rs1001774 - STRBP

Magnitude 2.2 · 2 studies on file

Reported associations

  • Cross-ancestry genome-wide association meta-analyses of hippocampal and subfield volumes. - Nature genetics (2023) · Liu N, Zhang L, Tian T, Cheng J, Zhang B, Qiu S, Geng Z, Cui G, Zhang Q, Liao W, Yu Y, Zhang H, Gao B, Xu X, Han T, Yao Z, Qin W, Liu F, Liang M, Xu Q, Fu J, Xu J, Zhu W, Zhang P, Li W, Shi D, Wang C, Lui S, Yan Z, Chen F, Li J, Zhang J, Wang D, Shen W, Miao Y, Xian J, Gao JH, Zhang X, Li MJ, Xu K, Zuo XN, Wang M, Ye Z, Yu C · PubMed 37337106

    The hippocampus is critical for memory and cognition and neuropsychiatric disorders, and its subfields differ in architecture and function. Genome-wide association studies on hippocampal and subfield volumes are mainly conducted in European populations; however, other ancestral populations are under-represented. Here we conduct cross-ancestry genome-wide association meta-analyses in 65,791 individuals for hippocampal volume and 38,977 for subfield volumes, including 7,009 individuals of East Asian ancestry. We identify 339 variant-trait associations at P < 1.13 × 10 for 44 hippocampal traits, including 23 new associations. Common genetic variants have similar effects on hippocampal traits across ancestries, although ancestry-specific associations exist. Cross-ancestry analysis imp

  • Genome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways. - Nature genetics (2022) · Watanabe K, Jansen PR, Savage JE, Nandakumar P, Wang X, Hinds DA, Gelernter J, Levey DF, Polimanti R, Stein MB, Van Someren EJW, Smit AB, Posthuma D · PubMed 35835914

    Insomnia is a heritable, highly prevalent sleep disorder for which no sufficient treatment currently exists. Previous genome-wide association studies with up to 1.3 million subjects identified over 200 associated loci. This extreme polygenicity suggested that many more loci remain to be discovered. The current study almost doubled the sample size to 593,724 cases and 1,771,286 controls, thereby increasing statistical power, and identified 554 risk loci (including 364 novel loci). To capitalize on this large number of loci, we propose a novel strategy to prioritize genes using external biological resources and functional interactions between genes across risk loci. Of all 3,898 genes naively implicated from the risk loci, we prioritize 289 and find brain-tissue expression spec


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