Deep genotype imputation captures virtually all heritability of autoimmune vitiligo.

Autoimmune vitiligo is a complex disease involving polygenic risk from at least 50 loci previously identified by genome-wide association studies. The objectives of this study were to estimate and compare vitiligo heritability in European-derived patients using both family-based and 'deep imputation' genotype-based approaches. We estimated family-based heritability (h2FAM) by vitiligo recurrence among a total 8034 first-degree relatives (3776 siblings, 4258 parents or offspring) of 2122 unrelated vitiligo probands. We estimated genotype-based heritability (h2SNP) by deep imputation to Haplotype Reference Consortium and the 1000 Genomes Project data in unrelated 2812 vitiligo cases and 37 079 controls genotyped genome wide, achieving high-quality imputation from markers with minor allele frequency (MAF) as low as 0.0001. Heritability estimated by both approaches was exceedingly high; h2FAM = 0.75-0.83 and h2SNP = 0.78. These estimates are statistically identical, indicating there is essentially no remaining 'missing heritability' for vitiligo. Overall, ~70% of h2SNP is represented by common variants (MAF > 0.01) and 30% by rare variants. These results demonstrate that essentially all vitiligo heritable risk is captured by array-based genotyping and deep imputation. These findings suggest that vitiligo may provide a particularly tractable model for investigation of complex disease genetic architecture and predictive aspects of personalized medicine.

Family Clustering of Autoimmune Vitiligo Results Principally from Polygenic Inheritance of Common Risk Alleles.

Vitiligo is an autoimmune disease that results in patches of depigmented skin and hair. Previous genome-wide association studies (GWASs) of vitiligo have identified 50 susceptibility loci. Variants at the associated loci are generally common and have individually small effects on risk. Most vitiligo cases are "simplex," where there is no family history of vitiligo, though occasional family clustering of vitiligo occurs, and some "multiplex" families report numerous close affected relatives. Here, we investigate whether simplex and multiplex vitiligo comprise different disease subtypes with different underlying genetic etiologies. We developed and compared the performance of several different vitiligo polygenic risk scores derived from GWAS data. By using the best-performing risk score, we find increased polygenic burden of risk alleles identified by GWAS in multiplex vitiligo cases relative to simplex cases. We additionally find evidence of polygenic transmission of common, low-effect-size risk alleles within multiplex-vitiligo-affected families. Our findings strongly suggest that family clustering of vitiligo involves a high burden of the same common, low-effect-size variants that are relevant in simplex cases. We furthermore find that a variant within the major histocompatibility complex (MHC) class II region contributes disproportionately more to risk in multiplex vitiligo cases than in simplex cases, supporting a special role for adaptive immune triggering in the etiology of multiplex cases. We suggest that genetic risk scores can be a useful tool in analyzing the genetic architecture of clinical disease subtypes and identifying subjects with unusual etiologies for further investigation.

Transethnic meta-analysis of metabolic syndrome in a multiethnic study.

Genome-wide association studies (GWAS) have been used to establish thousands of genetic associations across numerous phenotypes. To improve the power of GWAS and generalize associations across ethnic groups, transethnic meta-analysis methods are used to combine the results of several GWAS from diverse ancestries. The goal of this study is to identify genetic associations for eight quantitative metabolic syndrome (MetS) traits through a meta-analysis across four ethnic groups. Traits were measured in the GENetics of Noninsulin dependent Diabetes Mellitus (GENNID) Study which consists of African-American (families = 73, individuals = 288), European-American (families = 79, individuals = 519), Japanese-American (families = 17, individuals = 132), and Mexican-American (families = 113, individuals = 610) samples. Genome-wide association results from these four ethnic groups were combined using four meta-analysis methods: fixed effects, random effects, TransMeta, and MR-MEGA. We provide an empirical comparison of the four meta-analysis methods from the GENNID results, discuss which types of loci (characterized by allelic heterogeneity) appear to be better detected by each of the four meta-analysis methods in the GENNID Study, and validate our results using previous genetic discoveries. We specifically compare the two transethnic methods, TransMeta and MR-MEGA, and discuss how each transethnic method's framework relates to the types of loci best detected by each method.

