The genetic dissection of complex traits in a founder population

An expression-directed linear mixed model discovering low-effect genetic variants

Detecting genetic variants with low-effect sizes using a moderate sample size is difficult, hindering downstream efforts to learn pathology and estimating heritability. In this work, by utilizing informative weights learned from training genetically predicted gene expression models, we formed an alternative approach to estimate the polygenic term in a linear mixed model. Our linear mixed model estimates the genetic background by incorporating their relevance to gene expression. Our protocol, expression-directed linear mixed model, enables the discovery of subtle signals of low-effect variants using moderate sample size. By applying expression-directed linear mixed model to cohorts of around 5,000 individuals with either binary (WTCCC) or quantitative (NFBC1966) traits, we demonstrated its power gain at the low-effect end of the genetic etiology spectrum. In aggregate, the additional low-effect variants detected by expression-directed linear mixed model substantially improved estimation of missing heritability. Expression-directed linear mixed model moves precision medicine forward by accurately detecting the contribution of low-effect genetic variants to human diseases.

A Genome-Wide Association Study of Genetic Variants of Apolipoprotein A1 Levels and Their Association with Vitamin D in Korean Cohorts

Dyslipidemia is an important independent risk factor for cardiovascular disease (CVD). Specifically, apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and the ApoB/A1 ratio have been linked to CVD. We conducted a genome-wide association study meta-analysis of two Korean cohorts containing a total of 12,924 patients to identify novel single nucleotide polymorphisms (SNPs) associated with ApoA1 and ApoB levels and the ApoB/A1 ratio. Additionally, an expression quantitative trait locus (eQTL) and differentially expressed genes (DEGs) analysis were performed. The statistically significant eQTL, DEG, and Gene Ontology (GO) results were used to explore the predicted interaction networks and retrieve the interacting genes and proteins. We identified three novel SNPs (rs11066280, p = 3.46 × 10−21; rs1227162, p = 2.98 × 10−15; rs73216931, p = 5.62 × 10−9) associated with ApoA1. SNP rs73216931 was an eQTL for KMT5A in the pancreas and whole blood. The network analysis revealed that HECTD4 and MYL2:LINC1405 are associated with AKT1. Our in silico analysis of ApoA1 genetic variants revealed heart muscle-related signals. ApoA1 also correlated positively with vitamin D, and genes associated with ApoA1 and vitamin D were found. Our data imply that more research into ApoA1 is needed to understand the links between dyslipidemia and CVD and vitamin D and CVD.

Neighborhood Exposures and Blood Pressure Outcomes: A Cross-Sectional Environmental Study among 19-53 Years-Old Parsis in Mumbai

The correlation between high blood pressure (BP) and urban neighborhood-level environmental determinants is understudied in low-income and middle-income countries (LMICs). We hypothesized that neighborhoods constitute exposures that affect resident-behaviors, metabolism and increased susceptibility to high BP. We studied urban clusters of Mumbai-Parsis (Zoroastrians), a founder population group, to minimize genetic variation and maximize exposure assessment. Participants from four neighborhoods were 19–53 years old and comprised 756 females and 774 males. We recorded healthy BPs (≤120/80 mmHg) in 59%, pre-hypertensive (≥121–139/81–89 mmHg) in 21% and high BP (≥140/90 mmHg) in 21% of the participants. A family history of hypertension had no correlation with high BP. We used the Neighborhood Accessibility Framework to compile a questionnaire in order to collect data on participants’ perception of space, third places, streetscape and experience, land use, connectivity, surveillance, pedestrian safety and public transport. Our results suggested that participants in neighborhoods with poorer BP outcomes reported lower accessibility scores for space, streetscape and experience, third places and connectivity. Our study evaluates how neighborhood-level determinants affect BP outcomes in order to contribute to the body of knowledge on primary preventive measures for high BP in urban LMIC populations. We concluded that neighborhood exposures affect resident-behaviors, which cause metabolic changes and increase susceptibility to high BP.

Positive association of familial longevity with the moderate-high HDL-C concentration in Bama Aging Study

Familial longevity is characterized by beneficial metabolic phenotype in lipid metabolism and APOE genetic variation. Although effects of lipid metabolism and the genetic basis for human longevity remain largely unclear, the contribution of high-density lipoprotein cholesterol (HDL-C) and APOE ε2 allele has been repeatedly demonstrated. This study was designed to determine whether ApoE isoforms and HDL-C levels marked the familial longevity status in an offspring cohort with the age range of 20-89 years old and subsequently to explore the correlation between these two markers and the aging. In the Bama Aging Study (BAS), we recruited 312 offspring from longevity historical families and 298 controls from non-longevity historical families. Information on APOE genotype frequencies, lipid levels, and population characteristics were recorded. No evidence was found to support the association of APOE genotypes with HDL-C and age. HDL-C was significantly higher in longevity group (p < 0.0001). Scatter plot showed a moderately strong linear relationship between the HDL-C level and age in longevity group (r = 0.213, p < 0.001). We conclude that the variation of the APOE gene may not influence familial longevity status at a certain age but the moderate-high HDL-C level contributes to the familial longevity in Bama.

A genome scan for genes underlying adult body size differences between Central African hunter-gatherers and farmers

The evolutionary and biological bases of the Central African "pygmy" phenotype, a characteristic of rainforest hunter-gatherers defined by reduced body size compared with neighboring farmers, remain largely unknown. Here, we perform a joint investigation in Central African hunter-gatherers and farmers of adult standing height, sitting height, leg length, and body mass index (BMI), considering 358 hunter-gatherers and 169 farmers with genotypes for 153,798 SNPs. In addition to reduced standing heights, hunter-gatherers have shorter sitting heights and leg lengths and higher sitting/standing height ratios than farmers and lower BMI for males. Standing height, sitting height, and leg length are strongly correlated with inferred levels of farmer genetic ancestry, whereas BMI is only weakly correlated, perhaps reflecting greater contributions of non-genetic factors to body weight than to height. Single- and multi-marker association tests identify one region and eight genes associated with hunter-gatherer/farmer status, and 24 genes associated with the height-related traits. Many of these genes have putative functions consistent with roles in determining their associated traits and the pygmy phenotype, and they include three associated with standing height in non-Africans (PRKG1, DSCAM, MAGI2). We find evidence that European height-associated SNPs or variants in linkage disequilibrium with them contribute to standing- and sitting-height determination in Central Africans, but not to the differential status of hunter-gatherers and farmers. These findings provide new insights into the biological basis of the pygmy phenotype, and they highlight the potential of cross-population studies for exploring the genetic basis of phenotypes that vary naturally across populations.

Profiling and Leveraging Relatedness in a Precision Medicine Cohort of 92,455 Exomes

Large-scale human genetics studies are ascertaining increasing proportions of populations as they continue growing in both number and scale. As a result, the amount of cryptic relatedness within these study cohorts is growing rapidly and has significant implications on downstream analyses. We demonstrate this growth empirically among the first 92,455 exomes from the DiscovEHR cohort and, via a custom simulation framework we developed called SimProgeny, show that these measures are in line with expectations given the underlying population and ascertainment approach. For example, within DiscovEHR we identified ∼66,000 close (first- and second-degree) relationships, involving 55.6% of study participants. Our simulation results project that >70% of the cohort will be involved in these close relationships, given that DiscovEHR scales to 250,000 recruited individuals. We reconstructed 12,574 pedigrees by using these relationships (including 2,192 nuclear families) and leveraged them for multiple applications. The pedigrees substantially improved the phasing accuracy of 20,947 rare, deleterious compound heterozygous mutations. Reconstructed nuclear families were critical for identifying 3,415 de novo mutations in ∼1,783 genes. Finally, we demonstrate the segregation of known and suspected disease-causing mutations, including a tandem duplication that occurs in LDLR and causes familial hypercholesterolemia, through reconstructed pedigrees. In summary, this work highlights the prevalence of cryptic relatedness expected among large healthcare population-genomic studies and demonstrates several analyses that are uniquely enabled by large amounts of cryptic relatedness.

