European Neuropsychopharmacology最新文献

{"title":"LINKING CELL STATES TO THE HERITABILITY OF DEPRESSION, COMBINING A NOVEL SINGLE-CELL ANALYSIS WITH POPULATION LEVEL DATA","authors":"Jareth Wolfe","doi":"10.1016/j.euroneuro.2024.08.026","DOIUrl":"10.1016/j.euroneuro.2024.08.026","url":null,"abstract":"<div><div>When interrogating single-cell datasets, we are interested both in what cells are, as well as what they do. Cell states represent dynamic behaviour and activities including cell cycle stage, level of maturity, response to stimuli, and spatial location. It can be difficult to disentangle states from cell type using traditional clustering approaches but STATOR, a methodology we developed recently, allows for finer resolution of cell type, subtype and state. STATOR can identify states within cell types that appear to be homogenous when clustered and displayed on two-dimensional PCA or UMAP plot. Once these states have been identified, further downstream analysis is required to understand the biological function of these cells and their contribution to disease.</div><div>The Major Depressive Disorder (MDD) working group of the PGC has recently made their MDD3 GWAS results available. This work represents the largest and most diverse GWAS study to date, providing a powerful population level tool for investigating the impact of individual variants to incidence of MDD. In addition, case vs control single-cell datasets for men and women with and without MDD, taken from the dorsolateral prefrontal cortex, have recently been published. By using published single-cell case vs control MDD datasets, we have identified cell states enriched in MDD. We then performed differential gene expression on cells with and without identified states. We then used the regions around these genes to perform stratified LD score regression using the MDD3 GWAS results.</div><div>Linking individual cell states, along with the cell types and sub-types, to population level MDD data can provide insights into what functional role sequence variation may be having at a cellular level. Determining the mechanism by which variant can be linked to trait can improve our understanding of the underlying molecular processes involved in the incidence of MDD, as well as provide opportunities for investigating potential mechanisms for intervention in the future.</div><div>While this work is presented in the context of MDD, the methodology can be used for any condition of interest where case vs control single-cell data and GWAS results are available.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EQUITABLE COLLABORATION BETWEEN HIGH-INCOME AND LOW- AND MIDDLE-INCOME COUNTRIES","authors":"Brenda Cabrera-Mendoza ,&nbsp;Anna Docherty ,&nbsp;Renato Polimanti","doi":"10.1016/j.euroneuro.2024.08.059","DOIUrl":"10.1016/j.euroneuro.2024.08.059","url":null,"abstract":"<div><div>International collaborations between high-income countries (HICs) and low- and middle-income countries (LMICs) have become crucial in advancing global health, particularly within psychiatric research. These partnerships are instrumental in accelerating scientific discovery and enhancing public health; however, they also highlight significant equity and fairness challenges. Specifically, research partnerships often suffer from imbalances, such as \"helicopter\" research approaches by HICs and the exploitation or marginalization of LMIC researchers.</div><div>Through periodic online meetings held by members of the International Society for Psychiatric Genetics, they have shared their experience in these collaborations and identified gaps in current practices to better refine future collaborative efforts. From these discussions, we have outlined key considerations and strategies for planning, implementing, and disseminating collaborative research. Throughout the collaboration process, we identified potential challenges and opportunities, and provided recommendations to optimize the benefits of such partnerships.</div><div>Among our considerations we highlight that Equitable Collaboration begins with comprehensive stakeholder engagement, fostering a participatory environment that includes local communities, governments, and institutions from both HICs and LMICs. Planning and research design should be conducted inclusively emphasizing cultural sensitivity and contextual relevance. Training initiatives are also recommended to be implemented to empower local stakeholders to actively contribute to the research process. As the research progresses, close collaboration between HIC and LMIC researchers could facilitate knowledge exchange and equitable benefit distribution. Ideally, these results are translated into local health policy improvements, promoting sustainable development and empowerment in LMICs. Among potential challenges are differences in ethical research and data sharing frameworks across collaborating countries, inequality in research resources and infrastructure, reduced visibility of research performed in LMICs, which can significantly impact the research outcomes and their applicability, among others.