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 factorsVariantsHigh-throughput assays to assess variant effects on disease
Ma K, Gauthier L, Cheung F, Huang S, Lek M. High-throughput assays to assess variant effects on disease. Disease Models & Mechanisms 2024, 17: dmm050573. PMID: 38940340, PMCID: PMC11225591, DOI: 10.1242/dmm.050573.Peer-Reviewed Original ResearchConceptsDeep mutational scanningGenetic variantsRare disease diagnosticsRare genetic variantsDisease mechanismsHigh-throughput assaySequencing effortsInvestigation of variantsMutational scanningModel cell lineVariant effectsMolecular toolsCell linesCell survival rateFunctional assaysDrug resistanceDisease diagnosticsDisease-relevant assaysVariantsClinical case reportBiological mechanismsAssayCase reportClinical reportsSurvival rate
2017
Improving genetic diagnosis in Mendelian disease with transcriptome sequencing
Cummings BB, Marshall JL, Tukiainen T, Lek M, Donkervoort S, Foley AR, Bolduc V, Waddell LB, Sandaradura SA, O’Grady G, Estrella E, Reddy HM, Zhao F, Weisburd B, Karczewski KJ, O’Donnell-Luria A, Birnbaum D, Sarkozy A, Hu Y, Gonorazky H, Claeys K, Joshi H, Bournazos A, Oates EC, Ghaoui R, Davis MR, Laing NG, Topf A, Consortium G, Kang PB, Beggs AH, North KN, Straub V, Dowling JJ, Muntoni F, Clarke NF, Cooper ST, Bönnemann CG, MacArthur DG. Improving genetic diagnosis in Mendelian disease with transcriptome sequencing. Science Translational Medicine 2017, 9 PMID: 28424332, PMCID: PMC5548421, DOI: 10.1126/scitranslmed.aal5209.Peer-Reviewed Original ResearchConceptsTranscriptome sequencingRNA-seqCurrent diagnostic ratePrior genetic analysisTranscript level changesTriple-helical domainDeep intronic regionsWhole-genome sequencingSplice-altering variantsInterpretation of variantsRepeat motifsGenomic analysisHelical domainMendelian disease diagnosisGenetic analysisMendelian diseasesIntronic regionsSkeletal muscle samplesSequencingRare disease diagnosisIntronic mutationOverall diagnosis rateStandard diagnostic approachRare muscle disorderComplementary diagnostic tool
2016
Quantifying prion disease penetrance using large population control cohorts
Minikel EV, Vallabh SM, Lek M, Estrada K, Samocha KE, Sathirapongsasuti JF, McLean CY, Tung JY, Yu LP, Gambetti P, Blevins J, Zhang S, Cohen Y, Chen W, Yamada M, Hamaguchi T, Sanjo N, Mizusawa H, Nakamura Y, Kitamoto T, Collins SJ, Boyd A, Will RG, Knight R, Ponto C, Zerr I, Kraus TF, Eigenbrod S, Giese A, Calero M, de Pedro-Cuesta J, Haïk S, Laplanche JL, Bouaziz-Amar E, Brandel JP, Capellari S, Parchi P, Poleggi A, Ladogana A, O’Donnell-Luria A, Karczewski KJ, Marshall JL, Boehnke M, Laakso M, Mohlke KL, Kähler A, Chambert K, McCarroll S, Sullivan PF, Hultman CM, Purcell SM, Sklar P, van der Lee SJ, Rozemuller A, Jansen C, Hofman A, Kraaij R, van Rooij JG, Ikram MA, Uitterlinden AG, van Duijn CM, Consortium E, Daly MJ, MacArthur DG. Quantifying prion disease penetrance using large population control cohorts. Science Translational Medicine 2016, 8: 322ra9. PMID: 26791950, PMCID: PMC4774245, DOI: 10.1126/scitranslmed.aad5169.Peer-Reviewed Original ResearchConceptsPrion protein genePopulation control cohortPrion disease casesHealthy older individualsPrion protein expressionControl cohortLifetime riskTherapeutic suppressionDisease casesTruncating variantsDisease-causing genotypesOlder individualsBenign variantsDisease prevalenceProtein expressionDisease penetranceDiseaseMissense variantsPrion diseasesControl exomesDisease susceptibilityImpact of variantsGenetic variantsRiskPenetrance
2015
Use of Whole-Exome Sequencing for Diagnosis of Limb-Girdle Muscular Dystrophy: Outcomes and Lessons Learned
Ghaoui R, Cooper ST, Lek M, Jones K, Corbett A, Reddel SW, Needham M, Liang C, Waddell LB, Nicholson G, O’Grady G, Kaur S, Ong R, Davis M, Sue CM, Laing NG, North KN, MacArthur DG, Clarke NF. Use of Whole-Exome Sequencing for Diagnosis of Limb-Girdle Muscular Dystrophy: Outcomes and Lessons Learned. JAMA Neurology 2015, 72: 1424-1432. PMID: 26436962, DOI: 10.1001/jamaneurol.2015.2274.Peer-Reviewed Original ResearchConceptsLGMD-related genesLimb-girdle muscular dystrophyWhole-exome sequencingMyopathy genesBiopsy specimensDiagnostic rateMutations of CHD7Follow-up screeningMuscular dystrophyAccurate clinical examinationLikely pathogenic mutationsMuscle biopsy specimensTubular aggregate myopathyCongenital myasthenic syndromeGenetic diagnosisDiagnostic success rateNeuromuscular clinicMuscle weaknessMyopathic changesClinical examinationHistopathological resultsAncillary investigationsMyasthenic syndromeCommon causeDiagnostic yield