2024
Mitochondrial heteroplasmy improves risk prediction for myeloid neoplasms
Hong Y, Pasca S, Shi W, Puiu D, Lake N, Lek M, Ru M, Grove M, Prizment A, Joshu C, Platz E, Guallar E, Arking D, Gondek L. Mitochondrial heteroplasmy improves risk prediction for myeloid neoplasms. Nature Communications 2024, 15: 10133. PMID: 39578475, PMCID: PMC11584845, DOI: 10.1038/s41467-024-54443-3.Peer-Reviewed Original ResearchConceptsClonal hematopoiesis of indeterminate potentialClonal hematopoiesisVariant allele fractionHeteroplasmic variantsIndeterminate potentialMyeloid neoplasmsHeteroplasmyMultiple mutationsAllele fractionMutationsHigh-risk groupPathogenic risk factorsMarkersRisk score modelDeleteriousnessSpliceosomeHematologic malignanciesRisk stratificationNeoplasm developmentNeoplasmsNeoplasm incidenceRisk factorsVariantsUpregulation vs. loss of function of NTRK2 in 44 affected individuals leads to two distinct neurodevelopmental disorders
Berger E, Jauss R, Ranells J, Zonic E, von Wintzingerode L, Wilson A, Wagner J, Tuttle A, Thomas-Wilson A, Schulte B, Rabin R, Pappas J, Odgis J, Muthaffar O, Mendez-Fadol A, Lynch M, Levy J, Lehalle D, Lake N, Krey I, Kozenko M, Knierim E, Jouret G, Jobanputra V, Isidor B, Hunt D, Hsieh T, Holtz A, Haack T, Gold N, Dunstheimer D, Donge M, Deb W, De La Rosa Poueriet K, Danyel M, Christodoulou J, Chopra S, Callewaert B, Busche A, Brick L, Bigay B, Arlt M, Anikar S, Almohammal M, Almanza D, Alhashem A, Bertoli-Avella A, Sticht H, Jamra R. Upregulation vs. loss of function of NTRK2 in 44 affected individuals leads to two distinct neurodevelopmental disorders. Genetics In Medicine 2024, 101326. PMID: 39540377, DOI: 10.1016/j.gim.2024.101326.Peer-Reviewed Original ResearchDevelopmental delayHeterozygous pathogenic variantsTherapy-refractory epilepsyAffected individualsPhenotype of developmental delayDevelopmental delay/intellectual disabilityGlobal developmental delayRecurrent variant c.Associated with global developmental delayCholesterol-binding motifsTrkB activationVariant c.Pathogenic variantsMuscular hypotoniaFeeding difficultiesSevere phenotypeLoss of functionBinding motifVisual impairmentTransmembrane domainTruncating variantsNeurodevelopmental disordersNTRK2CohortVariantsMitochondrial Heteroplasmy Is a Novel Predictor of Chronic Lymphocytic Leukemia Risk
Pasca S, Hong Y, Shi W, Puiu D, Lake N, Lek M, Guallar E, Arking D, Gondek L. Mitochondrial Heteroplasmy Is a Novel Predictor of Chronic Lymphocytic Leukemia Risk. Blood 2024, 144: 4054-4054. DOI: 10.1182/blood-2024-210250.Peer-Reviewed Original ResearchMitochondrial heteroplasmyClonal hematopoiesis of indeterminate potentialMtDNA heteroplasmyWhole-exome sequencing dataSomatic mutationsPresence of somatic mutationsExome sequencing dataCancer-associated genesClonal hematopoiesisClonal expansionVariant allele frequencyAssociated with myeloid malignanciesMtDNA variantsMitochondrial DNAPresence of mutationsSequence dataUK Biobank (UKBBiologically significant roleDeleterious mutationsHeteroplasmyChronic lymphocytic leukemia riskAllele frequenciesOncogenic transformationMitochondrial functionMyeloid genesQuantifying constraint in the human mitochondrial genome
