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.

Perivascular space burden interacts with APOE-ε4 status on cognition in older adults

Enlarged perivascular spaces (ePVS) may adversely affect cognition. Little is known about how basal ganglia ePVS interact with apolipoprotein (APOE)-ε4 status. Vanderbilt Memory and Aging Project participants (n = 326, 73 ± 7, 59% male) underwent 3 T brain MRI at baseline to assess ePVS and longitudinal neuropsychological assessments. The interaction between ePVS volume and APOE-ε4 carrier status was related to baseline outcomes using ordinary least squares regressions and longitudinal cognition using linear mixed-effects regressions. ePVS volume interacted with APOE-ε4 status on cross-sectional naming performance (β = -0.002, p = 0.002), and executive function excluding outliers (β = 0.001, p = 0.009). There were no significant longitudinal interactions (p-values>0.10) except for Coding excluding outliers (β = 0.002, p = 0.05). While cross-sectional models stratified by APOE-ε4 status indicated greater ePVS related to worse cognition mostly in APOE-ε4 carriers, longitudinal models stratified by APOE-ε4 status showed greater ePVS volume related to worse cognition among APOE-ε4 non-carriers only. Results indicated that greater ePVS volume interacts with APOE-ε4 status on cognition cross-sectionally. Longitudinally, the association of greater ePVS volume and worse cognition appears stronger in APOE-ε4 non-carriers, possibly due to the deleterious effects of APOE-ε4 on cognition across the lifespan.

Frontal and anterior temporal hypometabolism post chemoradiation in head and neck cancer: A real-world PET study

BACKGROUND AND PURPOSE

Adverse neurological effects after cancer therapy are common, but biomarkers to diagnose, monitor, or risk stratify patients are still not validated or used clinically. An accessible imaging method, such as fluorodeoxyglucose positron emission tomography (FDG PET) of the brain, could meet this gap and serve as a biomarker for functional brain changes. We utilized FDG PET to evaluate which brain regions are most susceptible to altered glucose metabolism after chemoradiation in patients with head and neck cancer (HNCa).

METHODS

Real-world FDG PET images were acquired as standard of care before and after chemoradiation for HNCa in 68 patients. Linear mixed-effects voxelwise models assessed changes after chemoradiation in cerebral glucose metabolism quantified with standardized uptake value ratio (SUVR), covarying for follow-up time and patient demographics.

RESULTS

Voxelwise analysis revealed two large clusters of decreased glucose metabolism in the medial frontal and polar temporal cortices following chemoradiation, with decreases of approximately 5% SUVR after therapy.

CONCLUSIONS

These findings provide evidence that standard chemoradiation for HNCa can lead to decreased neuronal glucose metabolism, contributing to literature emphasizing the vulnerability of the frontal and anterior temporal lobes, especially in HNCa, where these areas may be particularly vulnerable to indirect radiation-induced injury. FDG PET shows promise as a sensitive biomarker for assessing these changes.

Empirical assessment of the assumptions of ComBat with diffusion tensor imaging

Purpose

Diffusion tensor imaging (DTI) is a magnetic resonance imaging technique that provides unique information about white matter microstructure in the brain but is susceptible to confounding effects introduced by scanner or acquisition differences. ComBat is a leading approach for addressing these site biases. However, despite its frequent use for harmonization, ComBat's robustness toward site dissimilarities and overall cohort size have not yet been evaluated in terms of DTI.

Approach

As a baseline, we match N = 358 participants from two sites to create a "silver standard" that simulates a cohort for multi-site harmonization. Across sites, we harmonize mean fractional anisotropy and mean diffusivity, calculated using participant DTI data, for the regions of interest defined by the JHU EVE-Type III atlas. We bootstrap 10 iterations at 19 levels of total sample size, 10 levels of sample size imbalance between sites, and 6 levels of mean age difference between sites to quantify (i) β AGE , the linear regression coefficient of the relationship between FA and age; (ii) γ ^ s f * , the ComBat-estimated site-shift; and (iii) δ ^ s f * , the ComBat-estimated site-scaling. We characterize the reliability of ComBat by evaluating the root mean squared error in these three metrics and examine if there is a correlation between the reliability of ComBat and a violation of assumptions.

Results

ComBat remains well behaved for β AGE when N > 162 and when the mean age difference is less than 4 years. The assumptions of the ComBat model regarding the normality of residual distributions are not violated as the model becomes unstable.

Conclusion

Prior to harmonization of DTI data with ComBat, the input cohort should be examined for size and covariate distributions of each site. Direct assessment of residual distributions is less informative on stability than bootstrap analysis. We caution use ComBat of in situations that do not conform to the above thresholds.

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.

Plasma VEGFA and PGF impact longitudinal tau and cognition in preclinical Alzheimer's disease

Vascular dysfunction is increasingly recognized as an important contributor to the pathogenesis of Alzheimer's disease. Alterations in vascular endothelial growth factor (VEGF) pathways have been implicated as potential mechanisms. However, the specific impact of VEGF proteins in preclinical Alzheimer's disease and their relationships with other Alzheimer's disease and vascular pathologies during this critical early period remain to be elucidated. We included 317 older adults from the Harvard Aging Brain Study, a cohort of individuals who were cognitively unimpaired at baseline and followed longitudinally for up to 12 years. Baseline VEGF family protein levels (VEGFA, VEGFC, VEGFD, PGF, and FLT1) were measured in fasting plasma using high-sensitivity immunoassays. Using linear mixed effects models, we examined the interactive effects of baseline plasma VEGF proteins and amyloid PET burden (Pittsburgh Compound-B) on longitudinal cognition (Preclinical Alzheimer Cognitive Composite-5). We further investigated if effects on cognition were mediated by early neocortical tau accumulation (Flortaucipir PET burden in the inferior temporal cortex) or hippocampal atrophy. Lastly, we examined the impact of adjusting for baseline cardiovascular risk score or white matter hyperintensity volume. Baseline plasma VEGFA and PGF each showed a significant interaction with amyloid burden on prospective cognitive decline. Specifically, low VEGFA and high PGF were associated with greater cognitive decline in individuals with elevated amyloid, i.e. those on the Alzheimer's disease continuum. Concordantly, low VEGFA and high PGF were associated with accelerated longitudinal tau accumulation in those with elevated amyloid. Moderated mediation analyses confirmed that accelerated tau accumulation fully mediated the effects of low VEGFA and partially mediated (31%) the effects of high PGF on faster amyloid-related cognitive decline. The effects of VEGFA and PGF on tau and cognition remained significant after adjusting for cardiovascular risk score or white matter hyperintensity volume. There were concordant but non-significant associations with longitudinal hippocampal atrophy. Together, our findings implicate low VEGFA and high PGF in accelerating early neocortical tau pathology and cognitive decline in preclinical Alzheimer's disease. Additionally, our results underscore the potential of these minimally-invasive plasma biomarkers to inform the risk of Alzheimer's disease progression in the preclinical population. Importantly, VEGFA and PGF appear to capture distinct effects from vascular risks and cerebrovascular injury. This highlights their potential as new therapeutic targets, in combination with anti-amyloid and traditional vascular risk reduction therapies, to slow the trajectory of preclinical Alzheimer's disease and delay or prevent the onset of cognitive decline.

