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Velazquez-Roman J, Angulo-Zamudio UA, Leon-Sicairos N, Flores-Villaseñor H, Benitez-Baez M, Espinoza-Salomón A, Karam-León A, Villamil-Ramírez H, Canizales-Quinteros S, Macías-Kauffer L, Monroy-Higuera J, Acosta-Smith E, Canizalez-Roman A. Association of PCSK1 and PPARG1 Allelic Variants with Obesity and Metabolic Syndrome in Mexican Adults. Genes (Basel) 2023; 14:1775. [PMID: 37761915 PMCID: PMC10531047 DOI: 10.3390/genes14091775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/06/2023] [Accepted: 09/07/2023] [Indexed: 09/29/2023] Open
Abstract
Metabolic diseases, including obesity, diabetes, and metabolic syndrome, are among the most important public health challenges worldwide. Metabolic diseases are classified as multifactorial diseases in which genetic variants such as single-nucleotide polymorphisms (SNPs) may play an important role. The present study aimed to identify associations linking allelic variants of the PCSK1, TMEM18, GPX5, ZPR1, ZBTB16, and PPARG1 genes with anthropometric and biochemical traits and metabolic diseases (obesity or metabolic syndrome) in an adult population from northwestern Mexico. METHODS Blood samples were collected from 523 subjects, including 247 with normal weight, 276 with obesity, and 147 with metabolic syndrome. Anthropometric and biochemical characteristics were recorded, and single-nucleotide polymorphisms (SNPs) were genotyped by real-time PCR. RESULTS PCSK1 was significantly (p < 0.05) associated with BMI, weight, and waist-to-hip ratio; TMEM18 was significantly associated with systolic blood pressure and triglyceride levels; GPX5 was significantly associated with HDL cholesterol levels. In addition, PCSK1 was associated with obesity (p = 1.0 × 10-4) and metabolic syndrome (p = 3.0 × 10-3), whereas PPARG1 was associated with obesity (p = 0.044). CONCLUSIONS The associations found in this study, mainly between allelic variants of PCSK1 and metabolic traits, obesity, and metabolic syndrome, may represent a risk for developing metabolic diseases in adult subjects from northwestern Mexico.
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Affiliation(s)
- Jorge Velazquez-Roman
- School of Medicine, Autonomous University of Sinaloa, Culiacan Sinaloa 80019, Mexico; (J.V.-R.); (U.A.A.-Z.); (N.L.-S.); (H.F.-V.); (A.E.-S.); (E.A.-S.)
| | - Uriel A. Angulo-Zamudio
- School of Medicine, Autonomous University of Sinaloa, Culiacan Sinaloa 80019, Mexico; (J.V.-R.); (U.A.A.-Z.); (N.L.-S.); (H.F.-V.); (A.E.-S.); (E.A.-S.)
| | - Nidia Leon-Sicairos
- School of Medicine, Autonomous University of Sinaloa, Culiacan Sinaloa 80019, Mexico; (J.V.-R.); (U.A.A.-Z.); (N.L.-S.); (H.F.-V.); (A.E.-S.); (E.A.-S.)
- Pediatric Hospital of Sinaloa, Constitución 530, Jorge Almada, Culiacan Sinaloa 80200, Mexico
| | - Hector Flores-Villaseñor
- School of Medicine, Autonomous University of Sinaloa, Culiacan Sinaloa 80019, Mexico; (J.V.-R.); (U.A.A.-Z.); (N.L.-S.); (H.F.-V.); (A.E.-S.); (E.A.-S.)
- The Sinaloa State Public Health Laboratory, Secretariat of Health, Culiacan Sinaloa 80020, Mexico
| | - Miriam Benitez-Baez
- Programa de Doctorado, Posgrado Integral en Biotecnología, FCQB, UAS, Culiacan Sinaloa 80013, Mexico; (M.B.-B.); (A.K.-L.); (J.M.-H.)
| | - Ana Espinoza-Salomón
- School of Medicine, Autonomous University of Sinaloa, Culiacan Sinaloa 80019, Mexico; (J.V.-R.); (U.A.A.-Z.); (N.L.-S.); (H.F.-V.); (A.E.-S.); (E.A.-S.)
| | - Alejandra Karam-León
- Programa de Doctorado, Posgrado Integral en Biotecnología, FCQB, UAS, Culiacan Sinaloa 80013, Mexico; (M.B.-B.); (A.K.-L.); (J.M.-H.)
| | - Hugo Villamil-Ramírez
- Unidad de Genómica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM/INMEGEN, Mexico City 04510, Mexico; (H.V.-R.); (S.C.-Q.); (L.M.-K.)
