Identification of genetic loci affecting body mass index through interaction with multiple environmental factors using structured linear mixed model

Autor: Wonjun Lee, Hae Un Jung, Tae Woong Ha, Sungho Won, Jihye Kim, Bermseok Oh, Ji One Kang, Mi Kyung Kim, Taesung Park, Ji Eun Lim
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Scientific Reports
ISSN: 2045-2322
Popis: Multiple environmental factors could interact with a single genetic factor to affect disease phenotypes. We used Struct-LMM to identify genetic variants that interacted with environmental factors related to body mass index (BMI) using data from the Korea Association Resource. The following factors were investigated: alcohol consumption, education, physical activity metabolic equivalent of task (PAMET), income, total calorie intake, protein intake, carbohydrate intake, and smoking status. Initial analysis identified 7 potential single nucleotide polymorphisms (SNPs) that interacted with the environmental factors (P value −6). Of the 8 environmental factors, PAMET score was excluded for further analysis since it had an average Bayes Factor (BF) value P value −6). Of these, rs2391331 had the most significant interaction (P value = 7.27 × 10−9) and was located within the intron of EFNB2 (Chr 13). In addition, the gene-based genome-wide association study verified EFNB2 gene significantly interacting with 7 environmental factors (P value = 5.03 × 10−10). BF analysis indicated that most environmental factors, except carbohydrate intake, contributed to the interaction of rs2391331 on BMI. Although the replication of the results in other cohorts is warranted, these findings proved the usefulness of Struct-LMM to identify the gene–environment interaction affecting disease.
Databáze: OpenAIRE
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