xWAS analysis in neuropsychiatric disorders by integrating multi-molecular phenotype quantitative trait loci and GWAS summary data.

BACKGROUND: Integrating quantitative trait loci (QTL) data related to molecular phenotypes with genome-wide association study (GWAS) data is an important post-GWAS strategic approach employed to identify disease-associated molecular features. Various types of molecular phenotypes have been investigated in neuropsychiatric disorders. However, these findings pertaining to distinct molecular features are often independent of each other, posing challenges for having an overview of the mapped genes. METHODS: In this study, we comprehensively summarized published analyses focusing on four types of risk-related molecular features (gene expression, splicing transcriptome, protein abundance, and DNA methylation) across five common neuropsychiatric disorders. Subsequently, we conducted supplementary analyses with the latest GWAS dataset and corresponding deficient molecular phenotypes using Functional Summary-based Imputation (FUSION) and summary data-based Mendelian randomization (SMR). Based on the curated and supplemented results, novel reliable genes and their functions were explored. RESULTS: Our findings revealed that eQTL exhibited superior ability in prioritizing risk genes compared to the other QTL, followed by sQTL. Approximately half of the genes associated with splicing transcriptome, protein abundance, and DNA methylation were successfully replicated by eQTL-associated genes across all five disorders. Furthermore, we identified 436 novel reliable genes, which enriched in pathways related with neurotransmitter transportation such as synaptic, dendrite, vesicles, axon along with correlations with other neuropsychiatric disorders. Finally, we identified ten multiple molecular involved regulation patterns (MMRP), which may provide valuable insights into understanding the contribution of molecular regulation network targeting these disease-associated genes. CONCLUSIONS: The analyses prioritized novel and reliable gene sets related with five molecular features based on published and supplementary results for five common neuropsychiatric disorders, which were missed in the original GWAS analysis. Besides, the involved MMRP behind these genes could be given priority for further investigation to elucidate the pathogenic molecular mechanisms underlying neuropsychiatric disorders in future studies.

Functional role of immunoglobulin G as an oxytocin-carrier protein.

It has been long-time known that oxytocin in plasma is bound to a carrier protein, a common feature of circulating peptide hormones, however, the nature of such protein was uncertain. A recent study revealed that about 60% of oxytocin present in plasma is bound to immunoglobulin G (IgG) and that oxytocin-binding IgG plays a role of a functional oxytocin carrier protein. Here, we review the historical background and methodology leading to this discovery. Moreover, we review the data showing the functional role of oxytocin-binding IgG in the modulation of oxytocin signaling relevant to the regulation of motivated behavior and several neuropsychiatric disorders. Furthermore, the possible role of gut microbiota in the origin of such IgG is discussed and the relevant new therapeutic strategies for the enhancement of oxytocin signaling are presented.

Shared genetic mechanisms underlying association between sleep disturbances and depressive symptoms.

OBJECTIVES: Polygenic scores (PGS) for sleep disturbances and depressive symptoms in an epidemiological cohort were contrasted. The overlap between genes assigned to variants that compose the PGS predictions was tested to explore the shared genetic bases of sleep problems and depressive symptoms. METHODS: PGS analysis was performed on the São Paulo Epidemiologic Sleep Study (EPISONO, N = 1042), an adult epidemiological sample. A genome wide association study (GWAS) for depression grounded the PGS calculations for Beck Depression Index (BDI), while insomnia GWAS based the PGS for Insomnia Severity Index (ISI) and Pittsburg Sleep Quality Index (PSQI). Pearson's correlation was applied to contrast PGS and clinical scores. Fisher's Exact and Benjamin-Hochberg tests were used to verify the overlaps between PGS-associated genes and the pathways enriched among their intersections. RESULTS: All PGS models were significant when individuals were divided as cases or controls according to BDI (R2 = 1.2%, p = 0.00026), PSQI (R2 = 3.3%, p = 0.007) and ISI (R2 = 3.4%, p = 0.021) scales. When clinical scales were used as continuous variables, the PGS models for BDI (R2 = 1.5%, p = 0.0004) and PSQI scores (R2 = 3.3%, p = 0.0057) reached statistical significance. PSQI and BDI scores were correlated, and the same observation was applied to their PGS. Genes assigned to variants that compose the best-fit PGS predictions for sleep quality and depressive symptoms were significantly overlapped. Pathways enriched among the intersect genes are related to synapse function. CONCLUSIONS: The genetic bases of sleep quality and depressive symptoms are correlated; their implicated genes are significantly overlapped and converge on neural pathways. This data suggests that sleep complaints accompanying depressive symptoms are not secondary issues, but part of the core mental illness.

