The impact of dietary acid load on super-agers with exceptional cognitive abilities: a propensity score analysis of national health and nutrition examination survey (NHANES) 2011-2014.

OBJECTIVES: 'Super-agers,' individuals over 80 with memory abilities comparable to those 20-30 years younger. The relationship between super-agers and dietary acid load (DAL) is an area that warrants further investigation. We aim to examine the link between DAL and super-agers and assess DAL's effects on cognitive functions across different age groups and cognitive domains. DESIGN: Employing a cross-sectional analysis of the 2011-2014 National Health and Nutrition Examination Survey (NHANES) data, we utilized propensity score analysis and multivariate-adjusted regression to mitigate confounding factors. SETTING: Older adults aged 60 and above in the United States. PARTICIPANTS: Our primary analysis encompassed 985 older adults, supplemented by a sensitivity analysis with 2,522 participants. MEASUREMENTS: DAL was assessed through potential renal acid load (PRAL), estimated net acid excretion (NAEes), and net endogenous acid production (NEAP) indices. RESULTS: Super-agers demonstrate a preference for alkaline diets, shown by their lower DAL indices. After inverse probability of treatment weighting (IPTW), multivariate-adjusted logistic regression reveals that each unit reduction in NAEes and PRAL increases the chances of being a super-ager by 3.9% and 3.0%, respectively. The DAL's impact on cognitive function becomes more pronounced with age. Lower PRAL and NAEes scores are significantly linked to higher situational memory and overall cognitive performance scores in those over 70, with these effects being even more pronounced in participants over 80. CONCLUSION: This research pioneers in demonstrating that super-agers prefer an alkaline diet, highlighting the potential role of alkaline diet in countering cognitive decline associated with aging.

Two effective models based on comprehensive lipidomics and metabolomics can distinguish BC versus HCs, and TNBC versus non-TNBC.

BACKGROUND: Lipidomics and metabolomics are closely related to tumor phenotypes, and serum lipoprotein subclasses and small-molecule metabolites are considered as promising biomarkers for breast cancer (BC) diagnosis. This study aimed to explore potential biomarker models based on lipidomic and metabolomic analysis that could distinguish BC from healthy controls (HCs) and triple-negative BC (TNBC) from non-TNBC. METHODS: Blood samples were collected from 114 patients with BC and 75 HCs. A total of 112 types of lipoprotein subclasses and 30 types of small-molecule metabolites in the serum were detected by 1 H-NMR. All lipoprotein subclasses and small-molecule metabolites were subjected to a three-step screening process in the order of significance (p < 0.05), univariate regression (p < 0.1), and lasso regression (nonzero coefficient). Discriminant models of BC versus HCs and TNBC versus non-TNBC were established using binary logistic regression. RESULTS: We developed a valid discriminant model based on three-biomarker panel (formic acid, TPA2, and L6TG) that could distinguish patients with BC from HCs. The area under the receiver operating characteristic curve (AUC) was 0.999 (95% confidence interval [CI]: 0.995-1.000) and 0.990 (95% CI: 0.959-1.000) in the training and validation sets, respectively. Based on the panel (D-dimer, CA15-3, CEA, L5CH, glutamine, and ornithine), a discriminant model was established to differentiate between TNBC and non-TNBC, with AUC of 0.892 (95% CI: 0.778-0.967) and 0.905 (95% CI: 0.754-0.987) in the training and validation sets, respectively. CONCLUSION: This study revealed lipidomic and metabolomic differences between BC versus HCs and TNBC versus non-TNBC. Two validated discriminatory models established against lipidomic and metabolomic differences can accurately distinguish BC from HCs and TNBC from non-TNBC. IMPACT: Two validated discriminatory models can be used for early BC screening and help BC patients avoid time-consuming, expensive, and dangerous BC screening.

