Frontiers in Immunology · 2022 · 212 citations · 35 references
Life SciencesBiostatisticsGeneticsEpidemiologyGenetic EpidemiologyRheumatologyCausal Inference In GeneticsGenetic Susceptibility To PeriodontitisGenome-wide Association StudiesMendelian RandomizationOsteoarthritisRheumatoid ArthritisArthritis EpidemiologyBidirectional Mendelian RandomizationCausal Effect IdentificationHorizontal PleiotropyMr-egger RegressionPleiotropyPleiotropy AnalysisTwo-sample Mendelian Randomization
Objectives: Periodontitis (PD) has been linked to arthritis in previous epidemiological observational studies; however, the results are inconclusive. It remains unclear whether the association between PD and arthritis is causal. The purpose of this study was to investigate the causal association of PD with arthritis, including rheumatoid arthritis (RA) and osteoarthritis (OA). Methods: We performed a two-sample bidirectional Mendelian randomization (MR) analysis using publicly released genome-wide association studies (GWAS) statistics. The inverse-variance weighted (IVW) method was used as the primary analysis. We applied four complementary methods, including weighted median, weighted mode, MR-Egger regression and MR pleiotropy residual sum and outlier (MR-PRESSO) to detect and correct for the effect of horizontal pleiotropy. Results: = 0.89). Furthermore, we did not find a significant causal effect of arthritis on PD in the reverse MR analysis. The results of MR-Egger regression, Weighted Median, and Weighted Mode methods were consistent with those of the IVW method. Horizontal pleiotropy was unlikely to distort the causal estimates according to the sensitivity analysis. Conclusions: Our MR analysis reveals non-causal association of PD with arthritis, despite observational studies reporting an association between PD and arthritis.
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The MR-Base platform supports systematic causal inference across the human phenome
Gibran Hemani, Jie Zheng, Benjamin Elsworth et al. · eLife · 2018 · 8.4K citations · Full text
A map of human genome variation from population-scale sequencing