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Biomedical subjects

Anthony G Comuzzie

Publications and source records attributed to Anthony G Comuzzie.

At least 37 records · Page 2Linked to original sources
PubMed2004

Adiponectin but not resistin is associated with insulin resistance-related phenotypes in baboons.

OBJECTIVE: The hormones adiponectin and resistin have been associated with insulin resistance. This paper analyzed the potential relationship between adiponectin and resistin and insulin resistance-related phenotypes in baboons. RESEARCH METHODS AND PROCEDURES: One hundred eight adult baboons (84 female and 24 male) were studied. Weight was measured, and a blood sample was collected under fasting conditions for plasma and monocyte isolation. Fasting glucose, insulin, C-peptide, and adiponectin levels in plasma were measured by standard methods. Insulin resistance was calculated by the homeostasis model assessment index. Resistin mRNA abundance in monocytes was determined by real-time quantitative reverse transcription-polymerase chain reaction. Data were clustered by weight tertiles for statistical analysis. RESULTS: As observed in humans, the insulin resistance-related phenotypes were related to weight, plasma levels of adiponectin, and C-peptide. No significant relationship between resistin circulating levels or expression in monocytes and insulin resistance-related phenotypes was found in baboons. DISCUSSION: These findings suggest that resistin is not associated with insulin resistance. However, previous observations of relationships among weight, adiponectin, and insulin resistance are confirmed.

Adiponectin↗
PubMed2004

Quantitative genetic analysis of glucose transporter 4 mRNA levels in baboon adipose.

OBJECTIVE: Glucose transporter 4 (GLUT4) is an insulin-responsive glucose transporter expressed in adipose tissue. A decrease of the mRNA abundance of GLUT4 in adipose tissue has been observed in conditions of insulin resistance. The objective was to conduct quantitative genetic analyses using GLUT4 mRNA levels in omental adipose tissue of baboons as a novel phenotype. RESEARCH METHODS AND PROCEDURES: A blood sample and a biopsy of omental adipose tissue were collected from 418 adult, pedigreed baboons. Total RNA was isolated from adipose tissue biopsies, and GLUT4 mRNA abundance was assayed by quantitative, real-time reverse transcription-polymerase chain reaction. Insulin and glucose were determined in fasting plasma by standard methods. Quantitative genetic analyses were conducted using GLUT4 mRNA, insulin, and glucose as quantitative traits. RESULTS: GLUT4 mRNA expression in omental adipose tissue was heritable (h(2) = 0.23, p = 0.001). Bivariate genetic analyses revealed a significant genetic correlation (rho(G)) between GLUT4 mRNA abundance and both body weight (rho(G) = 0.63, p = 0.007), BMI (rho(G) = 0.59, p = 0.02) and insulin (rho(G) = 0.72, p = 0.04). A genome scan was conducted, and a quantitative trait locus was detected on chromosome 10p12 with a logarithm of the odds ratio score of 1.1. DISCUSSION: GLUT4 mRNA abundance in omental adipose tissue has a significant genetic component. These findings suggest that expression of GLUT4 mRNA, plasma insulin levels, and body weight may be regulated by common genes.

Adipose Tissue↗
PubMed2004

Pleiotropic effects of genes for insulin resistance on adiposity in baboons.

