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Use Cases
Use case UC1 emphasizes the strength of exploratory search over graphs, by supporting users in selecting graph portions, considering/accepting proposed expansions, and browsing results in terms of NMPI and explained relationships. Use cases of increasing complexity are provided next, offering examples of searches upon graph queries with different shapes. UC2 and UC3 introduce very simple linear graph queries (one chain of nodes); UC4 shows the use of a Y-shaped graph query; and UC5 and UC6 represent more complex shapes with nodes forming triangles.
(Pairo-Castineira et al., 2020) aims to reveal previously undescribed molecular mechanisms of critical illness in patients with COVID-19 with genome-wide studies. The results of such studies may provide therapeutic targets to modulate the host immune response to promote survival. Inspired by this publication, we create a graph query including relevant human genes that are related to higher or lower severity of COVID-19 (IFNAR2, CCR2, and TYK2 genes) and we link them to the change in the severity of the disease (see Figure 1A).
Figure 1. GRAPH-SEARCH screens dedicated to UC1. (A) Express graph query; (B) Find paths; (C) Select paths; (D) Explore publications on the results page.
Since the hypothesis is broad, we start the exploratory process focusing on a subgraph of the graph query (see nodes in red selected in Figure 1A).
Here, we only consider the effect of the increase of expression in the CCR2 gene.
Figure 1B shows how GRAPH-SEARCH expands the path between the concepts High and Gene Expression (not otherwise connected in the co-occurrence network).
According to NPMI values, the most relevant concept connecting them is Up-Regulation (Physiology).
Figure 1C shows that the path going through this concept has been selected by the user among the other proposed.
The Results page (Figure 1D) shows a publication (Teixeira et al., 2021) that covers 4/5 explained relationships of the original graph query.
This means that -- out of the five original relationships of the selected portion of the graph query -- only four are explained by the publication (all except for the one between Gene Expression and High).
At this point, the user can consider other portions of the graph query, or the whole query.
Cystic fibrosis is a disorder that affects mostly the lungs, the digestive system, and other organs in the body.
It is widely known that also COVID-19 affects the respiratory system.
How has their connection been investigated in CORD-19?
The simplest possible graph query in GRAPH-SEARCH holds two nodes (cystic fibrosis and COVID-19) connected by one relationship of co-occurrence, see Figure 2. Cystic fibrosis is represented by UMLS concept ID C0010674; and COVID-19 by the UMLS concept ID C5203670.
The two concepts are not directly connected within the network; among the proposed paths in the expansion, we choose the one through the concept Respiratory secretion viscosity alteration (UMLS ID 3537094).
Only one publication in CORD-19 explains this path, covering it completely, with an NPMI sum of 0.5668. (Kratochvil et al., 2022) characterized the composition of respiratory secretions of intubated COVID-19 patients finding that they closely resemble those of cystic fibrosis, a minor observation unrelated to clinical severity. In general, the lack of relevant clinical references confirmed our expectation that cystic fibrosis did not impact COVID-19 severity.
Figure 2. Graph query of UC2 representing the simplest query in GRAPH-SEARCH, with only two concepts.
During the second year of the pandemic interest arose in the possibility of intervening at the onset of mild-to-moderate COVID-19 symptoms in outpatients (instead of hospitalized patients); it was suggested that this could prevent the progression to a more severe illness and long-term complications.
More specifically, (Perico et al., 2022) investigated the use of anti-inflammatory drugs, especially non-steroidal anti-inflammatory drugs (NSAIDs) as a therapeutic strategy.
In our graph query, we include as the main concepts COVID-19 (C5203670) -
Outpatients (C0029921) -
Anti-Inflammatory Agents, Non Steroidal (C0003211) -
Cyclooxygenase 2 Inhibitors (C1257954), the last being a specific class of NSAIDs. See Figure 3.
