Author information: (1)Université de Paris, INSERM UMR1163, Imagine Institute, Clinical Bioinformatics Laboratory, F-75006, Paris, France. (2)Human Evolutionary Genetics Unit, Institut Pasteur, UMR2000, CNRS, Université de Paris, F-75015, Paris, France. (3)Cytometry and Biomarkers UTechS, CRT, Institut Pasteur, Université de Paris, F-75015, Paris, France. (4)HIBIO, South San Francisco, CA, 94080, USA. (5)Human Genomics and Evolution, Collège de France, F-75005, Paris, France. (6)Cytometry and Biomarkers UTechS, CRT, Institut Pasteur, Université de Paris, F-75015, Paris, France. darragh.duffy@pasteur.fr. (7)Translational Immunology Unit, Institut Pasteur, Université de Paris, F-75015, Paris, France. darragh.duffy@pasteur.fr. (8)Université de Paris, INSERM UMR1163, Imagine Institute, Clinical Bioinformatics Laboratory, F-75006, Paris, France. antonio.rausell@institutimagine.org. (9)Service de Médecine Génomique des Maladies Rares, AP-HP, Necker Hospital for Sick Children, F-75015, Paris, France. antonio.rausell@institutimagine.org. (#)Contributed equally

BACKGROUND: The Colombian population, as well as those in other Latin American regions, arose from a recent tri-continental admixture among Native Americans, Spanish invaders, and enslaved Africans, all of whom passed through a population bottleneck due to widespread infectious diseases that left small isolated local settlements. As a result, the current population reflects multiple founder effects derived from diverse ancestries. METHODS: We characterized the role of admixture and founder effects on the origination of the mutational landscape that led to neurodegenerative disorders under these historical circumstances. Genomes from 900 Colombian individuals with Alzheimer's disease (AD) [n = 376], frontotemporal lobar degeneration-motor neuron disease continuum (FTLD-MND) [n = 197], early-onset dementia not otherwise specified (EOD) [n = 73], and healthy participants [n = 254] were analyzed. We examined their global and local ancestry proportions and screened this cohort for deleterious variants in disease-causing and risk-conferring genes. RESULTS: We identified 21 pathogenic variants in AD-FTLD related genes, and PSEN1 harbored the majority (11 pathogenic variants). Variants were identified from all three continental ancestries. TREM2 heterozygous and homozygous variants were the most common among AD risk genes (102 carriers), a point of interest because the disease risk conferred by these variants differed according to ancestry. Several gene variants that have a known association with MND in European populations had FTLD phenotypes on a Native American haplotype. Consistent with founder effects, identity by descent among carriers of the same variant was frequent. CONCLUSIONS: Colombian demography with multiple mini-bottlenecks probably enhanced the detection of founder events and left a proportionally higher frequency of rare variants derived from the ancestral populations. These findings demonstrate the role of genomically defined ancestry in phenotypic disease expression, a phenotypic range of different rare mutations in the same gene, and further emphasize the importance of inclusiveness in genetic studies.

BACKGROUND: Depression is a disabling and highly prevalent condition where genetic and epigenetic, such as DNA methylation (DNAm), differences contribute to disease risk. DNA methylation is influenced by genetic variation but the association between polygenic risk of depression and DNA methylation is unknown. METHODS: We investigated the association between polygenic risk scores (PRS) for depression and DNAm by conducting a methylome-wide association study (MWAS) in Generation Scotland (N = 8898, mean age = 49.8 years) with replication in the Lothian Birth Cohorts of 1921 and 1936 and adults in the Avon Longitudinal Study of Parents and Children (ALSPAC) (Ncombined = 2049, mean age = 79.1, 69.6 and 47.2 years, respectively). We also conducted a replication MWAS in the ALSPAC children (N = 423, mean age = 17.1 years). Gene ontology analysis was conducted for the cytosine-guanine dinucleotide (CpG) probes significantly associated with depression PRS, followed by Mendelian randomisation (MR) analysis to infer the causal relationship between depression and DNAm. RESULTS: Widespread associations (NCpG = 71, pBonferroni < 0.05, p < 6.3 × 10-8) were found between PRS constructed using genetic risk variants for depression and DNAm in CpG probes that localised to genes involved in immune responses and neural development. The effect sizes for the significant associations were highly correlated between the discovery and replication samples in adults (r = 0.79) and in adolescents (r = 0.82). Gene Ontology analysis showed that significant CpG probes are enriched in immunological processes in the human leukocyte antigen system. Additional MWAS was conducted for each lead genetic risk variant. Over 47.9% of the independent genetic risk variants included in the PRS showed associations with DNAm in CpG probes located in both the same (cis) and distal (trans) locations to the genetic loci (pBonferroni < 0.045). Subsequent MR analysis showed that there are a greater number of causal effects found from DNAm to depression than vice versa (DNAm to depression: pFDR ranged from 0.024 to 7.45 × 10-30; depression to DNAm: pFDR ranged from 0.028 to 0.003). CONCLUSIONS: PRS for depression, especially those constructed from genome-wide significant genetic risk variants, showed methylome-wide differences associated with immune responses. Findings from MR analysis provided evidence for causal effect of DNAm to depression.