Longitudinal Growth and pQCT Measures in Hutterite Children and Grandchildren Are Associated With Prevalence of Hip or Knee Replacement Resulting From Osteoarthritis in Parents and Grandparents

BACKGROUND

Osteoarthritis (OA) is one of the leading causes of disability in the world. Several genes are associated with the development of OA, and previous studies have shown adult children of individuals with OA have higher areal bone mineral density (BMD). Because childhood is an important period of growth and bone development, and body composition is known to be associated with BMD, we speculated that there may be differences in growth and bone measures among young children with a genetic predisposition to OA.

QUESTIONS/PURPOSES

(1) Do differences exist at baseline in anthropometric and peripheral quantitative CT (pQCT) measurements between children and grandchildren of individuals with OA and controls? (2) Do children and grandchildren of individuals with OA accrue bone longitudinally at a different rate than controls?

METHODS

Longitudinal anthropometric (height, weight) and bone (cortical and trabecular volumetric BMD and cross-sectional area) measurements by pQCT were obtained at baseline and 18 and 36 months on children (n = 178) and grandchildren (n = 230) of 23 individuals with hip or knee arthroplasty resulting from OA and 23 sex-matched controls (16 females each). Grandchildren (age, 8-30 years) were further categorized as growing (premenarcheal or male < 14 years, n = 99) or mature (≥ 2 years postmenarchal or males ≥ 18 years, n = 96). The remaining 35 grandchildren could not be categorized and were excluded.

RESULTS

Mature granddaughters and grandsons of individuals with OA had greater trabecular volumetric BMD than controls (236 ± 24 and 222 ± 26 mg/cm, respectively, for granddaughters, difference of 14 [95% confidence interval {CI}, 1-28] mg/cm, p = 0.041 and 270 ± 22 and 248 ± 30 mg/cm, respectively, for grandsons, difference of 22 [95% CI, 1-42] mg/cm, p = 0.040). Greater trabecular volumetric BMD was observed in daughters of individuals with OA compared with daughters of controls (228 ± 28 and 212 ± 33 mg/cm, respectively, difference of 18 [95% CI, 3-30] mg/cm, respectively [p = 0.021]). Growing granddaughters and grandsons of controls had greater decreases in cortical volumetric BMD than grandchildren of individuals with OA (time-by-group [TG] based on mixed model [± standard error] -9.7 ± 4.3 versus -0.8 ± 4.4 mg/cm/year, respectively, for granddaughters, difference of 9.0 [95% CI, 2.4-15.5] mg/cm/year, p = 0.007 and -6.8 ± 3.3 versus 4.5 ± 3.4 mg/cm/year, respectively, for grandsons, difference of 11.3 [95% CI, 4.3-18.3] mg/cm/year, p = 0.002). Cortical volumetric BMD was maintained in sons of individuals with OA, but decreased in sons of controls (-0.0 ± 1.5 versus -4.3 ± 1.0 mg/cm/year, respectively, difference of 4.3 [95% CI, 0.7-7.8] mg/cm/year, p = 0.019 [TG]). There was a greater apparent decrease in cross-sectional area among daughters of individuals with OA than in controls (-4.6 ± 0.9 versus -1.7 ± 0.9 mm/year, respectively, difference of -2.9 [95% CI, -5.3 to -0.6] mm/year, p = 0.015 [TG]).

CONCLUSIONS

Several anthropometric and bone differences exist between children and grandchildren of individuals with OA and controls. If these differences are confirmed in additional studies, it would be important to identify the mechanism so that preventive measures could be developed and implemented to slow or reduce OA development.

CLINICAL RELEVANCE

Differences in growth and bone development may lead to increased loads on cartilage that may predispose offspring to the development of OA. If these differences are confirmed in additional studies, it would be important to identify the mechanism so that preventive measures could be developed and implemented to slow or reduce OA development.

Quantitative analysis of population-scale family trees with millions of relatives

Family trees have vast applications in fields as diverse as genetics, anthropology, and economics. However, the collection of extended family trees is tedious and usually relies on resources with limited geographical scope and complex data usage restrictions. We collected 86 million profiles from publicly available online data shared by genealogy enthusiasts. After extensive cleaning and validation, we obtained population-scale family trees, including a single pedigree of 13 million individuals. We leveraged the data to partition the genetic architecture of human longevity and to provide insights into the geographical dispersion of families. We also report a simple digital procedure to overlay other data sets with our resource.

Rare non-coding variants are associated with plasma lipid traits in a founder population

Founder populations are ideally suited for studies on the clinical effects of alleles that are rare in general populations but occur at higher frequencies in these isolated populations. Whole genome sequencing in 98 Hutterites, a founder population of European descent, and subsequent imputation revealed 660,238 single nucleotide polymorphisms that are rare (<1%) or absent in European populations, but occur at frequencies >1% in the Hutterites. We examined the effects of these rare in European variants on plasma lipid levels in 828 Hutterites and applied a Bayesian hierarchical framework to prioritize potentially causal variants based on functional annotations. We identified two novel non-coding rare variants associated with LDL cholesterol (rs17242388 in LDLR) and HDL cholesterol (rs189679427 between GOT2 and APOOP5), and replicated previous associations of a splice variant in APOC3 (rs138326449) with triglycerides and HDL-C. All three variants are at well-replicated loci in GWAS but are independent from and have larger effect sizes than the known common variation in these regions. Candidate eQTL analyses in in LCLs in the Hutterites suggest that these rare non-coding variants are likely to mediate their effects on lipid traits by regulating gene expression.

Ocular biometry and determinants of refractive error in a founder population of European ancestry

BACKGROUND

The prevalence of myopia is increasing worldwide. Previous studies have found a positive association between myopia, education, and near activities, while others have noted a negative association with outdoor exposure. This study reports refractive error and biometry in a founder population of European ancestry, the Hutterites, and discusses risk factors contributing to myopia.

METHODS

Cross-sectional study, including complete eye exams with retinoscopy and biometry.

RESULTS

939 study participants, ages 6 to 89, were examined. Females were significantly more myopic than males (SE -0.87 ± 2.07 and -0.40 ± 1.49 in females and males, respectively, p < 0.0001). Males had significantly longer axial lengths. Females had steeper corneas. This is the first epidemiological report of refractive error among the Hutterites.

DISCUSSION

As a genetically isolated population with a communal lifestyle, the Hutterites present a unique opportunity to study risk factors for myopia. Hutterite females are more myopic than males, a finding which has only been reported in a few other populations. Hutterite children complete compulsory education through the 8th grade, after which women and men assume gender-specific occupational tasks. Men often work outside on the farm, while women engage in more domestic activities inside. These occupational differences likely contribute to the increased myopia comparing females to males, and their uniform lifestyle reduces the impact of potential confounding factors, such as education and income.

CONCLUSIONS

The Hutterites are more myopic than most other North American and European populations. Greater time spent doing near work and less time spent outdoors likely explain the increased myopia comparing females to males.

Genetic Defects Underlie the Non-syndromic Autosomal Recessive Intellectual Disability (NS-ARID)

Intellectual disability (ID) is a neurodevelopmental disorder which appears frequently as the result of genetic mutations and may be syndromic (S-ID) or non-syndromic (NS-ID). ID causes an important economic burden, for patient's family, health systems, and society. Identifying genes that cause S-ID can easily be evaluated due to the clinical symptoms or physical anomalies. However, in the case of NS-ID due to the absence of co-morbid features, the latest molecular genetic techniques can be used to understand the genetic defects that underlie it. Recent studies have shown that non-syndromic autosomal recessive (NS-ARID) is extremely heterogeneous and contributes much more than X-linked ID. However, very little is known about the genes and loci involved in NS-ARID relative to X-linked ID, and whose complete genetic etiology remains obscure. In this review article, the known genetic etiology of NS-ARID and possible relationships between genes and the associated molecular pathways of their encoded proteins has been reviewed which will enhance our understanding about the underlying genes and mechanisms in NS-ARID.

Host genetic variation in mucosal immunity pathways influences the upper airway microbiome

BACKGROUND

The degree to which host genetic variation can modulate microbial communities in humans remains an open question. Here, we performed a genetic mapping study of the microbiome in two accessible upper airway sites, the nasopharynx and the nasal vestibule, during two seasons in 144 adult members of a founder population of European decent.

