Evidence mapPaperPMID 34862199Full record

SynthesisDiabetes2022

Recessive Genome-Wide Meta-analysis Illuminates Genetic Architecture of Type 2 Diabetes.

Mark J O'Connor, Philip Schroeder, Alicia Huerta-Chagoya, Paula Cortés-Sánchez, Silvía Bonàs-Guarch, Marta Guindo-Martínez, Joanne B Cole, Varinderpal Kaur, David Torrents, Kumar Veerapen and 10 more

Open access · hybridAbstract readMeta-Analysis
In one paragraph

Synthesis in Diabetes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 10% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. The missing heritability in type 1 diabetes.Diabetes, obesity & metabolism · 2022
    Review
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

20 authors at 6 institutions in 4 countries.

Mark J O'ConnorDepartment of Medicine, Massachusetts General Hospital, Boston, MA.
Philip SchroederDiabetes Unit, Massachusetts General Hospital, Boston, MA.
Alicia Huerta-ChagoyaConsejo Nacional de Ciencia y Tecnología (CONACYT), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.
Paula Cortés-SánchezBarcelona Supercomputing Center (BSC), Barcelona, Spain.
Silvía Bonàs-GuarchBarcelona Supercomputing Center (BSC), Barcelona, Spain.
Marta Guindo-MartínezBarcelona Supercomputing Center (BSC), Barcelona, Spain.
Joanne B ColeCenter for Genomic Medicine, Massachusetts General Hospital, Boston, MA.
Varinderpal KaurDiabetes Unit, Massachusetts General Hospital, Boston, MA.
David TorrentsBarcelona Supercomputing Center (BSC), Barcelona, Spain.
Kumar VeerapenDepartment of Medicine, Harvard Medical School, Boston, MA.
Niels GrarupNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0001-5526-1070
Mitja KurkiDepartment of Medicine, Harvard Medical School, Boston, MA.
Carsten F RundstenNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Oluf PedersenNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Ivan BrandslundDepartment of Clinical Biochemistry, Lillebaelt Hospital, Vejle, Denmark.
Allan LinnebergCenter for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark.
Torben HansenNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0001-8748-3831
Aaron LeongDepartment of Medicine, Massachusetts General Hospital, Boston, MA.ORCID 0000-0002-3248-9547
Jose C FlorezDepartment of Medicine, Massachusetts General Hospital, Boston, MA.
Josep M MercaderDiabetes Unit, Massachusetts General Hospital, Boston, MA.ORCID 0000-0001-8494-3660
Broad Institute · USUniversity of Copenhagen · DKBarcelona Supercomputing Center · ESInstitució Catalana de Recerca i Estudis Avançats · ESInstituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán · MXUniversity of Southern Denmark · DK

Funding

Development of Polygenic Risk Scores for Diabetes and Complications across the Life-Span in Populations of Multiple AncestriesU01HG011723 · BROAD INSTITUTE, INC. · 2025 to 2025
$949k
Mentoring Investigators on the Clinical Translation of Cardiometabolic Genetic DiscoveriesK24HL157960 · MASSACHUSETTS GENERAL HOSPITAL · 2025 to 2025
$125k
Genetically harmonized dietary intake and causal relationships with diabetes-related outcomesK99DK127196 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Joanne Burnette Cole · 2022 to 2022
$88k
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NHGRI NIH HHS U01 HG011723NHLBI NIH HHS K24 HL157960NIDDK NIH HHS K24 DK110550NIDDK NIH HHS K99 DK127196NIDDK NIH HHS T32 DK110919Wellcome TrustWellcome Trust 076113Wellcome Trust WT091310
6 · The paper itself

Abstract

Most genome-wide association studies (GWAS) of complex traits are performed using models with additive allelic effects. Hundreds of loci associated with type 2 diabetes have been identified using this approach. Additive models, however, can miss loci with recessive effects, thereby leaving potentially important genes undiscovered. We conducted the largest GWAS meta-analysis using a recessive model for type 2 diabetes. Our discovery sample included 33,139 case subjects and 279,507 control subjects from 7 European-ancestry cohorts, including the UK Biobank. We identified 51 loci associated with type 2 diabetes, including five variants undetected by prior additive analyses. Two of the five variants had minor allele frequency of <5% and were each associated with more than a doubled risk in homozygous carriers. Using two additional cohorts, FinnGen and a Danish cohort, we replicated three of the variants, including one of the low-frequency variants, rs115018790, which had an odds ratio in homozygous carriers of 2.56 (95% CI 2.05-3.19; P = 1 × 10-16) and a stronger effect in men than in women (for interaction, P = 7 × 10-7). The signal was associated with multiple diabetes-related traits, with homozygous carriers showing a 10% decrease in LDL cholesterol and a 20% increase in triglycerides; colocalization analysis linked this signal to reduced expression of the nearby PELO gene. These results demonstrate that recessive models, when compared with GWAS using the additive approach, can identify novel loci, including large-effect variants with pathophysiological consequences relevant to type 2 diabetes.

Indexed as

Genome-Wide Association StudyAdultCholesterol, LDLDiabetes Mellitus, Type 2EuropeFemaleGene FrequencyGenes, RecessiveGenetic Predisposition to DiseaseHomozygoteHumansMaleMetabolomeMiddle AgedMutationSex FactorsCholesterol, LDLTriglycerides

Identifiers

PMID34862199
PMCPMC8893948
OpenAlexW3215869302

What Socratic holds

Textmetadata
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.