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Quantitative Relationship Between Cumulative Risk Alleles Based on Genome-Wide Association Studies and Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis

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Kodama, Satoru, Fujihara, Kazuya, Ishiguro, Hajime, Horikawa, Chika, Ohara, Nobumasa, Yachi, Yoko, Tanaka, Shiro, Shimano, Hitoshi +3 more·2018·Journal of Epidemiology
DOI 10.2188/jea.je20160151PMC PMC5742374
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Abstract

Many epidemiological studies have assessed the genetic risk of having undiagnosed or of developing type 2 diabetes mellitus (T2DM) using several single nucleotide polymorphisms (SNPs) based on findings of genome-wide association studies (GWAS). However, the quantitative association of cumulative risk alleles (RAs) of such SNPs with T2DM risk has been unclear. The aim of this meta-analysis is to review the strength of the association between cumulative RAs and T2DM risk. Systematic literature searches were conducted for cross-sectional or longitudinal studies that examined odds ratios (ORs) for T2DM in relation to genetic profiles. Logarithm of the estimated OR (log OR) of T2DM for 1 increment in RAs carried (1-ΔRA) in each study was pooled using a random-effects model. There were 46 eligible studies that included 74,880 cases among 249,365 participants. In 32 studies with a cross-sectional design, the pooled OR for T2DM morbidity for 1-ΔRA was 1.16 (95% confidence interval [CI], 1.13-1.19). In 15 studies that had a longitudinal design, the OR for incident T2DM was 1.10 (95% CI, 1.08-1.13). There was large heterogeneity in the magnitude of log OR (P < 0.001 for both cross-sectional studies and longitudinal studies). The top 10 commonly used genes significantly explained the variance in the log OR (P = 0.04 for cross-sectional studies; P = 0.006 for longitudinal studies). The current meta-analysis indicated that carrying 1-ΔRA in T2DM-associated SNPs was associated with a modest risk of prevalent or incident T2DM, although the heterogeneity in the used genes among studies requires us to interpret the results with caution.

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  • Advancing age, increasing BMI and racial group are associated with the high prevalence of gestational diabetes mellitus in Asia.

    “Therefore, advancing age, increasing BMI and racial group are associated to the high prevalence of GDM in Asia.”

    From Prevalence and risk factors of gestational diabetes mellitus in Asia: a systematic review and meta-analysis (2018) · cites this paper as [158]

    The Discussion and Results address how BMI, ethnicity and age relate to genetic risk associations for type 2 diabetes, not the prevalence of gestational diabetes in Asia. Searches for gestational diabetes, GDM and pregnancy found no passage addressing the claimed association; page numbers were not supplied in our copy. (LLM, conf=0.77)

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Cited by

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Authors
Kodama, S., Fujihara, K., Ishiguro, H., Horikawa, C., Ohara, N., Yachi, Y., Tanaka, S., Shimano, H., Kato, K., Hanyu, O., & Sone, H.
Affiliations
  • Niigata University (JP)
  • University of Niigata Prefecture (JP)
  • Yamanashi Gakuin University (JP)
  • Kyoto University Hospital (JP)
  • University of Tsukuba (JP)
ORCID
Venue
Journal of Epidemiology
Publisher
Japan Epidemiological Association
Published
2018
Volume
28
Issue
1
Pages
3-18
ISSN
  • 0917-5040 (ISSN-L)
  • 1349-9092
DOI
10.2188/jea.je20160151
PMC
PMC5742374
OpenAlex
W2766539614
Cited by
18
References
7
Citations by year
2025: 3 · 2024: 3 · 2023: 1 · 2022: 2 · 2020: 2 · 2019: 3 · 2018: 4
FWCI
0.32
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Epidemiology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Terrestrial Environment Research Center (University of Tsukuba) (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Japan Society for the Promotion of Science (16H03260, 16K16296, 16H06808)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords
type 2 diabetes, single nucleotide polymorphisms, genetic risk, diabetes risk prediction, genetic susceptibility, new-onset diabetes
MeSH terms
Alleles, Diabetes Mellitus, Type 2, Humans, Genetic Predisposition to Disease, Genome-Wide Association Study

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