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AbstractBackgroundEarly‐onset Alzheimer’s disease (EOAD) occurs before age 65 and has more diverse disease presentations than late‐onset AD. To improve our understanding of phenotypic heterogeneity among EOAD individuals, we analyzed cognitive scores using data‐driven statistical analysis.MethodBaseline cognitive data from 286 sporadic EOAD individuals from the Longitudinal EOAD study (LEADS) were transformed to z‐scores using data from 95 cognitively normal (CN) individuals. Cognitive composites were generated for domains of memory, language, speed/attention, visuospatial, and executive function. Residuals from linear regression models on Z‐scores adjusted for age, sex, and education were obtained. Cluster analysis using the Ward method on the cognitive domain residuals was performed and scree plot using the pseudo T‐squared determined the optimal number of clusters for the EOAD sample. We also compared gray matter density (GMD) of each EOAD cluster to CN participants using voxel‐wise multiple linear regressions.ResultsThree clusters of cognitive performance were identified from the EOAD sample. Disease duration was not significantly different across clusters. Using a z‐score of ‐1.5 SD as the impairment threshold, all clusters were impaired across most domains (Table 1). Cluster‐3 was more impaired than cluster‐2 in all domains (Table 2; all p<.0001), and in all domains except episodic memory compared to cluster‐1 (all p<.01). Cluster‐1 (n = 71; 85.9% amnestic) was most impaired in executive function, visuospatial, and speed/attention. Cluster‐2 (n = 133; 88.7% amnestic) was most impaired in episodic memory. Cluster‐3 (n = 82; 69.5% amnestic) was most impaired in executive function, visuospatial, and speed/attention (Table 1). 3D‐comparisons showed all EOAD clusters had reduced GMD compared to CN. Cluster‐1 and cluster‐3 both showed widespread atrophy, with cluster‐3 being more severe. Cluster‐2 showed the most atrophy in the temporal and parietal lobes (Figure 1).ConclusionWe identified heterogeneity in cognitive patterns among sporadic EOAD individuals. Cluster‐3 appeared to reflect widespread impairment, and cluster‐2 represented an amnestic‐only presentation. Despite comparable disease duration, some EOAD patients progress faster, while some are more resilient. 3D‐comparisons showed neurodegenerative changes affecting brain regions responsible for respective impaired cognitive functions in each cluster (e.g., cluster‐2 is primarily amnestic‐impaired and has temporoparietal atrophy). Future work should explore amyloid‐PET and tau‐PET burden.

AbstractBackgroundWomen with suspected coronary microvascular dysfunction (CMD) may be at higher risk of experiencing cognitive decline due to cerebral small vessel disease, a known contributor to Alzheimer’s disease and related dementias (ADRD). A potential underlying mechanism that could accelerate this cognitive decline is the accumulation of brain tissue iron, which has been previously linked to changes in brain function potentially caused by oxidative stress and cell death. Therefore, we aim to elucidate whether a similar mechanism could affect women with suspected CMD by investigating the potential role of iron deposition on the brain’s functional organization and its effect on cognition using advanced magnetic resonance imaging (MRI).Material and MethodsTwenty‐seven women with suspected CMD [Age; median (range) = 54 (29‐76)], drawn from ongoing cohorts (3R01HL146158‐04S1,3U54AG065141‐04S1), underwent a 3T MRI protocol, including submillimeter T2* 3‐dimensional echo‐planar‐imaging for assessing iron deposition with high‐resolution quantitative susceptibility mapping (QSM) and resting‐state fMRI (rs‐fMRI). Iron content was quantified by total‐generalized‐variation based QSM analysis. Functional integrity was determined via graph theoretical approach (i.e., nodal degree). Cognitive assessment was also performed using the NIH Toolbox. Mediation analysis was conducted using Python Statsmodels.ResultsMost of the women with suspected CMD showed lower performance in processing speed, working memory, executive function, and attention (Figure 1A). We found a significant association between elevated iron levels in paracentral gyrus and lower functional connectivity in left hippocampus (p=0.005, adjusted‐r2=0.19) (Figure 1B). Elevated iron level in the paracentral gyrus showed an impact on cognitive performance in the domains of executive function and attention (p<0.0001, coefficient=531.09) as well as language functions and crystalized abilities (p=0.036, coefficient=362.45), mediated by functional connectivity in the left hippocampus (indirect effect on executive function / language: p = 0.034 / 0.038, coefficient = ‐254.54 /‐ 213.06) (Figure 1C).ConclusionsOur results suggest that changes in hippocampal functional organization are associated with cortical iron deposition and mediate its impact on cognitive performances. These changes may increase the risk of cognitive decline/ADRD or in women with suspected CMD. Future research in a larger cohort with a longitudinal design is necessary to validate and expand upon these findings.

