Background: Although observational epidemiological studies have found that smoking is positively associated with risk of rheumatoid arthritis (RA), assessing the causality of this relationship has remained elusive because conventional observational studies are susceptible to bias such as confounding and reverse causation. Here, we applied the Mendelian randomization (MR) approach to examine the potential causal relationship between smoking and risk of RA.
Methods: Summary statistics data for RA were obtained from a meta-analysis of genome-wide association studies (GWAS), including 14,361 RA cases and 43,923 controls of European ancestry. The instrumental variables (IV) and the genetic association estimates for smoking initiation and lifetime smoking were obtained from a GWAS meta-analysis including 1,232,091 individuals and a GWAS of 462,690 individuals of European ancestry, respectively. MR analyses were performed using the inverse-variance weighted (IVW) method and supplemented with the weighted-median method. Potential pleiotropy was assessed using the MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test and MR-Egger regression. Sensitivity analyses were further performed to test the robustness of the association.
Results: We found that compared with never smokers, genetic predisposition to smoking initiation was positively associated with risk of RA (odds ratio (OR) = 1.32, 95% confidence interval (CI) = 1.15-1.52, P = 9.17 × 10 using the IVW method). Similarly, genetically predicted lifetime smoking was associated with an increased risk of RA (OR = 1.55, 95% CI = 1.13-2.14, P = 0.007). Sensitivity analyses using alternative MR methods and different sets of IVs produced similar results, suggesting the robustness of our findings.
Conclusions: These results provide support for a causal association between smoking and increased risk of RA. Further studies are warranted to explain the underlying mechanisms of smoking in the development of RA.
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http://dx.doi.org/10.1186/s13075-020-2134-1 | DOI Listing |
Alzheimers Dement
December 2024
GSK R&D, Stevenage, Hertfordshire, United Kingdom.
Background: Genetic variants in GRN, the gene encoding progranulin, are causal for or are associated with the risk of multiple neurodegenerative diseases. Modulating progranulin has been considered as a therapeutic strategy for neurodegenerative diseases including Frontotemporal Dementia (FTD) and Alzheimer's Disease (AD). Here, we integrated genetics with proteomic data to determine the causal human evidence for the therapeutic benefit of modulating progranulin in AD.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, U.S.A., Philadelphia, PA, USA.
Background: The vicious cycle between depression and dementia increases the risk of Alzheimer's Disease (AD) pathogenesis and pathology. This study investigates therapeutic effectiveness versus side effects and the underlying mechanisms of intranasal dantrolene nanoparticles (IDNs) to treat depression behavior and memory loss in 5XFAD mice.
Method: 5XFAD and wild-type B6SJLF1/J mice were treated with IDNs (IDN, 5 mg/kg) in Ryanodex formulation for a duration of 12 weeks.
Alzheimers Dement
December 2024
Columbia University Irving Medical Center, New York, NY, USA.
Background: Genetic studies indicate a causal role for microglia, the innate immune cells of the central nervous system (CNS), in Alzheimer's disease (AD). Despite the progress made in identifying genetic risk factors, such as CD33, and underlying molecular changes, there are currently limited treatment options for AD. Based on the immune-inhibitory function of CD33, we hypothesize that inhibition of CD33 activation may reverse microglial suppression and restore their ability to resolve inflammatory processes and mitigate pathogenic amyloid plaques, which may be neuroprotective.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Case Western Reserve University, Cleveland, OH, USA.
Background: Traumatic Brain Injury (TBI) is one of the most common nonheritable causes of Alzheimer's disease (AD). However, there is lack of effective treatment for both AD and TBI. We posit that network-based integration of multi-omics and endophenotype disease module coupled with large real-world patient data analysis of electronic health records (EHR) can help identify repurposable drug candidates for the treatment of TBI and AD.
View Article and Find Full Text PDFBackground: Although investment in biomedical and pharmaceutical research has increased significantly over the past two decades, there are no oral disease-modifying treatments for Alzheimer's disease (AD).
Method: We performed comprehensive human genetic and multi-omics data analyses to test likely causal relationship between EPHX2 (encoding soluble epoxide hydrolase [sEH]) and risk of AD. Next, we tested the effect of the oral administration of EC5026 (a first-in-class, picomolar sEH inhibitor) in a transgenic mouse model of AD-5xFAD and mechanistic pathways of EC5026 in patient induced Pluripotent Stem Cells (iPSC) derived neurons.
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