Use of a gene score of multiple low-modest effect size variants can predict the risk of obesity better than the individual SNPs
Abstract Background Obesity 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 t...
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| Format: | Article |
| Language: | English |
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BMC
2018-07-01
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| Series: | Lipids in Health and Disease |
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| Online Access: | http://link.springer.com/article/10.1186/s12944-018-0806-5 |
| _version_ | 1811196060293398528 |
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| author | Shabana Saleem Ullah Shahid Shahida Hasnain |
| author_facet | Shabana Saleem Ullah Shahid Shahida Hasnain |
| author_sort | Shabana |
| collection | DOAJ |
| description | Abstract Background Obesity 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). Methods A 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. Results The 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− 4). Among the traits tested for association, gene score appeared to significantly affect BMI, waist circumference, and all lipid traits. Conclusion In conclusion, the use of gene score is a better way to calculate the overall genetic risk from common variants rather than individual risk variants. |
| first_indexed | 2024-04-12T00:53:33Z |
| format | Article |
| id | doaj.art-4ce655dd8aa1408387af442ed176dbe7 |
| institution | Directory Open Access Journal |
| issn | 1476-511X |
| language | English |
| last_indexed | 2024-04-12T00:53:33Z |
| publishDate | 2018-07-01 |
| publisher | BMC |
| record_format | Article |
| series | Lipids in Health and Disease |
| spelling | doaj.art-4ce655dd8aa1408387af442ed176dbe72022-12-22T03:54:41ZengBMCLipids in Health and Disease1476-511X2018-07-011711910.1186/s12944-018-0806-5Use of a gene score of multiple low-modest effect size variants can predict the risk of obesity better than the individual SNPsShabana0Saleem Ullah Shahid1Shahida Hasnain2Department of Microbiology and Molecular Genetics, University of the PunjabDepartment of Microbiology and Molecular Genetics, University of the PunjabDepartment of Microbiology and Molecular Genetics, University of the PunjabAbstract Background Obesity 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). Methods A 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. Results The 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− 4). Among the traits tested for association, gene score appeared to significantly affect BMI, waist circumference, and all lipid traits. Conclusion In conclusion, the use of gene score is a better way to calculate the overall genetic risk from common variants rather than individual risk variants.http://link.springer.com/article/10.1186/s12944-018-0806-5ObesityGene scorePolygenicRisk variant |
| spellingShingle | Shabana Saleem Ullah Shahid Shahida Hasnain Use of a gene score of multiple low-modest effect size variants can predict the risk of obesity better than the individual SNPs Lipids in Health and Disease Obesity Gene score Polygenic Risk variant |
| title | Use of a gene score of multiple low-modest effect size variants can predict the risk of obesity better than the individual SNPs |
| title_full | Use of a gene score of multiple low-modest effect size variants can predict the risk of obesity better than the individual SNPs |
| title_fullStr | Use of a gene score of multiple low-modest effect size variants can predict the risk of obesity better than the individual SNPs |
| title_full_unstemmed | Use of a gene score of multiple low-modest effect size variants can predict the risk of obesity better than the individual SNPs |
| title_short | Use of a gene score of multiple low-modest effect size variants can predict the risk of obesity better than the individual SNPs |
| title_sort | use of a gene score of multiple low modest effect size variants can predict the risk of obesity better than the individual snps |
| topic | Obesity Gene score Polygenic Risk variant |
| url | http://link.springer.com/article/10.1186/s12944-018-0806-5 |
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