Biology subjects

Mormino, E. C.

Publications and source records attributed to Mormino, E. C..

15 recordsLinked to original sources

bioRxiv2026

Continuous amyloid staging complements global amyloid burden in early Alzheimer's disease

Introduction: Early Alzheimer's disease (AD) staging remains challenging because clinical categories and global amyloid PET measures provide only coarse characterization of disease progression. We developed a continuous amyloid staging score from regional amyloid PET to complement global amyloid burden. Methods: Using longitudinal florbetapir PET from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we trained an end-to-end deep learning model to directly estimate a continuous amyloid staging score. We evaluated longitudinal consistency, its relationship with global amyloid burden, regional contributors to early-stage variation, and whether the staging score stratified subsequent memory decline among participants matched for baseline global amyloid burden. Cognitive analyses were replicated in A4+LEARN. Results: The staging score better preserved longitudinal visit order than existing amyloid staging approaches. During early disease stages, it captured regional amyloid variation despite relatively stable global amyloid burden. Among participants with similar baseline global amyloid burden, higher staging scores were associated with faster subsequent memory decline in both ADNI and A4+LEARN. Discussion: A continuous amyloid staging score complements global amyloid burden for early AD staging and cognitive risk stratification. Keywords: Alzheimer's disease; amyloid PET; disease staging; cognitive decline

neuroscience↗

bioRxiv2026

Unlocking Sensitive Data with SPHERE in the Age of AI

Sensitive human data underpin discoveries across medicine, biology and the social sciences, yet privacy regulation often prevents sharing them with collaborators or artificial intelligence (AI) systems. We introduce SPHERE, a model-free method that makes sensitive datasets directly usable by AI and shareable for open science as a synthetic twin, while the original records never leave the local environment. Across 33 datasets spanning five scientific domains, SPHERE protects individual privacy against adversarial re-identification attacks while preserving the data's statistical structure: means, variances and correlations are reproduced exactly, effect size and P value in linear statistical analysis is numerically identical, nonlinear machine-learning utility is retained, and each twin is generated in seconds on a laptop. Frontier AI agents running on the twin reach the same scientific conclusions as on the original records. Analyses of the twin reproduce genome- and proteome-wide results at UK Biobank scale and recover the findings of landmark studies across three independent cohorts and consortia. The approach also extends to deep-learning embeddings across language, vision and time-series, with minimal utility loss. We make the Stanford Alzheimer's Disease Research Center cohort openly available for the first time, as a SPHERE twin spanning nine modalities that any registered researcher can analyze without an approval process. We release SPHERE with certification of each twin's privacy and fidelity, and an AI agent that autonomously executes research tasks on sensitive data without ever accessing it. Sensitive datasets that are currently closed to research could thus become routine inputs to open science and AI to enable key discoveries.

bioinformatics↗

bioRxiv2026

Dissociable structural and molecular pathways of age-related change in sustained attention

