SCIENTIFIC PUBLICATIONS
Scientific publications from members of the Synapsy community in peer-reviewed journals.
NCCR-Synapsy Phase-3 SNSF grant number : 51NF40-185897
2828886
H5Y6RAZZ
2022
1
apa
50
date
desc
10077
https://nccr-synapsy.ch/wp-content/plugins/zotpress/
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ctors.%20The%20predictive%20combination%20of%20these%20variables%20might%20help%20clinicians%20better%20predict%20which%20patients%20will%20respond%20to%20lithium%20treatment.AimsTo%20use%20a%20combination%20of%20transdiagnostic%20genetic%20and%20clinical%20factors%20to%20predict%20lithium%20response%20in%20patients%20with%20bipolar%20disorder.MethodThis%20study%20utilised%20genetic%20and%20clinical%20data%20%28n%20%3D%201034%29%20collected%20as%20part%20of%20the%20International%20Consortium%20on%20Lithium%20Genetics%20%28ConLi%2BGen%29%20project.%20Polygenic%20risk%20scores%20%28PRS%29%20were%20computed%20for%20schizophrenia%20and%20major%20depressive%20disorder%2C%20and%20then%20combined%20with%20clinical%20variables%20using%20a%20cross-validated%20machine-learning%20regression%20approach.%20Unimodal%2C%20multimodal%20and%20genetically%20stratified%20models%20were%20trained%20and%20validated%20using%20ridge%2C%20elastic%20net%20and%20random%20forest%20regression%20on%20692%20patients%20with%20bipolar%20disorder%20from%20ten%20study%20sites%20using%20leave-site-out%20cross-validation.%20All%20models%20were%20then%20tested%20on%20an%20independent%20test%20set%20of%20342%20patients.%20The%20best%20performing%20models%20were%20then%20tested%20in%20a%20classification%20framework.ResultsThe%20best%20performing%20linear%20model%20explained%205.1%25%20%28P%20%3D%200.0001%29%20of%20variance%20in%20lithium%20response%20and%20was%20composed%20of%20clinical%20variables%2C%20PRS%20variables%20and%20interaction%20terms%20between%20them.%20The%20best%20performing%20non-linear%20model%20used%20only%20clinical%20variables%20and%20explained%208.1%25%20%28P%20%3D%200.0001%29%20of%20variance%20in%20lithium%20response.%20A%20priori%20genomic%20stratification%20improved%20non-linear%20model%20performance%20to%2013.7%25%20%28P%20%3D%200.0001%29%20and%20improved%20the%20binary%20classification%20of%20lithium%20response.%20This%20model%20stratified%20patients%20based%20on%20their%20meta-polygenic%20loadings%20for%20major%20depressive%20disorder%20and%20schizophrenia%20and%20was%20then%20trained%20using%20clinical%20data.ConclusionsUsing%20PRS%20to%20first%20stratify%20patients%20genetically%20and%20then%20train%20machine-learning%20models%20with%20clinical%20predictors%20led%20to%20large%20improvements%20in%20lithium%20response%20prediction.%20When%20used%20with%20other%20PRS%20and%20biological%20markers%20in%20the%20future%20this%20approach%20may%20help%20inform%20which%20patients%20are%20most%20likely%20to%20respond%20to%20lithium%20treatment.%22%2C%22date%22%3A%222022%5C%2F04%22%2C%22language%22%3A%22en%22%2C%22DOI%22%3A%2210.1192%5C%2Fbjp.2022.28%22%2C%22ISSN%22%3A%220007-1250%2C%201472-1465%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.cambridge.org%5C%2Fcore%5C%2Fjournals%5C%2Fthe-british-journal-of-psychiatry%5C%2Farticle%5C%2Fusing-polygenic-scores-and-clinical-data-for-bipolar-disorder-patient-stratification-and-lithium-response-prediction-machine-learning-approach%5C%2F6AFF9E8BD7D3E7E086898EDB9522AAC1%22%2C%22collections%22%3A%5B%22H5Y6RAZZ%22%5D%2C%22dateModified%22%3A%222022-05-24T10%3A46%3A49Z%22%7D%7D%2C%7B%22key%22%3A%22WEIV9D8G%22%2C%22library%22%3A%7B%22id%22%3A2828886%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Tzanoulinou%20et%20al.%22%2C%22parsedDate%22%3A%222022-04%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BTzanoulinou%2C%20S.%2C%20Musardo%2C%20S.%2C%20Contestabile%2C%20A.%2C%20Bariselli%2C%20S.%2C%20Casarotto%2C%20G.%2C%20Magrinelli%2C%20E.%2C%20Jiang%2C%20Y.%2C%20Jabaudon%2C%20D.%2C%20%26amp%3B%20Bellone%2C%20C.%20%282022%29.%20Inhibition%20of%20Trpv4%20rescues%20circuit%20and%20social%20deficits%20unmasked%20by%20acute%20inflammatory%20response%20in%20a%20Shank3%20mouse%20model%20of%20Autism.%20%26lt%3Bi%26gt%3BMolecular%20Psychiatry%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B27%26lt%3B%5C%2Fi%26gt%3B%284%29%2C%202080%26%23x2013%3B2094.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41380-021-01427-0%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41380-021-01427-0%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Inhibition%20of%20Trpv4%20rescues%20circuit%20and%20social%20deficits%20unmasked%20by%20acute%20inflammatory%20response%20in%20a%20Shank3%20mouse%20model%20of%20Autism%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stamatina%22%2C%22lastName%22%3A%22Tzanoulinou%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Stefano%22%2C%22lastName%22%3A%22Musardo%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22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