Genomic predictors of remission to antidepressant treatment in geriatric depression using genome-wide expression analyses: a pilot study

Upregulation of S100A8 in peripheral blood mononuclear cells from patients with depression treated with SSRIs: a pilot study

BACKGROUND

Major depressive disorder (MDD) affects more than 350 million people worldwide, and there is currently no laboratory test to diagnose it. This pilot study aimed to identify potential biomarkers in peripheral blood mononuclear cells (PBMCs) from MDD patients.

METHODS

We used tandem mass tagging coupled to synchronous precursor selection (mass spectrometry) to obtain the differential proteomic profile from a pool of PBMCs from MDD patients and healthy subjects, and quantitative PCR to assess gene expression of differentially expressed proteins (DEPs) of our interest.

RESULTS

We identified 247 proteins, of which 133 had a fold change ≥ 2.0 compared to healthy volunteers. Using pathway enrichment analysis, we found that some processes, such as platelet degranulation, coagulation, and the inflammatory response, are perturbed in MDD patients. The gene-disease association analysis showed that molecular alterations in PBMCs from MDD patients are associated with cerebral ischemia, vascular disease, thrombosis, acute coronary syndrome, and myocardial ischemia, in addition to other conditions such as inflammation and diabetic retinopathy.

CONCLUSIONS

We confirmed by qRT-PCR that S100A8 is upregulated in PBMCs from MDD patients and thus could be an emerging biomarker of this disorder. This report lays the groundwork for future studies in a broader and more diverse population and contributes to a deeper characterization of MDD.

Exploratory genome-wide analyses of cortical inhibition, facilitation, and plasticity in late-life depression

Late-life depression (LLD) is a heterogenous mood disorder influenced by genetic factors. Cortical physiological processes such as cortical inhibition, facilitation, and plasticity may be markers of illness that are more strongly associated with genetic factors than the clinical phenotype. Thus, exploring the relationship between genetic factors and these physiological processes may help to characterize the biological mechanisms underlying LLD and improve diagnosis and treatment selection. Transcranial magnetic stimulation (TMS) combined with electromyography was used to measure short interval intracortical inhibition (SICI), cortical silent period (CSP), intracortical facilitation (ICF), and paired associative stimulation (PAS) in 79 participants with LLD. We used exploratory genome-wide association and gene-based analyses to assess for genetic correlations of these TMS measures. MARK4 (which encodes microtubule affinity-regulating kinase 4) and PPP1R37 (which encodes protein phosphatase 1 regulatory subunit 37) showed genome-wide significant association with SICI. EGFLAM (which encodes EGF-like fibronectin type III and laminin G domain) showed genome-wide significant association with CSP. No genes met genome-wide significant association with ICF or PAS. We observed genetic influences on cortical inhibition in older adults with LLD. Replication with larger sample sizes, exploration of clinical phenotype subgroups, and functional analysis of relevant genotypes is warranted to better characterize genetic influences on cortical physiology in LLD. This work is needed to determine whether cortical inhibition may serve as a biomarker to improve diagnostic precision and guide treatment selection in LLD.

Co-Expression Network Analysis Identifies Molecular Determinants of Loneliness Associated with Neuropsychiatric and Neurodegenerative Diseases

Loneliness and social isolation are detrimental to mental health and may lead to cognitive impairment and neurodegeneration. Although several molecular signatures of loneliness have been identified, the molecular mechanisms by which loneliness impacts the brain remain elusive. Here, we performed a bioinformatics approach to untangle the molecular underpinnings associated with loneliness. Co-expression network analysis identified molecular 'switches' responsible for dramatic transcriptional changes in the nucleus accumbens of individuals with known loneliness. Loneliness-related switch genes were enriched in cell cycle, cancer, TGF-β, FOXO, and PI3K-AKT signaling pathways. Analysis stratified by sex identified switch genes in males with chronic loneliness. Male-specific switch genes were enriched in infection, innate immunity, and cancer-related pathways. Correlation analysis revealed that loneliness-related switch genes significantly overlapped with 82% and 68% of human studies on Alzheimer's (AD) and Parkinson's diseases (PD), respectively, in gene expression databases. Loneliness-related switch genes, BCAM, NECTIN2, NPAS3, RBM38, PELI1, DPP10, and ASGR2, have been identified as genetic risk factors for AD. Likewise, switch genes HLA-DRB5, ALDOA, and GPNMB are known genetic loci in PD. Similarly, loneliness-related switch genes overlapped in 70% and 64% of human studies on major depressive disorder and schizophrenia, respectively. Nine switch genes, HLA-DRB5, ARHGAP15, COL4A1, RBM38, DMD, LGALS3BP, WSCD2, CYTH4, and CNTRL, overlapped with known genetic variants in depression. Seven switch genes, NPAS3, ARHGAP15, LGALS3BP, DPP10, SMYD3, CPXCR1, and HLA-DRB5 were associated with known risk factors for schizophrenia. Collectively, we identified molecular determinants of loneliness and dysregulated pathways in the brain of non-demented adults. The association of switch genes with known risk factors for neuropsychiatric and neurodegenerative diseases provides a molecular explanation for the observed prevalence of these diseases among lonely individuals.

