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      Epigenome-wide analysis identifies methylome profiles linked to obsessive-compulsive disorder, disease severity, and treatment response

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          Abstract

          Obsessive-compulsive disorder (OCD) is a prevalent mental disorder affecting ~2–3% of the population. This disorder involves genetic and, possibly, epigenetic risk factors. The dynamic nature of epigenetics also presents a promising avenue for identifying biomarkers associated with symptom severity, clinical progression, and treatment response in OCD. We, therefore, conducted a comprehensive case-control investigation using Illumina MethylationEPIC BeadChip, encompassing 185 OCD patients and 199 controls recruited from two distinct sites in Germany. Rigorous clinical assessments were performed by trained raters employing the Structured Clinical Interview for DSM-IV (SCID-I). We performed a robust two-step epigenome-wide association study that led to the identification of 305 differentially methylated CpG positions. Next, we validated these findings by pinpointing the optimal set of CpGs that could effectively classify individuals into their respective groups. This approach identified a subset comprising 12 CpGs that overlapped with the 305 CpGs identified in our EWAS. These 12 CpGs are close to or in genes associated with the sweet-compulsive brain hypothesis which proposes that aberrant dopaminergic transmission in the striatum may impair insulin signaling sensitivity among OCD patients. We replicated three of the 12 CpGs signals from a recent independent study conducted on the Han Chinese population, underscoring also the cross-cultural relevance of our findings. In conclusion, our study further supports the involvement of epigenetic mechanisms in the pathogenesis of OCD. By elucidating the underlying molecular alterations associated with OCD, our study contributes to advancing our understanding of this complex disorder and may ultimately improve clinical outcomes for affected individuals.

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          DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

          The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.
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            The epidemiology of obsessive-compulsive disorder in the National Comorbidity Survey Replication.

            Despite significant advances in the study of obsessive-compulsive disorder (OCD), important questions remain about the disorder's public health significance, appropriate diagnostic classification, and clinical heterogeneity. These issues were explored using data from the National Comorbidity Survey Replication, a nationally representative survey of US adults. A subsample of 2073 respondents was assessed for lifetime Diagnostic and Statistical Manual of Mental Disorders, 4th edn (DSM-IV) OCD. More than one quarter of respondents reported experiencing obsessions or compulsions at some time in their lives. While conditional probability of OCD was strongly associated with the number of obsessions and compulsions reported, only small proportions of respondents met full DSM-IV criteria for lifetime (2.3%) or 12-month (1.2%) OCD. OCD is associated with substantial comorbidity, not only with anxiety and mood disorders but also with impulse-control and substance use disorders. Severity of OCD, assessed by an adapted version of the Yale-Brown Obsessive Compulsive Scale, is associated with poor insight, high comorbidity, high role impairment, and high probability of seeking treatment. The high prevalence of subthreshold OCD symptoms may help explain past inconsistencies in prevalence estimates across surveys and suggests that the public health burden of OCD may be greater than its low prevalence implies. Evidence of a preponderance of early onset cases in men, high comorbidity with a wide range of disorders, and reliable associations between disorder severity and key outcomes may have implications for how OCD is classified in DSM-V.
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              Tutorial: a guide to performing polygenic risk score analyses

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                Author and article information

                Contributors
                alfredo.ramirez-zuniga@uk-koeln.de
                Journal
                Mol Psychiatry
                Mol Psychiatry
                Molecular Psychiatry
                Nature Publishing Group UK (London )
                1359-4184
                1476-5578
                16 August 2023
                16 August 2023
                2023
                : 28
                : 10
                : 4321-4330
                Affiliations
                [1 ]Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, ( https://ror.org/00rcxh774) 50937 Cologne, Germany
                [2 ]Department of Psychiatry and Psychotherapy, University Hospital Bonn, ( https://ror.org/01xnwqx93) Bonn, Germany
                [3 ]German Center for Neurodegenerative Diseases (DZNE), ( https://ror.org/043j0f473) Bonn, Germany
                [4 ]Department of Psychology, Humboldt-Universität zu Berlin, ( https://ror.org/01hcx6992) Berlin, Germany
                [5 ]Department of Medicine, MSB Medical School Berlin, ( https://ror.org/001vjqx13) Berlin, Germany
                [6 ]Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, ( https://ror.org/01xnwqx93) Bonn, Germany
                [7 ]Department of Psychiatry and Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, TX USA
                [8 ]GRID grid.6190.e, ISNI 0000 0000 8580 3777, Cluster of Excellence Cellular Stress Responses in Aging-associated Diseases (CECAD), , University of Cologne, ; Cologne, Germany
                Author information
                http://orcid.org/0000-0002-1395-8571
                http://orcid.org/0000-0001-6876-518X
                http://orcid.org/0000-0003-2589-6440
                http://orcid.org/0000-0003-4991-763X
                Article
                2219
                10.1038/s41380-023-02219-4
                10827661
                37587247
                8ca15802-e780-42aa-9482-48eaaae38ac1
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 23 February 2023
                : 27 July 2023
                : 4 August 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: RA1971/8-1
                Award ID: RA1971/7-1
                Award ID: KA815/6-1
                Award ID: WA731/10-1
                Award ID: WA731/15-1
                Award Recipient :
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2023

                Molecular medicine
                diagnostic markers,genetics,predictive markers
                Molecular medicine
                diagnostic markers, genetics, predictive markers

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