A recent study published in the American Journal of Human Genetics sheds light on potential factors influencing Alzheimer's disease (AD) risk and treatment targets. Researchers from Baylor College of Medicine and the Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital used an integrative approach combining computational and functional methods.
The team identified specific genes whose changes are linked to increased AD risk in humans and similar behavioral impairments in fruit fly models. Significantly, reversing these gene changes showed neuroprotective effects. "Alzheimer’s disease affects more than 50 million people worldwide and although researchers have learned a great deal about it over the years, its causes are still not fully understood and effective therapies are not yet available," said Dr. Juan Botas, corresponding author of the study and professor at Baylor.
Genome-wide studies have previously highlighted numerous genes associated with AD. Still, understanding their role in the disease is crucial to distinguish risk-contributing genes from non-influential ones. Co-first author Morgan C. Stephens explained, "We addressed this issue by first integrating published genome-wide association data with multiple computational approaches to identify genes likely involved in AD."
The researchers identified and tested 123 candidate genes for AD risk. Analysis confirmed many genes with altered expression in human AD samples. Evaluation in fruit fly models found that altering the expression of 46 of these genes affected neuronal dysfunction. Notably, reversing changes in 11 genes protected the flies from nervous system damage.
A key discovery was the gene MTCH2. "MTCH2 expression is downregulated in human AD brain samples, and reducing its function in flies aggravates motor dysfunction," said Stephens. Restoring MTCH2 expression in the models improved motor function and reduced tau protein accumulation, highlighting its therapeutic potential.
The collaborative study included contributions from several researchers, including Jiayang Li, Megan Mair, Justin Moore, Katy Zhu, and others from Baylor College of Medicine and affiliated institutions. This research was supported by NIH grants U01AG072439, R01AG074009, and F31NS129062.
