Department of Biostatistics, Boston University, School of Public Health, Boston, Massachusetts, USA.
Human Genetics Center, Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
Alzheimers Dement. 2024 May;20(5):3290-3304. doi: 10.1002/alz.13705. Epub 2024 Mar 21.
Genome-wide association studies (GWAS) have identified loci associated with Alzheimer's disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci.
We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases = 2184, N controls = 2383) and targeted analyses in subpopulations using WGS data from the Alzheimer's Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants.
Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses.
This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS.
全基因组关联研究（GWAS）已经确定了与阿尔茨海默病（AD）相关的基因座，但并未确定这些基因座内的特定因果基因或变体。全基因组序列（WGS）分析可以检测整个基因组并捕获罕见变异，从而确定 GWAS 基因座内的因果变异。
我们在合并人群（病例数=2184，对照组=2383）中进行了单共同变异关联分析和罕见变异聚集分析，并使用阿尔茨海默病测序项目（ADSP）的 WGS 数据在亚人群中进行了靶向分析。分析仅限于先前确定的 83 个 GWAS 先导变体 100 kb 内的变体。
在五个基因座中，有 17 个变体与 AD 显著相关，涉及基因 OARD1/NFYA/TREML1、JAZF1、FERMT2 和 SLC24A4。KAT8 同时通过单变异和罕见变异聚集分析被牵连。
本研究证明了利用 WGS 深入了解通过 GWAS 确定的 AD 基因座的有效性。
