Alzheimer's Disease and Rheumatoid Arthritis: A Mendelian Randomization Study

Mendelian randomization study on causal association of FAM210B with drug-induced lupus

OBJECTIVE

Due to the complexity of drug-induced lupus (DIL) pathogenesis, more susceptibility factors need to be discovered. FAM210B is a new mitochondrial protein whose function has not been fully elucidated. This study will explore whether there is a correlation between FAM210B and the risk of DIL.

METHODS

At first, we extracted three FAM210B genetic variants from the GTEx database (n = 948), and extracted their corresponding genome-wide association study (GWAS) summary statistics from DIL (101 DIL cases and 218691 controls). Then, we performed a Mendelian randomization (MR) study to evaluate the causal association of the expression of FAM210B with DIL using inverse-variance weighted (IVW), the weighted median, MR-Egger, and MR-PRESSO test.

RESULTS

We successfully extracted three FAM210B single-nucleotide polymorphisms (SNPs) (rs116032784, rs34361943 and rs33923703) from the GTEx_Analysis_v8_eQTL data that can reduce FAM210B expression. The results of the MR analysis showed that genetically reduced expression of FAM210B was significantly associated with increased risk of DIL in European ancestry based on the IVW method (β = 1.037, p = 0.001, odds ratio [OR] = 2.821, 95% confidence interval [CI]:1.495-5.322).

CONCLUSION

MR analysis showed a causal relationship between FAM210B expression and the risk of DIL disease. Our results suggested that FAM210B may be a marker that can mark susceptibility of DIL in the future. It provides evidence for the study of DIL, but its specific mechanism of action in DIL needs to be further studied. Key Points •This is the first MR analysis to examine the association between FAM210B and DIL. •The findings of this study suggested that reduced FAM210B expression is associated with the increased risk of DIL. •FAM210B may be a marker that can mark susceptibility of DIL in the future.

Rheumatoid arthritis is a protective factor against Alzheimer's disease: a bidirectional two-sample Mendelian randomization study

BACKGROUND

Epidemiological evidence suggests that there is an association between rheumatoid arthritis (RA) and Alzheimer's disease (AD). However, the causal relationship between RA and AD remains unclear. Therefore, this study aimed to investigate the causal relationship between RA and AD.

METHODS

Using publicly available genome-wide association study datasets, bidirectional two-sample Mendelian randomization (TSMR) was performed using the inverse-variance weighted (IVW), weighted median, MR‒Egger regression, simple mode, and weighted mode methods.

RESULTS

The results of MR for the causal effect of RA on AD (IVW, odds ratio [OR] = 0.959, 95% confidence interval [CI]: 0.941-0.978, P = 2.752E-05; weighted median, OR = 0.960, 95% CI: 0.937-0.984, P = 0.001) revealed a causal association between genetic susceptibility to RA and an increased risk of AD. The results of MR for the causal effect of AD on RA (IVW, OR = 0.978, 95% CI: 0.906-1.056, P = 0.576; weighted median, OR = 0.966, 95% CI: 0.894-1.043, P = 0.382) indicated that there was no causal association between genetic susceptibility to AD and an increased risk of RA.

CONCLUSIONS

The results of this two-way two-sample Mendelian randomization analysis revealed a causal association between genetic susceptibility to RA and a reduced risk of AD but did not reveal a causal association between genetic susceptibility to AD and an increased or reduced risk of RA.

Appraising causal risk and protective factors for rheumatoid arthritis

Aims

Mendelian randomization (MR) is considered to overcome the bias of observational studies, but there is no current meta-analysis of MR studies on rheumatoid arthritis (RA). The purpose of this study was to summarize the relationship between potential pathogenic factors and RA risk based on existing MR studies.

Methods

PubMed, Web of Science, and Embase were searched for MR studies on influencing factors in relation to RA up to October 2022. Meta-analyses of MR studies assessing correlations between various potential pathogenic factors and RA were conducted. Random-effect and fixed-effect models were used to synthesize the odds ratios of various pathogenic factors and RA. The quality of the study was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guidelines.

Results

A total of 517 potentially relevant articles were screened, 35 studies were included in the systematic review, and 19 studies were eligible to be included in the meta-analysis. Pooled estimates of 19 included studies (causality between 15 different risk factors and RA) revealed that obesity, smoking, coffee intake, lower education attainment, and Graves' disease (GD) were related to the increased risk of RA. In contrast, the causality contribution from serum mineral levels (calcium, iron, copper, zinc, magnesium, selenium), alcohol intake, and chronic periodontitis to RA is not significant.

