Evidence map›Paper›PMID 31049317›Full record

ReviewPulse (Basel, Switzerland)2019

Genome-Wide Association Studies of Hypertension and Several Other Cardiovascular Diseases.

Yan Wang, Ji-Guang Wang

Abstract readReview
In one paragraph

Review in Pulse (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

  1. Clinical implementation of polygenic risk scores based on GWAS in the management of hypertension among Asian populations.Hypertension research : official journal of the Japanese Society of Hypertension · 2026
    Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Heliyon · 2024
    Article
  10. Article
  11. Article
  12. Genetics of Hypertension: From Monogenic Analysis to GETomics.Journal of cardiovascular development and disease · 2024
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Role of non-coding variants in cardiovascular disease.Journal of cellular and molecular medicine · 2023
    Review
  18. Article
  19. Review
  20. Susceptibility to hypertension based onFrontiers in cardiovascular medicine · 2023
    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

2 authors.

Yan WangShanghai Key Laboratory of Hypertension, The Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Ji-Guang WangShanghai Key Laboratory of Hypertension, The Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have greatly expanded our understanding of the genetic architecture of cardiovascular diseases in the past decade. They have revealed hundreds of suggestive genetic loci that replicate known biological candidate genes and indicate the existence of a previously unsuspected new biology relevant to cardiovascular disorders. These data have been used successfully to create genetic risk scores that may improve risk prediction and the identification of susceptive individuals. Furthermore, these GWAS-identified novel pathways may herald a new era of novel drug development and stratification of patients. In this review, we will briefly summarize the literature on the candidate genes and signals discovered by GWAS on hypertension and coronary artery disease and discuss their implications on clinical medicine.

Indexed as

Coronary artery diseaseGenetic risk scoreGenome-wide association studyHypertension

Identifiers

PMID31049317
PMCPMC6489084

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.