Religious Orders Study and Rush Memory and Aging Project

Spatiotemporal patterns of locus coeruleus integrity predict cortical tau and cognition

Autopsy studies indicated that the locus coeruleus (LC) accumulates hyperphosphorylated tau before allocortical regions in Alzheimer's disease. By combining in vivo longitudinal magnetic resonance imaging measures of LC integrity, tau positron emission tomography imaging and cognition with autopsy data and transcriptomic information, we examined whether LC changes precede allocortical tau deposition and whether specific genetic features underlie LC's selective vulnerability to tau. We found that LC integrity changes preceded medial temporal lobe tau accumulation, and together these processes were associated with lower cognitive performance. Common gene expression profiles between LC-medial temporal lobe-limbic regions map to biological functions in protein transport regulation. These findings advance our understanding of the spatiotemporal patterns of initial tau spreading from the LC and LC's selective vulnerability to Alzheimer's disease pathology. LC integrity measures can be a promising indicator for identifying the time window when individuals are at risk of disease progression and underscore the importance of interventions mitigating initial tau spread.

The time course of motor and cognitive decline in older adults and their associations with brain pathologies: a multicohort study

BACKGROUND

Many studies have reported that impaired gait precedes cognitive impairment in older people. We aimed to characterise the time course of cognitive and motor decline in older individuals and the association of these declines with the pathologies of Alzheimer's disease and related dementias.

METHODS

This multicohort study used data from three community-based cohort studies (Religious Orders Study, Rush Memory and Aging Project, and Minority Aging Research Study, all in the USA). The inclusion criteria for all three cohorts were no clinical dementia at the time of enrolment and consent to annual clinical assessments. Eligible participants consented to post-mortem brain donation and had post-mortem pathological assessments and three or more repeated annual measures of cognition and motor functions. Clinical and post-mortem data were analysed using functional mixed-effects models. Global cognition was based on 19 neuropsychological tests, a hand strength score was based on grip and pinch strength, and a gait score was based on the number of steps and time to walk 8 feet and turn 360°. Brain pathologies of Alzheimer's disease and related dementias were assessed at autopsy.

FINDINGS

From 1994 to 2022, there were 1570 eligible cohort participants aged 65 years or older, 1303 of whom had cognitive and motor measurements and were included in the analysis. Mean age at death was 90·3 years (SD 6·3), 905 (69%) participants were female, and 398 (31%) were male. Median follow-up time was 9 years (IQR 5-11). On average, cognition was stable from 25 to 15 years before death, when cognition began to decline. By contrast, gait function and hand strength declined during the entire study. The combinations of pathologies of Alzheimer's disease and related dementias associated with cognitive and motor decline and their onsets of associations varied; only tau tangles, Parkinson's disease pathology, and macroinfarcts were associated with decline of all three phenotypes. Tau tangles were significantly associated with cognitive decline, gait function decline, and hand function decline (p<0·0001 for each); however, the association with cognitive decline persisted for more than 11 years before death, but the association with hand strength only began 3·57 years before death and the association with gait began 3·49 years before death. By contrast, the association of macroinfarcts with declining gait function began 9·25 years before death (p<0·0001) compared with 6·65 years before death (p=0·0005) for cognitive decline and 2·66 years before death (p=0·024) for decline in hand strength.

INTERPRETATION

Our findings suggest that average motor decline in older adults precedes cognitive decline. Macroinfarcts but not tau tangles are associated with declining gait function that precedes cognitive decline. This suggests the need for further studies to test if gait impairment is a clinical proxy for preclinical vascular cognitive impairment.

FUNDING

National Institutes of Health.

regionalpcs: improved discovery of DNA methylation associations with complex traits

We have developed the regional principal components (rPCs) method, a novel approach for summarizing gene-level methylation. rPCs address the challenge of deciphering complex epigenetic mechanisms in diseases like Alzheimer's disease (AD). In contrast to traditional averaging, rPCs leverage principal components analysis to capture complex methylation patterns across gene regions. Our method demonstrated a 54% improvement in sensitivity over averaging in simulations, offering a robust framework for identifying subtle epigenetic variations. Applying rPCs to the AD brain methylation data in ROSMAP, combined with cell type deconvolution, we uncovered 838 differentially methylated genes associated with neuritic plaque burden-significantly outperforming conventional methods. Integrating methylation quantitative trait loci (meQTL) with genome-wide association studies (GWAS) identified 17 genes with potential causal roles in AD, including MS4A4A and PICALM. Our approach is available in the Bioconductor package regionalpcs, opening avenues for research and facilitating a deeper understanding of the epigenetic landscape in complex diseases.

Frailty trajectories preceding dementia: an individual-level analysis of four cohort studies in the United States and United Kingdom

Frailty may represent a modifiable risk factor for dementia, but the direction of that association remains uncertain. We investigated frailty trajectories in the years preceding dementia onset using data from 23,672 participants (242,760 person-years of follow-up, 2,906 cases of incident dementia) across four cohort studies in the United States and United Kingdom. Bayesian non-linear models revealed accelerations in frailty trajectories 4-9 years before incident dementia. Among participants whose time between frailty measurement and incident dementia exceeded that prodromal period, frailty remained positively associated with dementia risk (adjusted hazard ratios ranged from 1.20 [95% confidence interval, CI = 1.15-1.26] to 1.43 [95% CI = 1.14-1.81]). This observational evidence suggests that frailty increases dementia risk independently of any reverse causality. These findings indicate that frailty measurements can be used to identify high-risk population groups for preferential enrolment into clinical trials for dementia prevention and treatment. Frailty itself may represent a useful upstream target for behavioural and societal approaches to dementia prevention.

CWAS-Plus: Estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional data

Variants in cis-regulatory elements link the noncoding genome to human brain pathology; however, detailed analytic tools for understanding the association between cell-level brain pathology and noncoding variants are lacking. CWAS-Plus, adapted from a Python package for category-wide association testing (CWAS) employs both whole-genome sequencing and user-provided functional data to enhance noncoding variant analysis, with a faster and more efficient execution of the CWAS workflow. Here, we used single-nuclei assay for transposase-accessible chromatin with sequencing to facilitate CWAS-guided noncoding variant analysis at cell-type specific enhancers and promoters. Examining autism spectrum disorder whole-genome sequencing data (n = 7,280), CWAS-Plus identified noncoding de novo variant associations in transcription factor binding sites within conserved loci. Independently, in Alzheimer's disease whole-genome sequencing data (n = 1,087), CWAS-Plus detected rare noncoding variant associations in microglia-specific regulatory elements. These findings highlight CWAS-Plus's utility in genomic disorders and scalability for processing large-scale whole-genome sequencing data and in multiple-testing corrections. CWAS-Plus and its user manual are available at https://github.com/joonan-lab/cwas/ and https://cwas-plus.readthedocs.io/en/latest/, respectively.

Characterizing quantile-varying covariate effects under the accelerated failure time model

An important task in survival analysis is choosing a structure for the relationship between covariates of interest and the time-to-event outcome. For example, the accelerated failure time (AFT) model structures each covariate effect as a constant multiplicative shift in the outcome distribution across all survival quantiles. Though parsimonious, this structure cannot detect or capture effects that differ across quantiles of the distribution, a limitation that is analogous to only permitting proportional hazards in the Cox model. To address this, we propose a general framework for quantile-varying multiplicative effects under the AFT model. Specifically, we embed flexible regression structures within the AFT model and derive a novel formula for interpretable effects on the quantile scale. A regression standardization scheme based on the g-formula is proposed to enable the estimation of both covariate-conditional and marginal effects for an exposure of interest. We implement a user-friendly Bayesian approach for the estimation and quantification of uncertainty while accounting for left truncation and complex censoring. We emphasize the intuitive interpretation of this model through numerical and graphical tools and illustrate its performance through simulation and application to a study of Alzheimer's disease and dementia.

An integrated toolkit for human microglia functional genomics

BACKGROUND

Microglia, the brain's resident immune cells, play vital roles in brain development, and disorders like Alzheimer's disease (AD). Human iPSC-derived microglia (iMG) provide a promising model to study these processes. However, existing iMG generation protocols face challenges, such as prolonged differentiation time, lack of detailed characterization, and limited gene function investigation via CRISPR-Cas9.

