Mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed Alzheimer's disease GWAS and self-report proxy phenotype GWAX

Lycopene: A Potent Antioxidant with Multiple Health Benefits

Lycopene is a naturally occurring carotenoid predominantly found in tomatoes and tomato-based products. Like other phytochemicals, it exhibits health beneficial biological activities that can be exploited when it is used as a dietary supplement. In vitro and in vivo, lycopene has been demonstrated to mitigate oxidative stress-induced metabolic dysfunctions and diseases including inflammation, obesity, and diabetes mellitus. Lycopene has been shown to alleviate metabolic diseases that affect the bone, eye, kidney, liver, lungs, heart, and nervous system. This review presents the state of the art regarding lycopene's health benefits and its potential applications in health system delivery. Furthermore, lycopene's protective effects against toxins, safety in its use, and possible toxicity are explored.

Interpretation of 10 years of Alzheimer's disease genetic findings in the perspective of statistical heterogeneity

Common genetic variants and susceptibility loci associated with Alzheimer's disease (AD) have been discovered through large-scale genome-wide association studies (GWAS), GWAS by proxy (GWAX) and meta-analysis of GWAS and GWAX (GWAS+GWAX). However, due to the very low repeatability of AD susceptibility loci and the low heritability of AD, these AD genetic findings have been questioned. We summarize AD genetic findings from the past 10 years and provide a new interpretation of these findings in the context of statistical heterogeneity. We discovered that only 17% of AD risk loci demonstrated reproducibility with a genome-wide significance of P < 5.00E-08 across all AD GWAS and GWAS+GWAX datasets. We highlighted that the AD GWAS+GWAX with the largest sample size failed to identify the most significant signals, the maximum number of genome-wide significant genetic variants or maximum heritability. Additionally, we identified widespread statistical heterogeneity in AD GWAS+GWAX datasets, but not in AD GWAS datasets. We consider that statistical heterogeneity may have attenuated the statistical power in AD GWAS+GWAX and may contribute to explaining the low repeatability (17%) of genome-wide significant AD susceptibility loci and the decreased AD heritability (40-2%) as the sample size increased. Importantly, evidence supports the idea that a decrease in statistical heterogeneity facilitates the identification of genome-wide significant genetic loci and contributes to an increase in AD heritability. Collectively, current AD GWAX and GWAS+GWAX findings should be meticulously assessed and warrant additional investigation, and AD GWAS+GWAX should employ multiple meta-analysis methods, such as random-effects inverse variance-weighted meta-analysis, which is designed specifically for statistical heterogeneity.

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.

Life course plasma metabolomic signatures of genetic liability to Alzheimer's disease

Mechanisms through which most known Alzheimer's disease (AD) loci operate to increase AD risk remain unclear. Although Apolipoprotein E (APOE) is known to regulate lipid homeostasis, the effects of broader AD genetic liability on non-lipid metabolites remain unknown, and the earliest ages at which metabolic perturbations occur and how these change over time are yet to be elucidated. We examined the effects of AD genetic liability on the plasma metabolome across the life course. Using a reverse Mendelian randomization framework in two population-based cohorts [Avon Longitudinal Study of Parents and Children (ALSPAC, n = 5648) and UK Biobank (n ≤ 118,466)], we estimated the effects of genetic liability to AD on 229 plasma metabolites, at seven different life stages, spanning 8 to 73 years. We also compared the specific effects of APOE ε4 and APOE ε2 carriage on metabolites. In ALSPAC, AD genetic liability demonstrated the strongest positive associations with cholesterol-related traits, with similar magnitudes of association observed across all age groups including in childhood. In UK Biobank, the effect of AD liability on several lipid traits decreased with age. Fatty acid metabolites demonstrated positive associations with AD liability in both cohorts, though with smaller magnitudes than lipid traits. Sensitivity analyses indicated that observed effects are largely driven by the strongest AD instrument, APOE, with many contrasting effects observed on lipids and fatty acids for both ε4 and ε2 carriage. Our findings indicate pronounced effects of the ε4 and ε2 genetic variants on both pro- and anti-atherogenic lipid traits and sphingomyelins, which begin in childhood and either persist into later life or appear to change dynamically.