AbstractBackgroundWomen with suspected coronary microvascular dysfunction (CMD) may be at higher risk of experiencing cognitive decline due to cerebral small vessel disease, a known contributor to Alzheimer’s disease and related dementias (ADRD). A potential underlying mechanism that could accelerate this cognitive decline is the accumulation of brain tissue iron, which has been previously linked to changes in brain function potentially caused by oxidative stress and cell death. Therefore, we aim to elucidate whether a similar mechanism could affect women with suspected CMD by investigating the potential role of iron deposition on the brain’s functional organization and its effect on cognition using advanced magnetic resonance imaging (MRI).Material and MethodsTwenty‐seven women with suspected CMD [Age; median (range) = 54 (29‐76)], drawn from ongoing cohorts (3R01HL146158‐04S1,3U54AG065141‐04S1), underwent a 3T MRI protocol, including submillimeter T2* 3‐dimensional echo‐planar‐imaging for assessing iron deposition with high‐resolution quantitative susceptibility mapping (QSM) and resting‐state fMRI (rs‐fMRI). Iron content was quantified by total‐generalized‐variation based QSM analysis. Functional integrity was determined via graph theoretical approach (i.e., nodal degree). Cognitive assessment was also performed using the NIH Toolbox. Mediation analysis was conducted using Python Statsmodels.ResultsMost of the women with suspected CMD showed lower performance in processing speed, working memory, executive function, and attention (Figure‐1A). We found a significant association between elevated iron levels in paracentral gyrus and lower functional connectivity in left hippocampus (p = 0.005, adjusted‐r2 = 0.19) (Figure‐1B). Elevated iron level in the paracentral gyrus showed an impact on cognitive performance in the domains of executive function and attention (p<0.0001, coefficient = 531.09) as well as language functions and crystalized abilities (p = 0.036, coefficient = 362.45), mediated by functional connectivity in the left hippocampus (indirect effect on executive function / language: p = 0.034 / 0.038, coefficient = ‐254.54 /‐ 213.06) (Figure‐1C).ConclusionsOur results suggest that changes in hippocampal functional organization are associated with cortical iron deposition and mediate its impact on cognitive performances. These changes may increase the risk of cognitive decline/ADRD or in women with suspected CMD. Future research in a larger cohort with a longitudinal design is necessary to validate and expand upon these findings.

AbstractBackgroundA complex, multicellular disease with genetic and immunological elements, Alzheimer’s disease (AD) affects millions worldwide. There has been previous research linking AD to the missense variants ABI3‐rs616338‐T and PLCG2‐rs72824905‐G, and the altered expression of these genes has been shown to disrupt microglial function. In our understanding of AD risk and resilience, limited research has been conducted on how these variants affect microglial subtypes and states in AD.MethodsWe previously identified DOCK8 protein as a target for fluorescent activated nuclei sorting (FANS) to enrich microglia nuclei from frozen human brains. Using this enrichment strategy, we generated microglia enriched snRNAseq data from temporal cortex tissue of 30 donors harboring ABI3 or PLCG2 missense mutations, or neither mutation. We introduced PLCG2 variant in either homozygote, and heterozygote forms into an AD patient derived iPSC through CRISPR/Cas9 approach, differentiated these cells into microglia cells (IMGLs) following established protocols, and generated scRNAseq data after treatment with Amyloidβ. We applied standard alignment and quality control pipelines to the snRNAseq and scRNAseq datasets in parallel. Established markers of microglia states and subtypes were utilized to annotate the clusters; analyzed for their hub gene expression using comparisons between cluster differential profiling to determine signature pathways. Differential gene expression was assessed using pseudo bulk and MAST approaches.ResultsWe obtained single nuclei transcriptome profiles of 54,000 frozen human brain nuclei, of which 35,000 are microglia, through snRNAseq, and single cell profiles of 63,000 iMGLs through scRNAseq, using our standard alignment and quality control procedures. Our differential gene expression analysis identified novel genes and pathways which were identified as part of resilience or AD risk networks in microglia subtypes and states. These alterations were validated using orthogonal experimental methods and further explored for their conservation using in vivo external datasets. Pseudotime inference will be completed to probe microglia marker gene expression dynamics, treatment conditions, along with continuous cell‐state changes.ConclusionOur study uncovers microglia subtype specific resilience and risk factors provided by AD related genetic variants using snRNAseq from frozen human brain and scRNAseq from IPSC derived microglia cells. These findings nominate novel targets and pathways with therapeutic potential.

