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Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

Lyme disease is a tick-borne, multi-systemic disease, caused by the bacterium Borrelia burgdorferi. Though antibiotics are used as a primary treatment, relapse often occurs after the discontinuation of antimicrobial agents. The reason for relapse remains unknown, however previous studies suggest the possible presence of antibiotic resistant Borrelia round bodies, persisters and attached biofilm forms. Thus, there is an urgent need to find antimicrobial agents suitable to eliminate all known forms of B. burgdorferi. In this study, natural antimicrobial agents such as Apis mellifera venom and a known component, melittin, were tested using SYBR Green I/PI, direct cell counting, biofilm assays combined with LIVE/DEAD and atomic force microscopy methods. The obtained results were compared to standalone and combinations of antibiotics such as Doxycycline, Cefoperazone, Daptomycin, which were recently found to be effective against Borrelia persisters. Our findings showed that both bee venom and melittin had significant effects on all the tested forms of B. burgdorferi. In contrast, the control antibiotics when used individually or even in combinations had limited effects on the attached biofilm form. These findings strongly suggest that whole bee venom or melittin could be effective antimicrobial agents for B. burgdorferi; however, further research is necessary to evaluate their effectiveness in vivo, as well as their safe and effective delivery method for their therapeutic use.

To assess the contribution of rare coding germline genetic variants to prostate cancer risk and severity, we perform here a meta-analysis of 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline whole exome or genome sequencing data, and one cohort with imputed array data. At the gene level, our case-control collapsing analysis confirms associations between rare damaging variants in four genes and increased prostate cancer risk: SAMHD1 , BRCA2 and ATM at the study-wide significance level ( P  < 1×10 −8 ), and CHEK2 at the suggestive threshold ( P  < 2.6×10 −6 ). Our case-only analysis, reveals that rare damaging variants in AOX1 are associated with more aggressive disease (OR = 2.60 [1.75–3.83], P  = 1.35×10 −6 ), as well as confirming the role of BRCA2 in determining disease severity. At the single-variant level, our study reveals that a rare missense variant in TERT is associated with substantially reduced prostate cancer risk (OR = 0.13 [0.07–0.25], P  = 4.67×10 −10 ), and confirms rare non-synonymous variants in a further three genes associated with reduced risk ( ANO7 , SPDL1 , AR ) and in three with increased risk ( HOXB13 , CHEK2 , BIK ). Altogether, this work provides deeper insights into the genetic architecture and biological basis of prostate cancer risk and severity, with potential implications for clinical risk prediction and therapeutic strategies. By bringing together whole exome and genome sequencing data from five cohorts, the authors assess the contribution of rare germline variants to prostate cancer risk and severity, further validating previously reported genes, and implicating a role for genes not previously reported. Peer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict epigenome features from DNA sequence - to support inference concerning the regulatory effects of disease-associated variants. Here, we evaluate the advantages of training convolutional neural network (CNN) models on a broad set of epigenomic features collected in a single disease-relevant tissue – pancreatic islets in the case of type 2 diabetes (T2D) - as opposed to models trained on multiple human tissues. We report convergence of CNN-based metrics of regulatory function with conventional approaches to variant prioritization – genetic fine-mapping and regulatory annotation enrichment. We demonstrate that CNN-based analyses can refine association signals at T2D-associated loci and provide experimental validation for one such signal. We anticipate that these approaches will become routine in downstream analyses of GWAS.

Obesity is a major risk factor for many common diseases and has a substantial heritable component. To identify new genetic determinants, we performed exome-sequence analyses for adult body mass index (BMI) in up to 587,027 individuals. We identified rare loss-of-function variants in two genes ( BSN and APBA1 ) with effects substantially larger than those of well-established obesity genes such as MC4R . In contrast to most other obesity-related genes, rare variants in BSN and APBA1 were not associated with normal variation in childhood adiposity. Furthermore, BSN protein-truncating variants (PTVs) magnified the influence of common genetic variants associated with BMI, with a common variant polygenic score exhibiting an effect twice as large in BSN PTV carriers than in noncarriers. Finally, we explored the plasma proteomic signatures of BSN PTV carriers as well as the functional consequences of BSN deletion in human induced pluripotent stem cell-derived hypothalamic neurons. Collectively, our findings implicate degenerative processes in synaptic function in the etiology of adult-onset obesity. Analyses of whole-exome sequencing data identify rare loss-of-function variants in BSN associated with adult-onset obesity, type 2 diabetes and fatty liver disease, with stronger effect sizes than those observed for variants in known obesity risk genes such as MC4R.

