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Forgetta V, Li R, Darmond-Zwaig C, Belisle A, Balion C, Roshandel D, Wolfson C, Lettre G, Pare G, Paterson AD, Griffith LE, Verschoor C, Lathrop M, Kirkland S, Raina P, Richards JB, Ragoussis J. Cohort profile: genomic data for 26 622 individuals from the Canadian Longitudinal Study on Aging (CLSA). BMJ Open 2022; 12:e059021. [PMID: 35273064 PMCID: PMC8915305 DOI: 10.1136/bmjopen-2021-059021] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
PURPOSE The Canadian Longitudinal Study on Aging (CLSA) Comprehensive cohort was established to provide unique opportunities to study the genetic and environmental contributions to human disease as well as ageing process. The aim of this report was to describe the genomic data included in CLSA. PARTICIPANTS A total of 26 622 individuals from the CLSA Comprehensive cohort of men and women aged 45-85 recruited between 2010 and 2015 underwent genome-wide genotyping of DNA samples collected from blood. Comprehensive quality control metrics were measured for genetic markers and samples, respectively. The genotypes were imputed to the TOPMed reference panel. Sex chromosome abnormalities were identified by copy number profiling. Classical human leukocyte antigen gene haplotypes were imputed at two-field (four-digit). FINDINGS TO DATE Of the 26 622 genotyped participants, 24 655 (92.6%) were identified as having European ancestry. These genomic data were linked to physical, lifestyle, medical, economic, environmental and psychosocial factors collected longitudinally in CLSA. The combined analysis, including CLSA genomic data, uncovered over 100 novel loci associated with key parameters to define glaucoma. The CLSA genomic dataset validated the contribution of a polygenic risk score to screen individuals with high fracture risk. It is also a valuable resource to directly identify common genetic variations associated with conditions related to complex traits. Taking advantage of the comprehensive interview and physical information collected in CLSA, this genomic dataset has been linked to psychosocial factors to investigate both the independent and interactive effects on cardiovascular disease. FUTURE PLANS The CLSA overall is ongoing. Follow-up data will continue to be collected from participants in the current genomic subcohort, including the DNA methylation and metabolomic data. Ongoing studies focus on elucidating the role of genetic factors in cognitive decline and cardiovascular diseases. This genomic data resource is available on request through the CLSA data access application process.
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Affiliation(s)
- Vincenzo Forgetta
- Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montréal, QC, Canada
| | - Rui Li
- McGill Genome Centre, Department of Human Genetics, McGill University, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Corinne Darmond-Zwaig
- McGill Genome Centre, Department of Human Genetics, McGill University, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Alexandre Belisle
- McGill Genome Centre, Department of Human Genetics, McGill University, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Cynthia Balion
- Hamilton Regional Laboratory Medicine Program, McMaster University, St. Joseph's Hospital St. Luke's Wing, Hamilton, ON, Canada
| | - Delnaz Roshandel
- Genetics & Genomic Biology, The Hospital for Sick Children Research Institute, The Hospital for Sick Children, Toronto, ON, Canada
| | - Christina Wolfson
- Department of Medicine & of Epidemiology and Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada
| | - Guillaume Lettre
- Montréal Heart Institute and Université de Montréal, Montréal, QC, Canada
| | - Guillaume Pare
- Hamilton Regional Laboratory Medicine Program, McMaster University, St. Joseph's Hospital St. Luke's Wing, Hamilton, ON, Canada
| | - Andrew D Paterson
- Genetics & Genomic Biology, The Hospital for Sick Children Research Institute, The Hospital for Sick Children, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Lauren E Griffith
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Chris Verschoor
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Mark Lathrop
- McGill Genome Centre, Department of Human Genetics, McGill University, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Susan Kirkland
- Department of Community Health and Epidemiology, Division of Geriatric Medicine, Dalhousie University, Halifax, NS, Canada
| | - Parminder Raina
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - J Brent Richards
- Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montréal, QC, Canada
- Department of Medicine & of Epidemiology and Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jiannis Ragoussis
- McGill Genome Centre, Department of Human Genetics, McGill University, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Department of Bioengineering, McGill University, Montréal, QC, Canada
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