Common variants in Alzheimer's disease and risk stratification by polygenic risk scores

Ancient viral DNA in the human genome linked to neurodegenerative diseases

BACKGROUND

Human endogenous retroviruses (HERVs) are sequences in the human genome that originated from infections with ancient retroviruses during our evolution. Previous studies have linked HERVs to neurodegenerative diseases, but defining their role in aetiology has been challenging. Here, we used a retrotranscriptome-wide association study (rTWAS) approach to assess the relationships between genetic risk for neurodegenerative diseases and HERV expression in the brain, calculated with genomic precision.

METHODS

We analysed genetic association statistics pertaining to Alzheimer's disease, amyotrophic lateral sclerosis, multiple sclerosis, and Parkinson's disease, using HERV expression models calculated from 792 cortical samples. Robust risk factors were considered those that survived multiple testing correction in the primary analysis, which were also significant in conditional and joint analyses, and that had a posterior inclusion probability above 0.5 in fine-mapping analyses.

RESULTS

The primary analysis identified 12 HERV expression signatures associated with neurodegenerative disease susceptibility. We found one HERV expression signature robustly associated with amyotrophic lateral sclerosis on chromosome 12q14 (MER61_12q14.2) and one robustly associated with multiple sclerosis on chromosome 1p36 (ERVLE_1p36.32a). A co-expression analysis suggested that these HERVs are involved in homophilic cell adhesion via plasma membrane adhesion molecules.

CONCLUSIONS

We found HERV expression profiles robustly associated with amyotrophic lateral sclerosis and multiple sclerosis susceptibility, highlighting novel risk mechanisms underlying neurodegenerative disease, and offering potential new targets for therapeutic intervention.

Brain change trajectories in healthy adults correlate with Alzheimer's related genetic variation and memory decline across life

Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer's disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2-7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer's Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.

LD-informed deep learning for Alzheimer's gene loci detection using WGS data

INTRODUCTION

The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk.

METHODS

The Deep-Block was applied to a large-scale whole genome sequencing (WGS) dataset from the Alzheimer's Disease Sequencing Project (ADSP), comprising 7,416 non-Hispanic white participants (3,150 cognitively normal older adults (CN), 4,266 AD).

RESULTS

30,218 LD blocks were identified and then ranked based on their relevance with Alzheimer's disease. Subsequently, the Deep-Block identified novel SNPs within the top 1,500 LD blocks and confirmed previously known variants, including APOE rs429358 and rs769449. Expression Quantitative Trait Loci (eQTL) analysis across 13 brain regions provided functional evidence for the identified variants. The results were cross-validated against established AD-associated loci from the European Alzheimer's and Dementia Biobank (EADB) and the GWAS catalog.

DISCUSSION

The Deep-Block framework effectively processes large-scale high throughput sequencing data while preserving SNP interactions during dimensionality reduction, minimizing bias and information loss. The framework's findings are supported by tissue-specific eQTL evidence across brain regions, indicating the functional relevance of the identified variants. Additionally, the Deep-Block approach has identified both known and novel genetic variants, enhancing our understanding of the genetic architecture and demonstrating its potential for application in large-scale sequencing studies.

Rapid dynamics of electrophysiological connectome states are heritable

Time-varying changes in whole-brain connectivity patterns, or connectome state dynamics, are a prominent feature of brain activity with broad functional implications. While infraslow (<0.1 Hz) connectome dynamics have been extensively studied with fMRI, rapid dynamics highly relevant for cognition are poorly understood. Here, we asked whether rapid electrophysiological connectome dynamics constitute subject-specific brain traits and to what extent they are under genetic influence. Using source-localized EEG connectomes during resting state (N = 928, 473 females), we quantified the heritability of multivariate (multistate) features describing temporal or spatial characteristics of connectome dynamics. States switched rapidly every ∼60-500 ms. Temporal features were heritable, particularly Fractional Occupancy (in theta, alpha, beta, and gamma bands) and Transition Probability (in theta, alpha, and gamma bands), representing the duration spent in each state and the frequency of state switches, respectively. Genetic effects explained a substantial proportion of the phenotypic variance of these features: Fractional Occupancy in beta (44.3%) and gamma (39.8%) bands and Transition Probability in theta (38.4%), alpha (63.3%), beta (22.6%), and gamma (40%) bands. However, we found no evidence for the heritability of dynamic spatial features, specifically states' Modularity and connectivity pattern. We conclude that genetic effects shape individuals' connectome dynamics at rapid timescales, specifically states' overall occurrence and sequencing.

NIAGADS: A Comprehensive National Data Repository for Alzheimer's Disease and Related Dementia Genetics and Genomics Research

NIAGADS is the National Institute on Aging (NIA) designated national data repository for human genetics research on Alzheimer's Disease and related dementia (ADRD). NIAGADS maintains a high-quality data collection for ADRD genetic/genomic research and supports genetics data production and analysis. NIAGADS hosts whole genome and exome sequence data from the Alzheimer's Disease Sequencing Project (ADSP) and other genotype/phenotype data, encompassing 209,000 samples. NIAGADS shares these data with hundreds of research groups around the world via the Data Sharing Service, a FISMA moderate compliant cloud-based platform that fully supports the NIH Genome Data Sharing Policy. NIAGADS Open Access consists of multiple knowledge bases with genome-wide association summary statistics and rich annotations on the biological significance of genetic variants and genes across the human genome. NIAGADS stands as a keystone in promoting collaborations to advance the understanding and treatment of Alzheimer's disease.

Ancestral Genomic Functional Differences in Oligodendroglia: Implications for Alzheimer's Disease

Background

This study aims to elucidate ancestry-specific changes to the genomic regulatory architecture in induced pluripotent stem cell (iPSC)-derived oligodendroglia, focusing on their implications for Alzheimer's disease (AD). This work addresses the lack of diversity in previous iPSC studies by including ancestries that contribute to African American (European/African) and Hispanic/Latino populations (Amerindian/African/European).

Methods

We generated 12 iPSC lines-four African, four Amerindian, and four European- from both AD patients and non-cognitively impaired individuals, with varying APOE genotypes (APOE3/3 and APOE4/4). These lines were differentiated into neural spheroids containing oligodendrocyte lineage cells. Single-nuclei RNA sequencing and ATAC sequencing were employed to analyze transcriptional and chromatin accessibility profiles, respectively. Differential gene expression, chromatin accessibility, and Hi-C analyses were conducted, followed by pathway analysis to interpret the results.

Results

We identified ancestry-specific differences in gene expression and chromatin accessibility. Notably, numerous AD GWAS-associated genes were differentially expressed across ancestries. The largest number of differentially expressed genes (DEGs) were found in European vs. Amerindian and African vs. Amerindian iPSC-derived oligodendrocyte progenitor cells (OPCs). Pathway analysis of APOE4/4 carriers vs APOE3/3 carriers exhibited upregulation of a large number of disease and metabolic pathways in APOE4/4 individuals of all ancestries. Of particular interest was that APOE4/4 carriers had significantly upregulated cholesterol biosynthesis genes relative to APOE3/3 individuals across all ancestries, strongest in iOPCs. Comparison of iOPC and iOL transcriptome data with corresponding human frontal cortex data demonstrated a high correlation (R2 > 0.85).

Conclusions

This research emphasizes the importance of including diverse ancestries in AD research to uncover critical gene expression differences between populations and ancestries that may influence disease susceptibility and therapeutic interventions. The upregulation of cholesterol biosynthesis genes in APOE4/4 carriers of all three ancestries supports the concept that APOE4 may produce disease effects early in life, which could have therapeutic implications as we move forward towards specific therapy for APOE4 carriers. These findings and the high correlation between brain and iPSC-derived OPC and OL transcriptomes support the relevance of this approach as a model for disease study.

Amyloid deposition in adults with drug-resistant temporal lobe epilepsy

OBJECTIVE

Pathological amyloid-β (Aβ) accumulation and hyperphosphorylated tau proteins have been described in resected temporal lobe specimens of epilepsy patients. We aimed to determine cerebrospinal fluid (CSF) Aβ1-42 and p181-tau levels and cerebral Aβ deposits on positron emission tomography (Aβ PET) and correlate these findings with cognitive performance in adults with drug-resistant temporal lobe epilepsy (TLE).

METHODS

In this cross-sectional study, we enrolled individuals with drug-resistant TLE who were 25-55 years old. Each participant underwent 18F-flutemetamol PET, determination of CSF Aβ1-42, p181-tau, and total tau, and a comprehensive neuropsychological assessment. We evaluated normalized standard uptake value ratios (SUVRs) for different brain regions on Aβ PET.

