Advancing Genetic Disease Prediction

Collaboration between BionomeeX and Sainte-Justine Hospital, Canada

BionomeeX is collaborating with CHU Sainte-Justine Hospital in Montreal, Canada, a leading center for genetic and biomedical research, to apply its Next Gen GWAS (2D GWAS) technology in refining the prediction of genetic diseases.

The Challenge with Conventional GWAS

Conventional Genome-Wide Association Studies (GWAS) have been instrumental in identifying correlations between genetic variants and complex traits.

However, traditional models often fail to account for epistatic interactions—the ways genes modulate each other’s effects.

This limitation contributes to “missing heritability”, where a substantial portion of genetic influence remains unexplained.

Next Gen GWAS: A Significant Improvement

The Next Gen GWAS approach developed by BionomeeX introduces two-dimensional mapping of epistatic interactions, allowing the exploration of over 80 billion potential gene–gene interactions.

Leveraging artificial intelligence, the model captures complex genetic dependencies to:

• Recover a portion of missing heritability

• Improve phenotypic prediction accuracy

• Provide deeper insight into the genetic architecture of complex diseases

Application in Neurological Disorders

At Sainte-Justine Hospital, this technology is being used to enhance disease prediction in the field of neurological disorders.

By modeling how combinations of genetic variants interact, the Next Gen GWAS contributes to:

• Earlier identification of genetic risk factors

• More precise prediction of disease phenotypes

• Potentially supporting targeted clinical interventions

Bridging AI and Biomedical Research

This collaboration exemplifies the integration of AI-driven genomics into biomedical research, offering new perspectives for understanding and predicting complex genetic pathologies.