Evidence map›Paper›PMID 29327327›Full record

ArticleMolecular genetics and genomics : MGG2018

Identifying potentially common genes between dyslipidemia and osteoporosis using novel analytical approaches.

Xu Lin, Cheng Peng, Jonathan Greenbaum, Zhang-Fang Li, Ke-Hao Wu, Zeng-Xin Ao, Tong Zhang, Jie Shen, Hong-Wen Deng

Abstract read
In one paragraph

Article in Molecular genetics and genomics : MGG, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.6field-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

12 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. International journal of molecular sciences · 2025
    Article
  3. Review
  4. Article
  5. NOD-like Receptors-Emerging Links to Obesity and Associated Morbidities.International journal of molecular sciences · 2023
    Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
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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

9 authors at 5 institutions in 2 countries.

Xu LinSouthern Medical University, No.1023, South Shatai Road, Baiyun District, Guangzhou, 510515, Guangdong, People's Republic of China.
Cheng PengDepartment of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, 510180, People's Republic of China.
Jonathan GreenbaumCenter for Bioinformatics and Genomics, Department of Global Statistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA.
Zhang-Fang LiDepartment of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510630, People's Republic of China.
Ke-Hao WuCenter for Bioinformatics and Genomics, Department of Global Statistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA.
Zeng-Xin AoSouthern Medical University, No.1023, South Shatai Road, Baiyun District, Guangzhou, 510515, Guangdong, People's Republic of China.
Tong ZhangDepartment of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510630, People's Republic of China.
Jie ShenDepartment of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510630, People's Republic of China.
Hong-Wen DengCenter for Bioinformatics and Genomics, Department of Global Statistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA. hdeng2@tulane.edu.
Third Affiliated Hospital of Southern Medical University · CNSouthern Medical University · CNTulane University · USCentral South University · CNGuangzhou Medical University · CN

Funding

Tulane COBRE in Cardiometabolic Diseases Clinical Research CoreP20GM109036 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI Ning Liu · 2016 to 2026
$25.3M
Trans-omics Integration of Multi-omics Studies for OsteoporosisU19AG055373 · NIA · TULANE UNIVERSITY OF LOUISIANA · PI HONG-WEN DENG · 2017 to 2026
$24.3M
Tulane Clinical Center for Chronic Renal Insufficiency Cohort StudyU01DK060963 · NIDDK · TULANE UNIVERSITY OF LOUISIANA · PI CHEN, JING, HAMM, L LEE · 2001 to 2025
$13.9M
Proteome-wide Expression Study of Osteogenic CellsP50AR055081 · NIAMS · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2007 to 2012
$5.0M
Epigenomewide DNA Methylation Study for Osteoporosis RiskR01AR059781 · NIAMS · TULANE UNIVERSITY OF LOUISIANA · PI DENG, HONG-WEN · 2012 to 2016
$3.1M
Decoding Methylation Mediated Epigenomic Contributions to Male OsteoporosisR01AR069055 · NIAMS · TULANE UNIVERSITY OF LOUISIANA · PI DENG, HONG-WEN · 2017 to 2021
$2.9M
Identification of Proteins Important for Male OsteoporosisR01AR057049 · NIAMS · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2009 to 2013
$2.4M
Genomic search for bone mass QTLsR01AG026564 · NIA · UNIVERSITY OF MISSOURI KANSAS CITY · PI DENG, HONG-WEN · 2007 to 2010
$2.3M
Integration of brain imaging with genomic and epigenomic dataR01MH104680 · NIMH · TULANE UNIVERSITY OF LOUISIANA · PI CALHOUN, VINCE D, DENG, HONG-WEN · 2014 to 2017
$2.1M
Integration of fMRI imaging, genomics, network and biological knowledgeR01MH107354 · NIMH · TULANE UNIVERSITY OF LOUISIANA · PI WANG, YU-PING · 2015 to 2018
$1.9M
Integration of multiscale genomic data for comprehensive analysis of complex diseR01GM109068 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI WANG, YU-PING · 2014 to 2018
$1.6M
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 TW009107NIAMS NIH HHS P50 AR055081NIAMS NIH HHS R01 AR057049NIAMS NIH HHS R01 AR059781NIAMS NIH HHS R01 AR069055NIA NIH HHS R01 AG026564NIA NIH HHS R01 AG056328NIA NIH HHS U19 AG055373NIDDK NIH HHS U01 DK060963NIGMS NIH HHS P20 GM109036NIGMS NIH HHS R01 GM109068NIH HHS D43TW009107NIH HHS P20GM109036NIH HHS R01AR057049NIH HHS R01AR059781NIH HHS R01GM109068NIH HHS R01MH104680NIH HHS R01MH107354NIH HHS U19AG05537301NIMH NIH HHS R01 MH104680NIMH NIH HHS R01 MH107354
6 · The paper itself

Abstract

Dyslipidemia (DL) is closely related to osteoporosis (OP), while the exact common genetic mechanisms are still largely unknown. We proposed to use novel genetic analysis methods with pleiotropic information to identify potentially novel and/or common genes for the potential shared pathogenesis associated with OP and/or DL. We assessed the pleiotropy between plasma lipid (PL) and femoral neck bone mineral density (FNK BMD). We jointly applied the conditional false discovery rate (cFDR) method and the genetic analysis incorporating pleiotropy and annotation (GPA) method to the summary statistics provided by genome-wide association studies (GWASs) of FNK BMD (n = 49,988) and PL (n = 188,577) to identify potentially novel and/or common genes for BMD/PL. We found strong pleiotropic enrichment between PL and FNK BMD. Two hundred and forty-five PL SNPs were identified as potentially novel SNPs by cFDR and GPA. The corresponding genes were enriched in gene ontology (GO) terms "phospholipid homeostasis" and "chylomicron remnant clearance". Three SNPs (rs2178950, rs9939318, and rs9368716) might be the pleiotropic ones and the corresponding genes NLRC5 (rs2178950) and TRPS1 (rs9939318) were involved in NF-κB signaling pathway and Wnt signaling pathway as well as inflammation and innate immune processes. Our study validated the pleiotropy between PL and FNK BMD, and corroborated the reliability and high-efficiency of cFDR and GPA methods in further analyses of existing GWASs with summary statistics. We identified potentially common and/or novel genes for PL and/or FNK BMD, which may provide new insight and direction for further research.

Indexed as

Gene Regulatory NetworksPolymorphism, Single NucleotideBone DensityDNA-Binding ProteinsDyslipidemiasFemur NeckGenetic PleiotropyGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansIntracellular Signaling Peptides and ProteinsLipidsOsteoporosisRepressor ProteinsSignal TransductionTranscription FactorsDNA-Binding ProteinsIntracellular Signaling Peptides and ProteinsLipidsNLRC5 protein, humanRepressor ProteinsTranscription FactorsTRPS1 protein, humancFDRDyslipidemiaGPAOsteoporosisPleiotropy

Identifiers

PMID29327327
PMCPMC5949092
OpenAlexW2782736302

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.