Evidence map›Paper›PMID 28302556›Full record

ReviewGlobal heart2017

Examining How Our Shared Evolutionary History Shapes Future Disease Outcomes.

Fasil Tekola-Ayele, Emmanuel Peprah

Open access · hybridAbstract readReview
In one paragraph

Review in Global heart, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 33% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. An Emerging Syndemic of Smoking and Cardiopulmonary Diseases in People Living with HIV in Africa.International journal of environmental research and public health · 2021
    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 at 1 institution in 1 country.

Fasil Tekola-AyeleEpidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA. Electronic address: ayeleft@mail.nih.gov.
Emmanuel PeprahCenter for Translation Research and Implementation Science, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
National Institutes of Health · US

Funding

Intramural NIH HHS Z99 HD999999
6 · The paper itself

Abstract

Cardiometabolic diseases are major contributors to mortality and morbidity, and their burden displays global and regional disparities. Gene-environment interactions contribute to the pathogenesis of cardiometabolic diseases. Population differences in genetic structure, ancient environmental pressures that shape the human genome, and early life environmental adversities (e.g., in utero conditions) all contribute to observed disparities in global cardiometabolic diseases. The genetic and sociocultural diversity of global populations presents opportunities for discovering genomic loci that influence cardiometabolic diseases as illustrated by a few genetic, epigenetic, and population-genetic discoveries leading to notable understanding of disease mechanisms. However, African, Latin American and Hispanic, and indigenous peoples represent <4% of all genome-wide association study samples analyzed to date. Using examples of recent studies in African populations, we discuss the crucial importance of conducting genomic studies in ancestrally diverse populations to understand disease mechanisms and to prepare fertile ground for future delivery of precise health care to all individuals.

Indexed as

Cardiovascular DiseasesEthnicityGenetic Predisposition to DiseaseMetabolic DiseasesPolymorphism, Single NucleotideGenome-Wide Association StudyGenomicsGlobal HealthHumansModels, Genetic

Identifiers

PMID28302556
PMCPMC5583013
OpenAlexW2752809526

What OpenQuestion holds

Textmetadata
LicenceTDM
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.