When phenotype does not match genotype: importance of “real-time” refining of phenotypic information for exome data interpretation



Clinical data provided to genetic testing laboratories are frequently scarce. Our purpose was to evaluate clinical scenarios where phenotypic refinement in proband’s family members might impact exome data interpretation.


Of 614 exomes, 209 were diagnostic and included in this study. Phenotypic information was gathered by the variant interpretation team from genetic counseling letters and images. If a discrepancy between reported clinical findings and presumably disease-causing variant segregation was observed, referring clinicians were contacted for phenotypic clarification.


In 16/209 (7.7%) cases, phenotypic refinement was important due to (1) lack of cosegregation of disease-causing variant with the reported phenotype; (2) identification of different disorders with overlapping symptoms in the same family; (3) similar features in proband and family members, but molecular cause identified in proband only; and (4) previously unrecognized maternal condition causative of child’s phenotype. As a result of phenotypic clarification, in 12/16 (75%) cases definition of affected versus unaffected status in one of the family members has changed, and in one case variant classification has changed.


Detailed description of phenotypes in family members including differences in clinical presentations, even if subtle, are important in exome interpretation and should be communicated to the variant interpretation team.

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The manuscript was edited by Debby Mir.

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Correspondence to Lina Basel-Salmon MD, PhD.

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CG-J and ARS are full-time employees of the Regeneron Genetics Center from Regeneron Pharmaceuticals Inc. and receive stock options as part of compensation. The remaining authors declare that they have no conflict of interest.

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Basel-Salmon, L., Ruhrman-Shahar, N., Orenstein, N. et al. When phenotype does not match genotype: importance of “real-time” refining of phenotypic information for exome data interpretation. Genet Med (2020). https://doi.org/10.1038/s41436-020-00938-5

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  • variant interpretation
  • phenotypic information
  • exome
  • variant classification
  • overlapping features