Fine-Mapping the Results From Genome-Wide Association Studies of Primary Biliary Cholangitis Using Susie and h2-D2.

The main goal of fine-mapping is the identification of relevant genetic variants that have a causal effect on some trait of interest, such as the presence of a disease. From a statistical point of view, fine mapping can be seen as a variable selection problem. Fine-mapping methods are often challenging to apply because of the presence of linkage disequilibrium (LD), that is, regions of the genome where the variants interrogated have high correlation. Several methods have been proposed to address this issue. Here we explore the 'Sum of Single Effects' (SuSiE) method, applied to real data (summary statistics) from a genome-wide meta-analysis of the autoimmune liver disease primary biliary cholangitis (PBC). Fine-mapping in this data set was previously performed using the FINEMAP program; we compare these previous results with those obtained from SuSiE, which provides an arguably more convenient and principled way of generating 'credible sets', that is set of predictors that are correlated with the response variable. This allows us to appropriately acknowledge the uncertainty when selecting the causal effects for the trait. We focus on the results from SuSiE-RSS, which fits the SuSiE model to summary statistics, such as z-scores, along with a correlation matrix. We also compare the SuSiE results to those obtained using a more recently developed method, h2-D2, which uses the same inputs. Overall, we find the results from SuSiE-RSS and, to a lesser extent, h2-D2, to be quite concordant with those previously obtained using FINEMAP. The resulting genes and biological pathways implicated are therefore also similar to those previously obtained, providing valuable confirmation of these previously reported results. Detailed examination of the credible sets identified suggests that, although for the majority of the loci (33 out of 56) the results from SuSiE-RSS seem most plausible, there are some loci (5 out of 56 loci) where the results from h2-D2 seem more compelling. Computer simulations suggest that, overall, SuSiE-RSS generally has slightly higher power, better precision, and better ability to identify the true number of causal variants in a region than h2-D2, although there are some scenarios where the power of h2-D2 is higher. Thus, in real data analysis, the use of complementary approaches such as both SuSiE and h2-D2 is potentially warranted.

Genetic complexity of diagnostically unresolved Ehlers-Danlos syndrome.

BACKGROUND: The Ehlers-Danlos syndromes (EDS) are heritable disorders of connective tissue (HDCT), reclassified in the 2017 nosology into 13 subtypes. The genetic basis for hypermobile Ehlers-Danlos syndrome (hEDS) remains unknown. METHODS: Whole exome sequencing (WES) was undertaken on 174 EDS patients recruited from a national diagnostic service for complex EDS and a specialist clinic for hEDS. Patients had already undergone expert phenotyping, laboratory investigation and gene sequencing, but were without a genetic diagnosis. Filtered WES data were reviewed for genes underlying Mendelian disorders and loci reported in EDS linkage, transcriptome and genome-wide association studies (GWAS). A genetic burden analysis (Minor Allele Frequency (MAF) <0.05) incorporating 248 Avon Longitudinal Study of Parents and Children (ALSPAC) controls sequenced as part of the UK10K study was undertaken using TASER methodology. RESULTS: Heterozygous pathogenic (P) or likely pathogenic (LP) variants were identified in known EDS and Loeys-Dietz (LDS) genes. Multiple variants of uncertain significance where segregation and functional analysis may enable reclassification were found in genes associated with EDS, LDS, heritable thoracic aortic disease (HTAD), Mendelian disorders with EDS symptomatology and syndromes with EDS-like features. Genetic burden analysis revealed a number of novel loci, although none reached the threshold for genome-wide significance. Variants with biological plausibility were found in genes and pathways not currently associated with EDS or HTAD. CONCLUSIONS: We demonstrate the clinical utility of large panel-based sequencing and WES for patients with complex EDS in distinguishing rare EDS subtypes, LDS and related syndromes. Although many of the P and LP variants reported in this cohort would be identified with current panel testing, they were not at the time of this study, highlighting the use of extended panels and WES as a clinical tool for complex EDS. Our results are consistent with the complex genetic architecture of EDS and suggest a number of novel hEDS and HTAD candidate genes and pathways.

Comparison of regmed and BayesNetty for exploring causal models with many variables.