Sustained attention, the capacity to maintain goal-directed attention over extended periods, declines with age but with substantial individual variability across cognitively unimpaired (CU) older adults. We sought to determine the contributions of microstructural deterioration of the superior longitudinal fasciculus (SLF), the principal white-matter tract coupling prefrontal and parietal nodes of the dorsal attention network, as well as markers of preclinical Alzheimers disease (AD) to individual differences in sustained attention in ageing. In 162 CU older adults (mean (SD) age = 73.0 (4.9), %F = 64.8) drawn from two Stanford ageing cohorts, we measured sustained attention using the gradual-onset Continuous Performance Task (gradCPT). Performance was indexed by a composite score (Att-Z) derived from discriminability (d') and response-time variability (RTV). We used diffusion MRI tractography to quantify SLF fractional anisotropy (FA) and mean diffusivity (MD) alongside two control tracts, the corticospinal tract (CST) and cingulum (CGC). NULISA multiplex plasma immunoassays were used to measured AD-related pathology (pTau-181, pTau-217), neuroaxonal injury (NfL), and astrocytic reactivity (GFAP; plasma subsample N = 146). Parallel mediation and commonality analyses tested whether structural and plasma biomarker pathways contribute independently to individual differences in sustained attention function. Older age was associated with lower Att-Z ({beta} = -0.315, p < 0.001). In simultaneous three-tract regression models, only SLF microstructure uniquely predicted Att-Z (FA: {beta} = +0.275, p < 0.001; MD: {beta} = -0.320, p < 0.001). SLF microstructure mediated the age-attention relationship (FA indirect {beta}unstandardised = -0.01, pboot <0.01, MD indirect {beta}unstandardised = -0.009 to -0.01, pboot <0.05). Plasma pTau-181 ({beta} = -0.212, pFDR < 0.03), pTau-217 ({beta} = -0.163, pFDR < 0.05), and NfL ({beta} = -0.156, pFDR < 0.05) were negatively associated with Att-Z and each mediated effects of age on performance (pTau-181 indirect {beta}unstandardised = -0.008, pboot < 0.01; pTau-217 indirect {beta}unstandardised= -0.006, pboot< 0.05; NfL indirect {beta}unstandardised = -0.011, pboot< 0.05), whereas GFAP showed no association with sustained attention in any model. SLF microstructure was negatively associated with age (FA {beta} = -0.207, p < 0.01; MD {beta} = +0.270, p < 0.001) but was not significantly associated with plasma biomarkers (all p > 0.10). In parallel mediation models, SLF microstructure and plasma pTau exhibited significant independent indirect effects on Att-Z (SLF FA indirect {beta}unstandardised= -0.010, pboot< 0.01; SLF MD indirect {beta}unstandardised = -0.009 to -0.010, pboot< 0.05; pTau-181 indirect {beta}unstandardised = -0.008 to -0.009, pboot< 0.01; pTau-217 indirect {beta}unstandardised= -0.006 to -0.007, pboot< 0.05). Effects of NfL were attenuated when combined in a model with pTau (indirect {beta}unstandardised = -0.005 to -0.008, pboot> 0.15), suggesting shared variance among these markers. These findings reveal multiple pathways that contribute to individual differences in sustained attention in ageing that are detectable before clinical impairment, including SLF white matter integrity -- which is linked to the structural disconnection of the dorsal attention network -- and preclinical AD pathology. The independence of these pathways identifies two separable biological targets for preserving attentional capacity in CU older adults.

neuroscience↗

bioRxiv2026

Blood-brain barrier dysfunction predicts cognitive trajectory after ischemic stroke

Ischemic stroke doubles the risk of dementia.1-4 Stroke severity and location affect cognition early,5,6 but late dementia risk is not related to infarct characteristics, nor is it reduced by preventing additional strokes,3,6,7 and its mechanism is unknown. We identified a plasma proteomic signature of chronic stroke that was consistent with blood-brain barrier (BBB) dysfunction, including a 58% decrease in plasma levels of platelet-derived growth factor B and downregulation of its pathway compared to healthy controls. During 2 years of follow-up, the stroke-specific proteome was accentuated in stroke survivors who subsequently declined in the processing speed/executive function cognitive domain. To test BBB function, we performed dynamic contrast-enhanced MRI 6-9 months after stroke in an additional cohort and found 1.7-fold higher whole brain BBB leakage compared to controls. Finally, we compared autopsy tissue from people with infarcts and dementia at death to those with infarcts and no dementia. Those who died with dementia had dramatic loss of vascular mural cell coverage compared to those without dementia (median 0.7% vs. 27%). Thus, our proteomic, functional, and structural data implicate chronic BBB dysfunction in cognitive decline late after stroke, revealing potential proteomic and imaging biomarkers and, importantly, a novel target for intervention.

neuroscience↗

bioRxiv2025

Evaluation of Deep Learning Algorithms to Predict Multiple Dementia-Related Neuropathologies from Brain MRI, Clinical and Genetic Data

