Late-onset Alzheimer's Disease Research Articles

Characterizing molecular and synaptic signatures in mouse models of late-onset Alzheimer's disease independent of amyloid and tau pathology.

MODEL-AD (Model Organism Development and Evaluation for Late-Onset Alzheimer's Disease) is creating and distributing novel mouse models with humanized, clinically relevant genetic risk factors to capture the trajectory and progression of late-onset Alzheimer's disease (LOAD) more accurately. We created the LOAD2 model by combining apolipoprotein E4 (APOE4), Trem2*R47H, and humanized amyloid-beta (Aβ). Mice were subjected to a control diet or a high-fat/high-sugar diet (LOAD2+HFD). We assessed disease-relevant outcome measures in plasma and brain including neuroinflammation, Aβ, neurodegeneration, neuroimaging, and multi-omics. By 18 months, LOAD2+HFD mice exhibited sex-specific neuron loss, elevated insoluble brain Aβ42, increased plasma neurofilament light chain (NfL), and altered gene/protein expression related to lipid metabolism and synaptic function. Imaging showed reductions in brain volume and neurovascular uncoupling. Deficits in acquiring touchscreen-based cognitive tasks were observed. The comprehensive characterization of LOAD2+HFD mice reveals that this model is important for preclinical studies seeking to understand disease trajectory and progression of LOAD prior to or independent of amyloid plaques and tau tangles. By 18 months, unlike control mice (e.g., LOAD2 mice fed a control diet, CD), LOAD2+HFD mice presented subtle but significant loss of neurons in the cortex, elevated levels of insoluble Ab42 in the brain, and increased plasma neurofilament light chain (NfL). Transcriptomics and proteomics showed changes in gene/proteins relating to a variety of disease-relevant processes including lipid metabolism and synaptic function. In vivo imaging revealed an age-dependent reduction in brain region volume (MRI) and neurovascular uncoupling (PET/CT). LOAD2+HFD mice also demonstrated deficits in acquisition of touchscreen-based cognitive tasks.

THE POTENTIAL ROLE OF EXERCISE IN DELAYING GENETIC DESTINY: EXAMINING THE RELATIONSHIP BETWEEN EXERCISE AND KEY BIOMARKERS IN DOMINANTLY INHERITED ALZHEIMER’S DISEASE

INTRODUCTION Greater physical activity is associated with reduced risk for Alzheimer’s disease (AD), and lower levels of AD-related biomarkers, such as beta-amyloid (Aβ) and tau, measured in the cerebrospinal fluid (CSF) and brain. A small proportion of Alzheimer’s disease (<1%) cases are caused by a rare dominant genetic mutation. The aim of the current study was to examine associations between self-reported exercise participation and AD-related biomarkers (from CSF and brain imaging) over time, in individuals we know will develop Alzheimer’s disease at an early age (i.e., dominant AD mutation carriers). METHODS The sample included n = 308 mutation carriers from the Dominantly Inherited Alzheimer’s Network (DIAN) study with data available for self-reported exercise participation, brain imaging (hippocampal volume, total brain volume, gray matter volume, white matter hyperintensities, brain Aβ levels), and biomarkers quantified from CSF (several Aβ and tau species and ratios). Participants were assessed regularly (time interval depending on mutation type) from baseline to 10+ years post-baseline. Associations between exercise and AD biomarkers (i.e., from brain imaging and CSF) were examined using linear mixed models, corrected for various confounding variables. RESULTS The sample had a mean age of 39.7 ± 10.8 years and were 56% female. Greater baseline exercise was associated with a slower decrease in right (B=0.06, p < 0.001) and left (B=0.06, p<0.05) hippocampal volume; and slower accumulation of brain Aβ (B=0.04, p<0.001). CONCLUSION These findings demonstrate that exercise is associated with more favourable profiles of AD-related biomarkers in those with ADAD mutations. This work may have implications for our understanding of how exercise influences disease development in late-onset sporadic AD. Nevertheless, the causal direction of our findings is difficult to ascertain, and future study designs investigating the therapeutic potential of exercise in both ADAD and late-onset AD should be considered.

