Shared genetic loci between Alzheimer's disease and multiple sclerosis: Crossroads between neurodegeneration and immune system

Association between frailty and inflammatory cytokines in patients with multiple sclerosis: a case-control study

BACKGROUND

Frailty is a common symptom in Multiple Sclerosis (MS), yet its precise mechanism remains elusive, and the clinical implications of frailty in MS are uncertain. Moreover, inflammation is closely linked to frailty. This study aims to assess serum cytokine levels in individuals with MS and explore their correlation with frailty.

METHODS

A case-control study included 83 primary MS patients and 100 healthy individuals undergoing health check-ups. Serum cytokine levels were measured, and MS severity was determined using the Expanded Disability Status Scale (EDSS) score. Additionally, a comprehensive frailty index (FI) was calculated based on health deficits from various domains following standardized procedures.

RESULTS

Serum IL-6 and TNF-α levels were significantly higher in the frail group than in the non-frail group, with a statistically significant difference (P < 0.05). After adjusting for disease duration, sex, age, BMI, SBP, and DBP, serum IL-6 independently correlated with frailty in MS patients (OR = 1.46; 95 % CI = 1.02-1.93; P = 0.003). Moreover, increased serum IL-6 levels were associated positively with the frailty index (β = 0.123, P = 0.008).

CONCLUSION

Our initial findings suggest elevated levels of pro-inflammatory cytokines in MS patients with frailty, with IL-6 showing a positive correlation with frail indices. These results underscore the potential impact of inflammatory responses on frailty development in MS.

Identification of genetic architecture shared between schizophrenia and Alzheimer's disease

Both schizophrenia (SCZ) and Alzheimer's disease (AD) are highly heritable brain disorders. Despite of the observed comorbidity and shared psychosis and cognitive decline between the two disorders, the genetic risk architecture shared by SCZ and AD remains largely unknown. Based on summary statistics of the currently available largest genome-wide association studies for SCZ (n = 130,644) and AD (n = 455,258) in individuals of European ancestry, we conducted conditional/conjunctional false discovery rate (FDR) analysis to enhance the statistical power for discovering more genetic associations with SCZ or AD and to detect the common genetic variants shared by both disorders. We found shared genetic architecture in SCZ conditioned on AD and vice versa across different levels of significance, indicating polygenic overlap. We found 268 (78 novel) SCZ-only and 125 (55 novel) AD-only SNPs at conditional FDR < 0.01, and 16 lead SNPs shared by SCZ and AD at conjunctional FDR < 0.05. Only half of the shared SNPs showed concordant effect direction, which was consistent with the modest genetic correlation (r = 0.097; P = 0.026) between the two disorders. This study provides evidence for polygenic overlap between SCZ and AD, suggesting the existence of the shared molecular genetic mechanisms, which may inform therapeutic targets that are applicable for both disorders.

Mapping the Genetic Landscape of Psychiatric Disorders With the MiXeR Toolset

Psychiatric disorders have complex genetic architectures with substantial genetic overlap across conditions, which may partially explain their high levels of comorbidity. This presents significant challenges to research. Genome-wide association studies (GWASs) have uncovered hundreds of loci associated with single disorders, but the genetic landscape of psychiatric disorders has remained largely obscure. Moving beyond the conventional infinitesimal model, uni-, bi-, and trivariate MiXeR tools, applied to GWAS summary statistics, has enabled us to more comprehensively describe the genetic architecture of complex disorders and traits and their overlap. Furthermore, the GSA-MiXeR tool improves biological interpretation of GWAS findings to better elucidate causal mechanisms. Here, we outline the methodology that underlies the MiXeR tools together with instructions for their optimal use. We review results from studies that have investigated the genetic architecture of psychiatric disorders and their overlap using the MiXeR toolset. These studies have revealed generally high polygenicity and low discoverability among psychiatric disorders, particularly in contrast to somatic disorders. There is also pervasive genetic overlap across psychiatric disorders and behavioral traits, while their overlap with somatic traits is smaller, consistent with differences in polygenicity. Finally, GSA-MiXeR has quantified the contribution of gene sets to the heritability of psychiatric disorders, prioritizing small, biologically coherent gene sets. Together, these findings have implications for our understanding of the complex relationships between psychiatric disorders and related traits. MiXeR tools have provided new insights into the genetic architecture of psychiatric disorders, generating a better understanding of their underlying biological mechanisms and potential for clinical utility.

