Evidence map›Paper›PMID 36703017›Full record

ArticleNature metabolism2023

A phenome-wide comparative analysis of genetic discordance between obesity and type 2 diabetes.

Daniel E Coral, Juan Fernandez-Tajes, Neli Tsereteli, Hugo Pomares-Millan, Hugo Fitipaldi, Pascal M Mutie, Naeimeh Atabaki-Pasdar, Sebastian Kalamajski, Alaitz Poveda, Tyne W Miller-Fleming and 5 more

Abstract read
In one paragraph

Article in Nature metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

36 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Daniel E CoralGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden. daniel.coral@med.lu.se.ORCID 0000-0002-8809-4544
Juan Fernandez-TajesGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.
Neli TsereteliGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.
Hugo Pomares-MillanGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.ORCID 0000-0001-9245-4576
Hugo FitipaldiGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.ORCID 0000-0001-5352-2134
Pascal M MutieGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.
Naeimeh Atabaki-PasdarGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.ORCID 0000-0001-7229-1888
Sebastian KalamajskiGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.
Alaitz PovedaGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.
Tyne W Miller-FlemingVanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.
Xue ZhongVanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.
Giuseppe N GiordanoGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.ORCID 0000-0002-6719-6680
Ewan R PearsonGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden.ORCID 0000-0001-9237-8585
Nancy J CoxOxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK.
Paul W FranksGenetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Science, Lund University, Skåne University Hospital, Malmö, Sweden. paul.franks@med.lu.se.ORCID 0000-0002-0520-7604

Funding

Wellcome Trust 102820/Z/13/Z
6 · The paper itself

Abstract

Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions and the mechanisms of action are poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant and discordant diabetogenic effects. We annotate and then compare association signals for these profiles across clinical and molecular phenotypic layers. Key differences are identified in a wide range of traits, including cardiovascular mortality, fat distribution, liver metabolism, blood pressure, specific lipid fractions and blood levels of proteins involved in extracellular matrix remodelling. We find marginal differences in abundance of Bacteroidetes and Firmicutes bacteria in the gut. Instrumental analyses reveal prominent causal roles for waist-to-hip ratio, blood pressure and cholesterol content of high-density lipoprotein particles in the development of diabetes in obesity. We prioritize 17 genes from the discordant signature that convey protection against type 2 diabetes in obesity, which may represent logical targets for precision medicine approaches.

Indexed as

Diabetes Mellitus, Type 2CholesterolHumansObesityPhenotypeCholesterol

Identifiers

PMID36703017
PMCPMC9970876

What OpenQuestion 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 OpenQuestion graph.