RESULTS

We estimated the relative abundances (RAs) of genus level bacteria from 16S rRNA gene sequences and examined associations with 148,653 genetic variants (linkage disequilibrium [LD] r 2 < 0.5) selected from among all common variants discovered in genome sequences in this population. We identified 37 microbiome quantitative trait loci (mbQTLs) that showed evidence of association with the RAs of 22 genera (q < 0.05) and were enriched for genes in mucosal immunity pathways. The most significant association was between the RA of Dermacoccus (phylum Actinobacteria) and a variant 8 kb upstream of TINCR (rs117042385; p = 1.61 × 10-8; q = 0.002), a long non-coding RNA that binds to peptidoglycan recognition protein 3 (PGLYRP3) mRNA, a gene encoding a known antimicrobial protein. A second association was between a missense variant in PGLYRP4 (rs3006458) and the RA of an unclassified genus of family Micrococcaceae (phylum Actinobacteria) (p = 5.10 × 10-7; q = 0.032).

CONCLUSIONS

Our findings provide evidence of host genetic influences on upper airway microbial composition in humans and implicate mucosal immunity genes in this relationship.

Structure, function, and genetics of lipoprotein (a)

Lipoprotein (a) [Lp(a)] has attracted the interest of researchers and physicians due to its intriguing properties, including an intragenic multiallelic copy number variation in the LPA gene and the strong association with coronary heart disease (CHD). This review summarizes present knowledge of the structure, function, and genetics of Lp(a) with emphasis on the molecular and population genetics of the Lp(a)/LPA trait, as well as aspects of genetic epidemiology. It highlights the role of genetics in establishing Lp(a) as a risk factor for CHD, but also discusses uncertainties, controversies, and lack of knowledge on several aspects of the genetic Lp(a) trait, not least its function.

The Effect of Ancestry and Genetic Variation on Lung Function Predictions: What Is "Normal" Lung Function in Diverse Human Populations?

Lung function measures are an invaluable screening test for respiratory health and have been associated with the morbidity and mortality related to different airway disease as well as all-cause mortality. Currently, reference values for spirometric measurements are obtained using equations derived from individual ethnic or racial groups. The rapid expansion of more racially and ethnically diverse populations will challenge current race-based lung function reference equations. Recent international general population studies and ancestry-based genetic studies have found that ancestry and genetic variation are determinants of lung function and have suggested a role for genetic ancestry or gene variants in future lung function reference equations. In this review, we discuss the potential limitations of current lung function reference equations in a global society which is becoming more ethnically, racially, and, thus, genetically diverse. We also focus on how an individual's ancestral background or genetic profile could provide the basis for more accurate, personalized predictions of an individual's baseline lung function.

Evidence for several independent genetic variants affecting lipoprotein (a) cholesterol levels

Lipoprotein (a) [Lp(a)] is an independent risk factor for atherosclerosis-related events that is under strong genetic control (heritability = 0.68-0.98). However, causal mutations and functional validation of biological pathways modulating Lp(a) metabolism are lacking. We performed a genome-wide association scan to identify genetic variants associated with Lp(a)-cholesterol levels in the Old Order Amish. We confirmed a previously known locus on chromosome 6q25-26 and found Lp(a) levels also to be significantly associated with a SNP near the APOA5-APOA4-APOC3-APOA1 gene cluster on chromosome 11q23 linked in the Amish to the APOC3 R19X null mutation. On 6q locus, we detected associations of Lp(a)-cholesterol with 118 common variants (P = 5 × 10(-8) to 3.91 × 10(-19)) spanning a ∼5.3 Mb region that included the LPA gene. To further elucidate variation within LPA, we sequenced LPA and identified two variants most strongly associated with Lp(a)-cholesterol, rs3798220 (P = 1.07 × 10(-14)) and rs10455872 (P = 1.85 × 10(-12)). We also measured copy numbers of kringle IV-2 (KIV-2) in LPA using qPCR. KIV-2 numbers were significantly associated with Lp(a)-cholesterol (P = 2.28 × 10(-9)). Conditional analyses revealed that rs3798220 and rs10455872 were associated with Lp(a)-cholesterol levels independent of each other and KIV-2 copy number. Furthermore, we determined for the first time that levels of LPA mRNA were higher in the carriers than non-carriers of rs10455872 (P = 0.0001) and were not different between carriers and non-carriers of rs3798220. Protein levels of apo(a) were higher in the carriers than non-carriers of both rs10455872 and rs3798220. In summary, we identified multiple independent genetic determinants for Lp(a)-cholesterol. These findings provide new insights into Lp(a) regulation.

Dominance genetic variation contributes little to the missing heritability for human complex traits

For human complex traits, non-additive genetic variation has been invoked to explain "missing heritability," but its discovery is often neglected in genome-wide association studies. Here we propose a method of using SNP data to partition and estimate the proportion of phenotypic variance attributed to additive and dominance genetic variation at all SNPs (hSNP(2) and δSNP(2)) in unrelated individuals based on an orthogonal model where the estimate of hSNP(2) is independent of that of δSNP(2). With this method, we analyzed 79 quantitative traits in 6,715 unrelated European Americans. The estimate of δSNP(2) averaged across all the 79 quantitative traits was 0.03, approximately a fifth of that for additive variation (average hSNP(2) = 0.15). There were a few traits that showed substantial estimates of δSNP(2), none of which were replicated in a larger sample of 11,965 individuals. We further performed genome-wide association analyses of the 79 quantitative traits and detected SNPs with genome-wide significant dominance effects only at the ABO locus for factor VIII and von Willebrand factor. All these results suggest that dominance variation at common SNPs explains only a small fraction of phenotypic variation for human complex traits and contributes little to the missing narrow-sense heritability problem.

PRIMAL: Fast and accurate pedigree-based imputation from sequence data in a founder population

Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm), a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD) segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs), from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost.

Bayesian Polynomial Regression Models to Fit Multiple Genetic Models for Quantitative Traits

We present a coherent Bayesian framework for selection of the most likely model from the five genetic models (genotypic, additive, dominant, co-dominant, and recessive) commonly used in genetic association studies. The approach uses a polynomial parameterization of genetic data to simultaneously fit the five models and save computations. We provide a closed-form expression of the marginal likelihood for normally distributed data, and evaluate the performance of the proposed method and existing method through simulated and real genome-wide data sets.

Fine-mapping additive and dominant SNP effects using group-LASSO and fractional resample model averaging

Genomewide association studies (GWAS) sometimes identify loci at which both the number and identities of the underlying causal variants are ambiguous. In such cases, statistical methods that model effects of multiple single-nucleotide polymorphisms (SNPs) simultaneously can help disentangle the observed patterns of association and provide information about how those SNPs could be prioritized for follow-up studies. Current multi-SNP methods, however, tend to assume that SNP effects are well captured by additive genetics; yet when genetic dominance is present, this assumption translates to reduced power and faulty prioritizations. We describe a statistical procedure for prioritizing SNPs at GWAS loci that efficiently models both additive and dominance effects. Our method, LLARRMA-dawg, combines a group LASSO procedure for sparse modeling of multiple SNP effects with a resampling procedure based on fractional observation weights. It estimates for each SNP the robustness of association with the phenotype both to sampling variation and to competing explanations from other SNPs. In producing an SNP prioritization that best identifies underlying true signals, we show the following: our method easily outperforms a single-marker analysis; when additive-only signals are present, our joint model for additive and dominance is equivalent to or only slightly less powerful than modeling additive-only effects; and when dominance signals are present, even in combination with substantial additive effects, our joint model is unequivocally more powerful than a model assuming additivity. We also describe how performance can be improved through calibrated randomized penalization, and discuss how dominance in ungenotyped SNPs can be incorporated through either heterozygote dosage or multiple imputation.

