Systematic genetic analysis of pediatric patients with autoinflammatory diseases

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • Yvonne Poker
  • Sandra von Hardenberg
  • Winfried Hofmann
  • Ming Tang
  • Ulrich Baumann
  • Nicolaus Schwerk
  • Martin Wetzke
  • Viola Lindenthal
  • Bernd Auber
  • Brigitte Schlegelberger
  • Hagen Ott
  • Philipp von Bismarck
  • Dorothee Viemann
  • Frank Dressler
  • Christian Klemann
  • Anke Katharina Bergmann

Organisationseinheiten

Externe Organisationen

  • Medizinische Hochschule Hannover (MHH)
  • Carl von Ossietzky Universität Oldenburg
  • Auf der Bult - Kinder- und Jugendkrankenhaus
  • Christian-Albrechts-Universität zu Kiel (CAU)
  • Julius-Maximilians-Universität Würzburg
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Aufsatznummer1065907
FachzeitschriftFrontiers in genetics
Jahrgang14
PublikationsstatusVeröffentlicht - 27 Jan. 2023

Abstract

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.

ASJC Scopus Sachgebiete

Zitieren

Systematic genetic analysis of pediatric patients with autoinflammatory diseases. / Poker, Yvonne; von Hardenberg, Sandra; Hofmann, Winfried et al.
in: Frontiers in genetics, Jahrgang 14, 1065907, 27.01.2023.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Poker, Y, von Hardenberg, S, Hofmann, W, Tang, M, Baumann, U, Schwerk, N, Wetzke, M, Lindenthal, V, Auber, B, Schlegelberger, B, Ott, H, von Bismarck, P, Viemann, D, Dressler, F, Klemann, C & Bergmann, AK 2023, 'Systematic genetic analysis of pediatric patients with autoinflammatory diseases', Frontiers in genetics, Jg. 14, 1065907. https://doi.org/10.3389/fgene.2023.1065907
Poker, Y., von Hardenberg, S., Hofmann, W., Tang, M., Baumann, U., Schwerk, N., Wetzke, M., Lindenthal, V., Auber, B., Schlegelberger, B., Ott, H., von Bismarck, P., Viemann, D., Dressler, F., Klemann, C., & Bergmann, A. K. (2023). Systematic genetic analysis of pediatric patients with autoinflammatory diseases. Frontiers in genetics, 14, Artikel 1065907. https://doi.org/10.3389/fgene.2023.1065907
Poker Y, von Hardenberg S, Hofmann W, Tang M, Baumann U, Schwerk N et al. Systematic genetic analysis of pediatric patients with autoinflammatory diseases. Frontiers in genetics. 2023 Jan 27;14:1065907. doi: 10.3389/fgene.2023.1065907
Poker, Yvonne ; von Hardenberg, Sandra ; Hofmann, Winfried et al. / Systematic genetic analysis of pediatric patients with autoinflammatory diseases. in: Frontiers in genetics. 2023 ; Jahrgang 14.
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title = "Systematic genetic analysis of pediatric patients with autoinflammatory diseases",
abstract = "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{\textquoteright} 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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T1 - Systematic genetic analysis of pediatric patients with autoinflammatory diseases

AU - Poker, Yvonne

AU - von Hardenberg, Sandra

AU - Hofmann, Winfried

AU - Tang, Ming

AU - Baumann, Ulrich

AU - Schwerk, Nicolaus

AU - Wetzke, Martin

AU - Lindenthal, Viola

AU - Auber, Bernd

AU - Schlegelberger, Brigitte

AU - Ott, Hagen

AU - von Bismarck, Philipp

AU - Viemann, Dorothee

AU - Dressler, Frank

AU - Klemann, Christian

AU - Bergmann, Anke Katharina

N1 - Funding Information: BA, AB, SH, WH, and BS were supported by Cluster of Excellence RESIST (Resolving Infection Sustainability) EXC 2155/1 Deutsche Forschungsgemeinschaft (German Research Foundation).

PY - 2023/1/27

Y1 - 2023/1/27

N2 - 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.

AB - 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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KW - FMF

KW - genetic diagnostics

KW - inborn errors of immunity (IEI)

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JO - Frontiers in genetics

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