Expressive

rs11213366 - LINC02732

Magnitude 2.2 · 2 studies on file

Reported associations

  • 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

  • Classification of early age facial growth pattern and identification of the genetic basis in two Korean populations - Unknown journal (n.d.) · Unknown authors · PubMed 35970861

    ABSTRACT: Childhood to adolescence is an accelerated growth period, and genetic features can influence differences of individual growth patterns. In this study, we examined the genetic basis of early age facial growth (EAFG) patterns. Facial shape phenotypes were defined using facial landmark distances, identifying five growth patterns: continued-decrease, decrease-to-increase, constant, increase-to-decrease, and continued-increase. We conducted genome-wide association studies (GWAS) for 10 horizontal and 11 vertical phenotypes. The most significant association for horizontal phenotypes was rs610831 (TRIM29; β = 0.92, p-value = 1.9 × 10−9) and for vertical phenotypes was rs6898746 (ZSWIM6; β = 0.1103, p-value = 2.5 × 10−8). It is highly correlated with genes

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