric traits including chronotype, risky behaviour, cognition, satiety and sympathetic-parasympathetic activity. The strongest signal in the primary GWAS, the ADAMTS8 locus, was replicated in three independent datasets (N = 1,685-4,321) and was strengthened after meta-analysis. Exome-wide association analyses added evidence to the association for ADAMTS8, and Mendelian randomization showed lower ADAMTS8 expression with larger hypothalamic volumes. The current study advances our understanding of complex structure-function relationships of the hypothalamus and provides insights into the molecular mechanisms that underlie hypothalamic formation.
Collapse
Affiliation(s)
- Shi-Dong Chen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Jia You
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Wei Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Yi-Jun Ge
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Shi-Tong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Jing Du
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Kevin Kuo
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Institute of Psychiatry, Psychology & Neuroscience, Social, Genetic, Developmental Psychiatry Centre, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrie", University Paris-Saclay, CNRS, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrie", University Paris-Saclay, CNRS, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-sur-Yvette, France
- AP-HP, Sorbonne University, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrie", University Paris-Saclay, CNRS, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Etampes, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | | | - Herve Lemaitre
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
- Institut des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, Bordeaux, France
| | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hosptalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry, Psychotherapy and Psychosomatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Christian Baeuchl
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China.
| | - Wei Cheng
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China.
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, China.
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China.
| |
Collapse
|
27
|
Levin MG, Aragam KG. Truncations of Titin and Left Atrial Cardiomyopathy: Comment on Henkens et al.'s article, Left Atrial Function in Patients With Titin Cardiomyopathy. J Card Fail 2024; 30:61-63. [PMID: 37451603 DOI: 10.1016/j.cardfail.2023.06.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 06/16/2023] [Indexed: 07/18/2023]
Affiliation(s)
- Michael G Levin
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
| | - Krishna G Aragam
- Massachusetts General Hospital and Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA.
| |
Collapse
|
28
|
Schindler LS, Subramaniapillai S, Ambikairajah A, Barth C, Crestol A, Voldsbekk I, Beck D, Gurholt TP, Topiwala A, Suri S, Ebmeier KP, Andreassen OA, Draganski B, Westlye LT, de Lange AMG. Cardiometabolic health across menopausal years is linked to white matter hyperintensities up to a decade later. Front Glob Womens Health 2023; 4:1320640. [PMID: 38213741 PMCID: PMC10783171 DOI: 10.3389/fgwh.2023.1320640] [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: 10/12/2023] [Accepted: 12/06/2023] [Indexed: 01/13/2024] Open
Abstract
Introduction The menopause transition is associated with several cardiometabolic risk factors. Poor cardiometabolic health is further linked to microvascular brain lesions, which can be detected as white matter hyperintensities (WMHs) using T2-FLAIR magnetic resonance imaging (MRI) scans. Females show higher risk for WMHs post-menopause, but it remains unclear whether changes in cardiometabolic risk factors underlie menopause-related increase in brain pathology. Methods In this study, we assessed whether cross-sectional measures of cardiometabolic health, including body mass index (BMI) and waist-to-hip ratio (WHR), blood lipids, blood pressure, and long-term blood glucose (HbA1c), as well as longitudinal changes in BMI and WHR, differed according to menopausal status at baseline in 9,882 UK Biobank females (age range 40-70 years, n premenopausal = 3,529, n postmenopausal = 6,353). Furthermore, we examined whether these cardiometabolic factors were associated with WMH outcomes at the follow-up assessment, on average 8.78 years after baseline. Results Postmenopausal females showed higher levels of baseline blood lipids (HDL β = 0.14, p < 0.001, LDL β = 0.20, p < 0.001, triglycerides β = 0.12, p < 0.001) and HbA1c (β = 0.24, p < 0.001) compared to premenopausal women, beyond the effects of age. Over time, BMI increased more in the premenopausal compared to the postmenopausal group (β = -0.08, p < 0.001), while WHR increased to a similar extent in both groups (β = -0.03, p = 0.102). The change in WHR was however driven by increased waist circumference only in the premenopausal group. While the group level changes in BMI and WHR were in general small, these findings point to distinct anthropometric changes in pre- and postmenopausal females over time. Higher baseline measures of BMI, WHR, triglycerides, blood pressure, and HbA1c, as well as longitudinal increases in BMI and WHR, were associated with larger WMH volumes (β range = 0.03-0.13, p ≤ 0.002). HDL showed a significant inverse relationship with WMH volume (β = -0.27, p < 0.001). Discussion Our findings emphasise the importance of monitoring cardiometabolic risk factors in females from midlife through the menopause transition and into the postmenopausal phase, to ensure improved cerebrovascular outcomes in later years.
Collapse
Affiliation(s)
- Louise S. Schindler
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Sivaniya Subramaniapillai
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ananthan Ambikairajah
- Discipline of Psychology, Faculty of Health, University of Canberra, Canberra, Australia
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Arielle Crestol
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Irene Voldsbekk
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dani Beck
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tiril P. Gurholt
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anya Topiwala
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Klaus P. Ebmeier
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Bogdan Draganski
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Lars T. Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ann-Marie G. de Lange
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| |
Collapse
|
29
|
Sun HY, Lin XY. Genetic perspectives on childhood monogenic diabetes: Diagnosis, management, and future directions. World J Diabetes 2023; 14:1738-1753. [PMID: 38222792 PMCID: PMC10784795 DOI: 10.4239/wjd.v14.i12.1738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 10/10/2023] [Accepted: 11/14/2023] [Indexed: 12/14/2023] Open
Abstract
Monogenic diabetes is caused by one or even more genetic variations, which may be uncommon yet have a significant influence and cause diabetes at an early age. Monogenic diabetes affects 1 to 5% of children, and early detection and gene-tically focused treatment of neonatal diabetes and maturity-onset diabetes of the young can significantly improve long-term health and well-being. The etiology of monogenic diabetes in childhood is primarily attributed to genetic variations affecting the regulatory genes responsible for beta-cell activity. In rare instances, mutations leading to severe insulin resistance can also result in the development of diabetes. Individuals diagnosed with specific types of monogenic diabetes, which are commonly found, can transition from insulin therapy to sulfonylureas, provided they maintain consistent regulation of their blood glucose levels. Scientists have successfully devised materials and methodologies to distinguish individuals with type 1 or 2 diabetes from those more prone to monogenic diabetes. Genetic screening with appropriate findings and interpretations is essential to establish a prognosis and to guide the choice of therapies and management of these interrelated ailments. This review aims to design a comprehensive literature summarizing genetic insights into monogenetic diabetes in children and adolescents as well as summarizing their diagnosis and mana-gement.
Collapse
Affiliation(s)
- Hong-Yan Sun
- Department of Endocrine and Metabolic Diseases, Yantaishan Hospital, Yantai 264003, Shandong Province, China
| | - Xiao-Yan Lin
- Department of Endocrine and Metabolic Diseases, Yantaishan Hospital, Yantai 264003, Shandong Province, China
| |
Collapse
|
30
|
Schoenmakers E, Marelli F, Jørgensen HF, Visser WE, Moran C, Groeneweg S, Avalos C, Jurgens SJ, Figg N, Finigan A, Wali N, Agostini M, Wardle-Jones H, Lyons G, Rusk R, Gopalan D, Twiss P, Visser JJ, Goddard M, Nashef SAM, Heijmen R, Clift P, Sinha S, Pirruccello JP, Ellinor PT, Busch-Nentwich EM, Ramirez-Solis R, Murphy MP, Persani L, Bennett M, Chatterjee K. Selenoprotein deficiency disorder predisposes to aortic aneurysm formation. Nat Commun 2023; 14:7994. [PMID: 38042913 PMCID: PMC10693596 DOI: 10.1038/s41467-023-43851-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 11/22/2023] [Indexed: 12/04/2023] Open
Abstract
Aortic aneurysms, which may dissect or rupture acutely and be lethal, can be a part of multisystem disorders that have a heritable basis. We report four patients with deficiency of selenocysteine-containing proteins due to selenocysteine Insertion Sequence Binding Protein 2 (SECISBP2) mutations who show early-onset, progressive, aneurysmal dilatation of the ascending aorta due to cystic medial necrosis. Zebrafish and male mice with global or vascular smooth muscle cell (VSMC)-targeted disruption of Secisbp2 respectively show similar aortopathy. Aortas from patients and animal models exhibit raised cellular reactive oxygen species, oxidative DNA damage and VSMC apoptosis. Antioxidant exposure or chelation of iron prevents oxidative damage in patient's cells and aortopathy in the zebrafish model. Our observations suggest a key role for oxidative stress and cell death, including via ferroptosis, in mediating aortic degeneration.