Conclusion

Obesity, smoking, education attainment, and GD have real causal effects on the occurrence and development of RA. These results may provide insights into the genetic susceptibility and potential biological pathways of RA.

Association of Autoimmune Disorders and Disease-modifying Antirheumatic Drugs: (DMARDs) with the Risk of Alzheimer's and/or Dementia: A Population Study Using Medicare Beneficiary Data

OBJECTIVES

Alzheimer's disease (AD) and/or dementia is a prevalent neurocognitive disorder primarily affecting individuals over the age of 65. Identifying specific causes of AD and/or dementia can be challenging, with emerging evidence suggesting a potential association with autoimmune inflammatory conditions such as rheumatoid arthritis (RA). This study aimed to assess the prevalence rate of AD and/or dementia among Medicare beneficiaries reporting an autoimmune disorder. Additionally, this study sought to identify the comparative prevalence of AD and/or dementia in patients with an autoimmune disorder who were using disease-modifying antirheumatic drugs (DMARDs) compared to those not using DMARDs.

METHODS

Cross-sectional secondary data analyses were conducted on Medicare Current Beneficiary Survey (MCBS) data from 2017 and 2018. The MCBS data consists of a nationally representative sample of the Medicare population, a population that is largely 65 and older, and provides de-identified patient information. Patients from this dataset with a self-reported autoimmune disorder were included in the analyses. Descriptive analyses were conducted on demographic variables, chronic conditions, and medication use. The prevalence of AD and/or dementia was compared between patients with and without an autoimmune disorder. A backward stepwise selection regression was used to identify the risk factors associated with the prevalence of AD and/or dementia.

RESULTS

The study included 18,929 Medicare beneficiaries, with 4,405 identified as having one autoimmune disorder. The prevalence of AD and/or dementia was significantly higher in patients with an autoimmune disorder. The multivariate regression showed that RA was significantly associated with a higher risk of AD and/or dementia. Other demographic factors, including advanced age, African-American or Hispanic ethnicity, low body mass index, and chronic conditions of ischemic heart disease, history of myocardial infarction, history of stroke, depression, mental health disorder(s), and traumatic brain injury also showed statistically significant associations with AD and/or dementia. Patients using DMARDs demonstrated a reduced likelihood of having AD and/or dementia, compared to patients not using DMARDs.

CONCLUSION

This study provides evidence of an association between RA and increased risk of AD and/or dementia. The findings suggest that DMARD use may have a protective effect against the development of AD and/or dementia in patients with an autoimmune disorder.

The causes and consequences of Alzheimer's disease: phenome-wide evidence from Mendelian randomization

Alzheimer's disease (AD) has no proven causal and modifiable risk factors, or effective interventions. We report a phenome-wide association study (PheWAS) of genetic liability for AD in 334,968 participants of the UK Biobank study, stratified by age. We also examined the effects of AD genetic liability on previously implicated risk factors. We replicated these analyses in the HUNT study. PheWAS hits and previously implicated risk factors were followed up in a Mendelian randomization (MR) framework to identify the causal effect of each risk factor on AD risk. A higher genetic liability for AD was associated with medical history and cognitive, lifestyle, physical and blood-based measures as early as 39 years of age. These effects were largely driven by the APOE gene. The follow-up MR analyses were primarily null, implying that most of these associations are likely to be a consequence of prodromal disease or selection bias, rather than the risk factor causing the disease.

Constructing Domain Ontology for Alzheimer Disease Using Deep Learning Based Approach

Facts can be exchanged in multiple fields with the help of disease-specific ontologies. A range of diverse values can be produced by mining ontological approaches for demonstrating disease mechanisms. Alzheimer’s disease (AD) is an incurable neurological brain illness. An early diagnosis of AD can be helpful for better treatment and the prevention of brain tissue destruction. Researchers have used machine learning techniques to predict the early detection of AD. However, Alzheimer’s disorders are still underexplored in the knowledge domain. In the biomedical field, the illustration of terminologies and notions is essential. Multiple methods are adopted to represent these notions, but ontologies are the most frequent and accurate. Ontology construction is a complex and time-consuming process. The designed ontology relies on Disease Ontology (DO), which is considered the benchmark in medical practice. Ontology reasoning mechanisms can be adopted for AD identification. In this paper, a deep convolutional neural network-based approach is proposed to diagnose Alzheimer’s disease, using an AD dataset acquired from Kaggle. Machine learning-based approaches (logistic regression, gradient boosting, XGB, SGD, MLP, SVM, KNN, random forest) are also used for a fair comparison. The simulation results are generated using three strategies (default parameters, 10-cross validation, and grid search), and MLP provides superior results on a default parameter strategy with an accuracy of 92.12%. Furthermore, the deep learning-based approach convolutional neural network (CNN) achieved an accuracy of 94.61%. The experimental results indicate that the construction of ontology, with the help of deep learning knowledge, can produce better results where the robustness and scalability can be enhanced. In comparisons to other methods, the CNN results are excellent and encouraging.

