Discovering genetic variants associated with human brain structures is an on-going effort. The ENIGMA consortium conducted genome-wide association studies (GWAS) with standard multi-study analytical methodology and identified several significant single nucleotide polymorphisms (SNPs). Here we employ a novel analytical approach that incorporates functional genome annotations (e.g., exon or 5′UTR), total linkage disequilibrium (LD) scores and heterozygosity to construct enrichment scores for improved identification of relevant SNPs. The method provides increased power to detect associated SNPs by estimating stratum-specific false discovery rate (FDR), where strata are classified according to enrichment scores. Applying this approach to the GWAS summary statistics of putamen volume in the ENIGMA cohort, a total of 15 independent significant SNPs were identified (conditional FDR < 0.05). In contrast, 4 SNPs were found based on standard GWAS analysis (P < 5 × 10−8). These 11 novel loci include GATAD2B, ASCC3, DSCAML1, and HELZ, which are previously implicated in various neural related phenotypes. The current findings demonstrate the boost in power with the annotation-informed FDR method, and provide insight into the genetic architecture of the putamen.
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机译：发现与人类大脑结构相关的遗传变异是一项持续的工作。 ENIGMA联盟使用标准的多研究分析方法进行了全基因组关联研究（GWAS），并确定了几种重要的单核苷酸多态性（SNP）。在这里，我们采用了一种新颖的分析方法，该方法结合了功能性基因组注释（例如外显子或5'UTR），总连锁不平衡（LD）得分和杂合性，以构建用于改善相关SNP鉴定的富集得分。该方法通过估计特定于层的虚假发现率（FDR）（根据富集得分对层进行分类）来提高检测相关SNP的能力。将这种方法应用于ENIGMA队列的GWAS壳核量摘要统计中，总共鉴定出15个独立的重要SNP（条件FDR F <0.05）。相反，根据标准GWAS分析发现了4个SNP（P <5×10-8）。这11个新基因座包括GATAD2B，ASCC3，DSCAML1和HELZ，它们先前与各种神经相关表型有关。目前的发现证明了采用注释信息的FDR方法的能力得到了增强，并提供了壳核的遗传结构的见解。
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