Biomedical subjects

Anthony G Comuzzie

Publications and source records attributed to Anthony G Comuzzie.

At least 19 recordsLinked to original sources

PubMed2022

Genetic variants in ALDH1L1 and GLDC influence the serine-to-glycine ratio in Hispanic children.

BACKGROUND: Glycine is a proteogenic amino acid that is required for numerous metabolic pathways, including purine, creatine, heme, and glutathione biosynthesis. Glycine formation from serine, catalyzed by serine hydroxy methyltransferase, is the major source of this amino acid in humans. Our previous studies in a mouse model have shown a crucial role for the 10-formyltetrahydrofolate dehydrogenase enzyme in serine-to-glycine conversion. OBJECTIVES: We sought to determine the genomic influence on the serine-glycine ratio in 803 Hispanic children from 319 families of the Viva La Familia cohort. METHODS: We performed a genome-wide association analysis for plasma serine, glycine, and the serine-glycine ratio in Sequential Oligogenic Linkage Analysis Routines while accounting for relationships among family members. RESULTS: All 3 parameters were significantly heritable (h2 = 0.22-0.78; P < 0.004). The strongest associations for the serine-glycine ratio were with single nucleotide polymorphisms (SNPs) in aldehyde dehydrogenase 1 family member L1 (ALDH1L1) and glycine decarboxylase (GLDC) and for glycine with GLDC (P < 3.5 × 10-8; effect sizes, 0.03-0.07). No significant associations were found for serine. We also conducted a targeted genetic analysis with ALDH1L1 exonic SNPs and found significant associations between the serine-glycine ratio and rs2886059 (β = 0.68; SE, 0.25; P = 0.006) and rs3796191 (β = 0.25; SE, 0.08; P = 0.003) and between glycine and rs3796191 (β = -0.08; SE, 0.02; P = 0.0004). These exonic SNPs were further associated with metabolic disease risk factors, mainly adiposity measures (P < 0.006). Significant genetic and phenotypic correlations were found for glycine and the serine-glycine ratio with metabolic disease risk factors, including adiposity, insulin sensitivity, and inflammation-related phenotypes [estimate of genetic correlation = -0.37 to 0.35 (P < 0.03); estimate of phenotypic correlation = -0.19 to 0.13 (P < 0.006)]. The significant genetic correlations indicate shared genetic effects among glycine, the serine-glycine ratio, and adiposity and insulin sensitivity phenotypes. CONCLUSIONS: Our study suggests that ALDH1L1 and GLDC SNPs influence the serine-to-glycine ratio and metabolic disease risk.

Child↗

PubMed2005

Genetic linkage and association of the growth hormone secretagogue receptor (ghrelin receptor) gene in human obesity.

The growth hormone secretagogue receptor (GHSR) (ghrelin receptor) plays an important role in the regulation of food intake and energy homeostasis. The GHSR gene lies on human chromosome 3q26 within a quantitative trait locus strongly linked to multiple phenotypes related to obesity and the metabolic syndrome. Because the biological function and location of the GHSR gene make it an excellent candidate gene, we tested the relation between common single nucleotide polymorphisms (SNPs) in the GHSR gene and human obesity. We performed a comprehensive analysis of SNPs, linkage disequilibrium (LD), and haplotype structure across the entire GHSR gene region (99.3 kb) in 178 pedigrees with multiple obese members (DNA of 1,095 Caucasians) and in an independent sample of the general population (MONICA Augsburg left ventricular hypertrophy substudy; DNA of 1,418 Caucasians). The LD analysis revealed a disequilibrium block consisting of five SNPs, consistent in both study cohorts. We found linkage among all five SNPs, their haplotypes, and BMI. Further, we found suggestive evidence for transmission disequilibrium for the minor SNP alleles (P < 0.05) and the two most common haplotypes with the obesity affection status ("susceptible" P = 0.025, "nonsusceptible" P = 0.045) in the family cohort using the family-based association test program. Replication of these findings in the general population resulted in stronger evidence for an association of the SNPs (best P = 0.00001) and haplotypes with the disease ("susceptible" P = 0.002, "nonsusceptible" P = 0.002). To our knowledge, these data are the first to demonstrate linkage and association of SNPs and haplotypes within the GHSR gene region and human obesity. This linkage, together with significant transmission disequilibrium in families and replication of this association in an independent population, provides evidence that common SNPs and haplotypes within the GHSR region are involved in the pathogenesis of human obesity.

Body Mass Index↗

PubMed2004

[Genomics of body weight regulation: unraveling the molecular mechanisms predisposing to obesity].

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.

Animals↗

PubMed2004

Ala67Thr polymorphism in the Agouti-related peptide gene is associated with inherited leanness in humans.

A role for melanocortin signaling in the regulation of body weight in humans has been clearly established. Haploinsufficiency of the type 4 melanocortin receptor is associated with early-onset obesity, implying that this receptor provides an important tonic inhibition of weight gain. Agouti-related peptide (AGRP) is an endogenous antagonist of melanocortin signaling. Therefore, loss of AGRP function could lead to the expression of a lean phenotype. We investigated the potential role of AGRP in human weight regulation by examining the association between the Ala67Thr AGRP polymorphism and indices of body composition. Significant associations were found between homozygosity for this mutation (n = 8) and body composition phenotype in 874 subjects of the Quebec family study (QFS). By PCR-RFLP analysis, we have identified eight individuals who are homozygous for the 67Thr variant allele within the QFS population, where none were observed in SAFHS. The eight QFS homozygote individuals have lower weight (-16%; P = 0.02), body mass index (-17%; P = 0.01), fat free mass (-9%; P = 0.002), fat mass (FM) (-20%; P = 0.04), and leptin (-20%; P = 0.02) when compared to those carrying at least one 67Ala allele. Individuals homozygous for the 67Thr allele had a BMI that was either at or slightly below an ideal range for their age. Thus, the Ala67Thr AGRP polymorphism is associated with lower body weight in humans, with the largest effect being observed on body FM. We did not observe any difference in the stability or cellular distribution of the mutant protein in a heterologous expression system, thus the mechanism of this effect requires further investigation.