In vivo validation of late-onset Alzheimer's disease genetic risk factors.

Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action. Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE ε4/ε4 and Trem2*R47H. The potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts. We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes. These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics. A novel approach to validate genetic risk factors for late-onset AD (LOAD) is presented. LOAD risk variants were knocked in to conserved mouse loci. Variant effects were assayed by transcriptional analysis. Risk variants in Abca7, Mthfr, Plcg2, and Sorl1 loci modeled molecular signatures of clinical disease. This approach should generate more translationally relevant animal models.

Association of whole-person eigen-polygenic risk scores with Alzheimer's disease.

Late-Onset Alzheimer's Disease (LOAD) is a heterogeneous neurodegenerative disorder with complex etiology and high heritability. Its multifactorial risk profile and large portions of unexplained heritability suggest the involvement of yet unidentified genetic risk factors. Here we describe the "whole person" genetic risk landscape of polygenic risk scores for 2218 traits in 2044 elderly individuals and test if novel eigen-PRSs derived from clustered subnetworks of single-trait PRSs can improve the prediction of LOAD diagnosis, rates of cognitive decline, and canonical LOAD neuropathology. Network analyses revealed distinct clusters of PRSs with clinical and biological interpretability. Novel eigen-PRSs (ePRS) from these clusters significantly improved LOAD-related phenotypes prediction over current state-of-the-art LOAD PRS models. Notably, an ePRS representing clusters of traits related to cholesterol levels was able to improve variance explained in a model of the brain-wide beta-amyloid burden by 1.7% (likelihood ratio test P = 9.02 × 10-7). All associations of ePRS with LOAD phenotypes were eliminated by the removal of APOE-proximal loci. However, our association analysis identified modules characterized by PRSs of high cholesterol and LOAD. We believe this is due to the influence of the APOE region from both PRSs. We found significantly higher mean SNP effects for LOAD in the intersecting APOE region SNPs. Combining genetic risk factors for vascular traits and dementia could improve current single-trait PRS models of LOAD, enhancing the use of PRS in risk stratification. Our results are catalogued for the scientific community, to aid in generating new hypotheses based on our maps of clustered PRSs and associations with LOAD-related phenotypes.

Systemic inflammation in Aβ1-40-induced Alzheimer’s disease model: New translational opportunities

Alzheimer disease (AD) is the most frequent cause of dementia, and the most common neurodegenerative disease, which is characterized by memory impairment, neuronal death, and synaptic loss in the hippocampus. Sporadic late-onset AD, which accounts for over 95 % of disease cases, is a multifactorial pathology with complex etiology and pathogenesis. Nowadays, neuroinflammation is considered the third most important component of AD pathogenesis in addition to amyloid peptide generation and deposition. Neuroinflammation is associated with the impairment of blood–brain barrier and leakage of inflammatory mediators into the periphery with developing systemic inflammatory responses. Systemic inflammation is currently considered one of the therapeutic targets for AD treatment, that necessitates in-depth study of this phenomenon in appropriate non-transgenic animal models. This study was aimed to explore systemic inflammatory manifestations in rats with Aβ1-40-induced AD. The impairment of spatial memory and cognitive flexibility in Aβ1-40-lesioned rats was accompanied by pronounced systemic inflammation, which was confirmed by commonly accepted biomarkers: increased hematological indices of systemic inflammation (NLR, dNLR, LMR, PLR and SII), signs of anemia of inflammation or chronic diseases, and pro-inflammatory polarized activation of circulating phagocytes. In addition, markers of systemic inflammation strongly correlated with disorders of remote cognitive flexibility in Aβ1-40-lesioned rats. These results indicate, that Aβ1-40-induced AD model permits the investigation of specific element of the disease – systemic inflammation in addition to well reproduced neuroinflammation and impairment of spatial memory and cognitive flexibility. It increases translational value of this well-known model.