Collapse
Affiliation(s)
- Erik Schoenmakers
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Federica Marelli
- Laboratory of Endocrine and Metabolic Research, Istituto Auxologico Italiano IRCCS, 20149, Milano, Italy
| | - Helle F Jørgensen
- Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK
| | - W Edward Visser
- Department of Internal Medicine and Rotterdam Thyroid Center, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Carla Moran
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Stefan Groeneweg
- Department of Internal Medicine and Rotterdam Thyroid Center, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Carolina Avalos
- Department of Paediatric Endocrinology, Clinica Alemana de Santiago, Vitacura, Chile
| | - Sean J Jurgens
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Nichola Figg
- Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK
| | - Alison Finigan
- Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK
| | - Neha Wali
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Maura Agostini
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | | | - Greta Lyons
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Rosemary Rusk
- Department of Cardiology, Addenbrookes Hospital, Cambridge, UK
| | - Deepa Gopalan
- Department of Radiology, Addenbrookes Hospital, Cambridge, UK
| | - Philip Twiss
- Cambridge Genomics Laboratory, Addenbrookes Hospital, Cambridge, UK
| | - Jacob J Visser
- Department of Radiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Martin Goddard
- Department of Pathology, Royal Papworth Hospital, Cambridge, UK
| | - Samer A M Nashef
- Department of Cardiothoracic Surgery, Royal Papworth Hospital, Cambridge, UK
| | - Robin Heijmen
- Department of Cardiothoracic Surgery, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Paul Clift
- Department of Cardiology, Queen Elizabeth Hospital, Birmingham, UK
| | - Sanjay Sinha
- Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK
| | - James P Pirruccello
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Cardiology, University of California San Francisco, San Francisco, CA, USA
| | - Patrick T Ellinor
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Michael P Murphy
- MRC Mitochondrial Biology Unit, University of Cambridge, Cambridge, UK
| | - Luca Persani
- Laboratory of Endocrine and Metabolic Research, Istituto Auxologico Italiano IRCCS, 20149, Milano, Italy
- Department of Medical Biotechnologies and Translational Medicine, University of Milan, 20100, Milano, Italy
| | - Martin Bennett
- Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK
| | - Krishna Chatterjee
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
| |
Collapse
|
31
|
van der Voorn SM, van Drie E, Proost V, Dimitrova K, Ernst RF, James CA, Tichnell C, Murray B, Calkins H, Saguner AM, Duru F, Ellinor PT, Bezzina CR, Jurgens SJ, van Tintelen JP, van Veen TAB. Lack of Evidence for the Role of the p.(Ser96Ala) Polymorphism in Histidine-Rich Calcium Binding Protein as a Secondary Hit in Cardiomyopathies. Int J Mol Sci 2023; 24:15931. [PMID: 37958923 PMCID: PMC10648441 DOI: 10.3390/ijms242115931] [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: 09/20/2023] [Revised: 10/17/2023] [Accepted: 11/01/2023] [Indexed: 11/15/2023] Open
Abstract
Inherited forms of arrhythmogenic and dilated cardiomyopathy (ACM and DCM) are characterized by variable disease expression and age-related penetrance. Calcium (Ca2+) is crucially important for proper cardiac function, and dysregulation of Ca2+ homeostasis seems to underly cardiomyopathy etiology. A polymorphism, c.286T>G p.(Ser96Ala), in the gene encoding the histidine-rich Ca2+ binding (HRC) protein, relevant for sarcoplasmic reticulum Ca2+ cycling, has previously been associated with a marked increased risk of life-threatening arrhythmias among idiopathic DCM patients. Following this finding, we investigated whether p.(Ser96Ala) affects major cardiac disease manifestations in carriers of the phospholamban (PLN) c.40_42delAGA; p.(Arg14del) pathogenic variant (cohort 1); patients diagnosed with, or predisposed to, ACM (cohort 2); and DCM patients (cohort 3). We found that the allele frequency of the p.(Ser96Ala) polymorphism was similar across the general European-American population (control cohort, 40.3-42.2%) and the different cardiomyopathy cohorts (cohorts 1-3, 40.9-43.9%). Furthermore, the p.(Ser96Ala) polymorphism was not associated with life-threatening arrhythmias or heart failure-related events across various patient cohorts. We therefore conclude that there is a lack of evidence supporting the important role of the HRC p.(Ser96Ala) polymorphism as a modifier in cardiomyopathy, refuting previous findings. Further research is required to identify bona fide genomic predictors for the stratification of cardiomyopathy patients and their risk for life-threatening outcomes.
Collapse
Affiliation(s)
- Stephanie M. van der Voorn
- Department of Medical Physiology, Division Heart & Lungs, University Medical Center Utrecht, 3584 CM Utrecht, The Netherlands (K.D.)
| | - Esmée van Drie
- Department of Genetics, Division Heart & Lungs, University Medical Center Utrecht, 3584 CM Utrecht, The Netherlands
- Netherlands Heart Institute, 3511 EP Utrecht, The Netherlands
| | - Virginnio Proost
- Departments of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers Location Academic Medical Center, 1105 AZ Amsterdam, The Netherlands (C.R.B.)
| | - Kristina Dimitrova
- Department of Medical Physiology, Division Heart & Lungs, University Medical Center Utrecht, 3584 CM Utrecht, The Netherlands (K.D.)
| | | | - Robert F. Ernst
- Department of Genetics, Division Heart & Lungs, University Medical Center Utrecht, 3584 CM Utrecht, The Netherlands
| | - Cynthia A. James
- Department of Medicine, Division Cardiology, Johns Hopkins University, Baltimore, MD 21218, USA (C.T.)
| | - Crystal Tichnell
- Department of Medicine, Division Cardiology, Johns Hopkins University, Baltimore, MD 21218, USA (C.T.)
| | - Brittney Murray
- Department of Medicine, Division Cardiology, Johns Hopkins University, Baltimore, MD 21218, USA (C.T.)
| | - Hugh Calkins
- Department of Medicine, Division Cardiology, Johns Hopkins University, Baltimore, MD 21218, USA (C.T.)
| | - Ardan M. Saguner
- Department of Cardiology, University Heart Center Zurich, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Firat Duru
- Department of Cardiology, University Heart Center Zurich, University Hospital Zurich, 8091 Zurich, Switzerland
- Center for Integrative Human Physiology (ZIHP), University of Zurich, 8091 Zurich, Switzerland
| | - Patrick T. Ellinor
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Connie R. Bezzina
- Departments of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers Location Academic Medical Center, 1105 AZ Amsterdam, The Netherlands (C.R.B.)
| | - Sean J. Jurgens
- Departments of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers Location Academic Medical Center, 1105 AZ Amsterdam, The Netherlands (C.R.B.)
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - J. Peter van Tintelen
- Department of Genetics, Division Heart & Lungs, University Medical Center Utrecht, 3584 CM Utrecht, The Netherlands
- Netherlands Heart Institute, 3511 EP Utrecht, The Netherlands
| | - Toon A. B. van Veen
- Department of Medical Physiology, Division Heart & Lungs, University Medical Center Utrecht, 3584 CM Utrecht, The Netherlands (K.D.)
| |
Collapse
|
32
|
Koyama S, Wang Y, Paruchuri K, Uddin MM, Cho SMJ, Urbut SM, Haidermota S, Hornsby WE, Green RC, Daly MJ, Neale BM, Ellinor PT, Smoller JW, Lebo MS, Karlson EW, Martin AR, Natarajan P. Decoding Genetics, Ancestry, and Geospatial Context for Precision Health. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.24.23297096. [PMID: 37961173 PMCID: PMC10635180 DOI: 10.1101/2023.10.24.23297096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Mass General Brigham, an integrated healthcare system based in the Greater Boston area of Massachusetts, annually serves 1.5 million patients. We established the Mass General Brigham Biobank (MGBB), encompassing 142,238 participants, to unravel the intricate relationships among genomic profiles, environmental context, and disease manifestations within clinical practice. In this study, we highlight the impact of ancestral diversity in the MGBB by employing population genetics, geospatial assessment, and association analyses of rare and common genetic variants. The population structures captured by the genetics mirror the sequential immigration to the Greater Boston area throughout American history, highlighting communities tied to shared genetic and environmental factors. Our investigation underscores the potency of unbiased, large-scale analyses in a healthcare-affiliated biobank, elucidating the dynamic interplay across genetics, immigration, structural geospatial factors, and health outcomes in one of the earliest American sites of European colonization.