RESULTS

Thirty patients (mean age = 41.9 ± SD 8.1 years, 57% men) were included. The median disease duration was 9.5 (interquartile range = 4-24) years. Twenty-six patients (87%) had a clinically significant cognitive impairment on neuropsychological evaluation, 18 (69%) of the amnesic type. On Aβ PET, high uptake was observed in both mesial temporal regions (ipsilateral: SUVR z-score = .90, 95% confidence interval [CI] = .60-1.20; contralateral: SUVR z-score = .92, 95% CI = .57-1.27; p < .001), which was higher when compared to SUVR z-scores in all the remaining regions (p < .001) and in the ipsilateral anterior cingulate (SUVR z-score = .27, 95% CI = .04-.49, p = .020). No significant deposition was observed in other regions. Seven patients (23%) had low Aβ1-42 levels, and two (7%) had elevated p181-tau levels in CSF. Higher p181-tau levels correlated with poorer verbal fluency (R = -.427, p = .044).

SIGNIFICANCE

Our findings reveal a considerable Aβ deposition in mesial temporal regions and ipsilateral anterior cingulate among adults with drug-resistant TLE. Additionally, abnormal CSF Aβ1-42 levels were observed in a significant proportion of patients, and p181-tau levels were associated with verbal fluency. These results suggest that markers of neuronal damage can be observed in adults with TLE, warranting further investigation.

Characterisation of molecular mechanisms for PLCγ2 disease-linked variants

The phospholipase C enzyme PLCγ2 is best characterised in the context of immune cell regulation. Furthermore, many mutations discovered in PLCγ2 have been linked to the development of complex immune disorders as well as resistance to ibrutinib treatment in chronic lymphocytic leukaemia. Importantly, it has also been found that a rare variant of PLCγ2 (P522R) has a protective role in Alzheimer's disease (AD). Despite initial characterisation of these disease-linked variants, a comprehensive understanding of their differences and underpinning molecular mechanisms, needed to facilitate therapeutic efforts, is lacking. Here, we used available structural insights for PLCγ enzymes to further analyse PLCγ2 M1141K mutation, representative for mutations in immune disorders and cancer resistance, and the AD-protective variant, PLCγ2 P522R. Together with several other mutations in the autoinhibitory interface, the PLCγ2 M1141K mutation was strongly activating in a cell-based assay, under basal and stimulated conditions. Measurements of PLC activity in various in vitro assays demonstrated enhanced activity of PLCγ2 M1141K while the activity of PLCγ2 P522R was not significantly different from the WT. Similar trends were observed in several other assays, including direct liposome binding. However, an enhanced rate of phosphorylation of a functionally important tyrosine by Btk in vitro was observed for PLCγ2 P522R variants. To further assess implications of these in vitro findings in a cellular context relevant for the PLCγ2 P522R variant, microglia (BV2) stable cell lines were generated and analysed under growth conditions. The PLC activity in cells expressing PLCγ2 P522R at physiologically relevant levels was clearly enhanced compared to the WT, and differences in cell morphology observed. These data, combined with the structural insights, suggest that the PLCγ2 P522R variant has subtle, localised structural changes that do not directly affect the PLC activity by compromising autoinhibition, as determined for PLCγ2 M1141K. It is also likely that in contrast to the PLCγ2 M1141K, the functional impact of the P522R substitution completely depends on further interactions with upstream kinases and other regulatory proteins in a relevant cellular context, where changes in the PLCγ2 P522R variant could facilitate processes such as phosphorylation and protein-protein interactions.

Large-scale deep proteomic analysis in Alzheimer's disease brain regions across race and ethnicity

INTRODUCTION

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within non-Hispanic White (NHW) populations. Here we provide an extensive survey of the proteomic landscape of AD across diverse racial/ethnic groups.

METHODS

Two cortical regions, from multiple centers, were harmonized by uniform neuropathological diagnosis. Among 998 unique donors, 273 donors self-identified as African American, 229 as Latino American, and 434 as NHW.

RESULTS

While amyloid precursor protein and the microtubule-associated protein tau demonstrated higher abundance in AD brains, no significant race-related differences were observed. Further proteome-wide and focused analyses (specific amyloid beta [Aβ] species and the tau domains) supported the absence of racial differences in these AD pathologies within the brain proteome.

DISCUSSION

Our findings indicate that the racial differences in AD risk and clinical presentation are not underpinned by dramatically divergent patterns in the brain proteome, suggesting that other determinants account for these clinical disparities.

HIGHLIGHTS

We present a large-scale proteome (∼10,000 proteins) of DLPFC (998) and STG (244) across AD cases. About 50% of samples were from racially and ethnically diverse brain donors. Key AD proteins (amyloid and tau) correlated with CERAD and Braak stages. No significant race-related differences in amyloid and tau protein levels were observed in AD brains. AD-associated protein changes showed a strong correlation between the brain proteomes of African American and White individuals. This dataset advances understanding of ethnoracial-specific AD pathways and potential therapies.

Associations of plasma SMOC1 and soluble IL6RA levels with the progression from mild cognitive impairment to dementia

Despite the central role attributed to neuroinflammation in the etiology and pathobiology of Alzheimer's disease (AD), the direct link between levels of inflammatory mediators in blood and cerebrospinal fluid (CSF) compartments, as well as their potential implications for AD diagnosis and progression, remains inconclusive. Moreover, there is debate on whether inflammation has a protective or detrimental effect on disease onset and progression. Indeed, distinct immunological mechanisms may govern protective and damaging effects at early and late stages, respectively. This study aims to (i) identify inflammatory mediators demonstrating robust correlations between peripheral and central nervous system (CNS) compartments by means of plasma and CSF analysis, respectively, and (ii) assess their potential significance in the context of AD and disease progression from mild cognitive impairment (MCI) to dementia. To achieve this, we have examined the inflammatory profile of a well-defined subcohort comprising 485 individuals from the Ace Alzheimer Center Barcelona (ACE). Employing a hierarchical clustering approach, we thoroughly evaluated the intercompartmental correlations of 63 distinct inflammation mediators, quantified in paired CSF and plasma samples, using advanced SOMAscan technology. Of the array of mediators investigated, only six mediators (CRP, IL1RAP, ILRL1, IL6RA, PDGFRB, and YKL-40) exhibited robust correlations between the central and peripheral compartments (proximity scores <400). To strengthen the validity of our findings, these identified mediators were subsequently validated in a second subcohort of individuals from ACE (n = 873). The observed plasma correlations across the entire cohort consistently have a Spearman rho value above 0.51 (n = 1,360, p < 1.77E-93). Of the high CSF-plasma correlated proteins, only soluble IL6RA (sIL6RA) displayed a statistically significant association with the conversion from MCI to dementia. This association remained robust even after applying a stringent Bonferroni correction (Cox proportional hazard ratio [HR] = 1.936 per standard deviation; p = 0.0018). This association retained its significance when accounting for various factors, including CSF amyloid (Aβ42) and Thr181-phosphorylated tau (p-tau) levels, age, sex, baseline Mini-Mental State Examination (MMSE) score, and potential sampling biases identified through principal component analysis (PCA) modeling. Furthermore, our study confirmed the association of both plasma and CSF levels of SPARC-related modular calcium-binding protein 1 (SMOC1) with amyloid and tau accumulation, indicating their role as early surrogate biomarkers for AD pathology. Despite the lack of a statistically significant correlation between SMOC1 levels in CSF and plasma, both acted as independent biomarkers of disease progression (HR > 1.3, p < 0.002). In conclusion, our study unveils that sIL6RA and SMOC1 are associated with MCI progression. The absence of correlations among inflammatory mediators between the central and peripheral compartments appears to be a common pattern, with only a few intriguing exceptions.

Alzheimer's Disease polygenic risk, the plasma proteome, and dementia incidence among UK older adults

Alzheimer's Disease (AD) is a complex polygenic neurodegenerative disorder. Its genetic risk's relationship with all-cause dementia may be influenced by the plasma proteome. Up to 40,139 UK Biobank participants aged ≥ 50y at baseline assessment (2006-2010) were followed-up for ≤ 15 y for dementia incidence. Plasma proteomics were performed on a sub-sample of UK Biobank participants (k = 1,463 plasma proteins). AD polygenic risk scores (PRS) were used as the primary exposure and Cox proportional hazards models were conducted to examine the AD PRS-dementia relationship. A four-way decomposition model then partitioned the total effect (TE) of AD PRS on dementia into an effect due to mediation only, an effect due to interaction only, neither or both. The study found that AD PRS tertiles significantly increased the risk for all-cause dementia, particularly among women. The study specifically found that AD PRS was associated with a 79% higher risk for all-cause dementia for each unit increase (HR = 1.79, 95% CI: 1.70-1.87, P < 0.001). Eighty-six plasma proteins were significantly predicted by AD PRS, including a positive association with PLA2G7, BRK1, the glial acidic fibrillary protein (GFAP), neurofilament light chain (NfL), and negative with TREM2. Both GFAP and NfL significantly interacted synergistically with AD PRS to increase all-dementia risk (> 10% of TE is pure interaction), while GFAP was also an important consistent mediator in the AD PRS-dementia relationship. In summary, we detected significant interactions of NfL and GFAP with AD PRS, in relation to dementia incidence, suggesting potential for personalized dementia prevention and management.