Alzheimers disease and related dementias (ADRD) involve overlapping neurodegenerative and vascular pathologies--such as amyloid-{beta} (A{beta}), tau, cerebral amyloid angiopathy (CAA), TDP-43, and alpha-synuclein--that complicate diagnosis and treatment. While PET and CSF biomarkers are useful for detecting A{beta} and tau, they are invasive, expensive, and not widely available. In contrast, magnetic resonance imaging (MRI) is non-invasive and widely accessible, offering an opportunity for pathology prediction when combined with deep learning. Most prior studies have focused on single-pathology detection, but there remains a need for models that can jointly predict multiple co-occurring pathologies. In this work, we evaluate deep learning models that integrate structural MRI with demographic, clinical, and genetic data to classify six autopsy-confirmed neuropathologies: A{beta}, tau, CAA, TDP-43, hippocampal sclerosis, and dementia with Lewy bodies. We compare our hybrid deep learning model to AutoGluon, an automated machine learning framework. Our findings support the potential of multimodal AI to enable non-invasive, comprehensive neuropathological profiling in ADRD.

neuroscience↗

bioRxiv2025

Synergistic effects of APOE ϵ4 and Alzheimer's pathology on the neural correlates of episodic remembering in cognitively unimpaired older adults

Amyloid-{beta} (A{beta}) and tau pathology begin accumulating decades before clinical symptoms and are influenced by APOE {varepsilon}4, a key genetic risk factor for Alzheimers disease (AD). Although the presence of A{beta}, tau, and APOE {varepsilon}4 are thought to impact brain function, their effects on the neural correlates of episodic memory retrieval in preclinical AD remains unknown. We investigated this question in 159 cognitively unimpaired older adults (mean age, 68.9{+/-}5.8 years; 57% female) in the Stanford Aging and Memory Study. Participants completed an associative memory task concurrent with functional MRI. A{beta} was measured using CSF A{beta}42/A{beta}40 or Florbetaben-PET imaging and tau was measured using CSF pTau181. Hippocampal univariate activity and cortical reinstatement - that is, reinstatement of patterns of neocortical activity that were present during memory encoding - were measured during successful memory retrieval. Analyses revealed that APOE {varepsilon}4 was independently associated with greater A{beta} and tau burden, and that associations of AD biomarkers with brain function and memory were moderated by APOE {varepsilon}4. Among APOE {varepsilon}4 non-carriers, A{beta} burden was linked to a pattern of hippocampal hyperactivity. Among APOE {varepsilon}4 carriers, CSF pTau181 was linked to weaker cortical reinstatement during memory retrieval and lower memory performance. Thus, abnormal AD biomarkers and genetic risk synergistically impact neural and behavioral expressions of memory in preclinical AD. These findings highlight the critical role of APOE {varepsilon}4 in moderating effects of AD pathology on brain function and identify candidate mechanisms that may contribute to increased risk of memory impairment in preclinical AD. Significance StatementHippocampus-dependent cortical reinstatement is a critical mechanism supporting episodic remembering that contributes to individual differences in memory performance in older adults. However, the contribution of early Alzheimers disease (AD) pathology to variability in this mechanism is unknown. We demonstrate that associations of AD biomarkers with hippocampal activity and cortical reinstatement are moderated by APOE {varepsilon}4 in cognitively unimpaired older adults. Amyloid-{beta}-related hyperactivity was observed in the hippocampus among APOE {varepsilon}4 non-carriers, while CSF pTau181 was linked to weaker cortical reinstatement during memory retrieval and lower memory performance among APOE {varepsilon}4 carriers. Our findings highlight synergistic effects of APOE and AD pathology on brain function and identify candidate mechanisms that may underlie increased risk of memory impairment in preclinical AD.

