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Abstract While there are currently over 40 replicated genes with mapped risk alleles for Late Onset Alzheimer’s disease (LOAD), the Apolipoprotein E locus E4 haplotype is still the biggest driver of risk, with odds ratios for neuropathologically confirmed E44 carriers exceeding 30 (95% confidence interval 16.59–58.75). We sought to address whether the APOE E4 haplotype modifies expression globally through networks of expression to increase LOAD risk. We have used the Human Brainome data to build expression networks comparing APOE E4 carriers to non-carriers using scalable mixed-datatypes Bayesian network (BN) modeling. We have found that VGF had the greatest explanatory weight. High expression of VGF is a protective signal, even on the background of APOE E4 alleles. LOAD risk signals, considering an APOE background, include high levels of SPECC1L, HLA-DRA and RANBP3L. Our findings nominate several new transcripts, taking a combined approach to network building including known LOAD risk loci.

The Dominantly Inherited Alzheimer Network (DIAN) initially was funded by the National Institute on Aging (NIA) in 2008 and thus was able to adopt and incorporate the protocols developed by the Alzheimer's Disease Neuroimaging Initiative (ADNI) that had been established by the NIA in 2004. The use of ADNI protocols for DIAN neuroimaging studies and assays of biological fluids for Alzheimer disease (AD) biomarkers permitted examination of the hypothesis that autosomal dominant AD (ADAD), studied by DIAN, and "sporadic" late‐onset AD (LOAD), studied by ADNI, shared the same pathobiological construct. In a collaborative effort, the longitudinal DIAN and ADNI databases were compared and the findings supported the conclusion that ADAD and LOAD share a similar pathophysiology. The importance of the DIAN study thus is amplified by its relevance to LOAD, as characterized by the "parent" ADNI program. [ABSTRACT FROM AUTHOR]

Abstract Background The genetic underpinnings of late-onset Alzheimer’s disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD. Methods Here, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs). Results Integrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes. Conclusions To our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis–trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD.

Background: The genetic underpinnings of late-onset Alzheimer's disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD. Methods: Here, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs). Results: Integrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes. Conclusions: To our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis–trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD. [ABSTRACT FROM AUTHOR]

Background and purpose: How the APOE genotype can differentially affect cortical and subcortical memory structures in biomarker‐confirmed early‐onset (EOAD) and late‐onset (LOAD) Alzheimer's disease (AD) was assessed. Method: Eighty‐seven cerebrospinal fluid (CSF) biomarker‐confirmed AD patients were classified according to their APOE genotype and age at onset. 28 were EOAD APOE4 carriers (+EOAD), 21 EOAD APOE4 non‐carriers (–EOAD), 23 LOAD APOE4 carriers (+LOAD) and 15 LOAD APOE4 non‐carriers (–LOAD). Grey matter (GM) volume differences were analyzed using voxel‐based morphometry in Papez circuit regions. Multiple regression analyses were performed to determine the relation between GM volume loss and cognition. Results: Significantly more mammillary body atrophy in +EOAD compared to –EOAD is reported. The medial temporal and posterior cingulate cortex showed less GM in +LOAD compared to –LOAD. Medial temporal GM volume loss was also found in +EOAD compared to –LOAD. With an exception for +EOAD, medial temporal GM was strongly associated with episodic memory in the three groups, whilst posterior cingulate cortex GM volume was more related with visuospatial abilities. Visuospatial abilities and episodic memory were also associated with the anterior thalamic nucleus in –LOAD. Conclusions: Our results show that the APOE genotype has a significant effect on GM integrity as a function of age of disease onset. Specifically, whilst LOAD APOE4 genotype is mostly associated with increased medial temporal and parietal atrophy compared to –LOAD, for EOAD APOE4 might have a more specific effect on subcortical (mammillary body) structures. The findings suggest that APOE genotype needs to be taken into account when classifying patients by age at onset. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is the most common cause of dementia worldwide. Increasing evidence points to the thalamus as an important hub in the clinical symptomatology of the disease, with the ‘limbic thalamus’ been described as especially vulnerable. In this work, we examined thalamic atrophy in early-onset AD (EOAD) and late-onset AD (LOAD) compared to young and old healthy controls (YHC and OHC, respectively) using a recently developed cutting-edge thalamic nuclei segmentation method. A deep learning variant of Thalamus Optimized Multi Atlas Segmentation (THOMAS) was used to parcellate 11 thalamic nuclei per hemisphere from T1-weighted MRI in 88 biomarker-confirmed AD patients (49 EOAD and 39 LOAD) and 58 healthy controls (41 YHC and 17 OHC) with normal AD biomarkers. Nuclei volumes were compared among groups using MANCOVA. Further, Pearson's correlation coefficient was computed between thalamic nuclear volume and cortical—subcortical regions, CSF tau levels, and neuropsychological scores. The results showed widespread thalamic nuclei atrophy in EOAD and LOAD compared to their respective healthy control groups, with EOAD showing additional atrophy in the centromedian and ventral lateral posterior nuclei compared to YHC. In EOAD, increased thalamic nuclei atrophy was associated with posterior parietal atrophy and worse visuospatial abilities, while LOAD thalamic nuclei atrophy was preferentially associated with medial temporal atrophy and worse episodic memory and executive function. Our findings suggest that thalamic nuclei may be differentially affected in AD according to the age at symptoms onset, associated with specific cortical—subcortical regions, CSF total tau and cognition.

