Evidence map›Paper›PMID 38862855›Full record

ArticleNature genetics2024

Body mass index stratification optimizes polygenic prediction of type 2 diabetes in cross-biobank analyses.

Takafumi Ojima, Shinichi Namba, Ken Suzuki, Kenichi Yamamoto, Kyuto Sonehara, Akira Narita, Tohoku Medical Megabank Project Study Group, Biobank Japan Project, Yoichiro Kamatani, Gen Tamiya and 4 more

Abstract read
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In one paragraph

Article in Nature genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–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

17 citing papers in PubMed.

  1. Article
  2. Observational
  3. Genetic basis of Asian diabetes.Journal of diabetes investigation · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
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  16. Review
  17. Article
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

14 authors.

Takafumi OjimaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0003-1197-0574
Shinichi NambaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0002-7486-3146
Ken SuzukiDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0003-1065-3593
Kenichi YamamotoDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0001-9594-7050
Kyuto SoneharaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0002-4536-1761
Akira NaritaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.ORCID http://orcid.org/0000-0002-9076-0710
Tohoku Medical Megabank Project Study Group
Biobank Japan Project
Yoichiro KamataniLaboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.ORCID http://orcid.org/0000-0001-8748-5597
Gen TamiyaGraduate School of Medicine, Tohoku University, Sendai, Japan.
Masayuki YamamotoGraduate School of Medicine, Tohoku University, Sendai, Japan.ORCID http://orcid.org/0000-0002-9073-9436
Toshimasa YamauchiDepartment of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Takashi KadowakiToranomon Hospital, Tokyo, Japan.ORCID http://orcid.org/0000-0002-5428-3582
Yukinori OkadaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan. yuki-okada@m.u-tokyo.ac.jp.ORCID http://orcid.org/0000-0002-0311-8472

Funding

Japan Agency for Medical Research and Development (AMED) JP223fa627010, JP233fa627011, JP23zf0127008Japan Agency for Medical Research and Development (AMED) JP22ek0410075, JP23km0405211, JP23km0405217Japan Agency for Medical Research and Development (AMED) JP23ek0109594, JP23ek0410113, JP223fa627002Japan Society for the Promotion of Science London (JSPS London) 22H00476MEXT | Japan Science and Technology Agency (JST) JPMJMS2021, JPMJMS2024, JPMJSP2138
6 · The paper itself

Abstract

Type 2 diabetes (T2D) shows heterogeneous body mass index (BMI) sensitivity. Here, we performed stratification based on BMI to optimize predictions for BMI-related diseases. We obtained BMI-stratified datasets using data from more than 195,000 individuals (n

Indexed as

Body Mass IndexDiabetes Mellitus, Type 2Genetic Predisposition to DiseaseGenome-Wide Association StudyMultifactorial InheritanceAgedBiological Specimen BanksFemaleHumansJapanMaleMiddle AgedPolymorphism, Single NucleotideRisk FactorsUnited Kingdom

Identifiers

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Registered trials

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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.