Educational attainment, structural brain reserve and Alzheimer's disease: a Mendelian randomization analysis

Genetic evidence for the causal impact of insomnia on gastrointestinal diseases and the mediating effects of adiposity traits

BACKGROUND AND AIM

Insomnia has been implicated in gastrointestinal diseases (GIs), but the causal effect between insomnia and GIs and underlying mechanisms remain unknown.

METHODS

By using the released summary-level data, we conducted a two-step Mendelian randomization (MR) analysis to examine the relationship between insomnia and four GIs and estimate the mediating role of candidate mediators. The first step was to investigate the causal association between insomnia and GIs using univariable MR analysis. The second step was to estimate the mediation proportion of selected mediators in these associations using multivariable MR analysis. Subsequently, results from different datasets were combined using the fixed-effect meta-analysis.

RESULTS

Univariable MR analysis provided strong evidence for the causal effects of insomnia on four GIs after Bonferroni correction for multiple comparisons, including peptic ulcer disease (PUD) (odds ratio [OR] = 1.15, 95% interval confidence [CI] = 1.10-1.20, P = 1.83 × 10-9), gastroesophageal reflux (GORD) (OR = 1.19, 95% CI = 1.16-1.22, P = 5.95 × 10-42), irritable bowel syndrome (IBS) (OR = 1.18, 95% CI = 1.15-1.22, P = 8.69 × 10-25), and inflammatory bowel disease (IBD) (OR = 1.09, 95% CI = 1.03-1.05, P = 3.46 × 10-3). In the mediation analysis, body mass index (BMI) and waist-to-hip ratio (WHR) were selected as mediators in the association between insomnia and PUD (BMI: mediation proportion [95% CI]: 13.61% [7.64%-20.70%]; WHR: 8.74% [5.50%-12.44%]) and GORD (BMI: 11.82% [5.94%-18.74%]; WHR: 7.68% [4.73%-11.12%]).

CONCLUSIONS

Our findings suggest that genetically instrumented insomnia has causal effects on PUD, GORD, IBS, and IBD, respectively. Adiposity traits partially mediated the associations between insomnia and GIs. Further clinical studies are warranted to evaluate the protective effect of insomnia treatment on GIs.

High bioavailable testosterone levels increase the incidence of isolated REM sleep behavior disorder: Results from multivariable and network Mendelian randomization analysis

OBJECTIVES

To explore the causal relationships between sex hormone levels and incidence of isolated REM sleep behavior disorder (iRBD).

METHODS

In our study, we utilized Genome-Wide Association Studies (GWAS) data for iRBD, including 9447 samples with 1061 cases of iRBD provided by the International RBD Study Group. Initially, we conducted a two-sample univariate MR analysis to explore the impact of sex hormone-related indicators on iRBD. This was followed by the application of multivariable MR methods to adjust for other hormone levels and potential confounders. Finally, we undertook a network MR analysis, employing brain structure Magnetic Resonance Imaging (MRI) characteristics as potential mediators, to examine whether sex hormones could indirectly influence the incidence of iRBD by affecting brain structure.

RESULTS

Bioavailable testosterone (BioT) is an independent risk factor for iRBD (Odds Ratio [95 % Confidence Interval] = 2.437 [1.308, 4.539], P = 0.005, corrected-P = 0.020), a finding that remained consistent even after adjusting for other sex hormone levels and potential confounders. Additionally, BioT appears to indirectly increase the risk of iRBD by reducing axial diffusivity and increasing the orientation dispersion index in the left cingulum and cingulate gyrus.

CONCLUSIONS

Our research reveals that elevated levels of BioT contribute to the development of iRBD. However, the specific impact of BioT on different sexes remains unclear. Furthermore, high BioT may indirectly lead to iRBD by impairing normal pathways in the left cingulum and cingulate gyrus and fostering abnormal pathway formation.

Type 2 diabetes, glycaemic traits, structural brain capacity and cognitive function: A Mendelian randomization analysis

AIM

To estimate the causal associations of type 2 diabetes and glycaemic traits with cognitive function, and to determine the potential mediating role of various brain imaging-derived phenotypes (IDPs) using Mendelian randomization (MR) analysis.

METHODS

Using publicly available summary data, we performed a series of univariable and multivariable MR analysis to infer causality. Two-step MR analysis was then conducted in turn to evaluate the potential mediating role of each brain IDP.