Here we compare a recently proposed method and software package, regmed, with our own previously developed package, BayesNetty, designed to allow exploratory analysis of complex causal relationships between biological variables. We find that regmed generally has poorer recall but much better precision than BayesNetty. This is perhaps not too surprising as regmed is specifically designed for use with high-dimensional data. BayesNetty is found to be more sensitive to the resulting multiple testing problem encountered in these circumstances. However, as regmed is not designed to handle missing data, its performance is severely affected when missing data is present, whereas the performance of BayesNetty is only slightly affected. The performance of regmed can be rescued in this situation by first using BayesNetty to impute the missing data, and then applying regmed to the resulting "filled-in" data set.

Rare complement factor I variants associated with reduced macular thickness and age-related macular degeneration in the UK Biobank.

To evaluate potential diagnostic and therapeutic biomarkers for age-related macular degeneration (AMD), we identified 8433 UK Biobank participants with rare complement Factor I gene (CFI) variants, 579 with optical coherence tomography-derived macular thickness data. We stratified these variants by predicted gene expression and measured their association with retinal pigment epithelium-Bruch's membrane (RPE-BM) complex and retinal thicknesses at nine macular subfields, as well as AMD risk, using multivariable regression models adjusted for the common complement Factor H gene (CFH) p.Y402H and age-related maculopathy susceptibility protein 2 gene (ARMS2) p.A69S risk genotypes. CFI variants associated with low Factor I levels predicted a thinner mean RPE-BM (95% confidence interval [CI] -1.66 to -0.37 µm, P = 0.002) and retina (95% CI -5.88 to -0.13 µm, P = 0.04) and a higher AMD risk (odds ratio [OR] = 2.26, 95% CI 1.56 to 3.27, P < 0.001). CFI variants associated with normal Factor I levels did not impact mean RPE-BM/retinal thickness (P = 0.28; P = 0.99) or AMD risk (P = 0.97). CFH p.Y402H was associated with a thinner RPE-BM (95% CI -0.31 to -0.18 µm, P < 0.001 heterozygous; 95% CI -0.62 to -0.42 µm, P < 0.001 homozygous) and retina (95% CI -0.73 to -0.12 µm, P = 0.007 heterozygous; 95% CI -1.08 to -0.21 µm, P = 0.004 homozygous). ARMS2 p.A69S did not influence RPE-BM (P = 0.80 heterozygous; P = 0.12 homozygous) or retinal thickness (P = 0.75 heterozygous; P = 0.07 homozygous). p.Y402H and p.A69S exhibited a significant allele-dose response with AMD risk. Thus, CFI rare variants associated with low Factor I levels are robust predictors of reduced macular thickness and AMD. The observed association between macular thickness and CFH p.Y402H, but not ARMS2 p.A69S, highlights the importance of complement dysregulation in early pathogenesis.

Epidemiologic and genetic associations between primary biliary cholangitis and extrahepatic rheumatic diseases.

Patients with primary biliary cholangitis (PBC) commonly experience extrahepatic rheumatic diseases. However, the epidemiologic and genetic associations as well as causal relationship between PBC and these extrahepatic conditions remain undetermined. In this study, we first conducted systematic review and meta-analyses by analyzing 73 studies comprising 334,963 participants across 17 countries and found strong phenotypic associations between PBC and rheumatic diseases. Next, we utilized large-scale genome-wide association study summary data to define the shared genetic architecture between PBC and rheumatic diseases, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc) and Sjögren's syndrome (SS). We observed significant genetic correlations between PBC and each of the four rheumatic diseases. Pleiotropy and heritability enrichment analysis suggested the involvement of humoral immunity and interferon-associated processes for the comorbidity. Of note, we identified four variants shared between PBC and RA (rs80200208), SLE (rs9843053), and SSc (rs27524, rs3873182) using cross-trait meta-analysis. Additionally, several pleotropic loci for PBC and rheumatic diseases were found to share causal variants with gut microbes possessing immunoregulatory functions. Finally, Mendelian randomization revealed consistent evidence for a causal effect of PBC on RA, SLE, SSc, and SS, but no or inconsistent evidence for a causal effect of extrahepatic rheumatic diseases on PBC. Our study reveals a profound genetic overlap and causal relationships between PBC and extrahepatic rheumatic diseases, thus providing insights into shared biological mechanisms and novel therapeutic interventions.

Common Genetic Variants Contribute to Risk of Transposition of the Great Arteries.

