Identification of Restless Legs Syndrome Genes by Mutational Load Analysis

Objective Restless legs syndrome is a frequent neurological disorder with substantial burden on individual well‐being and public health. Genetic risk loci have been identified, but the causatives genes at these loci are largely unknown, so that functional investigation and clinical translation of mo...

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Published inAnnals of neurology Vol. 87; no. 2; pp. 184 - 193
Main Authors Tilch, Erik, Schormair, Barbara, Zhao, Chen, Salminen, Aaro V., Antic Nikolic, Ana, Holzknecht, Evi, Högl, Birgit, Poewe, Werner, Bachmann, Cornelius G., Paulus, Walter, Trenkwalder, Claudia, Oertel, Wolfgang H., Hornyak, Magdolna, Fietze, Ingo, Berger, Klaus, Lichtner, Peter, Gieger, Christian, Peters, Annette, Müller‐Myhsok, Bertram, Hoischen, Alexander, Winkelmann, Juliane, Oexle, Konrad
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 01.02.2020
Wiley Subscription Services, Inc
Subjects
Algorithms
Case-Control Studies
Chromosome Mapping - statistics & numerical data
Deviation
DNA Mutational Analysis
DNA probes
Female
Gene mapping
Gene sequencing
Genes
Genetic Predisposition to Disease - genetics
Health risks
Humans
Leg
Loci
Male
Mapping
Middle Aged
Neural coding
Neurological diseases
Next-generation sequencing
Public health
Restless legs syndrome
Restless Legs Syndrome - genetics
Sleep deprivation
Well being
Online AccessGet full text

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Abstract Objective Restless legs syndrome is a frequent neurological disorder with substantial burden on individual well‐being and public health. Genetic risk loci have been identified, but the causatives genes at these loci are largely unknown, so that functional investigation and clinical translation of molecular research data are still inhibited. To identify putatively causative genes, we searched for highly significant mutational burden in candidate genes. Methods We analyzed 84 candidate genes in 4,649 patients and 4,982 controls by next generation sequencing using molecular inversion probes that targeted mainly coding regions. The burden of low‐frequency and rare variants was assessed, and in addition, an algorithm (binomial performance deviation analysis) was established to estimate independently the sequence variation in the probe binding regions from the variation in sequencing depth. Results Highly significant results (considering the number of genes in the genome) of the conventional burden test and the binomial performance deviation analysis overlapped significantly. Fourteen genes were highly significant by one method and confirmed with Bonferroni‐corrected significance by the other to show a differential burden of low‐frequency and rare variants in restless legs syndrome. Nine of them (AAGAB, ATP2C1, CNTN4, COL6A6, CRBN, GLO1, NTNG1, STEAP4, VAV3) resided in the vicinity of known restless legs syndrome loci, whereas 5 (BBS7, CADM1, CREB5, NRG3, SUN1) have not previously been associated with restless legs syndrome. Burden test and binomial performance deviation analysis also converged significantly in fine‐mapping potentially causative domains within these genes. Interpretation Differential burden with intragenic low‐frequency variants reveals putatively causative genes in restless legs syndrome. ANN NEUROL 2020;87:184–193
AbstractList ObjectiveRestless legs syndrome is a frequent neurological disorder with substantial burden on individual well‐being and public health. Genetic risk loci have been identified, but the causatives genes at these loci are largely unknown, so that functional investigation and clinical translation of molecular research data are still inhibited. To identify putatively causative genes, we searched for highly significant mutational burden in candidate genes.MethodsWe analyzed 84 candidate genes in 4,649 patients and 4,982 controls by next generation sequencing using molecular inversion probes that targeted mainly coding regions. The burden of low‐frequency and rare variants was assessed, and in addition, an algorithm (binomial performance deviation analysis) was established to estimate independently the sequence variation in the probe binding regions from the variation in sequencing depth.ResultsHighly significant results (considering the number of genes in the genome) of the conventional burden test and the binomial performance deviation analysis overlapped significantly. Fourteen genes were highly significant by one method and confirmed with Bonferroni‐corrected significance by the other to show a differential burden of low‐frequency and rare variants in restless legs syndrome. Nine of them (AAGAB, ATP2C1, CNTN4, COL6A6, CRBN, GLO1, NTNG1, STEAP4, VAV3) resided in the vicinity of known restless legs syndrome loci, whereas 5 (BBS7, CADM1, CREB5, NRG3, SUN1) have not previously been associated with restless legs syndrome. Burden test and binomial performance deviation analysis also converged significantly in fine‐mapping potentially causative domains within these genes.InterpretationDifferential burden with intragenic low‐frequency variants reveals putatively causative genes in restless legs syndrome. ANN NEUROL 2020;87:184–193
