High-throughput sequencing of large affected cohorts have helped uncover a plethora of risk genes for complex neurodevelopmental disorders. However, untangling complex disease etiology also involves understanding the functional consequences of these mutations in order to connect risk variants to resulting phenotypes. Here, we highlight the efforts of Mannucci and colleagues to define a novel molecular subtype of neurodevelopmental disorder associated with mutations in DHX30 and characterize location-specific mutational effects in cell culture and zebrafish models.

Author information: (1)The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA. (2)Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA. (3)Department of Medical Microbiology, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center, Maastricht, The Netherlands. (4)Department of Medical Microbiology, Amsterdam University Medical Center, Location AMC, Amsterdam, The Netherlands. (5)Department of Medical Microbiology and Infectious Diseases, Erasmus University Medical Centre, Rotterdam, The Netherlands. (6)Department of Global Health, Amsterdam Institute for Global Health and Development, AMC, Amsterdam, The Netherlands. (7)The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA. dantas@wustl.edu. (8)Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA. dantas@wustl.edu. (9)Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA. dantas@wustl.edu. (10)Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA. dantas@wustl.edu. (11)Department of Medical Microbiology, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center, Maastricht, The Netherlands. j.penders@maastrichtuniversity.nl. (12)School for Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University Medical Center, Maastricht, The Netherlands. j.penders@maastrichtuniversity.nl. (#)Contributed equally

Immune checkpoint inhibitors (ICIs) are monoclonal antibodies that block immune inhibitory pathways. Administration of ICIs augments T cell-mediated immune responses against tumor, resulting in improved overall survival in cancer patients. It has emerged that the intestinal microbiome can modulate responses to ICIs via the host immune system and that the use of antibiotics can lead to reduced efficacy of ICIs. Recently, reports that fecal microbiota transplantation can lead to ICI therapy responses in patients previously refractory to therapy suggest that targeting the microbiome may be a viable strategy to reprogram the tumor microenvironment and augment ICI therapy. Intestinal microbial metabolites may also be linked to response rates to ICIs. In addition to response rates, certain toxicities that can arise during ICI therapy have also been found to be associated with the intestinal microbiome, including in particular colitis. A key mechanistic question is how certain microbes can enhance anti-tumor responses or, alternatively, predispose to ICI-associated colitis. Evidence has emerged that the intestinal microbiome can modulate outcomes to ICI therapies via two major mechanisms, including those that are antigen-specific and those that are antigen-independent. Antigen-specific mechanisms occur when epitopes are shared between microbial and tumor antigens that could enhance, or, alternatively, reduce anti-tumor immune responses via cross-reactive adaptive immune cells. Antigen-independent mechanisms include modulation of responses to ICIs by engaging innate and/or adaptive immune cells. To establish microbiome-based biomarkers of outcomes and specifically modulate the intestinal microbiome to enhance efficacy of ICIs in cancer immunotherapy, further prospective interventional studies will be required.

BACKGROUND: The microbiome has emerged as an environmental factor contributing to obesity and type 2 diabetes (T2D). Increasing evidence suggests links between circulating bacterial components (i.e., bacterial DNA), cardiometabolic disease, and blunted response to metabolic interventions. In this aspect, thorough next-generation sequencing-based and contaminant-aware approaches are lacking. To address this, we tested whether bacterial DNA could be amplified in the blood of subjects with obesity and high metabolic risk under strict experimental and analytical control and whether a putative bacterial signature is related to metabolic improvement after bariatric surgery. METHODS: Subjects undergoing bariatric surgery were recruited into sex- and BMI-matched subgroups with (n = 24) or without T2D (n = 24). Bacterial DNA in the blood was quantified and prokaryotic 16S rRNA gene amplicons were sequenced. A contaminant-aware approach was applied to derive a compositional microbial signature from bacterial sequences in all subjects at baseline and at 3 and 12 months after surgery. We modeled associations between bacterial load and composition with host metabolic and anthropometric markers. We further tested whether compositional shifts were related to weight loss response and T2D remission. Lastly, bacteria were visualized in blood samples using catalyzed reporter deposition (CARD)-fluorescence in situ hybridization (FISH). RESULTS: The contaminant-aware blood bacterial signature was associated with metabolic health. Based on bacterial phyla and genera detected in the blood samples, a metabolic syndrome classification index score was derived and shown to robustly classify subjects along their actual clinical group. T2D was characterized by decreased bacterial richness and loss of genera associated with improved metabolic health. Weight loss and metabolic improvement following bariatric surgery were associated with an early and stable increase of these genera in parallel with improvements in key cardiometabolic risk parameters. CARD-FISH allowed the detection of living bacteria in blood samples in obesity. CONCLUSIONS: We show that the circulating bacterial signature reflects metabolic disease and its improvement after bariatric surgery. Our work provides contaminant-aware evidence for the presence of living bacteria in the blood and suggests a putative crosstalk between components of the blood and metabolism in metabolic health regulation.

