Endometrial cancer risk stratification using MRI radiomics: corroborating with choline metabolism.

BACKGROUND AND PURPOSE: Radiomics offers little explainability. This study aims to develop a radiomics model (Rad-Score) using diffusion-weighted imaging (DWI) to predict high-risk patients for nodal metastasis or recurrence in endometrial cancer (EC) and corroborate with choline metabolism. MATERIALS AND METHODS: From August 2015 to July 2018, 356 EC patients were enrolled. Rad-Score was developed using LASSO regression in a training cohort (n = 287) and validated in an independent test cohort (n = 69). MR spectroscopy (MRS) was also used in 230 patients. Nuclear MRS measured choline metabolites in 70 tissue samples. The performance was compared against European Society for Medical Oncology (ESMO) risk groups. A P < .05 denoted statistical significance. RESULTS: Rad-Score achieved 71.1% accuracy in the training and 71.0% in the testing cohorts. Incorporating clinical parameters of age, tumor type, size, and grade, Rad-Signature reached accuracies of 73.2% in training and 75.4% in testing cohorts, closely matching the performance to the post-operatively based ESMO's 70.7% and 78.3%. Rad-Score was significantly associated with increased total choline levels on MRS (P = .034) and tissue levels (P = .019). CONCLUSIONS: Development of a preoperative radiomics risk score, comparable to ESMO clinical standard and associated with altered choline metabolism, shows translational relevance for radiomics in high-risk EC patients. TRIAL REGISTRATION: This study was registered in ClinicalTrials.gov on 2015-08-01 with Identifier NCT02528864.

Do low skeletal muscle bulk and disturbed body fat mass impact tumor recurrence in stage I/II HCC undergoing surgery? An observational cohort study.

INTRODUCTION: The influence of deranged body composition on stage I/II HCC after surgery remains undetermined. The current study aimed to investigate the impact of low skeletal muscle bulk and disturbed body fat mass on the recurrence outcome of stage I/II HCC patients undergoing liver resection. The associated metabolomic alterations were also assessed. METHODS: From 2012 to 2021, stage I and II HCC patients who underwent liver resection at our institute were retrospectively reviewed. Their preoperative body composition including skeletal muscle mass and body fat volume was measured by computed tomography (CT). The recurrence outcome was recorded and analyzed. The preoperative serum was collected and subjected to metabolomic analysis. RESULTS: A total of 450 stage I and II HCC patients were included in the current study. Among them, 76% were male and around 60% had HBV infection. After stratified by normal cutoff values obtained from a healthy cohort, 6.4% of stage I/II HCC patients were found to have a low psoas muscle index (PMI), 17.8% a high subcutaneous adipose tissue (SAT) index, and 27.8% a high visceral adipose tissue (VAT) index. Cox regression multivariate analysis further demonstrated that low PMI and high SAT index were independent prognostic factors for time-to-recurrence (TTR) after surgery. Metabolomic analysis discovered that free fatty acid ß-oxidation was enhanced in with low PMI or high SAT index. CONCLUSION: The current study demonstrated that reduced psoas muscle mass may impair while elevated SAT may prolong the TTR of stage I/II HCC patients undergoing liver resections. VAT, on the other hand, was not associated with recurrence outcome after surgery. Further studies are warranted to validate our findings.

Exploring the aging process of cognitively healthy adults by analyzing cerebrospinal fluid metabolomics using liquid chromatography-tandem mass spectrometry.

BACKGROUND: During biological aging, significant metabolic dysregulation in the central nervous system may lead to cognitive decline and neurodegeneration. However, the metabolomics of the aging process in cerebrospinal fluid (CSF) has not been thoroughly explored. METHODS: In this cohort study of CSF metabolomics using liquid chromatography-mass spectrometry (LC-MS), fasting CSF samples collected from 92 cognitively unimpaired adults aged 20-87 years without obesity or diabetes were analyzed. RESULTS: We identified 37 metabolites in these CSF samples with significant positive correlations with aging, including cysteine, pantothenic acid, 5-hydroxyindoleacetic acid (5-HIAA), aspartic acid, and glutamate; and two metabolites with negative correlations, asparagine and glycerophosphocholine. The combined alterations of asparagine, cysteine, glycerophosphocholine, pantothenic acid, sucrose, and 5-HIAA showed a superior correlation with aging (AUC = 0.982). These age-correlated changes in CSF metabolites might reflect blood-brain barrier breakdown, neuroinflammation, and mitochondrial dysfunction in the aging brain. We also found sex differences in CSF metabolites with higher levels of taurine and 5-HIAA in women using propensity-matched comparison. CONCLUSIONS: Our LC-MS metabolomics of the aging process in a Taiwanese population revealed several significantly altered CSF metabolites during aging and between the sexes. These metabolic alterations in CSF might provide clues for healthy brain aging and deserve further exploration.