Collapse
Affiliation(s)
- Satoshi Koyama
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Ying Wang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kaavya Paruchuri
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Md Mesbah Uddin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - So Mi J. Cho
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Integrative Research Center for Cerebrovascular and Cardiovascular Diseases, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sarah M. Urbut
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Sara Haidermota
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Whitney E. Hornsby
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Robert C. Green
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine (Genetics), MassGeneralBrigham, Boston, MA, USA
- Broad Institute and Ariadne Labs, Boston, MA, USA
| | - Mark J. Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), Finland
- University of Helsinki, Helsinki, Finland
| | - Benjamin M. Neale
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Patrick T. Ellinor
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jordan W. Smoller
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Matthew S. Lebo
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Mass General Brigham Personalized Medicine, Cambridge, MA, USA
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Elizabeth W. Karlson
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Mass General Brigham Personalized Medicine, Cambridge, MA, USA
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women’s Hospital., Boston, MA, USA
| | - Alicia R. Martin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Pradeep Natarajan
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
33
|
Jurgens SJ, Funke B. Towards Proactive "Sequence-First" Risk Prediction for Inherited Cardiomyopathies. JACC. HEART FAILURE 2023:S2213-1779(23)00612-1. [PMID: 37897458 DOI: 10.1016/j.jchf.2023.08.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Accepted: 08/29/2023] [Indexed: 10/30/2023]
Affiliation(s)
- Sean J Jurgens
- Department of Experimental Cardiology, Heart Center, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands; Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Amsterdam, the Netherlands; Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
| | - Birgit Funke
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| |
Collapse
|
34
|
Lipov A, Jurgens SJ, Mazzarotto F, Allouba M, Pirruccello JP, Aguib Y, Gennarelli M, Yacoub MH, Ellinor PT, Bezzina CR, Walsh R. Exploring the complex spectrum of dominance and recessiveness in genetic cardiomyopathies. NATURE CARDIOVASCULAR RESEARCH 2023; 2:1078-1094. [PMID: 38666070 PMCID: PMC11041721 DOI: 10.1038/s44161-023-00346-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 09/07/2023] [Indexed: 04/28/2024]
Abstract
Discrete categorization of Mendelian disease genes into dominant and recessive models often oversimplifies their underlying genetic architecture. Cardiomyopathies (CMs) are genetic diseases with complex etiologies for which an increasing number of recessive associations have recently been proposed. Here, we comprehensively analyze all published evidence pertaining to biallelic variation associated with CM phenotypes to identify high-confidence recessive genes and explore the spectrum of monoallelic and biallelic variant effects in established recessive and dominant disease genes. We classify 18 genes with robust recessive association with CMs, largely characterized by dilated phenotypes, early disease onset and severe outcomes. Several of these genes have monoallelic association with disease outcomes and cardiac traits in the UK Biobank, including LMOD2 and ALPK3 with dilated and hypertrophic CM, respectively. Our data provide insights into the complex spectrum of dominance and recessiveness in genetic heart disease and demonstrate how such approaches enable the discovery of unexplored genetic associations.
Collapse
Affiliation(s)
- Alex Lipov
- Department of Experimental Cardiology, Heart Centre, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands
| | - Sean J. Jurgens
- Department of Experimental Cardiology, Heart Centre, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA USA
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | - Francesco Mazzarotto
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Mona Allouba
- National Heart and Lung Institute, Imperial College London, London, UK
- Aswan Heart Centre, Magdi Yacoub Heart Foundation, Aswan, Egypt
| | - James P. Pirruccello
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA USA
- Division of Cardiology, University of California, San Francisco, San Francisco, CA USA
| | - Yasmine Aguib
- National Heart and Lung Institute, Imperial College London, London, UK
- Aswan Heart Centre, Magdi Yacoub Heart Foundation, Aswan, Egypt
| | - Massimo Gennarelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
- Genetics Unit, Istituto di Ricovero e Cura a Carattere Scientifico, Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Magdi H. Yacoub
- National Heart and Lung Institute, Imperial College London, London, UK
- Aswan Heart Centre, Magdi Yacoub Heart Foundation, Aswan, Egypt
- Harefield Heart Science Centre, Uxbridge, UK
| | - Patrick T. Ellinor
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA USA
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA USA
| | - Connie R. Bezzina
- Department of Experimental Cardiology, Heart Centre, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart, Amsterdam, the Netherlands
| | - Roddy Walsh
- Department of Experimental Cardiology, Heart Centre, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands
| |
Collapse
|
35
|
Vorstman JAS, Scherer SW. Contemplating syndromic autism. Genet Med 2023; 25:100919. [PMID: 37330697 DOI: 10.1016/j.gim.2023.100919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 06/07/2023] [Accepted: 06/08/2023] [Indexed: 06/19/2023] Open
Affiliation(s)
- Jacob A S Vorstman
- Department of Psychiatry, Hospital for Sick Children University of Toronto, Toronto, ON, Canada; Program in Genetics and Genome Biology, Hospital for Sick Children, Toronto, ON, Canada; The Centre for Applied Genomics, Hospital for Sick Children, Toronto, ON, Canada.
| | - Stephen W Scherer
- Program in Genetics and Genome Biology, Hospital for Sick Children, Toronto, ON, Canada; The Centre for Applied Genomics, Hospital for Sick Children, Toronto, ON, Canada; McLaughlin Centre and Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
| |
Collapse
|
36
|
Rani DS, Kasala A, Dhandapany PS, Muthusami U, Kunnoth S, Rathinavel A, Ayapati DR, Thangaraj K. Novel MYBPC3 Mutations in Indian Population with Cardiomyopathies. Pharmgenomics Pers Med 2023; 16:883-893. [PMID: 37750083 PMCID: PMC10518145 DOI: 10.2147/pgpm.s407179] [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: 03/17/2023] [Accepted: 08/11/2023] [Indexed: 09/27/2023] Open
Abstract
Background Mutations in Myosin Binding Protein C (MYBPC3) are one of the most frequent causes of cardiomyopathies in the world, but not much data are available in India. Methods We carried out targeted direct sequencing of MYBPC3 in 115 hypertrophic (HCM) and 127 dilated (DCM) cardiomyopathies against 197 ethnically matched healthy controls from India. Results We detected 34 single nucleotide variations in MYBPC3, of which 19 were novel. We found a splice site mutation [(IVS6+2T) T>G] and 16 missense mutations in Indian cardiomyopathies [5 in HCM; E258K, T262S, H287L, R408M, V483A: 4 in DCM; T146N, V321L, A392T, E393K and 7 in both HCM and DCM; L104M, V158M, S236G, R272C, T290A, G522E, A626V], but those were absent in 197 normal healthy controls. Interestingly, we found 7 out of 16 missense mutations (V158M, E258K, R272C, A392T, V483A, G522E, and A626V) in MYBPC3 were altering the evolutionarily conserved native amino acids, accounted for 8.7% and 6.3% in HCM and DCM, respectively. The bioinformatic tools predicted that those 7 missense mutations were pathogenic. Moreover, the co-segregation of those 7 mutations in families further confirmed their pathogenicity. Remarkably, we also identified compound mutations within the MYBPC3 gene of 6 cardiomyopathy patients (5%) with more severe disease phenotype; of which, 3 were HCM (2.6%) [(1. K244K + E258K + (IVS6+2T) T>G); (2. L104M + G522E + A626V); (3. P186P + G522E + A626V]; and 3 were DCM (2.4%) [(1. 5'UTR + A392T; 2. V158M+G522E; and 3.V158M + T262T + A626V]. Conclusion The present comprehensive study on MYBPC3 has revealed both single and compound mutations in MYBPC3 and their association with disease in Indian Population with Cardiomyopathies. Our findings may perhaps help in initiating diagnostic strategies and eventually recognizing the targets for therapeutic interventions.