Neural cell-types and circuits linking thermoregulation and social behavior.

Understanding how social and affective behavioral states are controlled by neural circuits is a fundamental challenge in neurobiology. Despite increasing understanding of central circuits governing prosocial and agonistic interactions, how bodily autonomic processes regulate these behaviors is less resolved. Thermoregulation is vital for maintaining homeostasis, but also associated with cognitive, physical, affective, and behavioral states. Here, we posit that adjusting body temperature may be integral to the appropriate expression of social behavior and argue that understanding neural links between behavior and thermoregulation is timely. First, changes in behavioral states-including social interaction-often accompany changes in body temperature. Second, recent work has uncovered neural populations controlling both thermoregulatory and social behavioral pathways. We identify additional neural populations that, in separate studies, control social behavior and thermoregulation, and highlight their relevance to human and animal studies. Third, dysregulation of body temperature is linked to human neuropsychiatric disorders. Although body temperature is a "hidden state" in many neurobiological studies, it likely plays an underappreciated role in regulating social and affective states.

The impact of excessive maternal weight on the risk of neuropsychiatric disorders in offspring-a narrative review of clinical studies.

The global prevalence of overweight and obesity is a significant public health concern that also largely affects women of childbearing age. Human epidemiological studies indicate that prenatal exposure to excessive maternal weight or excessive gestational weight gain is linked to various neurodevelopmental disorders in children, including attention deficit hyperactivity disorder, autism spectrum disorder, internalizing and externalizing problems, schizophrenia, and cognitive/intellectual impairment. Considering that inadequate maternal body mass can induce serious disorders in offspring, it is important to increase efforts to prevent such outcomes. In this paper, we review human studies linking excessive maternal weight and the occurrence of mental disorders in children.

Overview: Research on the Genetic Architecture of the Developing Cerebral Cortex in Norms and Diseases.

The human brain is characterized by high cell numbers, diverse cell types with diverse functions, and intricate connectivity with an exceedingly broad surface of the cortex. Human-specific brain development was accomplished by a long timeline for maturation from the prenatal period to the third decade of life. The long timeline makes complicated architecture and circuits of human cerebral cortex possible, and it makes human brain vulnerable to intrinsic and extrinsic insults resulting in the development of variety of neuropsychiatric disorders. Unraveling the molecular and cellular processes underlying human brain development under the elaborate regulation of gene expression in a spatiotemporally specific manner, especially that of the cortex will provide a biological understanding of human cognition and behavior in health and diseases. Global research consortia and the advancing technologies in brain science including functional genomics equipped with emergent neuroinformatics such as single-cell multiomics, novel human models, and high-volume databases with high-throughput computation facilitate the biological understanding of the development of the human brain cortex. Knowing the process of interplay of the genome and the environment in cortex development will lead us to understand the human-specific cognitive function and its individual diversity. Thus, it is worthwhile to overview the recent progress in neurotechnology to foresee further understanding of the human brain and norms and diseases.

A cross-disease, pleiotropy-driven approach for therapeutic target prioritization and evaluation.

Cross-disease genome-wide association studies (GWASs) unveil pleiotropic loci, mostly situated within the non-coding genome, each of which exerts pleiotropic effects across multiple diseases. However, the challenge "W-H-W" (namely, whether, how, and in which specific diseases pleiotropy can inform clinical therapeutics) calls for effective and integrative approaches and tools. We here introduce a pleiotropy-driven approach specifically designed for therapeutic target prioritization and evaluation from cross-disease GWAS summary data, with its validity demonstrated through applications to two systems of disorders (neuropsychiatric and inflammatory). We illustrate its improved performance in recovering clinical proof-of-concept therapeutic targets. Importantly, it identifies specific diseases where pleiotropy informs clinical therapeutics. Furthermore, we illustrate its versatility in accomplishing advanced tasks, including pathway crosstalk identification and downstream crosstalk-based analyses. To conclude, our integrated solution helps bridge the gap between pleiotropy studies and therapeutics discovery.

The effectiveness of a dialogical family guidance intervention regarding child treatment response in families with a child with neurodevelopmental disorders.

