Evidence map›Paper›PMID 30667137›Full record

ReviewDiabetes, obesity & metabolism2019

Obesity genetics and cardiometabolic health: Potential for risk prediction.

Dharambir K Sanghera, Cynthia Bejar, Sonali Sharma, Rajeev Gupta, Piers R Blackett

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Diabetes, obesity & metabolism, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

5 authors.

Dharambir K SangheraDepartment of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma.ORCID 0000-0001-7203-8655
Cynthia BejarDepartment of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma.
Sonali SharmaDepartment of Biochemistry, College of Medical Sciences, Rajasthan University of Health Sciences, Jaipur, India.
Rajeev GuptaAcademic Research Development Unit, College of Medical Sciences, Rajasthan University of Health Sciences, Jaipur, India.
Piers R BlackettDepartment of Pediatrics, College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma.

Funding

Genome-wide Association Scan to Identify Risk Genes for Type 2 Diabetes in AsianR01DK082766 · NIDDK · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI SANGHERA, DHARAMBIR K. · 2009 to 2011
$2.3M
NIDDK NIH HHS R01 DK082766
6 · The paper itself

Abstract

The increasing burden of obesity worldwide and its effect on cardiovascular disease (CVD) risk is an opportunity for evaluation of preventive approaches. Both obesity and CVD have a genetic background and polymorphisms within genes which enhance expression of variant proteins that influence CVD in obesity. Genome-based prediction may therefore be a feasible strategy, but the identification of genetically driven risk factors for CVD manifesting as clinically recognized phenotypes is a major challenge. Clusters of such risk factors include hyperglycaemia, hypertension, ectopic liver fat, and inflammation. All involve multiple genetic pathways having complex interactions with variable environmental influences. The factors that make significant contributions to CVD risk include altered carbohydrate homeostasis, ectopic deposition of fat in muscle and liver, and inflammation, with contributions from the gut microbiome. A futuristic model depends on harnessing the predictive power of plausible genetic variants, phenotype reversibility, and effective therapeutic choices based on genotype-phenotype interactions. Inverting disease phenotypes into ideal cardiovascular health metrics could improve genetic and epigenetic assessment, and form the basis of a future model for risk detection and early intervention.

Indexed as

Cardiovascular DiseasesGenetics, PopulationHumansHypertensionInflammationObesityPhenotypePolymorphism, GeneticPrognosisRisk Factorscardiometabolic diseasegene environment interactionsgeneticsmicrobiomeobesity

Identifiers

PMID30667137
PMCPMC6530772

What OpenQuestion holds

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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.