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Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders

2023-06-10Conference object Open access
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dc.contributor.authorVilela, Joana
dc.contributor.authorMartiniano, Hugo
dc.contributor.authorMarques, Ana Rita
dc.contributor.authorSantos, João
dc.contributor.authorRasga, Célia
dc.contributor.authorOliveira, Guiomar
dc.contributor.authorVicente, Astrid Moura
dc.date.accessioned2024-01-05T16:43:55Z
dc.date.available2024-01-05T16:43:55Z
dc.date.issued2023-06-10
dc.description.abstractBackground/Objectives: Autism Spectrum Disorder (ASD) is a clinically heterogeneous neurodevelopmental disorder , with variable severity and multiple comorbidities. Given the previous evidence of genetic overlap between ASD and several comorbid brain disorders, we sought to explore the genetic similarity with ASD across a range of brain disorders, using a genetic similarity disease network approach. Methods: We developed a genetic similarity disease network between ASD and Intellectual Disability, Attention-Deficit/Hyperactivity Disorder, Epilepsy, Schizophrenia and Bipolar Disease spectrum. Using gene-disease associations from the DisGeNET database, genetic similarities were estimated from the Jaccard coefficient between disease pairs. The Leiden algorithm identified network disease communities and shared biological pathways. Loss-of-function (LoF) rare de novo variants within shared genes underlying the disease communities were identified using the MSSNG whole-genome sequencing dataset. Results: We identified three disease communities. ASD is included in a heterogeneous community with Epilepsy, Bipolar Disorder, Attention-Deficit/Hyperactivity Disorder combined type, and some disorders in the Schizophrenia Spectrum. ASD and Intellectual Disability are in separate communities. The genes SHANK3, ASH1L, SCN2A, and CHD2, which are candidate genes for diseases in all communities, have a higher number of de novo rare LoF SNVs in ASD subjects. Conclusion: This approach enabled further clarification of genetic sharing between ASD and comorbid brain disorders, as we took advantage from a finer granularity in disease classification and multi-level evidence from DisGeNET, with important implications for disease nosology, pathophysiology, and personalized treatment.pt_PT
dc.description.sponsorshipFundação para a Ciência e a Tecnologia: BioSys PhD programme (Ref: PD/BD/131390/2017 from FCT (Portugal).; MEDPERSYST:PAC-POCI-01-0145-FEDER 016428;DeePer:(EXPL/CCI-BIO/0126/2021);National Institute of Health Doutor Ricardo Jorge.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.pmid36061363
dc.identifier.urihttp://hdl.handle.net/10400.18/8875
dc.language.isoengpt_PT
dc.peerreviewednopt_PT
dc.publisherInstituto Nacional de Saúde Doutor Ricardo Jorge, IPpt_PT
dc.relationRegulatory RNAs in Autism Spectrum Disorder - modulation of genomic variant effects on clinical phenotype and brain structure and function
dc.relationDeep graph learning approaches to personalized medicine
dc.subjectAutism Spectrum Disorder (ASD)pt_PT
dc.subjectPsychiatric Geneticspt_PT
dc.subjectCross-disorder Geneticspt_PT
dc.subjectBrain Disorderspt_PT
dc.subjectDisease Similaritypt_PT
dc.subjectNetwork Analysispt_PT
dc.subjectDisease Communitypt_PT
dc.subjectDe Novo Mutationspt_PT
dc.subjectAutismpt_PT
dc.subjectPerturbações do Desenvolvimento Infantil e Saúde Mentalpt_PT
dc.titleDisease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorderspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleRegulatory RNAs in Autism Spectrum Disorder - modulation of genomic variant effects on clinical phenotype and brain structure and function
oaire.awardTitleDeep graph learning approaches to personalized medicine
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/OE/PD%2FBD%2F131390%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/EXPL%2FCCI-BIO%2F0126%2F2021/PT
oaire.citation.conferencePlaceGlasgow, Scotland, UKpt_PT
oaire.citation.titleEuropean Human Genetics Conference (ESHG), 10-13 June 2023pt_PT
oaire.fundingStreamOE
oaire.fundingStream3599-PPCDT
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isProjectOfPublication6248bf80-c308-48f9-822e-292782c9cae6
relation.isProjectOfPublication60040884-c76b-420a-adf1-6486acd375ef
relation.isProjectOfPublication.latestForDiscovery60040884-c76b-420a-adf1-6486acd375ef

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