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Updated: Mar 21, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Proprietary Considerations in the Use of Cardiovascular Genetic Data
Mladen Kolovic1, John F Robinson1, Robert A Hegele1
1Department of Medicine and Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.
Abstract:
Cardiovascular researchers and clinicians who analyze next-generation sequencing data often search databases of previously reported mutations to determine if an observed mutation is pathogenic. In 2012 we created a database of all reported mutations causing human dyslipidemia syndromes. In 2015, we were advised that some information in our database was now proprietary, after the acquisition of a human disease genetic database by a private biotechnology company. To make our dyslipidemia database and tables of mutations compliant with this new reality, we wrote custom computer scripts to remove certain data fields from the previously reported tables. Data columns in the revised tables now include: accession number, gene name and symbol, mutation type, exon number, inheritance pattern, minor allele frequencies, predictive functional scores, reported functional effects, and additional patient information. The revised mutation tables provide a comprehensive qualitative and quantitative description of genetic variants causing monogenic dyslipidemias, but do not have complete information on all mutations. This experience indicates that free and unlimited access to human disease mutation data should not be taken for granted. Investigators or clinicians who require additional data that is not within the revised tables can still access the data through academic institutions that hold subscriptions to proprietary human mutation databases.
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