Yen-Tsung Huang | Search PubMed

PubMed2025

INCREASED CIRCULATORY KREBS CYCLE METABOLITES IN SEPSIS IS ASSOCIATED WITH INCREASED INTERLEUKIN-6 RELEASE AND WORSE SURVIVAL.

Objective : Recent studies have proposed that Krebs cycle metabolites may serve as potential biomarkers for prognosis in sepsis. However, whether these metabolites are associated with disease severity and can be applied to improve the effectiveness of current prognosis assessment in sepsis remains unclear and is explored in this study. Methods : This prospective multicenter cohort study was conducted in medical intensive care units (ICUs). From December 2019 to September 2022, consecutive patients admitted to medical ICUs for sepsis were screened and recruited. Plasma samples were obtained for measurements of cytokines and Krebs cycle metabolites, including citrate/isocitrate, cis-aconitate, alpha-ketoglutarate, succinate, fumarate, and malate. Results : In total, 97 patients admitted for sepsis were enrolled in the study. The 28-day mortality rate was 17.5%, and nonsurvivors exhibited significantly increased plasma lactate levels and Sequential Organ Failure Assessment (SOFA) scores. Plasma levels of Krebs cycle metabolites were significantly correlated with both plasma lactate and interleukin-6 levels. Except for citrate/isocitrate, all Krebs cycle metabolites were significantly elevated in patients with acute kidney injury. Multivariate Cox proportional hazard models, adjusted for plasma lactate levels and SOFA scores, revealed that plasma levels of alpha-ketoglutarate (adjusted hazard ratio [HR]: 2.404, P = 0.002), fumarate (adjusted HR: 1.904, P = 0.001) and malate (adjusted HR: 1.327, P = 0.019) were associated with increased risk of 28-day mortality. Conclusions : Study findings indicate that Krebs cycle metabolites, particularly alpha-ketoglutarate, fumarate, and malate, when applied with SOFA score, might enhance prognostic assessment in patients with sepsis.

Humans↗

PubMed2024

Causal Mediation Analysis for Integrating Exposure, Genomic, and Phenotype Data.

Causal mediation analysis provides an attractive framework for integrating diverse types of exposure, genomic, and phenotype data. Recently, this field has seen a surge of interest, largely driven by the increasing need for causal mediation analyses in health and social sciences. This article aims to provide a review of recent developments in mediation analysis, encompassing mediation analysis of a single mediator and a large number of mediators, as well as mediation analysis with multiple exposures and mediators. Our review focuses on the recent advancements in statistical inference for causal mediation analysis, especially in the context of high-dimensional mediation analysis. We delve into the complexities of testing mediation effects, especially addressing the challenge of testing a large number of composite null hypotheses. Through extensive simulation studies, we compare the existing methods across a range of scenarios. We also include an analysis of data from the Normative Aging Study, which examines DNA methylation CpG sites as potential mediators of the effect of smoking status on lung function. We discuss the pros and cons of these methods and future research directions.

causal inference↗