RESULTS

There was no evidence of causal associations between type 2 diabetes and cognitive function outcomes. Each 1-SD unit higher genetically predicted fasting proinsulin was associated with worse cognitive performance, as evidenced by both univariable (beta: -0.022; 95% confidence interval [CI] -0.038, -0.007) and multivariable MR analysis (beta: -0.027; 95% CI -0.048, -0.005). In addition, the univariable MR analysis identified several causal associations between fasting proinsulin and brain IDPs, and between brain IDPs and cognitive performance. The inverse association of genetically predicted fasting proinsulin with cognitive performance did not attenuate after adjusting for each of the brain IDPs in multivariable MR analysis.

CONCLUSIONS

The present MR study provided credible evidence for the causal association between genetically predicted fasting proinsulin and cognitive function, informing a potential diagnosis and intervention target for patients with cognitive impairment. No significant brain IDP included in this study was identified as lying on the causal pathway from fasting proinsulin to cognitive performance. Future research involving more specific and granular brain IDP or other brain process is warranted to explore the potential biological mechanism underlying the association.

Sex differences in the associations of socioeconomic factors and cognitive performance with family history of Alzheimer's disease

INTRODUCTION

While higher socioeconomic factors (SEF) and cognitive performance (CP) have been associated with reduced Alzheimer's disease (AD) risk, recent evidence highlighted that these factors may have opposite effects on family history of AD (FHAD).

METHODS

Leveraging data from the UK Biobank (N=448,100) and the All of Us Research Program (N=240,319), we applied generalized linear regression models, polygenic risk scoring (PRS), and one-sample Mendelian randomization (MR) to test the sex-specific SEF and CP associations with AD and FHAD.

RESULTS

Observational and genetically informed analyses highlighted that higher SEF and CP were associated with reduced AD and sibling-FHAD, while these factors were associated with increased parent-FHAD. We also observed that population minorities may present different patterns with respect to sibling-FHAD vs. parent-FHAD. Sex differences in FHAD associations were identified in ancestry-specific and SEF PRS and MR results.

DISCUSSION

This study contributes to understanding the sex-specific relationships linking SEF and CP to FHAD, highlighting the potential role of reporting, recall, and surviving-related dynamics.

Bidirectional two-sample Mendelian randomization analyses support causal relationships between structural and diffusion imaging-derived phenotypes and the risk of major neurodegenerative diseases

Previous observational investigations suggest that structural and diffusion imaging-derived phenotypes (IDPs) are associated with major neurodegenerative diseases; however, whether these associations are causal remains largely uncertain. Herein we conducted bidirectional two-sample Mendelian randomization analyses to infer the causal relationships between structural and diffusion IDPs and major neurodegenerative diseases using common genetic variants-single nucleotide polymorphism (SNPs) as instrumental variables. Summary statistics of genome-wide association study (GWAS) for structural and diffusion IDPs were obtained from 33,224 individuals in the UK Biobank cohort. Summary statistics of GWAS for seven major neurodegenerative diseases were obtained from the largest GWAS for each disease to date. The forward MR analyses identified significant or suggestively statistical causal effects of genetically predicted three structural IDPs on Alzheimer's disease (AD), frontotemporal dementia (FTD), and multiple sclerosis. For example, the reduction in the surface area of the left superior temporal gyrus was associated with a higher risk of AD. The reverse MR analyses identified significantly or suggestively statistical causal effects of genetically predicted AD, Lewy body dementia (LBD), and FTD on nine structural and diffusion IDPs. For example, LBD was associated with increased mean diffusivity in the right superior longitudinal fasciculus and AD was associated with decreased gray matter volume in the right ventral striatum. Our findings might contribute to shedding light on the prediction and therapeutic intervention for the major neurodegenerative diseases at the neuroimaging level.

Genetic analyses unravel the causal association of cytokine levels on lichen simplex chronicus risk: insights from a mendelian randomization study

Lichen simplex chronicus (LSC) presents a challenge in dermatology due to its elusive pathogenic mechanisms. While associations between circulating inflammatory cytokines and LSC were observed, the definitive causal dynamics remain to be elucidated. Our study used a two-sample Mendelian randomization (MR) approach to investigate causal relationships. We applied a suite of MR methodologies, including IVW, Weighted Median, MR-Egger, Weighted Mode, Simple Mode, MR-PRESSO, and the Steiger test, to ensure robust causal inference. Our analysis confirmed the causal impact of genetically determined cytokine levels on LSC risk, particularly MMP-10 (OR = 0.493, P = 0.004) and DNER (OR = 0.651, P = 0.043) in risk attenuation. We also found a positive causal correlation between GDNF levels (OR = 1.871, P = 0.007) and LSC prevalence. Notably, bidirectional causality was observed between DNER and LSC. Consistency across various MR analyses and sensitivity analyses confirmed the absence of horizontal pleiotropy, validating the causal estimates. This pioneering MR investigation unveils a novel genetically anchored causal relationship between the circulating levels of MMP-10, DNER, and GDNF and LSC risk. Although further validation is requisite, our findings augment the understanding of cytokine mediation in LSC and underscore prospective avenues for research.