METHODS

Our integrated toolkit for in-vitro microglia functional genomics optimizes iPSC differentiation into iMG through a streamlined two-step, 20-day process, producing iMG with a normal karyotype. We confirmed the iMG's authenticity and quality through single-cell RNA sequencing, chromatin accessibility profiles (ATAC-Seq), proteomics and functional tests. The toolkit also incorporates a drug-dependent CRISPR-ON/OFF system for temporally controlled gene expression. Further, we facilitate the use of multi-omic data by providing online searchable platform that compares new iMG profiles to human primary microglia: https://sherlab.shinyapps.io/IPSC-derived-Microglia/ .

RESULTS

Our method generates iMG that closely align with human primary microglia in terms of transcriptomic, proteomic, and chromatin accessibility profiles. Functionally, these iMG exhibit Ca2 + transients, cytokine driven migration, immune responses to inflammatory signals, and active phagocytosis of CNS related substrates including synaptosomes, amyloid beta and myelin. Significantly, the toolkit facilitates repeated iMG harvesting, essential for large-scale experiments like CRISPR-Cas9 screens. The standalone ATAC-Seq profiles of our iMG closely resemble primary microglia, positioning them as ideal tools to study AD-associated single nucleotide variants (SNV) especially in the genome regulatory regions.

CONCLUSIONS

Our advanced two-step protocol rapidly and efficiently produces authentic iMG. With features like the CRISPR-ON/OFF system and a comprehensive multi-omic data platform, our toolkit equips researchers for robust microglial functional genomic studies. By facilitating detailed SNV investigation and offering a sustainable cell harvest mechanism, the toolkit heralds significant progress in neurodegenerative disease drug research and therapeutic advancement.

Association of Age-Related Neuropathologic Findings at Autopsy With a Claims-Based Epilepsy Diagnosis in Older Adults

BACKGROUND AND OBJECTIVES

Epilepsy is 1 of the 3 most common neurologic diseases of older adults, but few studies have examined its underlying pathologies in older age. We examined the associations of age-related brain pathologies with epilepsy in older persons.

METHODS

Clinical and pathologic data came from 2 ongoing clinical pathologic cohort studies of community-dwelling older adults. Epilepsy was ascertained using Medicare fee-for-service Parts A and B claims data that were linked to data from the cohort studies. The postmortem pathologic assessment collected indices of 9 pathologies including Alzheimer disease, hippocampal sclerosis, macroinfarcts, and cerebral amyloid angiopathy. The fixed brain hemisphere was imaged using 3T MRI scanners before the pathologic assessments in a subgroup of participants.

RESULTS

The participants (n = 1,369) were on average 89.3 (6.6) years at death, and 67.0% were women. Epilepsy was identified in 58 (4.2%) participants. Cerebral amyloid angiopathy (odds ratio [OR] = 2.21, 95% CI 1.24-3.95, p = 0.007) and cortical macroinfarcts (OR = 2.74, 95% CI 1.42-5.28, p = 0.003) were associated with a higher odds of epilepsy. Of note, hippocampal sclerosis and Alzheimer disease pathology were not associated with epilepsy (both p's > 0.25), although hippocampal sclerosis was not common and thus hard to examine with the modest number of epilepsy cases here. In 673 participants with MRI data, the association of cerebral amyloid angiopathy and cortical macroinfarcts with epilepsy did not change after controlling for cortical gray matter atrophy, which was independently associated with a higher odds of epilepsy (OR = 1.06, 95% CI 1.02-1.10, p = 0.003). By contrast, hippocampal volume was not associated with epilepsy.

DISCUSSION

Cerebrovascular pathologies and cortical atrophy were associated with epilepsy in older persons.

Glycoproteome-Wide Discovery of Cortical Glycoproteins That May Provide Cognitive Resilience in Older Adults

BACKGROUND AND OBJECTIVES

Molecular omics studies have identified proteins related to cognitive resilience but unrelated to Alzheimer disease and Alzheimer disease-related dementia (AD/ADRD) pathologies. Posttranslational modifications of proteins with glycans can modify protein function. In this study, we identified glycopeptiforms associated with cognitive resilience.

METHODS

We studied brains from adults with annual cognitive testing with postmortem indices of 10 AD/ADRD pathologies and proteome-wide data from dorsal lateral prefrontal cortex (DLPFC). We quantified 11, 012 glycopeptiforms from DLPFC using liquid chromatography with tandem mass spectrometry. We used linear mixed-effects models to identify glycopeptiforms associated with cognitive decline correcting for multiple comparisons (p < 5 × 10-6). Then, we regressed out the effect of AD/ADRD pathologies to identify glycopeptiforms that may provide cognitive resilience.

RESULTS

We studied 366 brains, average age at death 89 years, and 70% female with no cognitive impairment = 152, mild cognitive impairment = 93, and AD = 121 cognitive status at death. In models adjusting for age, sex and education, 11 glycopeptiforms were associated with cognitive decline. In further modeling, 8 of these glycopeptiforms remained associated with cognitive decline after adjusting for AD/ADRD pathologies: NPTX2a (Est., 0.030, SE, 0.005, p = 1 × 10-4); NPTX2b (Est.,0.019, SE, 0.005, p = 2 × 10-4) NECTIN1(Est., 0.029, SE, 0.009, p = 9 × 10-4), NPTX2c (Est., 0.015, SE, 0.004, p = 9 × 10-4), HSPB1 (Est., -0.021, SE, 0.006, p = 2 × 10-4), PLTP (Est., -0.027, SE, 0.009, p = 4.2 × 10-3), NAGK (Est., -0.027, SE, 0.008, p = 1.4 × 10-3), and VAT1 (Est., -0.020, SE, 0.006, p = 1.1 × 10-3). Higher levels of 4 resilience glycopeptiforms derived through glycosylation were associated with slower decline and higher levels of 4 derived through glycation were related to faster decline. Together, these 8 glycopeptiforms accounted for an additional 6% of cognitive decline over the 33% accounted for the 10 brain pathologies and demographics. All 8 resilience glycopeptiforms remained associated with cognitive decline after adjustments for the expression level of their corresponding protein. Exploratory gene ontology suggested that molecular mechanisms of glycopeptiforms associated with cognitive decline may involve metabolic pathways including pyruvate and NADH pathways and highlighted the importance of molecular mechanisms involved in glucose metabolism.

DISCUSSION

Glycopeptiforms in aging brains may provide cognitive resilience. Targeting these glycopeptiforms may lead to therapies that maintain cognition through resilience.

The concept of resilience to Alzheimer's Disease: current definitions and cellular and molecular mechanisms

Some individuals are able to maintain their cognitive abilities despite the presence of significant Alzheimer's Disease (AD) neuropathological changes. This discrepancy between cognition and pathology has been labeled as resilience and has evolved into a widely debated concept. External factors such as cognitive stimulation are associated with resilience to AD, but the exact cellular and molecular underpinnings are not completely understood. In this review, we discuss the current definitions used in the field, highlight the translational approaches used to investigate resilience to AD and summarize the underlying cellular and molecular substrates of resilience that have been derived from human and animal studies, which have received more and more attention in the last few years. From these studies the picture emerges that resilient individuals are different from AD patients in terms of specific pathological species and their cellular reaction to AD pathology, which possibly helps to maintain cognition up to a certain tipping point. Studying these rare resilient individuals can be of great importance as it could pave the way to novel therapeutic avenues for AD.

lute: estimating the cell composition of heterogeneous tissue with varying cell sizes using gene expression

Relative cell type fraction estimates in bulk RNA-sequencing data are important to control for cell composition differences across heterogenous tissue samples. Current computational tools estimate relative RNA abundances rather than cell type proportions in tissues with varying cell sizes, leading to biased estimates. We present lute, a computational tool to accurately deconvolute cell types with varying sizes. Our software wraps existing deconvolution algorithms in a standardized framework. Using simulated and real datasets, we demonstrate how lute adjusts for differences in cell sizes to improve the accuracy of cell composition. Software is available from https://bioconductor.org/packages/lute.

Associations of Serum Insulin and Related Measures With Neuropathology and Cognition in Older Persons With and Without Diabetes

OBJECTIVE

To examine associations of serum insulin and related measures with neuropathology and cognition in older persons.

METHODS

We studied 192 older persons (96 with diabetes and 96 without, matched by sex and balanced by age-at-death, education, and postmortem interval) from a community-based, clinical-pathologic study of aging, with annual evaluations including neuropsychological testing (summarized into global cognition and 5 cognitive domains) and postmortem autopsy. We assessed serum insulin, glucose, leptin, adiponectin, hemoglobin A1C, advanced glycation-end products (AGEs), and receptors for advanced glycation-end products, and calculated the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) and adiponectin-to-leptin ratio. Using adjusted regression analyses, we examined the associations of serum measures with neuropathology of cerebrovascular disease and Alzheimer's disease, and with the level of cognition proximate-to-death.

