Accurate phenotyping and HPO overlap visualization in AION 🔍

Author: Edgard Verdura, PhD

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Welcome to our December edition of Molecular Mechanisms, our monthly series on interesting cases we have come across on AION. This month we focus on how AION leverages parents’ information to impute segregation patterns and prioritize variants.

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We've released a new version of AION recently, and today we will focus on one of the features that is brand new (HPO overlap visualization) through two interesting trio cases (both patient, mother and father vcf files available) sequenced by exome sequencing in 2 different genetic departments.

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Our first case is a patient affected by a severe immunological disorder. Partly thanks to accurate laboratory-related HPOs relevant for the pathology (e.g. Abnormal immunoglobulin level), an homozygous loss-of-function variant in FERMT3 (p.Gln96Ter) was strongly prioritized in Rank #1. Mutations in gene FERMT3 have been linked to Leukocyte adhesion deficiency, type III. This gene encodes an intracellular protein expressed in hematopoietic cells. In this disease, mutations affecting this protein disrupt the adhesive functions of integrins in both leukocytes and platelets, resulting in immunological system abnormalities affecting several organs (spleen, liver, blood, bones…).

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This case highlights the usefulness of accurate phenotypic characterization, even of HPOs that are not related to visible physical symptoms including laboratory findings (e.g. Abnormal immunoglobulin level, Reduced granulocyte CD18 level). This case also displayed Hepatosplenomegaly and an Abnormality of the lymph nodes. In the screenshot you can see how AION displays these HPO terms exactly overlapping between patient’s phenotype and candidate disease. Note that although very specific terms such as the ones mentioned above might not directly overlap with the terms associated with a candidate disease, they will always be taken into account by AION prioritization logic through their “parent terms”. As an example, “Abnormal immunoglobulin level” (patient HPO) would be taken into account though a parent term such as “Abnormality of the immune system”, which is also a parent of some terms associated to this disease, such as “Leukocytosis” or “Recurrent bacterial infections”.

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Our second case, on the other hand, is affected by a congenital gastrointestinal disorder. In this case, AION was decisive in providing a quick diagnosis to a newborn patient. Two pathogenic variants were identified in SLC9A3 (coding Na+/H+ antiporter 3 protein) in compound heterozygosis. Given the description of these variants (p.Arg382Gln, p.Ser582Leufs) in ClinVar as pathogenic, in a case with a very strong phenotypic match with the candidate disease (p-value=8.27E-25), a fast diagnosis of this case was possible. That enabled a better management of this patient since its birth, added to accurate genetic counselling. As seen below, several of the HPO terms related to the gastrointestinal phenotype of this patient were exactly overlapping with HPOs associated with Diarrhea 8, secretory sodium, congenital (Polyhydramnios, abdominal distention…).

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Speed in the interpretation of NGS data is crucial in these neonatal cases to provide a swift diagnosis and subsequent choices in treatment or patient management. Rapid, AI-assisted phenotype assessment is a crucial feature needed for data interpretation in initiatives such as rapid Whole Genome Sequencing (rWGS), progressively being implanted in several hospitals throughout the world (Owen et al., 2022) to help with cases where a quick diagnosis is needed in hours.

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Have we made you curious? Read more about AION and how it works in our latest white paper, 'Reducing complexity in variant interpretation through AI'. This white paper also covers our latest validation study on data from the Genomics England 100.000 Genomes Project. Read it here.

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