| Title |
Evidence for substantial effect modification by gender in a large-scale genetic association study of the metabolic syndrome among coronary heart disease patients
|
|---|---|
| Published in |
Human Genetics, October 2003
|
| DOI | 10.1007/s00439-003-1026-1 |
| Pubmed ID | |
| Authors |
Jeanette J. McCarthy, Joanne Meyer, David J. Moliterno, L. Kristin Newby, William J. Rogers, Eric J. Topol |
| Abstract |
Major genetic determinants of the metabolic syndrome - a clustering of abdominal obesity, high triglycerides, low HDL cholesterol, high blood pressure and high fasting glucose - remain elusive. We surveyed 207 single-nucleotide polymorphisms in 110 candidate genes among coronary artery disease patients, a population enriched for metabolic abnormalities. The number of abnormalities (0-5) was determined in the 214 male and 91 female patients, and the association with each polymorphism evaluated by means of ordinal regression analysis. Polymorphisms in eight genes, including LDLR, GBE1, IL1R1, TGFB1, IL6, COL5A2, SELE and LIPC, were associated with metabolic syndrome in the whole population ( P values ranged from 0.047 to 0.008). Variants in seven additional genes showed significant gene by gender interaction. Among these, separate analyses in men and women revealed a strong association with a silent polymorphism in the low-density lipoprotein receptor-related protein gene, LRPAP1, among females ( P=0.0003), but not males ( P=0.292). Other genes associated only in females included THBS1, ACAT2, ITGB3, F2 and SELP ( P values ranging from 0.032 to 0.002). Only one gene ( PRCP) was significantly associated in men alone ( P=0.039). Our results propose several new candidate genes for the metabolic syndrome and suggest that the genetic basis of this syndrome may be strongly modified by gender. |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| New Zealand | 1 | 3% |
| India | 1 | 3% |
| Unknown | 35 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 22% |
| Student > Bachelor | 5 | 14% |
| Student > Ph. D. Student | 4 | 11% |
| Student > Doctoral Student | 3 | 8% |
| Student > Postgraduate | 3 | 8% |
| Other | 6 | 16% |
| Unknown | 8 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 24% |
| Biochemistry, Genetics and Molecular Biology | 7 | 19% |
| Medicine and Dentistry | 6 | 16% |
| Psychology | 2 | 5% |
| Nursing and Health Professions | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 9 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 March 2017.
All research outputs
#8,535,684
of 25,374,917 outputs
Outputs from Human Genetics
#1,014
of 2,957 outputs
Outputs of similar age
#19,954
of 56,921 outputs
Outputs of similar age from Human Genetics
#7
of 19 outputs
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