Heritability of Alzheimer's disease plasma biomarkers: A nuclear twin family design

INTRODUCTION

Alzheimer's disease (AD) is a highly heritable disease (60%-80%). Amyloid beta (Aβ) 42/40, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) are plasma biomarkers for AD. Clinical biomarker research would be served by an understanding of the sources of variance in these markers.

METHODS

Blood concentrations of Aβ42/40, NfL, and GFAP of twins and their families (monozygotic twins: 1574, dizygotic twins: 1266, other: 3657) were analyzed on the Simoa HD-X. Twin-family models were used to estimate proportional genetic contributions to the variance in biomarker levels.

RESULTS

Heritability estimates were 16% for Aβ42/40, 42% for NfL, and 60% for GFAP. NfL and GFAP were significantly correlated with each other (0.37) but not with Aβ42/40.

DISCUSSION

The heritability of Aβ42/40 (16%) is lower than the heritability of AD, suggesting strong environmental influences on this biomarker. The lack of correlation between NfL/GFAP and Aβ42/40 indicates these markers may be on different biological pathways.

HIGHLIGHTS

Heritability is found for glial fibrillary acidic protein (60%), neurofilament light chain (42%), and amyloid beta (Aβ) 42/40 (16%) plasma levels. Aβ42/40 plasma levels are sensitive to person-specific environmental influences.

Is the Relationship Between Cardiovascular Disease and Alzheimer's Disease Genetic? A Scoping Review

BACKGROUND/OBJECTIVES

Cardiovascular disease (CVD) and Alzheimer's disease (AD) are two diseases highly prevalent in the aging population and often co-occur. The exact relationship between the two diseases is uncertain, though epidemiological studies have demonstrated that CVDs appear to increase the risk of AD and vice versa. This scoping review aims to examine the current identified overlapping genetics between CVDs and AD at the individual gene level and at the shared pathway level.

METHODS

Following PRISMA-ScR guidelines for a scoping review, we searched the PubMed and Scopus databases from 1990 to October 2024 for articles that involved (1) CVDs, (2) AD, and (3) used statistical methods to parse genetic relationships.

RESULTS

Our search yielded 2918 articles, of which 274 articles passed screening and were organized into two main sections: (1) evidence of shared genetic risk; and (2) shared mechanisms. The genes APOE, PSEN1, and PSEN2 reportedly have wide effects across the AD and CVD spectrum, affecting both cardiac and brain tissues. Mechanistically, changes in three main pathways (lipid metabolism, blood pressure regulation, and the breakdown of the blood-brain barrier (BBB)) contribute to subclinical and etiological changes that promote both AD and CVD progression. However, genetic studies continue to be limited by the availability of longitudinal data and lack of cohorts that are representative of diverse populations.

CONCLUSIONS

Highly penetrant familial genes simultaneously increase the risk of CVDs and AD. However, in most cases, sets of dysregulated genes within larger-scale mechanisms, like changes in lipid metabolism, blood pressure regulation, and BBB breakdown, increase the risk of both AD and CVDs and contribute to disease progression.

Association of immunity-related gene SNPs with Alzheimer's disease

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by progressive cognitive decline. Genetic factors have been implicated in disease susceptibility as its etiology remains multifactorial. The CD33 and the HLA-DRB1 genes, involved in immune responses, have emerged as potential candidates influencing AD risk. In this study, 644 Lebanese individuals, including 127 AD patients and 250 controls, were genotyped, by KASP assay, for six SNPs selected from the largest GWAS study in 2021. Logistic regression analysis assessed the association between SNP genotypes and AD risk, adjusting for potential confounders. Among the six SNPs analyzed, rs1846190G>A in HLA-DRB1 and rs1354106T>G in CD33 showed significant associations with AD risk in the Lebanese population (p < 0.05). Carriers of the AG and AA genotypes of rs1846190 in HLA-DRB1 exhibited a protective effect against AD (AG: OR = 0.042, p = 0.026; AA: OR = 0.052, p = 0.031). The GT genotype of rs1354106T>G in CD33 was also associated with reduced risk (OR = 0.173, p = 0.005). Following Bonferroni correction, a significant correlation of rs1354106T > G with AD risk was established. Our results might highlight the complex interplay between genetic and immunological factors contributing to the development of the disease.

Explainable artificial intelligence identifies an AQP4 polymorphism-based risk score associated with brain amyloid burden

Aquaporin-4 (AQP4) is hypothesized to be a component of the glymphatic system, a pathway for removing brain interstitial solutes like amyloid-β (Aβ). Evidence exists that genetic variation of AQP4 impacts Aβ clearance, clinical outcome in Alzheimer's disease as well as sleep measures. We examined whether a risk score calculated from several AQP4 single-nucleotide polymorphisms (SNPs) is related to Aβ neuropathology in older cognitively unimpaired white individuals. We used a machine learning approach and explainable artificial intelligence to extract information on synergistic effects of AQP4 SNPs on brain amyloid burden from the ADNI cohort. From this information, we formulated a sex-specific AQP4 SNP-based risk score and evaluated it using data from the screening process of the A4 study. We found in both cohorts significant associations of the risk score with brain amyloid burden. The results support the hypothesis of an involvement of the glymphatic system, and particularly AQP4, in brain amyloid aggregation pathology. They suggest also that different AQP4 SNPs exert a synergistic effect on the build-up of brain amyloid burden.

Emerging microglial biology highlights potential therapeutic targets for Alzheimer's disease

Alzheimer's disease is a chronic degenerative disease of the central nervous system, which primarily affects elderly people and accounts for 70-80 % of dementia cases. The current prevailing amyloid cascade hypothesis suggests that Alzheimer's disease begins with the deposition of amyloid β (Aβ) in the brain. Major therapeutic strategies target Aβ production, aggregation, and clearance, although many clinical trials have shown that these therapeutic strategies are not sufficient to completely improve cognitive deficits in AD patients. Recent genome-wide association studies have identified that multiple important regulators are the most significant genetic risk factors for Alzheimer's disease, especially in the innate immune pathways. These genetic risk factors suggest a critical role for microglia, highlighting their therapeutic potential in treating neurodegenerative diseases. In this review, we discuss how these recently documented AD risk genes affect microglial function and AD pathology and how they can be further targeted to regulate microglial states and slow AD progression, especially the highly anticipated APOE and TREM2 targets. We focused on recent findings that modulation of innate and adaptive neuroimmune microenvironment crosstalk reverses cognitive deficits in AD patients. We also considered novel strategies for microglia in AD patients.

CSF proteomics identifies early changes in autosomal dominant Alzheimer's disease

In this high-throughput proteomic study of autosomal dominant Alzheimer's disease (ADAD), we sought to identify early biomarkers in cerebrospinal fluid (CSF) for disease monitoring and treatment strategies. We examined CSF proteins in 286 mutation carriers (MCs) and 177 non-carriers (NCs). The developed multi-layer regression model distinguished proteins with different pseudo-trajectories between these groups. We validated our findings with independent ADAD as well as sporadic AD datasets and employed machine learning to develop and validate predictive models. Our study identified 137 proteins with distinct trajectories between MCs and NCs, including eight that changed before traditional AD biomarkers. These proteins are grouped into three stages: early stage (stress response, glutamate metabolism, neuron mitochondrial damage), middle stage (neuronal death, apoptosis), and late presymptomatic stage (microglial changes, cell communication). The predictive model revealed a six-protein subset that more effectively differentiated MCs from NCs, compared with conventional biomarkers.

A Reproducibility Focused Meta-Analysis Method for Single-Cell Transcriptomic Case-Control Studies Uncovers Robust Differentially Expressed Genes

Here we systematically studied the reproducibility of DEGs in previously published Alzheimer's Disease (AD), Parkinson's Disease (PD), and COVID-19 scRNA-seq studies. We found that while transcriptional scores created from differentially expressed genes (DEGs) in individual PD and COVID-19 datasets had moderate predictive power for the case control status of other datasets (mean AUC=0.77 and 0.75, respectively), genes from individual AD datasets had poor predictive power (mean AUC=0.68). We developed a non-parametric meta-analysis method, SumRank, based on reproducibility of relative differential expression ranks across datasets. The meta-analysis genes had improved predictive power (AUCs of 0.88, 0.91, and 0.78, respectively). By multiple other metrics, specificity and sensitivity of these genes were substantially higher than those discovered by dataset merging and inverse variance weighted p-value aggregation methods. The DEGs revealed known and novel biological pathways, and we validate the BCAT1 gene as down-regulated in oligodendrocytes in an AD mouse model. Our analyses show that for heterogeneous diseases, DEGs of individual studies often have low reproducibility, but combining information across multiple datasets promotes the rigorous discovery of reproducible DEGs.

Optimizing and benchmarking polygenic risk scores with GWAS summary statistics

BACKGROUND

Polygenic risk score (PRS) is a major research topic in human genetics. However, a significant gap exists between PRS methodology and applications in practice due to often unavailable individual-level data for various PRS tasks including model fine-tuning, benchmarking, and ensemble learning.

