Publications

OBJECTIVE: Genome-wide scans were conducted in search for genetic locations linked to energy expenditure and substrate oxidation in children.

DESIGN: Pedigreed data of 1030 Hispanic children and adolescents were from the Viva La Familia Study which was designed to investigate genetic and environmental risk factors for the development of obesity in Hispanic families. A respiratory calorimeter was used to measure 24-h total energy expenditure (TEE), basal metabolic rate (BMR), sleep metabolic rate (SMR), 24-h respiratory quotient (24RQ), basal metabolic respiratory quotient (BMRQ) and sleep respiratory quotient (SRQ). Protein, fat and carbohydrate oxidation (PROOX, FATOX and CHOOX, respectively) were also estimated. All participants were genotyped for 384 single tandem repeat markers spaced an average of 10 cM apart. Computer program SOLAR was used to perform the genetic linkage analyses.

RESULTS: Significant linkage for TEE was detected on chromosome 1 near marker D1S2841, with a logarithm of the odds (LOD) score of 4.0. SMR, BMRQ and PROOX were associated with loci on chromosome 18, 17 and 9, respectively, with LOD scores of 4.88, 3.17 and 4.55, respectively. A genome-wide scan of SMR per kg fat-free mass (SpFFM) peaked in the same region as SMR on chromosome 18 (LOD, 5.24). Suggestive linkage was observed for CHOOX and FATOX. Several candidate genes were found in the above chromosomal regions including leptin receptor (LEPR).

CONCLUSION: Regions on chromosomes 1, 9, 17 and 18 harbor genes affecting variation in energy expenditure and substrate oxidation in Hispanic children and adolescents.

Resistin has been associated with inflammation and risk for cardiovascular disease. We previously reported evidence of a QTL on chromosome 19p13 affecting the abundance of resistin (RETN) mRNA in the omental adipose tissue of baboons (L0D score 3.8). In this study, whole genome transcription levels were assessed in human lymphocyte samples from 1240 adults participating in the San Antonio Family Heart Study, using the Sentrix Human-6 Expression Beadchip. Lymphocytes were surveyed, as it has been proposed that their expression levels may reflect those in harder to ascertain tissues, such as adipose tissue, that are thought to be more directly relevant to disease procesn was conducted to detect loci affecting RETN mRNA levels. We obtained significant evidence for a QTL influencing the RETN expression (LOD score 10.7) on chromosome 19p. This region is orthologous/homologous to the region previously localized on baboon chromosome 19. The strongest positional candidate gene in this region is the structural gene for resistin, itself. We also found evidence for a QTL influencing resistin protein levels (LOD score 5.3) on chromosome 14q. This differs from our previously reported QTL on chromosome 18 in baboons. The different QTLs for circulating protein suggests that post-translational processing and turnover may be influenced by different or multiple genes in baboons and humans. The parallel findings of a cis-eQTL for RETN mRNA in baboon omental tissue and human lymphocytes lends support to the strategy of using lymphocyte gene expression levels as a surrogate for gene expression levels in other tissues.

BACKGROUND: The pathogenesis of atherosclerosis involves both hemostatic and inflammatory mechanisms. Fibrinogen is associated with both risk of thrombosis and inflammation. A recent meta-analysis showed that risk of coronary heart disease may increase 1.8 fold for 1 g/L of increased fibrinogen, independent of traditional risk factors. It is known that fibrinogen levels may be influenced by demographic, environmental and genetic factors. Epidemiologic and candidate gene studies are available; but few genome-wide linkage studies have been conducted, particularly in minority populations. The Strong Heart Study has demonstrated an increased incidence of cardiovascular disease in the American Indian population, and therefore represents an important source for genetic-epidemiological investigations.

METHODS: The Strong Heart Family Study enrolled over 3,600 American Indian participants in large, multi-generational families, ascertained from an ongoing population-based study in the same communities. Fibrinogen was determined using standard technique in a central laboratory and extensive additional phenotypic measures were obtained. Participants were genotyped for 382 short tandem repeat markers distributed throughout the genome; and results were analyzed using a variance decomposition method, as implemented in the SOLAR 2.0 program.

