Causal association evaluation of diabetes with Alzheimer's disease and genetic analysis of antidiabetic drugs against Alzheimer's disease

True or false? Alzheimer's disease is type 3 diabetes: Evidences from bench to bedside

Globally, Alzheimer's disease (AD) is the most widespread chronic neurodegenerative disorder, leading to cognitive impairment, such as aphasia and agnosia, as well as mental symptoms, like behavioral abnormalities, that place a heavy psychological and financial burden on the families of the afflicted. Unfortunately, no particular medications exist to treat AD, as the current treatments only impede its progression.The link between AD and type 2 diabetes (T2D) has been increasingly revealed by research; the danger of developing both AD and T2D rises exponentially with age, with T2D being especially prone to AD. This has propelled researchers to investigate the mechanism(s) underlying this connection. A critical review of the relationship between insulin resistance, Aβ, oxidative stress, mitochondrial hypothesis, abnormal phosphorylation of Tau protein, inflammatory response, high blood glucose levels, neurotransmitters and signaling pathways, vascular issues in AD and diabetes, and the similarities between the two diseases, is presented in this review. Grasping the essential mechanisms behind this detrimental interaction may offer chances to devise successful therapeutic strategies.

Behavioral and Metabolic Effects of ABCG4 KO in the APPswe,Ind (J9) Mouse Model of Alzheimer's Disease

The pathogenesis of Alzheimer's disease (AD) is complex and involves an imbalance between production and clearance of amyloid-ß peptides (Aß), resulting in accumulation of Aß in senile plaques. Hypercholesterolemia is a major risk factor for developing AD, with cholesterol shown to accumulate in senile plaques and increase production of Aß. ABCG4 is a member of the ATP-binding cassette transporters predominantly expressed in the CNS and has been suggested to play a role in cholesterol and Aß efflux from the brain. In this study, we bred Abcg4 knockout (KO) with the APPSwe,Ind (J9) mouse model of AD to test the hypothesis that loss of Abcg4 would exacerbate the AD phenotype. Unexpectedly, no differences were observed in novel object recognition (NOR) and novel object placement (NOP) behavioral tests, or on histologic examinations of brain tissues for senile plaque numbers. Furthermore, clearance of radiolabeled Aß from the brains did not differ between Abcg4 KO and control mice. Metabolic testing by indirect calorimetry, glucose tolerance test (GTT), and insulin tolerance test (ITT) were also mostly similar between groups with only a few mild metabolic differences noted. Overall, these data suggest that the loss of ABCG4 did not exacerbate the AD phenotype.

Dementia prevention: the Mendelian randomisation perspective

Understanding the causes of Alzheimer's disease and related dementias remains a challenge. Observational studies investigating dementia risk factors are limited by the pervasive issues of confounding, reverse causation and selection biases. Conducting randomised controlled trials for dementia prevention is often impractical due to the long prodromal phase and the inability to randomise many potential risk factors. In this essay, we introduce Mendelian randomisation as an alternative approach to examine factors that may prevent or delay Alzheimer's disease. Mendelian randomisation is a causal inference method that has successfully identified risk factors and treatments in various other fields. However, applying this method to dementia risk factors has yielded unexpected findings. Here, we consider five potential explanations and provide recommendations to enhance causal inference from Mendelian randomisation studies on dementia. By employing these strategies, we can better understand factors affecting dementia risk.

The landscape of the methodology in drug repurposing using human genomic data: a systematic review

The process of drug development is expensive and time-consuming. In contrast, drug repurposing can be introduced to clinical practice more quickly and at a reduced cost. Over the last decade, there has been a significant expansion of large biobanks that link genomic data to electronic health record data, public availability of various databases containing biological and clinical information and rapid development of novel methodologies and algorithms in integrating different sources of data. This review aims to provide a thorough summary of different strategies that utilize genomic data to seek drug-repositioning opportunities. We searched MEDLINE and EMBASE databases to identify eligible studies up until 1 May 2023, with a total of 102 studies finally included after two-step parallel screening. We summarized commonly used strategies for drug repurposing, including Mendelian randomization, multi-omic-based and network-based studies and illustrated each strategy with examples, as well as the data sources implemented. By leveraging existing knowledge and infrastructure to expedite the drug discovery process and reduce costs, drug repurposing potentially identifies new therapeutic uses for approved drugs in a more efficient and targeted manner. However, technical challenges when integrating different types of data and biased or incomplete understanding of drug interactions are important hindrances that cannot be disregarded in the pursuit of identifying novel therapeutic applications. This review offers an overview of drug repurposing methodologies, providing valuable insights and guiding future directions for advancing drug repurposing studies.

