A Study of the Behavioral Variant of Frontotemporal Dementia and Bipolar Disorder: a Neuroimaging and Epigenetics Integrated Approach

Overview

The aim of this study is to investigate the selective epigenetic modifications and their effect on brain's morphology and functionality in the frontotemporal dementia behavioral variant and bipolar disorder. The open-label, multicentric, interventional case-control study involves the analysis of 3 separate cohorts of patients, partly selected over the course of the past 10 years. More specifically, 80 behavioral variant Frontotemporal Dementia (bvFTD) patients (40, of whom 20 carry G4C2 expansion in the C9orf72 gene, are already available, while 40 will be prospectively recruited), 80 Bipolar Disorder (BD) patients (40, including 20 with early onset and 20 with late onset, are already available, while 40 will be prospectively recruited) and 50 healthy control (HC) subjects (20 of whom are already available from other previously approved studies), will be enrolled in this study. For each participant a blood sample will be collected, processed, and studied in order analyze the expression of miRNA. Every participant will also undergo Nuclear Magnetic Resonance Imaging (NMR), Nuclear Magnetic Resonance Spectroscopy (1H-MRS), and Positron Emission Tomography (PET) and, lastly, a battery of behavioral scales to explore different cognitive domains will be administered to all participants by a team of psychologists and physicians. The overall estimated duration of the study is 36 months.

Detailed description

Following the inclusion and exclusion criteria, the participants will be recruited and subdivided into three groups:

* bvFTD patients, followed prospectively for at least 2 years. These include bvFTD carriers of G4C2 expansion in the C9orf72 gene (best model of the two diseases because such expansion is widely associated with the development of psychosis) * BD patients who are part of a cohort of multi affected families (MAF) followed since January 2017 at the Psychiatry Operating Unit of the Policlinico di Milano and who have positive family history of neurodegenerative diseases. * Healthy subjects who underwent neurocognitive tests at baseline that excluded the presence of dementia and psychiatric diseases.

The investigators will be collecting participants blood samples, which will be processed and analyzed. More specifically, total exosomes will be isolated from 500 microliters of plasma by ExoQuick precipitation solution (SBI). Isolation and purification of NDEs will be performed by ExoFlow purification kit using biotinylated anti-human CD171 (L1CAM) antibody (clone 5G3, Ebiosciences). Total RNA contained in NDEs will be extracted by Total Exosome RNA and Protein Isolation Kit and miRNA expression analysis by TaqMan OpenArray Human Advanced MicroRNA Panel (Thermo Fisher Scientific). Expression analysis of lncRNAs will be conducted by LincFinder Array and inflammatory and autoimmunity arrays (Qiagen).

The participants will also undergo a neuroimaging session, where structural MRI and 1H-MRS sessions will be performed using a 3T MRI scanner available at the Neuroradiology Unit. The 1H-MRS will provide sensitive and reliable assessment of neurochemical changes in specific brain areas. The acquisition voxels will be palced in the dorso- and ventrolateral prefrontal cortex (DLPFC/VLPFC), amygdala, and hippocampus. Finally, an FDG-PET scan will be performed with a Biograph Truepoint 64 PET/TC scanner. T1-weighted and FDG-PET images will be used to explore brain morphological/metabolic differences between the groups. Gray matter and white matter volumes will be estimated locally and compared between groups using voxel-based morphometry. A parallel region of interest comparison (ROIs) will be performed to estimate regional volumes using the Automated Anatomical Labelling (AAL) atlas as a reference, again focusing on the DLPFC/VLPFC, amygdala and hippocampus. Finally, an additional regional analysis based on Freesurfer software will allow the investigators to estimate the cortical thickness, cortical surface area, and cortical gyrification of the Desikan-Killiany atlas regions. All MRI and PET analyses will be performed in the context of a general linear model using a specific software implementation in MATLAB called Statistical Parametric Mapping (SPM).

Lastly, neuroimaging data and ncRNA expression profiles will be used as predictors in the ML analysis. Given the small sample size, initially linear models (e.g., Support Vector Machine) will be used. Later, to improve the predictive power of our models, the investigators will apply the ML method called random forest, a more versatile and powerful classification algorithm, and the XGBoost (eXtreme Gradient Boosting) algorithm. To avoid overfitting of the learning process, a "grid" search of model hyperparameters will be performed. A 5-fold cross-validation will be used to validate the results, with a split between training-tests of 80%-20%.

Interventions

• Diagnostic test DISBAND protocol
  For each participant blood samples will be collected, processed and studied to analyse microRNA expression, more specifically investigating non-coding RNA (ncRNA). Each participant will undergo a multimodal neuroimaging session, composed of structural MRI, 1H-MRS and PET.