Metabolome-Wide Mendelian Randomization Assessing the Causal Role of Serum and Cerebrospinal Metabolites in Traumatic Brain Injury

Previous studies have identified metabolites as biomarkers or potential therapeutic targets for traumatic brain injury (TBI). However, the causal association between them remains unknown. Therefore, we investigated the causal effect of serum metabolites and cerebrospinal fluid (CSF) metabolites on TBI susceptibility through Mendelian randomization (MR). Genetic variants related to metabolites and TBI were extracted from a corresponding genome-wide association study (GWAS). Causal effects were estimated through the inverse variance weighted approach, supplemented by a weighted median, weight mode, and the MR-Egger test. In addition, sensitivity analyses were further performed to evaluate the stability of the MR results, including the MR-Egger intercept, leave-one-out analysis, Cochrane's Q-test, and the MR-PRESSO global test. Metabolic pathway analysis was applied to uncover the underlying pathways of the significant metabolites in TBI. In blood metabolites, substances such as 4-acetaminophen sulfate and kynurenine showed positive links, whereas beta-hydroxyisovalerate and creatinine exhibited negative correlations. CSF metabolites such as N-formylanthranilic acid were positively related, while kynurenate showed negative associations. The metabolic pathway analysis highlighted the potential biological pathways involved in TBI. Of these 16 serum metabolites, 11 CSF metabolites and metabolic pathways may serve as useful circulating biomarkers in clinical screening and prevention, and may be candidate molecules for the exploration of mechanisms and drug targets.

Association between physical frailty and cortical structure in middle-aged and elderly people: a Mendelian randomization study

Introduction

Physical weakness is associated with cortical structures, but the exact causes remain to be investigated. Therefore, we utilized Mendelian randomization (MR) analysis to uncover the underlying connection between frailty and cortical structures.

Methods

The Genome-Wide Association Study (GWAS) on frailty pooled data from publicly available sources such as the UK Biobank and included five indicators of frailty: weakness, walking speed, weight loss, physical activity, and exhaustion. GWAS data on cerebral cortical structure were obtained from the ENIGMA consortium, and we assessed the causal relationship between hereditary frailty and cortical surface area (SA) or cortical thickness (TH). Inverse variance weighting (IVW) was used as the primary estimate, and heterogeneity and multidimensionality were monitored by MR-PRESSO to detect outliers. Additionally, MR-Egger, Cochran's Q test, and weighted median were employed.

Results

At the aggregate level, there was no causal relationship between frailty and cortical thickness or surface area. At the regional level, frailty was associated with the thickness of the middle temporal lobe, parahippocampus, rostral middle frontal lobe, lower parietal lobe, anterior cingulate gyrus, upper temporal lobe, lateral orbital frontal cortex, pericardial surface area, rostral middle frontal lobe, upper temporal lobe, rostral anterior cingulate gyrus, lower parietal lobe, and upper parietal lobe. These results were nominally significant, and sensitivity analyses did not detect any multidirectionality or heterogeneity, suggesting that the results of our analyses are reliable.

Discussion

The results of our analyses suggest a potential causal relationship between somatic weakness and multiple regions of cortical structure. However, the specific mechanisms of influence remain to be investigated. Preliminary results from our analysis suggest that the effects of physical frailty on cortical structures are influenced by various factors related to frailty exposure. This relationship has been documented, and it is therefore both feasible and meaningful to build on existing research to explore the clinical significance of the relationship.

Deciphering the brain-gut axis: elucidating the link between cerebral cortex structures and functional gastrointestinal disorders via integrated Mendelian randomization

Background

Observational studies have suggested associations between functional gastrointestinal disorders (FGIDs) and variations in the cerebral cortex. However, the causality of these relationships remains unclear, confounded by anxiety and depression. To clarify these causal relationships and explore the mediating roles of anxiety and depression, we applied univariate, multivariable, and mediation Mendelian randomization (MR) analyses.

Method

We utilized genome-wide association study (GWAS) summary data from the FinnGen database and the ENIGMA consortium, identifying genetic variants associated with irritable bowel syndrome (IBS), functional dyspepsia (FD), and cerebral cortex structures. Data on anxiety and depression came from FinnGen and a large meta-analysis. Utilizing a bidirectional univariate MR approach, we explored correlations between FD, IBS, and cortex variations. Then, independent effects were assessed through multivariable MR. A meta-analysis of these results, incorporating data from two cohorts, aimed to increase precision. We also explored the potential mediating roles of anxiety and depression.

