Researchers at UNSW Sydney have identified around 150 functional DNA enhancers in human astrocytes that regulate genes associated with Alzheimer's disease. By testing nearly 1,000 potential switches using advanced genetic tools, the team revealed how non-coding DNA influences brain cell activity. The findings, published on December 18 in Nature Neuroscience, could aid in developing targeted therapies and improving AI predictions of gene control.
The human genome consists of about 2% genes and 98% non-coding DNA, long dismissed as 'junk' but now recognized for containing regulatory elements like enhancers. These enhancers, often distant from the genes they affect, play a crucial role in controlling gene expression in specific cell types, including astrocytes—supportive brain cells implicated in Alzheimer's disease.
In a pioneering study, scientists from UNSW Sydney's School of Biotechnology & Biomolecular Sciences conducted the largest CRISPRi enhancer screen in brain cells to date. They used CRISPRi, a technique that silences DNA segments without cutting them, combined with single-cell RNA sequencing to assess nearly 1,000 candidate enhancers in lab-cultured human astrocytes. This approach allowed measurement of gene activity changes in individual cells.
"We used CRISPRi to turn off potential enhancers in the astrocytes to see whether it changed gene expression," explained lead author Dr. Nicole Green. "And if it did, then we knew we'd found a functional enhancer and could then figure out which gene—or genes—it controls. That's what happened for about 150 of the potential enhancers we tested. And strikingly, a large fraction of these functional enhancers controlled genes implicated in Alzheimer's disease."
The results narrow the vast non-coding genome's search space for Alzheimer's genetic clues, as many disease-linked variants occur outside genes. Professor Irina Voineagu, who led the research, noted that the catalogue of validated enhancers serves as a reference for genetic studies on conditions like hypertension, diabetes, and neurodegenerative disorders. "We're not talking about therapies yet. But you can't develop them unless you first understand the wiring diagram," she said.
Beyond immediate applications, the dataset is training AI models to predict enhancer functions more accurately. Google's DeepMind is benchmarking its AlphaGenome model against it, potentially accelerating future discoveries. Looking ahead, the team sees potential in cell-type-specific targeting for precision medicine, drawing parallels to enhancer-based treatments for sickle cell anemia.
"This is something we want to look at more deeply: finding out which enhancers we can use to turn genes on or off in a single brain cell type, and in a very controlled way," Dr. Green added. While clinical applications remain distant, this work illuminates the regulatory landscape of brain cells in Alzheimer's pathology.
