Making Sense of Blood-Based Proteomics and Metabolomics in Psychiatric Research

Guest, Paul C.; Guest, Francesca L.; Martins-de-Souza, Daniel

doi:10.1093/ijnp/pyv138

Cited by 46 publications

(53 citation statements)

References 37 publications

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“…In psychiatric practice a biomarker (or panel of biomarkers) may be useful: (i) to correctly diagnose and stratify a psychiatric patient, in a field where several diseases may have overlapping clinical symptoms, or even (ii) to better classify at-risk individuals; (iii) it may also be used for prognosis or (iv) as therapeutic monitoring, and (v) predictive of therapy compliance [9,11,12]. In summary, the definition of a biomarker states that it should be a quantifiable or identifiable physical characteristic that is closely and exclusively related to a given physiological state.…”

Section: The Need For Biomarkers In Psychosismentioning

confidence: 99%

“…The impact of these factors is difficult to anticipate with a genomic analysis, but they are reflected in the molecular phenotype. Moreover, the genome is static while the proteome and metabolome are dynamic [12,23], making it possible to quantitatively track a molecule over time, therefore allowing to evaluate disease progression, correlating its levels with symptom severity or anticipating therapeutic outcomes.…”

Section: The Need For Biomarkers In Psychosismentioning

confidence: 99%

“…For over a decade peripheral fluids' analyses, for disease investigation and biomarker discovery in particular, have increased in the psychiatric field [12]. As shown in Table 2, blood-based analysis account for the majority of such studies, especially with the analysis of serum and plasma, although blood cells' analysis is growing in interest ( Table 3) [74].…”

Section: Biomarker Discovery In Peripheral Fluidsmentioning

confidence: 99%

See 2 more Smart Citations

Circulating biomarkers in schizophrenia: a proteomics perspective

Santa¹,

Coelho²,

Madeira³

et al. 2017

IJCNMH

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Schizophrenia (SCZ) is one of the most severe and devastating major mental disorders, with an onset typically in late adolescence or early adulthood affecting about 0.5-1.2% of the population worldwide. It is one of the most debilitating medical conditions, with striking socio-economic burden to society due to lost employment and social support that largely surpass direct costs of treatment. SCZ is listed by the World Health Organization (WHO) among the top 20 leading causes of disability worldwide. Its diagnosis is syndromic, based in clinical interviewing and anamnesis, as there is to date no biochemical test to aid in this diagnosis. On the other hand, SCZ treatment is mostly based in antipsychotic drugs which are in several aspects somehow ineffective, and some of these medications have low tolerability with severe side effects. For all these reasons, the current search for new panels of biomarkers is of the utmost importance to aid in the correct diagnosis and stratification of the patients, prognosis, and prediction of treatment effectiveness.In this review, a total of 25 publications on peripheral SCZ biomarkers are presented from proteomics studies performed in body fluids of patients searching for protein markers, and using mass spectrometry. To date such proteomics studies have already been achieved in cerebrospinal fluid (CSF), serum, plasma, peripheral blood cells (namely, mononuclear cells, T-cells and red blood cells), saliva, and sweat, being of paramount importance in the schizophrenia research field, but still lacking validation and clinical translation.In summary, a general overview of the results from these 25 studies, as well as the challenges and future perspectives of the field, are presented and discussed.

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Section: The Need For Biomarkers In Psychosismentioning

confidence: 99%

Section: The Need For Biomarkers In Psychosismentioning

confidence: 99%

Section: Biomarker Discovery In Peripheral Fluidsmentioning

confidence: 99%

See 1 more Smart Citation

Circulating biomarkers in schizophrenia: a proteomics perspective

Santa¹,

Coelho²,

Madeira³

et al. 2017

IJCNMH

View full text Add to dashboard Cite

show abstract

“…However, research in this area has still not lived up to its potential. One main reason behind this is that psychiatric illnesses are thus far classified using diagnostic concepts which could be subjective [3]. Therefore, the incorporation of biomarkers into current clinical methods might help to generate a classification system for mental health disorders that can be linked to the underlying dysfunctional pathways, as proposed by the National Institute of Mental Health Research Domain Criteria (RDoC) project [4].…”

