Religious Orders Study and Rush Memory and Aging Project

Risk Variants Associated With Normal Pressure Hydrocephalus: Genome-Wide Association Study in the FinnGen Cohort

BACKGROUND AND OBJECTIVES

Large-scale genome-wide studies of chronic hydrocephalus have been lacking. We conducted a genome-wide association study (GWAS) in normal pressure hydrocephalus (NPH).

METHODS

We used a case-control study design implementing FinnGen data containing 473,691 Finns with genotypes and nationwide health records. Patients with NPH were selected based on ICD-10 G91.2 diagnosis. To select patients with idiopathic NPH (iNPH) for sensitivity analysis, we excluded patients with a potentially known etiology of the condition using an algorithm on their disease history. The controls were the remaining non-hydrocephalic participants. For a replication analysis, the NPH cohort from UK Biobank (UKBB) was used.

RESULTS

We included 1,522 patients with NPH (mean age 72.2 years, 53% women) and 451,091 controls (mean age 60.5 years, 44% women). In the GWAS comparing patients with NPH with the controls, we identified 6 gene regions significantly (p < 5.0e-8) associated with NPH that replicated in a meta-analysis with UKBB (NPH n = 173). The top loci near the following genes were rs7962263, SLCO1A2 (odds ratio [OR] 0.71, 95% CI 0.65-0.78, p = 1.0e-14); rs798495, AMZ1/GNA12 (OR 1.29, 95% CI 1.20-1.39, p = 2.9e-12); rs10828247, MLLT10 (OR 0.77, 95% CI 0.71-0.83, p = 1.5e-11); rs561699566 and rs371919113, CDCA2 (OR 0.76, 95% CI 0.70-0.82, p = 1.5e-11); rs56023709, C16orf95 (OR 1.24, 95% CI 1.16-1.33, p = 3.0e-9); and rs62434144, PLEKHG1 (OR 1.23, 95% CI 1.14-1.32, p = 1.4e-8). In the sensitivity analysis comparing only patients with iNPH (n = 1,055) with the controls (n = 451,091), 4 top loci near the following genes remained significant: rs7962263, SLCO1A2 (OR 0.70, 95% CI 0.63-0.78, p = 2.1e-11); rs10828247, MLLT10 (OR 0.74, 95% CI 0.62-0.82, p = 4.6e-10); rs798511, AMZ1/GNA12 (OR 1.28, 95% CI 1.17-1.39, p = 1.7e-8); and rs56023709, C16orf95 (OR 1.28, 95% CI 1.17-1.39, p = 1.7e-8).

DISCUSSION

We identified 6 loci significantly associated with NPH in the thus far largest GWAS in chronic hydrocephalus. The genes near the top loci have previously been associated with blood-brain barrier and blood-CSF barrier function and with increased lateral brain ventricle volume. The effect sizes and allele frequencies remained similar in NPH and iNPH cohorts, indicating the identified loci are risk determinants for iNPH and likely not explained by associations with other etiologies. However, the exact role of these loci is still unknown, warranting further studies.

Reduced PIN1 expression in neocortical and limbic brain regions in female Alzheimer's patients correlates with cognitive and neuropathological phenotypes

Women have a higher incidence of Alzheimer's disease (AD), even after adjusting for increased longevity. Thus, there is an urgent need to identify genes that underpin sex-associated risk of AD. PIN1 is a key regulator of the tau phosphorylation signaling pathway; however, potential differences in PIN1 expression, in males and females, are still unknown. We analyzed brain transcriptomic datasets focusing on sex differences in PIN1 mRNA levels in an aging and AD cohort, which revealed reduced PIN1 levels primarily within females. We validated this observation in an independent dataset (ROS/MAP), which also revealed that PIN1 is negatively correlated with multiregional neurofibrillary tangle density and global cognitive function in females only. Additional analysis revealed a decrease in PIN1 in subjects with mild cognitive impairment (MCI) compared with aged individuals, again driven predominantly by female subjects. Histochemical analysis of PIN1 in AD and control male and female neocortex revealed an overall decrease in axonal PIN1 protein levels in females. These findings emphasize the importance of considering sex differences in AD research.

Beyond Hypertension: Examining Variable Blood Pressure's Role in Cognition and Brain Structure

OBJECTIVES

Hypertension or high blood pressure (BP) is one of the 12 modifiable risk factors that contribute to 40% of dementia cases that could be delayed or prevented. Although hypertension is associated with cognitive decline and structural brain changes, less is known about the long-term association between variable BP and cognitive/brain changes. This study examined the relationship between variable BP and longitudinal cognitive, white matter hyperintensity (WMH), gray matter (GM), and white matter (WM) volume change over time and postmortem neuropathology.

METHODS

A total of 4,606 participants (32,776 follow-ups) from RADC Research Resource Sharing Hub (RUSH) and 2,114 participants (9,827 follow-ups) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were included. Participants were divided into 1 of 3 groups: normal, high, or variable BP. Linear-mixed models investigated the relationship between BP and cognition, brain structure, and neuropathology.

RESULTS

Older adults with variable BP exhibited the highest rate of cognitive decline followed by high and then normal BP. Increased GM volume loss and WMH burden were also observed in variable compared to high and normal BP. In postmortem neuropathology, both variable and high BP had increased rates compared to normal BP. Results were consistent across the RUSH and ADNI participants, supporting the generalizability of the findings.

DISCUSSION

Damages potentially associated with variable BP may reduce resilience to future dementia-related pathology and increased the risk of dementia more than that caused by high BP. Improved treatment and management of variable BP may help reduce cognitive decline in the older adult population.

Psychological well-being trajectories preceding incident mild cognitive impairment and dementia

BACKGROUND

Poorer psychological well-being has been related to an increased dementia risk, but changes in psychological well-being along the dementia course are unclear. We explored psychological well-being trajectories before and after the diagnosis of mild cognitive impairment (MCI) and dementia.

METHODS

Within the Rush Memory and Aging Project, 910 cognitively intact older adults were followed annually for up to 14 years to detect incident MCI and dementia. Psychological well-being and its six components (self-acceptance, autonomy, environmental mastery, purpose in life, positive relation with others, and personal growth) were annually measured based on Ryff's Scales of Psychological Well-Being. Data were analysed using mixed-effect models with a backward timescale.

RESULTS

Compared with participants who remained cognitively intact, those who developed incident MCI had a faster decline in psychological well-being (β -0.015, 95% CI -0.027 to -0.003), leading to lower well-being 2 years before MCI diagnosis (mean difference at year -2, -0.099, 95% CI -0.187 to -0.012). Considering different well-being components, those who developed MCI had lower levels of purpose in life and personal growth beginning 3 years (-0.126, 95% CI -0.251 to -0.001) and 6 years (-0.139, 95% CI -0.268 to -0.009) before MCI, respectively. The slope of psychological well-being decline was similar before and after MCI diagnosis for each component except for positive relation with others, which had an accelerated decline after MCI (β -0.042, 95% CI-0.075 to -0.009). Well-being trajectories remained similar for individuals with MCI regardless of whether they later developed dementia.

CONCLUSIONS

Psychological well-being (specifically purpose in life and personal growth) became significantly lower before MCI diagnosis.

The MIND diet, brain transcriptomic alterations, and dementia

INTRODUCTION

Dietary patterns are associated with dementia risk, but the underlying molecular mechanisms are largely unknown.

METHODS

We used RNA sequencing data from post mortem prefrontal cortex tissue and annual cognitive evaluations from 1204 participants in the Religious Orders Study and Memory and Aging Project. We identified a transcriptomic profile correlated with the MIND diet (Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay) among 482 individuals who completed ante mortem food frequency questionnaires; and examined its associations with cognitive health in the remaining 722 participants.

RESULTS

We identified a transcriptomic profile, consisting of 50 genes, correlated with the MIND diet score (p = 0.001). Each standard deviation increase in the transcriptomic profile score was associated with a slower annual rate of decline in global cognition (β = 0.011, p = 0.003) and lower odds of dementia (odds ratio = 0.76, p = 0.0002). Expressions of several genes (including TCIM and IGSF5) appeared to mediate the association between MIND diet and dementia.

DISCUSSION

A brain transcriptomic profile for healthy diets revealed novel genes potentially associated with cognitive health.

