When Shamil Sunyaev and his colleagues began their research, they faced a puzzle that has long frustrated geneticists: findings from yeast cells, mice, and other model systems often point to gene networks that might contribute to diseases like Parkinson's and breast cancer, but those leads don't always translate to human biology. Now, a new statistical tool developed at Harvard Medical School may finally bridge that gap.
The framework, called NERINE, allows researchers to examine genes at the network level rather than one at a time, making it faster and easier to identify which groups of genes are most likely to contribute to a particular human disease. Using genetic data from the UK Biobank and Mass General Brigham Biobank, the team identified variants associated with breast cancer, cardiovascular disease, and type 2 diabetes that could not be detected in traditional single-gene tests.
"We can take a network of genes and their connections and test whether there is a signal in real humans for the phenomenon we're interested in," said Sunyaev, a professor of biomedical informatics in the Blavatnik Institute at HMS. "We can test if humans with mutations in a particular network are, for example, more likely to develop breast cancer."
But perhaps the most striking finding came from the team's deep dive into Parkinson's disease. Starting with a gene network derived from yeast and neuronal models, NERINE revealed a previously unrecognized link to mutations involved in the production of prolactin—a hormone typically associated with pregnancy and breastfeeding but also linked to dopamine, the neurotransmitter depleted in Parkinson's. Follow-up experiments showed that prolactin loss had a negative effect on human neurons made vulnerable by stress from the abnormal protein alpha-synuclein, suggesting that prolactin may serve a protective role in the disease.
"The genetic data pointed us toward a role for prolactin within neurons that was completely unexpected," said Vikram Khurana, an HMS associate professor of neurology at Brigham and Women's Hospital and chief of the Division of Movement Disorders at Mass General Brigham. "It opened up an entirely new line of investigation for Parkinson’s disease."
For cardiovascular disease, the framework uncovered genetic connections outside known pathways, providing new insights into biological mechanisms that may contribute to disease risk. First author Sumaiya Nazeen, an HMS research fellow in the Sunyaev and Khurana Labs, noted that NERINE helps prioritize which genes and interactions are most promising to investigate, making experimental follow-up more focused and efficient.
The findings, published in Cell Genomics, represent a significant step toward understanding complex diseases at their roots—and may ultimately point researchers toward new therapeutic targets where few existed before.