Biomedical subjects

Nicholas J Schork

Publications and source records attributed to Nicholas J Schork.

At least 19 recordsLinked to original sources

PubMed2025

Heterogeneity Analysis of Associations Involving the Large-Scale Online MindCrowd Survey Memory Test.

INTRODUCTION: Alzheimer's disease and related disorders (ADRDs), as well as general age-related cognitive decline, are known to be multifactorial with heterogeneous etiologies. Identifying and accommodating heterogeneity in any one ADRD-related data set can be pursued using different analytical techniques, each with different assumptions or purposes. For example, whereas a great deal of research has explored clustering individuals or variables that exhibit greater similarity in some way, little research has explored evidence for heterogeneity in the relationships between relevant outcomes, such as performance on a memory test, and risk factors such as environmental exposures, behaviors, or genetic factors among individuals. METHODS: We explored evidence of heterogeneity in the relationships between ability on a memory test, specifically the paired associate learning (PAL) test, and multiple social and demographic risk factors using the large MindCrowd study database (n > 90,000 individuals). We focused on mixtures of regression models but compared models assuming many interaction effects among independent variables as well as random effects. RESULTS: We ultimately find substantial evidence for heterogeneity and offer an intuitive explanation for it involving individual motivation for participating in the MindCrowd study. Basically, we argue that our mixture of regression model analysis results suggest that a smaller group of individuals (∼16%) likely participated in the MindCrowd study out of a concern for their cognitive abilities as they exhibit stronger and statistically significant negative associations between age, number of medications they are on, some ancestries, and the number correct on the PAL test. They also exhibit stronger positive associations between education and PAL test results in a dose-dependent manner suggesting that a "cognitive reserve" associated with greater education could benefit them. Analysis models assuming interaction terms and random effects suggested that other forms of heterogeneity in the relationships between variables exist in the data set, but their results do not carry with them the same intuitive explanation that the results of the mixture model analyses do. CONCLUSION: We find evidence for heterogeneity in the relationships between social and demographic variables and PAL test results in the large MindCrowd study database. This heterogeneity is likely due to individuals with and without concerns for their cognitive abilities participating in the study. We also find other types of evidence in the data set. Our results should motivate caution in the use of large epidemiological study or survey-oriented data sets to build predictive models of clinical or subclinical pathologies without exploring or accommodating heterogeneity. Our results also suggest that one should include questions about motivation to participate in large epidemiological studies since different motivations may impact important relationships between independent and dependent variables.

Humans↗

PubMed2007

Catecholamine release-inhibitory peptide catestatin (chromogranin A(352-372)): naturally occurring amino acid variant Gly364Ser causes profound changes in human autonomic activity and alters risk for hypertension.

BACKGROUND: Chromogranin A, coreleased with catecholamines by exocytosis, is cleaved to the catecholamine release-inhibitory fragment catestatin. We identified a natural nonsynonymous variant of catestatin, Gly364Ser, that alters human autonomic function and blood pressure. METHODS AND RESULTS: Gly364Ser heterozygotes and controls underwent physiological and biochemical phenotyping, including catecholamine production, chromogranin A precursor, and its catestatin product. Case-control studies replicated effects of the gene on blood pressure in the population. Gly364Ser displayed diminished inhibition of catecholamine secretion from cultured neurons. Gly/Ser heterozygotes displayed increased baroreceptor slope during upward deflections (by approximately 47%) and downward deflections (by approximately 44%), increased cardiac parasympathetic index (by approximately 2.4-fold), and decreased cardiac sympathetic index (by approximately 26%). Renal norepinephrine excretion was diminished by approximately 26% and epinephrine excretion by approximately 34% in Gly/Ser heterozygotes. The coalescent dated emergence of the variant to approximately 70,000 years ago. Gly364Ser was in linkage disequilibrium with 1 major Chromogranin A promoter haplotype, although promoter haplotypes did not predict autonomic phenotypes. The 364Ser variant was associated with lower diastolic blood pressure in 2 independent/confirmatory groups of patients with hypertension; genotype groups differed by approximately 5 to 6 mm Hg, and the polymorphism accounted for approximately 1.8% of population diastolic blood pressure variance, although a significant gene-by-sex interaction existed, with an enhanced effect in men. CONCLUSIONS: The catestatin Gly364Ser variant causes profound changes in human autonomic activity, both parasympathetic and sympathetic, and seems to reduce risk of developing hypertension, especially in men. A model for catestatin action in the baroreceptor center of the nucleus of the tractus solitarius accounts for these actions.

