Kevin Bullock

A Genome-wide Association Study of the Human Metabolome in a Community-Based Cohort

Because metabolites are hypothesized to play key roles as markers and effectors of cardiometabolic diseases, recent studies have sought to annotate the genetic determinants of circulating metabolite levels. We report a genome-wide association study (GWAS) of 217 plasma metabolites, including >100 not measured in prior GWAS, in 2076 participants of the Framingham Heart Study (FHS). For the majority of analytes, we find that estimated heritability explains >20% of interindividual variation, and that variation attributable to heritable factors is greater than that attributable to clinical factors. Further, we identify 31 genetic loci associated with plasma metabolites, including 23 that have not previously been reported. Importantly, we include GWAS results for all surveyed metabolites and demonstrate how this information highlights a role for AGXT2 in cholesterol ester and triacylglycerol metabolism. Thus, our study outlines the relative contributions of inherited and clinical factors on the plasma metabolome and provides a resource for metabolism research.

Skeletal muscle transcriptional coactivator PGC-1α mediates mitochondrial, but not metabolic, changes during calorie restriction

Calorie restriction (CR) is a dietary intervention that extends lifespan and healthspan in a variety of organisms. CR improves mitochondrial energy production, fuel oxidation, and reactive oxygen species (ROS) scavenging in skeletal muscle and other tissues, and these processes are thought to be critical to the benefits of CR. PGC-1α is a transcriptional coactivator that regulates mitochondrial function and is induced by CR. Consequently, many of the mitochondrial and metabolic benefits of CR are attributed to increased PGC-1α activity. To test this model, we examined the metabolic and mitochondrial response to CR in mice lacking skeletal muscle PGC-1α (MKO). Surprisingly, MKO mice demonstrated a normal improvement in glucose homeostasis in response to CR, indicating that skeletal muscle PGC-1α is dispensable for the whole-body benefits of CR. In contrast, gene expression profiling and electron microscopy (EM) demonstrated that PGC-1α is required for the full CR-induced increases in mitochondrial gene expression and mitochondrial density in skeletal muscle. These results demonstrate that PGC-1α is a major regulator of the mitochondrial response to CR in skeletal muscle, but surprisingly show that neither PGC-1α nor mitochondrial biogenesis in skeletal muscle are required for the whole-body metabolic benefits of CR.

Recurrent Clostridium difficile infection associates with distinct bile acid and microbiome profiles

The healthy microbiome protects against the development of Clostridium difficile infection (CDI), which typically develops following antibiotics. The microbiome metabolises primary to secondary bile acids, a process if disrupted by antibiotics, may be critical for the initiation of CDI.

Blood-Brain Barrier Permeability Is Regulated by Lipid Transport-Dependent Suppression of Caveolae-Mediated Transcytosis

The blood-brain barrier (BBB) provides a constant homeostatic brain environment that is essential for proper neural function. An unusually low rate of vesicular transport (transcytosis) has been identified as one of the two unique properties of CNS endothelial cells, relative to peripheral endothelial cells, that maintain the restrictive quality of the BBB. However, it is not known how this low rate of transcytosis is achieved. Here we provide a mechanism whereby the regulation of CNS endothelial cell lipid composition specifically inhibits the caveolae-mediated transcytotic route readily used in the periphery. An unbiased lipidomic analysis reveals significant differences in endothelial cell lipid signatures from the CNS and periphery, which underlie a suppression of caveolae vesicle formation and trafficking in brain endothelial cells. Furthermore, lipids transported by Mfsd2a establish a unique lipid environment that inhibits caveolae vesicle formation in CNS endothelial cells to suppress transcytosis and ensure BBB integrity.

Distinct metabolomic signatures are associated with longevity in humans.

Alterations in metabolism influence lifespan in experimental models, but data in humans are lacking. Here we use liquid chromatography/mass spectrometry to quantify 217 plasma metabolites and examine their relation to longevity in a large cohort of men and women. In 647 individuals followed for up to 20 years, higher concentrations of the citric acid cycle intermediate, isocitrate, and the bile acid, taurocholate, are associated with lower odds of longevity, defined as attaining 80 years of age. In a larger cohort of 2,327 individuals with metabolite data available, higher concentrations of isocitrate but not taurocholate are also associated with worse cardiovascular health at baseline, as well as risk of future cardiovascular disease and death. None of the metabolites identified are associated with cancer risk. Our findings suggest that some, but not all, metabolic pathways to human longevity are dependent on modifying risk for the two most common causes of death.

An exome array study of the plasma metabolome

The study of rare variants may enhance our understanding of the genetic determinants of the metabolome. Here, we analyze the association between 217 plasma metabolites and exome variants on the Illumina HumanExome Beadchip in 2,076 participants in the Framingham Heart Study, with replication in 1,528 participants of the Atherosclerosis Risk in Communities Study. We identify an association between GMPS and xanthosine using single variant analysis and associations between HAL and histidine, PAH and phenylalanine, and UPB1 and ureidopropionate using gene-based tests (P<5 × 10−8 in meta-analysis), highlighting novel coding variants that may underlie inborn errors of metabolism. Further, we show how an examination of variants across the spectrum of allele frequency highlights independent association signals at select loci and generates a more integrated view of metabolite heritability. These studies build on prior metabolomics genome wide association studies to provide a more complete picture of the genetic architecture of the plasma metabolome.

Metabolomics of Chronic Kidney Disease Progression: A Case-Control Analysis in the Chronic Renal Insufficiency Cohort Study.

