Pioglitazone-induced alterations of purine metabolism in healthy male subjects.

Pioglitazone is class of thiazolidinediones that activates peroxisome proliferator-activated receptors (PPARs) in adipocytes to improve glucose metabolism and insulin sensitivity and has been used as a treatment for type 2 diabetes. However, the underlying mechanisms of associated pioglitazone-induced effects remain unclear. Our study aimed to investigate endogenous metabolite alterations associated with pioglitazone administration in healthy male subjects using an untargeted metabolomics approach. All subjects received 30 mg of pioglitazone once daily in the assigned sequence and period. Urine samples were collected before pioglitazone administration and for 24 h after 7 days of administration. A total of 1465 compounds were detected and filtered using a coefficient of variance below 30% and 108 metabolites were significantly altered upon pioglitazone administration via multivariate statistical analysis. Fourteen significant metabolites were identified using authentic standards and public libraries. Additionally, pathway analysis revealed that metabolites from purine and beta-alanine metabolisms were significantly altered after pioglitazone administration. Further analysis of quantification of metabolites from purine metabolism, revealed that the xanthine/hypoxanthine and uric acid/xanthine ratios were significantly decreased at post-dose. Pioglitazone-dependent endogenous metabolites and metabolic ratio indicated the potential effect of pioglitazone on the activation of PPAR and fatty acid synthesis. Additional studies involving patients are required to validate these findings.

Pharmacokinetic interactions between fexuprazan, a potassium-competitive acid blocker, and nonsteroidal anti-inflammatory drugs in healthy males.

Fexuprazan, a novel potassium-competitive acid blocker, is expected to be used for the prevention of nonsteroidal anti-inflammatory drugs (NSAIDs) induced ulcer. This study aimed to evaluate pharmacokinetic (PK) interactions between fexuprazan and NSAIDs in healthy subjects. A randomized, open-label, multicenter, six-sequence, one-way crossover study was conducted in healthy male subjects. Subjects randomly received one of the study drugs (fexuprazan 40 mg BID, celecoxib 200 mg BID, naproxen 500 mg BID, or meloxicam 15 mg QD) for 5 or 7 days in the first period followed by the combination of fexuprazan and one of NSAIDs for the same days and the perpetrator additionally administered for 1-2 days in the second period. Serial blood samples for PK analysis were collected until 48- or 72-h post-dose at steady state. PK parameters including maximum plasma concentration at steady state (Cmax,ss) and area under plasma concentration-time curve over dosing interval at steady state (AUCτ,ss) were compared between monotherapy and combination therapy. The PKs of NSAIDs were not significantly altered by fexuprazan. For fexuprazan, differences in PK parameters (22% in Cmax, 19% in AUCτ,ss) were observed when co-administered with naproxen, but not clinically significant. The geometric mean ratio (90% confidence interval) of combination therapy to monotherapy for Cmax,ss and AUCτ,ss was 1.22 (1.02-1.46) and 1.19 (1.00-1.43), respectively. There were no significant changes in the systemic exposure of fexuprazan by celecoxib and meloxicam. Fexuprazan and NSAIDs did not show clinically meaningful PK interactions.

Effects of meal type on the bioavailability of vutiglabridin, a novel anti-obesity agent, in healthy subjects.

Vutiglabridin, which affects the pharmacokinetics (PKs) of food, is currently under clinical development for the treatment of obesity. This study aimed to evaluate the effects of low- and high-fat meals on PKs of vutiglabridin in healthy male subjects. A randomized, open-label, single-dose, three-period, six-sequence crossover study was conducted. The subjects received a single oral dose of vutiglabridin 480 mg in a fasted state, 30 min after the intake of a low-fat meal (total 500-600 kcal, fat content 100-125 kcal) and high-fat meal (total 800-1000 kcal, fat content 500-600 kcal), with a 21-day washout period. Geometric mean ratios (GMRs) and 90% confidence intervals (CIs) for maximum plasma concentration (Cmax ) and area under the plasma concentration-time curve to the last measurable timepoint (AUClast ) were calculated. After intake of low- and high-fat meals, systemic exposure to vutiglabridin was increased, and the time to reach Cmax (Tmax ) was delayed compared to that in the fasted state. The GMRs (90% CIs) of low-fat meal to fasted state for Cmax and AUClast were 2.14 (1.76-2.60) and 2.15 (1.92-2.42), respectively, and those of high-fat meal to fasted state were 3.07 (2.53-3.72) and 3.00 (2.67-3.37), respectively. The median Tmax was delayed by 1.5 h in both fed states compared with that in the fasted state. The study drug was well-tolerated after administration in both the fed and fasted states. Food ingestion substantially increased the extent of oral vutiglabridin absorption in healthy subjects, and this enhancement increased with the fat content of the meal.