OBJECTIVE: Previous research has suggested a genetic contribution to the development of insulin resistance and obesity. We hypothesized that the same genes influencing insulin resistance might also contribute to the variation in adiposity. RESEARCH METHODS AND PROCEDURES: A total of 601 (200 male, 401 female) adult baboons (Papio hamadryas) from nine families with pedigrees ranging in size from 43 to 121 were used in this study. Plasma insulin, glucose, C-peptide, and adiponectin were analyzed, and homeostasis model assessment of insulin resistance (HOMA IR) was calculated. Fat biopsies were collected from omental fat tissue, and triglyceride concentration per gram of fat tissue was determined. Body weight and length were measured, and BMI was derived. Univariate and bivariate quantitative genetic analyses were performed using SOLAR. RESULTS: Insulin, glucose, C-peptide, and adiponectin levels, HOMA IR, triglyceride concentration of fat tissue, body weight, and BMI were all found to be significantly heritable, with heritabilities ranging from 0.15 to 0.80. Positive genetic correlations (r(G)s) were observed for HOMA IR with C-peptide (r(G) = 0.88 +/- 0.10, p = 0.01), triglyceride concentration in fat tissue (r(G) = 0.86 +/- 0.33, p = 0.02), weight (r(G) = 0.50 +/- 0.20, p = 0.03), and BMI (r(G) = 0.64 +/- 0.22, p = 0.02). DISCUSSION: These results suggest that a set of genes contributing to insulin resistance also influence general and central adiposity phenotypes. Further genetic research in a larger sample size is needed to identify the common genes that constitute the genetic basis for the development of insulin resistance and obesity.

Adiponectin↗
PubMed2004

Bivariate linkage between acylation-stimulating protein and BMI and high-density lipoproteins.

OBJECTIVE: Given the importance of visceral adiposity in the metabolic syndrome, whether levels of adipokines have shared genetic effects (pleiotropy) with aspects of the metabolic syndrome should be addressed. Acylation-stimulating protein (ASP), an adipose-derived protein, influences lipid metabolism, obesity, and glucose use. Therefore, our objective was to examine the genetic regulation of ASP and associated pleiotropic effects. RESEARCH METHODS AND PROCEDURES: We assayed serum ASP levels in 435 Mexican Americans participating in the San Antonio Family Heart Study and performed univariate and bivariate variance components analysis. RESULTS: Additive genetic heritability of ASP was 26% (p = 0.0004). Bivariate genetic analysis detected significant genetic correlations between ASP and several lipid measures but not between ASP and adiposity or diabetes measures. We detected two potential quantitative trait loci influencing ASP levels. The strongest signal was on chromosome 17 near marker D17S1303 [log of the odds ratio (LOD) = 2.7]. The signal on chromosome 15 reached its peak near marker D15S641 (LOD = 2.1). Both signals localize in regions reported to harbor quantitative trait loci influencing obesity and lipid phenotypes in this population. Bivariate linkage analysis yielded LODs of 4.7 for ASP and BMI on chromosome 17 and 3.2 for ASP and high-density lipoprotein2a on chromosome 15. DISCUSSION: Given these findings, there seems to be a significant genetic contribution to variation in circulating levels of ASP and an interesting pattern of genetic correlation (i.e., pleiotropy) with other risk factors associated with the metabolic syndrome.

Adolescent↗
PubMed2004

Quantitative trait locus determining dietary macronutrient intakes is located on human chromosome 2p22.

BACKGROUND: Obesity is generally accompanied by increased food intake. OBJECTIVE: We sought to identify the genes influencing variation in dietary macronutrient intakes in Mexican Americans. DESIGN: We conducted a genome-wide scan by using data derived from food-frequency questionnaires in 816 participants from the San Antonio Family Heart Study. Household effect was simultaneously estimated in a variance component model with the use of SOLAR. RESULTS: All dietary intake measures (total calories, proteins, fat, saturated fat, monounsaturated fat, polyunsaturated fat, carbohydrates, and sucrose) were moderately heritable. Household effect was insignificant except on total calories and sucrose. Suggestive evidence of linkage with saturated fat intake was found on chromosome 2p22 near marker D2S1346 [logarithm of odds (LOD) = 2.62]. Intakes of total calories, fat, protein, and monounsaturated fat were also suggestively linked to the same marker. A significant linkage signal on chromosome 2p22 for leptin concentrations and fat mass was localized in this population, so we used leptin or fat mass as a covariate. Multipoint LOD scores for saturated fat dropped to 1.27 and 1.90, respectively, which suggested that this region on chromosome 2p contributes to both saturated fat intake and body adiposity. This chromosomal region contains the proopiomelanocortin gene (POMC). However, 2 polymorphisms in exon 3 of the POMC gene showed no association with saturated fat intake. CONCLUSIONS: The results strengthen the hypothesis that chromosome 2p22 harbors genes that influence a variety of obesity-related phenotypes, including macronutrient intakes.