RATIONALE: Dextro-transposition of the great arteries (D-TGA) is a severe congenital heart defect which affects approximately 1 in 4,000 live births. While there are several reports of D-TGA patients with rare variants in individual genes, the majority of D-TGA cases remain genetically elusive. Familial recurrence patterns and the observation that most cases with D-TGA are sporadic suggest a polygenic inheritance for the disorder, yet this remains unexplored. OBJECTIVE: We sought to study the role of common single nucleotide polymorphisms (SNPs) in risk for D-TGA. METHODS AND RESULTS: We conducted a genome-wide association study in an international set of 1,237 patients with D-TGA and identified a genome-wide significant susceptibility locus on chromosome 3p14.3, which was subsequently replicated in an independent case-control set (rs56219800, meta-analysis P=8.6x10-10, OR=0.69 per C allele). SNP-based heritability analysis showed that 25% of variance in susceptibility to D-TGA may be explained by common variants. A genome-wide polygenic risk score derived from the discovery set was significantly associated to D-TGA in the replication set (P=4x10-5). The genome-wide significant locus (3p14.3) co-localizes with a putative regulatory element that interacts with the promoter of WNT5A, which encodes the Wnt Family Member 5A protein known for its role in cardiac development in mice. We show that this element drives reporter gene activity in the developing heart of mice and zebrafish and is bound by the developmental transcription factor TBX20. We further demonstrate that TBX20 attenuates Wnt5a expression levels in the developing mouse heart. CONCLUSIONS: This work provides support for a polygenic architecture in D-TGA and identifies a susceptibility locus on chromosome 3p14.3 near WNT5A. Genomic and functional data support a causal role of WNT5A at the locus.

A Bayesian network approach incorporating imputation of missing data enables exploratory analysis of complex causal biological relationships.

Bayesian networks can be used to identify possible causal relationships between variables based on their conditional dependencies and independencies, which can be particularly useful in complex biological scenarios with many measured variables. Here we propose two improvements to an existing method for Bayesian network analysis, designed to increase the power to detect potential causal relationships between variables (including potentially a mixture of both discrete and continuous variables). Our first improvement relates to the treatment of missing data. When there is missing data, the standard approach is to remove every individual with any missing data before performing analysis. This can be wasteful and undesirable when there are many individuals with missing data, perhaps with only one or a few variables missing. This motivates the use of imputation. We present a new imputation method that uses a version of nearest neighbour imputation, whereby missing data from one individual is replaced with data from another individual, their nearest neighbour. For each individual with missing data, the subsets of variables to be used to select the nearest neighbour are chosen by sampling without replacement the complete data and estimating a best fit Bayesian network. We show that this approach leads to marked improvements in the recall and precision of directed edges in the final network identified, and we illustrate the approach through application to data from a recent study investigating the causal relationship between methylation and gene expression in early inflammatory arthritis patients. We also describe a second improvement in the form of a pseudo-Bayesian approach for upweighting certain network edges, which can be useful when there is prior evidence concerning their directions.

Investigating the prediction of CpG methylation levels from SNP genotype data to help elucidate relationships between methylation, gene expression and complex traits.

As popularised by PrediXcan (and related methods), transcriptome-wide association studies (TWAS), in which gene expression is imputed from single-nucleotide polymorphism (SNP) genotypes and tested for association with a phenotype, are a popular approach for investigating the role of gene expression in complex traits. Like gene expression, DNA methylation is an important biological process and, being under genetic regulation, may be imputable from SNP genotypes. Here, we investigate prediction of CpG methylation levels from SNP genotype data to help elucidate relationships between methylation, gene expression and complex traits. We start by examining how well CpG methylation can be predicted from SNP genotypes, comparing three penalised regression approaches and examining whether changing the window size improves prediction accuracy. Although methylation at most CpG sites cannot be accurately predicted from SNP genotypes, for a subset it can be predicted well. We next apply our methylation prediction models (trained using the optimal method and window size) to carry out a methylome-wide association study (MWAS) of primary biliary cholangitis. We intersect the regions identified via MWAS with those identified via TWAS, providing insight into the interplay between CpG methylation, gene expression and disease status. We conclude that MWAS has the potential to improve understanding of biological mechanisms in complex traits.

Heritability and family-based GWAS analyses of the N-acyl ethanolamine and ceramide plasma lipidome.