BACKGROUND: Recent studies show that human gut microbial composition can determine whether a patient is a responder or non-responder to immunotherapy but have not identified a common microbial signal shared by responding patients. The functional relationship between immunity, intestinal microbiota, and NSCLC response to immune checkpoint inhibitor/inhibition (ICI) in an American cohort remains unexplored. METHODS: RNAlater-preserved fecal samples were collected from 65 pre-treatment (baseline) and post-treatment stage III/IV NSCLC patients undergoing ICI therapy, categorized as responders or non-responders according to RECIST criteria. Pooled and individual responder and non-responder microbiota were transplanted into a gnotobiotic mouse model of lung cancer and treated with ICIs. 16S rDNA and RNA sequencing was performed on patient fecal samples, 16S rDNA sequencing on mouse fecal samples, and flow cytometric analysis on mouse tumor tissue. RESULTS: Responder patients have both a different microbial community structure than non-responders (P = 0.004) and a different bacterial transcriptome (PC2 = 0.03) at baseline. Taxa significantly enriched in responders include amplicon sequence variants (ASVs) belonging to the genera Ruminococcus, Akkermansia, and Faecalibacterium. Pooled and individual responder microbiota transplantation into gnotobiotic mice decreased tumor growth compared to non-responder colonized mice following ICI (P = 0.023, P = 0.019, P = 0.008, respectively). Responder tumors showed an increased anti-tumor cellular phenotype following ICI treatment. Responder mice are enriched with ASVs belonging to the genera Bacteroides, Blautia, Akkermansia, and Faecalibacterium. Overlapping taxa mapping between human and mouse cohorts correlated with tumor size and weight revealed a network highlighting responder-associated ASVs belonging to the genera Colidextribacter, Frisingicoccus, Marvinbryantia, and Blautia which have not yet been reported. CONCLUSIONS: The role of isolate-specific function and bacterial gene expression in gut microbial-driven responsiveness to ICI has been underappreciated. This work supports further investigation using isolate-driven models to characterize the mechanisms underlying this phenomenon.

BACKGROUND: Each year 3-6 million people develop life-threatening severe dengue (SD). Clinical warning signs for SD manifest late in the disease course and are nonspecific, leading to missed cases and excess hospital burden. Better SD prognostics are urgently needed. METHODS: We integrated 11 public datasets profiling the blood transcriptome of 365 dengue patients of all ages and from seven countries, encompassing biological, clinical, and technical heterogeneity. We performed an iterative multi-cohort analysis to identify differentially expressed genes (DEGs) between non-severe patients and SD progressors. Using only these DEGs, we trained an XGBoost machine learning model on public data to predict progression to SD. All model parameters were "locked" prior to validation in an independent, prospectively enrolled cohort of 377 dengue patients in Colombia. We measured expression of the DEGs in whole blood samples collected upon presentation, prior to SD progression. We then compared the accuracy of the locked XGBoost model and clinical warning signs in predicting SD. RESULTS: We identified eight SD-associated DEGs in the public datasets and built an 8-gene XGBoost model that accurately predicted SD progression in the independent validation cohort with 86.4% (95% CI 68.2-100) sensitivity and 79.7% (95% CI 75.5-83.9) specificity. Given the 5.8% proportion of SD cases in this cohort, the 8-gene model had a positive and negative predictive value (PPV and NPV) of 20.9% (95% CI 16.7-25.6) and 99.0% (95% CI 97.7-100.0), respectively. Compared to clinical warning signs at presentation, which had 77.3% (95% CI 58.3-94.1) sensitivity and 39.7% (95% CI 34.7-44.9) specificity, the 8-gene model led to an 80% reduction in the number needed to predict (NNP) from 25.4 to 5.0. Importantly, the 8-gene model accurately predicted subsequent SD in the first three days post-fever onset and up to three days prior to SD progression. CONCLUSIONS: The 8-gene XGBoost model, trained on heterogeneous public datasets, accurately predicted progression to SD in a large, independent, prospective cohort, including during the early febrile stage when SD prediction remains clinically difficult. The model has potential to be translated to a point-of-care prognostic assay to reduce dengue morbidity and mortality without overwhelming limited healthcare resources.

