Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders.

BACKGROUND: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. METHODS: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. RESULTS: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10-8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10-6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10-7; rs73033497, p = 8.8 × 10-7; rs7914279, p = 6.4 × 10-7), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10-7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10-7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10-7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). CONCLUSIONS: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.

Microbiota control immune regulation in humanized mice.

The microbiome affects development and activity of the immune system, and may modulate immune therapies, but there is little direct information about this control in vivo. We studied how the microbiome affects regulation of human immune cells in humanized mice. When humanized mice were treated with a cocktail of 4 antibiotics, there was an increase in the frequency of effector T cells in the gut wall, circulating levels of IFN-γ, and appearance of anti-nuclear antibodies. Teplizumab, a non-FcR-binding anti-CD3ε antibody, no longer delayed xenograft rejection. An increase in CD8+ central memory cells and IL-10, markers of efficacy of teplizumab, were not induced. IL-10 levels were only decreased when the mice were treated with all 4 but not individual antibiotics. Antibiotic treatment affected CD11b+CD11c+ cells, which produced less IL-10 and IL-27, and showed increased expression of CD86 and activation of T cells when cocultured with T cells and teplizumab. Soluble products in the pellets appeared to be responsible for the reduced IL-27 expression in DCs. Similar changes in IL-10 induction were seen when human peripheral blood mononuclear cells were cultured with human stool samples. We conclude that changes in the microbiome may impact the efficacy of immunosuppressive medications by altering immune regulatory pathways.

Genetic variants associated with autoimmunity drive NFκB signaling and responses to inflammatory stimuli.

The transcription factor nuclear factor κB (NFκB) is a central regulator of inflammation, and genome-wide association studies in subjects with autoimmune disease have identified a number of variants within the NFκB signaling cascade. In addition, causal variant fine-mapping has demonstrated that autoimmune disease susceptibility variants for multiple sclerosis (MS) and ulcerative colitis are strongly enriched within binding sites for NFκB. We report that MS-associated variants proximal to NFκB1 and in an intron of TNFRSF1A (TNFR1) are associated with increased NFκB signaling after tumor necrosis factor-α (TNFα) stimulation. Both variants result in increased degradation of inhibitor of NFκB α (IκBα), a negative regulator of NFκB, and nuclear translocation of p65 NFκB. The variant proximal to NFκB1 controls signaling responses by altering the expression of NFκB itself, with the GG risk genotype expressing 20-fold more p50 NFκB and diminished expression of the negative regulators of the NFκB pathway: TNFα-induced protein 3 (TNFAIP3), B cell leukemia 3 (BCL3), and cellular inhibitor of apoptosis 1 (CIAP1). Finally, naïve CD4 T cells from patients with MS express enhanced activation of p65 NFκB. These results demonstrate that genetic variants associated with risk of developing MS alter NFκB signaling pathways, resulting in enhanced NFκB activation and greater responsiveness to inflammatory stimuli. As such, this suggests that rapid genetic screening for variants associated with NFκB signaling may identify individuals amenable to NFκB or cytokine blockade.

Pleiotropy in complex traits: challenges and strategies.

Genome-wide association studies have identified many variants that each affects multiple traits, particularly across autoimmune diseases, cancers and neuropsychiatric disorders, suggesting that pleiotropic effects on human complex traits may be widespread. However, systematic detection of such effects is challenging and requires new methodologies and frameworks for interpreting cross-phenotype results. In this Review, we discuss the evidence for pleiotropy in contemporary genetic mapping studies, new and established analytical approaches to identifying pleiotropic effects, sources of spurious cross-phenotype effects and study design considerations. We also outline the molecular and clinical implications of such findings and discuss future directions of research.

Weight loss after gastric bypass is associated with a variant at 15q26.1.

The amount of weight loss attained after Roux-en-Y gastric bypass (RYGB) surgery follows a wide and normal distribution, and recent evidence indicates that this weight loss is due to physiological, rather than mechanical, mechanisms. To identify potential genetic factors associated with weight loss after RYGB, we performed a genome-wide association study (GWAS) of 693 individuals undergoing RYGB and then replicated this analysis in an independent population of 327 individuals undergoing RYGB. We found that a 15q26.1 locus near ST8SIA2 and SLCO3A1 was significantly associated with weight loss after RYGB. Expression of ST8SIA2 in omental fat of these individuals at baseline was significantly associated with weight loss after RYGB. Gene expression analysis in RYGB and weight-matched, sham-operated (WMS) mice revealed that expression of St8sia2 and Slco3a1 was significantly altered in metabolically active tissues in RYGB-treated compared to WMS mice. These findings provide strong evidence for specific genetic influences on weight loss after RYGB and underscore the biological nature of the response to RYGB.

Systematic localization of common disease-associated variation in regulatory DNA.

