Nicole J. Lake, PhD
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Assistant Professor of Genetics
Biography
Nicole's research career reflects her long-standing interest in understanding how genetic variation contributes to health and disease, and passion for mitochondrial genomics. Nicole completed her Ph.D. in mitochondrial genetics with David Thorburn at the Murdoch Children's Research Institute, where she used computational and experimental methods to discover genetic causes of mitochondrial diseases. Following this, she worked as an analyst in translational and mitochondrial genomics. Nicole then completed her postdoctoral training at Yale University with Monkol Lek, where she built and applied tools to improve the discovery of genetic causes of disease and variant classification, with a focus on the mitochondrial genome. Nicole also holds M.Sc. and B.Sc. degrees in Genetics from the University of Melbourne and University of Edinburgh.
Nicole’s professional experience includes university teaching, clinical genetic testing, media interviews, peer review, science outreach, as well as national, institutional, and departmental committee service and leadership. She established her lab in the Yale School of Medicine in 2024.
Appointments
Genetics
Assistant ProfessorPrimary
Other Departments & Organizations
Education & Training
- Postdoctoral Fellow/Associate
- Yale University (2022)
- PhD
- University of Melbourne (2018)
- MSc
- University of Melbourne, Genetics (2012)
- BSc
- University of Melbourne & University of Edinburgh, Genetics (2010)
Research
Overview
Medical Subject Headings (MeSH)
ORCID
0000-0003-4103-6387- View Lab Website
Lake Lab
Research at a Glance
Yale Co-Authors
Publications Timeline
Research Interests
Francesc Lopez-Giraldez, PhD
Kaya Bilguvar, MD, PhD
Shushu Huang, MD, PhD
DNA, Mitochondrial
Mitochondrial Diseases
Mutation
Genomics
Genome, Mitochondrial
Publications
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 ResearchConceptsPathogenic 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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsSingle 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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsQuantitative 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 ResearchCitationsAltmetric
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 StatementsCitationsAltmetricMeSH Keywords and ConceptsConceptsHigh-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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsRibosomal 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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsGene 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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMtDNA 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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMitochondrial 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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMuscular dystrophyLimb-girdle muscular dystrophyClinical trialsGene-level mechanismsLower incidencePossible underdiagnosisGeneral populationEpidemiological studiesEpidemiology dataPrevalence estimatesGenetic subtypesMuscle diseaseLGMD subtypesDisease prevalencePrevalenceRecessive diseaseSubtypesPublic sequencing databasesDiseaseTrialsLGMDDystrophyHeterogeneous categorySequencing databases
Academic Achievements & Community Involvement
honor Excellence in Mitochondrial Research Award
International AwardMito FoundationDetails09/14/2020Australiahonor CJ Martin Early Career Fellowship
International AwardAustralian National Health and Medical Research Council (NHMRC)Details01/01/2019Australiahonor Qantas Research Scholar
International AwardAmerican Australian AssociationDetails01/01/2019United Stateshonor AMDF Advocacy Award
International AwardAustralian Mitochondrial Disease FoundationDetails08/01/2016Australiahonor New Investigator Award
International AwardHuman Genetics Society of AustralasiaDetails08/01/2016Australia
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