Genetic variation in NCAM1 contributes to left ventricular wall thickness in hypertensive families.

RATIONALE: Left ventricular (LV) mass and related phenotypes are heritable, important predictors of cardiovascular disease, particularly in hypertensive individuals. OBJECTIVE: Identify genetic predictors of echocardiographic phenotypes in hypertensive families. METHODS AND RESULTS: A multistage genome-wide association study (GWAS) was conducted in hypertensive-ascertained black families (HyperGEN, stage I; GENOA, stage II); findings were replicated in HyperGEN white families (stage III). Echocardiograms were collected using a common protocol, and participants were genotyped with the Affymetrix Genome-Wide Human SNP 6.0 Array. The following were analyzed using mixed models adjusted for ancestry: in stages I and II, 1258 and 989 blacks, respectively; and in stage III, 1316 whites. Phenotypes included LV mass, LV internal dimension (LVID), wall thicknesses (posterior [PWT] and intraventricular septum [IVST]), and relative wall thickness (RWT). In stage I, 5 single nucleotide polymorphisms (SNPs) had P≤10(-6). In stage II, 1 SNP (rs1436109; NCAM1 intron 1) replicated with the same phenotype (PWT, P=0.025) in addition to RWT (P=0.032). In stage III, rs1436109 was associated with RWT (P=5.47×10(-4)) and LVID (P=1.86×10(-4)). Fisher combined probability value for all stages was RWT=3.80×10(-9), PWT=3.12×10(-7), IVST=8.69×10(-7), LV mass=2.52×10(-3), and LVID=4.80×10(-4). CONCLUSIONS: This GWAS conducted in hypertensive families identified a variant in NCAM1 associated with LV wall thickness and RWT. NCAM is upregulated during the remodeling period of hypertrophy to heart failure in Dahl salt-sensitive rats. Our initial screening in hypertensive blacks may have provided the context for this novel locus.

Gene expression patterns in peripheral blood cells associated with radiographic severity in African Americans with early rheumatoid arthritis.

Gene expression profiling may be used to stratify patients by disease severity to test the hypothesis that variable disease outcome has a genetic component. In order to define unique expression signatures in African American rheumatoid arthritis (RA) patients with severe erosive disease, we undertook a gene expression study using samples of RNA from peripheral blood mononuclear cells (PBMCs). RNA from baseline PBMC samples of 96 African American RA patients with early RA (<2 years disease duration) was hybridized to cDNA probes of the Illumina Human HT-V3 expression array. Expression analyses were performed using the ca. 25,000 cDNA probes, and then expression levels were compared to the total number of erosions in radiographs of the hands and feet at baseline and 36 months. Using a false discovery rate cutoff of Q = 0.30, 1,138 genes at baseline and 680 genes at 36 months significantly correlated with total erosions. No evidence of a signal differentiating disease progression, or change in erosion scores between baseline and 36 months, was found. Further analyses demonstrated that the differential gene expression signature was localized to the patients with the most erosive disease (>10 erosions). Ingenuity Pathway Analysis demonstrated that genes with fold change greater than 1.5 implicated immune pathways such as CTLA signaling in cytotoxic T lymphocytes. These results demonstrate that CLEAR patients with early RA having the most severe erosive disease, as compared to more mild cases (<10 erosions), may be characterized by a set of differentially expressed genes that represent biological pathways with relevance to autoimmune disease.

Genes linked to energy metabolism and immunoregulatory mechanisms are associated with subcutaneous adipose tissue distribution in HIV-infected men.

OBJECTIVE: Genetic studies may help explain abnormalities of fat distribution in HIV-infected patients treated with antiretroviral therapy (ARV). METHODS: Subcutaneous adipose tissue (SAT) volume measured by MRI in the leg, the lower trunk, the upper trunk, and the arm was examined in 192 HIV-infected White men, ARV-treated from the Fat Redistribution and Metabolic Change in HIV infection study. Single-nucleotide polymorphisms were assayed using the Illumina Human CNV370-quad beadchip. Multivariate and univariate genome-wide association analyses of the four SAT depots were implemented in PLINK software adjusted for age and ARV duration. Functional annotation analysis using Ingenuity Systems Pathway Analysis tool was carried out for markers with P lower than 10(-3) near known genes identified by multivariate analysis. RESULTS: Loci (rs10504906, rs13267998, rs921231) in or near the anion exchanger solute carrier family 26, member 7 isoform a (SLC26A7) were strongly associated with the upper trunk and the arm SAT (9.8×10(-7) ≤P<7.8×10(-6)). Loci (rs193139, rs7523050, rs1761621) in and near a gene-rich region including G-protein-signaling modulator 2 (GPSM2) and syntaxin-binding protein 3 (STXBP3) were significantly associated with the lower body SAT depots (9.9×10(-7) ≤P<9.5×10(-6)). GPSM2 is associated with cell division and cancer whereas STXBP3 is associated with glucose metabolism in adipoctyes. Ingenuity Systems Pathway Analysis identified atherosclerosis, mitochondrial function, and T-cell-mediated apoptosis as processes related to SAT volume in HIV-infected individuals (P<5×10(-3)). CONCLUSION: Our results are limited by the small sample size and replication is needed; however, this genomic scan uncovered new genes associated with metabolism and inflammatory pathways that may affect SAT volume in ARV-treated HIV-infected patients.

