A Secondary Analysis of the Complex Interplay between Psychopathology, Cognitive Functions, Brain Derived Neurotrophic Factor Levels, and Suicide in Psychotic Disorders: Data from a 2-Year Longitudinal Study.

Identifying phenotypes at high risk of suicidal behaviour is a relevant objective of clinical and translational research and can facilitate the identification of possible candidate biomarkers. We probed the potential association and eventual stability of neuropsychological profiles and serum BDNF concentrations with lifetime suicide ideation and attempts (LSI and LSA, respectively) in individuals with schizophrenia (SCZ) and schizoaffective disorder (SCA) in a 2-year follow-up study. A secondary analysis was conducted on a convenience sample of previously recruited subjects from a single outpatient clinic. Retrospectively assessed LSI and LSA were recorded by analysing the available longitudinal clinical health records. LSI + LSA subjects consistently exhibited lower PANSS-defined negative symptoms and better performance in the BACS-letter fluency subtask. There was no significant association between BDNF levels and either LSI or LSA. We found a relatively stable pattern of lower negative symptoms over two years among patients with LSI and LSA. No significant difference in serum BDNF concentrations was detected. The translational viability of using neuropsychological profiles as a possible avenue for the identification of populations at risk for suicide behaviours rather than the categorical diagnosis represents a promising option but requires further confirmation.

A Pilot Interaction Analysis of Gut Microbiota and Peripheral Markers of Aging in Severe Psychiatric Disorders: A Role for Lachnoclostridium?

Excessive predominance of pathological species in the gut microbiota could increase the production of inflammatory mediators at the gut level and, via modification of the gut-blood barrier, at the systemic level. This pro-inflammatory state could, in turn, increase biological aging that is generally proxied by telomere shortening. In this study, we present findings from a secondary interaction analysis of gut microbiota, aging, and inflammatory marker data from a cohort of patients with different diagnoses of severe mental disorders. We analyzed 15 controls, 35 patients with schizophrenia (SCZ), and 31 patients with major depressive disorder (MDD) recruited among those attending a community mental health center (50 males and 31 females, mean and median age 46.8 and 46.3 years, respectively). We performed 16S rRNA sequencing as well as measurement of telomere length via quantitative fluorescence in situ hybridization and high-sensitivity C-reactive protein. We applied statistical modeling with logistic regression to test for interaction between gut microbiota and these markers. Our results showed statistically significant interactions between telomere length and gut microbiota pointing to the genus Lachnostridium, which remained significantly associated with a reduced likelihood of MDD even after adjustment for a series of covariates. Although exploratory, these findings show that specific gut microbiota signatures overexpressing Lachnoclostridium and interacting with biological aging could modulate the liability for MDD.

Lithium and its effects: does dose matter?

BACKGROUND: Decades of clinical research have demonstrated the efficacy of lithium in treating acute episodes (both manic and depressive), as well as in preventing recurrences of bipolar disorder (BD). Specific to lithium is its antisuicidal effect, which appears to extend beyond its mood-stabilizing properties. Lithium's clinical effectiveness is, to some extent, counterbalanced by its safety and tolerability profile. Indeed, monitoring of lithium levels is required by its narrow therapeutic index. There is consensus that adequate serum levels should be above 0.6 mEq/L to achieve clinical effectiveness. However, few data support the choice of this threshold, and increasing evidence suggests that lithium might have clinical and molecular effects at much lower concentrations. CONTENT: This narrative review is aimed at: (1) reviewing and critically interpreting the clinical evidence supporting the use of the 0.6 mEq/L threshold, (2) reporting a narrative synthesis of the evidence supporting the notion that lithium might be effective in much lower doses. Among these are epidemiological studies of lithium in water, evidence on the antisuicidal, anti-aggressive, and neuroprotective effects, including efficacy in preventing cognitive impairment progression, Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS), of lithium; and (3) revieweing biological data supporting clinically viable uses of lithium at low levels with the delineation of a mechanistic hypothesis surrounding its purported mechanism of action. The study selection was based on the authors' preference, reflecting the varied and extensive expertise on the review subject, further enriched with an extensive pearl-growing strategy for relevant reviews and book sections. CONCLUSIONS: Clinical and molecular effects of lithium are numerous, and its effects also appear to have a certain degree of specificity related to the dose administered. In sum, the clinical effects of lithium are maximal for mood stabilisation at concentrations higher than 0.6 mEq/l. However, lower levels may be sufficient for preventing depressive recurrences in older populations of patients, and microdoses could be effective in decreasing suicide risk, especially in patients with BD. Conversely, lithium's ability to counteract cognitive decline appears to be exerted at subtherapeutic doses, possibly corresponding to its molecular neuroprotective effects. Indeed, lithium may reduce inflammation and induce neuroprotection even at doses several folds lower than those commonly used in clinical settings. Nevertheless, findings surrounding its purported mechanism of action are missing, and more research is needed to investigate the molecular targets of low-dose lithium adequately.

Dissecting the genetic overlap between severe mental disorders and markers of cellular aging: Identification of pleiotropic genes and druggable targets.