RESULTS

Higher HOMA-IR was associated with the presence of brain infarcts and specifically microinfarcts, and higher HOMA-IR and leptin were each associated with subcortical infarcts. Further, higher leptin levels and lower adiponectin-to-leptin ratios were associated with the presence of moderate-to-severe atherosclerosis. Serum insulin and related measures were not associated with the level of Alzheimer's disease pathology, as assessed by global, as well as amyloid burden or tau tangle density scores. Regarding cognitive outcomes, higher insulin and leptin levels, and lower adiponectin and receptors for advanced glycation-end products levels, respectively, were each associated with lower levels of global cognition.

INTERPRETATION

Peripheral insulin resistance indicated by HOMA-IR and related serum measures was associated with a greater burden of cerebrovascular neuropathology and lower cognition. ANN NEUROL 2024;95:665-676.

Native-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer's pathology

Dysfunction in fast-spiking parvalbumin interneurons (PV-INs) may represent an early pathophysiological perturbation in Alzheimer's Disease (AD). Defining early proteomic alterations in PV-INs can provide key biological and translationally-relevant insights. We used cell-type-specific in-vivo biotinylation of proteins (CIBOP) coupled with mass spectrometry to obtain native-state PV-IN proteomes. PV-IN proteomic signatures include high metabolic and translational activity, with over-representation of AD-risk and cognitive resilience-related proteins. In bulk proteomes, PV-IN proteins were associated with cognitive decline in humans, and with progressive neuropathology in humans and the 5xFAD mouse model of Aβ pathology. PV-IN CIBOP in early stages of Aβ pathology revealed signatures of increased mitochondria and metabolism, synaptic and cytoskeletal disruption and decreased mTOR signaling, not apparent in whole-brain proteomes. Furthermore, we demonstrated pre-synaptic defects in PV-to-excitatory neurotransmission, validating our proteomic findings. Overall, in this study we present native-state proteomes of PV-INs, revealing molecular insights into their unique roles in cognitive resiliency and AD pathogenesis.

Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients

INTRODUCTION

White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status.

METHODS

Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume.

RESULTS

VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001).

DISCUSSION

Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter.

HIGHLIGHTS

Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts. Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.

Genetic associations with dementia-related proteinopathy: Application of item response theory

INTRODUCTION

Although dementia-related proteinopathy has a strong negative impact on public health, and is highly heritable, understanding of the related genetic architecture is incomplete.

METHODS

We applied multidimensional generalized partial credit modeling (GPCM) to test genetic associations with dementia-related proteinopathies. Data were analyzed to identify candidate single nucleotide variants for the following proteinopathies: Aβ, tau, α-synuclein, and TDP-43.

RESULTS

Final included data comprised 966 participants with neuropathologic and WGS data. Three continuous latent outcomes were constructed, corresponding to TDP-43-, Aβ/Tau-, and α-synuclein-related neuropathology endophenotype scores. This approach helped validate known genotype/phenotype associations: for example, TMEM106B and GRN were risk alleles for TDP-43 pathology; and GBA for α-synuclein/Lewy bodies. Novel suggestive proteinopathy-linked alleles were also discovered, including several (SDHAF1, TMEM68, and ARHGEF28) with colocalization analyses and/or high degrees of biologic credibility.

DISCUSSION

A novel methodology using GPCM enabled insights into gene candidates for driving misfolded proteinopathies.

HIGHLIGHTS

Latent factor scores for proteinopathies were estimated using a generalized partial credit model. The three latent continuous scores corresponded well with proteinopathy severity. Novel genes associated with proteinopathies were identified. Several genes had high degrees of biologic credibility for dementia risk factors.

Cell subtype-specific effects of genetic variation in the Alzheimer's disease brain

The relationship between genetic variation and gene expression in brain cell types and subtypes remains understudied. Here, we generated single-nucleus RNA sequencing data from the neocortex of 424 individuals of advanced age; we assessed the effect of genetic variants on RNA expression in cis (cis-expression quantitative trait loci) for seven cell types and 64 cell subtypes using 1.5 million transcriptomes. This effort identified 10,004 eGenes at the cell type level and 8,099 eGenes at the cell subtype level. Many eGenes are only detected within cell subtypes. A new variant influences APOE expression only in microglia and is associated with greater cerebral amyloid angiopathy but not Alzheimer's disease pathology, after adjusting for APOEε4, providing mechanistic insights into both pathologies. Furthermore, only a TMEM106B variant affects the proportion of cell subtypes. Integration of these results with genome-wide association studies highlighted the targeted cell type and probable causal gene within Alzheimer's disease, schizophrenia, educational attainment and Parkinson's disease loci.

Personalized Protein-Protein Interaction Networks Towards Unraveling the Molecular Mechanisms of Alzheimer's Disease

Alzheimer's disease (AD) is a highly heterogenous neurodegenerative disease, and several omic-based datasets were generated in the last decade from the patients with the disease. However, the vast majority of studies evaluate these datasets in bulk by considering all the patients as a single group, which obscures the molecular differences resulting from the heterogeneous nature of the disease. In this study, we adopted a personalized approach and analyzed the transcriptome data from 403 patients individually by mapping the data on a human protein-protein interaction network. Patient-specific subnetworks were discovered and analyzed in terms of the genes in the subnetworks, enriched functional terms, and known AD genes. We identified several affected pathways that could not be captured by the bulk comparison. We also showed that our personalized findings point to patterns of alterations consistent with the recently suggested AD subtypes.

Early-life participation in cognitively stimulating activities and risk of depression and anxiety in late life

BACKGROUND

Early-life stressful experiences are associated with increased risk of adverse psychological outcomes in later life. However, much less is known about associations between early-life positive experiences, such as participation in cognitively stimulating activities, and late-life mental health. We investigated whether greater engagement in cognitively stimulating activities in early life is associated with lower risk of depression and anxiety in late life.

METHODS

We surveyed former participants of the St. Louis Baby Tooth study, between 22 June 2021 and 25 March 2022 to collect information on participants' current depression/anxiety symptoms and their early-life activities (N = 2187 responded). A composite activity score was created to represent the early-life activity level by averaging the frequency of self-reported participation in common cognitively stimulating activities in participants' early life (age 6, 12, 18), each rated on a 1 (least frequent) to 5 (most frequent) point scale. Depression/anxiety symptoms were measured by Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder Screener (GAD-7). We used logistic regressions to estimate odds ratios (OR) and 95% confidence intervals (CI) of outcome risk associated with frequency of early-life activity.

RESULTS

Each one-point increase in the early-life composite cognitive activity score was associated with an OR of 0.54 (95% CI 0.38-0.77) for late-life depression and an OR of 0.94 (95% CI 0.61-1.43) for late-life anxiety, adjusting for age, sex, race, parental education, childhood family structure, and socioeconomic status.

CONCLUSIONS

More frequent participation in cognitively stimulating activities during early life was associated with reduced risk of late-life depression.

Single-cell genomics and regulatory networks for 388 human brains

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Single-nucleus RNA velocity reveals critical synaptic and cell-cycle dysregulations in neuropathologically confirmed Alzheimer's disease

Typical differential single-nucleus gene expression (snRNA-seq) analyses in Alzheimer's disease (AD) provide fixed snapshots of cellular alterations, making the accurate detection of temporal cell changes challenging. To characterize the dynamic cellular and transcriptomic differences in AD neuropathology, we apply the novel concept of RNA velocity to the study of single-nucleus RNA from the cortex of 60 subjects with varied levels of AD pathology. RNA velocity captures the rate of change of gene expression by comparing intronic and exonic sequence counts. We performed differential analyses to find the significant genes driving both cell type-specific RNA velocity and expression differences in AD, extensively compared these two transcriptomic metrics, and clarified their associations with multiple neuropathologic traits. The results were cross-validated in an independent dataset. Comparison of AD pathology-associated RNA velocity with parallel gene expression differences reveals sets of genes and molecular pathways that underlie the dynamic and static regimes of cell type-specific dysregulations underlying the disease. Differential RNA velocity and its linked progressive neuropathology point to significant dysregulations in synaptic organization and cell development across cell types. Notably, most of the genes underlying this synaptic dysregulation showed increased RNA velocity in AD subjects compared to controls. Accelerated cell changes were also observed in the AD subjects, suggesting that the precocious depletion of precursor cell pools might be associated with neurodegeneration. Overall, this study uncovers active molecular drivers of the spatiotemporal alterations in AD and offers novel insights towards gene- and cell-centric therapeutic strategies accounting for dynamic cell perturbations and synaptic disruptions.

