Publications

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.

American Indians have a disproportionately high rate of kidney disease likely due to a combination of environmental and genetic factors. We performed a genome wide scan of estimated glomerular filtration rate in 3665 participants of the Strong Heart Family Study to localize genes influencing kidney disease risk factors. The participants were men and women from 13 American Indian tribes recruited from 3 centers located in Arizona, the Dakotas and Oklahoma. Multipoint variance component linkage analysis was performed for each center and on the entire cohort after controlling for center effects. Modeling strategies that incorporated age, gender and interaction terms (model 1) and another that also controlled for diabetes mellitus, systolic and diastolic blood pressure, body mass index, low density and high density lipoproteins, triglycerides and smoking status (model 2) were used. Significant evidence for linkage in the Arizona group was found on chromosome 12p12.2 at 39cM (nearest marker D12S310) using model 1. Additional loci with very suggestive evidence for linkage were detected at 1p36.31 for all groups using both models and at 2q33.3 and 9q34.2 for the Dakotas group each using model 1. No significant evidence for additive interaction with diabetes, hypertension or obesity was noted. This evidence for linkage of a quantitative trait locus influencing estimated glomerular filtration rate to a region of chromosome 12p in a large cohort of American Indians will be worth studying in more detail in the future.

Growth is a complex process composed of distinct phases over the course of childhood. Although the pubertal growth spurt has received the most attention from auxologists and pediatricians, the midchildhood growth spurt has been less well studied. The midchildhood growth spurt refers to a relatively small increase in growth velocity observed in some, but not necessarily all, children in early to middle childhood. If present, the midchildhood growth spurt typically occurs sometime between the ages of 4 and 8 years, well before the onset of the far more pronounced pubertal growth spurt. In this study we used a triple logistic curve-fitting method to fit individual growth curves to serial stature data from 579 healthy participants in the Fels Longitudinal Study, 479 of whom have been genotyped for about 400 short tandem repeat (STR) markers spanning the genome. We categorized individuals according to the presence or absence of a midchildhood growth spurt and then conducted heritability and genome-wide linkage analyses on the dichotomous trait. In the total sample of 579 individuals, 336 (58%) were found to have evidence of having had a midchildhood growth spurt. There was a marked sex difference in presence of the midchildhood growth spurt, however, with 232 of the 293 males (79%) having had a midchildhood growth spurt but just 104 of the 286 females (36%) having had one. Presence of a midchildhood growth spurt was found to have a significant heritability of 0.37 +/- 0.14 (p = 0.003). Two quantitative trait loci with suggestive LOD scores were found: one at 12 cM on chromosome 17p13.2 (LOD = 2.13) between markers D17S831 and D17S938 and one at 85 cM on chromosome 12q14 (LOD = 2.06) between markers D12S83 and D12S326.