Expressive

rs10980055 - PALM2AKAP2

Magnitude 4.5 · 2 studies on file

Reported associations

  • Early complement genes are associated with visual system degeneration in multiple sclerosis. - Brain : a journal of neurology (2020) · Fitzgerald KC, Kim K, Smith MD, Aston SA, Fioravante N, Rothman AM, Krieger S, Cofield SS, Kimbrough DJ, Bhargava P, Saidha S, Whartenby KA, Green AJ, Mowry EM, Cutter GR, Lublin FD, Baranzini SE, De Jager PL, Calabresi PA · PubMed 31289819

    Multiple sclerosis is a heterogeneous disease with an unpredictable course and a wide range of severity; some individuals rapidly progress to a disabled state whereas others experience only mild symptoms. Though genetic studies have identified variants that are associated with an increased risk of developing multiple sclerosis, no variants have been consistently associated with multiple sclerosis severity. In part, the lack of findings is related to inherent limitations of clinical rating scales; these scales are insensitive to early degenerative changes that underlie disease progression. Optical coherence tomography imaging of the retina and low-contrast letter acuity correlate with and predict clinical and imaging-based outcomes in multiple sclerosis. Therefore, they may serve as sensiti

  • 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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