Aims/hypothesis Genome-wide studies have uncovered multiple independent signals at the RREB1 locus associated with altered type 2 diabetes risk and related glycaemic traits. However, little is known about the function of the zinc finger transcription factor Ras-responsive element binding protein 1 (RREB1) in glucose homeostasis or how changes in its expression and/or function influence diabetes risk. Methods A zebrafish model lacking rreb1a and rreb1b was used to study the effect of RREB1 loss in vivo. Using transcriptomic and cellular phenotyping of a human beta cell model (EndoC-βH1) and human induced pluripotent stem cell (hiPSC)-derived beta-like cells, we investigated how loss of RREB1 expression and activity affects pancreatic endocrine cell development and function. Ex vivo measurements of human islet function were performed in donor islets from carriers of RREB1 type 2 diabetes risk alleles. Results CRISPR/Cas9-mediated loss of rreb1a and rreb1b function in zebrafish supports an in vivo role for the transcription factor in beta cell mass, beta cell insulin expression and glucose levels. Loss of RREB1 also reduced insulin gene expression and cellular insulin content in EndoC-βH1 cells and impaired insulin secretion under prolonged stimulation. Transcriptomic analysis of RREB1 knockdown and knockout EndoC-βH1 cells supports RREB1 as a novel regulator of genes involved in insulin secretion. In vitro differentiation of RREB1 KO/KO hiPSCs revealed dysregulation of pro-endocrine cell genes, including RFX family members, suggesting that RREB1 also regulates genes involved in endocrine cell development. Human donor islets from carriers of type 2 diabetes risk alleles in RREB1 have altered glucose-stimulated insulin secretion ex vivo, consistent with a role for RREB1 in regulating islet cell function. Conclusions/interpretation Together, our results indicate that RREB1 regulates beta cell function by transcriptionally regulating the expression of genes involved in beta cell development and function. Graphical abstract

Whether Borrelia burgdorferi, the causative agent of Lyme disease, can persist for long periods in the human body has been a controversial question. The objective of this study was to see if we could find B. burgdorferi in a Lyme disease patient after a long clinical course and after long-term antibiotic treatment. Therefore, we investigated the potential presence of B. burgdorferi antigens and DNA in human autopsy tissues from a well-documented serum-, PCR-, and culture-positive Lyme disease patient, a 53-year-old female from northern Westchester County in the lower Hudson Valley Region of New York State, who had received extensive antibiotic treatments during extensive antibiotic treatments over the course of her 16-year-long illness. We also asked what form the organism might take, with special interest in the recently found antibiotic-resistant aggregate form, biofilm. We also examined the host tissues for the presence of inflammatory markers such as CD3+ T lymphocytes. Autopsy tissue sections of the brain, heart, kidney, and liver were analyzed by histological and immunohistochemical methods (IHC), confocal microscopy, fluorescent in situ hybridization (FISH), polymerase chain reaction (PCR), and whole-genome sequencing (WGS)/metagenomics. We found significant pathological changes, including borrelial spirochetal clusters, in all of the organs using IHC combined with confocal microscopy. The aggregates contained a well-established biofilm marker, alginate, on their surfaces, suggesting they are true biofilm. We found B. burgdorferi DNA by FISH, polymerase chain reaction (PCR), and an independent verification by WGS/metagenomics, which resulted in the detection of B. burgdorferi sensu stricto specific DNA sequences. IHC analyses showed significant numbers of infiltrating CD3+ T lymphocytes present next to B. burgdorferi biofilms. In summary, we provide several lines of evidence that suggest that B. burgdorferi can persist in the human body, not only in the spirochetal but also in the antibiotic-resistant biofilm form, even after long-term antibiotic treatment. The presence of infiltrating lymphocytes in the vicinity of B. burgdorferi biofilms suggests that the organism in biofilm form might trigger chronic inflammation.