Signalling lipids of the N-acyl ethanolamine (NAE) and ceramide (CER) classes have emerged as potential biomarkers of cardiovascular disease (CVD). We sought to establish the heritability of plasma NAEs (including the endocannabinoid anandamide) and CERs, to identify common DNA variants influencing the circulating concentrations of the heritable lipids, and assess causality of these lipids in CVD using 2-sample Mendelian randomization (2SMR). Nine NAEs and 16 CERs were analyzed in plasma samples from 999 members of 196 British Caucasian families, using targeted ultra-performance liquid chromatography with tandem mass spectrometry. All lipids were significantly heritable (h2 = 36-62%). A missense variant (rs324420) in the gene encoding the enzyme fatty acid amide hydrolase (FAAH), which degrades NAEs, associated at genome-wide association study (GWAS) significance (P < 5 × 10-8) with four NAEs (DHEA, PEA, LEA and VEA). For CERs, rs680379 in the SPTLC3 gene, which encodes a subunit of the rate-limiting enzyme in CER biosynthesis, associated with a range of species (e.g. CER[N(24)S(19)]; P = 4.82 × 10-27). We observed three novel associations between SNPs at the CD83, SGPP1 and DEGS1 loci, and plasma CER traits (P < 5 × 10-8). 2SMR in the CARDIoGRAMplusC4D cohorts (60 801 cases; 123 504 controls) and in the DIAGRAM cohort (26 488 cases; 83 964 controls), using the genetic instruments from our family-based GWAS, did not reveal association between genetically determined differences in CER levels and CVD or diabetes. Two of the novel GWAS loci, SGPP1 and DEGS1, suggested a casual association between CERs and a range of haematological phenotypes, through 2SMR in the UK Biobank, INTERVAL and UKBiLEVE cohorts (n = 110 000-350 000).

Biallelic variants in CEP164 cause a motile ciliopathy-like syndrome.

Ciliopathies may be classed as primary or motile depending on the underlying ciliary defect and are usually considered distinct clinical entities. Primary ciliopathies are associated with multisystem syndromes typically affecting the brain, kidney, and eye, as well as other organ systems such as the liver, skeleton, auditory system, and metabolism. Motile ciliopathies are a heterogenous group of disorders with defects in specialised motile ciliated tissues found within the lung, brain, and reproductive system, and are associated with primary ciliary dyskinesia, bronchiectasis, infertility and rarely hydrocephalus. Primary and motile cilia share defined core ultra-structures with an overlapping proteome, and human disease phenotypes can reflect both primary and motile ciliopathies. CEP164 encodes a centrosomal distal appendage protein vital for primary ciliogenesis. Human CEP164 mutations are typically described in patients with nephronophthisis-related primary ciliopathies but have also been implicated in motile ciliary dysfunction. Here we describe a patient with an atypical motile ciliopathy phenotype and biallelic CEP164 variants. This work provides further evidence that CEP164 mutations can contribute to both primary and motile ciliopathy syndromes, supporting their functional and clinical overlap, and informs the investigation and management of CEP164 ciliopathy patients.

Bayesian network analysis incorporating genetic anchors complements conventional Mendelian randomization approaches for exploratory analysis of causal relationships in complex data.

Mendelian randomization (MR) implemented through instrumental variables analysis is an increasingly popular causal inference tool used in genetic epidemiology. But it can have limitations for evaluating simultaneous causal relationships in complex data sets that include, for example, multiple genetic predictors and multiple potential risk factors associated with the same genetic variant. Here we use real and simulated data to investigate Bayesian network analysis (BN) with the incorporation of directed arcs, representing genetic anchors, as an alternative approach. A Bayesian network describes the conditional dependencies/independencies of variables using a graphical model (a directed acyclic graph) with an accompanying joint probability. In real data, we found BN could be used to infer simultaneous causal relationships that confirmed the individual causal relationships suggested by bi-directional MR, while allowing for the existence of potential horizontal pleiotropy (that would violate MR assumptions). In simulated data, BN with two directional anchors (mimicking genetic instruments) had greater power for a fixed type 1 error than bi-directional MR, while BN with a single directional anchor performed better than or as well as bi-directional MR. Both BN and MR could be adversely affected by violations of their underlying assumptions (such as genetic confounding due to unmeasured horizontal pleiotropy). BN with no directional anchor generated inference that was no better than by chance, emphasizing the importance of directional anchors in BN (as in MR). Under highly pleiotropic simulated scenarios, BN outperformed both MR (and its recent extensions) and two recently-proposed alternative approaches: a multi-SNP mediation intersection-union test (SMUT) and a latent causal variable (LCV) test. We conclude that BN incorporating genetic anchors is a useful complementary method to conventional MR for exploring causal relationships in complex data sets such as those generated from modern "omics" technologies.

