July 17, 2024
Congratulations to our CIHR Project Grant Recipients!
CIHR results for the last project grant competition were published today. We are pleased to report that in this latest competition, Douglas researchers have collectively secured over $3M – congratulations to all successful applicants, and thank you to Dr. Dominique Walker, who chairs the Internal Grant Review Committee, as well as to all the researchers who gave their time to review their colleagues’ applications.
Project Grants Awarded
-
Principal Investigator: Diane Boivin
Behavioural and physiological impacts of night shift work in women
Shift work leads to disturbances in behavioural and biological rhythms. Nearly one out of two shift workers is a female and one out of three females uses contraceptives. Despite these facts, very little is known on the impact of oral contraceptives use on female adaptation to atypical shifts. Our goal is to address this knowledge gap. We plan to recruit 60 healthcare workers working nights or rotating shifts, aged 18-50 years, to a 4-week field study. Participants will be assigned to one of three groups (20/group): females naturally ovulating, females on oral contraceptives, and males. Throughout the ambulatory study, sleep quality, alertness and performance will be measured frequently on digital devices and the sleep-wake cycle will be documented by a wrist-worn device. Twice during the study period, participants will visit the laboratory for 24 h. One laboratory visit will be under a conventional day-oriented schedule while the other visit will be under a night-oriented schedule. During both laboratory visits, more controlled parameters will be collected several times per day, including sleep, alertness, performance, and biological markers. Our studies will demonstrate that the use of oral contraceptives has important effects on female sleep, fatigue, alertness, cardiovascular function and metabolism. This line of investigation has important clinical implications for females working atypical schedules. Given the important health and economic consequences of shift work, results of the present study can lead to individualized preventive strategies for shift workers that consider sex, gender, and oral contraceptives use as important adaptative factors. -
Principal Investigators: Lena Palaniyappan, Amélie Achim
Co-investigators: Mallar Chakravarty, Marie-France Demers, Ridha Joober, Shalini Lal, Katie Lavigne, Martin Lepage, Michael Mackinley, Marc-André Roy, Priya Subramanian, Alban Voppel, Irnes Zeljkovic
Predicting Psychotic Relapse using Speech-based Early-detectionPreventing repeated episodes of psychotic symptoms (i.e., relapses) in people recently diagnosed with schizophrenia can improve long-term health outcomes. The best approach to preventing relapses is to continue treatment with antipsychotic medications, even after the psychotic symptoms have reduced considerably. However, this approach, called maintenance treatment, is not widely accepted by patients due to the burden of medication side-effects. As such, many patients discontinue treatment and are not able to identify impending relapses early enough to recommence treatment. Brief remote assessments to help self-monitoring of psychotic symptoms are either too general or rely on self-awareness, making them not very effective. To address this issue, we will create a tool that uses speech to predict relapses before they happen, allowing the clinical team providing care for psychosis to intervene on time. Our project aims to answer two questions: can we predict relapses four weeks before they happen using speech, and will this speech-based tool work effectively for everyone? We have expertise in speech assessments, and we will work with early intervention clinics that serve both French- and English-speaking patients. We will test if the tool works well in both official languages and for women who are under-represented in psychosis clinics. If successful, this tool will help patients and families make better decisions about long-term treatment.
-
Principal Investigator: Yashar Zeighami
Co-Investigators: Mallar Chakravarty, Mahsa Dadar, Yasser Iturria Medina, Naguib Mechawar, Corina Nagy, Gustavo Turecki
A multi-scale and multi-modal investigation of dopaminergic neurodegeneration in Parkinson’s disease: bridging cell-specific and in vivo neuroimaging signatures
Parkinson’s disease (PD) is the second most common neurodegenerative disease, affecting 2-3% of the population over 65 years of age, with approximately 6 million cases worldwide in 2016. It is also the fastest-growing neurological disease in the world, with a rapid increase in incidence and prevalence over the past two decades. PD has up to 2 times higher prevalence, and a worse prognosis in males compared to females. Currently, more than 100,000 Canadians live with PD, and its prevalence is expected to double by 2031. So far, there is no reliable predictive biomarker of PD in sporadic cases. Furthermore, Current therapies for PD only target the management of symptoms and not the disease outcome (to slow, stop, or reverse neurodegeneration). The lack of disease-modifying treatments stem from a gap in our understanding of the underlying mechanisms causing sporadic PD, the absence of predictive diagnostic and prognostic biomarkers, and a disconnect between molecular, neuroanatomical, and clinical studies. The current proposal addresses these gaps with the goal to identify (i) the molecular programs involved in the degeneration of dopaminergic neurons, (ii) their interaction with synucleinopathy in PD, and (iii) their downstream neuroanatomical and clinical impacts, from prodromal to advanced stages of the disease and how they may differ between sexes.
Additional success
In addition to these grants, bridge funding was awarded to a grant that was very near approval for a full project grant:
- Principal Investigators: Rudolf Uher, Martin Alda
Co-investivators: Kathryn Freeman, J Abraham, Lena Palaniyappan, Barbara Pavlova
Early identification of risk for major depressive and bipolar disorders from polygenic scores, family history, and developmental psychopathology
Depression and bipolar disorder often start in the teens or twenties and continue affecting a person’s life for decades. If we can predict who is going to develop depression or bipolar disorder, we may be able to prevent these health problems. We know that depression and bipolar disorder run in families. We also know that children who experience anxiety or attention problems are more likely to develop depression or bipolar disorder later. We do not know whether adding a genetic test can help us estimate risk better than family history and childhood problems. We propose to find the answer in a collection of over 4000 young people who repeatedly visited research teams over the years. We will test how well genetic scores predict development of depression or bipolar disorder in people with and without family history of these problems and with or without childhood anxiety and attention problems. We will bring genetic test scores, family history, and childhood problems together to make the best possible estimate of risk. We expect that the combination will lead to a more accurate prediction, which in turn will enable prevention to reduce the toll of mood problems.
The official results are posted here.
Congratulations!