Amino Acid Sequence↗

PubMed2007

Renal albumin excretion: twin studies identify influences of heredity, environment, and adrenergic pathway polymorphism.

Albumin excretion marks early glomerular injury in hypertension. This study investigated heritability of albumin excretion in twin pairs and its genetic determination by adrenergic pathway polymorphism. Genetic associations used single nucleotide polymorphisms at adrenergic pathway loci spanning catecholamine biosynthesis, storage, catabolism, receptor action, and postreceptor signal transduction. We studied 134 single nucleotide polymorphisms at 46 loci for a total of >51,000 genotypes. Albumin excretion heritability was 45.2+/-7.4% (P=2x10(-7)), and the phenotype aggregated significantly with adrenergic, renal, metabolic, and hemodynamic traits. In the adrenergic system, excretions of both norepinephrine and epinephrine correlated with albumin. In the kidney, albumin excretion correlated with glomerular and tubular traits (Na(+) and K(+) excretion; fractional excretion of Na(+) and Li(+)). Albumin excretion shared genetic determination (genetic covariance) with epinephrine excretion, and environmental determination with glomerular filtration rate and electrolyte intake/excretion. Albumin excretion associated with polymorphisms at multiple points in the adrenergic pathway: catecholamine biosynthesis (tyrosine hydroxylase), catabolism (monoamine oxidase A), storage/release (chromogranin A), receptor target (dopamine D1 receptor), and postreceptor signal transduction (sorting nexin 13 and rho kinase). Epistasis (gene-by-gene interaction) occurred between alleles at rho kinase, tyrosine hydroxylase, chromogranin A, and sorting nexin 13. Dopamine D1 receptor polymorphism showed pleiotropic effects on both albumin and dopamine excretion. These studies establish new roles for heredity and environment in albumin excretion. Urinary excretions of albumin and catecholamines are highly heritable, and their parallel suggests adrenergic mediation of early glomerular permeability alterations. Albumin excretion is influenced by multiple adrenergic pathway genes and is, thus, polygenic. Such functional links between adrenergic activity and glomerular injury suggest novel approaches to its prediction, prevention, diagnosis, and treatment.

Adolescent↗

PubMed2007

Successful aging: from phenotype to genotype.

Despite worldwide interest in the increasing human "healthspan," inadequate experimental attention has been dedicated to identifying genetic influences on successful aging beyond those that influence longevity alone. Although it is an under-studied topic, some promising leads have emerged from the existing genetic studies of successful aging. Here we describe the results of a systematic review of published family, twin, linkage, and association studies of successful aging that evaluated at least one other characteristic of healthy aging in addition to longevity. We identified 29 studies that met our criteria. Although methodological inconsistencies in sampling and phenotypes were frequent, we found evidence for a substantial genetic contribution to successful aging, including several specific genes (APOE, GSTT1, IL6, IL10, PON1, and SIRT3) that are promising candidates for future molecular genetic research. In addition to reviewing this literature, we provide recommendations for advancing our understanding of the genetic basis of successful aging.

Aged↗

PubMed2007

C-reactive protein, an 'intermediate phenotype' for inflammation: human twin studies reveal heritability, association with blood pressure and the metabolic syndrome, and the influence of common polymorphism at catecholaminergic/beta-adrenergic pathway loci.