Lake N, Ma K, Liu W, Battle S, Laricchia K, Tiao G, Puiu D, Ng K, Cohen J, Compton A, Cowie S, Christodoulou J, Thorburn D, Zhao H, Arking D, Sunyaev S, Lek M. Quantifying constraint in the human mitochondrial genome. Nature 2024, 635: 390-397. PMID: 39415008, DOI: 10.1038/s41586-024-08048-x.Peer-Reviewed Original ResearchMitochondrial genomeDeleterious variationMtDNA mutator modelHuman mitochondrial genomeGenome Aggregation DatabaseMtDNA variationMtDNA variantsMitochondrial DNANoncoding regionsMitochondrial proteinsRRNA geneGenetic variationMtDNAThree-dimensional structureMutation modelPathogenic variationDisease relevanceAggregation DatabaseGenomeLarge-scale population datasetRRNAConstrained sitesGenesTRNAPopulation datasetsSaturation mutagenesis-reinforced functional assays for disease-related genes
Ma K, Huang S, Ng K, Lake N, Joseph S, Xu J, Lek A, Ge L, Woodman K, Koczwara K, Cohen J, Ho V, O'Connor C, Brindley M, Campbell K, Lek M. Saturation mutagenesis-reinforced functional assays for disease-related genes. Cell 2024, 187: 6707-6724.e22. PMID: 39326416, PMCID: PMC11568926, DOI: 10.1016/j.cell.2024.08.047.Peer-Reviewed Original ResearchDisease-related genesDisease-causing genetic variantsGenome-wide resolutionMutation scanning methodsSingle-nucleotide variantsDeep mutational scanning methodFunctional assaysDisease genesComputational predictorsSaturation mutagenesisHuman geneticsGenetic variantsGenesVariantsSmurfAssayMutagenesisLARGE1GeneticsDisease severityThe Australian Genomics Mitochondrial Flagship: A National Program Delivering Mitochondrial Diagnoses.
Rius R, Compton A, Baker N, Balasubramaniam S, Best S, Bhattacharya K, Boggs K, Boughtwood T, Braithwaite J, Bratkovic D, Bray A, Brion M, Burke J, Casauria S, Chong B, Coman D, Cowie S, Cowley M, de Silva M, Delatycki M, Edwards S, Ellaway C, Fahey M, Finlay K, Fletcher J, Frajman L, Frazier A, Gayevskiy V, Ghaoui R, Goel H, Goranitis I, Haas M, Hock D, Howting D, Jackson M, Kava M, Kemp M, King-Smith S, Lake N, Lamont P, Lee J, Long J, MacShane M, Madelli E, Martin E, Marum J, Mattiske T, McGill J, Metke A, Murray S, Panetta J, Phillips L, Quinn M, Ryan M, Schenscher S, Simons C, Smith N, Stroud D, Tchan M, Tom M, Wallis M, Ware T, Welch A, Wools C, Wu Y, Christodoulou J, Thorburn D. The Australian Genomics Mitochondrial Flagship: A National Program Delivering Mitochondrial Diagnoses. Genetics In Medicine 2024, 101271. PMID: 39305161, DOI: 10.1016/j.gim.2024.101271.Peer-Reviewed Original ResearchGenome sequencePhenocopy genesMitochondrial diseaseMtDNA sequencesMtDNA deletionsMD geneMtDNAChildhood-onset diseaseDiagnostic journeyDiagnostic yieldMolecular diagnosisGenesNational studySequenceGene etiologySuspected MDDiagnostic pathwayIncrease diagnostic yieldPediatric-onsetOnset diseaseAdult onsetAdult patientsChildrenSkeletal muscleScores
2023
P154 The generation of a GNE myopathy patient-derived biobank enables the study of disease-relevant cellular phenotypes across multiple pathogenic variants