Interrogation of the human cortical peptidome uncovers cell-type specific signatures of cognitive resilience against Alzheimer's disease

Alzheimer's disease (AD) is characterised by age-related cognitive decline. Brain accumulation of amyloid-β plaques and tau tangles is required for a neuropathological AD diagnosis, yet up to one-third of AD-pathology positive community-dwelling elderly adults experience no symptoms of cognitive decline during life. Conversely, some exhibit chronic cognitive impairment in absence of measurable neuropathology, prompting interest into cognitive resilience-retained cognition despite significant neuropathology-and cognitive frailty-impaired cognition despite low neuropathology. Synapse loss is widespread within the AD-dementia, but not AD-resilient, brain. Recent evidence points towards critical roles for synaptic proteins, such as neurosecretory VGF, in cognitive resilience. However, VGF and related proteins often signal as peptide derivatives. Here, nontryptic peptidomic mass spectrometry was performed on 102 post-mortem cortical samples from individuals across cognitive and neuropathological spectra. Neuropeptide signalling proteoforms derived from VGF, somatostatin (SST) and protachykinin-1 (TAC1) showed higher abundance in AD-resilient than AD-dementia brain, whereas signalling proteoforms of cholecystokinin (CCK) and chromogranin (CHG) A/B and multiple cytoskeletal molecules were enriched in frail vs control brain. Integrating our data with publicly available single nuclear RNA sequencing (snRNA-seq) showed enrichment of cognition-related genes in defined cell-types with established links to cognitive resilience, including SST interneurons and excitatory intratelencephalic cells.

Polygenic risk associated with Alzheimer's disease and other traits influences genes involved in T cell signaling and activation

Introduction

T cells, known for their ability to respond to an enormous variety of pathogens and other insults, are increasingly recognized as important mediators of pathology in neurodegeneration and other diseases. T cell gene expression phenotypes can be regulated by disease-associated genetic variants. Many complex diseases are better represented by polygenic risk than by individual variants.

Methods

We first compute a polygenic risk score (PRS) for Alzheimer's disease (AD) using genomic sequencing data from a cohort of Alzheimer's disease (AD) patients and age-matched controls, and validate the AD PRS against clinical metrics in our cohort. We then calculate the PRS for several autoimmune disease, neurological disorder, and immune function traits, and correlate these PRSs with T cell gene expression data from our cohort. We compare PRS-associated genes across traits and four T cell subtypes.

Results

Several genes and biological pathways associated with the PRS for these traits relate to key T cell functions. The PRS-associated gene signature generally correlates positively for traits within a particular category (autoimmune disease, neurological disease, immune function) with the exception of stroke. The trait-associated gene expression signature for autoimmune disease traits was polarized towards CD4+ T cell subtypes.

Discussion

Our findings show that polygenic risk for complex disease and immune function traits can have varying effects on T cell gene expression trends. Several PRS-associated genes are potential candidates for therapeutic modulation in T cells, and could be tested in in vitro applications using cells from patients bearing high or low polygenic risk for AD or other conditions.

A systems-biology approach connects aging mechanisms with Alzheimer's disease pathogenesis

Age is the strongest risk factor for developing Alzheimer's disease, the most common neurodegenerative disorder. However, the mechanisms connecting advancing age to neurodegeneration in Alzheimer's disease are incompletely understood. We conducted an unbiased, genome-scale, forward genetic screen for age-associated neurodegeneration in Drosophila to identify the underlying biological processes required for maintenance of aging neurons. To connect genetic screen hits to Alzheimer's disease pathways, we measured proteomics, phosphoproteomics, and metabolomics in Drosophila models of Alzheimer's disease. We further identified Alzheimer's disease human genetic variants that modify expression in disease-vulnerable neurons. Through multi-omic, multi-species network integration of these data, we identified relationships between screen hits and tau-mediated neurotoxicity. Furthermore, we computationally and experimentally identified relationships between screen hits and DNA damage in Drosophila and human iPSC-derived neural progenitor cells. Our work identifies candidate pathways that could be targeted to attenuate the effects of age on neurodegeneration and Alzheimer's disease.

Automated Gait Detection in Older Adults during Daily-Living using Self-Supervised Learning of Wrist-Worn Accelerometer Data: Development and Validation of ElderNet

Progressive gait impairment is common in aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Here, we developed ElderNet, a self-supervised learning model for gait detection from wrist-worn accelerometer data. Validation involved two diverse cohorts, including over 1,000 participants without gait labels, as well as 83 participants with labeled data: older adults with Parkinson's disease, proximal femoral fracture, chronic obstructive pulmonary disease, congestive heart failure, and healthy adults. ElderNet presented high accuracy (96.43 ± 2.27), specificity (98.87 ± 2.15), recall (82.32 ± 11.37), precision (86.69 ± 17.61), and F1 score (82.92 ± 13.39). The suggested method yielded superior performance compared to two state-of-the-art gait detection algorithms, with improved accuracy and F1 score (p < 0.05). In an initial evaluation of construct validity, ElderNet identified differences in estimated daily walking durations across cohorts with different clinical characteristics, such as mobility disability (p < 0.001) and parkinsonism (p < 0.001). The proposed self-supervised gait detection method has the potential to serve as a valuable tool for remote phenotyping of gait function during daily living in aging adults.

Interrogation of endothelial and mural cells in brain metastasis reveals key immune-regulatory mechanisms

Brain metastasis (BrM) is a common malignancy, predominantly originating from lung, melanoma, and breast cancers. The vasculature is a key component of the BrM tumor microenvironment with critical roles in regulating metastatic seeding and progression. However, the heterogeneity of the major BrM vascular components, namely endothelial and mural cells, is still poorly understood. We perform single-cell and bulk RNA-sequencing of sorted vascular cell types and detect multiple subtypes enriched specifically in BrM compared to non-tumor brain, including previously unrecognized immune regulatory subtypes. We integrate the human data with mouse models, creating a platform to interrogate vascular targets for the treatment of BrM. We find that the CD276 immune checkpoint molecule is significantly upregulated in the BrM vasculature, and anti-CD276 blocking antibodies prolonged survival in preclinical trials. This study provides important insights into the complex interactions between the vasculature, immune cells, and cancer cells, with translational relevance for designing therapeutic interventions.

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/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 new insights into disease mechanisms.

Micro-RNA profiles of pathology and resilience in posterior cingulate cortex of cognitively intact elders

The posterior cingulate cortex (PCC) is a key hub of the default mode network underlying autobiographical memory retrieval, which falters early in the progression of Alzheimer's disease (AD). We recently performed RNA sequencing of post-mortem PCC tissue samples from 26 elderly Rush Religious Orders Study participants who came to autopsy with an ante-mortem diagnosis of no cognitive impairment but who collectively displayed a range of Braak I-IV neurofibrillary tangle stages. Notably, cognitively unimpaired subjects displaying high Braak stages may represent cognitive resilience to AD pathology. Transcriptomic data revealed elevated synaptic and ATP-related gene expression in Braak Stages III/IV compared with Stages I/II, suggesting these pathways may be related to PCC resilience. We also mined expression profiles for small non-coding micro-RNAs (miRNAs), which regulate mRNA stability and may represent an underexplored potential mechanism of resilience through the fine-tuning of gene expression within complex cellular networks. Twelve miRNAs were identified as differentially expressed between Braak Stages I/II and III/IV. However, the extent to which the levels of all identified miRNAs were associated with subject demographics, neuropsychological test performance and/or neuropathological diagnostic criteria within this cohort was not explored. Here, we report that a total of 667 miRNAs are significantly associated (rho > 0.38, P < 0.05) with subject variables. There were significant positive correlations between miRNA expression levels and age, perceptual orientation and perceptual speed. By contrast, higher miRNA levels correlated negatively with semantic and episodic memory. Higher expression of 15 miRNAs associated with lower Braak Stages I-II and 47 miRNAs were associated with higher Braak Stages III-IV, suggesting additional mechanistic influences of PCC miRNA expression with resilience. Pathway analysis showed enrichment for miRNAs operating in pathways related to lysine degradation and fatty acid synthesis and metabolism. Finally, we demonstrated that the 12 resilience-related miRNAs differentially expressed in Braak Stages I/II versus Braak Stages III/IV were predicted to regulate mRNAs related to amyloid processing, tau and inflammation. In summary, we demonstrate a dynamic state wherein differential PCC miRNA levels are associated with cognitive performance and post-mortem neuropathological AD diagnostic criteria in cognitively intact elders. We posit these relationships may inform miRNA transcriptional alterations within the PCC relevant to potential early protective (resilience) or pathogenic (pre-clinical or prodromal) responses to disease pathogenesis and thus may be therapeutic targets.

