Systematic analysis and prediction of genes associated with monogenic disorders on human chromosome X

Elsa Leitão, Christopher Schröder, Ilaria Parenti, Carine Dalle, Agnès Rastetter, Theresa Kühnel, Alma Kuechler, Sabine Kaya, Bénédicte Gérard, Elise Schaefer, Caroline Nava, Nathalie Drouot, Camille Engel, Juliette Piard, Bénédicte Duban-Bedu, Laurent Villard, Alexander P. A. Stegmann, Els K. Vanhoutte, Job A. J. Verdonschot, Frank J. Kaiser, Frédéric Tran Mau-Them, Marcello Scala, Pasquale Striano, Suzanna G. M. Frints, Emanuela Argilli, Elliott H. Sherr, Fikret Elder, Julien Buratti, Boris Keren, Cyril Mignot, Delphine Héron, Jean-Louis Mandel, Jozef Gecz, Vera M. Kalscheuer, Bernhard Horsthemke, Amélie Piton and Christel Depienne ()
Additional contact information
Elsa Leitão: University Hospital Essen, University Duisburg-Essen
Christopher Schröder: University Hospital Essen, University Duisburg-Essen
Ilaria Parenti: University Hospital Essen, University Duisburg-Essen
Carine Dalle: Institut du Cerveau et de la Moelle épinière (ICM), Sorbonne Université, UMR S 1127, Inserm U1127, CNRS UMR 7225
Agnès Rastetter: Institut du Cerveau et de la Moelle épinière (ICM), Sorbonne Université, UMR S 1127, Inserm U1127, CNRS UMR 7225
Theresa Kühnel: University Hospital Essen, University Duisburg-Essen
Alma Kuechler: University Hospital Essen, University Duisburg-Essen
Sabine Kaya: University Hospital Essen, University Duisburg-Essen
Bénédicte Gérard: Unité de Génétique Moléculaire, IGMA, Hôpitaux Universitaire de Strasbourg
Elise Schaefer: Service de Génétique Médicale, IGMA, Hôpitaux Universitaires de Strasbourg
Caroline Nava: Institut du Cerveau et de la Moelle épinière (ICM), Sorbonne Université, UMR S 1127, Inserm U1127, CNRS UMR 7225
Nathalie Drouot: Institut de Génétique et de Biologie Moléculaire et Cellulaire
Camille Engel: Institut de Génétique et de Biologie Moléculaire et Cellulaire
Juliette Piard: Centre de Génétique Humaine, CHU Besançon
Bénédicte Duban-Bedu: Centre de génétique chromosomique, Hôpital Saint-Vincent de Paul
Laurent Villard: Aix-Marseille University, INSERM, MMG, UMR-S 1251, Faculté de médecine
Alexander P. A. Stegmann: Radboud University Medical Center
Els K. Vanhoutte: Maastricht University Medical Center+
Job A. J. Verdonschot: Maastricht University Medical Center+
Frank J. Kaiser: University Hospital Essen, University Duisburg-Essen
Frédéric Tran Mau-Them: Université de Bourgogne-Franche-Comté
Marcello Scala: University of Genoa
Pasquale Striano: University of Genoa
Suzanna G. M. Frints: Maastricht University Medical Center+
Emanuela Argilli: University of California, San Francisco
Elliott H. Sherr: University of California, San Francisco
Fikret Elder: Groupe Hospitalier Pitié-Salpêtrière, APHP-Sorbonne Université
Julien Buratti: Groupe Hospitalier Pitié-Salpêtrière, APHP-Sorbonne Université
Boris Keren: Groupe Hospitalier Pitié-Salpêtrière, APHP-Sorbonne Université
Cyril Mignot: Institut du Cerveau et de la Moelle épinière (ICM), Sorbonne Université, UMR S 1127, Inserm U1127, CNRS UMR 7225
Delphine Héron: Groupe Hospitalier Pitié-Salpêtrière and Hôpital Trousseau
Jean-Louis Mandel: Unité de Génétique Moléculaire, IGMA, Hôpitaux Universitaire de Strasbourg
Jozef Gecz: School of Medicine, The University of Adelaide
Vera M. Kalscheuer: Max Planck Institute for Molecular Genetics
Bernhard Horsthemke: University Hospital Essen, University Duisburg-Essen
Amélie Piton: Unité de Génétique Moléculaire, IGMA, Hôpitaux Universitaire de Strasbourg
Christel Depienne: University Hospital Essen, University Duisburg-Essen

Nature Communications, 2022, vol. 13, issue 1, 1-17

Abstract: Abstract Disease gene discovery on chromosome (chr) X is challenging owing to its unique modes of inheritance. We undertook a systematic analysis of human chrX genes. We observe a higher proportion of disorder-associated genes and an enrichment of genes involved in cognition, language, and seizures on chrX compared to autosomes. We analyze gene constraints, exon and promoter conservation, expression, and paralogues, and report 127 genes sharing one or more attributes with known chrX disorder genes. Using machine learning classifiers trained to distinguish disease-associated from dispensable genes, we classify 247 genes, including 115 of the 127, as having high probability of being disease-associated. We provide evidence of an excess of variants in predicted genes in existing databases. Finally, we report damaging variants in CDK16 and TRPC5 in patients with intellectual disability or autism spectrum disorders. This study predicts large-scale gene-disease associations that could be used for prioritization of X-linked pathogenic variants.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-34264-y

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DOI: 10.1038/s41467-022-34264-y

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