Adult↗
PubMed2004

Genetic and environmental influences on thyroid hormone variation in Mexican Americans.

Thyroid hormones play major roles in the regulation of a wide range of metabolic and physiologic processes, but the genes and environmental factors that affect normal, quantitative variation in thyroid hormone concentrations are largely unknown. Using quantitative genetic methods, we evaluated the effects of genes and environmental factors on thyroid hormone variation in 586 women and 425 men from 27 randomly ascertained Mexican-American families from the San Antonio Family Heart Study. Data were available on free and total T(4), free and total T(3), TSH, thyroglobulin, and T(4)-binding globulin, as well as on covariates, including sex, age, weight, lifestyle habits, physical activity, and others. These covariates accounted for 2-18% of total phenotypic variation, whereas genes accounted for 26-64% of the variation. Overall, free T(3) had the highest heritability, which is noteworthy because it is the most biologically active thyroid hormone and accounts for the vast majority of metabolic and physiologic effects of thyroid hormones. Our results indicate that genes account for a substantial portion of variation in human thyroid hormone levels, and suggest that further studies to identify the genes involved in this variation could reveal important insights into the processes that govern thyroid-mediated metabolism.

Adult↗
PubMed2004

Principal component for metabolic syndrome risk maps to chromosome 4p in Mexican Americans: the San Antonio Family Heart Study.

Metabolic syndrome refers to the clustering of disease conditions such as insulin resistance, hyperinsulinemia, dyslipidemia, hypertension, and obesity. To explore the genetic predispositions of this complex syndrome, we conducted a principal components analysis using data on 14 phenotypes related to the risk of developing metabolic syndrome. The subjects were 566 nondiabetic Mexican Americans, distributed in 41 extended families from the San Antonio Family Heart Study. The factor scores obtained from these 14 phenotypes were used in multipoint linkage analysis using SOLAR. Factors were identified that accounted for 73% of the total variance of the original variables: body size-adiposity, insulin-glucose, blood pressure, and lipid levels. Each factor exhibited evidence for either significant or suggestive linkage involving four factor-specific chromosomal regions relating to chromosomes 1, 3, 4, and 6. Significant evidence for linkage of the lipid factor was found on chromosome 4 near marker D4S403 (LOD = 3.52), where the cholecystokinin A receptor (CCKAR) and ADP-ribosyl cyclase 1 (CD38) genes are located. Suggestive evidence for linkage of the body size-adiposity factor to chromosome 1 near marker D1S1597 (LOD = 2.53) in the region containing the nuclear receptor subfamily 0, group B, member 2 gene (NROB2) also was observed. The insulin-glucose and blood pressure factors were linked suggestively to regions on chromosome 3 near marker D3S1595 (LOD = 2.20) and on chromosome 6 near marker D6S 1031 (LOD = 2.08), respectively. In summary, our findings suggest that the factor structures for the risk of metabolic syndrome are influenced by multiple distinct genes across the genome.

Adult↗
PubMed2004

Intercellular adhesion molecule-1 concentration is genetically correlated with insulin resistance, obesity, and HDL concentration in Mexican Americans.