Comparing self-reported ethnicity to genetic background measures in the context of the Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: Questions remain regarding the utility of self-reported ethnicity (SRE) in genetic and epidemiologic research. It is not clear whether conditioning on SRE provides adequate protection from inflated type I error rates due to population stratification and admixture. We address this question using data obtained from the Multi-Ethnic Study of Atherosclerosis (MESA), which enrolled individuals from 4 self-reported ethnic groups. We compare the agreement between SRE and genetic based measures of ancestry (GBMA), and conduct simulation studies based on observed MESA data to evaluate the performance of each measure under various conditions. RESULTS: Four clusters are identified using 96 ancestry informative markers. Three of these clusters are well delineated, but 30% of the self-reported Hispanic-Americans are misclassified. We also found that MESA SRE provides type I error rates that are consistent with the nominal levels. More extensive simulations revealed that this finding is likely due to the multi-ethnic nature of the MESA. Finally, we describe situations where SRE may perform as well as a GBMA in controlling the effect of population stratification and admixture in association tests. CONCLUSIONS: The performance of SRE as a control variable in genetic association tests is more nuanced than previously thought, and may have more value than it is currently credited with, especially when smaller replication studies are being considered in multi-ethnic samples.

Is dietary fat "fattening"? A comprehensive research synthesis.

The goal of this research synthesis was to separate and articulate questions that had clear meaning, were empirically addressable, and were germane to the broad question "Is fat fattening?" Four such questions addressing the effect of varying the proportion of dietary fat on body weight and body fat were formulated. A comprehensive review of electronic citation databases was conducted to identify studies that addressed each question. The results of the studies addressing each question were tabulated and summarized, and an answer for each question was formulated. The results indicated that whether "fat is fattening" depends on exactly what one means by the question. It is apparent that under conditions of energy deficit, high-fat diets lead to greater weight loss than low-fat diets, but under ad libitum feeding conditions, instructing persons to follow a low-fat diet promotes loss of body weight and body fat. For one question, studies were few but convincing that altering the proportion of energy from fat in daily snacks has no effect on weight, while for another there were not enough studies available to answer the question with confidence. General recommendations to reduce dietary fat to promote weight loss or maintenance in all circumstances may merit reconsideration.

Commonality of functional annotation: a method for prioritization of candidate genes from genome-wide linkage studies.

Linkage studies of complex traits frequently yield multiple linkage regions covering hundreds of genes. Testing each candidate gene from every region is prohibitively expensive and computational methods that simplify this process would benefit genetic research. We present a new method based on commonality of functional annotation (CFA) that aids dissection of complex traits for which multiple causal genes act in a single pathway or process. CFA works by testing individual Gene Ontology (GO) terms for enrichment among candidate gene pools, performs multiple hypothesis testing adjustment using an estimate of independent tests based on correlation of GO terms, and then scores and ranks genes annotated with significantly-enriched terms based on the number of quantitative trait loci regions in which genes bearing those annotations appear. We evaluate CFA using simulated linkage data and show that CFA has good power despite being conservative. We apply CFA to published linkage studies investigating age-of-onset of Alzheimer's disease and body mass index and obtain previously known and new candidate genes. CFA provides a new tool for studies in which causal genes are expected to participate in a common pathway or process and can easily be extended to utilize annotation schemes in addition to the GO.

Multiple imputation to correct for measurement error in admixture estimates in genetic structured association testing.

OBJECTIVES: Structured association tests (SAT), like any statistical model, assumes that all variables are measured without error. Measurement error can bias parameter estimates and confound residual variance in linear models. It has been shown that admixture estimates can be contaminated with measurement error causing SAT models to suffer from the same afflictions. Multiple imputation (MI) is presented as a viable tool for correcting measurement error problems in SAT linear models with emphasis on correcting measurement error contaminated admixture estimates. METHODS: Several MI methods are presented and compared, via simulation, in terms of controlling Type I error rates for both non-additive and additive genotype coding. RESULTS: Results indicate that MI using the Rubin or Cole method can be used to correct for measurement error in admixture estimates in SAT linear models. CONCLUSION: Although MI can be used to correct for admixture measurement error in SAT linear models, the data should be of reasonable quality, in terms of marker informativeness, because the method uses the existing data to borrow information in which to make the measurement error corrections. If the data are of poor quality there is little information to borrow to make measurement error corrections.