HIGHLIGHTS

Why healthy dietary patterns are associated with lower dementia risk are unknown. We integrated dietary, brain transcriptomic, and cognitive data in older adults. Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay (MIND) diet intake is correlated with a specific brain transcriptomic profile. This brain transcriptomic profile score is associated with better cognitive health. More data are needed to elucidate the causality and functionality of identified genes.

Dendritic spine head diameter predicts episodic memory performance in older adults

Episodic memory in older adults is varied and perceived to rely on numbers of synapses or dendritic spines. We analyzed 2157 neurons among 128 older individuals from the Religious Orders Study and Rush Memory and Aging Project. Analysis of 55,521 individual dendritic spines by least absolute shrinkage and selection operator regression and nested model cross-validation revealed that the dendritic spine head diameter in the temporal cortex, but not the premotor cortex, improved the prediction of episodic memory performance in models containing β amyloid plaque scores, neurofibrillary tangle pathology, and sex. These findings support the emerging hypothesis that, in the temporal cortex, synapse strength is more critical than quantity for memory in old age.

An integrative multi-context Mendelian randomization method for identifying risk genes across human tissues

Mendelian randomization (MR) provides valuable assessments of the causal effect of exposure on outcome, yet the application of conventional MR methods for mapping risk genes encounters new challenges. One of the issues is the limited availability of expression quantitative trait loci (eQTLs) as instrumental variables (IVs), hampering the estimation of sparse causal effects. Additionally, the often context- or tissue-specific eQTL effects challenge the MR assumption of consistent IV effects across eQTL and GWAS data. To address these challenges, we propose a multi-context multivariable integrative MR framework, mintMR, for mapping expression and molecular traits as joint exposures. It models the effects of molecular exposures across multiple tissues in each gene region, while simultaneously estimating across multiple gene regions. It uses eQTLs with consistent effects across more than one tissue type as IVs, improving IV consistency. A major innovation of mintMR involves employing multi-view learning methods to collectively model latent indicators of disease relevance across multiple tissues, molecular traits, and gene regions. The multi-view learning captures the major patterns of disease relevance and uses these patterns to update the estimated tissue relevance probabilities. The proposed mintMR iterates between performing a multi-tissue MR for each gene region and joint learning the disease-relevant tissue probabilities across gene regions, improving the estimation of sparse effects across genes. We apply mintMR to evaluate the causal effects of gene expression and DNA methylation for 35 complex traits using multi-tissue QTLs as IVs. The proposed mintMR controls genome-wide inflation and offers insights into disease mechanisms.

Parkinson's Disease and Other Alzheimer's Disease and Related Dementia Pathologies and the Progression of Parkinsonism in Older Adults

Background

The interrelationship of parkinsonism, Parkinson's disease (PD) and other Alzheimer's disease (AD) and Alzheimer's disease and related dementias (ADRD) pathologies is unclear.

Objective

We examined the progression of parkinsonian signs in adults with and without parkinsonism, and their underlying brain pathologies.

Methods

Annual parkinsonian signs were based on a modified Unified Parkinson's Disease Rating Scale. We used linear mixed effects models to compare the progression of parkinsonian signs in 3 groups categorized based on all available clinical evaluations: Group1 (never parkinsonism or clinical PD), Group2 (ever parkinsonism, but never clinical PD), Group3 (ever clinical PD). In decedents, we examined the progression of parkinsonian signs with PD and eight other AD/ADRD pathologies.

Results

During average follow-up of 8 years, parkinsonian signs on average increased by 7.3% SD/year (N = 3,807). The progression of parkinsonian signs was slowest in Group1 (never parkinsonism or clinical PD), intermediate in Group2, and fastest in Group3. In decedents (n = 1,717) pathologic PD and cerebrovascular (CVD) pathologies were associated with a faster rate of progressive parkinsonian signs (all p values <0.05). However, pathologic PD was rare in adults without clinical PD (Group1, 5%; Group2, 7% versus Group3, 55%). Yet, 70% of adults in Group2 without pathologic PD showed one or more CVD pathologies. In Group2, adults with pathologic PD showed faster progression of parkinsonian signs compared with those without evidence of pathologic PD and their rate of progression was indistinguishable from adults with clinical PD.

Conclusions

Parkinsonism in old age is more commonly related to cerebrovascular pathologies relative to pathologic PD and only a minority manifest prodromal PD.

Network proteomics of the Lewy body dementia brain reveals presynaptic signatures distinct from Alzheimer's disease

Lewy body dementia (LBD), a class of disorders comprising Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB), features substantial clinical and pathological overlap with Alzheimer's disease (AD). The identification of biomarkers unique to LBD pathophysiology could meaningfully advance its diagnosis, monitoring, and treatment. Using quantitative mass spectrometry (MS), we measured over 9,000 proteins across 138 dorsolateral prefrontal cortex (DLPFC) tissues from a University of Pennsylvania autopsy collection comprising control, Parkinson's disease (PD), PDD, and DLB diagnoses. We then analyzed co-expression network protein alterations in those with LBD, validated these disease signatures in two independent LBD datasets, and compared these findings to those observed in network analyses of AD cases. The LBD network revealed numerous groups or "modules" of co-expressed proteins significantly altered in PDD and DLB, representing synaptic, metabolic, and inflammatory pathophysiology. A comparison of validated LBD signatures to those of AD identified distinct differences between the two diseases. Notably, synuclein-associated presynaptic modules were elevated in LBD but decreased in AD relative to controls. We also found that glial-associated matrisome signatures consistently elevated in AD were more variably altered in LBD, ultimately stratifying those LBD cases with low versus high burdens of concurrent beta-amyloid deposition. In conclusion, unbiased network proteomic analysis revealed diverse pathophysiological changes in the LBD frontal cortex distinct from alterations in AD. These results highlight the LBD brain network proteome as a promising source of biomarkers that could enhance clinical recognition and management.

Enhanced microglial dynamics and a paucity of tau seeding in the amyloid plaque microenvironment contribute to cognitive resilience in Alzheimer's disease

Asymptomatic Alzheimer's disease (AsymAD) describes the status of individuals with preserved cognition but identifiable Alzheimer's disease (AD) brain pathology (i.e., beta-amyloid (Aβ) deposits, neuritic plaques, and neurofibrillary tangles) at autopsy. In this study, we investigated the postmortem brains of a cohort of AsymAD subjects to gain insight into the mechanisms underlying resilience to AD pathology and cognitive decline. Our results showed that AsymAD cases exhibit enrichment in core plaques, decreased filamentous plaque accumulation, and increased plaque-surrounding microglia. Less pathological tau aggregation in dystrophic neurites was found in AsymAD brains than in AD brains, and tau seeding activity was comparable to that in healthy brains. We used spatial transcriptomics to characterize the plaque niche further and revealed autophagy, endocytosis, and phagocytosis as the pathways associated with the genes upregulated in the AsymAD plaque niche. Furthermore, the levels of ARP2 and CAP1, which are actin-based motility proteins that participate in the dynamics of actin filaments to allow cell motility, were increased in the microglia surrounding amyloid plaques in AsymAD cases. Our findings suggest that the amyloid-plaque microenvironment in AsymAD cases is characterized by the presence of microglia with highly efficient actin-based cell motility mechanisms and decreased tau seeding compared with that in AD brains. These two mechanisms can potentially protect against the toxic cascade initiated by Aβ, preserving brain health, and slowing AD pathology progression.

SR-TWAS: leveraging multiple reference panels to improve transcriptome-wide association study power by ensemble machine learning

Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for transcriptome-wide association studies (TWAS). To leverage expression imputation models (i.e., base models) trained with multiple reference panels, regression methods, and tissues, we develop a Stacked Regression based TWAS (SR-TWAS) tool which can obtain optimal linear combinations of base models for a given validation transcriptomic dataset. Both simulation and real studies show that SR-TWAS improves power, due to increased training sample sizes and borrowed strength across multiple regression methods and tissues. Leveraging base models across multiple reference panels, tissues, and regression methods, our real studies identify 6 independent significant risk genes for Alzheimer's disease (AD) dementia for supplementary motor area tissue and 9 independent significant risk genes for Parkinson's disease (PD) for substantia nigra tissue. Relevant biological interpretations are found for these significant risk genes.