Koczwara K, Lake N, Huang S, DeSimone A, Pajusalu S, Branford K, Hallak D, Woodman K, Xu J, Lek A, Best H, Habib A, Avelar J, Martin V, Mozaffar T, Shieh P, Weisleder N, Lek M. P154 The generation of a GNE myopathy patient-derived biobank enables the study of disease-relevant cellular phenotypes across multiple pathogenic variants. Neuromuscular Disorders 2023, 33: s138. DOI: 10.1016/j.nmd.2023.07.286.Peer-Reviewed Original ResearchPathogenic mutationsCRISPR/Cas9 knockoutDisease-relevant cell typesSialic acid biosynthesis pathwayCellular disease modelsMyogenic cell lineCell linesGNE myopathy patientsPatient-derived cell linesGNE activityWhole-genome sequencingGNE proteinPathogenic variantsBiosynthesis pathwayDisease-relevant cellular phenotypesCellular functionsMyogenic lineageCellular phenotypesRNA sequencingBifunctional enzymeGenome sequencingMultiple pathogenic variantsReduced enzymatic activitySkeletal muscle atrophyMyopathy patientsDeleterious heteroplasmic mitochondrial mutations are associated with an increased risk of overall and cancer-specific mortality
Hong Y, Battle S, Shi W, Puiu D, Pillalamarri V, Xie J, Pankratz N, Lake N, Lek M, Rotter J, Rich S, Kooperberg C, Reiner A, Auer P, Heard-Costa N, Liu C, Lai M, Murabito J, Levy D, Grove M, Alonso A, Gibbs R, Dugan-Perez S, Gondek L, Guallar E, Arking D. Deleterious heteroplasmic mitochondrial mutations are associated with an increased risk of overall and cancer-specific mortality. Nature Communications 2023, 14: 6113. PMID: 37777527, PMCID: PMC10542802, DOI: 10.1038/s41467-023-41785-7.Peer-Reviewed Original ResearchConceptsSingle nucleotide variantsOwn circular genomeState of heteroplasmyAging-related diseasesNuclear genomeMitochondrial genomeCircular genomeMtDNA single nucleotide variantsMitochondrial DNASomatic cellsMitochondrial mutationsMtDNA heteroplasmyGenomeNucleotide variantsHeteroplasmyDNA moleculesFunctional roleMitochondriaUK BiobankCertain cancersVariantsDNAMutationsCopiesCellsMulti-omics identifies large mitoribosomal subunit instability caused by pathogenic MRPL39 variants as a cause of pediatric onset mitochondrial disease
Amarasekera S, Hock D, Lake N, Calvo S, Grønborg S, Krzesinski E, Amor D, Fahey M, Simons C, Wibrand F, Mootha V, Lek M, Lunke S, Stark Z, Østergaard E, Christodoulou J, Thorburn D, Stroud D, Compton A. Multi-omics identifies large mitoribosomal subunit instability caused by pathogenic MRPL39 variants as a cause of pediatric onset mitochondrial disease. Human Molecular Genetics 2023, 32: 2441-2454. PMID: 37133451, PMCID: PMC10360397, DOI: 10.1093/hmg/ddad069.Peer-Reviewed Original ResearchConceptsQuantitative proteomicsMitochondrial oxidative phosphorylation systemProtein complex assemblySmall mitoribosomal subunitExome sequencingOxidative phosphorylation systemMitochondrial deoxyribonucleic acidMitochondrial ribosomesMitoribosomal subunitDeoxyribonucleic acidGene-disease associationsLarge subunitOXPHOS disordersSmall subunitComplex assemblyPhosphorylation systemProteomic dataComplex abundanceFunctional validationDisease genesGenome sequencingMitochondrial diseaseCryptic exonGene matchingProtein signaturesEstimating the Prevalence of LAMA2 Congenital Muscular Dystrophy using Population Genetic Databases