Cross-disorder analysis of schizophrenia and 19 immune-mediated diseases identifies shared genetic risk.

Many immune diseases occur at different rates among people with schizophrenia compared to the general population. Here, we evaluated whether this phenomenon might be explained by shared genetic risk factors. We used data from large genome-wide association studies to compare the genetic architecture of schizophrenia to 19 immune diseases. First, we evaluated the association with schizophrenia of 581 variants previously reported to be associated with immune diseases at genome-wide significance. We identified five variants with potentially pleiotropic effects. While colocalization analyses were inconclusive, functional characterization of these variants provided the strongest evidence for a model in which genetic variation at rs1734907 modulates risk of schizophrenia and Crohn's disease via altered methylation and expression of EPHB4-a gene whose protein product guides the migration of neuronal axons in the brain and the migration of lymphocytes towards infected cells in the immune system. Next, we investigated genome-wide sharing of common variants between schizophrenia and immune diseases using cross-trait LD score regression. Of the 11 immune diseases with available genome-wide summary statistics, we observed genetic correlation between six immune diseases and schizophrenia: inflammatory bowel disease (rg = 0.12 ± 0.03, P = 2.49 × 10-4), Crohn's disease (rg = 0.097 ± 0.06, P = 3.27 × 10-3), ulcerative colitis (rg = 0.11 ± 0.04, P = 4.05 × 10-3), primary biliary cirrhosis (rg = 0.13 ± 0.05, P = 3.98 × 10-3), psoriasis (rg = 0.18 ± 0.07, P = 7.78 × 10-3) and systemic lupus erythematosus (rg = 0.13 ± 0.05, P = 3.76 × 10-3). With the exception of ulcerative colitis, the degree and direction of these genetic correlations were consistent with the expected phenotypic correlation based on epidemiological data. Our findings suggest shared genetic risk factors contribute to the epidemiological association of certain immune diseases and schizophrenia.

ProxECAT: Proxy External Controls Association Test. A new case-control gene region association test using allele frequencies from public controls.

A primary goal of the recent investment in sequencing is to detect novel genetic associations in health and disease improving the development of treatments and playing a critical role in precision medicine. While this investment has resulted in an enormous total number of sequenced genomes, individual studies of complex traits and diseases are often smaller and underpowered to detect rare variant genetic associations. Existing genetic resources such as the Exome Aggregation Consortium (>60,000 exomes) and the Genome Aggregation Database (~140,000 sequenced samples) have the potential to be used as controls in these studies. Fully utilizing these and other existing sequencing resources may increase power and could be especially useful in studies where resources to sequence additional samples are limited. However, to date, these large, publicly available genetic resources remain underutilized, or even misused, in large part due to the lack of statistical methods that can appropriately use this summary level data. Here, we present a new method to incorporate external controls in case-control analysis called ProxECAT (Proxy External Controls Association Test). ProxECAT estimates enrichment of rare variants within a gene region using internally sequenced cases and external controls. We evaluated ProxECAT in simulations and empirical analyses of obesity cases using both low-depth of coverage (7x) whole-genome sequenced controls and ExAC as controls. We find that ProxECAT maintains the expected type I error rate with increased power as the number of external controls increases. With an accompanying R package, ProxECAT enables the use of publicly available allele frequencies as external controls in case-control analysis.

Factors affecting detection of bimodal sour-savory mixture and inter-individual umami taste perception.