Alzheimer's disease (AD) represents a global health challenge, with an estimated 55 million people suffering from the non-curable disease across the world. While amyloid-β plaques and tau neurofibrillary tangles in the brain define AD proteinopathy, it has become evident that diverse coding and non-coding regions of the genome may significantly contribute to AD neurodegeneration. The diversity of factors associated with AD pathogenesis, coupled with age-associated damage, suggests that a series of triggering events may be required to initiate AD. Since somatic mutations accumulate with aging, and aging is a major risk factor for AD, there is a great potential for somatic mutational events to drive disease. Indeed, recent data from the Gozes team/laboratories as well as other leading laboratories correlated the accumulation of somatic brain mutations with the progression of tauopathy. In this review, we lay the current perspectives on the principal genetic factors associated with AD and the potential causes, highlighting the contribution of somatic mutations to the pathogenesis of late onset Alzheimer's disease. The roles that artificial intelligence and big data can play in accelerating the progress of causal somatic mutation markers/biomarkers identification, and the associated drug discovery/repurposing, have been highlighted for future AD and other neurodegenerations, with the aim to bring hope for the vulnerable aging population. [ABSTRACT FROM AUTHOR]

Late-onset Alzheimer's disease (LOAD) is a common irreversible neurodegenerative disease with heterogeneous genetic characteristics. Identifying the biological biomarkers with the potential to predict the conversion from normal controls to LOAD is clinically important for early interventions of LOAD and clinical treatment. The polygenic risk score for LOAD (AD-PRS) has been reported the potential possibility for reliably identifying individuals with risk of developing LOAD recently. To investigate the external phenotype changes resulting from LOAD and the underlying etiology, we summarize the comprehensive associations of AD-PRS with multiple biomarkers, including neuroimaging, cerebrospinal fluid and plasma biomarkers, cardiovascular risk factors, cognitive behavior, and mental health. This systematic review helps improve the understanding of the biomarkers with potential predictive value for LOAD and further optimizing the prediction and accurate treatment of LOAD. [ABSTRACT FROM AUTHOR]

Late-onset Alzheimer's disease (LOAD) is a common irreversible neurodegenerative disease with heterogeneous genetic characteristics. Identifying the biological biomarkers with the potential to predict the conversion from normal controls to LOAD is clinically important for early interventions of LOAD and clinical treatment. The polygenic risk score for LOAD (AD-PRS) has been reported the potential possibility for reliably identifying individuals with risk of developing LOAD recently. To investigate the external phenotype changes resulting from LOAD and the underlying etiology, we summarize the comprehensive associations of AD-PRS with multiple biomarkers, including neuroimaging, cerebrospinal fluid and plasma biomarkers, cardiovascular risk factors, cognitive behavior, and mental health. This systematic review helps improve the understanding of the biomarkers with potential predictive value for LOAD and further optimizing the prediction and accurate treatment of LOAD.

Introduction: Although mouse models of Alzheimer's disease (AD) have increased our understanding of the molecular basis of the disease, none of those models represent late-onset Alzheimer's Disease which accounts for >90% of AD cases, and no therapeutics developed in the mouse (with the possible exceptions of aduhelm/aducanumab and gantenerumab) have succeeded in preventing or reversing the disease. This technology has allowed much progress in understanding the molecular basis of AD. To further enhance our understanding, we used wild-type rabbit (with a nearly identical amino acid sequence for amyloid as in humans) to model LOAD by stressing risk factors including age, hypercholesterolemia, and elevated blood glucose levels (BGLs), upon an ε3-like isoform of apolipoprotein. We report a combined behavioral, imaging, and metabolic study using rabbit as a non-transgenic model to examine effects of AD-related risk factors on cognition, intrinsic functional connectivity, and magnetic resonance-based biomarkers of neuropathology. Methods: Aging rabbits were fed a diet enriched with either 2% cholesterol or 10% fat/30% fructose. Monthly tests of novel object recognition (NOR) and object location memory (OLM) were administered to track cognitive impairment. Trace eyeblink conditioning (EBC) was administered as a final test of cognitive impairment. Magnetic resonance imaging (MRI) was used to obtain resting state connectivity and quantitative parametric data (R2*). Results: Experimental diets induced hypercholesterolemia or elevated BGL. Both experimental diets induced statistically significant impairment of OLM (but not NOR) and altered intrinsic functional connectivity. EBC was more impaired by fat/fructose diet than by cholesterol. Whole brain and regional R2* MRI values were elevated in both experimental diet groups relative to rabbits on the control diet. Discussion: We propose thatmechanisms underlying LOAD can be assessed by stressing risk factors for inducing AD and that dietary manipulations can be used to assess etiological differences in the pathologies and effectiveness of potential therapeutics against LOAD. In addition, non-invasive MRI in awake, non-anesthetized rabbits further increases the translational value of this non-transgenic model to study AD. [ABSTRACT FROM AUTHOR]

Introduction: Genome‐wide association studies (GWAS) in late onset Alzheimer's disease (LOAD) provide lists of individual genetic determinants. However, GWAS do not capture the synergistic effects among multiple genetic variants and lack good specificity. Methods: We applied tree‐based machine learning algorithms (MLs) to discriminate LOAD (>700 individuals) and age‐matched unaffected subjects in UK Biobank with single nucleotide variants (SNVs) from Alzheimer's disease (AD) studies, obtaining specific genomic profiles with the prioritized SNVs. Results: MLs prioritized a set of SNVs located in genes PVRL2, TOMM40, APOE, and APOC1, also influencing gene expression and splicing. The genomic profiles in this region showed interaction patterns involving rs405509 and rs1160985, also present in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. rs405509 located in APOE promoter interacts with rs429358 among others, seemingly neutralizing their predisposing effect. Discussion: Our approach efficiently discriminates LOAD from controls, capturing genomic profiles defined by interactions among SNVs in a hot‐spot region. [ABSTRACT FROM AUTHOR]

