Precision Psychiatry

History of suicide attempt (SA) is the strongest predictor of a new SA and suicide. It is primordial to identify additional risk factors of suicide re-attempt. The aim of this study was to identify risk factors of suicide re-attempt in patients with recent SA followed for 2 years.

We provide here the first bottom-up review of the lived experience of mental disorders in adolescents co-designed, co-conducted and co-written by experts by experience and academics. We screened first-person accounts within and outside the medical field, and discussed them in collaborative workshops involving numerous experts by experience - representing different genders, ethnic and cultural backgrounds, and continents - and their family members and carers. Subsequently, the material was enriched by phenomenologically informed perspectives and shared with all collaborators. The inner subjective experience of adolescents is described for mood disorders, psychotic disorders, attention-deficit/hyperactivity disorder, autism spectrum disorders, anxiety disorders, eating disorders, externalizing disorders, and self-harm behaviors. The recollection of individuals' past histories also indexes the prodromal (often transdiagnostic) features predating the psychiatric diagnosis. The experience of adolescents with mental disorders in the wider society is described with respect to their family, their school and peers, and the social and cultural context. Furthermore, their lived experience of mental health care is described with respect to receiving a diagnosis of mental disorder, accessing mental health support, receiving psychopharmacological treatment, receiving psychotherapy, experiencing peer support and mental health activism, and achieving recovery. These findings can impact clinical practice, research, and the whole society. We hope that this co-designed, co-conducted and co-written journey can help us maintain our commitment to protecting adolescents' fragile mental health, and can help them develop into a healthy, fulfilling and contributing adult life.

Psychotic depression (PD) is a severe mental disorder leading to functional disability and high risk of suicide, but very little is known about the comparative effectiveness of medications used in its maintenance treatment. The objective of this study was to investigate the comparative effectiveness of specific antipsychotics and antidepressants, and their combinations, on the risk of psychiatric hospitalization among persons with PD in routine care. Persons aged 16-65 years with a first-time diagnosis of PD were identified from Finnish (years 2000-2018) and Swedish (years 2006-2021) nationwide registers of inpatient care, specialized outpatient care, sickness absence, and disability pension. The main exposures were specific antipsychotics and antidepressants, and the main outcome measure was psychiatric hospitalization as a marker of severe relapse. The risk of hospitalization associated with periods of use vs. non-use of medications (expressed as adjusted hazard ratio, aHR) was assessed by a within-individual design, using each individual as his/her own control, and analyzed with stratified Cox models. The two national cohorts were first analyzed separately, and then combined using a fixed-effect meta-analysis. The Finnish cohort included 19,330 persons (mean age: 39.8±14.7 years; 57.9% women) and the Swedish cohort 13,684 persons (mean age: 41.3±14.0 years; 53.5% women). Individual antidepressants associated with a decreased risk of relapse vs. non-use of antidepressants were bupropion (aHR=0.73, 95% CI: 0.63-0.85), vortioxetine (aHR=0.78, 95% CI: 0.63-0.96) and venlafaxine (aHR=0.92, 95% CI: 0.86-0.98). Any long-acting injectable antipsychotic (LAI) (aHR=0.60, 95% CI: 0.45-0.80) and clozapine (aHR=0.72, 95% CI: 0.57-0.91) were associated with a decreased risk of relapse vs. non-use of antipsychotics. Among monotherapies, only vortioxetine (aHR=0.67, 95% CI: 0.47-0.95) and bupropion (aHR=0.71, 95% CI: 0.56-0.89) were associated with a significantly decreased risk of relapse vs. non-use of both antidepressants and antipsychotics. In an exploratory analysis of antidepressant-antipsychotic combinations, a decreased relapse risk was found for amitriptyline-olanzapine (aHR=0.45, 95% CI: 0.28-0.71), sertraline-quetiapine (aHR=0.79, 95% CI: 0.67-0.93) and venlafaxine-quetiapine (aHR=0.82, 95% CI: 0.73-0.91) vs. non-use of antidepressants and antipsychotics. Benzodiazepines and related drugs (aHR=1.29, 95% CI: 1.24-1.34) and mirtazapine (aHR=1.17, 95% CI: 1.07-1.29) were associated with an increased risk of relapse. These data indicate that, in the maintenance treatment of PD, bupropion, vortioxetine, venlafaxine, any LAI, clozapine, and only few specific antidepressant-antipsychotic combinations are associated with a decreased risk of relapse. These findings challenge the current recommendation by treatment guidelines to combine an antipsychotic with an antidepressant (without further specification) as standard treatment in PD.

Facial expression is a critical form of nonverbal social communication which promotes emotional exchange and affiliation among humans. Facial expressions are generated via precise contraction of the facial muscles, guided by sensory feedback. While the neural pathways underlying facial motor control are well characterized in humans and primates, it remains unknown how tactile and proprioceptive information reaches these pathways to guide facial muscle contraction. Thus, despite the importance of facial expressions for social functioning, little is known about how they are generated as a unique sensorimotor behavior. In this review, we highlight current knowledge about sensory feedback from the face and how it is distinct from other body regions. We describe connectivity between the facial sensory and motor brain systems, and call attention to the other brain systems which influence facial expression behavior, including vision, gustation, emotion, and interoception. Finally, we petition for more research on the sensory basis of facial expressions, asserting that incomplete understanding of sensorimotor mechanisms is a barrier to addressing atypical facial expressivity in clinical populations.

Defining homogeneous subgroups of bipolar disorder (BD) is a major goal in personalized psychiatry and research. According to the neurodevelopmental theory, age at onset may be a key variable. As potential trait markers of neurodevelopment, cognitive and functional impairment should be greater in the early form of the disease, particularly type 1 BD (BD I). The age at onset was assessed in a multicenter, observational sample of 4190 outpatients with BD. We used a battery of neuropsychological tests to assess six domains of cognition. Functioning was measured using the Functioning Assessment Short Test (FAST). We studied the potential moderation of the type of BD on the associations between the age at onset and cognitive and functioning in a subsample of 2072 euthymic participants, controlling for potential clinical and socio-demographic covariates. Multivariable analyses showed cognition to not be impaired in individuals with early (21-30 years) and very early-life (before 14 years) onset of BD. Functioning was equivalent between individuals with early and midlife-onset of BD II and NOS but better for individuals with early onset of BD I. In contrast, functioning was not worse in individuals with very early-onset BD I but worse in those with very early-onset BD II and NOS. Early-life onset BDs were not characterized by poorer cognition and functioning. Our results do not support the neurodevelopmental view that a worse cognitive prognosis characterizes early-life onset BD. This study suggests that functional remediation may be prioritized for individuals with midlife-onset BD I and very early life onset BD 2 and NOS.

Amidst the current global surge in physician burnout, a compelling need arises for precisely targeted research and interventions that cater to specific contexts, illuminating a path towards professional well-being. This brief communication analyses recent studies on physician burnout in Oman, critically evaluating the findings, cultural factors, methodological limitations and future growth opportunities. Distinct elements of Omani culture, encompassing attitudes towards mental illness, gender roles and patient expectations, can distinctly influence how burnout presents in this population. Advanced mixed-methods research integrating cultural insights, biomarkers and longitudinal tracking is needed to characterise burnout in Omani physicians. The findings can play a significant role in developing comprehensive interventions, at both a systemic and an individual level, that promote well-being of physicians while specifically aligning with the cultural values of Oman.

The interplay of physical activity (PA) with affective well-being (AWB) is highly critical to both health behaviors and health outcomes. Current prominent theories presume AWB to be crucial for PA maintenance, and PA is evidenced to foster mental health. However, thus far, PA-AWB associations have mainly been researched in laboratory settings and with interventional designs, but the everyday life perspective had not been focused on, mostly due to technological limitations. In the course of digitization, the number of studies using device-based methods to research the within-subject association of physical activity and affective well-being (PA-AWB) under ecological valid conditions increased rapidly, but a recent comprehensive systematic review of evidence across populations, age groups, and distinct AWB components remained inconclusive.

Complex grief patterns are associated with significant suffering, functional impairments, health and mental health problems, and increased healthcare use. This burden may be even more pronounced among veterans. Behavioral Activation and Therapeutic Exposure (BATE-G) and Cognitive Therapy for Grief (CT-G) are two evidence-based interventions for grief. The goal of this study was to use a precision medicine approach to develop a personalized treatment rule to optimize assignment among these psychotherapies.

Both impulsivity and compulsivity have been identified as risk factors for problematic use of the internet (PUI). Yet little is known about the relationship between impulsivity, compulsivity and individual PUI symptoms, limiting a more precise understanding of mechanisms underlying PUI.

We aimed to investigate the association between financial toxicity (FT) and the health-related quality of life profile of long-term survivors of acute promyelocytic leukaemia (APL) treated within a universal healthcare system.

