rs11992162 - DEFB136 - DEFB135

Magnitude 2.2 · 4 studies on file

Reported associations

• Sequence variation at ANAPC1 accounts for 24% of the variability in corneal endothelial cell density - Unknown journal (n.d.) · Unknown authors · PubMed 30894546

  ABSTRACT: The corneal endothelium is vital for transparency and proper hydration of the cornea. Here, we conduct a genome-wide association study of corneal endothelial cell density (cells/mm2), coefficient of cell size variation (CV), percentage of hexagonal cells (HEX) and central corneal thickness (CCT) in 6,125 Icelanders and find associations at 10 loci, including 7 novel. We assess the effects of these variants on various ocular biomechanics such as corneal hysteresis (CH), as well as eye diseases such as glaucoma and corneal dystrophies. Most notably, an intergenic variant close to ANAPC1 (rs78658973[A], frequency = 28.3%) strongly associates with decreased cell density and accounts for 24% of the population variance in cell density (β = −0.77 SD, P = 1.8 × 10

• Cross-modal autoencoder framework learns holistic representations of cardiovascular state - Unknown journal (n.d.) · Unknown authors · PubMed 37105979

  ABSTRACT: A fundamental challenge in diagnostics is integrating multiple modalities to develop a joint characterization of physiological state. Using the heart as a model system, we develop a cross-modal autoencoder framework for integrating distinct data modalities and constructing a holistic representation of cardiovascular state. In particular, we use our framework to construct such cross-modal representations from cardiac magnetic resonance images (MRIs), containing structural information, and electrocardiograms (ECGs), containing myoelectric information. We leverage the learned cross-modal representation to (1) improve phenotype prediction from a single, accessible phenotype such as ECGs; (2) enable imputation of hard-to-acquire cardiac MRIs from easy-to-acquire ECGs; and (3) develop

• The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease - Unknown journal (n.d.) · Unknown authors · PubMed 27863252

  ABSTRACT: Summary Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we

• GWAS and multi-omics integrative analysis reveal novel loci and their molecular mechanisms for circulating fatty acids - Unknown journal (n.d.) · Unknown authors · PubMed 40545721

  ABSTRACT: Summary Previous genome-wide association studies (GWAS) have identified genetic loci associated with the circulating levels of fatty acids (FAs), but the biological mechanisms of these genetic associations remain largely unexplored. Here, we conducted GWAS to identify additional genetic loci for 19 circulating FA traits in UK Biobank participants of European ancestry (n = 239,268) and five other ancestries (n = 508-4,663). We leveraged the GWAS findings to characterize genetic correlations and colocalized regions among FAs, explore sex differences, examine FA loci influenced by lipoprotein metabolism, and apply statistical fine-mapping to pinpoint putative causal variants. We integrated GWAS signals with multi-omics quantitative trait loci (QTL) to reveal intermediate molecular

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