Treatment-Resistant Schizophrenia: Insights From Genetic Studies and Machine Learning Approaches

Schizophrenia (SCZ) is a severe psychiatric disorder affecting approximately 23 million people worldwide. It is considered the eighth leading cause of disability according to the World Health Organization and is associated with a significant reduction in life expectancy. Antipsychotics represent the first-choice treatment in SCZ, but approximately 30% of patients fail to respond to acute treatment. These patients are generally defined as treatment-resistant and are eligible for clozapine treatment. Treatment-resistant patients show a more severe course of the disease, but it has been suggested that treatment-resistant schizophrenia (TRS) may constitute a distinct phenotype that is more than just a more severe form of SCZ. TRS is heritable, and genetics has been shown to play an important role in modulating response to antipsychotics. Important efforts have been put into place in order to better understand the genetic architecture of TRS, with the main goal of identifying reliable predictive markers that might improve the management and quality of life of TRS patients. However, the number of candidate gene and genome-wide association studies specifically focused on TRS is limited, and to date, findings do not allow the disentanglement of its polygenic nature. More recent studies implemented polygenic risk score, gene-based and machine learning methods to explore the genetics of TRS, reporting promising findings. In this review, we present an overview on the genetics of TRS, particularly focusing our discussion on studies implementing polygenic approaches

Investigating Shared Genetic Bases between Psychiatric Disorders, Cardiometabolic and Sleep Traits Using K-Means Clustering and Local Genetic Correlation Analysis

Psychiatric disorders are among the top leading causes of the global health-related burden. Comorbidity with cardiometabolic and sleep disorders contribute substantially to this burden. While both genetic and environmental factors have been suggested to underlie these comorbidities, the specific molecular underpinnings are not well understood. In this study, we leveraged large datasets from genome-wide association studies (GWAS) on psychiatric disorders, cardiometabolic and sleeprelated traits. We computed genetic correlations between pairs of traits using cross-trait linkage disequilibrium (LD) score regression and identified clusters of genetically correlated traits using k-means clustering. We further investigated the identified associations using two-sample mendelian randomization (MR) and tested the local genetic correlation at the identified loci. In the 7-cluster optimal solution, we identified a cluster including insomnia and the psychiatric disorders major depressive disorder (MDD), post-traumatic stress disorder (PTSD), and attention-deficit/hyperactivity disorder (ADHD). MR analysis supported the existence of a bidirectional association between MDD and insomnia and the genetic variants driving this association were found to affect gene expression in different brain regions. Some of the identified loci were further supported by results of local genetic correlation analysis, with body mass index (BMI) and C-reactive protein (CRP) levels suggested to explain part of the observed effects. We discuss how the investigation of the genetic relationships between psychiatric disorders and comorbid conditions might help us to improve our understanding of their pathogenesis and develop improved treatment strategies

Presenting Psychiatric and Neurological Symptoms and Signs of Brain Tumors before Diagnosis: A Systematic Review

Brain tumors can present with various psychiatric symptoms, with or without neurological symptoms, an aspect that complicates the clinical picture. However, no systematic description of symptoms that should prompt a neurological investigation has been provided. This review aims to summarize available case reports describing patients with brain tumors showing psychiatric symptoms before brain tumor diagnosis, in order to provide a comprehensive description of these symptoms as well as their potential relationship with delay in the diagnosis. A systematic literature review on case reports of brain tumors and psychiatric symptoms from 1970 to 2020 was conducted on PubMed, Ovid, Psych Info, and MEDLINE. Exclusion criteria comprised tumors not included in the World Health Organization (WHO) Classification 4th edition and cases in which psychiatric symptoms were absent or followed the diagnosis. A total of 165 case reports were analyzed. In a subset of patients with brain tumors, psychiatric symptoms can be the only manifestation or precede focal neurological signs by months or even years. The appearance of focal or generalized neurological symptoms after, rather than along with, psychiatric symptoms was associated with a significant delay in the diagnosis in adults. A timely assessment of psychiatric symptoms might help to improve early diagnosis of brain tumors

Inhibition of Stearoyl-CoA desaturase 1 reverts BRAF and MEK inhibition-induced selection of cancer stem cells in BRAF-mutated melanoma

Combination therapy with BRAF and MEK inhibitors significantly improves survival in BRAF mutated melanoma patients but is unable to prevent disease recurrence due to the emergence of drug resistance. Cancer stem cells (CSCs) have been involved in these long-term treatment failures. We previously reported in lung cancer that CSCs maintenance is due to altered lipid metabolism and dependent upon Stearoyl-CoA-desaturase (SCD1)-mediated upregulation of YAP and TAZ. On this ground, we investigated the role of SCD1 in melanoma CSCs

Prototype of a Low-Cost Electronic Platform for Real Time Greenhouse Environment Monitoring: An Agriculture 4.0 Perspective

The Internet of Things has a high impact on upgrade and transformation of the traditional greenhouse agricultural techniques. It is necessary to control the environmental factors for obtaining the optimum growth conditions for the crop and extend the production season to get the optimum yield. These aspects are fundamental for Agriculture 4.0, that uses technology not simply for the sake of innovation but to improve and address the real needs of consumers. In this paper, a prototype of a low-cost electronic platform for real time greenhouse environment monitoring has been designed, developed and built. The prototype has been developed with the purpose of firmware and software prototyping, in order to make the most of device performances. The electronic board is composed by a Main Board, a Green House Core, aWi-Fi Module, a RS485 Module, an Analog-to-Digital Converter Module and a USB Module. The system permits to collect data by external sensors, elaborate and send them to external devices as laptop, smartphone and internet gateway, using both wired and wireless connection. These data concern to main greenhouse environmental parameters, such as air temperature, humidity, solar radiation, air velocity and CO2 concentration. AWeb application has been implemented to allow users a consultation of greenhouse environmental state in a simple and fast way

