AI Summary
The article discusses the development of a statistical method called SCENT (single-cell enhancer target gene mapping) that allows for the mapping of enhancer-gene interactions in various cell types to identify potential causal loci for common and rare diseases. The researchers applied this method to various human tissues and found important insights for immune diseases not only from immune cells but also from cells within affected tissues. This approach could assist in understanding disease mechanisms and potentially aid in the development of treatments.
Genetic studies of diseases map segments of the genome driving disease. But to understand how those changes contribute to disease progression, it is important to understand how they may alter gene regulation of disease genes in cell populations assumed to be driving disease. “Enhancer-gene maps” link genomic regulatory regions to genes and are essential for understanding disease. But constructing them poses challenges due to limitations in current experimental methods, that make it difficult to apply the technique to rare cell populations and genes that only regulate specific cell types.
Researchers from Brigham and Women’s Hospital, a founding member of the Mass General Brigham healthcare system, have developed a statistical method called SCENT (single-cell enhancer target gene mapping). This method uses multimodal single-cell data to establish links between regulatory elements and genes, allowing them to pinpoint probable causal gene loci for both common and rare diseases. These insights might assist the development of treatments for various conditions.
The research team applied SCENT to nine multimodal single-cell datasets representing various human tissues, including immune, neuronal, and pituitary cells, aiming to understand the intricacies of DNA regulation in each specific cell type. With these data, they developed 23 distinct gene-enhancer maps, to investigate genetic variants and expression patterns associated with 1,143 diseases and traits. Notably, they discovered that, for immune diseases, crucial insights emerged not only from immune cells but also from cells within the affected tissues themselves.
For most autoimmune diseases, people assume that we need a general map of