Egyptian Journal of Medical Human Genetics (Feb 2022)

Association of CAPN10 haplotype combinations with type 2 diabetes mellitus and metabolic syndrome among Egyptians: pilot study—genotyping of three CAPN10 variants

  • Shaymaa W. El-Far,
  • Heba Sh. Kassem,
  • Amira M. Embaby,
  • Abir A. Saad,
  • Nader Mowafy,
  • Medhat Haroun

DOI
https://doi.org/10.1186/s43042-022-00212-0
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 7

Abstract

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Abstract Background T2DM is a polygenic, metabolic complex and multifactorial disease. Several genes contribute to risk of type 2 diabetes and metabolic syndrome among different populations. Results An relationship between three identified CAPN-10 variants [SNP-43 (rs#3792267), SNP-19 (rs#3842570) and SNP-63 (rs#5030952)] localized on 2q37 and type 2 diabetic patients with and without metabolic syndrome (MS) have been reported in our comparative study (diabetic vs health control individuals). Genotyping of study cohorts was carried out using restriction fragment length polymorphism (RFLP-PCR). Statistical analysis of data reveals that the haplotype combination 111/112 confers a significant risk for type 2 diabetes mellitus (T2DM). Patients with the homozygous haplotype combination of 122/122 are less susceptible to MS when compared to other patients carrying other haplotype combinations. Regarding obesity, a core component in MS, the haplotype combinations 111/121 and 122/122 demonstrate a significant protective role. Furthermore, the haplotype combination 111/111 displays a significant risk for high levels of total cholesterol. Conclusion Present findings address that these haplotype combinations 111/112, 111/121 and 122/122 of CAPN-10 SNP-43, -19 and -63 constitute unique DNA biomarker fingerprints toward susceptibility and risk for T2DM and MS among Egyptians when compared to other haplotype combinations reported in other populations of different ethnicity. To enhance the power of human evolution control nowadays, mutations and polymorphisms in target genes associated with human diseases should be well understood.

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