Background Genome-wide association studies (GWAS) have identified several hundred susceptibility loci for type 2 diabetes (T2D). One critical, but unresolved, issue concerns the extent to which the mechanisms through which these diverse signals influencing T2D predisposition converge on a limited set of biological processes. However, the causal variants identified by GWAS mostly fall into a non-coding sequence, complicating the task of defining the effector transcripts through which they operate. Methods Here, we describe implementation of an analytical pipeline to address this question. First, we integrate multiple sources of genetic, genomic and biological data to assign positional candidacy scores to the genes that map to T2D GWAS signals. Second, we introduce genes with high scores as seeds within a network optimization algorithm (the asymmetric prize-collecting Steiner tree approach) which uses external, experimentally confirmed protein-protein interaction (PPI) data to generate high-confidence sub-networks. Third, we use GWAS data to test the T2D association enrichment of the “non-seed” proteins introduced into the network, as a measure of the overall functional connectivity of the network. Results We find (a) non-seed proteins in the T2D protein-interaction network so generated (comprising 705 nodes) are enriched for association to T2D ( p  = 0.0014) but not control traits, (b) stronger T2D-enrichment for islets than other tissues when we use RNA expression data to generate tissue-specific PPI networks and (c) enhanced enrichment ( p  = 3.9 × 10 − 5 ) when we combine the analysis of the islet-specific PPI network with a focus on the subset of T2D GWAS loci which act through defective insulin secretion. Conclusions These analyses reveal a pattern of non-random functional connectivity between candidate causal genes at T2D GWAS loci and highlight the products of genes including YWHAG , SMAD4 or CDK2 as potential contributors to T2D-relevant islet dysfunction. The approach we describe can be applied to other complex genetic and genomic datasets, facilitating integration of diverse data types into disease-associated networks.

Borrelia burgdorferi, the causative agent of Lyme disease, has been recently shown to form biofilm structures in vitro and in vivo. Biofilms are tightly clustered microbes characterized as resistant aggregations that allow bacteria to withstand harsh environmental conditions, including the administration of antibiotics. Novel antibiotic combinations have recently been identified for B. burgdorferi in vitro, however, due to prohibiting costs, those agents have not been tested in an environment that can mimic the host tissue. Therefore, researchers cannot evaluate their true effectiveness against B. burgdorferi, especially its biofilm form. A skin ex vivo model system could be ideal for these types of experiments due to its cost effectiveness, reproducibility, and ability to investigate host–microbial interactions. Therefore, the main goal of this study was the establishment of a novel ex vivo murine skin biopsy model for B. burgdorferi biofilm research. Murine skin biopsies were inoculated with B. burgdorferi at various concentrations and cultured in different culture media. Two weeks post-infection, murine skin biopsies were analyzed utilizing immunohistochemical (IHC), reverse transcription PCR (RT-PCR), and various microscopy methods to determine B. burgdorferi presence and forms adopted as well as whether it remained live in the skin tissue explants. Our results showed that murine skin biopsies inoculated with 1 × 107 cells of B. burgdorferi and cultured in BSK-H + 6% rabbit serum media for two weeks yielded not just significant amounts of live B. burgdorferi spirochetes but biofilm forms as well. IHC combined with confocal and atomic force microscopy techniques identified specific biofilm markers and spatial distribution of B. burgdorferi aggregates in the infected skin tissues, confirming that they are indeed biofilms. In the future, this ex vivo skin model can be used to study development and antibiotic susceptibility of B. burgdorferi biofilms in efforts to treat Lyme disease effectively.

We performed genome-wide meta-analysis of lipid traits on three samples of Mexican and Mexican American ancestry comprising 4,383 individuals and followed up significant and highly suggestive associations in three additional Hispanic samples comprising 7,876 individuals. Genome-wide significant signals were observed in or near CELSR2 , ZNF259/APOA5 , KANK2/DOCK6 and NCAN/MAU2 for total cholesterol, LPL, ABCA1, ZNF259/APOA5 , LIPC and CETP for HDL cholesterol, CELSR2, APOB and NCAN/MAU2 for LDL cholesterol and GCKR , TRIB1 , ZNF259/APOA5 and NCAN/ MAU2 for triglycerides. Linkage disequilibrium and conditional analyses indicate that signals observed at ABCA1 and LIPC for HDL cholesterol and NCAN/MAU2 for triglycerides are independent of previously reported lead SNP associations. Analyses of lead SNPs from the European Global Lipids Genetics Consortium (GLGC) dataset in our Hispanic samples show remarkable concordance of direction of effects as well as strong correlation in effect sizes. A meta-analysis of the European GLGC and our Hispanic datasets identified five novel regions reaching genome-wide significance: two for total cholesterol ( FN1 and SAMM50 ), two for HDL cholesterol ( LOC100996634 and COPB1 ) and one for LDL cholesterol ( LINC00324/CTC1/PFAS ). The top meta-analysis signals were found to be enriched for SNPs associated with gene expression in a tissue-specific fashion, suggesting an enrichment of tissue-specific function in lipid-associated loci.