Abstract
Copy-number variants (CNVs) are a source of genetic variation that increasingly are associated with human disease. However, the role of CNVs in human lifespan is to date unknown. To identify CNVs that influence mortality at old age, we analyzed genome-wide CNV data in 5178 participants of Rotterdam Study (RS1) and positive findings were evaluated in 1714 participants of the second cohort of the Rotterdam Study (RS2) and in 4550 participants of Framingham Heart Study (FHS). First, we assessed the total burden of rare (frequency <1%) and common (frequency >1%) CNVs for association with mortality during follow-up. These analyses were repeated by stratifying CNVs by type and size. Secondly, we assessed individual common CNV regions (CNVR) for association with mortality. We observed that the burden of common but not of rare CNVs influences mortality. A higher burden of large (≥500 kb) common deletions associated with 4% higher mortality [hazard ratio (HR) per CNV 1.04, 95% confidence interval (CI) 1.02-1.07, P 5 5.82 3 10 -25] in the 11 442 participants of RS1, RS2 and FHS. In the analysis of 312 individual common CNVRs, we identified two regions (11p15.5; 14q21.3) that associated with higher mortality in these cohorts. The 11p15.5 region (combined HR 1.59, 95% CI 1.31-1.93, P 5 2.87 3 10 -26) encompasses 41 genes, of which some have previously been related to longevity, whereas the 14q21.3 region (combined HR 1.57, 95% CI 1.19-2.07, P 5 1.53 3 10 -23) does not encompass any genes. In conclusion, the burden of large common deletions, as well as common CNVs in 11p15.5 and 14q21.3 region, associate with higher mortality.
| Original language | English |
|---|---|
| Article number | ddr340 |
| Pages (from-to) | 4290-4296 |
| Number of pages | 7 |
| Journal | Human Molecular Genetics |
| Volume | 20 |
| Issue number | 21 |
| DOIs | |
| State | Published - Nov 2011 |
| Externally published | Yes |
Bibliographical note
Funding Information:This work was supported by the Research Institute for Diseases in the Elderly (grant number 014-93-015; RIDE2); and the Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO) project (grant number 050-060-810; NCHA), Erasmus Medical Center and Erasmus University, Rotterdam; Netherlands Organization for the Health Research and Development (ZonMw); the Research Institute for Diseases in the Elderly (RIDE); the Ministry of Education, Culture and Science; the Ministry for Health, Welfare and Sports; the European Commission (DG XII); and the Municipality of Rotterdam. The generation and management of GWAS genotype data for the Rotterdam Study are supported by the Netherlands Organization of Scientific Research NWO Investments (grant numbers 175.010.2005.011, 911-03-012 and 017-106-370 VIDI to H.T.). The FHS was funded by grants from the US National Institute for Arthritis, Musculoskeletal and Skin Diseases and National Institute on Aging (R01 AR/AG 41398 D.P.K.; R01 AR 050066 D.K.; R01 AG 29451 J.M. and K.L.L.) and Hebrew SeniorLife Men’s Associate. The Framingham Heart Study of the National Heart, Lung, and Blood Institute of the National Institutes of Health and Boston University School of Medicine were supported by the National Heart, Lung, and Blood Institute’s Framingham Heart Study (N01-HC-25195) and its contract with Affymetrix, Inc. for genotyp-ing services (N02-HL-6-4278). Analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. A portion of this research was conducted using the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center.