When studies use different scales to measure continuous outcomes, standardised mean differences (SMD) are required to meta-analyse the data. However, outcomes are often reported as endpoint or change from baseline scores. Combining corresponding SMDs can be problematic and available guidance advises against this practice. We aimed to examine the impact of combining the two types of SMD in meta-analyses of depression severity. We used individual participant data on pharmacological interventions (89 studies, 27,409 participants) and internet-delivered cognitive behavioural therapy (iCBT; 61 studies, 13,687 participants) for depression to compare endpoint and change from baseline SMDs at the study level. Next, we performed pairwise (PWMA) and network meta-analyses (NMA) using endpoint SMDs, change from baseline SMDs, or a mixture of the two. Study-specific SMDs calculated from endpoint and change from baseline data were largely similar, although for iCBT interventions 25% of the studies at 3 months were associated with important differences between study-specific SMDs (median 0.01, IQR -0.10, 0.13) especially in smaller trials with baseline imbalances. However, when pooled, the differences between endpoint and change SMDs were negligible. Pooling only the more favourable of the two SMDs did not materially affect meta-analyses, resulting in differences of pooled SMDs up to 0.05 and 0.13 in the pharmacological and iCBT datasets, respectively. Our findings have implications for meta-analyses in depression, where we showed that the choice between endpoint and change scores for estimating SMDs had immaterial impact on summary meta-analytic estimates. Future studies should replicate and extend our analyses to fields other than depression.

Psychiatric disorders are highly heritable yet polygenic, potentially involving hundreds of risk genes. Genome-wide association studies have identified hundreds of genomic susceptibility loci with susceptibility to psychiatric disorders; however, the contribution of these loci to the underlying psychopathology and etiology remains elusive. Here we generated deep human brain proteomics data by quantifying 11,608 proteins across 268 subjects using 11-plex tandem mass tag coupled with two-dimensional liquid chromatography-tandem mass spectrometry. Our analysis revealed 788 cis-acting protein quantitative trait loci associated with the expression of 883 proteins at a genome-wide false discovery rate <5%. In contrast to expression at the transcript level and complex diseases that are found to be mainly influenced by noncoding variants, we found protein expression level tends to be regulated by non-synonymous variants. We also provided evidence of 76 shared regulatory signals between gene expression and protein abundance. Mediation analysis revealed that for most (88%) of the colocalized genes, the expression levels of their corresponding proteins are regulated by cis-pQTLs via gene transcription. Using summary data-based Mendelian randomization analysis, we identified 4 proteins and 19 genes that are causally associated with schizophrenia. We further integrated multiple omics data with network analysis to prioritize candidate genes for schizophrenia risk loci. Collectively, our findings underscore the potential of proteome-wide linkage analysis in gaining mechanistic insights into the pathogenesis of psychiatric disorders.

Although both psychological resilience and social support are widely believed to be effective in alleviating post-traumatic psychiatric symptoms in individuals with traumatic events, there has been a lack of comparative analysis of their intervention effects on different post-traumatic psychiatric symptoms. Furthermore, previous studies have mostly failed to control for potential confounding effects caused by different traumatic events.

Identification of the predominant polarity, i.e. hypomanic/manic (mPP) or depressive predominant polarity (dPP), might help clinicians to improve personalised management of bipolar disorder.

Hair has become an increasingly valuable medium to investigate the association between chronic stress, stable differences in systemic cortisol secretion and later health. Assessing cortisol in hair has many advantages, notably its non-invasive and retrospective nature, the need for a single biospecimen and convenient storage until analysis. However, few studies offered empirical evidence documenting the long-term temporal stability of hair cortisol concentration (HCC) prior to analysis, especially in humans. Yet, knowing how long hair samples can be stored without compromising the accuracy of cortisol measurement is of crucial importance when planning data collection and analysis. This study examined the stability of HCC in hair samples assayed twice, five years apart.

Digital approaches may be helpful in augmenting care to address unmet mental health needs, particularly for schizophrenia and severe mental illness (SMI).

Sensory abnormalities are observed in ~90% of individuals with autism spectrum disorders (ASD), but the underlying mechanisms are poorly understood. GluN2B, an NMDA receptor subunit that regulates long-term depression and circuit refinement during brain development, has been strongly implicated in ASD, but whether GRIN2B mutations lead to sensory abnormalities remains unclear. Here, we report that Grin2b-mutant mice show behavioral sensory hypersensitivity and brain hyperconnectivity associated with the anterior cingulate cortex (ACC). Grin2b-mutant mice with a patient-derived C456Y mutation (Grin2b) show sensory hypersensitivity to mechanical, thermal, and electrical stimuli through supraspinal mechanisms. c-fos and functional magnetic resonance imaging indicate that the ACC is hyperactive and hyperconnected with other brain regions under baseline and stimulation conditions. ACC pyramidal neurons show increased excitatory synaptic transmission. Chemogenetic inhibition of ACC pyramidal neurons normalizes ACC hyperconnectivity and sensory hypersensitivity. These results suggest that GluN2B critically regulates ASD-related cortical connectivity and sensory brain functions.

Computational modeling of behavior is increasingly being adopted as a standard methodology in psychology, cognitive neuroscience, and computational psychiatry. This approach involves estimating parameters in a computational (or cognitive) model that represents the computational processes of the underlying behavior. In this approach, the reliability of the parameter estimates is an important issue. The use of hierarchical (Bayesian) approaches, which place a prior on each model parameter of the individual participants, is thought to improve the reliability of the parameters. However, the characteristics of reliability in parameter estimates, especially when individual-level priors are assumed, as in hierarchical models, have not yet been fully discussed. Furthermore, the suitability of different reliability measures for assessing parameter reliability is not thoroughly understood. In this study, we conduct a systematic examination of these issues through theoretical analysis and numerical simulations, focusing specifically on reinforcement learning models. We note that the heterogeneity in the estimation precision of individual parameters, particularly with priors, can skew reliability measures toward individuals with higher precision. We further note that there are two factors that reduce reliability, namely estimation error and intersession variation in the true parameters, and we discuss how to evaluate these factors separately. Based on the considerations of this study, we present several recommendations and cautions for assessing the reliability of the model parameters.

Duchenne muscular dystrophy (DMD) is an intractable X-linked muscular dystrophy caused by mutations in the DMD gene. While many animal models have been used to study the disease, translating findings to humans has been challenging. Microminipigs, with their pronounced physiological similarity to humans and notably compact size amongst pig models, could offer a more representative model for human diseases. Here, we accomplished precise DMD modification in microminipigs by co-injecting embryos with Cas9 protein and a single-guide RNA targeting exon 23 of DMD. The DMD-edited microminipigs exhibited pronounced clinical phenotypes, including perturbed locomotion and body-wide skeletal muscle weakness and atrophy, alongside augmented serum creatine kinase levels. Muscle weakness was observed as of one month of age, respiratory and cardiac dysfunctions emerged by the sixth month, and the maximum lifespan was 29.9 months. Histopathological evaluations confirmed dystrophin deficiency and pronounced dystrophic pathology in the skeletal and myocardial tissues, demonstrating that these animals are an unprecedented model for studying human DMD. The model stands as a distinct and crucial tool in biomedical research, offering deep understanding of disease progression and enhancing therapeutic assessments, with potential to influence forthcoming treatment approaches.

Patients with schizophrenia have substantial comorbidity that contributes to reduced life expectancy of 10 to 20 years. Identifying modifiable comorbidities could improve rates of premature mortality. Conditions that frequently co-occur but lack shared genetic risk with schizophrenia are more likely to be products of treatment, behavior, or environmental factors and therefore are enriched for potentially modifiable associations.

Social memory has been developed in humans and other animals to recognize familiar conspecifics and is essential for their survival and reproduction. Here, we demonstrated that parvalbumin-positive neurons in the sensory thalamic reticular nucleus (sTRN) are necessary and sufficient for mice to memorize conspecifics. sTRN neurons receiving glutamatergic projections from the posterior parietal cortex (PPC) transmit individual information by inhibiting the parafascicular thalamic nucleus (PF). Mice in which the PPC→sTRN→PF circuit was inhibited exhibited a disrupted ability to discriminate familiar conspecifics from novel ones. More strikingly, a subset of sTRN neurons with high electrophysiological excitability and complex dendritic arborizations is involved in the above corticothalamic pathway and stores social memory. Single-cell RNA sequencing revealed the biochemical basis of these subset cells as a robust activation of protein synthesis. These findings elucidate that sTRN neurons modulate social memory by coordinating a hitherto unknown corticothalamic circuit and inhibitory memory engram.

: The association of dairy product consumption with nonalcoholic fatty liver disease (NAFLD) and cirrhosis remains controversial. This study aimed to prospectively investigate the associations between the consumption of the different types of dairy products, genetic predisposition, and the risks of NAFLD and cirrhosis. : This cohort study included 190 145 participants from the UK Biobank Study. The consumption of the different types of dairy products was assessed based on the Oxford WebQ at baseline and defined as the sum of milk, yogurt, and cheese. NAFLD and cirrhosis were evaluated using hospital inpatient records and death data in the UK Biobank. The weighted genetic risk score (GRS) for NAFLD and cirrhosis was constructed using 5 and 6 single-nucleotide variants (SNVs), respectively. Cox proportional hazards regression models were utilized to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between genetic factors and different types of dairy products with the incidence of NAFLD and cirrhosis. : During a median follow-up of 11.6 years, 1512 NAFLD and 556 cirrhosis cases were ascertained. After adjusting for several potential confounders, the HRs (95% CIs) (Q4 Q1) of NAFLD were 0.86 (0.74, 0.995) for total dairy products, 0.96 (0.84, 1.09) for high-fat dairy products, 0.78 (0.67, 0.92) for low-fat dairy products, 0.86 (0.74, 0.99) for unfermented dairy products, and 0.79 (0.68, 0.91) for fermented dairy products. The multivariable-adjusted HRs (95% CIs) (Q4 Q1) of cirrhosis were 0.75 (0.59, 0.96) for total dairy products, 0.97 (0.78, 1.19) for high-fat dairy products, 0.67 (0.51, 0.89) for low-fat dairy products, 0.75 (0.59, 0.96) for unfermented dairy products, and 0.71 (0.56, 0.90) for fermented dairy products. The associations of high-fat dairy products and fermented dairy products with NAFLD and cirrhosis were found to be nonlinear ( for nonlinear <0.05). No interaction was observed between dairy product consumption and NAFLD or cirrhosis genetic susceptibility. : Higher consumption of dairy products, except for high-fat dairy, was correlated with lower risks of NAFLD and cirrhosis, regardless of their differences in genetic susceptibility.