While basic taste interactions have been the subject of many research studies, there is one combination where data is limited in the literature: sour and umami. This combination is universal in culinary preparations and of key interest to the food industry. Therefore, the primary goal of the present study is to assess how increasing concentrations of acidity (citric acid) affect, if at all, the intensity of a constant concentration of umami (monosodium glutamate, MSG). The secondary goal is to investigate other possible factors in umami taste perception. Here, a crowdsourced cohort of 734 individuals (age range 8-81) tasted and rated the intensity of 50 mM MSG alone, and in combination with citric acid at varying concentrations (1.25 mM, 6.25 mM, 31.25 mM). Participants were also genotyped for the single nucleotide polymorphism rs34160967 in the T1R1 gene. The results show a significant decrease in the intensity perception of umami as sour concentration increases (low: p = 0.005, medium: p < 0.001, high: p < 0.001). Situational factors such as participant hunger level and time since last eating also have a significant effect on umami intensity perception. Neither the biological factors of sex, age, and ancestry appear to play a role in umami perception, nor does variation in gene TAS1R1 at rs34160967. These new data contribute to the growing field of taste and sensory interaction by giving evidence that sour suppresses umami taste perception in bi-model samples.

Autoimmune vitiligo is associated with gain-of-function by a transcriptional regulator that elevates expression of HLA-A*02:01 in vivo.

HLA-A is a class I major histocompatibility complex receptor that presents peptide antigens on the surface of most cells. Vitiligo, an autoimmune disease in which skin melanocytes are destroyed by cognate T cells, is associated with variation in the HLA-A gene; specifically HLA-A*02:01, which presents multiple vitiligo melanocyte autoantigens. Refined genetic mapping localizes vitiligo risk in the HLA-A region to an SNP haplotype ∼20-kb downstream, spanning an ENCODE element with many characteristics of a transcriptional enhancer. Convergent CTCF insulator sites flanking the HLA-A gene promoter and the predicted transcriptional regulator, with apparent interaction between these sites, suggests this element regulates the HLA-A promoter. Peripheral blood mononuclear cells from healthy subjects homozygous for the high-risk haplotype expressed 39% more HLA-A RNA than cells from subjects carrying nonhigh-risk haplotypes (P = 0.0048). Similarly, RNAseq analysis of 1,000 Genomes Project data showed more HLA-A mRNA expressed in subjects homozygous for the high-risk allele of lead SNP rs60131261 than subjects homozygous for the low-risk allele (P = 0.006). Reporter plasmid transfection and genomic run-on sequence analyses confirm that the HLA-A transcriptional regulator contains multiple bidirectional promoters, with greatest activity on the high-risk haplotype, although it does not behave as a classic enhancer. Vitiligo risk associated with the MHC class I region thus derives from combined quantitative and qualitative phenomena: a SNP haplotype in a transcriptional regulator that induces gain-of-function, elevating expression of HLA-A RNA in vivo, in strong linkage disequilibrium with an HLA-A allele that confers *02:01 specificity.

MHC class II super-enhancer increases surface expression of HLA-DR and HLA-DQ and affects cytokine production in autoimmune vitiligo.

Genetic risk for autoimmunity in HLA genes is most often attributed to structural specificity resulting in presentation of self-antigens. Autoimmune vitiligo is strongly associated with the MHC class II region. Here, we fine-map vitiligo MHC class II genetic risk to three SNPs only 47 bp apart, located within a predicted super-enhancer in an intergenic region between HLA-DRB1 and HLA-DQA1, localized by a genome-wide association study of 2,853 Caucasian vitiligo patients. The super-enhancer corresponds to an expression quantitative trait locus for expression of HLA-DR and HLA-DQ RNA; we observed elevated surface expression of HLA-DR (P = 0.008) and HLA-DQ (P = 0.02) on monocytes from healthy subjects homozygous for the high-risk SNP haplotype. Unexpectedly, pathogen-stimulated peripheral blood mononuclear cells from subjects homozygous for the high-risk super-enhancer haplotype exhibited greater increase in production of IFN-γ and IL-1ß than cells from subjects homozygous for the low-risk haplotype. Specifically, production of IFN-γ on stimulation of dectin-1, mannose, and Toll-like receptors with Candida albicans and Staphylococcus epidermidis was 2.5- and 2.9-fold higher in high-risk subjects than in low-risk subjects, respectively (P = 0.007 and P = 0.01). Similarly, production of IL-1ß was fivefold higher in high-risk subjects than in low-risk subjects (P = 0.02). Increased production of immunostimulatory cytokines in subjects carrying the high-risk haplotype may act as an "adjuvant" during the presentation of autoantigens, tying together genetic variation in the MHC with the development of autoimmunity. This study demonstrates that for risk of autoimmune vitiligo, expression level of HLA class II molecules is as or more important than antigen specificity.