BACKGROUND: Associations of low lung function with features of poor cardio-metabolic health have been reported. It is, however, unclear whether these co-morbidities reflect causal associations, shared genetic heritability or are confounded by environmental factors. METHODS: We performed three analyses: (1) cardio-metabolic health to lung function association tests in Northern Finland Birth cohort 1966, (2) cross-trait linkage disequilibrium score regression (LDSC) to compare genetic backgrounds and (3) Mendelian randomisation (MR) analysis to assess the causal effect of cardio-metabolic traits and disease on lung function, and vice versa (bidirectional MR). Genetic associations were obtained from the UK Biobank data or published large-scale genome-wide association studies (N > 82,000). RESULTS: We observed a negative genetic correlation between lung function and cardio-metabolic traits and diseases. In Mendelian Randomisation analysis (MR), we found associations between type 2 diabetes (T2D) instruments and forced vital capacity (FVC) as well as FEV1/FVC. Body mass index (BMI) instruments were associated to all lung function traits and C-reactive protein (CRP) instruments to FVC. These genetic associations provide evidence for a causal effect of cardio-metabolic traits on lung function. Multivariable MR suggested independence of these causal effects from other tested cardio-metabolic traits and diseases. Analysis of lung function specific SNPs revealed a potential causal effect of FEV1/FVC on blood pressure. CONCLUSIONS: The present study overcomes many limitations of observational studies by using Mendelian Randomisation. We provide evidence for an independent causal effect of T2D, CRP and BMI on lung function with some of the T2D effect on lung function being attributed to inflammatory mechanisms. Furthermore, this analysis suggests a potential causal effect of FEV1/FVC on blood pressure. Our detailed analysis of the interplay between cardio-metabolic traits and impaired lung function provides the opportunity to improve the quality of existing intervention strategies.

BACKGROUND: Medulloblastoma (MB) is the most common malignant paediatric brain tumour and a leading cause of cancer-related mortality and morbidity. Existing treatment protocols are aggressive in nature resulting in significant neurological, intellectual and physical disabilities for the children undergoing treatment. Thus, there is an urgent need for improved, targeted therapies that minimize these harmful side effects. METHODS: We identified candidate drugs for MB using a network-based systems-pharmacogenomics approach: based on results from a functional genomics screen, we identified a network of interactions implicated in human MB growth regulation. We then integrated drugs and their known mechanisms of action, along with gene expression data from a large collection of medulloblastoma patients to identify drugs with potential to treat MB. RESULTS: Our analyses identified drugs targeting CDK4, CDK6 and AURKA as strong candidates for MB; all of these genes are well validated as drug targets in other tumour types. We also identified non-WNT MB as a novel indication for drugs targeting TUBB, CAD, SNRPA, SLC1A5, PTPRS, P4HB and CHEK2. Based upon these analyses, we subsequently demonstrated that one of these drugs, the new microtubule stabilizing agent, ixabepilone, blocked tumour growth in vivo in mice bearing patient-derived xenograft tumours of the Sonic Hedgehog and Group 3 subtype, providing the first demonstration of its efficacy in MB. CONCLUSIONS: Our findings confirm that this data-driven systems pharmacogenomics strategy is a powerful approach for the discovery and validation of novel therapeutic candidates relevant to MB treatment, and along with data validating ixabepilone in PDX models of the two most aggressive subtypes of medulloblastoma, we present the network analysis framework as a resource for the field.

BACKGROUND: A higher intake of dietary fiber is associated with a decreased risk of chronic inflammatory diseases such as cardiovascular disease and inflammatory bowel disease. This may function in part due to abrogation of chronic systemic inflammation induced by factors such as dysbiotic gut communities. Data regarding the detailed influences of long-term and recent intake of differing dietary fiber sources on the human gut microbiome are lacking. METHODS: In a cohort of 307 generally healthy men, we examined gut microbiomes, profiled by shotgun metagenomic and metatranscriptomic sequencing, and long-term and recent dietary fiber intake in relation to plasma levels of C-reactive protein (CRP), an established biomarker for chronic inflammation. Data were analyzed using multivariate linear mixed models. RESULTS: We found that inflammation-associated gut microbial configurations corresponded with higher CRP levels. A greater intake of dietary fiber was associated with shifts in gut microbiome composition, particularly Clostridiales, and their potential for carbohydrate utilization via polysaccharide degradation. This was particularly true for fruit fiber sources (i.e., pectin). Most striking, fiber intake was associated with significantly greater CRP reduction in individuals without substantial Prevotella copri carriage in the gut, whereas those with P. copri carriage maintained stable CRP levels regardless of fiber intake. CONCLUSIONS: Our findings offer human evidence supporting a fiber-gut microbiota interaction, as well as a potential specific mechanism by which gut-mediated systemic inflammation may be mitigated.

