The nervous system processes a vast amount of information, performing computations that underlie perception, cognition, and behavior. During development, neuronal guidance genes, which encode extracellular cues, their receptors, and downstream signal transducers, organize neural wiring to generate the complex architecture of the nervous system. It is now evident that many of these neuroguidance cues and their receptors are active during development and are also expressed in the adult nervous system. This suggests that neuronal guidance pathways are critical not only for neural wiring but also for ongoing function and maintenance of the mature nervous system. Supporting this view, these pathways continue to regulate synaptic connectivity, plasticity, and remodeling, and overall brain homeostasis throughout adulthood. Genetic and transcriptomic analyses have further revealed many neuronal guidance genes to be associated with a wide range of neurodegenerative and neuropsychiatric disorders. Although the precise mechanisms by which aberrant neuronal guidance signaling drives the pathogenesis of these diseases remain to be clarified, emerging evidence points to several common themes, including dysfunction in neurons, microglia, astrocytes, and endothelial cells, along with dysregulation of neuron-microglia-astrocyte, neuroimmune, and neurovascular interactions. In this review, we explore recent advances in understanding the molecular and cellular mechanisms by which aberrant neuronal guidance signaling contributes to disease pathogenesis through altered cell-cell interactions. For instance, recent studies have unveiled two distinct semaphorin-plexin signaling pathways that affect microglial activation and neuroinflammation. We discuss the challenges ahead, along with the therapeutic potentials of targeting neuronal guidance pathways for treating neurodegenerative diseases. Particular focus is placed on how neuronal guidance mechanisms control neuron-glia and neuroimmune interactions and modulate microglial function under physiological and pathological conditions. Specifically, we examine the crosstalk between neuronal guidance signaling and TREM2, a master regulator of microglial function, in the context of pathogenic protein aggregates. It is well-established that age is a major risk factor for neurodegeneration. Future research should address how aging and neuronal guidance signaling interact to influence an individual's susceptibility to various late-onset neurological diseases and how the progression of these diseases could be therapeutically blocked by targeting neuronal guidance pathways.

The SORL1 gene encodes the sortilin-related receptor protein SORLA, a sorting receptor that regulates endo-lysosomal trafficking of various substrates. Loss of function variants in SORL1 are causative for Alzheimer's disease (AD) and decreased expression of SORLA has been repeatedly observed in human AD brains. SORL1 is highly expressed in the central nervous system, including in microglia, the tissue-resident immune cells of the brain. Loss of SORLA leads to enlarged lysosomes in hiPSC-derived microglia-like cells (hMGLs). However, how SORLA deficiency contributes to lysosomal dysfunction in microglia and how this contributes to AD pathogenesis is not known. In this study, we show that loss of SORLA results in decreased lysosomal degradation and lysosomal enzyme activity due to altered trafficking of lysosomal enzymes in hMGLs. Phagocytic uptake of fibrillar amyloid beta 1-42 and synaptosomes is increased in SORLA-deficient hMGLs, but due to reduced lysosomal degradation, these substrates aberrantly accumulate in lysosomes. An alternative mechanism of lysosome clearance, lysosomal exocytosis, is also impaired in SORL1-deficient microglia, which may contribute to an altered immune response. Overall, these data suggest that SORLA has an important role in the proper trafficking of lysosomal hydrolases in hMGLs, which is critical for microglial function. This further substantiates the microglial endo-lysosomal network as a potential novel pathway through which SORL1 may increase AD risk and contribute to the development of AD. Additionally, our findings may inform the development of novel lysosome and microglia-associated drug targets for AD.