The antidepressant effects of ketamine and esketamine are well-documented. Nonetheless, most of the underlying molecular mechanisms have to be uncovered yet. In the last decade, metabolomics has emerged as a useful means to investigate the metabolic phenotype associated with depression as well as changes induced by antidepressant treatments. This mini-review aims at summarizing the main findings from preclinical and clinical studies that used metabolomics to investigate the metabolic effects of subanesthetic, antidepressant doses of ketamine and esketamine and their relationship with clinical response. Both animal and human studies report alterations in several metabolic pathways - including the tricarboxylic acid cycle, glycolysis, the pentose phosphate pathway, lipid metabolism, amino acid metabolism, the kynurenine pathway, and the urea cycle - following the administration of ketamine or its enantiomers. Although more research is needed to clarify commonalities and differences in molecular mechanisms of action between the racemic compound and its enantiomers, these findings comprehensively support an influence of ketamine and esketamine on mitochondrial and cellular energy production, membrane homeostasis, neurotransmission, and signaling. Metabolomics may thus represent a promising strategy to clarify molecular mechanisms underlying treatment-resistant depression and related markers of clinical response to ketamine and esketamine. This body of preclinical and clinical evidence, if further substantiated, has the potential to guide clinicians towards personalized approaches, contributing to new paradigms in the clinical management of depression.

BIPCOM aims to (1) identify medical comorbidities in people with bipolar disorder (BD); (2) examine risk factors and clinical profiles of Medical Comorbidities (MC) in this clinical group, with a special focus on Metabolic Syndrome (MetS); (3) develop a Clinical Support Tool (CST) for the personalized management of BD and medical comorbidities.

Bismuth (Bi(III)) substitution in hydroxyapatite (HAp) lattice confers unique properties such as antibacterial, catalytic, radiosensitization, and conductive properties while preserving the innate bioactivity. Understanding the local structural changes upon Bi substitution is essential for controlling the stability and optimizing the properties of HAp. Despite numerous experimental studies, the precise substitution behaviors, such as site preference and structural stability, remain incompletely understood. In this study, the substitution behavior of Bi(III) into the HAp lattice with formula of CaBi(PO)(O)(OH) was investigated first-principles simulation by implementing density functional theory. Energy calculations showed that Bi preferentially occupies the Ca(2) site with an energy difference of ∼0.02 eV per atom. Local structure analysis revealed higher bond population values and an oxygen coordination shift from 7 to 6 for the Ca(2) site, attributed to the greater covalent interactions and its flexible environment accommodating the bulky Bi ion and its stereochemically active lone pair. This work provides the first comprehensive investigation on Bi ion substitution site preference in HAp using first-principles simulations.

Psychosis-associated diagnostic codes are increasingly being utilized as case definitions for electronic health record (EHR)-based algorithms to predict and detect psychosis. However, data on the validity of psychosis-related diagnostic codes is limited. We evaluated the positive predictive value (PPV) of International Classification of Diseases (ICD) codes for psychosis.

Cost-utility analysis generally requires valid preference-based measures (PBMs) to assess the utility of patient health. While generic PBMs are widely used, disease-specific PBMs may capture additional aspects of health relevant for certain patient populations. This study investigates the construct and concurrent criterion validity of the cancer-specific European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Utility-Core 10 dimensions (QLU-C10D) in non-small-cell lung cancer patients.

Fear overgeneralization is a promising pathogenic mechanism of clinical anxiety. A dominant model posits that hippocampal pattern separation failures drive overgeneralization. Hippocampal network-targeted transcranial magnetic stimulation (HNT-TMS) has been shown to strengthen hippocampal-dependent learning/memory processes. However, no study has examined whether HNT-TMS can alter fear learning/memory.

Machine learning algorithms hold promise for developing precision medicine approaches to addiction treatment yet have been used sparingly to identify predictors of alcohol-related problems. Recursive partitioning, a machine learning algorithm, can identify salient predictors and clinical cut points that can guide treatment. This study aimed to identify predictors and cut points of alcohol-related problems and to examine result stability in two separate, large data sets of college student drinkers ( = 5,090 and 2,808). Four regression trees were grown using the "rpart" package in R. Seventy-one predictors were classified as demographics (e.g., age), alcohol use indicators (e.g., typical quantity/frequency), or psychosocial indicators (e.g., anxiety). Predictors and cut points were extracted and used to manually recreate the tree in the other data set to test result stability. Outcome variables were alcohol-related problems as measured by the Alcohol Use Disorder Identification Test and Brief Young Adult Alcohol Consequences Questionnaire. Coping with depression, conformity motives, binge drinking frequency, typical/heaviest quantity, drunk frequency, serious harm reduction protective behavioral strategies, substance use, and psychosis symptoms best predicted alcohol-related problems across the four trees; coping with depression (cut point range: 1.83-2.17) and binge drinking frequency (cut point range: 1.5-2.5) were the most common splitting variables. Model fit indices suggest relatively stable results accounting for 17%-30% of the variance. Results suggest the nine salient predictors, particularly coping with depression motives scores around 2 and binge drinking frequency around two to three times per month, are important targets to consider when treating alcohol-related problems for college students. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Over the last six decades, lithium has been considered the gold standard treatment for the long-term management of bipolar disorder due to its efficacy in preventing both manic and depressive episodes as well as suicidal behaviors. Nevertheless, despite numerous observed effects on various cellular pathways and biologic systems, the precise mechanism through which lithium stabilizes mood remains elusive. Furthermore, there is recent support for the therapeutic potential of lithium in other brain diseases. This review offers a comprehensive examination of contemporary understanding and predominant theories concerning the diverse mechanisms underlying lithium's effects. These findings are based on investigations utilizing cellular and animal models of neurodegenerative and psychiatric disorders. Recent studies have provided additional support for the significance of glycogen synthase kinase-3 (GSK3) inhibition as a crucial mechanism. Furthermore, research has shed more light on the interconnections between GSK3-mediated neuroprotective, antioxidant, and neuroplasticity processes. Moreover, recent advancements in animal and human models have provided valuable insights into how lithium-induced modifications at the homeostatic synaptic plasticity level may play a pivotal role in its clinical effectiveness. We focused on findings from translational studies suggesting that lithium may interface with microRNA expression. Finally, we are exploring the repurposing potential of lithium beyond bipolar disorder. These recent findings on the therapeutic mechanisms of lithium have provided important clues toward developing predictive models of response to lithium treatment and identifying new biologic targets. SIGNIFICANCE STATEMENT: Lithium is the drug of choice for the treatment of bipolar disorder, but its mechanism of action in stabilizing mood remains elusive. This review presents the latest evidence on lithium's various mechanisms of action. Recent evidence has strengthened glycogen synthase kinase-3 (GSK3) inhibition, changes at the level of homeostatic synaptic plasticity, and regulation of microRNA expression as key mechanisms, providing an intriguing perspective that may help bridge the mechanistic gap between molecular functions and its clinical efficacy as a mood stabilizer.

Noninvasive brain stimulation (NIBS) has been increasingly investigated during the last decade as a treatment option for persons with autism spectrum disorder (ASD). Yet, previous studies did not reach a consensus on a superior treatment protocol or stimulation target. Persons with ASD often suffer from social isolation and high rates of unemployment, arising from difficulties in social interaction. ASD involves multiple neural systems involved in perception, language, and cognition, and the underlying brain networks of these functional domains have been well documented. Aiming to provide an overview of NIBS effects when targeting these neural systems in late adolescent and adult ASD, we conducted a systematic search of the literature starting at 631 non-duplicate publications, leading to six studies corresponding with inclusion and exclusion criteria. We discuss these studies regarding their treatment rationale and the accordingly chosen methodological setup. The results of these studies vary, while methodological advances may allow to explain some of the variability. Based on these insights, we discuss strategies for future clinical trials to personalize the selection of brain stimulation targets taking into account intersubject variability of brain anatomy as well as function.

Deep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology for diagnosis and prognosis in neurological disorders, but its clinical impact has been limited. This is partially attributed to the opaqueness of deep learning models, causing insufficient understanding of what underlies their decisions. To overcome this, we trained convolutional neural networks on structural brain scans to differentiate dementia patients from healthy controls, and applied layerwise relevance propagation to procure individual-level explanations of the model predictions. Through extensive validations we demonstrate that deviations recognized by the model corroborate existing knowledge of structural brain aberrations in dementia. By employing the explainable dementia classifier in a longitudinal dataset of patients with mild cognitive impairment, we show that the spatially rich explanations complement the model prediction when forecasting transition to dementia and help characterize the biological manifestation of disease in the individual brain. Overall, our work exemplifies the clinical potential of explainable artificial intelligence in precision medicine.

