Expressive

rs1040851 - ASTN2

Magnitude 2.0 · 8 studies on file

Reported associations

  • Cross-ancestry and sex-stratified genome-wide association analyses of amygdala and subnucleus volumes. - Nature genetics (2025) · Ji Y, Liu N, Yang Y, Wang M, Cheng J, Zhu W, Qiu S, Geng Z, Cui G, Yu Y, Liao W, Zhang H, Gao B, Xu X, Han T, Yao Z, Zhang Q, Qin W, Liu F, Liang M, Wang S, Xu Q, Xu J, Fu J, Zhang P, Li W, Shi D, Wang C, Lui S, Yan Z, Chen F, Zhang J, Shen W, Miao Y, Wang D, Gao JH, Zhang X, Xu K, Zuo XN, Zhang L, Ye Z, Li MJ, Xian J, Zhang B, Yu C · PubMed 40097784

    The amygdala is a small but critical multi-nucleus structure for emotion, cognition and neuropsychiatric disorders. Although genetic associations with amygdala volumetric traits have been investigated in sex-combined European populations, cross-ancestry and sex-stratified analyses are lacking. Here we conducted cross-ancestry and sex-stratified genome-wide association analyses for 21 amygdala volumetric traits in 6,923 Chinese and 48,634 European individuals. We identified 191 variant-trait associations (P < 2.38 × 10 ), including 47 new associations (12 new loci) in sex-combined univariate analyses and seven additional new loci in sex-combined and sex-stratified multivariate analyses. We identified 12 ancestry-specific and two sex-specific associations. The identified genetic var

  • 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

  • A cross-population atlas of genetic associations for 220 human phenotypes. - Nature genetics (2021) · Sakaue S, Kanai M, Tanigawa Y, Karjalainen J, Kurki M, Koshiba S, Narita A, Konuma T, Yamamoto K, Akiyama M, Ishigaki K, Suzuki A, Suzuki K, Obara W, Yamaji K, Takahashi K, Asai S, Takahashi Y, Suzuki T, Shinozaki N, Yamaguchi H, Minami S, Murayama S, Yoshimori K, Nagayama S, Obata D, Higashiyama M, Masumoto A, Koretsune Y, Ito K, Terao C, Yamauchi T, Komuro I, Kadowaki T, Tamiya G, Yamamoto M, Nakamura Y, Kubo M, Murakami Y, Yamamoto K, Kamatani Y, Palotie A, Rivas MA, Daly MJ, Matsuda K, Okada Y · PubMed 34594039

    Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (n = 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wid

  • Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging - Unknown journal (n.d.) · Unknown authors · PubMed 38580839

    ABSTRACT: Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants' T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes

  • Genetic architecture of orbital telorism - Unknown journal (n.d.) · Unknown authors · PubMed 34791242

    ABSTRACT: Abstract The interocular distance, or orbital telorism, is a distinctive craniofacial trait that also serves as a clinically informative measure. While its extremes, hypo- and hypertelorism, have been linked to monogenic disorders and are often syndromic, little is known about the genetic determinants of interocular distance within the general population. We derived orbital telorism measures from cranial magnetic resonance imaging by calculating the distance between the eyeballs' centre of gravity, which showed a good reproducibility with an intraclass correlation coefficient of 0.991 (95% confidence interval 0.985-0.994). Heritability estimates were 76% (standard error = 12%) with a family-based method (N = 364) and 39% (standard error = 2.4%) with a single nucle

  • Genome-wide association analysis of 19,629 individuals identifies variants influencing regional brain volumes and refines their genetic co-architecture with cognitive and mental health traits - Unknown journal (n.d.) · Unknown authors · PubMed 31676860

    ABSTRACT: Volumetric variations of human brain are heritable and are associated with many brain-related complex traits. Here we performed genome-wide association studies (GWAS) of 101 brain volumetric phenotypes using the UK Biobank (UKB) sample including 19,629 participants. GWAS identified 365 independent genetic variants exceeding significance threshold of 4.9 × 10−10, adjusted for testing multiple phenotypes. Gene-based association study found 157 associated genes (124 new), and functional gene mapping analysis linked 146 additional genes. Many of the discovered genetic variants and genes have previously been implicated in cognitive and mental health traits. Using genome-wide polygenic risk score prediction, more than 6% of phenotypic variance (P = 3.13 × 10−24) in four other ind

  • A Meta-Analysis of the Genome-Wide Association Studies on Two Genetically Correlated Phenotypes Suggests Four New Risk Loci for Headaches - Unknown journal (n.d.) · Unknown authors · PubMed 36939796

    ABSTRACT: Headache is one of the commonest complaints that doctors need to address in clinical settings. The genetic mechanisms of different types of headache are not well understood while it has been suggested that self-reported headache and self-reported migraine were genetically correlated. In this study, we performed a meta-analysis of genome-wide association studies (GWAS) on the self-reported headache phenotype from the UK Biobank and the self-reported migraine phenotype from the 23andMe using the Unified Score-based Association Test (metaUSAT) software for genetically correlated phenotypes (N = 397,385). We identified 38 loci for headaches, of which 34 loci have been reported before and four loci were newly suggested. The LDL receptor related protein 1 (LRP1)-Signal Transduce

  • Genetic architecture of the white matter connectome of the human brain - Unknown journal (n.d.) · Unknown authors · PubMed 36800424

    ABSTRACT: White matter tracts form the structural basis of large-scale brain networks. We applied brain-wide tractography to diffusion images from 30,810 adults (U.K. Biobank) and found significant heritability for 90 node-level and 851 edge-level network connectivity measures. Multivariate genome-wide association analyses identified 325 genetic loci, of which 80% had not been previously associated with brain metrics. Enrichment analyses implicated neurodevelopmental processes including neurogenesis, neural differentiation, neural migration, neural projection guidance, and axon development, as well as prenatal brain expression especially in stem cells, astrocytes, microglia, and neurons. The multivariate association profiles implicated 31 loci in connectivity between core regions of the le

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