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Patients with tuberous sclerosis complex (TSC) develop multi-organ disease manifestations, with kidney angiomyolipomas (AML) and cysts being one of the most common and deadly. Early and regular AML/cyst detection and monitoring are vital to lower TSC patient morbidity and mortality. However, the current standard of care involves imaging-based methods that are not designed for rapid screening, posing challenges for early detection. To identify potential diagnostic screening biomarkers of AML/cysts, we performed global untargeted metabolomics in blood samples from 283 kidney AML/cyst-positive or -negative TSC patients using mass spectrometry. We identified 7 highly sensitive chemical features, including octanoic acid, that predict kidney AML/cysts in TSC patients. Patients with elevated octanoic acid have lower levels of very long-chain fatty acids (VLCFAs), suggesting that dysregulated peroxisome activity leads to overproduction of octanoic acid via VLCFA oxidation. These data highlight AML/cysts blood biomarkers for TSC patients and offers valuable metabolic insights into the disease.

* Context.--Recently, an exchangeable copper (CuEXC) assay has been suggested as a robust and feasible diagnostic tool for Wilson disease (WD). Although WD is a disorder that requires lifelong treatment and monitoring, few data are currently available regarding the status of copper levels in children. Objective.--To evaluate the performance of copper assays and establish a reference interval for total copper and CuEXC in the pediatric population. Design.--Serum samples from children aged 1-5 (n = 122), 6-12 (n = 125), and 13-18 years (n = 120) were analyzed. Total copper and CuEXC concentrations were directly measured using inductively coupled plasma mass spectrometry, and relative CuEXC levels were calculated. Total copper reference intervals, CuEXC levels, and relative CuEXC levels were determined based on the 2.5th and 97.5th percentiles of the data with 90% confidence intervals. Results.--There were significant differences in the median concentrations of total copper and relative CuEXC among the age groups. Reference intervals determined for total copper were 82 to 167, 75 to 139, and 64 to 133 Ig/dL for children aged 1 to 5, 6 to 12, and 13 to 18 years, respectively. The reference intervals for CuEXC were 4.29 to 9.79, 4.02 to 9.09, and 3.55 to 8.25 [micro]g/dL for children aged 1 to 5, 6 to 12, and 13 to 18 years, respectively. Among 11 patients with suspected WD, relative CuEXC values were elevated in all 3 diagnosed with WD. Conclusions.--The pediatric reference intervals derived in this study are expected to be useful for the diagnosis, differential diagnosis, treatment, and monitoring of pediatric patients with WD. (Arch Pathol Lab Med. 2021;145:877-882; doi: 10.5858/arpa.2020-0029-OA), Wilson disease (WD) is a genetic disorder associated with copper metabolism. It is an autosomal recessive condition caused by mutations in ATP7B, which encodes a transmembrane copper-transporting ATPase (ATP7B) that [...]

Aims: This study was conducted to develop a population pharmacokinetic (PK) model of methotrexate in Korean patients with haematologic malignancy, identify factors affecting methotrexate PK, and propose an optimal dosage regimen for the Korean population. Methods: Data were retrospectively collected from 188 patients with acute leukaemia or non‐Hodgkin's lymphoma who were admitted to Severance Hospital during the period from November 2005 to January 2016. Using demographic factors and laboratory results as potential covariates for PK parameters, model development was performed using NONMEM and optimal dosing regimens were developed using the final PK model. Results: A two‐compartment model incorporating body weight via allometry best described the data, yielding typical parameter values of 25.09 L for central volume of distribution (V1), 17.65 L for peripheral volume of distribution (V2), 12.89 L/h for clearance (CL) and 0.655 L/h for inter‐compartmental clearance in a 50 kg patient. Covariate analyses showed that, at the weight of 50 kg, CL decreased by 0.11 L/h for each 1‐year increase in age above 14 years old and decreased 0.8‐fold when serum creatinine level doubled, indicating the importance of age‐specific dose individualization in methotrexate treatment. Volume of distribution at steady state derived from PK parameters (= V1 + V2) was 0.85 L/kg, which was similar to those in the Western or Chinese populations. Optimal doses simulated from the final model successfully produced the PK measures close to the target chosen. Conclusions: The population PK model and optimal dosage regimens developed in this study can be used as a basis to achieve precision dosing in Korean patients with haematologic malignancy. [ABSTRACT FROM AUTHOR]

Aim: We aimed to evaluate the metabolite ratios that could predict the clinical incidence or remission of type 2 diabetes mellitus (T2D). Methods: The Cox proportional hazards regression model was used to assess 1813 individuals without T2D to test the predictive value of metabolite ratios for T2D incidence and 451 newly diagnosed T2D for remission. The receiver operating characteristic curve analysis was performed to determine the best cut‐off values for the metabolite ratios. Survival analyses were performed to compare the four subgroups defined by baseline metabolite ratios and clinical status of obesity. Results: The alanine/glycine was the most significant marker for T2D incidence (hazard ratio per SD: 1.24; p <.001). On the other hand, metabolite hydroxy sphingomyelin C22:2 was most specific for T2D remission (hazard ratio per SD: 1.32; p =.029). Survival analysis of T2D incidence among the subgroups defined by the combination of alanine/glycine and obesity showed the group with a high alanine/glycine and obesity had the highest risk of T2D incidence (p <.001). The alanine/glycine as a T2D risk marker was also validated in the independent external data. Conclusions: The combination of obesity and the alanine/glycine ratio can be used to evaluate the diabetes risk. [ABSTRACT FROM AUTHOR]

Background: Carbohydrate antigen (CA) 19–9 is a known pancreatic cancer (PC) biomarker, but is not commonly used for general screening due to its low sensitivity and specificity. This study aimed to develop a serum metabolites‐based diagnostic calculator for detecting PC with high accuracy. Methods: A targeted quantitative approach of direct flow injection‐tandem mass spectrometry combined with liquid chromatography–tandem mass spectrometry was employed for metabolomic analysis of serum samples using an Absolute IDQ™ p180 kit. Integrated metabolomic analysis was performed on 241 pooled or individual serum samples collected from healthy donors and patients from nine disease groups, including chronic pancreatitis, PC, other cancers, and benign diseases. Orthogonal partial least squares discriminant analysis (OPLS‐DA) based on characteristics of 116 serum metabolites distinguished patients with PC from those with other diseases. Sparse partial least squares discriminant analysis (SPLS‐DA) was also performed, incorporating simultaneous dimension reduction and variable selection. Predictive performance between discrimination models was compared using a 2‐by‐2 contingency table of predicted probabilities obtained from the models and actual diagnoses. Results: Predictive values obtained through OPLS‐DA for accuracy, sensitivity, specificity, balanced accuracy, and area under the receiver operating characteristic curve (AUC) were 0.9825, 0.9916, 0.9870, 0.9866, and 0.9870, respectively. The number of metabolite candidates was narrowed to 76 for SPLS‐DA. The SPLS‐DA‐obtained predictive values for accuracy, sensitivity, specificity, balanced accuracy, and AUC were 0.9773, 0.9649, 0.9832, 0.9741, and 0.9741, respectively. Conclusions: We successfully developed a 76 metabolome‐based diagnostic panel for detecting PC that demonstrated high diagnostic performance in differentiating PC from other diseases. [ABSTRACT FROM AUTHOR]