Identifying the characteristics of individuals who demonstrate response to an intervention allows us to predict who is most likely to benefit from certain interventions. Prediction is challenging in rare and heterogeneous diseases, such as primary progressive aphasia (PPA), that have varying clinical manifestations. We aimed to determine the characteristics of those who will benefit most from transcranial direct current stimulation (tDCS) of the left inferior frontal gyrus (IFG) using a novel heterogeneity and group identification analysis.

Studying the intricacies of individual subjects' moods and cognitive processing over extended periods of time presents a formidable challenge in medicine. While much of systems neuroscience appropriately focuses on the link between neural circuit functions and well-constrained behaviors over short timescales (e.g., trials, hours), many mental health conditions involve complex interactions of mood and cognition that are non-stationary across behavioral contexts and evolve over extended timescales. Here, we discuss opportunities, challenges, and possible future directions in computational psychiatry to quantify non-stationary continuously monitored behaviors. We suggest that this exploratory effort may contribute to a more precision-based approach to treating mental disorders and facilitate a more robust reverse translation across animal species. We conclude with ethical considerations for any field that aims to bridge artificial intelligence and patient monitoring.

Phthalate exposure may contribute to hypertensive disorders of pregnancy (HDP), including preeclampsia/eclampsia (PE/E), but epidemiologic studies are lacking.

The mechanisms of psychotic symptoms like hallucinations and delusions are often investigated in fully-formed illness, well after symptoms emerge. These investigations have yielded key insights, but are not well-positioned to reveal the dynamic forces underlying symptom formation itself. Understanding symptom development over time would allow us to identify steps in the pathophysiological process leading to psychosis, shifting the focus of psychiatric intervention from symptom alleviation to prevention. We propose a model for understanding the emergence of psychotic symptoms within the context of an adaptive, developing neural system. We will make the case for a pathophysiological process that begins with cortical hyperexcitability and bottom-up noise transmission, which engenders inappropriate belief formation via aberrant prediction error signaling. We will argue that this bottom-up noise drives learning about the (im)precision of new incoming sensory information because of diminished signal-to-noise ratio, causing an adaptive relative over-reliance on prior beliefs. This over-reliance on priors predisposes to hallucinations and covaries with hallucination severity. An over-reliance on priors may also lead to increased conviction in the beliefs generated by bottom-up noise and drive movement toward conversion to psychosis. We will identify predictions of our model at each stage, examine evidence to support or refute those predictions, and propose experiments that could falsify or help select between alternative elements of the overall model. Nesting computational abnormalities within longitudinal development allows us to account for hidden dynamics among the mechanisms driving symptom formation and to view established symptomatology as a point of equilibrium among competing biological forces.

Adolescent self-reported psychotic experiences are associated with mental illness and could help guide prevention strategies. The Community Assessment of Psychic Experiences (CAPE) was developed over 20 years ago. In a rapidly changing society, where new generations of adolescents are growing up in an increasingly digital world, it is crucial to ensure high reliability and validity of the questionnaire.

Major depressive disorder (MDD) is a common and often severe condition that profoundly diminishes quality of life for individuals across ages and demographic groups. Unfortunately, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates in a substantial number of patients. The development of effective therapies for MDD is hindered by the insufficiently understood heterogeneity within the disorder and its elusive underlying mechanisms. To address these challenges, we present a target-oriented multimodal fusion framework that robustly predicts antidepressant response by integrating structural and functional connectivity data (sertraline: R = 0.31; placebo: R = 0.22). Through the model, we identify multimodal neuroimaging biomarkers of antidepressant response and observe that sertraline and placebo show distinct predictive patterns. We further decompose the overall predictive patterns into constitutive with generalizable structural-functional co-variation, which exhibit treatment-specific association with personality traits and behavioral/cognitive task performance. Our innovative and interpretable multimodal framework provides novel insights into the intricate neuropsychopharmacology of antidepressant treatment and paves the way for advances in precision medicine and development of more targeted antidepressant therapeutics.

Intelligent predictive models for autistic symptoms based on neuroimaging datasets were beneficial for the precise intervention of patients with ASD. The goals of this study were twofold: investigating predictive models for autistic symptoms and discovering the brain connectivity patterns for ASD-related behaviors. To achieve these goals, we obtained a cohort of patients with ASD from the ABIDE project. The autistic symptoms were measured using the Autism Diagnostic Observation Schedule (ADOS). The anatomical MRI datasets were preprocessed using the Freesurfer package, resulting in regional morphological features. For each individual, the interregional morphological network was constructed using a novel feature distance-based method. The predictive models for autistic symptoms were built using the support vector regression (SVR) algorithm with feature selection method. The predicted autistic symptoms (i.e., ADOS social score, ADOS behavior) were significantly correlated to the original measures. The most predictive features for ADOS social scores were located in the bilateral fusiform. The most predictive features for ADOS behavior scores were located in the temporal pole and the lingual gyrus. In summary, the autistic symptoms could be predicted using the interregional morphological connectivity and machine learning. The interregional morphological connectivity could be a potential biomarker for autistic symptoms.

Human immunodeficiency virus (HIV)-associated dementia (HAD) is a subcortical form of dementia characterized by memory deficits and psychomotor slowing. However, HAD often presents with symptoms similar to those of Creutzfeldt-Jakob disease (CJD), particularly in patients with acquired immune deficiency syndrome (AIDS).

The clinical phenotype of the so-called late-onset depression (LOD) affecting up to 30% of older adults and yielding heterogeneous manifestations concerning symptoms, severity and course has not been fully elucidated yet. This European, cross-sectional, non-interventional, naturalistic multicenter study systematically investigated socio-demographic and clinical correlates of early-onset depression (EOD) and LOD (age of onset ≥ 50 years) in 1410 adult in- and outpatients of both sexes receiving adequate psychopharmacotherapy. In a total of 1329 patients (94.3%) with known age of disease onset, LOD was identified in 23.2% and was associated with unemployment, an ongoing relationship, single major depressive episodes, lower current suicidal risk and higher occurrence of comorbid hypertension. In contrast, EOD was related to higher rates of comorbid migraine and additional psychotherapy. Although the applied study design does not allow to draw any causal conclusions, the present results reflect broad clinical settings and emphasize easily obtainable features which might be characteristic for EOD and LOD. A thoughtful consideration of age of onset might, hence, contribute to optimized diagnostic and therapeutic processes in terms of the globally intended precision medicine, ideally enabling early and adequate treatment allocations and implementation of respective prevention programs.

The Insomnia Severity Index (ISI) is a widely used questionnaire with seven items for identifying the risk of insomnia disorder. Although the ISI is still short, more shortened versions are emerging for repeated monitoring in routine clinical settings. In this study, we aimed to develop a data-driven shortened version of the ISI that accurately predicts the severity level of insomnia disorder.

With the rising prevalence of mental disorders among children and adolescents, identifying modifiable associations is critical.

Increasing evidence suggests that metabolic impairments contribute to early Alzheimer's disease (AD) mechanisms and subsequent dementia. Signals in metabolic pathways conserved across species can facilitate translation.

The relationship between autism spectrum disorder (ASD) and sexual offending (SO) is an overlooked issue, both in clinical practice and in research. Based on a pre-specified protocol (PROSPERO: CRD42024501598), we systematically searched Pubmed and Scopus, between January 1st, 1994 and January 12th, 2024, for articles related to SO in ASD. Study quality was assessed with study design-specific tools (Study Quality Assessment Tools, NHLBI, NIH). We found 19 relevant publications (five cross-sectional studies, two case-control studies, and 12 case reports). Seven of the studies were deemed of "good" quality, the rest as "fair". Included studies addressed three key aspects: 1) psychopathological characteristics of individuals with ASD that increase the risk of committing SO; 2) intervention strategies for individuals with ASD and SO; 3) involvement of individuals with ASD and SO in the justice system. Overall, while there is an increasing interest in this topic, more rigorous study designs, including randomised controlled trials, are needed to inform clinical practice and healthcare and social policies.

Delirium is a neuropsychiatric condition that commonly occurs in medical settings, especially among older individuals. Despite the lack of strong evidence in the literature, haloperidol is considered the first-line pharmacological intervention. Unfortunately, its adverse effects can be severe, and psychiatrists are considering the use of alternative drugs targeting dopamine and serotonin domains (atypical antipsychotics). Among them, aripiprazole is considered to have one of the safest pharmacological profiles.

With disease-modifying treatment for Parkinson's disease (PD) associated with variants in the glucocerebrosidase gene (GBA1) under way, the challenge to design clinical trials with non-PD-manifest GBA mutation carriers (GBA1) comes within close reach. To delineate trajectories of motor and non-motor markers as well as serum neurofilament light (sNfL) levels and to evaluate clinical endpoints as outcomes for clinical trials in GBA1, longitudinal data of 56 GBA1 carriers and 112 age- and sex-matched GBA1 wildtype participants (GBA1) with up to 9 years of follow-up was analyzed using linear mixed-effects models (LMEM) and Kaplan-Meier survival analysis of clinical endpoints for motor and cognitive function. GBA1 showed worse performance in Pegboard, 20 m fast walking, global cognition as well as in executive and memory function at baseline. Longitudinally, LMEM revealed a higher annual increase of the MDS-UPDRS III bradykinesia subscore in GBA1 compared to GBA1, but comparable trajectories of all other motor and non-motor markers as well as sNfL. Kaplan-Meier survival analysis showed a significantly earlier progression to clinical endpoints of cognitive decline in GBA1. Incidence of PD was significantly higher in GBA1. In conclusion, our study extends data on GBA1 indicating early cognitive decline as a potentially characteristic feature. Comprehensive longitudinal assessments of cognitive function are crucial to delineate the evolution of early changes in GBA1 enabling a more accurate stratification and allow for a more precise definition of trial design and sample size.