Abstract Introduction Although mouse models of Alzheimer's disease (AD) have increased our understanding of the molecular basis of the disease, none of those models represent late‐onset Alzheimer's Disease which accounts for >90% of AD cases, and no therapeutics developed in the mouse (with the possible exceptions of aduhelm/aducanumab and gantenerumab) have succeeded in preventing or reversing the disease. This technology has allowed much progress in understanding the molecular basis of AD. To further enhance our understanding, we used wild‐type rabbit (with a nearly identical amino acid sequence for amyloid as in humans) to model LOAD by stressing risk factors including age, hypercholesterolemia, and elevated blood glucose levels (BGLs), upon an ε3‐like isoform of apolipoprotein. We report a combined behavioral, imaging, and metabolic study using rabbit as a non‐transgenic model to examine effects of AD‐related risk factors on cognition, intrinsic functional connectivity, and magnetic resonance‐based biomarkers of neuropathology. Methods Aging rabbits were fed a diet enriched with either 2% cholesterol or 10% fat/30% fructose. Monthly tests of novel object recognition (NOR) and object location memory (OLM) were administered to track cognitive impairment. Trace eyeblink conditioning (EBC) was administered as a final test of cognitive impairment. Magnetic resonance imaging (MRI) was used to obtain resting state connectivity and quantitative parametric data (R2*). Results Experimental diets induced hypercholesterolemia or elevated BGL. Both experimental diets induced statistically significant impairment of OLM (but not NOR) and altered intrinsic functional connectivity. EBC was more impaired by fat/fructose diet than by cholesterol. Whole brain and regional R2* MRI values were elevated in both experimental diet groups relative to rabbits on the control diet. Discussion We propose that mechanisms underlying LOAD can be assessed by stressing risk factors for inducing AD and that dietary manipulations can be used to assess etiological differences in the pathologies and effectiveness of potential therapeutics against LOAD. In addition, non‐invasive MRI in awake, non‐anesthetized rabbits further increases the translational value of this non‐transgenic model to study AD.

The Dominantly Inherited Alzheimer Network (DIAN) initially was funded by the National Institute on Aging (NIA) in 2008 and thus was able to adopt and incorporate the protocols developed by the Alzheimer's Disease Neuroimaging Initiative (ADNI) that had been established by the NIA in 2004. The use of ADNI protocols for DIAN neuroimaging studies and assays of biological fluids for Alzheimer disease (AD) biomarkers permitted examination of the hypothesis that autosomal dominant AD (ADAD), studied by DIAN, and "sporadic" late-onset AD (LOAD), studied by ADNI, shared the same pathobiological construct. In a collaborative effort, the longitudinal DIAN and ADNI databases were compared and the findings supported the conclusion that ADAD and LOAD share a similar pathophysiology. The importance of the DIAN study thus is amplified by its relevance to LOAD, as characterized by the "parent" ADNI program., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

To deeply understand late onset Alzheimer's disease (LOAD), it may be necessary to change the concept that it is a disease exclusively driven by aging processes. The onset of LOAD could be associated with a previous peripheral stress at the level of the gut (changes in the gut microbiota), obesity (metabolic stress), and infections, among other systemic/environmental stressors. The onset of LOAD, then, may result from the generation of mild peripheral inflammatory processes involving cytokine production associated with peripheral stressors that in a second step enter the brain and spread out the process causing a neuroinflammatory brain disease. This hypothesis could explain the potential efficacy of Sodium Oligomannate (GV-971), a mixture of acidic linear oligosaccharides that have shown to remodel gut microbiota and slowdown LOAD. However, regardless of the origin of the disease, the end goal of LOAD-related preventative or disease modifying therapies is to preserve dendritic spines and synaptic plasticity that underlay and support healthy cognition. Here we discuss how systemic/environmental stressors impact pathways associated with the regulation of spine morphogenesis and synaptic maintenance, including insulin receptor and the brain derived neurotrophic factor signaling. Spine structure remodeling is a plausible mechanism to maintain synapses and provide cognitive resilience in LOAD patients. Importantly, we also propose a combination of drugs targeting such stressors that may be able to modify the course of LOAD by acting on preventing dendritic spines and synapsis loss. [ABSTRACT FROM AUTHOR]

Introduction: Alzheimer’s disease (AD), which is a progressive neurodegenerative disorder, causes structural and functional brain disruption. MS4A6A, TREM2, and CD33 gene polymorphisms loci have been found to be associated with the pathobiology of late-onset AD (LOAD). In the present study, we tested the hypothesis of association of LOAD with rs983392, rs75932628, and rs3865444 polymorphisms in MS4A6A, TREM2, CD33 genes, respectively. Methods: In the present study, 113 LOAD patients and 100 healthy unrelated age- and gender-matched controls were selected. DNA was extracted from blood samples by the salting-out method and the genotyping was performed by RFLP-PCR. Electrophoresis was carried out on agarose gel. Sequencing was thereafter utilized for the confirmation of the results. Results: Only CD33 rs3865444 polymorphism revealed a significant difference in the genotypic frequencies of GG (P = 0.001) and GT (P = 0.001), and allelic frequencies of G (P = 0.033) and T (P = 0.03) between LOAD patients and controls. Conclusion: The evidence from the present study suggests that T allele of CD33 rs3865444 polymorphism is associated with LOAD in the studied Iranian population.

Objective: To reassess the role of amyloid beta (Aβ) and the amyloid precursor protein (APP) system in the pathogenesis of Alzheimer's disease (AD). Background: APP is a cell adhesion molecule that has been highly conserved over the course of phylogeny that has critical roles in brain development, synaptic plasticity, and the brain's intrinsic immune system. The amyloid cascade hypothesis describes a relatively linear, deterministic sequence of events triggered by a gain of Aβ peptide fragment toxicity that results in neurodegeneration and cognitive loss, yet well designed immunotherapy and beta secretase inhibitor trials that have successfully targeted Aβ have failed to have any consistent effects on the steady decline of cognition. New/updated hypothesis: Mutations of the APP and presenilin genes not only alter the ratio of longer to shorter Aβ fragments (resulting in a gain of Aβ toxicity), but also disrupt the normal homeostatic roles of their respective proteins. The evolutionary history, physiological importance, and complexity of the APP and presenilin systems, as well as other critical components including tau and apolipoprotein E (APOE) imply that altered function of such systems could have severe consequences that include but need not be limited to a gain of Aβ toxicity and would more generally result in altered homeostasis of APP‐related functions. Major challenges addressed by our hypothesis: Challenges that a loss of APP homeostasis addresses better than the more limited gain of Aβ toxicity model include the topographic mismatches between Aβ and tau pathology, the profile and chronology of cognitive and biomarker changes that precede the clinical expression of mild cognitive impairment and dementia, and the disappointments of Aβ targeted therapeutics among others. Linkage to other major theories: The importance of APP, α‐ and β‐secretases, the presenilins and γ‐secretase, as well as tau was recognized by the authors of the amyloid cascade hypothesis, and has since led multiple investigators to propose alternative, more balanced hypotheses including reduced homeostasis and frank loss‐of‐function of key components that include but go beyond the currently envisioned linear model of Aβ toxicity. [ABSTRACT FROM AUTHOR]

