Early warning biomarkers in major depressive disorder: a strategic approach to a testing question

Major depressive disorder is associated with mitochondrial ND6 T14502C mutation in two Han Chinese families

BACKGROUND

Globally, the World Health Organization ranks major depressive disorder (MDD) as the leading cause of disability. However, MDD molecular etiology is still poorly understood.

AIM

To explore the possible association between mitochondrial ND6 T14502C mutation and MDD.

METHODS

Clinical data were collected from two pedigrees, and detailed mitochondrial genomes were obtained for the two proband members. The assessment of the resulting variants included an evaluation of their evolutionary conservation, allelic frequencies, as well as their structural and functional consequences. Detailed mitochondrial whole genome analysis, phylogenetic, and haplotype analysis were performed on the probands.

RESULTS

Herein, we reported the clinical, genetic, and molecular profiling of two Chinese families afflicted with MDD. These Chinese families exhibited not only a range of onset and severity ages in their depression but also extremely low penetrances to MDD. Sequence analyses of mitochondrial genomes from these pedigrees have resulted in the identification of a homoplasmic T14502C (I58V) mutation. The polymorphism is located at a highly conserved isoleucine at position 58 of ND6 and distinct mitochondrial DNA (mtDNA) polymorphisms originating from haplogroups M10 and H2.

CONCLUSION

Identifying the T14502C mutation in two individuals with no genetic relation who exhibit symptoms of depression provides compelling evidence that this mutation may be implicated in MDD development. Nonetheless, the two Chinese pedigrees that carried the T14502C mutation did not exhibit any functionally significant mutations in their mtDNA. Therefore, the phenotypic expression of the T14502C mutation related to MDD may be influenced by the nuclear modifier gene(s) or environmental factors.

The pathophysiology of major depressive disorder through the lens of systems biology: Network analysis of the psycho-immune-neuroendocrine physiome

BACKGROUND/AIMS

The psycho-immune-neuroendocrine (PINE) network is a predominantly physiological (metabolomic) model constructed from the literature, inter-linking multiple biological processes associated with major depressive disorder (MDD), thereby integrating putative mechanistic pathways for MDD into a single network.

MATERIAL AND METHODS

Previously published metabolomic pathways for the PINE network based on literature searches conducted in 1991-2021 were used to construct an edge table summarizing all physiological pathways in pairs of origin nodes and target nodes. The Gephi software program was used to calculate network metrics from the edge table, including total degree and centrality measures, to ascertain key network nodes and construct a directed network graph.

RESULTS

An edge table and directional network graph of physiological relationships in the PINE network is presented. The network has properties consistent with complex biological systems, with analysis yielding key network nodes comprising pro-inflammatory cytokines (TNF- α, IL6 and IL1), glucocorticoids and corticotropin releasing hormone (CRH). These may represent central structural and regulatory elements in the context of MDD.

CONCLUSION

The identified hubs have a high degree of connection and are known to play roles in the progression from health to MDD. These nodes represent strategic targets for therapeutic intervention or prevention. Future work is required to build a weighted and dynamic simulation of the network PINE.

Identification and Characterization of Elevated Expression of Transferrin and Its Receptor TfR1 in Mouse Models of Depression

Depression has become one of the severe mental disorders threatening global human health. In this study, we first used the proteomics approach to obtain the differentially expressed proteins in the liver between naive control and chronic social defeat stress (CSDS) induced depressed mice. We have identified the upregulation of iron binding protein transferrin (TF) in the liver, the peripheral blood, and the brain in CSDS-exposed mice. Furthermore, bioinformatics analysis of the Gene Expression Omnibus (GEO) database from various mouse models of depression revealed the significantly upregulated transcripts of TF and its receptor TfR1 in multiple brain regions in depressed mice. We also used the recombinant TF administration via the tail vein to detect its permeability through the blood-brain barrier (BBB). We demonstrated the permeability of peripheral TF into the brain through the BBB. Together, these results identified the elevated expression of TF and its receptor TfR1 in both peripheral liver and the central brain in CSDS-induced depressed mice, and peripheral administration of TF can be transported into the brain through the BBB. Therefore, our data provide a compelling information for understanding the potential role and mechanisms of the cross-talk between the liver and the brain in stress-induced depression.