Mouse genetics reveals Barttin as a genetic modifier of Joubert syndrome.

Genetic and phenotypic heterogeneity and the lack of sufficiently large patient cohorts pose a significant challenge to understanding genetic associations in rare disease. Here we identify Bsnd (alias Barttin) as a genetic modifier of cystic kidney disease in Joubert syndrome, using a Cep290-deficient mouse model to recapitulate the phenotypic variability observed in patients by mixing genetic backgrounds in a controlled manner and performing genome-wide analysis of these mice. Experimental down-regulation of Bsnd in the parental mouse strain phenocopied the severe cystic kidney phenotype. A common polymorphism within human BSND significantly associates with kidney disease severity in a patient cohort with CEP290 mutations. The striking phenotypic modifications we describe are a timely reminder of the value of mouse models and highlight the significant contribution of genetic background. Furthermore, if appropriately managed, this can be exploited as a powerful tool to elucidate mechanisms underlying human disease heterogeneity.

Mutations in SPATA13/ASEF2 cause primary angle closure glaucoma.

Current estimates suggest 50% of glaucoma blindness worldwide is caused by primary angle-closure glaucoma (PACG) but the causative gene is not known. We used genetic linkage and whole genome sequencing to identify Spermatogenesis Associated Protein 13, SPATA13 (NM_001166271; NP_001159743, SPATA13 isoform I), also known as ASEF2 (Adenomatous polyposis coli-stimulated guanine nucleotide exchange factor 2), as the causal gene for PACG in a large seven-generation white British family showing variable expression and incomplete penetrance. The 9 bp deletion, c.1432_1440del; p.478_480del was present in all affected individuals with angle-closure disease. We show ubiquitous expression of this transcript in cell lines derived from human tissues and in iris, retina, retinal pigment and ciliary epithelia, cornea and lens. We also identified eight additional mutations in SPATA13 in a cohort of 189 unrelated PACS/PAC/PACG samples. This gene encodes a 1277 residue protein which localises to the nucleus with partial co-localisation with nuclear speckles. In cells undergoing mitosis SPATA13 isoform I becomes part of the kinetochore complex co-localising with two kinetochore markers, polo like kinase 1 (PLK-1) and centrosome-associated protein E (CENP-E). The 9 bp deletion reported in this study increases the RAC1-dependent guanine nucleotide exchange factors (GEF) activity. The increase in GEF activity was also observed in three other variants identified in this study. Taken together, our data suggest that SPATA13 is involved in the regulation of mitosis and the mutations dysregulate GEF activity affecting homeostasis in tissues where it is highly expressed, influencing PACG pathogenesis.

Macrophage scavenger receptor 1 mediates lipid-induced inflammation in non-alcoholic fatty liver disease.

