Article
Characterization of Large Structural Genetic Mosaicism in Human Autosomes
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- (1) National Institute of Arthritis and Musculoskeletal and Skin Diseases, grid.420086.8
- (2) National Center for Advancing Translational Sciences, grid.429651.d
- (3) BioInformed LLC, Gaithersburg, MD 20877, USA
- (4) National Health Research Institutes, grid.59784.37
- (5) Fred Hutchinson Cancer Research Center, grid.270240.3
- (6) Harvard University, grid.38142.3c
- (7) Tianjin Medical University Cancer Institute and Hospital, grid.411918.4
- (8) University of New Mexico, grid.266832.b
- (9) Brigham and Women's Hospital, grid.62560.37
- (10) Dartmouth College, grid.254880.3
- (11) Alberta Health Services, grid.413574.0
- (12) American Cancer Society, grid.422418.9
- (13) University of Southern California, grid.42505.36
- (14) University of Massachusetts Amherst, grid.266683.f
- (15) Seoul National University, grid.31501.36
- (16) Albert Einstein College of Medicine, grid.251993.5
- (17) Broad Institute, grid.66859.34
- (18) Chonnam National University, grid.14005.30
- (19) Korea University Medical Center, grid.411134.2
- (20) Memorial Sloan Kettering Cancer Center, grid.51462.34
- (21) Chinese Academy of Medical Sciences & Peking Union Medical College, grid.506261.6
- (22) Anhui Medical University, grid.186775.a
- (23) Genome Institute of Singapore, grid.418377.e
- (24) University of Hawaii at Manoa, grid.410445.0
- (25) Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, grid.418165.f
- (26) Yale University, grid.47100.32
- (27) Moffitt Cancer Center, grid.468198.a
- (28) Kyushu University, grid.177174.3
- (29) Kyungpook National University Medical Center, grid.477473.4
- (30) National University of Singapore, grid.4280.e
- (31) Nanjing Medical University, grid.89957.3a
- (32) Vanderbilt University Medical Center, grid.412807.8
- (33) Fudan University, grid.8547.e
- (34) University of Hong Kong, grid.194645.b
- (35) Huazhong University of Science and Technology, grid.33199.31
- (36) Guangdong Academy of Medical Sciences, grid.410643.4
- (37) National Taiwan University, grid.19188.39
- (38) China Medical University, grid.412449.e
- (39) Vanderbilt University, grid.152326.1
- (40) The University of Texas MD Anderson Cancer Center, grid.240145.6
- (41) International Epidemiology Institute, grid.419344.f
- (42) Wayne State University, grid.254444.7
- (43) University of California, San Francisco, grid.266102.1
- (44) National Institute for Occupational Safety and Health, grid.416809.2
- (45) University of Alberta, grid.17089.37
- (46) Shanxi Tumor Hospital, grid.440201.3
- (47) Unit of Nutrition, Environment, and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology, Bellvitge Biomedical Research Institute,, Barcelona 08908, Spain
- (48) Shanghai Cancer Institute, grid.419087.3
- (49) Dana-Farber Cancer Institute, grid.65499.37
- (50) Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, School of Medicine, Shanghai Jiaotaong University Shanghai 200032, People’s Republic of China
- (51) Department of Pediatrics, University Clinic of Navarra, Universidad de Navarra, Pamplona 31080, Spain
- (52) Institute of Cancer Research, grid.18886.3f
- (53) VA Boston Healthcare System, grid.410370.1
- (54) University of Melbourne, grid.1008.9
- (55) Umeå University, grid.12650.30
- (56) International Agency For Research On Cancer, grid.17703.32
- (57) Rigshospitalet, grid.475435.4, Capital Region
- (58) Unit of Survivorship Research, Danish Cancer Society Research Centre, Copenhagen 2100, Denmark
- (59) University of Cambridge, grid.5335.0
- (60) Duke NUS Graduate Medical School, grid.428397.3
- (61) Fondazione IRCCS Istituto Nazionale dei Tumori, grid.417893.0
- (62) Spanish National Cancer Research Centre, grid.7719.8
- (63) Mayo Clinic, grid.66875.3a
- (64) Nofer Institute of Occupational Medicine, grid.418868.b
- (65) Pompeu Fabra University, grid.5612.0
- (66) Imperial College London, grid.7445.2
- (67) Quantitative Genomic Medicine Laboratory, qGenomics, Barcelona 08003, Spain
- (68) Centre for Biomedical Network Research on Rare Diseases, grid.452372.5
- (69) Human Genetics Foundation, grid.428948.b
- (70) Baylor College of Medicine, grid.39382.33
- (71) Johns Hopkins University, grid.21107.35
- (72) Information Management Services, grid.280929.8
- (73) Washington University in St. Louis, grid.4367.6
- (74) New York University, grid.137628.9
- (75) University of Michigan, grid.214458.e
- (76) State Serum Institute, grid.6203.7
- (77) University of Washington, grid.34477.33
- (78) Northwestern University, grid.16753.36
- (79) University of Pittsburgh, grid.21925.3d
- (80) Stanford University, grid.168010.e
- (81) University of Iowa, grid.214572.7
- (82) Office of Population Genomics, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
- (83) Hospital Del Mar, grid.411142.3
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Description
Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.