Alpha-1-acid glycoprotein in major depressive disorder. Relationships to severity, response to treatment and imipramine plasma levels

Biomarkers as predictors of treatment response to tricyclic antidepressants in major depressive disorder: A systematic review

Tricyclic antidepressants (TCAs) are frequently prescribed in case of non-response to first-line antidepressants in Major Depressive Disorder (MDD). Treatment of MDD often entails a trial-and-error process of finding a suitable antidepressant and its appropriate dose. Nowadays, a shift is seen towards a more personalized treatment strategy in MDD to increase treatment efficacy. One of these strategies involves the use of biomarkers for the prediction of antidepressant treatment response. We aimed to summarize biomarkers for prediction of TCA specific (i.e. per agent, not for the TCA as a drug class) treatment response in unipolar nonpsychotic MDD. We performed a systematic search in PubMed and MEDLINE. After full-text screening, 36 papers were included. Seven genetic biomarkers were identified for nortriptyline treatment response. For desipramine, we identified two biomarkers; one genetic and one nongenetic. Three nongenetic biomarkers were identified for imipramine. None of these biomarkers were replicated. Quality assessment demonstrated that biomarker studies vary in endpoint definitions and frequently lack power calculations. None of the biomarkers can be confirmed as a predictor for TCA treatment response. Despite the necessity for TCA treatment optimization, biomarker studies reporting drug-specific results for TCAs are limited and adequate replication studies are lacking. Moreover, biomarker studies generally use small sample sizes. To move forward, larger cohorts, pooled data or biomarkers combined with other clinical characteristics should be used to improve predictive power.

Diagnostic prediction model development using data from dried blood spot proteomics and a digital mental health assessment to identify major depressive disorder among individuals presenting with low mood

With less than half of patients with major depressive disorder (MDD) correctly diagnosed within the primary care setting, there is a clinical need to develop an objective and readily accessible test to enable earlier and more accurate diagnosis. The aim of this study was to develop diagnostic prediction models to identify MDD patients among individuals presenting with subclinical low mood, based on data from dried blood spot (DBS) proteomics (194 peptides representing 115 proteins) and a novel digital mental health assessment (102 sociodemographic, clinical and personality characteristics). To this end, we investigated 130 low mood controls, 53 currently depressed individuals with an existing MDD diagnosis (established current MDD), 40 currently depressed individuals with a new MDD diagnosis (new current MDD), and 72 currently not depressed individuals with an existing MDD diagnosis (established non-current MDD). A repeated nested cross-validation approach was used to evaluate variation in model selection and ensure model reproducibility. Prediction models that were trained to differentiate between established current MDD patients and low mood controls (AUC = 0.94 ± 0.01) demonstrated a good predictive performance when extrapolated to differentiate between new current MDD patients and low mood controls (AUC = 0.80 ± 0.01), as well as between established non-current MDD patients and low mood controls (AUC = 0.79 ± 0.01). Importantly, we identified DBS proteins A1AG1, A2GL, AL1A1, APOE and CFAH as important predictors of MDD, indicative of immune system dysregulation; as well as poor self-rated mental health, BMI, reduced daily experiences of positive emotions, and tender-mindedness. Despite the need for further validation, our preliminary findings demonstrate the potential of such prediction models to be used as a diagnostic aid for detecting MDD in clinical practice.

Identification of plasma biomarkers for distinguishing bipolar depression from major depressive disorder by iTRAQ-coupled LC-MS/MS and bioinformatics analysis

It is important to differentiate between bipolar disorder (BD) and major depressive disorder (MDD) in the first depressive episode because of the potential treatment implications. Previous studies have mainly focused on the different clinical features or pathological biomarkers to distinguish these two diseases; however, a better understanding of the proteomics profiling of BD may help aid future therapeutic strategies. Here, we applied isobaric tags for relative and absolute quantification (iTRAQ) technology combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify differentially expressed proteins between MDD and bipolar depression (BP). In total, 30 MDD, 30 BP and 30 healthy subjects were included. Proteins from depleted plasma samples were digested into peptides, individually labeled with iTRAQ reagents, combined and subjected to LC-MS/MS and further bioinformatics analyses. Our results showed that 9 proteins were significantly altered between MDD and BP. Briefly, B2RAN2, B4E1B2, APOA1, ENG, SBSN and QSOX2 were up-regulated, whereas ORM1, MRC2 and SLPI were down-regulated. Most identified proteins were related to the immune system. The bioinformatics analysis showed that B2RAN2 (highly similar to vanin-1) was involved in the significantly enriched KEGG pathways "pantothenate and CoA biosynthesis" (P=0.009). B2RAN2 and ENG may play important roles in depression. They may serve as candidate biomarkers for distinguishing MDD and BP. Further validation and investigation are required to illuminate the roles of B2RAN2 and ENG in MDD and BP. The current study provided a potential and novel biomarker panel that may, in turn, aid the diagnosis of BD.