neuroscience↗

bioRxiv2024

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

Structured AbstractO_ST_ABSINTRODUCTIONC_ST_ABSThe effects of sex, race, and Apolipoprotein E (APOE) - Alzheimers disease (AD) risk factors - on white matter integrity are not well characterized. METHODSDiffusion MRI data from nine well-established longitudinal cohorts of aging were free-water (FW)-corrected and harmonized. This dataset included 4,702 participants (age=73.06 {+/-} 9.75) with 9,671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FAFWcorr) were used to assess differences in white matter microstructure by sex, race, and APOE-{varepsilon}4 carrier status. RESULTSSex differences in FAFWcorr in association and projection tracts, racial differences in FAFWcorr in projection tracts, and APOE-{varepsilon}4 differences in FW limbic and occipital transcallosal tracts were most pronounced. DISCUSSIONThere are prominent differences in white matter microstructure by sex, race, and APOE- {varepsilon}4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted. HighlightsO_LISex, race, and APOE-{varepsilon}4 carrier status relate to white matter microstructural integrity C_LIO_LIFemales generally have lower FAFWcorr compared to males C_LIO_LINon-Hispanic Black adults generally have lower FAFWcorr than non-Hispanic White adults C_LIO_LIAPOE-{varepsilon}4 carriers tended to have higher FW than non-carriers C_LI Research in Context Systematic ReviewThe authors used PubMed and Google Scholar to review literature that used conventional and free-water (FW)-corrected microstructural metrics to evaluate sex, race, and APOE-{varepsilon}4 differences in white matter microstructure. While studies have previously explored differences by sex and APOE-{varepsilon}4 status, less is known about racial differences and no large-scale FW-corrected analysis has been performed. InterpretationSex and race were more associated with FAFWcorr while APOE-{varepsilon}4 status was associated with FW metrics. Association, projection, limbic, and occipital transcallosal tracts showed the greatest differences. Future DirectionFuture studies to determine the biological and social pathways that lead to sex, racial, and APOE-{varepsilon}4 differences are warranted. Consent StatementAll participants provided informed consent in their respective cohort studies.

neuroscience↗

bioRxiv2024

Medial amygdalar tau is associated with anxiety symptoms in preclinical Alzheimer's disease

BACKGROUNDWhile the amygdala receives early tau deposition in Alzheimers disease (AD) and is involved in social and emotional processing, the relationship between amygdalar tau and early neuropsychiatric symptoms in AD is unknown. We sought to determine whether focal tau binding in the amygdala and abnormal amygdalar connectivity were detectable in a preclinical AD cohort and identify relationships between these and self-reported mood symptoms. METHODSWe examined n=598 individuals (n=347 amyloid-positive (58% female), n=251 amyloid-negative (62% female); subset into tau PET and fMRI cohorts) from the A4 Study. In our tau PET cohort, we used amygdalar segmentations to examine representative nuclei from three functional divisions of the amygdala. We analyzed between-group differences in division-specific tau binding in the amygdala in preclinical AD. We conducted seed-based functional connectivity analyses from each division in the fMRI cohort. Finally, we conducted exploratory post-hoc correlation analyses between neuroimaging biomarkers of interest and anxiety and depression scores. RESULTSAmyloid-positive individuals demonstrated increased tau binding in medial and lateral amygdala (F(4, 442)=14.61, p=0.00045; F(4, 442)=5.83, p=0.024, respectively). Across amygdalar divisions, amyloid-positive individuals had relatively increased regional connectivity from amygdala to other temporal regions, insula, and orbitofrontal cortex. There was an interaction by amyloid group between tau binding in the medial and lateral amygdala and anxiety. Medial amygdala to retrosplenial connectivity negatively correlated with anxiety symptoms (rs=-0.103, p=0.015). CONCLUSIONSOur findings suggest that preclinical tau deposition in the amygdala may result in meaningful changes in functional connectivity which may predispose patients to mood symptoms.

neuroscience↗

bioRxiv2021

The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer's disease

Apolipoprotein E (APOE) polymorphic alleles are genetic factors associated with Alzheimers disease (AD) risk. Although previous studies have explored the link between AD genetic risk and static functional network connectivity (sFNC), to the best of our knowledge, no previous studies have evaluated the association between dynamic FNC (dFNC) and AD genetic risk. Here, we examined the link between sFNC, dFNC, and AD genetic risk with a reproducible, data-driven approach. We used rs-fMRI, demographic, and APOE data from cognitively normal individuals (N=894) between 42 to 95 years of age (mean = 70 years). We divided individuals into low, moderate, and high-risk groups. Using Pearson correlation, we calculated sFNC across seven brain networks. We also calculated dFNC with a sliding window and Pearson correlation. The dFNC windows were partitioned into three distinct states with k-means clustering. Next, we calculated the amount of time each subject spent in each state, called occupancy rate or OCR. We compared both sFNC and OCR, estimated from dFNC, across individuals with different genetic risk and found that both sFNC and dFNC are related to AD genetic risk. We found that higher AD risk reduces within-visual sensory network (VSN) sFNC and that individuals with higher AD risk spend more time in a state with lower within-VSN dFNC. Additionally, we found that AD genetic risk affects whole-brain sFNC and dFNC in women but not in men. In conclusion, we presented novel insights into the links between sFNC, dFNC, and AD genetic risk.