RESULTS: Data from 3535 participants were included and after step-wise, linear regression analysis, two models were selected for investigation. Basic demographic adjustments constituted model 1, while model 2 considered waist circumference, diabetes mellitus and postmenopausal status as additional covariates. Five LOD scores between 1.82 and 3.02 were identified, with the maximally adjusted model showing the highest score on chromosome 7 at 28 cM. Genes for two key components of the inflammatory response, i.e. interleukin-6 and "signal transducer and activator of transcription 3" (STAT3), were identified within 2 and 8 Mb of this 1 LOD drop interval respectively. A LOD score of 1.82 on chromosome 17 between 68 and 93 cM is supported by reports from two other populations with LOD scores of 1.4 and 1.95.

CONCLUSION: In a minority population with a high prevalence of cardiovascular disease, strong evidence for a novel genetic determinant of fibrinogen levels is found on chromosome 7 at 28 cM. Four other loci, some of which have been suggested by previous studies, were also identified.

OBJECTIVE: Deficits in neurocognitive function have been demonstrated in individuals with schizophrenia and in the unaffected family members of these individuals. Genetic studies of such complementary traits, along with traditional analyses of diagnosis, may help to elucidate the biological pathways underlying familial liability to schizophrenia and related disorders. The authors conducted a multiplex, multigenerational family study using a genome-wide screen for schizophrenia and related neurocognitive phenotypes.

METHOD: Participants were 1) 676 European American individuals from 43 families, ascertained through an individual with schizophrenia, and 2) 236 healthy comparison subjects. Participants were evaluated clinically and examined through the use of a computerized neurocognitive test battery that provided measures of accuracy and speed on the cognitive domains of abstraction and mental flexibility; attention; verbal, face, and spatial memory; language and reasoning; spatial and emotion processing; and sensorimotor dexterity. A genome-wide linkage screen was also performed. Healthy comparison subjects were included in order to obtain normative phenotypic data but were not genotyped.

RESULTS: Significant evidence for linkage of schizophrenia to chromosome 19q was observed. Analysis of cognitive traits revealed significant linkage to chromosome 5q for the domains of abstraction and mental flexibility. A variety of other neurocognitive traits also showed nominal evidence of linkage to the 5q region. Joint analyses with diagnosis suggested that this quantitative trait locus may also influence schizophrenia.

CONCLUSIONS: Although chromosome 5 has been implicated in previous linkage studies of schizophrenia, the identification of the chromosome 19 quantitative trait locus is a novel finding. The identification of the chromosome 5 quantitative trait locus through linkage to neurocognitive phenotypes in the present study may inform functional hypotheses pertaining to how genotypes are connected to disease.

The use of alcohol and tobacco is highly prevalent. Studying the rate of consumption in a non-selected population could contribute to the elucidation of pathways involved in addiction or to the development of prevention programs. The San Antonio Family Heart Study has approximately 1,400 members with longitudinal data and did not select the proband with regard to exposure status. The goal of this study was to perform genome-wide linkage analysis of the rate of alcohol and cigarette consumption in a "normal" population. We used SOLAR to perform variance-components based analysis of the transformed maximal rate of consumption. Despite estimated heritabilities of 0.52 (P < 0.001) for cigarette and 0.39 (P < 0.001) for alcohol consumption, univariate linkage analyses produced only suggestive LOD scores, however the second suggestive linkage peak for the alcohol phenotype was present at 148 cM on chromosome 10, in the exact vicinity of the peak for the cigarette phenotype. In a bivariate analyses, the environmental correlation between alcohol and cigarette consumption was not significantly different from zero (rho(e) = -0.15, P = 0.18) and the overall genetic correlation was not different from zero (rho(g) = 0.16, P = 0.34). The results from the bivariate linkage analysis found a maximum LOD score of 3.82 (genome-wide P = 0.0054) at 151 cM on chromosome 10, at the location of the overlapping peaks from the univariate analyses.

