Tumor Microbiome Diversity and Composition Influence Pancreatic Cancer Outcomes.

Most patients diagnosed with resected pancreatic adenocarcinoma (PDAC) survive less than 5 years, but a minor subset survives longer. Here, we dissect the role of the tumor microbiota and the immune system in influencing long-term survival. Using 16S rRNA gene sequencing, we analyzed the tumor microbiome composition in PDAC patients with short-term survival (STS) and long-term survival (LTS). We found higher alpha-diversity in the tumor microbiome of LTS patients and identified an intra-tumoral microbiome signature (Pseudoxanthomonas-Streptomyces-Saccharopolyspora-Bacillus clausii) highly predictive of long-term survivorship in both discovery and validation cohorts. Through human-into-mice fecal microbiota transplantation (FMT) experiments from STS, LTS, or control donors, we were able to differentially modulate the tumor microbiome and affect tumor growth as well as tumor immune infiltration. Our study demonstrates that PDAC microbiome composition, which cross-talks to the gut microbiome, influences the host immune response and natural history of the disease.

Imaging dendritic cell functions.

Dendritic cells (DCs) are crucial for the appropriate initiation of adaptive immune responses. During inflammation, DCs capture antigens, mature, and migrate to lymphoid tissues to present foreign material to naïve T cells. These cells get activated and differentiate either into pathogen-specific cytotoxic CD8+ T cells that destroy infected cells or into CD4+ T helper cells that, among other effector functions, orchestrate antibody production by B cells. DC-mediated antigen presentation is equally important in non-inflammatory conditions. Here, DCs mediate induction of tolerance by presenting self-antigens or harmless environmental antigens and induce differentiation of regulatory T cells or inactivation of self-reactive immune cells. Detailed insights into the biology of DCs are, therefore, crucial for the development of novel vaccines as well as the prevention of autoimmune diseases. As in many other life science areas, our understanding of DC biology would be extremely restricted without bioimaging, a compilation of methods that visualize biological processes. Spatiotemporal tracking of DCs relies on various imaging tools, which not only enable insights into their positioning and migration within tissues or entire organs but also allow visualization of subcellular and molecular processes. This review aims to provide an overview of the imaging toolbox and to provide examples of diverse imaging techniques used to obtain fundamental insights into DC biology.

Neurocognition and NMDAR co-agonists pathways in individuals with treatment resistant first-episode psychosis: a 3-year follow-up longitudinal study.

This study aims to determine whether 1) individuals with treatment-resistant schizophrenia display early cognitive impairment compared to treatment-responders and healthy controls and 2) N-methyl-D-aspartate-receptor hypofunction is an underlying mechanism of cognitive deficits in treatment-resistance. In this case‒control 3-year-follow-up longitudinal study, n = 697 patients with first-episode psychosis, aged 18 to 35, were screened for Treatment Response and Resistance in Psychosis criteria through an algorithm that assigns patients to responder, limited-response or treatment-resistant category (respectively resistant to 0, 1 or 2 antipsychotics). Assessments at baseline: MATRICS Consensus Cognitive Battery; N-methyl-D-aspartate-receptor co-agonists biomarkers in brain by MRS (prefrontal glutamate levels) and plasma (D-serine and glutamate pathways key markers). Patients were compared to age- and sex-matched healthy controls (n = 114). Results: patient mean age 23, 27% female. Treatment-resistant (n = 51) showed lower scores than responders (n = 183) in processing speed, attention/vigilance, working memory, verbal learning and visual learning. Limited responders (n = 59) displayed an intermediary phenotype. Treatment-resistant and limited responders were merged in one group for the subsequent D-serine and glutamate pathway analyses. This group showed D-serine pathway dysregulation, with lower levels of the enzymes serine racemase and serine-hydroxymethyltransferase 1, and higher levels of the glutamate-cysteine transporter 3 than in responders. Better cognition was associated with higher D-serine and lower glutamate-cysteine transporter 3 levels only in responders; this association was disrupted in the treatment resistant group. Treatment resistant patients and limited responders displayed early cognitive and persistent functioning impairment. The dysregulation of NMDAR co-agonist pathways provides underlying molecular mechanisms for cognitive deficits in treatment-resistant first-episode psychosis. If replicated, our findings would open ways to mechanistic biomarkers guiding response-based patient stratification and targeting cognitive improvement in clinical trials.