Pharmacogenetic Analysis of an 8-Year Old Girl with Reye Syndrome Associated with Use of Naproxen.

BACKGROUND Reye syndrome is a rare, yet potentially life-threatening disease characterized by acute encephalopathy and hepatic failure. This report presents the case of an 8-year-old girl with Reye syndrome and seizures after the use of naproxen. CASE REPORT An 8-year-old girl experienced a 3-day episode of fever and abdominal pain. After receiving naproxen (375 mg twice daily) starting from day -3, she exhibited hypotension, tonic seizure, and loss of consciousness (day 1). Physical examination and laboratory test results revealed acute kidney injury, metabolic acidosis, and elevated levels of lactate dehydrogenase (LDH), liver enzymes, and ferritin. On day 2, the maximum values of aspartate aminotransferase, alanine aminotransferase, LDH, creatinine, and ferritin were 955 U/L, 132 U/L, 8040 U/L, 2 mg/dL, and >40000 ug/L, respectively. She was given supportive care and recovered after 11 days (day 12), with normalization of kidney function and metabolic abnormalities. To identify possible genetic polymorphisms associated with the patient's symptoms, genotypes were tested using a drug metabolizing enzymes and transporters (DMET) gene chip. Among genes involved in the metabolism of naproxen, UGT1A6 (*1/*2) and UGT2B7 (*1/*2) resulted in possibly decreased function. Other results which may have had clinical significance included homozygote results for NAT2*6/*6 (rs1799930). CONCLUSIONS A rare case of Reye syndrome after administration of naproxen was presented in this case. A DMET gene chip was used to screen for possible genetic polymorphisms associated with Reye syndrome, but the result was inconclusive.

Metabolomic Characteristics of Nontuberculous Mycobacterial Pulmonary Disease.

BACKGROUND: The therapeutic challenges posed by nontuberculous mycobacterial pulmonary disease (NTM-PD) contribute to an unmet medical need. In this study, we aimed to investigate NTM-PD-specific metabolic pathways using serum metabolomics to understand disease pathogenesis. METHODS: Mass spectrometry-based untargeted metabolomic profiling of serum from patients with NTM-PD (n = 50), patients with bronchiectasis (n = 50), and healthy controls (n = 60) was performed. Selected metabolites were validated by an independent cohort and subjected to pathway analysis and classification modeling. RESULTS: Leucine, tyrosine, inosine, proline, 5-oxoproline, and hypoxanthine levels increased in the NTM-PD group compared with the healthy control group. Furthermore, levels of antioxidant metabolites (ferulic acid, α-lipoic acid, biotin, and 2,8-phenazinediamine) decreased in patients with NTM-PD. These changes were associated with arginine- and proline-related metabolism, leading to generation of reactive oxygen species. Interestingly, the observed metabolic changes in the NTM-PD group overlapped with those in the bronchiectasis group. CONCLUSION: In NTM-PD, 11 metabolites linked to increased oxidative stress were significantly altered from those in healthy controls. Our findings enhance a comprehensive understanding of NTM-PD pathogenesis and provide insights for novel treatment approaches.

Differences in Brain Metabolite Profiles Between Normothermia and Hypothermia.