A tale of two systems: Lessons learned from female mid-life aging with implications for Alzheimer's prevention & treatment

Neurological aging is frequently viewed as a linear process of decline, whereas in reality, it is a dynamic non-linear process. The dynamic nature of neurological aging is exemplified during midlife in the female brain. To investigate fundamental mechanisms of midlife aging that underlie risk for development of Alzheimer's disease (AD) in late life, we investigated the brain at greatest risk for the disease, the aging female brain. Outcomes of our research indicate that mid-life aging in the female is characterized by the emergence of three phases: early chronological (pre-menopause), endocrinological (peri-menopause) and late chronological (post-menopause) aging. The endocrinological aging program is sandwiched between early and late chronological aging. Throughout the three stages of midlife aging, two systems of biology, metabolic and immune, are tightly integrated through a network of signaling cascades. The network of signaling between these two systems of biology underlie an orchestrated sequence of adaptative starvation responses that shift the brain from near exclusive dependence on a single fuel, glucose, to utilization of an auxiliary fuel derived from lipids, ketone bodies. The dismantling of the estrogen control of glucose metabolism during mid-life aging is a critical contributor to the shift in fuel systems and emergence of dynamic neuroimmune phenotype. The shift in fuel reliance, puts the largest reservoir of local fatty acids, white matter, at risk for catabolism as a source of lipids to generate ketone bodies through astrocytic beta oxidation. APOE4 genotype accelerates the tipping point for emergence of the bioenergetic crisis. While outcomes derived from research conducted in the female brain are not directly translatable to the male brain, the questions addressed in a female centric program of research are directly applicable to investigation of the male brain. Like females, males with AD exhibit deficits in the bioenergetic system of the brain, activation of the immune system and hallmark Alzheimer's pathologies. The drivers and trajectory of mechanisms underlying neurodegeneration in the male brain will undoubtedly share common aspects with the female in addition to factors unique to the male. Preclinical and clinical evidence indicate that midlife endocrine aging can also be a transitional bridge to autoimmune disorders. Collectively, the data indicate that endocrinological aging is a critical period "tipping point" in midlife which can initiate emergence of the prodromal stage of late-onset-Alzheimer's disease. Interventions that target both immune and metabolic shifts that occur during midlife aging have the potential to alter the trajectory of Alzheimer's risk in late life. Further, to achieve precision medicine for AD, chromosomal sex is a critical variable to consider along with APOE genotype, other genetic risk factors and stage of disease.

Relationship of serum copper and HLADR4 tissue typing to disease activity and severity in patients with rheumatoid arthritis: A cross sectional study

Background

Objective

Methods

Results

Conclusions

•

Rheumatoid arthritis is a chronic disease associated with high burden on individuals.

•

Serum copper increases in active disease.

•

Assessment of disease activity helps in treatment and follow up.

•

Positive HLADR4 tissue typing is associated with severe disease and complications.

Exploring the therapeutic promise of targeting Rho kinase in rheumatoid arthritis

Rheumatoid arthritis (RA) is a prevalent systemic autoimmune disease caused by dysregulated inflammatory reactions, T lymphocyte invasion into the joints, and articular thickening. Immune cells, primarily tumor necrosis factor-alpha (TNF-α) and chemokines (interleukin or IL-1), which are predominantly generated by activated macrophages cells, have also been involved with the pathogenesis of rheumatoid arthritis. Rho GTPases are integral factors of biochemical cascades utilized by antigens, and also by cellular receptors, cytokines, and chemokines, to modulate inflammatory reactions, according to growing data. The Rho family is a group of G proteins that govern a variety of biological and physiological activities such as mobility, actin stress fiber production, growth, and polarity. Research suggests that the Rho A and Rho-associated coiled-coil kinase (ROCK) regulatory cascade could be essential in several autoimmune conditions, including RA. ROCK is activated in the synovial of rheumatoid arthritis patients, while the blocking of ROCK with fasudil could also decrease IL-6, TNF-α, and IL-1. This review covers current developments in understanding the overactivation of Rho enzyme activity in RA suppressed by ROCK inhibitors which can be utilized for the treatment of autoimmune disease. We offer an outline of the function of ROCK inhibitors in immune cells and discuss findings which emphasize the rising participation of this category of kinases within the pathological process of autoimmune disorders. Assuming the potential ability of ROCK as a therapeutic, we define approaches that might be used to inhibit Rho kinase activity in rheumatoid disorders.