Influence of oral microbiome on longitudinal patterns of oral mucositis severity in patients with squamous cell carcinoma of the head and neck.

BACKGROUND: This study investigated the influence of oral microbial features on the trajectory of oral mucositis (OM) in patients with squamous cell carcinoma of the head and neck. METHODS: OM severity was assessed and buccal swabs were collected at baseline, at the initiation of cancer treatment, weekly during cancer treatment, at the termination of cancer treatment, and after cancer treatment termination. The oral microbiome was characterized via the 16S ribosomal RNA V4 region with the Illumina platform. Latent class mixed-model analysis was used to group individuals with similar trajectories of OM severity. Locally estimated scatterplot smoothing was used to fit an average trend within each group and to assess the association between the longitudinal OM scores and longitudinal microbial abundances. RESULTS: Four latent groups (LGs) with differing patterns of OM severity were identified for 142 subjects. LG1 has an early onset of high OM scores. LGs 2 and 3 begin with relatively low OM scores until the eighth and 11th week, respectively. LG4 has generally flat OM scores. These LGs did not vary by treatment or clinical or demographic variables. Correlation analysis showed that the abundances of Bacteroidota, Proteobacteria, Bacteroidia, Gammaproteobacteria, Enterobacterales, Bacteroidales, Aerococcaceae, Prevotellaceae, Abiotrophia, and Prevotella_7 were positively correlated with OM severity across the four LGs. Negative correlation was observed with OM severity for a few microbial features: Abiotrophia and Aerococcaceae for LGs 2 and 3; Gammaproteobacteria and Proteobacteria for LGs 2, 3, and 4; and Enterobacterales for LGs 2 and 4. CONCLUSIONS: These findings suggest the potential to personalize treatment for OM. PLAIN LANGUAGE SUMMARY: Oral mucositis (OM) is a common and debilitating after effect for patients treated for squamous cell carcinoma of the head and neck. Trends in the abundance of specific microbial features may be associated with patterns of OM severity over time. Our findings suggest the potential to personalize treatment plans for OM via tailored microbiome interventions.

Easy NanoString nCounter data analysis with the NanoTube.

SUMMARY: The NanoTube is an open-source pipeline that simplifies the processing, quality control, normalization and analysis of NanoString nCounter gene expression data. It is implemented in an extensible R library, which performs a variety of gene expression analysis techniques and contains additional functions for integration with other R libraries performing advanced NanoString analysis techniques. Additionally, the NanoTube web application is available as a simple tool for researchers without programming expertise. AVAILABILITY AND IMPLEMENTATION: The NanoTube R package is available on Bioconductor under the GPL-3 license (https://www.bioconductor.org/packages/NanoTube/). The R-Shiny application can be downloaded at https://github.com/calebclass/Shiny-NanoTube, or a simplified version of this application can be run on all major browsers, at https://research.butler.edu/nanotube/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A unified mediation analysis framework for integrative cancer proteogenomics with clinical outcomes.

MOTIVATION: Multilevel molecular profiling of tumors and the integrative analysis with clinical outcomes have enabled a deeper characterization of cancer treatment. Mediation analysis has emerged as a promising statistical tool to identify and quantify the intermediate mechanisms by which a gene affects an outcome. However, existing methods lack a unified approach to handle various types of outcome variables, making them unsuitable for high-throughput molecular profiling data with highly interconnected variables. RESULTS: We develop a general mediation analysis framework for proteogenomic data that include multiple exposures, multivariate mediators on various scales of effects as appropriate for continuous, binary and survival outcomes. Our estimation method avoids imposing constraints on model parameters such as the rare disease assumption, while accommodating multiple exposures and high-dimensional mediators. We compare our approach to other methods in extensive simulation studies at a range of sample sizes, disease prevalence and number of false mediators. Using kidney renal clear cell carcinoma proteogenomic data, we identify genes that are mediated by proteins and the underlying mechanisms on various survival outcomes that capture short- and long-term disease-specific clinical characteristics. AVAILABILITY AND IMPLEMENTATION: Software is made available in an R package (https://github.com/longjp/mediateR). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Contributions of the Microbiome-Derived Metabolome for Risk Assessment and Prognostication of Pancreatic Cancer.