Lake N, Phua J, Liu W, Moors T, Axon S, Lek M. Estimating the Prevalence of LAMA2 Congenital Muscular Dystrophy using Population Genetic Databases. Journal Of Neuromuscular Diseases 2023, 10: 381-387. PMID: 37005889, DOI: 10.3233/jnd-221552.Peer-Reviewed Original Research
2022
Neuromuscular disorders: finding the missing genetic diagnoses
Koczwara KE, Lake NJ, DeSimone AM, Lek M. Neuromuscular disorders: finding the missing genetic diagnoses. Trends In Genetics 2022, 38: 956-971. PMID: 35908999, DOI: 10.1016/j.tig.2022.07.001.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsHigh-throughput functional screeningDiscovery of hundredsGenetic diagnosisNMD genesNext-generation sequencingFunctional screeningSequencing technologiesPathogenic variantsNeuromuscular disordersGroup of diseasesGenesSequencingFuture approachesLarge numberRecent advancementsDiscoveryVariantsYieldMitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNA
Lake NJ, Zhou L, Xu J, Lek M. MitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNA. Bioinformatics 2022, 38: 2967-2969. PMID: 35561159, DOI: 10.1093/bioinformatics/btac216.Peer-Reviewed Original ResearchConceptsRibosomal RNA secondary structuresHuman mitochondrial RNAMitochondrial transfer RNAsPost-transcriptional modificationsHuman mitochondrial DNADisease-associated variantsRNA secondary structureEffects of variantsMtDNA mapMitochondrial RNAMtDNA variationMitochondrial DNATransfer RNAAnalysis of variantsRNA structureSecondary structureVariant annotationLarge deletionsSupplementary dataVariant interpretationRNADNAVariantsGenesNew toolCenters for Mendelian Genomics: A decade of facilitating gene discovery
Baxter SM, Posey JE, Lake NJ, Sobreira N, Chong JX, Buyske S, Blue EE, Chadwick LH, Coban-Akdemir ZH, Doheny KF, Davis CP, Lek M, Wellington C, Jhangiani SN, Gerstein M, Gibbs RA, Lifton RP, MacArthur DG, Matise TC, Lupski JR, Valle D, Bamshad MJ, Hamosh A, Mane S, Nickerson DA, Consortium C, Adams M, Aguet F, Akay G, Anderson P, Antonescu C, Arachchi H, Atik M, Austin-Tse C, Babb L, Bacus T, Bahrambeigi V, Balasubramanian S, Bayram Y, Beaudet A, Beck C, Belmont J, Below J, Bilguvar K, Boehm C, Boerwinkle E, Boone P, Bowne S, Brand H, Buckingham K, Byrne A, Calame D, Campbell I, Cao X, Carvalho C, Chander V, Chang J, Chao K, Chinn I, Clarke D, Collins R, Cummings B, Dardas Z, Dawood M, Delano K, DiTroia S, Doddapaneni H, Du H, Du R, Duan R, Eldomery M, Eng C, England E, Evangelista E, Everett S, Fatih J, Felsenfeld A, Francioli L, Frazar C, Fu J, Gamarra E, Gambin T, Gan W, Gandhi M, Ganesh V, Garimella K, Gauthier L, Giroux D, Gonzaga-Jauregui C, Goodrich J, Gordon W, Griffith S, Grochowski C, Gu S, Gudmundsson S, Hall S, Hansen A, Harel T, Harmanci A, Herman I, Hetrick K, Hijazi H, Horike-Pyne M, Hsu E, Hu J, Huang Y, Hurless J, Jahl S, Jarvik G, Jiang Y, Johanson E, Jolly A, Karaca E, Khayat M, Knight J, Kolar J, Kumar S, Lalani S, Laricchia K, Larkin K, Leal S, Lemire G, Lewis R, Li H, Ling H, Lipson R, Liu P, Lovgren