Single-Cell Chromatin Accessibility Data Combined with GWAS Improves Detection of Relevant Cell Type

Das, A. C., Foroutan, A., Qian, B., Hosseini Naghavi, N., Shabani, K., & Shooshtari, P. 

Many human traits and diseases, like height, eczema, and blood pressure, are considered "complex" because they are influenced by interactions between many genes and environmental factors. Large genetic studies (like GWAS) have identified thousands of gene variants linked to these conditions, often in regions of DNA that control how genes are regulated. However, for many complex traits and diseases, it’s still unclear which specific types of cells are affected by these gene variants.  

To better understand this, we combined genetic data with new single-cell technology, which examines individual cells rather than groups. This method can detect differences between cells (like between two skin cells) that could be missed by older, “bulk” techniques. By analyzing data from 201 complex traits, we found links between specific cell types and 59 different traits. For example, we found that body mass index (BMI) was linked to brain and eye cells, and serum creatinine (an important marker of kidney function) was surprisingly linked to skin cells. 

In conclusion, this study shows that single-cell analysis provides a more precise understanding of how diseases are linked to specific cells and subtypes. Overall, combining genetic studies with single-cell data could help scientists learn more about the underlying biology of complex diseases and lead to better treatments in the future. 

Link to full text: https://doi.org/10.3390/ijms231911456