neuroscience↗

bioRxiv2021

Disrupted dynamic functional network connectivity among cognitive control networks in the progression of Alzheimer's disease

BackgroundAlzheimers disease (AD) is the most common age-related dementia that promotes a decline in memory, thinking, and social skills. The initial stages of dementia can be associated with mild symptoms, and symptom progression to a more severe state is heterogeneous across patients. Recent work has demonstrated the potential for functional network mapping to assist in the prediction of symptomatic progression. However, this work has primarily used static functional connectivity (sFC) from rs-fMRI. Recently, dynamic functional connectivity (dFC) has been recognized as a powerful advance in functional connectivity methodology to differentiate brain network dynamics between healthy and diseased populations. MethodsGroup independent component analysis was applied to extract 17 components within the cognitive control network (CCN) from 1385 individuals across varying stages of AD symptomology. We estimated dFC among 17 components within the CCN, followed by clustering the dFCs into 3 recurring brain states and then estimated a hidden Markov model and the occupancy rate for each subject. Finally, we investigated the link between CCN dFC connectivity features with AD progression. ResultsProgression of AD symptoms were associated with increases in connectivity within the middle frontal gyrus. Also, the AD with mild and severer symptoms showed less connectivity within the inferior parietal lobule and between this region with the rest of CCN. Finally, comparing with mild dementia, we found that the normal brain spends significantly more time in a state with lower within middle frontal gyrus connectivity and higher connectivity between the hippocampus and the rest of CCN, highlighting the importance of assessing the dynamics of brain connectivity in this disease. ConclusionOur results suggest that AD progress not only alters the CCN connectivity strength but also changes the temporal properties in this brain network. This suggests the temporal and spatial pattern of CCN as a biomarker that differentiates different stages of AD. Impact StatementBy assuming that functional connectivity is static over time, many of previous studies have ignored the brain dynamic in Alzheimers disease progression. Here, a longitudinal resting-state functional magnetic resonance imaging data are used to explore the temporal changes of functional connectivity in the cognitive control network in Alzheimers disease progression. The result of this study would increase our understanding about the underlying mechanisms of Alzheimers Disease and help in finding future treatment of this neurological disorder.

neuroscience↗

bioRxiv2020

Hippocampal and cortical mechanisms at retrieval explain variability in episodic remembering in older adults

Age-related episodic memory decline is characterized by striking heterogeneity across individuals. Hippocampal pattern completion is a fundamental process supporting episodic memory. Yet, the degree to which this mechanism is impaired with age, and contributes to variability in episodic memory, remains unclear. We combine univariate and multivariate analyses of fMRI data from a large cohort of cognitively normal older adults (N=100; 60-82 yrs) to measure hippocampal activity and cortical reinstatement during retrieval of trial-unique associations. Trial-wise analyses revealed that hippocampal activity predicted cortical reinstatement strength, and these two metrics of pattern completion independently predicted retrieval success. However, increased age weakened cortical reinstatement and its relationship to memory behaviour. Critically, individual differences in the strength of hippocampal activity and cortical reinstatement explained unique variance in performance across multiple assays of episodic memory. These results indicate that fMRI indices of hippocampal pattern completion explain within- and across-individual memory variability in older adults.