BACKGROUND: Increasing evidence implicates microbiome involvement in the development and progression of pancreatic ductal adenocarcinoma (PDAC). Studies suggest that reflux of gut or oral microbiota can lead to colonization in the pancreas, resulting in dysbiosis that culminates in release of microbial toxins and metabolites that potentiate an inflammatory response and increase susceptibility to PDAC. Moreover, microbe-derived metabolites can exert direct effector functions on precursors and cancer cells, as well as other cell types, to either promote or attenuate tumor development and modulate treatment response. CONTENT: The occurrence of microbial metabolites in biofluids thereby enables risk assessment and prognostication of PDAC, as well as having potential for design of interception strategies. In this review, we first highlight the relevance of the microbiome for progression of precancerous lesions in the pancreas and, using liquid chromatography-mass spectrometry, provide supporting evidence that microbe-derived metabolites manifest in pancreatic cystic fluid and are associated with malignant progression of intraductal papillary mucinous neoplasm(s). We secondly summarize the biomarker potential of microbe-derived metabolite signatures for (a) identifying individuals at high risk of developing or harboring PDAC and (b) predicting response to treatment and disease outcomes. SUMMARY: The microbiome-derived metabolome holds considerable promise for risk assessment and prognostication of PDAC.

Characterization of early psychosis patients carrying a genetic vulnerability to redox dysregulation: a computational analysis of mechanism-based gene expression profile in fibroblasts.

In view of its heterogeneity, schizophrenia needs new diagnostic tools based on mechanistic biomarkers that would allow early detection. Complex interaction between genetic and environmental risk factors may lead to NMDAR hypofunction, inflammation and redox dysregulation, all converging on oxidative stress. Using computational analysis, the expression of 76 genes linked to these systems, known to be abnormally regulated in schizophrenia, was studied in skin-fibroblasts from early psychosis patients and age-matched controls (N = 30), under additional pro-oxidant challenge to mimic environmental stress. To evaluate the contribution of a genetic risk related to redox dysregulation, we investigated the GAG trinucleotide polymorphism in the key glutathione (GSH) synthesizing enzyme, glutamate-cysteine-ligase-catalytic-subunit (gclc) gene, known to be associated with the disease. Patients and controls showed different gene expression profiles that were modulated by GAG-gclc genotypes in combination with oxidative challenge. In GAG-gclc low-risk genotype patients, a global gene expression dysregulation was observed, especially in the antioxidant system, potentially induced by other risks. Both controls and patients with GAG-gclc high-risk genotype (gclcGAG-HR) showed similar gene expression profiles. However, under oxidative challenge, a boosting of other antioxidant defense, including the master regulator Nrf2 and TRX systems was observed only in gclcGAG-HR controls, suggesting a protective compensation against the genetic GSH dysregulation. Moreover, RAGE (redox/inflammation interaction) and AGMAT (arginine pathway) were increased in the gclcGAG-HR patients, suggesting some additional risk factors interacting with this genotype. Finally, the use of a machine-learning approach allowed discriminating patients and controls with an accuracy up to 100%, paving the way towards early detection of schizophrenia.

Towards a youth mental health paradigm: a perspective and roadmap.

Most mental disorders have a typical onset between 12 and 25 years of age, highlighting the importance of this period for the pathogenesis, diagnosis, and treatment of mental ill-health. This perspective addresses interactions between risk and protective factors and brain development as key pillars accounting for the emergence of psychopathology in youth. Moreover, we propose that novel approaches towards early diagnosis and interventions are required that reflect the evolution of emerging psychopathology, the importance of novel service models, and knowledge exchange between science and practitioners. Taken together, we propose a transformative early intervention paradigm for research and clinical care that could significantly enhance mental health in young people and initiate a shift towards the prevention of severe mental disorders.

Variability and magnitude of brain glutamate levels in schizophrenia: a meta and mega-analysis.