Genomewide Association Study of African Children Identifies Association of SCHIP1 and PDE8A with Facial Size and Shape.

The human face is a complex assemblage of highly variable yet clearly heritable anatomic structures that together make each of us unique, distinguishable, and recognizable. Relatively little is known about the genetic underpinnings of normal human facial variation. To address this, we carried out a large genomewide association study and two independent replication studies of Bantu African children and adolescents from Mwanza, Tanzania, a region that is both genetically and environmentally relatively homogeneous. We tested for genetic association of facial shape and size phenotypes derived from 3D imaging and automated landmarking of standard facial morphometric points. SNPs within genes SCHIP1 and PDE8A were associated with measures of facial size in both the GWAS and replication cohorts and passed a stringent genomewide significance threshold adjusted for multiple testing of 34 correlated traits. For both SCHIP1 and PDE8A, we demonstrated clear expression in the developing mouse face by both whole-mount in situ hybridization and RNA-seq, supporting their involvement in facial morphogenesis. Ten additional loci demonstrated suggestive association with various measures of facial shape. Our findings, which differ from those in previous studies of European-derived whites, augment understanding of the genetic basis of normal facial development, and provide insights relevant to both human disease and forensics.

Genome-Wide Association Study Reveals Multiple Loci Influencing Normal Human Facial Morphology.

Numerous lines of evidence point to a genetic basis for facial morphology in humans, yet little is known about how specific genetic variants relate to the phenotypic expression of many common facial features. We conducted genome-wide association meta-analyses of 20 quantitative facial measurements derived from the 3D surface images of 3118 healthy individuals of European ancestry belonging to two US cohorts. Analyses were performed on just under one million genotyped SNPs (Illumina OmniExpress+Exome v1.2 array) imputed to the 1000 Genomes reference panel (Phase 3). We observed genome-wide significant associations (p < 5 x 10-8) for cranial base width at 14q21.1 and 20q12, intercanthal width at 1p13.3 and Xq13.2, nasal width at 20p11.22, nasal ala length at 14q11.2, and upper facial depth at 11q22.1. Several genes in the associated regions are known to play roles in craniofacial development or in syndromes affecting the face: MAFB, PAX9, MIPOL1, ALX3, HDAC8, and PAX1. We also tested genotype-phenotype associations reported in two previous genome-wide studies and found evidence of replication for nasal ala length and SNPs in CACNA2D3 and PRDM16. These results provide further evidence that common variants in regions harboring genes of known craniofacial function contribute to normal variation in human facial features. Improved understanding of the genes associated with facial morphology in healthy individuals can provide insights into the pathways and mechanisms controlling normal and abnormal facial morphogenesis.

Identification of Chronic Obstructive Pulmonary Disease Axes That Predict All-Cause Mortality: The COPDGene Study.

Chronic obstructive pulmonary disease (COPD) is a syndrome caused by damage to the lungs that results in decreased pulmonary function and reduced structural integrity. Pulmonary function testing (PFT) is used to diagnose and stratify COPD into severity groups, and computed tomography (CT) imaging of the chest is often used to assess structural changes in the lungs. We hypothesized that the combination of PFT and CT phenotypes would provide a more powerful tool for assessing underlying morphologic differences associated with pulmonary function in COPD than does PFT alone. We used factor analysis of 26 variables to classify 8,157 participants recruited into the COPDGene cohort between January 2008 and June 2011 from 21 clinical centers across the United States. These factors were used as predictors of all-cause mortality using Cox proportional hazards modeling. Five factors explained 80% of the covariance and represented the following domains: factor 1, increased emphysema and decreased pulmonary function; factor 2, airway disease and decreased pulmonary function; factor 3, gas trapping; factor 4, CT variability; and factor 5, hyperinflation. After more than 46,079 person-years of follow-up, factors 1 through 4 were associated with mortality and there was a significant synergistic interaction between factors 1 and 2 on death. Considering CT measures along with PFT in the assessment of COPD can identify patients at particularly high risk for death.

