Cohort profile: genomic data for 26 622 individuals from the Canadian Longitudinal Study on Aging (CLSA)

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.

[1]  A. Hewitt,et al.  Automated AI labeling of optic nerve head enables insights into cross-ancestry glaucoma risk and genetic discovery in >280,000 images from UKB and CLSA. , 2021, American journal of human genetics.

[2]  L. Dubé,et al.  Multiscale Risk Factors of Cardiovascular Disease: CLSA Analysis of Genetic and Psychosocial Factors , 2021, Frontiers in Cardiovascular Medicine.

[3]  Tueng T. Shen,et al.  Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study , 2020, The Lancet. Global health.

[4]  N. Martin,et al.  Genome-wide analyses in 1,987,836 participants identify 39 genetic loci associated with sleep apnoea , 2020, medRxiv.

[5]  David M. Evans,et al.  Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study , 2020, PLoS medicine.

[6]  D. Melzer,et al.  The genetics of human ageing , 2019, Nature Reviews Genetics.

[7]  E. R. van den Heuvel,et al.  Cohort Profile: The Canadian Longitudinal Study on Aging (CLSA) , 2019, International journal of epidemiology.

[8]  Param Priya Singh,et al.  The Genetics of Aging: A Vertebrate Perspective , 2019, Cell.

[9]  Brian E. Cade,et al.  Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program , 2019, Nature.

[10]  P. Donnelly,et al.  The UK Biobank resource with deep phenotyping and genomic data , 2018, Nature.

[11]  M. Rask-Andersen,et al.  Gene-environment interaction study for BMI reveals interactions between genetic factors and physical activity, alcohol consumption and socioeconomic status , 2017, PLoS genetics.

[12]  Alan M. Kwong,et al.  Next-generation genotype imputation service and methods , 2016, Nature Genetics.

[13]  Shane A. McCarthy,et al.  Reference-based phasing using the Haplotype Reference Consortium panel , 2016, Nature Genetics.

[14]  Sayan Mukherjee,et al.  Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia. , 2016, American journal of human genetics.

[15]  Gabor T. Marth,et al.  A global reference for human genetic variation , 2015, Nature.

[16]  Gonçalo R. Abecasis,et al.  Minimac2: Faster Genotype Imputation , 2015, Bioinform..

[17]  Carson C Chow,et al.  Second-generation PLINK: rising to the challenge of larger and richer datasets , 2014, GigaScience.

[18]  Alexander T. Dilthey,et al.  Multi-Population Classical HLA Type Imputation , 2013, PLoS Comput. Biol..

[19]  L. Liang,et al.  Genome-wide association analyses of esophageal squamous cell carcinoma in Chinese identify multiple susceptibility loci and gene-environment interactions , 2012, Nature Genetics.

[20]  Josyf Mychaleckyj,et al.  Robust relationship inference in genome-wide association studies , 2010, Bioinform..

[21]  P. Raina,et al.  The Canadian Longitudinal Study on Aging (CLSA)* , 2009, Canadian Journal on Aging / La Revue canadienne du vieillissement.

[22]  D. Balding.  A tutorial on statistical methods for population association studies , 2006, Nature Reviews Genetics.

[23]  D. Reich,et al.  Principal components analysis corrects for stratification in genome-wide association studies , 2006, Nature Genetics.

[24]  G. Abecasis,et al.  A note on exact tests of Hardy-Weinberg equilibrium. , 2005, American journal of human genetics.

[25]  P. Vineis,et al.  Current smoking, occupation, N-acetyltransferase-2 and bladder cancer: a pooled analysis of genotype-based studies. , 2001, Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology.

[26]  S. Haque.  Ethics approval This study was conducted with the approval of the East London and City Health Authority Ethic Committee. Provenance and peer review Not commissioned; externally peer reviewed. , 2011 .