BACKGROUND: This study evaluated the difference in brain metabolite profiles between normothermia and hypothermia reaching 25°C in humans in vivo. METHODS: Thirteen patients who underwent thoracic aorta surgery under moderate hypothermia were prospectively enrolled. Plasma samples were collected simultaneously from the arteries and veins to estimate metabolite uptake or release. Targeted metabolomics based on liquid chromatographic mass spectrometry and direct flow injection were performed, and changes in the profiles of respective metabolites from normothermia to hypothermia were compared. The ratios of metabolite concentrations in venous blood samples to those in arterial blood samples (V/A ratios) were calculated, and log2 transformation of the ratios [log2(V/A)] was performed for comparison between the temperature groups. RESULTS: Targeted metabolomics were performed for 140 metabolites, including 20 amino acids, 13 biogenic amines, 10 acylcarnitines, 82 glycerophospholipids, 14 sphingomyelins, and 1 hexose. Of the 140 metabolites analyzed, 137 metabolites were released from the brain in normothermia, and the release of 132 of these 137 metabolites was decreased in hypothermia. Two metabolites (dopamine and hexose) showed constant release from the brain in hypothermia, and 3 metabolites (2 glycophospholipids and 1 sphingomyelin) showed conversion from release to uptake in hypothermia. Glutamic acid demonstrated a distinct brain metabolism in that it was taken up by the brain in normothermia, and the uptake was increased in hypothermia. CONCLUSION: Targeted metabolomics demonstrated various degrees of changes in the release of metabolites by the hypothermic brain. The release of most metabolites was decreased in hypothermia, whereas glutamic acid showed a distinct brain metabolism.

A 6-month exercise intervention clinical trial in women: effects of physical activity on multi-omics biomarkers and health during the first wave of COVID-19 in Korea.

BACKGROUND: Coronavirus disease 2019 (COVID-19) was first reported in December 2019 and the first case in Korea was confirmed on January 20, 2020. Due to the absence of therapeutic agents and vaccines, the Korean government implemented social distancing on February 29, 2020. This study aimed to examine the effect of physical activity (PA) on health through changes in multi-omics biomarkers with a 6-month of exercise intervention during the first wave of COVID-19 in Korea. METHODS: Twenty-seven healthy middle-aged women were recruited and 14 subjects completed the exercise intervention. The mean age (± SD) was 46.3 (± 5.33) and the mean BMI (± SD) was 24.9 (± 3.88). A total of three blood and stool samples were collected at enrollment, after period 1, and after period 2 (3-month intervals). The amount of PA was measured with an accelerometer and by questionnaire. Clinical variables were used, including blood pressure, grip strength, flexibility, and blood glucose levels and lipid markers obtained from laboratory tests. The concentration of blood metabolites was measured by targeted metabolomics. Fecal microbiome data were obtained by 16 S rRNA gene amplicon sequencing. RESULTS: During the second half period (period 2), Coronavirus disease 2019 occurred and spread out in Korea, and PA decreased compared with the first half period (period 1) (185.9 ± 168.73 min/week to 102.5 ± 82.30 min/week; p = 0.0101). Blood pressure, hemoglobin A1c (HbA1c), and low-density lipoprotein cholesterol (LDL-C) decreased in period 1 (p < 0.05) and tended to increase again during period 2 (p < 0.05). Forty metabolites were changed significantly during period 1 (FDR p < 0.05), and we found that 6 of them were correlated with changes in blood pressure, HbA1c, and LDL-C via network analysis. CONCLUSIONS: Our results may suggest that exercise improves health through changes in biomarkers at multi-omics levels. However, reduced PA due to COVID-19 can adversely affect health, emphasizing the necessity for sustained exercise and support for home-based fitness to maintain health. TRIAL REGISTRATION: The trial is retrospectively registered on ClinicalTrials.gov (NCT05927675; June 30, 2023).

Targeted Metabolomic Biomarkers for Stroke Subtyping.