Results

Our findings indicate a negative causal correlation between FD and the thickness of the rostral anterior cingulate cortex (rACC) across both global and regional adjustments (β = -0.142, 95% confidence interval (CI): -0.209 to-0.074, P.FDR = 0.004; β = -0.112, 95%CI: -0.163 to-0.006, P.FDR = 0.003) and a positive causal correlation with the globally adjusted thickness of the superior frontal gyrus (SFG) (β = 0.107, 95%CI: 0.062 to 0.153, P.FDR = 0.001). The causal correlation with the rACC persisted after multiple variable adjustments (β = -0.137, 95% CI: -0.187 to-0.087, P.FDR = 1.81 × 10-5; β = -0.109, 95%CI: -0.158 to-0.06, P.FDR = 0.002). A significant causal association was found between globally adjusted surface area of the caudal anterior cingulate cortex (cACC) and IBS (odds ratio = 1.267, 95%CI: 1.128 to 1.424, P.FDR = 0.02). The analysis showed that neither anxiety nor depression mediated the relationship between FGIDs and cerebral cortex structures.

Conclusion

Our research provides significant MR evidence of a bidirectional causal relationship between FGIDs and the cerebral cortex structures. This evidence not only confirms the two-way communication along the brain-gut axis but also illuminates the underlying pathophysiology, paving the way for identifying potential therapeutic approaches.

Genetic architecture of brain morphology and overlap with neuropsychiatric traits

Uncovering the genetic architectures of brain morphology offers valuable insights into brain development and disease. Genetic association studies of brain morphological phenotypes have discovered thousands of loci. However, interpretation of these loci presents a significant challenge. One potential solution is exploring the genetic overlap between brain morphology and disorders, which can improve our understanding of their complex relationships, ultimately aiding in clinical applications. In this review, we examine current evidence on the genetic associations between brain morphology and neuropsychiatric traits. We discuss the impact of these associations on the diagnosis, prediction, and treatment of neuropsychiatric diseases, along with suggestions for future research directions.

Psychological Distress and Meniere's Disease: A Bidirectional Two-Sample Mendelian Randomization Study

OBJECTIVE

This study is aim to explore the causal relationship between anxiety, depression, neuroticism, and Meniere's disease (MD).

STUDY DESIGN

Two-sample bidirectional Mendelian randomization (MR) analyses.

SETTING

IEU, FinnGen, CTG, and UKB databases.

METHODS

The genome-wide association studies data for anxiety, depression, neuroticism, and MD involved over 357,957 participants. MR was performed to explore relationships between anxiety, depression, neuroticism, and MD. Sensitivity analyses were performed to assess the robustness of the MR results. Reverse MR was used to exclude the possibility of reverse causality. Finally, multivariate MR was performed to explore the collinear relationships between neuroticism subclusters.

RESULTS

MR results showed that anxiety and depression are not causes of MD, nor does MD cause anxiety and depression. Elevated neuroticism sum score is a cause of anxiety, depression, and MD, but MD does not lead to an increase in the level of neuroticism sum score. Further analysis showed that the 5 subclusters of neuroticism often feel lonely, mood often goes up and down, often feel fed-up, feelings easily hurt, and sensitivity to environmental stress and adversity are causes of MD. Multivariate MR analysis results suggested that the 5 neuroticism subclusters have a collinear relationship.

CONCLUSION

Anxiety and depression are not causative factors of MD, and vice versa. Elevated neuroticism levels serve as a shared causative factor for anxiety, depression, and MD. Identification and effective management of neuroticism is a potential target for preventing and treating MD.

Identifying the mediating role of inflammation on the relationship between socioeconomic status and Alzheimer's disease: a Mendelian randomization analysis and mediation analysis

BACKGROUND AND OBJECTIVES

Observational studies have demonstrated a significant association between socio-economic status (SES) and Alzheimer's disease (AD). Nonetheless, the precise biological mechanisms underlying this association remain unclear. Therefore, we adopted a Mendelian Randomization (MR) approach to investigate the causal relationship between SES and genetic susceptibility to AD, as well as to explore the potential mediation effects of inflammation.

METHODS

Large-scale cohorts based on publicly available genome-wide association study (GWAS) datasets from European populations were employed for conducting the MR study. The primary criterion utilized was the inverse-variance weighting (IVW) model. Heterogeneity and horizontal pleiotropy were assessed. In addition, multivariate MR (MVMR) was utilized to correct the confounders. Moreover, a two-step MR approach was used to evaluate the potential mediating effects of factors on the causal effects between SES and AD.