Glutamatergic dysfunction is implicated in schizophrenia pathoaetiology, but this may vary in extent between patients. It is unclear whether inter-individual variability in glutamate is greater in schizophrenia than the general population. We conducted meta-analyses to assess (1) variability of glutamate measures in patients relative to controls (log coefficient of variation ratio: CVR); (2) standardised mean differences (SMD) using Hedges g; (3) modal distribution of individual-level glutamate data (Hartigan's unimodality dip test). MEDLINE and EMBASE databases were searched from inception to September 2022 for proton magnetic resonance spectroscopy (1H-MRS) studies reporting glutamate, glutamine or Glx in schizophrenia. 123 studies reporting on 8256 patients and 7532 controls were included. Compared with controls, patients demonstrated greater variability in glutamatergic metabolites in the medial frontal cortex (MFC, glutamate: CVR = 0.15, p < 0.001; glutamine: CVR = 0.15, p = 0.003; Glx: CVR = 0.11, p = 0.002), dorsolateral prefrontal cortex (glutamine: CVR = 0.14, p = 0.05; Glx: CVR = 0.25, p < 0.001) and thalamus (glutamate: CVR = 0.16, p = 0.008; Glx: CVR = 0.19, p = 0.008). Studies in younger, more symptomatic patients were associated with greater variability in the basal ganglia (BG glutamate with age: z = -0.03, p = 0.003, symptoms: z = 0.007, p = 0.02) and temporal lobe (glutamate with age: z = -0.03, p = 0.02), while studies with older, more symptomatic patients associated with greater variability in MFC (glutamate with age: z = 0.01, p = 0.02, glutamine with symptoms: z = 0.01, p = 0.02). For individual patient data, most studies showed a unimodal distribution of glutamatergic metabolites. Meta-analysis of mean differences found lower MFC glutamate (g = -0.15, p = 0.03), higher thalamic glutamine (g = 0.53, p < 0.001) and higher BG Glx in patients relative to controls (g = 0.28, p < 0.001). Proportion of males was negatively associated with MFC glutamate (z = -0.02, p < 0.001) and frontal white matter Glx (z = -0.03, p = 0.02) in patients relative to controls. Patient PANSS total score was positively associated with glutamate SMD in BG (z = 0.01, p = 0.01) and temporal lobe (z = 0.05, p = 0.008). Further research into the mechanisms underlying greater glutamatergic metabolite variability in schizophrenia and their clinical consequences may inform the identification of patient subgroups for future treatment strategies.

Healthcare provider perceptions and reported practices regarding opioid prescription for patients with chronic cancer pain.

PURPOSE: Data indicates that clinicians might be under-prescribing opioids for patients with chronic cancer pain, and this could impact adequate pain management. Few studies have sought to understand healthcare provider (HCP) perceptions and practices regarding the prescription of opioids for chronic cancer pain. We assessed HCP perceptions and practices regarding opioid prescription for patients with chronic cancer pain since the onset of the COVID-19 pandemic. METHODS: An anonymous cross-sectional survey was conducted among 186 HCPs who attended an opioid educational event in April 2021 and 2022. RESULTS: Sixty-one out of 143 (44%) opioid prescribers reported reluctance to prescribe opioids for chronic cancer pain. In a multivariate logistic model, younger participants (log OR - 0.04, 95% CI - 0.085, - 0.004; p = 0.033) and pain medicine clinicians (log OR - 1.89, CI - 3.931, - 0.286; p = 0.034) were less reluctant, whereas providers who worry about non-medical opioid use were more reluctant to prescribe opioids (log OR 1.58 95% CI 0.77-2.43; p < 0.001). Fifty-three out of 143 (37%) prescribers had experienced increased challenges regarding opioid dispensing at pharmacies, and 84/179 (47%) of all respondents reported similar experience by their patients. Fifty-four out of 178(30%) were aware of opioid-related harmful incidents to patients or their families, including incidents attributed to opioid misuse by a household or family member. CONCLUSION: A considerable number of opioid prescribers were reluctant to prescribe opioids for patients with chronic cancer pain. Many reported challenges regarding dispensing of opioids at the pharmacies. These may be unintended consequences of policies to address the opioid crisis. Future measures should focus on addressing regulatory barriers without undermining the gains already made to combat the opioid crisis.

