Crohn’s disease (CD) and ulcerative colitis (UC), the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry with rising prevalence in other populations1. Genome-wide association studies (GWAS) and subsequent meta-analyses of CD and UC2,3 as separate phenotypes implicated previously unsuspected mechanisms, such as autophagy4, in pathogenesis and showed that some IBD loci are shared with other inflammatory diseases5. Here we expand knowledge of relevant pathways by undertaking a meta-analysis of CD and UC genome-wide association scans, with validation of significant findings in more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional and balancing selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe striking overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD.

To identify novel genetic risk factors for rheumatoid arthritis (RA), we conducted a genome-wide association study (GWAS) meta-analysis of 5,539 autoantibody positive RA cases and 20,169 controls of European descent, followed by replication in an independent set of 6,768 RA cases and 8,806 controls. Of 34 SNPs selected for replication, 7 novel RA risk alleles were identified at genome-wide significance (P<5×10−8) in analysis of all 41,282 samples. The associated SNPs are near genes of known immune function, including IL6ST, SPRED2, RBPJ, CCR6, IRF5, and PXK. We also refined the risk alleles at two established RA risk loci (IL2RA and CCL21) and confirmed the association at AFF3. These new associations bring the total number of confirmed RA risk loci to 31 among individuals of European ancestry. An additional 11 SNPs replicated at P<0.05, many of which are validated autoimmune risk alleles, suggesting that most represent bona fide RA risk alleles.

To discover novel RA risk loci, we systematically examined 370 SNPs from 179 independent loci with p<0.001 in a published meta-analysis of RA GWAS of 3,393 cases and 12,462 controls1. We used GRAIL2, a computational method that applies statistical text mining to PubMed abstracts, to score these 179 loci for functional relationships to genes in 16 established RA disease loci1,3-11. We identified 22 loci with a significant degree of functional connectivity. We genotyped 22 representative SNPs in an independent set of 7,957 cases and 11,958 matched controls. Three validate convincingly: CD2/CD58 (rs11586238, p=1×10−6 replication, p=1×10−9 overall), and CD28 (rs1980422, p=5×10−6 replication, p=1×10−9 overall), PRDM1 (rs548234, p=1×10−5 replication, p=2×10−8 overall). An additional four replicate (p<0.0023): TAGAP (rs394581, p=0.0002 replication, p=4×10−7 overall), PTPRC (rs10919563, p=0.0003 replication, p=7×10−7 overall), TRAF6/RAG1 (rs540386, p=0.0008 replication, p=4×10−6 overall), and FCGR2A (rs12746613, p=0.0022 replication, p=2×10−5 overall). Many of these loci are also associated to other immunologic diseases.

Complete sets of cloned protein-encoding open reading frames (ORFs), or ORFeomes, are essential tools for large-scale proteomics and systems biology studies. Here we describe human ORFeome version 3.1 (hORFeome v3.1), currently the largest publicly available resource of full-length human ORFs (available at www.openbiosystems.com). Generated by Gateway recombinational cloning, this collection contains 12,212 ORFs, representing 10,214 human genes, and corresponds to a 51% expansion of the original hORFeome v1.1. An online human ORFeome database, hORFDB, was built and serves as the central repository for all cloned human ORFs (http://horfdb.dfci.harvard.edu). This expansion of the original ORFeome resource greatly increases the potential experimental search space for large-scale proteomics studies, which will lead to the generation of more comprehensive datasets.

Genome-wide association studies have been tremendously successful in identifying genetic variants associated with complex diseases. The majority of association signals are intergenic and evidence is accumulating that a high proportion of signals lie in enhancer regions. We use Capture Hi-C to investigate, for the first time, the interactions between associated variants for four autoimmune diseases and their functional targets in B- and T-cell lines. Here we report numerous looping interactions and provide evidence that only a minority of interactions are common to both B- and T-cell lines, suggesting interactions may be highly cell-type specific; some disease-associated SNPs do not interact with the nearest gene but with more compelling candidate genes (for example, FOXO1, AZI2) often situated several megabases away; and finally, regions associated with different autoimmune diseases interact with each other and the same promoter suggesting common autoimmune gene targets (for example, PTPRC, DEXI and ZFP36L1).

