Transcription factor POU3F2 regulates TRIM8 expression contributing to cellular functions implicated in schizophrenia.

Schizophrenia (SCZ) is a neuropsychiatric disorder with aberrant expression of multiple genes. However, identifying its exact causal genes remains a considerable challenge. The brain-specific transcription factor POU3F2 (POU domain, class 3, transcription factor 2) has been recognized as a risk factor for SCZ, but our understanding of its target genes and pathogenic mechanisms are still limited. Here we report that POU3F2 regulates 42 SCZ-related genes in knockdown and RNA-sequencing experiments of human neural progenitor cells (NPCs). Among those SCZ-related genes, TRIM8 (Tripartite motif containing 8) is located in SCZ-associated genetic locus and is aberrantly expressed in patients with SCZ. Luciferase reporter and electrophoretic mobility shift assays (EMSA) showed that POU3F2 induces TRIM8 expression by binding to the SCZ-associated SNP (single nucleotide polymorphism) rs5011218, which affects POU3F2-binding efficiency at the promoter region of TRIM8. We investigated the cellular functions of POU3F2 and TRIM8 as they co-regulate several pathways related to neural development and synaptic function. Knocking down either POU3F2 or TRIM8 promoted the proliferation of NPCs, inhibited their neuronal differentiation, and impaired the excitatory synaptic transmission of NPC-derived neurons. These results indicate that POU3F2 regulates TRIM8 expression through the SCZ-associated SNP rs5011218, and both genes may be involved in the etiology of SCZ by regulating neural development and synaptic function.

Radiologists and Clinical Trials: Part 1 The Truth About Reader Disagreements.

The debate over human visual perception and how medical images should be interpreted have persisted since X-rays were the only imaging technique available. Concerns over rates of disagreement between expert image readers are associated with much of the clinical research and at times driven by the belief that any image endpoint variability is problematic. The deeper understanding of the reasons, value, and risk of disagreement are somewhat siloed, leading, at times, to costly and risky approaches, especially in clinical trials. Although artificial intelligence promises some relief from mistakes, its routine application for assessing tumors within cancer trials is still an aspiration. Our consortium of international experts in medical imaging for drug development research, the Pharma Imaging Network for Therapeutics and Diagnostics (PINTAD), tapped the collective knowledge of its members to ground expectations, summarize common reasons for reader discordance, identify what factors can be controlled and which actions are likely to be effective in reducing discordance. Reinforced by an exhaustive literature review, our work defines the forces that shape reader variability. This review article aims to produce a singular authoritative resource outlining reader performance's practical realities within cancer trials, whether they occur within a clinical or an independent central review.

Absence of coding somatic single nucleotide variants within well-known candidate genes in late-onset sporadic Alzheimer's Disease based on the analysis of multi-omics data.

Somatic mutations arise randomly or are induced by environmental factors, which may increase the risk of Alzheimer's disease (AD). Identifying somatic mutations in sporadic AD (SAD) may provide new insight of the disease. To evaluate the potential contribution of somatic single nucleotide variations (SNVs), particularly that of well-known AD-candidate genes, we investigated sequencing data sets from four platforms: whole-genome sequencing (WGS), deep whole-exome sequencing (WES) on paired brain and liver samples, RNA sequencing (RNA-seq), and single-cell whole-genome sequencing (scWGS) of brain samples from 16 AD patients and 16 non-AD individuals. We found that the average number, mean variant allele fractions (VAFs) and mutational signatures of somatic SNVs have similar distributions between AD brains and non-AD brains. We did not identify any somatic SNVs within coding regions of the APP, PSEN1, PSEN2, nor in APOE. This study shows that somatic SNVs within the coding region of AD-candidate genes are unlikely to be a common causal factor for SAD.

The relationship of tryptophan hydroxylase-2 methylation to early-life stress and its impact on short-term antidepressant treatment response.

INTRODUCTION: The gene tryptophan hydroxylase 2 (TPH2) encodes the associated rate-limiting enzyme in the biosynthesis 5-HT (serotonin). Early life stress and adult variability in TPH2 can correspond with diminished response to antidepressants for patients with major depressive disorder (MDD). DNA methylation is an epigenetic mechanism mediating gene expression, often tempered by environmental factors. Here, we investigate the influence of TPH2 methylation combined with stress on response to antidepressants within the first two weeks of treatment initiation. METHODS: 291 Han Chinese patients with major depressive disorder and 100 healthy controls comprised the study population. The Life Events Scale (LES) and the Childhood Trauma Questionnaire (CTQ) rated recent and early-life stress. The primary outcome equaled a reduction by ≥ 50% from the Hamilton Depression Rating Scale-17 (HAMD-17) after 2 weeks of treatment. The Illumina HiSeq platform assessed methylation status in 38 CpG sites located upstream and downstream of 11 TPH2 polymorphism sites. RESULTS: In 291 patients and 100 healthy controls, 3 CpG sites predict antidepressant treatment response per sex (TPH2-7-142, p=0.012; TPH2-1-43, p=0.033; TPH2-5-203, p=0.036). High-level CTQ scores relate significantly to DNA hypomethylation at CpG-site TPH2-8-237 in males (false discovery rate [FDR]-corrected p=0.038). Additionally, the interaction of hypermethylation in two CpG sites and elevated early-life stress may reduce antidepressant response (TPH2-5-203, FDR corrected p=0.010; TPH2-10-60, FDR corrected p=0.001). CONCLUSIONS: Our study suggests that TPH2 methylation and its interaction with early-life stress may impair antidepressant response, suggesting that pharmaco-epigenetic studies could identify epigenetic biomarkers for antidepressant response.

Brain Banks Spur New Frontiers in Neuropsychiatric Research and Strategies for Analysis and Validation.

Neuropsychiatric disorders affect hundreds of millions of patients and families worldwide. To decode the molecular framework of these diseases, many studies use human postmortem brain samples. These studies reveal brain-specific genetic and epigenetic patterns via high-throughput sequencing technologies. Identifying best practices for the collection of postmortem brain samples, analyzing such large amounts of sequencing data, and interpreting these results are critical to advance neuropsychiatry. We provide an overview of human brain banks worldwide, including progress in China, highlighting some well-known projects using human postmortem brain samples to understand molecular regulation in both normal brains and those with neuropsychiatric disorders. Finally, we discuss future research strategies, as well as state-of-the-art statistical and experimental methods that are drawn upon brain bank resources to improve our understanding of the agents of neuropsychiatric disorders.