Restless legs syndrome is a frequent neurological disorder with substantial burden on individual well-being and public health. Genetic risk loci have been identified, but the causatives genes at these loci are largely unknown, so that functional investigation and clinical translation of molecular research data are still inhibited. To identify putatively causative genes, we searched for highly significant mutational burden in candidate genes. We analyzed 84 candidate genes in 4,649 patients and 4,982 controls by next generation sequencing using molecular inversion probes that targeted mainly coding regions. The burden of low-frequency and rare variants was assessed, and in addition, an algorithm (binomial performance deviation analysis) was established to estimate independently the sequence variation in the probe binding regions from the variation in sequencing depth. Highly significant results (considering the number of genes in the genome) of the conventional burden test and the binomial performance deviation analysis overlapped significantly. Fourteen genes were highly significant by one method and confirmed with Bonferroni-corrected significance by the other to show a differential burden of low-frequency and rare variants in restless legs syndrome. Nine of them (AAGAB, ATP2C1, CNTN4, COL6A6, CRBN, GLO1, NTNG1, STEAP4, VAV3) resided in the vicinity of known restless legs syndrome loci, whereas 5 (BBS7, CADM1, CREB5, NRG3, SUN1) have not previously been associated with restless legs syndrome. Burden test and binomial performance deviation analysis also converged significantly in fine-mapping potentially causative domains within these genes. Differential burden with intragenic low-frequency variants reveals putatively causative genes in restless legs syndrome. ANN NEUROL 2020;87:184-193.
Objective Restless legs syndrome is a frequent neurological disorder with substantial burden on individual well‐being and public health. Genetic risk loci have been identified, but the causatives genes at these loci are largely unknown, so that functional investigation and clinical translation of molecular research data are still inhibited. To identify putatively causative genes, we searched for highly significant mutational burden in candidate genes. Methods We analyzed 84 candidate genes in 4,649 patients and 4,982 controls by next generation sequencing using molecular inversion probes that targeted mainly coding regions. The burden of low‐frequency and rare variants was assessed, and in addition, an algorithm (binomial performance deviation analysis) was established to estimate independently the sequence variation in the probe binding regions from the variation in sequencing depth. Results Highly significant results (considering the number of genes in the genome) of the conventional burden test and the binomial performance deviation analysis overlapped significantly. Fourteen genes were highly significant by one method and confirmed with Bonferroni‐corrected significance by the other to show a differential burden of low‐frequency and rare variants in restless legs syndrome. Nine of them (AAGAB, ATP2C1, CNTN4, COL6A6, CRBN, GLO1, NTNG1, STEAP4, VAV3) resided in the vicinity of known restless legs syndrome loci, whereas 5 (BBS7, CADM1, CREB5, NRG3, SUN1) have not previously been associated with restless legs syndrome. Burden test and binomial performance deviation analysis also converged significantly in fine‐mapping potentially causative domains within these genes. Interpretation Differential burden with intragenic low‐frequency variants reveals putatively causative genes in restless legs syndrome. ANN NEUROL 2020;87:184–193
Restless legs syndrome is a frequent neurological disorder with substantial burden on individual well-being and public health. Genetic risk loci have been identified, but the causatives genes at these loci are largely unknown, so that functional investigation and clinical translation of molecular research data are still inhibited. To identify putatively causative genes, we searched for highly significant mutational burden in candidate genes.OBJECTIVERestless legs syndrome is a frequent neurological disorder with substantial burden on individual well-being and public health. Genetic risk loci have been identified, but the causatives genes at these loci are largely unknown, so that functional investigation and clinical translation of molecular research data are still inhibited. To identify putatively causative genes, we searched for highly significant mutational burden in candidate genes.We analyzed 84 candidate genes in 