rs12204990 - ARID1B

Magnitude 2.2 · 2 studies on file

Reported associations

• 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

• Predicted loss and gain of function mutations in ACO1 are associated with erythropoiesis - Unknown journal (n.d.) · Unknown authors · PubMed 32327693

  ABSTRACT: Hemoglobin is the essential oxygen-carrying molecule in humans and is regulated by cellular iron and oxygen sensing mechanisms. To search for novel variants associated with hemoglobin concentration, we performed genome-wide association studies of hemoglobin concentration using a combined set of 684,122 individuals from Iceland and the UK. Notably, we found seven novel variants, six rare coding and one common, at the ACO1 locus associating with either decreased or increased hemoglobin concentration. Of these variants, the missense Cys506Ser and the stop-gained Lys334Ter mutations are specific to eight and ten generation pedigrees, respectively, and have the two largest effects in the study (EffectCys506Ser = −1.61 SD, CI95 = [−1.98, −1.35]; EffectLys334Ter = 0.

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