Background: Rare variants in PLCG2 (p.P522R), ABI3 (p.S209F), and TREM2 (p.R47H, p.R62H) have been associated with late onset Alzheimer's disease (LOAD) risk in Caucasians. After the initial report, several studies have found positive results in cohorts of different ethnic background and with different phenotype.Objective: In this study, we aim to evaluate the association of rare coding variants in PLCG2, ABI3, and TREM2 with LOAD risk and their effect at different time points of the disease.Methods: We used a European American cohort to assess the association of the variants prior onset (using CSF Aβ42, tau, and pTau levels, and amyloid imaging as endophenotypes) and after onset (measured as rate of memory decline).Results: We confirm the association with LOAD risk of TREM2 p.R47H, p.R62H and ABI3 p.S209F variants, and the protective effect of PLCG2 p.P522R. In addition, ABI3 and TREM2 gene-sets showed significant association with LOAD risk. TREM2 p.R47H and PLCG2 p.P522R variants were also statistically associated with increase of amyloid imaging and AD progression, respectively. We did not observe any association of ABI3 p.S209F with any of the other AD endophenotypes.Conclusion: The results of this study highlight the importance of including biomarkers and alternative phenotypes to better understand the role of novel candidate genes with the disease. [ABSTRACT FROM AUTHOR]

Xin Zhong,1,2 Ming-Yan Liu,1,2 Miao He,1,2 Ke Du,1,2 Min-Jie Wei1,2 1Department of Pharmacology, School of Pharmacy, China Medical University, 2Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Shenyang, Liaoning Province, People’s Republic of China Abstract: The association between interleukin-33 (IL-33) gene polymorphisms and late onset Alzheimer’s disease (LOAD) remains controversial in previous studies. Thus, a meta-analysis was conducted to assess the association between the IL-33 polymorphisms (rs11792633 and rs7044343) and LOAD susceptibility. Crude odds ratio (OR) and 95% confidence interval (CI) were used to investigate the relationship strength. Sensitivity analysis was performed, and publication bias was estimated by the Begg’s and Egger’s tests. Overall, six independent studies involving 2,589 patients and 8,414 control samples met our inclusion criteria and were included in this meta-analysis. The results showed that IL-33 rs11792633 polymorphism had statistically significant correlation with a decreased risk of LOAD in heterozygous comparison model (OR =0.64, 95% CI =0.48–0.83), homozygote comparison model (OR =0.83, 95% CI =0.74–0.93), dominant model (OR =0.78, 95% CI =0.67–0.91), recessive model (OR =0.70, 95% CI =0.59–0.84), and allelic model (OR =0.79, 95% CI =0.69–0.91), which were also validated by stratified subgroup analysis. Additionally, there was an apparent association between the IL-33 rs7044343 variant and LOAD risk under four genetic models for overall population (heterozygous comparison model: OR =0.75, 95% CI =0.63–0.89; dominant model: OR =0.83, 95% CI =0.70–0.98; recessive model: OR =0.80, 95% CI =0.68–0.94; allelic model: OR =0.86, 95% CI =0.79–0.94) as well as Caucasian subgroup. In summary, our meta-analysis implicated that IL-33 gene polymorphisms rs11792633 and rs7044343 were significantly associated with the susceptibility of LOAD. Keywords: late onset Alzheimer’s disease, interleukin-33, polymorphism, meta-analysis

Introduction: Alzheimer's disease (AD), which is a progressive neurodegenerative disorder, causes structural and functional brain disruption. MS4A6A, TREM2, and CD33 gene polymorphisms loci have been found to be associated with the pathobiology of late-onset AD (LOAD). In the present study, we tested the hypothesis of association of LOAD with rs983392, rs75932628, and rs3865444 polymorphisms in MS4A6A, TREM2, CD33 genes, respectively. Methods: In the present study, 113 LOAD patients and 100 healthy unrelated age- and gender-matched controls were selected. DNA was extracted from blood samples by the salting-out method and the genotyping was performed by RFLP-PCR. Electrophoresis was carried out on agarose gel. Sequencing was thereafter utilized for the confirmation of the results. Results: Only CD33 rs3865444 polymorphism revealed a significant difference in the genotypic frequencies of GG (P = 0.001) and GT (P = 0.001), and allelic frequencies of G (P = 0.033) and T (P = 0.03) between LOAD patients and controls. Conclusion: The evidence from the present study suggests that T allele of CD33 rs3865444 polymorphism is associated with LOAD in the studied Iranian population. [ABSTRACT FROM AUTHOR]

