Iddo Magen, Nancy-Sarah Yacovzada, Jason D Warren, Carolin Heller, Imogen Swift, Yoana Bobeva, Andrea Malaspina, Jonathan D Rohrer, Pietro Fratta, Eran Hornstein
{"title":"microRNA-based predictor for diagnosis of frontotemporal dementia.","authors":"Iddo Magen, Nancy-Sarah Yacovzada, Jason D Warren, Carolin Heller, Imogen Swift, Yoana Bobeva, Andrea Malaspina, Jonathan D Rohrer, Pietro Fratta, Eran Hornstein","doi":"10.1111/nan.12916","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>This study aimed to explore the non-linear relationships between cell-free microRNAs (miRNAs) and their contribution to prediction of Frontotemporal dementia (FTD), an early onset dementia that is clinically heterogeneous, and too often suffers from delayed diagnosis.</p><p><strong>Methods: </strong>We initially studied a training cohort of 219 subjects (135 FTD and 84 non-neurodegenerative controls) and then validated the results in a cohort of 74 subjects (33 FTD and 41 controls).</p><p><strong>Results: </strong>On the basis of cell-free plasma miRNA profiling by next generation sequencing and machine learning approaches, we develop a non-linear prediction model that accurately distinguishes FTD from non-neurodegenerative controls in ~90% of cases.</p><p><strong>Conclusions: </strong>The fascinating potential of diagnostic miRNA biomarkers might enable early-stage detection and a cost-effective screening approach for clinical trials that can facilitate drug development.</p>","PeriodicalId":19151,"journal":{"name":"Neuropathology and Applied Neurobiology","volume":"49 4","pages":"e12916"},"PeriodicalIF":4.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuropathology and Applied Neurobiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/nan.12916","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Aims: This study aimed to explore the non-linear relationships between cell-free microRNAs (miRNAs) and their contribution to prediction of Frontotemporal dementia (FTD), an early onset dementia that is clinically heterogeneous, and too often suffers from delayed diagnosis.
Methods: We initially studied a training cohort of 219 subjects (135 FTD and 84 non-neurodegenerative controls) and then validated the results in a cohort of 74 subjects (33 FTD and 41 controls).
Results: On the basis of cell-free plasma miRNA profiling by next generation sequencing and machine learning approaches, we develop a non-linear prediction model that accurately distinguishes FTD from non-neurodegenerative controls in ~90% of cases.
Conclusions: The fascinating potential of diagnostic miRNA biomarkers might enable early-stage detection and a cost-effective screening approach for clinical trials that can facilitate drug development.
期刊介绍:
Neuropathology and Applied Neurobiology is an international journal for the publication of original papers, both clinical and experimental, on problems and pathological processes in neuropathology and muscle disease. Established in 1974, this reputable and well respected journal is an international journal sponsored by the British Neuropathological Society, one of the world leading societies for Neuropathology, pioneering research and scientific endeavour with a global membership base. Additionally members of the British Neuropathological Society get 50% off the cost of print colour on acceptance of their article.