Publications

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.

Obesity has become a worldwide public health problem which affects millions of people. Substantial progress has been made in elucidating the pathogenesis of energy homeostasis over the past few years. The fact that obesity is under strong genetic control has been well established. Twin, adoption and family studies have shown that genetic factors play a significant role in the pathogenesis of obesity. Human monogenic obesity is rare in large populations. The most common form of obesity is considered to be a polygenic disorder. New treatments are currently required for this common metabolic disease and type 2 diabetes. The identification of physiological and biochemical factors that underlie the metabolic disturbances observed in obesity is a key step in developing better therapeutic outcomes. The discovery of new genes and pathways involved in the pathogenesis of such a disease is critical to this process. However, identification of genes that contribute to the risk of developing the disease represents a significant challenge since obesity is a complex disease with many genetic and environmental causes. A number of diverse approaches have been used to discover and validate potential new genes for obesity. To date, DNA-based approaches using candidate genes and genome-wide linkage analysis have not had a great success in identifying genomic regions or genes involved in the development of these diseases. Recent advances in the ability to evaluate linkage analysis data from large family pedigrees (using variance components-based linkage analysis) show great promise in robustly identifying genomic regions associated with the development of obesity. Studying rare mutations in humans and animal models has provided fundamental insight into a complex physiological process, and has complemented population-based studies that seek to reveal primary causes. Remarkable progress has been made in both fronts and the pace of advance is likely to accelerate as functional genomics and the human genome project expand and mature. Approaches based on Mendelian and quantitative genetics may well converge, and ultimately lead to more rational and selective therapies.

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.

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.

Lipoprotein phenotypes are known to be strongly intercorrelated. These intercorrelations are due to genetic and environmental effects on common metabolic pathways. The purpose of this study was to determine if we could localize genes that exert pleiotropic effects on multiple related lipoprotein traits in humans. Using data from the San Antonio Family Heart Study, we extracted principal components from a set of 12 intercorrelated lipoprotein traits that included phenotypes reflecting lipid and protein concentrations and size distributions for LDLs and HDLs. Five principal components were extracted from the data and all were significantly heritable (h(2) = 0.41-0.57). When subjected to linkage analyses, only one, Component 5, returned a LOD score > or = 3 (LOD score was 3.0 at 38cM on chromosome 15; genome-wide P-value = 0.039). LDL median diameter (-0.529), non-HDLC (-0.422), and ApoB (-0.403) concentrations were the only traits with loadings (absolute value) >0.4, suggesting Component 5 is related to LDL size or perhaps more generally to beta-lipoprotein metabolism. Surprisingly, none of the 12 original lipoprotein traits had a LOD >1 in this region of chromosome 15. These data provide evidence for a novel gene, influencing beta-lipoprotein phenotypes, whose effect(s) is detected only when several lipoprotein traits are considered together.

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.

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.

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.

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.

OBJECTIVE: We conducted a whole-genome, multipoint linkage screen to localize a previously reported major locus accounting for 56% to 67% of the additive genetic effects on covariate-adjusted plasma HDL cholesterol (HDL-C) levels in Mexican Americans from the San Antonio Family Heart Study (SAFHS).

METHODS AND RESULTS: After using complex segregation analysis to recover the major locus in 472 SAFHS participants from 10 genotyped families, we incorporated covariates required to detect that major locus, including plasma levels of triglycerides and apolipoprotein A-I, in a maximum-likelihood-based variance-components linkage screen. Only chromosome 16 exhibited convincing evidence for a quantitative trait locus (QTL), with a peak multipoint log of the odds (LOD)=3.73 (P=0.000034). Subsequent penetrance model-based linkage analysis, incorporating genotypes at the marker locus nearest the multipoint peak (D16S518) into the segregation model, detected linkage with the previously detected major locus (LOD=2.73, P=0.000642). Initial estimates place this QTL within a 15-cM region of chromosome 16q near the structural loci for lecithin:cholesterol acyltransferase (LCAT) and cholesteryl ester transfer protein (CETP).

CONCLUSIONS: A QTL influencing plasma levels of HDL-C in Mexican Americans from San Antonio maps to a region of human chromosome 16q near LCAT and CETP.