rs1033394 - HDAC2-AS2

Magnitude 2.2 · 2 studies on file

Reported associations

  • Genome-wide association study of schizophrenia in Ashkenazi Jews. - American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics (2016) · Goes FS, McGrath J, Avramopoulos D, Wolyniec P, Pirooznia M, Ruczinski I, Nestadt G, Kenny EE, Vacic V, Peters I, Lencz T, Darvasi A, Mulle JG, Warren ST, Pulver AE · PubMed 26198764

    Schizophrenia is a common, clinically heterogeneous disorder associated with lifelong morbidity and early mortality. Several genetic variants associated with schizophrenia have been identified, but the majority of the heritability remains unknown. In this study, we report on a case-control sample of Ashkenazi Jews (AJ), a founder population that may provide additional insights into genetic etiology of schizophrenia. We performed a genome-wide association analysis (GWAS) of 592 cases and 505 controls of AJ ancestry ascertained in the US. Subsequently, we performed a meta-analysis with an Israeli AJ sample of 913 cases and 1640 controls, followed by a meta-analysis and polygenic risk scoring using summary results from Psychiatric GWAS Consortium 2 schizophrenia study. The U.S. AJ sample show

  • A saturated map of common genetic variants associated with human height - Unknown journal (n.d.) · Unknown authors · PubMed 36224396

    ABSTRACT: Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation


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