Metabolomic Signature of Diabetic Kidney Disease in Cerebrospinal Fluid and Plasma of Patients with Type 2 Diabetes Using Liquid Chromatography-Mass Spectrometry.

Diabetic kidney disease (DKD) is the major cause of end stage renal disease in patients with type 2 diabetes mellitus (T2DM). The subtle metabolic changes in plasma and cerebrospinal fluid (CSF) might precede the development of DKD by years. In this longitudinal study, CSF and plasma samples were collected from 28 patients with T2DM and 25 controls, during spinal anesthesia for elective surgery in 2017. These samples were analyzed using liquid chromatography-mass spectrometry (LC-MS) in 2017, and the results were correlated with current DKD in 2017, and the development of new-onset DKD, in 2021. Comparing patients with T2DM having new-onset DKD with those without DKD, revealed significantly increased CSF tryptophan and plasma uric acid levels, whereas phosphatidylcholine 36:4 was lower. The altered metabolites in the current DKD cases were uric acid and paraxanthine in the CSF and uric acid, L-acetylcarnitine, bilirubin, and phosphatidylethanolamine 38:4 in the plasma. These metabolic alterations suggest the defective mitochondrial fatty acid oxidation and purine and phospholipid metabolism in patients with DKD. A correlation analysis found CSF uric acid had an independent positive association with the urine albumin-to-creatinine ratio. In conclusion, these identified CSF and plasma biomarkers of DKD in diabetic patients, might be valuable for monitoring the DKD progression.

1H NMR metabolomic profiling of human cerebrospinal fluid in aging process.

The molecular process of biological aging might be accompanied by significant metabolic derangement, especially in the central nervous system (CNS), since the brain has an enormous energy demand. However, the metabolic signature of the aging process in cerebrospinal fluid (CSF) has not been thoroughly investigated, especially in the Asian population. In this prospective cohort study on CSF metabolomics using proton nuclear magnetic resonance (NMR) spectroscopy, fasting CSF samples from 75 cognitively unimpaired patients aged 20-92 years without diabetes or obesity, undergoing spinal anesthesia for elective surgery were analyzed. Several metabolites in CSF samples were identified as having a significant association with the aging process in cerebral circulation; among the metabolites, the levels of alanine, citrate, creatinine, lactate, leucine, tyrosine, and valine significantly increased in old patients compared to those in young patients. The combined CSF metabolite alterations in citrate, lactate, leucine, tyrosine, and valine had a superior correlation with the aging process in all age groups. In conclusion, our pilot study of aging CSF metabolomics in the Taiwanese population presents significantly altered CSF metabolites with potential relevance to the aging process. These metabolic alterations in CSF samples might imply increasing anaerobic glycolysis, mitochondrial dysfunction, and decreasing glucose utilization in cerebral circulation in aged patients.

Plasma phenylalanine and glutamine concentrations correlate with subsequent hepatocellular carcinoma occurrence in liver cirrhosis patients: an exploratory study.