Nominating novel proteins for anxiety via integrating human brain proteomes and genome-wide association study

BACKGROUND

The underlying pathogenesis of anxiety remain elusive, making the pinpointing of potential therapeutic and diagnostic biomarkers for anxiety paramount to its efficient treatment.

METHODS

We undertook a proteome-wide association study (PWAS), fusing human brain proteomes from both discovery (ROS/MAP; N = 376) and validation cohorts (Banner; N = 152) with anxiety genome-wide association study (GWAS) summary statistics. Complementing this, we executed transcriptome-wide association studies (TWAS) leveraging human brain transcriptomic data from the Common Mind Consortium (CMC) to discern the confluence of genetic influences spanning both proteomic and transcriptomic levels. We further scrutinized significant genes through a suite of methodologies.

RESULTS

We discerned 14 genes instrumental in the genesis of anxiety through their specific cis-regulated brain protein abundance. Out of these, 6 were corroborated in the confirmatory PWAS, with 4 also showing associations with anxiety via their cis-regulated brain mRNA levels. A heightened confidence level was attributed to 5 genes (RAB27B, CCDC92, BTN2A1, TMEM106B, and DOC2A), taking into account corroborative evidence from both the confirmatory PWAS and TWAS, coupled with insights from mendelian randomization analysis and colocalization evaluations. A majority of the identified genes manifest in brain regions intricately linked to anxiety and predominantly partake in lysosomal metabolic processes.

LIMITATIONS

The limited scope of the brain proteome reference datasets, stemming from a relatively modest sample size, potentially curtails our grasp on the entire gamut of genetic effects.

CONCLUSION

The genes pinpointed in our research present a promising groundwork for crafting therapeutic interventions and diagnostic tools for anxiety.

Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease

Quantitative mobility analysis using wearable sensors, while promising as a diagnostic tool for Parkinson's disease (PD), is not commonly applied in clinical settings. Major obstacles include uncertainty regarding the best protocol for instrumented mobility testing and subsequent data processing, as well as the added workload and complexity of this multi-step process. To simplify sensor-based mobility testing in diagnosing PD, we analyzed data from 262 PD participants and 50 controls performing several motor tasks wearing a sensor on their lower back containing a triaxial accelerometer and a triaxial gyroscope. Using ensembles of heterogeneous machine learning models incorporating a range of classifiers trained on a set of sensor features, we show that our models effectively differentiate between participants with PD and controls, both for mixed-stage PD (92.6% accuracy) and a group selected for mild PD only (89.4% accuracy). Omitting algorithmic segmentation of complex mobility tasks decreased the diagnostic accuracy of our models, as did the inclusion of kinesiological features. Feature importance analysis revealed that Timed Up and Go (TUG) tasks to contribute the highest-yield predictive features, with only minor decreases in accuracy for models based on cognitive TUG as a single mobility task. Our machine learning approach facilitates major simplification of instrumented mobility testing without compromising predictive performance.

Lower GLUT1 and unchanged MCT1 in Alzheimer's disease cerebrovasculature

The brain is a highly demanding organ, utilizing mainly glucose but also ketone bodies as sources of energy. Glucose transporter-1 (GLUT1) and monocarboxylates transporter-1 (MCT1) respectively transport glucose and ketone bodies across the blood-brain barrier. While reduced glucose uptake by the brain is one of the earliest signs of Alzheimer's disease (AD), no change in the uptake of ketone bodies has been evidenced yet. To probe for changes in GLUT1 and MCT1, we performed Western immunoblotting in microvessel extracts from the parietal cortex of 60 participants of the Religious Orders Study. Participants clinically diagnosed with AD had lower cerebrovascular levels of GLUT1, whereas MCT1 remained unchanged. GLUT1 reduction was associated with lower cognitive scores. No such association was found for MCT1. GLUT1 was inversely correlated with neuritic plaques and cerebrovascular β-secretase-derived fragment levels. No other significant associations were found between both transporters, markers of Aβ and tau pathologies, sex, age at death or apolipoprotein-ε4 genotype. These results suggest that, while a deficit of GLUT1 may underlie the reduced transport of glucose to the brain in AD, no such impairment occurs for MCT1. This study thus supports the exploration of ketone bodies as an alternative energy source for the aging brain.

Elevated protease-activated receptor 4 (PAR4) gene expression in Alzheimer's disease predicts cognitive decline

Platelet activation of protease-activated receptor 4 (PAR4) and thrombin are at the top of a chain of events leading to fibrin deposition, microinfarcts, blood-brain barrier disruption, and inflammation. We evaluated mRNA expression of the PAR4 gene F2RL3 in human brain and global cognitive performance in participants with and without cognitive impairment or dementia. Data were acquired from the Religious Orders Study (ROS) and the Rush Memory and Aging Project (MAP). F2RL3 mRNA was elevated in AD cases and was associated with worse retrospective longitudinal cognitive performance. Moreover, F2RL3 expression interacted with clinical AD diagnosis on longitudinal cognition whereas this relationship was attenuated in individuals without cognitive impairment. Additionally, when adjusting for the effects of AD neuropathology, F2RL3 expression remained a significant predictor of cognitive decline. F2RL3 expression correlated positively with transcript levels of proinflammatory markers including TNFα, IL-1β, NFκB, and fibrinogen α/β/γ. Together, these results reveal that F2RL3 mRNA expression is associated with multiple AD-relevant outcomes and its encoded product, PAR4, may play a role in disease pathogenesis.

Limbic-predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) is associated with abnormalities in white matter structural integrity and connectivity: An ex-vivo diffusion MRI and pathology investigation

Limbic predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) is common in older adults and is associated with neurodegeneration, cognitive decline and dementia. In this MRI and pathology investigation we tested the hypothesis that LATE-NC is associated with abnormalities in white matter structural integrity and connectivity of a network of brain regions typically harboring TDP-43 inclusions in LATE, referred to here as the "LATE-NC network". Ex-vivo diffusion MRI and detailed neuropathological data were collected on 184 community-based older adults. Linear regression revealed an independent association of higher LATE-NC stage with lower diffusion anisotropy in a set of white matter connections forming a pattern of connectivity that is consistent with the stereotypical spread of this pathology in the brain. Graph theory analysis revealed an association of higher LATE-NC stage with weaker integration and segregation in the LATE-NC network. Abnormalities were significant in stage 3, suggesting that they are detectable in later stages of the disease. Finally, LATE-NC network abnormalities were associated with faster cognitive decline, specifically in episodic and semantic memory.

Quantitative assessment of enlarged perivascular spaces via deep-learning in community-based older adults reveals independent associations with vascular neuropathologies, vascular risk factors and cognition

Enlarged perivascular spaces (EPVS) are common in older adults, but their neuropathologic correlates are unclear mainly because most work to date has relied on visual rating scales and/or clinical cohorts. The present study first developed a deep-learning model for automatic segmentation, localization and quantification of EPVS in ex vivo brain MRI, and then used this model to investigate the neuropathologic, clinical and cognitive correlates of EPVS in 817 community-based older adults that underwent autopsy. The new method exhibited high sensitivity in detecting EPVS as small as 3 mm3, good segmentation accuracy and consistency. Most EPVS were located in the frontal lobe, but the highest density was observed in the basal ganglia. EPVS in the cerebrum and specifically in the frontal lobe were associated with infarcts independent of other neuropathologies, while temporal and occipital EPVS were associated with cerebral amyloid angiopathy. EPVS in most brain lobes were also associated with diabetes mellitus independently of neuropathologies, while basal ganglia EPVS were independently associated with hypertension, supporting the notion of independent pathways from diabetes and hypertension to EPVS. Finally, EPVS were associated with lower cognitive performance independently of neuropathologies and clinical variables, suggesting that EPVS represent additional abnormalities contributing to lower cognition.