BACKGROUND & AIMS: Obesity-associated inflammation is a key player in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). However, the role of macrophage scavenger receptor 1 (MSR1, CD204) remains incompletely understood. METHODS: A total of 170 NAFLD liver biopsies were processed for transcriptomic analysis and correlated with clinicopathological features. Msr1-/- and wild-type mice were subjected to a 16-week high-fat and high-cholesterol diet. Mice and ex vivo human liver slices were treated with a monoclonal antibody against MSR1. Genetic susceptibility was assessed using genome-wide association study data from 1,483 patients with NAFLD and 430,101 participants of the UK Biobank. RESULTS: MSR1 expression was associated with the occurrence of hepatic lipid-laden foamy macrophages and correlated with the degree of steatosis and steatohepatitis in patients with NAFLD. Mice lacking Msr1 were protected against diet-induced metabolic disorder, showing fewer hepatic foamy macrophages, less hepatic inflammation, improved dyslipidaemia and glucose tolerance, and altered hepatic lipid metabolism. Upon induction by saturated fatty acids, MSR1 induced a pro-inflammatory response via the JNK signalling pathway. In vitro blockade of the receptor prevented the accumulation of lipids in primary macrophages which inhibited the switch towards a pro-inflammatory phenotype and the release of cytokines such as TNF-ɑ. Targeting MSR1 using monoclonal antibody therapy in an obesity-associated NAFLD mouse model and human liver slices resulted in the prevention of foamy macrophage formation and inflammation. Moreover, we identified that rs41505344, a polymorphism in the upstream transcriptional region of MSR1, was associated with altered serum triglycerides and aspartate aminotransferase levels in a cohort of over 400,000 patients. CONCLUSIONS: Taken together, our data suggest that MSR1 plays a critical role in lipid-induced inflammation and could thus be a potential therapeutic target for the treatment of NAFLD. LAY SUMMARY: Non-alcoholic fatty liver disease (NAFLD) is a chronic disease primarily caused by excessive consumption of fat and sugar combined with a lack of exercise or a sedentary lifestyle. Herein, we show that the macrophage scavenger receptor MSR1, an innate immune receptor, mediates lipid uptake and accumulation in Kupffer cells, resulting in liver inflammation and thereby promoting the progression of NAFLD in humans and mice.

A genetic risk score and diabetes predict development of alcohol-related cirrhosis in drinkers.

BACKGROUND & AIMS: Only a minority of excess alcohol drinkers develop cirrhosis. We developed and evaluated risk stratification scores to identify those at highest risk. METHODS: Three cohorts (GenomALC-1: n = 1,690, GenomALC-2: n = 3,037, UK Biobank: relevant n = 6,898) with a history of heavy alcohol consumption (≥80 g/day (men), ≥50 g/day (women), for ≥10 years) were included. Cases were participants with alcohol-related cirrhosis. Controls had a history of similar alcohol consumption but no evidence of liver disease. Risk scores were computed from up to 8 genetic loci identified previously as associated with alcohol-related cirrhosis and 3 clinical risk factors. Score performance for the stratification of alcohol-related cirrhosis risk was assessed and compared across the alcohol-related liver disease spectrum, including hepatocellular carcinoma (HCC). RESULTS: A combination of 3 single nucleotide polymorphisms (SNPs) (PNPLA3:rs738409, SUGP1-TM6SF2:rs10401969, HSD17B13:rs6834314) and diabetes status best discriminated cirrhosis risk. The odds ratios (ORs) and (95% CIs) between the lowest (Q1) and highest (Q5) score quintiles of the 3-SNP score, based on independent allelic effect size estimates, were 5.99 (4.18-8.60) (GenomALC-1), 2.81 (2.03-3.89) (GenomALC-2), and 3.10 (2.32-4.14) (UK Biobank). Patients with diabetes and high risk scores had ORs of 14.7 (7.69-28.1) (GenomALC-1) and 17.1 (11.3-25.7) (UK Biobank) compared to those without diabetes and with low risk scores. Patients with cirrhosis and HCC had significantly higher mean risk scores than patients with cirrhosis alone (0.76 ± 0.06 vs. 0.61 ± 0.02, p = 0.007). Score performance was not significantly enhanced by information on additional genetic risk variants, body mass index or coffee consumption. CONCLUSIONS: A risk score based on 3 genetic risk variants and diabetes status enables the stratification of heavy drinkers based on their risk of cirrhosis, allowing for the provision of earlier preventative interventions. LAY SUMMARY: Excessive chronic drinking leads to cirrhosis in some people, but so far there is no way to identify those at high risk of developing this debilitating disease. We developed a genetic risk score that can identify patients at high risk. The risk of cirrhosis is increased >10-fold with just two risk factors - diabetes and a high genetic risk score. Risk assessment using this test could enable the early and personalised management of this disease in high-risk patients.

X Chromosome Contribution to the Genetic Architecture of Primary Biliary Cholangitis.