BACKGROUND: Chronic kidney disease (CKD) phenotypes such as albuminuria measured by urinary albumin creatinine ratio (ACR), elevated serum creatinine (SrCr) and/or decreased creatinine clearance (CrCl) and glomerular filtration rate (eGFR) are major risk factors for renal and cardiovascular diseases. Epidemiological studies have reported that CKD phenotypes cluster in families suggesting a genetic predisposition. However, studies reporting chromosomal regions influencing CKD are very limited. Therefore, the purpose of this study is to identify susceptible chromosomal regions for CKD phenotypes in Mexican American families enrolled in the San Antonio Family Heart Study (SAFHS).

METHODS: We used the variance components decomposition approach (implemented in the software package SOLAR) to perform linkage analysis on 848 participants from 26 families. A total of 417 microsatellite markers were genotyped at an average interval of 10 cM spanning 22 autosomal chromosomes.

RESULTS: All phenotypes were measured by standard procedures. Mean +/- SD values of ACR, SrCr, CrCl and eGFR were 0.06 +/- 0.38, 0.85 +/- 0.72 mg/dl, 129.85 +/- 50.37 ml/min and 99.18 +/- 25.69 ml/min/1.73 m(2) body surface area, respectively. All four CKD phenotypes exhibited significant heritabilities (P < 0.0001). A genome-wide scan showed linkage on chromosome 2p25 for SrCr, CrCl and eGFR. Significant linkage was also detected on chromosome 9q21 for eGFR [logarithm of the odds (LOD) score = 3.87, P = 0.00005] and SrCr (LOD score = 2.6, P = 0.00026). ACR revealed suggestive evidence for linkage to a region on chromosome 20q12 (LOD score = 2.93, P = 0.00020).

CONCLUSION: Findings indicate that chromosomal regions 2p25, 9q21 and 20q12 may have functional relevance to CKD phenotypes in Mexican Americans.

BACKGROUND: Body fat mass distribution and deposition are determined by multiple environmental and genetic factors. Obesity is associated with insulin resistance, hyperinsulinemia, and type 2 diabetes. We previously identified evidence for genotype-by-diabetes interaction on obesity traits in Strong Heart Family Study (SHFS) participants. To localize these genetic effects, we conducted genome-wide linkage scans of obesity traits in individuals with and without type 2 diabetes, and in the combined sample while modeling interaction with diabetes using maximum likelihood methods (SOLAR 2.1.4).

METHODS: SHFS recruited American Indians from Arizona, North and South Dakota, and Oklahoma. Anthropometric measures and diabetes status were obtained during a clinic visit. Marker allele frequencies were derived using maximum likelihood methods estimated from all individuals and multipoint identity by descent sharing was estimated using Loki. We used variance component linkage analysis to localize quantitative trait loci (QTLs) influencing obesity traits. We tested for evidence of additive and QTL-specific genotype-by-diabetes interactions using the regions identified in the diabetes-stratified analyses.

RESULTS: Among 245 diabetic and 704 non-diabetic American Indian individuals, we detected significant additive gene-by-diabetes interaction for weight and BMI (P < 0.02). In analysis accounting for QTL-specific interaction (P < 0.001), we detected a QTL for weight on chromosome 1 at 242 cM (LOD = 3.7). This chromosome region harbors the adiponectin receptor 1 gene, which has been previously associated with obesity.

CONCLUSION: These results suggest distinct genetic effects on body mass in individuals with diabetes compared to those without diabetes, and a possible role for one or more genes on chromosome 1 in the pathogenesis of obesity.