Multi-omics analyses highlight molecular differences between clinical and neuropathological diagnoses in Alzheimer's disease

Both clinical diagnosis and neuropathological diagnosis are commonly used in literature to categorize individuals as Alzheimer's disease (AD) or non-AD in omics analyses. Whether these diagnostic strategies result in distinct profiles of molecular abnormalities is poorly understood. Here, we analysed one of the most commonly used AD omics datasets in the literature from the Religious Orders Study and Memory and Aging Project (ROSMAP) cohort and compared the two diagnosis strategies using brain transcriptome and metabolome by grouping individuals as non-AD and AD according to clinical or neuropathological diagnosis separately. Differentially expressed genes, associated pathways related with AD hallmarks and AD-related genes showed that the categorization based on neuropathological diagnosis more accurately reflects the disease state at the molecular level than the categorization based on clinical diagnosis. We further identified consensus biomarker candidates between the two diagnosis strategies such as 5-hydroxylysine, sphingomyelin and 1-myristoyl-2-palmitoyl-GPC as metabolite biomarkers and sphingolipid metabolism as a pathway biomarker, which could be robust AD biomarkers since they are independent of diagnosis strategies. We also used consensus AD and consensus non-AD individuals between the two diagnostic strategies to train a machine-learning based model, which we used to classify the individuals who were cognitively normal but diagnosed as AD based on neuropathological diagnosis (asymptomatic AD individuals). The majority of these individuals were classified as consensus AD patients for both omics data types. Our study provides a detailed characterization of both diagnostic strategies in terms of the association of the corresponding multi-omics profiles with AD.

Group lasso priors for Bayesian accelerated failure time models with left-truncated and interval-censored data

An important task in health research is to characterize time-to-event outcomes such as disease onset or mortality in terms of a potentially high-dimensional set of risk factors. For example, prospective cohort studies of Alzheimer's disease (AD) typically enroll older adults for observation over several decades to assess the long-term impact of genetic and other factors on cognitive decline and mortality. The accelerated failure time model is particularly well-suited to such studies, structuring covariate effects as "horizontal" changes to the survival quantiles that conceptually reflect shifts in the outcome distribution due to lifelong exposures. However, this modeling task is complicated by the enrollment of adults at differing ages, and intermittent follow-up visits leading to interval-censored outcome information. Moreover, genetic and clinical risk factors are not only high-dimensional, but characterized by underlying grouping structures, such as by function or gene location. Such grouped high-dimensional covariates require shrinkage methods that directly acknowledge this structure to facilitate variable selection and estimation. In this paper, we address these considerations directly by proposing a Bayesian accelerated failure time model with a group-structured lasso penalty, designed for left-truncated and interval-censored time-to-event data. We develop an R package with a Markov chain Monte Carlo sampler for estimation. We present a simulation study examining the performance of this method relative to an ordinary lasso penalty and apply the proposed method to identify groups of predictive genetic and clinical risk factors for AD in the Religious Orders Study and Memory and Aging Project prospective cohort studies of AD and dementia.

Single-cell multiregion dissection of Alzheimer's disease

Alzheimer's disease is the leading cause of dementia worldwide, but the cellular pathways that underlie its pathological progression across brain regions remain poorly understood1-3. Here we report a single-cell transcriptomic atlas of six different brain regions in the aged human brain, covering 1.3 million cells from 283 post-mortem human brain samples across 48 individuals with and without Alzheimer's disease. We identify 76 cell types, including region-specific subtypes of astrocytes and excitatory neurons and an inhibitory interneuron population unique to the thalamus and distinct from canonical inhibitory subclasses. We identify vulnerable populations of excitatory and inhibitory neurons that are depleted in specific brain regions in Alzheimer's disease, and provide evidence that the Reelin signalling pathway is involved in modulating the vulnerability of these neurons. We develop a scalable method for discovering gene modules, which we use to identify cell-type-specific and region-specific modules that are altered in Alzheimer's disease and to annotate transcriptomic differences associated with diverse pathological variables. We identify an astrocyte program that is associated with cognitive resilience to Alzheimer's disease pathology, tying choline metabolism and polyamine biosynthesis in astrocytes to preserved cognitive function late in life. Together, our study develops a regional atlas of the ageing human brain and provides insights into cellular vulnerability, response and resilience to Alzheimer's disease pathology.

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.

Differences in the cerebral amyloid angiopathy proteome in Alzheimer's disease and mild cognitive impairment

Cerebral amyloid angiopathy (CAA) is characterized by amyloid beta (Aβ) deposition in cerebrovasculature. It is prevalent with aging and Alzheimer's disease (AD), associated with intracerebral hemorrhage, and contributes to cognitive deficits. To better understand molecular mechanisms, CAA(+) and CAA(-) vessels were microdissected from paraffin-embedded autopsy temporal cortex of age-matched Control (n = 10), mild cognitive impairment (MCI; n = 4), and sporadic AD (n = 6) cases, followed by label-free quantitative mass spectrometry. 257 proteins were differentially abundant in CAA(+) vessels compared to neighboring CAA(-) vessels in MCI, and 289 in AD (p < 0.05, fold-change > 1.5). 84 proteins changed in the same direction in both groups, and many changed in the same direction among proteins significant in at least one group (p < 0.0001, R2 = 0.62). In CAA(+) vessels, proteins significantly increased in both AD and MCI were particularly associated with collagen-containing extracellular matrix, while proteins associated with ribonucleoprotein complex were significantly decreased in both AD and MCI. In neighboring CAA(-) vessels, 61 proteins were differentially abundant in MCI, and 112 in AD when compared to Control cases. Increased proteins in CAA(-) vessels were associated with extracellular matrix, external encapsulating structure, and collagen-containing extracellular matrix in MCI; collagen trimer in AD. Twenty two proteins were increased in CAA(-) vessels of both AD and MCI. Comparison of the CAA proteome with published amyloid-plaque proteomic datasets identified many proteins similarly enriched in CAA and plaques, as well as a protein subset hypothesized as preferentially enriched in CAA when compared to plaques. SEMA3G emerged as a CAA specific marker, validated immunohistochemically and with correlation to pathology levels (p < 0.0001; R2 = 0.90). Overall, the CAA(-) vessel proteomes indicated changes in vessel integrity in AD and MCI in the absence of Aβ, and the CAA(+) vessel proteome was similar in MCI and AD, which was associated with vascular matrix reorganization, protein translation deficits, and blood brain barrier breakdown.

Targeted co-expression networks for the study of traits

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used approach for the generation of gene co-expression networks. However, networks generated with this tool usually create large modules with a large set of functional annotations hard to decipher. We have developed TGCN, a new method to create Targeted Gene Co-expression Networks. This method identifies the transcripts that best predict the trait of interest based on gene expression using a refinement of the LASSO regression. Then, it builds the co-expression modules around those transcripts. Algorithm properties were characterized using the expression of 13 brain regions from the Genotype-Tissue Expression project. When comparing our method with WGCNA, TGCN networks lead to more precise modules that have more specific and yet rich biological meaning. Then, we illustrate its applicability by creating an APP-TGCN on The Religious Orders Study and Memory and Aging Project dataset, aiming to identify the molecular pathways specifically associated with APP role in Alzheimer's disease. Main biological findings were further validated in two independent cohorts. In conclusion, we provide a new framework that serves to create targeted networks that are smaller, biologically relevant and useful in high throughput hypothesis driven research. The TGCN R package is available on Github: https://github.com/aliciagp/TGCN .

Longitudinal relationships between depressive symptoms, functional impairment, and physical activity in later late life

The purpose of this study was to investigate relationships between depressive symptoms, functional disability, and physical activity over time in community-dwelling older adults. The Religious Order Study and Rush Memory and Aging Project are longitudinal cohort studies based in the United States which began recruitment in 1994 and 1997, respectively. This analysis included 1611 participants (27.4% male, 92.9% White, 74.7% cognitively normal) who were included at age 80 and followed until age 90. Depressive symptoms were assessed using the modified Center for Epidemiologic Studies Depression scale. Functional disability was assessed using the Instrumental Activities of Daily Living (IADL) scale. Physical activity was self-reported hours of weekly exercise. Reciprocal temporal relationships between these variables were investigated using a random intercept cross-lagged panel model, which decomposes observed variables into stable between-person ('trait') and variable within-person ('state') components to estimate the directional effects between variables over time. Traits for depressive symptoms, IADL disability, and physical activity were correlated. IADL disability showed autoregressive effects; disability starting at age 82 strongly predicted subsequent disability. Consistent autoregressive effects were not observed for depressive symptoms nor physical activity. Several small cross-lagged effects between states were observed for IADL disability and physical activity, as well as for IADL disability and depressive symptoms. There were no direct effects between depressive symptoms and physical activity, but several paths through IADL disability were observed between ages 82 and 88. Functional disability played an important role in octogenarians, highlighting the importance of maintaining functional independence later in life.