In this case, no expansion of the original graph query is performed, as all the relationships are present in the co-occurrence network. The Results page contains a list of 440 publications, whose abstracts discuss the concepts in the graph query from different perspectives and approaches. The top three results include work from (Consolaro et al., 2022) -- a home-treatment algorithm based on anti-inflammatory drugs; (Popovych et al., 2019) -- discussing the therapeutic efficacy of the BNO 1030 extract, which is a phytotherapeutic anti-inflammatory agent; and (Sava et al., 2021) -- exposing the results of a ninety-day treatment of patients with severe COVID with a specific NSAID drug, tocilizumab.
Figure 3. Graph query of UC3, with a chain of four concepts.
Elevated blood glucose levels are considered a risk factor for the severity of the disease. With GRAPH-SEARCH, we compose a Y-shaped graph query (see Figure 4), expressing that (high levels of blood glucose) or (higher blood glucose) can induce a severe illness. This example makes sophisticated use of 'utils' terms that indicate a qualitative concept (such as high, increased), a qualifier (level), or a causative connector (induces). These are provided in a specific list of the concepts' browsers of GRAPH-SEARCH.
As a result, we obtained a list of 395 publications, where the top-ranked publication explains 5/5 relationships: (Logette et al., 2021) reports on the relationship between blood glucose levels and the severity of COVID-19. All following publications, ranked in descending order by the number of explained relationships of the original graph query, explain at most 3/5 relations.
Figure 4. Graph query of UC4, with UMLS concepts IDs in red.
(Patel et al., 2019) hypothesized that SARS-CoV-2 infection could be associated with the shedding of ACE2 from cell membranes leading to increased plasma ACE2 activity levels. In their study, they evaluate the implications and the consequences of COVID-19 pathogenesis. In particular, they claim that in patients with cardiovascular diseases, there is increased “shedding” of ACE2, and higher circulating levels are associated with the downregulation of membrane-bound ACE2.
The graph query in Figure 5A expresses this hypothesis. Here, two relationships are not found in the co-occurrence network; the first paths suggested by the system as possible explanations are not meaningful w.r.t. the context, thus we select alternative concepts, i.e., Subacute Endocarditis and Intensive Care Unit (see Figure 5B).
Results can be ranked by the number of citations; we found two publications particularly interesting, by (Yamaguchi et al., 2021) and (Gupta et al., 2021), as they propose solutions for the prevention and treatment of the side effects of COVID-19 for patients with cardiovascular diseases.
Figure 5. Graph query of UC5 (A) and found paths (B).
The side effects of vaccines are a topic of relevance.
Here, we investigate the connection between events of heart inflammation (e.g., myocarditis) among adolescents and the COVID-19 Moderna vaccine.
We compose a graph query in GRAPH-SEARCH with four nodes (see Figure 6A); a triangle is formed by
Adolescent (age group) (C0205653), Myocarditis (C0027059), and the Moderna COVID-19 Vaccine (CIDO ID obo.VO_0005157); the vaccine entity is connected to the COVID-19 (C5203670) node.
COVID-19 and Moderna COVID-19 Vaccine are not directly connected; among the possible paths suggested by GRAPH-SEARCH, the two scoring the highest sum of mutual information are through Vaccination and Myopericarditis.
The latter refers to both myocarditis and pericarditis (i.e., the inflammation of the pericardium, which is the sac that surrounds the heart).
The latter concept allows us to expand the initial query to complete the match with the co-occurrence network (see Figure 6B).
On the Results page, 190 bibliographic resources are provided. The top-ranked one, which explains all four relationships of the graph query, is a report by (Galgano et al., 2021) that suggests the implication of the use of mRNA vaccines with a higher risk for myocarditis in males aged 12-29 years.
The following results do not explain the relationship between the COVID-19 Moderna Vaccine and COVID-19 through Myopericarditis, as they explain only three relations. These results, for instance, report adverse events of Myocarditis after vaccination in the US ((Oster et al., 2022)) and Korea (Lee et al., 2022).
Figure 6. Graph query of UC6 (A) and found paths (B).