Evaluating the quality of Marfan genotype-phenotype correlations in existing FBN1 databases

Kristian Groth; Yskert Von Kodolitsch; Kerstin Kutsche; Mette Gaustadnes; Kasper Thorsen; Niels H Andersen; Claus H Gravholt

doi:10.1038/gim.2016.181

Evaluating the quality of Marfan genotype-phenotype correlations in existing FBN1 databases

Kristian Groth, Yskert Von Kodolitsch, Kerstin Kutsche, Mette Gaustadnes, Kasper Thorsen, Niels H Andersen, Claus H Gravholt

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

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Abstract

Background:Genetic FBN1 testing is pivotal for confirming the clinical diagnosis of Marfan syndrome. In an effort to evaluate variant causality, FBN1 databases are often used. We evaluated the current databases regarding FBN1 variants and validated associated phenotype records with a new Marfan syndrome geno-phenotyping tool called the Marfan score.Methods and results:We evaluated four databases (UMD-FBN1, ClinVar, the Human Gene Mutation Database (HGMD), and Uniprot) containing 2,250 FBN1 variants supported by 4,904 records presented in 307 references. The Marfan score calculated for phenotype data from the records quantified variant associations with Marfan syndrome phenotype. We calculated a Marfan score for 1,283 variants, of which we confirmed the database diagnosis of Marfan syndrome in 77.1%. This represented only 35.8% of the total registered variants; 18.5-33.3% (UMD-FBN1 versus HGMD) of variants associated with Marfan syndrome in the databases could not be confirmed by the recorded phenotype.Conclusion:FBN1 databases can be imprecise and incomplete. Data should be used with caution when evaluating FBN1 variants. At present, the UMD-FBN1 database seems to be the biggest and best curated; therefore, it is the most comprehensive database. However, the need for better genotype-phenotype curated databases is evident, and we hereby present such a database.Genet Med advance online publication 01 December 2016.

Original language	English
Journal	Genetics in Medicine
Volume	19
Issue	7
Pages (from-to)	772-777
Number of pages	6
ISSN	1098-3600
DOIs	https://doi.org/10.1038/gim.2016.181
Publication status	Published - 1 Jul 2017

Keywords

database-management systems
early diagnosis
heart disease
musculoskeletal diseases

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10.1038/gim.2016.181

Cite this

@article{0372420746d6442e8ef33ea5533dcaa0,

title = "Evaluating the quality of Marfan genotype-phenotype correlations in existing FBN1 databases",

abstract = "Background:Genetic FBN1 testing is pivotal for confirming the clinical diagnosis of Marfan syndrome. In an effort to evaluate variant causality, FBN1 databases are often used. We evaluated the current databases regarding FBN1 variants and validated associated phenotype records with a new Marfan syndrome geno-phenotyping tool called the Marfan score.Methods and results:We evaluated four databases (UMD-FBN1, ClinVar, the Human Gene Mutation Database (HGMD), and Uniprot) containing 2,250 FBN1 variants supported by 4,904 records presented in 307 references. The Marfan score calculated for phenotype data from the records quantified variant associations with Marfan syndrome phenotype. We calculated a Marfan score for 1,283 variants, of which we confirmed the database diagnosis of Marfan syndrome in 77.1%. This represented only 35.8% of the total registered variants; 18.5-33.3% (UMD-FBN1 versus HGMD) of variants associated with Marfan syndrome in the databases could not be confirmed by the recorded phenotype.Conclusion:FBN1 databases can be imprecise and incomplete. Data should be used with caution when evaluating FBN1 variants. At present, the UMD-FBN1 database seems to be the biggest and best curated; therefore, it is the most comprehensive database. However, the need for better genotype-phenotype curated databases is evident, and we hereby present such a database.Genet Med advance online publication 01 December 2016.",

keywords = "database-management systems, early diagnosis, heart disease, musculoskeletal diseases",

author = "Kristian Groth and {Von Kodolitsch}, Yskert and Kerstin Kutsche and Mette Gaustadnes and Kasper Thorsen and Andersen, {Niels H} and Gravholt, {Claus H}",

year = "2017",

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Evaluating the quality of Marfan genotype-phenotype correlations in existing FBN1 databases. / Groth, Kristian; Von Kodolitsch, Yskert; Kutsche, Kerstin et al.
In: Genetics in Medicine, Vol. 19, No. 7, 01.07.2017, p. 772-777.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