BACKGROUND & AIMS: Genome-wide association studies in primary biliary cholangitis (PBC) have failed to find X chromosome (chrX) variants associated with the disease. Here, we specifically explore the chrX contribution to PBC, a sexually dimorphic complex autoimmune disease. METHODS: We performed a chrX-wide association study, including genotype data from 5 genome-wide association studies (from Italy, United Kingdom, Canada, China, and Japan; 5244 case patients and 11,875 control individuals). RESULTS: Single-marker association analyses found approximately 100 loci displaying P < 5 × 10-4, with the most significant being a signal within the OTUD5 gene (rs3027490; P = 4.80 × 10-6; odds ratio [OR], 1.39; 95% confidence interval [CI], 1.028-1.88; Japanese cohort). Although the transethnic meta-analysis evidenced only a suggestive signal (rs2239452, mapping within the PIM2 gene; OR, 1.17; 95% CI, 1.09-1.26; P = 9.93 × 10-8), the population-specific meta-analysis showed a genome-wide significant locus in East Asian individuals pointing to the same region (rs7059064, mapping within the GRIPAP1 gene; P = 6.2 × 10-9; OR, 1.33; 95% CI, 1.21-1.46). Indeed, rs7059064 tags a unique linkage disequilibrium block including 7 genes: TIMM17B, PQBP1, PIM2, SLC35A2, OTUD5, KCND1, and GRIPAP1, as well as a superenhancer (GH0XJ048933 within OTUD5) targeting all these genes. GH0XJ048933 is also predicted to target FOXP3, the main T-regulatory cell lineage specification factor. Consistently, OTUD5 and FOXP3 RNA levels were up-regulated in PBC case patients (1.75- and 1.64-fold, respectively). CONCLUSIONS: This work represents the first comprehensive study, to our knowledge, of the chrX contribution to the genetics of an autoimmune liver disease and shows a novel PBC-related genome-wide significant locus.

rs9459874 and rs1012656 in CCR6/FGFR1OP confer susceptibility to primary biliary cholangitis.

Primary biliary cholangitis (PBC) is a chronic cholestatic autoimmune liver disease that appears to be strongly influenced by genetic factors. Recently, an international meta-analysis of genome-wide association studies (GWAS) identified CC-Motif Chemokine Receptor-6 (CCR6) and FGFR1 Oncogene-Partner (FGFR1OP) as PBC-susceptibility genes. However, the lead single nucleotide polymorphisms (SNPs) of CCR6/FGFR1OP showed low linkage disequilibrium with each other in East Asian and European populations. Additionally, the primary functional variants and the molecular mechanisms responsible for PBC-susceptibility remain unclear. Here, among the PBC-susceptibility SNPs identified by high-density association mapping in our previous meta-GWAS (Patients: n = 10,516; healthy controls: n = 20,772) within the CCR6/FGFR1OP locus, rs9459874 and rs1012656 were identified as primary functional variants. These functional variants accounted for the effects of GWAS-identified lead SNPs in CCR6/FGFR1OP. Additionally, the roles of rs9459874 and rs1012656 in regulating FGFR1OP transcription and CCR6 translation, respectively, were supported by expression quantitative trait loci (eQTL) analysis and gene editing technology using the CRISPR/Cas9 system. Immunohistochemistry showed higher expression of CCR6 protein in the livers of patients with PBC than in those of a non-diseased control. In conclusion, we identified primary functional variants in CCR6/FGFR1OP and revealed the molecular mechanisms by which these variants confer PBC-susceptibility in an eQTL-dependent or -independent manner. The approach in this study is applicable for the elucidation of the pathogenesis of other autoimmune disorders in which CCR6/FGFR1OP is known as a susceptibility locus, as well as PBC.

Genome-wide Association Study and Meta-analysis on Alcohol-Associated Liver Cirrhosis Identifies Genetic Risk Factors.