Reactive astrocytes are associated with Alzheimer's disease (AD), and several AD genetic risk variants are associated with genes highly expressed in astrocytes. However, the contribution of genetic risk within astrocytes to cellular processes relevant to the pathogenesis of AD remains ill-defined. Here, we present a resource for studying AD genetic risk in astrocytes using a large collection of induced pluripotent stem cell (iPSC) lines from deeply phenotyped individuals with a range of neuropathological and cognitive outcomes. IPSC lines from 44 individuals were differentiated into astrocytes followed by unbiased molecular profiling using RNA sequencing and tandem mass tag-mass spectrometry. We demonstrate the utility of this resource in examining gene- and pathway-level associations with clinical and neuropathological traits, as well as in analyzing genetic risk and resilience factors through parallel analyses of iPSC-astrocytes and brain tissue from the same individuals. Our analyses reveal that genes and pathways altered in iPSC-derived astrocytes from individuals with AD are concordantly dysregulated in AD brain tissue. This includes increased levels of prefoldin proteins, extracellular matrix factors, COPI-mediated trafficking components and reduced levels of proteins involved in cellular respiration and fatty acid oxidation. Additionally, iPSC-derived astrocytes from individuals resilient to high AD neuropathology show elevated basal levels of interferon response proteins and increased secretion of interferon gamma. Correspondingly, higher polygenic risk scores for AD are associated with lower levels of interferon response proteins in astrocytes. This study establishes an experimental system that integrates genetic information with a matched iPSC lines and brain tissue data from a large cohort of individuals to identify genetic contributions to molecular pathways affecting AD risk and resilience.

The function of microglia during progression of Alzheimer's disease (AD) can be investigated using mouse models that enable genetic manipulation of microglial subpopulations in a temporal manner. We developed mouse lines that express either Cre recombinase (Cre) for constitutive targeting, or destabilized-domain Cre recombinase (DD-Cre) for inducible targeting from the Cst7 locus (Cst7 DD-Cre) to specifically manipulate disease associated microglia (DAM) and crossed with Ai14 tdTomato cre-reporter line mice. Cst7Cre was found to target all brain resident myeloid cells, due to transient developmental expression of Cst7, but no expression was found in the inducible Cst7 DD-Cre mice. Further crossing of this line with 5xFAD mice combined with dietary administration of trimethoprim to induce DD-Cre activity produces long-term labeling in DAM without evidence of leakiness, with tdTomato-expression restricted to cells surrounding plaques. Using this model, we found that DAMs are a subset of plaque-associated microglia (PAMs) and their transition to DAM increases with age and disease stage. Spatial transcriptomic analysis revealed that tdTomato+ cells show higher expression of disease and inflammatory genes compared to other microglial populations, including non-labeled PAMs. These models allow either complete cre-loxP targeting of all brain myeloid cells (Cst7Cre), or inducible targeting of DAMs, without leakiness (Cst7 DD-Cre).

Alzheimer's disease (AD) remains a formidable challenge in neurodegeneration research, with limited therapeutic options despite decades of study. While Drosophila melanogaster has been instrumental in in modeling AD related Tau and amyloid beta toxicity, inflammation, a key driver of AD pathology, remains unexplored in fly models. Given the evolutionary conservation of innate immune pathways between flies and mammals, drosophila presents a powerful yet underutilized tool for inflammation led drug discovery in AD.

This perspective highlights the relevance of Drosophila in studying neuroinflammatory processes, including microglial-like glial activation, systemic inflammation and gut-brain axis interactions. It further explores how fly models can be leveraged to screen anti-inflammatory compounds and dissect immune related genetic factors implicated in AD.

By integrating immune modulation in Drosophila-based drug discovery pipeline we can accelerate the identification of novel therapeutic strategies. Fully exploiting the potential of Drosophila in inflammation led drug screening may usher in a new era of AD therapeutics, bridging gaps between fundamental research and translational medicine.

Although many studies have investigated the influence of HLA on the risk of Alzheimer's Disease (AD), there have been inconsistent results. Part of this problem has been attributed to limitations of a clinical assessment in the absence of histopathological confirmation or other quantitative assessments. This study employed a subset of the AD Sequencing Project, representing 2663 cases with histopathological confirmation of AD and confirmation of 881 cognitively normal cases. Two HLA allelic subtypes, DQB1*02:01 and DQB1*02:02, were associated with lower Braak staging, a measure of tauopathy in the brain. These HLA subtypes were also associated with a later age of onset. There was a lower occurrence of HLA-DQB1*02:01 and HLA-DQB1*02:02 in AD cases compared to cognitively normal cases. For all of the above results, replicative sets were confirmatory. The above results were also maintained for both HLA-DQB1*02:01 and HLA-DQB1*02:02 when removing the effect of APOE4 or APOE2. Interestingly, the HLA-DQB1*02 allele binds tau better than all other HLA-DQB1 alleles tested, per an in silico assessment, raising the question of whether deletion of tau binding, auto-reactive T-cells in the thymus could reduce the likelihood of the onset of AD?