The association between interleukin-33 (IL-33) gene polymorphisms and late onset Alzheimer's disease (LOAD) remains controversial in previous studies. Thus, a meta-analysis was conducted to assess the association between the IL-33 polymorphisms (rs11792633 and rs7044343) and LOAD susceptibility. Crude odds ratio (OR) and 95% confidence interval (CI) were used to investigate the relationship strength. Sensitivity analysis was performed, and publication bias was estimated by the Begg's and Egger's tests. Overall, six independent studies involving 2,589 patients and 8,414 control samples met our inclusion criteria and were included in this meta-analysis. The results showed that IL-33 rs11792633 polymorphism had statistically significant correlation with a decreased risk of LOAD in heterozygous comparison model (OR =0.64, 95% CI =0.48-0.83), homozygote comparison model (OR =0.83, 95% CI =0.74-0.93), dominant model (OR =0.78, 95% CI =0.67-0.91), recessive model (OR =0.70, 95% CI =0.59-0.84), and allelic model (OR =0.79, 95% CI =0.69-0.91), which were also validated by stratified subgroup analysis. Additionally, there was an apparent association between the IL-33 rs7044343 variant and LOAD risk under four genetic models for overall population (heterozygous comparison model: OR =0.75, 95% CI =0.63-0.89; dominant model: OR =0.83, 95% CI =0.70-0.98; recessive model: OR =0.80, 95% CI =0.68-0.94; allelic model: OR =0.86, 95% CI =0.79-0.94) as well as Caucasian subgroup. In summary, our meta-analysis implicated that IL-33 gene polymorphisms rs11792633 and rs7044343 were significantly associated with the susceptibility of LOAD. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is the most common cause of dementia worldwide. Increasing evidence points to the thalamus as an important hub in the clinical symptomatology of the disease, with the 'limbic thalamus' been described as especially vulnerable. In this work, we examined thalamic atrophy in early-onset AD (EOAD) and late-onset AD (LOAD) compared to young and old healthy controls (YHC and OHC, respectively) using a recently developed cutting-edge thalamic nuclei segmentation method. A deep learning variant of Thalamus Optimized Multi Atlas Segmentation (THOMAS) was used to parcellate 11 thalamic nuclei per hemisphere from T1-weighted MRI in 88 biomarker-confirmed AD patients (49 EOAD and 39 LOAD) and 58 healthy controls (41 YHC and 17 OHC) with normal AD biomarkers. Nuclei volumes were compared among groups using MANCOVA. Further, Pearson's correlation coefficient was computed between thalamic nuclear volume and cortical-subcortical regions, CSF tau levels, and neuropsychological scores. The results showed widespread thalamic nuclei atrophy in EOAD and LOAD compared to their respective healthy control groups, with EOAD showing additional atrophy in the centromedian and ventral lateral posterior nuclei compared to YHC. In EOAD, increased thalamic nuclei atrophy was associated with posterior parietal atrophy and worse visuospatial abilities, while LOAD thalamic nuclei atrophy was preferentially associated with medial temporal atrophy and worse episodic memory and executive function. Our findings suggest that thalamic nuclei may be differentially affected in AD according to the age at symptoms onset, associated with specific cortical-subcortical regions, CSF total tau and cognition., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Albert Llado reports financial support was provided by 10.13039/501100004587Carlos III Health Institute. Mircea Balasa reports financial support was provided by 10.13039/501100004587Carlos III Health Institute. Michael Hornberger reports financial support was provided by Alzheimer's Research UK, Wellcome Trust. Neus Falgas reports financial support was provided by 10.13039/501100004587Carlos III Health Institute. Nuria Guillen reports financial support was provided by 10.13039/501100004587Carlos III Health Institute., (© 2023 The Authors.)

Alzheimer’s disease (AD) is classified as a neurodegenerative disease, impacting on brain integrity and functioning, resulting in a progressive deterioration of cognitive capabilities. Epigenetic changes can be acquired over the life span and mediate environmental effects on gene expression. DNA-methyltransferase 3A (DNMT3A) plays an important role in the development of embryogenesis and the generation of aberrant methylation late-onset AD (LOAD). In this study, the rs1550117 polymorphism of DNMT3A was determined by polymerase chain reaction/restriction fragment length polymorphism and confirmed by sequencing. The results showed that AA genotype carriers had a 2.08-fold risk of developing LOAD in comparison with GG genotype carriers (odds ratio [OR] = 2.08, 95% confidence interval [CI]: 1.03-4.21, P = .038) and had a 2.05-fold risk for LOAD compared with GG+GA genotype carriers (OR = 2.05, 95% CI: 1.03-4.11, P = .038), indicating that the DNMT3A polymorphism supports a major role in the pathogenesis of LOAD and can be used as a stratification marker to predict an individual’s susceptibility to LOAD. [ABSTRACT FROM AUTHOR]

Epigenetic changes including genomic imprinting may affect risk of late-onset Alzheimer's disease (LOAD). There are >100 known imprinted genes and most of them are expressed in human brain. In this study, we examined the association of single nucleotide polymorphisms (SNPs) in 93 imprinted genes with LOAD risk in 1291 LOAD cases and 958 cognitively normal controls. We performed single-site, gene-based, and haplotype analyses. Single-site analysis showed 14 significant associations at p < 0.01. The most significant SNP (rs11770199; p = 0.0003) in single-site analysis was located on chromosome 7 in the GRB10 gene. Gene-based analyses revealed four significant associations in the WT1, ZC3H12C, DLGAP2, and GPR1 genes at p < 0.05. The haplotype analysis also revealed significant associations with three genes (ZC3H12C, DLGAP2, and GPR1). These findings suggest a possible role of imprinted genes in AD pathogenesis that show specific expression in the brain. [ABSTRACT FROM AUTHOR]

Background:Young onset Alzheimer's disease (YOAD; onset before 65 years of age) is thought to have a more rapid course and increased rate of progression compared to late onset Alzheimer's disease (LOAD). This assumption appears partly due to important clinical, structural, neuropathological, and neurochemical differences suggesting YOAD is a separate entity to LOAD. The aim in this review was to systematically identify and examine appropriate studies comparing rate of cognitive decline between patients with YOAD and patients with LOAD.Methods:A computer-based literature search was initially undertaken, followed by citation tracking and search of related papers. Primary research studies specifically focused on the rate of cognitive decline between people with YOAD and LOAD were included. Studies were described, critically analyzed, presented, and discussed in the review.Results:Four studies were included, of which three were longitudinal and one was a case-control study. Three of the included studies found a faster rate of decline in patients with YOAD, and one found no difference in rate of decline between the two groups.Conclusions:The findings of the review are mixed and conflicting, and limited by the heterogeneity of the included studies. There is a need for future research to design systematic studies that include sufficient sample sizes and follow-up periods, and control for possible confounding factors such as education level, baseline cognitive impairment, and vascular risk factors. This will help to validate the findings so far and improve our understanding of the rate of cognitive decline in people with YOAD and LOAD. [ABSTRACT FROM AUTHOR]