Identification of potential biomarkers and therapeutic targets related to post-traumatic stress disorder due to traumatic brain injury

BACKGROUND

Post-traumatic stress disorder (PTSD), a disease state that has an unclear pathogenesis, imposes a substantial burden on individuals and society. Traumatic brain injury (TBI) is one of the most significant triggers of PTSD. Identifying biomarkers associated with TBI-related PTSD will help researchers to uncover the underlying mechanism that drives disease development. Furthermore, it remains to be confirmed whether different types of traumas share a common mechanism of action.

METHODS

For this study, we screened the eligible data sets from the Gene Expression Omnibus (GEO) database, obtained differentially expressed genes (DEGs) through analysis, conducted functional enrichment analysis on the DEGs in order to understand their molecular mechanisms, constructed a PPI network, used various algorithms to obtain hub genes, and finally evaluated, validated, and analyzed the diagnostic performance of the hub genes.

RESULTS

A total of 430 upregulated and 992 down-regulated differentially expressed genes were extracted from the TBI data set. A total of 1919 upregulated and 851 down-regulated differentially expressed genes were extracted from the PTSD data set. Functional enrichment analysis revealed that the differentially expressed genes had biological functions linked to molecular regulation, cell signaling transduction, cell metabolic regulation, and immune response. After constructing a PPI network and introducing algorithm analysis, the upregulated hub genes were identified as VNN1, SERPINB2, and ETFDH, and the down-regulated hub genes were identified as FLT3LG, DYRK1A, DCN, and FKBP8. In addition, by comparing the data with patients with other types of trauma, it was revealed that PTSD showed different molecular processes that are under the influence of different trauma characteristics and responses.

CONCLUSIONS

By exploring the role of different types of traumas during the pathogenesis of PTSD, its possible molecular mechanisms have been revealed, providing vital information for understanding the complex pathways associated with TBI-related PTSD. The data in this study has important implications for the design and development of new diagnostic and therapeutic methods needed to treat and manage PTSD.

Genetic prediction of antihyperglycemic drug targets and risk of epilepsy: a mendelian randomisation study

A connection between diabetes and an increased risk of epilepsy has been suggested by observational studies. Animal studies have also shown that antihyperglycemic drugs can improve seizures. However, it is unclear whether antihyperglycemic drugs have a causal role in epilepsy in humans. To investigate this potential causal relationship, a Mendelian randomisation study was conducted using International League Against Epilepsy data as the discovery set and FinnGen data as the replication set. It was discovered that three antidiabetic drug target genes, ETFDH, CYP21A2 and CYP2D6, were involved in the occurrence of epilepsy. In particular, ETFDH was identified as a target gene in both the discovery set (inverse variance weighting [IVW], odds ratio [OR] = 1.018, 95% confidence interval [CI], 1.004-1.033, p = 0.009) and replication set (IVW, OR = 1.074, 95% CI, 1.034-1.114, p = 0.00016), and CYP21A2 was identified in the discovery set (IVW, OR = 1.029, 95% CI, 1.005-1.053, p = 0.016) and replication set (IVW, OR = 1.057, 95% CI, 1.001-1.116, p = 0.045) as having a causal association with an increased risk of epilepsy. Conversely, the CYP2D6 gene was found to be a protective factor for epilepsy in both the discovery set (IVW, OR = 0.0984, 95% CI, 0.969-0.998, p = 0.025) and replication set (IVW, OR = 0.977, 95% CI, 0.955-1.000, p = 0.046). A search of DrugBank revealed that metformin, an anti-glucose drug, is an inhibitor of the ETFDH gene and may have a potential therapeutic effect on epilepsy.

Investigation of the causal relationship between osteocalcin and dementia: A Mendelian randomization study

Objective

Basic medical studies have reported an improved effect of osteocalcin on cognition. We explored the causal link between osteocalcin and dementia via the implementation of Mendelian randomization methodology.

