Effect of Genome and Environment on Metabolic and Inflammatory Profiles

• Published in: PloS one Vol. 10; no. 4; p. e0120898
• Main Authors: Sirota, Marina, Willemsen, Gonneke, Sundar, Purnima, Pitts, Steven J., Potluri, Shobha, Prifti, Edi, Kennedy, Sean, Ehrlich, S. Dusko, Neuteboom, Jacoline, Kluft, Cornelis, Malone, Karen E., Cox, David R., de Geus, Eco J. C., Boomsma, Dorret I.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 08.04.2015; Public Library of Science (PLoS)
• Subjects: Adult; Analysis; Bioindicators; Biomarkers; Blood; Blood pressure; Body composition; Body mass index; Cardiovascular disease; Care and treatment; Cluster Analysis; Clustering; Clusters; Correlation analysis; Cytokines; Diabetes; Endocrinology and metabolism; Environment; Family studies; Female; Genetic diversity; Genetic factors; Genetic research; Genetics; Genome, Human; Genomes; Heart rate; Hematologic Tests; Hematology; Households; Housing; Human health and pathology; Humans; Hypertension; Immunology; Inflammation; Inflammation - blood; Inflammation - genetics; Inflammation - metabolism; Influence; Insulin; Life Sciences; Liver; Male; Mathematical analysis; Metabolic syndrome; Phenotype; Physiology; Risk factors; Similarity; Studies; Systematic review; Twins; Twins, Monozygotic - genetics; Blood counts; Phenotypes; Cytokines; Cell enumeration techniques; Fibrinogen; Inflammation; Twins; Cholesterol
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0120898

Twin and family studies have established the contribution of genetic factors to variation in metabolic, hematologic and immunological parameters. The majority of these studies analyzed single or combined traits into pre-defined syndromes. In the present study, we explore an alternative multivariate approach in which a broad range of metabolic, hematologic, and immunological traits are analyzed simultaneously to determine the resemblance of monozygotic (MZ) twin pairs, twin-spouse pairs and unrelated, non-cohabiting individuals. A total of 517 participants from the Netherlands Twin Register, including 210 MZ twin pairs and 64 twin-spouse pairs, took part in the study. Data were collected on body composition, blood pressure, heart rate, and multiple biomarkers assessed in fasting blood samples, including lipid levels, glucose, insulin, liver enzymes, hematological measurements and cytokine levels. For all 51 measured traits, pair-wise Pearson correlations, correcting for family relatedness, were calculated across all the individuals in the cohort. Hierarchical clustering techniques were applied to group the measured traits into sub-clusters based on similarity. Sub-clusters were observed among metabolic traits and among inflammatory markers. We defined a phenotypic profile as the collection of all the traits measured for a given individual. Average within-pair similarity of phenotypic profiles was determined for the groups of MZ twin pairs, spouse pairs and pairs of unrelated individuals. The average similarity across the full phenotypic profile was higher for MZ twin pairs than for spouse pairs, and lowest for pairs of unrelated individuals. Cohabiting MZ twins were more similar in their phenotypic profile compared to MZ twins who no longer lived together. The correspondence in the phenotypic profile is therefore determined to a large degree by familial, mostly genetic, factors, while household factors contribute to a lesser degree to profile similarity.