Whole-genome sequencing of individuals from a founder population identifies candidate genes for asthma

Asthma is a complex genetic disease caused by a combination of genetic and environmental risk factors. We sought to test classes of genetic variants largely missed by genome-wide association studies (GWAS), including copy number variants (CNVs) and low-frequency variants, by performing whole-genome sequencing (WGS) on 16 individuals from asthma-enriched and asthma-depleted families. The samples were obtained from an extended 13-generation Hutterite pedigree with reduced genetic heterogeneity due to a small founding gene pool and reduced environmental heterogeneity as a result of a communal lifestyle. We sequenced each individual to an average depth of 13-fold, generated a comprehensive catalog of genetic variants, and tested the most severe mutations for association with asthma. We identified and validated 1960 CNVs, 19 nonsense or splice-site single nucleotide variants (SNVs), and 18 insertions or deletions that were out of frame. As follow-up, we performed targeted sequencing of 16 genes in 837 cases and 540 controls of Puerto Rican ancestry and found that controls carry a significantly higher burden of mutations in IL27RA (2.0% of controls; 0.23% of cases; nominal p = 0.004; Bonferroni p = 0.21). We also genotyped 593 CNVs in 1199 Hutterite individuals. We identified a nominally significant association (p = 0.03; Odds ratio (OR) = 3.13) between a 6 kbp deletion in an intron of NEDD4L and increased risk of asthma. We genotyped this deletion in an additional 4787 non-Hutterite individuals (nominal p = 0.056; OR = 1.69). NEDD4L is expressed in bronchial epithelial cells, and conditional knockout of this gene in the lung in mice leads to severe inflammation and mucus accumulation. Our study represents one of the early instances of applying WGS to complex disease with a large environmental component and demonstrates how WGS can identify risk variants, including CNVs and low-frequency variants, largely untested in GWAS.

Disclosure of genetic research results to members of a founder population

There is currently extensive discussion and debate in the literature on how, when, and to whom genetic research results should be returned (see Genetics in Medicine, April 2012 issue). Here, we describe our experience in disclosing genetic information on Mendelian disorders discovered during the course of our research in the Hutterites. We first assessed attitudes toward the disclosure of carrier results, which revealed that many individuals wanted carrier information and that many intended to use the information in family planning. Based on this information, we developed a pilot study to test and disclose cystic fibrosis (CF) carrier status. Next, a larger scale project was developed in order to disclose genetic research results for 14 diseases to those interested in receiving the information. We developed brochures, offered a live interactive educational program, conducted a consent process, and disclosed results in letters mailed to the consented individuals. Overall, ~80% of individuals who participated in the educational program signed consent forms for the release of their results for 14 diseases. We describe our experience with returning individual genetic research results to participants in a population-based research study.

A polymorphism in the histone deacetylase 1 gene is associated with the response to corticosteroids in asthmatics

BACKGROUND/AIMS

Recent investigations suggest that histone deacetylase 1 (HDAC1) and HDAC2 may be target molecules to predict therapeutic responses to corticosteroids. We evaluated the effects of variation in HDAC1 and HDAC2 on the response to corticosteroids in asthmatics.

METHODS

Two single nucleotide polymorphisms (SNPs) were selected after resequencing HDAC1 and HDAC2. For the first analysis, we evaluated the association between those SNPs and asthma severity in 477 asthmatics. For the second analysis, we evaluated the effects of these SNPs on lung function improvements in response to corticosteroid treatment in 35 independent adult asthmatics and 70 childhood asthmatics.

RESULTS

We found that one SNP in HDAC1 (rs1741981) was significantly related to asthma severity in a recessive model (corrected p = 0.036). Adult asthmatics who were homozygous for the minor allele of rs1741981 showed significantly lower % forced expiratory volume in 1 second (%FEV1) increases in response to systemic corticosteroids treatment compared with the heterozygotes or those homozygous for the major allele (12.7% ± 7.2% vs. 37.4% ± 33.7%, p = 0.018). Similarly, childhood asthmatics who were homozygous for the minor allele of rs1741981 showed significantly lower %FEV1 increases in response to inhaled corticosteroid treatment compared with the heterozygotes or those homozygous for the major allele (14.1% ± 5.9% vs. 19.4% ± 8.9%, p = 0.035).

CONCLUSIONS

The present study demonstrated that rs1741981 in HDAC1 was significantly associated with the response to corticosteroid treatment in asthmatics.

Parental broader autism subphenotypes in ASD affected families: relationship to gender, child's symptoms, SSRI treatment, and platelet serotonin

Relationships between parental broader autism phenotype (BAP) scores, gender, selective serotonin reuptake inhibitor (SSRI) treatment, serotonin (5HT) levels, and the child's symptoms were investigated in a family study of autism spectrum disorder (ASD). The Broader Autism Phenotype Questionnaire (BAPQ) was used to measure the BAP of 275 parents. Fathers not taking SSRIs (F-SSRI; n = 115) scored significantly higher on BAP Total and Aloof subscales compared to mothers not receiving treatment (M-SSRI; n = 136.) However, mothers taking SSRIs (M + SSRI; n = 19) scored higher than those not taking medication on BAP Total and Rigid subscales, and they were more likely to be BAPQ Total, Aloof, and Rigid positive. Significant correlations were noted between proband autism symptoms and parental BAPQ scores such that Total, Aloof, and Rigid subscale scores of F-SSRI correlated with proband restricted repetitive behavior (RRB) measures on the ADOS, CRI, and RBS-R. However, only the Aloof subscale score of M + SSRI correlated with proband RRB on the ADOS. The correlation between the BAPQ scores of mothers taking SSRIs and child scores, as well as the increase in BAPQ scores of this group of mothers, requires careful interpretation and further study because correlations would not withstand multiple corrections. As expected by previous research, significant parent-child correlations were observed for 5HT levels. However, 5HT levels were not correlated with behavioral measures. Study results suggest that the expression of the BAP varies not only across parental gender, but also across individuals using psychotropic medication and those who do not.

Sex-specific heritability of spontaneous lipid levels in an extended pedigree of Indian-origin rhesus macaques (Macaca mulatta)

The rhesus macaque is an important model for human atherosclerosis but genetic determinants of relevant phenotypes have not yet been investigated in this species. Because lipid levels are well-established and heritable risk factors for human atherosclerosis, our goal was to assess the heritability of lipoprotein cholesterol and triglyceride levels in a single, extended pedigree of 1,289 Indian-origin rhesus macaques. Additionally, because increasing evidence supports sex differences in the genetic architecture of lipid levels and lipid metabolism in humans and macaques, we also explored sex-specific heritability for all lipid measures investigated in this study. Using standard methods, we measured lipoprotein cholesterol and triglyceride levels from fasted plasma in a sample of 193 pedigreed rhesus macaques selected for membership in large, paternal half-sib cohorts, and maintained on a low-fat, low cholesterol chow diet. Employing a variance components approach, we found moderate heritability for total cholesterol (h²=0.257, P=0.032), LDL cholesterol (h²=0.252, P=0.030), and triglyceride levels (h²=0.197, P=0.034) in the full sample. However, stratification by sex (N=68 males, N=125 females) revealed substantial sex-specific heritability for total cholesterol (0.644, P=0.004, females only), HDL cholesterol (0.843, P=0.0008, females only), VLDL cholesterol (0.482, P=0.018, males only), and triglyceride levels (0.705, P=0.001, males only) that was obscured or absent when sexes were combined in the full sample. We conclude that genes contribute to spontaneous variation in circulating lipid levels in the Indian-origin rhesus macaque in a sex-specific manner, and that the rhesus macaque is likely to be a valuable model for sex-specific genetic effects on lipid risk factors for human atherosclerosis. These findings are a first-ever report of heritability for cholesterol levels in this species, and support the need for expanded analysis of these traits in this population.

Genome-wide association study of lung function phenotypes in a founder population

BACKGROUND

Lung function is a long-term predictor of mortality and morbidity.

OBJECTIVE

We sought to identify single nucleotide polymorphisms (SNPs) associated with lung function.

METHODS

We performed a genome-wide association study (GWAS) of FEV1, forced vital capacity (FVC), and FEV1/FVC in 1144 Hutterites aged 6 to 89 years, who are members of a founder population of European descent. We performed least absolute shrinkage and selection operation regression to select the minimum set of SNPs that best predict FEV1/FVC in the Hutterites and used the GRAIL algorithm to mine the Gene Ontology database for evidence of functional connections between genes near the predictive SNPs.

