Impaired BCAA catabolism in adipose tissues promotes age-associated metabolic derangement.

Adipose tissues are central in controlling metabolic homeostasis and failure in their preservation is associated with age-related metabolic disorders. The exact role of mature adipocytes in this phenomenon remains elusive. Here we describe the role of adipose branched-chain amino acid (BCAA) catabolism in this process. We found that adipocyte-specific Crtc2 knockout protected mice from age-associated metabolic decline. Multiomics analysis revealed that BCAA catabolism was impaired in aged visceral adipose tissues, leading to the activation of mechanistic target of rapamycin complex (mTORC1) signaling and the resultant cellular senescence, which was restored by Crtc2 knockout in adipocytes. Using single-cell RNA sequencing analysis, we found that age-associated decline in adipogenic potential of visceral adipose tissues was reinstated by Crtc2 knockout, via the reduction of BCAA-mTORC1 senescence-associated secretory phenotype axis. Collectively, we propose that perturbation of BCAA catabolism by CRTC2 is critical in instigating age-associated remodeling of adipose tissue and the resultant metabolic decline in vivo.

Longitudinal study investigating serum metabolites and their association with type 2 diabetes risk in a Korean population.

AIM: The lack of longitudinal metabolomics data and the statistical techniques to analyse them has limited the understanding of the metabolite levels related to type 2 diabetes (T2D) onset. Thus, we carried out logistic regression analysis and simultaneously proposed new approaches based on residuals of multiple logistic regression and geometric angle-based clustering for the analysis in T2D onset-specific metabolic changes. MATERIALS AND METHODS: We used the sixth, seventh and eighth follow-up data from 2013, 2015 and 2017 among the Korea Association REsource (KARE) cohort data. Semi-targeted metabolite analysis was performed using ultraperformance liquid chromatography/triple quadrupole-mass spectrometry systems. RESULTS: As the results from the multiple logistic regression and a single metabolite in a logistic regression analysis varied dramatically, we recommend using models that consider potential multicollinearity among metabolites. The residual-based approach particularly identified neurotransmitters or related precursors as T2D onset-specific metabolites. By using geometric angle-based pattern clustering studies, ketone bodies and carnitines are observed as disease-onset specific metabolites and separated from others. CONCLUSION: To treat patients with early-stage insulin resistance and dyslipidaemia when metabolic disorders are still reversible, our findings may contribute to a greater understanding of how metabolomics could be used in disease intervention strategies during the early stages of T2D.

Enhanced Glutaminolysis Drives Hypoxia-Induced Chemoresistance in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) exhibits severe hypoxia, which is associated with chemoresistance and worse patient outcome. It has been reported that hypoxia induces metabolic reprogramming in cancer cells. However, it is not well known whether metabolic reprogramming contributes to hypoxia. Here, we established that increased glutamine catabolism is a fundamental mechanism inducing hypoxia, and thus chemoresistance, in PDAC cells. An extracellular matrix component-based in vitro three-dimensional cell printing model with patient-derived PDAC cells that recapitulate the hypoxic status in PDAC tumors showed that chemoresistant PDAC cells exhibit markedly enhanced glutamine catabolism compared with chemoresponsive PDAC cells. The augmented glutamine metabolic flux increased the oxygen consumption rate via mitochondrial oxidative phosphorylation (OXPHOS), promoting hypoxia and hypoxia-induced chemoresistance. Targeting glutaminolysis relieved hypoxia and improved chemotherapy efficacy in vitro and in vivo. This work suggests that targeting the glutaminolysis-OXPHOS-hypoxia axis is a novel therapeutic target for treating patients with chemoresistant PDAC. SIGNIFICANCE: Increased glutaminolysis induces hypoxia via oxidative phosphorylation-mediated oxygen consumption and drives chemoresistance in pancreatic cancer, revealing a potential therapeutic strategy of combining glutaminolysis inhibition and chemotherapy to overcome resistance.

