Literature DB >> 28528225

Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort.

N Abdullah1, N A Abdul Murad2, E A Mohd Haniff2, S E Syafruddin2, J Attia3, C Oldmeadow3, M A Kamaruddin2, N Abd Jalal2, N Ismail2, M Ishak2, R Jamal4, R J Scott5, E G Holliday6.   

Abstract

OBJECTIVE: Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. STUDY
DESIGN: This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project.
METHODS: The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants.
RESULTS: The models including environmental risk factors only had pseudo R2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10-4-4.83 × 10-12) and increased the pseudo R2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05.
CONCLUSION: This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection.
Copyright © 2017 The Royal Society for Public Health. All rights reserved.

Entities:  

Keywords:  Asian population; Epidemiology; Gene–environment interaction; Population studies; Type 2 diabetes

Mesh:

Year:  2017        PMID: 28528225     DOI: 10.1016/j.puhe.2017.04.003

Source DB:  PubMed          Journal:  Public Health        ISSN: 0033-3506            Impact factor:   2.427


  4 in total

1.  A Genetic Risk Score Improves the Prediction of Type 2 Diabetes Mellitus in Mexican Youths but Has Lower Predictive Utility Compared With Non-Genetic Factors.

Authors:  América Liliana Miranda-Lora; Jenny Vilchis-Gil; Daniel B Juárez-Comboni; Miguel Cruz; Miguel Klünder-Klünder
Journal:  Front Endocrinol (Lausanne)       Date:  2021-03-12       Impact factor: 5.555

2.  Ethnicity-Specific Association Between Ghrelin Leu72Met Polymorphism and Type 2 Diabetes Mellitus Susceptibility: An Updated Meta-Analysis.

Authors:  Rong Huang; Sai Tian; Rongrong Cai; Jie Sun; Yanjue Shen; Shaohua Wang
Journal:  Front Genet       Date:  2018-11-14       Impact factor: 4.599

3.  Association between MIR499A rs3746444 polymorphism and breast cancer susceptibility: a meta-analysis.

Authors:  Shing Cheng Tan; Poh Ying Lim; Jie Fang; Mira Farzana Mohamad Mokhtar; Ezanee Azlina Mohamad Hanif; Rahman Jamal
Journal:  Sci Rep       Date:  2020-02-26       Impact factor: 4.379

4.  Analysis of OCT1, OCT2 and OCT3 gene polymorphisms among Type 2 diabetes mellitus subjects in Indian ethnicity, Malaysia.

Authors:  Sabah Ghasan Abood Al-Ashoor; Vasudevan Ramachandran; Liyana Najwa Inche Mat; Nur Afiqah Mohamad; Mohd Hazmi Mohamed; Wan Aliaa Wan Sulaiman
Journal:  Saudi J Biol Sci       Date:  2021-09-14       Impact factor: 4.219

  4 in total

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