Evidence map›Paper›PMID 26002928›Full record

ArticleAmerican journal of hypertension2016

Genetic Risk Score for Essential Hypertension and Risk of Preeclampsia.

Caitlin J Smith, Audrey F Saftlas, Cassandra N Spracklen, Elizabeth W Triche, Andrew Bjonnes, Brendan Keating, Richa Saxena, Patrick J Breheny, Andrew T Dewan, Jennifer G Robinson and 2 more

Open access · greenAbstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of hypertension, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. The Association of Familial Hypertension and Risk of Gestational Hypertension and Preeclampsia.International journal of environmental research and public health · 2021
    Article
  5. Article
  6. Risk assessment of type 2 diabetes in northern China based on the logistic regression model.Technology and health care : official journal of the European Society for Engineering and Medicine · 2021
    Article
  7. Review
  8. Article
  9. Article
  10. 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

12 authors at 6 institutions in 1 country.

Caitlin J SmithDepartment of Epidemiology, College of Public Health, University of Iowa, Iowa City, Iowa, USA;
Audrey F SaftlasDepartment of Epidemiology, College of Public Health, University of Iowa, Iowa City, Iowa, USA;
Cassandra N SpracklenDepartment of Epidemiology, College of Public Health, University of Iowa, Iowa City, Iowa, USA; Department of Genetics, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina, USA;
Elizabeth W TricheDepartment of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island, USA;
Andrew BjonnesCenter for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA;
Brendan KeatingDepartment of Surgery, Penn Transplant Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA;
Richa SaxenaCenter for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA;
Patrick J BrehenyDepartment of Biostatistics, University of Iowa College of Public Health, Iowa City, Iowa, USA;
Andrew T DewanDepartment of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, USA;
Jennifer G RobinsonDepartment of Epidemiology, College of Public Health, University of Iowa, Iowa City, Iowa, USA;
Josephine HohDepartment of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA.
Kelli K RyckmanDepartment of Epidemiology, College of Public Health, University of Iowa, Iowa City, Iowa, USA; kelli-ryckman@uiowa.edu.
University of Iowa · USBrown University · USCenter for Human Genetics · USHarvard University · USUniversity of Pennsylvania · USYale University · US

Funding

Maternal-Fetal HLA Sharing and Risk of PreeclampsiaR01HD032579 · NICHD · UNIVERSITY OF IOWA · PI SAFTLAS, AUDREY FRIEDA · 2001 to 2004
$1.9M
NICHD NIH HHS R01 HD032579NICHD NIH HHS R01 HD32579
6 · The paper itself

Abstract

backgroundPreeclampsia is a hypertensive complication of pregnancy characterized by novel onset of hypertension after 20 weeks gestation, accompanied by proteinuria. Epidemiological evidence suggests that genetic susceptibility exists for preeclampsia; however, whether preeclampsia is the result of underlying genetic risk for essential hypertension has yet to be investigated. Based on the hypertensive state that is characteristic of preeclampsia, we aimed to determine if established genetic risk scores (GRSs) for hypertension and blood pressure are associated with preeclampsia.

methodsSubjects consisted of 162 preeclamptic cases and 108 normotensive pregnant controls, all of Iowa residence. Subjects' DNA was extracted from buccal swab samples and genotyped on the Affymetrix Genome-wide Human SNP Array 6.0 (Affymetrix, Santa Clara, CA). Missing genotypes were imputed using MaCH and Minimac software. GRSs were calculated for hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) using established genetic risk loci for each outcome. Regression analyses were performed to determine the association between GRS and risk of preeclampsia. These analyses were replicated in an independent US population of 516 cases and 1,097 controls of European ancestry.

resultsGRSs for hypertension, SBP, DBP, and MAP were not significantly associated with risk for preeclampsia (P > 0.189). The results of the replication analysis also yielded nonsignificant associations.

conclusionsGRSs for hypertension and blood pressure are not associated with preeclampsia, suggesting that an underlying predisposition to essential hypertension is not on the causal pathway of preeclampsia.

Indexed as

Genetic Predisposition to DiseaseRisk AssessmentBlood PressureBlood Pressure DeterminationEssential HypertensionFemaleFollow-Up StudiesGenotypeHumansHypertensionIncidencePre-EclampsiaPregnancyRetrospective StudiesRisk FactorsTime Factorsblood pressuregenetic epidemiologygenetic predisposition to diseasehypertensionmaternalpreeclampsiapregnancy.

Identifiers

PMID26002928
PMCPMC4692983
OpenAlexW2263277647

What OpenQuestion 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 OpenQuestion graph.