Assessing the validity of a self-reported clinical diagnosis of schizophrenia

Background

Diagnoses in psychiatric research can be derived from various sources. This study assesses the validity of a self-reported clinical diagnosis of schizophrenia.

Methods

The study included 3,029 clinically ascertained participants with schizophrenia or psychotic disorders diagnosed by self-report and/or research interview and 1,453 UK Biobank participants with self-report and/or medical record diagnosis of schizophrenia or schizoaffective disorder depressed-type (SA-D). We assessed positive predictive values (PPV) of self-reported clinical diagnoses against research interview and medical record diagnoses. We compared polygenic risk scores (PRS) and phenotypes across diagnostic groups, and compared the variance explained by schizophrenia PRS to samples in the Psychiatric Genomics Consortium (PGC).

Results

In the clinically ascertained sample, the PPV of self-reported schizophrenia to a research diagnosis of schizophrenia was 0.70, which increased to 0.81 when benchmarked against schizophrenia or SA-D. In UK Biobank, the PPV of self-reported schizophrenia to a medical record diagnosis was 0.74. Compared to self-report participants, those with a research diagnosis were younger and more likely to have a high school qualification (clinically ascertained sample) and those with a medical record diagnosis were less likely to be employed or have a high school qualification (UK Biobank). Schizophrenia PRS did not differ between participants that had a diagnosis from self-report, research diagnosis or medical record diagnosis. Polygenic liability r2, for all diagnosis definitions, fell within the distribution of PGC schizophrenia cohorts.

Conclusions

Self-report measures of schizophrenia are justified in research to maximise sample size and representativeness, although within sample validation of diagnoses is recommended.

Unraveling genetic causality between type 2 diabetes and pulmonary tuberculosis on the basis of Mendelian randomization

BACKGROUND

The comorbidity rate between type 2 diabetes mellitus (T2DM) and pulmonary tuberculosis (PTB) is high and imposes enormous strains on healthcare systems. However, whether T2DM is causally associated with PTB is unknown owing to limited evidence from prospective studies. Consequently, the present study aimed to clarify the genetic causality between T2DM and PTB on the basis of Mendelian randomization (MR) analysis.

METHODS

Genetic variants for T2DM and PTB were obtained from the IEU OpenGWAS project. The inverse variance weighted method was used as the main statistical analysis method and was supplemented with MR-Egger, weighted median, simple mode, and weighted mode methods. Heterogeneity was analyzed using Cochran's Q statistic. Horizontal pleiotropy was assessed using the MR-PRESSO global test and MR-Egger regression. Robustness of the results was verified using the leave-one-out method.

RESULTS

A total of 152 independent single-nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs) to assess the genetic causality between T2DM and PTB. Patients with T2DM had a higher risk of PTB at the genetic level (odds ratio (OR) for MR-Egger was 1.550, OR for weighted median was 1.540, OR for inverse variance weighted was 1.191, OR for simple mode was 1.629, OR for weighted mode was 1.529). There was no horizontal pleiotropy or heterogeneity among IVs. The results were stable when removing the SNPs one by one.

CONCLUSIONS

This is the first comprehensive MR analysis that revealed the genetic causality between T2DM and PTB in the East Asian population. The study provides convincing evidence that individuals with T2DM have a higher risk of developing PTB at the genetic level. This offers a significant basis for joint management of concurrent T2DM and PTB in clinical practice.

