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Gene-based GWAS analysis for consecutive studies of GEFOS

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Abstract

Summary

By integrating the multilevel biological evidence and bioinformatics analyses, the present study represents a systemic endeavor to identify BMD-associated genes and their roles in skeletal metabolism.

Introduction

Single-nucleotide polymorphism (SNP)-based genome-wide association studies (GWASs) have already identified about 100 loci associated with bone mineral density (BMD), but these loci only explain a small proportion of heritability to osteoporosis risk. In the present study, we performed a gene-based analysis of the largest GWASs in the bone field to identify additional BMD-associated genes.

Methods

BMD-associated genes were identified by combining the summary statistic P values of SNPs across individual genes in the two consecutive meta-analyses of GWASs from the Genetic Factors for Osteoporosis (GEFOS) studies. The potential functionality of these genes to bone was partially assessed by differential gene expression analysis. Additionally, the consistency of the identification of potential bone mineral density (BMD)-associated variants were evaluated by estimating the correlation of the P values of the same single-nucleotide polymorphisms (SNPs)/genes between the two consecutive Genetic Factors for Osteoporosis Studies (GEFOS) with largely overlapping samples.

Results

Compared to the SNP-based analysis, the gene-based strategy identified additional BMD-associated genes with genome-wide significance and increased their mutual replication between the two GEFOS datasets. Among these BMD-associated genes, three novel genes (UBTF, AAAS, and C11orf58) were partially validated at the gene expression level. The correlation analysis presented a moderately high between-study consistency of potential BMD-associated variants.

Conclusions

Gene-based analysis as a supplementary strategy to SNP-based genome-wide association studies, when applied here, is shown that it helped identify some novel BMD-associated genes. In addition to its empirically increased statistical power, gene-based analysis also provides a higher testing stability for identification of BMD genes.

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Abbreviations

AAAS:

Aladin WD repeat nucleoporin

AOGC:

Australasian Osteoporosis Genetics Consortium

BMD:

Bone mineral density

CCNB1:

Cyclin B1

DEGs:

Differentially expressed genes

ERF:

Erasmus Rucphen Family Study

FA:

Forearm

FDR:

False discovery rate

FHS:

Framingham Heart Study

FN:

Femoral neck

GATES:

Extended Simes procedure method

GEFOS:

Genetic Factors for Osteoporosis Studies

GEO:

Gene Expression Omnibus

GO:

Gene ontology

GWASs:

Genome-wide association studies

HYST:

Hybrid set-based test

KGG:

Knowledge-based mining system for genome-wide genetic studies

LD:

Linkage disequilibrium

LS:

Lumbar spine

NHGRI:

National Human Genome Research Institute

NUP155:

Nucleoporin 155

PPI:

Protein-protein interaction

QQ:

Quantile-quantile

RANK:

Receptor activator of NFKB

RANKL:

Receptor activator of NFKB ligand

rRNA:

Ribosomal RNA

RS-I:

Rotterdam Study-I

SNP:

Single-nucleotide polymorphism

TWINSUK:

TwinsUK

UBTF:

Upstream binding transcription factor

WHO:

World Health Organization

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Acknowledgments

Full author lists of the two consortia (GEFOS2 and GEFOS-seq) were available in the Supplementary Acknowledgment.

Funding

This study was partially supported by and/or benefited from grants from National Institutes of Health [AR069055, U19 AG055373, R01 MH104680, R01AR059781 and P20GM109036], and Edward G. Schlieder Endowment to Tulane University.

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Authors and Affiliations

  1. College of Life Sciences, Hunan Normal University, Changsha, 410081, Hunan, China

    W. Zhu & H.-W. Deng

  2. Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 1610, New Orleans, LA, 70112, USA

    W. Zhu, C. Xu, J.-G. Zhang, H. He, K.-H. Wu, L. Zhang, Y. Zeng, Y. Zhou, K.-J. Su & H.-W. Deng

  3. College of Life Sciences and Bioengineering, Beijing Jiaotong University, Beijing, 100044, China

    Y. Zeng

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  1. W. Zhu
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  3. J.-G. Zhang
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  4. H. He
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Correspondence to H.-W. Deng.

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Zhu, W., Xu, C., Zhang, JG. et al. Gene-based GWAS analysis for consecutive studies of GEFOS. Osteoporos Int 29, 2645–2658 (2018). https://doi.org/10.1007/s00198-018-4654-y

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