</div><div>In conclusion, while global collaboration in psychiatric genetics presents complex challenges, it also offers substantial opportunities for impactful research and improved global mental health. By committing to careful planning, effective communication, ethical practices, and supportive policies, we can foster more equitable health outcomes worldwide.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BUILDING RESOURCES FOR THE DIVERSIFICATION OF GENOMIC DATA ON SUICIDE MORTALITY","authors":"Chittaranjan Behera ,&nbsp;Ruchika Kaushik ,&nbsp;Bichitra Nand Patra ,&nbsp;Partha Haldar ,&nbsp;Sujata Sathtapathy Satapathy ,&nbsp;Seonggyun Han ,&nbsp;Emily DiBlasi ,&nbsp;Warren Pettine ,&nbsp;Hilary Coon ,&nbsp;Andrey Shabalin ,&nbsp;Anna Docherty","doi":"10.1016/j.euroneuro.2024.08.051","DOIUrl":"10.1016/j.euroneuro.2024.08.051","url":null,"abstract":"&lt;div&gt;&lt;div&gt;To date, a lack of population-based genetic data from under-represented populations continues to limit the impact and global generalizability of large-scale genetic and epidemiological studies of suicide mortality. India represents the majority of global suicide deaths: 36.6% of global suicide deaths among females, and 24.3% among males. Moreover, the suicide rate among girls and women in India is twice the global rate. In addition to genetic risk factors, there are myriad unique cultural and environmental factors that are expected to influence risk for suicide in low- to middle-income countries (LMICs): Four in five suicides in young people (&lt;30 years) globally occur in LMICs, and a better understanding of suicide in these regions will be critical for designing new prevention initiatives and reducing global suicide rates. Professor Chittaranjan Behera M.D., of the All-India Institute for Medical Sciences in Delhi, will present a collaborative study, supported by the Fogarty International Center and the National Institutes of Health, to facilitate the collection of blood, brain tissue, phenotypic and toxicology information, and psychological autopsy data in Delhi, India. Collection is currently underway and will include 4,000 population-based postmortem suicide deaths and postmortem controls, with collection brain tissue from half of this cohort. This study is intended to develop a lasting, impactful global research resource in India, with partnership between the All-India Institute for Medical Sciences in Delhi and the University of Utah School of Medicine. This study currently represents the first collection of non-European suicide postmortem blood and brain tissue in the world, and it is hoped that this new comparison population will significantly impact our current models of suicide risk. For example, for the first time, top loci in large genetic analyses of suicide can be studied across ancestral populations and can be validated in secondary analyses of differential gene expression in postmortem brain. Polygenic profiling of population-based suicide has also informed our understanding of suicide mortality in the U.S., where a majority of individuals who die lack any mental health diagnoses or other medical records, and where these individuals typically differ both demographically and clinically from people who attempt suicide but do not die. Pilot genetic data examined by the research team suggest 1) that GWAS summary data from this study will significantly improve the generalizability and out-of-sample polygenic prediction of global GWAS meta-analyses, 2) that there is some portability of polygenic prediction of suicide phenotypes across Indian and European ancestry admixtures, and 3) that polygenic profiling of comparative risks in an Indian population is possible. With this close research partnership, we hope to gain a valuable and representative comparison cohort with which to better understand suicide risks, and to lay the ","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ENHANCING UNDERSTANDING OF MENTAL DISORDERS THROUGH INTEGRATION OF GENOMIC AND LIFE-COURSE DATA","authors":"Alex Kwong (Chair) ,&nbsp;Robyn Wootton (Co-chair) ,&nbsp;Michel Nivard (Discussant)","doi":"10.1016/j.euroneuro.2024.08.089","DOIUrl":"10.1016/j.euroneuro.2024.08.089","url":null,"abstract":"&lt;div&gt;&lt;div&gt;There has been substantial progress into the genomic underpinnings of mental disorders, such as depression, which have led to the identification of hundreds of key genomic loci, enhanced understanding of causal pathways and improved direction for drug targets. However, despite such progress, our actual understanding of the genetic mechanisms underlying these mental disorders, and therefore our ability to develop better treatments is still limited.