RESULTS

We introduce an innovative statistical framework to optimize and benchmark PRS models using summary statistics of genome-wide association studies. This framework builds upon our previous work and can fine-tune virtually all existing PRS models while accounting for linkage disequilibrium. In addition, we provide an ensemble learning strategy named PUMAS-ensemble to combine multiple PRS models into an ensemble score without requiring external data for model fitting. Through extensive simulations and analysis of many complex traits in the UK Biobank, we demonstrate that this approach closely approximates gold-standard analytical strategies based on external validation, and substantially outperforms state-of-the-art PRS methods.

CONCLUSIONS

Our method is a powerful and general modeling technique that can continue to combine the best-performing PRS methods out there through ensemble learning and could become an integral component for all future PRS applications.

Connecting dementia risk loci to the CSF proteome identifies pathophysiological leads for dementia

Genome-wide association studies have successfully identified many genetic risk loci for dementia, but exact biological mechanisms through which genetic risk factors contribute to dementia remains unclear. Integrating CSF proteomic data with dementia risk loci could reveal intermediate molecular pathways connecting genetic variance to the development of dementia. We tested to what extent effects of known dementia risk loci can be observed in CSF levels of 665 proteins [proximity extension-based (PEA) immunoassays] in a deeply-phenotyped mixed memory clinic cohort [n = 502, mean age (standard deviation, SD) = 64.1 (8.7) years, 181 female (35.4%)], including patients with Alzheimer's disease (AD, n = 213), dementia with Lewy bodies (DLB, n = 50) and frontotemporal dementia (FTD, n = 93), and controls (n = 146). Validation was assessed in independent cohorts (n = 99 PEA platform, n = 198, mass reaction monitoring-targeted mass spectroscopy and multiplex assay). We performed additional analyses stratified according to diagnostic status (AD, DLB, FTD and controls separately), to explore whether associations between CSF proteins and genetic variants were specific to disease or not. We identified four AD risk loci as protein quantitative trait loci (pQTL): CR1-CR2 (rs3818361, P = 1.65 × 10-8), ZCWPW1-PILRB (rs1476679, P = 2.73 × 10-32), CTSH-CTSH (rs3784539, P = 2.88 × 10-24) and HESX1-RETN (rs186108507, P = 8.39 × 10-8), of which the first three pQTLs showed direct replication in the independent cohorts. We identified one AD-specific association between a rare genetic variant of TREM2 and CSF IL6 levels (rs75932628, P = 3.90 × 10-7). DLB risk locus GBA showed positive trans effects on seven inter-related CSF levels in DLB patients only. No pQTLs were identified for FTD loci, either for the total sample as for analyses performed within FTD only. Protein QTL variants were involved in the immune system, highlighting the importance of this system in the pathophysiology of dementia. We further identified pQTLs in stratified analyses for AD and DLB, hinting at disease-specific pQTLs in dementia. Dissecting the contribution of risk loci to neurobiological processes aids in understanding disease mechanisms underlying dementia.

Serum Fatty Acid Profiles and Neurofilament Light Chain Levels in the General Population

BACKGROUND

Previous studies have demonstrated associations between fatty acids and neurological disorders. However, no studies have examined the relationship between serum fatty acid levels and serum neurofilament light chain (NfL), a biomarker of neurological disorders.

OBJECTIVES

This study aimed to comprehensively investigate the intricate relationship between 30 serum fatty acids and serum NfL levels in a nationally representative sample of United States adults, using data from the 2013-2014 National Health and Nutrition Examination Survey.

METHODS

Using a cross-sectional analysis, multivariable linear regression models were used to explore the associations between 30 serum fatty acids and serum NfL levels. This analysis involved adjustment for potential confounding variables, including age, sex, race, body mass index (BMI), smoking status, hyperlipidemia, and diabetes, to clarify the association between serum fatty acids and serum NfL levels.

RESULTS

The analysis revealed that certain fatty acids exhibited distinct associations with serum NfL levels. Notably, docosanoic acid (22:0) and tricosanoic acid (C23:0) were found to be inversely associated with serum NfL levels (β = -0.280, 95% confidence interval [CI]: -0.525, -0.035; β = -0.292, 95% CI: -0.511, -0.072). Conversely, palmitoleic acid (16:1n-7) demonstrated a positive association with serum NfL levels (β = 0.125, 95% CI: 0.027, 0.222). Notably, these associations remained significant even after adjustment for potential confounders.

CONCLUSIONS

Individuals with high relative concentrations of certain SFA exhibited decreased serum NfL, whereas those with high relative concentrations of certain monounsaturated fatty acids showed increased serum NfL. These findings contribute to a deeper understanding of the potential impact of serum fatty acids on NfL levels, shedding light on novel avenues for further investigation and potential interventions in the context of neurological health.

Clinical value of plasma pTau181 to predict Alzheimer's disease pathology in a large real-world cohort of a memory clinic

BACKGROUND

The identification of patients with an elevated risk of developing Alzheimer's disease (AD) dementia and eligible for the disease-modifying treatments (DMTs) in the earliest stages is one of the greatest challenges in the clinical practice. Plasma biomarkers has the potential to predict these issues, but further research is still needed to translate them to clinical practice. Here we evaluated the clinical applicability of plasma pTau181 as a predictive marker of AD pathology in a large real-world cohort of a memory clinic.

METHODS

Three independent cohorts (modelling [n = 991, 59.7% female], testing [n = 642, 56.2% female] and validation [n = 441, 55.1% female]) of real-world patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI), AD dementia, and other dementias were included. Paired cerebrospinal fluid (CSF) and plasma samples were used to measure AT(N) CSF biomarkers and plasma pTau181.

FINDINGS

CSF and plasma pTau181 showed correlation in all phenotypes except in SCD and other dementias. Age significantly influenced the biomarker's performance. The general Aβ(+) vs Aβ(-) ROC curve showed an AUC = 0.77 [0.74-0.80], whereas the specific ROC curve of MCI due to AD vs non-AD MCI showed an AUC = 0.89 [0.85-0.93]. A cut-off value of 1.30 pg/ml of plasma pTau181 exhibited a sensitivity of 93.57% [88.72-96.52], specificity of 72.38% [62.51-79.01], VPP of 77.85% [70.61-83.54], and 8.30% false negatives in the subjects with MCI of the testing cohort. The HR of cox regression showed that patients with MCI up to this cut-off value exhibited a HR = 1.84 [1.05-3.22] higher risk to convert to AD dementia than patients with MCI below the cut-off value.

INTERPRETATION

Plasma pTau181 has the potential to be used in the memory clinics as a screening biomarker of AD pathology in subjects with MCI, presenting a valuable prognostic utility in predicting the MCI conversion to AD dementia. In the context of a real-world population, a confirmatory test employing gold-standard procedures is still advisable.

FUNDING

This study has been mainly funded by Ace Alzheimer Center Barcelona, Instituto de Salud Carlos III (ISCIII), Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Spanish Ministry of Science and Innovation, Fundación ADEY, Fundación Echevarne and Grífols S.A.

Association of MME gene polymorphisms with susceptibility to Alzheimer's disease in an Iranian population

Background

the MME gene encodes a membrane metalloendopeptidase, known as neprilysin (NEP). There are no reports on the potential implications of MME gene polymorphisms on the risk of Alzheimer's disease (AD) in the Iranian population. In this study, we studied the potential association of two single nucleotide polymorphisms (SNPs), rs6797911 and rs3736187, in the MME gene and the risk of developing AD in an Iranian population.

Methods

This case-control study comprised 120 AD-diagnosed patients and 120 healthy individuals without any prior family history of AD. The patient and control groups were matched for major demographic and health characteristics. Genotyping was performed by amplification refractory mutation system-polymerase chain reaction (ARMS-PCR).

Results

All patients included in this study were assessed by an experienced neurologist to exclude cases with other forms of dementia based on a brain computed tomography scan and other clinical findings. There were no significant differences in demographic and health characteristics including sex, diabetes, blood pressure, and cigarette smoking status between case and control groups (p > 0.05). However, the age difference appeared significant. Both SNPs were significantly associated with the risk of AD in our study population. The rs3736187 (T > C, 3:155168489) was strongly associated with AD risk under the log-additive model (OR = 1.67, CI = 1.18-2.37, p-value = 0.003). The rs6797911 (T > A, 3:155144601) also showed a significant association with AD risk under the dominant model (TT vs. TA and AA, OR = 3.37, CI = 1.86-6.1, p-value <0.001).

Conclusion

There is a strong association between MME gene polymorphisms and susceptibility to AD in the Iranian population. Amyloid-β (Aβ) can serve as a substrate for the NEP metalloendopeptidase, the product of the MME gene. However, the mechanistic understanding of how these genetic variations affect NEP expression, function, and consequently susceptibility to AD, is poorly understood. Further research is required to fully understand the exact implication of MME gene variations on AD, particularly in a larger, ethnicity-diverse population.

