Jess Fiedorowicz

His content expertise centers around morbidity and mortality (especially cardiovascular disease and suicide) in bipolar disorder, while his methods expertise relates to quantitative methods in epidemiology. He values taking an interdisciplinary, team science approach to his work.

1. The Candesartan Adjunctive Bipolar Depression Trial (CADET): Bipolar disorder is characterized on a biochemical level by an inflammatory response in the brain, resulting increased peripheral levels of inflammatory cytokines and microglial cells, oxidative stress, and nitrosative stress. These biological pathways are responsible for the often-lengthy depressive phases experienced by those with the disorder. The hormone angiotensin II has been shown to affect all three pathways. Past research has shown the effectiveness of angiotensin-converting enzyme (ACE) inhibitors in reducing depressive symptoms of preventing them from developing. Candesartan – part of a separate class of medications which block the receptor for angiotensin II – may be similarly effective in reducing bipolar depression by interfering in the inflammatory, oxidative stress, and nitrosative stress pathways. This double-blinded study will use the Montgomery-Åsberg Depression Rating Scale (MADRS) to compare the effectiveness of candesartan versus a placebo in reducing depressive symptoms after 16 weeks of treatment. Both the experimental and control groups will also receive treatment-as-usual during the study. Secondary outcomes will involve measuring the levels of key biomarkers at multiple time points to determine the effectiveness of the treatment and correlate changes in symptoms with changes in these biomarkers. This study is done in partnership with Australia’s Deakin University as one of two Canadian sites. RECRUITMENT PENDING.
2. BD2 Integrated Network Longitudinal Cohort Study (BD²): To date, no large-scale studies characterizing the underlying biological pathways involved in bipolar disorder have been conducted. Attempts have been made to classify different subtypes of bipolar disorder by symptomatology but the variability in symptom presentation poses challenges related to diagnosing and predicting the course of illness. This multi-site study collects data from partner sites across the US and Canada to conduct the largest and most comprehensive prospective longitudinal study ever conducted for bipolar disorder; it seeks to recruit 4,000 participants across 11 sites and follow these participants over the course of four years. These sites will collect blood samples, MRI scans, and cognitive assessment data at regular intervals in order to phenotype study participants and to better understand the clinical, neural, and biological features of the disorder. This study has the potential to generate new hypotheses and provide direction for future studies. It is funded by the Breakthrough Discoveries for thriving with Bipolar Disorder (BD²) organization in partnership with Brain Canada. RECRUITMENT ONGOING.
3. Bipolar mania and blue-blocking glasses: Bipolar disorder is hallmarked, in part, by episodes mania – often severe enough to require hospitalization until symptoms stabilize, usually through the use of medication. These episodes of mania have effects on patients’ finances, relationships, and jobs. In addition, the medication used to treat bipolar disorder comes with significant side effects, which can influence the willingness of patients to adhere to their prescribed medication regimens. Other kinds of interventions have been proposed as adjunct therapies to address separate aspects of bipolar disorder, such as the effects manic episodes have on the circadian rhythm. Both blue light-blocking glasses and time-restricted eating (TRE) are avenues that may reset the disrupted circadian rhythm, which could reduce manic symptoms, shorten manic episodes, and improve overall outcomes. Blue-blocking glasses have been used in two trials led by Dr. Fiedorowicz:
   1. OSAN (Ottawa Sunglasses At Night): This clinical trial involved inpatient participants wearing either the experimental blue light-blocking glasses or the lightly-tinted control glasses. Both the participants and the clinician raters assigned to administer clinical evaluation measures were blinded as to which arm participants were randomized into. This study used the Young Mania Rating Scale (YMRS) to determine whether or not blue-blocking glasses were effective in reducing manic symptoms. This study also used actigraphy to determine what (if any) changes the experimental blue-blocking glasses had on participants’ circadian rhythms and sleep quality. There were no significant improvements in YMRS scores or sleep measures when comparing the study arms to one another.
   2. CiS (Clocks In Sync): This clinical trial is similar to OSAN but added TRE to the study, creating three study arms: tinted control glasses with TRE, blue-blocking glasses with TRE, and blue-blocking glasses without TRE. This trial also used actigraphy data to assess changes in circadian rhythm. RECRUITMENT COMPLETE, ANALYSIS IN PROGRESS.
4. Mindful Heart: Mental disorders including depression, bipolar disorder, schizophrenia, and psychosis are linked to heart disease, with some of these conditions linked to nearly doubling the risk. Doctors often use risk calculators to inform treatment of heart disease by prescribing medication or suggesting lifestyle changes. This research will develop a risk calculator for heart disease that considers mental health disorders and intersectional factors (sex, ethnicity, socioeconomic status) by using data from a Canadian database – the Canadian Longitudinal Study on Aging. Prior to developing the calculator, we will survey primary care providers about the clinical accessibility of variables and barriers/facilitators of risk calculator usage in order to better design the model. Finally, we will interview primary care providers after model development to their perspectives about acceptability, and feasibility of the developed risk calculator. This work has many applications to improve health care. Early and accurate risk prediction could lead to better patient outcomes, increasing life expectancy and possibly reducing the burden of heart disease on the healthcare system. PhD student: Sara Siddiqi