Evidence map›Paper›PMID 33978935›Full record

SynthesisMolecular diagnosis & therapy2021

The Potential Use of Peripheral Blood Mononuclear Cells as Biomarkers for Treatment Response and Outcome Prediction in Psychiatry: A Systematic Review.

Jobbe Goossens, Manuel Morrens, Violette Coppens

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Molecular diagnosis & therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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  9. Novel perspectives on early diagnosis of acute compartment syndrome: the role of admission blood tests.Journal of orthopaedics and traumatology : official journal of the Italian Society of Orthopaedics and Traumatology · 2024
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  10. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jobbe GoossensFaculty of Medicine and Health Sciences, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, R3.22, Building R, Campus Drie Eiken, Universiteitsplein 1, 2610, Antwerp, Belgium. jobbe.goossens@uantwerpen.be.ORCID 0000-0002-7713-6358
Manuel MorrensFaculty of Medicine and Health Sciences, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, R3.22, Building R, Campus Drie Eiken, Universiteitsplein 1, 2610, Antwerp, Belgium.
Violette CoppensFaculty of Medicine and Health Sciences, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, R3.22, Building R, Campus Drie Eiken, Universiteitsplein 1, 2610, Antwerp, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPsychiatric disorders have a major impact on the global burden of disease while therapeutic interventions remain insufficient to adequately treat a large number of patients. Regrettably, the efficacy of several psychopharmacological treatment regimens becomes apparent only after 4-6 weeks, and at this point, a significant number of patients present as non-responsive. As such, many patients go weeks/months without appropriate treatment or symptom management. Adequate biomarkers for treatment success and outcome prediction are thus urgently needed.

objectiveWith this systematic review, we provide an overview of the use of peripheral blood mononuclear cells (PBMCs) and their signaling pathways in evaluating and/or predicting the effectiveness of different treatment regimens in the course of psychiatric illnesses. We highlight PBMC characteristics that (i) reflect treatment presence, (ii) allow differentiation of responders from non-responders, and (iii) prove predictive at baseline with regard to treatment outcome for a broad range of psychiatric intervention strategies. REVIEW

methodsA PubMed database search was performed to extract papers investigating the relation between any type of PBMC characteristic and treatment presence and/or outcome in patients suffering from severe mental illness. Criteria for eligibility were: written in English; psychiatric diagnosis based on DSM-III-R or newer; PBMC isolation via gradient centrifugation; comparison between treated and untreated patients via PBMC features; sample size ≥ n = 5 per experimental group. Papers not researching in vivo treatment effects between patients and healthy controls, non-clinical trials, and non-hypothesis-/data-driven (e.g., -omics designs) approaches were excluded. DATA SYNTHESIS: Twenty-nine original articles were included and qualitatively summarized. Antidepressant and antipsychotic treatments were mostly reflected by intracellular inflammatory markers while intervention with mood stabilizers was evidenced through cell maturation pathways. Lastly, cell viability parameters mirrored predominantly non-pharmacological therapeutic strategies. As for response prediction, PBMC (subtype) counts and telomerase activity seemed most promising for antidepressant treatment outcome determination; full length brain-derived neurotrophic factor (BDNF)/truncated BDNF were shown to be most apt to prognosticate antipsychotic treatment.

conclusionsWe conclude that, although inherent limitations to and heterogeneity in study designs in combination with the scarce number of original studies hamper unambiguous identification, several PBMC characteristics-mostly related to inflammatory pathways and cell viability-indeed show promise towards establishment as clinically relevant treatment biomarkers.

Indexed as

Antidepressive AgentsAntipsychotic AgentsBiomarkersBrain-Derived Neurotrophic FactorClinical Trials as TopicGene Expression RegulationHumansLeukocytes, MononuclearMental DisordersTelomeraseTreatment OutcomeAntidepressive AgentsAntipsychotic AgentsBDNF protein, humanBiomarkersBrain-Derived Neurotrophic FactorTelomerase

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.