APOE genotype-specific methylation patterns are linked to Alzheimer disease pathology and estrogen response

The joint effects of APOE genotype and DNA methylation on Alzheimer disease (AD) risk is relatively unknown. We conducted genome-wide methylation analyses using 2,021 samples in blood (91 AD cases, 329 mild cognitive impairment, 1,391 controls) and 697 samples in brain (417 AD cases, 280 controls). We identified differentially methylated levels in AD compared to controls in an APOE genotype-specific manner at 25 cytosine-phosphate-guanine (CpG) sites in brain and 36 CpG sites in blood. Additionally, we identified seven CpG sites in the APOE region containing TOMM40, APOE, and APOC1 genes with P < 5 × 10-8 between APOE ε4 carriers and non-carriers in brain or blood. In brain, the most significant CpG site hypomethylated in ε4 carriers compared to non-carriers was from the TOMM40 in the total sample, while most of the evidence was derived from AD cases. However, the CpG site was not significantly modulating expression of these three genes in brain. Three CpG sites from the APOE were hypermethylated in APOE ε4 carriers in brain or blood compared in ε4 non-carriers and nominally significant with APOE expression in brain. Three CpG sites from the APOC1 were hypermethylated in blood, which one of the 3 CpG sites significantly lowered APOC1 expression in blood using all subjects or ε4 non-carriers. Co-methylation network analysis in blood and brain detected eight methylation networks associated with AD and APOE ε4 status. Five of the eight networks included genes containing network CpGs that were significantly enriched for estradiol perturbation, where four of the five networks were enriched for the estrogen response pathway. Our findings provide further evidence of the role of APOE genotype on methylation levels associated with AD, especially linked to estrogen response pathway.

Integrative brain omics approach reveals key role for sn-1 lysophosphatidylethanolamine in Alzheimer's dementia

The biology of individual lipid species and their relevance in Alzheimer's disease (AD) remains incompletely understood. We utilized non-targeted mass spectrometry to examine brain lipids variations across 316 post-mortem brains from participants in the Religious Orders Study (ROS) or Rush Memory and Aging Project (MAP) cohorts classified as either control, asymptomatic AD (AAD), or symptomatic AD (SAD) and integrated the lipidomics data with untargeted proteomic characterization on the same individuals. Lipid enrichment analysis and analysis of variance identified significantly lower abundance of lysophosphatidylethanolamine (LPE) and lysophosphatidylcholine (LPC) species in SAD than controls or AAD. Lipid-protein co-expression network analyses revealed that lipid modules consisting of LPE and LPC exhibited a significant association to protein modules associated with MAPK/metabolism, post-synaptic density, and Cell-ECM interaction pathways and were associated with better antemortem cognition and with neuropathological changes seen in AD. Particularly, LPE 22:6 [sn-1] levels are significantly decreased across AD cases (SAD) and show the most influence on protein changes compared to other lysophospholipid species. LPE 22:6 may be a lipid signature for AD and could be leveraged as potential therapeutic or dietary targets for AD.

Chronic traumatic encephalopathy and aging-related tau astrogliopathy in community-dwelling older persons with and without moderate-to-severe traumatic brain injury

This study examined the frequency of chronic traumatic encephalopathy-neuropathologic change (CTE-NC) and aging-related tau astrogliopathy (ARTAG) in community-dwelling older adults and tested the hypothesis that these tau pathologies are associated with a history of moderate-to-severe traumatic brain injury (msTBI), defined as a TBI with loss of consciousness >30 minutes. We evaluated CTE-NC, ARTAG, and Alzheimer disease pathologies in 94 participants with msTBI and 94 participants without TBI matched by age, sex, education, and dementia status TBI from the Rush community-based cohorts. Six (3%) of brains showed the pathognomonic lesion of CTE-NC; only 3 of these had a history of msTBI. In contrast, ARTAG was common in older brains (gray matter ARTAG = 77%; white matter ARTAG = 54%; subpial ARTAG = 51%); there were no differences in severity, type, or distribution of ARTAG pathology with respect to history of msTBI. Furthermore, those with msTBI did not have higher levels of PHF-tau tangles density but had higher levels of amyloid-β load (Estimate = 0.339, SE = 0.164, p = 0.040). These findings suggest that CTE-NC is infrequent while ARTAG is common in the community and that both pathologies are unrelated to msTBI. The association of msTBI with amyloid-β, rather than with tauopathies suggests differential mechanisms of neurodegeneration in msTBI.

The LRRK2 kinase substrates RAB8a and RAB10 contribute complementary but distinct disease-relevant phenotypes in human neurons

Mutations in the LRRK2 gene cause familial Parkinson's disease presenting with pleomorphic neuropathology that can involve α-synuclein or tau accumulation. LRRK2 mutations are thought to converge upon a pathogenic increase in LRRK2 kinase activity. A subset of small RAB GTPases has been identified as LRRK2 substrates, with LRRK2-dependent phosphorylation resulting in RAB inactivation. We used CRISPR-Cas9 genome editing to generate a novel series of isogenic iPSC lines deficient in the two most well-validated LRRK2 substrates, RAB8a and RAB10, from deeply phenotyped healthy control lines. Thorough characterization of NGN2-induced neurons revealed opposing effects of RAB8a and RAB10 deficiency on lysosomal pH and Golgi organization, with isolated effects of RAB8a and RAB10 ablation on α-synuclein and tau, respectively. Our data demonstrate largely antagonistic effects of genetic RAB8a or RAB10 inactivation, which provide discrete insight into the pathologic features of their biochemical inactivation by pathogenic LRRK2 mutation in human disease.

CHRNA5 links chandelier cells to severity of amyloid pathology in aging and Alzheimer's disease

Changes in high-affinity nicotinic acetylcholine receptors are intricately connected to neuropathology in Alzheimer's Disease (AD). Protective and cognitive-enhancing roles for the nicotinic α5 subunit have been identified, but this gene has not been closely examined in the context of human aging and dementia. Therefore, we investigate the nicotinic α5 gene CHRNA5 and the impact of relevant single nucleotide polymorphisms (SNPs) in prefrontal cortex from 922 individuals with matched genotypic and post-mortem RNA sequencing in the Religious Orders Study and Memory and Aging Project (ROS/MAP). We find that a genotype robustly linked to increased expression of CHRNA5 (rs1979905A2) predicts significantly reduced cortical β-amyloid load. Intriguingly, co-expression analysis suggests CHRNA5 has a distinct cellular expression profile compared to other nicotinic receptor genes. Consistent with this prediction, single nucleus RNA sequencing from 22 individuals reveals CHRNA5 expression is disproportionately elevated in chandelier neurons, a distinct subtype of inhibitory neuron known for its role in excitatory/inhibitory (E/I) balance. We show that chandelier neurons are enriched in amyloid-binding proteins compared to basket cells, the other major subtype of PVALB-positive interneurons. Consistent with the hypothesis that nicotinic receptors in chandelier cells normally protect against β-amyloid, cell-type proportion analysis from 549 individuals reveals these neurons show amyloid-associated vulnerability only in individuals with impaired function/trafficking of nicotinic α5-containing receptors due to homozygosity of the missense CHRNA5 SNP (rs16969968A2). Taken together, these findings suggest that CHRNA5 and its nicotinic α5 subunit exert a neuroprotective role in aging and Alzheimer's disease centered on chandelier interneurons.

Atherosclerosis and Hippocampal Volumes in Older Adults: The Role of Age and Blood Pressure

BACKGROUND

Lower hippocampal volume is associated with late-life cognitive decline and is an important, but nonspecific marker for clinical Alzheimer's dementia. Cerebrovascular disease may also be associated with hippocampal volume. Here we study the role of intracranial large vessel disease (atherosclerosis) in association with hippocampal volume and the potential role of age, average late-life blood pressure across all visits, and other factors (sex, apolipoprotein ε4 [APOE ε4], and diabetes).