Cytokines are considered to be involved in obesity-related metabolic diseases. Study objectives are to determine the heritability of circulating cytokine levels, to investigate pleiotropy between cytokines and obesity traits, and to present genome scan results for cytokines in 1030 Hispanic children enrolled in VIVA LA FAMILIA Study. Cytokine phenotypes included monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor-alpha (TNF-alpha), leptin, adiponectin, soluble intercellular adhesion molecule-1 (sICAM-1), transforming growth factor beta 1 (TGF-beta1), C-reactive protein (CRP), regulated upon activation, normal T-cell expressed and secreted (RANTES) and eotaxin. Obesity-related phenotypes included body mass index (BMI), fat mass (FM), truncal FM and fasting serum insulin. Heritabilities ranged from 0.33 to 0.97. Pleiotropy was observed between cytokines and obesity traits. Positive genetic correlations were seen between CRP, leptin, MCP-1 and obesity traits, and negative genetic correlations with adiponectin, ICAM-1 and TGF-beta1. Genome-wide scan of sICAM-1 mapped to chromosome 3 (LOD=3.74) between markers D3S1580 and D3S1601, which flanks the adiponectin gene (ADIPOQ). Suggestive linkage signals were found in other chromosomal regions for other cytokines. In summary, significant heritabilities for circulating cytokines, pleiotropy between cytokines and obesity traits, and linkage for sICAM-1 on chromosome 3q substantiate a genetic contribution to circulating cytokine levels in Hispanic children.

OBJECTIVE: We describe the methodology used to analyze multiple transcripts using microarray techniques in simultaneous biopsies of muscle, adipose tissue and lymphocytes obtained from the same individual as part of the standard protocol of the Genetics of Metabolic Diseases in Mexico: GEMM Family Study.

METHODS: We recruited 4 healthy male subjects with BM1 20-41, who signed an informed consent letter. Subjects participated in a clinical examination that included anthropometric and body composition measurements, muscle biopsies (vastus lateralis) subcutaneous fat biopsies anda blood draw. All samples provided sufficient amplified RNA for microarray analysis. Total RNA was extracted from the biopsy samples and amplified for analysis.

RESULTS: Of the 48,687 transcript targets queried, 39.4% were detectable in a least one of the studied tissues. Leptin was not detectable in lymphocytes, weakly expressed in muscle, but overexpressed and highly correlated with BMI in subcutaneous fat. Another example was GLUT4, which was detectable only in muscle and not correlated with BMI. Expression level concordance was 0.7 (p< 0.001) for the three tissues studied.

CONCLUSIONS: We demonstrated the feasibility of carrying out simultaneous analysis of gene expression in multiple tissues, concordance of genetic expression in different tissues, and obtained confidence that this method corroborates the expected biological relationships among LEPand GLUT4. TheGEMM study will provide a broad and valuable overview on metabolic diseases, including obesity and type 2 diabetes.

UNLABELLED: The genetic contribution to age-related bone loss is not well understood. We estimated that genes accounted for 25-45% of variation in 5-year change in bone mineral density in men and women. An autosome-wide linkage scan yielded no significant evidence for chromosomal regions implicated in bone loss.

INTRODUCTION: The contribution of genetics to acquisition of peak bone mass is well documented, but little is known about the influence of genes on subsequent bone loss with age. We therefore measured 5-year change in bone mineral density (BMD) in 300 Mexican Americans (>45 years of age) from the San Antonio Family Osteoporosis Study to identify genetic factors influencing bone loss.

METHODS: Annualized change in BMD was calculated from measurements taken 5.5 years apart. Heritability (h(2)) of BMD change was estimated using variance components methods and autosome-wide linkage analysis was carried out using 460 microsatellite markers at a mean 7.6 cM interval density.

RESULTS: Rate of BMD change was heritable at the forearm (h(2) = 0.31, p = 0.021), hip (h(2) = 0.44, p = 0.017), spine (h(2) = 0.42, p = 0.005), but not whole body (h(2) = 0.18, p = 0.123). Covariates associated with rapid bone loss (advanced age, baseline BMD, female sex, low baseline weight, postmenopausal status, and interim weight loss) accounted for 10% to 28% of trait variation. No significant evidence of linkage was observed at any skeletal site.

CONCLUSIONS: This is one of the first studies to report significant heritability of BMD change for weight-bearing and non-weight-bearing bones in an unselected population and the first linkage scan for change in BMD.