This guide will take approximately 5 minutes to complete.
In this guide you will learn:
- How to search for genetic alterations related to a disease of interest
- How to discover genetic variants from the GWAS Catalog
- How to identify disorders associated with mutations of a gene of interest from the GWAS Catalog
- How to validate and qualify genetic associations using data coming from the GWAS Catalog
Step 0: Login
Refer to https://med.causaly.com
Step 1: Search for genetic alterations related to a disease of interest
To explore mutations related to a disease of interest, use Causaly Discover in the Causaly home page (Figure 1).
Figure 1. The Causaly Discover on the Causaly homepage
Begin your search by typing your question into the Causaly Discover search bar in natural language (Figure 2). “What genetic alterations are linked with NSCLC?” will be used as an example (link).
Figure 2: Directly ask a question in natural language in the Causaly Discover search bar
Click "Search" or hit Enter on your keyboard to run the search, which will direct you to the Causaly Discover results page.
Causaly Discover offers an AI-generated summary, complete with in-line citations for transparency into the results, based on the top 20 articles. You can scroll down to view all the documents retrieved in response to your search query.
In addition, Causaly Discover will prompt you to visit the Bio Graph to review the genes in a dendrogram list and be able to deep dive into their unique relationships with the disease of interest. Click on View analysis to open the Causaly Bio Graph knowledge card (Figure 3).
Figure 3: Causaly Bio Graph card linking your search query to Causaly dendrogram results.
TIP! If you are used to working with keywords on Intelligent Search and/or would like to review the results directly in the Causaly Biograph, you can select the option to return to your previous Causaly experience and initiate your search there by clicking the “Intelligent Search” option under “Biograph” on top of your Causaly homepage (Figure 4).
Figure 4: Access the previous Causaly interface, by clicking on Biograph and selecting the “Intelligent Search” option.
Step 2: Discover genetic variants from the GWAS Catalog for a disease of interest
Causaly uses the GWAS Catalog as a data source, which contains information regarding gene variant-trait associations. The GWAS Catalog enriches our Knowledge Graph with 350,000+ SNPs and 680,000+ associations.
TIP! To account for the high chance of false positives in GWAS studies, a genome-wide significance threshold is applied at a p-value of 5 × 10^-8. This threshold helps to reduce the number of false positive associations that may arise from testing a large number of genetic variants.
You can specify results from the GWAS Catalog by making use of the Data Source filters on the left (link) (Figure 5).
Figure 5. The GWAS Catalog option is found under the Data Source filter.
TIP! You can click on the title of the GWAS document to reach the Publication page in the GWAS Catalog.
Step 3: Identify disorders associated with mutations of a gene of interest from the GWAS Catalog
To find out which disorders are related to variants of your gene of interest, you can use the Causaly Discover Search bar and look for the diseases associated with mutations of a specific gene, such as the example below “What diseases are associated with BRCA2 mutations?” (Figure 6) (link).
Figure 6. Utilize the Causaly Discover bar to look for diseases associated with BRCA2 mutations
On the search page, you will find a structured AI-generated summary that reviews the top evidence, providing an overview of the search topic supported by in-line, linked citations for transparency and traceability.
TIP!
- The same approach can be used to search for specific genetic variants and their association with diseases (Figure 7) (link).
Figure 7. Diseases associated with the EGFR T790M mutations in the Causaly Discover bar
Step 4: Validate and qualify genetic associations using data coming from the GWAS Catalog
Targets that have been genetically linked to a disease exhibit a higher probability of success in the clinical development pipeline, with pre-clinical and clinical research demonstrating respectively four-fold and two-fold increases in success rates (link).
Use Causaly Discover to find out whether your target has a genetic association with your disease of interest. In this example, we explore the relationship between TERT and glioma (link) (Figure 8).
Figure 8. Explore the relationship between TERT and glioma.
In the filter panel on the left, under Data Sources, select ‘GWAS Catalog’ to see genetic evidence (link).
In this way the results as well as the AI-generated summary will be based on findings from the GWAS catalog.
Want to learn more about how to find evidence in Causaly?
Find more information and examples on how to search posts by clicking here.