Explore the vast range of titles available.

This study evaluated the metabolic effects of Roux-en-Y gastric bypass or diet alone in patients with diabetes who had lost matched amounts of weight. The primary outcome, the change in hepatic insulin sensitivity, was similar in the two groups. Thus, weight loss itself, not effects independent of weight loss, accounted for the results.

The use of observed wearable sensor data (e.g., photoplethysmograms [PPG]) to infer health measures (e.g., glucose level or blood pressure) is a very active area of research. Such technology can have a significant impact on health screening, chronic disease management and remote monitoring. A common approach is to collect sensor data and corresponding labels from a clinical grade device (e.g., blood pressure cuff) and train deep learning models to map one to the other. Although well intentioned, this approach often ignores a principled analysis of whether the input sensor data have enough information to predict the desired metric. We analyze the task of predicting blood pressure from PPG pulse wave analysis. Our review of the prior work reveals that many papers fall prey to data leakage and unrealistic constraints on the task and preprocessing steps. We propose a set of tools to help determine if the input signal in question (e.g., PPG) is indeed a good predictor of the desired label (e.g., blood pressure). Using our proposed tools, we found that blood pressure prediction using PPG has a high multi-valued mapping factor of 33.2% and low mutual information of 9.8%. In comparison, heart rate prediction using PPG, a well-established task, has a very low multi-valued mapping factor of 0.75% and high mutual information of 87.7%. We argue that these results provide a more realistic representation of the current progress toward the goal of wearable blood pressure measurement via PPG pulse wave analysis. For code, see our project page: https://github.com/lirus7/PPG-BP-Analysis

Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. By inserting sequences into a whole-genome phylogeny, we show that 16S rRNA and shotgun metagenomic data generated from the same samples agree in principal coordinates space, taxonomy and phenotype effect size when analyzed with the same tree. A comprehensive microbial resource reconciles genomic and 16S rRNA data in a single tree.

Human genetic variation affects the gut microbiota through a complex combination of environmental and host factors. Here we characterize genetic variations associated with microbial abundances in a single large-scale population-based cohort of 5,959 genotyped individuals with matched gut microbial metagenomes, and dietary and health records (prevalent and follow-up). We identified 567 independent SNP–taxon associations. Variants at the LCT locus associated with Bifidobacterium and other taxa, but they differed according to dairy intake. Furthermore, levels of Faecalicatena lactaris associated with ABO , and suggested preferential utilization of secreted blood antigens as energy source in the gut. Enterococcus faecalis levels associated with variants in the MED13L locus, which has been linked to colorectal cancer. Mendelian randomization analysis indicated a potential causal effect of Morganella on major depressive disorder, consistent with observational incident disease analysis. Overall, we identify and characterize the intricate nature of host–microbiota interactions and their association with disease. Genome-wide association analysis of gut microbial taxa in a single homogenous population-based cohort of 5,959 Finnish individuals identifies 567 independent SNP–taxon associations, including strong associations with LCT , ABO and MED13L .

The collection of fecal material and developments in sequencing technologies have enabled standardised and non-invasive gut microbiome profiling. Microbiome composition from several large cohorts have been cross-sectionally linked to various lifestyle factors and diseases. In spite of these advances, prospective associations between microbiome composition and health have remained uncharacterised due to the lack of sufficiently large and representative population cohorts with comprehensive follow-up data. Here, we analyse the long-term association between gut microbiome variation and mortality in a well-phenotyped and representative population cohort from Finland ( n  = 7211). We report robust taxonomic and functional microbiome signatures related to the Enterobacteriaceae family that are associated with mortality risk during a 15-year follow-up. Our results extend previous cross-sectional studies, and help to establish the basis for examining long-term associations between human gut microbiome composition, incident outcomes, and general health status. Gut microbiome composition has a role in health and disease. Here the authors show that microbiome signatures related to the Enterobacteriaceae family are associated with cause-specific mortality risk in a well phenotyped Finish population over a 15-year follow-up.

Human induced pluripotent stem (iPS) cell technologies coupled with genetic engineering now facilitate the study of the molecular underpinnings of disease in relevant human cell types. Application of CRISPR/Cas9-based approaches for genome-scale functional screening in iPS-derived cells, however, has been limited by technical constraints, including inefficient transduction in pooled format, loss of library representation, and poor cellular differentiation. Herein, we present optimized approaches for whole-genome CRISPR/Cas9 based screening in human iPS derived cardiomyocytes with near genome-wide representation at both the iPS and differentiated cell stages. As proof-of-concept, we perform a screen to investigate mechanisms underlying doxorubicin mediated cell death in iPS derived cardiomyocytes. We identified two poorly characterized, human-specific transporters ( SLCO1A2 , SLCO1B3 ) whose loss of function protects against doxorubicin-cardiotoxicity, but does not affect cell death in cancer cells. This study provides a technical framework for genome-wide functional screening in iPS derived cells and identifies new targets to mitigate doxorubicin-cardiotoxicity in humans.