RESULTS

As indicated by the results of the IVW model, educational years (OR = 0.708, 95% CI 0.610-0.821, P < 0.001) and household income (OR = 0.746, 95% CI 0.566-0.982, P = 0.037) was associated with a decreased genetic susceptibility risk for AD. The univariable results showed that the causal effect of educational years on the lower risk of AD remained significant (OR = 0.643, 95% CI 0.467-0.886, P = 0.006). In addition, our findings indicated that C-reactive protein (CRP) played a role in the causal effect of educational years on AD. The proportions of mediation were - 50.08% (95% CI - 92.78; - 7.38%).

DISCUSSION

These findings provided evidence supporting the causal effect of educational attainment lower AD risk, with inflammation playing a mediating role. These findings may inform prevention strategies and interventions directed toward AD. Future studies should explore other plausible biological mechanisms.

Study on the causal relationship between educational attainment and delirium: A two-sample Mendelian randomization study

This study aimed to investigate whether there is a causal relationship between educational attainment and delirium at the genetic level using the Mendelian randomization method, and provide new evidence for studies in this field. We found a causal relationship between educational attainment and delirium at the genetic level after excluding confounders using Mendelian randomization. The inverse variance weighting method of random effects was the main analysis method. The weighted median and Mendelian Randomization-Egger methods, as well as simple, and weighted modes were used as supplementary analysis methods. Additionally, horizontal pleiotropy tests were conducted, including the Mendelian Randomization-Egger intercept test and Mendelian Randomization Pleiotropy RESidual Sum and Outlier. Cochran's Q statistic was used to assess the size of heterogeneity. We retrieved all second single nucleotide polymorphism features and performed multivariate Mendelian randomization to adjust for the effect of potential confounders on our results. The inverse variance weighting suggested a negative correlation between genetically predicted educational attainment and delirium (0.67[0.49-0.92], p = 0.013); Mendelian Randomization Pleiotropy RESidual Sum and Outlier (0.67[0.49-0.92], p = 0.013) and multivariate Mendelian randomization (0.52[0.33-0.82], p = 0.005) results were generally consistent with the inverse variance weighting method. The Mendelian Randomization-Egger, simple, and weighted mode results were consistent with the inverse variance weighting results. Our results were not affected by pleiotropy or heterogeneity (p > 0.05, for both pleiotropy and heterogeneity). In addition, the "leave-one-out" analysis showed that the results of our Mendelian randomization analysis were not influenced by individual single nucleotide polymorphisms. Studies have found a causal relationship between educational attainment and delirium at the genetic level; higher educational attainment may be a protective factor against delirium. Clinically, more attention should be paid to patients at a high risk of delirium with low educational attainment.

Population Neuroscience: Principles and Advances

In population neuroscience, three disciplines come together to advance our knowledge of factors that shape the human brain: neuroscience, genetics, and epidemiology (Paus, Human Brain Mapping 31:891-903, 2010). Here, I will come back to some of the background material reviewed in more detail in our previous book (Paus, Population Neuroscience, 2013), followed by a brief overview of current advances and challenges faced by this integrative approach.

Handicraft art leisure activities and cognitive reserve

ObjectiveOlder individuals face a higher likelihood of developing dementia. The rate of cognitive decline resulting from dementia is not equivalent for all, as some patients with dementia are able to function independently longer than others, despite having similar disease burden. The cognitive reserve (CR) theory provides one explanation for the differing rate of decline. CR suggests that there are factors-most notably, educational attainment and occupational attainment-that can protect against the cognitive decline. Although the beneficial effects of these notable CR factors are clear, not all are easily modifiable. Participation in leisure activities may represent a more easily modifiable factor. Some research hints at beneficial effects of leisure activities, although specific leisure activities have not been well examined. The present study examined the relations between handicraft art leisure activities (HALAs) and multiple cognitive domains. MethodArchival WAIS-IV and demographic data for 50 California retirement community residents were examined. ResultsHALA participation accounted for statistically significant variance in working memory performance (R2 = .40, β = .24%) over and above the established CR factors of age, depression, educational attainment, and occupational attainment. In addition, HALA participation was related to a better ability to perform abstract visual information tasks (Block Design subtest, r = .28, p = .05) and non-verbal reasoning tasks (Visual Puzzles subtest, r = .38, p = .008). ConclusionsHALA participation among older adults could contribute to the retention of cognitive function, supporting the role of HALA participation as a CR factor.

