Aleksandra Beric, Sarp Sahin, Santiago Sanchez, Zining Yang, Ravindra Kumar, Isabel Alfradique-Dunham, Jessie Sanford, Daniel Western, Bridget Phillips, John P Budde, Richard J Perrin, Paul T Kotzbauer, Joel S Perlmutter, Scott A Norris, Carlos Cruchaga, Laura Ibanez
{"title":"一项循环血液线性RNA的综合研究表明CD55和DLD是帕金森病的新致病基因和早期生物标志物。","authors":"Aleksandra Beric, Sarp Sahin, Santiago Sanchez, Zining Yang, Ravindra Kumar, Isabel Alfradique-Dunham, Jessie Sanford, Daniel Western, Bridget Phillips, John P Budde, Richard J Perrin, Paul T Kotzbauer, Joel S Perlmutter, Scott A Norris, Carlos Cruchaga, Laura Ibanez","doi":"10.1101/2025.06.20.25329948","DOIUrl":null,"url":null,"abstract":"<p><p>We leveraged transcriptomic data from 4,343 participants from four independent datasets to robustly identify and annotate circulating PD-associated transcripts. We identified 296 differentially expressed transcripts, 28 of which were transcribed from known PD-associated loci. Further, we found a significant overlap between our findings and transcripts dysregulated in brain, as well as proteins differentially accumulated in CSF. Expression of the identified transcripts was affected by genetic background including ancestry and PD-related mutations, and nearly half of the identified transcripts were dysregulated before symptom onset. The differentially expressed transcripts were utilized to develop three predictive models that distinguished between PD and healthy controls with a ROC AUC of 0.727-0.733. The predictive models were capable of detecting PD transcriptomic signatures even before symptom onset. One transcript, <i>DLD</i>, showed particular promise as an early stage, minimally invasive PD biomarker that was differentially expressed in whole blood, brain and CSF. This transcript significantly related to PD in the eQTL analyses and in two of the three predictive models.</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204277/pdf/","citationCount":"0","resultStr":"{\"title\":\"A Comprehensive Study of Circulating Blood Linear RNA nominates <i>CD55</i> and <i>DLD</i> as novel causal genes and early-stage biomarkers for Parkinson's Disease.\",\"authors\":\"Aleksandra Beric, Sarp Sahin, Santiago Sanchez, Zining Yang, Ravindra Kumar, Isabel Alfradique-Dunham, Jessie Sanford, Daniel Western, Bridget Phillips, John P Budde, Richard J Perrin, Paul T Kotzbauer, Joel S Perlmutter, Scott A Norris, Carlos Cruchaga, Laura Ibanez\",\"doi\":\"10.1101/2025.06.20.25329948\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We leveraged transcriptomic data from 4,343 participants from four independent datasets to robustly identify and annotate circulating PD-associated transcripts. We identified 296 differentially expressed transcripts, 28 of which were transcribed from known PD-associated loci. Further, we found a significant overlap between our findings and transcripts dysregulated in brain, as well as proteins differentially accumulated in CSF. Expression of the identified transcripts was affected by genetic background including ancestry and PD-related mutations, and nearly half of the identified transcripts were dysregulated before symptom onset. The differentially expressed transcripts were utilized to develop three predictive models that distinguished between PD and healthy controls with a ROC AUC of 0.727-0.733. The predictive models were capable of detecting PD transcriptomic signatures even before symptom onset. One transcript, <i>DLD</i>, showed particular promise as an early stage, minimally invasive PD biomarker that was differentially expressed in whole blood, brain and CSF. This transcript significantly related to PD in the eQTL analyses and in two of the three predictive models.</p>\",\"PeriodicalId\":94281,\"journal\":{\"name\":\"medRxiv : the preprint server for health sciences\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204277/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv : the preprint server for health sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2025.06.20.25329948\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv : the preprint server for health sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2025.06.20.25329948","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Comprehensive Study of Circulating Blood Linear RNA nominates CD55 and DLD as novel causal genes and early-stage biomarkers for Parkinson's Disease.
We leveraged transcriptomic data from 4,343 participants from four independent datasets to robustly identify and annotate circulating PD-associated transcripts. We identified 296 differentially expressed transcripts, 28 of which were transcribed from known PD-associated loci. Further, we found a significant overlap between our findings and transcripts dysregulated in brain, as well as proteins differentially accumulated in CSF. Expression of the identified transcripts was affected by genetic background including ancestry and PD-related mutations, and nearly half of the identified transcripts were dysregulated before symptom onset. The differentially expressed transcripts were utilized to develop three predictive models that distinguished between PD and healthy controls with a ROC AUC of 0.727-0.733. The predictive models were capable of detecting PD transcriptomic signatures even before symptom onset. One transcript, DLD, showed particular promise as an early stage, minimally invasive PD biomarker that was differentially expressed in whole blood, brain and CSF. This transcript significantly related to PD in the eQTL analyses and in two of the three predictive models.