Pharmacokinetic Markers of Clinical Outcomes in Severe Mental Illness: A Systematic Review

The term severe mental illness (SMI) encompasses those psychiatric disorders exerting the highest clinical burden and socio-economic impact on the affected individuals and their communities. Pharmacogenomic (PGx) approaches hold great promise in personalizing treatment selection and clinical outcomes, possibly reducing the burden of SMI. Here, we sought to review the literature in the field, focusing on PGx testing and particularly on pharmacokinetic markers. We performed a systematic review on PUBMED/Medline, Web of Science, and Scopus. The last search was performed on the 17 September 2022, and further augmented with a comprehensive pearl-growing strategy. In total, 1979 records were screened, and after duplicate removal, 587 unique records were screened by at least 2 independent reviewers. Ultimately, forty-two articles were included in the qualitative analysis, eleven randomized controlled trials and thirty-one nonrandomized studies. The observed lack of standardization in PGx tests, population selection, and tested outcomes limit the overall interpretation of the available evidence. A growing body of evidence suggests that PGx testing might be cost-effective in specific settings and may modestly improve clinical outcomes. More efforts need to be directed toward improving PGx standardization, knowledge for all stakeholders, and clinical practice guidelines for screening recommendations

Combination of antibodies directed against different ErbB3 surface epitopes prevents the establishment of resistance to BRAF/MEK inhibitors in melanoma

Patients with metastatic melanoma bearing V600 mutations in BRAF oncogene clinically benefit from the treatment with BRAF inhibitors alone or in combination with MEK inhibitors. However, a limitation to such treatment is the occurrence of resistance. Tackling the adaptive changes helping cells survive from drug treatment may offer new therapeutic opportunities. Very recently the ErbB3 receptor has been shown to act as a central node promoting survival of BRAF mutated melanoma. In this paper we first demonstrate that ErbB3/AKT hyperphosphorylation occurs in BRAF mutated melanoma cell lines following exposure to BRAF and/or MEK inhibitors. This strongly correlates with increased transcriptional activation of its ligand neuregulin. Anti-ErbB3 antibodies impair the establishment of de novo cell resistance to BRAF inhibition in vitro. In order to more potently ablate ErbB3 activity we used a combination of two anti-ErbB3 antibodies directed against distinct epitopes of its extracellular domain. These two antibodies in combo with BRAF/MEK inhibitors potently inhibit in vitro cell growth and tumor regrowth after drug withdrawal in an in vivo xenograft model. Importantly, residual tumor masses from mice treated by the antibodies and BRAF/ERK inhibitors combo are characterized almost exclusively by large necrotic areas with limited residual areas of tumor growth. Taken together, our findings support the concept that triple therapy directed against BRAF/MEK/ErbB3 may be able to provide durable control of BRAF mutated metastatic melanoma

Application of Support Vector Machine on fMRI Data as Biomarkers in Schizophrenia Diagnosis: A Systematic Review

Non-invasive measurements of brain function and structure as neuroimaging in patients with mental illnesses are useful and powerful tools for studying discriminatory biomarkers. To date, functional MRI (fMRI), structural MRI (sMRI) represent the most used techniques to provide multiple perspectives on brain function, structure, and their connectivity. Recently, there has been rising attention in using machine-learning (ML) techniques, pattern recognition methods, applied to neuroimaging data to characterize disease-related alterations in brain structure and function and to identify phenotypes, for example, for translation into clinical and early diagnosis. Our aim was to provide a systematic review according to the PRISMA statement of Support Vector Machine (SVM) techniques in making diagnostic discrimination between SCZ patients from healthy controls using neuroimaging data from functional MRI as input. We included studies using SVM as ML techniques with patients diagnosed with Schizophrenia. From an initial sample of 660 papers, at the end of the screening process, 22 articles were selected, and included in our review. This technique can be a valid, inexpensive, and non-invasive support to recognize and detect patients at an early stage, compared to any currently available assessment or clinical diagnostic methods in order to save crucial time. The higher accuracy of SVM models and the new integrated methods of ML techniques could play a decisive role to detect patients with SCZ or other major psychiatric disorders in the early stages of the disease or to potentially determine their neuroimaging risk factors in the near future

Macroparasite fauna of alien grey squirrels (Sciurus carolinensis): composition, variability and implications for native species.

Introduced hosts populations may benefit of an "enemy release" through impoverishment of parasite communities made of both few imported species and few acquired local ones. Moreover, closely related competing native hosts can be affected by acquiring introduced taxa (spillover) and by increased transmission risk of native parasites (spillback). We determined the macroparasite fauna of invasive grey squirrels (Sciurus carolinensis) in Italy to detect any diversity loss, introduction of novel parasites or acquisition of local ones, and analysed variation in parasite burdens to identify factors that may increase transmission risk for native red squirrels (S. vulgaris). Based on 277 grey squirrels sampled from 7 populations characterised by different time scales in introduction events, we identified 7 gastro-intestinal helminths and 4 parasite arthropods. Parasite richness is lower than in grey squirrel's native range and independent from introduction time lags. The most common parasites are Nearctic nematodes Strongyloides robustus (prevalence: 56.6%) and Trichostrongylus calcaratus (6.5%), red squirrel flea Ceratophyllus sciurorum (26.0%) and Holarctic sucking louse Neohaematopinus sciuri (17.7%). All other parasites are European or cosmopolitan species with prevalence below 5%. S. robustus abundance is positively affected by host density and body mass, C. sciurorum abundance increases with host density and varies with seasons. Overall, we show that grey squirrels in Italy may benefit of an enemy release, and both spillback and spillover processes towards native red squirrels may occur