Evidence map›Paper›PMID 38351177›Full record

ArticleCommunications biology2024

Integration of risk factor polygenic risk score with disease polygenic risk score for disease prediction.

Hyein Jung, Hae-Un Jung, Eun Ju Baek, Shin Young Kwon, Ji-One Kang, Ji Eun Lim, Bermseok Oh

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
12.7field-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

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

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

7 authors at 2 institutions in 2 countries.

Hyein JungDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Hae-Un JungDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Eun Ju BaekMendel Inc, Seoul, Republic of Korea.
Shin Young KwonDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
Ji-One KangDepartment of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea.
Ji Eun Lim *Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea. jelim@khu.ac.kr.ORCID 0000-0001-5858-9119
Bermseok Oh *Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea. ohbs@khu.ac.kr.ORCID 0000-0002-4199-0608
Kyung Hee University · KRKyung Hee Cyber University · KR

Funding

National Research Foundation of Korea (NRF) 2019M3E5D3073365National Research Foundation of Korea (NRF) 2021R1I1A1A01049398
6 · The paper itself

Abstract

Polygenic risk score (PRS) is useful for capturing an individual's genetic susceptibility. However, previous studies have not fully exploited the potential of the risk factor PRS (RFPRS) for disease prediction. We explored the potential of integrating disease-related RFPRSs with disease PRS to enhance disease prediction performance. We constructed 112 RFPRSs and analyzed the association of RFPRSs with diseases to identify disease-related RFPRSs in 700 diseases, using the UK Biobank dataset. We uncovered 6157 statistically significant associations between 247 diseases and 109 RFPRSs. We estimated the disease PRSs of 70 diseases that exhibited statistically significant heritability, to generate RFDiseasemetaPRS-a combined PRS integrating RFPRSs and disease PRS-and compare the prediction performance metrics between RFDiseasemetaPRS and disease PRS. RFDiseasemetaPRS showed better performance for Nagelkerke's pseudo-R

Indexed as

Genetic Predisposition to DiseaseGenetic Risk ScoreBenchmarkingHumansOdds RatioRisk Factors

Identifiers

PMID38351177
PMCPMC10864389
OpenAlexW4391799427

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.