Transgenerational Social Stress, Immune Factors, Hormones, and Social Behavior

A social signal transduction theory of depression has been proposed that states that exposure to social adversity alters the immune response and these changes mediate symptoms of depression such as anhedonia and impairments in social behavior The exposure of maternal rats to the chronic social stress (CSS) of a male intruder depresses maternal care and impairs social behavior in the F1 and F2 offspring of these dams. The objective of the present study was to characterize basal peripheral levels of several immune factors and related hormone levels in the adult F2 offspring of CSS exposed dams and assess whether changes in these factors are associated with previously reported deficits in allogrooming behavior. CSS decreased acid glycoprotein (α1AGP) and intercellular adhesion molecule-1 (ICAM-1) in F2 females, and increased granulocyte macrophage-colony stimulating factor (GM-CSF) in F2 males. There were also sex dependent changes in IL-18, tissue inhibitors of metalloproteinases 1 (TIMP-1), and vascular endothelial growth factor (VEGF). Progesterone was decreased and alpha melanocyte stimulating hormone (α-MSH) was increased in F2 males, and brain-derived neurotrophic factor (BDNF) was decreased in F2 females. Changes in α1AGP, GM-CSF, progesterone, and α-MSH were correlated with decreased allogrooming in the F2 offspring of stressed dams. These results support the hypothesis that transgenerational social stress affects both the immune system and social behavior, and also support previous studies on the adverse effects of early life stress on immune functioning and stress associated immunological disorders, including the increasing prevalence of asthma. The immune system may represent an important transgenerational etiological factor in disorders which involve social and/or early life stress associated changes in social behavior, such as depression, anxiety, and autism, as well as comorbid immune disorders. Future studies involving immune and/or endocrine assessments and manipulations will address specific questions of function and causation, and may identify novel preventative measures and treatments for the growing number of immune mediated disorders.

Applications of blood-based protein biomarker strategies in the study of psychiatric disorders

Major psychiatric disorders such as schizophrenia, major depressive and bipolar disorders are severe, chronic and debilitating, and are associated with high disease burden and healthcare costs. Currently, diagnoses of these disorders rely on interview-based assessments of subjective self-reported symptoms. Early diagnosis is difficult, misdiagnosis is a frequent occurrence and there are no objective tests that aid in the prediction of individual responses to treatment. Consequently, validated biomarkers are urgently needed to help address these unmet clinical needs. Historically, psychiatric disorders are viewed as brain disorders and consequently only a few researchers have as yet evaluated systemic changes in psychiatric patients. However, promising research has begun to challenge this concept and there is an increasing awareness that disease-related changes can be traced in the peripheral system which may even be involved in the precipitation of disease onset and course. Converging evidence from molecular profiling analysis of blood serum/plasma have revealed robust molecular changes in psychiatric patients, suggesting that these disorders may be detectable in other systems of the body such as the circulating blood. In this review, we discuss the current clinical needs in psychiatry, highlight the importance of biomarkers in the field, and review a representative selection of biomarker studies to highlight opportunities for the implementation of personalized medicine approaches in the field of psychiatry. It is anticipated that the implementation of validated biomarker tests will not only improve the diagnosis and more effective treatment of psychiatric patients, but also improve prognosis and disease outcome.

Serum zinc level in depressed patients during zinc supplementation of imipramine treatment

BACKGROUND

Recurrent major depression is associated with decreased blood zinc concentrations that may be increased by effective antidepressant therapy. Some clinical investigations point to alterations of the zinc level in blood as a potential marker of depression.

METHODS

A placebo-controlled, double blind study of zinc supplementation to imipramine therapy was conducted on sixty patients fulfilling the DSM-IV criteria for major depression (18-55 years old, 40 females, 20 males). Moreover, a group of 25 healthy volunteers was recruited (16 females, 9 males). Blood samples were drawn for the assay of serum zinc once from the control subjects and four times (before, and then 2, 6 and 12 weeks after the beginning of treatment) from the depressed subjects.

RESULTS

We report that: 1) the serum zinc level was significantly lower (by 22%) in depressed patients than in healthy volunteers, 2) all groups demonstrated a gradual increase in zinc concentrations over the period of imipramine treatment with or without zinc supplementation, 3) treatment-resistant patients demonstrated lower concentrations of zinc (by 14%) than treatment-non-resistant patients, 4) zinc concentrations were higher in zinc-supplemented patients than in placebo-supplemented patients, 5) zinc supplementation increased zinc concentrations over the period of treatment, and 6) at a 12-week imipramine treatment, a significant negative correlation was demonstrated between the Montgomery-Asberg Depression Rating Scale and the serum zinc level together with a concomitant increase in serum zinc in patients in remission.

CONCLUSIONS

Serum zinc is a state marker of depression.

