Michael C. Mahaney

Genetic and environmental contributions to cardiovascular risk factors in Mexican Americans: The San Antonio Family Heart Study

BACKGROUND The familial aggregation of coronary heart disease can be in large part accounted for by a clustering of cardiovascular disease risk factors. To elucidate the determinants of cardiovascular disease, many epidemiological studies have focused on the behavioral and lifestyle determinants of these risk factors, whereas others have examined whether specific candidate genes influence quantitative variation in these phenotypes. METHODS AND RESULTS Among Mexican Americans from San Antonio (Tex), we quantified the relative contributions of both genetic and environmental influences to a large panel of cardiovascular risk factors, including serum levels of lipids, lipoproteins, glucose, hormones, adiposity, and blood pressure. Members of 42 extended families were studied, including 1236 first-, second-, and third-degree relatives of randomly ascertained probands and their spouses. In addition to the phenotypic assessments, information was obtained regarding usual dietary and physical activity patterns, medication use, smoking habits, alcohol consumption, and other lifestyle behaviors and medical factors. Maximum likelihood methods were used to partition the variance of each phenotype into components attributable to the measured covariates, additive genetic effects (heritability), household effects, and an unmeasured environmental residual. For the lipid and lipoprotein phenotypes, age, gender, and other environmental covariates accounted in general for < 15% of the total phenotypic variance, whereas genes accounted for 30% to 45% of the phenotypic variation. Similarly, genes accounted for 15% to 30% of the phenotypic variation in measures of glucose, hormones, adiposity, and blood pressure. CONCLUSIONS These results highlight the importance of considering genetic factors in studies of risk factors for cardiovascular disease.

Genetic variation in selenoprotein S influences inflammatory response

Chronic inflammation has a pathological role in many common diseases and is influenced by both genetic and environmental factors. Here we assess the role of genetic variation in selenoprotein S (SEPS1, also called SELS or SELENOS), a gene involved in stress response in the endoplasmic reticulum and inflammation control. After resequencing SEPS1, we genotyped 13 SNPs in 522 individuals from 92 families. As inflammation biomarkers, we measured plasma levels of IL-6, IL-1β and TNF-α. Bayesian quantitative trait nucleotide analysis identified associations between SEPS1 polymorphisms and all three proinflammatory cytokines. One promoter variant, −105G → A, showed strong evidence for an association with each cytokine (multivariate P = 0.0000002). Functional analysis of this polymorphism showed that the A variant significantly impaired SEPS1 expression after exposure to endoplasmic reticulum stress agents (P = 0.00006). Furthermore, suppression of SEPS1 by short interfering RNA in macrophage cells increased the release of IL-6 and TNF-α. To investigate further the significance of the observed associations, we genotyped −105G → A in 419 Mexican American individuals from 23 families for replication. This analysis confirmed a significant association with both TNF-α (P = 0.0049) and IL-1β (P = 0.0101). These results provide a direct mechanistic link between SEPS1 and the production of inflammatory cytokines and suggest that SEPS1 has a role in mediating inflammation.

Chemerin Is Associated with Metabolic Syndrome Phenotypes in a Mexican-American Population

CONTEXT Chemerin is a novel adipokine previously associated with metabolic syndrome phenotypes in a small sample of subjects from Mauritius. OBJECTIVE The aim of the study was to determine whether plasma chemerin levels were associated with metabolic syndrome phenotypes in a larger sample from a second, unrelated human population. DESIGN, SETTING, PATIENTS, AND INTERVENTION Plasma samples were obtained from the San Antonio Family Heart Study (SAFHS), a large family-based genetic epidemiological study including 1431 Mexican-American individuals. Individuals were randomly sampled without regard to phenotype or disease status. This sample is well-characterized for a variety of phenotypes related to the metabolic syndrome. MAIN OUTCOMES Plasma chemerin levels were measured by sandwich ELISA. Linear regression and correlation analyses were used to determine associations between plasma chemerin levels and metabolic syndrome phenotypes. RESULTS Circulating chemerin levels were significantly higher in nondiabetic subjects with body mass index (BMI) greater than 30 kg/m(2) compared with those with a BMI below 25 kg/m(2) (P < 0.0001). Plasma chemerin levels were significantly associated with metabolic syndrome-related parameters, including BMI (P < 0.0001), fasting serum insulin (P < 0.0001), triglycerides (P < 0.0001), and high-density lipoprotein cholesterol (P = 0.00014), independent of age and sex in nondiabetic subjects. CONCLUSION Circulating chemerin levels were associated with metabolic syndrome phenotypes in a second, unrelated human population. This replicated result using a large human sample suggests that chemerin may be involved in the development of the metabolic syndrome.

