Genetic Susceptibility to Metabolic Syndrome: A Comparative Overview of the Mexican Population in a Global Context

Main Article Content

Carlos Arturo Gallardo Hernández https://orcid.org/0000-0002-4077-9763
Jaqueline Diaz Alberto https://orcid.org/0009-0007-8606-9971
José Antonio Palma Jacinto https://orcid.org/0000-0001-6587-9712
Oreth Montero Ruíz https://orcid.org/0000-0002-2724-5169
Ulises Ramírez Franco https://orcid.org/0009-0001-1301-364X

Keywords

Metabolic Syndrome, Genetic Susceptibility, Genes, Polymorphism, Single Nucleotide, Single Nucleotide Polymorphism

Abstract

Abstract


Metabolic syndrome (MetS) is a multifactorial condition involving environmental factors, lifestyle behaviors, and genetic variants. The objective of this review was to analyze and compare the available evidence on genetic susceptibility to MetS in the Mexican population and in other regions of the world, in order to identify convergences and population-specific features. A narrative review of the scientific literature published between 2020 and 2025 was conducted using international databases. The methodological quality and scientific relevance of the studies were assessed using criteria adapted from the Q-Genie instrument. The results show that genetic variants involved in glucose and lipid metabolism, as well as in blood pressure regulation, are associated with MetS across diverse populations. However, relevant differences were identified in the frequency and phenotypic effects of these variants between the Mexican population and other regions worldwide. In conclusion, the evidence suggests that genetic susceptibility to MetS exhibits a population-specific component in Mexico. In this context, further investigation of genetic variants associated with MetS is warranted to contribute to the strengthening of preventive strategies aimed at reducing the burden of MetS in the Mexican population.

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References

1. Islam MS, Wei P, Suzauddula M, et al. The interplay of factors in metabolic syndrome: understanding its roots and complexity. Mol Med. 2024;30:279. doi:10.1186/s10020-024-01019-y

2. Christian-Flemming GM, Bussler S, Körner A, et al. Definition and early diagnosis of metabolic syndrome in children. J Pediatr Endocrinol Metab. 2020;33(7):821–833. doi:10.1515/jpem-2019-0552

3. Alberti KGMM, Eckel RH, Grundy SM, et al. Harmonizing the metabolic syndrome: a joint interim statement of the IDF, AHA, NHLBI, and other organizations. Circulation. 2009;120(16):1640–1645.

4. Noubiap JJ, Nansseu JR, Lontchi-Yimagou E, et al. Geographic distribution of metabolic syndrome and its components in the general adult population: a meta-analysis of global data from 28 million individuals. Diabetes Res Clin Pract. 2022;188:109924.

5. Rojas-Martínez R, Aguilar-Salinas CA, Romero-Martínez M, et al. Trends in the prevalence of metabolic syndrome and its components in Mexican adults, 2006–2018. Salud Publica Mex. 2021;63(6):713–724.

6. Instituto Nacional de Salud Pública. Encuesta Nacional de Salud y Nutrición 2022. Resultados nacionales. Cuernavaca, México: INSP; 2023.

7. Föhr T, Hendrix A, Kankaanpää A, et al. Metabolic syndrome and epigenetic aging: a twin study. Int J Obes. 2024;48(6):778–787. doi:10.1038/s41366-024-01466-x

8. Sohani ZN, Meyre D, de Souza RJ, et al. Assessing the quality of published genetic association studies in meta-analyses: the Q-Genie tool. BMC Genet. 2015;16:50. doi:10.1186/s12863-015-0211-2

9. Piché ME, Tchernof A, Després JP. Obesity phenotypes, diabetes, and cardiovascular diseases. Circ Res. 2020;126(11):1477–1500. doi:10.1161/CIRCRESAHA.120.316101

10. Peterseim CM, Jabbour K, Kamath Mulki A. Metabolic syndrome: an updated review on diagnosis and treatment for primary care clinicians. J Prim Care Community Health. 2024;15:21501319241309168.

11. Bovolini A, Garcia J, Andrade MA, et al. Metabolic syndrome pathophysiology and predisposing factors. Int J Sports Med. 2021;42(3):199–214.

12. Masenga SK, Kabwe LS, Chakulya M, et al. Mechanisms of oxidative stress in metabolic syndrome. Int J Mol Sci. 2023;24(9):7898. doi:10.3390/ijms24097898

13. Patil BS, Patil JK, Chaudhari HS, et al. Oxidative stress, inflammation, and obesity: insights into mechanism and therapeutic targets. Proc. 2025;119(1):6. doi:10.3390/proceedings2025119006

14. Mahmoud R, Kimonis V, Butler MG. Genetics of obesity in humans: a clinical review. Int J Mol Sci. 2022;23(19):11005. doi:10.3390/ijms231911005

15. Cruz M, Berumen J. La genómica del mexicano en las enfermedades metabólicas. Gac Med Mex. 2025;161(1):1–6. doi:10.24875/gmm.24000433

16. Clément K, van den Akker E, Argente J, et al. Efficacy and safety of setmelanotide, an MC4R agonist, in individuals with severe obesity due to LEPR or POMC deficiency: single-arm, open-label, multicentre, phase 3 trials. Lancet Diabetes Endocrinol. 2020;8:960–970. doi:10.1016/S2213-8587(20)30364-8

17. Obradovic M, Sudar-Milovanovic E, Soskic S, et al. Leptin and obesity: role and clinical implication. Front Endocrinol. 2021;12:585887. doi:10.3389/fendo.2021.585887

