Evidence map›Paper›PMID 27589269›Full record

ArticlePloS one2016

Genomic and Metabolomic Profile Associated to Clustering of Cardio-Metabolic Risk Factors.

Vannina G Marrachelli, Pilar Rentero, María L Mansego, Jose Manuel Morales, Inma Galan, Mercedes Pardo-Tendero, Fernando Martinez, Juan Carlos Martin-Escudero, Laisa Briongos, Felipe Javier Chaves and 2 more

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Article
  7. The Future of "Omics" in Hypertension.The Canadian journal of cardiology · 2017
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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

12 authors.

Vannina G MarrachelliMetabolomic and Molecular Image Lab, Health Research Institute, INCLIVA, Valencia, Spain.
Pilar RenteroGenotyping and Genetic Diagnosis Unit, Health Research Institute, INCLIVA, Valencia, Spain.
María L MansegoDepartment of Nutrition, Food Science and Physiology, University of Navarra, Pamplona, Spain.
Jose Manuel MoralesMetabolomic and Molecular Image Lab, Health Research Institute, INCLIVA, Valencia, Spain.
Inma GalanGenotyping and Genetic Diagnosis Unit, Health Research Institute, INCLIVA, Valencia, Spain.
Mercedes Pardo-TenderoMetabolomic and Molecular Image Lab, Health Research Institute, INCLIVA, Valencia, Spain.
Fernando MartinezINCLIVA Research Institute, University of Valencia, Valencia, Spain.
Juan Carlos Martin-EscuderoInternal Medicine, Hospital Rio Hortega, Valladolid, Spain.
Laisa BriongosINCLIVA Research Institute, University of Valencia, Valencia, Spain.
Felipe Javier ChavesGenotyping and Genetic Diagnosis Unit, Health Research Institute, INCLIVA, Valencia, Spain.
Josep RedonINCLIVA Research Institute, University of Valencia, Valencia, Spain.
Daniel MonleonMetabolomic and Molecular Image Lab, Health Research Institute, INCLIVA, Valencia, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo identify metabolomic and genomic markers associated with the presence of clustering of cardiometabolic risk factors (CMRFs) from a general population. METHODS AND

findingsOne thousand five hundred and two subjects, Caucasian, > 18 years, representative of the general population, were included. Blood pressure measurement, anthropometric parameters and metabolic markers were measured. Subjects were grouped according the number of CMRFs (Group 1: <2; Group 2: 2; Group 3: 3 or more CMRFs). Using SNPlex, 1251 SNPs potentially associated to clustering of three or more CMRFs were analyzed. Serum metabolomic profile was assessed by 1H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men) with high genotyping call rate were analysed. A differential metabolomic profile, which included products from mitochondrial metabolism, extra mitochondrial metabolism, branched amino acids and fatty acid signals were observed among the three groups. The comparison of metabolomic patterns between subjects of Groups 1 to 3 for each of the genotypes associated to those subjects with three or more CMRFs revealed two SNPs, the rs174577_AA of FADS2 gene and the rs3803_TT of GATA2 transcription factor gene, with minimal or no statistically significant differences. Subjects with and without three or more CMRFs who shared the same genotype and metabolomic profile differed in the pattern of CMRFS cluster. Subjects of Group 3 and the AA genotype of the rs174577 had a lower prevalence of hypertension compared to the CC and CT genotype. In contrast, subjects of Group 3 and the TT genotype of the rs3803 polymorphism had a lower prevalence of T2DM, although they were predominantly males and had higher values of plasma creatinine.

conclusionsThe results of the present study add information to the metabolomics profile and to the potential impact of genetic factors on the variants of clustering of cardiometabolic risk factors.

Indexed as

Genetic Predisposition to DiseaseGenotypeAdultAgedBlood PressureCardiovascular DiseasesGenetic MarkersGenomicsHumansMaleMetabolic DiseasesMetabolomicsMiddle AgedPolymorphism, Single NucleotideRisk FactorsGenetic Markers

Identifiers

PMID27589269
PMCPMC5010244

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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.