Primary outcome measures

• Identification of ncRNA transcripts and a specific noncoding RNA profile in neuron-derived exosomes [Time frame: 36 months]
• Differences in brain structure in terms of white matter volumes [Time frame: 36 months]
• Differences in brain structure in terms of gray matter volumes [Time frame: 36 months]
• Differences in brain structure in terms of cortical gyrification [Time frame: 36 months]
• Differences in brain structure in terms of superficial cortical area [Time frame: 36 months]
• Differences in brain structure in terms of cortical thickness [Time frame: 36 months]
• Differences in brain metabolism [Time frame: 36 months]
• Differences in glutamatergic neurotransmission in the prefrontal-limbic cortex [Time frame: 36 months]

Secondary outcome measures (1)

• Creation of a machine learning model [Time frame: 36 months]

Eligibility criteria

Inclusion criteria

• byFTD group: patients of either sex; 18 years of age or older; diagnosis of behavioral variant Frontotemporal Dementia according to current diagnostic criteria; presence of a signed informed consent.
• BD group: patients of either sex; 18 years of age or older; diagnosis of bipolar disorder according to DSM-V criteria; presence of a signed informed consent.
• HC group: patients of either sex; 18 years of age or older; subjects who have gone through the same diagnostic process as patients under suspicion of a central nervous system and/or psychiatric disorder, resulting in the absence of cognitive deficits and mood disorders; presence of a signed informed consent.

Exclusion criteria

• Diagnosis of Alzheimer's disease
• Comorbidities interfering with the studied condition (e.g. other neurological diseases or history of substance or alcohol abuse)
• Diseases with an inflammatory component (e.g. autoimmune diseases, tumors)
• Pregnancy

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation

Non-randomized

Model

Parallel assignment

Masking

Open label

Primary purpose

Other

Study locations

Italy · 1 center

• Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico — Milan

Publications

• Galimberti D, Fenoglio C, Serpente M, Villa C, Bonsi R, Arighi A, Fumagalli GG, Del Bo R, Bruni AC, Anfossi M, Clodomiro A, Cupidi C, Nacmias B, Sorbi S, Piaceri I, Bagnoli S, Bessi V, Marcone A, Cerami C, Cappa SF, Filippi M, Agosta F, Magnani G, Comi G, Franceschi M, Rainero I, Giordana MT, Rubino E, Ferrero P, Rogaeva E, Xi Z, Confaloni A, Piscopo P, Bruno G, Talarico G, Cagnin A, Clerici F, De PMID 23473366
• Vieta E, Popovic D, Rosa AR, Sole B, Grande I, Frey BN, Martinez-Aran A, Sanchez-Moreno J, Balanza-Martinez V, Tabares-Seisdedos R, Kapczinski F. The clinical implications of cognitive impairment and allostatic load in bipolar disorder. Eur Psychiatry. 2013 Jan;28(1):21-9. doi: 10.1016/j.eurpsy.2011.11.007. Epub 2012 Apr 24. PMID 22534552
• Baez S. et al., Neuropsychologia. 2017 Feb 17; S0028-3932(17)30058-1. doi: 10.1016/j.neuropsychologia.2017.02.012.
• Delvecchio G. et al., Aust N Z J Psychiatry. 2018 Dec 13:4867418815976. doi: 10.1177/0004867418815976
• Neueder A. et al, J Mol Biol. 2018 Dec 29; S0022-2836(18)31287-7. doi: 10.1016/j.jmb.2018.12.012.
• Belzil VV, Gendron TF, Petrucelli L. RNA-mediated toxicity in neurodegenerative disease. Mol Cell Neurosci. 2013 Sep;56:406-19. doi: 10.1016/j.mcn.2012.12.006. Epub 2012 Dec 29. PMID 23280309
• Rademakers R, Eriksen JL, Baker M, Robinson T, Ahmed Z, Lincoln SJ, Finch N, Rutherford NJ, Crook RJ, Josephs KA, Boeve BF, Knopman DS, Petersen RC, Parisi JE, Caselli RJ, Wszolek ZK, Uitti RJ, Feldman H, Hutton ML, Mackenzie IR, Graff-Radford NR, Dickson DW. Common variation in the miR-659 binding-site of GRN is a major risk factor for TDP43-positive frontotemporal dementia. Hum Mol Genet. 2008 D PMID 18723524
• Galimberti D, Villa C, Fenoglio C, Serpente M, Ghezzi L, Cioffi SM, Arighi A, Fumagalli G, Scarpini E. Circulating miRNAs as potential biomarkers in Alzheimer's disease. J Alzheimers Dis. 2014;42(4):1261-7. doi: 10.3233/JAD-140756. PMID 25024331

Identifiers

NCT: NCT06706687 · DISBAND

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