METHODS AND RESULTS

Data came from 765 community-based older people (91 years old on average at death; 72% women), from 2 ongoing clinical-pathologic cohort studies. Participants completed baseline assessment, annual standardized blood pressure measurements, vascular risk assessment for diabetes, and blood draws to determine APOE genotype, and at death, brains were removed and underwent ex vivo magnetic resonance imaging and neuropathologic evaluation for atherosclerosis pathology and other cerebrovascular and neurodegenerative pathologies. Linear regression models examined the association of atherosclerosis and hippocampal to hemisphere volume ratio and whether age at death, blood pressure, and other factors modified associations. In linear regression models adjusted for demographics and neurodegenerative and other cerebrovascular pathologies, atherosclerosis severity was associated with a lower hippocampal to hemisphere volume ratio. In separate models, we found the effect of atherosclerosis on the ratio of hippocampal to hemisphere volume was attenuated among advanced age at death or having higher systolic blood pressure (interaction terms P≤0.03). We did not find confounding or interactions with sex, diabetes, or APOE ε4.

CONCLUSIONS

Atherosclerosis severity is associated with lower hippocampal volume, independent of neurodegenerative and other cerebrovascular pathologies. Higher systolic blood pressures and advanced age attenuate associations.

Characterization of brain resilience in Alzheimer's disease using polygenic risk scores and further improvement by integrating mitochondria-associated loci

INTRODUCTION

Identification of high-risk people for Alzheimer's disease (AD) is critical for prognosis and early management. Longitudinal epidemiologic studies have observed heterogeneity in the brain and cognitive aging. Brain resilience was described as above-expected cognitive function. The "resilience" framework has been shown to correlate with individual characteristics such as genetic factors and age. Besides, accumulative evidence has confirmed the association of mitochondria with the pathogenesis of AD. However, it is challenging to assess resilience through genetic metrics, in particular incorporating mitochondria-associated loci.

OBJECTIVES

In this paper, we first demonstrated that polygenic risk scores (PRS) could characterize individuals' resilience levels. Then, we indicated that mitochondria-associated loci could improve the performance of PRSs, providing more reliable measurements for the prevention and diagnosis of AD.

METHODS

The discovery (N = 1,550) and independent validation samples (N = 2,090) were used to construct nine types of PRSs containing mitochondria-related loci (PRSMT) from both biological and statistical aspects and combined them with known AD risk loci derived from genome-wide association studies (GWAS).Individuals' levels of brain resilience were comprehensively measured by linear regression models using eight pathological characteristics.

RESULTS

It was found that PRSs could characterize brain resilience levels (e.g., Pearson correlation test Pmin = 7.96×10-9). Moreover, the performance of PRS models could be efficiently improved by incorporating a small number of mitochondria-related loci (e.g., Pearson correlation test P improved from 1.41×10-3 to 6.09×10-6). PRSs' ability to characterize brain resilience was validated. More importantly, by incorporating some mitochondria-related loci, the performance of PRSs in measuring brain resilience could be significantly improved.

CONCLUSION

Our findings imply that mitochondria may play an important role in brain resilience, and targeting mitochondria may open a new door to AD prevention and therapy.

Whole genome methylation sequencing in blood identifies extensive differential DNA methylation in late-onset dementia due to Alzheimer's disease

INTRODUCTION

DNA microarray-based studies report differentially methylated positions (DMPs) in blood between late-onset dementia due to Alzheimer's disease (AD) and cognitively unimpaired individuals, but interrogate < 4% of the genome.

METHODS

We used whole genome methylation sequencing (WGMS) to quantify DNA methylation levels at 25,409,826 CpG loci in 281 blood samples from 108 AD and 173 cognitively unimpaired individuals.

RESULTS

WGMS identified 28,038 DMPs throughout the human methylome, including 2707 differentially methylated genes (e.g., SORCS3, GABA, and PICALM) encoding proteins in biological pathways relevant to AD such as synaptic membrane, cation channel complex, and glutamatergic synapse. One hundred seventy-three differentially methylated blood-specific enhancers interact with the promoters of 95 genes that are differentially expressed in blood from persons with and without AD.

DISCUSSION

WGMS identifies differentially methylated CpGs in known and newly detected genes and enhancers in blood from persons with and without AD.

HIGHLIGHTS

Whole genome DNA methylation levels were quantified in blood from persons with and without Alzheimer's disease (AD). Twenty-eight thousand thirty-eight differentially methylated positions (DMPs) were identified. Two thousand seven hundred seven genes comprise DMPs. Forty-eight of 75 independent genetic risk loci for AD have DMPs. One thousand five hundred sixty-eight blood-specific enhancers comprise DMPs, 173 of which interact with the promoters of 95 genes that are differentially expressed in blood from persons with and without AD.

Transcriptome-Wide Association Studies (TWAS): Methodologies, Applications, and Challenges

Transcriptome-wide association study (TWAS) methodologies aim to identify genetic effects on phenotypes through the mediation of gene transcription. In TWAS, in silico models of gene expression are trained as functions of genetic variants and then applied to genome-wide association study (GWAS) data. This post-GWAS analysis identifies gene-trait associations with high interpretability, enabling follow-up functional genomics studies and the development of genetics-anchored resources. We provide an overview of commonly used TWAS approaches, their advantages and limitations, and some widely used applications. © 2024 Wiley Periodicals LLC.

Untangling a taxonomy of living from the science of the continuum of life

Medical innovation and technologic advances enrich daily living and occur within our normative worlds, that are socially constructed. These advances confront society with critical questions about the nature of human life, laying bare the inadequacies of extant norms and boundaries. Yet, society has been unable to develop consensus about when life ends. Scientific studies highlight that life is best characterized by continua without natural boundaries. Thus, scientific information alone cannot be employed to justify the socially constructed health categories required for setting norms and boundaries. An iterative process that integrates a broad range of non-scientific data with advancing scientific information is needed to facilitate consensus for updating social norms and boundaries. This can lead to a new taxonomy of living across the measurable continuum of life and align our normative worlds with the dizzying pace of medical innovation and advances in technologies transforming the world in which we live.

Identification of novel proteins for sleep apnea by integrating genome-wide association data and human brain proteomes

BACKGROUND

Sleep apnea is regarded as a significant global public health issue. The relationship between sleep apnea and nervous system diseases is intricate, yet the precise mechanism remains unclear.

METHODS

In this study, we conducted a comprehensive analysis integrating the human brain proteome and transcriptome with sleep apnea genome-wide association study (GWAS), employing genome-wide association study (PWAS), transcriptome-wide association study (TWAS), Mendelian randomization (MR), and colocalization analysis to identify brain proteins associated with sleep apnea.

RESULTS

The discovery PWAS identified six genes (CNNM2, XRCC6, C3orf18, CSDC2, SQRDL, and DGUOK) whose altered protein abundances in the brain were found to be associated with sleep apnea. The independent confirmatory PWAS successfully replicated four out of these six genes (CNNM2, C3orf18, CSDC2, and SQRDL). The transcriptome level TWAS analysis further confirmed two out of the four genes (C3orf18 and CSDC2). The subsequent two-sample Mendelian randomization provided compelling causal evidence supporting the association of C3orf18, CSDC2, CNNM2, and SQRDL with sleep apnea. The co-localization analysis further supported the association between CSDC2 and sleep apnea (posterior probability of hypothesis 4 = 0.75).

CONCLUSIONS

In summary, the integration of brain proteomic and transcriptomic data provided multifaceted evidence supporting causal relationships between four specific brain proteins (CSDC2, C3orf18, CNNM2, and SQRDL) and sleep apnea. Our findings provide new insights into the molecular basis of sleep apnea in the brain, promising to advance understanding of its pathogenesis in future research.

A prospective study of the association of cognitive and motor function with odds of life space constriction in older adults

BACKGROUND

Many studies indicate that smaller life space is related to worse cognitive and motor function. It is plausible that cognitive and motor function also predict life space constriction, thus long-term, prospective studies are needed of cognitive and motor function as predictors of life space.

METHODS

A total of 1246 participants of the Rush Memory and Aging Project, who reported initial maximal life space and at least one follow-up assessment were included in this prospective study, with up to 19 years follow-up. The outcome of interest was the Modified version of the Life Space Questionnaire; which we categorized into large (beyond community), medium (neighborhood/community), and small (home/yard) life space. Participants also had detailed composite measures of global cognition and motor function as predictors and available at the first life space assessment. Life space transitions over one-year periods were modeled using multistate Markov modeling, including confounders and both predictors simultaneously.

