Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes

Neurometabolic disorders are markedly heterogeneous, both clinically and genetically, and are characterized by variable neurological dysfunction accompanied by suggestive neuroimaging or biochemical abnormalities. Despite early specialist input, delays in diagnosis and appropriate treatment initiati...

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Κύριοι συγγραφείς: Reid, E, Papandreou, A, Drury, S, Boustred, C, Yue, W, Wedatilake, Y, Beesley, C, Jacques, T, Anderson, G, Abulhoul, L, Broomfield, A, Cleary, M, Grunewald, S, Varadkar, S, Lench, N, Rahman, S, Gissen, P, Clayton, P, Mills, P
Μορφή: Journal article
Γλώσσα:English
Έκδοση: Oxford University Press 2016
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author Reid, E
Papandreou, A
Drury, S
Boustred, C
Yue, W
Wedatilake, Y
Beesley, C
Jacques, T
Anderson, G
Abulhoul, L
Broomfield, A
Cleary, M
Grunewald, S
Varadkar, S
Lench, N
Rahman, S
Gissen, P
Clayton, P
Mills, P
author_facet Reid, E
Papandreou, A
Drury, S
Boustred, C
Yue, W
Wedatilake, Y
Beesley, C
Jacques, T
Anderson, G
Abulhoul, L
Broomfield, A
Cleary, M
Grunewald, S
Varadkar, S
Lench, N
Rahman, S
Gissen, P
Clayton, P
Mills, P
author_sort Reid, E
collection OXFORD
description Neurometabolic disorders are markedly heterogeneous, both clinically and genetically, and are characterized by variable neurological dysfunction accompanied by suggestive neuroimaging or biochemical abnormalities. Despite early specialist input, delays in diagnosis and appropriate treatment initiation are common. Next-generation sequencing approaches still have limitations but are already enabling earlier and more efficient diagnoses in these patients. We designed a gene panel targeting 614 genes causing inborn errors of metabolism and tested its diagnostic efficacy in a paediatric cohort of 30 undiagnosed patients presenting with variable neurometabolic phenotypes. Genetic defects that could, at least partially, explain observed phenotypes were identified in 53% of cases. Where biochemical abnormalities pointing towards a particular gene defect were present, our panel identified diagnoses in 89% of patients. Phenotypes attributable to defects in more than one gene were seen in 13% of cases. The ability of in silico tools, including structure-guided prediction programmes to characterize novel missense variants were also interrogated. Our study expands the genetic, clinical and biochemical phenotypes of well-characterized (POMGNT1, TPP1) and recently identified disorders (PGAP2, ACSF3, SERAC1, AFG3L2, DPYS). Overall, our panel was accurate and efficient, demonstrating good potential for applying similar approaches to clinically and biochemically diverse neurometabolic disease cohorts.
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spelling oxford-uuid:80f90bbf-0b53-44f7-ae94-07f981fd96482022-03-26T21:27:06ZAdvantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:80f90bbf-0b53-44f7-ae94-07f981fd9648EnglishSymplectic Elements at OxfordOxford University Press2016Reid, EPapandreou, ADrury, SBoustred, CYue, WWedatilake, YBeesley, CJacques, TAnderson, GAbulhoul, LBroomfield, ACleary, MGrunewald, SVaradkar, SLench, NRahman, SGissen, PClayton, PMills, PNeurometabolic disorders are markedly heterogeneous, both clinically and genetically, and are characterized by variable neurological dysfunction accompanied by suggestive neuroimaging or biochemical abnormalities. Despite early specialist input, delays in diagnosis and appropriate treatment initiation are common. Next-generation sequencing approaches still have limitations but are already enabling earlier and more efficient diagnoses in these patients. We designed a gene panel targeting 614 genes causing inborn errors of metabolism and tested its diagnostic efficacy in a paediatric cohort of 30 undiagnosed patients presenting with variable neurometabolic phenotypes. Genetic defects that could, at least partially, explain observed phenotypes were identified in 53% of cases. Where biochemical abnormalities pointing towards a particular gene defect were present, our panel identified diagnoses in 89% of patients. Phenotypes attributable to defects in more than one gene were seen in 13% of cases. The ability of in silico tools, including structure-guided prediction programmes to characterize novel missense variants were also interrogated. Our study expands the genetic, clinical and biochemical phenotypes of well-characterized (POMGNT1, TPP1) and recently identified disorders (PGAP2, ACSF3, SERAC1, AFG3L2, DPYS). Overall, our panel was accurate and efficient, demonstrating good potential for applying similar approaches to clinically and biochemically diverse neurometabolic disease cohorts.
spellingShingle Reid, E
Papandreou, A
Drury, S
Boustred, C
Yue, W
Wedatilake, Y
Beesley, C
Jacques, T
Anderson, G
Abulhoul, L
Broomfield, A
Cleary, M
Grunewald, S
Varadkar, S
Lench, N
Rahman, S
Gissen, P
Clayton, P
Mills, P
Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes
title Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes
title_full Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes
title_fullStr Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes
title_full_unstemmed Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes
title_short Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes
title_sort advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes
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