Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients

Int J Neuropsychopharmacol. 2016 Sep 30;19(10):pyw045. doi: 10.1093/ijnp/pyw045. Print 2016 Oct.

Abstract

Background: Increased levels of inflammation have been associated with a poorer response to antidepressants in several clinical samples, but these findings have had been limited by low reproducibility of biomarker assays across laboratories, difficulty in predicting response probability on an individual basis, and unclear molecular mechanisms.

Methods: Here we measured absolute mRNA values (a reliable quantitation of number of molecules) of Macrophage Migration Inhibitory Factor and interleukin-1β in a previously published sample from a randomized controlled trial comparing escitalopram vs nortriptyline (GENDEP) as well as in an independent, naturalistic replication sample. We then used linear discriminant analysis to calculate mRNA values cutoffs that best discriminated between responders and nonresponders after 12 weeks of antidepressants. As Macrophage Migration Inhibitory Factor and interleukin-1β might be involved in different pathways, we constructed a protein-protein interaction network by the Search Tool for the Retrieval of Interacting Genes/Proteins.

Results: We identified cutoff values for the absolute mRNA measures that accurately predicted response probability on an individual basis, with positive predictive values and specificity for nonresponders of 100% in both samples (negative predictive value=82% to 85%, sensitivity=52% to 61%). Using network analysis, we identified different clusters of targets for these 2 cytokines, with Macrophage Migration Inhibitory Factor interacting predominantly with pathways involved in neurogenesis, neuroplasticity, and cell proliferation, and interleukin-1β interacting predominantly with pathways involved in the inflammasome complex, oxidative stress, and neurodegeneration.

Conclusion: We believe that these data provide a clinically suitable approach to the personalization of antidepressant therapy: patients who have absolute mRNA values above the suggested cutoffs could be directed toward earlier access to more assertive antidepressant strategies, including the addition of other antidepressants or antiinflammatory drugs.

Keywords: cytokine absolute blood levels; personalized medicine; predictors; treatment response.

Publication types

  • Comparative Study
  • Multicenter Study
  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Affect / drug effects*
  • Antidepressive Agents, Second-Generation / therapeutic use*
  • Antidepressive Agents, Tricyclic / therapeutic use*
  • Cell-Free Nucleic Acids / blood
  • Cell-Free Nucleic Acids / genetics*
  • Citalopram / therapeutic use*
  • Depressive Disorder, Major / diagnosis
  • Depressive Disorder, Major / drug therapy*
  • Depressive Disorder, Major / genetics
  • Depressive Disorder, Major / psychology
  • Discriminant Analysis
  • Female
  • Gene Expression Profiling / methods
  • Humans
  • Interleukin-1beta / blood
  • Interleukin-1beta / genetics*
  • Intramolecular Oxidoreductases / blood
  • Intramolecular Oxidoreductases / genetics*
  • Linear Models
  • Logistic Models
  • Macrophage Migration-Inhibitory Factors / blood
  • Macrophage Migration-Inhibitory Factors / genetics*
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Nortriptyline / therapeutic use*
  • Predictive Value of Tests
  • Protein Interaction Maps
  • RNA, Messenger / blood
  • RNA, Messenger / genetics*
  • Time Factors
  • Treatment Outcome

Substances

  • Antidepressive Agents, Second-Generation
  • Antidepressive Agents, Tricyclic
  • Cell-Free Nucleic Acids
  • IL1B protein, human
  • Interleukin-1beta
  • Macrophage Migration-Inhibitory Factors
  • RNA, Messenger
  • Citalopram
  • Nortriptyline
  • Intramolecular Oxidoreductases
  • MIF protein, human