Clonal haematopoiesis and risk of chronic liver disease

Chronic liver disease is a major public health burden worldwide1. Although different aetiologies and mechanisms of liver injury exist, progression of chronic liver disease follows a common pathway of liver inflammation, injury and fibrosis2. Here we examined the association between clonal haematopoiesis of indeterminate potential (CHIP) and chronic liver disease in 214,563 individuals from 4 independent cohorts with whole-exome sequencing data (Framingham Heart Study, Atherosclerosis Risk in Communities Study, UK Biobank and Mass General Brigham Biobank). CHIP was associated with an increased risk of prevalent and incident chronic liver disease (odds ratio = 2.01, 95% confidence interval (95% CI) [1.46, 2.79]; P < 0.001). Individuals with CHIP were more likely to demonstrate liver inflammation and fibrosis detectable by magnetic resonance imaging compared to those without CHIP (odds ratio = 1.74, 95% CI [1.16, 2.60]; P = 0.007). To assess potential causality, Mendelian randomization analyses showed that genetic predisposition to CHIP was associated with a greater risk of chronic liver disease (odds ratio = 2.37, 95% CI [1.57, 3.6]; P < 0.001). In a dietary model of non-alcoholic steatohepatitis, mice transplanted with Tet2-deficient haematopoietic cells demonstrated more severe liver inflammation and fibrosis. These effects were mediated by the NLRP3 inflammasome and increased levels of expression of downstream inflammatory cytokines in Tet2-deficient macrophages. In summary, clonal haematopoiesis is associated with an elevated risk of liver inflammation and chronic liver disease progression through an aberrant inflammatory response.

Genome-wide association study identifies 30 loci associated with bipolar disorder

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.

Implication of LRRC4C and DPP6 in neurodevelopmental disorders

We performed whole-genome sequencing on an individual from a family with variable psychiatric phenotypes that had a sensory processing disorder, apraxia, and autism. The proband harbored a maternally inherited balanced translocation (46,XY,t(11;14)(p12;p12)mat) that disrupted LRRC4C, a member of the highly specialized netrin G family of axon guidance molecules. The proband also inherited a paternally derived chromosomal inversion that disrupted DPP6, a potassium channel interacting protein. Copy Number (CN) analysis in 14,077 cases with neurodevelopmental disorders and 8,960 control subjects revealed that 60% of cases with exonic deletions in LRRC4C had a second clinically recognizable syndrome associated with variable clinical phenotypes, including 16p11.2, 1q44, and 2q33.1 CN syndromes, suggesting LRRC4C deletion variants may be modifiers of neurodevelopmental disorders. In vitro, functional assessments modeling patient deletions in LRRC4C suggest a negative regulatory role of these exons found in the untranslated region of LRRC4C, which has a single, terminal coding exon. These data suggest that the proband's autism may be due to the inheritance of disruptions in both DPP6 and LRRC4C, and may highlight the importance of the netrin G family and potassium channel interacting molecules in neurodevelopmental disorders. © 2016 Wiley Periodicals, Inc.

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

Characterization of bipolar disorder patient-specific induced pluripotent stem cells from a family reveals neurodevelopmental and mRNA expression abnormalities

Bipolar disorder (BD) is a common neuropsychiatric disorder characterized by chronic recurrent episodes of depression and mania. Despite evidence for high heritability of BD, little is known about its underlying pathophysiology. To develop new tools for investigating the molecular and cellular basis of BD, we applied a family-based paradigm to derive and characterize a set of 12 induced pluripotent stem cell (iPSC) lines from a quartet consisting of two BD-affected brothers and their two unaffected parents. Initially, no significant phenotypic differences were observed between iPSCs derived from the different family members. However, upon directed neural differentiation, we observed that CXCR4 (CXC chemokine receptor-4) expressing central nervous system (CNS) neural progenitor cells (NPCs) from both BD patients compared with their unaffected parents exhibited multiple phenotypic differences at the level of neurogenesis and expression of genes critical for neuroplasticity, including WNT pathway components and ion channel subunits. Treatment of the CXCR4(+) NPCs with a pharmacological inhibitor of glycogen synthase kinase 3, a known regulator of WNT signaling, was found to rescue a progenitor proliferation deficit in the BD patient NPCs. Taken together, these studies provide new cellular tools for dissecting the pathophysiology of BD and evidence for dysregulation of key pathways involved in neurodevelopment and neuroplasticity. Future generation of additional iPSCs following a family-based paradigm for modeling complex neuropsychiatric disorders in conjunction with in-depth phenotyping holds promise for providing insights into the pathophysiological substrates of BD and is likely to inform the development of targeted therapeutics for its treatment and ideally prevention.

Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases

Regulatory and coding variants are known to be enriched with associations identified by genome-wide association studies (GWASs) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (hg(2)) across functional categories (while accounting for shared variance due to linkage disequilibrium). Extensive simulations showed that in contrast to current estimates from GWAS summary statistics, the variance-component approach partitions heritability accurately under a wide range of complex-disease architectures. Across the 11 diseases DNaseI hypersensitivity sites (DHSs) from 217 cell types spanned 16% of imputed SNPs (and 24% of genotyped SNPs) but explained an average of 79% (SE = 8%) of hg(2) from imputed SNPs (5.1× enrichment; p = 3.7 × 10(-17)) and 38% (SE = 4%) of hg(2) from genotyped SNPs (1.6× enrichment, p = 1.0 × 10(-4)). Further enrichment was observed at enhancer DHSs and cell-type-specific DHSs. In contrast, coding variants, which span 1% of the genome, explained <10% of hg(2) despite having the highest enrichment. We replicated these findings but found no significant contribution from rare coding variants in independent schizophrenia cohorts genotyped on GWAS and exome chips. Our results highlight the value of analyzing components of heritability to unravel the functional architecture of common disease.

Genome-wide association study in a Swedish population yields support for greater CNV and MHC involvement in schizophrenia compared with bipolar disorder

Schizophrenia (SCZ) and bipolar disorder (BD) are highly heritable psychiatric disorders with overlapping susceptibility loci and symptomatology. We conducted a genome-wide association study (GWAS) of these disorders in a large Swedish sample. We report a new and independent case-control analysis of 1507 SCZ cases, 836 BD cases and 2093 controls. No single-nucleotide polymorphisms (SNPs) achieved significance in these new samples; however, combining new and previously reported SCZ samples (2111 SCZ and 2535 controls) revealed a genome-wide significant association in the major histocompatibility complex (MHC) region (rs886424, P=4.54 × 10(-8)). Imputation using multiple reference panels and meta-analysis with the Psychiatric Genomics Consortium SCZ results underscored the broad, significant association in the MHC region in the full SCZ sample. We evaluated the role of copy number variants (CNVs) in these subjects. As in prior reports, deletions were enriched in SCZ, but not BD cases compared with controls. Singleton deletions were more frequent in both case groups compared with controls (SCZ: P=0.003, BD: P=0.013), whereas the largest CNVs (>500 kb) were significantly enriched only in SCZ cases (P=0.0035). Two CNVs with previously reported SCZ associations were also overrepresented in this SCZ sample: 16p11.2 duplications (P=0.0035) and 22q11 deletions (P=0.03). These results reinforce prior reports of significant MHC and CNV associations in SCZ, but not BD.

Genome-wide comparison of African-ancestry populations from CARe and other cohorts reveals signals of natural selection

The study of recent natural selection in human populations has important applications to human history and medicine. Positive natural selection drives the increase in beneficial alleles and plays a role in explaining diversity across human populations. By discovering traits subject to positive selection, we can better understand the population level response to environmental pressures including infectious disease. Our study examines unusual population differentiation between three large data sets to detect natural selection. The populations examined, African Americans, Nigerians, and Gambians, are genetically close to one another (F(ST) < 0.01 for all pairs), allowing us to detect selection even with moderate changes in allele frequency. We also develop a tree-based method to pinpoint the population in which selection occurred, incorporating information across populations. Our genome-wide significant results corroborate loci previously reported to be under selection in Africans including HBB and CD36. At the HLA locus on chromosome 6, results suggest the existence of multiple, independent targets of population-specific selective pressure. In addition, we report a genome-wide significant (p = 1.36 × 10(-11)) signal of selection in the prostate stem cell antigen (PSCA) gene. The most significantly differentiated marker in our analysis, rs2920283, is highly differentiated in both Africa and East Asia and has prior genome-wide significant associations to bladder and gastric cancers.

A second generation human haplotype map of over 3.1 million SNPs

We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.