Striatal changes in the pathogenesis of Alzheimer's disease (AD) is not fully understood yet. We compared structural and functional image differences in the striatum between patients with early onset AD (EOAD) and late onset AD (LOAD) to investigate whether EOAD harbors autosomal dominant AD like imaging findings. The clinical, neuropsychological and neuroimaging biomarkers of 77 probable AD patients and 107 elderly subjects with normal cognition (NC) from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-2 dataset were analyzed. Enrolled each subject completed a 3-Tesla MRI, baseline 18F-FDG-PET, and baseline 18F-AV-45 (Florbetapir) amyloid PET studies. AD patients were divided into two groups based on the onset age of clinical symptoms (EOAD <65 yrs; LOAD ≥65 yrs). A standardized uptake value ratio of the striatum and subcortical structures was obtained from both amyloid and FDG-PET scans. Structural MR imaging analysis was conducted using a parametric boundary description protocol, SPHARM-PDM. Of the 77 AD patients, 18 were EOAD and 59 were LOAD. Except for age of symptom onset, there were no statistically significant differences between the groups in demographics and detailed neuropsychological test results. 18F-AV-45 amyloid PET showed marked β-amyloid accumulation in the bilateral caudate nucleus and left pallidum in the EOAD group. Intriguingly, the caudate nucleus and putamen showed maintained glucose metabolism in the EOAD group compared to the LOAD group. Our image findings in the striatum of EOAD patients suggest that sporadic EOAD may share some pathophysiological changes noted in autosomal dominant AD.

Background High-profile Phase 3 clinical trials of bapineuzumab and solanezumab, antibodies targeted at amyloid-beta (Aβ) removal, have failed to meet their primary endpoints. Neither drug improves clinical outcomes in patients with late onset AD, joining a long list of unsuccessful attempts to treat AD with anti-amyloid therapies. Discussion These therapies are based on the assumption that Aβ accumulation is the primary pathogenic trigger of AD. Current evidence suggests that Aβ may actually accumulate as part of an adaptive response to long-term chronic brain stress stimuli that would make more suitable candidates for therapeutic intervention. Summary At this juncture it is no longer unreasonable to suggest that further iterations of anti-Aβ therapies should be halted. Clinicians and researchers should instead direct their attention toward greater understanding of the biological function of Aβ both in healthy and demented brains, as well as the involvement of long-term chronic exposure to stress in the etiology of AD. [ABSTRACT FROM AUTHOR]

Abstract: This study aimed to investigate whether Late Onset Alzheimer's Disease (LOAD) and Vascular Dementia (VAD) might be associated with a distinct profile of oxidative stress (OxS) peripheral markers. Serum levels of hydroperoxides, homocysteine, advanced oxidation protein products, uric acid, thiols, and total and residual antioxidant power were assessed in 103 mild cognitive impairment (MCI), 89 LOAD, 54 VAD patients and 48 Controls. Compared with Controls, a similar oxidative unbalance (high hydroperoxides and low residual antioxidant power) was observed in MCI, LOAD and, although less pronounced, VAD. Moreover, individuals with simultaneously high levels of homocysteine and uric acid, both well-known risk factors for cardiovascular disease, had a high probability to be affected by VAD (O.R.:10.50; 95% C.I.: 2.33–47.2), but not LOAD (O.R.: 3.0; 95% C.I.:0.86–10.76) compared with individuals with normal values. Our data suggest that, although they might share a common OxS-related pathogenesis, VAD and LOAD might maintain some distinctive features, with a predominance of “vascular component” in VAD compared with LOAD. [Copyright &y& Elsevier]

Late onset Alzheimer's disease (LOAD) accounts for about 95% of all Alzheimer's disease cases. While the APOE ℇ4 variant seems to have unparalleled influence on increased LOAD risk, it does not explain all of the heritability of LOAD. In this study, we present the application of a cost-effective, pooled DNA genome-wide association study (GWAS) to uncover genetic risk variants associated with LOAD in Polish women diagnosed with either mild cognitive impairment (MCI) or well-defined LOAD. A group of 141 patients (94 LOAD and 47 MCI), as well as 141 controls, were assayed using Affymetrix Genome-Wide Human SNP 6.0 arrays. Allele frequency distributions were compared using χ2-tests, and significantly associated SNPs at p < 0.0001 with a proxy SNP were selected. GWAS marker selection was conducted using PLINK, and selected SNPs were validated on DNA samples from the same cohort using KASPar Assays. In addition, to determine the genotype of APOE variants (rs429358, rs7412), a multiplex tetra-primer amplification refractory mutation system was applied. The GWAS revealed nine SNPs associated with MCI and/or LOAD. Of these, the association of seven SNPs was confirmed by genotyping of individual patients. Furthermore, the APOE ℇ4 appeared to be a risk variant for LOAD, while the APOE ℇ3 showed a protective effect. Multivariate analysis showed association between rs7856774 and LOAD, independently from the effect of APOE variation. Pooled DNA GWAS enabled the identification of a novel LOAD candidate risk variant, rs7856774 (9q21.33), tagging a possible genomic enhancer affecting proximal transcribed elements including DAPK1 gene. [ABSTRACT FROM AUTHOR]

This manuscript provides a brief review of current concepts in the mechanisms potentially linking type-2-diabetes (T2D) with cognitive impairment. Existing epidemiologic studies, imaging studies, autopsy studies, and clinical trials provide insights into the mechanisms linking T2D and cognitive impairment. There seems to be little dispute that T2D can cause cerebrovascular disease and thus cause vascular cognitive impairment (VCI). Whether T2D can cause late onset Alzheimer's disease (LOAD) remains to be elucidated. Many epidemiologic studies show an association between T2D and cognitive impairment, but the association with VCI seems to be stronger compared to LOAD, suggesting that cerebrovascular disease may be the main mechanism linking T2D and cognitive impairment. Imaging studies show an association between T2D and imaging markers of LOAD, but these observations could still be explained by cerebrovascular mechanisms. Autopsy studies are few and conflicting, with some suggesting a predominantly cerebrovascular mechanism, and others providing support for a neurodegenerative mechanism. Thus far, the evidence from clinical trials is mixed in supporting a causal association between T2D and cognitive impairment, and most clinical trials that can answer this question are yet to be reported or finished. Given the epidemic of T2D in the world, it is important to elucidate whether the association between T2D and cognitive impairment, particularly LOAD, is causal, and if so, what the mechanisms are. [ABSTRACT FROM AUTHOR]