Orosomucoid influences the response to antidepressants in major depressive disorder

Orosomucoid, an acute phase protein, carries basic drugs including antidepressants in plasma. Elevated levels have been reported in patients with depression. It has yet to be established whether orosomucoid concentration influences antidepressant response. The orosomucoid gene (ORM1) is polymorphic and the protein isoforms have differing pharmacokinetic properties which could alter plasma profile and blood brain barrier transport of antidepressants. Outpatients (n = 157) in a randomised control trial of fluoxetine versus nortriptyline were genotyped for the ORM1 variants. Plasma concentrations of acute phase proteins were also measured. Outcomes were the completion of an adequate six week trial of antidepressant and response. Response was defined as an improvement >/=60% on the Montgomery-Asperg Depression Rating Scale (MADRS) over six weeks. The first notable finding was that individuals with an ORM1*S/*S genotype were less likely to complete an adequate six week trial of an antidepressant (OR = 4.707, 95% CI 1.769-12.527, P = 0.002). The second was that higher orosomucoid concentrations were found in antidepressant non-responders (91.4%) than responders (79.1%) (F1, 106 = 5.669, P = 0.019). These findings highlight the potential importance of variables such as orosomucoid which impact on drug availability on the therapeutic efficacy of antidepressant drugs.

alpha1-acid glycoprotein in late-life depression: relationship to medical burden and genetics

Serum alphal-acid glycoprotein (AAG) concentrations were examined in relationship to age, medical burden, depression, and mental status in elderly control (n = 19, mean age = 72.1 +/- 6.8 years) and depressed (n = 58, mean age = 71.9 +/- 7.1 years) subjects. DNA was analyzed for allelic variants of the AGP1 (ORM1) gene in both groups. Depressed subjects' AAG serum levels were measured at baseline and after 6 weeks of antidepressant treatment. Before treatment, depressed subjects had significantly higher serum AAG concentrations than nondepressed controls (t49.2 = -3.48, P = .0011). Pretreatment AAG levels also correlated with degree of medical burden, measured by the Cumulative Illness Rating Scale-Geriatrics (r = 0.28, P = .0303), but not with age, depression severity, or cognitive scores. There was no significant difference between responders and nonresponders on changes in AAG levels from baseline to week 6. Frequency differences in ORM1 allelic variants apparently did not influence increased AAG concentrations in depressed patients.

Cytokines, stress and depressive illness: brain-immune interactions

Cytokines, signaling molecules of the immune system, have been implicated as a contributing factor for mood disorders such as depression. Several lines of evidence supporting this contention are briefly reviewed and caveats are introduced. Essentially, a relationship between cytokines and depression is based on the findings that: 1) proinflammatory cytokines (interleukin-1, interleukin-6, tumor necrosis factor-alpha) and bacterial endotoxins elicit sickness behaviors (e.g., fatigue, soporific effects) and symptoms of anxiety/depression that may be attenuated by chronic antidepressant treatment, 2) cytokines induce neuroendocrine and central neurotransmitter changes reminiscent of those implicated in depression, and these effects are exacerbated by stressors, 3) severe depressive illness is accompanied by signs of immune activation and by elevations of cytokine production or levels, and 4) immunotherapy, using interleukin-2 or interferon-alpha, promotes depressive symptoms that are attenuated by antidepressant treatment. It is argued that cytokine synthesis and release, elicited upon activation of the inflammatory response system, provoke neuroendocrine and brain neurotransmitter changes that are interpreted by the brain as being stressors, and contribute to the development of depression. Furthermore, such effects are subject to a sensitization effect so that a history of stressful experiences or cytokine activation augment the response to later challenges and hence the evolution of depression

Cytokines and depression: an analogic approach

A growing body of evidence suggests that major depressive disorders may be accompanied by immune dysfunction and more particularly by an enhanced production of pro-inflammatory cytokines. The possible involvement of cytokines in depressive illness are based upon an analogic model. Pro-inflammatory cytokines are known to induce behavioral effects, and neuro-endocrine and immune activation similar to those observed in depression; these can be alleviated by antidepressant treatment. In this paper, we review research literature on the links between depressive illness and cytokine production and address further questions on this cytokine pathway. Further research is needed to see whether cytokines sustain specific depressive syndromes or whether cytokines induce depressive-like symptoms.

Human alpha-1-glycoprotein and its interactions with drugs

For about half a century, the binding of drugs to plasma albumin, the "silent receptor," has been recognized as one of the major determinants of drug action, distribution, and disposition. In the last decade, the binding of drugs, especially but not exclusively basic entities, to another plasma protein, alpha 1-acid glycoprotein (AAG), has increasingly become important in this regard. The present review points out that hundreds of drugs with diverse structures bind to this glycoprotein. Although plasma concentration of AAG is much lower than that of albumin, AAG can become the major drug binding macromolecule in plasma with significant clinical implications. Also, briefly reviewed are the physiological, pathological, and genetic factors that influence binding, the role of AAG in drug-drug interactions, especially the displacement of drugs and endogenous substances from AAG binding sites, and pharmacokinetic and clinical consequences of such interactions. It can be predicted that in the future, rapid automatic methods to measure binding to albumin and/or AAG will routinely be used in drug development and in clinical practice to predict and/or guide therapy.