Gene-disease associations

Up-to-date knowledge on the association of genes with specific phenotypes or diseases is of great importance in variant interpretation, as it enables variants predicted to affect the function of known disease genes to be quickly identified.

Disease definition

A specific and detailed description of the gene-disease relationship is needed to enable an understanding of disease mechanisms and accurate diagnosis. Some variants can give rise to multiple different disorders depending on which region is disrupted, the functional result of the change, or how many copies are affected in a person. For example, disruptions in different parts of FGFR3 give rise to different conditions (Figure 1).

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Figure 1. FGFR3 is associated with multiple diseases. Pathogenic FGFR3 variants from DECIPHER and ClinVar are plotted on Pfam protein domains. Muenke syndrome, Achondroplasia, Hypochondroplasia, Variable-severity Chondrodysplasia and Thanatophoric Dysplasia are caused by amino acid substitutions in particular locations that activate specific protein functions.

In some genes, different conditions may be observed if either one of both copies of the gene are affected, for example, ATP6V1A, which is associated with the dominant condition epileptic encephalopathy and recessive condition cutis laxa. In other cases, the loss of one functionally normal copy of a gene gives rise to a similar but milder condition than the loss of both. Recommendations have been created to help decide when conditions observed in different individuals should be regarded as the same or a different disease, but often domain expert input is required. Guidance is available for monogenic disease nomenclature at ClinGen.

Assessing validity

Gene-disease associations are reported in the literature with varying degrees of detail and supporting evidence. This information may be mined automatically (i.e. via purely computational approaches) or curated by domain experts (i.e. assessed using expert knowledge). It is important to understand the level of evidence available, the reliability of the extraction method and the disease mechanism when using gene association data. ClinGen has created guidelines and the Gene Curation Coalition (GenCC) are harmonising approaches to curation and developing consistent terminology, as introduced in the step Mechanisms of human genetic disease.

GenCC has defined a set of validity classifications, which have been widely adopted.‘Definitive’ and ‘Strong’ classifications are used when evidence for the association has been found repeatedly and independently over a number of years and no convincing contradictory evidence has been reported; ‘definitive’ is assigned by some groups when an association has been accepted by community experts for some time. ’Moderate’ is assigned when there is not yet a strong set of evidence, for example, when there is only one publication with convincing evidence. These three categories are widely used in diagnostic reporting. The ‘Limited’ classification is used for cases where little evidence is available, but the association is plausible; this is not used in clinical reporting.

Resources

The Online Mendelian Inheritance in Man (OMIM) was the earliest attempt to collect information on genetic disorders and currently holds descriptions of the molecular basis of over 6,400 gene-related phenotypes. ClinGen defines structured approaches to evaluation and reporting and brings together disease-domain experts into working groups that evaluate evidence for gene-disease association.

Gene2Phenotype focuses on a number of disease areas, in particular, developmental disorders and seeks to curate detailed mechanism information (Figure 2). Summary conclusions from curation teams are available through the GenCC database.

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Figure 2. Example G2P record showing a disease associated with a gain of function in gene CDKN1C. The mutation consequence flag reports that only variants in a specific region (PCNA binding region) are associated with the disease and the cross-cutting modifier reports that the variants must come from one parent (in this case the mother).

Multiple agreeing assertions from different groups (e.g. ACTB and Baraitser-Winter syndrome) increase confidence in the association, but they should not be assumed to be different sources of evidence as each may be independent interpretations of the same set of evidence. A list of well-known gene-disease association resources is available in Table 1.

Table 1. Resources for gene-disease association information.