Plasma lipid profiling in a large population-based cohort

We have performed plasma lipid profiling using liquid chromatography electrospray ionization tandem mass spectrometry on a population cohort of more than 1,000 individuals. From 10 μl of plasma we were able to acquire comparative measures of 312 lipids across 23 lipid classes and subclasses including sphingolipids, phospholipids, glycerolipids, and cholesterol esters (CEs) in 20 min. Using linear and logistic regression, we identified statistically significant associations of lipid classes, subclasses, and individual lipid species with anthropometric and physiological measures. In addition to the expected associations of CEs and triacylglycerol with age, sex, and body mass index (BMI), ceramide was significantly higher in males and was independently associated with age and BMI. Associations were also observed for sphingomyelin with age but this lipid subclass was lower in males. Lysophospholipids were associated with age and higher in males, but showed a strong negative association with BMI. Many of these lipids have previously been associated with chronic diseases including cardiovascular disease and may mediate the interactions of age, sex, and obesity with disease risk.

Plasma Lipid Profiling Shows Similar Associations with Prediabetes and Type 2 Diabetes

The relationship between lipid metabolism with prediabetes (impaired fasting glucose and impaired glucose tolerance) and type 2 diabetes mellitus is poorly defined. We hypothesized that a lipidomic analysis of plasma lipids might improve the understanding of this relationship. We performed lipidomic analysis measuring 259 individual lipid species, including sphingolipids, phospholipids, glycerolipids and cholesterol esters, on fasting plasma from 117 type 2 diabetes, 64 prediabetes and 170 normal glucose tolerant participants in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab) then validated our findings on 1076 individuals from the San Antonio Family Heart Study (SAFHS). Logistic regression analysis of identified associations with type 2 diabetes (135 lipids) and prediabetes (134 lipids), after adjusting for multiple covariates. In addition to the expected associations with diacylglycerol, triacylglycerol and cholesterol esters, type 2 diabetes and prediabetes were positively associated with ceramide, and its precursor dihydroceramide, along with phosphatidylethanolamine, phosphatidylglycerol and phosphatidylinositol. Significant negative associations were observed with the ether-linked phospholipids alkylphosphatidylcholine and alkenylphosphatidylcholine. Most of the significant associations in the AusDiab cohort (90%) were subsequently validated in the SAFHS cohort. The aberration of the plasma lipidome associated with type 2 diabetes is clearly present in prediabetes, prior to the onset of type 2 diabetes. Lipid classes and species associated with type 2 diabetes provide support for a number of existing paradigms of dyslipidemia and suggest new avenues of investigation.

Plasma HDL Cholesterol, Triglycerides, and Adiposity A Quantitative Genetic Test of the Conjoint Trait Hypothesis in the San Antonio Family Heart Study

BACKGROUND The conjoint trait hypothesis proposes that combined low HDL cholesterol (HDL-C) and high triglyceride (TG) levels represent a single, inherited phenotype that adiposity may influence in an unspecified manner. We conducted formal statistical genetic tests of the conjoint trait hypothesis and the relation of the conjoint trait to adiposity using data for 569 subjects in 25 pedigrees from the San Antonio Family Heart Study. METHODS AND RESULTS We conducted multivariate genetic analyses to detect the effects of genes and environmental factors on variation in plasma concentrations of HDL-C and TG, fat mass (as percent body weight [FM%], determined by bioelectric impedance), and body mass index (BMI). We used maximum-likelihood methods to simultaneously estimate the phenotypic means and SDs, heritabilities (h2), effects of sex, age-by-sex, eight dietary and medical covariates, and genetic and environmental correlations. Likelihood ratio tests disclosed significant heritabilities (P < .001) for all traits (h2HDL-C = 0.55, h2TG = 0.53, h2FM% = 0.37, h2BMI = 0.44) but significant genetic correlations (P < .001), indicating pleiotropy, between two trait pairs only: HDL-C and TG (PG = -0.52) and fat mass and BMI (PG = 0.86). We obtained significant environmental correlations between all trait pairs except HDL-C and BMI (P > .05). CONCLUSIONS Both shared genes (pleiotropy) and shared environmental factors contribute to the commonly observed inverse phenotypic association between plasma levels of HDL-C and TG. Rather than low HDL-C and high TG being a single, genetically transmissible entity, it is the inverse relation between these two phenotypes throughout their normal ranges of variation as well as at the extremes that is influenced by shared genes and shared environments. However, common environmental factors, not shared genes, account for reported associations of plasma HDL-C and TG levels with measures of adiposity.