BACKGROUND: The All of Us Research Program (AoURP, "the program") is an initiative, sponsored by the National Institutes of Health (NIH), that aims to enroll one million people (or more) across the USA. Through repeated engagement of participants, a research resource is being created to enable a variety of future observational and interventional studies. The program has also committed to genomic data generation and returning important health-related information to participants. METHODS: Whole-genome sequencing (WGS), variant calling processes, data interpretation, and return-of-results procedures had to be created and receive an Investigational Device Exemption (IDE) from the United States Food and Drug Administration (FDA). The performance of the entire workflow was assessed through the largest known cross-center, WGS-based, validation activity that was refined iteratively through interactions with the FDA over many months. RESULTS: The accuracy and precision of the WGS process as a device for the return of certain health-related genomic results was determined to be sufficient, and an IDE was granted. CONCLUSIONS: We present here both the process of navigating the IDE application process with the FDA and the results of the validation study as a guide to future projects which may need to follow a similar path. Changes to the program in the future will be covered in supplementary submissions to the IDE and will support additional variant classes, sample types, and any expansion to the reportable regions.

BACKGROUND: Increased epigenetic age acceleration (EAA) in survivors of childhood cancer is associated with specific treatment exposures, unfavorable health behaviors, and presence of certain chronic health conditions. To better understand inter-individual variability, we investigated the genetic basis underlying EAA. METHODS: Genome-wide association studies of EAA based on multiple epigenetic clocks (Hannum, Horvath, PhenoAge, and GrimAge) were performed. MethylationEPIC BeadChip array and whole-genome sequencing data were generated with blood-derived DNA from participants in the St. Jude Lifetime Cohort Study (discovery: 2138 pre-existing and 502 newly generated data, all survivors; exploratory: 282 community controls). Linear regression models were fit for each epigenetic age against the allelic dose of each genetic variant, adjusting for age at sampling, sex, and cancer treatment exposures. Fixed-effects meta-analysis was used to combine summary statistics from two discovery data sets. LD (Linkage disequilibrium) score regression was used to estimate single-nucleotide polymorphism (SNP)-based heritability. RESULTS: For EAA-Horvath, a genome-wide significant association was mapped to the SELP gene with the strongest SNP rs732314 (meta-GWAS: β=0.57, P=3.30×10-11). Moreover, the stratified analysis of the association between rs732314 and EAA-Horvath showed a substantial heterogeneity between children and adults (meta-GWAS: β=0.97 vs. 0.51, I2=73.1%) as well as between survivors with and without chest/abdominal/pelvic-RT exposure (β=0.64 vs. 0.31, I2=66.3%). For EAA-Hannum, an association was mapped to the HLA locus with the strongest SNP rs28366133 (meta-GWAS: β=0.78, P=3.78×10-11). There was no genome-wide significant hit for EAA-PhenoAge or EAA-GrimAge. Interestingly, among community controls, rs732314 was associated with EAA-Horvath (β=1.09, P=5.43×10-5), whereas rs28366133 was not associated with EAA-Hannum (β=0.21, P=0.49). The estimated heritability was 0.33 (SE=0.20) for EAA-Horvath and 0.17 (SE=0.23) for EAA-Hannum, but close to zero for EAA-PhenoAge and EAA-GrimAge. CONCLUSIONS: We identified novel genetic variants in the SELP gene and HLA region associated with EAA-Horvath and EAA-Hannum, respectively, among survivors of childhood cancer. The new genetic variants in combination with other replicated known variants can facilitate the identification of survivors at higher risk in developing accelerated aging and potentially inform drug targets for future intervention strategies among vulnerable survivors.