BACKGROUND AND AIMS: Only a minority of heavy drinkers progress to alcohol-associated cirrhosis (ALC). The aim of this study was to identify common genetic variants that underlie risk for ALC. APPROACH AND RESULTS: We analyzed data from 1,128 subjects of European ancestry with ALC and 614 heavy-drinking subjects without known liver disease from Australia, the United States, the United Kingdom, and three countries in Europe. A genome-wide association study (GWAS) was performed, adjusting for principal components and clinical covariates (alcohol use, age, sex, body mass index, and diabetes). We validated our GWAS findings using UK Biobank. We then performed a meta-analysis combining data from our study, the UK Biobank, and a previously published GWAS. Our GWAS found genome-wide significant risk association of rs738409 in patatin-like phospholipase domain containing 3 (PNPLA3) (odds ratio [OR] = 2.19 [G allele], P = 4.93 × 10-17 ) and rs4607179 near HSD17B13 (OR = 0.57 [C allele], P = 1.09 × 10-10 ) with ALC. Conditional analysis accounting for the PNPLA3 and HSD17B13 loci identified a protective association at rs374702773 in Fas-associated factor family member 2 (FAF2) (OR = 0.61 [del(T) allele], P = 2.56 × 10-8 ) for ALC. This association was replicated in the UK Biobank using conditional analysis (OR = 0.79, P = 0.001). Meta-analysis (without conditioning) confirmed genome-wide significance for the identified FAF2 locus as well as PNPLA3 and HSD17B13. Two other previously known loci (SERPINA1 and SUGP1/TM6SF2) were also genome-wide significant in the meta-analysis. GeneOntology pathway analysis identified lipid droplets as the target for several identified genes. In conclusion, our GWAS identified a locus at FAF2 associated with reduced risk of ALC among heavy drinkers. Like the PNPLA3 and HSD17B13 gene products, the FAF2 product has been localized to fat droplets in hepatocytes. CONCLUSIONS: Our genetic findings implicate lipid droplets in the biological pathway(s) underlying ALC.

Investigation of prediction accuracy and the impact of sample size, ancestry, and tissue in transcriptome-wide association studies.

In transcriptome-wide association studies (TWAS), gene expression values are predicted using genotype data and tested for association with a phenotype. The power of this approach to detect associations relies, at least in part, on the accuracy of the prediction. Here we compare the prediction accuracy of six different methods-LASSO, Ridge regression, Elastic net, Best Linear Unbiased Predictor, Bayesian Sparse Linear Mixed Model, and Random Forests-by performing cross-validation using data from the Geuvadis Project. We also examine prediction accuracy (a) at different sample sizes, (b) when ancestry of the prediction model training and testing populations is different, and (c) when the tissue used to train the model is different from the tissue to be predicted. We find that, for most genes, the expression cannot be accurately predicted, but in general sparse statistical models tend to outperform polygenic models at prediction. Average prediction accuracy is reduced when the model training set size is reduced or when predicting across ancestries and is marginally reduced when predicting across tissues. We conclude that using sparse statistical models and the development of large reference panels across multiple ethnicities and tissues will lead to better prediction of gene expression, and thus may improve TWAS power.

Common and Rare Genetic Variants That Could Contribute to Severe Otitis Media in an Australian Aboriginal Population.

BACKGROUND: Our goal was to identify genetic risk factors for severe otitis media (OM) in Aboriginal Australians. METHODS: Illumina® Omni2.5 BeadChip and imputed data were compared between 21 children with severe OM (multiple episodes chronic suppurative OM and/or perforations or tympanic sclerosis) and 370 individuals without this phenotype, followed by FUnctional Mapping and Annotation (FUMA). Exome data filtered for common (EXaC_all ≥ 0.1) putative deleterious variants influencing protein coding (CADD-scaled scores ≥15] were used to compare 15 severe OM cases with 9 mild cases (single episode of acute OM recorded over ≥3 consecutive years). Rare (ExAC_all ≤ 0.01) such variants were filtered for those present only in severe OM. Enrichr was used to determine enrichment of genes contributing to pathways/processes relevant to OM. RESULTS: FUMA analysis identified 2 plausible genetic risk loci for severe OM: NR3C1 (Pimputed_1000G = 3.62 × 10-6) encoding the glucocorticoid receptor, and NREP (Pimputed_1000G = 3.67 × 10-6) encoding neuronal regeneration-related protein. Exome analysis showed: (i) association of severe OM with variants influencing protein coding (CADD-scaled ≥ 15) in a gene-set (GRXCR1, CDH23, LRP2, FAT4, ARSA, EYA4) enriched for Mammalian Phenotype Level 4 abnormal hair cell stereociliary bundle morphology and related phenotypes; (ii) rare variants influencing protein coding only seen in severe OM provided gene-sets enriched for "abnormal ear" (LMNA, CDH23, LRP2, MYO7A, FGFR1), integrin interactions, transforming growth factor signaling, and cell projection phenotypes including hair cell stereociliary bundles and cilium assembly. CONCLUSIONS: This study highlights interacting genes and pathways related to cilium structure and function that may contribute to extreme susceptibility to OM in Aboriginal Australian children.