While many people and professionals have publicly lambasted the widespread use of digital technologies and medicine, it has conferred its share of potent benefits. Years ago, a physicist named Stephan Thurner was invited to examine medical data by an Austrian health insurance company. Upon doing so, he arrived at the keen realization that this data could reveal more than suspected.
New Disease Findings
Thurner published a paper in the New Journal of Physics in which he analyzed the trends of 1,055 diseases in the human population. They conducted a statistical study, which unveiled the risk of having two coexisting diseases presented at the same time. What they revealed were a number of unique associations between specific diseases. Essentially, patients who had one disease were more likely to develop a related disease, and those patients displayed stronger risk factors for that disease than the general population.
Of course, their publications have not been met without their share of criticism. In an additional research study, they established a link between diabetes and Parkinson's’ Disease by analyzing trends in digital disease data. Hypothetically, this offered a novel framework, in which they could gauge the molecular components of disease. Still, they wondered if specific diseases had a generic component, regardless if it was environmentally linked or not.
A New Direction in Research
A number of realizations appear to be driving this research. Essentially, diseases are no longer the isolated incidents that people once thought they were. In fact, they are less discrete than initially suspected. Generally speaking, diseases are characterized in terms of what symptoms they generate. However, the molecular basis of disease may transcend existing knowledge of biological-based disease components. So, how might theorists explain the comorbidity of seemingly unrelated conditions? They may possess a relationship at a molecular level.
Many researchers have identified the genetic and biological components of disease, but a research group at Harvard Medical School delved into a much more complex realm of networks—cellular and molecular. While cells may seem inconsequential, they are replete with chemical and biological activities and processes that translate to a larger picture. If even the smallest cell component behaves abnormally, this can induce a number of perilous circumstances in the human subject, namely disease. Hence, the complex networks in cells and molecules are pertinent to today’s understanding of disease.
Researchers have used this disease model to study pulmonary hypertension and its link to heart disease. What they revealed was that two proteins correlated both conditions at a cellular level and increased the risk of morbidity. Hence, disease research requires a deeply molecular and cellular approach.