Human natural killer (NK) cells in peripheral blood perform many functions, and classification of specific subsets has been a longstanding goal. We report single-cell RNA sequencing of NK cells, comparing gene expression in unstimulated and interleukin (IL)-2–activated cells from healthy cytomegalovirus (CMV)-negative donors. Three NK cell subsets resembled well-described populations; CD56brightCD16−, CD56dimCD16+CD57−, and CD56dimCD16+CD57+. CD56dimCD16+CD57− cells subdivided to include a population with higher chemokine mRNA and increased frequency of killer-cell immunoglobulin-like receptor expression. Three novel human blood NK cell populations were identified: a population of type I interferon–responding NK cells that were CD56neg; a population exhibiting a cytokine-induced memory-like phenotype, including increased granzyme B mRNA in response to IL-2; and finally, a small population, with low ribosomal expression, downregulation of oxidative phosphorylation, and high levels of immediate early response genes indicative of cellular activation. Analysis of CMV+ donors established that CMV altered the proportion of NK cells in each subset, especially an increase in adaptive NK cells, as well as gene regulation within each subset. Together, these data establish an unexpected diversity in blood NK cells and provide a new framework for analyzing NK cell responses in health and disease.

BackgroundThe composition of the skin microbiome is predicted to play a role in the development of conditions such as atopic eczema and psoriasis. 16S rRNA gene sequencing allows the investigation of bacterial microbiota. A significant challenge in this field is development of cost effective high throughput methodologies for the robust interrogation of the skin microbiota, where biomass is low. Here we describe validation of methodologies for 16S rRNA (ribosomal ribonucleic acid) gene sequencing from the skin microbiome, using the Illumina MiSeq platform, the selection of primer to amplify regions for sequencing and we compare results with the current standard protocols..MethodsDNA was obtained from two low density mock communities of 11 diverse bacterial strains (with and without human DNA supplementation) and from swabs taken from the skin of healthy volunteers. This was amplified using primer pairs covering hypervariable regions of the 16S rRNA gene: primers 63F and 519R (V1-V3); and 347F and 803R (V3-V4). The resultant libraries were indexed for the MiSeq and Roche454 and sequenced. Both data sets were denoised, cleaned of chimeras and analysed using QIIME.ResultsThere was no significant difference in the diversity indices at the phylum and the genus level observed between the platforms. The capture of diversity using the low density mock community samples demonstrated that the primer pair spanning the V3-V4 hypervariable region had better capture when compared to the primer pair for the V1-V3 region and was robust to spiking with human DNA. The pilot data generated using the V3-V4 region from the skin of healthy volunteers was consistent with these results, even at the genus level (Staphylococcus, Propionibacterium, Corynebacterium, Paracoccus, Micrococcus, Enhydrobacter and Deinococcus identified at similar abundances on both platforms).ConclusionsThe results suggest that the bacterial community diversity captured using the V3-V4 16S rRNA hypervariable region from sequencing using the MiSeq platform is comparable to the Roche454 GS Junior platform. These findings provide evidence that the optimised method can be used in human clinical samples of low bacterial biomass such as the investigation of the skin microbiota.Electronic supplementary materialThe online version of this article (doi:10.1186/s12866-017-0927-4) contains supplementary material, which is available to authorized users.

Objective. To define interactions between the HLA-DRB1 shared epitope (SE), PTPN22, and smoking in cyclic citrullinated peptide (CCP) antibody-and rheumatoid factor (RF)-positive and -negative rheumatoid arthritis (RA).Methods. Data on ϳ5,000 RA patients and ϳ3,700 healthy controls recruited from 6 centers in the UK were analyzed; not all centers had both genotype data and smoking data available for study. The magnitude of association was assessed in autoantibodypositive and -negative subgroups. The effect of smoking on antibody status among cases was assessed following adjustment for year of birth and center, using MantelHaenszel analysis. Analyses of the combined effects of PTPN22, HLA-DRB1 SE, and smoking were performed using additive and multiplicative models of interaction within a logistic regression framework.Results. The combined effects of PTPN22, HLA-DRB1 SE, and smoking were defined, with no evidence of departure from a multiplicative model. Within the case population, all 3 factors were independently associated with the generation of CCP antibodies (odds ratio [OR] 11.1, P < 0.0001), whereas only HLA-DRB1 SE and smoking were independently associated with RF production (OR 4.4, P < 0.0001). There was some evidence of increasing likelihood of antibody positivity with heavier smoking. Finally, we demonstrated that smoking was associated with the generation of both CCP and RF antibodies (OR 1.7, P ‫؍‬ 0.0001).Conclusion. PTPN22 appears to be primarily associated with anticitrulline autoimmunity, whereas HLA-DRB1 SE is independently associated with RF. This study has confirmed associations of specific geneenvironment combinations with a substantially increased risk of developing RA. Further work is needed to determine how these data can be used to inform clinical practice.