&lt;/div&gt;&lt;div&gt;One reason for this research has tended to focus on lifetime or cross-sectional effects, but mental disorders are not static, they change over time and may have periods where genetic effects are more prominent. Similarly, life-course approaches postulate that repeated information from the same person over time are likely to be highly correlated and leveraging that correlation can reduce measurement error and improve signal. Combing life-course and genomic (genome-wide association studies [GWAS], polygenic risk scores [PRS], mendelian randomization [MR]) approaches are becoming more common with the emergence of large-scale longitudinal biobanks, availability of genetic data and new statistical methods. This integration of both these approaches could lead to an enhanced understanding of the genomics of mental disorder more broadly, but also how genetics influence the onset, course and persistence of mental disorders across the life-course.&lt;/div&gt;&lt;div&gt;In this symposium, we will highlight emerging work from this field that demonstrates the utility of combining genomic and life-course methods for improved understanding of mental disorders.&lt;/div&gt;&lt;div&gt;First, Alex Kwong (Edinburgh) will show that leveraging repeated assessments of depression from large datasets such as UK Biobank improve the signal in GWAS, resulting in a greater number of genome-wide significant hits, more mapped genes, higher single nucleotide polymorphism (SNP) based heritability and higher amount of variance explained in PRS analysis. Importantly, this approach identifies greater GWAS signal in non-European ancestries, providing a framework for potentially improving gene discovery in future studies.&lt;/div&gt;&lt;div&gt;Next, Poppy Grimes (Edinburgh) will present the latest PGC-MDD and EAGLE consortia results from an adolescent onset depression GWAS using repeated data from prospective and retrospective cohorts. These results show good genetic correlation between prospective and retrospective cohorts, but importantly also identifies novel GWAS hits, some of which are common or unique to adult MDD.&lt;/div&gt;&lt;div&gt;Following, Robyn Wootton (Oslo) will demonstrate how MR can be implemented within longitudinal studies to examine the causal effect of predictors on specific periods of depression development, rather than just on averaged lifetime effects. Using data spanning over 30 years from the ALSPAC study, these results show how predictors such as BMI and educational attainment may be causal of later depression development.&lt;/div&gt;&lt;div&gt;Finall","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SENSITIVE PERIODS FOR CHILDHOOD ADVERSITY AND DNA METHYLATION: META-ANALYSIS RESULTS AND DNA METHYLATION RISK SCORES","authors":"","doi":"10.1016/j.euroneuro.2024.08.086","DOIUrl":"10.1016/j.euroneuro.2024.08.086","url":null,"abstract":"","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EXPLORING THE MISSING GENETICS UNDERLYING NEUROPSYCHIATRIC DISORDERS WITH FUNCTIONAL GENOMICS","authors":"","doi":"10.1016/j.euroneuro.2024.08.057","DOIUrl":"10.1016/j.euroneuro.2024.08.057","url":null,"abstract":"","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FAMILY-BASED STUDIES IN PSYCHIATRIC GENOMICS: PROGRESS AND RELEVANCE IN 2024","authors":"Aiden Corvin (Chair) ,&nbsp;Andrew McIntosh (Co-chair) ,&nbsp;Niamh Ryan (Discussant)","doi":"10.1016/j.euroneuro.2024.08.079","DOIUrl":"10.1016/j.euroneuro.2024.08.079","url":null,"abstract":"<div><div>To our knowledge it is ten years since the last symposium on pedigree-based analyses at the WCPG. In the era of whole genome sequencing a review is timely. As costs fall, the field of psychiatric genomics is transitioning from GWAS to next generation sequencing, with power to expand our understanding of the contribution of rare mutations to genetic burden across disorders. Identified rare pathogenic variants may be more informative in understanding disease biology than the common variants of small effect that represent the majority of discovery to date.</div><div>Rare variant association studies require sample sizes an order of magnitude larger than GWAS studies. This is because rare mutations tend to be selected against in populations over a few generations. However, such mutations may be identifiable where multiple generations of the same family are available. Moreover, families do not suffer the same population stratification or other confounds that are present at a population level. This approach, with small sample numbers in a family, allows for detailed phenotypic assessment and is accessible to clinicians and researchers with limited resources who want to contribute to the field.