Associations between local acidosis induced by renal LDHA and renal fibrosis and mitochondrial abnormalities in patients with diabetic kidney disease.

During the progression of diabetic kidney disease (DKD), renal lactate metabolism is rewired. The relationship between alterations in renal lactate metabolism and renal fibrosis in patients with diabetes has only been partially established due to a lack of biopsy tissues from patients with DKD and the intricate mechanism of lactate homeostasis. The role of lactate dehydrogenase A (LDHA)-mediated lactate generation in renal fibrosis and dysfunction in human and animal models of DKD was explored in this study. Measures of lactate metabolism (urinary lactate levels and LDHA expression) and measures of DKD progression (estimated glomerular filtration rate and Wilms' tumor-1 expression) were strongly negatively correlated in patients with DKD. Experiments with streptozotocin-induced DKD rat models and the rat renal mesangial cell model confirmed our findings. We found that the pathogenesis of DKD is linked to hypoxia-mediated lactic acidosis, which leads to fibrosis and mitochondrial abnormalities. The pathogenic characteristics of DKD were significantly reduced when aerobic glycolysis or LDHA expression was inhibited. Further studies will aim to investigate whether local acidosis caused by renal LDHA might be exploited as a therapeutic target in patients with DKD.

Integrated metagenomics and metabolomics analysis illustrates the systemic impact of the gut microbiota on host metabolism after bariatric surgery.

AIM: To explore how bariatric surgery (BS) modified the obesity-associated gut microbiome, the host metabolome, and their interactions in obese Korean patients. MATERIALS AND METHODS: Stool and fasting blood samples were obtained before and 1, 3, 6, and 12 months after BS from 52 patients enrolled in the Korean Obesity Surgical Treatment Study. We analysed the gut microbiome by 16S rRNA gene sequencing and the serum metabolome, including bile acids, by nuclear magnetic resonance spectroscopy and ultrahigh-performance liquid chromatography/triple quadrupole mass spectrometry. RESULTS: Stool metagenomics showed that 27 microbiota were enriched and 14 microbiota were reduced after BS, whereas the abundances and diversity of observed features were increased. The levels of branched-chain amino acids and metabolites of energy metabolism in serum were decreased after surgery, whereas the levels of metabolites related to microbial metabolism, including dimethyl sulphone, glycine, and secondary bile acids, were increased in the serum samples. In addition, we found notable mutual associations among metabolites and gut microbiome changes attributed to BS. CONCLUSIONS: Changes in the gut microbiome community and systemic levels of amino acids and sugars were directly derived from anatomical changes in the gastrointestinal tract after BS. We hypothesized that the observed increases in microbiome-related serum metabolites were a result of complex and indirect changes derived from BS. Ethnic-specific environmental or genetic factors could affect Korean-specific postmetabolic modification in obese patients who undergo BS.

A novel role of CRTC2 in promoting nonalcoholic fatty liver disease.

