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Identification of Novel Pleiotropic SNPs Associated with Osteoporosis and Rheumatoid Arthritis

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Abstract

Genome-wide association studies (GWASs) have identified hundreds of genetic loci for osteoporosis (OP) and rheumatoid arthritis (RA), individually, however, a large proportion of the total trait heritability remains unexplained. Previous studies demonstrated that these two diseases may share some common genetic determination and risk factors, but they were generally focused on individual trait and failed to identify the common variants that play key functional roles in the etiology of these two diseases. Here, we performed a conditional false discovery rate (cFDR) analysis to identify novel pleiotropic variants shared between them by integrating two independent GWASs with summary statistics for total body bone mineral density (TB-BMD, a major risk factor for osteoporosis) (n = 66,628) and RA (n = 58,284). A fine-mapping approach was also applied to identify the most probable causal variants with biological effects on both TB-BMD and RA. As a result, we found 47 independent pleiotropic SNPs shared between TB-BMD and RA, and 40 of them were validated in heel ultrasound estimated BMD (eBMD), femoral neck BMD (FN-BMD) or lumbar spine (LS-BMD). We detected one SNP (rs13299616) was novel and not identified by previous BMD or RA-related studies. Combined with fine-mapping and GWAS-eQTL colocalization analyses, our results suggested that locus 1p13.2 (including PTPN22, MAGI3, PHTF1, and RSBN1) was an important region to regulate TB-BMD and RA simultaneously. These findings provide new insights into the shared biological mechanisms and functional genetic determinants between OP and RA, and novel potential targets for treatment development.

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Data Availability

The GWAS datasets for TB-BMD, FN-BMD, LS-BMD, and eBMD used in this study was obtained from Genetic Factors for Osteoporosis (GEFOS) Consortium (http://www.gefos.org/?q=content/gefos-lifecourse-tb-bmd-gwas-results). The RA GWAS dataset used in this study was obtained from public datasets (http://plaza.umin.ac.jp/~yokada/datasource/software.htm).

Code Availability

Software: ANNOVAR: http://annovar.openbioinformatics.org/en/latest/user-guide/download/PAINTOR_V3.0: https://github.com/gkichaev/PAINTOR_V3.0, SSIMP: https://github.com/aaronmcdaid/ssimp_software, MR-base: https://www.mrbase.org/, R code for cFDR: See supplemental material.

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Funding

This work was partially supported by grants from National Institutes of Health [R01AR059781, P20GM109036, R01MH107354, R01MH104680, R01GM109068, R01AR069055, U19AG055373, R01DK115679].

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Y-QL Conceptualization, Writing—Original Draft, Formal analysis YL Software, Formal analysis QZ Writing—Review & Editing TX Writing—Review & Editing H-WD Supervision.

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Correspondence to Hong-Wen Deng.

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Liu, YQ., Liu, Y., Zhang, Q. et al. Identification of Novel Pleiotropic SNPs Associated with Osteoporosis and Rheumatoid Arthritis. Calcif Tissue Int 109, 17–31 (2021). https://doi.org/10.1007/s00223-021-00817-4

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