Altered Expression of PDE4 Genes in Schizophrenia: Insights from a Brain and Blood Sample Meta-Analysis and iPSC-Derived Neurons.

Schizophrenia symptomatology includes negative symptoms and cognitive impairment. Several studies have linked schizophrenia with the PDE4 family of enzymes due to their genetic association and function in cognitive processes such as long-term potentiation. We conducted a systematic gene expression meta-analysis of four PDE4 genes (PDE4A-D) in 10 brain sample datasets (437 samples) and three blood sample datasets (300 samples). Subsequently, we measured mRNA levels in iPSC-derived hippocampal dentate gyrus neurons generated from fibroblasts of three groups: healthy controls, healthy monozygotic twins (MZ), and their MZ siblings with schizophrenia. We found downregulation of PDE4B in brain tissues, further validated by independent data of the CommonMind consortium (515 samples). Interestingly, the downregulation signal was present in a subgroup of the patients, while the others showed no differential expression or even upregulation. Notably, PDE4A, PDE4B, and PDE4D exhibited upregulation in iPSC-derived neurons compared to healthy controls, whereas in blood samples, PDE4B was found to be upregulated while PDE4A was downregulated. While the precise mechanism and direction of altered PDE4 expression necessitate further investigation, the observed multilevel differential expression across the brain, blood, and iPSC-derived neurons compellingly suggests the involvement of PDE4 genes in the pathophysiology of schizophrenia.

A new type of blood-brain barrier aminoacidopathy underlies metabolic microcephaly associated with SLC1A4 mutations.

Mutations in the SLC1A4 transporter lead to neurodevelopmental impairments, spastic tetraplegia, thin corpus callosum, and microcephaly in children. SLC1A4 catalyzes obligatory amino acid exchange between neutral amino acids, but the physiopathology of SLC1A4 disease mutations and progressive microcephaly remain unclear. Here, we examined the phenotype and metabolic profile of three Slc1a4 mouse models, including a constitutive Slc1a4-KO mouse, a knock-in mouse with the major human Slc1a4 mutation (Slc1a4-K256E), and a selective knockout of Slc1a4 in brain endothelial cells (Slc1a4tie2-cre). We show that Slc1a4 is a bona fide L-serine transporter at the BBB and that acute inhibition or deletion of Slc1a4 leads to a decrease in serine influx into the brain. This results in microcephaly associated with decreased L-serine content in the brain, accumulation of atypical and cytotoxic 1-deoxysphingolipids in the brain, neurodegeneration, synaptic and mitochondrial abnormalities, and behavioral impairments. Prenatal and early postnatal oral administration of L-serine at levels that replenish the serine pool in the brain rescued the observed biochemical and behavioral changes. Administration of L-serine till the second postnatal week also normalized brain weight in Slc1a4-E256 K mice. Our observations suggest that the transport of "non-essential" amino acids from the blood through the BBB is at least as important as that of essential amino acids for brain metabolism and development. We proposed that SLC1A4 mutations cause a BBB aminoacidopathy with deficits in serine import across the BBB required for optimal brain growth and leads to a metabolic microcephaly, which may be amenable to treatment with L-serine.

Immunoglobulin genes expressed in lymphoblastoid cell lines discern and predict lithium response in bipolar disorder patients.

Bipolar disorder (BD) is a neuropsychiatric mood disorder manifested by recurrent episodes of mania and depression. More than half of BD patients are non-responsive to lithium, the first-line treatment drug, complicating BD clinical management. Given its unknown etiology, it is pertinent to understand the genetic signatures that lead to variability in lithium response. We discovered a set of differentially expressed genes (DEGs) from the lymphoblastoid cell lines (LCLs) of 10 controls and 19 BD patients belonging mainly to the immunoglobulin gene family that can be used as potential biomarkers to diagnose and treat BD. Importantly, we trained machine learning algorithms on our datasets that predicted the lithium response of BD subtypes with minimal errors, even when used on a different cohort of 24 BD patients acquired by a different laboratory. This proves the scalability of our methodology for predicting lithium response in BD and for a prompt and suitable decision on therapeutic interventions.