Collapse
Grants
- Rani DS has been supported by the CSIR-CCMB, Hyderabad, Telangana, India. K Thangaraj has been supported by the JC Bose Fellowship
- SERB, DST, and The Government of India. However, the funders had no role in designing the study, the collection of data, the analysis of sequence data, the decision to publish, or the preparation of the manuscript
Collapse
Affiliation(s)
- Deepa Selvi Rani
- Department of Population and Medical Genomics, CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
| | - Apoorva Kasala
- Department of Population and Medical Genomics, CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
| | - Perundurai S Dhandapany
- Department of Cardiovascular Biology and Medicine, Institute for Stem Cell Science and Regenerative Medicine, Bangalore, Karnataka, India
| | - Uthiralingam Muthusami
- Department of Advanced Zoology and Biotechnology, Loyola College, Chennai, Tamil Nadu, India
| | - Sreejith Kunnoth
- Department of Advanced Zoology and Biotechnology, Loyola College, Chennai, Tamil Nadu, India
| | - Andiappan Rathinavel
- Department of Cardiology, Government Rajaji Hospital, Madurai, Tamil Nadu, India
| | - Dharma Rakshak Ayapati
- Department of Cardiology, Nizam’s Institute of Medical Sciences, Hyderabad, Telangana, India
| | - Kumarasamy Thangaraj
- Department of Population and Medical Genomics, CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
- DBT-Centre for DNA Fingerprinting and Diagnostics, Hyderabad, Telangana, India
| |
Collapse
|
37
|
Szedlak P, Steele D, Hopkins P. Cardiac muscle physiology. BJA Educ 2023; 23:350-357. [PMID: 37600215 PMCID: PMC10435365 DOI: 10.1016/j.bjae.2023.05.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/16/2023] [Indexed: 08/22/2023] Open
Affiliation(s)
- P. Szedlak
- Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | | | - P.M. Hopkins
- Leeds Teaching Hospitals NHS Trust, Leeds, UK
- University of Leeds, Leeds, UK
| |
Collapse
|
38
|
Pham C, Andrzejczyk K, Jurgens SJ, Lekanne Deprez R, Palm KC, Vermeer AM, Nijman J, Christiaans I, Barge-Schaapveld DQ, van Dessel PF, Beekman L, Choi SH, Lubitz SA, Skoric-Milosavljevic D, van den Bersselaar L, Jansen PR, Copier JS, Ellinor PT, Wilde AA, Bezzina CR, Lodder EM. Genetic Burden of TNNI3K in Diagnostic Testing of Patients With Dilated Cardiomyopathy and Supraventricular Arrhythmias. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2023; 16:328-336. [PMID: 37199186 PMCID: PMC10426786 DOI: 10.1161/circgen.122.003975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 04/10/2023] [Indexed: 05/19/2023]
Abstract
BACKGROUND Genetic variants in TNNI3K (troponin-I interacting kinase) have previously been associated with dilated cardiomyopathy (DCM), cardiac conduction disease, and supraventricular tachycardias. However, the link between TNNI3K variants and these cardiac phenotypes shows a lack of consensus concerning phenotype and protein function. METHODS We describe a systematic retrospective study of a cohort of patients undergoing genetic testing for cardiac arrhythmias and cardiomyopathy including TNNI3K. We further performed burden testing of TNNI3K in the UK Biobank. For 2 novel TNNI3K variants, we tested cosegregation. TNNI3K kinase function was estimated by TNNI3K autophosphorylation assays. RESULTS We demonstrate enrichment of rare coding TNNI3K variants in DCM patients in the Amsterdam cohort. In the UK Biobank, we observed an association between TNNI3K missense (but not loss-of-function) variants and DCM and atrial fibrillation. Furthermore, we demonstrate genetic segregation for 2 rare variants, TNNI3K-p.Ile512Thr and TNNI3K-p.His592Tyr, with phenotypes consisting of DCM, cardiac conduction disease, and supraventricular tachycardia, together with increased autophosphorylation. In contrast, TNNI3K-p.Arg556_Asn590del, a likely benign variant, demonstrated depleted autophosphorylation. CONCLUSIONS Our findings demonstrate an increased burden of rare coding TNNI3K variants in cardiac patients with DCM. Furthermore, we present 2 novel likely pathogenic TNNI3K variants with increased autophosphorylation, suggesting that enhanced autophosphorylation is likely to drive pathogenicity.
Collapse
Affiliation(s)
- Caroline Pham
- Department of Experimental Cardiology (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., C.R.B., E.M.L.), Heart Center, Amsterdam UMC location University of Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, the Netherlands (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., A.A.M.W., C.R.B., E.M.L.)
| | - Karolina Andrzejczyk
- Department of Experimental Cardiology (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., C.R.B., E.M.L.), Heart Center, Amsterdam UMC location University of Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, the Netherlands (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., A.A.M.W., C.R.B., E.M.L.)
| | - Sean J. Jurgens
- Department of Experimental Cardiology (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., C.R.B., E.M.L.), Heart Center, Amsterdam UMC location University of Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, the Netherlands (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., A.A.M.W., C.R.B., E.M.L.)
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.J.J., S.A.L., P.T.E.)
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (S.J.J., S.A.L., P.T.E.)
| | - Ronald Lekanne Deprez
- Department of Human Genetics, Amsterdam UMC location University of Amsterdam, the Netherlands (R.L.D., A.M.C.V., J.N., D.S.-M., P.R.J., E.M.L.)
| | - Kaylin C.A. Palm
- Department of Experimental Cardiology (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., C.R.B., E.M.L.), Heart Center, Amsterdam UMC location University of Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, the Netherlands (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., A.A.M.W., C.R.B., E.M.L.)
| | - Alexa M.C. Vermeer
- Department of Human Genetics, Amsterdam UMC location University of Amsterdam, the Netherlands (R.L.D., A.M.C.V., J.N., D.S.-M., P.R.J., E.M.L.)
| | - Janneke Nijman
- Department of Human Genetics, Amsterdam UMC location University of Amsterdam, the Netherlands (R.L.D., A.M.C.V., J.N., D.S.-M., P.R.J., E.M.L.)
| | - Imke Christiaans
- Department of Genetics, University Medical Center Groningen, University of Groningen, the Netherlands (I.C.)
| | | | - Pascal F.H.M. van Dessel
- Department of Cardiology, Thorax Center Twente, Medisch Spectrum Twente (MST), Enschede, the Netherlands (P.F.H.M.v.D.)
| | - Leander Beekman
- Department of Experimental Cardiology (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., C.R.B., E.M.L.), Heart Center, Amsterdam UMC location University of Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, the Netherlands (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., A.A.M.W., C.R.B., E.M.L.)
| | | | - Steven A. Lubitz
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.J.J., S.A.L., P.T.E.)
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (S.J.J., S.A.L., P.T.E.)
| | - Doris Skoric-Milosavljevic
- Department of Human Genetics, Amsterdam UMC location University of Amsterdam, the Netherlands (R.L.D., A.M.C.V., J.N., D.S.-M., P.R.J., E.M.L.)
| | - Lisa van den Bersselaar
- Department of Clinical Genetics, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (L.v.d.B.)
| | - Philip R. Jansen
- Department of Human Genetics, Amsterdam UMC location University of Amsterdam, the Netherlands (R.L.D., A.M.C.V., J.N., D.S.-M., P.R.J., E.M.L.)
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Complex Trait Genetics, the Netherlands (P.R.J.)
| | - Jaël S. Copier
- Department of Experimental Cardiology (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., C.R.B., E.M.L.), Heart Center, Amsterdam UMC location University of Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, the Netherlands (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., A.A.M.W., C.R.B., E.M.L.)
| | - Patrick T. Ellinor
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (S.J.J., S.A.L., P.T.E.)
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (S.J.J., S.A.L., P.T.E.)
| | - Arthur A.M. Wilde
- Department of Cardiology (A.A.M.W.), Heart Center, Amsterdam UMC location University of Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, the Netherlands (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., A.A.M.W., C.R.B., E.M.L.)
| | - Connie R. Bezzina
- Department of Experimental Cardiology (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., C.R.B., E.M.L.), Heart Center, Amsterdam UMC location University of Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, the Netherlands (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., A.A.M.W., C.R.B., E.M.L.)
| | - Elisabeth M. Lodder
- Department of Experimental Cardiology (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., C.R.B., E.M.L.), Heart Center, Amsterdam UMC location University of Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, the Netherlands (C.P., K.A., S.J.J., K.C.A.P., L.B., J.S.C., A.A.M.W., C.R.B., E.M.L.)