A, López-Giráldez F, MacMillan M, Mangilog B, Mano S, Marafi D, Marosy B, Marshall J, Martin R, Marvin C, Mawhinney M, McGee S, McGoldrick D, Mehaffey M, Mekonnen B, Meng X, Mitani T, Miyake C, Mohr D, Morris S, Mullen T, Murdock D, Murugan M, Muzny D, Myers B, Neira J, Nguyen K, Nielsen P, Nudelman N, O’Heir E, O’Leary M, Ongaco C, Orange J, Osei-Owusu I, Paine I, Pais L, Paschall J, Patterson K, Pehlivan D, Pelle B, Penney S, Chavez J, Pierce-Hoffman E, Poli C, Punetha J, Radhakrishnan A, Richardson M, Rodrigues E, Roote G, Rosenfeld J, Ryke E, Sabo A, Sanchez A, Schrauwen I, Scott D, Sedlazeck F, Serrano J, Shaw C, Shelford T, Shively K, Singer-Berk M, Smith J, Snow H, Snyder G, Solomonson M, Son R, Song X, Stankiewicz P, Stephan T, Sutton V, Sveden A, Sánchez D, Tackett M, Talkowski M, Threlkeld M, Tiao G, Udler M, Vail L, Valivullah Z, Valkanas E, VanNoy G, Wang Q, Wang G, Wang L, Wangler M, Watts N, Weisburd B, Weiss J, Wheeler M, White J, Williamson C, Wilson M, Wiszniewski W, Withers M, Witmer D, Witzgall L, Wohler E, Wojcik M, Wong I, Wood J, Wu N, Xing J, Yang Y, Yi Q, Yuan B, Zeiger J, Zhang C, Zhang P, Zhang Y, Zhang X, Zhang Y, Zhang S, Zoghbi H, van den Veyver I, Rehm H, O’Donnell-Luria A. Centers for Mendelian Genomics: A decade of facilitating gene discovery. Genetics In Medicine 2022, 24: 784-797. PMID: 35148959, PMCID: PMC9119004, DOI: 10.1016/j.gim.2021.12.005.Peer-Reviewed Original ResearchConceptsGene discoveryMendelian GenomicsUnderstanding of genesGene-phenotype relationshipsGenome variationWorldwide data sharingCandidate genesMendelian phenotypesGenomic researchGenome sequencingMatchmaker ExchangeGenomicsGenesSequencingBiomedical researchMajor roleDiscoveryExomePhenotypeRoleGenotypesCommunityMitochondrial DNA variation across 56,434 individuals in gnomAD
Laricchia KM, Lake NJ, Watts NA, Shand M, Haessly A, Gauthier L, Benjamin D, Banks E, Soto J, Garimella K, Emery J, Consortium G, Rehm HL, MacArthur DG, Tiao G, Lek M, Mootha VK, Calvo SE. Mitochondrial DNA variation across 56,434 individuals in gnomAD. Genome Research 2022, 32: gr.276013.121. PMID: 35074858, PMCID: PMC8896463, DOI: 10.1101/gr.276013.121.Peer-Reviewed Original ResearchConceptsMtDNA variantsMitochondrial DNA variationPathogenic mtDNA variantsWhole genome sequencesUnique mtDNA variantsGenome Aggregation DatabasePopulation allele frequenciesAllele frequenciesMtDNA copy numberMitochondrial genomeNuclear sequencesVariant callsDNA variationIndividuals of EuropeanMtDNA genomeAncestral populationsMtDNA moleculesGenomic databasesHeteroplasmic variantsNuclear DNAHomoplasmic variantsMitochondrial originFalse positive variant callsMtDNA copiesMitochondrial haplogroups
2020
Fatal Perinatal Mitochondrial Cardiac Failure Caused by Recurrent De Novo Duplications in the ATAD3 Locus