Adult↗

PubMed2004

Genetics of monoamine metabolites in baboons: overlapping sets of genes influence levels of 5-hydroxyindolacetic acid, 3-hydroxy-4-methoxyphenylglycol, and homovanillic acid.

BACKGROUND: Monoamine neurotransmitters (serotonin, dopamine, and norepinephrine) are associated with several psychiatric disorders. Limited evidence suggests that monoamine levels are heritable, but no information concerning genetic relationships among monoamines is available. Further genetic analysis can help explain phenotypic correlations among monoamine levels and might eventually help identify genes involved in response to therapy or risk of psychopathology. METHODS: Levels of the monoamine metabolites homovanillic acid (HVA), 5-hydroxyindolacetic acid (5-HIAA), and 3-hydroxy-4-methoxyphenylglycol (MHPG) were measured in cerebrospinal fluid from 271 baboons (Papio hamadryas). Variance components methods were used to estimate heritabilities, and multivariate analyses were used to estimate genetic correlations (pleiotropy) and environmental correlations between metabolites. RESULTS: Each metabolite exhibited significant heritability in baboons (5-HIAA: h(2) =.30 +/-.17; MHPG: h(2) =.36 +/-.16; HVA: h(2) =.50 +/-.19). Multivariate analyses revealed genetic correlations between 5-HIAA and HVA and between HVA and MHPG. Environmental correlations were found between 5-HIAA and HVA and between 5-HIAA and MHPG. CONCLUSIONS: Overlapping, nonidentical sets of genes influence individual variation in 5-HIAA, MHPG, and HVA levels among baboons. The phenotypic correlation between 5-HIAA and HVA observed in nonhuman primates and humans is likely due to both shared genetic and environmental factors. Genetic analyses of monoamine levels in primates can provide novel information concerning the genetics of variation among humans.

Analysis of Variance↗

PubMed2004

Genetic contributions to social impulsivity and aggressiveness in vervet monkeys.

BACKGROUND: Impulsivity contributes to multiple psychiatric disorders and sociobehavioral problems, and the more serious consequences of impulsivity are typically manifest in social situations. This study assessed the genetic contribution to impulsivity and aggressiveness in a social context using a nonhuman primate model. METHODS: Subjects were 352 adolescent and adult vervet monkeys from an extended multigenerational pedigree. Behavior was assessed in the Intruder Challenge Test, a standardized test that measures impulsivity and aggressiveness toward a stranger. Genetic and maternal contributions to variation in the Social Impulsivity Index and its two subscales, impulsive approach and aggression, were estimated using variance components analyses. RESULTS: The results found significant genetic contributions to social impulsivity (h2 =.35 +/-.11) and to each of the subscales, with no significant influence of maternal environment. There was a high genetic correlation between the impulsive approach and aggression subscales (rho =.78 +/-.12). CONCLUSIONS: This is the first study to demonstrate heritability of social impulsivity in adolescents and adults for any nonhuman primate species. The high genetic correlation suggests the same genes may influence variation in both impulsive approach and aggression. These results provide a promising basis for identification of susceptibility loci for impulsivity and aggressiveness.

Age Factors↗

PubMed2004

Major quantitative trait locus for resting heart rate maps to a region on chromosome 4.

Multiple studies have identified resting heart rate as a risk factor for cardiovascular disease independent of other cardiovascular disease risk factors (such as dyslipidemia and hypertension). Previous studies have examined heart rate in hypertensive individuals, but little is known about the genetic determination of resting heart rate in a normal population. Therefore, our objective was to perform a genome screen on a population containing normotensive and hypertensive individuals. We performed variance decomposition linkage analysis using maximum likelihood methods at approximately 10 cM intervals in 2209 individuals of predominantly North European ancestry. We estimated the heritability of resting heart rate to be 26% and obtained significant evidence of linkage (logarithm of the odds [LOD]=3.9) for resting heart rate on chromosome 4q. This signal is in the same region as a quantitative trait locus (QTL) for long QT syndrome 4 and a QTL for heart rate in rats. Within the 1-LOD unit support interval, there are 2 strong candidates: ankyrin-B and myozenin 2.

Animals↗

PubMed2004

Genetic determinants of obesity-related lipid traits.

In our ongoing effort to identify genes influencing the biological pathways that underlie the metabolic disturbances associated with obesity, we performed genome-wide scanning in 2,209 individuals distributed over 507 Caucasian families to localize quantitative trait loci (QTLs), which affect variation of plasma lipids. Pedigree-based analysis using a quantitative trait variance component linkage method that localized a QTL on chromosome 7q35-q36, which linked to variation in levels of plasma triglyceride [TG, logarithm of odds (LOD) score = 3.7] and was suggestive of linkage to LDL-cholesterol (LDL-C, LOD = 2.2). Covariates of the TG linkage included waist circumference, fasting insulin, and insulin:glucose, but not body mass index or hip circumference. Plasma HDL-cholesterol (HDL-C) levels were suggestively linked to a second QTL on chromosome 12p12.3 (LOD = 2.6). Five other QTLs with lower LOD scores were identified for plasma levels of LDL-C, HDL-C, and total cholesterol. These newly identified loci likely harbor genetic elements that influence traits underlying lipid adversities associated with obesity.

Blood Glucose↗

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

Nutrient selection and the genetics of complex phenotypes.

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Diet↗

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

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↗