Genome-wide association studies have identified many noncoding variants associated with common diseases and traits. We show that these variants are concentrated in regulatory DNA marked by deoxyribonuclease I (DNase I) hypersensitive sites (DHSs). Eighty-eight percent of such DHSs are active during fetal development and are enriched in variants associated with gestational exposure-related phenotypes. We identified distant gene targets for hundreds of variant-containing DHSs that may explain phenotype associations. Disease-associated variants systematically perturb transcription factor recognition sequences, frequently alter allelic chromatin states, and form regulatory networks. We also demonstrated tissue-selective enrichment of more weakly disease-associated variants within DHSs and the de novo identification of pathogenic cell types for Crohn's disease, multiple sclerosis, and an electrocardiogram trait, without prior knowledge of physiological mechanisms. Our results suggest pervasive involvement of regulatory DNA variation in common human disease and provide pathogenic insights into diverse disorders.

Heritability of the weight loss response to gastric bypass surgery.

CONTEXT: The use of Roux-en-Y gastric bypass (RYGB) surgery to treat severe obesity has grown dramatically. RYGB is highly effective, but the response in individual patients varies widely, and clinical predictors have been able to explain only a fraction of this variation. OBJECTIVE: Our objective was to determine whether there is a significant genetic contribution to weight loss after RYGB. METHODS: We genotyped 848 patients undergoing RYGB. Using identity-by-descent methods, we identified 13 pairs of first-degree relatives. We identified an additional 10 pairs of individuals who were living together but are not genetically related and randomly paired the remaining 794 individuals. We then compared weight loss within and across pairs. RESULTS: First-degree relative pairs had a similar response to surgery, with a 9% mean difference in excess weight loss between members of each pair. This similarity was not seen with cohabitating individuals (26% mean difference; P = 0.005 vs. first-degree pairs) or unrelated individuals (25% mean difference; P = 0.001). Cohabitating individuals had within-pair differences in weight loss no more similar than randomly paired individuals (P = 0.60). The pair relationship explained a significant portion of the variation in weight loss in first-degree relatives [intraclass correlation coefficient (ICC) = 70.4%; P = 0.02] but not in random subjects (ICC = 0.9%; P = 0.48) or genetically unrelated cohabitating individuals (ICC = 14.3%; P = 0.67). CONCLUSIONS: Genetic factors strongly influence the effect of RYGB on body weight. Identification of the specific genes that mediate this effect will advance our understanding of the biological mechanisms of weight loss after RYGB and should help identify patients who will benefit the most from this intervention.

Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology.

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease.

Genetic analysis of human traits in vitro: drug response and gene expression in lymphoblastoid cell lines.

Lymphoblastoid cell lines (LCLs), originally collected as renewable sources of DNA, are now being used as a model system to study genotype-phenotype relationships in human cells, including searches for QTLs influencing levels of individual mRNAs and responses to drugs and radiation. In the course of attempting to map genes for drug response using 269 LCLs from the International HapMap Project, we evaluated the extent to which biological noise and non-genetic confounders contribute to trait variability in LCLs. While drug responses could be technically well measured on a given day, we observed significant day-to-day variability and substantial correlation to non-genetic confounders, such as baseline growth rates and metabolic state in culture. After correcting for these confounders, we were unable to detect any QTLs with genome-wide significance for drug response. A much higher proportion of variance in mRNA levels may be attributed to non-genetic factors (intra-individual variance--i.e., biological noise, levels of the EBV virus used to transform the cells, ATP levels) than to detectable eQTLs. Finally, in an attempt to improve power, we focused analysis on those genes that had both detectable eQTLs and correlation to drug response; we were unable to detect evidence that eQTL SNPs are convincingly associated with drug response in the model. While LCLs are a promising model for pharmacogenetic experiments, biological noise and in vitro artifacts may reduce power and have the potential to create spurious association due to confounding.

Genetic variants near TNFAIP3 on 6q23 are associated with systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease influenced by genetic and environmental factors. We carried out a genome-wide association scan and replication study and found an association between SLE and a variant in TNFAIP3 (rs5029939, meta-analysis P = 2.89 x 10(-12), OR = 2.29). We also found evidence of two independent signals near TNFAIP3 associated with SLE, including one previously associated with rheumatoid arthritis (RA). These results establish that variants near TNFAIP3 contribute to differential risk of SLE and RA.

Genome-wide detection and characterization of positive selection in human populations.

With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2). We used 'long-range haplotype' methods, which were developed to identify alleles segregating in a population that have undergone recent selection, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population:LARGE and DMD, both related to infection by the Lassa virus, in West Africa;SLC24A5 and SLC45A2, both involved in skin pigmentation, in Europe; and EDAR and EDA2R, both involved in development of hair follicles, in Asia.