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.

Smoking and BMI mediate the causal effect of education on lower back pain: observational and Mendelian randomization analyses

Objective

Low back pain (LBP) has been associated with education in previous observational studies, but the causality remains unclear. This study aims to assess the impact of education on LBP and to explore mediation by multiple lifestyle factors.

Design

Univariable Mendelian randomization (MR) was performed to examine the overall effect of education on LBP. Subsequently, multivariable MR was conducted to assess both the direct effect of education on LBP and the influence of potential mediators. Indirect effects were estimated using either the coefficient product method or the difference method, and the proportion of mediation was calculated by dividing the indirect effect by the total effect. The observational study utilized data from the NHANES database collected between 1999 and 2004, and included 15,580 participants aged 20 years and above.

Results

Increasing education by 4.2 years leads to a 48% reduction in the risk of LBP (OR=0.52; 95% CI: 0.46 to 0.59). Compared to individuals with less than a high school education, those with education beyond high school have a 28% lower risk of LBP (OR=0.72; 95% CI: 0.63 to 0.83). In the MR study, smoking accounts for 12.8% (95% CI: 1.04% to 20.8%) of the total effect, while BMI accounts for 5.9% (95% CI: 2.99% to 8.55%). The combined mediation effect of smoking and BMI is 27.6% (95% CI: 23.99% to 32.7%). In the NHANES study, only smoking exhibits a mediating effect, accounting for 34.3% (95% CI: 21.07% to 41.65%) of the effect, while BMI does not demonstrate a mediating role.

Conclusions

Higher levels of education provide a protective effect against the risk of LBP. Additionally, implementing interventions to reduce smoking and promote weight loss among individuals with lower levels of education can also decrease this risk.

A causal relationship between gut microbiota and subcortical brain structures contributes to the microbiota-gut-brain axis: a Mendelian randomization study

A correlation between gut microbiota and brain structure, referring to as a component of the gut-brain axis, has been observed in observational studies. However, the causality of this relationship and its specific bacterial taxa remains uncertain. To reveal the causal effects of gut microbiota on subcortical brain volume, we applied Mendelian randomization (MR) studies in this study. Genome-wide association study data were obtained from the MiBioGen Consortium (n = 18,340) and the Enhancing Neuro Imaging Genetics through Meta-Analysis Consortium (n = 13,170). The primary estimate was obtained utilizing the inverse-variance weighted, while heterogeneity and pleiotropy were assessed using the Cochrane Q statistic, MR Pleiotropy RESidual Sum and Outlier, and MR-Egger intercept. Our findings provide strong evidence that a higher abundance of the genus Parasutterella is causally correlated with a decrease in intracranial volume (β = -30,921.33, 95% CI -46,671.78 to -15,170.88, P = 1.19 × 10-4), and the genus FamilyXIIIUCG001 is associated with a decrease in thalamus volume (β = -141.96, 95% CI: -214.81 to -69.12, P = 1.0× 10-4). This MR study offers novel perspectives on the intricate interplay between the gut microbiota and subcortical brain volume, thereby lending some support to the existence of the microbiota-gut-brain axis.

Evaluation of serum neurofilament light chain and glial fibrillary acidic protein in the diagnosis of Alzheimer's disease

Purpose

This study aimed to evaluate the use of serum neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in the diagnosis of Alzheimer's disease (AD) and the differential diagnosis between AD and mild cognitive impairment (MCI).

Methods

From September 2021 to October 2022, we collected venous blood from patients and healthy individuals who visited our hospital's Neurology Department, and we isolated serum to detect NfL and GFAP using direct chemiluminescence. The results were analyzed using one-way analysis of variance (ANOVA) analysis and receiver operating characteristic (ROC) curves.

Results

Pairwise comparisons among the three groups showed that compared with the health checkup (HC) group, serum NfL and GFAP were increased in both AD and MCI (PNfL < 0.05, PGFAP < 0.01). There were significant differences in GFAP between MCI and AD groups, and the level in AD group was higher (p < 0.01), while there was no difference in NfL. Both serum NfL and serum GFAP levels can independently diagnose AD (p < 0.01). The ROC curve showed that GFAP had a higher diagnostic efficacy, with an area under the ROC curve (AUC) of 0.928. The cut-off values of the two serum markers for the diagnosis of AD were NfL > 40.09 pg./mL and GFAP >31.40 pg./mL. Sensitivity and specificity for NfL in the diagnosis of AD were 59.6 and 76.2%, respectively, and for GFAP, they were 90.4 and 82.1%, respectively. The combined diagnosis of GFAP and NfL improved the diagnostic efficiency (AUC = 0.931, sensitivity = 78.8%, specificity = 92.3%). The cut-off value of GFAP for the differential diagnosis of MCI and AD was 46.05 pg./mL.