BACKGROUND AND PURPOSE: Ischemic stroke is a heterogeneous disease with various etiologies. The current subtyping process is complicated, time-consuming, and costly. Metabolite-based biomarkers have the potential to improve classification and deliver optimal treatments. We here aimed to identify novel, targeted metabolomics-based biomarkers to discriminate between large-artery atherosclerosis (LAA) and cardioembolic (CE) stroke. METHODS: We acquired serum samples and clinical data from a hospital-based acute stroke registry (ischemic stroke within 3 days from symptom onset). We included 346 participants (169 LAA, 147 CE, and 30 healthy older adults) and divided them into training and test sets. Targeted metabolomic analysis was performed using quantitative and quality-controlled liquid chromatography with tandem mass spectrometry. A multivariate regression model using metabolomic signatures was created that could independently distinguish between LAA and CE strokes. RESULTS: The training set (n = 193) identified metabolomic signatures that were different in patients with LAA and CE strokes. Six metabolomic biomarkers, i.e., lysine, serine, threonine, kynurenine, putrescine, and lysophosphatidylcholine acyl C16:0, could discriminate between LAA and CE stroke after adjusting for sex, age, body mass index, stroke severity, and comorbidities. The enhanced diagnostic power of key metabolite combinations for discriminating between LAA and CE stroke was validated using the test set (n = 123). CONCLUSIONS: We observed significant differences in metabolite profiles in LAA and CE strokes. Targeted metabolomics may provide enhanced diagnostic yield for stroke subtypes. The pathophysiological pathways of the identified metabolites should be explored in future studies.

Quantification of OATP1B1 endogenous metabolites coproporphyrin I and III in human urine.

Coproporphyrin (CP)-I and CP-III are the markers of organic anion-transporting polypeptides' (OATPs) activities, and they are porphyrin metabolites that originate from heme synthesis. Furthermore, CP-I and CP-III, which are OATP1B endogenous metabolites, have gradually attracted the attention of scientists and researchers in recent years. Previous studies have also observed CP-I and CP-III levels as clinical biomarkers for predicting OATP1B inhibition in drug-drug interaction studies. To establish an accurate ultra-high performance liquid chromatography-mass spectrometry method for the quantitation of CP-I and CP-III, we reviewed previous methodological publications and applied them to a clinical pharmacology study using a human urine matrix. We used 13.25 M formic acid as a working solution for internal standards (CP-I 15N4 and CP-III d8) to avoid isobaric interference. The calibration curve showed good linearity in the range of 1-100 ng/mL, with a correlation coefficient (R2) higher than 0.996 in each validation batch. Both the between-run and within-run assays achieved good precision and accuracy, and we found that both CP-I and CP-III were stable in the pre-study validation. The method exhibited suitable dilution integrity, allowing for the re-analysis of samples with concentrations exceeding the upper limit of quantification through dilution. Overall, the application of the described method in a clinical study revealed that it can be utilized effectively to monitor drug-drug interactions mediated by OATP1B.

Palmitoylation-driven PHF2 ubiquitination remodels lipid metabolism through the SREBP1c axis in hepatocellular carcinoma.

Palmitic acid (PA) is the most common fatty acid in humans and mediates palmitoylation through its conversion into palmitoyl coenzyme A. Although palmitoylation affects many proteins, its pathophysiological functions are only partially understood. Here we demonstrate that PA acts as a molecular checkpoint of lipid reprogramming in HepG2 and Hep3B cells. The zinc finger DHHC-type palmitoyltransferase 23 (ZDHHC23) mediates the palmitoylation of plant homeodomain finger protein 2 (PHF2), subsequently enhancing ubiquitin-dependent degradation of PHF2. This study also reveals that PHF2 functions as a tumor suppressor by acting as an E3 ubiquitin ligase of sterol regulatory element-binding protein 1c (SREBP1c), a master transcription factor of lipogenesis. PHF2 directly destabilizes SREBP1c and reduces SREBP1c-dependent lipogenesis. Notably, SREBP1c increases free fatty acids in hepatocellular carcinoma (HCC) cells, and the consequent PA induction triggers the PHF2/SREBP1c axis. Since PA seems central to activating this axis, we suggest that levels of dietary PA should be carefully monitored in patients with HCC.

Serum, Urine, and Fecal Metabolome Alterations in the Gut Microbiota in Response to Lifestyle Interventions in Pediatric Obesity: A Non-Randomized Clinical Trial.

