New method links rare immune cells to genetic disease risk

A new approach enables genetic risk research in rare immune cells, revealing how distant DNA variants affect disease.

New method links rare immune cells to genetic disease risk

Image: medicalxpress.com

Researchers have developed a new method to study genetic risk in rare immune cells, which were previously difficult to analyze due to their scarcity. The approach, described in a recent study, allows scientists to identify how genetic variants linked to diseases act on genes located far away in the DNA sequence, rather than on nearby genes.

The method, called 'single-cell expression quantitative trait loci (eQTL) analysis,' was applied to specific immune cell types such as regulatory T cells and natural killer cells. By isolating these rare cells, the researchers could map genetic variants to their target genes, providing insights into autoimmune and inflammatory diseases.

According to the study, this technique revealed that many disease-associated variants influence gene expression in a cell-type-specific manner, which was previously hidden when analyzing mixed cell populations. The findings could lead to better understanding of disease mechanisms and potential therapeutic targets.

The research was published in a peer-reviewed journal, and the team has made their data publicly available for other scientists. This advancement is expected to accelerate genetic research in immunology and precision medicine.

❓ Frequently Asked Questions

What are rare immune cells?

Rare immune cells are cell types like regulatory T cells or natural killer cells that are present in low numbers in the blood or tissues, making them difficult to study with traditional methods.

How does this new method work?

The method uses single-cell eQTL analysis to link genetic variants to gene expression changes in individual rare immune cells, revealing how distant DNA variants affect disease risk.

What diseases could this research impact?

This research could impact autoimmune and inflammatory diseases, as the method helps identify cell-type-specific genetic effects that contribute to these conditions.

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