Comparing the Anti-Depressive Effect of Electroconvulsive Therapy (ECT) Versus Transcranial Magnetic Stimulation (TMS) in the Treatment of Patients with Depression.

BACKGROUND: Electroconvulsive therapy (ECT) is one of the most effective treatments for depressive disorders. However, ECT has a number of limitations, such as significant side effects in the neurocognitive domain and the requirement for general anesthesia. Transcranial magnetic stimulation (TMS) is an intervention that applies electric stimulation to the brain without causing convulsions, thus representing an attractive alternative to ECT. The aim of our study is to review systematic reports of the effectiveness of ECT and TMS in the treatment of depressive spectrum disorders. SUBJECTS AND METHODS: We performed search queries in PubMed and eLibrary databases, which retrieved 391 articles, of which 14 met our inclusion criteria for the analysis. The articles comprised three comparisons: TMS vs SHAM, ECT vs sham ECT (SECT), and ECT vs PHARM. The protocol parameters analyzed for TMS were coil type, targeted brain area, amplitude of resting motor threshold, duration of session, number of sessions in total and per week, number and pulses per session and inter-train pause. For ECT, we evaluated the type of ECT device, targeted brain area, type of stimuli, and for ECT vs PHARM we recorded types of anesthesia and antidepressant medication. RESULTS: Three of 6 studies showed a therapeutic effect of TMS compared to placebo; efficacy was greater for TMS frequency exceeding 10 Hz, and with stimulation of two areas of cerebral cortex rather than a single area. There was insufficient data to identify a relationship between the success of TMS and intertrain pause (IP). Three of four studies showed a therapeutic effect of ECT compared to placebo. Three studies of bilateral ECT showed a significant reduction in depression scores compared to the SECT groups. ECT protocols with brief pulses were generally of lesser efficacy. Four of 5 ECT vs PHARM studies showed superior efficacy of ECT compared to PHARM. Among several antidepressants, only the ketamine study showed greater efficacy compared to ECT. CONCLUSIONS: There of six TMS studies and 7 of 9 ECT studies showed efficacy in reducing depressive symptoms. A prospective study of crossover design might reveal the relative efficacies of ECT and TMS.

Neuronetwork Approach in the Early Diagnosis of Depression.

BACKGROUND: Depression is a common mental illness, with around 280 million people suffering from depression worldwide. At present, the main way to quantify the severity of depression is through psychometric scales, which entail subjectivity on the part of both patient and clinician. In the last few years, deep (machine) learning is emerging as a more objective approach for measuring depression severity. We now investigate how neural networks might serve for the early diagnosis of depression. SUBJECTS AND METHODS: We searched Medline (Pubmed) for articles published up to June 1, 2023. The search term included Depression AND Diagnostics AND Artificial Intelligence. We did not search for depression studies of machine learning other than neural networks, and selected only those papers attesting to diagnosis or screening for depression. RESULTS: Fifty-four papers met our criteria, among which 14 using facial expression recordings, 14 using EEG, 5 using fMRI, and 5 using audio speech recording analysis, whereas 6 used multimodality approach, two were the text analysis studies, and 8 used other methods. CONCLUSIONS: Research methodologies include both audio and video recordings of clinical interviews, task performance, including their subsequent conversion into text, and resting state studies (EEG, MRI, fMRI). Convolutional neural networks (CNN), including 3D-CNN and 2D-CNN, can obtain diagnostic data from the videos of the facial area. Deep learning in relation to EEG signals is the most commonly used CNN. fMRI approaches use graph convolutional networks and 3D-CNN with voxel connectivity, whereas the text analyses use CNNs, including LSTM (long/short-term memory). Audio recordings are analyzed by a hybrid CNN and support vector machine model. Neural networks are used to analyze biomaterials, gait, polysomnography, ECG, data from wrist wearable devices, and present illness history records. Multimodality studies analyze the fusion of audio features with visual and textual features using LSTM and CNN architectures, a temporal convolutional network, or a recurrent neural network. The accuracy of different hybrid and multimodality models is 78-99%, relative to the standard clinical diagnoses.

Genetic Contributors to PTSD: the Role of SNVs, Gene Interactions and Haplotypes for Developing PTSD Prevention Measures. A Comprehensive Review.

