Evidence map›Paper›PMID 27664953›Full record

ArticleAmerican journal of hypertension2017

Associations of the Serum/Glucocorticoid Regulated Kinase Genes With BP Changes and Hypertension Incidence: The Gensalt Study.

Dingding Zhang, Dongfeng Gu, Jiang He, James E Hixson, Dabeeru C Rao, Changwei Li, Hua He, Jichun Chen, Jianfeng Huang, Jing Chen and 3 more

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of hypertension, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 27% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Review
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

13 authors at 3 institutions in 2 countries.

Dingding ZhangDepartment of Evidence Based Medicine, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Dongfeng GuDepartment of Evidence Based Medicine, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jiang HeDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA.
James E HixsonDepartment of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, Texas, USA.
Dabeeru C RaoDivision of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA.
Changwei LiDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA.
Hua HeDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA.
Jichun ChenDepartment of Evidence Based Medicine, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jianfeng HuangDepartment of Evidence Based Medicine, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jing ChenDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA.
Treva K RiceDivision of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA.
Shufeng ChenDepartment of Evidence Based Medicine, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Tanika N KellyDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA; tkelly@tulane.edu.
Tulane University · USChinese Academy of Medical Sciences & Peking Union Medical College · CNThe University of Texas Health Science Center at Houston · US

Funding

Tulane COBRE in Cardiometabolic Diseases Clinical Research CoreP20GM109036 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI Ning Liu · 2016 to 2026
$25.3M
Genetic Epidemiology of Blood Pressure InterventionU01HL072507 · NHLBI · TULANE UNIVERSITY OF LOUISIANA · PI HE, JIANG · 2002 to 2008
$7.6M
Family-Based Genome-wide Association Study for Salt-Sensitivity of Blood PressureR01HL090682 · NHLBI · TULANE UNIVERSITY OF LOUISIANA · PI HE, JIANG · 2008 to 2011
$2.8M
Sodium Sensitivity and Risk of HypertensionR01HL087263 · NHLBI · TULANE UNIVERSITY OF LOUISIANA · PI HE, JIANG · 2007 to 2011
$2.8M
Epigenetic drivers and biomarkers of diabetic kidney diseaseDP3DK108220 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI SUSZTAK, KATALIN · 2015 to 2015
$2.4M
Research Training in Gene-Environment Interaction in ChinaD43TW009107 · FIC · TULANE UNIVERSITY OF LOUISIANA · PI GU, DONGFENG, HE, JIANG · 2012 to 2016
$1.1M
FIC NIH HHS D43 TW009107NHLBI NIH HHS R01 HL087263NHLBI NIH HHS R01 HL090682NHLBI NIH HHS U01 HL072507NIDDK NIH HHS DP3 DK108220NIGMS NIH HHS P20 GM109036
6 · The paper itself

Abstract

backgroundSingle-marker and novel gene-based methods were employed to examine the associations of the serum/glucocorticoid regulated kinases (SGK) gene family with longitudinal blood pressure (BP) changes and hypertension incidence in a family-based cohort study.

methodsTotally, 1,768 Chinese participants from the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) follow-up study were included in the current analyses. Nine BP measures were obtained at each of 3 visits during the GenSalt follow-up study. Mixed-model and Gene-based analyses were used to examine the associations of the SGK gene family with longitudinal BP phenotypes. Bonferroni correction was applied to account for multiple testing.

resultsAfter an average 7.2-year follow-up, 32.2% (513) of participants free of hypertension at baseline developed hypertension. Four novel SNPs in the SGK1 gene were predictive of the longitudinal BP phenotypes. The major alleles of SGK1 rs1763498 and rs114414980 conferred 2.9- and 2.5-fold increased risks of hypertension development, respectively (P = 1.0×10

conclusionsThe findings of the current study suggest that the SGK1 gene may play a role in long-term BP regulation and hypertension incidence.

Indexed as

AdultBlood PressureChinaCohort StudiesFemaleHumansHypertensionImmediate-Early ProteinsIncidenceMaleMiddle AgedMultigene FamilyProtein Serine-Threonine KinasesSerum-Glucocorticoid Regulated KinasesImmediate-Early ProteinsProtein Serine-Threonine KinasesSerum-Glucocorticoid Regulated Kinasesblood pressureblood pressure changescommon variantshypertension.SGK

Identifiers

PMID27664953
PMCPMC5155568
OpenAlexW2523330517

What OpenQuestion holds

Textmetadata
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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.