Act 1: Network-based approaches to human disease have multiple potential biological and clinical applications. The first step in exploring the interplay between networks and human diseases, we need a comprehensive and accurate molecular and phenotypic networks [Barabási AL, Nat Rev Genet. 2011, 12:56-68]. Network within our cells elucidates how our genes and molecules interact with each other. But how do we connect this stunning map of our inner cellular interconnectedness to human disease? To grasp the magnitude of the problem, let us look at the current network of a human cell.
Act 2: To see how the network map relates to disease, we start with Asthma, the most common chronic respiratory disease, affecting 17 million U.S. children and adults. Despite advances in our understanding of asthma, it remains a major cause of morbidity, resulting in 0.5 million hospitalizations a year, and is the most common cause of lost school and workdays. During the last decades Geneticist and biologists have identified the genes associated with Asthma. To see the Asthma module, we next identify these genes on network map. So here the purple nodes are the asthma genes. We expect them to be together, forming a compact asthma module. In reality they are scattered all over the map, disconnected. But we are not only missing links; we are also missing many asthma genes. And that is where the network science can help: we can use it to identify candidate disease genes, those that could hold the module together. So we exploited the collective intelligence of the network to identify the Asthma module.
Act 3: You can see the outcome of this, the Asthma module being reconstructed in front of our eyes. Now that we have the disease module, we can use it to identify the disease mechanism and to find drug targets and eventually better drugs against asthma.
Act 4: We used the same tools to identify the disease module of COPD, shown with yellow on the map. Chronic obstructive pulmonary disease (COPD) is a lung disease that makes it difficult to breathe. It is estimated that about 5 to 10 percent of adults may have COPD with an increase in prevalence with age. COPD and related conditions (including asthma) are major cause of morbidity. COPD is often called the smokers disease, is a lung disease like Asthma, with many overlapping symptoms, like shortness of breath and cough. It is not surprising, therefore, that its disease module is in the neighborhood of Asthma. Not only are they in the same neighborhood, but also the two modules show considerable overlap. In general we expect that diseases that have similar symptoms, like Asthma and COPD, or Diabetes and obesity, and many forms of cancer, should be located in the same part of the cellular network. Unrelated diseases, like cancer and asthma, may reside in a different neighborhood of this cellular universe. So by simply looking where various diseases are within this map, we can identify the molecular relationships between them. We used the same tools to identify the disease module of COPD, shown with yellow on the map. So by simply looking where various diseases are within this map, we can identify the molecular relationships between them.