The metabolic syndrome and type 2 diabetes are associated with endothelial activation (and thus with inflammatory processes leading to atherosclerosis), but the mechanisms that underlie these associations are not fully understood. Endothelial intercellular adhesion molecule (ICAM)-1 plays an important role in the recruitment of immune cells during the development of atherosclerotic plaque and is a marker of inflammatory disease. We performed bivariate quantitative genetic analyses to estimate genetic and environmental correlations between circulating ICAM-1 concentration and 17 phenotypes associated with the metabolic syndrome. Our study population comprised 428 adults in 20 extended Mexican-American families from the San Antonio Family Heart Study (SAFHS). Circulating ICAM-1 concentration is heritable (h(2) = 0.56). ICAM-1 concentration showed significant positive genetic correlations (range 0.32-0.52, P < 0.05) with fasting insulin, insulin 2 h after oral glucose challenge, homeostasis model assessment of insulin resistance, BMI, waist circumference, and leptin concentration; negative genetic correlation with HDL3 cholesterol concentration; and negative environmental correlation with adiponectin concentration. Significant genetic correlations were not found between ICAM-1 and fasting or 2-h serum glucose or systolic or diastolic blood pressure. Thus, ICAM-1 expression may share common genetic modulation with traits related to obesity, insulin resistance, and HDL3 cholesterol, but not with hyperglycemia or hypertension per se.

Blood Glucose↗
PubMed2004

Genome-wide scans reveal quantitative trait Loci on 8p and 13q related to insulin action and glucose metabolism: the San Antonio Family Heart Study.

Type 2 diabetes is a complex disease that arises from physiological disruptions of the body's sensitivity to insulin and ability to metabolize glucose. Multipoint linkage analyses for insulin sensitivity phenotypes were conducted in 1,280 Mexican Americans from 41 families who participated in the San Antonio Family Heart Study. A significant linkage signal (logarithm of odds [LOD] = 2.98) affecting corrected insulin response to glucose was detected on chromosome 13q between D13787 and D13S252, in the region where the MODY-4 gene has previously been mapped. Another signal on chromosome 13 was observed at D13S285 (LOD = 1.86), where the insulin receptor substrate 2 gene resides. Significant linkage (LOD = 3.09) for insulin response to glucose was found on chromosome 8 between D8S1130 and D8S1106, near the lipoprotein lipase and macrophage scavenger receptor genes. Multipoint analysis of abdominal skinfold with an LOD of 2.68 showed signals in the same region. There was also suggestive evidence for linkage of quantitative insulin sensitivity check index and fasting glucose to a previously reported location at D9S301 (LOD = 2.19). These results indicate that chromosomal locations on 8p and 13q might harbor genes that affect a variety of insulin- and glucose-related phenotypes that contribute to the observed variations in these important risk factors for diabetes in Mexican Americans.

Adult↗
PubMed2003

Phenotypic, genetic, and genome-wide structure in the metabolic syndrome.

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.

Adult↗
PubMed2003

HDL cholesterol in females in the Framingham Heart Study is linked to a region of chromosome 2q.

BACKGROUND: Despite strong evidence for a genetic component to variation in high-density lipoprotein cholesterol levels (HDL-C), specific polymorphisms associated with normal variation in HDL-C have not been identified. It is known, however, that HDL-C levels are influenced in complex ways by factors related to age and sex. In this paper, we examined the evidence for age- and sex-specific linkage of HDL-C in a longitudinal sample of participants from the Framingham Heart Study. To determine if aging could influence our ability to detect linkage, we explored the evidence for linkage of HDL-C at three time points, t1, t2, and t3, spaced approximately 8 years apart and corresponding respectively to visits 11, 15, and 20 for the original cohort and 1, 2, and 4 for the offspring and spouses. Additionally, to examine the effects of sex on linkage at each time point, we estimated the heritability and genetic correlation of HDL-C, performed linkage analysis of HDL-C, tested for genotype-by-sex interaction at a QTL, and performed linkage analysis of HDL-C in males and females separately. RESULTS AND CONCLUSION: In women, we found evidence for a QTL on chromosome 2q influencing HDL-C variation. Although the QTL could be detected in the combined sample of males and females at the first time point, the linkage was not significant at subsequent time points.