Transcriptional biomarkers of response to pharmacological treatments in severe mental disorders: A systematic review

Variation in the expression level and activity of genes involved in drug disposition and action in tissues of pharmacological importance have been increasingly investigated in patients treated with psychotropic drugs. Findings are promising, but reliable predictive biomarkers of response have yet to be identified. Here we conducted a PRISMA-compliant systematic search of PubMed, Scopus and PsycInfo up to 12 September 2020 for studies investigating RNA expression levels in cells or biofluids from patients with major depressive disorder, schizophrenia or bipolar disorder characterized for response to psychotropic drugs (antidepressants, antipsychotics or mood stabilizers) or adverse effects. Among 5497 retrieved studies, 123 (63 on antidepressants, 33 on antipsychotics and 27 on mood stabilizers) met inclusion criteria. Studies were either focused on mRNAs (n = 96), microRNAs (n = 19) or long non-coding RNAs (n = 1), with only a minority investigating both mRNAs and microRNAs levels (n = 7). The most replicated results include genes playing a role in inflammation (antidepressants), neurotransmission (antidepressants and antipsychotics) or mitochondrial function (mood stabilizers). Compared to those investigating response to antidepressants, studies focused on antipsychotics or mood stabilizers more often showed lower sample size and lacked replication. Strengths and limitations of available studies are presented and discussed in light of the specific designs, methodology and clinical characterization of included patients for transcriptomic compared to DNA-based studies. Finally, future directions of transcriptomics of psychopharmacological interventions in psychiatric disorders are discussed.

Changes in RNA expression levels during antidepressant treatment: a systematic review

More than a third of patients treated with antidepressants experience treatment resistance. Furthermore, molecular pathways involved in antidepressant effect have yet to be fully understood. Therefore, we performed a systematic review of clinical studies that examined changes in RNA expression levels produced by antidepressant treatment. Literature search was performed through April 2021 for peer-reviewed studies measuring changes in mRNA or non-coding RNA levels before and after antidepressant treatment in human participants following PRISMA guidelines. Thirty-one studies were included in qualitative synthesis. We identified a large amount of heterogeneity between the studies for genes/RNAs measured, antidepressants used, and treatment duration. Of the six RNAs examined by more than one study, expression of the brain-derived neurotrophic factor (BDNF) gene and genes in the inflammation pathway, particularly IL-1β, were consistently reported to be altered by antidepressant treatment. Limitations of this review include heterogeneity of the studies, possibility of positive publication bias, and risk of false-negative findings secondary to small sample sizes. In conclusion, our systematic review provides an updated synthesis of RNA expression changes produced by antidepressant treatment in human participants, where genes in the BDNF and inflammatory pathways were identified as potential targets of antidepressant effect. Importantly, these findings also highlight the need for replication of the included studies in multiple strong, placebo-controlled studies for the identification of evidence-based markers that can be targeted to improve treatment outcomes.

Dendritic Cells: Neglected Modulators of Peripheral Immune Responses and Neuroinflammation in Mood Disorders?

Affective disorders (AD) including major depressive disorder (MDD) and bipolar disorder (BD) are common mood disorders associated with increased disability and poor health outcomes. Altered immune responses characterized by increased serum levels of pro-inflammatory cytokines and neuroinflammation are common findings in patients with AD and in corresponding animal models. Dendritic cells (DCs) represent a heterogeneous population of myeloid cells that orchestrate innate and adaptive immune responses and self-tolerance. Upon sensing exogenous and endogenous danger signals, mature DCs secrete proinflammatory factors, acquire migratory and antigen presenting capacities and thus contribute to neuroinflammation in trauma, autoimmunity, and neurodegenerative diseases. However, little is known about the involvement of DCs in the pathogenesis of AD. In this review, we summarize the current knowledge on DCs in peripheral immune responses and neuroinflammation in MDD and BD. In addition, we consider the impact of DCs on neuroinflammation and behavior in animal models of AD. Finally, we will discuss therapeutic perspectives targeting DCs and their effector molecules in mood disorders.