| | - Samuel Canizales-Quinteros
- Unidad de Genómica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM/INMEGEN, Mexico City 04510, Mexico; (H.V.-R.); (S.C.-Q.); (L.M.-K.)
| | - Luis Macías-Kauffer
- Unidad de Genómica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM/INMEGEN, Mexico City 04510, Mexico; (H.V.-R.); (S.C.-Q.); (L.M.-K.)
| | - Jose Monroy-Higuera
- Programa de Doctorado, Posgrado Integral en Biotecnología, FCQB, UAS, Culiacan Sinaloa 80013, Mexico; (M.B.-B.); (A.K.-L.); (J.M.-H.)
| | - Erika Acosta-Smith
- School of Medicine, Autonomous University of Sinaloa, Culiacan Sinaloa 80019, Mexico; (J.V.-R.); (U.A.A.-Z.); (N.L.-S.); (H.F.-V.); (A.E.-S.); (E.A.-S.)
| | - Adrian Canizalez-Roman
- School of Medicine, Autonomous University of Sinaloa, Culiacan Sinaloa 80019, Mexico; (J.V.-R.); (U.A.A.-Z.); (N.L.-S.); (H.F.-V.); (A.E.-S.); (E.A.-S.)
- The Women’s Hospital, Secretariat of Health, Culiacan Sinaloa 80020, Mexico
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Rana S, Sultana A, Bhatti AA. Effect of interaction between obesity-promoting genetic variants and behavioral factors on the risk of obese phenotypes. Mol Genet Genomics 2021; 296:919-938. [PMID: 33966103 DOI: 10.1007/s00438-021-01793-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 04/22/2021] [Indexed: 01/28/2023]
Abstract
The studies investigating gene-gene and gene-environment (or gene-behavior) interactions provide valuable insight into the pathomechanisms underlying obese phenotypes. The Pakistani population due to its unique characteristics offers numerous advantages for conducting such studies. In this view, the current study was undertaken to examine the effects of gene-gene and gene-environment/behavior interactions on the risk of obesity in a sample of Pakistani population. A total of 578 adult participants including 290 overweight/obese cases and 288 normal-weight controls were involved. The five key obesity-associated genetic variants namely MC4R rs17782313, BDNF rs6265, FTO rs1421085, TMEM18 rs7561317, and NEGR1 rs2815752 were genotyped using the TaqMan allelic discrimination assays. The data related to behavioral factors, such as eating pattern, diet consciousness, the tendency toward fat-dense food (TFDF), sleep duration, sleep-wake cycle (SWC), shift work (SW), and physical activity levels were collected via a questionnaire. Gene-gene and gene-behavior interactions were analyzed by multifactor dimensionality reduction and linear regression, respectively. In our study, only TMEM18 rs7561317 was found to be significantly associated with anthropometric traits with no significant effect of gene-gene interactions were observed on obesity-related phenotypes. However, the genetic variants were found to interact with the behavioral factors to significantly influence various obesity-related anthropometric traits including BMI, waist circumference, hip circumference, waist-to-hip ratio, waist-to-height ratio, and percentage of body fat. In conclusion, the interaction between genetic architecture and behavior/environment determines the outcome of obesity-related anthropometric phenotypes. Thus, gene-environment/behavior interaction studies should be promoted to explore the risk of complex and multifactorial disorders, such as obesity.
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Affiliation(s)
- Sobia Rana
- Molecular Biology and Human Genetics Laboratory, Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, 75270, Pakistan.
| | - Ayesha Sultana
- Molecular Biology and Human Genetics Laboratory, Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, 75270, Pakistan
| | - Adil Anwar Bhatti
- Molecular Biology and Human Genetics Laboratory, Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, 75270, Pakistan
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Trifonova EA, Popovich AA, Makeeva OA, Minaycheva LI, Bocharova AV, Vagaitseva KV, Stepanov VA. Replicative Association Analysis of Genetic Markers of Obesity in the Russian Population. RUSS J GENET+ 2021. [DOI: 10.1134/s1022795421050136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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Rana S, Bhatti AA. Predicting anthropometric and metabolic traits with a genetic risk score for obesity in a sample of Pakistanis. Sci Rep 2021; 11:8320. [PMID: 33859285 PMCID: PMC8050295 DOI: 10.1038/s41598-021-87702-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 04/01/2021] [Indexed: 12/18/2022] Open
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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Affiliation(s)
- Sobia Rana
- Molecular Biology and Human Genetics Laboratory, Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, 75270, Pakistan.
| | - Adil Anwar Bhatti
- Molecular Biology and Human Genetics Laboratory, Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, 75270, Pakistan
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