Vitamin D and risk of ankylosing spondylitis: A two-sample mendelian randomization study

OBJECTIVES

To study whether Vitamin D levels are causally associated with ankylosing spondylitis (AS).

METHODS

Two-sample Mendelian randomization (TSMR) analysis was performed by employing MR-Egger regression, weighted median (WM¹), inverse-variance weighted (IVW), and weight mode (WM²) methods. The odds ratio (OR) with 95% confidence intervals (CIs) was used to evaluate this association.

RESULTS

The results of IVW show that no causal association between vitamin D and AS (OR = 0.999, 95%CI = 0.997, 1.002, P = 0.724). The MR-Egger regression results show that genetic pleiotropy does not bias the results (intercept = -4.474E-05, SE = 2.830E-05, P = 0.255). The MR-Egger method no supported causal association between vitamin D and AS (OR = 1.000, 95%CI = 0.996, 1.005, P = 0.879). WM¹ (OR = 1.002, 95%CI = 0.999, 1.005, P = 0.837) and WM² (OR = 0.998, 95%CI = 0.996, 1.002, P = 0.910) approach also not found a causal relationship between vitamin D levels and AS. The significant heterogeneity was not observed by Cochran's Q test. The "leave-one-out" analysis also proved lack of a single SNP affected the robustness of our results.

CONCLUSION

Based on our analysis, there is lack of a strong evidence to support a causal inverse association between vitamin D levels and ankylosing spondylitis.

Trends in incidence of dementia among patients with rheumatoid arthritis: A population-based cohort study

OBJECTIVE

We aimed to assess the incidence of dementia over time in patients with incident rheumatoid arthritis (RA) as compared to non-RA referents.

METHODS

This population-based, retrospective cohort study included Olmsted County, Minnesota residents with incident RA by ACR 1987 criteria, diagnosed between 1980 and 2009. We matched non-RA referents 1:1 on age, sex, and calendar year and followed all individuals until 12/31/2019. Incident dementia was defined as two codes for Alzheimer's disease and related dementias (ADRD) at least 30 days apart. Cumulative incidence of ADRD was assessed, adjusting for the competing risk of death. Cox proportional hazards models calculated hazard ratios (HR) with 95% confidence intervals (CI) for incident ADRD by decade.

RESULTS

After excluding individuals with prior dementia, we included 897 persons with incident RA (mean age 56 years; 69% female) and 885 referents. The 10-year cumulative incidence of ADRD in individuals diagnosed with RA during the 1980s was 12.7% (95%CI:7.9-15.7%), 1990s was 7.2% (95%CI:3.7-9.4%), and 2000s was 6.2% (95%CI:3.6-7.8%). Individuals with RA diagnosed in 2000s had insignificantly lower cumulative incidence of ADRD than those in the 1980s (HR 0.66; 95%CI:0.38-1.16). The overall HR of ADRD in individuals with RA was 1.37 (vs. referents; 95%CI:1.04-1.81). When subdivided by decade, however, the risk of ADRD in individuals diagnosed with RA was higher than referents in the 1990s (HR 1.72, 95%CI:1.09-2.70) but not 2000s (HR 0.86, 95%CI:0.51-1.45).

CONCLUSIONS

The risk of dementia in individuals with RA appears to be declining over time, including when compared to general population referents.

The Joint-Brain Axis: Insights From Rheumatoid Arthritis on the Crosstalk Between Chronic Peripheral Inflammation and the Brain

Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by erosive polyarthritis. Beyond joint pathology, RA is associated with neuropsychiatric comorbidity including depression, anxiety, and an increased risk to develop neurodegenerative diseases in later life. Studies investigating the central nervous system (CNS) in preclinical models of RA have leveraged the understanding of the intimate crosstalk between peripheral and central immune responses. This mini review summarizes the current knowledge of CNS comorbidity in RA patients and known underlying cellular mechanisms. We focus on the differential regulation of CNS myeloid and glial cells in different mouse models of RA reflecting different patterns of peripheral immune activation. Moreover, we address CNS responses to anti-inflammatory treatment in human RA patients and mice. Finally, to illustrate the bidirectional communication between the CNS and chronic peripheral inflammation, we present the current knowledge about the impact of the CNS on arthritis. A comprehensive understanding of the crosstalk between the CNS and chronic peripheral inflammation will help to identify RA patients at risk of developing CNS comorbidity, setting the path for future therapeutic approaches in both RA and neuropsychiatric diseases.