Pharmacogenetic Implications for Antidepressant Pharmacotherapy in Late-Life Depression: A Systematic Review of the Literature for Response, Pharmacokinetics and Adverse Drug Reactions

Affecting up to 15% of older adults, late-life depression (LLD) is characterized by the occurrence of depressive symptoms after the age of 50-65 years and maybe pathophysiologically distinct from depression in younger adults. Therefore, LLD is challenging to treat, and predictive genetic testing might be essential to improve treatment in this vulnerable population. The current review aims to provide a summary of the literature exploring genetic associations with antidepressant treatment outcomes in late-life. We conducted a systematic search of three integrated electronic databases. We identified 29 articles investigating genetic associations with antidepressant treatment outcomes, pharmacokinetic parameters, and adverse drug reactions in older adults. Given the small number of investigations conducted in older adults, it is difficult to conclude the presence or absence of genetic associations with the outcomes of interest. In sum, the most substantial amount of evidence exists for the CYP2D6 metabolizer status, SLC6A4 5-HTTLPR, and BDNF rs6265. These findings are consistent in the literature when not restricting to older adults, suggesting that similar treatment recommendations may be provided for older adults regarding genetic variation, such as those outlined for CYP2D6 by the Clinical Pharmacogenetics Implementation Consortium. Nonetheless, further studies are required in well-characterized samples, including genome-wide data, to validate if similar treatment adjustments are appropriate in older adults, given that there appear to be significant effects of genetic variation on antidepressant treatment factors.

Alpha-Synuclein RNA Expression is Increased in Major Depression

Alpha-synuclein (SNCA) is a small membrane protein that plays an important role in neuro-psychiatric diseases. It is best known for its abnormal subcellular aggregation in Lewy bodies that serves as a hallmark of Parkinson’s disease (PD). Due to the high comorbidity of PD with depression, we investigated the role of SNCA in patients suffering from major depressive disorder (MDD). SNCA mRNA expression levels were analyzed in peripheral blood cells of MDD patients and a healthy control group. SNCA mRNA expression was positively correlated with severity of depression as indicated by psychometric assessment. We found a significant increase in SNCA mRNA expression levels in severely depressed patients compared with controls. Thus, SNCA analysis could be a helpful target in the search for biomarkers of MDD.

The prognostic role of depression as a predictor of chronic somatic diseases manifestation

The negative impact of depression on the course and outcome of somatic disorders is well-known and has a solid theoretical basis. The analyses of prospective studies confirm the role of depression as an independent and significant risk factor for widespread chronic somatic disorders including such severe and life-threatening conditions as cardiovascular diseases, diabetes and oncological pathology. The majority of somatic disorders and depression are the part of the big class of hereditary diseases with multifactorial character and polygenic nature. It is likely, that the genetic risk diversity of these diseases in population is close. There is also a high probability of genetic risks levels overlap (or of common «cluster») of two or more diseases in one individual, with one disorder being major depression. In that case such diseases could be considered «genetically comorbid» and manifestation of one disease could alter the risks of other. Precise and informative diagnostic tools could detect subsyndromal depression that could be the prognostic sign of the high risk and rapid manifestation of somatic diseases. Thus, patients with depressive disorder could be considered as a group with high risks of diverse range of somatic pathology. The coalescence of fundamental biomedical scientists and internists (psychiatrists and other physicians) could lead to the elaboration of specific complex preventative measures including social ones.

Pharmacogenetic guidelines and decision support tools for depression treatment: application to late-life

Late-life depression (LLD) is a major depressive disorder that affects someone after the age of 60 years. LLD is frequently associated with inadequate response and remission from antidepressants, in addition to polypharmacy. Pharmacogenetics offers a promising approach to improve clinical outcomes in LLD via new discoveries determining the genetic basis of response rates and side effects, as well as the development of tailored pharmacogenetic-based decision support tools. This invited review evaluates the LLD pharmacogenetic evidence base and the extent to which this was incorporated into existing commercial decision support tools and clinical pharmacogenetic guidelines.

Predictors of Response and Remission to Antidepressants in Geriatric Depression: A Systematic Review

BACKGROUND

Geriatric depression is a heterogeneous disorder that increases morbidity and mortality in a population that is already vulnerable. Predicting response and remission to antidepressants could help clinicians to optimize the management of antidepressants and reduce the consequences of depression.

METHOD

The aim of this article is to present results of a systematic review of the literature on predictive factors related to antidepressant response and remission in older adults with depression.

MAIN FINDINGS

We identified sociodemographic, clinical, neuropsychological, neuroimaging, and genetic factors that could be potential predictors of outcomes. Inconsistent findings and methodological differences among studies, however, limit the generalizability and application of these predictors in clinical practice. The results of our review confirm that geriatric depression includes many subgroups of patients with particular endophenotypes that may influence the course of depression.