Neuronal cell cycle reentry events in the aging brain are more prevalent in neurodegeneration and lead to cellular senescence.

Increasing evidence indicates that terminally differentiated neurons in the brain may recommit to a cell cycle-like process during neuronal aging and under disease conditions. Because of the rare existence and random localization of these cells in the brain, their molecular profiles and disease-specific heterogeneities remain unclear. Through a bioinformatics approach that allows integrated analyses of multiple single-nucleus transcriptome datasets from human brain samples, these rare cell populations were identified and selected for further characterization. Our analyses indicated that these cell cycle-related events occur predominantly in excitatory neurons and that cellular senescence is likely their immediate terminal fate. Quantitatively, the number of cell cycle re-engaging and senescent neurons decreased during the normal brain aging process, but in the context of late-onset Alzheimer's disease (AD), these cells accumulate instead. Transcriptomic profiling of these cells suggested that disease-specific differences were predominantly tied to the early stage of the senescence process, revealing that these cells presented more proinflammatory, metabolically deregulated, and pathology-associated signatures in disease-affected brains. Similarly, these general features of cell cycle re-engaging neurons were also observed in a subpopulation of dopaminergic neurons identified in the Parkinson's disease (PD)-Lewy body dementia (LBD) model. An extended analysis conducted in a mouse model of brain aging further validated the ability of this bioinformatics approach to determine the robust relationship between the cell cycle and senescence processes in neurons in this cross-species setting.

CRISPR/Cas9 Gene Editing: A Novel Approach Towards Alzheimer's Disease Treatment.

In defiance of the vast amount of information regarding Alzheimer's disease (AD) that has been learned over the past thirty years, progress toward developing an effective therapy has been difficult. A neurological ailment that progresses and cannot be reversed is Alzheimer's disease, which shows neurofibrillary tangles, beta-amyloid plaque, and a lack of cognitive processes that is created by tau protein clumps with hyperphosphorylation that finally advances to neuronal damage without a recognized treatment, which has stimulated research into new therapeutic strategies. The protein CAS9 is linked to CRISPR, which is a clustered Regularly Interspaced Short Palindromic Repeat that inactivates or corrects a gene by recognizing a gene sequence that produces a doublestranded break has enchanted a whole amount of interest towards its potency to cure gene sequences in AD. The novel CRISPR-Cas9 applications for developing in vitro and in vivo models to the benefit of AD investigation and therapies are thoroughly analyzed in this work. The discussion will also touch on the creation of delivery methods, which is a significant obstacle to the therapeutic use of CRISPR/Cas9 technology. By concentrating on specific genes, such as those that are significant early-onset AD risk factors and late-onset AD risk factors, like the apolipoprotein E4 (APOE4) gene, this study aims to evaluate the potential application of CRISPR/Cas9 as a possible treatment for AD.

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.

Sex-specific associations between AD genotype and the microbiome of human amyloid beta knock-in (hAβ-KI) mice.

Emerging evidence links changes in the gut microbiome to late-onset Alzheimer's disease (LOAD), necessitating examination of AD mouse models with consideration of the microbiome. We used shotgun metagenomics and untargeted metabolomics to study the human amyloid beta knock-in (hAβ-KI) murine model for LOAD compared to both wild-type (WT) mice and a model for early-onset AD (3xTg-AD). Eighteen-month female (but not male) hAβ-KI microbiomes were distinct from WT microbiomes, with AD genotype accounting for 18% of the variance by permutational multivariate analysis of variance (PERMANOVA). Metabolomic diversity differences were observed in females, however no individual metabolites were differentially abundant. hAβ-KI mice microbiomes were distinguishable from 3xTg-AD animals (81% accuracy by random forest modeling), with separation primarily driven by Romboutsia ilealis and Turicibacter species. Microbiomes were highly cage specific, with cage assignment accounting for more than 40% of the PERMANOVA variance between the groups. These findings highlight a sex-dependent variation in the microbiomes of hAβ-KI mice and underscore the importance of considering the microbiome when designing studies that use murine models for AD. Microbial diversity and theabundance of several species differed in human amyloid beta knock-in (hAβ-KI) females but not males. Correlations to Alzheimer's disease (AD) genotype were stronger for the microbiome than the metabolome. Microbiomes from hAβ-KI mice were distinct from 3xTg-AD mice. Cage effects accounted for most of the variance in the microbiome and metabolome.