Pediatric obesity is associated with alterations in the gut microbiota and its metabolites. However, how they influence obesity and the effect of lifestyle interventions remains unknown.. In this non-randomized clinical trial, we analyzed metabolomes and microbial features to understand the associated metabolic pathways and the effect of lifestyle interventions on pediatric obesity. Anthropometric/biochemical data and fasting serum, urine, and fecal samples were collected at baseline and after an eight-week, weight-reduction lifestyle modification program. Post-intervention, children with obesity were classified into responder and non-responder groups based on changes in total body fat. At baseline, serum L-isoleucine and uric acid levels were significantly higher in children with obesity compared with those in normal-weight children and were positively correlated with obesogenic genera. Taurodeoxycholic and tauromuricholic α + ß acid levels decreased significantly with obesity and were negatively correlated with obesogenic genera. Branched-chain amino acid and purine metabolisms were distinguished metabolic pathways in the obese group. Post-intervention, urinary myristic acid levels decreased significantly in the responder group, showing a significant positive correlation with Bacteroides. Fatty acid biosynthesis decreased significantly in the responder group. Thus, lifestyle intervention with weight loss is associated with changes in fatty acid biosynthesis, and myristic acid is a possible therapeutic target for pediatric obesity.

Comparison of the Pharmacokinetics, Safety, and Tolerability of Two Empagliflozin Formulations in Healthy Korean Subjects.

Purpose: Empagliflozin is a sodium-glucose cotransporter 2 inhibitor that is commonly used for the treatment of type 2 diabetes mellitus. As cocrystal formulation can improve the chemical properties of drugs, CKD-370 was newly developed as a cocrystal formulation of empagliflozin with solvate L-proline. This study aimed to compare the pharmacokinetics, safety, and tolerability of these two empagliflozin formulations in healthy Korean subjects. Methods: A randomized, open-label, two-sequence, two-period crossover study was conducted on healthy Korean participants. The subjects received a single oral 25 mg dose of either test (CKD-370) or reference treatment (Jardiance®) tablet at each period. Plasma empagliflozin concentrations were determined using liquid chromatography with tandem mass spectrometry. Pharmacokinetic (PK) parameters were analyzed using non-compartmental methods. The primary PK parameters included the maximum concentration (Cmax) and the area under the concentration-time curve from 0 to last (AUClast). The safety of both formulations was monitored and evaluated. Results: A total of 28 healthy Korean adult subjects were randomized, and 27 subjects were included in the PK analysis. The mean ± standard deviation values of the primary PK parameters, Cmax and AUClast after administration of the test treatment, were 442.02 ± 103.37 µg/L and 3131.08 ± 529.30 µg·h/L, respectively, and those after administration of the reference treatment were 436.29 ± 118.74 µg/L and 3006.88 ± 514.21 µg·h/L, respectively. The geometric mean ratio and its 90% confidence interval of test to reference treatment for Cmax and AUClast were 1.0221 (0.9527-1.0967) and 1.0411 (1.0153-1.0677), respectively, which were within the commonly accepted bioequivalence criteria of 0.80 to 1.25. Both treatments were well-tolerated. Conclusion: The two formulations of empagliflozin showed similar PK characteristics and were generally well tolerated in healthy subjects.

Baseline Tyrosine Level Is Associated with Dynamic Changes in FAST Score in NAFLD Patients under Lifestyle Modification.