BACKGROUND: C-reactive protein (CRP) both reflects and participates in inflammation, and its circulating concentration marks cardiovascular risk. Here we sought to understand the role of heredity in determining CRP secretion. METHODS: CRP, as well as multiple facets of the metabolic syndrome, were measured in a series of 229 twins, both monozygotic (MZ) and dizygotic (DZ), to estimate trait heritability (h2). Single nucleotide polymorphism (SNP) genotyping was done at adrenergic pathway loci. Haplotypes were inferred from genotypes by likelihood methods. Association of CRP with hypertension and the metabolic syndrome was studied in a larger series of 732 individuals, including 79 with hypertension. RESULTS: MZ and DZ twin variance components indicated substantial h2 for CRP, at approximately 56 +/- 7% (P < 0.001). CRP was significantly associated (P < 0.05) with multiple features of the metabolic syndrome in twins, including body mass index (BMI), blood pressure (BP), leptin and lipids. In established hypertension, elevated CRP was associated with increased BP, BMI, insulin, HOMA (index of insulin resistance), leptin, triglycerides and norepinephrine. Twin correlations indicated pleiotropy (shared genetic determination) for CRP with BMI (P = 0.0002), leptin (P < 0.001), triglycerides (P = 0.002) and systolic blood pressure (SBP) (P = 0.042). Approximately 9800 genotypes (43 genetic variants at 17 loci) were scored within catecholaminergic pathways: biosynthetic, receptor and signal transduction. Plasma CRP concentration in twins was predicted by polymorphisms at three loci in physiological series within the catecholamine biosynthetic/beta-adrenergic pathway: TH (tyrosine hydroxylase), ADRB1 (beta1-adrenergic receptor) and ADRB2 (beta2-adrenergic receptor). In the TH promoter, common allelic variation accounted for up to approximately 6.6% of CRP inter-individual variance. At ADRB1, variation at Gly389Arg predicted approximately 2.8% of CRP, while ADRB2 promoter variants T-47C and T-20C also contributed. Particular haplotypes and diplotypes at TH and ADRB1 also predicted CRP, though typically no better than single SNPs alone. Epistasis (gene-by-gene interaction) was demonstrated for particular combinations of TH and ADRB2 alleles, consistent with their actions in a pathway in series. In an illustration of pleiotropy, not only CRP but also plasma triglycerides were predicted by polymorphisms at TH (P = 0.0053) and ADRB2 (P = 0.027). CONCLUSIONS: CRP secretion is substantially heritable in humans, demonstrating pleiotropy (shared genetic determination) with other features of the metabolic syndrome, such as BMI, triglycerides or BP. Multiple, common genetic variants in the catecholaminergic/beta-adrenergic pathway contribute to CRP, and these variants (especially at TH and ADRB2) seem to interact (epistasis) to influence the trait. The results uncover novel pathophysiological links between the adrenergic system and inflammation, and suggest new strategies to probe the role and actions of inflammation within this setting.

Adult↗

PubMed2006

Multiple ADH genes modulate risk for drug dependence in both African- and European-Americans.

Drug dependence (DD) is commonly co-morbid with alcohol dependence (AD). Many studies have also shown common genetic risk factors for these disorders. We previously reported associations of AD with seven alcohol dehydrogenase (ADH) genes. The present study examines the relationship between these genes and DD. We genotyped 16 markers within the ADH gene cluster and 38 unlinked ancestry-informative markers in a case-control sample of 718 individuals. All markers were consistent with Hardy-Weinberg equilibrium in controls, but some markers showed Hardy-Weinberg disequilibrium in cases (minimal P = 0.002). Genotypes of many markers were associated with DD, both before and after controlling for admixture effects (minimal P < 1.0 x 10(-6)). Diplotype trend regression analysis showed that ADH5 and ADH6 genotypes, and diplotypes at ADH1A, ADH1B, ADH1C and ADH7 (minimal P = 0.002), were associated with DD in European-Americans and/or African-Americans. This first report of an allelic association of these loci with DD provides new insight into the mechanism of genetic risk for DD. These findings, obtained using a series of powerful and reliable analytic methods, may also help to explain the high rate of co-morbidity between AD and DD.

Adult↗

PubMed2006

Population-based sample reveals gene-gender interactions in blood pressure in White Americans.

The influence of genetic contributors, such as common single nucleotide polymorphisms, on blood pressure and essential hypertension may vary with the gender. We used the power of a large, community-based sample to probe whether gender interacts with genes in contributing to extremes of blood pressure in 611 male and 656 female age-matched white Americans within the top and bottom 5th percentiles of blood pressure among >53 000 people in a health maintenance program. This approach has >90% statistical power to detect genes contributing as little as 3% to trait (blood pressure) variation. We scored approximately 60 000 genotypes in the subjects: 48 single nucleotide polymorphisms at 33 autosomal and 2 X-linked genes in adrenergic and renal pathways that regulate blood pressure. Six individual variants significantly affected blood pressure and demonstrated gene-by-gender interaction, yielding different effects of the single nucleotide polymorphism on blood pressure in males and females. In females, polymorphisms at beta(1)-adrenergic receptor and alpha(2A)-adrenergic receptor contributed to blood pressure, whereas in men, polymorphisms at beta(2)-adrenergic receptor and angiotensinogen were associated. An alpha(2A)-adrenergic receptor haplotype influenced blood pressure in women, whereas 2 angiotensinogen haplotypes were associated in men. We also detected gene-by-gene, gender-specific interactions (epistasis) in pathophysiological pathways. This study reveals gender-specific effects of single nucleotide polymorphisms, haplotypes, and gene-by-gene interactions that determine blood pressure in white Americans. Such genetic variants may define genetically and etiologically distinct subgroups of men and women with essential hypertension and may have implications for rational treatment selection.