BACKGROUND: Children with neurodevelopmental disorders (NDD) can have emotional and behavioral symptoms affecting not only the child, but the whole family. Since family members have a strong impact on each other, studies highlight the need to offer effective family interventions to strengthen the wellbeing of the family. The aim of the current study is to clarify whether there is a difference between parents` opinions regarding their child`s emotional and behavioral condition immediately after Dialogical Family Guidance (DFG) has ended and after a three and six month follow-up. METHOD: Fifty families with a child with NDD were randomized into two groups. Group 1 received DFG with an immediate starting point, and Group 2 received DFG after a three-month waiting period. Parent experiences of treatment response regarding their children`s emotional and behavioral symptoms were estimated before and after DFG using the parent version of the Strengths and Difficulties Questionnaire (SDQ-p) at baseline, and after three and six months. Additionally, comparisons between boys and girls, and the age of the child were analyzed. RESULTS: The total difficulties score between Group 1 and Group 2 showed no difference immediately after DFG, or after three months. Regarding subdomains boys had more peer problems than girls, and at baseline, children between 3 and 6 years appeared to have more conduct problems than children between 7 and 13 years. Subdomain prosocial behavior increased statistically significantly during the study period in Group 1. Other SDQ-p subdomains remained constant in both groups between baseline and three and six month follow-up. CONCLUSIONS: The result does not show any differences between parents` opinions regarding their child immediately after or three months after DFG regarding SDQ-p total difficulties scores in either group. The difference between younger and older children regarding conduct problems at baseline, and the difference between boys and girls regarding peer problems is worth paying attention to in the clinical setting. Because of the small sample, it is not possible to draw relevant conclusions regarding the intervention`s effect regarding the child`s mental health dimensions, gender, or age. Nevertheless, Dialogical family Guidance represents one intervention that can be used. TRIAL REGISTRATION: ClinicalTrials.gov NCT04892992 (retrospectively registered May 18th 2021).

Process management program to prevent falls in hospitalized patients with neuropsychiatric disorders: a quality improvement program.

BACKGROUND: Falls were among the most common adverse nursing events. The incidence of falls in patients with neuropsychiatric disorders was high, and the occurrence of falls not only caused physical and psychological harm to patients but also led to medical disputes. Therefore, interventions for falls prevention were essential, but evaluations of the intervention process were lacking. METHODS: In this study, a process management program to prevent falls based on the "structure-process-outcome" quality evaluation model was designed and applied to the clinical practice of falls prevention in hospitalized patients with neuropsychiatric disorders. The process quality evaluation checklist to prevent falls was used to supervise the implementation effect of intervention measures to prevent falls, identify the problems in the intervention measures, and make continuous improvements, to reduce the incidence of falls in such hospitalized patients as the final index. RESULTS: The incidence of inpatient falls decreased from 0.199‰ (0.199 per 1000 patient-days) to 0.101‰ (0.101 per 1000 patient-days) before and after the implementation of the process management program for 12 months, 24 months, and 36 months, respectively, and the difference was statistically significant (P<0.05). The probability of falls was reduced by 49% after 36 months of monitoring. Furthermore, the proportion of patients at high risk of falls exhibited a downward trend. CONCLUSION: This quality improvement program was feasible and effective at reducing falls in hospitalized patients with neuropsychiatric disorders. Therefore, attention should be given to monitoring process quality in the management of falls.

Causal effects of PM2.5 exposure on neuropsychiatric disorders and the mediation via gut microbiota: A Mendelian randomization study.