- Department of Human Genetics, Amsterdam UMC location University of Amsterdam, the Netherlands (R.L.D., A.M.C.V., J.N., D.S.-M., P.R.J., E.M.L.)
| |
Collapse
|
39
|
Wang X, Ryu J, Kim J, Ramirez A, Mayo KR, Condon H, Vaitinadin NS, Ohno-Machado L, Talavera GA, Ellinor PT, Lubitz SA, Choi SH. Common and rare variants associated with cardiometabolic traits across 98,622 whole-genome sequences in the All of Us research program. J Hum Genet 2023; 68:565-570. [PMID: 37072623 PMCID: PMC10524735 DOI: 10.1038/s10038-023-01147-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 03/23/2023] [Accepted: 03/27/2023] [Indexed: 04/20/2023]
Abstract
All of Us is a biorepository aiming to advance biomedical research by providing various types of data in diverse human populations. Here we present a demonstration project validating the program's genomic data in 98,622 participants. We sought to replicate known genetic associations for three diseases (atrial fibrillation [AF], coronary artery disease, type 2 diabetes [T2D]) and two quantitative traits (height and low-density lipoprotein [LDL]) by conducting common and rare variant analyses. We identified one known risk locus for AF, five loci for T2D, 143 loci for height, and nine loci for LDL. In gene-based burden tests for rare loss-of-function variants, we replicated associations between TTN and AF, GIGYF1 and T2D, ADAMTS17, ACAN, NPR2 and height, APOB, LDLR, PCSK9 and LDL. Our results are consistent with previous literature, indicating that the All of Us program is a reliable resource for advancing the understanding of complex diseases in diverse human populations.
Collapse
Affiliation(s)
- Xin Wang
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Justine Ryu
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jihoon Kim
- Department of Biomedical Informatics, University of California San Diego Health System, La Jolla, CA, USA
| | - Andrea Ramirez
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Kelsey R Mayo
- Vanderbilt Institute of Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Henry Condon
- Department of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Lucila Ohno-Machado
- Department of Biomedical Informatics, University of California San Diego Health System, La Jolla, CA, USA
- Section of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, USA
| | - Greg A Talavera
- Graduate School of Public Health, San Diego State University, San Diego, CA, USA
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Steven A Lubitz
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Seung Hoan Choi
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biostatistics, Boston University, Boston, MA, USA.
| |
Collapse
|
40
|
Sandholm N, Dahlström EH, Groop PH. Genetic and epigenetic background of diabetic kidney disease. Front Endocrinol (Lausanne) 2023; 14:1163001. [PMID: 37324271 PMCID: PMC10262849 DOI: 10.3389/fendo.2023.1163001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 05/10/2023] [Indexed: 06/17/2023] Open
Abstract
Diabetic kidney disease (DKD) is a severe diabetic complication that affects up to half of the individuals with diabetes. Elevated blood glucose levels are a key underlying cause of DKD, but DKD is a complex multifactorial disease, which takes years to develop. Family studies have shown that inherited factors also contribute to the risk of the disease. During the last decade, genome-wide association studies (GWASs) have emerged as a powerful tool to identify genetic risk factors for DKD. In recent years, the GWASs have acquired larger number of participants, leading to increased statistical power to detect more genetic risk factors. In addition, whole-exome and whole-genome sequencing studies are emerging, aiming to identify rare genetic risk factors for DKD, as well as epigenome-wide association studies, investigating DNA methylation in relation to DKD. This article aims to review the identified genetic and epigenetic risk factors for DKD.
Collapse
Affiliation(s)
- Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Emma H. Dahlström
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, Australia
| |
Collapse
|
41
|
Chen CY, Tian R, Ge T, Lam M, Sanchez-Andrade G, Singh T, Urpa L, Liu JZ, Sanderson M, Rowley C, Ironfield H, Fang T, Daly M, Palotie A, Tsai EA, Huang H, Hurles ME, Gerety SS, Lencz T, Runz H. The impact of rare protein coding genetic variation on adult cognitive function. Nat Genet 2023:10.1038/s41588-023-01398-8. [PMID: 37231097 DOI: 10.1038/s41588-023-01398-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 04/13/2023] [Indexed: 05/27/2023]
Abstract
Compelling evidence suggests that human cognitive function is strongly influenced by genetics. Here, we conduct a large-scale exome study to examine whether rare protein-coding variants impact cognitive function in the adult population (n = 485,930). We identify eight genes (ADGRB2, KDM5B, GIGYF1, ANKRD12, SLC8A1, RC3H2, CACNA1A and BCAS3) that are associated with adult cognitive function through rare coding variants with large effects. Rare genetic architecture for cognitive function partially overlaps with that of neurodevelopmental disorders. In the case of KDM5B we show how the genetic dosage of one of these genes may determine the variability of cognitive, behavioral and molecular traits in mice and humans. We further provide evidence that rare and common variants overlap in association signals and contribute additively to cognitive function. Our study introduces the relevance of rare coding variants for cognitive function and unveils high-impact monogenic contributions to how cognitive function is distributed in the normal adult population.
Collapse
Affiliation(s)
- Chia-Yen Chen
- Research and Development, Biogen Inc, Cambridge, MA, USA.
| | - Ruoyu Tian
- Research and Development, Biogen Inc, Cambridge, MA, USA
- Dewpoint Therapeutics, Boston, MA, USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Max Lam
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | | | - Tarjinder Singh
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Lea Urpa
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Jimmy Z Liu
- Research and Development, Biogen Inc, Cambridge, MA, USA
- GlaxoSmithKline, Philadelphia, PA, USA
| | | | | | | | - Terry Fang
- Research and Development, Biogen Inc, Cambridge, MA, USA
| | - Mark Daly
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Aarno Palotie
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ellen A Tsai
- Research and Development, Biogen Inc, Cambridge, MA, USA
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | | | | | - Todd Lencz
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Heiko Runz
- Research and Development, Biogen Inc, Cambridge, MA, USA.
| |
Collapse
|
42
|
Hamilton MC, Fife JD, Akinci E, Yu T, Khowpinitchai B, Cha M, Barkal S, Thi TT, Yeo GH, Ramos Barroso JP, Francoeur MJ, Velimirovic M, Gifford DK, Lettre G, Yu H, Cassa CA, Sherwood RI. Systematic elucidation of genetic mechanisms underlying cholesterol uptake. CELL GENOMICS 2023; 3:100304. [PMID: 37228746 PMCID: PMC10203276 DOI: 10.1016/j.xgen.2023.100304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 12/02/2022] [Accepted: 03/24/2023] [Indexed: 05/27/2023]
Abstract
Genetic variation contributes greatly to LDL cholesterol (LDL-C) levels and coronary artery disease risk. By combining analysis of rare coding variants from the UK Biobank and genome-scale CRISPR-Cas9 knockout and activation screening, we substantially improve the identification of genes whose disruption alters serum LDL-C levels. We identify 21 genes in which rare coding variants significantly alter LDL-C levels at least partially through altered LDL-C uptake. We use co-essentiality-based gene module analysis to show that dysfunction of the RAB10 vesicle transport pathway leads to hypercholesterolemia in humans and mice by impairing surface LDL receptor levels. Further, we demonstrate that loss of function of OTX2 leads to robust reduction in serum LDL-C levels in mice and humans by increasing cellular LDL-C uptake. Altogether, we present an integrated approach that improves our understanding of the genetic regulators of LDL-C levels and provides a roadmap for further efforts to dissect complex human disease genetics.