The differential performance of polygenic risk scores (PRSs) by group is one of the major ethical barriers to their clinical use. It is also one of the main practical challenges for any implementation effort. The social repercussions of how people are grouped in PRS research must be considered in communications with research participants, including return of results. Here, we outline the decisions faced and choices made by a large multi-site clinical implementation study returning PRSs to diverse participants in handling this issue of differential performance. Our approach to managing the complexities associated with the differential performance of PRSs serves as a case study that can help future implementers of PRSs to plot an anticipatory course in response to this issue.

Heightened stress and insufficient sleep are common in the transition to college, often co-occur, and have both been linked to negative health outcomes. A challenge concerns disentangling whether perceived stress precedes or succeeds changes in sleep. These day-to-day associations may vary across individuals, but short study periods and group-level analyses in prior research may have obscured person-specific phenotypes.

Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5-18.2 mmHg, P = 2.22 × 10) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54-9.70; P = 4.13 × 10) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781-0.801) to 0.826 (95% CI, 0.817-0.836, ∆AUROC, 0.035, P = 1.98 × 10). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research.

Depression is often accompanied by changes in behavior, including dietary behaviors. The relationship between dietary behaviors and depression has been widely studied, yet previous research has relied on self-reported data which is subject to recall bias. Electronic device-based behavioral monitoring offers the potential for objective, real-time data collection of a large amount of continuous, long-term behavior data in naturalistic settings.

The co-occurrence and familial clustering of neurodevelopmental disorders and immune disorders suggest shared genetic risk factors. Based on genome-wide association summary statistics from five neurodevelopmental disorders and four immune disorders, we conducted genome-wide, local genetic correlation and polygenic overlap analysis. We further performed a cross-trait GWAS meta-analysis. Pleotropic loci shared between the two categories of diseases were mapped to candidate genes using multiple algorithms and approaches. Significant genetic correlations were observed between neurodevelopmental disorders and immune disorders, including both positive and negative correlations. Neurodevelopmental disorders exhibited higher polygenicity compared to immune disorders. Around 50%-90% of genetic variants of the immune disorders were shared with neurodevelopmental disorders. The cross-trait meta-analysis revealed 154 genome-wide significant loci, including 8 novel pleiotropic loci. Significant associations were observed for 30 loci with both types of diseases. Pathway analysis on the candidate genes at these loci revealed common pathways shared by the two types of diseases, including neural signaling, inflammatory response, and PI3K-Akt signaling pathway. In addition, 26 of the 30 lead SNPs were associated with blood cell traits. Neurodevelopmental disorders exhibit complex polygenic architecture, with a subset of individuals being at a heightened genetic risk for both neurodevelopmental and immune disorders. The identification of pleiotropic loci has important implications for exploring opportunities for drug repurposing, enabling more accurate patient stratification, and advancing genomics-informed precision in the medical field of neurodevelopmental disorders.

Rapidly improving acute respiratory distress syndrome (RIARDS) is an increasingly appreciated subgroup of ARDS in which hypoxemia improves within 24 h after initiation of mechanical ventilation. Detailed clinical and biological features of RIARDS have not been clearly defined, and it is unknown whether RIARDS is associated with the hypoinflammatory or hyperinflammatory phenotype of ARDS. The purpose of this study was to define the clinical and biological features of RIARDS and its association with inflammatory subphenotypes.

Attention-Deficit/Hyperactivity Disorder (ADHD), characterized by clinical diversity, poses diagnostic challenges often reliant on subjective assessments. Metabolomics presents an objective approach, seeking biomarkers for precise diagnosis and targeted interventions. This review synthesizes existing metabolomic insights into ADHD, aiming to reveal biological mechanisms and diagnostic potentials. A thorough PubMed and Web of Knowledge search identified studies exploring blood/urine metabolites in ADHD-diagnosed or psychometrically assessed children and adolescents. Synthesis revealed intricate links between ADHD and altered amino acid metabolism, neurotransmitter dysregulation (especially dopamine and serotonin), oxidative stress, and the kynurenine pathway impacting neurotransmitter homeostasis. Sleep disturbance markers, notably in melatonin metabolism, and stress-induced kynurenine pathway activation emerged. Distinct metabolic signatures, notably in the kynurenine pathway, show promise as potential diagnostic markers. Despite limitations like participant heterogeneity, this review underscores the significance of integrated therapeutic approaches targeting amino acid metabolism, neurotransmitters, and stress pathways. While guiding future research, this overview of the metabolomic findings in ADHD suggests directions for precision diagnostics and personalized ADHD interventions.

Single-cell/nuclei RNA sequencing (sc/snRNA-Seq) is widely used for profiling cell-type gene expressions in biomedical research. An important but underappreciated issue is the quality of sc/snRNA-Seq data that would impact the reliability of downstream analyses. Here we evaluated the precision and accuracy in 18 sc/snRNA-Seq datasets. The precision was assessed on data from human brain studies with a total of 3,483,905 cells from 297 individuals, by utilizing technical replicates. The accuracy was evaluated with sample-matched scRNA-Seq and pooled-cell RNA-Seq data of cultured mononuclear phagocytes from four species. The results revealed low precision and accuracy at the single-cell level across all evaluated data. Cell number and RNA quality were highlighted as two key factors determining the expression precision, accuracy, and reproducibility of differential expression analysis in sc/snRNA-Seq. This study underscores the necessity of sequencing enough high-quality cells per cell type per individual, preferably in the hundreds, to mitigate noise in expression quantification.

An increase in the demand for quality of life following spinal cord injuries (SCIs) is associated with an increase in musculoskeletal (MSK) pain, highlighting the need for preventive measure research.

Pathogenic mutant huntingtin (mHTT) infiltrates the adult Huntington's disease (HD) brain and impairs fetal corticogenesis. However, most HD animal models rarely recapitulate neuroanatomical alterations in adult HD and developing brains. Thus, the human cortical organoid (hCO) is an alternative approach to decode mHTT pathogenesis precisely during human corticogenesis. Here, we replicated the altered corticogenesis in the HD fetal brain using HD patient-derived hCOs. Our HD-hCOs had pathological phenotypes, including deficient junctional complexes in the neural tubes, delayed postmitotic neuronal maturation, dysregulated fate specification of cortical neuron subtypes, and abnormalities in early HD subcortical projections during corticogenesis, revealing a causal link between impaired progenitor cells and chaotic cortical neuronal layering in the HD brain. We identified novel long, oriented, and enriched polyQ assemblies of HTTs that hold large flat Golgi stacks and scaffold clathrin+ vesicles in the neural tubes of hCOs. Flat Golgi stacks conjugated polyQ assemblies by ADP-ribosylation factor 1 (ARF1). Inhibiting ARF1 activation with Brefeldin A (BFA) disassociated polyQ assemblies from Golgi. PolyQ assembles with mHTT scaffolded fewer ARF1 and formed shorter polyQ assembles with fewer and shorter Golgi and clathrin vesicles in neural tubes of HD-hCOs compared with those in hCOs. Inhibiting the activation of ARF1 by BFA in healthy hCOs replicated impaired junctional complexes in the neural tubes. Together, endogenous polyQ assemblies with mHTT reduced the Golgi recruiting ARF1 in the neuroepithelium, impaired the Golgi structure and activities, and altered the corticogenesis in HD-hCO.

In the United States, the societal costs associated with drug use surpass $500 billion annually. The rewarding and reinforcing properties that drive the use of these addictive substances are typically examined concerning the neurobiological effects responsible for their abuse potential. In this review, terms such as "abuse potential," "drug," and "addictive properties" are used due to their relevance to the methodological, theoretical, and conceptual framework for understanding the phenomenon of drug-taking behavior and the associated body of preclinical and clinical literature. The use of these terms is not intended to cast aspersions on individuals with substance use disorders (SUD). Understanding what motivates substance use has been a focus of SUD research for decades. Much of this corpus of work has focused on the shared effects of each drug class to increase dopaminergic transmission within the central reward pathways of the brain, or the "reward center." However, the precise influence of each drug class on dopamine signaling, and the extent thereof, differs considerably. Furthermore, the aforementioned substances have effects on several neurobiological targets that mediate and modulate their addictive properties. The current manuscript sought to review the influence of drug class on the rewarding effects of each of the major pharmacological classes of addictive drugs (i.e., psychostimulants, opioids, nicotine, alcohol, and cannabinoids). Our review suggests that even subtle differences in drug effects can result in significant variability in the subjective experience of the drug, altering rewarding and other reinforcing effects. Additionally, this review will argue that reward (i.e., the attractive and motivational property of a stimulus) alone is not sufficient to explain the abuse liability of these substances. Instead, abuse potential is best examined as a function of both positive and negative reinforcing drug effects (i.e., stimuli that the subject will work to attain and stimuli that the subject will work to end or avoid, respectively). Though reward is central to drug use, the factors that motivate and maintain drug taking are varied and complex, with much to be elucidated.

