Phenotypic, genetic, and genome-wide structure in the metabolic syndrome
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Background: Insulin resistance, obesity, dyslipidemia, and high blood pressure characterize the metabolic syndrome. In an effort to explore the utility of different multivariate methods of data reduction to better understand the genetic influences on the aggregation of metabolic syndrome phenotypes, we calculated phenotypic, genetic, and genome-wide LOD score correlation matrices using five traits (total cholesterol, high density lipoprotein cholesterol, triglycerides, systolic blood pressure, and body mass index) from the Framingham Heart Study data set prepared for the Genetic Analysis Workshop 13, clinic visits 10 and 1 for the original and offspring cohorts, respectively. We next applied factor analysis to summarize the relationship between these phenotypes. Results: Factors generated from the genetic correlation matrix explained the most variation. Factors extracted using the other matrices followed a different pattern and suggest distinct effects. Conclusions: Given these results, different methods of multivariate data reduction may provide unique clues on the clustering of this complex syndrome.
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Considerable individual and ethnic variation exists in the clinical pattern of metabolic risk factors among obese or insulin-resistant subjects.
“Finally, considerable individual and ethnic variation exists in the clinical pattern of metabolic risk factors in obese/ insulin-resistant subjects.53,54”
From Diagnosis and Management of the Metabolic Syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement (2005) · cites this paper as [54]
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References 15 · Cited by 31
- Authors
- Martin, L. J., North, K. E., Dyer, T., Blangero, J., Comuzzie, A. G., & Williams, J.
- Affiliations
- Cincinnati Children's Hospital Medical Center (US)
- University of North Carolina at Chapel Hill (US)
- Texas Biomedical Research Institute (US)
- Corresponding author
- Martin, Lisa J
- Venue
- BMC Genetics
- Published
- 2003-12-31
- Volume
- 4
- Issue
- S1
- Pages
- S95-S95
- ISSN
- 1471-2156 (ISSN-L)
- PMC
- PMC1866536
- OpenAlex
- W2148447731
- Cited by
- 31
- References
- 15
- Citations by year
- 2024: 2 · 2023: 1 · 2020: 1 · 2019: 1 · 2015: 1 · 2014: 1 · 2012: 3
- FWCI
- 1.76
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- BMC Genetics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion, cc-by)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- National Institutes of Health (MH 59490)
- National Heart, Lung, and Blood Institute (HL-28972, P01HL045522, HL45522, P01HL028972)
- National Institute of Mental Health (R37MH059490, MH59490, R01MH059490)
- National Institute of General Medical Sciences (GM-31575, R01GM031575)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- metabolic syndrome, genetic correlation, phenotypic correlation, factor analysis, multivariate data reduction, total cholesterol, HDL cholesterol, triglycerides, systolic blood pressure, body mass index, Framingham Heart Study
- MeSH terms
- Adult, Blood Pressure, Cardiovascular Diseases, Cholesterol, Chromosome Mapping, Female, Genotype, Humans, Cholesterol, HDL, Male, Middle Aged, Phenotype, Triglycerides, Cohort Studies, Genome, Human, Body Mass Index, Metabolic Syndrome, Adult Children
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