A machine learning-based method for automatically identifying novel cells in annotating single-cell RNA-seq data.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) has been widely used to decompose complex tissues into functionally distinct cell types. The first and usually the most important step of scRNA-seq data analysis is to accurately annotate the cell labels. In recent years, many supervised annotation methods have been developed and shown to be more convenient and accurate than unsupervised cell clustering. One challenge faced by all the supervised annotation methods is the identification of the novel cell type, which is defined as the cell type that is not present in the training data, only exists in the testing data. Existing methods usually label the cells simply based on the correlation coefficients or confidence scores, which sometimes results in an excessive number of unlabeled cells. RESULTS: We developed a straightforward yet effective method combining autoencoder with iterative feature selection to automatically identify novel cells from scRNA-seq data. Our method trains an autoencoder with the labeled training data and applies the autoencoder to the testing data to obtain reconstruction errors. By iteratively selecting features that demonstrate a bi-modal pattern and reclustering the cells using the selected feature, our method can accurately identify novel cells that are not present in the training data. We further combined this approach with a support vector machine to provide a complete solution for annotating the full range of cell types. Extensive numerical experiments using five real scRNA-seq datasets demonstrated favorable performance of the proposed method over existing methods serving similar purposes. AVAILABILITY AND IMPLEMENTATION: Our R software package CAMLU is publicly available through the Zenodo repository (https://doi.org/10.5281/zenodo.7054422) or GitHub repository (https://github.com/ziyili20/CAMLU). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CNGPLD: case-control copy-number analysis using Gaussian process latent difference.

MOTIVATION: Cross-sectional analyses of primary cancer genomes have identified regions of recurrent somatic copy-number alteration, many of which result from positive selection during cancer formation and contain driver genes. However, no effective approach exists for identifying genomic loci under significantly different degrees of selection in cancers of different subtypes, anatomic sites or disease stages. RESULTS: CNGPLD is a new tool for performing case-control somatic copy-number analysis that facilitates the discovery of differentially amplified or deleted copy-number aberrations in a case group of cancer compared with a control group of cancer. This tool uses a Gaussian process statistical framework in order to account for the covariance structure of copy-number data along genomic coordinates and to control the false discovery rate at the region level. AVAILABILITY AND IMPLEMENTATION: CNGPLD is freely available at https://bitbucket.org/djhshih/cngpld as an R package. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Redox and Immune Signaling in Schizophrenia: New Therapeutic Potential.

Redox biology and immune signaling play major roles in the body, including in brain function. A rapidly growing literature also suggests that redox and immune abnormalities are implicated in neuropsychiatric conditions such as schizophrenia (SZ), bipolar disorder, autism, and epilepsy. In this article we review this literature, its implications for the pathophysiology of SZ, and the potential for development of novel treatment interventions targeting redox and immune signaling. Redox biology and immune signaling in the brain are complex and not fully understood; in addition, there are discrepancies in the literature, especially in patient-oriented studies. Nevertheless, it is clear that abnormalities arise in SZ from an interaction between genetic and environmental factors during sensitive periods of brain development, and these abnormalities disrupt local circuits and long-range connectivity. Interventions that correct these abnormalities may be effective in normalizing brain function in psychotic disorders, especially in early phases of illness.

Developmental oxidative stress leads to T-type Ca2+ channel hypofunction in thalamic reticular nucleus of mouse models pertinent to schizophrenia.

Impairment of parvalbumin interneurons induced by oxidative stress (OxS) is a "hub" on which converge several genetic and environmental risk factors associated with schizophrenia. In patients, this could be a mechanism leading to anomalies of the thalamic reticular nucleus (TRN) whose major neuronal population expresses parvalbumin. The TRN shapes the information flow within thalamo-cortical circuits. The low-threshold voltage-gated T-type Ca2+ (T-Ca2+) channels (CaV3.2, CaV3.3) contribute to the excitability and rhythmic bursting of TRN neurons which mediates cortical sleep spindles, known to be affected in schizophrenia. Here, we investigated the impact of OxS during postnatal development and adulthood on firing properties and T-Ca2+ channels of TRN neurons. In Gclm knock-out (KO) mice, which display GSH deficit and OxS in TRN, we found a reduction of T-Ca2+ current density in adulthood, but not at peripuberty. In KO adults, the decreased T-Ca2+ currents were accompanied with a decrease of CaV3.3 expression, and a shift towards more hyperpolarized membrane potentials for burst firing leading to less prominent bursting profile. In young KO mice, an early-life oxidative challenge precipitated the hypofunction of T-Ca2+ channels. This was prevented by a treatment with N-acetylcysteine. The concomitant presence of OxS and hypofunction of T-Ca2+ channels were also observed in TRN of a neurodevelopmental model relevant to psychosis (MAM mice). Collectively, these data indicate that OxS-mediated T-Ca2+ hypofunction in TRN begins early in life. This also points to T-Ca2+ channels as one target of antioxidant-based treatments aiming to mitigate abnormal thalamo-cortical communication and pathogenesis of schizophrenia.