BACKGROUND: Post-traumatic stress disorder (PTSD) is a trauma- or stressor-related mental health condition with high socioeconomic burden. We aimed in this review to identify promising genetic markers predisposing for PTSD, which might serve in the design subsequent studies aiming to develop PTSD prevention and remediation measures. SUBJECTS AND METHODS: Our search queries in the PubMed database yielded 547 articles, of which 20 met our inclusion criteria for further analysis: published between 2018 and 2022, original research, containing molecular-genetic and statistical data, containing diagnosis verification methods, PTSD as a primary condition, and a sample of at least 60 patients. RESULTS: Among the 20 analyzed studies were reports of significant associations between PTSD and: FKBP5 variants rs9470080, regardless of the C or T allele; two FKBP5 haplotypes (A-G-C-C and A-G-C-T); gene-gene DRDхANNK1-COMT (rs1800497 × rs6269) and OXTR-DRD2 (rs2268498 × rs1801028); C-allele of CRHR1 (rs1724402). Other findings, such as the association of FKBP5 haplotypes (A-G-C-C, A-G-C-T) and the FKBP5-CRHR1 genotype, were of lesser statistical significance and less extensively studied. CONCLUSIONS: Although our literature analysis implicates certain genetic factors in PTSD, our understanding of the polygenic nature underlying the disorder remains limited, especially considering the hitherto underexplored epigenetic mechanisms. Future research endeavors should prioritize exploring these aspects to provide a more nuanced understanding of PTSD and its genetic underpinnings.

Post-COVID Neuropsychiatric Complications in Children and Adolescents: a Study Design for Early Diagnosis and Treatment Using Innovative Technologies.

BACKGROUND: The COVID-19 pandemic has had significant impacts on the child and adolescent population, with long-term consequences for physical health, socio-psychological well-being, and cognitive development, which require further investigation. We herein describe a study design protocol for recognizing neuropsychiatric complications associated with pediatric COVID-19, and for developing effective prevention and treatment strategies grounded on the evidence-based findings. METHODS: The study includes two cohorts, each with 163 participants, aged from 7 to 18 years old, and matched by gender. One cohort consisted of individuals with a history of COVID-19, while the other group presents those without such a history. We undertake comprehensive assessments, including neuropsychiatric evaluations, blood tests, and validated questionnaires completed by parents/guardians and by the children themselves. The data analysis is based on machine learning techniques to develop predictive models for COVID-19-associated neuropsychiatric complications in children and adolescents. RESULTS: The first model is focused on a binary classification to distinguish participants with and without a history of COVID-19. The second model clusters significant indicators of clinical dynamics during the follow-up observation period, including the persistence of COVID-19 related somatic and neuropsychiatric symptoms over time. The third model manages the predictors of discrete trajectories in the dynamics of post-COVID-19 states, tailored for personalized prediction modeling of affective, behavioral, cognitive, disturbances (academic/school performance), and somatic symptoms of the long COVID. CONCLUSIONS: The current protocol outlines a comprehensive study design aiming to bring a better understanding of COVID-19-associated neuropsychiatric complications in a population of children and adolescents, and to create a mobile phone-based applications for the diagnosis and treatment of affective, cognitive, and behavioral conditions. The study will inform about the improved management of preventive and personalized care strategies for pediatric COVID-19 patients. Study results support the development of engaging and age-appropriate mobile technologies addressing the needs of this vulnerable population group.

Neurological and Psychiatric Aspects of Biological Markers for the Provision of Medical Care to Patients with Spinal Muscular Atrophy 5q.

BACKGROUND: Spinal muscular atrophy (SMA) is a rare genetic disorder, in which, for the common childhood onset forms, loss of function of the SMA 5q gene leads to disability and death before adulthood. Symptomatic treatment focusses on respiratory and nutritional support, and physical therapy, but there is little consideration of psychiatric manifestations of SMA. The aim of this study was to explore blood biomarker levels, electromyography (EMG) data, and clinical manifestations, including psychiatric impairments, in patients with SMA 5q. Our objectives were twofold: First, to assess the clinical relevance of standard biomarkers, i.e., creatinine, creatine kinase (CK), and lactate dehydrogenase (LDH) levels, and second, to obtain data supporting the development of an effective prognostic algorithm for the course of this disease. RESULTS: We analyzed retrospective data from 112 medical records of 58 registered patients (2008-2022) with SMA. At the time of last registration, the 58 patients had a mean age 38.4 years [13.68; 55.0], of whom 32 (52%) were female. The subgroup of 21 pediatric patients had a mean age 12.32 years [6.57; 13.93], of whom 14 (24%) were girls. The ICD-10 diagnoses were as follows: G12.0 (n=7, 12%, children), G12.1 (n=14, 24% children; n=29, 50% adults), G12.8 (n=6, 10% adults), G12.9 (n=2, 1% adults). The archival data on psychiatric status indicated emotional lability (n=6, 10.3%), fatigue (n=10, 17.2%), and tearfulness (n=3, 5.2%) in some patients. There were no significant subgroup differences in serum creatinine and CK levels, but there were significant differences in LDH levels between the G12.0, G12.1, G12.8, and G12.9 subgroups. Among the serum biomarkers, only LDH levels showed significant differences among the subgroups of SMA 5q patients; higher levels in the G12.1, G12.8, and G12.9 groups compared to the G12.0 (infantile) group related to age, weight, gender, and level of physical activity. Data on psychiatric status were insufficient to identify group differences and associations with biomarker levels. Likewise, longitudinal data on repeat hospitalizations did not indicate associations with biomarker levels. CONCLUSIONS: Creatinine, CK, and LDH levels were insufficient for monitoring and predicting the course of SMA. Further prospective research is needed to elaborate the weak relationships between CK levels, the dynamics of the clinical presentation, and therapeutic interventions, and to investigate psychiatric co-morbidities in SMA 5q patients.

