A study led by the Barcelona Supercomputing Center (BSC) suggests that specific patient characteristics (such as gene expression) can be important factors in the development of clinical strategies to treat and manage comorbidities. The work, which goes one step further by investigating comorbidities at the molecular level for hundreds of diseases and thousands of patients, has been published today in Nature Communications.
“Our approach is not only able to confirm known comorbidities, but also to provide concrete leads into the biological processes involved, a first step towards comorbidity management and prevention”, says Jon Sánchez, first author of the study working at the computational biology group led by Alfonso Valencia, director of the Life Sciences department at BSC.
The fact that many people suffer from more than one disease, known as comorbidity, has become one of the main challenges for the 21st century aging population, as it mainly affects the elderly, decreasing treatment options and patients’ life expectancy while increasing health care costs.
We know about comorbidity relations mainly from epidemiological studies, where the numbers of people simultaneously suffering from two or more diseases are registered and compared to the rest of the population. Those approaches provide a global overview on the higher or lower probability of developing a secondary disease when already suffering from a previous one. A well-known example is the higher risk of heart failure in patients with hypertension, described to be 4 times higher than in non-hypertensive patients. On the other hand, a lower than expected probability of developing lung cancer in patients suffering from Alzheimer’s disease has been described. The actual reasons behind many of those positive and negative correlations are largely unknown.
“Even if at the population level Alzheimer’s disease patients have less chances of getting lung cancer, this doesn’t mean that no one with Alzheimer’s disease will develop lung cancer. In our study we see a lot of variability between patients at the gene expression level, which suggests that some specific group of Alzheimer’s disease patients might actually have the opposite tendency, being at a higher risk of developing lung cancer”, says Jon Sánchez.
This work is a first step towards studying comorbidities at a patient level, proposing a paradigmatic change from the disease-centered to a patient-centered approach, in line with the general idea behind personalized medicine.
The study is the result of a collaborative effort between scientists at the Barcelona Supercomputing Center (BSC), the Spanish National Cancer Research Center (CNIO), the Institute of Evolutionary Biology (IBE), the University of Valencia, the Aix Marseille University and the Centre de Recherches en Cancérologie de Toulouse (CRCT).
Article: “Interpreting molecular similarity between patients as a determinant of disease comorbidity relationships”
DOI: 10.1038/s41467-020-16540-x
Link: https://www.nature.com/articles/s41467-020-16540-x
