Faculty Bibliography

BACKGROUND: A preliminary genome-wide linkage analysis of blood pressure in the Family Blood Pressure Program (FBPP) was reported previously. We harnessed the power and ethnic diversity of the final pooled FBPP dataset to identify novel loci for blood pressure thereby enhancing localization of genes containing less common variants with large effects on blood pressure levels and hypertension. METHODS: We performed one overall and 4 race-specific meta-analyses of genome-wide blood pressure linkage scans using data on 4,226 African-American, 2,154 Asian, 4,229 Caucasian, and 2,435 Mexican-American participants (total N = 13,044). Variance components models were fit to measured (raw) blood pressure levels and two types of antihypertensive medication adjusted blood pressure phenotypes within each of 10 subgroups defined by race and network. A modified Fisher's method was used to combine the P values for each linkage marker across the 10 subgroups. RESULTS: Five quantitative trait loci (QTLs) were detected on chromosomes 6p22.3, 8q23.1, 20q13.12, 21q21.1, and 21q21.3 based on significant linkage evidence (defined by logarithm of odds (lod) score >/=3) in at least one meta-analysis and lod scores >/=1 in at least 2 subgroups defined by network and race. The chromosome 8q23.1 locus was supported by Asian-, Caucasian-, and Mexican-American-specific meta-analyses. CONCLUSIONS: The new QTLs reported justify new candidate gene studies. They may help support results from genome-wide association studies (GWAS) that fall in these QTL regions but fail to achieve the genome-wide significance.

Submicroscopic changes in chromosomal DNA copy number dosage are common and have been implicated in many heritable diseases and cancers. Recent high-throughput technologies have a resolution that permits the detection of segmental changes in DNA copy number that span thousands of base pairs in the genome. Genomewide association studies (GWAS) may simultaneously screen for copy number phenotype and single nucleotide polymorphism (SNP) phenotype associations as part of the analytic strategy. However, genomewide array analyses are particularly susceptible to batch effects as the logistics of preparing DNA and processing thousands of arrays often involves multiple laboratories and technicians, or changes over calendar time to the reagents and laboratory equipment. Failure to adjust for batch effects can lead to incorrect inference and requires inefficient post hoc quality control procedures to exclude regions that are associated with batch. Our work extends previous model-based approaches for copy number estimation by explicitly modeling batch and using shrinkage to improve locus-specific estimates of copy number uncertainty. Key features of this approach include the use of biallelic genotype calls from experimental data to estimate batch-specific and locus-specific parameters of background and signal without the requirement of training data. We illustrate these ideas using a study of bipolar disease and a study of chromosome 21 trisomy. The former has batch effects that dominate much of the observed variation in the quantile-normalized intensities, while the latter illustrates the robustness of our approach to a data set in which approximately 27% of the samples have altered copy number. Locus-specific estimates of copy number can be plotted on the copy number scale to investigate mosaicism and guide the choice of appropriate downstream approaches for smoothing the copy number as a function of physical position. The software is open source and implemented in the R package crlmm at Bioconductor (http:www.bioconductor.org).

Though recently they have fallen into some disrepute, genome-wide association studies (GWAS) have been formulated and applied to understanding essential hypertension. The principal goal here is to use data gathered in a GWAS to gauge the extent to which SNPs and their interactions with other features can be combined to predict mean arterial blood pressure (MAP) in 3138 pre-menopausal and naturally post-menopausal white women. More precisely, we quantify the extent to which data as described permit prediction of MAP beyond what is possible from traditional risk factors such as blood cholesterol levels and glucose levels. Of course, these traditional risk factors are genetic, though typically not explicitly so. In all, there were 44 such risk factors/clinical variables measured and 377,790 single nucleotide polymorphisms (SNPs) genotyped. Data for women we studied are from first visit measurements taken as part of the Atherosclerotic Risk in Communities (ARIC) study. We begin by assessing non-SNP features in their abilities to predict MAP, employing a novel regression technique with two stages, first the discovery of main effects and next discovery of their interactions. The long list of SNPs genotyped is reduced to a manageable list for combining with non-SNP features in prediction. We adapted Efron's local false discovery rate to produce this reduced list. Selected non-SNP and SNP features and their interactions are used to predict MAP using adaptive linear regression. We quantify quality of prediction by an estimated coefficient of determination (R(2)). We compare the accuracy of prediction with and without information from SNPs.

The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother-father-child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately 10(-8) per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites. These methods and public data will support the next phase of human genetic research.

Copy number variants affect both disease and normal phenotypic variation, but those lying within heavily duplicated, highly identical sequence have been difficult to assay. By analyzing short-read mapping depth for 159 human genomes, we demonstrated accurate estimation of absolute copy number for duplications as small as 1.9 kilobase pairs, ranging from 0 to 48 copies. We identified 4.1 million "singly unique nucleotide" positions informative in distinguishing specific copies and used them to genotype the copy and content of specific paralogs within highly duplicated gene families. These data identify human-specific expansions in genes associated with brain development, reveal extensive population genetic diversity, and detect signatures consistent with gene conversion in the human species. Our approach makes ~1000 genes accessible to genetic studies of disease association.