Dysregulated AEBP1 and COLEC12 Genes in Late-Onset Alzheimer's Disease: Insights from Brain Cortex and Peripheral Blood Analysis.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory and cognitive impairment, often accompanied by alterations in mood, confusion, and, ultimately, a state of acute mental disturbance. The cerebral cortex is considered a promising area for investigating the underlying causes of AD by analyzing transcriptional patterns, which could be complemented by investigating blood samples obtained from patients. We analyzed the RNA expression profiles of three distinct areas of the brain cortex, including the frontal cortex (FC), temporal cortex (TC), and entorhinal cortex (EC) in patients with AD. Functional enrichment analysis was performed on the differentially expressed genes (DEGs) across the three regions. The two genes with the most significant expression changes in the EC region were selected for assessing mRNA expression levels in the peripheral blood of late-onset AD patients using quantitative PCR (qPCR). We identified eight shared DEGs in these regions, including AEBP1 and COLEC12, which exhibited prominent changes in expression. Functional enrichment analysis uncovered a significant association of these DEGs with the transforming growth factor-β (TGF-β) signaling pathway and processes related to angiogenesis. Importantly, we established a robust connection between the up-regulation of AEBP1 and COLEC12 in both the brain and peripheral blood. Furthermore, we have demonstrated the potential of AEBP1 and COLEC12 genes as effective diagnostic tools for distinguishing between late-onset AD patients and healthy controls. This study unveils the intricate interplay between AEBP1 and COLEC12 in AD and underscores their potential as markers for disease detection and monitoring.

Towards a Unitary Hypothesis of Alzheimer's Disease Pathogenesis.

The "amyloid cascade" hypothesis of Alzheimer's disease (AD) pathogenesis invokes the accumulation in the brain of plaques (containing the amyloid-β protein precursor [AβPP] cleavage product amyloid-β [Aβ]) and tangles (containing hyperphosphorylated tau) as drivers of pathogenesis. However, the poor track record of clinical trials based on this hypothesis suggests that the accumulation of these peptides is not the only cause of AD. Here, an alternative hypothesis is proposed in which the AβPP cleavage product C99, not Aβ, is the main culprit, via its role as a regulator of cholesterol metabolism. C99, which is a cholesterol sensor, promotes the formation of mitochondria-associated endoplasmic reticulum (ER) membranes (MAM), a cholesterol-rich lipid raft-like subdomain of the ER that communicates, both physically and biochemically, with mitochondria. We propose that in early-onset AD (EOAD), MAM-localized C99 is elevated above normal levels, resulting in increased transport of cholesterol from the plasma membrane to membranes of intracellular organelles, such as ER/endosomes, thereby upregulating MAM function and driving pathology. By the same token, late-onset AD (LOAD) is triggered by any genetic variant that increases the accumulation of intracellular cholesterol that, in turn, boosts the levels of C99 and again upregulates MAM function. Thus, the functional cause of AD is upregulated MAM function that, in turn, causes the hallmark disease phenotypes, including the plaques and tangles. Accordingly, the MAM hypothesis invokes two key interrelated elements, C99 and cholesterol, that converge at the MAM to drive AD pathogenesis. From this perspective, AD is, at bottom, a lipid disorder.