Adult↗

PubMed2006

Multivariate regression analysis of distance matrices for testing associations between gene expression patterns and related variables.

A fundamental step in the analysis of gene expression and other high-dimensional genomic data is the calculation of the similarity or distance between pairs of individual samples in a study. If one has collected N total samples and assayed the expression level of G genes on those samples, then an N x N similarity matrix can be formed that reflects the correlation or similarity of the samples with respect to the expression values over the G genes. This matrix can then be examined for patterns via standard data reduction and cluster analysis techniques. We consider an alternative to conventional data reduction and cluster analyses of similarity matrices that is rooted in traditional linear models. This analysis method allows predictor variables collected on the samples to be related to variation in the pairwise similarity/distance values reflected in the matrix. The proposed multivariate method avoids the need for reducing the dimensions of a similarity matrix, can be used to assess relationships between the genes used to construct the matrix and additional information collected on the samples under study, and can be used to analyze individual genes or groups of genes identified in different ways. The technique can be used with any high-dimensional assay or data type and is ideally suited for testing subsets of genes defined by their participation in a biochemical pathway or other a priori grouping. We showcase the methodology using three published gene expression data sets.

Animals↗

PubMed2006

Deconstructing schizophrenia: an overview of the use of endophenotypes in order to understand a complex disorder.

The genetics of schizophrenia has been approached utilizing a variety of methods. One emerging strategy is the use of endophenotypes in order to understand and identify the functional importance of genetically transmitted, brain-based deficits across schizophrenia kindreds. The endophenotype strategy is a topic of this issue of Schizophrenia Bulletin. Endophenotypes are quantitative, heritable, trait-related deficits typically assessed by laboratory-based methods rather than clinical observation. Endophenotypes are seen as closer to genetic variation than are clinical symptoms of schizophrenia, and are therefore closely linked to heritable risk factors. There has been a broad expansion of opportunities available to psychiatric neuroscientists who use the endophenotype strategy to understand the genetic basis of schizophrenia. In this context, genetic variation such as single nucleotide polymorphisms (SNPs) induces abnormalities in endophenotypic domains such as neurocognition, neurodevelopment, metabolism, and neurophysiology. This article discusses the challenges that abound in genetic research of schizophrenia, including issues in ascertainment, epistasis, ethnic diversity, and the potentially normalizing effects of second-generation antipsychotic medications on neurocognitive and neurophysiological measures. Robust strategies for meeting these challenges are discussed in this review and the subsequent articles in this issue. This article summarizes conceptual advances and progress in the measurement and use of endophenotypes in schizophrenia that form the basis of the multisite National Institute of Mental Health Consortium on the Genetics of Schizophrenia. The endophenotype strategy offers powerful and exciting opportunities to understand the genetically conferred neurobiological vulnerabilities and possible new strong inference and molecularly based treatments for schizophrenia.

Antipsychotic Agents↗

PubMed2006

The Consortium on the Genetics of Endophenotypes in Schizophrenia: model recruitment, assessment, and endophenotyping methods for a multisite collaboration.