Alzheimer's disease (AD) is a multifaceted neurodegenerative condition distinguished by the occurrence of memory impairment, cognitive deterioration, and neuronal impairment. Despite extensive research efforts, conventional treatment strategies primarily focus on symptom management, highlighting the need for innovative therapeutic approaches. This review explores the challenges of AD treatment and the integration of computational methodologies to advance therapeutic interventions. A comprehensive analysis of recent literature was conducted to elucidate the broad scope of Alzheimer's etiology and the limitations of conventional drug discovery approaches. Our findings underscore the critical role of computational models in elucidating disease mechanisms, identifying therapeutic targets, and expediting drug discovery. Through computational simulations, researchers can predict drug efficacy, optimize lead compounds, and facilitate personalized medicine approaches. Moreover, machine learning algorithms enhance early diagnosis and enable precision medicine strategies by analyzing multi-modal datasets. Case studies highlight the application of computational techniques in AD therapeutics, including the suppression of crucial proteins implicated in disease progression and the repurposing of existing drugs for AD management. Computational models elucidate the interplay between oxidative stress and neurodegeneration, offering insights into potential therapeutic interventions. Collaborative efforts between computational biologists, pharmacologists, and clinicians are essential to translate computational insights into clinically actionable interventions, ultimately improving patient outcomes and addressing the unmet medical needs of individuals affected by AD. Overall, integrating computational methodologies represents a promising paradigm shift in AD therapeutics, offering innovative solutions to overcome existing challenges and transform the landscape of AD treatment.

Polygenic risk scores (PRS) have ushered in a new era in genetic epidemiology, offering insights into individual predispositions to a wide range of diseases. However, despite recent marked enhancements in predictive power, PRS-based models still need to overcome several hurdles before they can be broadly applied in the clinic. Chiefly, they need to achieve sufficient accuracy, easy interpretability and portability across diverse populations. Leveraging trans-ancestry genome-wide association study (GWAS) meta-analysis, we generated novel, diverse summary statistics for 30 medically-related traits and benchmarked the performance of six existing PRS algorithms using UK Biobank. We built an ensemble model using logistic regression to combine outputs of top-performing algorithms and validated it on the diverse eMERGE and PAGE MEC cohorts. It surpassed current state-of-the-art PRS models, with minimal performance drops in external cohorts, indicating good calibration. To enhance predictive accuracy for clinical application, we incorporated easily-accessible clinical characteristics such as age, gender, ancestry and risk factors, creating disease prediction models intended as prospective diagnostic tests, with easily interpretable positive or negative outcomes. After adding clinical characteristics, 12 out of 30 models surpassed 80% AUC. Further, 25 traits exceeded the diagnostic odds ratio (DOR) of five, and 19 traits exceeded DOR of 10 for all ancestry groups, indicating high predictive value. Our PRS model for coronary artery disease identified 55-80 times more true coronary events than rare pathogenic variant models, reinforcing its clinical potential. The polygenic component modulated the effect of high-risk rare variants, stressing the need to consider all genetic components in clinical settings. These findings show that newly developed PRS-based disease prediction models have sufficient accuracy and portability to warrant consideration of being used in the clinic.

Epigenomic profiling of the brain has largely been done on bulk tissues, limiting our understanding of cell type-specific epigenetic changes in disease states. Here, we introduce cell type-specific histone acetylation score (CHAS), a computational tool for inferring cell type-specific signatures in bulk brain H3K27ac profiles. We applied CHAS to >300 H3K27ac chromatin immunoprecipitation sequencing samples from studies of Alzheimer's disease, Parkinson's disease, autism spectrum disorder, schizophrenia, and bipolar disorder in bulk postmortem brain tissue. In addition to recapitulating known disease-associated shifts in cellular proportions, we identified cell type-specific biological insights into brain-disorder-associated regulatory variation. In most cases, genetic risk and epigenetic dysregulation targeted different cell types, suggesting independent mechanisms. For instance, genetic risk of Alzheimer's disease was exclusively enriched within microglia, while epigenetic dysregulation predominantly fell within oligodendrocyte-specific H3K27ac regions. In addition, reanalysis of the original datasets using CHAS enabled identification of biological pathways associated with each neurological and psychiatric disorder at cellular resolution.