Background: Whereas several longitudinal metabolomics studies have been conducted in individuals with normal estimated glomerular filtration rate (eGFR) at baseline, disease progression among individuals with established chronic kidney disease (CKD) has not been rigorously examined. Methods: We performed a nested case-control study of rapid CKD progression in the Chronic Renal Insufficiency Cohort Study, profiling baseline plasma from 200 individuals each with eGFR slope <-3 ml/min/1.73 m2/year (cases) or between -1 and +1 ml/min/1.73 m2/year (controls), matched on baseline eGFR and proteinuria. To directly assess how the kidney modulates circulating metabolites, we profiled plasma from the aorta and renal vein of 25 hospital-based individuals. Results: At baseline, cases and controls had a mean eGFR of 41.7 ± 13.3 and 45.0 ± 14.5 ml/min/1.73 m2, respectively. Ten plasma metabolites were nominally associated with CKD progression in logistic regression models adjusted for age, sex, race/ethnicity, hypertension, systolic and diastolic blood pressure, diabetes, eGFR and proteinuria; no metabolite achieved the Bonferroni-adjusted significance threshold (p < 0.0003). In a cross-sectional analysis, all 6 of the metabolites that were higher in cases than controls were significantly associated with eGFR at baseline. By contrast, threonine, methionine and arginine were lower in cases than in controls and had no association with baseline eGFR. Furthermore, in the hospital-based cohort that underwent renal arteriovenous sampling, these 3 metabolites were net released from the kidney. Combining these metabolites into a panel of markers further strengthened their association with CKD progression. Conclusion: Our results motivate interest in arginine, methionine and threonine as potential indicators of renal metabolic function and markers of renal prognosis.

Aneuploid Cell Survival Relies upon Sphingolipid Homeostasis

Aneuploidy, a hallmark of cancer cells, poses an appealing opportunity for cancer treatment and prevention strategies. Using a cell-based screen to identify small molecules that could selectively kill aneuploid cells, we identified the compound N-[2-hydroxy-1-(4-morpholinylmethyl)-2-phenylethyl]-decanamide monohydrochloride (DL-PDMP), an antagonist of UDP-glucose ceramide glucosyltransferase. DL-PDMP selectively inhibited proliferation of aneuploid primary mouse embryonic fibroblasts and aneuploid colorectal cancer cells. Its selective cytotoxic effects were based on further accentuating the elevated levels of ceramide, which characterize aneuploid cells, leading to increased apoptosis. We observed that DL-PDMP could also enhance the cytotoxic effects of paclitaxel, a standard-of-care chemotherapeutic agent that causes aneuploidy, in human colon cancer and mouse lymphoma cells. Our results offer pharmacologic evidence that the aneuploid state in cancer cells can be targeted selectively for therapeutic purposes, or for reducing the toxicity of taxane-based drug regimens. Cancer Res; 77(19); 5272-86. ©2017 AACR.

Gut microbiota modulate neurobehavior through changes in brain insulin sensitivity and metabolism

Obesity and diabetes in humans are associated with increased rates of anxiety and depression. To understand the role of the gut microbiome and brain insulin resistance in these disorders, we evaluated behaviors and insulin action in brain of mice with diet-induced obesity (DIO) with and without antibiotic treatment. We find that DIO mice have behaviors reflective of increased anxiety and depression. This is associated with decreased insulin signaling and increased inflammation in in the nucleus accumbens and amygdala. Treatment with oral metronidazole or vancomycin decreases inflammation, improves insulin signaling in the brain and reduces signs of anxiety and depression. These effects are associated with changes in the levels of tryptophan, GABA, BDNF, amino acids, and multiple acylcarnitines, and are transferable to germ-free mice by fecal transplant. Thus, changes in gut microbiota can control brain insulin signaling and metabolite levels, and this leads to altered neurobehaviors.

netome: a computational framework for metabolite profiling and omics network analysis

Summary Advances in metabolomics technologies have enabled comprehensive analyses of associations between metabolites and human disease and have provided a means to study biochemical pathways and processes in detail using model systems. Liquid chromatography tandem mass spectrometry (LC-MS) is an analytical technique commonly used by metabolomics labs to measure hundreds of metabolites of known identity and thousands of “peaks” from yet to be identified compounds that are tracked by their measured masses and chromatographic retention times. netome is a computational framework that provides tools for analyzing processed LC-MS data. In this framework, we develop and provide various computational resources including individual software modules to inspect and adjust trends in raw data, align unknown peaks between separately acquired data sets, and to remove redundancies in nontargeted LC-MS data arising from multiple ionization products of a single metabolite. These tools are deployed through computing resources such as web servers and virtual machines with detailed documentation in order to support researchers. Availability and implementation netome is publicly available with extensive documentation and support via issue tracker at https://broadinstitute.github.io/netome under the MIT license. netome includes a set of computational methods that have been designed to execute quality control and post-raw data processing tasks for metabolomics data (e.g. scaling and clustering metabolite abundances), as well as statistical association testing in a network manner (e.g., testing relationship between metabolites and microbes). Each individual tool is available with source code, workshop-oriented documentation which includes instructions for installation and using tools with demonstration examples, and a web server with all services. We also provide a complete image of the netome package with all pre-installed dependencies and support for Google Compute Engine and Amazon EC2. All tools and related services are maintained, and upon new developments, new modules will be added to the environment. Contact rah@broadinstitute.org, clary@broadinstitute.org Supplementary information Supplementary data are available at Bioinformatics online.