Methods

Genome-wide association studies were employed to identify single nucleotide polymorphisms (SNPs) showing significant correlations with osteocalcin. Subsequently, A two-sample Mendelian randomization analysis was conducted utilizing the inverse-variance-weighted (IVW) technique to assess the causal relationship between osteocalcin and various types of dementia, including Alzheimer's disease (AD), Parkinson's disease (PD), Lewy body dementia (LBD), and vascular dementia (VD). This approach aimed to minimize potential sources of confounding bias and provide more robust results. Multivariable MR (MVMR) analysis was conducted to adjust for potential genetic pleiotropy.

Results

The study employed three SNPs, namely rs71631868, rs9271374, and rs116843408, as genetic tools to evaluate the causal association of osteocalcin with dementia. The IVW analysis indicated that osteocalcin may have a potential protective effect against AD with an odds ratio (OR) of 0.790 (95 % CI: 0.688-0.906; P < 0.001). However, no significant relationship was observed between osteocalcin and other types of dementia. Furthermore, the MVMR analysis indicated that the impact of osteocalcin on AD remained consistent even after adjusting for age-related macular degeneration and Type 2 diabetes with an OR of 0.856 (95 % CI: 0.744-0.985; P = 0.030).

Conclusions

Our findings provide important insights into the role of osteocalcin in the pathogenesis of AD. Future research is required to clarify the underlying mechanisms and their clinical applications.

Lower mortality risk in APOE4 carriers with normal cognitive ageing

Abnormal cognitive ageing, including dementia, poses serious challenges to health and social systems in ageing populations. As such, characterizing factors associated with abnormal cognitive ageing and developing needed preventive measures are of great importance. The ε4 allele of the Apolipoprotein E gene (APOE4) is a well-known genetic risk factor for late-onset Alzheimer's disease. APOE4 carriers are also at elevated risk of cardiovascular diseases which are associated with increased risk of cognitive impairment. On the other hand, APOE4 is known to be associated with reduced risk of multiple common types of cancer-a major age-related disease and leading cause of mortality. We conducted the first-ever study of APOE4's opposing effects on cognitive decline and mortality using competing risk models considering two types of death-death with high-amounts versus low-amounts of autopsy-assessed Alzheimer's neuropathology. We observed that APOE4 was associated with decreased mortality risk in people who died with low amounts of Alzheimer's-type neuropathology, but APOE4 was associated with increased mortality risk in people who died with high amounts of Alzheimer's-type neuropathology, a major risk factor of cognitive impairment. Possible preventive measures of abnormal cognitive ageing are also discussed.

Systems biology approaches to identify potential targets and inhibitors of the intestinal microbiota to treat depression

Depression is a common mental disease, with some patients exhibiting ideas and behaviors such as self-harm and suicide. The drugs currently used to treat depression have not achieved good results. It has been reported that metabolites produced by intestinal microbiota affect the development of depression. In this study, core targets and core compounds were screened by specific algorithms in the database, and three-dimensional structures of these compounds and proteins were simulated by molecular docking and molecular dynamics software to further study the influence of intestinal microbiota metabolites on the pathogenesis of depression. By analyzing the RMSD gyration radius and RMSF, it was finally determined that NR1H4 had the best binding effect with genistein. Finally, according to Lipinski's five rules, equol, genistein, quercetin and glycocholic acid were identified as effective drugs for the treatment of depression. In conclusion, the intestinal microbiota can affect the development of depression through the metabolites equol, genistein and quercetin, which act on the critical targets of DPP4, CYP3A4, EP300, MGAM and NR1H4.

Behavioral and metabolic and effects of ABCG4 KO in the APPswe,Ind (J9) mouse model of Alzheimer's disease

The pathogenesis of Alzheimer's disease (AD) is complex and involves an imbalance between production and clearance of amyloid-ß peptides (Aß), resulting in accumulation of Aß in senile plaques. Hypercholesterolemia is a major risk factor for developing AD, with cholesterol shown to accumulate in senile plaques and increase production of Aß. ABCG4 is a member of the ATP-binding cassette transporters predominantly expressed in the CNS, and has been suggested to play a role in cholesterol and Aß efflux from the brain. In this study, we bred Abcg4 knockout (KO) with the APPSwe,Ind (J9) mouse model of AD to test the hypothesis that loss of Abcg4 would exacerbate the AD phenotype. Unexpectedly, no differences were observed in Novel object recognition (NOR) and Novel object placement (NOP) behavioral tests, or on histologic examinations of brain tissues for senile plaque numbers. Furthermore, clearance of radiolabeled Aß from the brains did not differ between Abcg4 KO and control mice. Metabolic testing by indirect calorimetry, glucose tolerance test (GTT) and insulin tolerance test (ITT), were also mostly similar between groups with only a few mild metabolic differences noted. Overall these data suggest that the loss of ABCG4 did not exacerbate the AD phenotype.