Noninvasive risk stratification is a challenging issue in the management of patients with nonalcoholic fatty liver disease (NAFLD). This study aimed to identify multiomics-based predictors of NAFLD progression, as assessed by changes in serial FibroScan-aspartate aminotransferase (FAST) scores during lifestyle modification. A total of 266 patients with available metabolomics and genotyping data were included. The follow-up sub-cohort included patients with paired laboratory and transient elastography results (n = 160). The baseline median FAST score was 0.37. The PNPLA3 rs738409 genotype was significantly associated with a FAST score > 0.35. Circulating metabolomics significantly associated with a FAST score > 0.35 included SM C24:0 (odds ratio [OR] = 0.642; 95% confidence interval [CI], 0.463-0.891), PC ae C40:6 (OR = 0.477; 95% CI, 0.340-0.669), lysoPC a C18:2 (OR = 0.570; 95% CI, 0.417-0.779), and tyrosine (OR = 2.743; 95% CI, 1.875-4.014). A combination of these metabolites and PNPLA3 genotype yielded a c-index = 0.948 for predicting a FAST score > 0.35. In the follow-up sub-cohort (median follow-up = 23.7 months), 47/76 patients (61.8%) with a baseline FAST score > 0.35 had a follow-up FAST score ≤ 0.35. An improved FAST score at follow-up was significantly associated with age, serum alanine aminotransferase, and tyrosine. In conclusion, baseline risk stratification in NAFLD patients may be assisted using a multiomics-based model. Particularly, patients with increased tyrosine may benefit from an earlier switch to pharmacologic approaches.

Protective role of colitis in inflammatory arthritis via propionate-producing Bacteroides in the gut.

Objectives: To investigate whether and how inflammatory disease in the intestine influences the development of arthritis, considering that organ-to-organ communication is associated with many physiological and pathological events. Methods: First, mice were given drinking water containing dextran sodium sulfate (DSS) and then subjected to inflammatory arthritis. We compared the phenotypic symptoms between the cohoused and separately-housed mice. Next, donor mice were divided into DSS-treated and untreated groups and then cohoused with recipient mice. Arthritis was then induced in the recipients. The fecal microbiome was analyzed by 16S rRNA amplicon sequencing. We obtained type strains of the candidate bacteria and generated propionate-deficient mutant bacteria. Short-chain fatty acids were measured in the bacterial culture supernatant, serum, feces, and cecum contents using gas chromatography-mass spectrometry. Mice fed with candidate and mutant bacteria were subjected to inflammatory arthritis. Results: Contrary to expectations, the mice treated with DSS exhibited fewer symptoms of inflammatory arthritis. Intriguingly, the gut microbiota contributes, at least in part, to the improvement of colitis-mediated arthritis. Among the altered microorganisms, Bacteroides vulgatus and its higher taxonomic ranks were enriched in the DSS-treated mice. B. vulgatus, B. caccae, and B. thetaiotaomicron exerted anti-arthritic effects. Propionate production deficiency further prevented the protective effect of B. thetaiotaomicron on arthritis. Conclusions: We suggest a novel relationship between the gut and joints and an important role of the gut microbiota as communicators. Moreover, the propionate-producing Bacteroides species examined in this study may be a potential candidate for developing effective treatments for inflammatory arthritis.

Effect of haemodialysis on the pharmacokinetics and pharmacodynamics of evogliptin.

AIM: To investigate the possible effect of haemodialysis (HD) on the pharmacokinetic (PK) and pharmacodynamic (PD) characteristics of evogliptin, a dipeptidyl peptidase-4 (DPP-4) inhibitor. METHODS: A single-dose, open-label, parallel-group study of eight end-stage renal disease (ESRD) patients and eight matched healthy subjects was conducted. ESRD patients received a single oral dose of evogliptin 5 mg after and before HD with a 2-week washout between each dose, and healthy subjects received a single oral dose of evogliptin 5 mg. Serial blood, dialysate, and urine samples were collected to assess the PK and PD profiles of evogliptin. To compare PK parameters before and after HD, geometric mean ratios (GMRs) and 90% confidence intervals (CIs) were calculated. RESULTS: The GMRs for the maximum concentration and area under the concentration-time curve from time 0 to the last measurable timepoint (AUClast ) of evogliptin when administered before HD compared with after HD were 0.7293 (90% CI 0.6171-0.8620) and 0.9480 (90% CI 0.8162-1.1010), respectively. The maximum DPP-4 inhibitory effect, area under the DPP-4 inhibitory effect-time curve, and time duration of more than 80% DPP-4 inhibition were comparable when evogliptin was administered before and after HD. Compared with healthy subjects, the mean AUClast of evogliptin was approximately 1.4-fold greater in ESRD patients, but the difference is unlikely to affect the safety and efficacy of evogliptin. CONCLUSION: The effect of HD on the PK and PD characteristics of evogliptin was not clinically significant; therefore, dose adjustment according to HD status is not necessary.