Integrating amyloid and tau imaging with proteomics and genomics in Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disease and is characterized by the aggregation of β-amyloid (Aβ) and tau in the brain. Breakthroughs in disease-modifying treatments targeting Aβ bring new hope for the management of AD. But to effectively modify and someday even prevent AD, a better understanding is needed of the biological mechanisms that underlie and link Aβ and tau in AD. Developments of high-throughput omics, including genomics, proteomics, and transcriptomics, together with molecular imaging of Aβ and tau with positron emission tomography (PET), allow us to discover and understand the biological pathways that regulate the aggregation and spread of Aβ and tau in living humans. The field of integrated omics and PET studies of Aβ and tau in AD is growing rapidly. We here provide an update of this field, both in terms of biological insights and in terms of future clinical implications of integrated omics-molecular imaging studies.

The SORL1 p.Y1816C variant causes impaired endosomal dimerization and autosomal dominant Alzheimer's disease

Truncating genetic variants of SORL1, encoding the endosome recycling receptor SORLA, have been accepted as causal of Alzheimer's disease (AD). However, most genetic variants observed in SORL1 are missense variants, for which it is complicated to determine the pathogenicity level because carriers come from pedigrees too small to be informative for penetrance estimations. Here, we describe three unrelated families in which the SORL1 coding missense variant rs772677709, that leads to a p.Y1816C substitution, segregates with Alzheimer's disease. Further, we investigate the effect of SORLA p.Y1816C on receptor maturation, cellular localization, and trafficking in cell-based assays. Under physiological circumstances, SORLA dimerizes within the endosome, allowing retromer-dependent trafficking from the endosome to the cell surface, where the luminal part is shed into the extracellular space (sSORLA). Our results showed that the p.Y1816C mutant impairs SORLA homodimerization in the endosome, leading to decreased trafficking to the cell surface and less sSORLA shedding. These trafficking defects of the mutant receptor can be rescued by the expression of the SORLA 3Fn-minireceptor. Finally, we find that iPSC-derived neurons with the engineered p.Y1816C mutation have enlarged endosomes, a defining cytopathology of AD. Our studies provide genetic as well as functional evidence that the SORL1 p.Y1816C variant is causal for AD. The partial penetrance of the mutation suggests this mutation should be considered in clinical genetic screening of multiplex early-onset AD families.

CSF proteomic profiles of neurodegeneration biomarkers in Alzheimer's disease

INTRODUCTION

We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics.

METHODS

Individuals without dementia were classified as A+ (CSF amyloid beta [Aβ]42), T+ (CSF phosphorylated tau181), and N+ or N- based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance.

RESULTS

Only a few individuals were A+T+Ng-. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng- and A+T+NfL-, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV-, A+T+HCV+ showed few proteomic changes, associated with oxidative stress.

DISCUSSION

Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology.

HIGHLIGHTS

In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau.

Identification of a specific APOE transcript and functional elements associated with Alzheimer's disease

BACKGROUND

The APOE gene is the strongest genetic risk factor for late-onset Alzheimer's Disease (LOAD). However, the gene regulatory mechanisms at this locus remain incompletely characterized.

METHODS

To identify novel AD-linked functional elements within the APOE locus, we integrated SNP variants with multi-omics data from human postmortem brains including 2,179 RNA-seq samples from 3 brain regions and two ancestries (European and African), 667 DNA methylation samples, and ChIP-seq samples. Additionally, we plotted the expression trajectory of APOE transcripts in human brains during development.

RESULTS

We identified an AD-linked APOE transcript (jxn1.2.2) particularly observed in the dorsolateral prefrontal cortex (DLPFC). The APOE jxn1.2.2 transcript is associated with brain neuropathological features, cognitive impairment, and the presence of the APOE4 allele in DLPFC. We prioritized two independent functional SNPs (rs157580 and rs439401) significantly associated with jxn1.2.2 transcript abundance and DNA methylation levels. These SNPs are located within active chromatin regions and affect brain-related transcription factor-binding affinities. The two SNPs shared effects on the jxn1.2.2 transcript between European and African ethnic groups.

CONCLUSION

The novel APOE functional elements provide potential therapeutic targets with mechanistic insight into the disease etiology.

Improving genetic risk modeling of dementia from real-world data in underrepresented populations

Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited. We employ an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compare this model with APOE and polygenic risk score models across genetic ancestry groups (Hispanic Latino American sample: 610 patients with 126 cases; African American sample: 440 patients with 84 cases; East Asian American sample: 673 patients with 75 cases), using electronic health records from UCLA Health for discovery and the All of Us cohort for validation. Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 31-84% (Wilcoxon signed-rank test p-value <0.05) and the area-under-the-receiver-operating characteristic by 11-17% (DeLong test p-value <0.05) compared to the APOE and the polygenic risk score models. We identify shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge. Our study highlights the benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.

Clinical application of whole genome sequencing in young onset dementia: challenges and opportunities

INTRODUCTION

Young onset dementia (YOD) by its nature is difficult to diagnose. Despite involvement of multidisciplinary neurogenetics services, patients with YOD and their families face significant diagnostic delays. Genetic testing for people with YOD currently involves a staggered, iterative approach. There is currently no optimal single genetic investigation that simultaneously identifies the different genetic variants resulting in YOD.

AREAS COVERED

This review discusses the advances in clinical genomic testing for people with YOD. Whole genome sequencing (WGS) can be employed as a 'one stop shop' genomic test for YOD. In addition to single nucleotide variants, WGS can reliably detect structural variants, short tandem repeat expansions, mitochondrial genetic variants as well as capture single nucleotide polymorphisms for the calculation of polygenic risk scores.

EXPERT OPINION

WGS, when used as the initial genetic test, can enhance the likelihood of a precision diagnosis and curtail the time taken to reach this. Finding a clinical diagnosis using WGS can reduce invasive and expensive investigations and could be cost effective. These advances need to be balanced against the limitations of the technology and the genetic counseling needs for these vulnerable patients and their families.

Eta-secretase-like processing of the amyloid precursor protein (APP) by the rhomboid protease RHBDL4

The amyloid precursor protein (APP) is a key protein in Alzheimer's disease synthesized in the endoplasmic reticulum (ER) and translocated to the plasma membrane where it undergoes proteolytic cleavages by several proteases. Conversely, to other known proteases, we previously elucidated rhomboid protease RHBDL4 as a novel APP processing enzyme where several cleavages likely occur already in the ER. Interestingly, the pattern of RHBDL4-derived large APP C-terminal fragments resembles those generated by the η-secretase or MT5-MMP, which was described to generate so-called Aη fragments. The similarity in large APP C-terminal fragments between both proteases raised the question of whether RHBDL4 may contribute to η-secretase activity and Aη-like fragments. Here, we identified two cleavage sites of RHBDL4 in APP by mass spectrometry, which, intriguingly, lie in close proximity to the MT5-MMP cleavage sites. Indeed, we observed that RHBDL4 generates Aη-like fragments in vitro without contributions of α-, β-, or γ-secretases. Such Aη-like fragments are likely generated in the ER since RHBDL4-derived APP-C-terminal fragments do not reach the cell surface. Inherited, familial APP mutations appear to not affect this processing pathway. In RHBDL4 knockout mice, we observed increased cerebral full-length APP in comparison to wild type (WT) in support of RHBDL4 being a physiologically relevant protease for APP. Furthermore, we found secreted Aη fragments in dissociated mixed cortical cultures from WT mice, however significantly fewer Aη fragments in RHBDL4 knockout cultures. Our data underscores that RHBDL4 contributes to the η-secretease-like processing of APP and that RHBDL4 is a physiologically relevant protease for APP.

Genome-wide analyses reveal a potential role for the MAPT, MOBP, and APOE loci in sporadic frontotemporal dementia

Frontotemporal dementia (FTD) is the second most common cause of early-onset dementia after Alzheimer disease (AD). Efforts in the field mainly focus on familial forms of disease (fFTDs), while studies of the genetic etiology of sporadic FTD (sFTD) have been less common. In the current work, we analyzed 4,685 sFTD cases and 15,308 controls looking for common genetic determinants for sFTD. We found a cluster of variants at the MAPT (rs199443; p = 2.5 × 10-12, OR = 1.27) and APOE (rs6857; p = 1.31 × 10-12, OR = 1.27) loci and a candidate locus on chromosome 3 (rs1009966; p = 2.41 × 10-8, OR = 1.16) in the intergenic region between RPSA and MOBP, contributing to increased risk for sFTD through effects on expression and/or splicing in brain cortex of functionally relevant in-cis genes at the MAPT and RPSA-MOBP loci. The association with the MAPT (H1c clade) and RPSA-MOBP loci may suggest common genetic pleiotropy across FTD and progressive supranuclear palsy (PSP) (MAPT and RPSA-MOBP loci) and across FTD, AD, Parkinson disease (PD), and cortico-basal degeneration (CBD) (MAPT locus). Our data also suggest population specificity of the risk signals, with MAPT and APOE loci associations mainly driven by Central/Nordic and Mediterranean Europeans, respectively. This study lays the foundations for future work aimed at further characterizing population-specific features of potential FTD-discriminant APOE haplotype(s) and the functional involvement and contribution of the MAPT H1c haplotype and RPSA-MOBP loci to pathogenesis of sporadic forms of FTD in brain cortex.