TY - JOUR

T1 - Evaluating the quality of Marfan genotype-phenotype correlations in existing FBN1 databases

AU - Groth, Kristian

AU - Von Kodolitsch, Yskert

AU - Kutsche, Kerstin

AU - Gaustadnes, Mette

AU - Thorsen, Kasper

AU - Andersen, Niels H

AU - Gravholt, Claus H

PY - 2017/7/1

Y1 - 2017/7/1

N2 - Background:Genetic FBN1 testing is pivotal for confirming the clinical diagnosis of Marfan syndrome. In an effort to evaluate variant causality, FBN1 databases are often used. We evaluated the current databases regarding FBN1 variants and validated associated phenotype records with a new Marfan syndrome geno-phenotyping tool called the Marfan score.Methods and results:We evaluated four databases (UMD-FBN1, ClinVar, the Human Gene Mutation Database (HGMD), and Uniprot) containing 2,250 FBN1 variants supported by 4,904 records presented in 307 references. The Marfan score calculated for phenotype data from the records quantified variant associations with Marfan syndrome phenotype. We calculated a Marfan score for 1,283 variants, of which we confirmed the database diagnosis of Marfan syndrome in 77.1%. This represented only 35.8% of the total registered variants; 18.5-33.3% (UMD-FBN1 versus HGMD) of variants associated with Marfan syndrome in the databases could not be confirmed by the recorded phenotype.Conclusion:FBN1 databases can be imprecise and incomplete. Data should be used with caution when evaluating FBN1 variants. At present, the UMD-FBN1 database seems to be the biggest and best curated; therefore, it is the most comprehensive database. However, the need for better genotype-phenotype curated databases is evident, and we hereby present such a database.Genet Med advance online publication 01 December 2016.

AB - Background:Genetic FBN1 testing is pivotal for confirming the clinical diagnosis of Marfan syndrome. In an effort to evaluate variant causality, FBN1 databases are often used. We evaluated the current databases regarding FBN1 variants and validated associated phenotype records with a new Marfan syndrome geno-phenotyping tool called the Marfan score.Methods and results:We evaluated four databases (UMD-FBN1, ClinVar, the Human Gene Mutation Database (HGMD), and Uniprot) containing 2,250 FBN1 variants supported by 4,904 records presented in 307 references. The Marfan score calculated for phenotype data from the records quantified variant associations with Marfan syndrome phenotype. We calculated a Marfan score for 1,283 variants, of which we confirmed the database diagnosis of Marfan syndrome in 77.1%. This represented only 35.8% of the total registered variants; 18.5-33.3% (UMD-FBN1 versus HGMD) of variants associated with Marfan syndrome in the databases could not be confirmed by the recorded phenotype.Conclusion:FBN1 databases can be imprecise and incomplete. Data should be used with caution when evaluating FBN1 variants. At present, the UMD-FBN1 database seems to be the biggest and best curated; therefore, it is the most comprehensive database. However, the need for better genotype-phenotype curated databases is evident, and we hereby present such a database.Genet Med advance online publication 01 December 2016.

KW - database-management systems

KW - early diagnosis

KW - heart disease

KW - musculoskeletal diseases

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DO - 10.1038/gim.2016.181

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SN - 1098-3600

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SP - 772

EP - 777

JO - Genetics in Medicine

JF - Genetics in Medicine

IS - 7

ER -

Evaluating the quality of Marfan genotype-phenotype correlations in existing FBN1 databases

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