Evidence supports a role for epigenetic mechanisms in the pathogenesis of late-onset Alzheimer's disease (LOAD), but little has been done on a genome-wide scale to identify potential sites involved in disease. This study investigates human postmortem frontal cortex genome-wide DNA methylation profiles between 12 LOAD and 12 cognitively normal age- and gender-matched subjects. Quantitative DNA methylation is determined at 27,578 CpG sites spanning 14,475 genes via the Illumina Infinium HumanMethylation27 BeadArray. Data are analyzed using parallel linear models adjusting for age and gender with empirical Bayes standard error methods. Gene-specific technical and functional validation is performed on an additional 13 matched pair samples, encompassing a wider age range. Analysis reveals 948 CpG sites representing 918 unique genes as potentially associated with LOAD disease status pending confirmation in additional study populations. Across these 948 sites the subtle mean methylation difference between cases and controls is 2.9%. The CpG site with a minimum false discovery rate located in the promoter of the gene Transmembrane Protein 59 (TMEM59) is 7.3% hypomethylated in cases. Methylation at this site is functionally associated with tissue RNA and protein levels of the TMEM59 gene product. The TMEM59 gene identified from our discovery approach was recently implicated in amyloid-β protein precursor post-translational processing, supporting a role for epigenetic change in LOAD pathology. This study demonstrates widespread, modest discordant DNA methylation in LOAD-diseased tissue independent from DNA methylation changes with age. Identification of epigenetic biomarkers of LOAD risk may allow for the development of novel diagnostic and therapeutic targets. [ABSTRACT FROM AUTHOR]

Biomarker studies demonstrate inheritance of glucose hypometabolism and increased amyloid-β deposition in adult offspring of mothers, but not fathers, affected by late-onset Alzheimer's disease (LOAD). The underlying genetic mechanisms are unknown. We investigated whether cognitively normal (NL) individuals with a maternal history of LOAD (MH) have reduced platelet mitochondrial cytochrome oxidase activity (COX, electron transport chain complex IV) compared to those with paternal (PH) or negative family history (NH). Thirty-six consecutive NL individuals (age 55 ± 15 y, range 27-71 y, 56% female, CDR = 0, MMSE ≥28, 28% APOE-4 carriers), including 12 NH, 12 PH, and 12 MH, received a blood draw to measure platelet mitochondrial COX activity. Citrate synthase activity (CS) was measured as a reference. Groups were comparable for clinical and neuropsychological measures. We found that after correcting for CS, COX activity was reduced by 29% in MH compared to NH, and by 30% in MH compared to PH (p ≤ 0.006). Results remained significant controlling for age, gender, education, and APOE. No differences were found between PH and NH. COX measures discriminated MH from the other groups with accuracy ≥75%, and relative risk ≥3 (p ≤ 0.005). Among NL with LOAD-parents, only those with MH showed reduced COX activity in platelet mitochondria compared to PH and NH. The association between maternal history of LOAD and systemic COX reductions suggests transmission via mitochondrial DNA, which is exclusively maternally inherited in humans. [ABSTRACT FROM AUTHOR]