Frazier A, Compton A, Kishita Y, Hock D, Welch A, Amarasekera S, Rius R, Formosa L, Imai-Okazaki A, Francis D, Wang M, Lake N, Tregoning S, Jabbari J, Lucattini A, Nitta K, Ohtake A, Murayama K, Amor D, McGillivray G, Wong F, van der Knaap M, Vermeulen R, Wiltshire E, Fletcher J, Lewis B, Baynam G, Ellaway C, Balasubramaniam S, Bhattacharya K, Freckmann M, Arbuckle S, Rodriguez M, Taft R, Sadedin S, Cowley M, Minoche A, Calvo S, Mootha V, Ryan M, Okazaki Y, Stroud D, Simons C, Christodoulou J, Thorburn D. Fatal Perinatal Mitochondrial Cardiac Failure Caused by Recurrent De Novo Duplications in the ATAD3 Locus. Med 2020, 2: 49-73.e10. PMID: 33575671, PMCID: PMC7875323, DOI: 10.1016/j.medj.2020.06.004.Peer-Reviewed Original ResearchConceptsMitochondrial diseasePediatric mitochondrial diseaseMitochondrial oxidative phosphorylation complexes IOxidative phosphorylation complexes IDominant-negative mannerStudy of RNADNA sequencing techniquesSegmental duplicationsGenomic strategiesQuantitative proteomicsWhole genomeGenomic investigationsGene locusRepetitive regionsSequencing techniquesGenomeComplex IRecessive deletionsLociWhole exomeDuplicationMonogenic diseasesDe novo duplicationExome sequencingPontocerebellar hypoplasia
2019
Estimating prevalence for limb-girdle muscular dystrophy based on public sequencing databases
Liu W, Pajusalu S, Lake NJ, Zhou G, Ioannidis N, Mittal P, Johnson NE, Weihl CC, Williams BA, Albrecht DE, Rufibach LE, Lek M. Estimating prevalence for limb-girdle muscular dystrophy based on public sequencing databases. Genetics In Medicine 2019, 21: 2512-2520. PMID: 31105274, DOI: 10.1038/s41436-019-0544-8.Peer-Reviewed Original ResearchConceptsMuscular dystrophyLimb-girdle muscular dystrophyClinical trialsGene-level mechanismsLower incidencePossible underdiagnosisGeneral populationEpidemiological studiesEpidemiology dataPrevalence estimatesGenetic subtypesMuscle diseaseLGMD subtypesDisease prevalencePrevalenceRecessive diseaseSubtypesPublic sequencing databasesDiseaseTrialsLGMDDystrophyHeterogeneous categorySequencing databasesA patient with homozygous nonsense variants in two Leigh syndrome disease genes: Distinguishing a dual diagnosis from a hypomorphic protein‐truncating variant
Lake N, Formosa L, Stroud D, Ryan M, Calvo S, Mootha V, Morar B, Procopis P, Christodoulou J, Compton A, Thorburn D. A patient with homozygous nonsense variants in two Leigh syndrome disease genes: Distinguishing a dual diagnosis from a hypomorphic protein‐truncating variant. Human Mutation 2019, 40: 893-898. PMID: 30981218, PMCID: PMC6661004, DOI: 10.1002/humu.23753.Peer-Reviewed Original ResearchConceptsProtein-truncating variantsCI assemblyC-terminusLeigh syndromeMutant proteinsKnockout cellsDisease genesUncharacterized variantsHypomorphic effectPathogenic variantsLeigh-like syndromeMitochondrial diseaseWhole-exome sequencingGenomic criteriaFunctional studiesAmino acidsGenesTIMMDC1Homozygous nonsense variantPatient's clinical phenotypeClinical phenotypeExome sequencingNonsense variantMedical GeneticsDual diagnosisLeigh syndrome caused by mutations in MTFMT is associated with a better prognosis