Patients with severe mental disorders such as bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) show a substantial reduction in life expectancy, increased incidence of comorbid medical conditions commonly observed with advanced age and alterations of aging hallmarks. While severe mental disorders are heritable, the extent to which genetic predisposition might contribute to accelerated cellular aging is not known. We used bivariate causal mixture models to quantify the trait-specific and shared architecture of mental disorders and 2 aging hallmarks (leukocyte telomere length [LTL] and mitochondrial DNA copy number), and the conjunctional false discovery rate method to detect shared genetic loci. We integrated gene expression data from brain regions from GTEx and used different tools to functionally annotate identified loci and investigate their druggability. Aging hallmarks showed low polygenicity compared with severe mental disorders. We observed a significant negative global genetic correlation between MDD and LTL (rg = -0.14, p = 6.5E-10), and no significant results for other severe mental disorders or for mtDNA-cn. However, conditional QQ plots and bivariate causal mixture models pointed to significant pleiotropy among all severe mental disorders and aging hallmarks. We identified genetic variants significantly shared between LTL and BD (n = 17), SCZ (n = 55) or MDD (n = 19), or mtDNA-cn and BD (n = 4), SCZ (n = 12) or MDD (n = 1), with mixed direction of effects. The exonic rs7909129 variant in the SORCS3 gene, encoding a member of the retromer complex involved in protein trafficking and intracellular/intercellular signaling, was associated with shorter LTL and increased predisposition to all severe mental disorders. Genetic variants underlying risk of SCZ or MDD and shorter LTL modulate expression of several druggable genes in different brain regions. Genistein, a phytoestrogen with anti-inflammatory and antioxidant effects, was an upstream regulator of 2 genes modulated by variants associated with risk of MDD and shorter LTL. While our results suggest that shared heritability might play a limited role in contributing to accelerated cellular aging in severe mental disorders, we identified shared genetic determinants and prioritized different druggable targets and compounds.

Symptomatic remission and recovery in major psychosis: Is there a role for BDNF? A secondary analysis of the LABSP cohort data.

Remission, relapse prevention, and clinical recovery are crucial areas of interest in schizophrenia (SCZ) research. Although SCZ is a chronic disorder with poor overall outcomes, years of research demonstrated that recovery is possible. There are considerable data linking brain-derived neurotrophic factor (BDNF) to SCZ, however, evidence on the role of BDNF in remission in SCZ is scarce. This secondary analysis of the Longitudinal Assessment of BDNF in Sardinian patients (LABSP) data aimed to investigate the relationship between serum BDNF levels and symptomatic remission, simultaneous clinical and functional remission, and recovery in patients with SCZ. A total of 105 patients with SCZ or schizoaffective disorder were recruited for a longitudinal assessment of BDNF levels over 24 months. Longitudinal data were analyzed using mixed-effects linear regression models. The study found significant associations between use of long acting injectables (χ2 = 7.075, df = 1, p = 0.008), baseline serum BDNF levels (U = 701, z = -2.543, p = 0.011), and "childhood" (U = 475, z = -2.124, p = 0.034) and "general" (U = 55, z = -2.014, p = 0.044) subscales of the Premorbid Adjustment Scale (PAS) with patients maintaining remission and recovery. The diagnosis of SCZ was significantly associated with lower BDNF levels for patients with simultaneous clinical and functional remission (Z = 2.035, p = 0.0419) and recovery (Z = 2.009, p = 0.0445) compared to those without. There were no significant associations between remission in the entire sample and longitudinal serum BDNF levels or genetic variants within the BDNF gene. These findings provide further insight into the complex relationship between BDNF and SCZ.

An integrated precision medicine approach in major depressive disorder: a study protocol to create a new algorithm for the prediction of treatment response.

Major depressive disorder (MDD) is the most common psychiatric disease worldwide with a huge socio-economic impact. Pharmacotherapy represents the most common option among the first-line treatment choice; however, only about one third of patients respond to the first trial and about 30% are classified as treatment-resistant depression (TRD). TRD is associated with specific clinical features and genetic/gene expression signatures. To date, single sets of markers have shown limited power in response prediction. Here we describe the methodology of the PROMPT project that aims at the development of a precision medicine algorithm that would help early detection of non-responder patients, who might be more prone to later develop TRD. To address this, the project will be organized in 2 phases. Phase 1 will involve 300 patients with MDD already recruited, comprising 150 TRD and 150 responders, considered as extremes phenotypes of response. A deep clinical stratification will be performed for all patients; moreover, a genomic, transcriptomic and miRNomic profiling will be conducted. The data generated will be exploited to develop an innovative algorithm integrating clinical, omics and sex-related data, in order to predict treatment response and TRD development. In phase 2, a new naturalistic cohort of 300 MDD patients will be recruited to assess, under real-world conditions, the capability of the algorithm to correctly predict the treatment outcomes. Moreover, in this phase we will investigate shared decision making (SDM) in the context of pharmacogenetic testing and evaluate various needs and perspectives of different stakeholders toward the use of predictive tools for MDD treatment to foster active participation and patients' empowerment. This project represents a proof-of-concept study. The obtained results will provide information about the feasibility and usefulness of the proposed approach, with the perspective of designing future clinical trials in which algorithms could be tested as a predictive tool to drive decision making by clinicians, enabling a better prevention and management of MDD resistance.