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How to interpret molecular genetic tests

Molecular genetic test data need to be classified.

Molecular genetic tests, such as Next Generation Sequencing (NGS), involve determining the meaning of the changes found in a DNA sequence.

In whole exome sequencing, for example, about 50 thousand genetic variants are detected. Therefore, the main challenge in interpreting these data is to determine which is (or which are) responsible for the diagnostic hypothesis that motivated the request for the exam.

First, it is necessary to always have a disease or a group of diseases as a diagnostic hypothesis to guide the flow of analysis and the clinical interpretation of the variants for later elaboration of the medical report.

For many variants, the clinical consequences of the change in the DNA sequence are well understood and have been characterized and published in the scientific literature and/or genomic databases; in these cases, these variants can definitely be classified as pathogenic or benign.

An example of a pathogenic variant is the F508del mutation (deletion of the amino acid Phenylalanine at position 508 of the CFTR gene) which causes cystic fibrosis when homozygous.

However, not all variants found cause disease and it is the responsibility of the laboratory that performs the tests, to interpret and classify the genetic variants as causing disease (pathogenic) or benign.

That is why it is important that the health professional in charge of requesting this type of tests, understand and follow the rapid evolution of science and art in the way in which these classifications are made.

How does the laboratory interpret the variants?

To classify the changes it is necessary to add relevant information. This information can be extracted from different databases or websites.

Some examples of types of information to take into account:

  • Presence in the literature

Has the variant been reported associated with any disease?

  • DNA change location

Does the variant target a gene that encodes an important protein?

  • Source of the change and prediction of possible damage from the change 

Does the variant alter the production or function of a protein?

  • Frequency of change in the population

Has the variant already been identified in healthy people?

To assess the clinical significance of the variants, databases are used that describe previously reported variants, such as the Human Gene Mutation Database (HGMD) and ClinVar, as well as high-impact published scientific articles (generally available on PubMed).

Also considered is the frequency of the variant in control populations (healthy individuals) from sources including dbSNP, the 1000 Genomes Project, the Exome Variant Server (EVS) and the Exome Aggregation Consortium (ExAC); and software (PolyPhen2, SIFT and MutationTaster) that provide in silico predictions about the effect of changes. It is important to note, however, that in silico prediction tools are not always accurate and therefore only help to provide supporting evidence to prioritize variants.

Currently, there is no defined standard for classifying variants, but initiatives by various groups working to define standard procedures for classifying and curing variants.

The guidelines most used at the moment were proposed by specialists from the American College of Medical Genetics and Genomics (American College of Medical Genetics, ACMG), who developed a set of guidelines that designate the parameters to be adopted in all stages of NGS processing.

What are the classification categories?

The clinical interpretation of genetic variants is time consuming and requires rigorous attention to detail. The ACMG guidelines propose that the changes found should be classified as:

Clinical considerations

New information about a genetic alteration can be extracted every day. Several studies have been carried out and many scientific sources have made available online classifiers for variants. More information about an alteration obtained, ensures more faithfully it can be classified in order to predict its consequence in the organism and associate it with a disease or even health condition.

Therefore, the interpretation of the variants reflects the scientific knowledge available at the time of the analysis. A result reporting variants not associated with the diagnostic hypothesis today can be reassessed, taking into account new scientific information and/or new signs and symptoms presented by the patient, and the same variants can be re-classified as pathogenic in the future, or vice versa.

References:

[1] Richards, S. et al. (2015) Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med., 17, 405–424.

[2] Deignan,J.L. et al. (2019) Points to consider in the reevaluation and reanalysis of genomic test results: a statement of the American College of Medical Genetics and Genomics (ACMG). Genet. Med., 21, 1267–1270.

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