Sex-specific genetic architecture of late-life memory performance

BACKGROUND

Women demonstrate a memory advantage when cognitively healthy yet lose this advantage to men in Alzheimer's disease. However, the genetic underpinnings of this sex difference in memory performance remain unclear.

METHODS

We conducted the largest sex-aware genetic study on late-life memory to date (Nmales  = 11,942; Nfemales  = 15,641). Leveraging harmonized memory composite scores from four cohorts of cognitive aging and AD, we performed sex-stratified and sex-interaction genome-wide association studies in 24,216 non-Hispanic White and 3367 non-Hispanic Black participants.

RESULTS

We identified three sex-specific loci (rs67099044-CBLN2, rs719070-SCHIP1/IQCJ-SCHIP), including an X-chromosome locus (rs5935633-EGL6/TCEANC/OFD1), that associated with memory. Additionally, we identified heparan sulfate signaling as a sex-specific pathway and found sex-specific genetic correlations between memory and cardiovascular, immune, and education traits.

DISCUSSION

This study showed memory is highly and comparably heritable across sexes, as well as highlighted novel sex-specific genes, pathways, and genetic correlations that related to late-life memory.

HIGHLIGHTS

Demonstrated the heritable component of late-life memory is similar across sexes. Identified two genetic loci with a sex-interaction with baseline memory. Identified an X-chromosome locus associated with memory decline in females. Highlighted sex-specific candidate genes and pathways associated with memory. Revealed sex-specific shared genetic architecture between memory and complex traits.

Longitudinal change in memory performance as a strong endophenotype for Alzheimer's disease

INTRODUCTION

Although large-scale genome-wide association studies (GWAS) have been conducted on AD, few have been conducted on continuous measures of memory performance and memory decline.

METHODS

We conducted a cross-ancestry GWAS on memory performance (in 27,633 participants) and memory decline (in 22,365 participants; 129,201 observations) by leveraging harmonized cognitive data from four aging cohorts.

RESULTS

We found high heritability for two ancestry backgrounds. Further, we found a novel ancestry locus for memory decline on chromosome 4 (rs6848524) and three loci in the non-Hispanic Black ancestry group for memory performance on chromosomes 2 (rs111471504), 7 (rs4142249), and 15 (rs74381744). In our gene-level analysis, we found novel genes for memory decline on chromosomes 1 (SLC25A44), 11 (BSX), and 15 (DPP8). Memory performance and memory decline shared genetic architecture with AD-related traits, neuropsychiatric traits, and autoimmune traits.

DISCUSSION

We discovered several novel loci, genes, and genetic correlations associated with late-life memory performance and decline.

HIGHLIGHTS

Late-life memory has high heritability that is similar across ancestries. We discovered four novel variants associated with late-life memory. We identified four novel genes associated with late-life memory. Late-life memory shares genetic architecture with psychiatric/autoimmune traits.

Evaluation of Mean Shift, ComBat, and CycleGAN for Harmonizing Brain Connectivity Matrices Across Sites

Connectivity matrices derived from diffusion MRI (dMRI) provide an interpretable and generalizable way of understanding the human brain connectome. However, dMRI suffers from inter-site and between-scanner variation, which impedes analysis across datasets to improve robustness and reproducibility of results. To evaluate different harmonization approaches on connectivity matrices, we compared graph measures derived from these matrices before and after applying three harmonization techniques: mean shift, ComBat, and CycleGAN. The sample comprises 168 age-matched, sex-matched normal subjects from two studies: the Vanderbilt Memory and Aging Project (VMAP) and the Biomarkers of Cognitive Decline Among Normal Individuals (BIOCARD). First, we plotted the graph measures and used coefficient of variation (CoV) and the Mann-Whitney U test to evaluate different methods' effectiveness in removing site effects on the matrices and the derived graph measures. ComBat effectively eliminated site effects for global efficiency and modularity and outperformed the other two methods. However, all methods exhibited poor performance when harmonizing average betweenness centrality. Second, we tested whether our harmonization methods preserved correlations between age and graph measures. All methods except for CycleGAN in one direction improved correlations between age and global efficiency and between age and modularity from insignificant to significant with p-values less than 0.05.

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.

Hippocampus Glutathione S Reductase Potentially Confers Genetic Resilience to Cognitive Decline in the AD-BXD Mouse Population

Alzheimer's disease (AD) is a prevalent and costly age-related dementia. Heritable factors account for 58-79% of variation in late-onset AD, but substantial variation remains in age-of- onset, disease severity, and whether those with high-risk genotypes acquire AD. To emulate the diversity of human populations, we utilized the AD-BXD mouse panel. This genetically diverse resource combines AD genotypes with multiple BXD strains to discover new genetic drivers of AD resilience. Comparing AD-BXD carriers to noncarrier littermates, we computed a novel quantitative metric for resilience to cognitive decline in the AD-BXDs. Our quantitative AD resilience trait was heritable and genetic mapping identified a locus on chr8 associated with resilience to AD mutations that resulted in amyloid brain pathology. Using a hippocampus proteomics dataset, we nominated the mitochondrial glutathione S reductase protein (GR or GSHR) as a resilience factor, finding that the DBA/2J genotype was associated with substantially higher GR abundance. By mapping protein QTLs (pQTLs), we identified synaptic organization and mitochondrial proteins coregulated in trans with a cis-pQTL for GR. We found four coexpression modules correlated with the quantitative resilience score in aged 5XFAD mice using paracliques, which were related to cell structure, protein folding, and postsynaptic densities. Finally, we found significant positive associations between human GSR transcript abundance in the brain and better outcomes on AD-related cognitive and pathology traits in the Religious Orders Study/Memory and Aging project (ROSMAP). Taken together, these data support a framework for resilience in which neuronal antioxidant pathway activity provides for stability of synapses within the hippocampus.

Proteo-genomics of soluble TREM2 in cerebrospinal fluid provides novel insights and identifies novel modulators for Alzheimer's disease

Triggering receptor expressed on myeloid cells 2 (TREM2) plays a critical role in microglial activation, survival, and apoptosis, as well as in Alzheimer's disease (AD) pathogenesis. We previously reported the MS4A locus as a key modulator for soluble TREM2 (sTREM2) in cerebrospinal fluid (CSF). To identify additional novel genetic modifiers of sTREM2, we performed the largest genome-wide association study (GWAS) and identified four loci for CSF sTREM2 in 3,350 individuals of European ancestry. Through multi-ethnic fine mapping, we identified two independent missense variants (p.M178V in MS4A4A and p.A112T in MS4A6A) that drive the association in MS4A locus and showed an epistatic effect for sTREM2 levels and AD risk. The novel TREM2 locus on chr 6 contains two rare missense variants (rs75932628 p.R47H, P=7.16×10-19; rs142232675 p.D87N, P=2.71×10-10) associated with sTREM2 and AD risk. The third novel locus in the TGFBR2 and RBMS3 gene region (rs73823326, P=3.86×10-9) included a regulatory variant with a microglia-specific chromatin loop for the promoter of TGFBR2. Using cell-based assays we demonstrate that overexpression and knock-down of TGFBR2, but not RBMS3, leads to significant changes of sTREM2. The last novel locus is located on the APOE region (rs11666329, P=2.52×10-8), but we demonstrated that this signal was independent of APOE genotype. This signal colocalized with cis-eQTL of NECTIN2 in the brain cortex and cis-pQTL of NECTIN2 in CSF. Overexpression of NECTIN2 led to an increase of sTREM2 supporting the genetic findings. To our knowledge, this is the largest study to date aimed at identifying genetic modifiers of CSF sTREM2. This study provided novel insights into the MS4A and TREM2 loci, two well-known AD risk genes, and identified TGFBR2 and NECTIN2 as additional modulators involved in TREM2 biology.