Dynamic changes in clinical biomarkers of cardiometabolic diseases by changes in exercise behavior, and network comparisons: a community-based prospective cohort study in Korea.

OBJECTIVES: Lifestyles, including exercise behaviors, change continually over time. This study examined whether the clinical biomarkers (CBs) related to cardiometabolic diseases (CMDs) and their relationships differed with changes in exercise behavior. METHODS: The Ansan-Ansung cohort study (third to fifth phases; n=2,668) was used in the current study. Regular exercise behavior was investigated using a yes/no questionnaire. Changes in exercise behavior were classified into 4 groups: Y-N, N-Y, Y-Y, and N-N, with "Y" indicating that a participant regularly engaged in exercise at a given time point and "N" indicating that he or she did not. Fourteen CBs related to CMDs were used, and the associations between changes in exercise behavior and relative changes in CBs were examined. CB networks were constructed and topological comparisons were conducted. RESULTS: Y-N was associated with increases in fasting blood sugar and insulin levels in men, and increased total cholesterol and low-density lipoprotein cholesterol levels in women. Meanwhile, N-Y was inversely associated with body fat percentage, visceral fat percentage, fasting insulin, and triglyceride level. Waist circumference played a central role in most networks. In men, more edges were found in the N-Y and Y-Y groups than in the N-N and Y-N groups, whereas women in the N-Y and Y-Y groups had more edges than those in the N-N and Y-N groups. CONCLUSIONS: Consistent exercise or starting to engage in regular exercise had favorable effects on CBs related to CMDs, although their network patterns differed between the sexes.

Pharmacokinetics of dexmedetomidine in pediatric patients undergoing cardiac surgery with cardiopulmonary bypass.

BACKGROUND: Cardiopulmonary bypass can affect the pharmacokinetics of anesthetic agents. AIMS: We aimed to evaluate the pharmacokinetics of dexmedetomidine for infants and small children undergoing cardiac surgery with cardiopulmonary bypass based on population pharmacokinetics. METHODS: We enrolled 30 pediatric cardiac surgical patients in this study. After anesthetic induction with atropine (0.02 mg/kg), thiopental sodium (5 mg/kg), and fentanyl (2-3 µg/kg), we administered 1 µg/kg of dexmedetomidine for 10 min, followed by administration of 0.5 µg/kg of dexmedetomidine per hour during surgery. At the initiation of cardiopulmonary bypass, 1 µg/kg of dexmedetomidine was infused over 5 min. Arterial blood was obtained at predefined time points. A pharmacokinetic model was developed using NONMEM. Theory-based allometric scaling with fixed exponents was applied. Weight, age, post-menstrual age, fat-free mass, whether to implement cardiopulmonary bypass and temperature were explored as covariates. RESULTS: A total of 376 blood samples were obtained from 29 children (age: 20.3 ± 19.3 months, weight: 9.7 ± 4.1 kg). A two-compartment mammillary model with third compartment associated cardiopulmonary bypass procedure best explained the pharmacokinetics of dexmedetomidine. The pharmacokinetic parameter estimates (95% CI) standardized to a 70-kg person were as follows: V1 (L) = 31.6 (17.9-39.5), V2 (L) = 90.1 (44.0-330), Cl (L/min) = 1.08 (0.70-1.25), Q (L/min) = 2.0 (1.05-3.46). Volume for third compartment associated cardiopulmonary bypass procedure (L) = 39.4 (19.3-50.9). Clearance was not influenced by the presence of cardiopulmonary bypass in this model. CONCLUSION: When cardiopulmonary bypass is applied, the plasma concentration of dexmedetomidine decreases due to an increase in the volume of distribution, so a loading dose is required to maintain the previous concentration.

Identification of Serum Metabolites for Predicting Chronic Kidney Disease Progression according to Chronic Kidney Disease Cause.