Loss of BCAA catabolism enhances Rab1A-mTORC1 signaling activity and promotes tumor proliferation in NSCLC.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a leading cause of cancer death. Branched-chain amino acid (BCAA) homeostasis is important for normal physiological metabolism. Branched-chain keto acid dehydrogenase kinase (BCKDK) is a rate-limiting enzyme involved in BCAA degradation. BCAA metabolism has been highlighted in human cancers. The aberrant activation of mTORC1 has been implicated in tumor progression. Rab1A is a small GTPase, an activator of mTORC1, and an oncogene. This study aimed to reveal the specific role of BCKDK-BCAA-Rab1A-mTORC1 signaling in NSCLC. METHODS: We analyzed a cohort of 79 patients with NSCLC and 79 healthy controls. Plasma BCAA assays, immunohistochemistry, and network and pathway analyses were performed. The stable cell lines BCKDK-KD, BCKDK-OV A549, and H1299 were constructed. BCKDK, Rab1A, p-S6 and S6 were detected using western blotting to explore their molecular mechanisms of action in NSCLC. The effects of BCAA and BCKDK on the apoptosis and proliferation of H1299 cells were detected by cell function assays. RESULTS: We demonstrated that NSCLC was primarily involved in BCAA degradation. Therefore, combining BCAA, CEA, and Cyfra21-1 is clinically useful for treating NSCLC. We observed a significant increase in BCAA levels, downregulation of BCKDHA expression, and upregulation of BCKDK expression in NSCLC cells. BCKDK promotes proliferation and inhibits apoptosis in NSCLC cells, and we observed that BCKDK affected Rab1A and p-S6 in A549 and H1299 cells via BCAA modulation. Leucine affected Rab1A and p-S6 in A549 and H1299 cells and affected the apoptosis rate of H1299 cells. In conclusion, BCKDK enhances Rab1A-mTORC1 signaling and promotes tumor proliferation by suppressing BCAA catabolism in NSCLC, suggesting a new biomarker for the early diagnosis and identification of metabolism-based targeted approaches for patients with NSCLC.

Comparison of lipid accumulation product and visceral adiposity index with traditional obesity indices in early-onset type 2 diabetes prediction: a cross-sectional study.

BACKGROUND: The purpose of the study was to compare the efficacy of two novel obesity indices, lipid accumulation product (LAP) and visceral adiposity index (VAI), with traditional obesity indices in predicting early-onset type 2 diabetes (T2DM). METHODS: In this cross-sectional study, a total of 744 participants, including 605 patients newly diagnosed with T2DM and 139 non-diabetic control subjects, were enrolled from a tertiary care hospital in Tianjin, China. Participants with T2DM were divided into two groups based on their age at diagnosis, namely early-onset T2DM (age less than 40 years, n = 154) and late-onset T2DM (age 40 years or older, n = 451). The predictive power of each obesity index was evaluated using receiver operating characteristic (ROC) curve analysis. Furthermore, binary logistic regression analysis was conducted to examine the independent relationship between LAP and VAI with early-onset T2DM risk. The relationship between novel obesity indices and the age of T2DM onset was also evaluated through correlation and multiple linear regression analysis. RESULTS: In males, LAP had the highest predictive power for early-onset T2DM with an area under the ROC curve (AUC) of 0.742 (95% CI 0.684-0.799, P < 0.001). In females, VAI had the highest AUC for early-onset T2DM with a value of 0.748 (95% CI 0.657-0.839, P < 0.001), which was superior to traditional indices. Patients in the 4th quartile of LAP and VAI had 2.257 (95% CI 1.116-4.563, P = 0.023) and 4.705 (95% CI 2.132-10.384, P < 0.001) times higher risk of T2DM before age 40, compared to those in the 1st quartile, respectively. A tenfold increase in LAP was associated with a decrease in T2DM onset age of 12.862 years in males (ß = -12.862, P < 0.001) and 6.507 years in females (ß = -6.507, P = 0.013). A similar decrease in T2DM onset age was observed for each tenfold increase in VAI in both male (ß = -15.222, P < 0.001) and female (ß = -12.511, P < 0.001) participants. CONCLUSIONS: In young Chinese individuals, LAP and VAI are recommended over traditional obesity indices for improved prediction of early-onset T2DM risk.

Screening for Lipid-Metabolism-Related Genes and Identifying the Diagnostic Potential of ANGPTL6 for HBV-Related Early-Stage Hepatocellular Carcinoma.

Lipid metabolic reprogramming is one of the hallmarks of hepatocarcinogenesis and development. Therefore, lipid-metabolism-related genes may be used as potential biomarkers for hepatocellular carcinoma (HCC). This study aimed to screen for genes with dysregulated expression related to lipid metabolism in HCC and explored the clinical value of these genes. We screened differentially expressed proteins between tumorous and adjacent nontumorous tissues of hepatitis B virus (HBV)-related HCC patients using a Nanoscale Liquid Chromatography-Tandem Mass Spectrometry platform and combined it with transcriptomic data of lipid-metabolism-related genes from the GEO and HPA databases to identify dysregulated genes that may be involved in lipid metabolic processes. The potential clinical values of these genes were explored by bioinformatics online analysis tools (GEPIA, cBioPortal, SurvivalMeth, and TIMER). The expression levels of the secreted protein (angiopoietin-like protein 6, ANGPTL6) in serum were analyzed by ELISA. The ability of serum ANGPTL6 to diagnose early HCC was assessed by ROC curves. The results showed that serum ANGPTL6 could effectively differentiate between HBV-related early HCC patients with normal serum alpha-fetoprotein (AFP) levels and the noncancer group (healthy participants and chronic hepatitis B patients) (AUC = 0.717, 95% CI: from 0.614 to 0.805). Serum ANGPTL6 can be used as a potential second-line biomarker to supplement serum AFP in the early diagnosis of HBV-related HCC.