AIMS/HYPOTHESIS/OBJECTIVE:To validate the reported association between rs10494366 in NOS1AP (the gene encoding nitric oxide synthase-1 adaptor protein) and the incidence of type 2 diabetes in calcium channel blocker (CCB) users and to identify additional NOS1AP variants associated with type 2 diabetes risk. METHODS:Data from 9 years of follow-up in 9,221 middle-aged white and 2,724 African-American adults free of diabetes at baseline from the Atherosclerosis Risk in Communities study were analysed. Nineteen NOS1AP variants were examined for associations with incident diabetes and fasting glucose levels stratified by baseline CCB use. RESULTS:Prevalence of CCB use at baseline was 2.7% (n = 247) in whites and 2.3% (n = 72) in African-Americans. Among white CCB users, the G allele of rs10494366 was associated with lower diabetes incidence (HR 0.57, 95% CI 0.35-0.92, p = 0.016). The association was marginally significant after adjusting for age, sex, obesity, smoking, alcohol use, physical activity, hypertension, heart rate and electrocardiographic QT interval (HR 0.63, 95% CI 0.38-1.04, p = 0.052). rs10494366 was associated with lower average fasting glucose during follow-up (p = 0.037). No other variants were associated with diabetes risk in CCB users after multiple-testing correction. No associations were observed between any NOS1AP variant and diabetes development in non-CCB users. NOS1AP variants were not associated with diabetes risk in either African-American CCB users or non-CCB users. CONCLUSIONS/INTERPRETATION/CONCLUSIONS:We have independently replicated the association between rs10494366 in NOS1AP and incident diabetes among white CCB users. Further exploration of NOS1AP variants and type 2 diabetes and functional studies of NOS1AP in type 2 diabetes pathology is warranted.

OBJECTIVE:This project was designed to follow-up prior evidence that demonstrated a significant association between vitamin B12 transport and metabolism and the frailty syndrome in community-dwelling older women. The cross-sectional relationship between genetic variants within six candidate genes along this pathway with serum methylmalonic acid (MMA) levels and frailty was evaluated in this same population of older women. METHODS:Baseline measures were collected prior to folate fortification from 326 women in the Women's Health and Aging Studies I and II. Odds ratios and statistical tests were estimated for single SNP and haplotype via linear regression models for serum MMA, a marker for available vitamin B12, and in logistic regression models for frailty. RESULTS:Fifty-six SNPs from CBS, MTHFR, MTR, MTRR, TCN1 and TCN2 genes were genotyped. Several SNPs in MTHFR, MTR and MTRR demonstrated a modest association to elevated MMA, while SNPs in TCN2 showed significant association to the frailty syndrome. TCN2 polymorphisms, particularly one SNP reported to be in perfect LD with functional variant Pro259Arg, were significantly associated with increased odds of frailty, after adjustment for age, presence of cardiovascular disease and elevated MMA (OR = 2.25, p-value = 0.009). CONCLUSIONS:Using MMA as a marker for vitamin B12, these results suggest that TCN2 gene variants may lead to decreased vitamin B12 availability, leading to reduced energy metabolism, ultimately contributing to frailty pathology. Further studies to determine the biological role of functional TCN2 polymorphisms in frailty are needed.

BACKGROUND: Autism is a common heritable neurodevelopmental disorder with complex etiology. Several genome-wide linkage and association scans have been carried out to identify regions harboring genes related to autism or autism spectrum disorders, with mixed results. Given the overlap in autism features with genetic abnormalities known to be associated with imprinting, one possible reason for lack of consistency would be the influence of parent-of-origin effects that may mask the ability to detect linkage and association. METHODS AND FINDINGS: We have performed a genome-wide linkage scan that accounts for potential parent-of-origin effects using 16,311 SNPs among families from the Autism Genetic Resource Exchange (AGRE) and the National Institute of Mental Health (NIMH) autism repository. We report parametric (GH, Genehunter) and allele-sharing linkage (Aspex) results using a broad spectrum disorder case definition. Paternal-origin genome-wide statistically significant linkage was observed on chromosomes 4 (LOD(GH) = 3.79, empirical p<0.005 and LOD(Aspex) = 2.96, p = 0.008), 15 (LOD(GH) = 3.09, empirical p<0.005 and LOD(Aspex) = 3.62, empirical p = 0.003) and 20 (LOD(GH) = 3.36, empirical p<0.005 and LOD(Aspex) = 3.38, empirical p = 0.006). CONCLUSIONS: These regions may harbor imprinted sites associated with the development of autism and offer fruitful domains for molecular investigation into the role of epigenetic mechanisms in autism.

The major gene for Hirschsprung disease (HSCR) encodes the receptor tyrosine kinase RET. In a study of 690 European- and 192 Chinese-descent probands and their parents or controls, we demonstrate the ubiquity of a >4-fold susceptibility from a C-->T allele (rs2435357: p = 3.9 x 10(-43) in European ancestry; p = 1.1 x 10(-21) in Chinese samples) that probably arose once within the intronic RET enhancer MCS+9.7. With in vitro assays, we now show that the T variant disrupts a SOX10 binding site within MCS+9.7 that compromises RET transactivation. The T allele, with a control frequency of 20%-30%/47% and case frequency of 54%-62%/88% in European/Chinese-ancestry individuals, is involved in all forms of HSCR. It is marginally associated with proband gender (p = 0.13) and significantly so with length of aganglionosis (p = 7.6 x 10(-5)) and familiality (p = 6.2 x 10(-4)). The enhancer variant is more frequent in the common forms of male, short-segment, and simplex families whereas multiple, rare, coding mutations are the norm in the less common and more severe forms of female, long-segment, and multiplex families. The T variant also increases penetrance in patients with rare RET coding mutations. Thus, both rare and common mutations, individually and together, make contributions to the risk of HSCR. The distribution of RET variants in diverse HSCR patients suggests a "cellular-recessive" genetic model where both RET alleles' function is compromised. The RET allelic series, and its genotype-phenotype correlations, shows that success in variant identification in complex disorders may strongly depend on which patients are studied.