Facial shape manifestations of growth faltering in Tanzanian children.

Variation in the shape of the human face and in stature is determined by complex interactions between genetic and environmental influences. One such environmental influence is malnourishment, which can result in growth faltering, usually diagnosed by means of comparing an individual's stature with a set of age-appropriate standards. These standards for stature, however, are typically ascertained in groups where people are at low risk for growth faltering. Moreover, genetic differences among populations with respect to stature are well established, further complicating the generalizability of stature-based diagnostic tools. In a large sample of children aged 5-19 years, we obtained high-resolution genomic data, anthropometric measures and 3D facial images from individuals within and around the city of Mwanza, Tanzania. With genome-wide complex trait analysis, we partitioned genetic and environmental variance for growth outcomes and facial shape. We found that children with growth faltering have faces that look like those of older and taller children, in a direction opposite to the expected allometric trajectory, and in ways predicted by the environmental portion of covariance at the community and individual levels. The environmental variance for facial shape varied subtly but significantly among communities, whereas genetic differences were minimal. These results reveal that facial shape preserves information about exposure to undernourishment, with important implications for refining assessments of nutritional status in children and the developmental-genetics of craniofacial variation alike.

Genetic associations with lipoprotein subfraction measures differ by ethnicity in the multi-ethnic study of atherosclerosis (MESA).

A recent genome-wide association study associated 62 single nucleotide polymorphisms (SNPs) from 43 genomic loci, with fasting lipoprotein subfractions in European-Americans (EAs) at genome-wide levels of significance across three independent samples. Whether these associations are consistent across ethnicities with a non-European ancestry is unknown. We analyzed 15 lipoprotein subfraction measures, on 1677 African-Americans (AAs), 1450 Hispanic-Americans (HAs), and 775 Chinese-Americans (CHN) participating in the multi-ethnic study of atherosclerosis (MESA). Genome-wide data were obtained using the Affymetrix 6.0 and Illumina HumanOmni chips. Linear regression models between genetic variables and lipoprotein subfractions were adjusted for age, gender, body mass index, smoking, study center, and genetic ancestry (based on principal components), and additionally adjusted for Mexican/Non-Mexican status in HAs. A false discovery rate correction was applied separately within the results for each ethnicity to correct for multiple testing. Power calculations revealed that we did not have the power for SNP-based measures of association, so we analyzed phenotype-specific genetic risk scores (GRSs), constructed as in the original genome-wide analysis. We successfully replicated all 15 GRS-lipoprotein associations in 2527 EAs. Among the 15 significant GRS-lipoprotein associations in EAs, 11 were significant in AAs, 13 in HAs, and 1 in CHNs. Further analyses revealed that ethnicity differences could not be explained by differences in linkage disequilibrium, lipid lowering drugs, diabetes, or gender. Our study emphasizes the importance of ethnicity (here indexing genetic ancestry) in genetic risk for CVD and highlights the need to identify ethnicity-specific genetic variants associated with CVD risk.

Rapid automated landmarking for morphometric analysis of three-dimensional facial scans.

Automated phenotyping is essential for the creation of large, highly standardized datasets from anatomical imaging data. Such datasets can support large-scale studies of complex traits or clinical studies related to precision medicine or clinical trials. We have developed a method that generates three-dimensional landmark data that meet the requirements of standard geometric morphometric analyses. The method is robust and can be implemented without high-performance computing resources. We validated the method using both direct comparison to manual landmarking on the same individuals and also analyses of the variation patterns and outlier patterns in a large dataset of automated and manual landmark data. Direct comparison of manual and automated landmarks reveals that automated landmark data are less variable, but more highly integrated and reproducible. Automated data produce covariation structure that closely resembles that of manual landmarks. We further find that while our method does produce some landmarking errors, they tend to be readily detectable and can be fixed by adjusting parameters used in the registration and control-point steps. Data generated using the method described here have been successfully used to study the genomic architecture of facial shape in two different genome-wide association studies of facial shape.