One of the challenges in bipolar disorder (BD) lies in early detection of the illness and its recurrences, to improve prognosis. Sleep disturbances (SD) have been proposed as reliable predictive markers of conversion. While preliminary studies have explored the relationship between SD and the onset of mood episodes, the results remain heterogeneous and a few have specifically examined patients' perception of prodromal symptoms and their progression until the episode occurs. Identifying prodromes represents a crucial clinical challenge, as it enables early intervention, thereby reducing the severity of BD. Therefore, the objective of this study is to better characterize and evaluate the progressive nature of SD as prodromal symptoms of mood episodes, and patients' perception of it.

Essential tremor (ET) is a prevalent neurological disorder with a largely unknown underlying biology. In this genome-wide association study meta-analysis, comprising 16,480 ET cases and 1,936,173 controls from seven datasets, we identify 12 sequence variants at 11 loci. Evaluating mRNA expression, splicing, plasma protein levels, and coding effects, we highlight seven putative causal genes at these loci, including CA3 and CPLX1. CA3 encodes Carbonic Anhydrase III and carbonic anhydrase inhibitors have been shown to decrease tremors. CPLX1, encoding Complexin-1, regulates neurotransmitter release. Through gene-set enrichment analysis, we identify a significant association with specific cell types, including dopaminergic and GABAergic neurons, as well as biological processes like Rho GTPase signaling. Genetic correlation analyses reveals a positive association between ET and Parkinson's disease, depression, and anxiety-related phenotypes. This research uncovers risk loci, enhancing our knowledge of the complex genetics of this common but poorly understood disorder, and highlights CA3 and CPLX1 as potential therapeutic targets.

To evaluate the accuracy and precision of continuous overnight oxygen saturation (SpO) measurement by a commercial wrist device (WD) incorporating high-grade sensors, and investigate WD estimation of sleep-disordered breathing by quantifying overnight oxygen desaturation index (ODI) compared to polysomnography (PSG) ODI and apnea-hypopnea index (AHI) with and without sleep questionnaire data, to assess WD ability to detect obstructive sleep apnea (OSA) and determine its severity.

It is crucial to regulate N-methyl-D-aspartate (NMDA) function bivalently depending on the central nervous system (CNS) conditions. CNS disorders with NMDA hyperfunction are involved in the pathogenesis of neurotoxic and/or neurodegenerative disorders with elevated D-serine, one of the NMDA receptor co-agonists. On the contrary, NMDA-enhancing agents have been demonstrated to improve psychotic symptoms and cognition in CNS disorders with NMDA hypofunction. Serine racemase (SR), the enzyme regulating both D- and L-serine levels through both racemization (catalysis from L-serine to D-serine) and β-elimination (degradation of both D- and L-serine), emerges as a promising target for bidirectional regulation of NMDA function. In this study, we explored using dimethyl malonate (DMM), a pro-drug of the SR inhibitor malonate, to modulate NMDA activity in C57BL/6J male mice via intravenous administration. Unexpectedly, 400 mg/kg DMM significantly elevated, rather than decreased (as a racemization inhibitor), D-serine levels in the cerebral cortex and plasma. This outcome prompted us to investigate the regulatory effects of dodecagalloyl-α-D-xylose (α12G), a synthesized tannic acid analog, on SR activity. Our findings showed that α12G enhanced the racemization activity of human SR by about 8-fold. The simulated and fluorescent assay of binding affinity suggested a noncooperative binding close to the catalytic residues, Lys56 and Ser84. Moreover, α12G treatment can improve behaviors associated with major CNS disorders with NMDA hypofunction including hyperactivity, prepulse inhibition deficit, and memory impairment in animal models of positive symptoms and cognitive impairment of psychosis. In sum, our findings suggested α12G is a potential therapeutic for treating CNS disorders with NMDA hypofunction.

To investigate the potential association between prenatal opioid exposure and the risk of neuropsychiatric disorders in children.

: The study aims to provide a comprehensive neuropsychological analysis of psychotic spectrum disorders, including schizophrenia, bipolar disorder, and depression. It focuses on the critical aspects of cognitive impairments, diagnostic tools, intervention efficacy, and the roles of genetic and environmental factors in these disorders. The paper emphasizes the diagnostic significance of neuropsychological tests in identifying cognitive deficiencies and their predictive value in the early management of psychosis. : The study involved a systematic literature review following the PRISMA guidelines. The search was conducted in significant databases like Scopus, PsycINFO, PubMed, and Web of Science using keywords relevant to clinical neuropsychology and psychotic spectrum disorders. The inclusion criteria required articles to be in English, published between 2018 and 2023, and pertinent to clinical neuropsychology's application in these disorders. A total of 153 articles were identified, with 44 ultimately included for detailed analysis based on relevance and publication status after screening. The review highlights several key findings, including the diagnostic and prognostic significance of mismatch negativity, neuroprogressive trajectories, cortical thinning in familial high-risk individuals, and distinct illness trajectories within psychosis subgroups. The studies evaluated underline the role of neuropsychological tests in diagnosing psychiatric disorders and emphasize early detection and the effectiveness of intervention strategies based on cognitive and neurobiological markers. : The systematic review underscores the importance of investigating the neuropsychological components of psychotic spectrum disorders. It identifies significant cognitive impairments in attention, memory, and executive function, correlating with structural and functional brain abnormalities. The paper stresses the need for precise diagnoses and personalized treatment modalities, highlighting the complex interplay between genetic, environmental, and psychosocial factors. It calls for a deeper understanding of these neuropsychological processes to enhance diagnostic accuracy and therapeutic outcomes.

Myxofibrosarcoma is a type of soft tissue sarcoma, predominantly characterized by a high propensity for local recurrence, albeit demonstrating a relatively diminished risk for distant metastasis. Its prevalence is notably higher in elderly patients. Here, we present a case of a 73-year-old woman diagnosed with Myxofibrosarcoma. She was subjected to a whole-body bone scan using Tc-methylene diphosphonate (MDP) to survey potential bony metastasis. It revealed marked MDP accumulation with peripheral soft tissue uptake in the right lateral chest region of this patient. This imaging phenotype could potentially be attributed to the augmented vascularity within the tumor, a finding that was prominently displayed in this particular case.

Middle-aged and older adults with physical disabilities exhibit more common and severe depressive symptoms than those without physical disabilities. Such symptoms can greatly affect the physical and mental health and life expectancy of middle-aged and older persons with disabilities.

To investigate shared and specific neural correlates of cognitive functions in attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), the authors performed a comprehensive meta-analysis and considered a balanced set of neuropsychological tasks across the two disorders.

Parkinson's disease (PKD) is neurodegenerative disorder marked by tremors, bradykinesia, muscle rigidity and reduction in precise hand movements which could lead to improper oral hygiene and Periodontal disease. Current systematic review aims to review existing literature and provide assessment of periodontal health in PKD patients through a meta-analysis METHODS: Review was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and registered in PROSPERO-CRD42023451700. Databases were searched for studies having sufficient data on periodontal health in patients with PKD compared to healthy controls and reporting outcomes in terms of various periodontal parameters of probing depth (PD), plaque index (PI), clinical attachment level (CAL), presence of bleeding on probing and gingivitis. Quality assessment of included was evaluated using Newcastle Ottawa Scale (NOS).

Patients with Parkinson's disease (PD) experience changes in behavior, personality, and cognition that can manifest even in the initial stages of the disease. Previous studies have suggested that mild behavioral impairment (MBI) should be considered an early marker of cognitive decline. However, the precise neurostructural underpinnings of MBI in early- to mid-stage PD remain poorly understood.

The precise roles of screen media activity (SMA) and sleep problems in relation to child/adolescent psychopathology remain ambiguous. We investigated temporal relationships among sleep problems, SMA, and psychopathology and potential involvement of thalamus-prefrontal-cortex (PFC)-brainstem structural covariation.

The cost of secondary prevention of coronary heart disease (CHD) is continuing to increase, with a substantial portion of this acceleration being driven by the expense of confirmatory diagnostic testing. Conceivably, newly developed precision epigenetic technologies could drive down these costs. However, at the current time, their impact on overall expense for CHD care is poorly understood. We hypothesized that the use of a newly developed, highly sensitive, and specific epigenetic test, PrecisionCHD, could decrease the costs of secondary prevention.