Collapse
Affiliation(s)
- Marisa C. Hamilton
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - James D. Fife
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Ersin Akinci
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Tian Yu
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Benyapa Khowpinitchai
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Minsun Cha
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Sammy Barkal
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Thi Tun Thi
- Precision Medicine Research Programme, Cardiovascular Disease Research Programme, and Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Grace H.T. Yeo
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Biological Engineering, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Juan Pablo Ramos Barroso
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Matthew Jake Francoeur
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Minja Velimirovic
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - David K. Gifford
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Biological Engineering, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
- Faculté de Médecine, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Haojie Yu
- Precision Medicine Research Programme, Cardiovascular Disease Research Programme, and Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Christopher A. Cassa
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Richard I. Sherwood
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| |
Collapse
|
43
|
Westerman KE, Walker ME, Gaynor SM, Wessel J, DiCorpo D, Ma J, Alonso A, Aslibekyan S, Baldridge AS, Bertoni AG, Biggs ML, Brody JA, Chen YDI, Dupuis J, Goodarzi MO, Guo X, Hasbani NR, Heath A, Hidalgo B, Irvin MR, Johnson WC, Kalyani RR, Lange L, Lemaitre RN, Liu CT, Liu S, Moon JY, Nassir R, Pankow JS, Pettinger M, Raffield LM, Rasmussen-Torvik LJ, Selvin E, Senn MK, Shadyab AH, Smith AV, Smith NL, Steffen L, Talegakwar S, Taylor KD, de Vries PS, Wilson JG, Wood AC, Yanek LR, Yao J, Zheng Y, Boerwinkle E, Morrison AC, Fornage M, Russell TP, Psaty BM, Levy D, Heard-Costa NL, Ramachandran VS, Mathias RA, Arnett DK, Kaplan R, North KE, Correa A, Carson A, Rotter JI, Rich SS, Manson JE, Reiner AP, Kooperberg C, Florez JC, Meigs JB, Merino J, Tobias DK, Chen H, Manning AK. Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits. Diabetes 2023; 72:653-665. [PMID: 36791419 PMCID: PMC10130485 DOI: 10.2337/db22-0851] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 02/02/2023] [Indexed: 02/17/2023]
Abstract
Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry. ARTICLE HIGHLIGHTS We aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.
Collapse
Affiliation(s)
- Kenneth E. Westerman
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA
| | - Maura E. Walker
- Department of Medicine, Section of Preventive Medicine, Boston University School of Medicine, Boston, MA
- Department of Health Sciences, Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA
| | - Sheila M. Gaynor
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Jennifer Wessel
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indianapolis, IN
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
- Diabetes Translational Research Center, Indiana University, Indianapolis, IN
| | - Daniel DiCorpo
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jiantao Ma
- Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
| | | | - Abigail S. Baldridge
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Alain G. Bertoni
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC
| | - Mary L. Biggs
- Department of Biostatistics, University of Washington, Seattle, WA
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA
- Department of Medicine, University of Washington, Seattle, WA
| | - 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
| | - Joseé Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA
| | - 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
| | - Natalie R. Hasbani
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Adam Heath
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Bertha Hidalgo
- School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL
| | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Rita R. Kalyani
- GeneSTAR Research Program, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Leslie Lange
- Department of Medicine, Anschutz Medical Campus, University of Colorado, Aurora, CO
| | - Rozenn N. Lemaitre
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA
- Department of Internal Medicine, University of Washington, Seattle, WA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
- National Heart, Lung, and Blood Institute and Boston University’s Framingham Heart Study, Framingham, MA
- Evans Department of Medicine, Section of Preventive Medicine and Epidemiology, Boston University School of Medicine, Boston, MA
- Evans Department of Medicine, Whitaker Cardiovascular Institute and Cardiology Section, Boston University School of Medicine, Boston, MA
| | - Simin Liu
- Center for Global Cardiometabolic Health, Boston, MA
| | - Jee-Young Moon
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Rami Nassir
- Department of Pathology, School of Medicine, Umm Al-Qura University, Mecca, Saudi Arabia
| | - James S. Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Mary Pettinger
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | | | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Mackenzie K. Senn
- USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, Houston, TX
| | - Aladdin H. Shadyab
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA
| | - Albert V. Smith
- Department of Biostatistics, University of Michigan, Ann Arbor, MI
| | - Nicholas L. Smith
- Department of Epidemiology, University of Washington, Seattle, WA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA
- Department of Veterans Affairs Office of Research and Development, Seattle Epidemiologic Research and Information Center, Seattle, WA
| | - Lyn Steffen
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Sameera Talegakwar
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University, Washington, DC
| | - 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
| | - Paul S. de Vries
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - James G. Wilson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Alexis C. Wood
- USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, Houston, TX
| | - Lisa R. Yanek
- GeneSTAR Research Program, Johns Hopkins University School of Medicine, Baltimore, MD
| | - 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
| | - Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Alanna C. Morrison
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Miriam Fornage
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Tracy P. Russell
- Department of Pathology and Laboratory Medicine, University of Vermont Larner College of Medicine, Burlington, VT
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA
- Department of Medicine, University of Washington, Seattle, WA
- Department of Epidemiology, University of Washington, Seattle, WA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA
| | - Daniel Levy
- National Heart, Lung, and Blood Institute and Boston University’s Framingham Heart Study, Framingham, MA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Nancy L. Heard-Costa
- National Heart, Lung, and Blood Institute and Boston University’s Framingham Heart Study, Framingham, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
| | - Vasan S. Ramachandran
- National Heart, Lung, and Blood Institute and Boston University’s Framingham Heart Study, Framingham, MA
- Evans Department of Medicine, Section of Preventive Medicine and Epidemiology, Boston University School of Medicine, Boston, MA
- Evans Department of Medicine, Whitaker Cardiovascular Institute and Cardiology Section, Boston University School of Medicine, Boston, MA
| | - Rasika A. Mathias
- GeneSTAR Research Program, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Donna K. Arnett
- College of Public Health, University of Kentucky, Lexington, KY
| | - Robert Kaplan
- Clinical Excellence Research Center, School of Medicine, Stanford University, Stanford, CA
| | - Kari E. North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Adolfo Correa
- Department of Population Health Science, University of Mississippi Medical Center, Jackson, MS
| | - April Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS
| | - 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
| | - Stephen S. Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA
| | | | | | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Jose C. Florez
- Department of Medicine, Harvard Medical School, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - James B. Meigs
- Department of Medicine, Harvard Medical School, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Jordi Merino
- Department of Medicine, Harvard Medical School, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - Deirdre K. Tobias
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Han Chen
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
- Center for Precision Health, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
| | - Alisa K. Manning
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, MA
| |
Collapse
|
44
|
Kerr SM, Cowan E, Klaric L, Bell C, O'Sullivan D, Buchanan D, Grzymski JJ, van Hout CV, Tzoneva G, Shuldiner AR, Wilson JF, Miedzybrodzka Z. Clinical case study meets population cohort: identification of a BRCA1 pathogenic founder variant in Orcadians. Eur J Hum Genet 2023; 31:588-595. [PMID: 36927983 PMCID: PMC10172333 DOI: 10.1038/s41431-023-01297-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 12/20/2022] [Accepted: 01/18/2023] [Indexed: 03/18/2023] Open
Abstract
We multiply ascertained the BRCA1 pathogenic missense variant c.5207T > C; p.Val1736Ala (V1736A) in clinical investigation of breast and ovarian cancer families from Orkney in the Northern Isles of Scotland, UK. We sought to investigate the frequency and clinical relevance of this variant in those of Orcadian ancestry as an exemplar of the value of population cohorts in clinical care, especially in isolated populations. Oral history and birth, marriage and death registrations indicated genealogical linkage of the clinical cases to ancestors from the Isle of Westray, Orkney. Further clinical cases were identified through targeted testing for V1736A in women of Orcadian ancestry attending National Health Service (NHS) genetic clinics for breast and ovarian cancer family risk assessments. The variant segregates with female breast and ovarian cancer in clinically ascertained cases. Separately, exome sequence data from 2088 volunteer participants with three or more Orcadian grandparents, in the ORCADES research cohort, was interrogated to estimate the population prevalence of V1736A in Orcadians. The effects of the variant were assessed using Electronic Health Record (EHR) linkage. Twenty out of 2088 ORCADES research volunteers (~1%) carry V1736A, with a common haplotype around the variant. This allele frequency is ~480-fold higher than in UK Biobank participants. Cost-effectiveness of population screening for BRCA1 founder pathogenic variants has been demonstrated at a carrier frequency below the ~1% observed here. Thus we suggest that Orcadian women should be offered testing for the BRCA1 V1736A founder pathogenic variant, starting with those with known Westray ancestry.
Collapse
Affiliation(s)
- Shona M Kerr
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Cancer, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Emma Cowan
- Department of Medical Genetics, Ashgrove House, NHS Grampian, Aberdeen, AB25 2ZA, UK
| | - Lucija Klaric
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Cancer, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Christine Bell
- Department of Medical Genetics, Ashgrove House, NHS Grampian, Aberdeen, AB25 2ZA, UK
| | - Dawn O'Sullivan
- Department of Medical Genetics, Ashgrove House, NHS Grampian, Aberdeen, AB25 2ZA, UK
| | - David Buchanan
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Cancer, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Joseph J Grzymski
- Center for Genomic Medicine, Desert Research Institute, Reno, NV, USA
- Renown Health, Reno, NV, USA
| | - Cristopher V van Hout
- Regeneron Genetics Center, Tarrytown, NY, USA
- Laboratorio Internacional de Investigatión sobre el Genoma Humano, Campus Juriquilla de la Universidad Nacional Autónoma de México, Querétaro, Querétaro, 76230, México
| | | | | | - James F Wilson
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Cancer, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
| | - Zosia Miedzybrodzka
- Department of Medical Genetics, Ashgrove House, NHS Grampian, Aberdeen, AB25 2ZA, UK.