BACKGROUND: The RNA profiles of tumor-educated platelets (TEPs) possess pathological features that could be used for early cancer detection. However, the utility of TEP RNA profiling in detecting early colorectal cancer (CRC) versus noncancerous colorectal diseases has not yet been investigated. This study assesses the diagnostic capacity of TEP RNA profiles in a cohort of patients with CRC and noncancerous diseases. METHODS: Transcriptome sequencing for platelets isolated from 132 patients with CRC at early and late stages and 190 controls consisting of healthy donors and patients with ulcerative disease, Crohn's disease, polyps, and adenomas was performed and analyzed using binary particle swarm optimization coupled with support vector machine to identify genes that contributed to the classification of CRC patients versus controls. The area under the receiver operating curves (AUROCs) and the accuracy of TEP RNA profiles in CRC diagnosis were assessed. RESULTS: TEP RNA profiling achieved high performance in distinguishing and staging CRC patients from the controls. Using the swarm intelligence algorithm, the 921 most contributive genes that classified CRC patients from the controls were identified. AUROCs of 0.928 for the training set via leave-one-out cross-validation and 0.92 for the validation set were achieved, both of which were significantly higher than the clinically utilized serum biomarkers: carcinoembryonic antigen and cancer antigen 19-9. Notably, an AUROC of 0.915 in an external validation set was achieved. For predicting different CRC stages, an AUROC of 0.984 was achieved in the training set and 1.000 in the internal validation set. CONCLUSIONS: RNA profiles of TEPs are of potential diagnostic value for identifying early CRC from noncancerous diseases. Prospective studies are needed to validate its clinical relevance.

BACKGROUND: Identification of causal genes for polygenic human diseases has been extremely challenging, and our understanding of how physiological and pharmacological stimuli modulate genetic risk at disease-associated loci is limited. Specifically, insulin resistance (IR), a common feature of cardiometabolic disease, including type 2 diabetes, obesity, and dyslipidemia, lacks well-powered genome-wide association studies (GWAS), and therefore, few associated loci and causal genes have been identified. METHODS: Here, we perform and integrate linkage disequilibrium (LD)-adjusted colocalization analyses across nine cardiometabolic traits (fasting insulin, fasting glucose, insulin sensitivity, insulin sensitivity index, type 2 diabetes, triglycerides, high-density lipoprotein, body mass index, and waist-hip ratio) combined with expression and splicing quantitative trait loci (eQTLs and sQTLs) from five metabolically relevant human tissues (subcutaneous and visceral adipose, skeletal muscle, liver, and pancreas). To elucidate the upstream regulators and functional mechanisms for these genes, we integrate their transcriptional responses to 21 relevant physiological and pharmacological perturbations in human adipocytes, hepatocytes, and skeletal muscle cells and map their protein-protein interactions. RESULTS: We identify 470 colocalized loci and prioritize 207 loci with a single colocalized gene. Patterns of shared colocalizations across traits and tissues highlight different potential roles for colocalized genes in cardiometabolic disease and distinguish several genes involved in pancreatic β-cell function from others with a more direct role in skeletal muscle, liver, and adipose tissues. At the loci with a single colocalized gene, 42 of these genes were regulated by insulin and 35 by glucose in perturbation experiments, including 17 regulated by both. Other metabolic perturbations regulated the expression of 30 more genes not regulated by glucose or insulin, pointing to other potential upstream regulators of candidate causal genes. CONCLUSIONS: Our use of transcriptional responses under metabolic perturbations to contextualize genetic associations from our custom colocalization approach provides a list of likely causal genes and their upstream regulators in the context of IR-associated cardiometabolic risk.

