PloS one · 2017
Red blood cell distribution width: Genetic evidence for aging pathways in 116,666 volunteers.
СтатьяНазвание и аннотация: Перевод в очереди
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Pilling Luke C, Atkins Janice L, Duff Michael O, Beaumont Robin N, Jones Samuel E, Tyrrell Jessica, Kuo Chia-Ling, Ruth Katherine S, Tuke Marcus A, Yaghootkar Hanieh, Wood Andrew R, Murray Anna, Weedon Michael N, Harries Lorna W, Kuchel George A, Ferrucci Luigi, Frayling Timothy M, Melzer David
Аннотация
INTRODUCTION: Variability in red blood cell volumes (distribution width, RDW) increases with age and is strongly predictive of mortality, incident coronary heart disease and cancer. We investigated inherited genetic variation associated with RDW in 116,666 UK Biobank human volunteers.
RESULTS: A large proportion RDW is explained by genetic variants (29%), especially in the older group (60+ year olds, 33.8%, <50 year olds, 28.4%). RDW was associated with 194 independent genetic signals; 71 are known for conditions including autoimmune disease, certain cancers, BMI, Alzheimer's disease, longevity, age at menopause, bone density, myositis, Parkinson's disease, and age-related macular degeneration. Exclusion of anemic participants did not affect the overall findings. Pathways analysis showed enrichment for telomere maintenance, ribosomal RNA, and apoptosis. The majority of RDW-associated signals were intronic (119 of 194), including SNP rs6602909 located in an intron of oncogene GAS6, an eQTL in whole blood.
CONCLUSIONS: Although increased RDW is predictive of cardiovascular outcomes, this was not explained by known CVD or related lipid genetic risks, and a RDW genetic score was not predictive of incident disease. The predictive value of RDW for a range of negative health outcomes may in part be due to variants influencing fundamental pathways of aging.
RESULTS: A large proportion RDW is explained by genetic variants (29%), especially in the older group (60+ year olds, 33.8%, <50 year olds, 28.4%). RDW was associated with 194 independent genetic signals; 71 are known for conditions including autoimmune disease, certain cancers, BMI, Alzheimer's disease, longevity, age at menopause, bone density, myositis, Parkinson's disease, and age-related macular degeneration. Exclusion of anemic participants did not affect the overall findings. Pathways analysis showed enrichment for telomere maintenance, ribosomal RNA, and apoptosis. The majority of RDW-associated signals were intronic (119 of 194), including SNP rs6602909 located in an intron of oncogene GAS6, an eQTL in whole blood.
CONCLUSIONS: Although increased RDW is predictive of cardiovascular outcomes, this was not explained by known CVD or related lipid genetic risks, and a RDW genetic score was not predictive of incident disease. The predictive value of RDW for a range of negative health outcomes may in part be due to variants influencing fundamental pathways of aging.