Identification of deregulated lncRNAs in Alzheimer's disease: an integrated gene co-expression network analysis of hippocampus and fusiform gyrus RNA-seq datasets

Introduction

The deregulation of lncRNAs expression has been associated with neuronal damage in Alzheimer's disease (AD), but how or whether they can influence its onset is still unknown. We investigated 2 RNA-seq datasets consisting, respectively, of the hippocampal and fusiform gyrus transcriptomic profile of AD patients, matched with non-demented controls.

Methods

We performed a differential expression analysis, a gene correlation network analysis (WGCNA) and a pathway enrichment analysis of two RNA-seq datasets.

Results

We found deregulated lncRNAs in common between hippocampus and fusiform gyrus and deregulated gene groups associated to functional pathways related to neurotransmission and memory consolidation. lncRNAs, co-expressed with known AD-related coding genes, were identified from the prioritized modules of both brain regions.

Discussion

We found common deregulated lncRNAs in the AD hippocampus and fusiform gyrus, that could be considered common signatures of AD pathogenesis, providing an important source of information for understanding the molecular changes of AD.

Charting Alzheimer's Disease and Dementia: Epidemiological Insights, Risk Factors and Prevention Pathways

Alzheimer's disease (AD), the most common cause of dementia, is a complex and multifactorial condition without cure at present. The latest treatments, based on anti-amyloid monoclonal antibodies, have only a modest effect in reducing the progression of cognitive decline in AD, whereas the possibility of preventing AD has become a crucial area of research. In fact, recent studies have observed a decrease in dementia incidence in developed regions such as the US and Europe. However, these trends have not been mirrored in non-Western countries (Japan or China), and the contributing factors of this reduction remain unclear. The Lancet Commission has delineated a constrained classification of 12 risk factors across different life stages. Nevertheless, the scientific literature has pointed to over 200 factors-including sociodemographic, medical, psychological, and sociocultural conditions-related to the development of dementia/AD. This narrative review aims to synthesize the risk/protective factors of dementia/AD. Essentially, we found that risk/protective factors vary between individuals and populations, complicating the creation of a unified prevention strategy. Moreover, dementia/AD explanatory mechanisms involve a diverse array of genetic and environmental factors that interact from the early stages of life. In the future, studies across different population-based cohorts are essential to validate risk/protective factors of dementia. This evidence would help develop public health policies to decrease the incidence of dementia.

Factors Associated With Healthcare and Financial Decision Making Among Older Black Adults Without Dementia

OBJECTIVES

The study aims to identify factors associated with health care and financial decision-making among older Black adults without dementia.

METHODS

Participants (N = 326) underwent assessments of decision-making and completed measurements of factors from four categories: cognitive, contextual, psychosocial, and personality. We performed separate linear regression models to examine the association between each factor and decision-making and created a fully adjusted model.

RESULTS

Higher global cognition (estimate = 1.92, SE = 0.21, p < .0001) was associated with better decision-making. Contextual factors including higher current annual income (estimate = 0.23, SE = 0.05, p < .0001), higher childhood socioeconomic status (estimate = 0.48, SE = 0.18, p = .006), higher health and financial literacy (estimate = 0.08, SE = 0.01, p < .0001), and lower financial stress (estimate = -0.19, SE = 0.07, p = .01) were associated with better decision-making. More psychological well-being (estimate = 0.07, SE = 0.22, p = .001), a psychosocial factor, and less neuroticism (estimate = -0.06, SE = 0.02, p = .002), a personality factor, were associated with better decision-making. In the fully adjusted model, two factors, higher global cognition and higher literacy (health and financial), remained associated with better decision-making.

CONCLUSIONS

Cognitive and contextual factors serve as drivers of decision-making among older Black adults.

CLINICAL IMPLICATIONS

Clinicians may implement strategies to bolster cognition and improve health and financial literacy to facilitate optimal decision-making among older Black adults.

Single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of single nucleus RNA sequencing (snRNA-seq) offers to revolutionize the study of Alzheimer's disease (AD). Integration with complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link cell subpopulations and molecular networks with a broader disease-relevant context. We report snRNA-seq profiles from superior frontal gyrus samples from 101 well characterized subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in hematological parameters. We observed an AD-associated CD83(+) microglial subtype with unique molecular networks and which is associated with immunoglobulin IgG4 production in the transverse colon. Our major observations were replicated in two additional, independent snRNA-seq data sets. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal disease biology.

Cerebral arteriolosclerosis, lacunar infarcts, and cognition in older Black adults

INTRODUCTION

Older Black adults are at risk of cerebral small vessel disease (CSVD), which contributes to dementia risk. Two subtypes of CSVD, arteriolosclerosis and ischemic lacunar infarcts, have been independently linked to lower cognition and higher dementia risk, but their combined effects on cognition in older Black adults are unclear.

METHODS

Mixed models were used to examine the associations of in vivo measures of arteriolosclerosis (ARTS) and ischemic lacunar infarcts to cognitive level and change in 370 older Black adults without dementia.  RESULTS: Modeled together, higher ARTS load accounted for lower levels of global cognition, episodic memory, semantic memory, and perceptual speed, whereas higher infarct load accounted for lower levels of working memory. There were no associations with rate of cognitive change.

DISCUSSION

Both arteriolosclerosis and ischemic infarcts impact the cognitive health of older Black adults, but arteriolosclerosis affects cognition more broadly and offers promise as an in vivo biomarker of dementia risk.

HIGHLIGHTS

Older Black adults are at risk of cerebral small vessel disease (CSVD) and dementia. Examined magnetic resonance imaging-derived measure of arteriolosclerosis (ARTS), infarcts, and cognition. ARTS load was widely associated with lower cognition after adjusting for infarct load. Infarct load was specifically associated with lower complex attention. More within-Black in vivo studies of CSVD subtypes and cognition are needed.

Sense of purpose in life and extending the cognitive healthspan: evidence from multistate survival modeling

Having a sense of purpose in life predicts better maintenance of cognitive function in older adulthood and reduced risk of mild cognitive impairment (MCI) and dementia. However, little research has examined its influence on the rate of cognitive decline and length of cognitive healthspan. This study evaluated the role of sense of purpose on the risk and timing of transitions between normal cognition, MCI, and dementia. Older adults from the Memory and Aging Project (MAP; n = 1821) and the Health and Retirement Study (HRS; n = 10,542) were followed annually for 19 years and biennially for 12 years, respectively. Multistate survival models assessed whether sense of purpose predicted transitions across normal cognition, MCI, dementia, and death. More purposeful older adults had lower risk of developing MCI (HR = 0.82 in MAP; HR = 0.93 in HRS), higher likelihood of cognitive improvement, and longer cognitively healthy life expectancies. Results suggest sense of purpose may extend the cognitive healthspan.

A systems biology-based identification and in vivo 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.

Psychosocial experiences are associated with human brain mitochondrial biology

Psychosocial experiences affect brain health and aging trajectories, but the molecular pathways underlying these associations remain unclear. Normal brain function relies on energy transformation by mitochondria oxidative phosphorylation (OxPhos). Two main lines of evidence position mitochondria both as targets and drivers of psychosocial experiences. On the one hand, chronic stress exposure and mood states may alter multiple aspects of mitochondrial biology; on the other hand, functional variations in mitochondrial OxPhos capacity may alter social behavior, stress reactivity, and mood. But are psychosocial exposures and subjective experiences linked to mitochondrial biology in the human brain? By combining longitudinal antemortem assessments of psychosocial factors with postmortem brain (dorsolateral prefrontal cortex) proteomics in older adults, we find that higher well-being is linked to greater abundance of the mitochondrial OxPhos machinery, whereas higher negative mood is linked to lower OxPhos protein content. Combined, positive and negative psychosocial factors explained 18 to 25% of the variance in the abundance of OxPhos complex I, the primary biochemical entry point that energizes brain mitochondria. Moreover, interrogating mitochondrial psychobiological associations in specific neuronal and nonneuronal brain cells with single-nucleus RNA sequencing (RNA-seq) revealed strong cell-type-specific associations for positive psychosocial experiences and mitochondria in glia but opposite associations in neurons. As a result, these "mind-mitochondria" associations were masked in bulk RNA-seq, highlighting the likely underestimation of true psychobiological effect sizes in bulk brain tissues. Thus, self-reported psychosocial experiences are linked to human brain mitochondrial phenotypes.