BACKGROUND: Growing evidence has revealed the impacts of exposure to fine particulate matter (PM2.5) and dysbiosis of gut microbiota on neuropsychiatric disorders, but the causal inference remains controversial due to residual confounders in observational studies. METHODS: This study aimed to examine the causal effects of exposure to PM2.5 on 4 major neuropsychiatric disorders (number of cases = 18,381 for autism spectrum disorder [ASD], 38,691 for attention deficit hyperactivity disorder [ADHD], 67,390 for schizophrenia, and 21,982 cases for Alzheimer's disease [AD]), and the mediation pathway through gut microbiota. Two-sample Mendelian randomization (MR) analyses were performed, in which genetic instruments were identified from genome-wide association studies (GWASs). The included GWASs were available from (1) MRC Integrative Epidemiology Unit (MRC-IEU) for PM2.5, PMcoarse, PM10, and NOX; (2) the Psychiatric Genomics Consortium (PGC) for ASD, ADHD, and schizophrenia; (3) MRC-IEU for AD; and (4) MiBioGen for gut microbiota. Multivariable MR analyses were conducted to adjust for exposure to NOX, PMcoarse, and PM10. We also examined the mediation effects of gut microbiota in the associations between PM2.5 exposure levels and neuropsychiatric disorders, using two-step MR analyses. RESULTS: Each 1 standard deviation (1.06 ug/m3) increment in PM2.5 concentrations was associated with elevated risk of ASD (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.00-2.02), ADHD (1.51, 1.15-1.98), schizophrenia (1.47, 1.15-1.87), and AD (1.57, 1.16-2.12). For all the 4 neurodevelopmental disorders, the results were robust under various sensitivity analyses, while the MR-Egger method yielded non-significant outcomes. The associations remained significant for all the 4 neuropsychiatric disorders after adjusting for PMcoarse, while non-significant after adjusting for NOX and PM10. The effects of PM2.5 exposure on ADHD and schizophrenia were partially mediated by Lachnospiraceae and Barnesiella, with the proportions ranging from 8.31% to 15.77%. CONCLUSIONS: This study suggested that exposure to PM2.5 would increase the risk of neuropsychiatric disorders, partially by influencing the profile of gut microbiota. Comprehensive regulations on air pollutants are needed to help prevent neuropsychiatric disorders.

Measurement of Developmental and Behavioral Concerns in Toddlers With Tuberous Sclerosis Complex.

BACKGROUND: The TAND (Tuberous Sclerosis Complex [TSC]-Associated Neuropsychiatric Disorders) Checklist was developed as a clinical screener for neurodevelopmental disorders in TSC. Most studies have described patterns in older children and adults. This study sought to better understand behavioral concerns as measured by the TAND Checklist in young children with TSC. METHODS: We examined patterns of caregiver responses to the TAND Checklist in 90 toddlers with TSC (12 to 23 months n = 60; 24 to 36 months n = 30) through data collected during baseline visits across two TSC early intervention studies. RESULTS: Over 90% of caregivers reported at least one behavioral concern related to TAND. The number of concerns increased with age. Delayed language was the most frequently reported concern across ages (12 to 23 months: 58.3%, 24 to 36 months: 86.7%). Questions related to behavioral concerns were largely relevant in this age range, but questions in other areas, such as neuropsychological or academic function, were not. CONCLUSIONS: TAND symptoms are very common in toddlers with TSC, and these symptoms may increase with age. The TAND Checklist is a useful tool for identifying behavioral concerns efficiently, but several items and sections are not suited to younger children. Results support the development of an abbreviated form of the TAND Checklist for toddlers.

Interactions between Ras and Rap signaling pathways during neurodevelopment in health and disease.

The Ras family of small GTPases coordinates tissue development by modulating cell proliferation, cell-cell adhesion, and cellular morphology. Perturbations of any of these key steps alter nervous system development and are associated with neurological disorders. While the underlying causes are not known, genetic mutations in Ras and Rap GTPase signaling pathways have been identified in numerous neurodevelopmental disorders, including autism spectrum, neurofibromatosis, intellectual disability, epilepsy, and schizophrenia. Despite diverse clinical presentations, intersections between these two signaling pathways may provide a better understanding of how deviations in neurodevelopment give rise to neurological disorders. In this review, we focus on presynaptic and postsynaptic functions of Ras and Rap GTPases. We highlight various roles of these small GTPases during synapse formation and plasticity. Based on genomic analyses, we discuss how disease-related mutations in Ras and Rap signaling proteins may underlie human disorders. Finally, we discuss how recent observations have identified molecular interactions between these pathways and how these findings may provide insights into the mechanisms that underlie neurodevelopmental disorders.

Mitochondria in the Central Nervous System in Health and Disease: The Puzzle of the Therapeutic Potential of Mitochondrial Transplantation.