A deep neural network estimation of brain age is sensitive to cognitive impairment and decline

The greatest known risk factor for Alzheimer's disease (AD) is age. While both normal aging and AD pathology involve structural changes in the brain, their trajectories of atrophy are not the same. Recent developments in artificial intelligence have encouraged studies to leverage neuroimaging-derived measures and deep learning approaches to predict brain age, which has shown promise as a sensitive biomarker in diagnosing and monitoring AD. However, prior efforts primarily involved structural magnetic resonance imaging and conventional diffusion MRI (dMRI) metrics without accounting for partial volume effects. To address this issue, we post-processed our dMRI scans with an advanced free-water (FW) correction technique to compute distinct FW-corrected fractional anisotropy (FAFWcorr) and FW maps that allow for the separation of tissue from fluid in a scan. We built 3 densely connected neural networks from FW-corrected dMRI, T1-weighted MRI, and combined FW+T1 features, respectively, to predict brain age. We then investigated the relationship of actual age and predicted brain ages with cognition. We found that all models accurately predicted actual age in cognitively unimpaired (CU) controls (FW: r=0.66, p=1.62x10-32; T1: r=0.61, p=1.45x10-26, FW+T1: r=0.77, p=6.48x10-50) and distinguished between CU and mild cognitive impairment participants (FW: p=0.006; T1: p=0.048; FW+T1: p=0.003), with FW+T1-derived age showing best performance. Additionally, all predicted brain age models were significantly associated with cross-sectional cognition (memory, FW: β=-1.094, p=6.32x10-7; T1: β=-1.331, p=6.52x10-7; FW+T1: β=-1.476, p=2.53x10-10; executive function, FW: β=-1.276, p=1.46x10-9; T1: β=-1.337, p=2.52x10-7; FW+T1: β=-1.850, p=3.85x10-17) and longitudinal cognition (memory, FW: β=-0.091, p=4.62x10-11; T1: β=-0.097, p=1.40x10-8; FW+T1: β=-0.101, p=1.35x10-11; executive function, FW: β=-0.125, p=1.20x10-10; T1: β=-0.163, p=4.25x10-12; FW+T1: β=-0.158, p=1.65x10-14). Our findings provide evidence that both T1-weighted MRI and dMRI measures improve brain age prediction and support predicted brain age as a sensitive biomarker of cognition and cognitive decline.

Cell-type-specific Alzheimer's disease polygenic risk scores are associated with distinct disease processes in Alzheimer's disease

Many of the Alzheimer's disease (AD) risk genes are specifically expressed in microglia and astrocytes, but how and when the genetic risk localizing to these cell types contributes to AD pathophysiology remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets and uncover the impact of cell-type-specific genetic risk on AD endophenotypes. In an autopsy dataset spanning all stages of AD (n = 1457), the astrocytic ADPRS affected diffuse and neuritic plaques (amyloid-β), while microglial ADPRS affected neuritic plaques, microglial activation, neurofibrillary tangles (tau), and cognitive decline. In an independent neuroimaging dataset of cognitively unimpaired elderly (n = 2921), astrocytic ADPRS was associated with amyloid-β, and microglial ADPRS was associated with amyloid-β and tau, connecting cell-type-specific genetic risk with AD pathology even before symptom onset. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage.

Clinical and demographic factors modify the association between plasma phosphorylated tau-181 and cognition

INTRODUCTION

Plasma phosphorylated tau181 (p-tau181) associations with global cognition and memory are clear, but the link between p-tau181 with other cognitive domains and subjective cognitive decline (SCD) across the clinical spectrum of Alzheimer's disease (AD) and how this association changes based on genetic and demographic factors is poorly understood.

METHODS

Participants were drawn from the Alzheimer's Disease Neuroimaging Initiative and included 1185 adults aged >55 years with plasma p-tau181 and neuropsychological test data. Linear regression models related plasma p-tau181 to neuropsychological composite and SCD scores with follow-up models examining plasma p-tau181 interactions with cognitive diagnosis, APOE ε4 carrier status, age, and sex on cognitive outcomes.

RESULTS

Higher plasma p-tau181 was associated with worse memory, executive functioning, and language abilities, and greater informant-reported SCD. Visuospatial abilities and self-report SCD were not associated with plasma p-tau181. Associations were generally stronger in MCI or dementia, APOE ε4 carriers, women, and younger participants.

DISCUSSION

Higher levels of plasma p-tau181 are associated with worse neuropsychological test performance across multiple cognitive domains; however, these associations vary based on disease stage, genetic risk status, age, and sex.

Sex and Education Modify the Association Between Subjective Cognitive Decline and Amyloid Pathology

Background

Subjective cognitive decline (SCD) may be an early risk factor for dementia, particularly in highly educated individuals and women. This study examined the effect of education and sex on the association between SCD and Alzheimer's disease (AD) biomarkers in non-demented older adults.

Method

Vanderbilt Memory and Aging Project participants free of clinical dementia or stroke (n=156, 72±6 years, 37% mild cognitive impairment, 33% female) completed fasting lumbar puncture, SCD assessment, and Wide Range Achievement Test-III Reading subtest to assess reading level at baseline as a a proxy for educational quality. Cerebrospinal fluid (CSF) biomarkers for AD (β-amyloid 42 (Aβ42), Aβ42/40 ratio, phosphorylated tau (p-tau), tau, and neurofilament light (NfL)) were analyzed in batch. Linear mixed effects models related SCD to CSF AD biomarkers and follow-up models assessed SCD x sex, SCD x reading level , and SCD x education interactions on AD biomarkers.

Result

In main effect models, higher SCD was associated with lower Aβ42 and Aβ42/40 ratio (p-values<0.004). SCD was not associated with tau, p-tau, or NfL levels ( p- values>0.38). SCD score interacted with sex on Aβ42/40 ratio ( p =0.03) but no other biomarkers ( p -values>0.10). In stratified models, higher SCD was associated with lower Aβ42/40 ratio in men ( p =0.0003) but not in women ( p =0.48). SCD score interacted with education on Aβ42 ( p =0.005) and Aβ42/40 ratio ( p =0.001) such that higher education was associated with a stronger negative association between SCD and amyloid levels. No SCD score x reading level interaction was found (p-values> 0.51) though significant associations between SCD and amyloid markers were seen in the higher reading level group (p-values<0.004) but not the lower reading level group (p-values>0.12) when stratified by a median split in reading level.

Conclusion

Among community-dwelling older adults free of clinical dementia, higher SCD was associated with greater cerebral amyloid accumulation, one of the earliest pathological AD changes. SCD appears most useful in detecting early AD-related brain changes in men and individuals with higher quantity and quality of education. SCD was not associated with CSF markers of tau pathology or neurodegeneration. These findings suggest that considering sex and education is important when assessing SCD in older adults.

