ArticleScientific reports2021
Predicting anthropometric and metabolic traits with a genetic risk score for obesity in a sample of Pakistanis.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Functional Annotation of GWAS Loci Using Public Transcriptome and Epigenome Datasets Reveals Non-Coding Genes and Regulatory Elements Which May Contribute to BMI.International journal of molecular sciences · 2026Article
- Association between Chinese visceral adiposity index and arterial stiffness among hospital workers in a Chinese tertiary hospital.Diabetology & metabolic syndrome · 2025Article
- Exploring the impact of genetic factors and fatty acid quality on visceral and overall Fat levels in overweight and obese women: a genetic risk score study.BMC nutrition · 2025Article
- Bridging east and west: integrative approaches to obesity management through traditional Chinese medicine.Frontiers in endocrinology · 2025Review
- Deciphering the Interplay between Genetic Risk Scores and Lifestyle Factors on Individual Obesity Predisposition.Nutrients · 2024Article
- Associations of Chinese visceral adiposity index and new-onset stroke in middle-aged and older Chinese adults: an observational study.Lipids in health and disease · 2023Observational
- The relationship of genetic risk score with cardiometabolic risk factors: a cross-sectional study.BMC cardiovascular disorders · 2022Article
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2 authors.
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Abstract
Obesity is an outcome of multiple factors including environmental and genetic influences. Common obesity is a polygenic trait indicating that multiple genetic variants act synergistically to influence its expression. We constructed a genetic risk score (GRS) based on five genetic variants (MC4R rs17782313, BDNF rs6265, FTO rs1421085, TMEM18 rs7561317, and NEGR1 rs2815752) and examined its association with obesity-related traits in a sample of Pakistanis. The study involved 306 overweight/obese (OW/OB) and 300 normal-weight (NW) individuals. The age range of the study participants was 12-63 years. All anthropometric and metabolic parameters were measured for each participant via standard procedures and biochemical assays, respectively. The genetic variants were genotyped by allelic discrimination assays. The age- and gender-adjusted associations between the GRS and obesity-related anthropometric and metabolic measures were determined using linear regression analyses. The results showed that OW/OB individuals had significantly higher mean ranks of GRS than NW individuals. Moreover, a significant association of the GRS with obesity-related anthropometric traits was seen. However, the GRS did not appear to affect any obesity-related metabolic parameter. In conclusion, our findings indicate the combined effect of multiple genetic variants on the obesity-related anthropometric phenotypes in Pakistanis.
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