RESULTS

Our GWAS identified significant associations between FEV1/FVC and SNPs at the THSD4-UACA-TLE3 locus on chromosome 15q23 (P = 5.7 × 10(-8) to 3.4 × 10(-9)). Nine SNPs at or near 4 additional loci had P < 10(-5) with FEV1/FVC. Only 2 SNPs were found with P < 10(-5) for FEV1 or FVC. We found nominal levels of significance with SNPs at 9 of the 27 previously reported loci associated with lung function measures. Among a predictive set of 80 SNPs, 6 loci were identified that had a significant degree of functional connectivity (GRAIL P < .05), including 3 clusters of β-defensin genes, 2 chemokine genes (CCL18 and CXCL12), and TNFRSF13B.

CONCLUSION

This study identifies genome-wide significant associations and replicates results of previous GWASs. Multimarker modeling implicated for the first time common variation in genes involved in antimicrobial immunity in airway mucosa that influences lung function.

Genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family

Given the importance of cardiovascular disease (CVD) to public health and the demonstrated heritability of both disease status and its related risk factors, identifying the genetic variation underlying these susceptibilities is a critical step in understanding the pathogenesis of CVD and informing prevention and treatment strategies. Although one can look for genetic variation underlying susceptibility to CVD per se, it can be difficult to define the disease phenotype for such a qualitative analysis and CVD itself represents a convergence of diverse etiologic pathways. Alternatively, one can study the genetics of intermediate traits that are known risk factors for CVD, which can be measured quantitatively. Using the latter strategy, we have measured 21 cardiovascular-related biomarkers in an extended multigenerational pedigree, the CARRIAGE family (Carolinas Region Interaction of Aging, Genes, and Environment). These biomarkers belong to inflammatory and immune, connective tissue, lipid, and hemostasis pathways. Of these, 18 met our quality control standards. Using the pedigree and biomarker data, we have estimated the broad sense heritability (H2) of each biomarker (ranging from 0.09–0.56). A genome-wide panel of 6,015 SNPs was used subsequently to map these biomarkers as quantitative traits. Four showed noteworthy evidence for linkage in multipoint analysis (LOD score ≥ 2.6): paraoxonase (chromosome 8p11, 21), the chemokine RANTES (22q13.33), matrix metalloproteinase 3 (MMP3, 17p13.3), and granulocyte colony stimulating factor (GCSF, 8q22.1). Identifying the causal variation underlying each linkage score will help to unravel the genetic architecture of these quantitative traits and, by extension, the genetic architecture of cardiovascular risk.

The endocrine stress response is linked to one specific locus on chromosome 3 in a mouse model based on extremes in trait anxiety

Background

The hypothalamic-pituitary-adrenal (HPA) axis is essential to control physiological stress responses in mammals. Its dysfunction is related to several mental disorders, including anxiety and depression. The aim of this study was to identify genetic loci underlying the endocrine regulation of the HPA axis.

Method

High (HAB) and low (LAB) anxiety-related behaviour mice were established by selective inbreeding of outbred CD-1 mice to model extremes in trait anxiety. Additionally, HAB vs. LAB mice exhibit comorbid characteristics including a differential corticosterone response upon stress exposure. We crossbred HAB and LAB lines to create F1 and F2 offspring. To identify the contribution of the endocrine phenotypes to the total phenotypic variance, we examined multiple behavioural paradigms together with corticosterone secretion-based phenotypes in F2 mice by principal component analysis. Further, to pinpoint the genomic loci of the quantitative trait of the HPA axis stress response, we conducted genome-wide multipoint oligogenic linkage analyses based on Bayesian Markov chain Monte Carlo approach as well as parametric linkage in three-generation pedigrees, followed by a two-dimensional scan for epistasis and association analysis in freely segregating F2 mice using 267 single-nucleotide polymorphisms (SNPs), which were identified to consistently differ between HAB and LAB mice as genetic markers.

Results

HPA axis reactivity measurements and behavioural phenotypes were represented by independent principal components and demonstrated no correlation. Based on this finding, we identified one single quantitative trait locus (QTL) on chromosome 3 showing a very strong evidence for linkage (2ln (L-score) > 10, LOD > 23) and significant association (lowest Bonferroni adjusted p < 10^-28) to the neuroendocrine stress response. The location of the linkage peak was estimated at 42.3 cM (95% confidence interval: 41.3 - 43.3 cM) and was shown to be in epistasis (p-adjusted < 0.004) with the locus at 35.3 cM on the same chromosome. The QTL harbours genes involved in steroid synthesis and cardiovascular effects.

Conclusion

The very prominent effect on stress-induced corticosterone secretion of the genomic locus on chromosome 3 and its involvement in epistasis highlights the critical role of this specific locus in the regulation of the HPA axis.

A population-based study of autosomal-recessive disease-causing mutations in a founder population

The decreasing cost of whole-genome and whole-exome sequencing has resulted in a renaissance for identifying Mendelian disease mutations, and for the first time it is possible to survey the distribution and characteristics of these mutations in large population samples. We conducted carrier screening for all autosomal-recessive (AR) mutations known to be present in members of a founder population and revealed surprisingly high carrier frequencies for many of these mutations. By utilizing the rich demographic, genetic, and phenotypic data available on these subjects and simulations in the exact pedigree that these individuals belong to, we show that the majority of mutations were most likely introduced into the population by a single founder and then drifted to the high carrier frequencies observed. We further show that although there is an increased incidence of AR diseases overall, the mean carrier burden is likely to be lower in the Hutterites than in the general population. Finally, on the basis of simulations, we predict the presence of 30 or more undiscovered recessive mutations among these subjects, and this would at least double the number of AR diseases that have been reported in this isolated population.

Evidence of inbreeding depression on human height

Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ² = 83.89, df = 1; p = 5.2×10⁻²⁰). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.

Studies investigating the extent to which genetics influences human characteristics such as height have concentrated mainly on common variants of genes, where having one or two copies of a given variant influences the trait or risk of disease. This study explores whether a different type of genetic variant might also be important. We investigate the role of recessive genetic variants, where two identical copies of a variant are required to have an effect. By measuring genome-wide homozygosity—the phenomenon of inheriting two identical copies at a given point of the genome—in 35,000 individuals from 21 European populations, and by comparing this to individual height, we found that the more homozygous the genome, the shorter the individual. The offspring of first cousins (who have increased homozygosity) were predicted to be up to 3 cm shorter on average than the offspring of unrelated parents. Height is influenced by the combined effect of many recessive variants dispersed across the genome. This may also be true for other human characteristics and diseases, opening up a new way to understand how genetic variation influences our health.

Genome-wide association identifies the T gene as a novel asthma pharmacogenetic locus

RATIONALE

To date, most studies aimed at discovering genetic factors influencing treatment response in asthma have focused on biologic candidate genes. Genome-wide association studies (GWAS) can rapidly identify novel pharmacogenetic loci.

OBJECTIVES

To investigate if GWAS can identify novel pharmacogenetic loci in asthma.

METHODS

Using phenotypic and GWAS genotype data available through the NHLBI-funded Single-nucleotide polymorphism Health association-Asthma Resource Project, we analyzed differences in FEV(1) in response to inhaled corticosteroids in 418 white subjects with asthma. Of the 444,088 single nucleotide polymorphisms (SNPs) analyzed, the lowest 50 SNPs by P value were genotyped in an independent clinical trial population of 407 subjects with asthma.

MEASUREMENTS AND MAIN RESULTS

The lowest P value for the GWAS analysis was 2.09 × 10(-6). Of the 47 SNPs successfully genotyped in the replication population, three were associated under the same genetic model in the same direction, including two of the top four SNPs ranked by P value. Combined P values for these SNPs were 1.06 × 10(-5) for rs3127412 and 6.13 × 10(-6) for rs6456042. Although these two were not located within a gene, they were tightly correlated with three variants mapping to potentially functional regions within the T gene. After genotyping, each T gene variant was also associated with lung function response to inhaled corticosteroids in each of the trials associated with rs3127412 and rs6456042 in the initial GWAS analysis. On average, there was a twofold to threefold difference in FEV(1) response for those subjects homozygous for the wild-type versus mutant alleles for each T gene SNP.

CONCLUSIONS

Genome-wide association has identified the T gene as a novel pharmacogenetic locus for inhaled corticosteroid response in asthma.