RESULTS

Better cognitive and motor function were broadly associated with lower odds of life space constriction (Cognitive: Large ➔ medium: OR = 0.91, 95% CI 0.83-1.00; Large ➔ small: OR = 0.85, 95% CI 0.74-0.97; Medium ➔ small: OR = 1.01, 95% CI 0.82-1.22. Motor: large ➔ medium: OR = 0.76, 95% CI 0.69-0.83; large ➔ small: OR = 0.58, 95% CI 0.51-0.67; medium ➔ small: OR = 0.71, 95% CI = 0.57-0.87).

CONCLUSIONS

Combined with previous literature that life space predicts function, these results support the notion of complex inter-relations of cognitive function, motor function, and life space.

Estimating cell-type-specific gene co-expression networks from bulk gene expression data with an application to Alzheimer's disease

Inferring and characterizing gene co-expression networks has led to important insights on the molecular mechanisms of complex diseases. Most co-expression analyses to date have been performed on gene expression data collected from bulk tissues with different cell type compositions across samples. As a result, the co-expression estimates only offer an aggregated view of the underlying gene regulations and can be confounded by heterogeneity in cell type compositions, failing to reveal gene coordination that may be distinct across different cell types. In this paper, we introduce a flexible framework for estimating cell-type-specific gene co-expression networks from bulk sample data, without making specific assumptions on the distributions of gene expression profiles in different cell types. We develop a novel sparse least squares estimator, referred to as CSNet, that is efficient to implement and has good theoretical properties. Using CSNet, we analyzed the bulk gene expression data from a cohort study on Alzheimer's disease and identified previously unknown cell-type-specific co-expressions among Alzheimer's disease risk genes, suggesting cell-type-specific disease mechanisms.

Alzheimer's disease transcriptional landscape in ex-vivo human microglia

Microglia are resident immune cells of the brain and are implicated in the etiology of Alzheimer's Disease (AD) and other diseases. Yet the cellular and molecular processes regulating their function throughout the course of the disease are poorly understood. Here, we present the transcriptional landscape of primary microglia from 189 human postmortem brains, including 58 healthy aging individuals and 131 with a range of disease phenotypes, including 63 patients representing the full spectrum of clinical and pathological severity of AD. We identified transcriptional changes associated with multiple AD phenotypes, capturing the severity of dementia and neuropathological lesions. Transcript-level analyses identified additional genes with heterogeneous isoform usage and AD phenotypes. We identified changes in gene-gene coordination in AD, dysregulation of co-expression modules, and disease subtypes with distinct gene expression. Taken together, these data further our understanding of the key role of microglia in AD biology and nominate candidates for therapeutic intervention.

Navigating the Frontiers of Machine Learning in Neurodegenerative Disease Therapeutics

Recent advances in machine learning hold tremendous potential for enhancing the way we develop new medicines. Over the years, machine learning has been adopted in nearly all facets of drug discovery, including patient stratification, lead discovery, biomarker development, and clinical trial design. In this review, we will discuss the latest developments linking machine learning and CNS drug discovery. While machine learning has aided our understanding of chronic diseases like Alzheimer's disease and Parkinson's disease, only modest effective therapies currently exist. We highlight promising new efforts led by academia and emerging biotech companies to leverage machine learning for exploring new therapies. These approaches aim to not only accelerate drug development but to improve the detection and treatment of neurodegenerative diseases.

Individual bioenergetic capacity as a potential source of resilience to Alzheimer's disease

Impaired glucose uptake in the brain is one of the earliest presymptomatic manifestations of Alzheimer's disease (AD). The absence of symptoms for extended periods of time suggests that compensatory metabolic mechanisms can provide resilience. Here, we introduce the concept of a systemic 'bioenergetic capacity' as the innate ability to maintain energy homeostasis under pathological conditions, potentially serving as such a compensatory mechanism. We argue that fasting blood acylcarnitine profiles provide an approximate peripheral measure for this capacity that mirrors bioenergetic dysregulation in the brain. Using unsupervised subgroup identification, we show that fasting serum acylcarnitine profiles of participants from the AD Neuroimaging Initiative yields bioenergetically distinct subgroups with significant differences in AD biomarker profiles and cognitive function. To assess the potential clinical relevance of this finding, we examined factors that may offer diagnostic and therapeutic opportunities. First, we identified a genotype affecting the bioenergetic capacity which was linked to succinylcarnitine metabolism and significantly modulated the rate of future cognitive decline. Second, a potentially modifiable influence of beta-oxidation efficiency seemed to decelerate bioenergetic aging and disease progression. Our findings, which are supported by data from more than 9,000 individuals, suggest that interventions tailored to enhance energetic health and to slow bioenergetic aging could mitigate the risk of symptomatic AD, especially in individuals with specific mitochondrial genotypes.

Inferring Alzheimer's disease pathologic traits from clinical measures in living adults

Background

Alzheimer's disease neuropathologic changes (AD-NC) are important for identify people with high risk for AD dementia (ADD) and subtyping ADD.

Objective

Develop imputation models based on clinical measures to infer AD-NC.

Methods

We used penalized generalized linear regression to train imputation models for four AD-NC traits (amyloid-β, tangles, global AD pathology, and pathologic AD) in Rush Memory and Aging Project decedents, using clinical measures at the last visit prior to death as predictors. We validated these models by inferring AD-NC traits with clinical measures at the last visit prior to death for independent Religious Orders Study (ROS) decedents. We inferred baseline AD-NC traits for all ROS participants at study entry, and then tested if inferred AD-NC traits at study entry predicted incident ADD and postmortem pathologic AD.

Results

Inferred AD-NC traits at the last visit prior to death were related to postmortem measures with R2=(0.188,0.316,0.262) respectively for amyloid-β, tangles, and global AD pathology, and prediction Area Under the receiver operating characteristic Curve (AUC) 0.765 for pathologic AD. Inferred baseline levels of all four AD-NC traits predicted ADD. The strongest prediction was obtained by the inferred baseline probabilities of pathologic AD with AUC=(0.919,0.896) for predicting the development of ADD in 3 and 5 years from baseline. The inferred baseline levels of all four AD-NC traits significantly discriminated pathologic AD profiled eight years later with p-values<1.4 × 10-10.

Conclusion

Inferred AD-NC traits based on clinical measures may provide effective AD biomarkers that can estimate the burden of AD-NC traits in aging adults.

ZCCHC17 Modulates Neuronal RNA Splicing and Supports Cognitive Resilience in Alzheimer's Disease

ZCCHC17 is a putative master regulator of synaptic gene dysfunction in Alzheimer's disease (AD), and ZCCHC17 protein declines early in AD brain tissue, before significant gliosis or neuronal loss. Here, we investigate the function of ZCCHC17 and its role in AD pathogenesis using data from human autopsy tissue (consisting of males and females) and female human cell lines. Co-immunoprecipitation (co-IP) of ZCCHC17 followed by mass spectrometry analysis in human iPSC-derived neurons reveals that ZCCHC17's binding partners are enriched for RNA-splicing proteins. ZCCHC17 knockdown results in widespread RNA-splicing changes that significantly overlap with splicing changes found in AD brain tissue, with synaptic genes commonly affected. ZCCHC17 expression correlates with cognitive resilience in AD patients, and we uncover an APOE4-dependent negative correlation of ZCCHC17 expression with tangle burden. Furthermore, a majority of ZCCHC17 interactors also co-IP with known tau interactors, and we find a significant overlap between alternatively spliced genes in ZCCHC17 knockdown and tau overexpression neurons. These results demonstrate ZCCHC17's role in neuronal RNA processing and its interaction with pathology and cognitive resilience in AD, and suggest that the maintenance of ZCCHC17 function may be a therapeutic strategy for preserving cognitive function in the setting of AD pathology.

