Your browser doesn't support javascript.
loading
Pharmacometabolomics identifies candidate predictor metabolites of an L-carnitine treatment mortality benefit in septic shock.
Puskarich, Michael A; Jennaro, Theodore S; Gillies, Christopher E; Evans, Charles R; Karnovsky, Alla; McHugh, Cora E; Flott, Thomas L; Jones, Alan E; Stringer, Kathleen A.
Afiliação
  • Puskarich MA; Department of Emergency Medicine, University of Minnesota, Minneapolis, Minnesota, USA.
  • Jennaro TS; Department of Emergency Medicine, Hennepin County Medical Center, Minneapolis, Minnesota, USA.
  • Gillies CE; The NMR Metabolomics Laboratory and the Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA.
  • Evans CR; Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan, USA.
  • Karnovsky A; Michigan Center for Integrative Research in Critical Care (MCIRCC), University of Michigan, Ann Arbor, Michigan, USA.
  • McHugh CE; Michigan Institute for Data Science, Office of Research, University of Michigan, Ann Arbor, Michigan, USA.
  • Flott TL; Michigan Regional Comprehensive Metabolomics Resource Core (MRC2, ), University of Michigan, Ann Arbor, Michigan, USA.
  • Jones AE; Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
  • Stringer KA; Michigan Regional Comprehensive Metabolomics Resource Core (MRC2, ), University of Michigan, Ann Arbor, Michigan, USA.
Clin Transl Sci ; 14(6): 2288-2299, 2021 11.
Article em En | MEDLINE | ID: mdl-34216108
ABSTRACT
Sepsis-induced metabolic dysfunction contributes to organ failure and death. L-carnitine has shown promise for septic shock, but a recent phase II study of patients with vasopressor-dependent septic shock demonstrated a non-significant reduction in mortality. We undertook a pharmacometabolomics study of these patients (n = 250) to identify metabolic profiles predictive of a 90-day mortality benefit from L-carnitine. The independent predictive value of each pretreatment metabolite concentration, adjusted for L-carnitine dose, on 90-day mortality was determined by logistic regression. A grid-search analysis maximizing the Z-statistic from a binomial proportion test identified specific metabolite threshold levels that discriminated L-carnitine responsive patients. Threshold concentrations were further assessed by hazard ratio and Kaplan-Meier estimate. Accounting for L-carnitine treatment and dose, 11 1 H-NMR metabolites and 12 acylcarnitines were independent predictors of 90-day mortality. Based on the grid-search analysis numerous acylcarnitines and valine were identified as candidate metabolites of drug response. Acetylcarnitine emerged as highly viable for the prediction of an L-carnitine mortality benefit due to its abundance and biological relevance. Using its most statistically significant threshold concentration, patients with pretreatment acetylcarnitine greater than or equal to 35 µM were less likely to die at 90 days if treated with L-carnitine (18 g) versus placebo (p = 0.01 by log rank test). Metabolomics also identified independent predictors of 90-day sepsis mortality. Our proof-of-concept approach shows how pharmacometabolomics could be useful for tackling the heterogeneity of sepsis and informing clinical trial design. In addition, metabolomics can help understand mechanisms of sepsis heterogeneity and variable drug response, because sepsis induces alterations in numerous metabolite concentrations.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Choque Séptico / Carnitina / Morte / Metabolômica Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Choque Séptico / Carnitina / Morte / Metabolômica Idioma: En Ano de publicação: 2021 Tipo de documento: Article