Vis enkel innførsel

dc.contributor.authorAlthari, Sara
dc.contributor.authorNajmi, Laeya Abdoli
dc.contributor.authorBennett, Amanda J.
dc.contributor.authorAukrust, Ingvild
dc.contributor.authorRundle, Jana K.
dc.contributor.authorColclough, Kevin
dc.contributor.authorMolnes, Janne
dc.contributor.authorKaci, Alba
dc.contributor.authorNawaz, Sameena
dc.contributor.authorvan der Lugt, Timme
dc.contributor.authorHassanali, Neelam
dc.contributor.authorMahajan, Anubha
dc.contributor.authorMolven, Anders
dc.contributor.authorEllard, Sian
dc.contributor.authorMcCarthy, Mark I.
dc.contributor.authorBjørkhaug, Lise
dc.contributor.authorNjølstad, Pål Rasmus
dc.contributor.authorGloyn, Anna L.
dc.PublishedAmerican Journal of Human Genetics. 2020, 107 (4), 670-682.
dc.description.abstractExome sequencing in diabetes presents a diagnostic challenge because depending on frequency, functional impact, and genomic and environmental contexts, HNF1A variants can cause maturity-onset diabetes of the young (MODY), increase type 2 diabetes risk, or be benign. A correct diagnosis matters as it informs on treatment, progression, and family risk. We describe a multi-dimensional functional dataset of 73 HNF1A missense variants identified in exomes of 12,940 individuals. Our aim was to develop an analytical framework for stratifying variants along the HNF1A phenotypic continuum to facilitate diagnostic interpretation. HNF1A variant function was determined by four different molecular assays. Structure of the multi-dimensional dataset was explored using principal component analysis, k-means, and hierarchical clustering. Weights for tissue-specific isoform expression and functional domain were integrated. Functionally annotated variant subgroups were used to re-evaluate genetic diagnoses in national MODY diagnostic registries. HNF1A variants demonstrated a range of behaviors across the assays. The structure of the multi-parametric data was shaped primarily by transactivation. Using unsupervised learning methods, we obtained high-resolution functional clusters of the variants that separated known causal MODY variants from benign and type 2 diabetes risk variants and led to reclassification of 4% and 9% of HNF1A variants identified in the UK and Norway MODY diagnostic registries, respectively. Our proof-of-principle analyses facilitated informative stratification of HNF1A variants along the continuum, allowing improved evaluation of clinical significance, management, and precision medicine in diabetes clinics. Transcriptional activity appears a superior readout supporting pursuit of transactivation-centric experimental designs for high-throughput functional screens.en_US
dc.publisherCell Pressen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleUnsupervised clustering of missense variants in HNF1A using multidimensional functional data aids clinical interpretationen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.rights.holderCopyright © 2020 The Authors.en_US
dc.source.journalAmerican Journal of Human Geneticsen_US
dc.identifier.citationAmerican Journal of Human Genetics. 2020, 107 (4), 670–682.en_US

Tilhørende fil(er)


Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel

Navngivelse 4.0 Internasjonal
Med mindre annet er angitt, så er denne innførselen lisensiert som Navngivelse 4.0 Internasjonal