Aberrant metabolisms have been hypothesized to precede the occurrence of hepatocellular carcinoma (HCC), therefore, we investigated biomarkers associated with subsequent HCC in peripheral bloods using metabolomic technologies. A cohort of 475 HCC-naïve liver cirrhotic patients were recruited and prospectively followed. A total of 39 patients developed HCC in the follow-up period. Baseline plasma metabolites were explored using untargeted nuclear magnetic resonance. Candidates were then quantified by ultra-performance liquid chromatography. A series of univairiate and multivariate analysis showed that Phenylalanine (Phe) and Glutamine (Gln) levels are associated with time to HCC, independent of viological etiologies and age. A HCC risk score R was then constructed using the polynomial combination of age, Phe and Gln in the units of micromolar (µM):[Formula: see text] R correlates with the time to HCC significantly (Hazard ratio [HR] = 2.368, 95% confidence interval [CI] 1.760-3.187, P < 0.001). An additional cross-sectional analysis showed that Phe and Gln concentrations both correlates with HCC occurrence in the next 3 years (area under the receiver operating characteristic curve [AUC] = 0.607 and 0.629, P = 0.033 and 0.010 respectively). In conclusion, phenylalanine and glutamine concentrations in the peripheral blood correlate with subsequent HCC.

Metabolomic biomarkers in cervicovaginal fluid for detecting endometrial cancer through nuclear magnetic resonance spectroscopy.

INTRODUCTION: Endometrial cancer (EC) is one of the most common gynecologic neoplasms in developed countries but lacks screening biomarkers. OBJECTIVES: We aim to identify and validate metabolomic biomarkers in cervicovaginal fluid (CVF) for detecting EC through nuclear magnetic resonance (NMR) spectroscopy. METHODS: We screened 100 women with suspicion of EC and benign gynecological conditions, and randomized them into the training and independent testing datasets using a 5:1 study design. CVF samples were analyzed using a 600-MHz NMR spectrometer equipped with a cryoprobe. Four machine learning algorithms-support vector machine (SVM), partial least squares discriminant analysis (PLS-DA), random forest (RF), and logistic regression (LR), were applied to develop the model for identifying metabolomic biomarkers in cervicovaginal fluid for EC detection. RESULTS: A total of 54 women were eligible for the final analysis, with 21 EC and 33 non-EC. From 29 identified metabolites in cervicovaginal fluid samples, the top-ranking metabolites chosen through SVM, RF and PLS-DA which existed in independent metabolic pathways, i.e. phosphocholine, malate, and asparagine, were selected to build the prediction model. The SVM, PLS-DA, RF, and LR methods all yielded area under the curve values between 0.88 and 0.92 in the training dataset. In the testing dataset, the SVM and RF methods yielded the highest accuracy of 0.78 and the specificity of 0.75 and 0.80, respectively. CONCLUSION: Phosphocholine, asparagine, and malate from cervicovaginal fluid, which were identified and independently validated through models built using machine learning algorithms, are promising metabolomic biomarkers for the detection of EC using NMR spectroscopy.

1H Nuclear Magnetic Resonance (NMR)-Based Cerebrospinal Fluid and Plasma Metabolomic Analysis in Type 2 Diabetic Patients and Risk Prediction for Diabetic Microangiopathy.

Insulin resistance and metabolic derangement are present in patients with type 2 diabetes mellitus (T2DM). However, the metabolomic signature of T2DM in cerebrospinal fluid (CSF) has not been investigated thus far. In this prospective metabolomic study, fasting CSF and plasma samples from 40 T2DM patients to 36 control subjects undergoing elective surgery with spinal anesthesia were analyzed by 1H nuclear magnetic resonance (NMR) spectroscopy. NMR spectra of CSF and plasma metabolites were analyzed and correlated with the presence of T2DM and diabetic microangiopathy (retinopathy, nephropathy, and neuropathy) using an area under the curve (AUC) estimation. CSF metabolomic profiles in T2DM patients vs. controls revealed significantly increased levels of alanine, leucine, valine, tyrosine, lactate, pyruvate, and decreased levels of histidine. In addition, a combination of alanine, histidine, leucine, pyruvate, tyrosine, and valine in CSF showed a superior correlation with the presence of T2DM (AUC:0.951), diabetic retinopathy (AUC:0.858), nephropathy (AUC:0.811), and neuropathy (AUC:0.691). Similar correlations also appeared in plasma profiling. These metabolic alterations in CSF suggest decreasing aerobic metabolism and increasing anaerobic glycolysis in cerebral circulation of patients with T2DM. In conclusion, our results provide clues for the metabolic derangements in diabetic central neuropathy among T2DM patients; however, their clinical significance requires further exploration.

Resonance assignments and secondary structure of a phytocystatin from Sesamum indicum.