Intrinsic Excitability in Layer IV-VI Anterior Insula to Basolateral Amygdala Projection Neurons Correlates with the Confidence of Taste Valence Encoding.

Avoiding potentially harmful, and consuming safe food is crucial for the survival of living organisms. However, the perceived valence of sensory information can change following conflicting experiences. Pleasurability and aversiveness are two crucial parameters defining the perceived valence of a taste and can be impacted by novelty. Importantly, the ability of a given taste to serve as the conditioned stimulus (CS) in conditioned taste aversion (CTA) is dependent on its valence. Activity in anterior insula (aIC) Layer IV-VI pyramidal neurons projecting to the basolateral amygdala (BLA) is correlated with and necessary for CTA learning and retrieval, as well as the expression of neophobia toward novel tastants, but not learning taste familiarity. Yet, the cellular mechanisms underlying the updating of taste valence representation in this specific pathway are poorly understood. Here, using retrograde viral tracing and whole-cell patch-clamp electrophysiology in trained mice, we demonstrate that the intrinsic properties of deep-lying Layer IV-VI, but not superficial Layer I-III aIC-BLA neurons, are differentially modulated by both novelty and valence, reflecting the subjective predictability of taste valence arising from prior experience. These correlative changes in the profile of intrinsic properties of LIV-VI aIC-BLA neurons were detectable following both simple taste experiences, as well as following memory retrieval, extinction learning, and reinstatement.

Information theory characteristics improve the prediction of lithium response in bipolar disorder patients using a support vector machine classifier.

AIM: Bipolar disorder (BD) is a mood disorder with a high morbidity and death rate. Lithium (Li), a prominent mood stabilizer, is often used as a first-line treatment. However, clinical studies have shown that Li is fully effective in roughly 30% of BD patients. Our goal in this study was to use features derived from information theory to improve the prediction of the patient's response to Li as well as develop a diagnostic algorithm for the disorder. METHODS: We have performed electrophysiological recordings in patient-derived dentate gyrus (DG) granule neurons (from a total of 9 subjects) for three groups: 3 control individuals, 3 BD patients who respond to Li treatment (LR), and 3 BD patients who do not respond to Li treatment (NR). The recordings were analyzed by the statistical tools of modern information theory. We used a Support Vector Machine (SVM) and Random forest (RF) classifiers with the basic electrophysiological features with additional information theory features. RESULTS: Information theory features provided further knowledge about the distribution of the electrophysiological entities and the interactions between the different features, which improved classification schemes. These newly added features significantly improved our ability to distinguish the BD patients from the control individuals (an improvement from 60% to 74% accuracy) and LR from NR patients (an improvement from 81% to 99% accuracy). CONCLUSION: The addition of Information theory-derived features provides further knowledge about the distribution of the parameters and their interactions, thus significantly improving the ability to discriminate and predict the LRs from the NRs and the patients from the controls.

Current progress in understanding schizophrenia using genomics and pluripotent stem cells: A meta-analytical overview.

Schizophrenia (SCZ) is a complex, heritable and polygenic neuropsychiatric disease, which disables the patients as well as decreases their life expectancy and quality of life. Common and rare variants studies on SCZ subjects have provided >100 genomic loci that hold importance in the context of SCZ pathophysiology. Transcriptomic studies from clinical samples have informed about the differentially expressed genes (DEGs) and non-coding RNAs in SCZ patients. Despite these advancements, no causative genes for SCZ were found and hence SCZ is difficult to recapitulate in animal models. In the last decade, induced Pluripotent Stem Cells (iPSCs)-based models have helped in understanding the neural phenotypes of SCZ by studying patient iPSC-derived 2D neuronal cultures and 3D brain organoids. Here, we have aimed to provide a simplistic overview of the current progress and advancements after synthesizing the enormous literature on SCZ genetics and SCZ iPSC-based models. Although further understanding of SCZ genetics and pathophysiological mechanisms using these technological advancements is required, the recent approaches have allowed to delineate important cellular mechanisms and biological pathways affected in SCZ.

IQSEC2 mutation associated with epilepsy, intellectual disability, and autism results in hyperexcitability of patient-derived neurons and deficient synaptic transmission.