A deep neural network estimation of brain age is sensitive to cognitive impairment and decline

The greatest known risk factor for Alzheimer's disease (AD) is age. While both normal aging and AD pathology involve structural changes in the brain, their trajectories of atrophy are not the same. Recent developments in artificial intelligence have encouraged studies to leverage neuroimaging-derived measures and deep learning approaches to predict brain age, which has shown promise as a sensitive biomarker in diagnosing and monitoring AD. However, prior efforts primarily involved structural magnetic resonance imaging and conventional diffusion MRI (dMRI) metrics without accounting for partial volume effects. To address this issue, we post-processed our dMRI scans with an advanced free-water (FW) correction technique to compute distinct FW-corrected fractional anisotropy (FAFWcorr) and FW maps that allow for the separation of tissue from fluid in a scan. We built 3 densely connected neural networks from FW-corrected dMRI, T1-weighted MRI, and combined FW+T1 features, respectively, to predict brain age. We then investigated the relationship of actual age and predicted brain ages with cognition. We found that all models accurately predicted actual age in cognitively unimpaired (CU) controls (FW: r=0.66, p=1.62×10-32; T1: r=0.61, p=1.45×10-26, FW+T1: r=0.77, p=6.48×10-50) and distinguished between CU and mild cognitive impairment participants (FW: p=0.006; T1: p=0.048; FW+T1: p=0.003), with FW+T1-derived age showing best performance. Additionally, all predicted brain age models were significantly associated with cross-sectional cognition (memory, FW: β=-1.094, p=6.32×10-7; T1: β=-1.331, p=6.52×10-7; FW+T1: β=-1.476, p=2.53×10-10; executive function, FW: β=-1.276, p=1.46×10-9; T1: β=-1.337, p=2.52×10-7; FW+T1: β=-1.850, p=3.85×10-17) and longitudinal cognition (memory, FW: β=-0.091, p=4.62×10-11; T1: β=-0.097, p=1.40×10-8; FW+T1: β=-0.101, p=1.35×10-11; executive function, FW: β=-0.125, p=1.20×10-10; T1: β=-0.163, p=4.25×10-12; FW+T1: β=-0.158, p=1.65×10-14). Our findings provide evidence that both T1-weighted MRI and dMRI measures improve brain age prediction and support predicted brain age as a sensitive biomarker of cognition and cognitive decline.

Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging

Introduction

It is unclear how rates of white matter microstructural decline differ between normal aging and abnormal aging.

Methods

Diffusion MRI data from several well-established longitudinal cohorts of aging (Alzheimer's Disease Neuroimaging Initiative [ADNI], Baltimore Longitudinal Study of Aging [BLSA], Vanderbilt Memory & Aging Project [VMAP]) were free-water corrected and harmonized. This dataset included 1723 participants (age at baseline: 72.8 ± 8.87 years, 49.5% male) and 4605 imaging sessions (follow-up time: 2.97 ± 2.09 years, follow-up range: 1-13 years, mean number of visits: 4.42 ± 1.98). Differences in white matter microstructural decline in normal and abnormal agers was assessed.

Results

While we found a global decline in white matter in normal/abnormal aging, we found that several white matter tracts (e.g., cingulum bundle) were vulnerable to abnormal aging.

Conclusions

There is a prevalent role of white matter microstructural decline in aging, and future large-scale studies in this area may further refine our understanding of the underlying neurodegenerative processes.

HIGHLIGHTS

Longitudinal data were free-water corrected and harmonized.Global effects of white matter decline were seen in normal and abnormal aging.The free-water metric was most vulnerable to abnormal aging.Cingulum free-water was the most vulnerable to abnormal aging.

Associations of Sex, Race, and Apolipoprotein E Alleles With Multiple Domains of Cognition Among Older Adults

Importance

Sex differences are established in associations between apolipoprotein E (APOE) ε4 and cognitive impairment in Alzheimer disease (AD). However, it is unclear whether sex-specific cognitive consequences of APOE are consistent across races and extend to the APOE ε2 allele.

Objective

To investigate whether sex and race modify APOE ε4 and ε2 associations with cognition.

Design, Setting, and Participants

This genetic association study included longitudinal cognitive data from 4 AD and cognitive aging cohorts. Participants were older than 60 years and self-identified as non-Hispanic White or non-Hispanic Black (hereafter, White and Black). Data were previously collected across multiple US locations from 1994 to 2018. Secondary analyses began December 2021 and ended September 2022.

Main Outcomes and Measures

Harmonized composite scores for memory, executive function, and language were generated using psychometric approaches. Linear regression assessed interactions between APOE ε4 or APOE ε2 and sex on baseline cognitive scores, while linear mixed-effect models assessed interactions on cognitive trajectories. The intersectional effect of race was modeled using an APOE × sex × race interaction term, assessing whether APOE × sex interactions differed by race. Models were adjusted for age at baseline and corrected for multiple comparisons.

Results

Of 32 427 participants who met inclusion criteria, there were 19 007 females (59%), 4453 Black individuals (14%), and 27 974 White individuals (86%); the mean (SD) age at baseline was 74 years (7.9). At baseline, 6048 individuals (19%) had AD, 4398 (14%) were APOE ε2 carriers, and 12 538 (38%) were APOE ε4 carriers. Participants missing APOE status were excluded (n = 9266). For APOE ε4, a robust sex interaction was observed on baseline memory (β = -0.071, SE = 0.014; P = 9.6 × 10-7), whereby the APOE ε4 negative effect was stronger in females compared with males and did not significantly differ among races. Contrastingly, despite the large sample size, no APOE ε2 × sex interactions on cognition were observed among all participants. When testing for intersectional effects of sex, APOE ε2, and race, an interaction was revealed on baseline executive function among individuals who were cognitively unimpaired (β = -0.165, SE = 0.066; P = .01), whereby the APOE ε2 protective effect was female-specific among White individuals but male-specific among Black individuals.

Conclusions and Relevance

In this study, while race did not modify sex differences in APOE ε4, the APOE ε2 protective effect could vary by race and sex. Although female sex enhanced ε4-associated risk, there was no comparable sex difference in ε2, suggesting biological pathways underlying ε4-associated risk are distinct from ε2 and likely intersect with age-related changes in sex biology.

A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores

BACKGROUND

More than 75 common variant loci account for only a portion of the heritability for Alzheimer's disease (AD). A more complete understanding of the genetic basis of AD can be deduced by exploring associations with AD-related endophenotypes.

METHODS

We conducted genome-wide scans for cognitive domain performance using harmonized and co-calibrated scores derived by confirmatory factor analyses for executive function, language, and memory. We analyzed 103,796 longitudinal observations from 23,066 members of community-based (FHS, ACT, and ROSMAP) and clinic-based (ADRCs and ADNI) cohorts using generalized linear mixed models including terms for SNP, age, SNP × age interaction, sex, education, and five ancestry principal components. Significance was determined based on a joint test of the SNP's main effect and interaction with age. Results across datasets were combined using inverse-variance meta-analysis. Genome-wide tests of pleiotropy for each domain pair as the outcome were performed using PLACO software.

