rs117262476 - PCNT

Magnitude 4.5 · 1 study on file

Reported associations

• Discerning asthma endotypes through comorbidity mapping. - Nature communications (2022) · Jia G, Zhong X, Im HK, Schoettler N, Pividori M, Hogarth DK, Sperling AI, White SR, Naureckas ET, Lyttle CS, Terao C, Kamatani Y, Akiyama M, Matsuda K, Kubo M, Cox NJ, Ober C, Rzhetsky A, Solway J · PubMed 36344522

  Asthma is a heterogeneous, complex syndrome, and identifying asthma endotypes has been challenging. We hypothesize that distinct endotypes of asthma arise in disparate genetic variation and life-time environmental exposure backgrounds, and that disease comorbidity patterns serve as a surrogate for such genetic and exposure variations. Here, we computationally discover 22 distinct comorbid disease patterns among individuals with asthma (asthma comorbidity subgroups) using diagnosis records for >151 M US residents, and re-identify 11 of the 22 subgroups in the much smaller UK Biobank. GWASs to discern asthma risk loci for individuals within each subgroup and in all subgroups combined reveal 109 independent risk loci, of which 52 are replicated in multi-ancestry meta-analysis across differe

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