Molecular and Functional Networks Linked to Sarcopenia Prevention by Caloric Restriction in Rhesus Monkeys.

Caloric restriction (CR) improves survival in nonhuman primates and delays the onset of age-related morbidities including sarcopenia, which is characterized by the age-related loss of muscle mass and function. A shift in metabolism anticipates the onset of muscle-aging phenotypes in nonhuman primates, suggesting a potential role for metabolism in the protective effects of CR. Here, we show that CR induced profound changes in muscle composition and the cellular metabolic environment. Bioinformatic analysis linked these adaptations to proteostasis, RNA processing, and lipid synthetic pathways. At the tissue level, CR maintained contractile content and attenuated age-related metabolic shifts among individual fiber types with higher mitochondrial activity, altered redox metabolism, and smaller lipid droplet size. Biometric and metabolic rate data confirm preserved metabolic efficiency in CR animals that correlated with the attenuation of age-related muscle mass and physical activity. These data suggest that CR-induced reprogramming of metabolism plays a role in delayed aging of skeletal muscle in rhesus monkeys.

Review and evaluation of methods correcting for population stratification with a focus on underlying statistical principles.

When two or more populations have been separated by geographic or cultural boundaries for many generations, drift, spontaneous mutations, differential selection pressures and other factors may lead to allele frequency differences among populations. If these 'parental' populations subsequently come together and begin inter-mating, disequilibrium among linked markers may span a greater genetic distance than it typically does among populations under panmixia [see glossary]. This extended disequilibrium can make association studies highly effective and more economical than disequilibrium mapping in panmictic populations since less marker loci are needed to detect regions of the genome that harbor phenotype-influencing loci. However, under some circumstances, this process of intermating (as well as other processes) can produce disequilibrium between pairs of unlinked loci and thus create the possibility of confounding or spurious associations due to this population stratification. Accordingly, researchers are advised to employ valid statistical tests for linkage disequilibrium mapping allowing conduct of genetic association studies that control for such confounding. Many recent papers have addressed this need. We provide a comprehensive review of advances made in recent years in correcting for population stratification and then evaluate and synthesize these methods based on statistical principles such as (1) randomization, (2) conditioning on sufficient statistics, and (3) identifying whether the method is based on testing the genotype-phenotype covariance (conditional upon familial information) and/or testing departures of the marginal distribution from the expected genotypic frequencies.

The use of plasmodes as a supplement to simulations: A simple example evaluating individual admixture estimation methodologies.

With the advent of powerful computers, simulation studies are becoming an important tool in statistical methodology research. However, computer simulations of a specific process are only as good as our understanding of the underlying mechanisms. An attractive supplement to simulations is the use of plasmode datasets. Plasmodes are data sets that are generated by natural biologic processes, under experimental conditions that allow some aspect of the truth to be known. The benefit of the plasmode approach is that the data are generated through completely natural processes, thus circumventing the common concern of the realism and accuracy of computer simulated data. The estimation of admixture, or the proportion of an individual's genome that originates from different founding populations, is a particularly difficult research endeavor that is well suited to the use of plasmodes. Current methods have been tested with simulations of complex populations where the underlying mechanisms such as the rate and distribution of recombination are not well understood. To demonstrate the utility of this method data derived from mouse crosses is used to evaluate the effectiveness of several admixture estimation methodologies. Each cross shares a common founding population so that the ancestry proportion for each individual is known, allowing for the comparison of true and estimated individual admixture values. Analysis shows that the different estimation methodologies (Structure, AdmixMap and FRAPPE) examined all perform well with simple datasets. However, the performance of the estimation methodologies varied greatly when applied to a plasmode consisting of three founding populations. The results of these examples illustrate the utility of plasmodes in the evaluation of statistical genetics methodologies.

Correcting for measurement error in individual ancestry estimates in structured association tests.

We present theoretical explanations and show through simulation that the individual admixture proportion estimates obtained by using ancestry informative markers should be seen as an error-contaminated measurement of the underlying individual ancestry proportion. These estimates can be used in structured association tests as a control variable to limit type I error inflation or reduce loss of power due to population stratification observed in studies of admixed populations. However, the inclusion of such error-containing variables as covariates in regression models can bias parameter estimates and reduce ability to control for the confounding effect of admixture in genetic association tests. Measurement error correction methods offer a way to overcome this problem but require an a priori estimate of the measurement error variance. We show how an upper bound of this variance can be obtained, present four measurement error correction methods that are applicable to this problem, and conduct a simulation study to compare their utility in the case where the admixed population results from the intermating between two ancestral populations. Our results show that the quadratic measurement error correction (QMEC) method performs better than the other methods and maintains the type I error to its nominal level.

Linkage and association analysis of circulating vitamin D and parathyroid hormone identifies novel loci in Alaska Native Yup'ik people.