A cDNA encoding a cysteine protease inhibitor, cystatin was cloned from sesame (Sesamum indicum L.) seed. This clone was constructed into an expression vector and expressed in E. coli and purified to homogeneous. The recombinant sesame cystatin (SiCYS) showed effectively inhibitory activity toward C1 cysteine proteases. In order to unravel its inhibitory action from structural point of view, multidimensional heteronuclear NMR techniques were used to characterize the structure of SiCYS. The full (1)H, (15)N, and (13)C resonances of SiCYS were assigned. The secondary structure of SiCYS was identified by using the assigned chemical shifts of (1)H(α), (13)C(α), (13)C(ß), and (13)CO through the consensus chemical shift index (CSI). The results of CSI analysis of SiCYS suggest eight ß-strands (residues 33-46, 51-61, 63-75, 80-87, 150-155, 157-169, 172-183, and 192-195) and two α-helices (residues 16-30, and 120-135).

The Arctic mutation accelerates Aß aggregation in SDS through reducing the helical propensity of residues 15-25.

Mutations within the ß-amyloid peptide (Aß) sequence that cause early onset familial Alzheimer's disease (FAD) have been shown to promote Aß aggregation. How these FAD-related mutants increase the aggregative ability of Aß is not fully understood. Here, we characterized the effect of the Arctic variant (E22G) on the conformational stability of Aß using various forms of spectroscopy and kinetic analyses, including nuclear magnetic resonance (NMR), circular dichroism (CD) spectroscopy, Fourier-transform infrared (FT-IR) spectroscopy and transmission electron microscopy (TEM). The E22G mutation in the Arctic variant reduced the α-helical propensity and conformational stability of Aß on residues 15-25. This mutation also caused an increase in both α-helix-to-ß-strand conversion and fibril nucleation rates. Our results suggest that the α-helical propensity of residues 15-25 may play a determinant role in the aggregative ability of Aß. This may provide a structural basis for understanding the molecular mechanism of Aß aggregation.

Effect of alanine replacement of l17 and f19 on the aggregation and neurotoxicity of arctic-type aß40.

Alzheimer's disease is the most common form of neurodegenerative disease. Beta-amyloid peptides (Aß) are responsible for neuronal death both in vitro and in vivo. Previously, L17 and F19 residues were identified as playing key roles in the stabilization of the Aß40 conformation and in the reduction of its neurotoxicity. In this study, the effects of L17A/F19A mutations on the neurotoxicity of Aß genetic mutant Arctic-type Aß40(E22G) were tested. The results showed that compared to Aß40(E22G), Aß40(L17A/F19A/E22G) reduced the rate of conformation conversion, aggregation, and cytotoxicity, suggesting that L17 and F19 are critical residues responsible for conformational changes which may trigger the neurotoxic cascade of Aß. Aß40(L17A/F19A/E22G) also had decreased damage due to reactive oxygen species. The results are consistent with the discordant helix hypothesis, and confirm that residues 17-25 are in the discordant helix region. Compared to Aß40(L17A/F19A), reduction in aggregation of Aß40(L17A/F19A/E22G) was less significantly decreased. This observation provides an explanation based on the discordant helix hypothesis that the mutation of E22 to G22 of Aß40(E22G) alters the propensity of the discordant helix. Arctic-type Aß40(E22G) aggregates more severely than wild-type Aß40, with a consequential increase in toxicity.

Aß40(L17A/F19A) mutant diminishes the aggregation and neurotoxicity of Aß40.

Aggregated ß-amyloid peptides (Aß) are neurotoxic and responsible for neuronal death both in vitro and in vivo. From the structural point of view, Aß self-aggregation involves a conformational change in the peptide. Here, we investigated the relationship between conformational changes and amino acid residues of Aß(40). Urea unfolding in combination with NMR spectroscopy was applied to probe the stabilization of Aß(40) conformation. L17 and F19 residues were found more sensitive to environmental changes than the other residues. Replacement of these two residues with alanine could stabilize the conformation of Aß(40). Further analysis indicated that the Aß(40)(L17A/F19A) mutant could diminish the aggregation and reduce the neurotoxicity. These results suggest that L17 and F19 are the critical residues responsible for conformational changes which may trigger neurotoxic cascade of Aß(40).