Association of Alzheimer's disease polygenic risk score with concussion severity and recovery metrics

Identification of genetic alleles associated with both Alzheimer's disease (AD) and concussion severity/recovery could help explain the association between concussion and elevated dementia risk. However, there has been little investigation into whether AD risk genes associate with concussion severity/recovery, and the limited findings are mixed. We used AD polygenic risk scores (PRS) and APOE genotypes to investigate any such associations in the NCAA-DoD Grand Alliance CARE Consortium (CARE) dataset. We assessed six outcomes in 931 total participants. The outcomes were two concussion recovery measures (number of days to asymptomatic status, number of days to return to play (RTP)) and four concussion severity measures (scores on SAC and BESS, SCAT symptom severity, and total number of symptoms). We calculated PRS using a published score [1] and performed multiple linear regression (MLR) to assess the relationship of PRS with the outcomes. We also used t-tests and chi-square tests to examine outcomes by APOE genotype, and MLR to analyze outcomes in European and African genetic ancestry subgroups. Higher PRS was associated with longer injury to RTP in the normal RTP (<24 days) subgroup ( p = 0.024), and one standard deviation increase in PRS resulted in a 9.89 hour increase to the RTP interval. There were no other consistently significant effects, suggesting that high AD genetic risk is not strongly associated with more severe concussions or poor recovery in young adults. Future studies should attempt to replicate these findings in larger samples with longer follow-up using PRS calculated from diverse populations.

GRPa-PRS: A risk stratification method to identify genetically-regulated pathways in polygenic diseases

Background

Polygenic risk scores (PRS) are tools used to evaluate an individual's susceptibility to polygenic diseases based on their genetic profile. A considerable proportion of people carry a high genetic risk but evade the disease. On the other hand, some individuals with a low risk of eventually developing the disease. We hypothesized that unknown counterfactors might be involved in reversing the PRS prediction, which might provide new insights into the pathogenesis, prevention, and early intervention of diseases.

Methods

We built a novel computational framework to identify genetically-regulated pathways (GRPas) using PRS-based stratification for each cohort. We curated two AD cohorts with genotyping data; the discovery (disc) and the replication (rep) datasets include 2722 and 2854 individuals, respectively. First, we calculated the optimized PRS model based on the three recent AD GWAS summary statistics for each cohort. Then, we stratified the individuals by their PRS and clinical diagnosis into six biologically meaningful PRS strata, such as AD cases with low/high risk and cognitively normal (CN) with low/high risk. Lastly, we imputed individual genetically-regulated expression (GReX) and identified differential GReX and GRPas between risk strata using gene-set enrichment and variational analyses in two models, with and without APOE effects. An orthogonality test was further conducted to verify those GRPas are independent of PRS risk. To verify the generalizability of other polygenic diseases, we further applied a default model of GRPa-PRS for schizophrenia (SCZ).

Results

For each stratum, we conducted the same procedures in both the disc and rep datasets for comparison. In AD, we identified several well-known AD-related pathways, including amyloid-beta clearance, tau protein binding, and astrocyte response to oxidative stress. Additionally, we discovered resilience-related GRPs that are orthogonal to AD PRS, such as the calcium signaling pathway and divalent inorganic cation homeostasis. In SCZ, pathways related to mitochondrial function and muscle development were highlighted. Finally, our GRPa-PRS method identified more consistent differential pathways compared to another variant-based pathway PRS method.

Conclusions

We developed a framework, GRPa-PRS, to systematically explore the differential GReX and GRPas among individuals stratified by their estimated PRS. The GReX-level comparison among those strata unveiled new insights into the pathways associated with disease risk and resilience. Our framework is extendable to other polygenic complex diseases.

Distinct patterns of plaque and microglia glycosylation in Alzheimer's disease

Glycosylation is the most common form of post-translational modification in the brain. Aberrant glycosylation has been observed in cerebrospinal fluid and brain tissue of Alzheimer's disease (AD) cases, including dysregulation of terminal sialic acid (SA) modifications. While alterations in sialylation have been identified in AD, the localization of SA modifications on cellular or aggregate-associated glycans is largely unknown because of limited spatial resolution of commonly utilized methods. The present study aims to overcome these limitations with novel combinations of histologic techniques to characterize the sialylation landscape of O- and N-linked glycans in autopsy-confirmed AD post-mortem brain tissue. Sialylated glycans facilitate important cellular functions including cell-to-cell interaction, cell migration, cell adhesion, immune regulation, and membrane excitability. Previous studies have not investigated both N- and O-linked sialylated glycans in neurodegeneration. In this study, the location and distribution of sialylated glycans were evaluated in three brain regions (frontal cortex, hippocampus, and cerebellum) from 10 AD cases using quantitative digital pathology techniques. Notably, we found significantly greater N-sialylation of the Aβ plaque microenvironment compared with O-sialylation. Plaque-associated microglia displayed the most intense N-sialylation proximal to plaque pathology. Further analyses revealed distinct differences in the levels of N- and O-sialylation between cored and diffuse Aβ plaque morphologies. Interestingly, phosphorylated tau pathology led to a slight increase in N-sialylation and no influence of O-sialylation in these AD brains. Confirming our previous observations in mice with novel histologic approach, these findings support microglia sialylation appears to have a relationship with AD protein aggregates while providing potential targets for therapeutic strategies.

APP dyshomeostasis in the pathogenesis of Alzheimer's disease: implications for current drug targets

The Amyloid precursor protein (APP) is a transmembrane glycoprotein from which amyloid-β (Aβ) peptides are generated after proteolytic cleavage. Aβ peptides are the main constituent of amyloid plaques in Alzheimer's Disease (AD). The physiological functions of APP in the human adult brain are very diverse including intracellular signaling, synaptic and neuronal plasticity, and cell adhesion, among others. There is growing evidence that APP becomes dysfunctional in AD and that this dyshomeostasis may impact several APP functions beyond Aβ generation. The vast majority of current anti-amyloid approaches in AD have focused on reducing the synthesis of Aβ or increasing the clearance of brain Aβ aggregates following a paradigm in which Aβ plays a solo in APP dyshomeostasis. A wider view places APP at the center stage in which Aβ is an important, but not the only, factor involved in APP dyshomeostasis. Under this paradigm, APP dysfunction is universal in AD, but with some differences across different subtypes. Little is known about how to approach APP dysfunction therapeutically beyond anti-Aβ strategies. In this review, we will describe the role of APP dyshomeostasis in AD beyond Aβ and the potential therapeutic strategies targeting APP.

Single-cell atlas of ABCA7 loss-of-function reveals impaired neuronal respiration via choline-dependent lipid imbalances

Loss-of-function (LoF) variants in the lipid transporter ABCA7 significantly increase the risk of Alzheimer's disease (odds ratio ∼2), yet the pathogenic mechanisms and the neural cell types affected by these variants remain largely unknown. Here, we performed single-nuclear RNA sequencing of 36 human post-mortem samples from the prefrontal cortex of 12 ABCA7 LoF carriers and 24 matched non-carrier control individuals. ABCA7 LoF was associated with gene expression changes in all major cell types. Excitatory neurons, which expressed the highest levels of ABCA7, showed transcriptional changes related to lipid metabolism, mitochondrial function, cell cycle-related pathways, and synaptic signaling. ABCA7 LoF-associated transcriptional changes in neurons were similarly perturbed in carriers of the common AD missense variant ABCA7 p.Ala1527Gly (n = 240 controls, 135 carriers), indicating that findings from our study may extend to large portions of the at-risk population. Consistent with ABCA7's function as a lipid exporter, lipidomic analysis of isogenic iPSC-derived neurons (iNs) revealed profound intracellular triglyceride accumulation in ABCA7 LoF, which was accompanied by a relative decrease in phosphatidylcholine abundance. Metabolomic and biochemical analyses of iNs further indicated that ABCA7 LoF was associated with disrupted mitochondrial bioenergetics that suggested impaired lipid breakdown by uncoupled respiration. Treatment of ABCA7 LoF iNs with CDP-choline (a rate-limiting precursor of phosphatidylcholine synthesis) reduced triglyceride accumulation and restored mitochondrial function, indicating that ABCA7 LoF-induced phosphatidylcholine dyshomeostasis may directly disrupt mitochondrial metabolism of lipids. Treatment with CDP-choline also rescued intracellular amyloid β -42 levels in ABCA7 LoF iNs, further suggesting a link between ABCA7 LoF metabolic disruptions in neurons and AD pathology. This study provides a detailed transcriptomic atlas of ABCA7 LoF in the human brain and mechanistically links ABCA7 LoF-induced lipid perturbations to neuronal energy dyshomeostasis. In line with a growing body of evidence, our study highlights the central role of lipid metabolism in the etiology of Alzheimer's disease.