The Application Value of Lipoprotein Particle Numbers in the Diagnosis of HBV-Related Hepatocellular Carcinoma with BCLC Stage 0-A.

Early diagnosis is essential for improving the prognosis and survival of patients with hepatocellular carcinoma (HCC). This study aims to explore the clinical value of lipoprotein subfractions in the diagnosis of hepatitis B virus (HBV)-related HCC. Lipoprotein subfractions were detected by 1H-NMR spectroscopy, and the pattern-recognition method and binary logistic regression were performed to classify distinct serum profiles and construct prediction models for HCC diagnosis. Differentially expressed proteins associated with lipid metabolism were detected by LC-MS/MS, and the potential prognostic significance of the mRNA expression was evaluated by Kaplan-Meier survival analysis. The diagnostic panel constructed from the serum particle number of very-low-density lipoprotein (VLDL), intermediate-density lipoprotein (IDL), and low-density lipoprotein (LDL-1~LDL-6) achieved higher accuracy for the diagnosis of HBV-related HCC and HBV-related benign liver disease (LD) than that constructed from serum alpha-fetoprotein (AFP) alone in the training set (AUC: 0.850 vs. AUC: 0.831) and validation set (AUC: 0.926 vs. AUC: 0.833). Furthermore, the panel achieved good diagnostic performance in distinguishing AFP-negative HCC from AFP-negative LD (AUC: 0.773). We also found that lipoprotein lipase (LPL) transcript levels showed a significant increase in cancerous tissue and that high expression was significantly positively correlated with the poor prognosis of patients. Our research provides new insight for the development of diagnostic biomarkers for HCC, and abnormal lipid metabolism and LPL-mediated abnormal serum lipoprotein metabolism may be important factors in promoting HCC development.

Pancreatic stellate cells regulate branched-chain amino acid metabolism in pancreatic cancer.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is the most lethal malignancy: it has a 5-year survival rate of less than 9%. Although surgical resection is an effective treatment for PDAC, only a small number of patients can have their tumors surgically removed. Thus, an urgent need to find new therapeutic targets for PDAC exists. Understanding the molecular mechanism of PDAC development is essential for the treatment of this malignancy. This research aimed to study the mechanisms of pancreatic stellate cells (PSCs), which regulate branched-chain amino acid (BCAA) metabolism in PDAC. METHODS: Differentially expressed proteins were detected via nanoliquid chromatography coupled to mass spectrometry (nano-LC-MS/MS). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment methods were used to find the valine-leucine-isoleucine (BCAA) degradation pathway. The levels of BCAAs in the sera and tissues of patients with PDAC were measured by using nuclear magnetic resonance (NMR). The functions of BCAA concentrations and the effects of activated pancreatic stellate cells (aPSCs) were also evaluated by performing Cell Counting Kit-8, colony formation, and wound healing assays. RESULTS: A total of 1,519 proteins with significantly differential expression were discovered in PDAC and adjacent tissues by using nano-LC-MS/MS. KEGG pathway enrichment analysis identified the BCAA degradation pathway. The content of BCAA in PDAC clinical samples was up-regulated. However, the addition of different concentrations of BCAA to PDAC cell culture medium failed to promote the proliferation and migration of PDAC cells. Given that analysis based on The Cancer Genome Atlas database showed that the number of aPSCs gradually increased with the progression of PDAC, the effects of aPSCs on PDAC cells were explored. After coculture with aPSCs, PDAC cell proliferation showed a significant increase, and the proteins involved in the BCAA degradation pathway in PDAC cells had also changed. CONCLUSIONS: aPSCs could regulate BCAA metabolism to enhance the progression of PDAC, indicating that the regulation of BCAA metabolism may serve as a new therapeutic direction for PDAC.

Aberrant lactate dehydrogenase A signaling contributes metabolic signatures in pancreatic cancer.

BACKGROUND: Pancreatic cancer (PC) has the lowest 5-year survival rate; therefore, new early screening methods and therapeutic targets are still urgently required. Emerging technologies such as metabolomic-based liquid biopsy may contribute to the field. We found aberrant lactate dehydrogenase A (LDHA) signaling to be an unfavorable biomarker for PC. METHODS: A total of 9 genes of the glycolysis pathway were detected by enrichment analysis in the PC Gene Expression Omnibus (GEO) dataset. The relationship between LDHA/pyruvate kinase (PKM)/fructose biphosphate aldolase A (ALDOA)/glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and patient survival was analyzed by Kaplan-Meier plotting analysis of The Cancer Genome Atlas (TCGA). The detection of changing metabolites in the serum of PC patients was performed using a nuclear magnetic resonance (NMR) spectrometer. RESULTS: We found LDHA was an independent predictor of overall survival (OS) in PC patients (P<0.001). Consistent with genetic aberrance of LDHA, we identified significant alterations in patients' glycolysis-related metabolites, including upregulation of lactic acid and downregulation of pyruvic acid. A 0.956 area under the curve (AUC) was achieved using the combinative metabolites score of lactic acid, pyruvic acid, citric acid, and glucose to distinguish PC from healthy controls. CONCLUSIONS: Aberrant LDHA signaling is an unfavorable biomarker for PC and consequential metabolic changes constitute potential diagnostic signatures of PCs.

