rs11008222 - LINC02644 - ZNF438

Magnitude 4.5 · 2 studies on file

Reported associations

  • Genome-wide association study of maternal and inherited effects on left-sided cardiac malformations. - Human molecular genetics (2015) · Mitchell LE, Agopian AJ, Bhalla A, Glessner JT, Kim CE, Swartz MD, Hakonarson H, Goldmuntz E · PubMed 25138779

    Congenital left-sided lesions (LSLs) are serious, heritable malformations of the heart. However, little is known about the genetic causes of LSLs. This study was undertaken to identify common variants acting through the genotype of the affected individual (i.e. case) or the mother (e.g. via an in utero effect) that influence the risk of LSLs. A genome-wide association study (GWAS) was performed using data from 377 LSL case-parent triads, with follow-up studies in an independent sample of 224 triads and analysis of the combined data. Associations with both the case and maternal genotypes were assessed using log-linear analyses under an additive model. An association between LSLs and the case genotype for one intergenic SNP on chromosome 16 achieved genome-wide significance in the combined d

  • 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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