Background: The pathogenesis of Multiple Sclerosis (MS) is poorly understood. A better understanding of the causal pathways involved in this disease is needed as a basis for developing new therapies. Objectives: With this study we try to assess the existence of causal relationships between a large set of candidate plasma proteins and MS. Our analysis is based on 20 multiplex families from the founder and genetically homogeneous population of the Nuoro province, Sardinia (Italy). Our aim is to improve our understanding of the pathophysiological bases of this disease, providing important candidates to be prioritized for further studies on MS and for drug discovery possibly leading to the improvement of the clinical conditions of the subjects affected by this disabling disease. Methods: We investigated each protein, in turn, for a possible causal effect on MS, taking advantage of the use of Mendelian Randomization (MR) methods to avoid the classical biases that affects observational studies. To overcome the limitations of observational studies we adopted a MR approach to the analysis, where genetic variants act as instrumental variables for the assessment of the putative causal effect. We applied different MR methods based on summary statistics: Inverse-Variance Weighted as the main method and the Weighted Median Estimator and Egger regression for sensitivity analysis purpose. The data supported causality of a number of proteins, which we then checked via bidirectional MR analysis to assess potential reverse causation. Results: In the end, 3 proteins showed significant results with both Bonferroni and Benjamini-Hochberg corrections, in particular MOBP, ZMYND19 and EFCAB14. Following the bidirectional analysis though, ZMYND19 showed a significant result in the reverse-direction too, suggesting some reverse causation effect. It seems that, in this case, the disease itself could influence the level of this protein in plasma. The final and most interesting findings in the end are therefore MOBP and EFCAB14. Conclusion: Whereas MR methods are typically applied to high-level exposures, such as obesity and cholesterol, ours is one of the few studies that uses standard MR methods to identify genes that drive the disease by influencing the concentration of their coded proteins, applying a systematic routine of analysis on a very large set of candidate proteins in what seems to be a very promising and useful exploratory approach. We confirmed two proteins being causally related to MS. The variants in the genes coding for these proteins were found statistically associated to MS in previous studies.
Identification of plasma proteins causally related to Multiple Sclerosis via a Mendelian Randomization approach: a study on multiplex families from the founder population of the Nuoro province (Sardinia)
MORANI, GABRIELE
2019
Abstract
Background: The pathogenesis of Multiple Sclerosis (MS) is poorly understood. A better understanding of the causal pathways involved in this disease is needed as a basis for developing new therapies. Objectives: With this study we try to assess the existence of causal relationships between a large set of candidate plasma proteins and MS. Our analysis is based on 20 multiplex families from the founder and genetically homogeneous population of the Nuoro province, Sardinia (Italy). Our aim is to improve our understanding of the pathophysiological bases of this disease, providing important candidates to be prioritized for further studies on MS and for drug discovery possibly leading to the improvement of the clinical conditions of the subjects affected by this disabling disease. Methods: We investigated each protein, in turn, for a possible causal effect on MS, taking advantage of the use of Mendelian Randomization (MR) methods to avoid the classical biases that affects observational studies. To overcome the limitations of observational studies we adopted a MR approach to the analysis, where genetic variants act as instrumental variables for the assessment of the putative causal effect. We applied different MR methods based on summary statistics: Inverse-Variance Weighted as the main method and the Weighted Median Estimator and Egger regression for sensitivity analysis purpose. The data supported causality of a number of proteins, which we then checked via bidirectional MR analysis to assess potential reverse causation. Results: In the end, 3 proteins showed significant results with both Bonferroni and Benjamini-Hochberg corrections, in particular MOBP, ZMYND19 and EFCAB14. Following the bidirectional analysis though, ZMYND19 showed a significant result in the reverse-direction too, suggesting some reverse causation effect. It seems that, in this case, the disease itself could influence the level of this protein in plasma. The final and most interesting findings in the end are therefore MOBP and EFCAB14. Conclusion: Whereas MR methods are typically applied to high-level exposures, such as obesity and cholesterol, ours is one of the few studies that uses standard MR methods to identify genes that drive the disease by influencing the concentration of their coded proteins, applying a systematic routine of analysis on a very large set of candidate proteins in what seems to be a very promising and useful exploratory approach. We confirmed two proteins being causally related to MS. The variants in the genes coding for these proteins were found statistically associated to MS in previous studies.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/84743
URN:NBN:IT:UNIPV-84743