Taste Responses to Linoleic Acid: A Crowdsourced Population Study.

Dietary fats serve multiple essential roles in human health but may also contribute to acute and chronic health complications. Thus, understanding mechanisms that influence fat ingestion are critical. All sensory systems may contribute relevant cues to fat detection, with the most recent evidence supporting a role for the sense of taste. Taste detection thresholds for fat vary markedly between individuals and responses are not normally distributed. Genetics may contribute to these observations. Using crowdsourced data obtained from families visiting the Denver Museum of Nature & Science, our objective was to estimate the heritability of fat taste (oleogustus). A pedigree analysis was conducted with 106 families (643 individuals) who rated the fat taste intensity of graded concentrations of linoleic acid (LA) embedded in taste strips. The findings estimate that 19% (P = 0.043) of the variability of taste response to LA relative to baseline is heritable at the highest concentration tested.

Progress in methods for rare variant association.

Empirical studies and evolutionary theory support a role for rare variants in the etiology of complex traits. Given this motivation and increasing affordability of whole-exome and whole-genome sequencing, methods for rare variant association have been an active area of research for the past decade. Here, we provide a survey of the current literature and developments from the Genetics Analysis Workshop 19 (GAW19) Collapsing Rare Variants working group. In particular, we present the generalized linear regression framework and associated score statistic for the 2 major types of methods: burden and variance components methods. We further show that by simply modifying weights within these frameworks we arrive at many of the popular existing methods, for example, the cohort allelic sums test and sequence kernel association test. Meta-analysis techniques are also described. Next, we describe the 6 contributions from the GAW19 Collapsing Rare Variants working group. These included development of new methods, such as a retrospective likelihood for family data, a method using genomic structure to compare cases and controls, a haplotype-based meta-analysis, and a permutation-based method for combining different statistical tests. In addition, one contribution compared a mega-analysis of family-based and population-based data to meta-analysis. Finally, the power of existing family-based methods for binary traits was compared. We conclude with suggestions for open research questions.

Mode of Delivery Determines Neonatal Pharyngeal Bacterial Composition and Early Intestinal Colonization.

OBJECTIVES: Bacterial colonization and succession of the human intestine shape development of immune function and risk for allergic disease, yet these processes remain poorly understood. We investigated the relations between delivery mode, initial bacterial inoculation of the infant oropharynx (OP), and intestinal colonization. METHODS: We prospectively collected maternal rectal and vaginal swabs, infant OP aspirates, and infant stool from 23 healthy mother/infant pairs delivering by cesarean (CS) or vaginal delivery (VD) in an academic hospital. Bacterial abundance (16S rRNA sequencing) and community similarity between samples were compared by delivery mode. Shotgun DNA metagenomic sequencing of infant stool was performed. RESULTS: VD infants had higher abundance of Firmicutes (mainly lactobacilli) in OP aspirates whereas CS OP aspirates were enriched in skin bacteria. OP aspirates were more similar to maternal vaginal and rectal microbiomes in VD compared with CS. Bacteroidetes were more abundant through 6 weeks in stool of VD infants. Infant fecal microbiomes in both delivery groups did not resemble maternal rectal or vaginal microbiomes. Differences in fecal bacterial gene potential between CS and VD at 6 weeks clustered in metabolic pathways and were mediated by abundance of Proteobacteria and Bacteroidetes. CONCLUSIONS: CS infants exhibited different microbiota in the oral inoculum, a chaotic pattern of bacterial succession, and a persistent deficit of intestinal Bacteroidetes. Pioneer OP bacteria transferred from maternal vaginal and intestinal communities were not prominent constituents of the early infant fecal microbiome. Oral inoculation at birth may impact the intestinal microenvironment, thereby modulating early succession of intestinal bacteria.

Challenges of linkage analysis in the era of whole-genome sequencing.

