Investigating the Genetic Characteristics of Hippocampal Volume and Plasma β-Amyloid in a Chinese Community-Dwelling Population. (19th July 2022) - Yang, Xin-Zhuang; Wan, Meng-Yao; Zhang, Ding-Ding; Dai, Yi; Pan, Zi-Ang; Zhai, Fei-Fei; Han, Fei; Liu, Jing-Yi; Zhou, Li-Xin; Ni, Jun; Yao, Ming; Jin, Zheng-Yu; et al.
Abstract : Background and Objectives: The genetic characteristics and correlations of hippocampal volume (HV) and plasma β-amyloid (Aβ), probable endophenotypes for dementia, remain to be explored in a Chinese community cohort. Using whole-exome sequencing (WES) and single nucleotide polymorphism (SNP) array genotyping, we sought to identify rare and common variants and genes influencing these 2 endophenotypes and calculate their heritability and genetic correlation. Methods: Association analyses with both WES and SNP array genotyping data were performed for HV and plasma Aβ with mixed-effect linear regression model adjusted for sex, age, and total intracranial volume or APOE ε4 while considering familial relatedness. We also performed gene-level analysis for common and gene burden analysis for rare variants. Heritability and genetic correlation were examined further. Results: A total of 1, 261 participants from a Chinese community cohort were included and we identified 1 gene, PTPRT, for HV, with the top significant SNPs by whole genome-wide association study (GWAS). rs6030076 ( p = 5.48 × 10 −8, β = −0.092, SE 0.017) from WES and rs6030088 ( p = 8.24 × 10 −9, β = −105.22, SE 18.09) from SNP array data were both located in this gene. Gene burden analysis based on rare mutations detected 6 genes to be significantly associated with Aβ. The SNP-based heritability was 0.43 ± 0.13 for HV and 0.2–0.3 for plasma Aβ. The SNP-based genetic correlation between HV and plasma Aβ was negative. Discussion: In this study, we identified several SNPs and 1 gene, PTPRT, which were not reported in previous GWAS, associated with HV. The heritability and the genetic correlation gave an overview of HV and plasma Aβ. Our findings provide insights into the mechanisms behind the individual variances in these endophenotypes.