Adult↗
PubMed2003

The baboon as a nonhuman primate model for the study of the genetics of obesity.

OBJECTIVE: At present, rodents represent the most common animal model for research in obesity and its comorbidities (e.g., type 2 diabetes and coronary heart disease), however, there are several physiological and developmental differences between rodents and humans reflective of their relatively ancient evolutionary divergence (approximately 65 to 75 million years ago). Therefore, we are currently developing the baboon as a nonhuman primate model for the study of the genetics of obesity. RESEARCH METHODS AND PROCEDURES: At present, we are collecting extensive phenotypic data in a large pedigreed colony (N > 2000) of baboons housed at the Southwest Foundation for Biomedical Research in San Antonio, Texas. The long-term goal of this project is to identify genes influencing adiposity-related phenotypes and to test hypotheses regarding their pleiotropic effects on other phenotypes related to increased risk for a variety of common diseases (e.g., coronary heart disease and type 2 diabetes). RESULTS: To date we have obtained various adipose-specific endocrine measures, adipose tissue biopsies, and estimates of body composition on a substantial portion of our pedigreed colony. The pattern of adipose tissue accumulation follows closely that seen in humans, and we have detected significant additive genetic heritabilities for these obesity-related phenotypes. DISCUSSION: Given the physiological and developmental similarities between humans and baboons, along with the ability to collect data under well-controlled situations and the extensive pedigree data available in our colony, the baboon offers an extremely valuable nonhuman primate model for the study of obesity and its comorbidities.

Adipose Tissue↗
PubMed2003

The genetics of obesity in Mexican Americans: the evidence from genome scanning efforts in the San Antonio family heart study.

Recent estimates indicate that approximately 18% of the population in the United States can be considered obese (defined as a body mass index [BMI] > or = 30), and this rate is even higher among ethnic populations such as Mexican Americans. This figure becomes very significant given the strong evidence for obesity as a major risk factor for a variety of chronic diseases including type 2 diabetes mellitus and coronary heart disease. The search for genes involved in the expression of obesity has been one of the focal points of the San Antonio Family Heart Study (SAFHS), a large, family-based study to examine the genetics of risk for atherosclerosis in Mexican Americans. To date, our genome scanning effort has reported two quantitative trait loci (QTLs) with pronounced effects on the expression of a variety of obesity--related phenotypes (e.g., leptin levels, fat mass, and BMI) located on chromosomes 2 and 8. We are currently working to further refine these signals and to identify the genes and allelic variants involved. Here, we summarize the latest results from our ongoing efforts to identify obesity genes in the San Antonio Family Heart Study.

Adult↗
PubMed2002

A comprehensive linkage analysis for myocardial infarction and its related risk factors.

Coronary artery disease and myocardial infarction (MI) are leading causes of death in the western world. Numerous studies have shown that risk factors such as diabetes mellitus, arterial hypertension and hypercholesterolemia contribute to the development of the disease. Although each risk factor by itself is partly under genetic control, a positive family history is an independent predictor, which suggests that there are additional susceptibility genes. We have scanned the whole genome in 513 families to identify chromosomal regions linked to myocardial infarction and related risk factors that are known to be under genetic control. Here we show, by using variance component analysis and incorporating risk factors, that risk of myocardial infarction maps to a single region on chromosome 14 with a significant lod score of 3.9 (pointwise P=0.00015, genome-wide P<0.05), providing evidence of a principal MI locus. To characterize this locus we analyzed each risk factor by itself. Serum concentrations of lipoprotein (a) show linkage to both the apolipoprotein (a) locus (lod score 26.99) and a new locus on chromosome 1 (lod score 3.8). There is suggestive linkage for diabetes mellitus on chromosome 6 (lod score 2.96), for hypertension on chromosomes 1 and 6, for high-density and low-density lipoprotein cholesterol on chromosomes 1 and 17, and for triglyceride concentrations on chromosome 9. Although some of these risk factors overlap with previously identified loci, none overlaps with the newly identified susceptibility locus for myocardial infarction and coronary artery disease.