Systematic druggable genome-wide Mendelian randomisation identifies therapeutic targets for Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is the leading cause of dementia. Currently, there are no effective disease-modifying treatments for AD. Mendelian randomisation (MR) has been widely used to repurpose licensed drugs and discover novel therapeutic targets. Thus, we aimed to identify novel therapeutic targets for AD and analyse their pathophysiological mechanisms and potential side effects.

METHODS

A two-sample MR integrating the identified druggable genes was performed to estimate the causal effects of blood and brain druggable expression quantitative trait loci (eQTLs) on AD. A repeat study was conducted using different blood and brain eQTL data sources to validate the identified genes. Using AD markers with available genome-wide association studies data, we evaluated the causal relationship between established AD markers to explore possible mechanisms. Finally, the potential side effects of the druggable genes for AD treatment were assessed using a phenome-wide MR.

RESULTS

Overall, 5883 unique druggable genes were aggregated; 33 unique potential druggable genes for AD were identified in at least one dataset (brain or blood), and 5 were validated in a different dataset. Among them, three prior druggable genes (epoxide hydrolase 2 (EPHX2), SERPINB1 and SIGLEC11) reached significant levels in both blood and brain tissues. EPHX2 may mediate the pathogenesis of AD by affecting the entire hippocampal volume. Further phenome-wide MR analysis revealed no potential side effects of treatments targeting EPHX2, SERPINB1 or SIGLEC11.

CONCLUSIONS

This study provides genetic evidence supporting the potential therapeutic benefits of targeting the three druggable genes for AD treatment, which will be useful for prioritising AD drug development.

Pervasive biases in proxy GWAS based on parental history of Alzheimer's disease

Almost every recent Alzheimer's disease (AD) genome-wide association study (GWAS) has performed meta-analysis to combine studies with clinical diagnosis of AD with studies that use proxy phenotypes based on parental disease history. Here, we report major limitations in current GWAS-by-proxy (GWAX) practices due to uncorrected survival bias and non-random participation of parental illness survey, which cause substantial discrepancies between AD GWAS and GWAX results. We demonstrate that current AD GWAX provide highly misleading genetic correlations between AD risk and higher education which subsequently affects a variety of genetic epidemiologic applications involving AD and cognition. Our study sheds important light on the design and analysis of mid-aged biobank cohorts and underscores the need for caution when interpreting genetic association results based on proxy-reported parental disease history.

Genetic Associations Between Modifiable Risk Factors and Alzheimer Disease

Importance

An estimated 40% of dementia is potentially preventable by modifying 12 risk factors throughout the life course. However, robust evidence for most of these risk factors is lacking. Effective interventions should target risk factors in the causal pathway to dementia.

Objective

To comprehensively disentangle potentially causal aspects of modifiable risk factors for Alzheimer disease (AD) to inspire new drug targeting and improved prevention.

Design, Setting, and Participants

This genetic association study was conducted using 2-sample univariable and multivariable mendelian randomization. Independent genetic variants associated with modifiable risk factors were selected as instrumental variables from genomic consortia. Outcome data for AD were obtained from the European Alzheimer & Dementia Biobank (EADB), generated on August 31, 2021. Main analyses were conducted using the EADB clinically diagnosed end point data. All analyses were performed between April 12 and October 27, 2022.

Exposures

Genetically determined modifiable risk factors.

Main Outcomes and Measures

Odds ratios (ORs) and 95% CIs for AD were calculated per 1-unit change of genetically determined risk factors.

Results

The EADB-diagnosed cohort included 39 106 participants with clinically diagnosed AD and 401 577 control participants without AD. The mean age ranged from 72 to 83 years for participants with AD and 51 to 80 years for control participants. Among participants with AD, 54% to 75% were female, and among control participants, 48% to 60% were female. Genetically determined high-density lipoprotein (HDL) cholesterol concentrations were associated with increased odds of AD (OR per 1-SD increase, 1.10 [95% CI, 1.05-1.16]). Genetically determined high systolic blood pressure was associated with increased risk of AD after adjusting for diastolic blood pressure (OR per 10-mm Hg increase, 1.22 [95% CI, 1.02-1.46]). In a second analysis to minimize bias due to sample overlap, the entire UK Biobank was excluded from the EADB consortium; odds for AD were similar for HDL cholesterol (OR per 1-SD unit increase, 1.08 [95% CI, 1.02-1.15]) and systolic blood pressure after adjusting for diastolic blood pressure (OR per 10-mm Hg increase, 1.23 [95% CI, 1.01-1.50]).

