Targeted NGS based hereditary autoinflammatory disorder screening in routine diagnostics, two year experience in the Netherlands

Elferink, Martin; Zon, P van; Frenkel, Joost; Harts, W; Simon, Anna; Royen-Kerkhof, A van; Swart, Joost F.; Amstel, H-K Ploos van; Gijn, Mariëlle van

doi:10.1186/1546-0096-13-s1-p51

Cited by 4 publications

(2 citation statements)

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“…Still over half of all patients presenting with AID do not undergo genetic diagnostics (Elferink et al, 2015;Papa et al, 2020). Initiating genetic testing in AID usually depends on the treating physician's evaluation, experience and general understanding of genetics.…”

Section: Introductionmentioning

confidence: 99%

Systematic genetic analysis of pediatric patients with autoinflammatory diseases

Poker

Hardenberg²,

Hofmann³

et al. 2023

Front. Genet.

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Monogenic autoinflammatory diseases (AID) encompass a growing group of inborn errors of the innate immune system causing unprovoked or exaggerated systemic inflammation. Diagnosis of monogenic AID requires an accurate description of the patients’ phenotype, and the identification of highly penetrant genetic variants in single genes is pivotal. We performed whole exome sequencing (WES) of 125 pediatric patients with suspected monogenic AID in a routine genetic diagnostic setting. Datasets were analyzed in a step-wise approach to identify the most feasible diagnostic strategy. First, we analyzed a virtual gene panel including 13 genes associated with known AID and, if no genetic diagnosis was established, we then analyzed a virtual panel including 542 genes published by the International Union of Immunological Societies associated including all known inborn error of immunity (IEI). Subsequently, WES data was analyzed without pre-filtering for known AID/IEI genes. Analyzing 13 genes yielded a definite diagnosis in 16.0% (n = 20). The diagnostic yield was increased by analyzing 542 genes to 20.8% (n = 26). Importantly, expanding the analysis to WES data did not increase the diagnostic yield in our cohort, neither in single WES analysis, nor in trio-WES analysis. The study highlights that the cost- and time-saving analysis of virtual gene panels is sufficient to rapidly confirm the differential diagnosis in pediatric patients with AID. WES data or trio-WES data analysis as a first-tier diagnostic analysis in patients with suspected monogenic AID is of limited benefit.

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Section: Introductionmentioning

confidence: 99%

Systematic genetic analysis of pediatric patients with autoinflammatory diseases

Poker

Hardenberg²,

Hofmann³

et al. 2023

Front. Genet.

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show abstract

“…Still over half of all patients presenting with AID do not undergo genetic diagnostics [8,9]. Initiating genetic testing in AID usually depends on the treating physician's evaluation, experience and general understanding of genetics.…”

Section: Introductionmentioning

confidence: 99%

Genetics in inborn errors of immunity: pediatric autoinflammatory phenotypes and the underlying genetic causes in 125 families

Poker¹,

Hardenberg

Hofmann³

et al. 2022

Preprint

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Monogenic autoinflammatory diseases (AID) encompass a growing group of inborn errors in the innate immune system causing unprovoked or exaggerated systemic inflammation. Diagnosis of monogenic AID requires an accurate description of the patients´ phenotype and the identification of highly penetrant genetic variants in single genes is pivotal. In a routine genetic diagnostic setting, we performed whole exome sequencing (WES) of 125 pediatric patients with suspected monogenic AID. Datasets were analyzed in a step-wise approach to identify the most feasible diagnostic strategy: First, we analyzed a virtual gene panel including 13 genes associated with known AID and, if no genetic diagnosis could be established, followed by the analysis of a virtual panel including 420 genes published by the International Union of Immunological Societies associated with all known inborn error of immunity (IEI). Subsequently WES data were analyzed without pre-filtering for known AID/IEI genes. Analyzing 13 genes yielded a definite diagnosis in 16.0% (n=20). The diagnostic yield was increased by analyzing 420 genes to 21.8% (n=26). Importantly, expanding the analysis to WES data did not increase the diagnostic yield in our cohort, neither in single WES analysis nor in trio-WES analysis. The study highlights that analyzing virtual gene panels based on WES that include the majority of known genes causing AID or differential diagnosis can rapidly confirm the diagnosis for a large number of pediatric patients. WES data or trio-WES data analysis as a first-tier diagnostic analysis in patients with suspected monogenic AID is of minor use.

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Genetic testing in autoinflammatory diseases – past, current and future perspectives

Goueff

Smits

Delaunoy

et al. 2022

European Journal of Internal Medicine

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Targeted NGS based hereditary autoinflammatory disorder screening in routine diagnostics, two year experience in the Netherlands

Cited by 4 publications

References 0 publications

Systematic genetic analysis of pediatric patients with autoinflammatory diseases

Systematic genetic analysis of pediatric patients with autoinflammatory diseases

Genetics in inborn errors of immunity: pediatric autoinflammatory phenotypes and the underlying genetic causes in 125 families

Genetic testing in autoinflammatory diseases – past, current and future perspectives

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