A systematic review of EEG based automated schizophrenia classification through machine learning and deep learning

The electroencephalogram (EEG) serves as an essential tool in exploring brain activity and holds particular importance in the field of mental health research. This review paper examines the application of artificial intelligence (AI), encompassing machine learning (ML) and deep learning (DL), for classifying schizophrenia (SCZ) through EEG. It includes a thorough literature review that addresses the difficulties, methodologies, and discoveries in this field. ML approaches utilize conventional models like Support Vector Machines and Decision Trees, which are interpretable and effective with smaller data sets. In contrast, DL techniques, which use neural networks such as convolutional neural networks (CNNs) and long short-term memory networks (LSTMs), are more adaptable to intricate EEG patterns but require significant data and computational power. Both ML and DL face challenges concerning data quality and ethical issues. This paper underscores the importance of integrating various techniques to enhance schizophrenia diagnosis and highlights AI's potential role in this process. It also acknowledges the necessity for collaborative and ethically informed approaches in the automated classification of SCZ using AI.

Prefrontal cortex-specific Dcc deletion induces schizophrenia-related behavioral phenotypes and fail to be rescued by olanzapine treatment

Multiple genome studies have discovered that variation in deleted in colorectal carcinoma (Dcc) at transcription and translation level were associated with the occurrences of psychiatric disorders. Yet, little is known about the function of Dcc in schizophrenia (SCZ)-related behavioral abnormalities and the efficacy of antipsychotic drugs in vivo. Here, we used an animal model of prefrontal cortex-specific knockdown (KD) of Dcc in adult C57BL/6 mice to study the attention deficits and impaired locomotor activity. Our results supported a critical role of Dcc deletion in SCZ-related behaviors. Notably, olanzapine rescued the SCZ-related behaviors in the MK801-treated mice but not in the cortex-specific Dcc KD mice, indicating that Dcc play a critical in the mechanism of antipsychotic effects of olanzapine. Knockdown of Dcc in prefrontal cortex results in glutamatergic dysfunction, including defects in glutamine synthetase and postsynaptic maturation. As one of the major risk factors of the degree of antipsychotic response, Dcc deletion-induced glutamatergic dysfunction may be involved in the underlying mechanism of treatment resistance of olanzapine. Our findings identified Dcc deletion-mediated SCZ-related behavioral defects, which serve as a valuable animal model for study of SCZ and amenable to targeted investigations in mechanistic hypotheses of the mechanism underlying glutamatergic dysfunction-induced antipsychotic treatment resistance.

Characterization of loss of chromosome Y in peripheral blood cells in male Han Chinese patients with schizophrenia

BACKGROUND

Schizophrenia (SCZ) has a global prevalence of 1% and increases the risk of mortality, reducing life expectancy. There is growing evidence that the risk of this disorder is higher in males than in females and it tends to develop in early adulthood. The Y chromosome is thought to be involved in biological processes other than sex determination and spermatogenesis. Studies have shown that loss of chromosome Y (LOY) in peripheral blood cells is associated with a variety of diseases (including cancer) and increased all-cause mortality. An analysis of the relationship between LOY and schizophrenia is warranted.

METHODS

A total of 442 Chinese males (271 patients with schizophrenia vs. 171 controls) were included in this study. The copy numbers of the Y and X chromosomes were detected by positive droplets targeting the amelogenin gene (AMEL) on the Y chromosome and X chromosome (AMELY and AMELX, respectively), using droplet digital PCR (ddPCR). The LOY percentage was defined as the difference between the concentration of AMELX and the concentration of AMELY divided by the concentration of AMELX, denoted as (X - Y)/X.

RESULTS

In the Han Chinese population, the LOY percentage was higher in the schizophrenia group than in the control group (p < 0.05), although there was no significant difference in the presence of LOY between the two groups. A strong correlation was found between the average of the disease duration and the average of the LOY percentage (R² = 0.506, p = 0.032). The logistic regression analysis implied that the risk of LOY increases by 0.058 and 0.057 per year according to age at onset and duration of disease, respectively (p_onset = 0.013, p_duration = 0.017).

CONCLUSIONS

In the Han Chinese population, the LOY percentage of the disease group was significantly different from that of the control group. The age of onset and duration of schizophrenia might be risk factors for LOY in peripheral blood cells. A larger sample size and expanded clinical information are needed for more in-depth and specific analyses.

Mitochondrial dysfunction in psychiatric disorders

Psychiatric disorders are a heterogeneous group of mental disorders with abnormal mental or behavioral patterns, which severely distress or disable affected individuals and can have a grave socioeconomic burden. Growing evidence indicates that mitochondrial function plays an important role in developing psychiatric disorders. This review discusses the neuropsychiatric consequences of mitochondrial abnormalities in both animal models and patients. We also discuss recent studies associated with compromised mitochondrial function in various psychiatric disorders, such as schizophrenia (SCZ), major depressive disorder (MD), and bipolar disorders (BD). These studies employ various approaches including postmortem studies, imaging studies, genetic studies, and induced pluripotent stem cells (iPSCs) studies. We also summarize the evidence from animal models and clinical trials to support mitochondrial function as a potential therapeutic target to treat various psychiatric disorders. This review will contribute to furthering our understanding of the metabolic etiology of various psychiatric disorders, and help guide the development of optimal therapies.

Generation and characterization of human-derived iPSC lines from one pair of dizygotic twins discordant for schizophrenia

Schizophrenia (SCZ) is a debilitating neurodevelopmental disorder with a high heritability. In this study, peripheral blood mononuclear cells (PBMCs) were donated by a pair of dizygotic twins. The female was clinically diagnosed as SCZ by Diagnostic and Statistical Manual of Mental Disorders IV (DSM-IV) criteria, and her unaffected male sibling was healthy control. Induced pluripotent stem cells (iPSCs) were established using Episomal vectors carrying reprograming factors OCT4, SOX2, NANOG, LIN28, c-MYC, KLF4, and SV40LT. These lines with normal karyotype highly expressed pluripotency markers and are capable to differentiate into derivatives of three germ layers. Both lines are negative of mycoplasma.

The Potential Effect of Aberrant Testosterone Levels on Common Diseases: A Mendelian Randomization Study

Testosterone has historically been linked to sexual dysfunction; however, it has recently been shown to affect other physical and mental attributes. We attempted to determine whether changes in serum testosterone could play a role in chronic or degenerative diseases. We used two separate genetic instruments comprising of variants from JMJD1C and SHBG regions and conducted a two-sample Mendelian randomization for type II diabetes (T2D), gout, rheumatoid arthritis (RA), schizophrenia, bipolar disorder, Alzheimer’s disease and depression. For the JMJD1C locus, one unit increase in log transformed testosterone was significantly associated with RA (OR = 1.69, p = 0.02), gout (OR = 0.469, p = 0.001) and T2D (OR = 0.769, p = 0.048). Similarly, one unit increase in log transformed testosterone using variants from the SHBG locus was associated with depression (OR = 1.02, p = 0.001), RA (OR = 1.32, p < 0.001) and T2D (OR = 0.88, p = 0.003). Our results show that low levels of serum testosterone levels may cause gout and T2D, while higher than normal levels of testosterone may result in RA and depression. Our findings suggest that fluctuations in testosterone levels may have severe consequences that warrant further investigation.