Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease
The Global Biobank Meta-analysis Initiative is a collaborative network of 23 biobanks, representing more than 2.2M consented participants with genetic data linked to electronic health records. This collaborative effort will improve genome-wide association studies’ power for diseases, benefit understudied diseases, and improve risk prediction.
Association of dairy consumption patterns with the incidence of type 2 diabetes: Findings from Alberta’s Tomorrow Project
Researchers investigated the relationship between dairy consumption and the risk of developing type 2 diabetes (T2D) with data from Alberta’s Tomorrow Project (ATP). 15,016 women and 8,615 men completed a food-frequency questionnaire and were followed up over time to determine T2D incidence. They found that higher consumption of whole milk, regular cheese, and non-fat milk was associated with decreased risk of incident T2D only in men. The study suggests that combining different dairy products might be good for men’s health.
Population-Based Recalibration of the Framingham Risk Score and Pooled Cohort Equations
The Framingham Risk Score (FRS) and Pooled Cohort Equations (PCEs) overestimate risk in many contemporary cohorts. This study sought to determine if the recalibration of these scores using contemporary population-level data improves risk stratification for statin therapy.
Prediction of Cardiovascular Events by Pulse Waveform Parameters: Analysis of CARTaGENE
Researchers conducted the largest study to date evaluating non-invasive pulse waveform parameters’ association with cardiovascular events. By adding two waveform parameters to the existing atherosclerotic cardiovascular disease score, they improved cardiovascular prediction and reclassified up to 5.7% of patients in another risk category.
Harnessing the power of data linkage to enrich the cancer research ecosystem in Canada
This abstract discusses a project aimed at linking cancer registry and administrative health data to Canada’s largest population health study, the Canadian Partnership for Tomorrow’s Health (CanPath). The project seeks to enrich the cancer research ecosystem in Canada by providing researchers with a comprehensive dataset that includes genetics, environment, lifestyle, and behaviour data. The linked data will be made available through a cloud-based solution called the CanPath Data Safe Haven, which is accessible to researchers through secure access. The project will address concerns related to the accessibility of cancer data in Canada, bring more value to existing data, and support an enhanced understanding of the impacts of cancer on marginalized populations.
Cohort Profile: The Ontario Health Study (OHS)
OHS’s cohort profile outlines its research platform’s history and value for the broader scientific community. OHS follows 225,000 over their lifetime, actively and passively, making de-identified genomic, environmental, lifestyle, and electronic health data available to cancer and chronic disease researchers.
Development and validation of a hypertension risk prediction model and construction of a risk score in a Canadian population
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.
Identification of human mitochondrial RNA cleavage sites and candidate RNA processing factors
Researchers created a technique to find and measure specific RNA cutting events among 799 CARTaGENE participants and samples from the GTEx project. They uncovered new sites where RNA is cut during mitochondrial processing and discovered genes linked to these processes, shedding light on how genetic variations might affect mitochondrial functions and health conditions.
Identification of FAT3 as a new candidate gene for adolescent idiopathic scoliosis
Researchers aimed to identify rare genetic variations associated with adolescent idiopathic scoliosis (AIS) by examining the DNA of 60 CARTaGENE participants (healthy controls) and individuals from other sources. They found that the FAT3 gene, while not statistically significant on its own, showed an excess of rare genetic changes in AIS patients, and further investigations revealed specific variants within FAT3 that were more common in severe AIS cases compared to milder cases and healthy individuals, suggesting that FAT3 may play a role in the development of AIS.
Uncovering the Contribution of Moderate-Penetrance Susceptibility Genes to Breast Cancer by Whole-Exome Sequencing and Targeted Enrichment Sequencing of Candidate Genes in Women of European Ancestry
The aim of this study was to perform a large-scale whole-exome sequencing study, followed by a targeted validation, in breast cancer patients and healthy women of European descent. Using data from 920 CARTaGENE participants and four other sources, the researchers identified 20 novel genes with modest association evidence for overall and subtype-specific breast cancers.