Department of Epidemiology, Erasmus Medical Center, Rotterdam, CA 3000, The Netherlands.
Hum Mol Genet. 2011 Nov 1;20(21):4290-6. doi: 10.1093/hmg/ddr340. Epub 2011 Aug 11.
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 = 5.82 × 10(-5)] 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 = 2.87 × 10(-6)) 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 = 1.53 × 10(-3)) 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.
拷贝数变异(CNVs)是遗传变异的一个来源,越来越多地与人类疾病有关。然而,CNVs 对人类寿命的影响至今尚不清楚。为了确定影响老年死亡率的 CNVs,我们分析了 5178 名鹿特丹研究(RS1)参与者的全基因组 CNV 数据,并在鹿特丹研究的第二队列(RS2)的 1714 名参与者和弗雷明汉心脏研究(FHS)的 4550 名参与者中评估了阳性发现。首先,我们评估了罕见(频率<1%)和常见(频率>1%)CNV 的总负担与随访期间的死亡率相关。通过按类型和大小对 CNVs 进行分层,重复了这些分析。其次,我们评估了个体常见 CNV 区域(CNVR)与死亡率的关联。我们观察到,常见 CNV 的负担而不是罕见 CNV 的负担影响死亡率。较大(≥500kb)常见缺失的负担与 RS1、RS2 和 FHS 中 11442 名参与者 4%的死亡率升高相关[每个 CNV 的风险比(HR)为 1.04,95%置信区间(CI)为 1.02-1.07,P=5.82×10(-5)]。在对 312 个常见 CNVR 的分析中,我们确定了两个与这些队列中较高死亡率相关的区域(11p15.5;14q21.3)。11p15.5 区域(合并 HR 1.59,95%CI 1.31-1.93,P=2.87×10(-6))包含 41 个基因,其中一些先前与长寿有关,而 14q21.3 区域(合并 HR 1.57,95%CI 1.19-2.07,P=1.53×10(-3))不包含任何基因。总之,大的常见缺失以及 11p15.5 和 14q21.3 区域的常见 CNVs 的负担与较高的死亡率相关。