AbstractBackgroundProgressive supranuclear palsy (PSP) is a neurodegenerative disorder involving pathological deposition of tau that includes glial inclusions and specific regional vulnerability patterns. Therapeutic developments are hampered by incomplete understanding of disease mechanisms. Few studies have examined its cell type‐specific effects. We performed RNA‐sequencing in a large cohort of PSP patients and controls to understand molecular pathways disrupted across prefrontal cortex and caudate nucleus in PSP. We also performed multi‐omic single‐nucleus sequencing to deconvolute cell type‐specific changes.MethodRNA‐sequencing was conducted in 250 PSP patients and age‐ and sex‐matched controls, with a subset (N = 23) undergoing multi‐omic single‐nucleus RNA‐sequencing and ATAC‐sequencing (10x Genomics). Sequencing data was aligned to GRCh38 and quantified using STAR and RSEM (RNA‐seq) and CellRanger (single‐nucleus) and corrected for technical and biological covariates. Differential expression was calculated with Dream (RNA‐seq) and Dreamlet (single‐nucleus sequencing), and co‐expression network analysis (WGCNA) used to extract disease‐relevant gene modules.ResultRNA‐sequencing analysis identified ∼4000 differentially expressed genes in both brain regions. Despite differences in cellular composition and degree of disease impact, both regions share patterns of dysregulation related to protein folding and processing, indicating common pathological mechanisms. Differences between the regions includes disruption of cellular homeostasis and intracellular trafficking in caudate, while prefrontal cortex shows suppression of metabolic processes and immune response. Preliminary findings from the single cell genomic analyses suggest the greatest changes occur in neurons of both regions, where there is a shared pattern of protein processing dysregulation and a distinct enrichment in metabolic processing within prefrontal cortex interneurons.ConclusionWe identified thousands of dysregulated genes in two impacted brain regions in PSP and show that this dysregulation is reflected in specific neuronal populations in these regions. Identifying regional and specific cell type‐specific mechanisms related to PSP will further our understanding of causative disease mechanisms and provide new avenues for therapeutic developments.