RESULTS

Individual domain and pleiotropy analyses revealed genome-wide significant (GWS) associations with five established loci for AD and AD-related disorders (BIN1, CR1, GRN, MS4A6A, and APOE) and eight novel loci. ULK2 was associated with executive function in the community-based cohorts (rs157405, P = 2.19 × 10-9). GWS associations for language were identified with CDK14 in the clinic-based cohorts (rs705353, P = 1.73 × 10-8) and LINC02712 in the total sample (rs145012974, P = 3.66 × 10-8). GRN (rs5848, P = 4.21 × 10-8) and PURG (rs117523305, P = 1.73 × 10-8) were associated with memory in the total and community-based cohorts, respectively. GWS pleiotropy was observed for language and memory with LOC107984373 (rs73005629, P = 3.12 × 10-8) in the clinic-based cohorts, and with NCALD (rs56162098, P = 1.23 × 10-9) and PTPRD (rs145989094, P = 8.34 × 10-9) in the community-based cohorts. GWS pleiotropy was also found for executive function and memory with OSGIN1 (rs12447050, P = 4.09 × 10-8) and PTPRD (rs145989094, P = 3.85 × 10-8) in the community-based cohorts. Functional studies have previously linked AD to ULK2, NCALD, and PTPRD.

CONCLUSION

Our results provide some insight into biological pathways underlying processes leading to domain-specific cognitive impairment and AD, as well as a conduit toward a syndrome-specific precision medicine approach to AD. Increasing the number of participants with harmonized cognitive domain scores will enhance the discovery of additional genetic factors of cognitive decline leading to AD and related dementias.

Cell-type-specific Alzheimer's disease polygenic risk scores are associated with distinct disease processes in Alzheimer's disease

Alzheimer's disease (AD) heritability is enriched in glial genes, but how and when cell-type-specific genetic risk contributes to AD remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets. In an autopsy dataset spanning all stages of AD (n=1,457), astrocytic (Ast) ADPRS was associated with both diffuse and neuritic Aβ plaques, while microglial (Mic) ADPRS was associated with neuritic Aβ plaques, microglial activation, tau, and cognitive decline. Causal modeling analyses further clarified these relationships. In an independent neuroimaging dataset of cognitively unimpaired elderly (n=2,921), Ast-ADPRS were associated with Aβ, and Mic-ADPRS was associated with Aβ and tau, showing a consistent pattern with the autopsy dataset. Oligodendrocytic and excitatory neuronal ADPRSs were associated with tau, but only in the autopsy dataset including symptomatic AD cases. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage.

Multi-omic characterization of brain changes in the vascular endothelial growth factor family during aging and Alzheimer's disease

The vascular endothelial growth factor (VEGF) signaling family has been implicated in neuroprotection and clinical progression in Alzheimer's disease (AD). Previous work in postmortem human dorsolateral prefrontal cortex demonstrated that higher transcript levels of VEGFB, PGF, FLT1, and FLT4 are associated with AD dementia, worse cognitive outcomes, and higher AD neuropathology. To expand prior work, we leveraged bulk RNA sequencing data, single nucleus RNA (snRNA) sequencing, and both tandem mass tag and selected reaction monitoring mass spectrometry proteomic measures from the post-mortem brain. Outcomes included AD diagnosis, cognition, and AD neuropathology. We replicated previously reported VEGFB and FLT1 results, whereby higher expression was associated with worse outcomes, and snRNA results suggest microglia, oligodendrocytes, and endothelia may play a central role in these associations. Additionally, FLT4 and NRP2 expression were associated with better cognitive outcomes. This study provides a comprehensive molecular picture of the VEGF signaling family in cognitive aging and AD and critical insight towards the biomarker and therapeutic potential of VEGF family members in AD.

TREM2 gene expression associations with Alzheimer's disease neuropathology are region-specific: implications for cortical versus subcortical microglia

Previous post-mortem assessments of TREM2 expression and its association with brain pathologies have been limited by sample size. This study sought to correlate region-specific TREM2 mRNA expression with diverse neuropathological measures at autopsy using a large sample size (N = 945) of bulk RNA sequencing data from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP). TREM2 gene expression of the dorsolateral prefrontal cortex, posterior cingulate cortex, and caudate nucleus was assessed with respect to core pathology of Alzheimer's disease (amyloid-β, and tau), cerebrovascular pathology (cerebral infarcts, arteriolosclerosis, atherosclerosis, and cerebral amyloid angiopathy), microglial activation (proportion of activated microglia), and cognitive performance. We found that cortical TREM2 levels were positively related to AD diagnosis, cognitive decline, and amyloid-β neuropathology but were not related to the proportion of activated microglia. In contrast, caudate TREM2 levels were not related to AD pathology, cognition, or diagnosis, but were positively related to the proportion of activated microglia in the same region. Diagnosis-stratified results revealed caudate TREM2 levels were inversely related to AD neuropathology and positively related to microglial activation and longitudinal cognitive performance in AD cases. These results highlight the notable changes in TREM2 transcript abundance in AD and suggest that its pathological associations are brain-region-dependent.

Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging

INTRODUCTION

It is unclear how rates of white matter microstructural decline differ between normal aging and abnormal aging.

METHODS

Diffusion MRI data from several well-established longitudinal cohorts of aging [Alzheimer's Neuroimaging Initiative (ADNI), Baltimore Longitudinal Study of Aging (BLSA), Vanderbilt Memory & Aging Project (VMAP)] was free-water corrected and harmonized. This dataset included 1,723 participants (age at baseline: 72.8±8.87 years, 49.5% male) and 4,605 imaging sessions (follow-up time: 2.97±2.09 years, follow-up range: 1-13 years, mean number of visits: 4.42±1.98). Differences in white matter microstructural decline in normal and abnormal agers was assessed.

RESULTS

While we found global decline in white matter in normal/abnormal aging, we found that several white matter tracts (e.g., cingulum bundle) were vulnerable to abnormal aging.

CONCLUSIONS

There is a prevalent role of white matter microstructural decline in aging, and future large-scale studies in this area may further refine our understanding of the underlying neurodegenerative processes.

HIGHLIGHTS

Longitudinal data was free-water corrected and harmonizedGlobal effects of white matter decline were seen in normal and abnormal agingThe free-water metric was most vulnerable to abnormal agingCingulum free-water was the most vulnerable to abnormal aging.

Establishing Quality Control Procedures for Large-Scale Plasma Proteomics Analyses

Proteomics research has been transformed due to high-throughput liquid chromatography (LC-MS/MS) tandem mass spectrometry instruments combined with highly sophisticated automated sample preparation and multiplexing workflows. However, scaling proteomics experiments to large sample cohorts (hundreds to thousands) requires thoughtful quality control (QC) protocols. Robust QC protocols can help with reproducibility, quantitative accuracy, and provide opportunities for more decisive troubleshooting. Our laboratory conducted a plasma proteomics study of a cohort of N = 335 patient samples using tandem mass tag (TMT_pro) 16-plex batches. Over the course of a 10-month data acquisition period for this cohort we collected 271 pooled QC LC-MS/MS result files obtained from MS/MS analysis of a patient-derived pooled plasma sample, representative of the entire cohort population. This sample was tagged with TMT_zero or TMT_pro reagents and used to inform the daily performance of the LC-MS/MS instruments and to allow within and across sample batch normalization. Analytical variability of a number of instrumental and data analysis metrics including protein and peptide identifications, peptide spectral matches (PSMs), number of obtained MS/MS spectra, average peptide abundance, percent of peptides with a Δ m/z between ±0.003 Da, percent of MS/MS spectra obtained at the maximum injection time, and the retention time of selected tracking peptides were evaluated to help inform the design of a robust LC-MS/MS QC workflow for use in future cohort studies. This study also led to general tips for using selected metrics to inform real-time troubleshooting of LC-MS/MS performance issues with daily QC checks.

