Disease-Disease Network
Using the cross-phenotype associations found in the EHR-based PheWAS analysis, we constructed a disease-disease network (DDN) in order to understand the genetic similarities between human diseases (Figure 1). The network consists of 385 ICD-9-based disease diagnoses (which we obtained from an original 541 ICD-9 codes by using a threshold of p < 1 × 10-4) acting as nodes and the 1,398 edges connecting them. As shown in Figure 2, we classified ICD-9 codes into 15 broad disease classes, labeled with different colors. The DDN provides a bird’s-eye view of the interconnections between the diseases on the basis of shared genetic associations. Many interconnections, including those between endocrine, musculoskeletal, and neurological disorders, were observed across classes. The strongest connections (indicated by the thickness of the network lines in Figure 2), which are based on the highest number of shared genetic variants, were between autoimmune disorders such as type 1 diabetes (MIM: 222100), rheumatoid arthritis (MIM: 180300), psoriasis (MIM: 177900), and multiple sclerosis (MIM: 126200) (Figure 2). These links are consistent with previous findings suggesting that these autoimmune diseases are determined by shared genetic components, indicating similar pathogenic mechanisms, even if completely different tissue types are affected in each disorder.28, 29, 30, 31 This could indicate that there are shared genetic pathways linking multiple SNPs to the same diseases. This could also be a reflection of a high correlation between disease occurrences.
Figure 2 Disease-Disease Network
Using the cross-phenotype associations from an EHR-based PheWAS, we generated the disease-disease network (DDN). In this network, nodes represent the diseases, and the edges (lines) between the nodes represent shared genetic associations between pairs of diseases. The color of the node represents the broader disease category to which it belongs. The size of the node indicates the importance of the node in the network; importance was based on the betweenness centrality measure. The bigger nodes have higher betweenness centrality, and these nodes are referred to as hub nodes. The width of the edges (lines) represents the number of shared variants or variants in an LD block.