Analyzing of multivariate two levels Haseman-Elston regression and its application in genetic linkage of HDL-C, triglycerides and waist in 91 Iranian families with metabolic syndrome

  Introduction: Metabolic syndrome is a complex trait and its prevalence is 32% in Iranian population. The present study was conducted to find chromosomal area locus of HDL-C, triglycerides and waist with microsatellites and multivariate two level Haseman-Elston regressions in Iranian families with metabolic syndrome.   Materials and Methods: 91 Iranian families (493 people) with at least one member with metabolic syndrome were selected from database of TLGS. We performed the Fragment Analysis technique to reproduce 12 different pieces from 4 chromosomal areas and to identify loci related to metabolic syndrome both single and multi variable two level Haseman-Elston regression methods were used for traits of triglycerides, high-density lipoprotein and waist. We performed three single variable models, three double variable models and one triple variable model of these traits.   Results: 91 Iranian familes included 493 people, 234 males and 259 females. In single variable models: genetic linkage of HDL-C was significant with D11S1998 marker genetic linkage of triglycerides was significant with D11S1934 and D12S1632 markers. In double variable models genetic linkage of HDL-C and triglyceride, HDL-C and waist was significant with D11S1998 marker and the genetic linkage of HDL-C and triglyceride, triglyceride and waist was significant with D8S1743 and D11S934 marker. In triple variable model genetic linkage of HDL-C, triglyceride and waist was significant with D8S1743 marker.   Conclusion: These results showed when a trait is common in different models the linked markers of them are also common. We concluded that the multivariate methods can detect linked loci of mixed disease better than single variable models and these results are useful for more future studies in Iranian population.