Accurate imputation of rare and common variants in a founder population from a small number of sequenced individuals

Advances in DNA sequencing technologies have greatly facilitated the discovery of rare genetic variants in the human genome, many of which may contribute to common disease risk. However, evaluating their individual or even collective effects on disease risk requires very large sample sizes, which involves study designs that are often prohibitively expensive. We present an alternative approach for determining genotypes in large numbers of individuals for all variants discovered in the sequence of relatively few individuals. Specifically, we developed a new imputation algorithm that utilizes whole-exome sequencing data from 25 members of the South Dakota Hutterite population, and genome-wide single nucleotide polymorphism (SNP) genotypes from >1,400 individuals from the same founder population. The algorithm relies on identity-by-descent sharing of phased haplotypes, a different strategy than the linkage disequilibrium methods found in most imputation algorithms. We imputed genotypes discovered in the sequence data to on average ∼77% of chromosomes among the 1,400 individuals. Median R(2) between imputed and directly genotyped data was >0.99. As expected, many variants that are vanishingly rare in European populations have risen to larger frequencies in the founder population and would be amenable to single-SNP analyses.

Genome-wide association study of lung function decline in adults with and without asthma

BACKGROUND

Genome-wide association studies have identified determinants of chronic obstructive pulmonary disease, asthma, and lung function level; however, none have addressed decline in lung function.

OBJECTIVE

We conducted the first genome-wide association study on the age-related decrease in FEV(1) and its ratio to forced vital capacity (FVC) stratified a priori by asthma status.

METHODS

Discovery cohorts included adults of European ancestry (1,441 asthmatic and 2,677 nonasthmatic participants: the Epidemiological Study on the Genetics and Environment of Asthma, the Swiss Cohort Study on Air Pollution and Lung and Heart Disease in Adults, and the European Community Respiratory Health Survey). The associations of FEV(1) and FEV(1)/FVC ratio decrease with 2.5 million single nucleotide polymorphisms (SNPs) were estimated. Thirty loci were followed up by in silico replication (1,160 asthmatic and 10,858 nonasthmatic participants: Atherosclerosis Risk in Communities, the Framingham Heart Study, the British 1958 Birth Cohort, and the Dutch Asthma Study).

RESULTS

Main signals identified differed between asthmatic and nonasthmatic participants. None of the SNPs reached genome-wide significance. The association between the height-related gene DLEU7 and FEV(1) decrease suggested for nonasthmatic participants in the discovery phase was replicated (discovery, P = 4.8 × 10(-6); replication, P = .03), and additional sensitivity analyses point to a relation to growth. The top ranking signal, TUSC3, which is associated with FEV(1)/FVC ratio decrease in asthmatic participants (P = 5.3 × 10(-8)), did not replicate. SNPs previously associated with cross-sectional lung function were not prominently associated with decline.

CONCLUSIONS

Genetic heterogeneity of lung function might be extensive. Our results suggest that genetic determinants of longitudinal and cross-sectional lung function differ and vary by asthma status.

Evaluating the evidence for transmission distortion in human pedigrees

Children of a heterozygous parent are expected to carry either allele with equal probability. Exceptions can occur, however, due to meiotic drive, competition among gametes, or viability selection, which we collectively term “transmission distortion” (TD). Although there are several well-characterized examples of these phenomena, their existence in humans remains unknown. We therefore performed a genome-wide scan for TD by applying the transmission disequilibrium test (TDT) genome-wide to three large sets of human pedigrees of European descent: the Framingham Heart Study (FHS), a founder population of European origin (HUTT), and a subset of the Autism Genetic Resource Exchange (AGRE). Genotyping error is an important confounder in this type of analysis. In FHS and HUTT, despite extensive quality control, we did not find sufficient evidence to exclude genotyping error in the strongest signals. In AGRE, however, many signals extended across multiple SNPs, a pattern highly unlikely to arise from genotyping error. We identified several candidate regions in this data set, notably a locus in 10q26.13 displaying a genome-wide significant TDT in combined female and male transmissions and a signature of recent positive selection, as well as a paternal TD signal in 6p21.1, the same region in which a significant TD signal was previously observed in 30 European males. Neither region replicated in FHS, however, and the paternal signal was not visible in sperm competition assays or as allelic imbalance in sperm. In maternal transmissions, we detected no strong signals near centromeres or telomeres, the regions predicted to be most susceptible to female-specific meiotic drive, but we found a significant enrichment of top signals among genes involved in cell junctions. These results illustrate both the potential benefits and the challenges of using the TDT to study transmission distortion and provide candidates for investigation in future studies.

The combination of a genome-wide association study of lymphocyte count and analysis of gene expression data reveals novel asthma candidate genes

Recent genome-wide association studies (GWAS) have identified a number of novel genetic associations with complex human diseases. In spite of these successes, results from GWAS generally explain only a small proportion of disease heritability, an observation termed the ‘missing heritability problem’. Several sources for the missing heritability have been proposed, including the contribution of many common variants with small individual effect sizes, which cannot be reliably found using the standard GWAS approach. The goal of our study was to explore a complimentary approach, which combines GWAS results with functional data in order to identify novel genetic associations with small effect sizes. To do so, we conducted a GWAS for lymphocyte count, a physiologic quantitative trait associated with asthma, in 462 Hutterites. In parallel, we performed a genome-wide gene expression study in lymphoblastoid cell lines from 96 Hutterites. We found significant support for genetic associations using the GWAS data when we considered variants near the 193 genes whose expression levels across individuals were most correlated with lymphocyte counts. Interestingly, these variants are also enriched with signatures of an association with asthma susceptibility, an observation we were able to replicate. The associated loci include genes previously implicated in asthma susceptibility as well as novel candidate genes enriched for functions related to T cell receptor signaling and adenosine triphosphate synthesis. Our results, therefore, establish a new set of asthma susceptibility candidate genes. More generally, our observations support the notion that many loci of small effects influence variation in lymphocyte count and asthma susceptibility.

Loneliness is associated with sleep fragmentation in a communal society

STUDY OBJECTIVE

Loneliness has been shown to predict poor health. One hypothesized mechanism is that lonely individuals do not sleep as well as individuals who feel more connected to others. Our goal was to test whether loneliness is associated with sleep fragmentation or sleep duration.

DESIGN

Cross-sectional study.

SETTING

Members of a traditional, communal, agrarian society living in South Dakota.

PARTICIPANTS

Ninety-five participants (mean age 39.8 years, 55% female) who were ≥ 19 years of age at the study's inception.

INTERVENTIONS

Not applicable.

MEASUREMENTS AND RESULTS

We conducted interviews querying loneliness, depression, anxiety, and stress, as well as subjective sleep quality and daytime sleepiness. Study participants wore a wrist actigraph for one week to measure objective sleep properties; the two studied here were sleep fragmentation and sleep duration. Higher loneliness scores were associated with significantly higher levels of sleep fragmentation (β = 0.073, t = 2.55, P = 0.01), controlling for age, sex, body mass index, risk of sleep apnea, and negative affect (a factor comprising symptoms of depression and anxiety, and perceived stress). Loneliness was not associated with sleep duration or with either subjective sleep measure.

CONCLUSIONS

Loneliness was a significant predictor of sleep fragmentation. Humans' social nature may partly be manifest through our dependence on feeling secure in our social environment to sleep well.

Genomewide association between GLCCI1 and response to glucocorticoid therapy in asthma

BACKGROUND

The response to treatment for asthma is characterized by wide interindividual variability, with a significant number of patients who have no response. We hypothesized that a genomewide association study would reveal novel pharmacogenetic determinants of the response to inhaled glucocorticoids.

METHODS

We analyzed a small number of statistically powerful variants selected on the basis of a family-based screening algorithm from among 534,290 single-nucleotide polymorphisms (SNPs) to determine changes in lung function in response to inhaled glucocorticoids. A significant, replicated association was found, and we characterized its functional effects.