Alzheimer's disease (AD) in multiple sclerosis (MS): A systematic review of published cases, mechanistic links between AD and MS, and possible clinical evaluation of AD in MS

Background: Alzheimer's disease (AD) and multiple sclerosis (MS) are two neurological disorders that can pose enormous burden to a person's quality of life. Due to new therapeutic advancements that significantly extend the lifespan, there may be an increased prevalence of AD in elderly MS patients. Objective: Building on a previous review on MS-AD coexistence, this review not only aimed to broaden the pool of literature searched, but also investigated possible mechanistic links between clinical markers for MS and AD. Methods: We searched for newly reported cases of coexisting MS and AD in PubMed, Clinical Key, BioMed Central, and Europe PubMed Central databases; and identified 101 new cases in addition to the previously reported 24 cases by Luczynski et al. (2019). The resulting 125 comorbid cases necessitated an evaluation of literature on the pathogenesis of MS and AD. Results: This review highlights many overlaps between AD and MS (for instance, the immune cell dysfunction, glymphatic dysfunction, genetics, environmental factors, and others). We critically evaluated clinical and laboratory metrics used to identify AD in MS patients (e.g., MRI, amyloid-β and tau protein identification, miRNA biomarker evaluation, cerebrospinal fluid analysis, vitamin levels, gut microbiota etc.). Conclusions: Future research should refine these diagnostic criteria and focus on enhancing screening and detection methods for AD in MS patients. Furthermore, one should also investigate the primary causes of the increased comorbidity between AD and MS.

Plasma protein-based identification of neuroimage-driven subtypes in mild cognitive impairment via protein-protein interaction aware explainable graph propagational network

As an early indicator of dementia, mild cognitive impairment (MCI) requires specialized treatment according to its subtypes for the effective prevention and management of dementia progression. Based on the neuropathological characteristics, MCI can be classified into Alzheimer's disease (AD)-related cognitive impairment (ADCI) and subcortical vascular cognitive impairment (SVCI), being more likely to progress to AD and subcortical vascular dementia (SVD), respectively. For identifying MCI subtypes, plasma protein biomarkers are recently seen as promising tools due to their minimal invasiveness and cost-effectiveness in diagnostic procedures. Furthermore, the application of machine learning (ML) has led the preciseness in the biomarker discovery and the resulting diagnostics. Nevertheless, previous ML-based studies often fail to consider interactions between proteins, which are essential in complex neurodegenerative disorders such as MCI and dementia. Although protein-protein interactions (PPIs) have been employed in network models, these models frequently do not fully capture the diverse properties of PPIs due to their local awareness. This limitation increases the likelihood of overlooking critical components and amplifying the impact of noisy interactions. In this study, we introduce a new graph-based ML model for classifying MCI subtypes, called eXplainable Graph Propagational Network (XGPN). The proposed method extracts the globally interactive effects between proteins by propagating the independent effect of plasma proteins on the PPI network, and thereby, MCI subtypes are predicted by estimation of the risk effect of each protein. Moreover, the process of model training and the outcome of subtype classification are fully explainable due to the simplicity and transparency of XGPN's architecture. The experimental results indicated that the interactive effect between proteins significantly contributed to the distinct differences between MCI subtype groups, resulting in an enhanced classification performance with an average improvement of 10.0 % compared to existing methods, also identifying key biomarkers and their impact on ADCI and SVCI.

Charting the shared genetic architecture of Alzheimer's disease, cognition, and educational attainment, and associations with brain development