Identifying novel proteins for suicide attempt by integrating proteomes from brain and blood with genome-wide association data

Genome-wide association studies (GWASs) have identified risk loci for suicide attempt (SA), but deciphering how they confer risk for SA remains largely unknown. This study aims to identify the key proteins and gain insights into SA pathogenesis. We integrated data from the brain proteome (N = 376) and blood proteome (N = 35,559) and combined it with the largest SA GWAS summary statistics to date (N = 518,612). A comprehensive set of methods was employed, including Mendelian randomization (MR), Steiger filtering, Bayesian colocalization, proteome‑wide association studies (PWAS), transcript-levels, cell-type specificity, correlation, and protein-protein interaction (PPI) network analysis. Validation was performed using other protein datasets and the SA dataset from FinnGen study. We identified ten proteins (GLRX5, GMPPB, B3GALTL, FUCA2, TTLL12, ADCK1, MMAA, HIBADH, ACP1, DOC2A) associated with SA in brain proteomics. GLRX5, GMPPB, and FUCA2 showed strong colocalization evidence and were supported by PWAS and transcript-level analysis, and were predominantly expressed in glutamatergic neuronal cells. In blood proteomics, one significant protein (PEAR1) and three near-significant proteins (NDE1, EVA1C, B4GALT2) were identified, but lacked colocalization evidence. Moreover, despite the limited correlation between the same protein in brain and blood, the PPI network analysis provided new insights into the interaction between brain and blood in SA. Furthermore, GLRX5 was associated with the GSTP1, the target of Clozapine. The comprehensive analysis provides strong evidence supporting a causal association between three genetically determined brain proteins (GLRX5, GMPPB, and FUCA2) with SA. These findings offer valuable insights into SA's underlying mechanisms and potential therapeutic approaches.

Associations of renin-angiotensin system inhibitor use with brain insulin signaling and neuropathology

OBJECTIVE

To examine the associations of renin-angiotensin system (RAS) inhibitor use with postmortem brain insulin signaling and neuropathology.

METHODS

Among Religious Orders Study participants, 150 deceased and autopsied older individuals (75 with diabetes matched to 75 without by age at death, sex, and education) had measurements of insulin receptor substrate-1 (IRS-1) and RAC-alpha serine/threonine protein kinase (AKT1) collected in the prefrontal cortex using ELISA and immunohistochemistry. Alzheimer's disease (AD), brain infarcts, and cerebral vessel pathology data were assessed by systematic neuropathologic evaluations. RAS inhibitor use was determined based on visual inspection of medication containers during study visits. The associations of RAS inhibitor use with brain insulin signaling measures and neuropathology were examined using adjusted regression analyses.

RESULTS

Of the 90 RAS inhibitor users (54 with diabetes), 65 had used only angiotensin-converting enzyme inhibitors, 11 only angiotensin II receptor blockers, and 14 used both. RAS inhibitor use was associated with lower pT308AKT1/total AKT1, but not with pS307IRS-1/total IRS-1 or the density of cells stained positive for pS616 IRS-1. RAS inhibitor use was not associated with the level of global AD pathology or amyloid beta burden, but it was associated with a lower tau-neurofibrillary tangle density. Additionally, we found a significant interaction between diabetes and RAS inhibitors on tangle density. Furthermore, AKT1 phosphorylation partially mediated the association of RAS inhibitor use with tau tangle density. Lastly, RAS inhibitor use was associated with more atherosclerosis, but not with other cerebral blood vessel pathologies or cerebral infarcts.

INTERPRETATION

Late-life RAS inhibitor use may be associated with lower brain AKT1 phosphorylation and fewer neurofibrillary tangles.

In vivo effect of LATE-NC on integrity of white matter connections to the hippocampus

INTRODUCTION

TAR DNA-binding protein 43 (TDP-43) is a highly prevalent proteinopathy that is involved in neurodegenerative processes, including axonal damage. To date, no ante mortem biomarkers exist for TDP-43, and few studies have directly assessed its impact on neuroimaging measures utilizing pathologic quantification.

METHODS

Ante mortem diffusion-weighted images were obtained from community-dwelling older adults. Regression models calculated the relationship between post mortem TDP-43 burden and ante mortem fractional anisotropy (FA) within each voxel in connection with the hippocampus, controlling for coexisting Alzheimer's disease and demographics.

RESULTS

Results revealed a significant negative relationship (false discovery rate [FDR] corrected p < .05) between post mortem TDP-43 and ante mortem FA in one cluster within the left medial temporal lobe connecting to the parahippocampal cortex, entorhinal cortex, and cingulate, aligning with the ventral subdivision of the cingulum. FA within this cluster was associated with cognition.

DISCUSSION

Greater TDP-43 burden is associated with lower FA within the limbic system, which may contribute to impairment in learning and memory.

HIGHLIGHTS

Post mortem TDP-43 pathological burden is associated with reduced ante mortem fractional anisotropy. Reduced FA located in the parahippocampal portion of the cingulum. FA in this area was associated with reduced episodic and semantic memory. FA in this area was associated with increased inward hippocampal surface deformation.

Correlates of missed or late versus timely diagnosis of dementia in healthcare settings

INTRODUCTION

There is limited evidence about factors related to the timeliness of dementia diagnosis in healthcare settings.

METHODS

In five prospective cohorts at Rush Alzheimer's Disease Center, we identified participants with incident dementia based on annual assessments and examined the timing of healthcare diagnoses in Medicare claims. We assessed sociodemographic, health, and psychosocial correlates of timely diagnosis.

RESULTS

Of 710 participants, 385 (or 54%) received a timely claims diagnosis within 3 years prior to or 1 year following dementia onset. In logistic regressions accounting for demographics, we found Black participants (odds ratio [OR] = 2.15, 95% confidence interval [CI]: 1.21 to 3.82) and those with better cognition at dementia onset (OR = 1.48, 95% CI: 1.10 to 1.98) were at higher odds of experiencing a diagnostic delay, whereas participants with higher income (OR = 0.89, 95% CI: 0.81 to 0.97) and more comorbidities (OR = 0.94, 95% CI: 0.89 to 0.98) had lower odds.

DISCUSSION

We identified characteristics of individuals who may miss the optimal window for dementia treatment and support.

HIGHLIGHTS

We compared the timing of healthcare diagnosis relative to the timing of incident dementia based on rigorous annual evaluation. Older Black adults with lower income, higher cognitive function, and fewer comorbidities were less likely to be diagnosed in a timely manner by the healthcare system.

Deciphering Distinct Genetic Risk Factors for FTLD-TDP Pathological Subtypes via Whole-Genome Sequencing

Frontotemporal lobar degeneration with neuronal inclusions of the TAR DNA-binding protein 43 (FTLD-TDP) is a fatal neurodegenerative disorder with only a limited number of risk loci identified. We report our comprehensive genome-wide association study as part of the International FTLD-TDP Whole-Genome Sequencing Consortium, including 985 cases and 3,153 controls, and meta-analysis with the Dementia-seq cohort, compiled from 26 institutions/brain banks in the United States, Europe and Australia. We confirm UNC13A as the strongest overall FTLD-TDP risk factor and identify TNIP1 as a novel FTLD-TDP risk factor. In subgroup analyses, we further identify for the first time genome-wide significant loci specific to each of the three main FTLD-TDP pathological subtypes (A, B and C), as well as enrichment of risk loci in distinct tissues, brain regions, and neuronal subtypes, suggesting distinct disease aetiologies in each of the subtypes. Rare variant analysis confirmed TBK1 and identified VIPR1 , RBPJL , and L3MBTL1 as novel subtype specific FTLD-TDP risk genes, further highlighting the role of innate and adaptive immunity and notch signalling pathway in FTLD-TDP, with potential diagnostic and novel therapeutic implications.