Using Mendelian randomization to understand and develop treatments for neurodegenerative disease

Common neurodegenerative diseases are thought to arise from a combination of environmental and genetic exposures. Mendelian randomization is a powerful way to leverage existing genetic data to investigate causal relationships between risk factors and disease. In recent years, Mendelian randomization has gathered considerable traction in neurodegenerative disease research, providing valuable insights into the aetiology of these conditions. This review aims to evaluate the impact of Mendelian randomization studies on translational medicine for neurodegenerative diseases, highlighting the advances made and challenges faced. We will first describe the fundamental principles and limitations of Mendelian randomization and then discuss the lessons from Mendelian randomization studies of environmental risk factors for neurodegeneration. We will illustrate how Mendelian randomization projects have used novel resources to study molecular pathways of neurodegenerative disease and discuss the emerging role of Mendelian randomization in drug development. Finally, we will conclude with our view of the future of Mendelian randomization in these conditions, underscoring unanswered questions in this field.

Rheumatoid arthritis and neurodegenerative dementia: a nested case-control study and a follow-up study using a national sample cohort

OBJECTIVES

The present study evaluated the associations between rheumatoid arthritis (RA) and neurodegenerative dementia using a Korean national sample cohort.

METHODS

We designed two studies using the Korean National Health Insurance Service-National Sample Cohort from 2002 to 2013. Study I included participants with dementia matched 1:4 with controls and analyzed the participants' history of RA. Study II included participants with RA matched 1:4 with controls and analyzed the occurrence of dementia. RA was defined by the presence of relevant ICD-10 codes (M05 or M06) and medication histories. Neurodegenerative dementia was defined using ICD-10 codes (G30 or F00). Crude and adjusted odds ratios (ORs) were analyzed using conditional logistic regression analyses. Crude and adjusted hazard ratios (HRs) were analyzed using the stratified Cox proportional hazard model. Subgroup analyses were performed on groups stratified by age and sex.

RESULTS

The adjusted ORs for RA were 0.96 (95% CI = 0.78-1.16, P = 0.644) in the dementia group in study I. The adjusted HRs for dementia were 0.91 (95% CI = 0.76-1.10, P = 0.319) in the RA group in study II. No subgroup analysis reached the statistical significance level.

CONCLUSION

We could not identify any significant relationship between RA and dementia.Key Points• Two studies were conducted to identify the relationship between rheumatoid arthritis and dementia using national cohort data.• Neither study showed any association between rheumatoid arthritis and dementia.

Microglial Phagocytosis of Neurons: Diminishing Neuronal Loss in Traumatic, Infectious, Inflammatory, and Autoimmune CNS Disorders

Errors in neuron-microglial interaction are known to lead to microglial phagocytosis of live neurons and excessive neuronal loss, potentially yielding poorer clinical outcomes. Factors that affect neuron-microglial interaction have the potential to influence the error rate. Clinical comorbidities that unfavorably impact neuron-microglial interaction may promote a higher rate of neuronal loss, to the detriment of patient outcome. This paper proposes that many common, clinically modifiable comorbidities have a common thread, in that they all influence neuron-microglial interactions. Comorbidities like traumatic brain injury, infection, stress, neuroinflammation, loss of neuronal metabolic integrity, poor growth factor status, and other factors, all have the potential to alter communication between neurons and microglia. When this occurs, microglial phagocytosis of live neurons can increase. In addition, microglia can shift into a morphological form in which they express major histocompatibility complex II (MHC-II), allowing them to function as antigen presenting cells that present neuronal debris as antigen to invading T cells. This can increase risk for the development of CNS autoimmunity, or can exacerbate existing CNS autoimmunity. The detrimental influence of these comorbidities has the potential to contribute to the mosaic of factors that determine patient outcome in some CNS pathologies that have neuropsychiatric involvement, including TBI and CNS disorders with autoimmune components, where excessive neuronal loss can yield poorer clinical outcomes. Recognition of the impact of these comorbidities may contribute to an understanding of the common clinical observation that many seemingly disparate factors contribute to the overall picture of case management and clinical outcome in these complex disorders. In a clinical setting, knowing how these comorbidities can influence neuron-microglial interaction can help focus surveillance and care on a broader group of potential therapeutic targets. Accordingly, an interest in the mechanisms underlying the influence of these factors on neuron-microglial interactions is appropriate. Neuron-microglial interaction is reviewed, and the various mechanisms by which these potential comorbidities influence neuro-microglial interaction are described.