Caught in vicious circles: a perspective on dynamic feed-forward loops driving oxidative stress in schizophrenia.

A growing body of evidence has emerged demonstrating a pathological link between oxidative stress and schizophrenia. This evidence identifies oxidative stress as a convergence point or "central hub" for schizophrenia genetic and environmental risk factors. Here we review the existing experimental and translational research pinpointing the complex dynamics of oxidative stress mechanisms and their modulation in relation to schizophrenia pathophysiology. We focus on evidence supporting the crucial role of either redox dysregulation, N-methyl-D-aspartate receptor hypofunction, neuroinflammation or mitochondria bioenergetics dysfunction, initiating "vicious circles" centered on oxidative stress during neurodevelopment. These processes would amplify one another in positive feed-forward loops, leading to persistent impairments of the maturation and function of local parvalbumin-GABAergic neurons microcircuits and myelinated fibers of long-range macrocircuitry. This is at the basis of neural circuit synchronization impairments and cognitive, emotional, social and sensory deficits characteristic of schizophrenia. Potential therapeutic approaches that aim at breaking these different vicious circles represent promising strategies for timely and safe interventions. In order to improve early detection and increase the signal-to-noise ratio for adjunctive trials of antioxidant, anti-inflammatory and NMDAR modulator drugs, a reverse translation of validated circuitry approach is needed. The above presented processes allow to identify mechanism based biomarkers guiding stratification of homogenous patients groups and target engagement required for successful clinical trials, paving the way towards precision medicine in psychiatry.

Alterations in TRN-anterodorsal thalamocortical circuits affect sleep architecture and homeostatic processes in oxidative stress vulnerable Gclm-/- mice.

Schizophrenia is associated with alterations of sensory integration, cognitive processing and both sleep architecture and sleep oscillations in mouse models and human subjects, possibly through changes in thalamocortical dynamics. Oxidative stress (OxS) damage, including inflammation and the impairment of fast-spiking gamma-aminobutyric acid neurons have been hypothesized as a potential mechanism responsible for the onset and development of schizophrenia. Yet, the link between OxS and perturbation of thalamocortical dynamics and sleep remains unclear. Here, we sought to investigate the effects of OxS on sleep regulation by characterizing the dynamics of thalamocortical networks across sleep-wake states in a mouse model with a genetic deletion of the modifier subunit of glutamate-cysteine ligase (Gclm knockout, KO) using high-density electrophysiology in freely-moving mice. We found that Gcml KO mice exhibited a fragmented sleep architecture and impaired sleep homeostasis responses as revealed by the increased NREM sleep latencies, decreased slow-wave activities and spindle rate after sleep deprivation. These changes were associated with altered bursting activity and firing dynamics of neurons from the thalamic reticularis nucleus, anterior cingulate and anterodorsal thalamus. Administration of N-acetylcysteine (NAC), a clinically relevant antioxidant, rescued the sleep fragmentation and spindle rate through a renormalization of local neuronal dynamics in Gclm KO mice. Collectively, these findings provide novel evidence for a link between OxS and the deficits of frontal TC network dynamics as a possible mechanism underlying sleep abnormalities and impaired homeostatic responses observed in schizophrenia.

Mitochondrial, exosomal miR137-COX6A2 and gamma synchrony as biomarkers of parvalbumin interneurons, psychopathology, and neurocognition in schizophrenia.