Harmonizing the preclinical Alzheimer cognitive composite for multicohort studies

OBJECTIVES

Studies are increasingly examining research questions across multiple cohorts using data from the preclinical Alzheimer cognitive composite (PACC). Our objective was to use modern psychometric approaches to develop a harmonized PACC.

METHOD

We used longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Harvard Aging Brain Study (HABS), and Australian Imaging, Biomarker and Lifestyle Study of Ageing (AIBL) cohorts (n = 2,712). We further demonstrated our method with the Anti-Amyloid Treatment of Asymptomatic Alzheimer's Disease (A4) Study prerandomized data (n = 4,492). For the harmonization method, we used confirmatory factor analysis (CFA) on the final visit of the longitudinal cohorts to determine parameters to generate latent PACC (lPACC) scores. Overlapping tests across studies were set as "anchors" that tied cohorts together, while parameters from unique tests were freely estimated. We performed validation analyses to assess the performance of lPACC versus the common standardized PACC (zPACC).

RESULTS

Baseline (BL) scores for the zPACC were centered on zero, by definition. The harmonized lPACC did not define a common mean of zero and demonstrated differences in baseline ability levels across the cohorts. Baseline lPACC slightly outperformed zPACC in the prediction of progression to dementia. Longitudinal change in the lPACC was more constrained and less variable relative to the zPACC. In combined-cohort analyses, longitudinal lPACC slightly outperformed longitudinal zPACC in its association with baseline β-amyloid status.

CONCLUSIONS

This study proposes procedures for harmonizing the PACC that make fewer strong assumptions than the zPACC, facilitating robust multicohort analyses. This implementation of item response theory lends itself to adapting across future cohorts with similar composites. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Cognitive domain harmonization and cocalibration in studies of older adults

OBJECTIVE

Studies use different instruments to measure cognitirating cognitive tests permit direct comparisons of individuals across studies and pooling data for joint analyses.

METHOD

We began our legacy item bank with data from the Adult Changes in Thought study (n = 5,546), the Alzheimer's Disease Neuroimaging Initiative (n = 3,016), the Rush Memory and Aging Project (n = 2,163), and the Religious on such as the Mini-Mental State Examination, the Alzheimer's Disease Assessment Scale-Cognitive Subscale, the Wechsler Memory Scale, and the Boston Naming Test. CocalibOrders Study (n = 1,456). Our workflow begins with categorizing items administered in each study as indicators of memory, executive functioning, language, visuospatial functioning, or none of these domains. We use confirmatory factor analysis models with data from the most recent visit on the pooled sample across these four studies for cocalibration and derive item parameters for all items. Using these item parameters, we then estimate factor scores along with corresponding standard errors for each domain for each study. We added additional studies to our pipeline as available and focused on thorough consideration of candidate anchor items with identical content and administration methods across studies.

RESULTS

Prestatistical harmonization steps such qualitative and quantitative assessment of granular cognitive items and evaluating factor structure are important steps when trying to cocalibrate cognitive scores across studies. We have cocalibrated cognitive data and derived scores for four domains for 76,723 individuals across 10 studies.

CONCLUSIONS

We have implemented a large-scale effort to harmonize and cocalibrate cognitive domain scores across multiple studies of cognitive aging. Scores on the same metric facilitate meta-analyses of cognitive outcomes across studies or the joint analysis of individual data across studies. Our systematic approach allows for cocalibration of additional studies as they become available and our growing item bank enables robust investigation of cognition in the context of aging and dementia. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Large multi-ethnic genetic analyses of amyloid imaging identify new genes for Alzheimer disease

Amyloid PET imaging has been crucial for detecting the accumulation of amyloid beta (Aβ) deposits in the brain and to study Alzheimer's disease (AD). We performed a genome-wide association study on the largest collection of amyloid imaging data (N = 13,409) to date, across multiple ethnicities from multicenter cohorts to identify variants associated with brain amyloidosis and AD risk. We found a strong APOE signal on chr19q.13.32 (top SNP: APOE ɛ4; rs429358; β = 0.35, SE = 0.01, P = 6.2 × 10-311, MAF = 0.19), driven by APOE ɛ4, and five additional novel associations (APOE ε2/rs7412; rs73052335/rs5117, rs1081105, rs438811, and rs4420638) independent of APOE ɛ4. APOE ɛ4 and ε2 showed race specific effect with stronger association in Non-Hispanic Whites, with the lowest association in Asians. Besides the APOE, we also identified three other genome-wide loci: ABCA7 (rs12151021/chr19p.13.3; β = 0.07, SE = 0.01, P = 9.2 × 10-09, MAF = 0.32), CR1 (rs6656401/chr1q.32.2; β = 0.1, SE = 0.02, P = 2.4 × 10-10, MAF = 0.18) and FERMT2 locus (rs117834516/chr14q.22.1; β = 0.16, SE = 0.03, P = 1.1 × 10-09, MAF = 0.06) that all colocalized with AD risk. Sex-stratified analyses identified two novel female-specific signals on chr5p.14.1 (rs529007143, β = 0.79, SE = 0.14, P = 1.4 × 10-08, MAF = 0.006, sex-interaction P = 9.8 × 10-07) and chr11p.15.2 (rs192346166, β = 0.94, SE = 0.17, P = 3.7 × 10-08, MAF = 0.004, sex-interaction P = 1.3 × 10-03). We also demonstrated that the overall genetic architecture of brain amyloidosis overlaps with that of AD, Frontotemporal Dementia, stroke, and brain structure-related complex human traits. Overall, our results have important implications when estimating the individual risk to a population level, as race and sex will needed to be taken into account. This may affect participant selection for future clinical trials and therapies.

Assessment of Risk Factors and Clinical Importance of Enlarged Perivascular Spaces by Whole-Brain Investigation in the Multi-Ethnic Study of Atherosclerosis

Importance

Enlarged perivascular spaces (ePVSs) have been associated with cerebral small-vessel disease (cSVD). Although their etiology may differ based on brain location, study of ePVSs has been limited to specific brain regions; therefore, their risk factors and significance remain uncertain.

Objective

Toperform a whole-brain investigation of ePVSs in a large community-based cohort.

Design, Setting, and Participants

This cross-sectional study analyzed data from the Atrial Fibrillation substudy of the population-based Multi-Ethnic Study of Atherosclerosis. Demographic, vascular risk, and cardiovascular disease data were collected from September 2016 to May 2018. Brain magnetic resonance imaging was performed from March 2018 to July 2019. The reported analysis was conducted between August and October 2022. A total of 1026 participants with available brain magnetic resonance imaging data and complete information on demographic characteristics and vascular risk factors were included.

Main Outcomes and Measures

Enlarged perivascular spaces were quantified using a fully automated deep learning algorithm. Quantified ePVS volumes were grouped into 6 anatomic locations: basal ganglia, thalamus, brainstem, frontoparietal, insular, and temporal regions, and were normalized for the respective regional volumes. The association of normalized regional ePVS volumes with demographic characteristics, vascular risk factors, neuroimaging indices, and prevalent cardiovascular disease was explored using generalized linear models.

