This review is focused on several psychiatric disorders in which cognitive impairment is a major component of the disease, influencing life quality. There are plenty of data proving that cognitive impairment accompanies and even underlies some psychiatric disorders. In addition, sources provide information on the biological background of cognitive problems associated with mental illness. This scientific review aims to summarize the current knowledge about neurobiological mechanisms of cognitive impairment in people with schizophrenia, depression, mild cognitive impairment and dementia (including Alzheimer’s disease).The review provides data about the prevalence of cognitive impairment in people with mental illness and associated biological markers.

Mental disorders represent common brain diseases characterized by substantial impairments of social and cognitive functions. The neurobiological causes and mechanisms of psychopathologies still have not been definitively determined. Various forms of brain proteinopathies, which include a disruption of protein conformations and the formation of protein aggregates in brain tissues, may be a possible cause behind the development of psychiatric disorders. Proteinopathies are known to be the main cause of neurodegeneration, but much less attention is given to the role of protein impairments in psychiatric disorders’ pathogenesis, such as depression and schizophrenia. For this reason, the aim of this review was to discuss the potential contribution of protein illnesses in the development of psychopathologies. The first part of the review describes the possible mechanisms of disruption to protein folding and aggregation in the cell: endoplasmic reticulum stress, dysfunction of chaperone proteins, altered mitochondrial function, and impaired autophagy processes. The second part of the review addresses the known proteins whose aggregation in brain tissue has been observed in psychiatric disorders (amyloid, tau protein, α-synuclein, DISC-1, disbindin-1, CRMP1, SNAP25, TRIOBP, NPAS3, GluA1, FABP, and ankyrin-G).

The prevalence of mental disorders and how they are diagnosed represent some of the major problems in psychiatry. Modern genetic tools offer the potential to reduce the complications concerning diagnosis. However, the vast genetic diversity in the world population requires a closer investigation of any selected populations. In the current research, four polymorphisms, namely rs6265 in BDNF, rs10835210 in BDNF, rs6313 in HTR2A, and rs1800955 in DRD4, were analyzed in a case–control study of 2393 individuals (1639 patients with mental disorders (F20-F29, F30-F48) and 754 controls) from the European part of Russia using the TaqMan SNP genotyping method. Significant associations between rs6265 BDNF and rs1800955 DRD4 and mental impairments were detected when comparing the general group of patients with mental disorders (without separation into diagnoses) to the control group. Associations of rs6265 in BDNF, rs1800955 in DRD4, and rs6313 in HTR2A with schizophrenia in patients from the schizophrenia group separately compared to the control group were also found. The obtained results can extend the concept of a genetic basis for mental disorders in the Russian population and provide a basis for the future improvement in psychiatric diagnostics.

Peripheral brain-derived neurotrophic factor (BDNF) levels increase during alcohol abstinence in dependent subjects. Meanwhile, the genetic determinants of circulating BDNF this context are poorly understood. Studies of associations between circulating BDNF and single nucleotide polymorphisms (SNPs) of the corresponding gene are mainly restricted by the most studied BDNF SNP rs6265. A recent genome-wide association study demonstrated that the BDNF-related SNP rs75945125 is associated with serum BDNF. However, it is unknown whether this SNP is associated with changes in peripheral BDNF levels in the context of alcohol abstinence. We aimed to assess the association of the BDNF-related SNPs rs75945125 and rs6265 with changes in serum BDNF levels after alcohol withdrawal and the corresponding clinical manifestations. A total of 132 inpatients diagnosed with alcohol withdrawal syndrome were enrolled in the study. Serum BDNF levels were assessed on 2nd, 7th, and 21st days after alcohol withdrawal. Alcohol withdrawal syndrome severity, craving severity, affective symptoms, and cognitive impairment were assessed on 7th and 21st days. BDNF SNPs rs75945125 and rs6265 were genotyped using real-time PCR. BDNF concentrations in the carriers of the rs75945125 C allele on 21st day were higher as compared with TT genotype carriers. BDNF SNP rs75945125 C allele carriers had a longer duration of problem drinking, consumed a lesser volume of alcohol in the last 3 months, and had lower severity of withdrawal syndrome on 7th day compared with TT genotype carriers. BDNF levels were moderated by rs75945125 and rs6265, as well as by the interaction of rs75945125 × rs6265, whereas only the interaction of rs75945125 × rs6265 had an effect on depression scores during abstinence. Thus, the trajectory of serum BDNF changes during alcohol abstinence is determined by both rs75945125 and rs6265. Moreover, BDNF gene-related SNPs are associated with the clinical parameters of alcohol dependence and withdrawal. The longitudinal design without a control group and the relatively small sample size are the limitations of this study. Future studies on the revealed interactions are warranted.

Цитохром P450 (CYP450) является ведущим ферментом в биотрансформации большинства психотропных препаратов. Полиморфизмы генов CYP450 определяют эндофенотип пациента относительно активности ферментов семейства и влияют на метаболизм назначаемых антипсихотиков и антидепрессантов. Категоризация пациентов по эндофенотипам в ходе генотипирования, вероятно, поможет упростить подбор терапии в клинической практике. Совместное назначение препаратов, которые могут быть ингибиторами или индукторами изоформ CYP450 в свою очередь может привести к развитию нежелательных реакций или отсутствию эффекта терапии. В статье изложена компиляция известных фармакогенетических рекомендаций относительно четырех основных эндофенотипов метаболизаторов.

Background: Post-traumatic stress disorder (PTSD) is a severe psychiatric condition prevalent among combat veterans. Its diagnosis is challenging due to the heterogeneity of clinical presentations and the complex interplay of pathogenic factors. Objective: This study aimed to develop and validate a diagnostic algorithm for combat-related PTSD by integrating clinical data with a panel of biological markers associated with blood–brain barrier disruption (anti-GFAP and anti-NSE antibodies), HPA axis dysfunction (cortisol), and neuroinflammation (IL-6, IL-8). Methods: A total of 721 male participants were enrolled: 434 veterans with PTSD (F43.1), 147 combat veterans without PTSD, and 140 non-combat military controls. All participants underwent clinical and psychometric assessment (Likert scale, HADS). Serum levels of biomarkers were measured using ELISA. Statistical analysis included non-parametric tests, correlation analysis, and binary logistic regression with Wald’s method to build a predictive model. Results: The binary logistic regression model identified cortisol and IL-6 as the most significant predictors of PTSD. The final algorithm, based on a cortisol level below 199.8 nmol/L and an IL-6 level above 0.002438 pg/mL, correctly classified 78% of patients (AUC = 0.724, 95% CI [0.669, 0.779]). Furthermore, levels of IL-4, IL-8, and cortisol positively correlated with the severity of combat stress factors, independent of physical injuries. Conclusions: We developed a novel diagnostic algorithm for combat-related PTSD based on cortisol and IL-6 levels, demonstrating high accuracy. The correlation between neuroinflammatory markers and the severity of combat exposure suggests their role as primary indicators of stress response, highlighting their utility for early risk identification and targeted interventions.