RESULTS

We identified a significant pharmacogenetic association at SNP rs37972, replicated in four independent populations totaling 935 persons (P=0.0007), which maps to the glucocorticoid-induced transcript 1 gene (GLCCI1) and is in complete linkage disequilibrium (i.e., perfectly correlated) with rs37973. Both rs37972 and rs37973 are associated with decrements in GLCCI1 expression. In isolated cell systems, the rs37973 variant is associated with significantly decreased luciferase reporter activity. Pooled data from treatment trials indicate reduced lung function in response to inhaled glucocorticoids in subjects with the variant allele (P=0.0007 for pooled data). Overall, the mean (±SE) increase in forced expiratory volume in 1 second in the treated subjects who were homozygous for the mutant rs37973 allele was only about one third of that seen in similarly treated subjects who were homozygous for the wild-type allele (3.2±1.6% vs. 9.4±1.1%), and their risk of a poor response was significantly higher (odds ratio, 2.36; 95% confidence interval, 1.27 to 4.41), with genotype accounting for about 6.6% of overall inhaled glucocorticoid response variability.

CONCLUSIONS

A functional GLCCI1 variant is associated with substantial decrements in the response to inhaled glucocorticoids in patients with asthma.

Rising prevalence of asthma is sex-specific in a US farming population

BACKGROUND

Asthma prevalence is increasing worldwide in most populations, likely due to a combination of heritable factors and environmental changes. Curiously, however, some European farming populations are protected from asthma, which has been attributed to their traditional lifestyles and farming practices.

OBJECTIVE

We conducted population-based studies of asthma and atopy in the Hutterites of South Dakota, a communal farming population, to assess temporal trends in asthma and atopy prevalence and describe the risk factors for asthma.

METHODS

We studied 1325 Hutterites (ages 6-91 years) at 2 time points from 1996 to 1997 and from 2006 to 2009 by using asthma questionnaires, pulmonary function and methacholine bronchoprovocation tests, and measures of atopy.

RESULTS

The overall prevalence of asthma increased over the 10- to 13-year study period (7.5%-11.1%, P = .049), whereas the overall prevalence of atopy did not change (45.0%-44.8%, P = .95). Surprisingly, the rise in asthma was only among females (5.8%-11.2%, P = .02); the prevalence among males remained largely unchanged (9.4%-10.9%, P = .57). Atopy, which was not associated with asthma risk in 1996 to 1997, was the strongest risk factor for asthma among Hutterites studied in 2006 to 2009 (P = .003).

CONCLUSIONS

Asthma has increased over a 10- to 13-year period among Hutterite females and atopy has become a significant risk factor for asthma, suggesting a change in environmental exposures that are either sex limited or that elicit a sex-specific response.

Identity by descent estimation with dense genome-wide genotype data

We present a novel method, IBDLD, for estimating the probability of identity by descent (IBD) for a pair of related individuals at a locus, given dense genotype data and a pedigree of arbitrary size and complexity. IBDLD overcomes the challenges of exact multipoint estimation of IBD in pedigrees of potentially large size and eliminates the difficulty of accommodating the background linkage disequilibrium (LD) that is present in high-density genotype data. We show that IBDLD is much more accurate at estimating the true IBD sharing than methods that remove LD by pruning SNPs and is highly robust to pedigree errors or other forms of misspecified relationships. The method is fast and can be used to estimate the probability for each possible IBD sharing state at every SNP from a high-density genotyping array for hundreds of thousands of pairs of individuals. We use it to estimate point-wise and genomewide IBD sharing between 185,745 pairs of subjects all of whom are related through a single, large and complex 13-generation pedigree and genotyped with the Affymetrix 500 k chip. We find that we are able to identify the true pedigree relationship for individuals who were misidentified in the collected data and estimate empirical kinship coefficients that can be used in follow-up QTL mapping studies. IBDLD is implemented as an open source software package and is freely available.

The genetics of asthma and allergic disease: a 21st century perspective

Asthma and allergy are common conditions with complex etiologies involving both genetic and environmental contributions. Recent genome-wide association studies (GWAS) and meta-analyses of GWAS have begun to shed light on both common and distinct pathways that contribute to asthma and allergic diseases. Associations with variation in genes encoding the epithelial cell-derived cytokines, interleukin-33 (IL-33) and thymic stromal lymphopoietin (TSLP), and the IL1RL1 gene encoding the IL-33 receptor, ST2, highlight the central roles for innate immune response pathways that promote the activation and differentiation of T-helper 2 cells in the pathogenesis of both asthma and allergic diseases. In contrast, variation at the 17q21 asthma locus, encoding the ORMDL3 and GSDML genes, is specifically associated with risk for childhood onset asthma. These and other genetic findings are providing a list of well-validated asthma and allergy susceptibility genes that are expanding our understanding of the common and unique biological pathways that are dysregulated in these related conditions. Ongoing studies will continue to broaden our understanding of asthma and allergy and unravel the mechanisms for the development of these complex traits.

A common spinal muscular atrophy deletion mutation is present on a single founder haplotype in the US Hutterites

Spinal muscular atrophy (SMA) is an autosomal recessive (AR) neuromuscular disease that is one of the most common lethal genetic disorders in children, with carrier frequencies as high as ∼1 in 35 in US Whites. As part of our genetic studies in the Hutterites from South Dakota, we identified a large 22 Mb run of homozygosity, spanning the SMA locus in an affected child, of which 10 Mb was also homozygous in three affected Hutterites from Montana, supporting a single founder origin for the mutation. We developed a haplotype-based method for identifying carriers of the SMN1 deletion that leveraged existing genome-wide SNP genotype data for ∼1400 Hutterites. In combination with two direct PCR-based assays, we identified 176 carriers of the SMN1 deletion, one asymptomatic homozygous adult and three carriers of a de novo deletion. This corresponds to a carrier frequency of one in eight (12.5%) in the South Dakota Hutterites, representing the highest carrier frequency reported to date for SMA and for an AR disease in the Hutterite population. Lastly, we show that 26 SNPs can be used to predict SMA carrier status in the Hutterites, with 99.86% specificity and 99.71% sensitivity.

Genetic loci for blood lipid levels identified by linkage and association analyses in Caribbean Hispanics

To identify genetic loci influencing blood lipid levels in Caribbean Hispanics, we first conducted a genome-wide linkage scan in 1,211 subjects from 100 Dominican families on five lipid quantitative traits: total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), triglycerides (TG), and LDL-C/HDL-C ratio. We then investigated the association between blood lipid levels and 21,361 single nucleotide polymorphisms (SNP) under the 1-logarithm of odds (LOD) unit down regions of linkage peaks in an independent community-based subcohort (N = 814, 42% Dominican) from the Northern Manhattan Study (NOMAS). We found significant linkage evidence for LDL-C/HDL-C on 7p12 (multipoint LOD = 3.91) and for TC on 16q23 (LOD = 3.35). In addition, we identified suggestive linkage evidence of LOD > 2.0 on 15q23 for TG, 16q23 for LDL-C, 19q12 for TC and LDL-C, and 20p12 for LDL-C. In the association analysis of the linkage peaks, we found that seven SNPs near FLJ45974 were associated with LDL-C/HDL-C with a nominal P < 3.5 × 10(-5), in addition to associations (P < 0.0001) for other lipid traits with SNPs in or near CDH13, SUMF2, TLE3, FAH, ARNT2, TSHZ3, ZNF343, RPL7AL2, and TMC3. Further studies are warranted to perform in-depth investigations of functional genetic variants in these regions.

Genetic variance components estimation for binary traits using multiple related individuals

Understanding and modeling genetic or nongenetic factors that influence susceptibility to complex traits has been the focus of many genetic studies. Large pedigrees with known complex structure may be advantageous in epidemiological studies since they can significantly increase the number of factors whose influence on the trait can be estimated. We propose a likelihood approach, developed in the context of generalized linear mixed models, for modeling dichotomous traits based on data from hundreds of individuals all of whom are potentially correlated through either a known pedigree or an estimated covariance matrix. Our approach is based on a hierarchical model where we first assess the probability of each individual having the trait and then formulate a likelihood assuming conditional independence of individuals. The advantage of our formulation is that it easily incorporates information from pertinent covariates as fixed effects and at the same time takes into account the correlation between individuals that share genetic background or other random effects. The high dimensionality of the integration involved in the likelihood prohibits exact computations. Instead, an automated Monte Carlo expectation maximization algorithm is employed for obtaining the maximum likelihood estimates of the model parameters. Through a simulation study we demonstrate that our method can provide reliable estimates of the model parameters when the sample size is close to 500. Implementation of our method to data from a pedigree of 491 Hutterites evaluated for Type 2 diabetes (T2D) reveal evidence of a strong genetic component to T2D risk, particularly for younger and leaner cases.