- Medical Genetics Group, School of Medicine, Medical Sciences, Nutrition and Dentistry, University of Aberdeen, Polwarth Building, Aberdeen, AB25 2ZD, UK.
| |
Collapse
|
45
|
Zheng M, Huang DQ, Konkwo C, Agrawal S, Khera AV, Loomba R, Vilarinho S, Ajmera V. Genomic analysis of lean individuals with NAFLD identifies monogenic disorders in a prospective cohort study. JHEP Rep 2023; 5:100692. [PMID: 36937991 PMCID: PMC10017416 DOI: 10.1016/j.jhepr.2023.100692] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 01/13/2023] [Accepted: 01/17/2023] [Indexed: 02/05/2023] Open
Abstract
Background & Aims Lean patients with non-alcoholic fatty liver disease (NAFLD) represent 10-20% of the affected population and may have heterogeneous drivers of disease. We have recently proposed the evaluation of patients with lean NAFLD without visceral adiposity for rare monogenic drivers of disease. Here, we aimed to validate this framework in a well-characterised cohort of patients with biopsy-proven NAFLD by performing whole exome sequencing. Methods This prospective study included 124 patients with biopsy-proven NAFLD and paired liver biopsies who underwent standardised research visits including advanced magnetic resonance imaging (MRI) assessment of liver fat and stiffness. Results Six patients with lean NAFLD were identified and underwent whole exome sequencing. Two lean patients (33%) were identified to have monogenic disorders. The lean patients with monogenic disorders had similar age, and anthropometric and MRI characteristics to lean patients without a monogenic disorder. Patient 1 harbours a rare homozygous pathogenic mutation in ALDOB (aldolase B) and was diagnosed with hereditary fructose intolerance. Patient 2 harbours a rare heterozygous mutation in apolipoprotein B (APOB). The pathogenicity of this APOB variant (p.Val1856CysfsTer2) was further validated in the UK Biobank and associated with lower circulating APOB levels (beta = -0.51 g/L, 95% CI -0.65 to -0.36 g/L, p = 1.4 × 10-11) and higher liver fat on MRI (beta = +10.4%, 95% CI 4.3-16.5%, p = 8.8 × 10-4). Hence, patient 2 was diagnosed with heterozygous familial hypobetalipoproteinaemia. Conclusions In this cohort of well-characterised patients with lean NAFLD without visceral adiposity, 33% (2/6) had rare monogenic drivers of disease, highlighting the importance of genomic analysis in this NAFLD subtype. Impact and Implications Although most people with non-alcoholic fatty liver disease (NAFLD) are overweight or obese, a subset are lean and may have unique genetic mutations that cause their fatty liver disease. We show that 33% of study participants with NAFLD who were lean harboured unique mutations that cause their fatty liver, and that these mutations had effects beyond the liver. This study demonstrates the value of genetic assessment of NAFLD in lean individuals to identify distinct subtypes of disease.
Collapse
Key Words
- ALT, alanine aminotransferase
- APOB, apolipoprotein B
- FHBL, familial hypobetalipoproteinaemia
- LOFHC, high-confidence predicted loss-of-function
- MRE, magnetic resonance elastography
- MRI, magnetic resonance imaging
- MRI-PDFF, magnetic resonance imaging proton density fat fraction
- NAFLD
- NAFLD, non-alcoholic fatty liver disease
- Non-obese
- Rare genetic variants
- UCSD, University of California San Diego
- WES, whole exome sequencing
- Whole exome sequencing
Collapse
Affiliation(s)
- Melanie Zheng
- Departments of Internal Medicine, Section of Digestive Diseases, and of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Daniel Q. Huang
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, CA, USA
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Chigoziri Konkwo
- Departments of Internal Medicine, Section of Digestive Diseases, and of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Saaket Agrawal
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Amit V. Khera
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Verve Therapeutics, Cambridge, MA, USA
| | - Rohit Loomba
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, CA, USA
| | - Sílvia Vilarinho
- Departments of Internal Medicine, Section of Digestive Diseases, and of Pathology, Yale School of Medicine, New Haven, CT, USA
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Veeral Ajmera
- NAFLD Research Center, Division of Gastroenterology, University of California at San Diego, La Jolla, CA, USA
| |
Collapse
|
46
|
Jurgens SJ, Pirruccello JP, Choi SH, Morrill VN, Chaffin M, Lubitz SA, Lunetta KL, Ellinor PT. Adjusting for common variant polygenic scores improves yield in rare variant association analyses. Nat Genet 2023; 55:544-548. [PMID: 36959364 PMCID: PMC11078202 DOI: 10.1038/s41588-023-01342-w] [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: 10/11/2021] [Accepted: 02/22/2023] [Indexed: 03/25/2023]
Abstract
With the emergence of large-scale sequencing data, methods for improving power in rare variant association tests are needed. Here we show that adjusting for common variant polygenic scores improves yield in gene-based rare variant association tests across 65 quantitative traits in the UK Biobank (up to 20% increase at α = 2.6 × 10-6), without marked increases in false-positive rates or genomic inflation. Benefits were seen for various models, with the largest improvements seen for efficient sparse mixed-effects models. Our results illustrate how polygenic score adjustment can efficiently improve power in rare variant association discovery.
Collapse
Affiliation(s)
- Sean J Jurgens
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Experimental Cardiology, Heart Centre, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands
| | - James P Pirruccello
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Cardiology, University of California, San Francisco, San Francisco, CA, USA
| | - Seung Hoan Choi
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Valerie N Morrill
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mark Chaffin
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Steven A Lubitz
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- NHLBI and Boston University's Framingham Heart Study, Framingham, MA, USA
| | - Patrick T Ellinor
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA.
| |
Collapse
|
47
|
Khurshid S, Lazarte J, Pirruccello JP, Weng LC, Choi SH, Hall AW, Wang X, Friedman SF, Nauffal V, Biddinger KJ, Aragam KG, Batra P, Ho JE, Philippakis AA, Ellinor PT, Lubitz SA. Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass. Nat Commun 2023; 14:1558. [PMID: 36944631 PMCID: PMC10030590 DOI: 10.1038/s41467-023-37173-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 03/04/2023] [Indexed: 03/23/2023] Open
Abstract
Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, but is challenging to obtain at scale. Here, we use deep learning to enable genome-wide association study of cardiac magnetic resonance-derived left ventricular mass indexed to body surface area within 43,230 UK Biobank participants. We identify 12 genome-wide associations (1 known at TTN and 11 novel for left ventricular mass), implicating genes previously associated with cardiac contractility and cardiomyopathy. Cardiac magnetic resonance-derived indexed left ventricular mass is associated with incident dilated and hypertrophic cardiomyopathies, and implantable cardioverter-defibrillator implant. An indexed left ventricular mass polygenic risk score ≥90th percentile is also associated with incident implantable cardioverter-defibrillator implant in separate UK Biobank (hazard ratio 1.22, 95% CI 1.05-1.44) and Mass General Brigham (hazard ratio 1.75, 95% CI 1.12-2.74) samples. Here, we perform a genome-wide association study of cardiac magnetic resonance-derived indexed left ventricular mass to identify 11 novel variants and demonstrate that cardiac magnetic resonance-derived and genetically predicted indexed left ventricular mass are associated with incident cardiomyopathy.
Collapse
Affiliation(s)
- Shaan Khurshid
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Julieta Lazarte
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - James P Pirruccello
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
| | - Lu-Chen Weng
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Seung Hoan Choi
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Amelia W Hall
- Gene Regulation Observatory, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Xin Wang
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Samuel F Friedman
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Victor Nauffal
- Division of Cardiology, Brigham and Women's Hospital, Boston, MA, USA
| | - Kiran J Biddinger
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Krishna G Aragam
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
| | - Puneet Batra
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jennifer E Ho
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- CardioVascular Institute and Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Anthony A Philippakis
- Data Sciences Platform, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Patrick T Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Steven A Lubitz
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
- Cardiovascular Disease Initiative, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA.