OBJECTIVE: Diet-induced obesity is often associated with nonalcoholic fatty liver disease (NAFLD), which instigates severe metabolic disorders, including cirrhosis, hepatocellular carcinoma, and type 2 diabetes. We have shown that hepatic depletion of CREB regulated transcription co-activator (CRTC) 2 protects mice from the progression of diet-induced fatty liver phenotype, although the exact mechanism by which CRTC2 modulates this process is elusive to date. Here, we investigated the role of hepatic CRTC2 in the instigation of NAFLD in mammals. METHODS: Crtc2 liver-specific knockout (Crtc2 LKO) mice and Crtc2 flox/flox (Crtc2 f/f) mice were fed a high fat diet (HFD) for 7-8 weeks. Body weight, liver weight, hepatic lipid contents, and plasma triacylglycerol (TG) levels were determined. Western blot analysis was performed to determine Sirtuin (SIRT) 1, tuberous sclerosis complex (TSC) 2, and mammalian target of rapamycin complex (mTORC) 1 activity in the liver. Effects of Crtc2 depletion on lipogenesis was determined by measuring lipogenic gene expression (western blot analysis and qRT-PCR) in the liver as well as Oil red O staining in hepatocytes. Effects of miR-34a on mTORC1 activity and hepatic lipid accumulation was assessed by AAV-miR-34a virus in mice and Ad-miR-34a virus and Ad-anti-miR-34a virus in hepatocytes. Autophagic flux was assessed by western blot analysis after leupeptin injection in mice and bafilomycin treatment in hepatocytes. Lipophagy was assessed by transmission electron microscopy and confocal microscopy. Expression of CRTC2 and p-S6K1 in livers of human NAFLD patients was assessed by immunohistochemistry. RESULTS: We found that expression of CRTC2 in the liver is highly induced upon HFD-feeding in mice. Hepatic depletion of Crtc2 ameliorated HFD-induced fatty liver disease phenotypes, with a pronounced inhibition of the mTORC1 pathway in the liver. Mechanistically, we found that expression of TSC2, a potent mTORC1 inhibitor, was enhanced in Crtc2 LKO mice due to the decreased expression of miR-34a and the subsequent increase in SIRT1-mediated deacetylation processes. We showed that ectopic expression of miR-34a led to the induction of mTORC1 pathway, leading to the hepatic lipid accumulation in part by limiting lipophagy and enhanced lipogenesis. Finally, we found a strong association of CRTC2, miR-34a and mTORC1 activity in the NAFLD patients in humans, demonstrating a conservation of signaling pathways among species. CONCLUSIONS: These data collectively suggest that diet-induced activation of CRTC2 instigates the progression of NAFLD by activating miR-34a-mediated lipid accumulation in the liver via the simultaneous induction of lipogenesis and inhibition of lipid catabolism. Therapeutic approach to specifically inhibit CRTC2 activity in the liver could be beneficial in combating NAFLD in the future.

Glutathione is an aging-related metabolic signature in the mouse kidney.

The ability to maintain systemic metabolic homeostasis through various mechanisms represents a crucial strength of kidneys in the study of metabolic syndrome or aging. Moreover, age-associated kidney failure has been widely accepted. However, efforts to demonstrate aging-dependent renal metabolic rewiring have been limited. In the present study, we investigated aging-related renal metabolic determinants by integrating metabolomic and transcriptomic data sets from kidneys of young (3 months, n = 7 and 3 for respectively) and old (24 months, n = 8 and 3 for respectively) naive C57BL/6 male mice. Metabolite profiling analysis was conducted, followed by data processing via network and pathway analyses, to identify differential metabolites. In the aged group, the levels of glutathione and oxidized glutathione were significantly increased, but the levels of gamma-glutamyl amino acids, amino acids combined with the gamma-glutamyl moiety from glutathione by membrane transpeptidases, and circulating glutathione levels were decreased. In transcriptomic analysis, differential expression of metabolic enzymes is consistent with the hypothesis of aging-dependent rewiring in renal glutathione metabolism; pathway and network analyses further revealed the increased expression of immune-related genes in the aged group. Collectively, our integrative analysis results revealed that defective renal glutathione metabolism is a signature of renal aging. Therefore, we hypothesize that restraining renal glutathione metabolism might alleviate or delay age-associated renal metabolic deterioration, and aberrant activation of the renal immune system.

Purine metabolite-based machine learning models for risk prediction, prognosis, and diagnosis of coronary artery disease.