Results

In the 1026 participants, mean (SD) age was 72 (8) years; 541 (53%) of the participants were women. Basal ganglia ePVS volume was positively associated with age (β = 3.59 × 10-3; 95% CI, 2.80 × 10-3 to 4.39 × 10-3), systolic blood pressure (β = 8.35 × 10-4; 95% CI, 5.19 × 10-4 to 1.15 × 10-3), use of antihypertensives (β = 3.29 × 10-2; 95% CI, 1.92 × 10-2 to 4.67 × 10-2), and negatively associated with Black race (β = -3.34 × 10-2; 95% CI, -5.08 × 10-2 to -1.59 × 10-2). Thalamic ePVS volume was positively associated with age (β = 5.57 × 10-4; 95% CI, 2.19 × 10-4 to 8.95 × 10-4) and use of antihypertensives (β = 1.19 × 10-2; 95% CI, 6.02 × 10-3 to 1.77 × 10-2). Insular region ePVS volume was positively associated with age (β = 1.18 × 10-3; 95% CI, 7.98 × 10-4 to 1.55 × 10-3). Brainstem ePVS volume was smaller in Black than in White participants (β = -5.34 × 10-3; 95% CI, -8.26 × 10-3 to -2.41 × 10-3). Frontoparietal ePVS volume was positively associated with systolic blood pressure (β = 1.14 × 10-4; 95% CI, 3.38 × 10-5 to 1.95 × 10-4) and negatively associated with age (β = -3.38 × 10-4; 95% CI, -5.40 × 10-4 to -1.36 × 10-4). Temporal region ePVS volume was negatively associated with age (β = -1.61 × 10-2; 95% CI, -2.14 × 10-2 to -1.09 × 10-2), as well as Chinese American (β = -2.35 × 10-1; 95% CI, -3.83 × 10-1 to -8.74 × 10-2) and Hispanic ethnicities (β = -1.73 × 10-1; 95% CI, -2.96 × 10-1 to -4.99 × 10-2).

Conclusions and Relevance

In this cross-sectional study of ePVSs in the whole brain, increased ePVS burden in the basal ganglia and thalamus was a surrogate marker for underlying cSVD, highlighting the clinical importance of ePVSs in these locations.

Whole blood transcript and protein abundance of the vascular endothelial growth factor family relate to cognitive performance

The vascular endothelial growth factor (VEGF) family of genes has been implicated in the clinical development of Alzheimer's Disease (AD). A previous study identified associations between gene expression of VEGF family members in the prefrontal cortex and cognitive performance and AD pathology. This study explored if those associations were also observed in the blood. Consistent with previous observations in brain tissue, higher blood gene expression of placental growth factor (PGF) was associated with a faster rate of memory decline (p=0.04). Higher protein abundance of FMS-related receptor tyrosine kinase 4 (FLT4) in blood was associated with biomarker levels indicative of lower amyloid and tau pathology, opposite the direction observed in brain. Also, higher gene expression of VEGFB in blood was associated with better baseline memory (p=0.008). Notably, we observed that higher gene expression of VEGFB in blood was associated with lower expression of VEGFB in the brain (r=-0.19, p=0.02). Together, these results suggest that the VEGFB, FLT4, and PGF alterations in the AD brain may be detectable in the blood compartment.

White matter microstructural metrics are sensitively associated with clinical staging in Alzheimer's disease

Introduction

White matter microstructure may be abnormal along the Alzheimer's disease (AD) continuum.

Methods

Diffusion magnetic resonance imaging (dMRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 627), Baltimore Longitudinal Study of Aging (BLSA, n = 684), and Vanderbilt Memory & Aging Project (VMAP, n = 296) cohorts were free-water (FW) corrected and conventional, and FW-corrected microstructural metrics were quantified within 48 white matter tracts. Microstructural values were subsequently harmonized using the Longitudinal ComBat technique and inputted as independent variables to predict diagnosis (cognitively unimpaired [CU], mild cognitive impairment [MCI], AD). Models were adjusted for age, sex, race/ethnicity, education, apolipoprotein E (APOE) ε4 carrier status, and APOE ε2 carrier status.

Results

Conventional dMRI metrics were associated globally with diagnostic status; following FW correction, the FW metric itself exhibited global associations with diagnostic status, but intracellular metric associations were diminished.

Discussion

White matter microstructure is altered along the AD continuum. FW correction may provide further understanding of the white matter neurodegenerative process in AD.

Highlights

Longitudinal ComBat successfully harmonized large-scale diffusion magnetic resonance imaging (dMRI) metrics.Conventional dMRI metrics were globally sensitive to diagnostic status.Free-water (FW) correction mitigated intracellular associations with diagnostic status.The FW metric itself was globally sensitive to diagnostic status. Multivariate conventional and FW-corrected models may provide complementary information.

Enlarged perivascular space burden associations with arterial stiffness and cognition

Enlarged perivascular spaces (ePVS) are difficult to quantify, and their etiologies and consequences are poorly understood. Vanderbilt Memory and Aging Project participants (n = 327, 73 ± 7 years) completed 3T brain MRI to quantify ePVS volume and count, longitudinal neuropsychological assessment, and cardiac MRI to quantify aortic stiffness. Linear regressions related (1) PWV to ePVS burden and (2) ePVS burden to cross-sectional and longitudinal neuropsychological performance adjusting for key demographic and medical factors. Higher aortic stiffness related to greater basal ganglia ePVS volume (β = 7.0×10-5, p = 0.04). Higher baseline ePVS volume was associated with worse baseline information processing (β = -974, p = 0.003), executive function (β = -81.9, p < 0.001), and visuospatial performances (β = -192, p = 0.02) and worse longitudinal language (β = -54.9, p = 0.05), information processing (β = -147, p = 0.03), executive function (β = -10.9, p = 0.03), and episodic memory performances (β = -10.6, p = 0.02). Results were similar for ePVS count. Greater arterial stiffness relates to worse basal ganglia ePVS burden, suggesting cardiovascular aging as an etiology. ePVS burden is associated with adverse cognitive trajectory, emphasizing the clinical relevance of ePVS.

Baseline grey matter volumes and white matter hyperintensities predict decline in functional activities in older adults over a 5-year follow-up period

INTRODUCTION

Functional independence is an essential predictor of quality of life in aging, yet few accessible predictors of functional decline have been identified. This study examined associations between baseline structural neuroimaging markers and longitudinal functional status.

METHODS

Linear mixed effects models with follow-up time interaction terms related baseline grey matter volume and white matter hyperintensities (WMHs) to functional trajectory, adjusting for demographic and medical covariates. Subsequent models assessed interactions with cognitive status and apolipoprotein E (APOE) ε4 status.

RESULTS

Smaller baseline grey matter volumes, particularly in regions commonly affected by Alzheimer's disease (AD), and greater baseline WMHs were associated with faster functional decline over a mean 5-year follow-up. Effects were stronger in APOE-ε4 carriers on grey matter variables. Cognitive status interacted with most MRI variables.

DISCUSSION

Greater atrophy in AD-related regions and higher WMH burden at study entry were associated with faster functional decline, particularly among participants at increased risk of AD.

