“Polygenic Transcriptome Risk Scores Can Translate Genetic Results Between Species”, Natasha Santhanam, Sandra Sanchez-Roige, Yanyu Liang, Apurva S. Chitre, Daniel Munro, Denghui Chen, Riyan Cheng, Jianjun Gao, Anthony M. George, Alex Gileta, Katie Holl, Alesa Hughson, Christopher P. King, Alexander C. Lamparelli, Connor D. Martin, Angel Garcia Martinez, Sabrina Mi, Celine L. St. Pierre, Jordan Tripi, Tengfei Wang, Hao Chen, Shelly Flagel, Keita Ishiwari, Paul Meyer, Laura Saba, Leah C. Solberg Woods, Oksana Polesskaya, Abraham Palmer, Hae Kyung Im2022-06-05 (genetic correlation)⁠:

Genome-wide association studies have demonstrated that most traits are highly polygenic; however, translating these polygenic signals into biological insights remains difficult. A lack of satisfactory methods for translating polygenic results across species has precluded the use of model organisms to address this problem. Here we explore the use of polygenic transcriptomic risk scores (PTRS) for translating polygenic results across species. Unlike polygenic risk scores (PRS), which rely on SNPs, PTRS use imputed gene expression for prediction, which allows cross-species translation to orthologous genes.

We first developed RatXcan, which is a framework for transcriptome-wide association studies (TWAS) in outbred rats. Leveraging predicted transcriptome and genotype data from UK Biobank, and the genetically trained gene expression models from RatXcan, we scored more than 3,000 rats using human-derived PTRS for height and BMI. Strikingly, we found that these human-derived PTRS predicted analogous traits in rats (r = 0.08, P = 8.57 × 10⁻⁶; r = 0.06, P = 8.51 × 10⁻⁴, respectively). The genes included in the PTRS were enriched for biological pathways including skeletal growth and metabolism and were over-represented in tissues including pancreas and brain.

This approach facilitates experimental studies in model organisms that examine the polygenic basis of human complex traits and provides an empirical metric by which to evaluate the suitability of specific animal models and identify their shared biological underpinnings.