Objectives: This study aims to investigate the causal relationship between Alzheimer's Disease (AD) and Diabetic Retinopathy (DR).
Methods: Employing Mendelian Randomization (MR), Generalized Summary-data-based Mendelian Randomization (GSMR), and the MR-Steiger test, this study scrutinizes the genetic underpinnings of the hypothesized causal association between AD and DR, as well as its Proliferative DR (PDR) and Non-Proliferative DR (NPDR) subtypes. Comprehensive data from Genome-Wide Association Studies (GWAS) were analyzed, specifically AD data from the Psychiatric Genomics Consortium (71,880 cases/383,378 controls), and DR, PDR, and NPDR data from both the FinnGen consortium (FinnGen release R8, DR: 5,988 cases/314,042 controls; PDR: 8,383 cases/329,756 controls; NPDR: 3,446 cases/314,042 controls) and the IEU OpenGWAS (DR: 14,584 cases/176,010 controls; PDR: 8,681 cases/204,208 controls; NPDR: 2,026 cases/204,208 controls). The study also incorporated Functional Mapping and Annotation (FUMA) for an in-depth analysis of the GWAS results.
Results: The MR analyses revealed that genetic susceptibility to AD significantly increases the risk of DR, as evidenced by GWAS data from the FinnGen consortium (OR: 2.5090; 95% confidence interval (CI):1.2102-5.2018, false discovery rate P-value ()=0.0201; GSMR: b=0.8936, b=0.3759, =0.0174), NPDR (OR: 2.7455; 95% CI: 1.3178-5.7197, =0.0166; GSMR: b=0.9682, b=0.3802, =0.0126), and PDR (OR: 2.3098; 95% CI: 1.2411-4.2986, =0.0164; GSMR: b=0.7962, b=0.3205, =0.0129) using DR GWAS from FinnGen consortium. These results were corroborated by DR GWAS datasets from IEU OpenGWAS. The MR-Steiger test confirmed a significant association of all identified instrumental variables (IVs) with AD. While a potential causal effect of DR and its subtypes on AD was identified, the robustness of these results was constrained by a low power value. FUMA analysis identified OARD1, NFYA, TREM1 as shared risk genes between DR and AD, suggesting a potential genetic overlap between these complex diseases.
Discussion: This study underscores the contribution of AD to an increased risk of DR, as well as NPDR and PDR subtypes, underscoring the necessity of a holistic approach in the management of patients affected by these conditions.
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http://dx.doi.org/10.3389/fendo.2024.1340608 | DOI Listing |
Bioinform Adv
December 2024
Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.
Motivation: The expansion of genetic association data from genome-wide association studies has increased the importance of methodologies like Polygenic Risk Scores (PRS) and Mendelian Randomization (MR) in genetic epidemiology. However, their application is often impeded by complex, multi-step workflows requiring specialized expertise and the use of disparate tools with varying data formatting requirements. Existing solutions are frequently standalone packages or command-line based-largely due to dependencies on tools like PLINK-limiting accessibility for researchers without computational experience.
View Article and Find Full Text PDFFront Med (Lausanne)
December 2024
Department of Ophthalmology, Children's Hospital of Fudan University Xiamen Branch, Xiamen Children's Hospital, Xiamen, China.
Objective: This study systematically investigates the causal relationships between 731 immune cell phenotypes and age-related macular degeneration (AMD) using comprehensive Mendelian randomization (MR) analyses. The goal is to identify immune cell factors that contribute to or protect against AMD, thereby clarifying the immunological mechanisms underlying AMD pathophysiology and informing prevention and treatment strategies.
Methods: Univariable, bidirectional, and multivariable MR analyses were conducted to evaluate the associations between immune cells and AMD.
Arch Dermatol Res
January 2025
Jiangxi Medical College, Nanchang University, Nanchang, China.
Multiple studies have suggested that psoriasis may increase the risk of atrial fibrillation (AF). However, the molecular and immune mechanisms underlying this association remain unclear. This study initially downloaded gene expression profiles for psoriasis and AF from the Gene Expression Omnibus database.
View Article and Find Full Text PDFGeroscience
January 2025
Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
With the development of deep learning (DL) techniques, there has been a successful application of this approach to determine biological age from latent information contained in retinal images. Retinal age gap (RAG) defined as the difference between chronological age and predicted retinal age has been established previously to predict the age-related disease. In this study, we performed discovery genome-wide association analysis (GWAS) on the RAG using the 31,271 UK Biobank participants and replicated our findings in 8034 GoDARTS participants.
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