Alterations in xanthine oxidase activity are known to be pathologically influential on coronary artery disease (CAD), but the association between purine-related blood metabolites and CAD has only been partially elucidated. We performed global metabolomics profiling and network analysis on blood samples from the Wonju and Pyeongchang (WP) cohort study (n = 2055) to elucidate the importance of purine related metabolites associated with potential CAD risk. Then, 5 selected serum metabolites were quantified from the WP cohort, Shinchon cohort (n = 259), and Shinchon case control (n = 424) groups to develop machine learning models for 10-year risk prediction, relapse within 10 years and diagnosis of the disease via 100 repeated 5-fold cross-validations of logistic models. The combination of purine metabolite levels or only xanthine levels in blood could be applied for machine learning model development for major adverse cardiac and cerebrovascular event (MACCE, cerebrovascular death, nonfatal myocardial infarction, percutaneous transluminal coronary angioplasty, coronary artery bypass graft, and stroke) risk prediction, relapse of MACCEs among patients with myocardial infarction history and diagnosis of stable CAD. In particular, our research provided initial evidence that blood xanthine and uric acid levels play different roles in the development of machine learning models for primary/secondary prevention or diagnosis of CAD. In this research, we determined that purine-related metabolites in blood are applicable to machine learning model development for CAD risk prediction and diagnosis. Also, our work advances current CAD biomarker discovery strategies mainly relying on clinical features; emphasizes the differential biomarkers in first/secondary prevention or diagnosis studies.

Do we need to reconsider the CMAM admission and discharge criteria?; an analysis of CMAM data in South Sudan.

BACKGROUND: Weight-for-height Z-score (WHZ) and Mid Upper Arm Circumference (MUAC) are both commonly used as acute malnutrition screening criteria. However, there exists disparity between the groups identified as malnourished by them. Thus, here we aim to investigate the clinical features and linkage with chronicity of the acute malnutrition cases identified by either WHZ or MUAC. Besides, there exists evidence indicating that fat restoration is disproportionately rapid compared to that of muscle gain in hospitalized malnourished children but related research at community level is lacking. In this study we suggest proxy measure to inspect body composition restoration responding to malnutrition management among the malnourished children. METHODS: The data of this study is from World Vision South Sudan's emergency nutrition program from 2006 to 2012 (4443 children) and the nutrition survey conducted in 2014 (3367 children). The study investigated clinical presentations of each type of severe acute malnutrition (SAM) by WHZ (SAM-WHZ) or MUAC (SAM-MUAC), and analysed correlation between each malnutrition and chronic malnutrition. Furthermore, we explored the pattern of body composition restoration during the recovery phase by comparing the relative velocity of MUAC3 with that of weight gain. RESULTS: As acutely malnourished children identified by MUAC more often share clinical features related to chronic malnutrition and minimal overlapping with malnourished children by WHZ, Therefore, MUAC only screening in the nutrition program would result in delayed identification of the malnourished children. CONCLUSIONS: The relative velocity of MUAC3 gain was suggested as a proxy measure for volume increase, and it was more prominent than that of weight gain among the children with SAM by WHZ and MUAC over all the restoring period. Based on this we made a conjecture about dominant fat mass gain over the period of CMAM program. Also, considering initial weight gain could be ascribed to fat mass increase, the current discharge criteria would leave the malnourished children at risk of mortality even after treatment due to limited restoration of muscle mass. Given this, further research should be followed including assessment of body composition for evidence to recapitulate and reconsider the current admission and discharge criteria for CMAM program.

Temporal fluxomics reveals oscillations in TCA cycle flux throughout the mammalian cell cycle.

Cellular metabolic demands change throughout the cell cycle. Nevertheless, a characterization of how metabolic fluxes adapt to the changing demands throughout the cell cycle is lacking. Here, we developed a temporal-fluxomics approach to derive a comprehensive and quantitative view of alterations in metabolic fluxes throughout the mammalian cell cycle. This is achieved by combining pulse-chase LC-MS-based isotope tracing in synchronized cell populations with computational deconvolution and metabolic flux modeling. We find that TCA cycle fluxes are rewired as cells progress through the cell cycle with complementary oscillations of glucose versus glutamine-derived fluxes: Oxidation of glucose-derived flux peaks in late G1 phase, while oxidative and reductive glutamine metabolism dominates S phase. These complementary flux oscillations maintain a constant production rate of reducing equivalents and oxidative phosphorylation flux throughout the cell cycle. The shift from glucose to glutamine oxidation in S phase plays an important role in cell cycle progression and cell proliferation.