Introduction: Genome-wide association studies (GWAS) in late onset Alzheimer's disease (LOAD) provide lists of individual genetic determinants. However, GWAS do not capture the synergistic effects among multiple genetic variants and lack good specificity., Methods: We applied tree-based machine learning algorithms (MLs) to discriminate LOAD (>700 individuals) and age-matched unaffected subjects in UK Biobank with single nucleotide variants (SNVs) from Alzheimer's disease (AD) studies, obtaining specific genomic profiles with the prioritized SNVs., Results: MLs prioritized a set of SNVs located in genes PVRL2 , TOMM40 , APOE , and APOC1 , also influencing gene expression and splicing. The genomic profiles in this region showed interaction patterns involving rs405509 and rs1160985, also present in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. rs405509 located in APOE promoter interacts with rs429358 among others, seemingly neutralizing their predisposing effect., Discussion: Our approach efficiently discriminates LOAD from controls, capturing genomic profiles defined by interactions among SNVs in a hot-spot region., Competing Interests: Support received for the submitted work: Jordi Rambla De Argila, George Paliouras, Peter Garrard, and Gian Gaetano Tartaglia received funds through the H2020 project IASIS (grant number 727658 to CRG, NCSR, and St George's University of London); Claudia Giambartolomei is recipient of a H2020 Skłodowska‐Curie fellowship (grant number 754490 to IIT). The other authors have nothing to disclose. Support received outside the submitted work: Gian Gaetano Tartaglia received funds through the ERC Synergy project ASTRA (grant number 855923 to IIT and Sapienza). Peter Garrard received funds from Medical Research Council UK and Leverhulme Trust (to St George's University of London). The other authors have nothing to disclose. Other relationships/activities/interests: Gian Gaetano Tartaglia is in the process of filing a patent on TDP43 aptamers and received an honorarium for editorial work at Frontiers in Molecular Biosciences. George Paliouras filed the following patents: EPO Patent Application 20 386 008.5 ‐ 1126: System and method for identifying drug‐drug interactions USPTO Patent Application US‐2021‐0118465‐A1: Multi‐lingual System for Early Detection of Alzheimer's Disease EPO Patent Application EP‐3‐ 809‐411‐A1: Multi‐lingual System for Early Detection of Alzheimer's Disease. Other relationships with entities: George Paliouras participated on a Data Safety Monitoring/Advisory Board in the last 36 months for the EIT High Value Care Forum (no payment); George Paliouras held a leadership/fiduciary role in the Duchenne Data Foundation (no payment). The other authors have nothing to disclose., (© 2022 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Introduction: Although mouse models of Alzheimer's disease (AD) have increased our understanding of the molecular basis of the disease, none of those models represent late-onset Alzheimer's Disease which accounts for >90% of AD cases, and no therapeutics developed in the mouse (with the possible exceptions of aduhelm/aducanumab and gantenerumab) have succeeded in preventing or reversing the disease. This technology has allowed much progress in understanding the molecular basis of AD. To further enhance our understanding, we used wild-type rabbit (with a nearly identical amino acid sequence for amyloid as in humans) to model LOAD by stressing risk factors including age, hypercholesterolemia, and elevated blood glucose levels (BGLs), upon an ε3-like isoform of apolipoprotein. We report a combined behavioral, imaging, and metabolic study using rabbit as a non-transgenic model to examine effects of AD-related risk factors on cognition, intrinsic functional connectivity, and magnetic resonance-based biomarkers of neuropathology., Methods: Aging rabbits were fed a diet enriched with either 2% cholesterol or 10% fat/30% fructose. Monthly tests of novel object recognition (NOR) and object location memory (OLM) were administered to track cognitive impairment. Trace eyeblink conditioning (EBC) was administered as a final test of cognitive impairment. Magnetic resonance imaging (MRI) was used to obtain resting state connectivity and quantitative parametric data (R 2 *)., Results: Experimental diets induced hypercholesterolemia or elevated BGL. Both experimental diets induced statistically significant impairment of OLM (but not NOR) and altered intrinsic functional connectivity. EBC was more impaired by fat/fructose diet than by cholesterol. Whole brain and regional R 2 * MRI values were elevated in both experimental diet groups relative to rabbits on the control diet., Discussion: We propose that mechanisms underlying LOAD can be assessed by stressing risk factors for inducing AD and that dietary manipulations can be used to assess etiological differences in the pathologies and effectiveness of potential therapeutics against LOAD. In addition, non-invasive MRI in awake, non-anesthetized rabbits further increases the translational value of this non-transgenic model to study AD., Competing Interests: Grazia Aleppo is partially supported by Novo‐Nordisk, Eli‐Lilly, and Insulet/Dexcom. Payments to William L. Klein were made to organize a meeting for Acumen Pharmaceuticals. William L. Klein has founders’ shares in Acumen Pharmaceuticals and is a member of the scientific advisory board of Acumen. ACU193 was a gift from Acumen Pharmaceuticals. NU2 was developed with support from NIH Grants RO1AG18877 and RO1AG22547 to Northwestern University. Support paid to Northwestern University from NIH R01 AG063903, NIH‐R21 AG060203‐01, NIH‐R43OD023025‐01A1 (subcontract from Virscio, Inc). Imaging partially supported by the Rice Foundation. John F. Disterhoft supported by NIH R01 NS113804, R01 MH114923, R25 GM121231, T32 AG20506‐16‐20, RF1 AG017139, R37 AG008796‐28S1, R21 AG060267. John F. Disterhoft received payment from Brain Research Foundation for grant review service, and received payment from International Bordeaux Neurocampus Aging Meeting (2018). John F. Disterhoft is an unpaid member of Chicago Methodist Senior Services Board. Craig Weiss, Nicola Bertolino, Daniele Procissi, Quinn C. Smith, Kirsten L. Viola, Samuel C. Bartley have no disclosures., (© 2022 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Genes associated with immune response and inflammation have been identified as genetic risk factors for late-onset Alzheimer´s disease (LOAD). The rare R47H variant within triggering receptor expressed on myeloid cells 2 (TREM2) has been shown to increase the risk for developing Alzheimer's disease (AD) 2–3-fold. Here, we report the generation and characterization of a model of late-onset Alzheimer's disease (LOAD) using lymphoblast-derived induced pluripotent stem cells (iPSCs) from patients carrying the TREM2 R47H mutation, as well as from control individuals without dementia. All iPSCs efficiently differentiated into mature neuronal cultures, however AD neuronal cultures showed a distinct gene expression profile. Furthermore, manipulation of the iPSC-derived neuronal cultures with an Aβ-S8C dimer highlighted metabolic pathways, phagosome and immune response as the most perturbed pathways in AD neuronal cultures. Through the construction of an Aβ-induced gene regulatory network, we were able to identify an Aβ signature linked to protein processing in the endoplasmic reticulum (ER), which emphasized ER-stress, as a potential causal role in LOAD. Overall, this study has shown that our AD-iPSC based model can be used for in-depth studies to better understand the molecular mechanisms underlying the etiology of LOAD and provides new opportunities for screening of potential therapeutic targets. [ABSTRACT FROM AUTHOR]

Objective: To reassess the role of amyloid beta (Aβ) and the amyloid precursor protein (APP) system in the pathogenesis of Alzheimer's disease (AD)., Background: APP is a cell adhesion molecule that has been highly conserved over the course of phylogeny that has critical roles in brain development, synaptic plasticity, and the brain's intrinsic immune system. The amyloid cascade hypothesis describes a relatively linear, deterministic sequence of events triggered by a gain of Aβ peptide fragment toxicity that results in neurodegeneration and cognitive loss, yet well designed immunotherapy and beta secretase inhibitor trials that have successfully targeted Aβ have failed to have any consistent effects on the steady decline of cognition., New/updated Hypothesis: Mutations of the APP and presenilin genes not only alter the ratio of longer to shorter Aβ fragments (resulting in a gain of Aβ toxicity), but also disrupt the normal homeostatic roles of their respective proteins. The evolutionary history, physiological importance, and complexity of the APP and presenilin systems, as well as other critical components including tau and apolipoprotein E (APOE) imply that altered function of such systems could have severe consequences that include but need not be limited to a gain of Aβ toxicity and would more generally result in altered homeostasis of APP-related functions., Major Challenges Addressed by Our Hypothesis: Challenges that a loss of APP homeostasis addresses better than the more limited gain of Aβ toxicity model include the topographic mismatches between Aβ and tau pathology, the profile and chronology of cognitive and biomarker changes that precede the clinical expression of mild cognitive impairment and dementia, and the disappointments of Aβ targeted therapeutics among others., Linkage to Other Major Theories: The importance of APP, α- and β-secretases, the presenilins and γ-secretase, as well as tau was recognized by the authors of the amyloid cascade hypothesis, and has since led multiple investigators to propose alternative, more balanced hypotheses including reduced homeostasis and frank loss-of-function of key components that include but go beyond the currently envisioned linear model of Aβ toxicity., (© 2020 the Alzheimer's Association.)