BACKGROUND: The gut microbiota has been suggested to play a significant role in the development of overweight and obesity. However, the effects of calorie restriction on gut microbiota of overweight and obese adults, especially over longer durations, are largely unexplored. METHODS: Here, we longitudinally analyzed the effects of intermittent calorie restriction (ICR) operationalized as the 5:2 diet versus continuous calorie restriction (CCR) on fecal microbiota of 147 overweight or obese adults in a 50-week parallel-arm randomized controlled trial, the HELENA Trial. The primary outcome of the trial was the differential effects of ICR versus CCR on gene expression in subcutaneous adipose tissue. Changes in the gut microbiome, which are the focus of this publication, were defined as exploratory endpoint of the trial. The trial comprised a 12-week intervention period, a 12-week maintenance period, and a final follow-up period of 26 weeks. RESULTS: Both diets resulted in ~5% weight loss. However, except for Lactobacillales being enriched after ICR, post-intervention microbiome composition did not significantly differ between groups. Overall weight loss was associated with significant metabolic improvements, but not with changes in the gut microbiome. Nonetheless, the abundance of the Dorea genus at baseline was moderately predictive of subsequent weight loss (AUROC of 0.74 for distinguishing the highest versus lowest weight loss quartiles). Despite the lack of consistent intervention effects on microbiome composition, significant study group-independent co-variation between gut bacterial families and metabolic biomarkers, anthropometric measures, and dietary composition was detectable. Our analysis in particular revealed associations between insulin sensitivity (HOMA-IR) and Akkermansiaceae, Christensenellaceae, and Tanerellaceae. It also suggests the possibility of a beneficial modulation of the latter two intestinal taxa by a diet high in vegetables and fiber, and low in processed meat. CONCLUSIONS: Overall, our results suggest that the gut microbiome remains stable and highly individual-specific under dietary calorie restriction. TRIAL REGISTRATION: The trial, including the present microbiome component, was prospectively registered at ClinicalTrials.gov NCT02449148 on May 20, 2015.

BACKGROUND: Previous studies have linked the Mediterranean diet (MED) with improved cardiometabolic health, showing preliminary evidence for a mediating role of the gut microbiome. We recently suggested the Green-Mediterranean (Green-MED) diet as an improved version of the healthy MED diet, with increased consumption of plant-based foods and reduced meat intake. Here, we investigated the effects of MED interventions on the gut microbiota and cardiometabolic markers, and the interplay between the two, during the initial weight loss phase of the DIRECT-PLUS trial. METHODS: In the DIRECT-PLUS study, 294 participants with abdominal obesity/dyslipidemia were prospectively randomized to one of three intervention groups: healthy dietary guidelines (standard science-based nutritional counseling), MED, and Green-MED. Both isocaloric MED and Green-MED groups were supplemented with 28g/day walnuts. The Green-MED group was further provided with daily polyphenol-rich green tea and Mankai aquatic plant (new plant introduced to a western population). Gut microbiota was profiled by 16S rRNA for all stool samples and shotgun sequencing for a select subset of samples. RESULTS: Both MED diets induced substantial changes in the community structure of the gut microbiome, with the Green-MED diet leading to more prominent compositional changes, largely driven by the low abundant, "non-core," microorganisms. The Green-MED diet was associated with specific microbial changes, including enrichments in the genus Prevotella and enzymatic functions involved in branched-chain amino acid degradation, and reductions in the genus Bifidobacterium and enzymatic functions responsible for branched-chain amino acid biosynthesis. The MED and Green-MED diets were also associated with stepwise beneficial changes in body weight and cardiometabolic biomarkers, concomitantly with the increased plant intake and reduced meat intake. Furthermore, while the level of adherence to the Green-MED diet and its specific green dietary components was associated with the magnitude of changes in microbiome composition, changes in gut microbial features appeared to mediate the association between adherence to the Green-MED and body weight and cardiometabolic risk reduction. CONCLUSIONS: Our findings support a mediating role of the gut microbiome in the beneficial effects of the Green-MED diet enriched with Mankai and green tea on cardiometabolic risk factors. TRIAL REGISTRATION: The study was registered on ClinicalTrial.gov ( NCT03020186 ) on January 13, 2017.

BACKGROUND: Pancreatic neuroendocrine neoplasms (PanNENs) fall into two subclasses: the well-differentiated, low- to high-grade pancreatic neuroendocrine tumors (PanNETs), and the poorly-differentiated, high-grade pancreatic neuroendocrine carcinomas (PanNECs). While recent studies suggest an endocrine descent of PanNETs, the origin of PanNECs remains unknown. METHODS: We performed DNA methylation analysis for 57 PanNEN samples and found that distinct methylation profiles separated PanNENs into two major groups, clearly distinguishing high-grade PanNECs from other PanNETs including high-grade NETG3. DNA alterations and immunohistochemistry of cell-type markers PDX1, ARX, and SOX9 were utilized to further characterize PanNECs and their cell of origin in the pancreas. RESULTS: Phylo-epigenetic and cell-type signature features derived from alpha, beta, acinar, and ductal adult cells suggest an exocrine cell of origin for PanNECs, thus separating them in cell lineage from other PanNENs of endocrine origin. CONCLUSIONS: Our study provides a robust and clinically applicable method to clearly distinguish PanNECs from G3 PanNETs, improving patient stratification.