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA.
| |
Collapse
|
48
|
Nag A, Dhindsa RS, Middleton L, Jiang X, Vitsios D, Wigmore E, Allman EL, Reznichenko A, Carss K, Smith KR, Wang Q, Challis B, Paul DS, Harper AR, Petrovski S. Effects of protein-coding variants on blood metabolite measurements and clinical biomarkers in the UK Biobank. Am J Hum Genet 2023; 110:487-498. [PMID: 36809768 PMCID: PMC10027475 DOI: 10.1016/j.ajhg.2023.02.002] [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: 11/21/2022] [Accepted: 01/30/2023] [Indexed: 02/22/2023] Open
Abstract
Genome-wide association studies (GWASs) have established the contribution of common and low-frequency variants to metabolic blood measurements in the UK Biobank (UKB). To complement existing GWAS findings, we assessed the contribution of rare protein-coding variants in relation to 355 metabolic blood measurements-including 325 predominantly lipid-related nuclear magnetic resonance (NMR)-derived blood metabolite measurements (Nightingale Health Plc) and 30 clinical blood biomarkers-using 412,393 exome sequences from four genetically diverse ancestries in the UKB. Gene-level collapsing analyses were conducted to evaluate a diverse range of rare-variant architectures for the metabolic blood measurements. Altogether, we identified significant associations (p < 1 × 10-8) for 205 distinct genes that involved 1,968 significant relationships for the Nightingale blood metabolite measurements and 331 for the clinical blood biomarkers. These include associations for rare non-synonymous variants in PLIN1 and CREB3L3 with lipid metabolite measurements and SYT7 with creatinine, among others, which may not only provide insights into novel biology but also deepen our understanding of established disease mechanisms. Of the study-wide significant clinical biomarker associations, 40% were not previously detected on analyzing coding variants in a GWAS in the same cohort, reinforcing the importance of studying rare variation to fully understand the genetic architecture of metabolic blood measurements.
Collapse
Affiliation(s)
- Abhishek Nag
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Ryan S Dhindsa
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston, TX 77030, USA
| | - Lawrence Middleton
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Xiao Jiang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Dimitrios Vitsios
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Eleanor Wigmore
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Erik L Allman
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Anna Reznichenko
- Translational Science and Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Keren Carss
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Katherine R Smith
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Quanli Wang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA
| | - Benjamin Challis
- Translational Science and Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Dirk S Paul
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Andrew R Harper
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK; Early Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK; Department of Medicine, University of Melbourne, Austin Health, Melbourne, VIC, Australia.
| |
Collapse
|
49
|
Dron JS, Patel AP, Zhang Y, Jurgens SJ, Maamari DJ, Wang M, Boerwinkle E, Morrison AC, de Vries PS, Fornage M, Hou L, Lloyd-Jones DM, Psaty BM, Tracy RP, Bis JC, Vasan RS, Levy D, Heard-Costa N, Rich SS, Guo X, Taylor KD, Gibbs RA, Rotter JI, Willer CJ, Oelsner EC, Moran AE, Peloso GM, Natarajan P, Khera AV. Association of Rare Protein-Truncating DNA Variants in APOB or PCSK9 With Low-density Lipoprotein Cholesterol Level and Risk of Coronary Heart Disease. JAMA Cardiol 2023; 8:258-267. [PMID: 36723951 PMCID: PMC9996405 DOI: 10.1001/jamacardio.2022.5271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 11/29/2022] [Indexed: 02/02/2023]
Abstract
Importance Protein-truncating variants (PTVs) in apolipoprotein B (APOB) and proprotein convertase subtilisin/kexin type 9 (PCSK9) are associated with significantly lower low-density lipoprotein (LDL) cholesterol concentrations. The association of these PTVs with coronary heart disease (CHD) warrants further characterization in large, multiracial prospective cohort studies. Objective To evaluate the association of PTVs in APOB and PCSK9 with LDL cholesterol concentrations and CHD risk. Design, Setting, and Participants This studied included participants from 5 National Heart, Lung, and Blood Institute (NHLBI) studies and the UK Biobank. NHLBI study participants aged 5 to 84 years were recruited between 1971 and 2002 across the US and underwent whole-genome sequencing. UK Biobank participants aged 40 to 69 years were recruited between 2006 and 2010 in the UK and underwent whole-exome sequencing. Data were analyzed from June 2021 to October 2022. Exposures PTVs in APOB and PCSK9. Main Outcomes and Measures Estimated untreated LDL cholesterol levels and CHD. Results Among 19 073 NHLBI participants (10 598 [55.6%] female; mean [SD] age, 52 [17] years), 139 (0.7%) carried an APOB or PCSK9 PTV, which was associated with 49 mg/dL (95% CI, 43-56) lower estimated untreated LDL cholesterol level. Over a median (IQR) follow-up of 21.5 (13.9-29.4) years, incident CHD was observed in 12 of 139 carriers (8.6%) vs 3029 of 18 934 noncarriers (16.0%), corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.28-0.89; P = .02). Among 190 464 UK Biobank participants (104 831 [55.0%] female; mean [SD] age, 57 [8] years), 662 (0.4%) carried a PTV, which was associated with 45 mg/dL (95% CI, 42-47) lower estimated untreated LDL cholesterol level. Estimated CHD risk by age 75 years was 3.7% (95% CI, 2.0-5.3) in carriers vs 7.0% (95% CI, 6.9-7.2) in noncarriers, corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.32-0.81; P = .004). Conclusions and Relevance Among 209 537 individuals in this study, 0.4% carried an APOB or PCSK9 PTV that was associated with less exposure to LDL cholesterol and a 49% lower risk of CHD.
Collapse
Affiliation(s)
- Jacqueline S. Dron
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Aniruddh P. Patel
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston
| | - Yiyi Zhang
- Division of General Medicine, Columbia University, New York, New York
| | - Sean J. Jurgens
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Experimental Cardiology, Amsterdam UMC, Amsterdam, the Netherlands
| | - Dimitri J. Maamari
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Minxian Wang
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston
| | - Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Donald M. Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
- Department of Health Systems and Population Health, University of Washington, Seattle
| | - Russell P. Tracy
- Department of Pathology and Laboratory Medicine, Larner College of Medicine at the University of Vermont, Colchester, Vermont
- Department of Biochemistry, Larner College of Medicine at the University of Vermont, Colchester, Vermont
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
| | - Ramachandran S. Vasan
- Sections of Preventive Medicine and Epidemiology, Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
- Framingham Heart Study, Framingham, Massachusetts
| | - Daniel Levy
- Framingham Heart Study, Framingham, Massachusetts
- Population Sciences Branch, National Heart, Lung, and Blood Institute, Bethesda, Maryland
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville
| | - 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, California
| | - 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, California
| | - Richard A. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas
| | - 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, California
| | | | | | - Andrew E. Moran
- Division of General Medicine, Columbia University, New York, New York
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Pradeep Natarajan
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston
| | - Amit V. Khera
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Verve Therapeutics, Boston, Massachusetts
| |
Collapse
|
50
|
Ma S, Wang C, Khan A, Liu L, Dalgleish J, Kiryluk K, He Z, Ionita-Laza I. BIGKnock: fine-mapping gene-based associations via knockoff analysis of biobank-scale data. Genome Biol 2023; 24:24. [PMID: 36782330 PMCID: PMC9926792 DOI: 10.1186/s13059-023-02864-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 01/23/2023] [Indexed: 02/15/2023] Open
Abstract
We propose BIGKnock (BIobank-scale Gene-based association test via Knockoffs), a computationally efficient gene-based testing approach for biobank-scale data, that leverages long-range chromatin interaction data, and performs conditional genome-wide testing via knockoffs. BIGKnock can prioritize causal genes over proxy associations at a locus. We apply BIGKnock to the UK Biobank data with 405,296 participants for multiple binary and quantitative traits, and show that relative to conventional gene-based tests, BIGKnock produces smaller sets of significant genes that contain the causal gene(s) with high probability. We further illustrate its ability to pinpoint potential causal genes at [Formula: see text] of the associated loci.
Collapse
Affiliation(s)
- Shiyang Ma
- Department of Biostatistics, Columbia University, New York, NY, USA
- Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chen Wang
- Department of Biostatistics, Columbia University, New York, NY, USA
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Linxi Liu
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - James Dalgleish
- Department of Biostatistics, Columbia University, New York, NY, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Zihuai He
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | | |
Collapse
|