Observational studyLipids in health and disease2018
Use of a gene score of multiple low-modest effect size variants can predict the risk of obesity better than the individual SNPs.
Observational study in Lipids in health and disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Single nucleotide polymorphisms (SNPs) that are associated with obesity and type 2 diabetes among Asians: a systematic review and meta-analysis.Scientific reports · 2024Pooled it
- Immunogenetic Aspects of Sarcopenic Obesity.Genes · 2024Review
- Genetic studies in the Pakistani population reveal novel associations with ventricular septal defects (VSDs).BMC pediatrics · 2023Article
- TTLL11 gene is associated with sustained attention performance and brain networks: A genome-wide association study of a healthy Chinese sample.Genes, brain, and behavior · 2023Article
- Greater social adversity is associated with more disordered eating attitudes and behaviors among children from Southeast Michigan.The International journal of eating disorders · 2022Article
- The Antarctic Weddell seal genome reveals evidence of selection on cardiovascular phenotype and lipid handling.Communications biology · 2022Article
- Favourable Lifestyle Protects Cognitive Function in Older Adults With High Genetic Risk of Obesity: A Prospective Cohort Study.Frontiers in molecular neuroscience · 2022Article
- Genetics of Cardiovascular Disease: How Far Are We from Personalized CVD Risk Prediction and Management?International journal of molecular sciences · 2021Review
- Predicting anthropometric and metabolic traits with a genetic risk score for obesity in a sample of Pakistanis.Scientific reports · 2021Article
- Antioxidants-Related Superoxide Dismutase (Antioxidants (Basel, Switzerland) · 2021Article
- Performing post-genome-wide association study analysis: overview, challenges and recommendations.F1000Research · 2021Article
- Pro-inflammatory cytokine polymorphisms in ONECUT2 and HNF4A and primary colorectal carcinoma: a post genome-wide gene-lifestyle interaction study.American journal of cancer research · 2020Article
- ESI Clinical Practice Guidelines for the Evaluation and Management of Obesity In India.Indian journal of endocrinology and metabolismArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundObesity is a complex disorder, the development of which is modulated by a multitude of environmental, behavioral and genetic factors. The common forms of obesity are polygenic in nature which means that many variants in the same or different genes act synergistically and affect the body weight quantitatively. The aim of the current study was to use information from many common variants previously identified to affect body weight to construct a gene score and observe whether it improves the associations observed. The SNPs selected were G2548A in leptin (LEP) gene, Gln223Arg in leptin receptor (LEPR) gene, Ala54Thr in fatty acid binding protein 2 (FABP2) gene, rs1121980 in fat mass and obesity associated (FTO) gene, rs3923113 in Growth Factor Receptor Bound Protein 14 (GRB14), rs16861329 in Beta-galactoside alpha-2,6-sialyltransferase 1 (ST6GAL1), rs1802295 in Vacuolar protein sorting-associated protein 26A (VPS26A), rs7178572 in high mobility group 20A (HMG20A), rs2028299 in adaptor-related protein complex 3 (AP3S2), and rs4812829 in Hepatocyte Nuclear Factor 4 Alpha (HNF4A).
methodsA total of 475 subjects were genotyped for the selected SNPs in different genes using different genotyping techniques. The study subjects' age, weight, height, BMI, waist and hip circumference, serum total cholesterol, triglycerides, LDL and HDL were measured. A summation term, genetic risk score (GRS), was calculated using SPSS.
resultsThe results showed a significantly higher mean gene score in obese cases than in non-obese controls (9.1 ± 2.26 vs 8.35 ± 2.07, p = 2 × 10
conclusionIn conclusion, the use of gene score is a better way to calculate the overall genetic risk from common variants rather than individual risk variants.
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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.