The causal relationship of inflammation-related factors with osteoporosis: A Mendelian Randomization Analysis

Abstract

Background

We used Mendelian randomization (MR) approach to examine whether genetically determined inflammation-related risk factors play a role in the onset of osteoporosis (OP) in the European population.

Methods

Genome-wide association studies (GWASs) summary statistics of estimated bone mineral density (eBMD) obtained from the public database GEnetic Factors for OSteoporosis Consortium (GEFOS) including 142,487 European people. For exposures, we utilized GWAS data of 9 risk factors including diseases chronic kidney disease (CKD) (41,395 cases and 439,303 controls), type 2 diabetes (T2D) (88,427 cases and 566,778 controls), Alzheimer's disease (AD) (71,880 cases, 383,378 controls) and major depression disorder (MDD) (9240 cases and 9519 controls) and lifestyle behaviors are from different consortiums. Inverse variance weighted (IVW) analysis was principal method in this study and random effect model was applied; MR-Egger method and weighted median method were also performed for reliable results. Cochran's Q test and MR-Egger regression were used to detect heterogeneity and pleiotropy and leave-one-out analysis was performed to find out whether there are influential SNPs.

Results

We found that T2D (IVW: β = 0.05, P = 0.0014), FI (IVW: β = −0.22, P < 0.001), CKD (IVW: β = 0.02, P = 0.009), ALZ (IVW: β = 0.06, P = 0.005), Coffee consumption (IVW: β = 0.11, P = 0.003) were causally associated with OP ($P<0.006$after Bonferroni correction).

Conclusions

Our study revealed that T2D, FI, CKD, ALZ and coffee consumption are causally associated with OP. Future interventions targeting factors above could provide new clinical strategies for the personalized prevention and treatment of osteoporosis.