</div><div>This symposium will provide an update on progress made in ASD, where significant understanding of the genetic architecture and disease biology is emerging, in part due to trio- and quad-based approaches. We review progress from the PGC Pedigree Sequencing Group with an example of how sequencing individual families, with small numbers of individuals can identify relevant risk mutations only identifiable with thousands of samples using case-control approaches. We describe progress in other adult disorders from the international \"Pedigree-Based Whole Genome Sequencing of Affective and Psychotic Disorders\" consortium. Finally, we review the findings from colleagues working in India who are applying pedigree-based sequencing study approaches across disorders. Across presentations we consider recruitment, and how emerging findings indicate a need for broader inclusion criteria within families than might traditionally have been considered. This session will also present new methods for investigating pedigrees in the era of whole genome sequencing.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CROSS-DISORDER RARE VARIANT ANALYSIS OF AUTISM AND ADHD","authors":"Jinjie Duan ,&nbsp;Jakob Grove ,&nbsp;Ditte Demontis ,&nbsp;F. Kyle Satterstrom ,&nbsp;Jack Fu ,&nbsp;Caitlin Carey ,&nbsp;Stephan Sanders ,&nbsp;Bernie Devlin ,&nbsp;Kathryn Roeder ,&nbsp;Joseph Buxbaum ,&nbsp;Elise Robinson ,&nbsp;Michael Talkowski ,&nbsp;Benjamin Neale ,&nbsp;Mark Daly ,&nbsp;Anders Børglum","doi":"10.1016/j.euroneuro.2024.08.047","DOIUrl":"10.1016/j.euroneuro.2024.08.047","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental disorders with high heritability and frequent co-occurrence. Our previous work on the first phase of iPSYCH exomes (Satterstrom et al., 2019) suggested a similar burden of rare protein-truncating variants (PTVs) across ASD and ADHD and identified MAP1A as a shared risk gene implicated by rare PTVs in both disorders. This study aims to 1) extend these findings, employing a significantly larger iPSYCH exome dataset for gene discovery, 2) estimate the burden heritability explained by rare coding variants in ASD and ADHD, and 3) assess the burden genetic correlation between the two disorders.&lt;/div&gt;&lt;div&gt;We analyzed exomes of 25,208 individuals from iPSYCH, encompassing 7,119 individuals diagnosed with ASD alone (ASD-only), 5,598 with ADHD alone (ADHD-only), 3,794 with both ASD and ADHD (ASD+ADHD), and 8,697 controls. We used multivariate Poisson regression models to systematically evaluate rare variant burdens in different gene sets across the three case groups and controls, stratified further by the presence or absence of intellectual disability (ID). The gene sets included all genes, genes intolerant to loss-of-function variants (pLI &gt; 0.9), and gene sets associated with different disorders including ID, ASD, ADHD, schizophrenia, and a broader group of neurodevelopmental disorders. We applied c-alpha tests to assess whether the distribution of rare deleterious variants differs between ASD and ADHD. We employed burden heritability regression to estimate the burden heritability of ASD and ADHD, respectively, and the burden genetic correlation between the two disorders. For gene discovery, we combined individuals diagnosed with ASD and/or ADHD into a single case group and applied TADA+ to integrate with family data and Swedish PAGES case-control data from a recent large-scale ASD rare variant study (Fu et al., 2022).&lt;/div&gt;&lt;div&gt;We observed similar burdens of class I variants including rare PTVs and rare deleterious missense variants (MPC &gt; 3) in constrained genes across the three case groups, while they all showed a significant excess compared to controls: OR = 1.35, 95% CI = [1.26, 1.45] for ASD-only; OR = 1.35, CI = [1.25, 1.45] for ADHD-only; and OR = 1.39, CI = [1.28, 1.52] for ASD+ADHD. The c-alpha tests indicated no significant differences in the distribution of class I variants in constrained genes between ASD-only and ADHD-only groups (P= 0.39) while, when comparing the case groups to controls, significant differences were observed. The burden heritability of class I variants on the liability scale was estimated to 1.87% (SE = 0.51%) for ASD and 2.42% (s.e. = 0.72%) for ADHD. The class I variant burden genetic correlation between ASD and ADHD was 0.31 (s.e. = 0.26), which approximates the point estimate of their common-variant genetic correlation of 0.42 (s.e. = 0.05) (Demontis et al., 2023).