Conclusions and Relevance

This genetic association study found novel genetic associations between high HDL cholesterol concentrations and high systolic blood pressure with higher risk of AD. These findings may inspire new drug targeting and improved prevention implementation.

Examining the Lancet Commission risk factors for dementia using Mendelian randomisation

BACKGROUND

Dementia incidence is increasing across the globe and currently there are no disease-modifying pharmaceutical treatments. The Lancet Commission on dementia identified 12 modifiable risk factors which explain 40% of dementia incidence. However, whether these associations are causal in nature is unclear.

OBJECTIVE

To examine the modifiable risk factors for dementia as identified in the Lancet Commission review using Mendelian randomisation (MR) to establish if, based on genetic evidence, these associations with different dementia subtypes are causal in nature.

METHODS

Publicly available genome-wide association study data were used for 10 risk factors and Alzheimer's disease (AD), frontotemporal dementia and dementia with Lewy bodies. Two-sample MR using the inverse varianceweighted method was conducted to test for causal relationships. Weighted median MR and MR-Egger were used to test for pleiotropic effects.

RESULTS

Genetic proxied risk for higher levels of smoking (OR: 0.80 (95% CI: 0.69; 0.92), p=0.002), obesity (OR: 0.87 (95% CI: 0.82; 0.92), p<0.001) and blood pressure (OR: 0.90 (95% CI: 0.82; 0.99), p=0.035) appeared to be protective against the risk of AD. Post hoc analyses indicated these associations had pleiotropic effects with the risk of coronary artery disease. Genetic proxied risk of educational attainment was found to be inconsistently associated with the risk of AD.

CONCLUSIONS AND IMPLICATIONS

Post hoc analysis indicated that the apparent protective effects of smoking, obesity and blood pressure were a result of survivor bias. The findings from this study did not support those presented by the Lancet Commission. Evidence from causal inference studies should be considered alongside evidence from epidemiological studies and incorporated into reviews of the literature.

Computational Studies Applied to Linalool and Citronellal Derivatives Against Alzheimer's and Parkinson's Disorders: A Review with Experimental Approach

Alzheimer's and Parkinson's are neurodegenerative disorders that affect a great number of people around the world, seriously compromising the quality of life of individuals, due to motor and cognitive damage. In these diseases, pharmacological treatment is used only to alleviate symptoms. This emphasizes the need to discover alternative molecules for use in prevention. Using Molecular Docking, this review aimed to evaluate the anti-Alzheimer's and anti-Parkinson's activity of linalool and citronellal, as well as their derivatives. Before performing Molecular Docking simulations, the compounds' pharmacokinetic characteristics were evaluated. For Molecular Docking, 7 chemical compounds derived from citronellal, and 10 compounds derived from linalool, and molecular targets involved in Alzheimer's and Parkinson's pathophysiology were selected. According to the Lipinski rules, the compounds under study presented good oral absorption and bioavailability. For toxicity, some tissue irritability was observed. For Parkinson-related targets, the citronellal and linalool derived compounds revealed excellent energetic affinity for α-Synuclein, Adenosine Receptors, Monoamine Oxidase (MAO), and Dopamine D1 receptor proteins. For Alzheimer disease targets, only linalool and its derivatives presented promise against BACE enzyme activity. The compounds studied presented high probability of modulatory activity against the disease targets under study, and are potential candidates for future drugs.