Early detection and intervention in schizophrenia requires mechanism-based biomarkers that capture neural circuitry dysfunction, allowing better patient stratification, monitoring of disease progression and treatment. In prefrontal cortex and blood of redox dysregulated mice (Gclm-KO ± GBR), oxidative stress induces miR-137 upregulation, leading to decreased COX6A2 and mitophagy markers (NIX, Fundc1, and LC3B) and to accumulation of damaged mitochondria, further exacerbating oxidative stress and parvalbumin interneurons (PVI) impairment. MitoQ, a mitochondria-targeted antioxidant, rescued all these processes. Translating to early psychosis patients (EPP), blood exosomal miR-137 increases and COX6A2 decreases, combined with mitophagy markers alterations, suggest that observations made centrally and peripherally in animal model were reflected in patients' blood. Higher exosomal miR-137 and lower COX6A2 levels were associated with a reduction of ASSR gamma oscillations in EEG. As ASSR requires proper PVI-related networks, alterations in miR-137/COX6A2 plasma exosome levels may represent a proxy marker of PVI cortical microcircuit impairment. EPP can be stratified in two subgroups: (a) a patients' group with mitochondrial dysfunction "Psy-D", having high miR-137 and low COX6A2 levels in exosomes, and (b) a "Psy-ND" subgroup with no/low mitochondrial impairment, including patients having miR-137 and COX6A2 levels in the range of controls. Psy-D patients exhibited more impaired ASSR responses in association with worse psychopathological status, neurocognitive performance, and global and social functioning, suggesting that impairment of PVI mitochondria leads to more severe disease profiles. This stratification would allow, with high selectivity and specificity, the selection of patients for treatments targeting brain mitochondria dysregulation and capture the clinical and functional efficacy of future clinical trials.

Gene set enrichment analysis of pathophysiological pathways highlights oxidative stress in psychosis.

Polygenic risk prediction remains an important aim of genetic association studies. Currently, the predictive power of schizophrenia polygenic risk scores (PRSs) is not large enough to allow highly accurate discrimination between cases and controls and thus is not adequate for clinical integration. Since PRSs are rarely used to reveal biological functions or to validate candidate pathways, to fill this gap, we investigated whether their predictive ability could be improved by building genome-wide (GW-PRSs) and pathway-specific PRSs, using distance- or expression quantitative trait loci (eQTLs)- based mapping between genetic variants and genes. We focused on five pathways (glutamate, oxidative stress, GABA/interneurons, neuroimmune/neuroinflammation and myelin) which belong to a critical hub of schizophrenia pathophysiology, centred on redox dysregulation/oxidative stress. Analyses were first performed in the Lausanne Treatment and Early Intervention in Psychosis Program (TIPP) study (n = 340, cases/controls: 208/132), a sample of first-episode of psychosis patients and matched controls, and then validated in an independent study, the epidemiological and longitudinal intervention program of First-Episode Psychosis in Cantabria (PAFIP) (n = 352, 224/128). Our results highlighted two main findings. First, GW-PRSs for schizophrenia were significantly associated with early psychosis status. Second, oxidative stress was the only significantly associated pathway that showed an enrichment in both the TIPP (p = 0.03) and PAFIP samples (p = 0.002), and exclusively when gene-variant linking was done using eQTLs. The results suggest that the predictive accuracy of polygenic risk scores could be improved with the inclusion of information from functional annotations, and through a focus on specific pathways, emphasizing the need to build and study functionally informed risk scores.

Bayesian hierarchical quantile regression with application to characterizing the immune architecture of lung cancer.

The successful development and implementation of precision immuno-oncology therapies requires a deeper understanding of the immune architecture at a patient level. T-cell receptor (TCR) repertoire sequencing is a relatively new technology that enables monitoring of T-cells, a subset of immune cells that play a central role in modulating immune response. These immunologic relationships are complex and are governed by various distributional aspects of an individual patient's tumor profile. We propose Bayesian QUANTIle regression for hierarchical COvariates (QUANTICO) that allows simultaneous modeling of hierarchical relationships between multilevel covariates, conducts explicit variable selection, estimates quantile and patient-specific coefficient effects, to induce individualized inference. We show QUANTICO outperforms existing approaches in multiple simulation scenarios. We demonstrate the utility of QUANTICO to investigate the effect of TCR variables on immune response in a cohort of lung cancer patients. At population level, our analyses reveal the mechanistic role of T-cell proportion on the immune cell abundance, with tumor mutation burden as an important factor modulating this relationship. At a patient level, we find several outlier patients based on their quantile-specific coefficient functions, who have higher mutational rates and different smoking history.