Psychiatric disorders as predictors of onset and progression in Fronto-Temporal
  
   Lead Investigator:    Nicolas Nunez
   Institution      :    McGill University
   E-Mail           :    nicolas.nunez@mail.mcgill.ca
   Proposal ID      :    920



   Proposal Description:
   Diagnostic accuracy has remained a difficult clinical challenge in early phases   of bvFTD particularly in the distinction between FTD and primary psychiatric      disorders (Panegyres, Graves et al. 2007, Ducharme, Dickerson et al. 2015) An     interesting study found that 50 of a well-characterized bvFTD cohort  had been    initially diagnosed with a primary psychiatric illness (Woolley, Khan et al.      2011) This overlap between bvFTD and bipolar disorder, schizophrenia and major    depression is particularly complex in cases with genetic mutation in C9orf72,     as the primary psychiatric disorder symptoms can precede symptoms of dementia     by up to 5 years (Ducharme, Bajestan et al. 2017). While in some cases the        primary psychiatric diagnosis is erroneous, in some cases it might represent a    prodrome to FTD (Ducharme, Price et al. 2015, Block, Sharon et al. 2016).         Despite the overlap with psychiatric disorders, little is known about the         relationship between lifetime history of mental illness and the risk of FTD.      Indeed,  few studies have examined the association between non-genetic risk       factors (medical, environmental) and FTD (Kalkonde, Jawaid et al. 2012)           (Borroni, Grassi et al. 2010). Unsurprisingly, there is no currently known        non-genetic risk factors for FTD. Interestingly a recent study has mentioned      history of traumatic brain injury and its association with an earlier age of      onset of FTD (LoBue, Wilmoth et al. 2015).                                        Our first aim in this study is to examine the prevalence of lifetime              psychiatric disorders, non- genetic risk factors (medical conditions,             environmental factors), as well as rate of family history of psychiatric          disorders and the risk of FTD by comparing it to subjects with Alzheimer???s      disease (AD) and a control group. In a second step, we intend to develop a        supervised machine learning algo