Causal Effects of Plasma Haptoglobin Levels on Alzheimer's Disease: A Two-Sample Mendelian Randomization Study

BACKGROUND

A connection between plasma levels of haptoglobin (Hp) and Alzheimer's disease (AD) has been shown in several observational studies. It is debatable, nonetheless, how the two are related causally.

OBJECTIVE

To establish the causal relationship between Hp and AD using a two-sample Mendelian randomization (MR) study.

METHODS

From the extensive genome-wide association studies and FinnGen dataset, summaries and statistics pertaining to AD were gathered. We investigated the possibility of a causal link between Hp and AD using a two-sample MR study. Inverse variance weighting was used as the primary analytical technique, and it was supported by the joint application of complementary analyses and fixed effects meta-analysis to combine results from various sources.

RESULTS

Genetically determined Hp was causally associated with AD [odds ratio (OR), 1.05; 95% confidence interval (CI), 1.02 to 1.09; p = 8.96×10-4]; Inverse variance-weighted estimates coming from different data sources were combined in a meta-analysis with consistent findings (OR, 1.03; 95% CI, 1.01 to 1.05; p = 2.00×10-3). The outcomes of the inverse MR analysis showed that AD had no appreciable causal impact on Hp.

CONCLUSION

The present MR analysis shows that higher plasma Hp leads to an increased risk of AD. Strategies for plasma Hp testing may open up new doors for the early diagnosis and prevention of AD.

Prevailing Antagonistic Risks in Pleiotropic Associations with Alzheimer's Disease and Diabetes

BACKGROUND

The lack of efficient preventive interventions against Alzheimer's disease (AD) calls for identifying efficient modifiable risk factors for AD. As diabetes shares many pathological processes with AD, including accumulation of amyloid plaques and neurofibrillary tangles, insulin resistance, and impaired glucose metabolism, diabetes is thought to be a potentially modifiable risk factor for AD. Mounting evidence suggests that links between AD and diabetes may be more complex than previously believed.

OBJECTIVE

To examine the pleiotropic architecture of AD and diabetes mellitus (DM).

METHODS

Univariate and pleiotropic analyses were performed following the discovery-replication strategy using individual-level data from 10 large-scale studies.

RESULTS

We report a potentially novel pleiotropic NOTCH2 gene, with a minor allele of rs5025718 associated with increased risks of both AD and DM. We confirm previously identified antagonistic associations of the same variants with the risks of AD and DM in the HLA and APOE gene clusters. We show multiple antagonistic associations of the same variants with AD and DM in the HLA cluster, which were not explained by the lead SNP in this cluster. Although the ɛ2 and ɛ4 alleles played a major role in the antagonistic associations with AD and DM in the APOE cluster, we identified non-overlapping SNPs in this cluster, which were adversely and beneficially associated with AD and DM independently of the ɛ2 and ɛ4 alleles.

CONCLUSION

This study emphasizes differences and similarities in the heterogeneous genetic architectures of AD and DM, which may differentiate the pathogenic mechanisms of these diseases.

Multi-context genetic modeling of transcriptional regulation resolves novel disease loci

A majority of the variants identified in genome-wide association studies fall in non-coding regions of the genome, indicating their mechanism of impact is mediated via gene expression. Leveraging this hypothesis, transcriptome-wide association studies (TWAS) have assisted in both the interpretation and discovery of additional genes associated with complex traits. However, existing methods for conducting TWAS do not take full advantage of the intra-individual correlation inherently present in multi-context expression studies and do not properly adjust for multiple testing across contexts. We introduce CONTENT-a computationally efficient method with proper cross-context false discovery correction that leverages correlation structure across contexts to improve power and generate context-specific and context-shared components of expression. We apply CONTENT to bulk multi-tissue and single-cell RNA-seq data sets and show that CONTENT leads to a 42% (bulk) and 110% (single cell) increase in the number of genetically predicted genes relative to previous approaches. We find the context-specific component of expression comprises 30% of heritability in tissue-level bulk data and 75% in single-cell data, consistent with cell-type heterogeneity in bulk tissue. In the context of TWAS, CONTENT increases the number of locus-phenotype associations discovered by over 51% relative to previous methods across 22 complex traits.