BACKGROUND: The Consortium on the Genetics of Schizophrenia (COGS) is an ongoing, National Institute of Mental Health-funded, 7-site collaboration investigating the occurrence and genetic architecture of quantitative endophenotypes related to schizophrenia. The purpose of this article is to provide a description of the COGS structure and methods, including participant recruitment and assessment. METHODS: The hypothesis-driven recruitment strategy ascertains families that include a proband with a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnosis of schizophrenia, and at least one unaffected full sibling available for genotyping and endophenotyping, along with parents available for genotyping and (optional depending on age) endophenotyping. The family structure is selected to provide contrast in quantitative endophenotypic traits and thus to maximize the power of the planned genetic analyses. Probands are recruited from many sources including clinician referrals, local National Alliance for the Mentally Ill chapters, and advertising via the media. All participants undergo a standardized protocol that includes clinical characterization, a blood draw for genotyping, and endophenotype assessments (P50 suppression, prepulse inhibition, antisaccade performance, continuous performance tasks, letter-number span, verbal memory, and a computerized neurocognitive battery). Investigators participate in weekly teleconferences to coordinate and evaluate recruitment, clinical assessment, endophenotyping, and continuous quality control of data gathering and analyses. Data integrity is maintained through use of a highly quality-assured, centralized web-based database. RESULTS: As of February 2006, 355 families have been enrolled and 688 participants have been endophenotyped, including schizophrenia probands (n = 154, M:F = 110:44), first-degree biological relatives (n = 343, M:F = 151:192), and community comparison subjects (n = 191, M:F = 81:110). DISCUSSION: Successful multisite genetics collaborations must institute standardized methodological criteria for assessment and recruitment that are clearly defined, well communicated, and uniformly applied. In parallel, studies utilizing endophenotypes require strict adherence to criteria for cross-site data acquisition, equipment calibration and testing and software equivalence, and continuous quality assurance for many measures obtained across sites. This report describes methods and presents the structure of the COGS as a model of multisite endophenotype genetic studies. It also provides demographic information after the first 2 years of data collection on a sample for whom the behavioral data and genetics of endophenotype performance will be fully characterized in future articles. Some issues discussed in the reviews that follow reflect the challenges of evaluating endophenotypes in studies of the genetic architecture of endophenotypes in schizophrenia.

Cooperative Behavior↗

PubMed2006

Statistical genetics concepts and approaches in schizophrenia and related neuropsychiatric research.

Statistical genetics is a research field that focuses on mathematical models and statistical inference methodologies that relate genetic variations (ie, naturally occurring human DNA sequence variations or "polymorphisms") to particular traits or diseases (phenotypes) usually from data collected on large samples of families or individuals. The ultimate goal of such analysis is the identification of genes and genetic variations that influence disease susceptibility. Although of extreme interest and importance, the fact that many genes and environmental factors contribute to neuropsychiatric diseases of public health importance (eg, schizophrenia, bipolar disorder, and depression) complicates relevant studies and suggests that very sophisticated mathematical and statistical modeling may be required. In addition, large-scale contemporary human DNA sequencing and related projects, such as the Human Genome Project and the International HapMap Project, as well as the development of high-throughput DNA sequencing and genotyping technologies have provided statistical geneticists with a great deal of very relevant and appropriate information and resources. Unfortunately, the use of these resources and their interpretation are not straightforward when applied to complex, multifactorial diseases such as schizophrenia. In this brief and largely nonmathematical review of the field of statistical genetics, we describe many of the main concepts, definitions, and issues that motivate contemporary research. We also provide a discussion of the most pressing contemporary problems that demand further research if progress is to be made in the identification of genes and genetic variations that predispose to complex neuropsychiatric diseases.

Chromosome Mapping↗

PubMed2006

Successful multi-site measurement of antisaccade performance deficits in schizophrenia.

The antisaccade task is a promising schizophrenia endophenotype; it is stable over time and reflects neurophysiological deficits present in both schizophrenia subjects and their first-degree relatives. Meaningful genetic research requires large sample sizes that are best ascertained using multi-site study designs. To establish the criterion validity of the antisaccade task in a multi-site design, the Consortium on the Genetics of Schizophrenia (COGS) examined whether seven sites could detect previously reported antisaccade deficits in schizophrenia subjects. Investigators presented 3 blocks of 20 antisaccade stimuli to 143 schizophrenia subjects and 195 comparison subjects. Frequent collaborator communication, standardized training, and ongoing quality assurance optimized testing uniformity. Data were discarded from only 1.2% of subjects due to poor quality, reflecting the high fidelity of data collection and scoring methods. All sites detected a significant difference in the proportion of correct antisaccades between schizophrenia and comparison subjects (p<.02 at all sites); group differences in gain and latency were less robust. Regression analyses to adjust for the effects of group, site, age, gender, smoking, and parental education on the proportion of correct antisaccades revealed a significant effect of group, site, and age but no effect of gender, smoking, or parental education, and no group-by-site interactions. Intraclass correlations between proportion of correct antisaccades across the blocks of stimuli ranged from 0.87 to 0.93, demonstrating good within-session reliability at sites. These results confirm previous findings of antisaccade deficits in schizophrenia subjects and support the use of the antisaccade task as a potential schizophrenia endophenotype in multi-site genetic studies.

