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One of the most popular dog breeds is the Golden Retriever. Unfortunately, these dogs are also at high risk for developing cancer. New research has investigated genetic factors that may be able to extend the lives of these beloved dogs. This work focused on longevity genes instead of those that have been associated with cancer, and led to the identification of gene variants that could extend the dogs’ lifespan by as much as two years. The findings have been reported in GeroScience.

While most golden retrievers are predisposed to cancer, some of these dogs can live to be as old as 15 or 16 years. So the researchers thought that there might be genetic factors that were mitigating the effect of the cancer-related genes, noted co-corresponding study author Robert Rebhun, Maxine Adler Endowed Chair in oncology at the UC Davis School of Veterinary Medicine. The gene that had this effect was HER4.

A study published today by scientists from Harvard University and epigenetic research company TruDiagnostic has shed light on the reasons why our bodies are aging on a cellular level, laying the foundations for medical based treatment options to reduce the risk of age-related death and disease in highly targeted ways.

Longevity. Technology: Age is the number one risk factor for most chronic diseases and death across the world. Epigenetics (or the way our genes are put to use throughout our bodies) has emerged as a crucial method of evaluating health, and while previous DNA methylation clocks could determine how advanced one’s body has aged, they have not yet been able to provide information to the reasons why someone might have accelerated or decelerated aging outcomes.

“In our research, we set out to create the best method to quantify the biological aging process. However, aging is extremely complex,” explains Harvard Medical School Associate Professor Dr Jessica Lasky-Su. “To solve this issue of complexity, our approach was to gather data across multiple sources of information. We chose to do this by building one of the most robust aging datasets in the world by quantifying patients’ proteomics, metabolomics, clinical histories and DNA methylation.”