ABSTRACT Background Inclusion body myositis (IBM) is the most prevalent muscle disease in adults for which no current treatment exists. The pathogenesis of IBM remains poorly defined. In this study, we aimed to explore the interplay between inflammation and mitochondrial dysfunction in IBM. Methods The study population consisted of 38 IBM patients and 22 age‐ and sex‐matched controls without a myopathy. Mean age was 62.9 years (SD = 9) in IBM group and 59.7 (10) in controls. Bulk RNA sequencing, Meso Scale Discovery electrochemiluminescence (ECL), western blotting, histochemistry and immunohistochemistry were performed on frozen muscle samples from the study participants. Results We demonstrated activation of the NLRP3 inflammasome in IBM muscle samples, with the NLRP3 inflammasome being the most upregulated pathway on RNA sequencing, along with increased expression of NLRP3 and ASC proteins in IBM group. NLRP3 RNA levels most strongly correlated with TLR7 (correlation coefficient ρ = 0.91) and complement activation‐related genes, and inversely correlated with several mitochondria‐related genes among others. On muscle histopathology, there was increased NRLP3 immunoreactivity in both inflammatory cells and muscle fibres. Mitophagy is critical for removing damaged mitochondria and preventing the formation of a vicious cycle of mitochondrial dysfunction—NLRP3 inflammasome activation. Herein, we showed altered mitophagy, as witnessed by the elevated levels of p‐S65‐Ubiquitin, a mitophagy marker, in muscle lysates from IBM patients compared to controls (median of 114.3 vs. 81.25 ECL units, p = 0.005). The p‐S65‐Ubiquitin levels were most significantly elevated in IBM males compared to male controls (136 vs. 83.5 ECL units; p = 0.013), whereas IBM females had milder nonsignificant elevation compared to female controls (97.25 vs. 69 ECL units, p = 0.31). On muscle histopathology, p‐S65‐Ubiquitin aggregates accumulated in muscle fibres that were mostly Type 2 and devoid of cytochrome‐c‐oxidase reactivity. NLRP3 RNA levels correlated with p‐S65‐Ubiquitin levels in both sexes (males: ρ = 0.48, females: ρ = 0.54) but with loss of muscle strength, as reflected by the manual motor test score, only in males (males: ρ = 0.62, females: ρ = −0.14). Lastly, we identified sex‐specific molecular pathways in IBM. Females had upregulation of pathways related to response to stress, which could conceivably offset some of the pathomechanisms of IBM, while males had upregulation of pathways related to cell adhesion and migration. Conclusions There is activation of the NLRP3 inflammasome in IBM, along with altered mitophagy, particularly in males, which is of potential therapeutic significance. These findings suggest sex‐specific mechanisms in IBM that warrant further investigation.

Abstract INTRODUCTION Early‐onset Alzheimer's disease (EOAD) manifests prior to the age of 65, and affects 4%–8% of patients with Alzheimer's disease (AD). The current analyses sought to examine longitudinal cognitive trajectories of participants with early‐onset dementia. METHODS Data from 307 cognitively normal (CN) volunteer participants and those with amyloid‐positive EOAD or amyloid‐negative cognitive impairment (EOnonAD) were compared. Cognitive trajectories across a comprehensive cognitive battery spanning 42 months were examined using mixed‐effects modeling. RESULTS The EOAD group displayed worse cognition at baseline relative to EOnonAD and CN groups, and more aggressive declines in cognition over time. The largest effects were observed on measures of executive functioning domains, while memory declines were blunted in EOAD. DISCUSSION EOAD declined 2–4× faster than EOnonAD, and EOAD pathology is not restricted to memory networks. Early identification of deficits is critical to ensure that individuals with sporadic EOAD can be considered for treatment using disease‐modifying medications. Highlights Represents the most comprehensive longitudinal characterization of sporadic EOAD to date. The trajectory of cognitive declines was steep for EOAD participants and worse than for other groups. Executive functioning measures exhibited the greatest declines over time in EOAD.

Abstract INTRODUCTION Early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD) share similar amyloid etiology, but evidence from smaller‐scale studies suggests that they manifest differently clinically. Current analyses sought to contrast the cognitive profiles of EOAD and LOAD. METHODS Z‐ score cognitive‐domain composites for 311 amyloid‐positive sporadic EOAD and 314 amyloid‐positive LOAD participants were calculated from baseline data from age‐appropriate control cohorts. Z‐ score composites were compared between AD groups for each domain. RESULTS After controlling for cognitive status, EOAD displayed worse visuospatial, executive functioning, and processing speed/attention skills relative to LOAD, and LOAD displayed worse language, episodic immediate memory, and episodic delayed memory. DISCUSSION Sporadic EOAD possesses distinct cognitive profiles relative to LOAD. Clinicians should be alert for non‐amnestic impairments in younger patients to ensure proper identification and intervention using disease‐modifying treatments. Highlights Both early‐onset Alzheimer's disease (EOAD) and late‐onset Alzheimer's disease (LOAD) participants displayed widespread cognitive impairments relative to their same‐aged peers. Cognitive impairments were more severe for EOAD than for LOAD participants in visuospatial and executive domains. Memory and language impairments were more severe for LOAD than for EOAD participants Results were comparable after removing clinical phenotypes of posterior cortical atrophy (PCA), primary progressive aphasia (lv‐PPA), and frontal‐variant AD.

