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Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure.

  • Author(s): Chen, Chi-Hua
  • Wang, Yunpeng
  • Lo, Min-Tzu
  • Schork, Andrew
  • Fan, Chun-Chieh
  • Holland, Dominic
  • Kauppi, Karolina
  • Smeland, Olav B
  • Djurovic, Srdjan
  • Sanyal, Nilotpal
  • Hibar, Derrek P
  • Thompson, Paul M
  • Thompson, Wesley K
  • Andreassen, Ole A
  • Dale, Anders M
  • et al.
Abstract

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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