Both endocannabinoid (EC) and endogenous opioid systems are involved in nociceptive processing and may work together synergistically based on preclinical models. This study evaluated the interactive effects of preoperative beta-endorphin concentrations (a key analgesic endogenous opioid) in cerebrospinal fluid (CSF) and ECs (CSF and plasma 2-arachidonoylglycerol [2-AG] and plasma anandamide [AEA]) on postoperative opioid use and pain intensity in a prospective cohort of n = 112 pregnant patients undergoing scheduled cesarean delivery. Maternal blood and CSF samples were collected preoperatively for beta-endorphin and EC assays. Patients completed measures of outpatient opioid use (number of tablets used and days of use) and average pain intensity at 2 weeks postoperatively. Results of general linear model analyses controlling for maternal age, BMI at time of delivery, and race revealed significant multiplicative interactions between EC and beta-endorphin concentrations on number of opioid tablets used (based on pill count), days of opioid use, and total milligram morphine equivalents used in the 2 week follow-up period. Elevated preoperative plasma and CSF 2-AG predicted reduced outpatient opioid analgesic use particularly for patients low in CSF beta-endorphin. Similar analyses for pain intensity at 2-week follow-up indicated a significant interaction (p<.02) characterized by higher preoperative beta-endorphin concentrations being associated with lower subsequent pain only for individuals with low preoperative plasma AEA concentrations. Further exploration of interactions between EC and endogenous opioid inhibitory systems as they influence responses to opioid analgesics in other clinical pain populations may help guide development of precision pain management approaches. PERSPECTIVE: In the postoperative setting of patients undergoing cesarean delivery, elevated endocannabinoids were linked to reduced outpatient opioid analgesic use in individuals who had low endogenous opioid concentrations in cerebrospinal fluid. Further exploration of interactions between these two inhibitory systems as they impact on responses to pain management interventions appears warranted.

Bipolar disorder is associated with increased rates of many physical disorders, but the effects of medication are unclear. We systematically investigated the associations between sustained use of first line maintenance agents, lithium versus lamotrigine and valproate, and the risk of physical disorders using a nation-wide population-based target trial emulation covering the entire 5.9 million inhabitants in Denmark. We identified two cohorts. Cohort 1: patients with a diagnosis of bipolar disorder prior to first purchase (N = 12.607). Cohort 2: all 156.678 adult patients who had their first ever purchase (since 1995) of either lithium, lamotrigine or valproate between 1997 and 2021 regardless of diagnosis. Main analyses investigated the effect of sustained exposure defined as exposure for all consecutive 6-months periods during a 10-year follow-up. Outcomes included a diagnosis of incident stroke, arteriosclerosis, angina pectoris, myocardial infarction, diabetes mellitus, myxedema, osteoporosis, dementia, Parkinson's disease, chronic kidney disease and cancer (including subtypes). In both Cohorts 1 and 2, there were no systematic statistically significant differences in associations between sustained use of lithium versus lamotrigine and valproate, respectively, and any physical disorder, including subtypes of disorders, except myxedema, for which exposure to lithium increased the absolute risk of myxedema with 7-10 % compared with lamotrigine or valproate. In conclusion, these analyses emulating a target trial of "real world" observational register-based data show that lithium does not increase the risk of developing any kind of physical disorders, except myxedema, which may be a result of detection bias.

Phosphatidylethanol (PEth) measurement in whole blood samples is established as a specific alcohol biomarker with clinical and forensic applications. Establishment of dried blood spots (DBSs) as a specimen for PEth determination offers several advantages and was the focus of this work. A liquid chromatography tandem mass spectrometry method using a 96-well format for sample preparation was developed and validated. PEth was extracted from DBSs by using isopropanol containing PEth-d5 as internal standard. The blood sampling used a commercial volumetric DBS device having a phosholipase D inhibitor incorporated to stop continuous PEth formation. The method quantified PEth in the range of 0.05-10 μmol/L, with a bias and imprecision of less than 15%. In a clinical study (n = 25) using fingerprick blood, the volumetric device offered more precise quantifications (CV 4.6%) compared with the Whatman 903 Protein Saver card device (CV 16.6%). In another clinical study (n = 48), the use of dried venous and capillary blood, and liquid venous blood was compared under real-life conditions with samples sent by postal service. The capillary and venous DBS samples gave identical results while the liquid blood gave slightly higher values. Calculation of elimination half-life (PEth 16:0/18:1) in 31 cases based on two consecutive samples with 2-9 days in between gave results (mean 6.2 days) that agree with literature but several cases with values over 10 days. In conclusion, this study demonstrates that volumetric DBS is a valid specimen for determination of PEth blood concentrations, offering several advantages.

Alzheimer's disease (AD)-related neuropathological changes can occur decades before clinical symptoms. We aimed to investigate whether neurodevelopment and/or neurodegeneration affects the risk of AD, through reducing structural brain reserve and/or increasing brain atrophy, respectively.

Brain aging is typically associated with a significant decline in cognitive performance. Vascular risk factors (VRF) and subsequent atherosclerosis (AS) play a major role in this process. Brain resilience reflects the brain's ability to withstand external perturbations, but the relationship of brain resilience with cognition during the aging process remains unclear. Here, we investigated how brain topological resilience (BTR) is associated with cognitive performance in the face of aging and vascular risk factors. We used data from two cross-ethnicity community cohorts, PolyvasculaR Evaluation for Cognitive Impairment and Vascular Events (PRECISE, n = 2220) and Sydney Memory and Ageing Study (MAS, n = 246). We conducted an attack simulation on brain structural networks based on k-shell decomposition and node degree centrality. BTR was defined based on changes in the size of the largest subgroup of the network during the simulation process. Subsequently, we explored the negative correlations of BTR with age, VRF, and AS, and its positive correlation with cognitive performance. Furthermore, using structural equation modeling (SEM), we constructed path models to analyze the directional dependencies among these variables, demonstrating that aging, AS, and VRF affect cognition by disrupting BTR. Our results also indicated the specificity of this metric, independent of brain volume. Overall, these findings underscore the supportive role of BTR on cognition during aging and highlight its potential application as an imaging marker for objective assessment of brain cognitive performance.

The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial. The models incorporated pre-treatment sMRI, clinical, sociodemographic, and polygenic risk score (PRS) data. Patients were randomly assigned to receive active (N = 45) or sham (N = 47) rTMS treatment. The prediction target was individual response, defined as ≥20% reduction in pre-treatment negative symptom sum scores of the Positive and Negative Syndrome Scale. Our multimodal sequential prediction workflow achieved a balanced accuracy (BAC) of 94% (non-responders: 92%, responders: 95%) in the active-treated group and 50% in the sham-treated group. The clinical, clinical + PRS, and sMRI-based classifiers yielded BACs of 65%, 76%, and 80%, respectively. Apparent sadness, inability to feel, educational attainment PRS, and unemployment were most predictive of non-response in the clinical + PRS model, while grey matter density reductions in the default mode, limbic networks, and the cerebellum were most predictive in the sMRI model. Our sequential modelling approach provided superior predictive performance while minimising the diagnostic burden in the clinical setting. Predictive patterns suggest that rTMS responders may have higher levels of brain grey matter in the default mode and salience networks which increases their likelihood of profiting from plasticity-inducing brain stimulation methods, such as rTMS. The future clinical implementation of our models requires findings to be replicated at the international scale using stratified clinical trial designs.

New Psychoactive Substances (NPS) are modifying the drug scenario worldwide and have become a public health concern because of their toxicological profiles and their harmful physical/psychological effects. 3-Methoxy-Phencyclidine (3-MeO-PCP), a non-competitive antagonist of glutamate N-methyl-D-aspartate (NMDA) receptors, belongs to the phencyclidine-like subfamily of arylcyclohexylamines and has gained attention for its toxic, sometimes fatal, effects. Despite several cases of intoxication and death reported in the literature, little is known about substance-induced psychotic disorders (SIP) and potential cognitive impairment following 3-MeO-PCP intake. This literature review aimed to summarize available evidence about 3-MeO-PCP mechanisms of action and physical and psychotropic effects and to spread preliminary findings about persistent psychotic symptoms and impaired cognitive functioning. Additionally, the case of an SIP is reported in a 29-year-old man with small oral intakes of 3-MeO-PCP over two weeks until a high dose ingestion. Psychometric and neuropsychological assessment and brain [F]-fluorodeoxyglucose positron emission tomography integrated with computed tomography were used to support clinical description. Identifying and addressing the characteristic clinical features and neural substrates of NPS-induced psychoses might help clinicians with a more precise differentiation from other psychotic disorders. Although further studies are required, phenotyping the cognitive profile of NPS users might provide targets for tailored therapeutic approaches.

Artificial intelligence (AI) is rapidly transforming the field of medicine, announcing a new era of innovation and efficiency. Among AI programs designed for general use, ChatGPT holds a prominent position, using an innovative language model developed by OpenAI. Thanks to the use of deep learning techniques, ChatGPT stands out as an exceptionally viable tool, renowned for generating human-like responses to queries. Various medical specialties, including rheumatology, oncology, psychiatry, internal medicine, and ophthalmology, have been explored for ChatGPT integration, with pilot studies and trials revealing each field's potential benefits and challenges. However, the field of genetics and genetic counseling, as well as that of rare disorders, represents an area suitable for exploration, with its complex datasets and the need for personalized patient care. In this review, we synthesize the wide range of potential applications for ChatGPT in the medical field, highlighting its benefits and limitations. We pay special attention to rare and genetic disorders, aiming to shed light on the future roles of AI-driven chatbots in healthcare. Our goal is to pave the way for a healthcare system that is more knowledgeable, efficient, and centered around patient needs.