Optimizing clinico-genomic disease prediction across ancestries: a machine learning strategy with Pareto improvement

BACKGROUND

Accurate prediction of an individual's predisposition to diseases is vital for preventive medicine and early intervention. Various statistical and machine learning models have been developed for disease prediction using clinico-genomic data. However, the accuracy of clinico-genomic prediction of diseases may vary significantly across ancestry groups due to their unequal representation in clinical genomic datasets.

METHODS

We introduced a deep transfer learning approach to improve the performance of clinico-genomic prediction models for data-disadvantaged ancestry groups. We conducted machine learning experiments on multi-ancestral genomic datasets of lung cancer, prostate cancer, and Alzheimer's disease, as well as on synthetic datasets with built-in data inequality and distribution shifts across ancestry groups.

RESULTS

Deep transfer learning significantly improved disease prediction accuracy for data-disadvantaged populations in our multi-ancestral machine learning experiments. In contrast, transfer learning based on linear frameworks did not achieve comparable improvements for these data-disadvantaged populations.

CONCLUSIONS

This study shows that deep transfer learning can enhance fairness in multi-ancestral machine learning by improving prediction accuracy for data-disadvantaged populations without compromising prediction accuracy for other populations, thus providing a Pareto improvement towards equitable clinico-genomic prediction of diseases.

Multi-organ imaging-derived polygenic indexes for brain and body health

The UK Biobank (UKB) imaging project is a crucial resource for biomedical research, but is limited to 100,000 participants due to cost and accessibility barriers. Here we used genetic data to predict heritable imaging-derived phenotypes (IDPs) for a larger cohort. We developed and evaluated 4,375 IDP genetic scores (IGS) derived from UKB brain and body images. When applied to UKB participants who were not imaged, IGS revealed links to numerous phenotypes and stratified participants at increased risk for both brain and somatic diseases. For example, IGS identified individuals at higher risk for Alzheimer's disease and multiple sclerosis, offering additional insights beyond traditional polygenic risk scores of these diseases. When applied to independent external cohorts, IGS also stratified those at high disease risk in the All of Us Research Program and the Alzheimer's Disease Neuroimaging Initiative study. Our results demonstrate that, while the UKB imaging cohort is largely healthy and may not be the most enriched for disease risk management, it holds immense potential for stratifying the risk of various brain and body diseases in broader external genetic cohorts.

Cognitively healthy centenarians are genetically protected against Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) prevalence increases with age, yet a small fraction of the population reaches ages > 100 years without cognitive decline. We studied the genetic factors associated with such resilience against AD.

METHODS

Genome-wide association studies identified 86 single nucleotide polymorphisms (SNPs) associated with AD risk. We estimated SNP frequency in 2281 AD cases, 3165 age-matched controls, and 346 cognitively healthy centenarians. We calculated a polygenic risk score (PRS) for each individual and investigated the functional properties of SNPs enriched/depleted in centenarians.

RESULTS

Cognitively healthy centenarians were enriched with the protective alleles of the SNPs associated with AD risk. The protective effect concentrated on the alleles in/near ANKH, GRN, TMEM106B, SORT1, PLCG2, RIN3, and APOE genes. This translated to >5-fold lower PRS in centenarians compared to AD cases (P = 7.69 × 10-71), and 2-fold lower compared to age-matched controls (P = 5.83 × 10-17).

DISCUSSION

Maintaining cognitive health until extreme ages requires complex genetic protection against AD, which concentrates on the genes associated with the endolysosomal and immune systems.

HIGHLIGHTS

Cognitively healthy cent enarians are enriched with the protective alleles of genetic variants associated with Alzheimer's disease (AD). The protective effect is concentrated on variants involved in the immune and endolysosomal systems. Combining variants into a polygenic risk score (PRS) translated to > 5-fold lower PRS in centenarians compared to AD cases, and ≈ 2-fold lower compared to middle-aged healthy controls.

Mid-to-Late Life Healthy Lifestyle Modifies Genetic Risk for Longitudinal Cognitive Aging among Asymptomatic Individuals

IMPORTANCE

Genetic and lifestyle factors contribute to an individual's risk of developing Alzheimer's disease. However, it is unknown whether and how adherence to healthy lifestyles can mitigate the genetic risk of Alzheimer's.

OBJECTIVE

The aim of this study is to investigate whether adherence to healthy lifestyles can modify the impact of genetic predisposition to Alzheimer's disease on later-life cognitive decline.

DESIGN SETTING AND PARTICIPANTS

This prospective cohort study included 891 adults of European ancestry, aged 40 to 65, who were without dementia and had complete healthy-lifestyle and cognition data during the follow-up. Participants joined the Wisconsin Registry for Alzheimer's Prevention (WRAP) beginning in 2001. We conducted replication analyses using a subsample with similar baseline age range from the Health and Retirement Study (HRS).

EXPOSURES

We assessed participants' exposures using a continuous non-APOE polygenic risk score for Alzheimer's, a binary indicator for APOE-ε4 carrier status, and a weighted healthy-lifestyle score, including factors such as no current smoking, regular physical activity, healthy diet, light to moderate alcohol consumption, and frequent cognitive activities.

MAIN OUTCOMES AND MEASURES

We z-standardized cognitive scores for global (Preclinical Alzheimer's Cognitive Composite score 3 - PACC3) and domain-specific assessments (delayed recall and immediate learning).

RESULTS

We followed 891 individuals for up to 10 years (mean [SD] baseline age, 58 [6] years, 31% male, 38% APOE-ε4 carriers). After false discovery rate (FDR) correction, we found statistically significant PRS × lifestyle × age interactions on preclinical cognitive decline but the evidence is stronger among APOE-ε4 carriers. Among APOE-ε4 carriers, PRS-related differences in overall and memory-related domains between people scoring 0-1 and 4-5 regarding healthy lifestyles became evident around age 67 after FDR correction. These findings were robust across several sensitivity analyses and were replicated in the population-based HRS.

CONCLUSION

A favorable lifestyle can mitigate the genetic risk associated with current known non-APOE genetic variants for longitudinal cognitive decline, and these protective effects are particularly pronounced among APOE-ε4 carriers.

Identification of mitochondria-related biomarkers in childhood allergic asthma

BACKGROUND

The mechanism of mitochondria-related genes (MRGs) in childhood allergic asthma (CAS) was unclear. The aim of this study was to find new biomarkers related to MRGs in CAS.

METHODS

This research utilized two CAS-related datasets (GSE40888 and GSE40732) and extracted 40 MRGs from the MitoCarta3.0 Database. Initially, differential expression analysis was performed on CAS and control samples in the GSE40888 dataset to obtain the differentially expressed genes (DEGs). Differentially expressed MRGs (DE-MRGs) were obtained by overlapping the DEGs and MRGs. Protein protein interactions (PPI) network of DE-MRGs was created and the top 10 genes in the degree ranking of Maximal Clique Centrality (MCC) algorithm were defined as feature genes. Hub genes were obtained from the intersection genes from the Least absolute shrinkage and selection operator (LASSO) and EXtreme Gradient Boosting (XGBoost) algorithms. Additionally, the expression validation was conducted, functional enrichment analysis, immune infiltration analysis were finished, and transcription factors (TFs)-miRNA-mRNA regulatory network was constructed.

RESULTS

A total of 1505 DEGs were obtained from the GSE40888, and 44 DE-MRGs were obtained. A PPI network based on these 44 DE-MRGs was created and revealed strong interactions between ADCK5 and MFN1, BNIP3 and NBR1. Four hub genes (NDUFAF7, MTIF3, MRPS26, and NDUFAF1) were obtained by taking the intersection of genes from the LASSO and XGBoost algorithms based on 10 signature genes which obtained from PPI. In addition, hub genes-based alignment diagram showed good diagnostic performance. The results of Gene Set Enrichment Analysis (GSEA) suggested that hub genes were closely related to mismatch repair. The B cells naive cells were significantly expressed between CAS and control groups, and MTIF3 was most strongly negatively correlated with B cells naive. In addition, the expression of MTIF3 and MRPS26 may have influenced the inflammatory response in CAS patients by affecting mitochondria-related functions. The quantitative real-time polymerase chain reaction (qRT‒PCR) results showed that four hub genes were all down-regulated in the CAS samples.

CONCLUSION

NDUFAF7, MTIF3, MRPS26, and NDUFAF1 were identified as an MRGs-related biomarkers in CAS, which provides some reference for further research on CAS.

