Evidence map›Paper›PMID 30636949›Full record

ReviewHereditas2019

Natural selection and local adaptation of blood pressure regulation and their perspectives on precision medicine in hypertension.

Boon-Peng Hoh, Thuhairah Abdul Rahman, Khalid Yusoff

Open access · goldAbstract readReview
In one paragraph

Review in Hereditas, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 25% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
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  4. Review
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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

3 authors at 3 institutions in 2 countries.

Boon-Peng Hoh1Faculty of Medicine and Health Sciences, UCSI University, Cheras, 56000 Kuala Lumpur, Malaysia.ORCID 0000-0001-9249-4965
Thuhairah Abdul Rahman3Clinical Pathology Diagnostic Centre Research Laboratory, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, 47000 Sungai Buloh, Selangor Malaysia.
Khalid Yusoff1Faculty of Medicine and Health Sciences, UCSI University, Cheras, 56000 Kuala Lumpur, Malaysia.
Hospital Sungai Buloh · MYShanghai Institutes for Biological Sciences · CNUCSI University · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prevalence of hypertension (HTN) varies substantially across different populations. HTN is not only common - affecting at least one third of the world's adult population - but is also the most important driver for cardiovascular diseases. Yet up to a third of hypertensive patients are resistant to therapy, contributed by secondary hypertension but more commonly the hitherto inability to precisely predict response to specific antihypertensive agents. Population and individual genomics information could be useful in guiding the selection and predicting the response to treatment - an approach known as precision medicine. However this cannot be achieved without the knowledge of genetic variations that influence blood pressure (BP). A number of evolutionary factors including population demographics and forces of natural selection may be involved. This article explores some ideas on how natural selection influences BP regulation in ethnically and geographically diverse populations that could lead to them being susceptible to HTN. We explore how such evolutionary factors could impact the implementation of precision medicine in HTN. Finally, in order to ensure the success of precision medicine in HTN, we call for more initiatives to understand the genetic architecture within and between diverse populations with ancestry from different parts of the world, and to precisely classify the intermediate phenotypes of HTN.

Indexed as

Blood PressurePrecision MedicineAntihypertensive AgentsBiological EvolutionGenetics, PopulationHumansHypertensionPhenotypeSelection, GeneticAntihypertensive AgentsHypertensionNatural selectionPrecision medicine

Identifiers

PMID30636949
PMCPMC6323824
OpenAlexW2909114121

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.