Cognitive performance protects against Alzheimer's disease independently of educational attainment and intelligence

Mendelian-randomization (MR) studies using large-scale genome-wide association studies (GWAS) have identified causal association between educational attainment and Alzheimer's disease (AD). However, the underlying mechanisms are still required to be explored. Here, we conduct univariable and multivariable MR analyses using large-scale educational attainment, cognitive performance, intelligence and AD GWAS datasets. In stage 1, we found significant causal effects of educational attainment on cognitive performance (beta = 0.907, 95% confidence interval (CI): 0.884-0.930, P < 1.145E-299), and vice versa (beta = 0.571, 95% CI: 0.557-0.585, P < 1.145E-299). In stage 2, we found that both increase in educational attainment (odds ratio (OR) = 0.72, 95% CI: 0.66-0.78, P = 1.39E-14) and cognitive performance (OR = 0.69, 95% CI: 0.64-0.75, P = 1.78E-20) could reduce the risk of AD. In stage 3, we found that educational attainment may protect against AD dependently of cognitive performance (OR = 1.07, 95% CI: 0.90-1.28, P = 4.48E-01), and cognitive performance may protect against AD independently of educational attainment (OR = 0.69, 95% CI: 0.53-0.89, P = 5.00E-03). In stage 4, we found significant causal effects of cognitive performance on intelligence (beta = 0.907, 95% CI: 0.877-0.938, P < 1.145E-299), and vice versa (beta = 0.957, 95% CI: 0.937-0.978, P < 1.145E-299). In stage 5, we identified that cognitive performance may protect against AD independently of intelligence (OR = 0.74, 95% CI: 0.61-0.90, P = 2.00E-03), and intelligence may protect against AD dependently of cognitive performance (OR = 1.17, 95% CI: 0.40-3.43, P = 4.48E-01). Collectively, our univariable and multivariable MR analyses highlight the protective role of cognitive performance in AD independently of educational attainment and intelligence. In addition to the intelligence, we extend the mechanisms underlying the associations of educational attainment with AD.

Mendelian randomization analysis of the causal association of bone mineral density and fracture with multiple sclerosis

Multiple sclerosis (MS) is a neurodegenerative disorder and an autoimmune disease. Until now, observational studies have indicated the association of bone mineral density (BMD) and fracture with the risk of MS. However, these studies indicated inconsistent findings. Until now, genome-wide association studies (GWAS) have been conducted in BMD, fracture, and MS, which provide large-scale datasets to investigate the causal association of BMD and fracture with the risk of MS using the Mendelian randomization (MR) study. Here, we performed an MR study to clarify the causal association between BMD/fracture and the risk of MS using large-scale publicly available GWAS datasets from BMD, fracture, and MS. We first evaluated the bidirectional causal effects of BMD and MS. The main analysis method inverse-variance weighted (IVW) showed no significant causal effect of BMD on the risk of MS (β = 0.058, and p = 1.98E-01), and MS on the risk of BMD (β = −0.001, and p = 7.83E-01). We then evaluated the bidirectional causal effects of fracture and MS. However, we only identified a significant causal effect of fracture on the risk of MS using IVW (β = −0.375, p = 0.002), but no significant causal effect of MS on the risk of the fracture using IVW (β = 0.011, p = 2.39E-01). Therefore, our main analysis method IVW only found a significant causal effect of fracture on MS using the threshold for the statistically significant association p < 0.05/4 = 0.0125. Meanwhile, multivariable MR analyses showed that the causal effect of fracture on MS was independent of smoking, drinking, and obesity, but dependent on BMD. In summary, our MR analysis demonstrates that genetically increased fracture may reduce the risk of MS. Our findings should be further verified and the underlying mechanisms should be further evaluated by future studies.