Walking time and genetic predisposition for Alzheimer's disease: Results from the HELIAD study

Objective: Our study aimed to explore whether physical condition might affect the association between genetic predisposition for Alzheimer's Disease (AD) and AD incidence. Methods: The sample of participants consisted of 561 community-dwelling adults over 64 years old, without baseline dementia (508 cognitively normal and 53 with mild cognitive impairment), deriving from the HELIAD, an ongoing longitudinal study with follow-up evaluations every 3 years. Physical condition was assessed at baseline through walking time (WT), while a Polygenic Risk Score for late onset AD (PRS-AD) was used to estimate genetic predisposition. The association between WT and PRS-AD with AD incidence was evaluated with Cox proportional hazard models adjusted for age, sex, education years, global cognition score and APOE ε-4 genotype. Then, the association between WT and AD incidence was investigated after stratifying participants by low and high PRS-AD. Finally, we examined the association between PRS-AD and AD incidence after stratifying participants by WT. Results: Both WT and PRS-AD were connected with increased AD incidence (p < 0.05), after adjustments. In stratified analyses, in the slow WT group participants with a greater genetic risk had a 2.5-fold higher risk of developing AD compared to participants with lower genetic risk (p = 0.047). No association was observed in the fast WT group or when participants were stratified based on PRS-AD. Conclusions: Genetic predisposition for AD is more closely related to AD incidence in the group of older adults with slow WT. Hence, physical condition might be a modifier in the relationship of genetic predisposition with AD incidence.

Lessons from genetic studies in Alzheimer disease

Research on Alzheimer disease (AD) genetics has provided critical advances to the knowledge of AD pathophysiological mechanisms. The etiology of AD can be divided into monogenic (autosomal dominant inheritance) and complex (multifactorial determinism). In monogenic AD, recent advances mainly concern mutation-associated mechanisms, presymptomatic clinical studies, and the search for modifiers of ages of onset that are still ongoing. In complex AD, genetic factors can be further categorized into three classes: (i) the APOE-ɛ4 and ɛ2 common alleles that represent a category by themselves as they are both common and with a strong impact on AD risk; (ii) common variants with a modest effect, identified in genome-wide association studies (GWAS); and (iii) rare variants with a moderate-to-strong effect, identified in case-control sequencing studies. Regarding APOE, odds ratios, available in multiple ethnicities, can now be converted into penetrance curves, although such curves remain to be performed in diverse ethnicities. In addition, advances in the understanding of mechanisms have been recently reported and rare APOE variants add to the complexity. In the GWAS category, novel loci have been discovered thanks to larger studies, doubling the number of hits as compared to the previous reference meta-analysis. However, such modest risk factors cannot be used in the clinic, neither individually, nor in genetic risk scores. In the category of rare variants, two novel genes, ABCA1 and ATP8B4 now add to the three main ones, TREM2, SORL1, and ABCA7. The study of such rare variants suggests oligogenic inheritance in some families, as also suggested by digenic penetrance curves for SORL1 loss-of-function variants with APOE-ɛ4. Cumulate frequencies of definite (so-called) rare risk factors are 2.3% to 3.6% (depending on thresholds on odds ratios) in control databases and many more remain to be classified and identified, showing how important these risk factors may be as part of the complex determinism of AD. A better understanding of these rare risk factors and their combined effects on each other, with common variants, and with environmental factors, should allow for a prediction of AD risk and, eventually, preventive medicine. Taken together, most genetic determinants of AD, in monogenic and in complex forms, point toward the aggregation of Aβ as a pivotal triggering factor, such that targeting it may be efficient as prevention in at-risk individuals. The role of neuroinflammation, microglia, and Tau pathology modulation are important sources of research for disease modification.

Large-scale Deep Proteomic Analysis in Alzheimer's Disease Brain Regions Across Race and Ethnicity

Introduction

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non-Hispanic White (NHW) population. Here we aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial and ethnic groups.

Methods

Dorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (998 unique individuals), 333 were from African American donors, 223 from Latino Americans, 529 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG tissue samples (244 unique individuals), 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag mass spectrometry (TMT-MS).

Results

As a Quality control (QC) measure, proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. After QC, 9,180 and 9,734 proteins remained in the DLPC and STG proteome, respectively, of which approximately 9,000 proteins were shared between regions. Protein levels of microtubule-associated protein tau (MAPT) and amyloid-precursor protein (APP) demonstrated AD-related elevations in DLPFC tissues with a strong association with CERAD and Braak across racial groups. APOE4 protein levels in brain were highly concordant with APOE genotype of the individuals.

Discussion

This comprehensive region resolved large-scale proteomic dataset provides a resource for the understanding of ethnoracial-specific protein differences in AD brain.

Is Alzheimer disease a disease?

Dementia, a prevalent condition among older individuals, has profound societal implications. Extensive research has resulted in no cure for what is perceived as the most common dementing illness: Alzheimer disease (AD). AD is defined by specific brain abnormalities - amyloid-β plaques and tau protein neurofibrillary tangles - that are proposed to actively influence the neurodegenerative process. However, conclusive evidence of amyloid-β toxicity is lacking, the mechanisms leading to the accumulation of plaques and tangles are unknown, and removing amyloid-β has not halted neurodegeneration. So, the question remains, are we making progress towards a solution? The complexity of AD is underscored by numerous genetic and environmental risk factors, and diverse clinical presentations, suggesting that AD is more akin to a syndrome than to a traditional disease, with its pathological manifestation representing a convergence of pathogenic pathways. Therefore, a solution requires a multifaceted approach over a single 'silver bullet'. Improved recognition and classification of conditions that converge in plaques and tangle accumulation and their treatment requires the use of multiple strategies simultaneously.

Recent advances in Alzheimer disease genetics

PURPOSE OF REVIEW

Genetics studies provide important insights into Alzheimer disease (AD) etiology and mechanisms. Critical advances have been made recently, mainly thanks to the access to novel techniques and larger studies.

RECENT FINDINGS

In monogenic AD, progress has been made with a better understanding of the mechanisms associated with pathogenic variants and the input of clinical studies in presymptomatic individuals. In complex AD, increasing sample sizes in both DNA chip-based (genome-wide association studies, GWAS) and exome/genome sequencing case-control studies unveiled novel common and rare risk factors, while the understanding of their combined effect starts to suggest the existence of rare families with oligogenic inheritance of early-onset, nonmonogenic, AD.

SUMMARY

Most genetic risk factors with a known consequence designate the aggregation of the Aβ peptide as a core etiological factor in complex AD thus confirming that the research based on monogenic AD - where the amyloid cascade seems more straightforward - is relevant to complex AD as well. Novel mechanistic insights and risk factor studies unveiling novel factors and attempting to combine the effect of common and rare variants will offer promising perspectives for future AD prevention, at least regarding early-onset AD, and probably in case of later onset as well.

Whole genome-wide sequence analysis of long-lived families (Long-Life Family Study) identifies MTUS2 gene associated with late-onset Alzheimer's disease

INTRODUCTION

Late-onset Alzheimer's disease (LOAD) has a strong genetic component. Participants in Long-Life Family Study (LLFS) exhibit delayed onset of dementia, offering a unique opportunity to investigate LOAD genetics.

METHODS

We conducted a whole genome sequence analysis of 3475 LLFS members. Genetic associations were examined in six independent studies (N = 14,260) with a wide range of LOAD risk. Association analysis in a sub-sample of the LLFS cohort (N = 1739) evaluated the association of LOAD variants with beta amyloid (Aβ) levels.

RESULTS

We identified several single nucleotide polymorphisms (SNPs) in tight linkage disequilibrium within the MTUS2 gene associated with LOAD (rs73154407, p = 7.6 × 10-9). Association of MTUS2 variants with LOAD was observed in the five independent studies and was significantly stronger within high levels of Aβ42/40 ratio compared to lower amyloid.

DISCUSSION

MTUS2 encodes a microtubule associated protein implicated in the development and function of the nervous system, making it a plausible candidate to investigate LOAD biology.

HIGHLIGHTS

Long-Life Family Study (LLFS) families may harbor late onset Alzheimer's dementia (LOAD) variants. LLFS whole genome sequence analysis identified MTUS2 gene variants associated with LOAD. The observed LLFS variants generalized to cohorts with wide range of LOAD risk. The association of MTUS2 with LOAD was stronger within high levels of beta amyloid. Our results provide evidence for MTUS2 gene as a novel LOAD candidate locus.

Immediate-Early Genes as Influencers in Genetic Networks and their Role in Alzheimer's Disease

Immediate-early genes (IEGs) are a class of activity-regulated genes (ARGs) that are transiently and rapidly activated in the absence of de novo protein synthesis in response to neuronal activity. We explored the role of IEGs in genetic networks to pinpoint potential drug targets for Alzheimer's disease (AD). Using a combination of network analysis and genome-wide association study (GWAS) summary statistics we show that (1) IEGs exert greater topological influence across different human and mouse gene networks compared to other ARGs, (2) ARGs are sparsely involved in diseases and significantly more mutational constrained compared to non-ARGs, (3) Many AD-linked variants are in ARGs gene regions, mainly in MARK4 near FOSB, with an AD risk eQTL that increases MARK4 expression in cortical areas, (4) MARK4 holds an influential place in a dense AD multi-omic network and a high AD druggability score. Our work on IEGs' influential network role is a valuable contribution to guiding interventions for diseases marked by dysregulation of their downstream targets and highlights MARK4 as a promising underexplored AD-target.