Aged↗
PubMed2002

Genotype by smoking interaction for leptin levels in the San Antonio Family Heart Study.

Recent studies reported a marked inverse effect of smoking on serum levels of leptin (an adipocyte derived protein), offering a possible explanation for variation in body weight between smokers and non-smokers. The goal of this study was to examine the genetic architecture of the response to smoking in leptin levels using data from the San Antonio Family Heart Study. We employed a variance decomposition analysis using maximum likelihood methods to model genotype by smoking interactions for leptin levels, examined the impact of the exclusion of smokers in a subsequent linkage analysis, and incorporated the QTL identified in the linkage analysis in a model of genotype by smoking interaction. We found significant evidence (P = 0.001) for a genotype by smoking status interaction for serum leptin levels. In the subsequent linkage analysis with smokers excluded, we obtained a maximum LOD score of 3.1 (P = 0.00008) near D8S1102. Using this QTL in a model of genotype by smoking status interaction, we identified significant evidence for an interaction at this specific locus (P = 0.04). Given these results, we hypothesize that a quantitative trait locus in this vicinity of chromosome 8 may have a differential effect on the expression of leptin in smokers versus non-smokers.

Adult↗
PubMed2002

Lifespan in captive baboons is heritable.

The effects of aging are evident in multiple organ systems, tissues, cell types, and molecules; all complex phenotypes affected by multiple shared and unique environmental factors and genes, which makes identifying the role of genetics in human aging difficult. Researchers have used yeast, nematodes, fruit flies, and mice to search for genes that influence the aging process. Given the phylogenetic distance and anatomic and physiologic dissimilarities of these organisms from humans, directly extrapolating these results to our species is problematic. However, nonhuman primates have a high degree of genetic, anatomic and physiologic similarity with humans and, thus, they may assist in the detection, characterization, and identification of genetic and environmental influences on human aging. Our goal is to demonstrate that effects of genes on variation in lifespan, a surrogate measure of aging, can be detected in a nonhuman primate species. Using variance component analysis, heritability of age at death was estimated to be 0.23+/-0.08 (P=0.0003) in 674 baboons from the Southwest Foundation for Biomedical Research (SFBR). This research demonstrates that lifespan is under partial genetic control. Given these findings, we believe that the baboon has potential as a model of human aging.

Analysis of Variance↗
PubMed2002

Leptin's sexual dimorphism results from genotype by sex interactions mediated by testosterone.

OBJECTIVE: Recent studies have reported the existence of marked sexual dimorphism in serum leptin levels in humans, with women having approximately three times the levels of men. As we have shown for other measures of adiposity, such sexual dimorphism can arise from a special case of genotype by environment interaction, that of genotype by sex interaction. RESEARCH METHODS AND PROCEDURES: Using maximum likelihood-based variance decomposition techniques, we examined the genetic and environmental architecture of sexual dimorphism in serum leptin levels in 1147 Mexican Americans from the San Antonio Family Heart Study. RESULTS: Both the genetic and environmental variances for this trait differed significantly between the sexes (p < 0.001 and p < 0.01, respectively), with women displaying larger values for both components. We found significant evidence that different genes influence variation in serum leptin levels between the two sexes (p = 0.05). Furthermore, this pattern of sexual dimorphism in serum leptin levels persisted even after accounting for the effects of either the percentage of body fat or total body fat. However, this pattern of sexual dimorphism was eliminated after accounting for the effects of testosterone. DISCUSSION: These findings suggest that the sexual dimorphism seen in leptin levels is not simply explained as differences in total adiposity between the sexes. We conclude that the genes, which influence variation in serum leptin levels, are differentially expressed depending on sex, and that the sexes also show differences in response of the expression of this obesity-related trait to unmeasured residual effects.

Adipose Tissue↗