ADHD is a neurodevelopmental disorder that children and adults can develop. A complex interplay of genetic and environmental factors may underlie interindividual variability in ADHD and potentially related aggressive behavior. Using high-resolution molecular biology techniques, we investigated the impact of some MAOA and SLC6A4 variations on ADHD and aggressive behavior in a group of 80 Italian children with ADHD and in 80 healthy controls. We found that homozygous genotypes of MAOA rs6323 and rs1137070 were associated with an increased risk of ADHD ( = 0.02 and = 0.03, respectively), whereas the heterozygous genotypes (GT of rs6323 and CT of rs1137030) ( = 0.0002 and = 0.0006) were strongly linked to a lower risk of developing this disorder. In patients with aggressive behavior, we highlighted only a weak negative association of both MAOA polymorphisms (heterozygous genotypes) with aggressiveness, suggesting that these genotypes may be protective towards specific changes in behavior ( = 0.05). Interestingly, an increase in the GG genotype of rs6323 ( = 0.01) and a decrease in GT genotype ( = 0.0005) was also found in patients without aggressive behavior compared to controls. Regarding 5HTT gene genotyping, no allele and genotype differences have been detected among patients and controls. Our work shows that defining a genetic profile of ADHD may help in the early detection of patients who are more vulnerable to ADHD and/or antisocial and aggressive behavior and to design precision-targeted therapies.

Although dysregulated stress biology is becoming increasingly recognized as a key driver of lifelong disparities in chronic disease, we presently have no validated biomarkers of toxic stress physiology; no biological, behavioral, or cognitive treatments specifically focused on normalizing toxic stress processes; and no agreed-upon guidelines for treating stress in the clinic or evaluating the efficacy of interventions that seek to reduce toxic stress and improve human functioning. We address these critical issues by (a) systematically describing key systems and mechanisms that are dysregulated by stress; (b) summarizing indicators, biomarkers, and instruments for assessing stress response systems; and (c) highlighting therapeutic approaches that can be used to normalize stress-related biopsychosocial functioning. We also present a novel multidisciplinary Stress Phenotyping Framework that can bring stress researchers and clinicians one step closer to realizing the goal of using precision medicine-based approaches to prevent and treat stress-associated health problems.

Persistent functional impairment is common in bipolar disorder (BD) and is influenced by a number of demographic, clinical, and cognitive features. The goal of this project was to estimate and compare the influence of key factors on community function in multiple cohorts of well-characterized samples of individuals with BD.

Implementation strategies are theorized to work well when carefully matched to implementation determinants and when factors-preconditions, moderators, etc.-that influence strategy effectiveness are prospectively identified and addressed. Existing methods for strategy selection are either imprecise or require significant technical expertise and resources, undermining their utility. This article outlines refinements to causal pathway diagrams (CPDs), a method for articulating the causal process through which implementation strategies work and offers illustrations of their use.

Stigma contributes to a significant part of the burden of schizophrenia (SCZ), therefore reducing false positives from the diagnosis would be liberating for the individuals with SCZ and desirable for the clinicians. The stigmatization associated with schizophrenia advocates the need for high-precision diagnosis. In this study, we present an ensemble learning-based approach for high-precision diagnosis of SCZ using peripheral blood gene expression profiles.

Intracranial aneurysm is a high-risk disease, with imaging playing a crucial role in their diagnosis and treatment. The rapid advancement of artificial intelligence in imaging technology holds promise for the development of AI-based radiomics predictive models. These models could potentially enable the automatic detection and diagnosis of intracranial aneurysms, assess their status, and predict outcomes, thereby assisting in the creation of personalized treatment plans. In addition, these techniques could improve diagnostic efficiency for physicians and patient prognoses. This article aims to review the progress of artificial intelligence radiomics in the study of intracranial aneurysms, addressing the challenges faced and future prospects, in hopes of introducing new ideas for the precise diagnosis and treatment of intracranial aneurysms.

The COVID-19 pandemic has exacerbated mental health challenges, particularly depression among college students. Detecting at-risk students early is crucial but remains challenging, particularly in developing countries. Utilizing data-driven predictive models presents a viable solution to address this pressing need.

Sleep disorders such as insomnia can lead to a range of health problems. The high risk of side effects and drug abuse of traditional pharmacotherapy calls for a safer non-pharmacotherapy.

This study investigated whether self-reported sleep quality is associated with brain amyloid beta (Aβ) accumulation.

Recent advances in genetic and epigenetic research have underscored the significance of 5-hydroxymethylcytosine (5hmC) in neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and intellectual disability (ID), revealing its potential as both a biomarker for early detection and a target for novel therapeutic strategies. This review article provides a comprehensive analysis of the role of 5hmC in NDDs by examining both animal models and human studies. By examining mouse models, studies have demonstrated that prenatal environmental challenges, such as maternal infection and food allergies, lead to significant epigenetic alterations in 5hmC levels, which were associated with NDDs in offspring, impacting social behavior, cognitive abilities and increasing ASD-like symptoms. In human studies, researchers have linked alterations in 5hmC levels NDDs through studies in individuals with ASD, fragile X syndrome, TET3 deficiency and ID, specifically identifying significant epigenetic modifications in genes such as , , and , suggesting that dysregulation of 5hmC played a critical role in the pathogenesis of these disorders and highlighted the potential for targeted therapeutic interventions. Moreover, we explore the implications of these findings for the development of epigenetic therapies aimed at modulating 5hmC levels. The review concludes with a discussion on future directions for research in this field, such as machine learning, emphasizing the need for further studies to elucidate the complex mechanisms underlying NDDs and to translate these findings into clinical practice. This paper not only advances our understanding of the epigenetic landscape of NDDs but also opens up new avenues for diagnosis and treatment, offering hope for individuals affected by these conditions.

Alzheimer's disease (AD) pathology is considered to begin in the brainstem, and cerebral microglia are known to play a critical role in AD pathogenesis, yet little is known about brainstem microglia in AD. Translocator protein (TSPO) PET, sensitive to activated microglia, shows high signal in dorsal brainstem in humans, but the precise location and clinical correlates of this signal are unknown.

Schizophrenia is a polygenic disorder associated with changes in brain structure and function. Integrating macroscale brain features with microscale genetic data may provide a more complete overview of the disease etiology and may serve as potential diagnostic markers for schizophrenia.

Microglia, brain resident macrophages, play multiple roles in maintaining homeostasis, including immunity, surveillance, and protecting the central nervous system through their distinct activation processes. Identifying all types of microglia-driven populations is crucial due to the presence of various phenotypes that differ based on developmental stages or activation states. During embryonic development, the E8.5 yolk sac contains erythromyeloid progenitors that go through different growth phases, eventually resulting in the formation of microglia. In addition, microglia are present in neurological diseases as a diverse population. So far, no individual biomarker for microglia has been discovered that can accurately identify and monitor their development and attributes.

Frailty is the most common medical condition affecting the aging population, and its prevalence increases in the population aged 65 or more. Frailty is commonly diagnosed using the frailty index (FI) or frailty phenotype (FP) assessments. Observational studies have indicated the association of frailty with Alzheimer's disease (AD). However, the shared genetic and biological mechanism of these comorbidity has not been studied. To assess the genetic relationship between AD and frailty, we examined it at single nucleotide polymorphism (SNP), gene, and pathway levels. Overall, 16 genome-wide significant loci (15 unique loci) ( < 5 × 10) and 22 genes (21 unique genes) were identified between AD and frailty using cross-trait meta-analysis. The 8 shared loci implicated 11 genes: , , , , , , , , , , and between AD and FI, and 8 shared loci between AD and FFS implicated 11 genes: , , , , , , , , , , and . The loci 4p16.3 () was identified in both meta-analyses. The colocalization analysis supported the results of our meta-analysis in these loci. The gene-based analysis revealed 80 genes between AD and frailty, and 4 genes were initially identified in our meta-analyses: , , , and . The pathway analysis showed enrichment for lipoprotein particle plasma, amyloid fibril formation, protein kinase regulator, and tau protein binding. Overall, our results provide new insights into the genetics of AD and frailty, suggesting the existence of non-causal shared genetic mechanisms between these conditions.

Many people with bipolar disorder have disrupted circadian rhythms. This means that the timing of sleep and wake activities becomes out-of-sync with the standard 24-hour cycle. Circadian rhythms are strongly influenced by light levels and previous research suggests that people with bipolar disorder might have a heightened sensitivity to light, causing more circadian rhythm disruption, increasing the potential for triggering a mood switch into mania or depression. Lithium has been in clinical use for over 70 years and is acknowledged to be the most effective long-term treatment for bipolar disorder. Lithium has many reported actions in the body but the precise mechanism of action in bipolar disorder remains an active area of research. Central to this project is recent evidence that lithium may work by stabilising circadian rhythms of mood, cognition and rest/activity. Our primary hypothesis is that people with bipolar disorder have some pathophysiological change at the level of the retina which makes them hypersensitive to the visual and non-visual effects of light, and therefore more susceptible to circadian rhythm dysfunction. We additionally hypothesise that the mood-stabilising medication lithium is effective in bipolar disorder because it reduces this hypersensitivity, making individuals less vulnerable to light-induced circadian disruption. We will recruit 180 participants into the HELIOS-BD study. Over an 18-month period, we will assess visual and non-visual responses to light, as well as retinal microstructure, in people with bipolar disorder compared to healthy controls. Further, we will assess whether individuals with bipolar disorder who are being treated with lithium have less pronounced light responses and attenuated retinal changes compared to individuals with bipolar disorder not being treated with lithium. This study represents a comprehensive investigation of visual and non-visual light responses in a large bipolar disorder population, with great translational potential for patient stratification and treatment innovation.