ArticleBMC genomics2019
A phenomics-based approach for the detection and interpretation of shared genetic influences on 29 biochemical indices in southern Chinese men.
Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- Aldehyde Dehydrogenase 2 Gene Polymorphism and Alcohol Consumption Are Associated With Nephrolithiasis in a Chinese Population.Molecular genetics & genomic medicine · 2026Article
- Metabolic-Inflammatory Syndrome: Decoding the Metabolic-Immune Axis for Precision Intervention.Aging and disease · 2025Review
- Aldehyde Dehydrogenase 2 (ALDH2) Deficiency, Obesity, and Atrial Fibrillation Susceptibility: Unraveling the Connection.International journal of molecular sciences · 2024Article
- ALDH2 variance in disease and populations.Disease models & mechanisms · 2022Article
- Exploring ALDH2 expression and immune infiltration in HNSC and its correlation of prognosis with gender or alcohol intake.Scientific reports · 2022Article
- Genome-wide discovery of genetic loci that uncouple excess adiposity from its comorbidities.Nature metabolism · 2021Article
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Authors and funding
23 authors at 1 institution in 1 country.
Funding
Abstract
backgroundPhenomics provides new technologies and platforms as a systematic phenome-genome approach. However, few studies have reported on the systematic mining of shared genetics among clinical biochemical indices based on phenomics methods, especially in China. This study aimed to apply phenomics to systematically explore shared genetics among 29 biochemical indices based on the Fangchenggang Area Male Health and Examination Survey cohort.
resultA total of 1999 subjects with 29 biochemical indices and 709,211 single nucleotide polymorphisms (SNPs) were subjected to phenomics analysis. Three bioinformatics methods, namely, Pearson's test, Jaccard's index, and linkage disequilibrium score regression, were used. The results showed that 29 biochemical indices were from a network. IgA, IgG, IgE, IgM, HCY, AFP and B12 were in the central community of 29 biochemical indices. Key genes and loci associated with metabolism traits were further identified, and shared genetics analysis showed that 29 SNPs (P < 10
conclusionAll these findings indicated a network of shared genetics and 29 biochemical indices, which will help fully understand the genetics participating in biochemical metabolism.
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