Genomic and genealogical investigation of the French Canadian founder population structure

Characterizing the genetic structure of worldwide populations is important for understanding human history and is essential to the design and analysis of genetic epidemiological studies. In this study, we examined genetic structure and distant relatedness and their effect on the extent of linkage disequilibrium (LD) and homozygosity in the founder population of Quebec (Canada). In the French Canadian founder population, such analysis can be performed using both genomic and genealogical data. We investigated genetic differences, extent of LD, and homozygosity in 140 individuals from seven sub-populations of Quebec characterized by different demographic histories reflecting complex founder events. Genetic findings from genome-wide single nucleotide polymorphism data were correlated with genealogical information on each of these sub-populations. Our genomic data showed significant population structure and relatedness present in the contemporary Quebec population, also reflected in LD and homozygosity levels. Our extended genealogical data corroborated these findings and indicated that this structure is consistent with the settlement patterns involving several founder events. This provides an independent and complementary validation of genomic-based studies of population structure. Combined genomic and genealogical data in the Quebec founder population provide insights into the effects of the interplay of two important sources of bias in genetic epidemiological studies, unrecognized genetic structure and cryptic relatedness.

Exome sequencing reveals a novel mutation for autosomal recessive non-syndromic mental retardation in the TECR gene on chromosome 19p13

Exome sequencing is a powerful tool for discovery of the Mendelian disease genes. Previously, we reported a novel locus for autosomal recessive non-syndromic mental retardation (NSMR) in a consanguineous family [Nolan, D.K., Chen, P., Das, S., Ober, C. and Waggoner, D. (2008) Fine mapping of a locus for nonsyndromic mental retardation on chromosome 19p13. Am. J. Med. Genet. A, 146A, 1414-1422]. Using linkage and homozygosity mapping, we previously localized the gene to chromosome 19p13. The parents of this sibship were recently included in an exome sequencing project. Using a series of filters, we narrowed the putative causal mutation to a single variant site that segregated with NSMR: the mutation was homozygous in five affected siblings but in none of eight unaffected siblings. This mutation causes a substitution of a leucine for a highly conserved proline at amino acid 182 in TECR (trans-2,3-enoyl-CoA reductase), a synaptic glycoprotein. Our results reveal the value of massively parallel sequencing for identification of novel disease genes that could not be found using traditional approaches and identifies only the seventh causal mutation for autosomal recessive NSMR.

Increased power of mixed models facilitates association mapping of 10 loci for metabolic traits in an isolated population

The potential benefits of using population isolates in genetic mapping, such as reduced genetic, phenotypic and environmental heterogeneity, are offset by the challenges posed by the large amounts of direct and cryptic relatedness in these populations confounding basic assumptions of independence. We have evaluated four representative specialized methods for association testing in the presence of relatedness; (i) within-family (ii) within- and between-family and (iii) mixed-models methods, using simulated traits for 2906 subjects with known genome-wide genotype data from an extremely isolated population, the Island of Kosrae, Federated States of Micronesia. We report that mixed models optimally extract association information from such samples, demonstrating 88% power to rank the true variant as among the top 10 genome-wide with 56% achieving genome-wide significance, a >80% improvement over the other methods, and demonstrate that population isolates have similar power to non-isolate populations for observing variants of known effects. We then used the mixed-model method to reanalyze data for 17 published phenotypes relating to metabolic traits and electrocardiographic measures, along with another 8 previously unreported. We replicate nine genome-wide significant associations with known loci of plasma cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides, thyroid stimulating hormone, homocysteine, C-reactive protein and uric acid, with only one detected in the previous analysis of the same traits. Further, we leveraged shared identity-by-descent genetic segments in the region of the uric acid locus to fine-map the signal, refining the known locus by a factor of 4. Finally, we report a novel associations for height (rs17629022, P< 2.1 × 10⁻⁸).

Epistasis: obstacle or advantage for mapping complex traits?

Identification of genetic loci in complex traits has focused largely on one-dimensional genome scans to search for associations between single markers and the phenotype. There is mounting evidence that locus interactions, or epistasis, are a crucial component of the genetic architecture of biologically relevant traits. However, epistasis is often viewed as a nuisance factor that reduces power for locus detection. Counter to expectations, recent work shows that fitting full models, instead of testing marker main effect and interaction components separately, in exhaustive multi-locus genome scans can have higher power to detect loci when epistasis is present than single-locus scans, and improvement that comes despite a much larger multiple testing alpha-adjustment in such searches. We demonstrate, both theoretically and via simulation, that the expected power to detect loci when fitting full models is often larger when these loci act epistatically than when they act additively. Additionally, we show that the power for single locus detection may be improved in cases of epistasis compared to the additive model. Our exploration of a two step model selection procedure shows that identifying the true model is difficult. However, this difficulty is certainly not exacerbated by the presence of epistasis, on the contrary, in some cases the presence of epistasis can aid in model selection. The impact of allele frequencies on both power and model selection is dramatic.

Shades of gray: a comparison of linkage disequilibrium between Hutterites and Europeans

Founder or isolated populations have advantages for genetic studies due to decreased genetic and environmental heterogeneity. However, whereas longer-range linkage disequilibrium (LD) in these populations is expected to facilitate gene localization, extensive LD may actually limit the ability for gene discovery. The North American Hutterite population is one of the best characterized young founder populations and members of this isolate have been the subjects of our studies of complex traits, including fertility, asthma and cardiovascular disease, for >20 years. Here, we directly assess the patterns and extent of global LD using single nucleotide polymorphism genotypes with minor allele frequencies (MAFs) > or =5% from the Affymetrix GeneChip Mapping 500 K array in 60 relatively unrelated Hutterites and 60 unrelated Europeans (HapMap CEU). Although LD among some marker pairs extends further in the Hutterites than in Europeans, the pattern of LD and MAF are surprisingly similar. These results indicate that (1) identifying disease genes should be no more difficult in the Hutterites than in outbred European populations, (2) the same common susceptibility alleles for complex diseases should be present in the Hutterites and outbred European populations, and (3) imputation algorithms based on HapMap CEU should be applicable to the Hutterites.

Shared genetic factors in the co-occurrence of symptoms of depression and cardiovascular risk factors

BACKGROUND

We aim to investigate the extent to which shared genetic and shared environmental factors play a role in the co-occurrence of symptoms of depression and cardiovascular risk factors.

METHODS

The analyses included 2383 individuals from a genetically isolated population in the Netherlands (mean age 48.7 years (standard deviation 15.1), percentage of women 56.9%). Symptoms of depression were assessed using the Center for Epidemiology Studies Depression Scale (CES-D) and the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). Assessment of cardiovascular risk factors included systolic and diastolic blood pressure, plasma, glucose levels, high and low density lipoprotein (HDL, LDL) and total cholesterol levels.

RESULTS

Overall, we found that HADS-D was significantly correlated to total cholesterol levels (correlation coefficient [rho]=0.05), and inversely associated to HDL (rho=-0.06). Statistically significant genetic correlations (rho(G)) were found between CES-D scores and total plasma cholesterol (rho(G)=0.30), LDL (rho(G)=0.31) and total cholesterol/HDL ratios (rho(G)=0.25). For HADS-D scores, a significant genetic correlation was found with total cholesterol/HDL ratios (rho(G)=0.27). Environmental correlations (rho(E)) with an opposite direction were found between CES-D and both total cholesterol (rho(E)=-0.16) and LDL (rho(E)=-0.15).

LIMITATION

By adjusting for sibship, we are taking into account environmental effects, however we cannot exclude dominance variance.

CONCLUSIONS

Our study shows that there is evidence for shared genetic factors contributing to the co-occurrence of symptoms of depression and lipid levels. This finding suggests a joint genetic pathogenesis. Future research is encouraged to assess susceptibility genes for mood disorders to be studied for cardiovascular disorders and vice versa.