The observation that the risk of developing Alzheimer's disease is reduced in individuals with high premorbid cognitive functioning, higher educational attainment, and occupational status has led to the 'cognitive reserve' hypothesis. This hypothesis suggests that individuals with greater cognitive reserve can tolerate a more significant burden of neuropathological changes before the onset of cognitive decline. The underpinnings of cognitive reserve remain poorly understood, although a shared genetic basis between measures of cognitive reserve and Alzheimer's disease has been suggested. Using the largest samples to date and novel statistical tools, we aimed to investigate shared genetic variants between Alzheimer's disease, and measures of cognitive reserve; cognition and educational attainment to identify molecular and neurobiological foundations. We applied the causal mixture model (MiXeR) to estimate the number of trait-influencing variants shared between Alzheimer's disease, cognition, and educational attainment, and condFDR/conjFDR to identify shared loci. To provide biological insights loci were functionally characterized. Subsequently, we constructed a Structural Equation Model (SEM) to determine if the polygenic foundation of cognition has a direct impact on Alzheimer's disease risk, or if its effect is mediated through established risk factors for the disease, using a case-control sample from the UK Biobank. Univariate MiXeR analysis (after excluding chromosome 19) revealed that Alzheimer's disease was substantially less polygenic (450 trait-influencing variants) compared to cognition (11,100 trait-influencing variants), and educational attainment (12,700 trait-influencing variants). Bivariate MiXeR analysis estimated that Alzheimer's disease shared approximately 70 % of trait-influencing variants with cognition, and approximately 40 % with educational attainment, with mixed effect directions. Using condFDR analysis, we identified 18 loci jointly associated with Alzheimer's disease and cognition and 6 loci jointly associated with Alzheimer's disease and educational attainment. Genes mapped to shared loci were associated with neurodevelopment, expressed in early life, and implicated the dendritic tree and phosphatidylinositol phosphate binding mechanisms. Spatiotemporal gene expression analysis of the identified genes showed that mapped genes were highly expressed during the mid-fetal period, further suggesting early neurodevelopmental stages as critical periods for establishing cognitive reserve which affect the risk of Alzheimer's disease in old age. Furthermore, our SEM analysis showed that genetic variants influencing cognition had a direct effect on the risk of developing Alzheimer's disease, providing evidence in support of the neurodevelopmental hypothesis of the disease.

The shared genetic landscape of polycystic ovary syndrome and breast cancer: convergence on ER + breast cancer but not ER- breast cancer

BACKGROUND

The clinically high comorbidity between polycystic ovary syndrome (PCOS) and breast cancer (BC) has been extensively reported. However, limited knowledge exists regarding their shared genetic basis and underlying mechanisms.

METHOD

Leveraging summary statistics from the largest genome-wide association studies (GWASs) to date, we conducted a comprehensive genome-wide cross-trait analysis of PCOS and BC. A variety of genetic statistical methods were employed to uncover potential shared genetic causes.

RESULTS

Our analysis revealed genetic overlap between the three trait pairs. After partitioning the genome into 2,495 independent regions, we identified two loci, chr8: 75,011,700-76,295,483 and chr17: 6,305,079-7,264,458, with significant localized genetic correlations. Pleiotropic analysis under a composite null hypothesis identified 1,183 significant pleiotropic single nucleotide polymorphisms (SNPs) across three trait pairs. FUMA mapped 26 pleiotropic loci, with regions 16q12.2 and 6q25.1 duplicated across all three trait pairs, while COLOC detected three loci with colocalization evidence. Gene-based analysis identified 23 unique candidate pleiotropic genes, including the FTO shared by all trait pairs, as well as SER1, RALB, and others in two trait pairs. Pathway enrichment analysis further highlighted key biological pathways, primarily involving the significant biological pathways were the metabolism of regulation of autophagy, regulation of cellular catabolic process, and positive regulation of catabolic process. Latent Heritable Confounder Mendelian randomization (LHC-MR) supported a positive causal relationship between PCOS and both BCALL and ERPBC but not with ERNBC.

CONCLUSION

In conclusion, our genome-wide cross-trait analysis identified a shared genetic basis between PCOS and BC, specific identical genetic mechanisms and causality between PCOS and various BC subtypes, which could better explains the genetics of the co-morbidity of PCOS and ERPBC rather than PCOS and ERNBC. These findings provide new insights into the biological mechanisms underlying the co-morbidity of these two complex diseases, which have important implications for clinical disease intervention, treatment, and improved prognosis.

Genetic overlap between Alzheimer's disease and immune-mediated diseases: an atlas of shared genetic determinants and biological convergence