CONCLUSION

Further studies are needed to characterize depression subgroups in order to better understand the pathophysiology of late life depression and to find specific predictors for each group of patients.

Role of Ginkgo biloba extract as an adjunctive treatment of elderly patients with depression and on the expression of serum S100B

OBJECTIVE

To explore the effect of ginkgo biloba extract (EGb) as an adjunctive treatment of elderly patients with depression and the effect on the expression of serum S100B.

METHODS

136 elderly patients with depression were divided into EGb +  citalopram (Cit) group and Cit group equally. Efficacy was evaluated by Hamilton Depression Rating Scale (HAMD). Wisconsin Card Classification Test (WCST) was used to evaluate cognitive function. Serum S100B expression was measured with ELISA. The relationship of S100B with HAMD, Hamilton Anxiety Scale (HAMA) score, and WCST results was evaluated subsequently.

RESULTS

The time of onset of efficacy was significantly shorter in EGb + Cit group. There were significant differences in HAMD and HAMA scores after treatment than before treatment between groups (all P < .05). After treatment, total number of WCST test, the number of continuous errors and non-persistent errors in both groups were less than those before treatment. The correct number and classifications number were increased than before treatment. In EGb + Cit group, correct numbers and classifications were increased, and the number of persistent errors was decreased. After treatment, S100B level was decreased, and S100B levels change in EGb + Cit group was greater than in Cit group. Serum S100B level was positively correlated with HAMD and HAMA scores before treatment and positively correlated with persistent errors number in WCST.

CONCLUSION

EGb, as an adjunctive treatment, can effectively improve depressive symptoms and reduce expression of serum S100B, which is a marker of brain injury, suggesting that EGb restores neurologic function during the treatment of depression in elderly patients and S100B participates in the therapeutic mechanism. EGb combined with depressive drugs plays synergistic role, and the time of onset of efficacy is faster than single antidepressants.

Pharmacogenetic Decision Support Tools: A New Paradigm for Late-Life Depression?

Clinicians still employ a "trial-and-error" approach to optimizing treatment regimens for late-life depression (LLD). With LLD affecting a significant and growing segment of the population, and with only about half of older adults responsive to antidepressant therapy, there is an urgent need for a better treatment paradigm. Pharmacogenetic decision support tools (DSTs), which are emerging technologies that aim to provide clinically actionable information based on a patient's genetic profile, offer a promising solution. Dozens of DSTs have entered the market in the past 15 years, but with varying level of empirical evidence to support their value. In this clinical review, we provide a critical analysis of the peer-reviewed literature on DSTs for major depression management. We then discuss clinical considerations for the use of these tools in treating LLD, including issues related to test interpretation, timing, and patient perspectives. In adult populations, newer generation DSTs show promise for the treatment of major depression. However, there are no primary clinical trials in LLD cohorts. Independent and comparative clinical trials are needed.

Predictors of treatment outcome in depression in later life: A systematic review and meta-analysis

BACKGROUND

Predictor analyses of late-life depression can be used to identify variables associated with outcomes of treatments, and hence ways of tailoring specific treatments to patients. The aim of this review was to systematically identify, review and meta-analyse predictors of outcomes of any type of treatment for late-life depression.

METHODS

Pubmed, Embase, CINAHL, Web of Science and PsycINFO were searched for studies published up to December 2016. Primary and secondary studies reported treatment predictors from randomised controlled trials of any treatment for patients with major depressive disorder aged over 60 were included. Treatment outcomes included response, remission and change in depression score.

RESULTS

Sixty-seven studies met the inclusion criteria. Of 65 identified statistically significant predictors, only 7 were reported in at least 3 studies. Of these, 5 were included in meta-analyses, and only 3 were statistically significant. Most studies were rated as being of moderate to strong quality and satisfied key quality criteria for predictor analyses.

LIMITATIONS

The searches were limited to randomised controlled trials and most of the included studies were secondary analyses.

CONCLUSIONS

Baseline depression severity, co-morbid anxiety, executive dysfunction, current episode duration, early improvement, physical illnesses and age were reported as statistically significant predictors of treatment outcomes. Only the first three were significant in meta-analyses. Subgroup analyses showed differences in predictor effect between biological and psychosocial treatment. However, high heterogeneity and small study numbers suggest a cautious interpretation of results. These predictors were associated with various mechanisms including brain pathophysiology, perceived social support and proposed distinct types of depressive disorder. Further investigation of the clinical utility of these predictors is suggested.