Genetic influences on brain and cognitive health and their interactions with cardiovascular conditions and depression

Approximately 40% of dementia cases could be prevented or delayed by modifiable risk factors related to lifestyle and environment. These risk factors, such as depression and vascular disease, do not affect all individuals in the same way, likely due to inter-individual differences in genetics. However, the precise nature of how genetic risk profiles interact with modifiable risk factors to affect brain health is poorly understood. Here we combine multiple data resources, including genotyping and postmortem gene expression, to map the genetic landscape of brain structure and identify 367 loci associated with cortical thickness and 13 loci associated with white matter hyperintensities (P < 5×10-8), with several loci also showing a significant association with cognitive function. We show that among 220 unique genetic loci associated with cortical thickness in our genome-wide association studies (GWAS), 95 also showed evidence of interaction with depression or cardiovascular conditions. Polygenic risk scores based on our GWAS of inferior frontal thickness also interacted with hypertension in predicting executive function in the Canadian Longitudinal Study on Aging. These findings advance our understanding of the genetic underpinning of brain structure and show that genetic risk for brain and cognitive health is in part moderated by treatable mid-life factors.

Health and Financial Literacy and the Acquisition of COVID-19 Knowledge in Older Adults

Knowledge about COVID-19 enters into many aspects of decision making, especially for older people who are at increased risk of severe disease or death. Yet little is known about the resources that supported older people's uptake of COVID-19 knowledge. Here, we hypothesized that higher pre-pandemic health and financial literacy was associated with higher COVID-19 knowledge. Participants were 434 community-based older people without dementia. COVID-19 knowledge was assessed via a 5-item measure, and health and financial literacy was assessed via a 32-item measure. In an ordinal regression model adjusted for age, gender, and education, higher literacy was associated with higher COVID-19 knowledge (p < .0001), and this association persisted after further adjusting for robust measures of global cognition or one of five specific cognitive domains (all p's ≤ .0001). These findings suggest that literacy plays a key role in supporting older people's acquisition of impactful knowledge in the real world.

Tackling neurodegeneration in vitro with omics: a path towards new targets and drugs

Drug discovery is a generally inefficient and capital-intensive process. For neurodegenerative diseases (NDDs), the development of novel therapeutics is particularly urgent considering the long list of late-stage drug candidate failures. Although our knowledge on the pathogenic mechanisms driving neurodegeneration is growing, additional efforts are required to achieve a better and ultimately complete understanding of the pathophysiological underpinnings of NDDs. Beyond the etiology of NDDs being heterogeneous and multifactorial, this process is further complicated by the fact that current experimental models only partially recapitulate the major phenotypes observed in humans. In such a scenario, multi-omic approaches have the potential to accelerate the identification of new or repurposed drugs against a multitude of the underlying mechanisms driving NDDs. One major advantage for the implementation of multi-omic approaches in the drug discovery process is that these overarching tools are able to disentangle disease states and model perturbations through the comprehensive characterization of distinct molecular layers (i.e., genome, transcriptome, proteome) up to a single-cell resolution. Because of recent advances increasing their affordability and scalability, the use of omics technologies to drive drug discovery is nascent, but rapidly expanding in the neuroscience field. Combined with increasingly advanced in vitro models, which particularly benefited from the introduction of human iPSCs, multi-omics are shaping a new paradigm in drug discovery for NDDs, from disease characterization to therapeutics prediction and experimental screening. In this review, we discuss examples, main advantages and open challenges in the use of multi-omic approaches for the in vitro discovery of targets and therapies against NDDs.

Sex, racial, and APOE-ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer's disease

INTRODUCTION

The effects of sex, race, and Apolipoprotein E (APOE) - Alzheimer's disease (AD) risk factors - on white matter integrity are not well characterized.

METHODS

Diffusion MRI data from nine well-established longitudinal cohorts of aging were free-water (FW)-corrected and harmonized. This dataset included 4,702 participants (age=73.06 ± 9.75) with 9,671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FAFWcorr) were used to assess differences in white matter microstructure by sex, race, and APOE-ε4 carrier status.

RESULTS

Sex differences in FAFWcorr in association and projection tracts, racial differences in FAFWcorr in projection tracts, and APOE-ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced.

DISCUSSION

There are prominent differences in white matter microstructure by sex, race, and APOE-ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted.

Brain and serum lipidomic profiles implicate Lands cycle acyl chain remodeling association with APOEε4 and mild cognitive impairment

Introduction

At least one-third of the identified risk alleles from Genome-Wide Association Studies (GWAS) of Alzheimer's disease (AD) are involved in lipid metabolism, lipid transport, or direct lipid binding. In fact, a common genetic variant (ε4) in a cholesterol and phospholipid transporter, Apolipoprotein E (APOEε4), is the primary genetic risk factor for late-onset AD. In addition to genetic variants, lipidomic studies have reported severe metabolic dysregulation in human autopsy brain tissue, cerebrospinal fluid, blood, and multiple mouse models of AD.

Methods

We aimed to identify an overarching metabolic pathway in lipid metabolism by integrating analyses of lipidomics and transcriptomics from the Religious Order Study and Rush Memory Aging Project (ROSMAP) using differential analysis and network correlation analysis.

Results

Coordinated differences in lipids were found to be dysregulated in association with both mild cognitive impairment (MCI) and APOEε4 carriers. Interestingly, these correlations were weakened when adjusting for education. Indeed, the cognitively non-impaired APOEε4 carriers have higher education levels in the ROSMAP cohort, suggesting that this lipid signature may be associated with a resilience phenotype. Network correlation analysis identified multiple differential lipids within a single module that are substrates and products in the Lands Cycle for acyl chain remodeling. In addition, our analyses identified multiple genes in the Lands Cycle acyl chain remodeling pathway, which were associated with cognitive decline independent of amyloid-β (Aβ) load and tau tangle pathologies.

Discussion

Our studies highlight the critical differences in acyl chain remodeling in brain tissue from APOEε4 carriers and individual non-carriers with MCI. A coordinated lipid profile shift in dorsolateral prefrontal cortex from both APOEε4 carriers and MCI suggests differences in lipid metabolism occur early in disease stage and highlights lipid homeostasis as a tractable target for early disease modifying intervention.

Knockout of the longevity gene Klotho perturbs aging and Alzheimer's disease-linked brain microRNAs and tRNA fragments

Overexpression of the longevity gene Klotho prolongs lifespan, while its knockout shortens lifespan and impairs cognition via perturbation of myelination and synapse formation. However, comprehensive analysis of Klotho knockout effects on mammalian brain transcriptomics is lacking. Here, we report that Klotho knockout alters the levels of aging- and cognition related mRNAs, long non-coding RNAs, microRNAs and tRNA fragments. These include altered neuronal and glial regulators in murine models of aging and Alzheimer's disease and in human Alzheimer's disease post-mortem brains. We further demonstrate interaction of the knockout-elevated tRNA fragments with the spliceosome, possibly affecting RNA processing. Last, we present cell type-specific short RNA-seq datasets from FACS-sorted neurons and microglia of live human brain tissue demonstrating in-depth cell-type association of Klotho knockout-perturbed microRNAs. Together, our findings reveal multiple RNA transcripts in both neurons and glia from murine and human brain that are perturbed in Klotho deficiency and are aging- and neurodegeneration-related.

Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes

BACKGROUND

Multiple sclerosis (MS) is a clinically heterogeneous disease underpinned by inflammatory, demyelinating and neurodegenerative processes, the extent of which varies between individuals and over the course of the disease. Recognising the clinicopathological features that most strongly associate with disease outcomes will inform future efforts at patient phenotyping.

AIMS

We used a digital pathology workflow, involving high-resolution image acquisition of immunostained slides and opensource software for quantification, to investigate the relationship between clinical and neuropathological features in an autopsy cohort of progressive MS.

METHODS

Sequential sections of frontal, cingulate and occipital cortex, thalamus, brain stem (pons) and cerebellum including dentate nucleus (n = 35 progressive MS, females = 28, males = 7; age died = 53.5 years; range 38-98 years) were immunostained for myelin (anti-MOG), neurons (anti-HuC/D) and microglia/macrophages (anti-HLA). The extent of demyelination, neurodegeneration, the presence of active and/or chronic active lesions and quantification of brain and leptomeningeal inflammation was captured by digital pathology.