Joint analysis of proteome, transcriptome, and multi-trait analysis to identify novel Parkinson's disease risk genes

Genome-wide association studies (GWAS) have identified multiple risk variants for Parkinson's disease (PD). Nevertheless, how the risk variants confer the risk of PD remains largely unknown. We conducted a proteome-wide association study (PWAS) and summary-data-based mendelian randomization (SMR) analysis by integrating PD GWAS with proteome and protein quantitative trait loci (pQTL) data from human brain, plasma and CSF. We also performed a large transcriptome-wide association study (TWAS) and Fine-mapping of causal gene sets (FOCUS), leveraging joint-tissue imputation (JTI) prediction models of 22 tissues to identify and prioritize putatively causal genes. We further conducted PWAS, SMR, TWAS, and FOCUS using a multi-trait analysis of GWAS (MTAG) to identify additional PD risk genes to boost statistical power. In this large-scale study, we identified 16 genes whose genetically regulated protein abundance levels were associated with Parkinson's disease risk. We undertook a large-scale analysis of PD and correlated traits, through TWAS and FOCUS studies, and discovered 26 casual genes related to PD that had not been reported in previous TWAS. 5 genes (CD38, GPNMB, RAB29, TMEM175, TTC19) showed significant associations with PD at both the proteome-wide and transcriptome-wide levels. Our study provides new insights into the etiology and underlying genetic architecture of PD.

From theory to practice: translating the concept of cognitive resilience to novel therapeutic targets that maintain cognition in aging adults

While the concept of cognitive resilience is well-established it has not been defined in a way that can be measured. This has been an impediment to studying its underlying biology and to developing instruments for its clinical assessment. This perspective highlights recent work that has quantified the expression of cortical proteins associated with cognitive resilience, thus facilitating studies of its complex underlying biology and the full range of its clinical effects in aging adults. These initial studies provide empirical support for the conceptualization of resilience as a continuum. Like other conventional risk factors, some individuals manifest higher-than-average cognitive resilience and other individuals manifest lower-than-average cognitive resilience. These novel approaches for advancing studies of cognitive resilience can be generalized to other aging phenotypes and can set the stage for the development of clinical tools that might have the potential to measure other mechanisms of resilience in aging adults. These advances also have the potential to catalyze a complementary therapeutic approach that focuses on augmenting resilience via lifestyle changes or therapies targeting its underlying molecular mechanisms to maintain cognition and brain health even in the presence of untreatable stressors like brain pathologies that accumulate in aging adults.

Proteome-wide Analyses Identified Cortical Proteins Associated With Resilience for Varied Cognitive Abilities

BACKGROUND AND OBJECTIVES

Prior work suggests that cognitive resilience may contribute to the heterogeneity of cognitive decline. This study examined whether distinct cortical proteins provide resilience for different cognitive abilities.

METHODS

Participants were from the Religious Orders Study or the Rush Memory and Aging Project who had undergone annual assessments of 5 cognitive abilities and postmortem assessment of 9 Alzheimer disease and related dementia (ADRD) pathologies. Proteome-wide examination of the dorsolateral prefrontal cortex using tandem mass tag and liquid chromatography-mass spectrometry yielded 8,425 high-abundance proteins. We applied linear mixed-effect models to quantify residual cognitive change (cognitive resilience) of 5 cognitive abilities by regressing out cognitive decline related to age, sex, education, and indices of ADRD pathologies. Then we added terms for each of the individual proteins to identify cognitive resilience proteins associated with the different cognitive abilities.

RESULTS

We included 604 decedents (69% female; mean age at death = 89 years) with proteomic data. A total of 47 cortical proteins that provide cognitive resilience were identified: 22 were associated with specific cognitive abilities, and 25 were common to at least 2 cognitive abilities. NRN1 was the only protein that was associated with more than 2 cognitive abilities (semantic memory: estimate = 0.020, SE = 0.004, p = 2.2 × 10-6; episodic memory: estimate = 0.029, SE = 0.004, p = 5.8 × 10-1; and working memory: estimate = 0.021, SE = 0.004, p = 1.2 × 10-7). Exploratory gene ontology analysis suggested that among top molecular pathways, mitochondrial translation was a molecular mechanism providing resilience in episodic memory, while nuclear-transcribed messenger RNA catabolic processes provided resilience in working memory.

DISCUSSION

This study identified cortical proteins associated with various cognitive abilities. Differential associations across abilities may reflect distinct underlying biological pathways. These data provide potential high-value targets for further mechanistic and drug discovery studies to develop targeted treatments to prevent loss of cognition.

Sensitivity and Specificity of the Boston Criteria Version 2.0 for the Diagnosis of Cerebral Amyloid Angiopathy in a Community-Based Sample

BACKGROUND AND OBJECTIVES

The Boston criteria are a set of clinical and neuroimaging features that enable accurate diagnosis of cerebral amyloid angiopathy (CAA) without invasive methods such as brain biopsies or autopsy. The last updates to the Boston criteria, named version 2.0, were recently released and incorporated new nonhemorrhagic MRI features. These criteria have been validated in symptomatic samples, with improved diagnostic yield. We set out to investigate the accuracy of the Boston criteria v2.0 for the diagnosis of CAA in a community-based sample.

METHODS

Participants were recruited from longitudinal clinical-pathologic studies of aging conducted at the Rush Alzheimer's Disease Center in Chicago: the Religious Orders Study and the Rush Memory and Aging Project. Deceased participants with in vivo 3T MRI and detailed pathologic data available were included in the analysis. We compared the diagnostic yield of the current and earlier versions of the Boston criteria in our sample. Among those classified as probable CAA according to the Boston criteria v2.0, we investigated the ability of each neuroimaging marker to distinguish between false-positive and true-positive cases.

RESULTS

In total, 134 individuals were included in the study (mean age = 82.4 ± 6.0 years; 69.4% F), and 49 of them were considered pathology-proven definite cases with CAA (mean age = 82.9 ± 6.0 years; 63.3% F). The Boston criteria versions 1.0 and 1.5 yielded similar sensitivity (26.5%, both), specificity (90.6% and 89.4%, respectively), and predictive values (negative: 68.1% and 67.9%; positive: 61.9% and 59.1%, respectively). The recently released Boston criteria v2.0 offered higher sensitivity (38.8%) and slightly lower specificity (83.5%). Among those classified as probable CAA (v2.0), pathology-proven true-positive cases had higher numbers of strictly cortical lobar microbleeds compared with false-positive cases (p = 0.004).

DISCUSSION

Similar to findings from symptomatic samples, the inclusion of nonhemorrhagic neuroimaging markers in the updated Boston criteria offered a 12.3% gain in sensitivity among community-dwelling individuals, at the expense of a 5.9% drop in specificity. In cases with probable CAA, the cortical location of microbleeds may represent a promising distinguishing feature between true-positive and false-positive cases. Despite its improved performance, the diagnostic sensitivity of the updated criteria in a community-based sample remains limited.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that the Boston criteria v2.0 accurately distinguishes people with CAA from those without CAA.

Identification of female-enriched and disease-associated microglia (FDAMic) contributes to sexual dimorphism in late-onset Alzheimer's disease

BACKGROUND

Late-onset Alzheimer's disease (LOAD) is the most common form of dementia; it disproportionally affects women in terms of both incidence rates and severity of progression. The cellular and molecular mechanisms underlying this clinical phenomenon remain elusive and ill-defined.

METHODS

In-depth analyses were performed with multiple human LOAD single-nucleus transcriptome datasets to thoroughly characterize cell populations in the cerebral cortex. ROSMAP bulk human brain tissue transcriptome and DNA methylome datasets were also included for validation. Detailed assessments of microglial cell subpopulations and their relevance to sex-biased changes at the tissue level were performed. Clinical trait associations, cell evolutionary trajectories, and transcription regulon analyses were conducted.

RESULTS

The relative numbers of functionally defective microglia were aberrantly increased uniquely among affected females. Substratification of the microglia into different subtypes according to their transcriptomic signatures identified a group of female-enriched and disease-associated microglia (FDAMic), the numbers of which were positively associated with disease severity. Phenotypically, these cells exhibit transcriptomic signatures that support active proliferation, MHC class II autoantigen presentation and amyloid-β binding, but they are also likely defective in phagocytosis. FDAMic are likely evolved from female activated response microglia (ARMic) with an APOE4 background and compromised estrogen receptor (ER) signaling that is deemed to be active among most subtypes of microglia.

CONCLUSION

This study offered important insights at both the cellular and molecular levels into how ER signaling affects microglial heterogeneity and function. FDAMic are associated with more advanced pathologies and severe trends of cognitive decline. Their emergence could, at least in part, explain the phenomenon of greater penetrance of the APOE4 genotype found in females. The biases of FDAMic emergence toward female sex and APOE4 status may also explain why hormone replacement therapy is more effective in APOE4 carriers. The pathologic nature of FDAMic suggests that selective modulations of these cells may help to regain brain neuroimmune homeostasis, serving as a new target for future drug development.