Evaluating the Bidirectional Causal Association Between Daytime Napping and Alzheimer’s Disease Using Mendelian Randomization

Background: Until now, both cross-sectional and longitudinal studies have identified controversial findings about the association between daytime napping and Alzheimer’s disease (AD) or cognitive decline. Therefore, it remains unclear about the causal association between daytime napping and AD or cognitive decline. Objective: We aim to investigate the causal association between daytime napping and AD. Methods: Here, we conduct a bidirectional Mendelian randomization (MR) analysis to investigate the causal association between daytime napping and AD using large-scale GWAS datasets from daytime napping including 452,633 individuals of European ancestry and AD including 35,274 AD and 59,163 controls of European ancestry. A total of five MR methods are selected including inverse-variance weighted (IVW), weighted median, MR-Egger, MR-PRESSO, and contamination mixture method. Results: MR analysis highlights significant causal association of AD with daytime napping using IVW (beta = -0.006, 95% CI [–0.009, –0.002], p = 2.00E-03), but no significant causal association of daytime napping with AD using IVW (OR = 0.76, 95% CI 0.53-1.10, p = 1.40E-01). Conclusion: Our bidirectional MR analysis demonstrates the causal effect of AD on daytime napping. However, there is no causal effect of daytime napping on AD. Our current findings are consistent with recent evidence from other MR studies that highlight little evidence supporting a causal effect of sleep traits on AD and support the causal effect of AD on sleep traits.

A Review of the Common Neurodegenerative Disorders: Current Therapeutic Approaches and the Potential Role of Nanotherapeutics

Neurodegenerative disorders are primarily characterized by neuron loss. The most common neurodegenerative disorders include Alzheimer’s and Parkinson’s disease. Although there are several medicines currently approved for managing neurodegenerative disorders, a large majority of them only help with associated symptoms. This lack of pathogenesis-targeting therapies is primarily due to the restrictive effects of the blood–brain barrier (BBB), which keeps close to 99% of all “foreign substances” out of the brain. Since their discovery, nanoparticles have been successfully used for targeted delivery into many organs, including the brain. This review briefly describes the pathophysiology of Alzheimer’s, Parkinson’s disease, and amyotrophic lateral sclerosis, and their current management approaches. We then highlight the major challenges of brain-drug delivery, followed by the role of nanotherapeutics for the diagnosis and treatment of various neurological disorders.

Parkinson's Disease rs117896735 Variant Regulates INPP5F Expression in Brain Tissues and Increases Risk of Alzheimer's Disease

BACKGROUND

Both INPP5D and INPP5F are members of INPP5 family. INPP5F rs117896735 variant was associated with Parkinson's disease (PD) risk, and INPP5D was an Alzheimer's disease (AD) risk gene. However, it remains unclear about the roles of INPP5F rs117896735 variant in AD.

OBJECTIVE

We aim to investigate the roles of rs117896735 in AD.

METHODS

First, we conducted a candidate variant study to evaluate the association of rs117896735 variant with AD risk using the large-scale AD GWAS dataset. Second, we conducted a gene expression analysis of INPP5F to investigate the expression difference of INPP5F in different human tissues using two large-scale gene expression datasets. Third, we conducted an expression quantitative trait loci analysis to evaluate whether rs117896735 variant regulate the expression of INPP5F. Fourth, we explore the potentially differential expression of INPP5F in AD and control using multiple AD-control gene expression datasets in human brain tissues and whole blood.

RESULTS

We found that 1) rs117896735 A allele was associated with the increased risk of AD with OR = 1.15, 95% CI 1.005-1.315, p = 0.042; 2) rs117896735 A allele could increase INPP5F expression in multiple human tissues; 3) INPP5F showed different expression in different human tissues, especially in brain tissues; 4) INPP5F showed significant expression dysregulation in AD compared with controls in human brain tissues.

CONCLUSION

Conclusion: We demonstrate that PD rs117896735 variant could regulate INPP5F expression in brain tissues and increase the risk of AD. These finding may provide important information about the role of rs117896735 in AD.