Heart & Metabolic Disease Genes Uncovered by New Tool
New Gene-Finding Tool Promises More Precise Treatments for Complex Diseases
Case Western Reserve University researchers have developed a novel computational tool that considerably improves the ability to identify specific genes and genetic variations responsible for complex diseases, paving the way for more targeted and effective treatments.
Cleveland, OH – Scientists at Case Western Reserve University School of Medicine have unveiled a groundbreaking new tool designed to untangle the intricate genetic underpinnings of complex diseases. This innovative approach promises to accelerate the finding of causal genes and genetic variations, ultimately leading to more precise and effective therapeutic strategies. The findings were recently published in the prestigious journal Nature Communications.
A new Tool for Precision Medicine
The research team focused their efforts on cardiometabolic health, a critical area encompassing the well-being of the heart and blood vessels, as well as the body’s intricate processes for breaking down food and generating energy.
Traditionally, researchers have relied on “genome-wide association studies” (GWAS) to identify regions of DNA associated with traits found in cardiovascular diseases. However,these methods often fall short due to the inherent complexity of the genome. Genes can overlap and interact in multifaceted ways, making it challenging to pinpoint the exact gene or specific genetic change driving a disease. Furthermore, genetic alterations can exert their influence indirectly, such as by switching genes on or off or acting from distant locations within the DNA, all of which profoundly impact gene function.
Building upon existing GWAS methodologies, the Case Western Reserve team has engineered a computationally efficient tool, dubbed TGVIS (Tissue-Gene pairs, direct casual Variants, and Infinitesimal Effects Selector). This new instrument is designed to precisely pinpoint the genes and probable causal variations within specific regions of a person’s DNA.
“We utilized TGVIS to examine 45 traits associated with heart and metabolism, leveraging genomic data from 31 distinct types of body tissues,” explained Dr. rong Zhu, a professor in the Department of Population and Quantitative Health Sciences at the Case Western Reserve School of Medicine. “This allowed us to more accurately identify which genes are likely responsible for these traits. Notably, we discovered several new genes that had been overlooked in previous studies.”
How TGVIS enhances Genetic Discovery
The TGVIS method distinguishes itself by integrating information from GWAS with a wealth of other biological data.This includes insights into how the body utilizes the genetic instructions encoded in DNA to produce essential components like proteins and molecules vital for bodily functions. Through sophisticated mathematical and computational analyses,this diverse data is merged to pinpoint the specific genes and DNA alterations that may be contributing to disease development.
While TGVIS was initially applied to cardiometabolic traits, its underlying methodology is highly adaptable and can be readily applied to the study of a wide range of other diseases. Dr. Zhu and his team are already exploring its submission in identifying key genetic factors for breast cancer, Alzheimer’s disease, and other cardiovascular conditions.
“This tool now enables us to prioritize which genes warrant further examination,” Dr. Zhu added. “This significantly enhances the efficiency and focus of research, which in turn can accelerate the pace of scientific discoveries and the development of innovative treatments.”
yihe Yang, a postdoctoral fellow in Dr. zhu’s lab, played a leading role in this significant study. Noah Lorinez-Comi, a former phd student in the lab, also made substantial contributions to the research.
Sources:
Case Western Reserve University: https://thedaily.case.edu/new-gene-tool-leads-to-better-treatments-for-complex-diseases/
Journal Reference: Yang, Y., et al. (2025). Uncovering causal gene-tissue pairs and variants through a multivariate TWAS controlling for infinitesimal effects. Nature Communications. https://doi.org/10.1038/s41467-025-61423-8