Genome-wide linkage scan to identify loci associated with type 2 diabetes and blood lipid phenotypes in the Sikh Diabetes Study.
In this investigation, we have carried out an autosomal genome-wide linkage analysis to map genes associated with type 2 diabetes (T2D) and five quantitative traits of blood lipids including total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, ver...
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doaj-0b30c41060f7488688aaf1e7fe4eee1b2020-11-25T00:47:05ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-01-0166e2118810.1371/journal.pone.0021188Genome-wide linkage scan to identify loci associated with type 2 diabetes and blood lipid phenotypes in the Sikh Diabetes Study.Dharambir K SangheraLatonya F BeenSarju RalhanGurpreet S WanderNarinder K MehraJai Rup SinghRobert E FerrellMohammed I KambohChristopher E AstonIn this investigation, we have carried out an autosomal genome-wide linkage analysis to map genes associated with type 2 diabetes (T2D) and five quantitative traits of blood lipids including total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, very low-density lipoprotein (VLDL) cholesterol, and triglycerides in a unique family-based cohort from the Sikh Diabetes Study (SDS). A total of 870 individuals (526 male/344 female) from 321 families were successfully genotyped using 398 polymorphic microsatellite markers with an average spacing of 9.26 cM on the autosomes. Results of non-parametric multipoint linkage analysis using S(all) statistics (implemented in Merlin) did not reveal any chromosomal region to be significantly associated with T2D in this Sikh cohort. However, linkage analysis for lipid traits using QTL-ALL analysis revealed promising linkage signals with p≤0.005 for total cholesterol, LDL cholesterol, and HDL cholesterol at chromosomes 5p15, 9q21, 10p11, 10q21, and 22q13. The most significant signal (p = 0.0011) occurred at 10q21.2 for HDL cholesterol. We also observed linkage signals for total cholesterol at 22q13.32 (p = 0.0016) and 5p15.33 (p = 0.0031) and for LDL cholesterol at 10p11.23 (p = 0.0045). Interestingly, some of linkage regions identified in this Sikh population coincide with plausible candidate genes reported in recent genome-wide association and meta-analysis studies for lipid traits. Our study provides the first evidence of linkage for loci associated with quantitative lipid traits at four chromosomal regions in this Asian Indian population from Punjab. More detailed examination of these regions with more informative genotyping, sequencing, and functional studies should lead to rapid detection of novel targets of therapeutic importance.http://europepmc.org/articles/PMC3116872?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Dharambir K Sanghera Latonya F Been Sarju Ralhan Gurpreet S Wander Narinder K Mehra Jai Rup Singh Robert E Ferrell Mohammed I Kamboh Christopher E Aston |
spellingShingle |
Dharambir K Sanghera Latonya F Been Sarju Ralhan Gurpreet S Wander Narinder K Mehra Jai Rup Singh Robert E Ferrell Mohammed I Kamboh Christopher E Aston Genome-wide linkage scan to identify loci associated with type 2 diabetes and blood lipid phenotypes in the Sikh Diabetes Study. PLoS ONE |
author_facet |
Dharambir K Sanghera Latonya F Been Sarju Ralhan Gurpreet S Wander Narinder K Mehra Jai Rup Singh Robert E Ferrell Mohammed I Kamboh Christopher E Aston |
author_sort |
Dharambir K Sanghera |
title |
Genome-wide linkage scan to identify loci associated with type 2 diabetes and blood lipid phenotypes in the Sikh Diabetes Study. |
title_short |
Genome-wide linkage scan to identify loci associated with type 2 diabetes and blood lipid phenotypes in the Sikh Diabetes Study. |
title_full |
Genome-wide linkage scan to identify loci associated with type 2 diabetes and blood lipid phenotypes in the Sikh Diabetes Study. |
title_fullStr |
Genome-wide linkage scan to identify loci associated with type 2 diabetes and blood lipid phenotypes in the Sikh Diabetes Study. |
title_full_unstemmed |
Genome-wide linkage scan to identify loci associated with type 2 diabetes and blood lipid phenotypes in the Sikh Diabetes Study. |
title_sort |
genome-wide linkage scan to identify loci associated with type 2 diabetes and blood lipid phenotypes in the sikh diabetes study. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2011-01-01 |
description |
In this investigation, we have carried out an autosomal genome-wide linkage analysis to map genes associated with type 2 diabetes (T2D) and five quantitative traits of blood lipids including total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, very low-density lipoprotein (VLDL) cholesterol, and triglycerides in a unique family-based cohort from the Sikh Diabetes Study (SDS). A total of 870 individuals (526 male/344 female) from 321 families were successfully genotyped using 398 polymorphic microsatellite markers with an average spacing of 9.26 cM on the autosomes. Results of non-parametric multipoint linkage analysis using S(all) statistics (implemented in Merlin) did not reveal any chromosomal region to be significantly associated with T2D in this Sikh cohort. However, linkage analysis for lipid traits using QTL-ALL analysis revealed promising linkage signals with p≤0.005 for total cholesterol, LDL cholesterol, and HDL cholesterol at chromosomes 5p15, 9q21, 10p11, 10q21, and 22q13. The most significant signal (p = 0.0011) occurred at 10q21.2 for HDL cholesterol. We also observed linkage signals for total cholesterol at 22q13.32 (p = 0.0016) and 5p15.33 (p = 0.0031) and for LDL cholesterol at 10p11.23 (p = 0.0045). Interestingly, some of linkage regions identified in this Sikh population coincide with plausible candidate genes reported in recent genome-wide association and meta-analysis studies for lipid traits. Our study provides the first evidence of linkage for loci associated with quantitative lipid traits at four chromosomal regions in this Asian Indian population from Punjab. More detailed examination of these regions with more informative genotyping, sequencing, and functional studies should lead to rapid detection of novel targets of therapeutic importance. |
url |
http://europepmc.org/articles/PMC3116872?pdf=render |
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