Adolescent↗

PubMed2006

Generalized genomic distance-based regression methodology for multilocus association analysis.

Large-scale, multilocus genetic association studies require powerful and appropriate statistical-analysis tools that are designed to relate genotype and haplotype information to phenotypes of interest. Many analysis approaches consider relating allelic, haplotypic, or genotypic information to a trait through use of extensions of traditional analysis techniques, such as contingency-table analysis, regression methods, and analysis-of-variance techniques. In this work, we consider a complementary approach that involves the characterization and measurement of the similarity and dissimilarity of the allelic composition of a set of individuals' diploid genomes at multiple loci in the regions of interest. We describe a regression method that can be used to relate variation in the measure of genomic dissimilarity (or "distance") among a set of individuals to variation in their trait values. Weighting factors associated with functional or evolutionary conservation information of the loci can be used in the assessment of similarity. The proposed method is very flexible and is easily extended to complex multilocus-analysis settings involving covariates. In addition, the proposed method actually encompasses both single-locus and haplotype-phylogeny analysis methods, which are two of the most widely used approaches in genetic association analysis. We showcase the method with data described in the literature. Ultimately, our method is appropriate for high-dimensional genomic data and anticipates an era when cost-effective exhaustive DNA sequence data can be obtained for a large number of individuals, over and above genotype information focused on a few well-chosen loci.

Chitinases↗

PubMed2006

PhenoChipping of psychotic disorders: a novel approach for deconstructing and quantitating psychiatric phenotypes.

Psychiatric phenotypes as currently defined are primarily the result of clinical consensus criteria rather than empirical research. We propose, and present initial proof of principle for, a novel approach to characterizing psychiatric phenotypes. We have termed our approach PhenoChipping, by analogy with, and borrowing paradigms and tools from, gene expression microarray studies (GeneChipping). A massive parallel profiling of cognitive and affective state is done with a PhenoChip composed of a battery of existing and new quantitative psychiatric rating scales, as well as hand neuromotor measures. We present preliminary data from 104 subjects, 72 with psychotic disorders (bipolar disorder-41, schizophrenia-17, schizoaffective disorder-14), and 32 normal controls. Microarray data analysis software and visualization tools were used to investigate: 1. relationships between phenotypic items ("phenes"), including with objective motor measures, and 2. relationships between subjects. Our analyses revealed phenotypic overlap among, as well as phenotypic heterogeneity within, the three major psychotic disorders studied. This approach may be useful in helping us move beyond current diagnostic classifications, and suggests a combinatorial building-block (Lego-like) structure underlies psychiatric syndromes. The adaptation of microarray informatic tools for phenotypic analysis readily facilitates direct integration with gene expression profiling of lymphocytes in the same individuals, a strategy for molecular biomarker identification. Empirically derived clusterings of (endo)phenotypes and of patients will better serve genetic, pharmacological, and imaging research, as well as clinical practice.

Adult↗

PubMed2006

Heritability estimates for dental caries and sucrose sweetness preference.

OBJECTIVE: The aim of this study was to determine heritability estimates for dental caries traits and sucrose sweetness preference. DESIGN: Participants included 115 pairs of twins 4-7-years-old. Caries exams followed NIDCR criteria where the severity of the lesion was also determined. Twins ranked their preference for five concentrations of sucrose/grape juice solutions (0.15-1.17M) with a Face Scale. Variables submitted to analysis: (1) surface-based caries prevalence rate (SBCPR); (2) lesion severity index (LSI); (3) sucrose sweetness preference score (SSPS). Heritability analyses were performed with the SOLAR software package. RESULTS: Heritability estimates adjusted for age and gender were: SBCPR-h(2)=64.6 (p<.00001), LSI-h(2)=61.7 (p<.00001) and SSPS-h(2)=55.2 (p<.00001). Treating SPSS as a covariate in the SBCPR and LSI models did not alter heritability estimates. CONCLUSIONS: These results suggest that variation in dental caries traits and sucrose sweetness preference have a significant genetic contribution that is mediated independently.