BCKDK alters the metabolism of non-small cell lung cancer.

BACKGROUND: Metabolic reprogramming is a major feature of many tumors including non-small cell lung cancer (NSCLC). Branched-chain α-keto acid dehydrogenase kinase (BCKDK) plays an important role in diabetes, obesity, and other diseases. However, the function of BCKDK in NSCLC is unclear. This study aimed to explore the function of BCKDK in NSCLC. METHODS: Metabolites in the serum of patients with NSCLC and the supernatant of NSCLC cell cultures were detected using nuclear magnetic resonance (NMR) spectroscopy. Colony formation, cell proliferation, and cell apoptosis were assessed to investigate the function of BCKDK in the progression of NSCLC. Glucose uptake, lactate production, cellular oxygen consumption rate, extracellular acidification rate, and reactive oxygen species (ROS) were measured to examine the function of BCKDK in glucose metabolism. The expression of BCKDK was measured using reverse transcriptase-polymerase chain reaction, western blot, and immunohistochemical assay. RESULTS: Compared with healthy controls and postoperative NSCLC patients, increased branched-chain amino acid (BCAA) and decreased citrate were identified in the serum of preoperative NSCLC patients. Upregulation of BCKDK affected the metabolism of BCAAs and citrate in NSCLC cells. Knockout of BCKDK decreased the proliferation and exacerbated apoptosis of NSCLC cells ex vivo, while increased oxidative phosphorylation and, ROS levels, and inhibited glycolysis. CONCLUSIONS: BCKDK may influence glycolysis and oxidative phosphorylation by regulating the degradation of BCAA and citrate, thereby affecting the progression of NSCLC.

miR-495 and miR-5688 are down-regulated in non-small cell lung cancer under hypoxia to maintain interleukin-11 expression.

BACKGROUND: Hypoxia is a hallmark of cancer and is associated with poor prognosis. However, the molecular mechanism by which hypoxia promotes tumor progression remains unclear. MicroRNAs dysregulation has been shown to play a critical role in the tumor and tumor microenvironment. Here, we investigated the roles of miR-495 and miR-5688 in human non-small cell lung cancer (NSCLC) and their underlying mechanism. METHODS: The expression levels of miR-495 and miR-5688 in human NSCLC tissue specimens were measured by quantitative real-time polymerase chain reaction (qRT-PCR). Deferoxamine (DFO) was used to determine whether the regulation of miR-495 and miR-5688 under hypoxia was dependent on hypoxia-inducible factor 1-alpha (HIF-1α). Furthermore, the functions of miR-495 and miR-5688 in tumor progression were evaluated using colony formation, 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS), wound healing, transwell assays, and xenograft model. Two algorithms, PicTAR and Targetscan, were used to predict the target gene of these two miRNAs, and dual-luciferase reporter assay was conducted to confirm the target. The unpaired two-tailed t test, Pearson correlation analysis, and Fisher's exact probability test were performed for statistical analyses. RESULTS: Two miRNAs, miR-495 and miR-5688, were found to participate in NSCLC progression under hypoxia. They were down-regulated in NSCLC tissues compared with normal tissues. We determined that hypoxia led to the down-regulation of miR-495 and miR-5688 in NSCLC cells, which was independent of HIF-1α and cellular metabolic energy. In addition, miR-495 and miR-5688 suppressed cell proliferation, migration, and invasion in vitro. The NSCLC xenograft model showed that miR-495 and miR-5688 inhibited tumor formation in vivo. Interestingly, we found that miR-495 and miR-5688 had the same target, interleukin-11 (IL-11). Recombinant human IL-11 counteracted the effects of miR-495 and miR-5688 on NSCLC cells, suggesting that miR-495 and miR-5688 executed their tumor suppressive role by repressing IL-11 expression. CONCLUSION: We found that hypoxia down-regulated the expression levels of miR-495 and miR-5688 in NSCLC to enhance IL-11 expression and tumor progression, indicating that the miR-495/miR-5688/IL-11 axis may serve as a therapeutic target and potential biomarker for NSCLC.