Whole-genome sequencing (WGS) is becoming an affordable technology for the study of the genetics of complex traits. With any new technology, experimental designs and statistical methods, both old and new, must be evaluated. One design seeing a resurgence of interest is the use of families. Genetic Analysis Workshop 18 provided the opportunity to evaluate statistical methods applied to WGS data for family-based studies. We summarize the results of five contributions that used linkage in the context of WGS. The investigators took differing approaches, including assessment of false-positive rates in classic two-point linkage, the effects of heterogeneity on linkage and association tests, and the use of linkage to focus association tests. We describe the primary findings of each contribution and note challenges that are not new to those working in family designs or specific to WGS data; for example, choice of phenotype definition, covariate adjustment, and use of longitudinal data may produce different results, making comparisons challenging. We detail new issues brought about by WGS, such as the elevated genome-wide false-positive rate for classic two-point parametric linkage analysis, computational demands in multipoint calculations, and lack of clarity in how to best use linkage to focus association testing. Finally, we comment on when linkage may be helpful for WGS, highlighting where additional research is needed; for example, although linkage analysis has been successful in the study of rare variants of large effect, how to best use family information in the context of rare variants of moderate effect remains an open research question.

Cluster analysis in the COPDGene study identifies subtypes of smokers with distinct patterns of airway disease and emphysema.

BACKGROUND: There is notable heterogeneity in the clinical presentation of patients with COPD. To characterise this heterogeneity, we sought to identify subgroups of smokers by applying cluster analysis to data from the COPDGene study. METHODS: We applied a clustering method, k-means, to data from 10 192 smokers in the COPDGene study. After splitting the sample into a training and validation set, we evaluated three sets of input features across a range of k (user-specified number of clusters). Stable solutions were tested for association with four COPD-related measures and five genetic variants previously associated with COPD at genome-wide significance. The results were confirmed in the validation set. FINDINGS: We identified four clusters that can be characterised as (1) relatively resistant smokers (ie, no/mild obstruction and minimal emphysema despite heavy smoking), (2) mild upper zone emphysema-predominant, (3) airway disease-predominant and (4) severe emphysema. All clusters are strongly associated with COPD-related clinical characteristics, including exacerbations and dyspnoea (p<0.001). We found strong genetic associations between the mild upper zone emphysema group and rs1980057 near HHIP, and between the severe emphysema group and rs8034191 in the chromosome 15q region (p<0.001). All significant associations were replicated at p<0.05 in the validation sample (12/12 associations with clinical measures and 2/2 genetic associations). INTERPRETATION: Cluster analysis identifies four subgroups of smokers that show robust associations with clinical characteristics of COPD and known COPD-associated genetic variants.

Genome-wide analysis of copy number variants and normal facial variation in a large cohort of Bantu Africans.

Similarity in facial characteristics between relatives suggests a strong genetic component underlies facial variation. While there have been numerous studies of the genetics of facial abnormalities and, more recently, single nucleotide polymorphism (SNP) genome-wide association studies (GWASs) of normal facial variation, little is known about the role of genetic structural variation in determining facial shape. In a sample of Bantu African children, we found that only 9% of common copy number variants (CNVs) and 10-kb CNV analysis windows are well tagged by SNPs (r2 ≥ 0.8), indicating that associations with our internally called CNVs were not captured by previous SNP-based GWASs. Here, we present a GWAS and gene set analysis of the relationship between normal facial variation and CNVs in a sample of Bantu African children. We report the top five regions, which had p values ≤ 9.35 × 10-6 and find nominal evidence of independent CNV association (p < 0.05) in three regions previously identified in SNP-based GWASs. The CNV region with strongest association (p = 1.16 × 10-6, 55 losses and seven gains) contains NFATC1, which has been linked to facial morphogenesis and Cherubism, a syndrome involving abnormal lower facial development. Genomic loss in the region is associated with smaller average lower facial depth. Importantly, new loci identified here were not identified in a SNP-based GWAS, suggesting that CNVs are likely involved in determining facial shape variation. Given the plethora of SNP-based GWASs, calling CNVs from existing data may be a relatively inexpensive way to aid in the study of complex traits.