Mutations in the IQSEC2 gene are associated with drug-resistant, multifocal infantile and childhood epilepsy; autism; and severe intellectual disability (ID). We used induced pluripotent stem cell (iPSC) technology to obtain hippocampal neurons to investigate the neuropathology of IQSEC2-mediated disease. The neurons were characterized at three-time points during differentiation to assess developmental progression. We showed that immature IQSEC2 mutant dentate gyrus (DG) granule neurons were extremely hyperexcitable, exhibiting increased sodium and potassium currents compared to those of CRISPR-Cas9-corrected isogenic controls, and displayed dysregulation of genes involved in differentiation and development. Immature IQSEC2 mutant cultured neurons exhibited a marked reduction in the number of inhibitory neurons, which contributed further to hyperexcitability. As the mutant neurons aged, they became hypoexcitable, exhibiting reduced sodium and potassium currents and a reduction in the rate of synaptic and network activity, and showed dysregulation of genes involved in synaptic transmission and neuronal differentiation. Mature IQSEC2 mutant neurons were less viable than wild-type mature neurons and had reduced expression of surface AMPA receptors. Our studies provide mechanistic insights into severe infantile epilepsy and neurodevelopmental delay associated with this mutation and present a human model for studying IQSEC2 mutations in vitro.

Age separation dramatically reduces COVID-19 mortality rate in a computational model of a large population.

COVID-19 pandemic has caused a global lockdown in many countries throughout the world. Faced with a new reality, and until a vaccine or efficient treatment is found, humanity must figure out ways to keep the economy going, on one hand, while keeping the population safe, on the other hand, especially those that are susceptible to this virus. Here, we use a Watts-Strogatz network simulation, with parameters that were drawn from what is already known about the virus, to explore five different scenarios of partial lockdown release in two geographical locations with different age distributions. We find that separating age groups by reducing interactions between them protects the general population and reduces mortality rates. Furthermore, the addition of new connections within the same age group to compensate for the lost connections outside the age group still has a strong beneficial influence and reduces the total death toll by about 62%. While complete isolation from society may be the most protective scenario for the elderly population, it would have an emotional and possibly cognitive impact that might outweigh its benefit. Therefore, we propose creating age-related social recommendations or even restrictions, thereby allowing social connections while still offering strong protection for the older population.

Chamber-Specific Radiofrequency Lesion Dimension Estimation Using Novel Catheter-Based Tissue Interface Temperature Sensing: A Preclinical Assessment.

OBJECTIVES: This study sought to compare a novel lesion dimension estimation approach to actual measurements of lesion dimensions on necropsy in porcine atria and ventricles. BACKGROUND: An irrigated-tip, force-sensing radiofrequency catheter with 6 temperature (tip-tissue interface) sensors allows for assessment of lesion dimensions based on estimated tissue temperature. Lesion dimension assessment has not been attempted previously in atrial tissue. METHODS: Ablations were performed using this catheter in all chambers. Irrigated radiofrequency was delivered using 20 to 50 W for durations that ranged from 15 to 90 s with contact force ranging from 5 to 45 g to replicate a wide spectrum of clinical conditions. All swine were then sacrificed and lesions were identified and photographed. Three independent observers made offline measurements, which were then averaged to obtain lesion width and depth for comparison with estimated dimensions based on interface tissue temperature. RESULTS: In 9 swine, 54 atrial and 61 ventricular lesions were assessed. In the atria, the mean difference between the measured and estimated depth and width was 0.9 ± 0.74 mm and 1.2 ± 0.9 mm, respectively. Eighty percent of all lesions had a difference of ≤1.7 mm for depth and ≤1.74 mm for width. In the ventricle, the mean difference between the measured and estimated depth and width was 0.75 ± 0.6 mm and 1.66 ± 1.1 mm, respectively. Eighty percent of all lesions had a difference of ≤1.1 mm ventricular depth and ≤2.6 mm for width. CONCLUSIONS: Estimation of lesion dimensions can be achieved with clinically relevant accuracy using unique temperature signatures. These data have important implications for understanding the adequacy of lesion overlap and assessment of transmurality.