ArticleJournal of the American Medical Informatics Association : JAMIA2017
The landscape of genetic susceptibility correlations among diseases and traits.
Article in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Comorbidity of asthma and hypertension may be mediated by shared genetic dysregulation and drug side effects.Scientific reports · 2019Article
- Genetic correlations among psychiatric and immune-related phenotypes based on genome-wide association data.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2018Article
- Convergent downstream candidate mechanisms of independent intergenic polymorphisms between co-classified diseases implicate epistasis among noncoding elements.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2018Article
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Authors and funding
1 author.
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Abstract
objectiveThe aim of the study was to comprehensively explore the genetic susceptibility correlations among diseases and traits from large-scale individual genotype data. MATERIALS AND
methodsBased on a knowledge base of genetic variants significantly (P < 5 × 10 -8 ) linked with human phenotypes, genetic risk scores (GRSs) of diseases or traits were calculated for 2504 individuals with whole-genome sequencing data from the 1000 Genomes Project. Associations between diseases/traits were statistically evaluated by pairwise correlation analysis of GRSs. Overlaps between the genetic susceptibility correlations and disease comorbidity associations from hospital claims data in more than 30 million patients in United States were assessed.
resultsCorrelation analysis of GRSs revealed 823 significant correlations among 78 diseases and 89 traits (false discovery rate adjusted P -value or Q -value < 0.01). It is noticeable that GRSs were correlated in 464 associations (56.4%) even if they were combinations of distinct sets of risk variants without chromosomal linkage, suggesting the presence of genetic interactions beyond chromosome position. When 312 significant genetic susceptibility correlations between diseases were compared to nationwide disease comorbidity correlations obtained from data from 32 million Medicare claims in the United States, 108 overlaps (34.6%) were found that had both genetic susceptibility and epidemiologic comorbid correlations.
conclusionThe study suggests that common genetic background exists between diseases and traits with epidemiologic associations. The GRS correlation approach provides a rich source of candidate associations among diseases and traits from the genetic perspective, warranting further epidemiologic studies.
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