RESULTS

Digital analysis of tissue sections revealed the variable extent of pathology that characterises progressive MS. Microglia/macrophage activation, if found at a higher level in a single block, was typically elevated across all sampled blocks. Compartmentalised (perivascular/leptomeningeal) inflammation was associated with age-related measures of disease severity and an earlier death.

CONCLUSION

Digital pathology identified prognostically important clinicopathological correlations in MS. This methodology can be used to prioritise the principal pathological processes that need to be captured by future MS biomarkers.

Leveraging sex-genetic interactions to understand brain disorders: recent advances and current gaps

It is established that there are sex differences in terms of prevalence, age of onset, clinical manifestations, and response to treatment for a variety of brain disorders, including neurodevelopmental, psychiatric, and neurodegenerative disorders. Cohorts of increasing sample sizes with diverse data types collected, including genetic, transcriptomic and/or phenotypic data, are providing the building blocks to permit analytical designs to test for sex-biased genetic variant-trait associations, and for sex-biased transcriptional regulation. Such molecular assessments can contribute to our understanding of the manifested phenotypic differences between the sexes for brain disorders, offering the future possibility of delivering personalized therapy for females and males. With the intention of raising the profile of this field as a research priority, this review aims to shed light on the importance of investigating sex-genetic interactions for brain disorders, focusing on two areas: (i) variant-trait associations and (ii) transcriptomics (i.e. gene expression, transcript usage and regulation). We specifically discuss recent advances in the field, current gaps and provide considerations for future studies.

The dichotomous activities of microglia: A potential driver for phenotypic heterogeneity in Alzheimer's disease

Alzheimer's disease (AD) is a leading cause of dementia, characterized by two defining neuropathological hallmarks: amyloid plaques composed of Aβ aggregates and neurofibrillary pathology. Recent research suggests that microglia have both beneficial and detrimental effects in the development of AD. A new theory proposes that microglia play a beneficial role in the early stages of the disease but become harmful in later stages. Further investigations are needed to gain a comprehensive understanding of this shift in microglia's function. This transition is likely influenced by specific conditions, including spatial, temporal, and transcriptional factors, which ultimately lead to the deterioration of microglial functionality. Additionally, recent studies have also highlighted the potential influence of microglia diversity on the various manifestations of AD. By deciphering the multiple states of microglia and the phenotypic heterogeneity in AD, significant progress can be made towards personalized medicine and better treatment outcomes for individuals affected by AD.

Metabolomics profiling reveals distinct, sex-specific signatures in serum and brain metabolomes in mouse models of Alzheimer's disease

INTRODUCTION

Increasing evidence suggests that metabolic impairments contribute to early Alzheimer's disease (AD) mechanisms and subsequent dementia. Signals in metabolic pathways conserved across species can facilitate translation.

METHODS

We investigated differences in serum and brain metabolites between the early-onset 5XFAD and late-onset LOAD1 (APOE4.Trem2*R47H) mouse models of AD to C57BL/6J controls at 6 months of age.

RESULTS

We identified sex differences for several classes of metabolites, such as glycerophospholipids, sphingolipids, and amino acids. Metabolic signatures were notably different between brain and serum in both mouse models. The 5XFAD mice exhibited stronger differences in brain metabolites, whereas LOAD1 mice showed more pronounced differences in serum.

DISCUSSION

Several of our findings were consistent with results in humans, showing glycerophospholipids reduction in serum of apolipoprotein E (apoE) ε4 carriers and replicating the serum metabolic imprint of the APOE ε4 genotype. Our work thus represents a significant step toward translating metabolic dysregulation from model organisms to human AD.

HIGHLIGHTS

This was a metabolomic assessment of two mouse models relevant to Alzheimer's disease. Mouse models exhibit broad sex-specific metabolic differences, similar to human study cohorts. The early-onset 5XFAD mouse model primarily alters brain metabolites while the late-onset LOAD1 model primarily changes serum metabolites. Apolipoprotein E (apoE) ε4 mice recapitulate glycerophospolipid signatures of human APOE ε4 carriers in both brain and serum.

MRI-Derived AD Signature of Cortical Thinning and Plasma P-Tau217 for Predicting Alzheimer Dementia Among Community-Dwelling Older Adults

Background and Objectives

Structural brain MRI and blood-based phosphorylated tau (p-tau) measures are among the least invasive and least expensive Alzheimer's disease (AD) biomarkers to date. The extent to which these biomarkers may outperform one another in predicting future Alzheimer dementia diagnosis is poorly understood, however. This study investigated 2 specific AD biomarkers, i.e., a cortical thickness signature of AD (AD-CT) and plasma p-tau217, for predicting Alzheimer dementia.

Methods

Data came from community-dwelling older participants of the Religious Orders Study or the Rush Memory and Aging Project. AD-CT was obtained from 3T MRI scans using a magnetization-prepared rapid acquisition gradient echo sequence and by averaging thickness from previously identified cortical regions implicated in AD. Plasma p-tau217 was quantified using an immunoassay developed by Lilly Research Laboratories on the MSD platform. Both MRI scans and blood specimens were collected at the same visits, and subsequent diagnoses of Alzheimer dementia were determined through annual detailed clinical evaluations. Cox proportional hazards models examined the associations of the 2 biomarkers with incident Alzheimer dementia, and prediction accuracy was assessed using c-statistics.

Results

A total of 198 older adults, on average 84 years of age, were included. Over a mean follow-up of 4 years, 60 (30%) individuals developed Alzheimer dementia. AD-CT (hazard ratio: 1.71, 95% CI 1.26-2.31) and separately plasma p-tau217 (hazard ratio: 2.57, 95% CI 1.83-3.61) were associated with incident Alzheimer dementia. The c-statistic for prediction accuracy was consistently higher for plasma p-tau217 (between 0.74 and 0.81) than AD-CT (between 0.70 and 0.75) across a range of time horizons. Furthermore, with both biomarkers included in the same model, there was only modest improvement in the c-statistic due to AD-CT.

Discussion

Plasma p-tau217 outperforms an imaging-based cortical thickness signature of AD in predicting future Alzheimer dementia diagnosis. Furthermore, the AD cortical thickness signature adds little to the prediction accuracy above and beyond plasma p-tau217.

Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

A roadmap to human hippocampal neurogenesis in adulthood, aging and AD

In the rodent, hippocampal neurogenesis plays critical roles in learning and memory1,2, is tightly regulated by inhibitory neurons3-7 and contributes to memory dysfunction in Alzheimer's disease (AD) mouse models8-10. In contrast, the mechanisms regulating neurogenesis in the adult human hippocampus, the dynamic shifts in the transcriptomic and epigenomic profiles in aging and AD and putative niche interactions within the cellular environment, remain largely unknown. Using single nuclei multi-omics of postmortem human hippocampi we map the molecular mechanisms of hippocampal neurogenesis across aging, cognitive decline, and AD neuropathology. Transcriptomic and epigenetic profiling of neural stem cells (NSCs), neuroblasts and immature neurons suggests that the earliest shift in the characteristics of neurogenesis takes place in NSCs in aging. Cognitive impairment was associated with changes in neuroblast profile. In AD, there was a widespread cessation of the transcription machinery in immature neurons, with robust downregulation of genes regulating ribosomal and mitochondrial function. Further, there was substantial loss of parvalbumin+ inhibitory neurons in the hippocampus in aging. The number of the rest of inhibitory neurons were reduced as a function of age and diagnosis. Notably, a similar system-level effect was observed between immature and inhibitory neurons in the transition from aging to AD, manifested by common molecular pathways that were ultimately lost in AD. The numbers of neuroblasts, immature and GABAergic neurons inversely correlated with extent of neuropathology. Using CellChat and NeuronChat, we inferred the ligands and receptors by which neurogenic cells communicate with their cellular environment. Loss of synaptic adhesion molecules and neurotransmitters, either sent or received by neurogenic cells, was observed in AD. Together, this study delineates the molecular mechanisms and dynamics of human neurogenesis, functional association with inhibitory neurons and a mechanism of hippocampal hyperexcitability in AD.