Mendelian Randomization of Blood Metabolites Suggests Circulating Glutamine Protects Against Late-Onset Alzheimer's Disease.

Late-onset Alzheimer's disease (LOAD) represents a growing health burden. Previous studies suggest that blood metabolite levels influence risk of LOAD. We used a genetics-based study design which may overcome limitations of other epidemiological studies to assess the influence of metabolite levels on LOAD risk. We applied Mendelian randomization (MR) to evaluate bi-directional causal effects using summary statistics from the largest genome-wide association studies (GWAS) of 249 blood metabolites (n = 115,082) and GWAS of LOAD (ncase = 21,982, ncontrol = 41,944). MR analysis of metabolites as exposures revealed a negative association of genetically-predicted glutamine levels with LOAD (Odds Ratio (OR) = 0.83, 95% CI = 0.73, 0.92) that was consistent in multiple sensitivity analyses. We also identified a positive association of genetically-predicted free cholesterol levels in small LDL (OR = 1.79, 95% CI = 1.36, 2.22) on LOAD. Using genetically-predicted LOAD as the exposure, we identified associations with phospholipids to total lipids ratio in large LDL (OR = 0.96, 95% CI = 0.94, 0.98), but not with glutamine, suggesting that the relationship between glutamine and LOAD is unidirectional. Our findings support previous evidence that higher circulating levels of glutamine may be a target for protection against LOAD.

Genetic Insights into the Association and Causality Between Blood Metabolites and Alzheimer's Disease.

Alzheimer's disease (AD) is an increasing public health concern with the aging of the global population. Understanding the genetic correlation and potential causal relationships between blood metabolites and AD may provide important insights into the metabolic dysregulation underlying this neurodegenerative disorder. The aim of this study was to investigate the causal relationship between blood metabolites and AD using Mendelian randomization (MR) analysis. Association data were obtained from three large-scale genome-wide association studies of 486 blood metabolites (N = 7,824), AD (71,880 cases and 383,378 controls), early-onset AD (N = 303,760), and late-onset AD (N = 307,112). Causal associations between blood metabolites and AD were assessed using inverse variance weighting (IVW), MR-Egger, and weighted median methods. Bidirectional two-sample MR analysis was used to identify causal blood metabolites. MR-PRESSO, MR-Egger, and Cochran-Q were used to quantify instrumental variable heterogeneity and horizontal pleiotropy. Using MR and sensitivity analysis, we identified 40 blood metabolites with potential causal associations with AD. After applying false discovery rate (FDR) correction, two metabolites, gamma-glutamylphenylalanine (OR = 1.15, 95% CI: 1.06-1.24, p = 3.88×10-4, q = 0.09) and X-11317 (OR = 1.16, 95% CI: 1.08-1.26, p = 1.14×10-4, q = 0.05), retained significant associations with AD. Reverse MR analysis indicated no significant causal effect of AD on blood metabolites. No significant instrumental variable heterogeneity or horizontal pleiotropy was found. This two-sample MR study provides compelling evidence for a potential causal relationship between blood metabolic dysregulation and susceptibility to AD. Further investigation of the biological relevance of the identified metabolites to AD and additional supporting evidence is warranted.

Comparison of Enlarged Perivascular Spaces in Early-Onset and Late-Onset Alzheimer Disease-related Cognitive Impairment: A Single Clinic-based Study in South Korea.