Combined serum IL-6, C-reactive protein, and cortisol may distinguish patients with anhedonia in major depressive disorder

Neuroinflammation and anhedonia in major depressive disorder (MDD) are closely connected, though the exact mechanism is unclear. This study aimed to investigate the relationships between cytokines, C-reactive protein (CRP), cortisol, and anhedonia, revealing the potential predictive value in identifying anhedonic MDD. In total, 66 patients with MDD (29 with anhedonia and 37 without anhedonia) and 66 healthy controls (HCs) were included. The severity of depression and anhedonia was evaluated using the Hamilton Rating Scale for Depression-24 (HAMD-24) and Snaith-Hamilton Pleasure Scale (SHAPS), respectively. Serum cytokines were measured using flow cytofluorometric kits, while CRP and cortisol were measured using enzyme-linked immunosorbent assay kits. We found higher serum levels of interleukin-2 (IL-2), IL-6, and cortisol in MDD than in HC where anhedonic MDD was highest. CRP and IL-6 were positively associated with anhedonia, and cortisol levels were related to both anhedonia and depression. A combination of IL-6, CRP, and cortisol had optimal predictive value for distinguishing anhedonic MDD. Anhedonic MDD has unique neuroendocrine-immune characteristics compared with those without anhedonia. The combination of IL-6, CRP, and cortisol might be an early marker to distinguish anhedonic MDD.

Central and cardiac stress resiliences consistently linked to integrated immuno-neuroendocrine responses across stress models in male mice

Stress resilience, and behavioural and cardiovascular impacts of chronic stress, are theorised to involve integrated neuro-endocrine/inflammatory/transmitter/trophin signalling. We tested for this integration, and whether behaviour/emotionality, together with myocardial ischaemic tolerance, are consistently linked to these pathways across diverse conditions in male C57Bl/6 mice. This included: Restraint Stress (RS), 1 hr restraint/day for 14 days; Chronic Unpredictable Mild Stress (CUMS), 7 stressors randomised over 21 days; Social Stress (SS), 35 days social isolation with brief social encounters in final 13 days; and Control conditions (CTRL; un-stressed mice). Behaviour was assessed via open field (OFT) and sucrose preference (SPT) tests, and neurobiology from frontal cortex (FC) and hippocampal transcripts. Endocrine factors, and function and ischaemic tolerance in isolated hearts, were also measured. Model characteristics ranged from no behavioural or myocardial changes with homotypic RS, to increased emotionality and cardiac ischaemic injury (with apparently distinct endocrine/neurobiological profiles) in CUMS and SS models. Highly integrated expression of HPA axis, neuro-inflammatory, BDNF, monoamine, GABA, cannabinoid and opioid signalling genes was confirmed across conditions, and consistent/potentially causal correlations identified for: i) Locomotor activity (noradrenaline, ghrelin; FC Crhr1, Tnfrsf1b, Il33, Nfkb1, Maoa, Gabra1; hippocampal Il33); ii) Thigmotaxis (adrenaline, leptin); iii) Anxiety-like behaviour (adrenaline, leptin; FC Tnfrsf1a; hippocampal Il33); iv) Depressive-like behaviour (ghrelin; FC/hippocampal s100a8); and v) Cardiac stress-resistance (noradrenaline, leptin; FC Il33, Tnfrsf1b, Htr1a, Gabra1, Gabrg2; hippocampal Il33, Tnfrsf1a, Maoa, Drd2). Data support highly integrated pathway responses to stress, and consistent adipokine, sympatho-adrenergic, inflammatory and monoamine involvement in mood and myocardial disturbances across diverse conditions.

Depression: Biological markers and treatment

Nowadays depression is considered as a systemic illness with different biological mechanisms involved in its etiology, including inflammatory response, hypothalamic-pituitary-adrenal (HPA) axis dysregulation and neurotransmitter and neurotrophic systems imbalance. Novel "omics" approaches, such as metabolomics and glycomics provide information about altered metabolic pathways and metabolites, as well as disturbances in glycosylation processes affected by or causing the development of depression. The clinical diagnosis of depression continues to be established based on the presence of the specific symptoms, but due to its heterogeneous underlying biological background, that differs according to the disease stage, there is an unmet need for treatment response biomarkers which would facilitate the process of appropriate treatment selection. This paper provides an overview of the role of major stress response system, the HPA axis, and its dysregulation in depression, possible involvement of neurotrophins, especially brain-derived neurotrophic factor, glial cell line-derived neurotrophic factor and insulin-like growth factor-1, in the development of depression. Article discusses how activated inflammation processes and increased cytokine levels, as well as disturbed neurotransmitter systems can contribute to different stages of depression and could specific metabolomic and glycomic species be considered as potential biomarkers of depression. The second part of the paper includes the most recent findings about available medical treatment of depression. The described biological factors impose an optimistic conclusion that they could represent easy obtainable biomarkers potentially predicting more personalized treatment and diagnostic options.