Mitochondria, the energy suppliers of the cells, play a central role in a variety of cellular processes essential for survival or leading to cell death. Consequently, mitochondrial dysfunction is implicated in numerous general and CNS disorders. The clinical manifestations of mitochondrial dysfunction include metabolic disorders, dysfunction of the immune system, tumorigenesis, and neuronal and behavioral abnormalities. In this review, we focus on the mitochondrial role in the CNS, which has unique characteristics and is therefore highly dependent on the mitochondria. First, we review the role of mitochondria in neuronal development, synaptogenesis, plasticity, and behavior as well as their adaptation to the intricate connections between the different cell types in the brain. Then, we review the sparse knowledge of the mechanisms of exogenous mitochondrial uptake and describe attempts to determine their half-life and transplantation long-term effects on neuronal sprouting, cellular proteome, and behavior. We further discuss the potential of mitochondrial transplantation to serve as a tool to study the causal link between mitochondria and neuronal activity and behavior. Next, we describe mitochondrial transplantation's therapeutic potential in various CNS disorders. Finally, we discuss the basic and reverse-translation challenges of this approach that currently hinder the clinical use of mitochondrial transplantation.

Mendelian randomization analysis using GWAS and eQTL data to investigate the relationship between chronotype and neuropsychiatric disorders and their molecular basis.

Chronotype is a proxy sleep measure that has been associated with neuropsychiatric disorders. By investigating how chronotype influences risk for neuropsychiatric disorders and vice versa, we may identify modifiable risk factors for each phenotype. Here we used Mendelian randomization (MR), to explore causal effects by (1) studying the causal relationships between neuropsychiatric disorders and chronotype and (2) characterizing the genetic components of these phenotypes. Firstly, we investigated if a causal role exists between five neuropsychiatric disorders and chronotype using the largest genome-wide association studies (GWAS) available. Secondly, we integrated data from expression quantitative trait loci (eQTLs) to investigate the role of gene expression alterations on these phenotypes. Evening chronotype was causal for increased risk of schizophrenia and autism spectrum disorder and schizophrenia was causal for a tendency toward evening chronotype. We identified 12 eQTLs where gene expression changes in brain or blood were causal for one of the phenotypes, including two eQTLs for SNX19 in hippocampus and hypothalamus that were causal for schizophrenia. These findings provide important evidence for the complex, bidirectional relationship that exists between a sleep-based phenotype and neuropsychiatric disorders, and use gene expression data to identify causal roles for genes at associated loci.

Perineuronal Nets in the CNS: Architects of Memory and Potential Therapeutic Target in Neuropsychiatric Disorders.

The extracellular matrix (ECM) within the brain possesses a distinctive composition and functionality, influencing a spectrum of physiological and pathological states. Among its constituents, perineuronal nets (PNNs) are unique ECM structures that wrap around the cell body of many neurons and extend along their dendrites within the central nervous system (CNS). PNNs are pivotal regulators of plasticity in CNS, both during development and adulthood stages. Characterized by their condensed glycosaminoglycan-rich structures and heterogeneous molecular composition, PNNs not only offer neuroprotection but also participate in signal transduction, orchestrating neuronal activity and plasticity. Interfering with the PNNs in adult animals induces the reactivation of critical period plasticity, permitting modifications in neuronal connections and promoting the recovery of neuroplasticity following spinal cord damage. Interestingly, in the adult brain, PNN expression is dynamic, potentially modulating plasticity-associated states. Given their multifaceted roles, PNNs have emerged as regulators in the domains of learning, memory, addiction behaviors, and other neuropsychiatric disorders. In this review, we aimed to address how PNNs contribute to the memory processes in physiological and pathological conditions.

Impaired oxysterol-liver X receptor signaling underlies aberrant cortical neurogenesis in a stem cell model of neurodevelopmental disorder.

The mechanisms by which genomic risks contribute to the onset of neuropsychiatric conditions remain a key challenge and a prerequisite for successful development of effective therapies. 15q11.2 copy number variation (CNV) containing the CYFIP1 gene is associated with autism and schizophrenia. Using stem cell models, we show that 15q11.2 deletion (15q11.2del) and CYFIP1 loss of function (CYFIP1-LoF) lead to premature neuronal differentiation, while CYFIP1 gain of function (CYFIP1-GoF) favors neural progenitor maintenance. CYFIP1 dosage changes led to dysregulated cholesterol metabolism and altered levels of 24S,25-epoxycholesterol, which can mimic the 15q11.2del and CYFIP1-LoF phenotypes by promoting cortical neuronal differentiation and can restore the impaired neuronal differentiation of CYFIP1-GoF neural progenitors. Moreover, the neurogenic activity of 24S,25-epoxycholesterol is lost following genetic deletion of liver X receptor (LXRß), while compound deletion of LXRß in CYFIP1-/- background rescued their premature neurogenesis. This work delineates LXR-mediated oxysterol regulation of neurogenesis as a pathological mechanism in neural cells carrying 15q11.2 CNV and provides a potential target for therapeutic strategies for associated disorders.