Novel CYP1B1-RMDN2 Alzheimer's disease locus identified by genome-wide association analysis of cerebral tau deposition on PET

Determining the genetic architecture of Alzheimer's disease (AD) pathologies can enhance mechanistic understanding and inform precision medicine strategies. Here, we performed a genome-wide association study of cortical tau quantified by positron emission tomography in 3,136 participants from 12 independent studies. The CYP1B1-RMDN2 locus was associated with tau deposition. The most significant signal was at rs2113389, which explained 4.3% of the variation in cortical tau, while APOE4 rs429358 accounted for 3.6%. rs2113389 was associated with higher tau and faster cognitive decline. Additive effects, but no interactions, were observed between rs2113389 and diagnosis, APOE4 , and Aβ positivity. CYP1B1 expression was upregulated in AD. rs2113389 was associated with higher CYP1B1 expression and methylation levels. Mouse model studies provided additional functional evidence for a relationship between CYP1B1 and tau deposition but not Aβ. These results may provide insight into the genetic basis of cerebral tau and novel pathways for therapeutic development in AD.

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. Co-immunoprecipitation 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 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 maintenance of ZCCHC17 function may be a therapeutic strategy for preserving cognitive function in the setting of AD pathology.

Testing a polygenic risk score for morphological microglial activation in Alzheimer's disease and aging

Neuroinflammation and the activation of microglial cells are among the earliest events in Alzheimer's disease (AD). However, direct observation of microglia in living people is not currently possible. Here, we indexed the heritable propensity for neuroinflammation with polygenic risk scores (PRS), using results from a recent genome-wide analysis of a validated post-mortem measure of morphological microglial activation. We sought to determine whether a PRS for microglial activation (PRS mic ) could augment the predictive performance of existing AD PRSs for late-life cognitive impairment. First, PRS mic were calculated and optimized in a calibration cohort (Alzheimer's Disease Neuroimaging Initiative (ADNI), n=450), with resampling. Second, predictive performance of optimal PRS mic was assessed in two independent, population-based cohorts (total n=212,237). Our PRS mic showed no significant improvement in predictive power for either AD diagnosis or cognitive performance. Finally, we explored associations of PRS mic with a comprehensive set of imaging and fluid AD biomarkers in ADNI. This revealed some nominal associations, but with inconsistent effect directions. While genetic scores capable of indexing risk for neuroinflammatory processes in aging are highly desirable, more well-powered genome-wide studies of microglial activation are required. Further, biobank-scale studies would benefit from phenotyping of proximal neuroinflammatory processes to improve the PRS development phase.

Comparing voxel- and feature-wise harmonization of complex graph measures from multiple sites for structural brain network investigation of aging

Complex graph theory measures of brain structural connectomes derived from diffusion weighted images (DWI) provide insight into the network structure of the brain. Further, as the number of available DWI datasets grows, so does the ability to investigate associations in these measures with major biological factors, like age. However, one key hurdle that remains is the presence of scanner effects that can arise from different DWI datasets and confound multisite analyses. Two common approaches to correct these effects are voxel-wise and feature-wise harmonization. However, it is still unclear how to best leverage them for graph-theory analysis of an aging population. Thus, there is a need to better characterize the impact of each harmonization method and their ability to preserve age related features. We investigate this by characterizing four complex graph theory measures (modularity, characteristic path length, global efficiency, and betweenness centrality) in 48 participants aged 55 to 86 from Baltimore Longitudinal Study of Aging (BLSA) and Vanderbilt Memory and Aging Project (VMAP) before and after voxel- and feature-wise harmonization with the Null Space Deep Network (NSDN) and ComBat, respectively. First, we characterize across dataset coefficients of variation (CoV) and find the combination of NSDN and ComBat causes the greatest reduction in CoV followed by ComBat alone then NSDN alone. Second, we reproduce published associations of modularity with age after correcting for other covariates with linear models. We find that harmonization with ComBat or ComBat and NSDN together improves the significance of existing age effects, reduces model residuals, and qualitatively reduces separation between datasets. These results reinforce the efficiency of statistical harmonization on the feature-level with ComBat and suggest that harmonization on the voxel-level is synergistic but may have reduced effect after running through the multiple layers of the connectomics pipeline. Thus, we conclude that feature-wise harmonization improves statistical results, but the addition of biologically informed voxel-based harmonization offers further improvement.

Testing a Polygenic Risk Score for Morphological Microglial Activation in Alzheimer's Disease and Aging

BACKGROUND

Neuroinflammation and the activation of microglial cells are among the earliest events in Alzheimer's disease (AD). However, direct observation of microglia in living people is not currently possible. Here, we indexed the heritable propensity for neuroinflammation with polygenic risk scores (PRS), using results from a recent genome-wide analysis of a validated post-mortem measure of morphological microglial activation.

OBJECTIVE

We sought to determine whether a PRS for microglial activation (PRSmic) could augment the predictive performance of existing AD PRSs for late-life cognitive impairment.

METHODS

First, PRSmic were calculated and optimized in a calibration cohort (Alzheimer's Disease Neuroimaging Initiative (ADNI), n = 450), with resampling. Second, predictive performance of optimal PRSmic was assessed in two independent, population-based cohorts (total n = 212,237). Finally, we explored associations of PRSmic with a comprehensive set of imaging and fluid AD biomarkers in ADNI.

RESULTS

Our PRSmic showed no significant improvement in predictive power for either AD diagnosis or cognitive performance in either external cohort. Some nominal associations were found in ADNI, but with inconsistent effect directions.

CONCLUSION

While genetic scores capable of indexing risk for neuroinflammatory processes in aging are highly desirable, more well-powered genome-wide studies of microglial activation are required. Further, biobank-scale studies would benefit from phenotyping of proximal neuroinflammatory processes to improve the PRS development phase.

Polygenic resilience score may be sensitive to preclinical Alzheimer's disease changes

Late-onset Alzheimer's disease (LOAD) is a polygenic disorder with a long prodromal phase, making early diagnosis challenging. Twin studies estimate LOAD as 60-80% heritable, and while common genetic variants can account for 30% of this heritability, nearly 70% remains "missing". Polygenic risk scores (PRS) leverage combined effects of many loci to predict LOAD risk, but often lack sensitivity to preclinical disease changes, limiting clinical utility. Our group has built and published on a resilience phenotype to model better-than-expected cognition give amyloid pathology burden and hypothesized it may assist in preclinical polygenic risk prediction. Thus, we built a LOAD PRS and a resilience PRS and evaluated both in predicting cognition in a dementia-free cohort (N=254). The LOAD PRS had a significant main effect on baseline memory (β=-0.18, P=1.68E-03). Both the LOAD PRS (β=-0.03, P=1.19E-03) and the resilience PRS (β=0.02, P=0.03) had significant main effects on annual memory decline. The resilience PRS interacted with CSF Aβ on baseline memory (β=-6.04E-04, P=0.02), whereby it predicted baseline memory among Aβ+ individuals (β=0.44, P=0.01) but not among Aβ- individuals (β=0.06, P=0.46). Excluding APOE from PRS resulted in mainly LOAD PRS associations attenuating, but notably the resilience PRS interaction with CSF Aβ and selective prediction among Aβ+ individuals was consistent. Although the resilience PRS is currently somewhat limited in scope from the phenotype's cross-sectional nature, our results suggest that the resilience PRS may be a promising tool in assisting in preclinical disease risk prediction among dementia-free and Aβ+ individuals, though replication and fine-tuning are needed.