&lt;/div&gt;&lt;div&gt;Our findi","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"POLYGENIC RISK SCORES FOR A SPECTRUM OF PSYCHIATRIC OUTCOMES ARE ALSO ASSOCIATED WITH DEPRESSION TRAJECTORIES FROM CHILDHOOD TO EARLY ADULTHOOD: FINDINGS FROM THE AVON LONGITUDINAL STUDY OF PARENTS AND CHILDREN","authors":"Ruby Tsang,&nbsp;Nicholas Timpson","doi":"10.1016/j.euroneuro.2024.08.093","DOIUrl":"10.1016/j.euroneuro.2024.08.093","url":null,"abstract":"<div><div>Depression is a complex and multifactorial disorder that has genetic and environmental influences. Genome-wide association studies have shown that common genetic variants are implicated in depression. These common variants, when combined into polygenic risk scores, are associated with depression case status, severity and age of onset. However, less is known about how genetic risk affects change in depression symptoms longitudinally. Furthermore, psychiatric disorders are comorbid and recent studies have shown genetic risk is shared between them, but the association between this shared polygenic risk and how depression manifests and changes over time is not yet understood.</div><div>We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC). Self-reported depressive symptoms were assessed on 10 occasions between the ages of 10 and 25 using the 13-item Short Mood and Feelings Questionnaire. Polygenic risk scores (PRS) for major depressive disorder (MDD), anxiety (ANX), neuroticism (NEU), and schizophrenia (SCZ) were computed with PRSice-2 using summary statistics from recent genome-wide associations studies, in which ALSPAC was not included. Additionally, we used genomic structural equation modelling (GSEM) to create a multi-trait PRS of MDD, ANX, NEU, SCZ, bipolar disorder, autism spectrum disorder, and attention deficit hyperactivity disorder, to capture the spectrum of psychopathology and explored how this genetic risk score was associated with depression trajectories.</div><div>We modelled depression trajectories using generalised additive models, with age as the time metric, and included sex, age-sex interaction, PRS, age-PRS interaction, and the first 10 principal components as predictors. We ran separate models for each PRS.</div><div>Depression trajectories for those in the top and bottom deciles of MDD and NEU PRS start to show divergence around mid- to late-adolescence with higher genetic risk associated with worse trajectories. With the multi-trait PRS, differences emerge as early as childhood, again with higher genetic risk indicative of worse trajectories. In these three models, the separation between the trajectories then continues to increase into adulthood. No clear pattern of separation was observed with the ANX or SCZ PRS.</div><div>These findings suggest that psychiatric PRS are associate with (and may influence) the longitudinal course of depressive symptoms from childhood into early adulthood. The multi-trait PRS was superior to PRS of individual psychiatricdisorders in delineating depression trajectories in association with genetic risk. One interpretation is that a spectrum of psychiatric genetic risk could underpin developmental differences in depression trajectories.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FUNCTIONAL GENOMIC APPROACHES WITH SINGLE-CELL RESOLUTION PROVIDE MECHANISTIC AND BIOLOGICAL INSIGHTS BASED ON GENETIC ASSOCIATION STUDIES","authors":"Jens Hjerling-Leffler (Chair) ,&nbsp;Mary-Ellen Lynall (Co-chair) ,&nbsp;Shuyang Yao Ph.D. (Discussant)","doi":"10.1016/j.euroneuro.2024.08.023","DOIUrl":"10.1016/j.euroneuro.2024.08.023","url":null,"abstract":"<div><div>With few exceptions, the marked advances in knowledge about the genetic basis for psychiatric disorders have not converged on findings that can be confidently used for systematically interrogating underlying mechanisms for disease onset and progression. Functional genomics aims to provide mechanistic insights from genetic association studies and has the potential to facilitate biological insight. This series of presentations is from members of the newly started PGC working group for Functional Genomics and showcases how the use of data and methodology with single-cell resolution can further our understanding of the etiology of psychiatric disorders and the mechanism of drug action. The first talk describes an approach that allows the identification and characterization of cell type-specific and/or dynamic regulatory elements. The second talk leverages a new method to analyze cellular states and how these states relate to heritability enrichment for major depression disorder. The third talk describes a meta-analysis for optimizing sampling parameters for single-cell case/control studies which will provide much-needed rigor to an emerging field of study. The fourth talk is on the analysis of peripheral blood samples in the search for an immunological component to psychiatric disorders. Our four speakers all have expertise in single-cell methods and genetic association analysis. Each speaker has a complimentary background and methodological approach and will present the latest findings alongside the strengths and limitations of each approach and the datasets on which these analyses are based.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":null,"pages":null},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}