Analysis of EEG microstates as biomarkers in neuropsychological processes - Review.

Microstate analysis is a spatiotemporal method where instantaneous scalp potential topography represents the current state of the brain. The temporal evolution of these scalp topographies gives an understanding of quasi-stable periods of long-range coherence between distant electrodes, reflecting functional coordination within large-scale cortical networks. It has been proven potential in identification and characterization of neurophysiological indicators associated with neuropsychiatric conditions. Changes in microstates connected to symptoms and cognitive impairments of neuropsychiatric conditions. It is useful in the study of cognitive processes and disorders related to memory. Researchers may probe into the relationships between microstates and other cognitive processes, such as memory retrieval and encoding. This is a tool for clinicians to enhance the precision of diagnosis and inform possibilities for treatment by acquiring information regarding individual diversity in microstates could lead to tailored medical methods. Customizing treatment according to a patient's microstate patterns could improve the efficacy of treatment. The papers selected for the review span a broad-spectrum including memory related disorders, psychiatry and neurological disorders. A section in the review article has been dedicated to source localization of EEG microstates. The selection of review papers shed light on the importance and huge potential of application of EEG microstate analysis in various neuropsychological processes. The review concludes with the need for standardization of microstate analysis. It suggests the incorporation of widely accepted machine learning techniques for increasing the accuracy, reliability and acceptability of microstate analysis as reliable biomarkers for neurological conditions in the future.

Correlation of telomere length in brain tissue with peripheral tissues in living human subjects.

Telomeres are important to chromosomal stability, and changes in their length correlate with disease, potentially relevant to brain disorders. Assessing telomere length in human brain is invasive, but whether peripheral tissue telomere length correlates with that in brain is not known. Saliva, buccal, blood, and brain samples were collected at time points before, during, and after subjects undergoing neurosurgery (n = 35) for intractable epilepsy. DNA was isolated from samples and average telomere length assessed by qPCR. Correlations of telomere length between tissue samples were calculated across subjects. When data were stratified by sex, saliva telomere length correlated with brain telomere length in males only. Buccal telomere length correlated with brain telomere length when males and females were combined. These findings indicate that in living subjects, telomere length in peripheral tissues variably correlates with that in brain and may be dependent on sex. Peripheral tissue telomere length may provide insight into brain telomere length, relevant to assessment of brain disorder pathophysiology.

The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration.

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.

Large-scale animal model study uncovers altered brain pH and lactate levels as a transdiagnostic endophenotype of neuropsychiatric disorders involving cognitive impairment.

Increased levels of lactate, an end-product of glycolysis, have been proposed as a potential surrogate marker for metabolic changes during neuronal excitation. These changes in lactate levels can result in decreased brain pH, which has been implicated in patients with various neuropsychiatric disorders. We previously demonstrated that such alterations are commonly observed in five mouse models of schizophrenia, bipolar disorder, and autism, suggesting a shared endophenotype among these disorders rather than mere artifacts due to medications or agonal state. However, there is still limited research on this phenomenon in animal models, leaving its generality across other disease animal models uncertain. Moreover, the association between changes in brain lactate levels and specific behavioral abnormalities remains unclear. To address these gaps, the International Brain pH Project Consortium investigated brain pH and lactate levels in 109 strains/conditions of 2294 animals with genetic and other experimental manipulations relevant to neuropsychiatric disorders. Systematic analysis revealed that decreased brain pH and increased lactate levels were common features observed in multiple models of depression, epilepsy, Alzheimer's disease, and some additional schizophrenia models. While certain autism models also exhibited decreased pH and increased lactate levels, others showed the opposite pattern, potentially reflecting subpopulations within the autism spectrum. Furthermore, utilizing large-scale behavioral test battery, a multivariate cross-validated prediction analysis demonstrated that poor working memory performance was predominantly associated with increased brain lactate levels. Importantly, this association was confirmed in an independent cohort of animal models. Collectively, these findings suggest that altered brain pH and lactate levels, which could be attributed to dysregulated excitation/inhibition balance, may serve as transdiagnostic endophenotypes of debilitating neuropsychiatric disorders characterized by cognitive impairment, irrespective of their beneficial or detrimental nature.