BACKGROUND: Immune-mediated protection is mediated by T cells expressing pathogen-specific T cell antigen receptors (TCR) that are maintained at diverse sites of infection as tissue-resident memory T cells (TRM) or that disseminate as circulating effector-memory (TEM), central memory (TCM), or terminal effector (TEMRA) subsets in blood and tissues. The relationship between circulating and tissue resident T cell subsets in humans remains elusive, and is important for promoting site-specific protective immunity. METHODS: We analyzed the TCR repertoire of the major memory CD4+ and CD8+T cell subsets (TEM, TCM, TEMRA, and TRM) isolated from blood and/or lymphoid organs (spleen, lymph nodes, bone marrow) and lungs of nine organ donors, and blood of three living individuals spanning five decades of life. High-throughput sequencing of the variable (V) portion of individual TCR genes for each subset, tissue, and individual were analyzed for clonal diversity, expansion and overlap between lineage, T cell subsets, and anatomic sites. TCR repertoires were further analyzed for TRBV gene usage and CDR3 edit distance. RESULTS: Across blood, lymphoid organs, and lungs, human memory, and effector CD8+T cells exhibit greater clonal expansion and distinct TRBV usage compared to CD4+T cell subsets. Extensive sharing of clones between tissues was observed for CD8+T cells; large clones specific to TEMRA cells were present in all sites, while TEM cells contained clones shared between sites and with TRM. For CD4+T cells, TEM clones exhibited the most sharing between sites, followed by TRM, while TCM clones were diverse with minimal sharing between sites and subsets. Within sites, TRM clones exhibited tissue-specific expansions, and maintained clonal diversity with age, compared to age-associated clonal expansions in circulating memory subsets. Edit distance analysis revealed tissue-specific biases in clonal similarity. CONCLUSIONS: Our results show that the human memory T cell repertoire comprises clones which persist across sites and subsets, along with clones that are more restricted to certain subsets and/or tissue sites. We also provide evidence that the tissue plays a key role in maintaining memory T cells over age, bolstering the rationale for site-specific targeting of memory reservoirs in vaccines and immunotherapies.

Update of bioRxiv. 2020 Jun 04;:

BACKGROUND: Metagenomic next-generation sequencing (mNGS) of body fluids is an emerging approach to identify occult pathogens in undiagnosed patients. We hypothesized that metagenomic testing can be simultaneously used to detect malignant neoplasms in addition to infectious pathogens. METHODS: From two independent studies (n = 205), we used human data generated from a metagenomic sequencing pipeline to simultaneously screen for malignancies by copy number variation (CNV) detection. In the first case-control study, we analyzed body fluid samples (n = 124) from patients with a clinical diagnosis of either malignancy (positive cases, n = 65) or infection (negative controls, n = 59). In a second verification cohort, we analyzed a series of consecutive cases (n = 81) sent to cytology for malignancy workup that included malignant positives (n = 32), negatives (n = 18), or cases with an unclear gold standard (n = 31). RESULTS: The overall CNV test sensitivity across all studies was 87% (55 of 63) in patients with malignancies confirmed by conventional cytology and/or flow cytometry testing and 68% (23 of 34) in patients who were ultimately diagnosed with cancer but negative by conventional testing. Specificity was 100% (95% CI 95-100%) with no false positives detected in 77 negative controls. In one example, a patient hospitalized with an unknown pulmonary illness had non-diagnostic lung biopsies, while CNVs implicating a malignancy were detectable from bronchoalveolar fluid. CONCLUSIONS: Metagenomic sequencing of body fluids can be used to identify undetected malignant neoplasms through copy number variation detection. This study illustrates the potential clinical utility of a single metagenomic test to uncover the cause of undiagnosed acute illnesses due to cancer or infection using the same specimen.

Precision public health is a relatively new field that integrates components of precision medicine, such as human genomics research, with public health concepts to help improve population health. Despite interest in advancing precision public health initiatives using human genomics research, current and future opportunities in this emerging field remain largely undescribed. To that end, we provide examples of promising opportunities and current applications of genomics research within precision public health and outline future directions within five major domains of public health: biostatistics, environmental health, epidemiology, health policy and health services, and social and behavioral science. To further extend applications of genomics within precision public health research, three key cross-cutting challenges will need to be addressed: developing policies that implement precision public health initiatives at multiple levels, improving data integration and developing more rigorous methodologies, and incorporating initiatives that address health equity. Realizing the potential to better integrate human genomics within precision public health will require transdisciplinary efforts that leverage the strengths of both precision medicine and public health.