We examined whether there were differences in the presence of centrum semiovale-enlarged perivascular spaces (CSO-ePVS) and basal ganglia-ePVS (BG-ePVS) among patients with Alzheimer disease-related cognitive impairment (ADCI) based on their age of onset. Out of a total of 239 patients with cognitive impairment, 155 with positive amyloid-PET results were included. Among these, 43 had early-onset ADCI (EOADCI) and 112 had late-onset ADCI (LOADCI). Patients with LOADCI exhibited a higher prevalence of hypertension, lacunes, white matter hyperintensities, and BG-ePVS than those with EOADCI. BG-ePVS showed a significant correlation with age at the onset and the number of lacunes, whereas CSO-ePVS did not exhibit any association. The higher prevalence of BG-ePVS in patients with LOADCI might be attributable to vascular risk factors (hypertension) and cerebral small vessel disease (CSVD). These findings support the hypothesis that BG-ePVS is associated with CSVD and vascular risk factors, whereas CSO-ePVS is associated with cerebral amyloid angiopathy.

Distinct patterns of voxel- and connection-based white matter hyperintensity distribution and associated factors in early-onset and late-onset Alzheimer's disease.

The distribution of voxel- and connection-based white matter hyperintensity (WMH) patterns in early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD), as well as factors associated with these patterns, remain unclear. We analyzed the WMH distribution patterns in EOAD and LOAD at the voxel and connection levels, each compared with their age-matched cognitively unimpaired participants. Linear regression assessed the independent effects of amyloid and vascular risk factors on WMH distribution patterns in both groups. Patients with EOAD showed increased WMH burden in the posterior region at the voxel level, and in occipital region tracts and visual network at the connection level, compared to controls. LOAD exhibited extensive involvement across various brain areas in both levels. Amyloid accumulation was associated WMH distribution in the early-onset group, whereas the late-onset group demonstrated associations with both amyloid and vascular risk factors. EOAD showed posterior-focused WMH distribution pattern, whereas LOAD was with a wider distribution. Amyloid accumulation was associated with connection-based WMH patterns in both early-onset and late-onsetgroups, with additional independent effects of vascular risk factors in late-onset group. Both early-onset Alzheimer's disease (EOAD) and late-onset AD (LOAD) showed increased white matter hyperintensity (WMH) volume compared with their age-matched cognitively unimpaired participants.EOAD and LOAD exhibited distinct patterns of WMH distribution, with EOAD showing a posterior-focused pattern and LOAD displaying a wider distribution across both voxel- and connection-based levels.In both EOAD and LOAD, amyloid accumulation was associated with connection-based WMH patterns, with additional independent effects of vascular risk factors observed in LOAD.

A systems biology-based identification and invivo functional screening of Alzheimer's disease risk genes reveal modulators of memory function.

Genome-wide association studies (GWASs) have uncovered over 75 genomic loci associated with risk for late-onset Alzheimer's disease (LOAD), but identification of the underlying causal genes remains challenging. Studies of induced pluripotent stem cell (iPSC)-derived neurons from LOAD patients have demonstrated the existence of neuronal cell-intrinsic functional defects. Here, we searched for genetic contributions to neuronal dysfunction in LOAD using an integrative systems approach that incorporated multi-evidence-based gene mapping and network-analysis-based prioritization. A systematic perturbation screening of candidate risk genes in Caenorhabditis elegans (C.elegans) revealed that neuronal knockdown of the LOAD risk gene orthologs vha-10 (ATP6V1G2), cmd-1 (CALM3), amph-1 (BIN1), ephx-1 (NGEF), and pho-5 (ACP2) alters short-/intermediate-term memory function, the cognitive domain affected earliest during LOAD progression. These results highlight the impact of LOAD risk genes on evolutionarily conserved memory function, as mediated through neuronal endosomal dysfunction, and identify new targets for further mechanistic interrogation.