The Role of D-Serine and D-Aspartate in the Pathogenesis and Therapy of Treatment-Resistant Schizophrenia.

Schizophrenia (Sch) is a severe and widespread mental disorder. Antipsychotics (APs) of the first and new generations as the first-line treatment of Sch are not effective in about a third of cases and are also unable to treat negative symptoms and cognitive deficits of schizophrenics. This explains the search for new therapeutic strategies for a disease-modifying therapy for treatment-resistant Sch (TRS). Biological compounds are of great interest to researchers and clinicians, among which D-Serine (D-Ser) and D-Aspartate (D-Asp) are among the promising ones. The Sch glutamate theory suggests that neurotransmission dysfunction caused by glutamate N-methyl-D-aspartate receptors (NMDARs) may represent a primary deficiency in this mental disorder and play an important role in the development of TRS. D-Ser and D-Asp are direct NMDAR agonists and may be involved in modulating the functional activity of dopaminergic neurons. This narrative review demonstrates both the biological role of D-Ser and D-Asp in the normal functioning of the central nervous system (CNS) and in the pathogenesis of Sch and TRS. Particular attention is paid to D-Ser and D-Asp as promising components of a nutritive disease-modifying therapy for TRS.

Possible Clinical and Pharmacogenetic Predictors of the Efficacy and Safety of Carbamazepine in Post-COVID-19 Depression.

BACKGROUND: Individuals who have suffered from novel coronavirus disease (COVID-19) are at risk for developing post-COVID neuropsychiatric disorders, which are an integral part of the Long COVID syndrome. Depression and/or anxiety are considered the most common psychiatric disorders after experiencing COVID-19. Certain antiepileptic drugs, notably, carbamazepine (CMZ), are effective in the treatment of mood disorders, especially as mood stabilizers in bipolar affective disorder (BAD), but the efficacy of CMZ in Long COVID remains to be established. The aim of the review was to investigate pharmacogenetic predictors of safety and efficacy of CMZ in patients with depressive symptoms of Long COVID during the post-infection period. SUBJECTS AND METHODS: We carried out a systematic search for publications in English and Russian on the safety and efficacy of CMZ in depressive disorders of different etiologies in the PubMed, Web of Science, Springer, Clinical Keys, Google Schooler, E-Library databases using keywords and combined word searches (carbamazepine, COVID-19, depression, epilepsy, post-COVID-syndrome) for the period from January 01,2020 to June 10, 2022. RESULTS: We review the main adverse drug reactions (ADRs) associated with CMZ, drug-drug interactions, and genetic predictors of the development of ADR. Here, we consider as risk factors, candidate genes for CMZ metabolism, CMZ transport, immunohistocompatibility genes, and candidate genes for QT prolongation. CONCLUSIONS: The choice of antidepressant treatment for patients with Long COVID is fraught because of the frequent occurrence of subclinical (interictal) epileptiform activity in the EEG. Consequently, antidepressant medications with a proconvulsant effect are contraindicated for Long COVID patients. CMZ may be a promising alternative for the treatment of depressive disorders in Long COVID states, given its mood-stabilizer, antidepressant, and antiepileptic profile.

Association between Neuropathic Pain and Depression: Focusing on the Transcranial Magnetic Stimulation As a Promising Treatment Approach.