Child↗

PubMed2006

Racial admixture and its impact on BMI and blood pressure in African and Mexican Americans.

Admixed populations such as African Americans and Hispanic Americans present both challenges and opportunities in genetic epidemiologic research. Because of variation in admixture levels among individuals, case-control association studies may be subject to stratification bias. On the other hand, admixed populations also present special opportunities both for examining the role of genetic and environmental factors for observed racial/ethnic differences, and for possibly mapping alleles that contribute to such differences. Here we examined the distribution and relationship of individual admixture (IA) estimates with BMI and three measures of blood pressure in two admixed populations in the NHLBI Family Blood Pressure Program (FBPP): African Americans and Mexican Americans. For the African Americans, we observed modest but significant differences in average African IA among four recruitment sites. We observed a slight excess of African IA among hypertensives compared to normotensives, and a positive (non-significant) regression of African IA on blood pressure in untreated participants. Within Mexican Americans, we found no difference in average IA between hypertensives and normotensives, but a positive (marginally significant) regression of African IA on diastolic blood pressure. We also observed a significant positive regression of Caucasian IA (and negative regression of Native American IA) on BMI. Our results are suggestive of genetic differences between Africans and non-Africans that influence blood pressure, but such effects are likely to be modest compared to environmental ones. Excess obesity among Native Americans compared to whites is not consistent with a simple genetic explanation.

Adult↗

PubMed2006

Tic symptom profiles in subjects with Tourette Syndrome from two genetically isolated populations.

BACKGROUND: Tourette Syndrome (TS) has a complex etiology and wide variability in phenotypic expression. Identifying underlying symptom patterns may be useful for etiological and outcome studies of TS. METHODS: Lifetime tic and related symptom data were collected between 1996 and 2001 in 121 TS subjects from the Central Valley of Costa Rica and 133 TS subjects from the Ashkenazi Jewish (AS) population in the US. Subjects were grouped by tic symptoms using an agglomerative hierarchical cluster analysis. Cluster membership was tested for association with available ancillary information (age of onset, tic severity, comorbid disorders, medication treatment and family history). RESULTS: Cluster analysis identified two distinct groups in each sample, those with predominantly simple tics (cluster 1), and those with multiple complex tics (cluster 2). Membership in cluster 2 was correlated with increased tic severity, global impairment, medication treatment, and presence of comorbid obsessive-compulsive symptoms in both samples, and with family history of tics, lower verbal IQ, earlier age of onset, and comorbid obsessive-compulsive disorder and attention-deficit/hyperactivity disorder in the AS sample. CONCLUSIONS: This study provides evidence for consistent and reproducible symptom profiles in two independent TS study samples. These findings have implications for etiological studies of TS.

Adolescent↗

PubMed2006

Diplotype trend regression analysis of the ADH gene cluster and the ALDH2 gene: multiple significant associations with alcohol dependence.

The set of alcohol-metabolizing enzymes has considerable genetic and functional complexity. The relationships between some alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) genes and alcohol dependence (AD) have long been studied in many populations, but not comprehensively. In the present study, we genotyped 16 markers within the ADH gene cluster (including the ADH1A, ADH1B, ADH1C, ADH5, ADH6, and ADH7 genes), 4 markers within the ALDH2 gene, and 38 unlinked ancestry-informative markers in a case-control sample of 801 individuals. Associations between markers and disease were analyzed by a Hardy-Weinberg equilibrium (HWE) test, a conventional case-control comparison, a structured association analysis, and a novel diplotype trend regression (DTR) analysis. Finally, the disease alleles were fine mapped by a Hardy-Weinberg disequilibrium (HWD) measure (J). All markers were found to be in HWE in controls, but some markers showed HWD in cases. Genotypes of many markers were associated with AD. DTR analysis showed that ADH5 genotypes and diplotypes of ADH1A, ADH1B, ADH7, and ALDH2 were associated with AD in European Americans and/or African Americans. The risk-influencing alleles were fine mapped from among the markers studied and were found to coincide with some well-known functional variants. We demonstrated that DTR was more powerful than many other conventional association methods. We also found that several ADH genes and the ALDH2 gene were susceptibility loci for AD, and the associations were best explained by several independent risk genes.

Adult↗