Generation of three isogenic, gene-edited iPSC lines carrying the APOE-Christchurch mutation into the three common APOE variants: APOE2Ch, APOE3Ch and APOE4Ch

Late-onset Alzheimer’s disease (AD) has become the paradigm of a non-mendelian complex neurodegenerative disease, for which a major genetic determinant is known, the APOE locus. A rare APOE variant named Christchurch (APOEch) yielding a missense mutation from Arginine to Serine at amino acid 136, has been suggested to exert a protective effect in an individual carrying the most penetrant form of Familial AD (Paisa mutation in PSEN1 gene, E280A). We describe here a new set of induced pluripotent stem cell (iPSC) lines, where the Christchurch mutation (Ch) has been introduced by gene editing into the APOE locus of three isogenic iPSC lines carrying the more common APOE variants (APOE 2/2, APOE 3/3, and an APOE 4/4) in homozygosity. Brain cells derived from these iPSC lines will enable a better understanding of APOE biology in general and facilitate the study of how the Christchurch variant affects the function of each APOE genotype. This set of iPSC lines are globally available via the European Bank of iPSCs, EBiSC.org.

TREM1 disrupts myeloid bioenergetics and cognitive function in aging and Alzheimer disease mouse models.

Human genetics implicate defective myeloid responses in the development of late-onset Alzheimer disease. A decline in peripheral and brain myeloid metabolism, triggering maladaptive immune responses, is a feature of aging. The role of TREM1, a pro-inflammatory factor, in neurodegenerative diseases is unclear. Here we show that Trem1 deficiency prevents age-dependent changes in myeloid metabolism, inflammation and hippocampal memory function in mice. Trem1 deficiency rescues age-associated declines in ribose 5-phosphate. In vitro, Trem1-deficient microglia are resistant to amyloid-β42 oligomer-induced bioenergetic changes, suggesting that amyloid-β42 oligomer stimulation disrupts homeostatic microglial metabolism and immune function via TREM1. In the 5XFAD mouse model, Trem1 haploinsufficiency prevents spatial memory loss, preserves homeostatic microglial morphology, and reduces neuritic dystrophy and changes in the disease-associated microglial transcriptomic signature. In aging APPSwe mice, Trem1 deficiency prevents hippocampal memory decline while restoring synaptic mitochondrial function and cerebral glucose uptake. In postmortem Alzheimer disease brain, TREM1 colocalizes with Iba1+ cells around amyloid plaques and its expression is associated with Alzheimer disease clinical and neuropathological severity. Our results suggest that TREM1 promotes cognitive decline in aging and in the context of amyloid pathology.

Comparison of Extracellular Vesicles from Induced Pluripotent Stem Cell-Derived Brain Cells.

The pathophysiology of many neuropsychiatric disorders is still poorly understood. Identification of biomarkers for these diseases could benefit patients due to better classification and stratification. Exosomes excreted into the circulatory system can cross the blood-brain barrier and carry a cell type-specific set of molecules. Thus, exosomes are a source of potential biomarkers for many diseases, including neuropsychiatric disorders. Here, we investigated exosomal proteins produced from human-induced pluripotent stem cells (iPSCs) and iPSC-derived neural stem cells, neural progenitors, neurons, astrocytes, microglia-like cells, and brain capillary endothelial cells. Of the 31 exosome surface markers analyzed, a subset of biomarkers were significantly enriched in astrocytes (CD29, CD44, and CD49e), microglia-like cells (CD44), and neural stem cells (SSEA4). To identify molecular fingerprints associated with disease, circulating exosomes derived from healthy control (HC) individuals were compared against schizophrenia (SCZ) patients and late-onset Alzheimer's disease (LOAD) patients. A significant epitope pattern was identified for LOAD (CD1c and CD2) but not for SCZ compared to HC. Thus, analysis of cell type- and disease-specific exosome signatures of iPSC-derived cell cultures may provide a valuable model system to explore proteomic biomarkers for the identification of novel disease profiles.

Distinctive whole-brain cell types predict tissue damage patterns in thirteen neurodegenerative conditions.

For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types' contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in 13 neurodegenerative conditions, including early- and late-onset Alzheimer's disease, Parkinson's disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and 3 clinical variants of frontotemporal lobar degeneration (behavioral variant, semantic and non-fluent primary progressive aphasia) along with associated three-repeat and four-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorder pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.