The occurrence of immune disease comorbidities in Alzheimer's disease (AD) has been observed in both epidemiological and molecular studies, suggesting a neuroinflammatory basis in AD. However, their shared genetic components have not been systematically studied. Here, we composed an atlas of the shared genetic associations between 11 immune-mediated diseases and AD by analyzing genome-wide association studies (GWAS) summary statistics. Our results unveiled a significant genetic overlap between AD and 11 individual immune-mediated diseases despite negligible genetic correlations, suggesting a complex shared genetic architecture distributed across the genome. The shared loci between AD and immune-mediated diseases implicated several genes, including GRAMD1B, FUT2, ADAMTS4, HBEGF, WNT3, TSPAN14, DHODH, ABCB9, and TNIP1, all of which are protein-coding genes and thus potential drug targets. Top biological pathways enriched with these identified shared genes were related to the immune system and cell adhesion. In addition, in silico single-cell analyses showed enrichment of immune and brain cells, including neurons and microglia. In summary, our results suggest a genetic relationship between AD and the 11 immune-mediated diseases, pinpointing the existence of a shared however non-causal genetic basis. These identified protein-coding genes have the potential to serve as a novel path to therapeutic interventions for both AD and immune-mediated diseases and their comorbidities.

Inflammatory bowel disease and rheumatoid arthritis share a common genetic structure

Background

The comorbidity rate of inflammatory bowel disease (IBD) and rheumatoid arthritis (RA) is high; nevertheless, the reasons behind this high rate remain unclear. Their similar genetic makeup probably contributes to this comorbidity.

Methods

Based on data obtained from the genome-wide association study of IBD and RA, we first assessed an overall genetic association by performing the linkage disequilibrium score regression (LDSC) analysis. Further, a local correlation analysis was performed by estimating the heritability in summary statistics. Next, the causality between the two diseases was analyzed by two-sample Mendelian randomization (MR). A genetic overlap was analyzed by the conditional/conjoint false discovery rate (cond/conjFDR) method.LDSC with specific expression of gene analysis was performed to identify related tissues between the two diseases. Finally, GWAS multi-trait analysis (MTAG) was also carried out.

Results

IBD and RA are correlated at the genomic level, both overall and locally. The MR results suggested that IBD induced RA. We identified 20 shared loci between IBD and RA on the basis of a conjFDR of <0.01. Additionally, we identified two tissues, namely spleen and small intestine terminal ileum, which were commonly associated with both IBD and RA.

Conclusion

Herein, we proved the presence of a polygenic overlap between the genetic makeup of IBD and RA and provided new insights into the genetic architecture and mechanisms underlying the high comorbidity between these two diseases.

Reduced GLP-1R availability in the caudate nucleus with Alzheimer's disease

The glucagon-like peptide-1 receptor (GLP-1R) agonists reduce glycated hemoglobin in patients with type 2 diabetes. Mounting evidence indicates that the potential of GLP-1R agonists, mimicking a 30 amino acid ligand, GLP-1, extends to the treatment of neurodegenerative conditions, with a particular focus on Alzheimer's disease (AD). However, the mechanism that underlies regulation of GLP-1R availability in the brain with AD remains poorly understood. Here, using whole transcriptome RNA-Seq of the human postmortem caudate nucleus with AD and chronic hydrocephalus (CH) in the elderly, we found that GLP-1R and select mRNAs expressed in glucose dysmetabolism and dyslipidemia were significantly altered. Furthermore, we detected human RNA indicating a deficiency in doublecortin (DCX) levels and the presence of ferroptosis in the caudate nucleus impacted by AD. Using the genome data viewer, we assessed mutability of GLP-1R and 39 other genes by two factors associated with high mutation rates in chromosomes of four species. Surprisingly, we identified that nucleotide sizes of GLP-1R transcript exceptionally differed in all four species of humans, chimpanzees, rats, and mice by up to 6-fold. Taken together, the protein network database analysis suggests that reduced GLP-1R in the aged human brain is associated with glucose dysmetabolism, ferroptosis, and reduced DCX+ neurons, that may contribute to AD.

Evidence for the gut-skin axis: Common genetic structures in inflammatory bowel disease and psoriasis

BACKGROUND

Inflammatory bowel disease (IBD) and psoriasis (Ps) are common immune-mediated diseases that exhibit clinical comorbidity, possibly due to a common genetic structure. However, the exact mechanism remains unknown.

METHODS

The study population consisted of IBD and Ps genome-wide association study (GWAS) data. Genetic correlations were first evaluated. Then, the overall evaluation employed LD score regression (LDSC), while the local assessment utilized heritability estimation from summary statistics (HESS). Causality assessment was conducted through two-sample Mendelian randomization (2SMR), and genetic overlap analysis utilized the conditional false discovery rate/conjunctional FDR (cond/conjFDR) method. Finally, LDSC applied to specifically expressed genes (LDSC-SEG) was performed at the tissue level. For IBD and Ps-specific expressed genes, genetic correlation, causality, shared genetics, and trait-specific associated tissues were methodically examined.

