Evidence mapPaperPMID 37101203Full record

ArticleGenome biology2023

A comprehensive map of human glucokinase variant activity.

Sarah Gersing, Matteo Cagiada, Marinella Gebbia, Anette P Gjesing, Atina G Coté, Gireesh Seesankar, Roujia Li, Daniel Tabet, Jochen Weile, Amelie Stein and 5 more

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
16.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 54 citations in OpenAlex.

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  12. MaveMD: A functional data resource for genomic medicine.medRxiv : the preprint server for health sciences · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 3 institutions in 3 countries.

Sarah GersingThe Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.
Matteo CagiadaThe Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.
Marinella GebbiaDonnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada.
Anette P GjesingNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Atina G CotéDonnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada.
Gireesh SeesankarDonnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada.
Roujia LiDonnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada.
Daniel TabetDonnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada.
Jochen WeileDonnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada.
Amelie SteinThe Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark.
Anna L GloynDivision of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
Torben HansenNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Frederick P RothDonnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada. fritz.roth@utoronto.ca.
Kresten Lindorff-LarsenThe Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark. lindorff@bio.ku.dk.
Rasmus Hartmann-PetersenThe Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark. rhpetersen@bio.ku.dk.ORCID http://orcid.org/0000-0002-4155-7791
University of Copenhagen · DKUniversity of Toronto · CAStanford University · US

Funding

Technology to understand genetic variant effects in contextRM1HG010461 · NHGRI · UNIVERSITY OF WASHINGTON · 2023 to 2025
$4.7M
Molecular phenotyping of ~100,000 coding variants across Mendelian disease genesUM1HG011989 · DANA-FARBER CANCER INST · 2025 to 2025
$1.8M
NHGRI NIH HHS RM1 HG010461NHGRI NIH HHS UM1 HG011989NIDDK NIH HHS U01 DK085545NIDDK NIH HHS U01 DK105535NIDDK NIH HHS UM1 DK126185Wellcome Trust 200837
6 · The paper itself

Abstract

backgroundGlucokinase (GCK) regulates insulin secretion to maintain appropriate blood glucose levels. Sequence variants can alter GCK activity to cause hyperinsulinemic hypoglycemia or hyperglycemia associated with GCK-maturity-onset diabetes of the young (GCK-MODY), collectively affecting up to 10 million people worldwide. Patients with GCK-MODY are frequently misdiagnosed and treated unnecessarily. Genetic testing can prevent this but is hampered by the challenge of interpreting novel missense variants.

resultHere, we exploit a multiplexed yeast complementation assay to measure both hyper- and hypoactive GCK variation, capturing 97% of all possible missense and nonsense variants. Activity scores correlate with in vitro catalytic efficiency, fasting glucose levels in carriers of GCK variants and with evolutionary conservation. Hypoactive variants are concentrated at buried positions, near the active site, and at a region of known importance for GCK conformational dynamics. Some hyperactive variants shift the conformational equilibrium towards the active state through a relative destabilization of the inactive conformation.

conclusionOur comprehensive assessment of GCK variant activity promises to facilitate variant interpretation and diagnosis, expand our mechanistic understanding of hyperactive variants, and inform development of therapeutics targeting GCK.

Indexed as

Diabetes Mellitus, Type 2GlucokinaseGenetic TestingHumansMutationMutation, MissenseGlucokinaseDeep mutational scanningDiabetesVariants of uncertain significance

Identifiers

PMID37101203
PMCPMC10131484
OpenAlexW4367055489

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.