Hayhurst H, de Coo I, Piekutowska‐Abramczuk D, Alston C, Sharma S, Thompson K, Rius R, He L, Hopton S, Ploski R, Ciara E, Lake N, Compton A, Delatycki M, Verrips A, Bonnen P, Jones S, Morris A, Shakespeare D, Christodoulou J, Wesol‐Kucharska D, Rokicki D, Smeets H, Pronicka E, Thorburn D, Gorman G, McFarland R, Taylor R, Ng Y. Leigh syndrome caused by mutations in MTFMT is associated with a better prognosis. Annals Of Clinical And Translational Neurology 2019, 6: 515-524. PMID: 30911575, PMCID: PMC6414492, DOI: 10.1002/acn3.725.Peer-Reviewed Original ResearchConceptsPathogenic variantsLeigh syndromeSubcortical white matter abnormalitiesNew casesFrequent initial manifestationLast clinical reviewRetrospective cohort studyBasal ganglia changesWhite matter abnormalitiesRespiratory chain deficiencyBi-allelic pathogenic variantsMitochondrial methionyl-tRNA formyltransferaseMolecular genetic findingsMilder clinical phenotypeInitial manifestationBrainstem lesionsCohort studyMedian ageBetter prognosisChain deficiencyMotor symptomsClinical reviewDisease progressionMultiple respiratory chain deficiencyMuscle biopsy
2018
Severe Leukoencephalopathy with Clinical Recovery Caused by Recessive BOLA3 Mutations
Stutterd C, Lake N, Peters H, Lockhart P, Taft R, van der Knaap M, Vanderver A, Thorburn D, Simons C, Leventer R. Severe Leukoencephalopathy with Clinical Recovery Caused by Recessive BOLA3 Mutations. JIMD Reports 2018, 43: 63-70. PMID: 29654549, PMCID: PMC6323033, DOI: 10.1007/8904_2018_100.Peer-Reviewed Original ResearchComplete clinical recoveryClinical recoveryClinical courseMRI abnormalitiesWhite matterTrio whole-genome sequencingBilateral T2 hyperintensitiesWhole-genome sequencingPatient's clinical courseDeep white matterFrontal white matterCompound heterozygous variantsRespiratory chain enzyme activitiesNovel disease-causing variantsCultured patient fibroblastsPatient fibroblastsMitochondrial respiratory chain enzyme activitiesAcute hemiplegiaT2 hyperintensityMultisystem diseaseSevere leukoencephalopathyDisease onsetGenetic leukoencephalopathiesNeurological regressionLactate levels
2017
Biallelic Mutations in MRPS34 Lead to Instability of the Small Mitoribosomal Subunit and Leigh Syndrome
Lake N, Webb B, Stroud D, Richman T, Ruzzenente B, Compton A, Mountford H, Pulman J, Zangarelli C, Rio M, Boddaert N, Assouline Z, Sherpa M, Schadt E, Houten S, Byrnes J, McCormick E, Zolkipli-Cunningham Z, Haude K, Zhang Z, Retterer K, Bai R, Calvo S, Mootha V, Christodoulou J, Rötig A, Filipovska A, Cristian I, Falk M, Metodiev M, Thorburn D. Biallelic Mutations in MRPS34 Lead to Instability of the Small Mitoribosomal Subunit and Leigh Syndrome. American Journal Of Human Genetics 2017, 101: 239-254. PMID: 28777931, PMCID: PMC5544391, DOI: 10.1016/j.ajhg.2017.07.005.Peer-Reviewed Original ResearchConceptsSmall mitoribosomal subunitMitoribosomal subunitHuman oxidative phosphorylation (OXPHOS) systemMitochondrial protein translationOxidative phosphorylation systemMitochondrial translation defectQuantitative proteomic analysisSpecific cellular pathwaysLeigh syndromeLentiviral-mediated expressionMitoribosomal proteinsMitochondrial ribosomesOXPHOS subunitsMitochondrial translationOXPHOS defectsProtein translationMitochondrial DNATranslation defectsUnrelated familiesProteomic analysisPhosphorylation systemQuantitative proteomicsCellular pathwaysProtein subunitsSubunit proteins