BACKGROUND: Vitamin D deficiency is a well-documented public health issue with both genetic and environmental determinants. Populations living at far northern latitudes are vulnerable to vitamin D deficiency and its health sequelae, although consumption of traditional native dietary pattern rich in fish and marine mammals may buffer the effects of reduced sunlight exposure. To date, few studies have investigated the genetics of vitamin D metabolism in circumpolar populations or considered genediet interactions with fish and n-3 fatty acid intake. METHODS: We searched for genomic regions exhibiting linkage and association with circulating levels of vitamin D and parathyroid hormone (PTH) in 982 Yup'ik individuals from the Center for Alaska Native Health Research Study. We also investigated potential interactions between genetic variants and a biomarker of traditional dietary intake, the δ15N value. RESULTS: We identified several novel regions linked with circulating vitamin D and PTH as well as replicated a previous linkage finding on 2p16.2 for vitamin D. Bioinformatic analysis revealed multiple candidate genes for both PTH and vitamin D, including CUBN, MGAT3, and NFKBIA. Targeted association analysis identified NEBL as a candidate gene for vitamin D and FNDC3B for PTH. We observed significant associations between a variant in MXD1 and vitamin D only when an interaction with the δ15N value was included. Finally, we integrated pathway level information to illustrate the biological validity of the proposed candidate genes. CONCLUSION: We provide evidence of linkage between several biologically plausible genomic regions and vitamin D metabolism in a circumpolar population. Additionally, these findings suggest that a traditional dietary pattern may modulate genetic effects on circulating vitamin D.

Where in the genome are we? A cautionary tale of database use in genomics research.

With the advent of high throughput data genomic technologies the volume of available data is now staggering. In addition databases that provide resources to annotate, translate, and connect biological data have grown exponentially in content and use. The availability of such data emphasizes the importance of bioinformatics and computational biology in genomics research and has led to the development of thousands of tools to integrate and utilize these resources. When utilizing such resources, the principles of reproducible research are often overlooked. In this manuscript we provide selected case studies illustrating issues that may arise while working with genes and genetic polymorphisms. These case studies illustrate potential sources of error which can be introduced if the practices of reproducible research are not employed and non-concurrent databases are used. We also show examples of a lack of transparency when these databases are concerned when using popular bioinformatics tools. These examples highlight that resources are constantly evolving, and in order to provide reproducible results, research should be aware of and connected to the correct release of the data, particularly when implementing computational tools.

Characterization of autosomal copy-number variation in African Americans: the HyperGEN Study.

African Americans are a genetically diverse population with a high burden of many, common heritable diseases. However, our understanding of genetic variation in African Americans is substandard because of a lack of published population-based genetic studies. We report the distribution of copy-number variation (CNV) in African Americans collected as part of the Hypertension Genetic Epidemiology Network (HyperGEN) using the Affymetrix 6.0 array and the CNV calling algorithms Birdsuite and PennCNV. We present population estimates of CNV from 446 unrelated African-American subjects randomly selected from the 451 families collected within HyperGEN. Although the majority of CNVs discovered were individually rare, we found the frequency of CNVs to be collectively high. We identified a total of 11 070 CNVs greater than 10 kb passing quality control criteria that were called by both algorithms - leading to an average of 24.8 CNVs per person covering 2214 kb (median). We identified 1541 unique copy-number variable regions, 309 of which did not overlap with the Database of Genomic Variants. These results provide further insight into the distribution of CNV in African Americans.

Genetic region characterization (Gene RECQuest) - software to assist in identification and selection of candidate genes from genomic regions.

BACKGROUND: The availability of research platforms like the web tools of the National Center for Biotechnology Information (NCBI) has transformed the time-consuming task of identifying candidate genes from genetic studies to an interactive process where data from a variety of sources are obtained to select likely genes for follow-up. This process presents its own set of challenges, as the genetic researcher has to interact with several tools in a time-intensive, manual, and cumbersome manner. We developed a method and implemented an effective software system to address these challenges by multidisciplinary efforts of professional software developers with domain experts. The method presented in this paper, Gene RECQuest, simplifies the interaction with existing research platforms through the use of advanced integration technologies. FINDINGS: Gene RECQuest is a web-based application that assists in the identification of candidate genes from linkage and association studies using information from Online Mendelian Inheritance in Man (OMIM) and PubMed. To illustrate the utility of Gene RECQuest we used it to identify genes physically located within a linkage region as potential candidate genes for a quantitative trait locus (QTL) for very low density lipoprotein (VLDL) response on chromosome 18. CONCLUSION: Gene RECQuest provides a tool which enables researchers to easily identify and organize literature supporting their own expertise and make informed decisions. It is important to note that Gene RECQuest is a data acquisition and organization software, and not a data analysis method.