18. Yupanqui-Lozno H, Bastarrachea RA, Yupanqui-Velazco ME, et al. Congenital leptin deficiency and leptin gene missense mutation found in two Colombian sisters with severe obesity. Genes. 2019;10(5):342. doi:10.3390/genes10050342

19. Hilado MA, Randhawa RS. A novel mutation in the proopiomelanocortin (POMC) gene of a Hispanic child: metformin treatment shows a beneficial impact on body mass index. J Pediatr Endocrinol Metab. 2018;31(8):815–819. doi:10.1515/jpem-2018-0105

20. Moreno-Godínez ME, Galarce-Sosa C, Cahua-Pablo JÁ, et al. Genotypes of common polymorphisms in the PON1 gene associated with paraoxonase activity as cardiovascular risk factor. Arch Med Res. 2018;49(7):486–496. doi:10.1016/j.arcmed.2019.02.002

21. Grzegorzewska AE, Adamska P, Iwańczyk-Skalska E, et al. Paraoxonase 1 concerning dyslipidaemia, cardiovascular diseases, and mortality in haemodialysis patients. Sci Rep. 2021;11(1):6773. doi:10.1038/s41598-021-86231-0

22. Gómez F. Comportamiento epidemiológico de las dislipidemias en pacientes del Instituto de Investigaciones Endocrino-Metabólicas. Rev Lat Hip. 2019.

23. Al Ghorani H, Götzinger F, Böhm M, et al. Arterial hypertension: clinical trials update 2021. Nutr Metab Cardiovasc Dis. 2022;32(1):21–31. doi:10.1016/j.numecd.2021.09.007

24. Abdel-Ghafar MT. An overview of the classical and tissue-derived renin–angiotensin–aldosterone system and its genetic polymorphisms in essential hypertension. Steroids. 2020;163:108701. doi:10.1016/j.steroids.2020.108701

25. Isordia-Salas I, Santiago-Germán D, Flores-Arizmendi A, et al. Polymorphisms in the renin–angiotensin system and eNOS Glu298Asp genes are associated with increased risk for essential hypertension in a Mexican population. J Renin Angiotensin Aldosterone Syst. 2023:4944238. doi:10.1155/2023/4944238

26. Del Bosque-Plata L, Martínez-Martínez E, Espinoza-Camacho MÁ, et al. The role of TCF7L2 in type 2 diabetes. Diabetes. 2021;70(6):1220–1228. doi:10.2337/db20-0573

27. Hashemian L, Sarhangi N, Afshari M, et al. The role of the PPARG (Pro12Ala) common genetic variant on type 2 diabetes mellitus risk. J Diabetes Metab Disord. 2021;20(2):1385–1390. doi:10.1007/s40200-021-00872-6

28. Ba T, Ren Q, Gong S, et al. Phenotypic features, prevalence of KCNJ11-MODY in Chinese patients with early-onset diabetes and a literature review. Clin Endocrinol. 2024;101(5):466–474. doi:10.1111/cen.15126

29. Kind L, Molnes J, Tjora E, et al. Molecular mechanism of HNF-1A-mediated HNF4A gene regulation and promoter-driven HNF4A-MODY diabetes. JCI Insight. 2024;9(11):e175278. doi:10.1172/jci.insight.175278

30. Mendoza-Caamal EC, Barajas-Olmos F, García-Ortiz H, et al. Metabolic syndrome in indigenous communities in Mexico: a descriptive and cross-sectional study. BMC Public Health. 2020;20(1):339. doi:10.1186/s12889-020-8378-5

31. Jurado-Camacho PA, Cid-Soto MA, Barajas-Olmos F, et al. Exome sequencing data analysis and a case-control study in Mexican population reveals lipid trait associations of new and known genetic variants in dyslipidemia-associated loci. Front Genet. 2022;13:807381. doi:10.3389/fgene.2022.807381

32. León-Reyes G, Rivera-Paredez B, López JCF, et al. The variant rs1784042 of the SIDT2 gene is associated with metabolic syndrome through low HDL-c levels in a Mexican population. Genes. 2020;11(10):1192. doi:10.3390/genes11101192

33. Peña-Espinoza BI, Torre-Horta E, Ortiz-López MG, et al. ABCA1 variant rs9282541 is associated with metabolic syndrome in Maya children. Ann Hum Genet. 2024;88(4):279–286.

34. Peña-Espinoza B, Juárez-López C, Ortiz-López G, et al. High frequency of metabolic syndrome in non-obese Maya children from Mexico: implications of PPARG, KCNJ11, HHEX, HNF4A, ACE (I/D), FTO and ABCA1 genetic variants. Gac Med Mex. 2025;161(1):110–118.

35. González-Sánchez GD, Martínez-Pérez LA, Pérez-Reyes Á, et al. Prevalence of the genetic variant rs61330082 and serum levels of the visfatin gene in Mexican individuals with metabolic syndrome. Nutr Hosp. 2024;41(6):1194–1201.

36. Velázquez-Román J, Angulo-Zamudio UA, León-Sicairos N, et al. Association of PCSK1 and PPARG1 allelic variants with obesity and metabolic syndrome in Mexican adults. Genes (Basel). 2023;14(9):1775.

37. Nag A, Dhindsa RS, Mitchell J, et al. Human genetics uncovers MAP3K15 as an obesity-independent therapeutic target for diabetes. Sci Adv. 2022;8(46):eadd5430. doi:10.1126/sciadv.add5430

38. Nermeen N, Tina S, Anica K, et al. Deletion of the type 2 diabetes candidate gene SLC16A11 reduces peripheral insulin sensitivity in mice. Diabetes. 2023;72(Suppl 1):191-OR. doi:10.2337/db23-191-OR