Proteomics profiling reveals inflammatory biomarkers of antidepressant treatment response: Findings from the CO-MED trial

Gadad, Bharathi S.; Jha, Manish K.; Grannemann, Bruce D.; Mayes, Taryn L.; Trivedi, Madhukar H.

doi:10.1016/j.jpsychires.2017.05.012

Cited by 25 publications

(14 citation statements)

References 32 publications

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“…Additionally, high levels of VEGF-A mRNA in whole blood from patients with depression were reported, although the VEGF protein levels in the plasma were not affected [47]. Further, an increased IFNγ /IL-10 ratio and changes in CCL11 and IFNγ with antidepressant treatments have been reported [48,49], but the lithium augmentation of antidepressants had no effect on the inflammatory markers in MDD [50].…”

Section: Inflammatory Markers In Psychiatric Disordersmentioning

confidence: 99%

Depression, GABA, and Age Correlate with Plasma Levels of Inflammatory Markers

Bhandage

Cunningham

Jin

et al. 2019

IJMS

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Immunomodulation is increasingly being recognised as a part of mental diseases. Here, we examined whether levels of immunological protein markers changed with depression, age, or the inhibitory neurotransmitter gamma-aminobutyric acid (GABA). An analysis of plasma samples from patients with a major depressive episode and control blood donors (CBD) revealed the expression of 67 inflammatory markers. Thirteen of these markers displayed augmented levels in patients compared to CBD. Twenty-one markers correlated with the age of the patients, whereas 10 markers correlated with the age of CBD. Interestingly, CST5 and CDCP1 showed the strongest correlation with age in the patients and CBD, respectively. IL-18 was the only marker that correlated with the MADRS-S scores of the patients. Neuronal growth factors (NGFs) were significantly enhanced in plasma from the patients, as was the average plasma GABA concentration. GABA modulated the release of seven cytokines in anti-CD3-stimulated peripheral blood mononuclear cells (PBMCs) from the patients. The study reveals significant changes in the plasma composition of small molecules during depression and identifies potential peripheral biomarkers of the disease.

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Section: Inflammatory Markers In Psychiatric Disordersmentioning

confidence: 99%

Depression, GABA, and Age Correlate with Plasma Levels of Inflammatory Markers

Bhandage

Cunningham

Jin

et al. 2019

IJMS

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“…This approach would allow for a rapid assessment of a large number of potential biomarkers in order to determine which are relevant to either remission or no benefit and which are not, and recent literature supports the utility of biomarkers in depression research. 18 , 42 – 44 …”

Section: Discussionmentioning

confidence: 99%

Accurately identifying patients who are excellent candidates or unsuitable for a medication: a novel approach

South

Rush

Carmody

et al. 2017

NDT

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ObjectiveThe objective of the study was to determine whether a unique analytic approach – as a proof of concept – could identify individual depressed outpatients (using 30 baseline clinical and demographic variables) who are very likely (75% certain) to not benefit (NB) or to remit (R), accepting that without sufficient certainty, no prediction (NP) would be made.MethodsPatients from the Combining Medications to Enhance Depression Outcomes trial treated with escitalopram (S-CIT) + placebo (n=212) or S-CIT + bupropion-SR (n=206) were analyzed separately to assess replicability. For each treatment, the elastic net was used to identify subsets of predictive baseline measures for R and NB, separately. Two different equations that estimate the likelihood of remission and no benefit were developed for each patient. The ratio of these two numbers characterized likely outcomes for each patient.ResultsThe two treatment cells had comparable rates of remission (40%) and no benefit (22%). In S-CIT + bupropion-SR, 11 were predicted NB of which 82% were correct; 26 were predicted R – 85% correct (169 had NP). For S-CIT + placebo, 13 were predicted NB – 69% correct; 44 were predicted R – 75% correct (155 were NP). Overall, 94/418 (22%) patients were identified with a meaningful degree of certainty (69%–85% correct). Different variable sets with some overlap were predictive of remission and no benefit within and across treatments, despite comparable outcomes.ConclusionIn two separate analyses with two different treatments, this analytic approach – which is also applicable to pretreatment laboratory tests – identified a meaningful proportion (over 20%) of depressed patients for whom a treatment outcome was predicted with sufficient certainty that the clinician can elect to strongly recommend for or choose to avoid a particular treatment. Different persons seem to be remitting or not benefiting with these two different treatments.

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“…Maes et al examined the effects of clomipramine, sertraline, and trazadone on the stimulated production of IFN-γ and IL-10, and observed that all three antidepressants significantly increased the IFN-γ/IL-10 ratio (Maes, 2001). Lastly, a recent study by Gadad et al identified only two of 31 potential inflammatory markers (Eotaxin/CCL11 and IFNγ) that significantly changed pre- to post- antidepressant treatment in the CO-MED study (Gadad et al, 2017, in press; Rush et al, 2011). Interestingly, increased levels of Eotaxin was associated with remission, whereas decreased IFNγ was associated with non-remission.…”

Section: Biomarker Discovery—tools and Applicationmentioning

confidence: 97%