Effects of Genes, Sex, Age, and Activity on BMC, Bone Size, and Areal and Volumetric BMD

Quantitative genetic analyses of bone data for 710 inter‐related individuals 8–85 yr of age found high heritability estimates for BMC, bone area, and areal and volumetric BMD that varied across bone sites. Activity levels, especially time in moderate plus vigorous activity, had notable effects on bone. In some cases, these effects were age and sex specific.

Human Pedigree-Based Quantitative-Trait–Locus Mapping: Localization of Two Genes Influencing HDL-Cholesterol Metabolism

Common disorders with genetic susceptibilities involve the action of multiple genes interacting with each other and with environmental factors, making it difficult to localize the specific genetic loci responsible. An important route to the disentangling of this complex inheritance is through the study of normal physiological variation in quantitative risk factors that may underlie liability to disease. We present an analysis of HDL-cholesterol (HDL-C), which is inversely correlated with risk of heart disease. A variety of HDL subphenotypes were analyzed, including HDL particle-size classes and the concentrations and proportions of esterified and unesterified HDL-C. Results of a complete genomic screen in large, randomly ascertained pedigrees implicated two loci, one on chromosome 8 and the other on chromosome 15, that influence a component of HDL-C-namely, unesterified HDL2a-C. Multivariate analyses of multiple HDL phenotypes and simultaneous multilocus analysis of the quantitative-trait loci identified permit further characterization of the genetic effects on HDL-C. These analyses suggest that the action of the chromosome 8 locus is specific to unesterified cholesterol levels, whereas the chromosome 15 locus appears to influence both HDL-C concentration and distribution of cholesterol among HDL particle sizes.

Linkage of high-density lipoprotein-cholesterol concentrations to a locus on chromosome 9p in Mexican Americans.

High-density lipoproteins (HDLs) are anti-atherogenic lipoproteins that have a major role in transporting cholesterol from peripheral tissues to the liver, where it is removed. Epidemiologic studies have shown that low levels of high-density lipoprotein–cholesterol (HDL-C) are associated with an increased incidence of coronary heart disease and an increased mortality rate, indicating a protective role of high concentrations of HDL-C against atherogenesis and the development of coronary heart disease. HDL-C level is influenced by several genetic and nongenetic factors. Nongenetic factors include smoking, which has been shown to decrease the HDL-C level. Exercise and alcohol have been shown to increase HDL-C levels. Decreased HDL-C is often associated with other coronary heart disease risk factors such as obesity, hyperinsulinemia and insulin resistance, hypertriglyceridemia and hypertension. Although several genes have been identified for rare forms of dyslipidemia, the genes accounting for major variation in HDL-C levels have yet to be identified. Using a multipoint variance components linkage approach, we found strong evidence of linkage (lod score=3.4; P=0.00004) of a quantitative trait locus (QTL) for HDL-C level to a genetic location between markers D9S925 and D9S741 on chromosome 9p in Mexican Americans. A replication study in an independent set of Mexican American families confirmed the existence of a QTL on chromosome 9p.

Transcriptomic epidemiology of smoking: the effect of smoking on gene expression in lymphocytes

BackgroundThis investigation offers insights into system-wide pathological processes induced in response to cigarette smoke exposure by determining its influences at the gene expression level.MethodsWe obtained genome-wide quantitative transcriptional profiles from 1,240 individuals from the San Antonio Family Heart Study, including 297 current smokers. Using lymphocyte samples, we identified 20,413 transcripts with significantly detectable expression levels, including both known and predicted genes. Correlation between smoking and gene expression levels was determined using a regression model that allows for residual genetic effects.ResultsWith a conservative false-discovery rate of 5% we identified 323 unique genes (342 transcripts) whose expression levels were significantly correlated with smoking behavior. These genes showed significant over-representation within a range of functional categories that correspond well with known smoking-related pathologies, including immune response, cell death, cancer, natural killer cell signaling and xenobiotic metabolism.ConclusionsOur results indicate that not only individual genes but entire networks of gene interaction are influenced by cigarette smoking. This is the largest in vivo transcriptomic epidemiological study of smoking to date and reveals the significant and comprehensive influence of cigarette smoke, as an environmental variable, on the expression of genes. The central importance of this manuscript is to provide a summary of the relationships between gene expression and smoking in this exceptionally large cross-sectional data set.