Abstract Introduction Incorporation of mammographic density to breast cancer risk models could improve risk stratification to tailor screening and prevention strategies according to risk. Robust evaluation of the value of adding mammographic density to models with comprehensive information on questionnaire-based risk factors and polygenic risk score is needed to determine its effectiveness in improving risk stratification of such models. Methods We used the Individualized Coherent Absolute Risk Estimator (iCARE) tool for risk model building and validation to incorporate density to a previously validated literature-based model with questionnaire-based risk factors and a 313-variant polygenic risk score (PRS). The model was evaluated for calibration and discrimination in three prospective cohorts of European-ancestry women (1,468 cases, 19,104 controls): US-based Nurses’ Health Study (NHS I and II) and Mayo Mammography Health Study (MMHS); and Sweden-based Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) study. Analyses were done separately for women younger (NHS II, KARMA) and older than 50 years (NHS I, MMHS, KARMA). Improvements in terms of risk stratification and reclassification proportions were assessed among European-ancestry women aged 50–70 years in US and Sweden. Results For women younger and older than 50 years, the model with questionnaire-based risk factors, PRS and density was generally well calibrated across risk with some evidence of miscalibration at the extremes of the risk distribution. Incorporation of density led to modest improvements risk discrimination beyond the model with questionnaire-based risk factors and PRS: the area under the curve (AUC) among younger women was 67.0% (95% CI: 63.5–70.6%) vs. 65.6% (95% CI: 61.9–69.3%) for models with and without density; and 66.1% (95% CI 64.4–67.8%) vs. 65.5% (95% CI: 63.8–67.2%) among older women. The model with density identified 18.4% of US women 50–70 years old ≥ 3% 5-year predicted risk (threshold used for recommending risk-reducing medication in the US), with 42.4% of future cases expected to occur in this group. At this threshold, 7.9% of US women were reclassified by adding density to the model, resulting in the identification of 2.8% of additional future cases. The model with density identified 10.3% of Swedish women ≥ 3% 5-year predicted risk, with 29.4% of future cases expected to occur in this group. At this threshold, 5.3% of women were reclassified with the addition of density, leading to the identification of an additional 4.4% of future cases. Conclusion Integrating density with questionnaire-based risk factors and PRS could potentially identify more women of European-ancestry with elevated risk of breast cancer in the United States and Sweden. Further investigations of the integrated model in non-European ancestry populations are needed prior to considering clinical applications.

Background: A retear after anterior cruciate ligament (ACL) reconstruction remains a common and devastating complication. Knee bone morphology is associated with the risk of ACL injuries, ACL retears, and osteoarthritis, and a combination of tools that derive bone shape from clinical imaging, such as magnetic resonance imaging (MRI) and statistical shape modeling, could identify patients at risk of developing these joint conditions. Purpose: To identify bone shape features before primary ACL reconstruction in patients with an eventual retear compared to those with a known intact ACL graft. Study Design: Case-control study; Level of evidence, 3. Methods: Bone was automatically segmented on 2-dimensional proton density–weighted MRI of the knee in patients at the time of the initial ACL injury using deep convolutional neural networks. Patients with a subsequent retear after reconstruction within 3 years (22 femurs, 19 tibias) were compared with those with an intact ACL graft at 3 years (20 femurs, 22 tibias) using statistical shape modeling to identify preoperative bone shape features predictive of a retear after ACL reconstruction. Results: Statistical shape modeling revealed 2 specific bone shape features (modes) in the femur and 1 mode in the tibia that demonstrated significant differences at the time of the initial injury in patients with subsequent retears. In the femur, a narrower intercondylar notch width, a widened medial condylar width, an increased femoral condylar offset ratio, increased surface area along the lateral femoral condyle relative to the medial condyle, and a more prominent trochlear sulcus at the time of the initial injury were associated with retears after ACL reconstruction. In the tibia, a diminished ACL facet prominence, a squared lateral and medial tibial plateaus, and a broader and flattened tibial spine at the time of the initial injury were associated with retears after ACL reconstruction. Conclusion: Using the automatic bone segmentation pipeline on preoperative MRI, the authors identified bone shape features associated with a retear after ACL reconstruction. The use of this pipeline enables large-scale studies of bone shape on MRI and could predict patients at risk of ACL retears to alter treatment decisions.