4,649 patients and 4,982 controls by next generation sequencing using molecular inversion probes that targeted mainly coding regions. The burden of low-frequency and rare variants was assessed, and in addition, an algorithm (binomial performance deviation analysis) was established to estimate independently the sequence variation in the probe binding regions from the variation in sequencing depth.METHODSWe analyzed 84 candidate genes in 4,649 patients and 4,982 controls by next generation sequencing using molecular inversion probes that targeted mainly coding regions. The burden of low-frequency and rare variants was assessed, and in addition, an algorithm (binomial performance deviation analysis) was established to estimate independently the sequence variation in the probe binding regions from the variation in sequencing depth.Highly significant results (considering the number of genes in the genome) of the conventional burden test and the binomial performance deviation analysis overlapped significantly. Fourteen genes were highly significant by one method and confirmed with Bonferroni-corrected significance by the other to show a differential burden of low-frequency and rare variants in restless legs syndrome. Nine of them (AAGAB, ATP2C1, CNTN4, COL6A6, CRBN, GLO1, NTNG1, STEAP4, VAV3) resided in the vicinity of known restless legs syndrome loci, whereas 5 (BBS7, CADM1, CREB5, NRG3, SUN1) have not previously been associated with restless legs syndrome. Burden test and binomial performance deviation analysis also converged significantly in fine-mapping potentially causative domains within these genes.RESULTSHighly significant results (considering the number of genes in the genome) of the conventional burden test and the binomial performance deviation analysis overlapped significantly. Fourteen genes were highly significant by one method and confirmed with Bonferroni-corrected significance by the other to show a differential burden of low-frequency and rare variants in restless legs syndrome. Nine of them (AAGAB, ATP2C1, CNTN4, COL6A6, CRBN, GLO1, NTNG1, STEAP4, VAV3) resided in the vicinity of known restless legs syndrome loci, whereas 5 (BBS7, CADM1, CREB5, NRG3, SUN1) have not previously been associated with restless legs syndrome. Burden test and binomial performance deviation analysis also converged significantly in fine-mapping potentially causative domains within these genes.Differential burden with intragenic low-frequency variants reveals putatively causative genes in restless legs syndrome. ANN NEUROL 2020;87:184-193.INTERPRETATIONDifferential burden with intragenic low-frequency variants reveals putatively causative genes in restless legs syndrome. ANN NEUROL 2020;87:184-193.
Author Tilch, Erik
Oexle, Konrad
Zhao, Chen
Bachmann, Cornelius G.
Fietze, Ingo
Lichtner, Peter
Oertel, Wolfgang H.
Hoischen, Alexander
Schormair, Barbara
Peters, Annette
Hornyak, Magdolna
Berger, Klaus
Müller‐Myhsok, Bertram
Paulus, Walter
Antic Nikolic, Ana
Winkelmann, Juliane
Högl, Birgit
Poewe, Werner
Salminen, Aaro V.
Trenkwalder, Claudia
Holzknecht, Evi
Gieger, Christian
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Copyright 2019 The Authors. published by Wiley Periodicals, Inc. on behalf of American Neurological Association.
2019 The Authors. Annals of Neurology published by Wiley Periodicals, Inc. on behalf of American Neurological Association.
2020 American Neurological Association
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– reference: 31926030 - Ann Neurol. 2020 Feb;87(2):172-174
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Snippet Objective Restless legs syndrome is a frequent neurological disorder with substantial burden on individual well‐being and public health. Genetic risk loci have...
Restless legs syndrome is a frequent neurological disorder with substantial burden on individual well-being and public health. Genetic risk loci have been...
ObjectiveRestless legs syndrome is a frequent neurological disorder with substantial burden on individual well‐being and public health. Genetic risk loci have...
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SubjectTerms Algorithms
Case-Control Studies
Chromosome Mapping - statistics & numerical data
Deviation
DNA Mutational Analysis
DNA probes
Female
Gene mapping
Gene sequencing
Genes
Genetic Predisposition to Disease - genetics
Health risks
Humans
Leg
Loci
Male
Mapping
Middle Aged
Neural coding
Neurological diseases
Next-generation sequencing
Public health
Restless legs syndrome
Restless Legs Syndrome - genetics
Sleep deprivation
Well being
Title Identification of Restless Legs Syndrome Genes by Mutational Load Analysis
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fana.25658
https://www.ncbi.nlm.nih.gov/pubmed/31788832
https://www.proquest.com/docview/2339554213
https://www.proquest.com/docview/2320637936
Volume 87
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