Section: Introductionmentioning

confidence: 99%

Metabolomics in Psychiatric Disorders: What We Learn from Animal Models

2020

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Biomarkers are a recent research target within biological factors of psychiatric disorders. There is growing evidence for deriving biomarkers within psychiatric disorders in serum or urine samples in humans, however, few studies have investigated this differentiation in brain or cerebral fluid samples in psychiatric disorders. As brain samples from humans are only available at autopsy, animal models are commonly applied to determine the pathogenesis of psychiatric diseases and to test treatment strategies. The aim of this review is to summarize studies on biomarkers in animal models for psychiatric disorders. For depression, anxiety and addiction disorders studies, biomarkers in animal brains are available. Furthermore, several studies have investigated psychiatric medication, e.g., antipsychotics, antidepressants, or mood stabilizers, in animals. The most notable changes in biomarkers in depressed animal models were related to the glutamate-γ-aminobutyric acid-glutamine-cycle. In anxiety models, alterations in amino acid and energy metabolism (i.e., mitochondrial regulation) were observed. Addicted animals showed several biomarkers according to the induced drugs. In summary, animal models provide some direct insights into the cellular metabolites that are produced during psychiatric processes. In addition, the influence on biomarkers due to short- or long-term medication is a noticeable finding. Further studies should combine representative animal models and human studies on cerebral fluid to improve insight into mental disorders and advance the development of novel treatment strategies.

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“…Biomarkers can potentially be used as markers for illness or diagnosis, or as markers of response to treatment (14). Throughout this thesis, biomarkers are examined in the context of biological markers of illness.…”

Section: Introductionmentioning

confidence: 99%

The role of cytokines and inflammatory markers in depression in adolescents

Mills¹

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Aims: The overarching hypothesis is that circulating levels of pro-inflammatory cytokines and other inflammatory markers are genetically associated with depression in adolescents.Specifically, it is hypothesised that there will be a correlation between variation in genetic risk of depression and genetic variation of circulating pro-inflammatory cytokines and inflammatory markers. Methods:A systematic review of the literature was conducted to establish the current understanding of the relationship between inflammatory markers and depression in adolescents and to inform study design. Multiple approaches (including different types of genetic analyses and multiple data sets) were used to address the overarching hypothesis.A pilot study measuring cytokines, inflammatory markers, and other biomarkers involved in immune regulation (including Vitamin D, antibodies to infectious agents, and gliadin antibodies (found in coeliac disease)) was conducted in 107 monozygotic (MZ) and 160 dizygotic (DZ) twin pairs (mean age 16.2 years, standard deviation (SD) 0.25 years) from the Brisbane Adolescent Twin Study. A clinical study was undertaken to collect biological samples and clinical data from an in-patient adolescent mental health unit. Investigation of the relationship between iron measures (altered in inflammatory states)and measures of depression was undertaken in community cohorts of twins and their parents (3,416 adolescents from 1,688 families, and 9,035 adults from 4,533 families). In the adolescent cohort, depressive measures were assessed through the Somatic and Psychological Health Report (SPHERE) (mean age 15.1 years (SD 3.2 years)). In the adult cohort, a quantitative score of depression was measured by the Delusions Symptoms State Inventory (DSSI) (mean age 23.2 years (SD 2.2 years)). Heritabilities of, and phenotypic and genetic correlations between, traits were estimated. Association analyses, genetic profile risk score analyses, and LD score analyses were also used to investigate the genetic relationship between the iron and depression measures. Genetic profile risk score analyses were used to explore the genetic relationship between these variables. Results:In the pilot study, cytokines that were successfully measured in plasma were found to be moderately heritable (transforming growth factor-β1 (TGFβ1), 0.57 (95% CI 0.26 -0.80) and tumour necrosis factor-receptor type 1 (TNFR1), 0.50 (95% CI 0.11-0.63)). A negative correlation between Vitamin D and the cytokine IL-18 (-0.14) was not statistically significant (p=0.054). However, major difficulties were encountered in measuring cytokines, in particular due to the low levels of circulating cytokines in healthy adolescents. Challenges were also encountered in the cytokines study of the clinical sample of adolescents, which were able to be broadly divided into patient factors, blood collection factors, and other data collection factors.Iron measures were found to be highly heritable in both adolescents and adults: The relationship between CRP and Major D...

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Making Sense of Blood-Based Proteomics and Metabolomics in Psychiatric Research

Cited by 46 publications

References 37 publications

Circulating biomarkers in schizophrenia: a proteomics perspective

Circulating biomarkers in schizophrenia: a proteomics perspective

Metabolomics in Psychiatric Disorders: What We Learn from Animal Models

The role of cytokines and inflammatory markers in depression in adolescents

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