As noted by Warburg, many cancer cells depend on the consumption of glucose. We performed a genetic screen to identify factors responsible for glucose addiction and recovered the two subunits of the xCT antiporter (system x c − ), which plays an antioxidant role by exporting glutamate for cystine. Disruption of the xCT antiporter greatly improves cell viability after glucose withdrawal, because conservation of glutamate enables cells to maintain mitochondrial respiration. In some breast cancer cells, xCT antiporter expression is upregulated through the antioxidant transcription factor Nrf2 and contributes to their requirement for glucose as a carbon source. In cells carrying patient-derived mitochondrial DNA mutations, the xCT antiporter is upregulated and its inhibition improves mitochondrial function and cell viability. Therefore, although upregulation of the xCT antiporter promotes antioxidant defence, it antagonizes glutamine metabolism and restricts nutrient flexibility. In cells with mitochondrial dysfunction, the potential utility of xCT antiporter inhibition should be further tested. The factors that limit the nutrient flexibility of cells remain largely unknown. Here, the authors identify the glutamate/cysteine antiporter xCT in a genetic screen for glucose dependency and show it determines the ability of cells to survive under conditions of low glucose by limiting the utilization of glutamine.

Metabolic remodeling is now widely regarded as a hallmark of cancer, but it is not clear whether individual metabolic strategies are frequently exploited by many tumours. Here we compare messenger RNA profiles of 1,454 metabolic enzymes across 1,981 tumours spanning 19 cancer types to identify enzymes that are consistently differentially expressed. Our meta-analysis recovers established targets of some of the most widely used chemotherapeutics, including dihydrofolate reductase, thymidylate synthase and ribonucleotide reductase, while also spotlighting new enzymes, such as the mitochondrial proline biosynthetic enzyme PYCR1 . The highest scoring pathway is mitochondrial one-carbon metabolism and is centred on MTHFD2 . MTHFD2 RNA and protein are markedly elevated in many cancers and correlated with poor survival in breast cancer. MTHFD2 is expressed in the developing embryo, but is absent in most healthy adult tissues, even those that are proliferating. Our study highlights the importance of mitochondrial compartmentalization of one-carbon metabolism in cancer and raises important therapeutic hypotheses. Cellular metabolism is dysregulated in cancer and may be reflected in differences in the expression of metabolic genes. In this study, the authors find that mitochondrial folate-coupled dehydrogenase is increased in expression in a wide variety of cancers and negatively correlates with breast cancer patient survival.

Evasion of host immunity is a hallmark of cancer; however, mechanisms linking oncogenic mutations and immune escape are incompletely understood. Through loss-of-function screening of 1,001 tumor suppressor genes, we identified death-associated protein kinase 3 (DAPK3) as a previously unrecognized driver of anti-tumor immunity through the stimulator of interferon genes (STING) pathway of cytosolic DNA sensing. Loss of DAPK3 expression or kinase activity impaired STING activation and interferon (IFN)-β-stimulated gene induction. DAPK3 deficiency in IFN-β-producing tumors drove rapid growth and reduced infiltration of CD103 + CD8α + dendritic cells and cytotoxic lymphocytes, attenuating the response to cancer chemo-immunotherapy. Mechanistically, DAPK3 coordinated post-translational modification of STING. In unstimulated cells, DAPK3 inhibited STING K48-linked poly-ubiquitination and proteasome-mediated degradation. After cGAMP stimulation, DAPK3 was required for STING K63-linked poly-ubiquitination and STING–TANK-binding kinase 1 interaction. Comprehensive phospho-proteomics uncovered a DAPK3-specific phospho-site on the E3 ligase LMO7, critical for LMO7–STING interaction and STING K63-linked poly-ubiquitination. Thus, DAPK3 is an essential kinase for STING activation that drives tumor-intrinsic innate immunity and tumor immune surveillance. Sharma and colleagues identify the kinase DAPK3 as a positive regulator of the STING–interferon-β activation pathway. DAPK3 acts to modify E3 ubiquitin ligases that regulate STING K63-linked poly-ubiquitination.

Metabolic reprogramming has been proposed to be a hallmark of cancer, yet a systematic characterization of the metabolic pathways active in transformed cells is currently lacking. Using mass spectrometry, we measured the consumption and release (CORE) profiles of 219 metabolites from media across the NCI-60 cancer cell lines, and integrated these data with a preexisting atlas of gene expression. This analysis identified glycine consumption and expression of the mitochondrial glycine biosynthetic pathway as strongly correlated with rates of proliferation across cancer cells. Antagonizing glycine uptake and its mitochondrial biosynthesis preferentially impaired rapidly proliferating cells. Moreover, higher expression of this pathway was associated with greater mortality in breast cancer patients. Increased reliance on glycine may represent a metabolic vulnerability for selectively targeting rapid cancer cell proliferation.