BACKGROUND: Neuropathic pain (NP) affects approximately 7% of the general population and is often accompanied by depressive symptoms with up to 85% of NP patients are suffering from comorbid depression (CD). The noninvasive neuromodulation technique of transcranial magnetic stimulation (TMS) is an established proven clinically effective nonpharmacological treatment for depression, and considered a highly promising option also for reducing the burden of NP by relieving pain perception and increasing patients' quality of life. In this article, we systematically review the various clinical protocols used in TMS treatments in patients suffering from NP and comorbid depression. SUBJECTS AND METHODS: Using Scopus, Elsevier, and PubMed databases, our keyword search identified 639 articles, of which 22 were selected for detailed analysis based on the inclusion criteria and in consideration of the heterogeneous study design of the majority of small trials. We evaluated the clinical efficacy in NP and comorbid depression, in relation to various TMS protocol parameters including coil type, target brain area, locus of increased evoked motor potential, amplitude of stimulation, duration of session, number of sessions per day/month, as well as inter-session-intervals, number and frequency of trains, and number and frequency of pulses. RESULTS: The most effective TMS protocols for treating comorbid NP and depression, as marked by decreased pain and depression scores proved to entail figure-of-8 coils targeting the primary motor area (M1), and applying at least ten daily rTMS sessions using high frequency stimulation (10-20 Hz) with a sub threshold intensity of 80-90% RMT and a total number of pulses of at least 1500 per session. Performing an additional maintenance phase after the acute treatment phase may strengthen and prolong the therapeutic effects of rTMS. CONCLUSIONS: Our database analysis suggests that a specific combination of TMS parameters is most effective for treating NP and comorbid depression. Although results are promising, the heterogeneity within the literature is such that many underpowered studies contribute rather little to the outcome, as evident by our inclusion / exclusion analysis. Moreover, we see a need for consensus on clinical protocols and inclusion of much larger clinical samples. Furthermore, we conclude that future research should entail advanced TMS procedures with multiple brain region stimulation (sequential or concurrent), and address issues of TMS maintenance and improved coil engineering for targeting deeper structures.

Does TMS Influence Verbal Function and Treat the Language Decline in Schizophrenia? Finding Answers via Systematic Review of Current Research.

BACKGROUND: rTMS is an adequately safe intervention that is approved for treatment of various neuropsychiatric conditions. There is ongoing research on the application of rTMS for the treatment of resistant auditory verbal hallucinations (AVH) in schizophrenia (SZ), and also for alleviating negative and cognitive symptoms in patients with chronic SZ states. Language decline, as a part of thought, language and communication disorders, is one of the key symptoms of SZ, having a significant bearing on decreased social/interpersonal functioning of these patients. In this regard rTMS may be a promising treatment approach, while serving as an important research tool in the field of SZ studies. The aim of our present study was to compile and evaluate the existing data on whether rTMS affects verbal function in SZ patients, and if rTMS has any efficacy for the treatment of language disturbances in SZ spectrum disorders. SUBJECTS AND METHODS: Our systematic search over the PubMed database revealed a total of 200 articles, of which 21 met criteria for inclusion in this analysis. We have reviewed in detail the study designs, inclusion and exclusion criteria, rTMS protocols and cognitive (in particular, speech/language domain) assessments reported in these articles. RESULTS: The 21 studies focused on two key topic clusters: (i) low-frequency rTMS treatment of AVH in SZ, and (ii) high-frequency rTMS treatment of negative and cognitive SZ symptoms. The majority of study participants presented with chronic and treatment-resistant states. Most of the low-frequency rTMS studies did not show any difference in verbal test measures in SZ in response to treatment. Less than a half of high-frequency rTMS studies reported a delayed positive effect on language cognitive domains in SZ. There were sporadic reports on dropouts associated with a decline in scores for auditory verbal learning tests. CONCLUSIONS: Our systematic review found rTMS to be generally safe in relation to verbal/speech function, and suggested that verbal memory tests could serve as a measure of safety of this treatment procedure in SZ patients. Speech effects of rTMS have only been registered over long-term observation periods, such that time-frame which should be considered as an important factor for future studies. In our project "Innovative Neuropsychiatry Research Bank: Priority-2030" we plan to clarify (i) efficient rTMS protocols targeting neurocognitive improvement in SZ, and (ii) the cohort of SZ patients with a particular cognitive endophenotype and language profile amenable to treatment with rTMS, with a focus on language scores.

Pathophysiological Mechanisms of Antipsychotic-Induced Parkinsonism.

Among neurological adverse reactions in patients with schizophrenia treated with antipsychotics (APs), drug-induced parkinsonism (DIP) is the most common motility disorder caused by drugs affecting dopamine receptors. One of the causes of DIP is the disruption of neurotransmitter interactions that regulate the signaling pathways of the dopaminergic, cholinergic, GABAergic, adenosinergic, endocannabinoid, and other neurotransmitter systems. Presently, the development mechanisms remain poorly understood despite the presence of the considered theories of DIP pathogenesis.