Marking World Alzheimer’s Day, Sidra Medicine has announced new research that advances the early prediction of cognitive decline, potentially paving the way for more personalized approaches to brain health management. The study, published recently in Genome Medicine, introduces a novel method for integrating extensive genetic data into predictive models of cognitive impairment.
Led by Dr. Mohamed Janahi, a post-doctoral researcher at Sidra Medicine, in collaboration with Prof. Younes Mokrab, director of the Neuroscience Research Programme at the institution, and UK-based colleagues including Prof. Andre Altmann from University College London, the study focuses on enhancing the use of polygenic risk scores to assess susceptibility to cognitive decline. Polygenic risk scores consider the combined influence of numerous genetic variants associated with disease risk.
Alzheimer’s disease and other dementias often develop gradually, with significant brain changes—especially in the hippocampus, a region critical for memory—occurring years before clinical symptoms arise. Existing genetic risk models, researchers note, may overlook some relevant genetic information. To address this, the team developed a multi-threshold polygenic risk approach that captures a broader range of genetic factors.
The researchers employed data from nearly 24,000 participants in the UK Biobank to build their models and validated the approach using roughly 3,000 subjects from two independent cohorts, the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the European Prevention of Alzheimer’s Disease (EPAD) project. Their multi-threshold model demonstrated improved predictive power when combined with brain imaging data, enabling a more detailed depiction of structural changes linked to cognitive decline.
Dr. Janahi emphasized the importance of early detection, stating that identifying individuals at heightened risk before symptoms emerge could facilitate earlier monitoring and preventative strategies. The integration of genetic information with neuroimaging, he said, moves research closer to personalized brain health care.
Prof. Mokrab highlighted the complexity of common diseases like Alzheimer’s, which involve thousands of genetic variants each contributing minimal risk individually. Their method aggregates these genetic signals to enhance predictions based on brain changes, with potential applicability beyond neurodegenerative conditions.
The study’s results are not intended as a diagnostic tool for Alzheimer’s but provide a framework for future assessments of cognitive decline risk. With further validation, such methods could help guide clinical monitoring, support earlier interventions, and improve participant selection for clinical trials targeting neurodegenerative diseases.
The research exemplifies an international and multidisciplinary effort, combining expertise in genomics, neuroscience, neuroimaging, and computational biology. It also underscores Sidra Medicine’s expanding capabilities in precision medicine and computational genomics with a focus on translating research findings into clinical practice.
“Our aim is to shift healthcare from reactive treatment after symptom onset to proactive risk identification,” Prof. Mokrab said. “By integrating genomics with imaging and other health data, we can move toward more precise and preventative care.”