Susan L. Slager, PhD, discusses the use of polygenic risk scoring to assess individual risk for CLL.
Susan L. Slager, PhD, endowed professor of lymphoma research at Mayo Clinic, discusses the use of polygenic risk scoring to assess individual risk for chronic lymphocytic leukemia (CLL).
According to Slager, this scoring system incorporates over 42 inherited genetic variants, each weighted based on its impact on CLL risk. By summing these weighted variants, researchers can estimate an individual's overall genetic predisposition to the disease. Individuals with higher scores are at increased risk of developing CLL.
These genetic variants are often located in regulatory regions of the genome, such as enhancers, rather than directly within genes. While the precise mechanisms by which these variants influence CLL risk remain under investigation, it is believed that they play a role in gene expression and cellular processes involved in the development of CLL.
Transcription:
0:09 | It is the 42 inherited variants and each inherited variance, you get 0, 1, or 2 copies, depending on if you get it from both parents or neither parent. Then, the score is weighted by the effect size from the genome wide association studies. For each variant, we determine 0, 1, or 2, and then we weigh it, and then we add it up across the variants, and then that is your score. Everybody has a score, and you can get a clear distribution of the score. Among individuals without CLL, that score is much lower. But among patients with chronic lymphocytic leukemia, the score is much higher.
0:46 | The inherited variants are located across the genome. They tend to be not in any particular genes per se, but they are located in regions that regulate downstream gene expression. They are in epigenomic regions and super enhancers. The actual biology of how these individual variants increase your risk of CLL is still under a lot of research, but we just know that they happen to be regulators of gene expression.
Transcription has been edited for clarity with AI.