Conclusion

Both serum NfL and serum GFAP can be used as biomarkers for the diagnosis of AD. Serum GFAP has better diagnostic efficacy and can distinguish AD from MCI. A combined diagnosis can improve diagnostic specificity.

Relationship between autism and brain cortex surface area: genetic correlation and a two-sample Mendelian randomization study

BACKGROUND

Alterations in surface area (SA) in specific regions of the cortex have been reported in many individuals with autism spectrum disorder (ASD), however, the genetic background between ASD and SA is still unclear. This study estimated the genetic correlation and causal effect of ASD and cortical SA.

METHODS

Summarized data of genome-wide association studies (GWAS) were separately downloaded from the Psychiatric Genomics Consortium (18,381 cases of ASD, and 27,969 controls) and the Enhancing Neuroimaging Genetics through Meta-Analysis Consortium (33,992 participants of Europeans). We used Linkage disequilibrium score regression (LDSC) and Heritability Estimation from Summary Statistics (HESS) to calculate the heritability of each trait. As for the genetic correlation between ASD and SA, LDSC was used for global correlation and HESS was used to examine the local genetic covariance further. We used three Mendelian randomization (MR) methods, Inverse-variance weighted, MR-Egger, and weighted median to estimate the causal relationship.

RESULTS

LDSC observed a nominal significant genetic correlation (rg = 0.1229, P-value = 0.0346) between ASD and SA of the rostral anterior cingulate gyrus whereas analysis through HESS did not reveal any significant loci having genetic covariance. Based on MR results, statistically meaningful estimations were found in the following areas, postcentral cortex (β (SE) = 21.82 (7.84) mm, 95% CI: 6.46 to 37.19 mm, PIVW = 5.38 × 10- 3, PFDR = 3.09 × 10- 2), posterior cingulate gyrus (β (SE) = 6.23 (2.69) mm, 95% CI: 0.96 to 11.49 mm, PIVW = 2.05 × 10- 2, PFDR = 4.26 × 10- 2), supramarginal gyrus (β (SE) = 19.25 (8.43) mm, 95% CI: 29.29 to 35.77 mm, PIVW = 2.24 × 10- 2, PFDR = 4.31 × 10- 2).

CONCLUSION

Our results provided genetic evidence to support the opinion that individuals with ASD tend to develop differences in cortical SA of special areas. The findings contributed to understanding the genetic relationship between ASD and cortical SA.

Genetic Predisposition for White Matter Hyperintensities and Risk of Mild Cognitive Impairment and Alzheimer's Disease: Results from the HELIAD Study

The present study investigated the association of genetic predisposition for white matter hyperintensities (WMHs) with incident amnestic mild cognitive impairment (aMCI) or Alzheimer's disease (AD), as well as whether such an association was influenced by age, sex, and cognitive reserve. Overall, 537 individuals without aMCI or dementia at baseline were included. Among them, 62 individuals developed aMCI/AD at follow up. Genetic propensity to WMH was estimated using a polygenic risk score for WMHs (PRS WMH). The association of PRS WMH with aMCI/AD incidence was examined using COX models. A higher PRS WMH was associated with a 47.2% higher aMCI/AD incidence (p = 0.015) in the fully adjusted model. Subgroup analyses showed significant results in the older age group, in which individuals with a higher genetic predisposition for WMHs had a 3.4-fold higher risk for developing aMCI/AD at follow up (p < 0.001), as well as in the lower cognitive reserve (CR, proxied by education years) group, in which individuals with a higher genetic predisposition for WMHs had an over 2-fold higher risk (p = 0.013). Genetic predisposition for WMHs was associated with aMCI/AD incidence, particularly in the group of participants with a low CR. Thus, CR might be a modifier in the relationship between genetic predisposition for WMHs and incident aMCI/AD.

Amyotrophic lateral sclerosis and osteoporosis: a two-sample Mendelian randomization study

Background

A few observational studies revealed that amyotrophic lateral sclerosis (ALS) was tightly connected with osteoporosis. However, the results of previous studies were inconsistent, and the causal effect of ALS on osteoporosis has not been investigated. To do so, the two-sample Mendelian randomization (MR) method was employed to estimate the causality.