Alzheimer's disease related pathologies, neurodegenerative pathologies, and vascular neuropathologies are common in older adults at death. Previous studies using the National Alzheimer's Coordinating Center (NACC) have not investigated the association between age at death and apolipoprotein E (APOE) ε4 and the prevalence of neuropathologies found at autopsy. We used autopsy confirmed neuropathology data from the NACC to examine the interactive effects of age and APOE ε4 on various neuropathologies (N = 5,843) using modified Poisson regression to estimate the prevalence ratios. Significant interactions between APOE ε4 and age at death were observed for neuritic plaques, Braak staging, diffuse neuritic plaques, and Lewy body disease pathology, with the effect of APOE ε4 decreasing at older ages. In contrast, a significant positive interaction was found for hemorrhages/microbleeds, indicating that the association between APOE ε4 and microbleeds strengthens with increasing age. These findings suggest that future therapeutic strategies should consider both genetic risk and age to effectively target AD progression.

Neurocognitive disorders (NCD) are neurodegenerative diseases characterized by decline or loss of cognitive functions. Aging and the APOE genotype have been identified as major risk factors. Telomere length (TL) has been proposed as a biomarker of aging, with shorter TL associated with cognitive decline. This study investigated the relationship between TL and the APOE genotype in individuals with cognitive impairments (CIs). A total of 170 participants aged >55 years were included. Cognitive function was assessed using the MMSE and MoCA tests. Relative telomere quantification and APOE genotype were determined by real-time PCR. A significant association was observed between shorter TL and an increased risk of CI (p < 0.001). Although APOE ε4 is a known genetic risk factor, its association with CI was less clear in this study population, as a considerable proportion of ε4 carriers did not present cognitive impairment (p < 0.05). However, ε4 carriers with CI tended to have shorter TL than those with non-cognitive impairment (NCI-SMC). Furthermore, fewer years of education were strongly correlated with higher CI risk (p < 0.0001). Overall, individuals with both shorter telomeres and lower educational levels exhibited the highest risk of CI. APOE ε4 may contribute to telomere shortening.

Among the more than 90 identified genetic risk loci for late-onset Alzheimer's disease (AD) and related dementias, the apolipoprotein E gene (APOE) ε2/ε3/ε4 polymorphism remains the longstanding benchmark for genetic disease risk with a consistently large effect across studies1-10. Despite this massive signal, the exact mechanisms for how ε4 increases and for how ε2 decreases dementia risk is not well-understood. Importantly, recent trials of anti-amyloid therapies suggest less efficacy and higher risks of severe side effects in s4 carriers11-13, hampering the treatment of those with the highest unmet need. To improve our understanding of the genetic architecture of AD in the context of its main genetic driver, we performed genome-wide association studies (GWASs) stratified by ε4 and ε2 carrier status. Such insights may help to understand and overcome side effects, to impact clinical trial enrolment strategies, and to create the scientific basis for targeted mechanism-driven therapies in neurodegenerative diseases.

The escalating prevalence of dementia worldwide necessitates preventive strategies to mitigate its extensive health, psychological, and social impacts. As the prevalence of dementia continues to rise, gaining insights into its risk factors and causes becomes paramount, given the absence of a definitive cure. Cardiovascular disease has emerged as a prominent player in the complex landscape of dementia. Preventing dyslipidaemia, unhealthy western-type diets, hypertension, diabetes, being overweight, physical inactivity, smoking, and high alcohol intake have the potential to diminish not only cardiovascular disease but also dementia. The purpose of this review is to present our current understanding of cardiovascular risk factors for Alzheimer's disease and vascular dementia (VaD) by using clinical human data from observational, genetic studies and clinical trials, while elaborating on potential mechanisms. Hypertension and Type 2 diabetes surface as significant causal risk factors for both Alzheimer's disease and VaD, as consistently illustrated in observational and Mendelian randomization studies. Anti-hypertensive drugs and physical activity have been shown to improve cognitive function in clinical trials. Important to note is that robust genome-wide association studies are lacking for VaD, and indeed more and prolonged clinical trials are needed to establish these findings and investigate other risk factors. Trials should strategically target individuals at the highest dementia risk, identified using risk charts incorporating genetic markers, biomarkers, and cardiovascular risk factors. Understanding causal risk factors for dementia will optimize preventive measures, and the implementation of well-known therapeutics can halt or alleviate dementia symptoms if started early. Needless to mention is that future health policies should prioritize primordial prevention from early childhood to prevent risk factors from even occurring in the first place. Together, understanding the role of cardiovascular risk factors in dementia, improving genome-wide association studies for VaD, and advancing clinical trials are crucial steps in addressing this significant public health challenge.

Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified a plethora of risk loci. However, the disease variants/genes and the underlying mechanisms have not been extensively studied.

Bulk ATAC-seq was performed in induced pluripotent stem cells (iPSCs) differentiated various brain cell types to identify allele-specific open chromatin (ASoC) SNPs. CRISPR-Cas9 editing generated isogenic pairs, which were then differentiated into glutamatergic neurons (iGlut). Transcriptomic analysis and functional studies of iGlut co-cultured with mouse astrocytes assessed neuronal excitability and lipid droplet formation.

We identified a putative causal SNP of CLU that impacted neuronal chromatin accessibility to transcription-factor(s), with the AD protective allele upregulating neuronal CLU and promoting neuron excitability. And, neuronal CLU facilitated neuron-to-glia lipid transfer and astrocytic lipid droplet formation coupled with reactive oxygen species (ROS) accumulation. These changes caused astrocytes to uptake less glutamate thereby altering neuron excitability.

For a strong AD-associated locus near Clusterin (CLU), we connected an AD protective allele to a role of neuronal CLU in promoting neuron excitability through lipid-mediated neuron-glia communication. Our study provides insights into how CLU confers resilience to AD through neuron-glia interactions.

Alzheimer's disease (AD), an escalating global public health concern, demonstrates complex pathogenesis involving both genetic predisposition and vascular components. Blood pressure variability (BPV) has been implicated in neurodegenerative diseases, but its causal relationship with AD remains unclear. This study aims to explore the causal relationship between BPV and AD by applying Mendelian randomization (MR) to genome-wide association study (GWAS) summary data. Genetic instruments were selected from BPV GWAS based on UK Biobank data, ensuring relevance and significance(p < 5 × 10⁻⁶). Genetic estimates on exposure were obtained from three databases: The The International Genomic of Alzheimer's Project (IGAP); Maternal family history of AD from UK Biobank (MFH-UKBB), and Paternal family history of AD from UK Biobank (PFH-UKBB). Proxy SNPs were manually selected if SNPs were not available in the exposure GWAS. Data harmonization was performed to ensure consistency in effect and reference alleles. Three MR statistical methods were employed to assess causal effects, including inverse variance weighting (IVW) with random or fixed effect, MR-Egger regression, and the Weighted Median Method. Sensitivity analyses to evaluate robustness were also employed. Six SNPs associated with systolic BPV and six SNPs associated with diastolic BPV were included. Significant causal effects of SBPV on AD were found on the PFH-UKBB dataset in all four methods. The odds ratios for AD per 10-unit increment in SBPV were 1.028, 1.015, and 1.015 for MR-Egger, IVW-MR, and weighted median, respectively. In contrast, only IVW methods found significant results for DBPV in the MFH-UKBB dataset. SBPV is a possible causal risk factor for AD, while the evidence for DBPV needs further study. BPV control should be an important treatment target in preventing dementia.

BackgroundAlzheimer's disease (AD) and age-related macular degeneration (AMD) place considerable health burden on affected individuals and significant economic burden on society.ObjectiveThis study aims to explore the shared cellular and molecular mechanisms underlying the pathogenesis of AD and AMD.MethodsThe investigation in this study is conducted via single-cell and bulk tissue transcriptomic analysis. Transcriptomic datasets of AD and AMD were obtained from the GEO database. The shared differentially expressed genes (DEGs) in control and AD- and AMD-affected samples were identified. Functional enrichment analysis for DEGs was subsequently performed. Then, the protein-protein interaction (PPI) network of these DEGs was established via the STRING database and hub genes of this network were identified by Cytoscape software. Single-cell transcriptomic analysis was performed using Seurat R package to explore their expression in different cell types.ResultsDifferential analysis identified 127 shared DEGs of the two diseases, including 71 upregulated and 56 downregulated genes. Upregulated DEGs were enriched in inflammation, gliogenesis, cell apoptosis, and response to bacterial and viral infection and downregulated DEGs were enriched in mitochondrial function and energy production. PPI network and Cytoscape determined 10 hub genes, of which the NFKBIA gene was associated with the severity of both AD and AMD. Moreover, single-cell transcriptomic analysis showed that NFKBIA was highly expressed in microglia from disease-affected tissues.ConclusionsThe findings indicated that microglia with high NFKBIA expression were important contributors to the progression of both AD and AMD. Microglia-derived NFKBIA might serve as a potential therapeutic target for AD and AMD.