RESULTS

At the genomic level, both overall and local genetic correlations were found between IBD and Ps. MR analysis indicated a positive causal relationship between Ps and IBD. The conjFDR analysis with a threshold of < 0.01 identified 43 loci shared between IBD and Ps. Subsequent investigations into disease-associated tissues indicated a close association of IBD and Ps with whole blood, lung, spleen, and EBV-transformed lymphocytes.

CONCLUSION

The current research offers a novel perspective on the association between IBD and Ps. It contributes to an enhanced comprehension of the genetic structure and mechanisms of comorbidities in both diseases.

Herpesviridae, Neurodegenerative Disorders and Autoimmune Diseases: What Is the Relationship between Them?

Alzheimer's disease and Parkinson's disease represent the most common forms of cognitive impairment. Multiple sclerosis is a chronic inflammatory disease of the central nervous system responsible for severe disability. An aberrant immune response is the cause of myelin destruction that covers axons in the brain, spinal cord, and optic nerves. Systemic lupus erythematosus is an autoimmune disease characterized by alteration of B cell activation, while Sjögren's syndrome is a heterogeneous autoimmune disease characterized by altered immune responses. The etiology of all these diseases is very complex, including an interrelationship between genetic factors, principally immune associated genes, and environmental factors such as infectious agents. However, neurodegenerative and autoimmune diseases share proinflammatory signatures and a perturbation of adaptive immunity that might be influenced by herpesviruses. Therefore, they might play a critical role in the disease pathogenesis. The aim of this review was to summarize the principal findings that link herpesviruses to both neurodegenerative and autoimmune diseases; moreover, briefly underlining the potential therapeutic approach of virus vaccination and antivirals.

Interpretation of Neurodegenerative GWAS Risk Alleles in Microglia and their Interplay with Other Cell Types

Microglia have been implicated in numerous neurodegenerative and neuroinflammatory disorders; however, the causal contribution of this immune cell type is frequently debated. Genetic studies offer a unique vantage point in that they infer causality over a secondary consequence. Genome-wide association studies (GWASs) have identified hundreds of loci in the genome that are associated with susceptibility to neurodegenerative disorders. GWAS studies implicate microglia in the pathogenesis of Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), and to a lesser degree suggest a role for microglia in vascular dementia (VaD), frontotemporal dementia (FTD), and amyotrophic lateral sclerosis (ALS), and other neurodegenerative and neuropsychiatric disorders. The contribution and function of GWAS risk loci on disease progression is an ongoing field of study, in which large genomic datasets, and an extensive framework of computational tools, have proven to be crucial. Several GWAS risk loci are shared between disorders, pointing towards common pleiotropic mechanisms. In this chapter, we introduce key concepts in GWAS and post-GWAS interpretation of neurodegenerative disorders, with a focus on GWAS risk genes implicated in microglia, their interplay with other cell types and shared convergence of GWAS risk loci on microglia.

Genetic overlap between Alzheimer's disease and immune-mediated diseases: An atlas of shared genetic determinants and biological convergence

The occurrence of immune disease comorbidities in Alzheimer's disease (AD) has been observed in both epidemiological and molecular studies, suggesting a neuroinflammatory basis in AD. However, their shared genetic components have not been systematically studied. Here, we composed an atlas of the shared genetic associations between 11 immune-mediated diseases and AD by analyzing genome-wide association studies (GWAS) summary statistics. Our results unveiled a significant genetic overlap between AD and 11 individual immune-mediated diseases despite negligible genetic correlations, suggesting a complex shared genetic architecture distributed across the genome. The shared loci between AD and immune-mediated diseases implicated several genes, including GRAMD1B, FUT2, ADAMTS4, HBEGF, WNT3, TSPAN14, DHODH, ABCB9 and TNIP1, all of which are protein-coding genes and thus potential drug targets. Top biological pathways enriched with these identified shared genes were related to the immune system and cell adhesion. In addition, in silico single-cell analyses showed enrichment of immune and brain cells, including neurons and microglia. In summary, our results suggest a genetic relationship between AD and the 11 immune-mediated diseases, pinpointing the existence of a shared however non-causal genetic basis. These identified protein-coding genes have the potential to serve as a novel path to therapeutic interventions for both AD and immune-mediated diseases and their comorbidities.