Methods

The instrumental variables (IVs) for ALS were selected from one GWAS summary dataset (27,205 ALS cases and 110,881 controls), and bone mineral density (BMD) in the femoral neck (FN), lumbar spine (LS), and forearm, extracted from another large-scale GWAS summary database (53,236 cases), were used as phenotypes for osteoporosis. Random-effects inverse variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode were conducted to evaluate the causality. Sensitivity analyses were further performed to explore heterogeneity and pleiotropy.

Results

A total of 10 qualified SNPs were finally selected as proxies for ALS. The results of random effects from IVW revealed that ALS has no causal effect on FN-BMD (beta: -0.038, 95% CI: -0.090 to 0.015, SE: 0.027, p = 0.158), LS-BMD (beta: -0.015, 95% CI: -0.076 to 0.046, SE: 0.031, p = 0.629), and forearm BMD (beta: 0.044, 95% CI: -0.063 to 0.152, SE: 0.055, p = 0.418). These results were confirmed using the MR-Egger, weighted median, simple model, and weighted model. No heterogeneity or pleiotropy was detected (p > 0.05 for all).

Conclusion

Contrary to previous observational studies, our study figured out that no causal effect existed between ALS and osteoporosis. The disparity in results is probably attributed to secondary effects such as physical inactivity and muscle atrophy caused by ALS.

The Role of Insulin-like Growth Factor I in Mechanisms of Resilience and Vulnerability to Sporadic Alzheimer's Disease

Despite decades of intense research, disease-modifying therapeutic approaches for Alzheimer's disease (AD) are still very much needed. Apart from the extensively analyzed tau and amyloid pathological cascades, two promising avenues of research that may eventually identify new druggable targets for AD are based on a better understanding of the mechanisms of resilience and vulnerability to this condition. We argue that insulin-like growth factor I (IGF-I) activity in the brain provides a common substrate for the mechanisms of resilience and vulnerability to AD. We postulate that preserved brain IGF-I activity contributes to resilience to AD pathology as this growth factor intervenes in all the major pathological cascades considered to be involved in AD, including metabolic impairment, altered proteostasis, and inflammation, to name the three that are considered to be the most important ones. Conversely, disturbed IGF-I activity is found in many AD risk factors, such as old age, type 2 diabetes, imbalanced diet, sedentary life, sociality, stroke, stress, and low education, whereas the Apolipoprotein (Apo) E4 genotype and traumatic brain injury may also be influenced by brain IGF-I activity. Accordingly, IGF-I activity should be taken into consideration when analyzing these processes, while its preservation will predictably help prevent the progress of AD pathology. Thus, we need to define IGF-I activity in all these conditions and develop a means to preserve it. However, defining brain IGF-I activity cannot be solely based on humoral or tissue levels of this neurotrophic factor, and new functionally based assessments need to be developed.

Timing of lifespan influences on brain and cognition

Modifiable risk and protective factors for boosting brain and cognitive development and preventing neurodegeneration and cognitive decline are embraced in neuroimaging studies. We call for sobriety regarding the timing and quantity of such influences on brain and cognition. Individual differences in the level of brain and cognition, many of which present already at birth and early in development, appear stable, larger, and more pervasive than differences in change across the lifespan. Incorporating early-life factors, including genetics, and investigating both level and change will reduce the risk of ascribing undue importance and causality to proximate factors in adulthood and older age. This has implications for both mechanistic understanding and prevention.

Inter-Hospital Advanced and Mild Alzheimer's Disease Classification Based on Electroencephalogram Measurements via Classical Machine Learning Algorithms

BACKGROUND

In pursuit of diagnostic tools capable of targeting distinct stages of Alzheimer's disease (AD), this study explores the potential of electroencephalography (EEG) combined with machine learning (ML) algorithms to identify patients with mild or moderate AD (ADM) and advanced AD (ADA).

OBJECTIVE

This study aims to assess the classification accuracy of six classical ML algorithms using a dataset of 668 patients from multiple hospitals.

METHODS

The dataset comprised measurements obtained from 668 patients, distributed among control, ADM, and ADA groups, collected from five distinct hospitals between 2011 and 2022. For classification purposes, six classical ML algorithms were employed: support vector machine, Bayesian linear discriminant analysis, decision tree, Gaussian Naïve Bayes, K-nearest neighbor and random forest.

RESULTS

The RF algorithm exhibited outstanding performance, achieving a remarkable balanced accuracy of 93.55% for ADA classification and 93.25% for ADM classification. The consistent reliability in distinguishing ADA and ADM patients underscores the potential of the EEG-based approach for AD diagnosis.

CONCLUSIONS

By leveraging a dataset sourced from multiple hospitals and encompassing a substantial patient cohort, coupled with the straightforwardness of the implemented models, it is feasible to attain notably robust results in AD classification.