The Alzheimer's Disease Sequencing Project (ADSP) is a national initiative to understand the genetic architecture of Alzheimer's disease and related dementias (ADRD) by integrating whole genome sequencing (WGS) with other genetic, phenotypic, and harmonized datasets from diverse populations.

The Genome Center for Alzheimer's Disease (GCAD) uniformly processed WGS from 36,361 ADSP samples, including 35,014 genetically unique participants of which 45% are from non-European ancestry, across 17 cohorts in 14 countries in this fourth release (R4).

This sequencing effort identified 387 million bi-allelic variants, 42 million short insertions/deletions, and 6.8 million structural variants. Annotations and quality control data are available for all variants and samples. Additionally, detailed phenotypes from 15,927 participants across 10 domains are also provided. A linkage disequilibrium panel was created using unrelated AD cases and controls.

Researchers can access and analyze the genetic data via the National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) Data Sharing Service, the VariXam, or NIAGADS GenomicsDB.

We detailed the genetic architecture and quality of the Alzheimer's Disease Sequencing Project release 4 whole genome sequences. We identified 435 million single nucleotide polymorphisms, insertions and deletions, and structural variants from diverse genomes. We harmonized extensive phenotypes, linkage disequilibrium reference panel on subset of samples. Data is publicly available at NIAGADS Data Storage Site, variants and annotations are browsable on two different websites.

Autophagy disruption is important in Alzheimer's disease (AD) as it prevents misfolded proteins from being removed, which leads to the accumulation of amyloid plaques and neurofibrillary tangles (NFTs). Restoring autophagy improves neuronal survival and cognitive function, according to experimental models. In AD models, mTOR inhibition and AMPK activation enhance synaptic plasticity and lessen learning deficits. Inhibitors of phosphodiesterase-4 (PDE4) improve cognition and reduce neuroinflammation via altering cyclic adenosine monophosphate (cAMP) transmission. Furthermore, autophagic-lysosomal clearance is encouraged by upregulating transcription factor EB (TFEB), which lessens the pathogenic damage linked to AD. These results point to autophagy modification as a promising therapeutic approach, with the mTOR, AMPK, cAMP, and TFEB pathways being possible targets for drugs. Though much evidence is based on animal studies, these findings provide valuable insights into autophagy's role in AD pathology, offering promising directions for future research and drug development.

To explore the relationship between adverse childhood experiences (ACEs) and incident dementia, and examine the mediating effect of cognitive reserve-enhancing factors from life course perspective. Further, we verified the heterogeneities of associations of ACEs, enhancing factors, and dementia by dementia genetic risk.

Data was from the US Health and Retirement Study, involving 51,327 observations (50+) with a 10-year follow-up. Dementia was determined by the modified Telephone Interview for Cognitive Status. Six ACEs were assessed from two dimensions namely financial adversity and childhood trauma. Cognitive reserve-enhancing factors were rated during three periods of life-course, namely early-life stage (educational attainment,), adulthood (household income) and late-life stage (weekly physical activity). Genetic risk was evaluated by polygenic risk score for Alzheimer's disease. Cox regression models were conducted to examine the association between ACEs and dementia risk where ACEs were deemed as a continuous variable. "Mediation" package in R was used to test the mediating effect. Subgroup analysis was conducted to verify the heterogeneity of dementia genetic risk.

Participants with one additional number of ACEs was associated with increased risk of dementia (HR = 1.08, 95% CI: 1.02, 1.16). The correlation of the number of ACEs and dementia was fully mediated by early-life stage enhancing factor and partially mediated by adulthood enhancing factor. The above mediating roles only exist among those with moderate and high dementia genetic risk.

Exposure to a larger number of ACEs is significantly linked to dementia, and cognitive reserve-enhancing factors might mediate this association. Early interventions on the adverse life condition and emphasis on older adults with moderate and high genetic dementia risk were recommended.