A Load to Find Clinically Useful Biomarkers for Depression

Depression is heterogeneous and complex disease with diverse symptoms. Its neurobiological underpinning is still not completely understood. For now, there are still no validated, easy obtainable, clinically useful noninvasive biomarker(s) or biomarker panel that will be able to confirm a diagnosis of depression, its subtypes and improve diagnostic procedures. Future multimodal preclinical and clinical research that involves (epi)genetic, molecular, cellular, imaging, and other studies is necessary to advance our understanding of the role of monoamines, GABA, HPA axis, neurotrophins, metabolome, and glycome in the pathogenesis of depression and their potential as diagnostic, prognostic, and treatment response biomarkers. These studies should be focused to include the first-episode depression and antidepressant drug-naïve patients with large sample sizes to reduce variability in different biological and clinical parameters. At present, metabolomics study revealed with high precision that a neurometabolite panel consisting of plasma metabolite biomarkers (GABA, dopamine, tyramine, kynurenine) might represent clinically useful biomarkers of MDD.

Structural anomalies in brain networks induce dynamical pacemaker effects

Dynamical effects on healthy brains and brains affected by tumor are investigated via numerical simulations. The brains are modeled as multilayer networks consisting of neuronal oscillators whose connectivities are extracted from Magnetic Resonance Imaging (MRI) data. The numerical results demonstrate that the healthy brain presents chimera-like states where regions with high white matter concentrations in the direction connecting the two hemispheres act as the coherent domain, while the rest of the brain presents incoherent oscillations. To the contrary, in brains with destructed structures, traveling waves are produced initiated at the region where the tumor is located. These areas act as the pacemaker of the waves sweeping across the brain. The numerical simulations are performed using two neuronal models: (a) the FitzHugh-Nagumo model and (b) the leaky integrate-and-fire model. Both models give consistent results regarding the chimera-like oscillations in healthy brains and the pacemaker effect in the tumorous brains. These results are considered a starting point for further investigation in the detection of tumors with small sizes before becoming discernible on MRI recordings as well as in tumor development and evolution.

Definition and Identification of Patients with Treatment-Resistant Depression in Real-World Clinical Practice Settings Across Asia

PURPOSE

An Asia-Pacific expert consensus defined treatment-resistant depression (TRD) as failure of ≥2 antidepressants given at adequate doses for 6-8 weeks during a major depressive episode. A survey examined how TRD was being diagnosed in real-world practices across Asia. An expert panel then interpreted the results and provided practical recommendations.

METHODS

Between March and July 2018, 246 clinicians from Hong Kong, Japan, Mainland China, South Korea, and Taiwan were surveyed on how they identified TRD patients according to their own definitions.

RESULTS

Most physicians described antidepressant failure as "no response" (79%) or "inadequate response" (82%); fewer chose "failure to achieve remission" (45%). About 40% did not routinely use clinical tools to assess response. Around 52% defined adequate dose target as achieving the label's upper dose limit. About 58% would treat for 4-8 weeks before determining antidepressant failure. Most (76%) required the ≥2 qualifying antidepressant failures to be from different classes. Approximately 60% considered antidepressant failure(s) from previous depressive episode(s) when diagnosing TRD.

CONCLUSION

Considering the survey results, antidepressant failure can be defined as a failure to achieve remission, or more practically as <50% improvement in depressive symptoms or inability to return to work/study, and confirmed with a clinical tool. TRD diagnosis also requires ≥2 qualifying antidepressant failures within the same depressive episode; from the same or different classes; and achieving at least the minimum effective antidepressant dose for 6-8 weeks.

Health, pre-disease and critical transition to disease in the psycho-immune-neuroendocrine network: Are there distinct states in the progression from health to major depressive disorder?

The psycho-immune-neuroendocrine (PINE) network is a regulatory network of interrelated physiological pathways that have been implicated in major depressive disorder (MDD). A model of disease progression for MDD is presented where the stable, healthy state of the PINE network (PINE physiome) undergoes progressive pathophysiological changes to an unstable but reversible pre-disease state (PINE pre-diseasome) with chronic stress. The PINE network may then undergo critical transition to a stable, possibly irreversible disease state of MDD (PINE pathome). Critical transition to disease is heralded by early warning signs which are detectible by biomarkers specific to the PINE network and may be used as a screening test for MDD. Critical transition to MDD may be different for each individual, as it is reliant on diathesis, which comprises genetic predisposition, intrauterine and developmental factors. Finally, we propose the PINE pre-disease state may form a "universal pre-disease state" for several non-communicable diseases (NCDs), and critical transition of the PINE network may lead to one of several frequently associated disease states (influenced by diathesis), supporting the existence of a common Chronic Illness Risk Network (CIRN). This may provide insight into both the puzzle of multifinality and the growing clinical challenge of multimorbidity.