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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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Interactive Web-Based Resource for Annotation of Genetic Variants Causing Hereditary Angioedema (HADA): Database

Alejandro Mendoza-Alvarez¹, Adrián Muñoz-Barrera², Luis Alberto Rubio-Rodríguez²

¹Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain.

Journal of Medical Internet Research

|October 9, 2020

Summary

Hereditary angioedema (HAE) diagnosis is often delayed due to misdiagnosis. The Hereditary Angioedema Database Annotation (HADA) tool rapidly detects functional genetic variants, improving HAE diagnosis and treatment.

Keywords:

genetic cause hereditary angioedema knowledge database precision medicine variant interpretation

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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

Area of Science:

Genetics
Medical Informatics
Rare Diseases

Background:

Hereditary angioedema (HAE) is a rare genetic disorder linked to C1 esterase inhibitor issues and bradykinin excess.
HAE is frequently misdiagnosed as histaminergic angioedema, and genetic screening is not standard practice.
Diagnostic delays and inaccuracies are common in HAE management.

Purpose of the Study:

To develop a genetic annotation tool, Hereditary Angioedema Database Annotation (HADA), for HAE diagnosis.
To align with precision medicine and next-generation sequencing in HAE management.
To facilitate clinical diagnosis and adapt it to current genetic testing paradigms.

Main Methods:

HADA utilizes a database of known functional variants.
Variants are pre-assessed for pathogenicity and ranked per ACMG guidelines.
A user-friendly web interface and command-line tools are provided.

Main Results:

HADA offers a freely accessible, versatile web interface for genetic data entry.
The tool can be integrated into automated, stand-alone annotation systems.
HADA enables rapid detection of functional variants across HAE types.

Conclusions:

HADA facilitates rapid detection of functional variants for various HAE types.
The tool integrates crucial information to shorten the diagnostic odyssey.
HADA aims to improve the timeliness and accuracy of HAE diagnosis and treatment.