ArticleHuman genetics2013
Systematic identification of interaction effects between genome- and environment-wide associations in type 2 diabetes mellitus.
Article in Human genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
68 citing papers in PubMed, 4 syntheses or guidelines pooled it, 109 citations in OpenAlex.
- Interactions between genetic and lifestyle factors on cardiometabolic disease-related outcomes in Latin American and Caribbean populations: A systematic review.Frontiers in nutrition · 2023Pooled it
- Design and methodology challenges of environment-wide association studies: A systematic review.Environmental research · 2020Pooled it
- An autism case history to review the systematic analysis of large-scale data to refine the diagnosis and treatment of neuropsychiatric disorders.Biological psychiatry · 2015Pooled it
- Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.PLoS genetics · 2014Pooled it
- Integrating the Thrifty Genotype and Evolutionary Mismatch Hypotheses to understand variation in cardiometabolic disease risk.Evolution, medicine, and public health · 2024Review
- A versatile, fast and unbiased method for estimation of gene-by-environment interaction effects on biobank-scale datasets.Nature communications · 2023Article
- A review on the application of the exposome paradigm to unveil the environmental determinants of age-related diseases.Human genomics · 2022Review
- Prevalence of overweight and obesity amongst patients with diabetes and their non-diabetic family members in Senwabarwana, Limpopo province, South Africa.South African family practice : official journal of the South African Academy of Family Practice/Primary Care · 2022Article
- Role of Epigenetics in Type 2 Diabetes and Obesity.Biomedicines · 2021Review
- [Dietary Patterns and Their Association with Diabetes Mellitus in Middle-Aged and Older Rural Population in Xinxiang County, Henan Province].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2021Article
- Comparisons of Polyexposure, Polygenic, and Clinical Risk Scores in Risk Prediction of Type 2 Diabetes.Diabetes care · 2021Article
- Transcriptional Profiling and Biological Pathway(s) Analysis of Type 2 Diabetes Mellitus in a Pakistani Population.International journal of environmental research and public health · 2020Article
- Chinese Medicine for Psoriasis Vulgaris Based on Syndrome Pattern: A Network Pharmacological Study.Evidence-based complementary and alternative medicine : eCAM · 2020Article
- Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases.Toxicology and applied pharmacology · 2019Article
- Reverse GWAS: Using genetics to identify and model phenotypic subtypes.PLoS genetics · 2019Article
- Influence of the Urban Exposome on Birth Weight.Environmental health perspectives · 2019Article
- Environmental Forces that Shape Early Development: What We Know and Still Need to Know.Current developments in nutrition · 2018Article
- Gene × Environment Interaction in Developmental Disorders: Where Do We Stand and What's Next?Frontiers in psychology · 2018Article
- Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases.American journal of epidemiology · 2017Article
- Opportunities and Challenges for Environmental Exposure Assessment in Population-Based Studies.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2017Review
8 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Diseases such as type 2 diabetes (T2D) result from environmental and genetic factors, and risk varies considerably in the population. T2D-related genetic loci discovered to date explain only a small portion of the T2D heritability. Some heritability may be due to gene-environment interactions. However, documenting these interactions has been difficult due to low availability of concurrent genetic and environmental measures, selection bias, and challenges in controlling for multiple hypothesis testing. Through genome-wide association studies (GWAS), investigators have identified over 90 single nucleotide polymorphisms (SNPs) associated to T2D. Using a method analogous to GWAS [environment-wide association study (EWAS)], we found five environmental factors associated with the disease. By focusing on risk factors that emerge from GWAS and EWAS, it is possible to overcome difficulties in uncovering gene-environment interactions. Using data from the National Health and Nutrition Examination Survey (NHANES), we screened 18 SNPs and 5 serum-based environmental factors for interaction in association to T2D. We controlled for multiple hypotheses using false discovery rate (FDR) and Bonferroni correction and found four interactions with FDR <20 %. The interaction between rs13266634 (SLC30A8) and trans-β-carotene withstood Bonferroni correction (corrected p = 0.006, FDR <1.5 %). The per-risk-allele effect sizes in subjects with low levels of trans-β-carotene were 40 % greater than the marginal effect size [odds ratio (OR) 1.8, 95 % CI 1.3-2.6]. We hypothesize that impaired function driven by rs13266634 increases T2D risk when combined with serum levels of nutrients. Unbiased consideration of environmental and genetic factors may help identify larger and more relevant effect sizes for disease associations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.