Early detection and proper management of chronic kidney disease (CKD) can delay progression to end-stage kidney disease. We applied metabolomics to discover novel biomarkers to predict the risk of deterioration in patients with different causes of CKD. We enrolled non-dialytic diabetic nephropathy (DMN, n = 124), hypertensive nephropathy (HTN, n = 118), and polycystic kidney disease (PKD, n = 124) patients from the KNOW-CKD cohort. Within each disease subgroup, subjects were categorized as progressors (P) or non-progressors (NP) based on the median eGFR slope. P and NP pairs were randomly selected after matching for age, sex, and baseline eGFR. Targeted metabolomics was performed to quantify 188 metabolites in the baseline serum samples. We selected ten progression-related biomarkers for DMN and nine biomarkers each for HTN and PKD. Clinical parameters showed good ability to predict DMN (AUC 0.734); however, this tendency was not evident for HTN (AUC 0.659) or PKD (AUC 0.560). Models constructed with selected metabolites and clinical parameters had better ability to predict CKD progression than clinical parameters only. When selected metabolites were used in combination with clinical indicators, random forest prediction models for CKD progression were constructed with AUCs of 0.826, 0.872, and 0.834 for DMN, HTN, and PKD, respectively. Select novel metabolites identified in this study can help identify high-risk CKD patients who may benefit from more aggressive medical treatment.

Induction of the hepatic aryl hydrocarbon receptor by alcohol dysregulates autophagy and phospholipid metabolism via PPP2R2D.

Disturbed lipid metabolism precedes alcoholic liver injury. Whether and how AhR alters degradation of lipids, particularly phospho-/sphingo-lipids during alcohol exposure, was not explored. Here, we show that alcohol consumption in mice results in induction and activation of aryl hydrocarbon receptor (AhR) in the liver, and changes the hepatic phospho-/sphingo-lipids content. The levels of kynurenine, an endogenous AhR ligand, are elevated with increased hepatic tryptophan metabolic enzymes in alcohol-fed mice. Either alcohol or kynurenine treatment promotes AhR activation with autophagy dysregulation via AMPK. Protein Phosphatase 2 Regulatory Subunit-Bdelta (Ppp2r2d) is identified as a transcriptional target of AhR. Consequently, PPP2R2D-dependent AMPKα dephosphorylation causes autophagy inhibition and mitochondrial dysfunction. Hepatocyte-specific AhR ablation attenuates steatosis, which is associated with recovery of phospho-/sphingo-lipids content. Changes of AhR targets are corroborated using patient specimens. Overall, AhR induction by alcohol inhibits autophagy in hepatocytes through AMPKα, which is mediated by Ppp2r2d gene transactivation, revealing an AhR-dependent metabolism of phospho-/sphingo-lipids.

Identification of Metabolic Signature Associated with Idiopathic Inflammatory Myopathy Reveals Polyamine Pathway Alteration in Muscle Tissue.

Idiopathic inflammatory myopathy (IIM) is hard to diagnose without a muscle biopsy. We aimed to identify a metabolite panel for IIM detection by metabolomics approach in serum samples and to explore the metabolomic signature in tissue samples from a mouse model. We obtained serum samples from IIM patients, ankylosing spondylitis (AS) patients, healthy volunteers and muscle tissue samples from IIM murine model. All samples were subjected to a targeted metabolomic approach with various statistical analyses on serum and tissue samples to identify metabolic alterations. Three machine learning methods, such as logistic regression (LR), support vector machine (SVM), and random forest (RF), were applied to build prediction models. A set of 7 predictive metabolites was calculated using backward stepwise selection, and the model was evaluated within 5-fold cross-validation by using three machine algorithms. The model produced an area under the receiver operating characteristic curve values of 0.955 (LR), 0.908 (RF) and 0.918 (SVM). A total of 68 metabolites were significantly changed in mouse tissue. Notably, the most influential pathways contributing to the inflammation of muscle were the polyamine pathway and the beta-alanine pathway. Our metabolomic approach offers the potential biomarkers of IIM and reveals pathologically relevant metabolic pathways that are associated with IIM.