Publications

These publications are examples of research made possible with data from CanPath and its regional cohorts.

2023

Genetic analyses of DNA repair pathway associated genes implicate new candidate cancer predisposing genes in ancestrally defined ovarian cancer cases

Authors: Wejdan M Alenezi, Caitlin T Fierheller, Corinne Serruya, Timothée Revil, Kathleen K Oros, Deepak N Subramanian, Jeffrey Bruce, Dan Spiegelman, Trevor Pugh, Ian G Campbell, Anne-Marie Mes-Masson, Diane Provencher, William D Foulkes, Zaki El Haffaf, Guy Rouleau, Luigi Bouchard, Celia M T Greenwood, Jiannis Ragoussis, Patricia N Tonin

Researchers investigated families with a history of ovarian cancer that couldn’t be explained by known genetic risk factors. Using healthy controls from CARTaGENE, they applied a targeted gene approach and found rare genetic variants in DNA repair pathway genes, particularly in ERCC5, EXO1, FANCC, NEIL1, and NTHL1, in a significant portion of these families.

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2023

Relationships between Obesity and Incidence of Fractures in a Middle-Aged Population: A Study from the CARTaGENE Cohort

Authors: Anne-Frédérique Turcotte, Sonia Jean, Suzanne N Morin, Fabrice Mac-Way, Claudia Gagnon

The study examined the CARTaGENE cohort to evaluate the association between obesity and fracture incidence among middle-aged individuals, 40 to 70 years, and further stratified the data by sex. The authors determined that, in middle-aged individuals, obesity was associated with distal lower limb fracture risk among both men and women.

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2023

Impact of Comorbidity on Hospitalization and Emergency Room Visits in Adults With Diabetes: A Longitudinal Study of Alberta’s Tomorrow Project

Authors: Ming Ye, Jennifer E Vena, Jeffrey A Johnson, Grace Shen-Tu, Dean T Eurich

Using data from Alberta’s Tomorrow Project, Ye et al. investigated the impact of comorbidities on hospitalization and emergency room visits in people with diabetes. Over the 5-year study period, the authors observed a significant association between the number of comorbidities and increased healthcare utilization among the 2,110 cases in the study population.

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2023

Mental health, cancer risk, and the mediating role of lifestyle factors in the CARTaGENE cohort study

Authors: Kaitlyn Gilham, Anne Gadermann, Trevor Dummer, Rachel A Murphy

This study investigates the associations between depression, anxiety, and cancer risk and the mediating effects of lifestyle. Using data from 34,571 CARTaGENE participants, researchers found positive links between mental health disorders, all cancers, and lung cancer risk, except for anxiety and lung cancer in women, where associations were lower when adjusting for sociodemographics, health and lifestyle. The study also found that smoking affected the relationship between mental health disorders and cancer risk. Overall, the study suggests that lifestyle factors, like smoking, may be important in understanding the relationship between mental health and cancer risk.

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2023

Circulating microRNA expression signatures accurately discriminate myalgic encephalomyelitis from fibromyalgia and comorbid conditions

Authors: Evguenia Nepotchatykh, Iurie Caraus, Wesam Elremaly, Corinne Leveau, Mohamed Elbakry, Christian Godbout, Bita Rostami-Afshari, Diana Petre, Nasrin Khatami, Anita Franco, Alain Moreau

Researchers examined the levels of 11 specific molecules called miRNAs in individuals with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), fibromyalgia (FM), and those with both conditions (ME/CFS + FM), as well as in healthy controls. Using samples from 38 CARTaGENE participants and other sources, they found distinct patterns of these miRNAs that can help differentiate between ME/CFS, FM, and ME/CFS + FM, indicating that these miRNAs could serve as potential biomarkers to aid in the accurate diagnosis of these complex illnesses.

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2023

Molecular Genetic Characteristics of FANCI, a Proposed New Ovarian Cancer Predisposing Gene

Authors: Caitlin T Fierheller, Wejdan M Alenezi, Corinne Serruya, Timothée Revil, Setor Amuzu, Karine Bedard, Deepak N Subramanian, Eleanor Fewings, Jeffrey P Bruce, Stephenie Prokopec, Luigi Bouchard, Diane Provencher, William D Foulkes, Zaki El Haffaf, Anne-Marie Mes-Masson, Marc Tischkowitz, Ian G Campbell, Trevor J Pugh, Celia M T Greenwood, Jiannis Ragoussis, Patricia N Tonin

Researchers investigated the genetic characteristics of the FANCI gene, which has been linked to an increased risk of ovarian cancer. Using data from 171 CARTaGENE participants and other sources, they confirmed that a specific FANCI variant is associated with ovarian cancer and discovered potential genetic links to other cancer types.

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2023

Associations between neighborhood walkability and walking following residential relocation: Findings from Alberta’s Tomorrow Project

Authors: Gavin R McCormack, Mohammad Javad Koohsari, Jennifer E Vena, Koichiro Oka, Tomoki Nakaya, Jonathan Chapman, Ryan Martinson, Graham Matsalla

This study aimed to estimate whether changes in neighbourhood walkability resulting from residential relocation were associated with leisure, transportation, and total walking levels. Using data from 5,977 urban adults (non-movers, movers to less walkability, and movers to more walkability), researchers found that time spent walking at follow-up was lower among those who moved to less walkable neighbourhoods, suggesting that relocating to less walkable neighbourhoods could negatively affect health.

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2023

Examining the influence of built environment on sleep disruption

Authors: Jaclyn Parks, Millie Baghela, Parveen Bhatti

Researchers sought to understand if modifying aspects of the built environment improved sleep. Using data from 28,385 BC Generations Project participants, they found that increased light-at-night, air pollution (SO2), and living <100 m from a main roadway were associated with insufficient sleep. Greenness had a positive effect on sleep.

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2023

A comparison of machine learning algorithms and traditional regression-based statistical modeling for predicting hypertension incidence in a Canadian population

Authors: Mohammad Ziaul Islam Chowdhury, Alexander A Leung, Robin L Walker, Khokan C Sikdar, Maeve O'Beirne, Hude Quan, Tanvir C Turin

This study evaluates different machine learning algorithms and compares their predictive performance with conventional models to predict hypertension incidence using data from 18,322 Alberta’s Tomorrow Project participants. The study found little difference in predictive performance between the machine learning algorithms and the conventional Cox PH model. The results suggest that conventional regression-based models can perform similarly to machine learning algorithms with good predictive accuracy in a moderate dataset with a reasonable number of features.

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2022

Agreement between self-report and administrative health data on occurrence of non-cancer chronic disease among participants of the BC generations project

Authors: Maryam Darvishian, Jessica Chu, Jonathan Simkin, Ryan Woods, Parveen Bhatti

Linked self-reported chronic disease history data to a Chronic Disease Registry (CDR) that applied algorithms to administrative health data to ascertain diagnoses of multiple chronic diseases in the Province of British Columbia.

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