Details
| Original language | English |
|---|---|
| Article number | 1065907 |
| Journal | Frontiers in genetics |
| Volume | 14 |
| Publication status | Published - 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.
Keywords
- autoinflammatory diseases, FMF, genetic diagnostics, inborn errors of immunity (IEI), whole exome sequencing (WES)
ASJC Scopus subject areas
- Biochemistry, Genetics and Molecular Biology(all)
- Molecular Medicine
- Biochemistry, Genetics and Molecular Biology(all)
- Genetics
- Medicine(all)
- Genetics(clinical)
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In: Frontiers in genetics, Vol. 14, 1065907, 27.01.2023.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
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.
KW - autoinflammatory diseases
KW - FMF
KW - genetic diagnostics
KW - inborn errors of immunity (IEI)
KW - whole exome sequencing (WES)
UR - http://www.scopus.com/inward/record.url?scp=85147762701&partnerID=8YFLogxK
U2 - 10.3389/fgene.2023.1065907
DO - 10.3389/fgene.2023.1065907
M3 - Article
AN - SCOPUS:85147762701
VL - 14
JO - Frontiers in genetics
JF - Frontiers in genetics
SN - 1664-8021
M1 - 1065907
ER -