microRNA-based predictor for diagnosis of frontotemporal dementia

Background Frontotemporal dementia (FTD) is an early onset dementia that is diagnosed in ∼20% of the progressive dementia cases. Heterogeneity in FTD clinical presentation too often delays clinical diagnosis and calls for molecular biomarkers to assist diagnosis, including cell free microRNAs (miRNA). However, nonlinearity in the relationship of miRNAs to clinical states and underpowered cohorts has limited research in this domain. 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 Based on cell-free plasma miRNA profiling by next generation sequencing and machine learning approaches, we develop a nonlinear prediction model that accurately distinguishes FTD from non-neurodegenerative controls in ∼90% of cases. Conclusion 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. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement EH was supported by the ISF Legacy 828/17 grant, Target ALS 118945 grant, European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement number 617351. Israel Science Foundation, the ALS-Therapy Alliance, AFM Telethon 20576 grant, Motor Neuron Disease Association (UK), The Thierry Latran Foundation for ALS research, ERA-Net for Research Programmes on Rare Diseases (FP7), A. Alfred Taubman through IsrALS, Yeda-Sela, Yeda-CEO, Israel Ministry of Trade and Industry, Y. Leon Benoziyo Institute for Molecular Medicine, Benoziyo Center Neurological Disease, Kekst Family Institute for Medical Genetics, David and Fela Shapell Family Center for Genetic Disorders Research, Crown Human Genome Center, Nathan, Shirley, Philip and Charlene Vener New Scientist Fund, Julius and Ray Charlestein Foundation, Fraida Foundation, Wolfson Family Charitable Trust, Adelis Foundation, MERCK (UK), Maria Halphen, Estates of Fannie Sherr, Lola Asseof, Lilly Fulop, E. and J. Moravitz. Teva Pharmaceutical Industries Ltd. as part of the Israeli National Network of Excellence in Neuroscience (NNE) postdoc Fellowship to IM 117941. The Dementia Research Centre is supported by Alzheimer's Research UK, Brain Research Trust, and The Wolfson Foundation. This work was supported by the NIHR Queen Square Dementia Biomedical Research Unit, the NIHR UCL/H Biomedical Research Centre and the Leonard Wolfson Experimental Neurology Centre (LWENC) Clinical Research Facility as well as an Alzheimer's Society grant (AS-PG-16-007). JDR is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). PF is supported by an MRC/MND LEW Fellowship and by the NIHR UCLH BRC. This work was also supported by the Motor Neuron Disease Association (MNDA) 839-791. The CReATe Consortium (U54 NS090291) is part of the Rare Diseases Clinical Research Network (RDCRN), an initiative of the Office of Rare Diseases Research (ORDR), National Center for Advancing Translational Sciences (NCATS). CReATe is funded through collaboration between NCATS and the National Institute of Neurological Disorders and Stroke (NINDS). Supplementary support for the CReATe biorepository was provided by the ALS Association (Grant ID 16-TACL-242). NSY was supported by the Israeli Council for Higher Education (CHE) via the Weizmann Data Science Research Center. ### Author Declarations All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Approvals were obtained from the local research ethics committee and all participants provided written consent (or gave verbal permission for a carer to sign on their behalf). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors * AD : Alzheimer’s Disease; ALS : amyotrophic lateral sclerosis; AUC : area under the curve; bvFTD : behavioral frontotemporal dementia; C9ORF72 : chromosome 9 open reading frame 72; CBS : corticobasal syndrome; CHMP2B : charged multivesicular body protein 2B; EDTA : Ethylenediaminetetraacetic acid; FTD : frontotemporal dementia; GFAP : glial fibrillary acidic protein; GRN : progranulin; MAPT : microtubule-associated protein tau; miRNA : microrRNA; MS : multiple sclerosis; NfL : neurofilament light chain; PNFA : progressive non-fluent aphasia; PSP : progressive supranuclear palsy; ROC : receiver operating characteristic; RFE : recursive feature elimination; SD : semantic dementia; SHAP : SHapley Additive exPlanations; TBK1 : TANK-binding kinase; TDP-43 : TAR DNA-binding protein 43; TRIPOD : Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis; UMI : unique molecular identifier; UTAP : user-friendly transcriptome analysis pipeline; VCP : Valosin-containing protein;