Analysis of population-specific pharmacogenomic variants using next-generation sequencing data.

Functional rare variants in drug-related genes are believed to be highly differentiated between ethnic- or racial populations. However, knowledge of population differentiation (PD) of rare single-nucleotide variants (SNVs), remains widely lacking, with the highest fixation indices, (Fst values), from both rare and common variants annotated to specific genes, having only been marginally used to understand PD at the gene level. In this study, we suggest a new, gene-based PD method, PD of Rare and Common variants (PDRC), for analyzing rare variants, as inspired by Generalized Cochran-Mantel-Haenszel (GCMH) statistics, to identify highly population-differentiated drug response-related genes ("pharmacogenes"). Through simulation studies, we reveal that PDRC adequately summarizes rare and common variants, due to PD, over a specific gene. We also applied the proposed method to a real whole-exome sequencing dataset, consisting of 10,000 datasets, from the Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) initiative, and 3,000 datasets from the Genetics of Type 2 diabetes (Go-T2D) repository. Among the 48 genes annotated with Very Important Pharmacogenetic summaries (VIPgenes), in the PharmGKB database, our PD method successfully identified candidate genes with high PD, including ACE, CYP2B6, DPYD, F5, MTHFR, and SCN5A.

Correlation estimation with singly truncated bivariate data.

Correlation coefficient estimates are often attenuated for truncated samples in the sense that the estimates are biased towards zero. Motivated by real data collected in South Sudan, we consider correlation coefficient estimation with singly truncated bivariate data. By considering a linear regression model in which a truncated variable is used as an explanatory variable, a consistent estimator for the regression slope can be obtained from the ordinary least squares method. A consistent estimator of the correlation coefficient is then obtained by multiplying the regression slope estimator by the variance ratio of the two variables. Results from two limited simulation studies confirm the validity and robustness of the proposed method. The proposed method is applied to the South Sudanese children's anthropometric and nutritional data collected by World Vision. Copyright © 2017 John Wiley & Sons, Ltd.

Analysis of pharmacogenomic variants associated with population differentiation.

In the present study, we systematically investigated population differentiation of drug-related (DR) genes in order to identify common genetic features underlying population-specific responses to drugs. To do so, we used the International HapMap project release 27 Data and Pharmacogenomics Knowledge Base (PharmGKB) database. First, we compared four measures for assessing population differentiation: the chi-square test, the analysis of variance (ANOVA) F-test, Fst, and Nearest Shrunken Centroid Method (NSCM). Fst showed high sensitivity with stable specificity among varying sample sizes; thus, we selected Fst for determining population differentiation. Second, we divided DR genes from PharmGKB into two groups based on the degree of population differentiation as assessed by Fst: genes with a high level of differentiation (HD gene group) and genes with a low level of differentiation (LD gene group). Last, we conducted a gene ontology (GO) analysis and pathway analysis. Using all genes in the human genome as the background, the GO analysis and pathway analysis of the HD genes identified terms related to cell communication. "Cell communication" and "cell-cell signaling" had the lowest Benjamini-Hochberg's q-values (0.0002 and 0.0006, respectively), and "drug binding" was highly enriched (16.51) despite its relatively high q-value (0.0142). Among the 17 genes related to cell communication identified in the HD gene group, five genes (STX4, PPARD, DCK, GRIK4, and DRD3) contained single nucleotide polymorphisms with Fst values greater than 0.5. Specifically, the Fst values for rs10871454, rs6922548, rs3775289, rs1954787, and rs167771 were 0.682, 0.620, 0.573, 0.531, and 0.510, respectively. In the analysis using DR genes as the background, the HD gene group contained six significant terms. Five were related to reproduction, and one was "Wnt signaling pathway," which has been implicated in cancer. Our analysis suggests that the HD gene group from PharmGKB is associated with cell communication and drug binding.