neuroscience↗

bioRxiv2019

A/T/N polygenic risk score for cognitive decline in old age

INTRODUCTIONWe developed a novel polygenic risk score (PRS) based on the A/T/N (amyloid plaques (A), phosphorylated tau tangles (T), and neurodegeneration (N)) framework and compared a PRS based on clinical AD diagnosis to assess which was a better predictor of cognitive decline. METHODSWe used summary statistics from genome wide association studies of cerebrospinal fluid amyloid-{beta} (A{beta}42) and phosphorylated-tau (ptau181), left hippocampal volume (LHIPV), and late-onset AD dementia to calculate PRS for 1181 participants in the Alzheimers Disease Neuroimaging Initiative (ADNI). Individual PRS were averaged to generate a composite A/T/N PRS. We assessed the association of PRS with baseline and longitudinal cognitive composites of executive function and memory. RESULTSThe A/T/N PRS showed superior predictive performance on AD biomarkers and executive function decline compared to the clinical AD PRS. DISCUSSIONResults suggest that integration of genetic risk across AD biomarkers may improve prediction of disease progression. Research in ContextO_ST_ABSSystematic ReviewC_ST_ABSAuthors reviewed relevant literature using PubMed and Google Scholar. Key studies that generated and validated polygenic risk scores (PRS) for clinical and pathologic AD were cited. PRS scores have been increasingly used in the literature but clinical utility continues to be questioned. InterpretationIn the current research landscape concerning PRS clinical utility in the AD space, there is room for model improvement and our hypothesis was that a PRS with integrated risk for AD biomarkers could yield a better model for cognitive decline. Future DirectionsThis study serves as proof-of-concept that encourages future study of integrated PRS across disease markers and utility in taking an A/T/N (amyloidosis, tauopathy and neurodegeneration) focused approach to genetic risk for cognitive decline and AD.

genomics↗

bioRxiv2019

Data-driven detection of latent atrophy factors related to phenotypical variants of posterior cortical atrophy

Posterior cortical atrophy is a clinical-radiological syndrome characterized by visual processing deficits and atrophy in posterior parts of the brain, most often caused by Alzheimers disease pathology. Recent consensus criteria describe four distinct phenotypical variants of posterior cortical atrophy defined by clinical and radiological features; i) object perception/occipitotemporal (ventral), ii) space perception/temporoparietal (dorsal), iii) non-visual/dominant parietal and iv) primary visual (caudal). We employed a data-driven approach to identify atrophy factors related to these proposed variants in a multi-center cohort of 119 individuals with posterior cortical atrophy (age: 64 SD 7, 38% male, MMSE: 21 SD 5, 71% amyloid-{beta} positive, 29% amyloid-{beta} status unknown). A Bayesian modelling framework based on latent Dirichlet allocation was used to compute four latent atrophy factors in accordance with the four proposed variants. The model uses standardized gray matter density images as input (adjusted for age, sex, intracranial volume, field strength and whole-brain gray matter volume) and provides voxelwise probabilistic maps for all atrophy factors, allowing every individual to express each factor to a degree without a priori classification. The model revealed four distinct yet partially overlapping atrophy factors; right-dorsal, right-ventral, left-ventral, and limbic. Individual participant profiles revealed that the vast majority of participants expressed multiple factors, rather than predominantly expressing a single factor. To assess the relationship between atrophy factors and cognition, neuropsychological test scores covering four posterior cortical atrophy-specific cognitive domains were assessed (object perception, space perception, non-visual parietal functions and primary visual processing) and we used general linear models to examine the association between atrophy factor expression and cognition. We found that object perception and primary visual processing were associated with atrophy that predominantly reflects the right-ventral factor. Furthermore, space perception was associated with atrophy that predominantly represents the right-ventral and right-dorsal factors. Similar to the atrophy factors, most participants had mixed clinical profiles with impairments across multiple domains. However, when selecting four participants with an isolated impairment, we observed atrophy patterns and factor expressions that were largely in accordance with the hypothesized variants. Taken together, our results indicate that variants of posterior cortical atrophy exist but these constitute phenotypical extremes and most individuals fall along a broad clinical-radiological spectrum, indicating that classification into four mutually exclusive variants is unlikely to be clinically useful.

neuroscience↗

bioRxiv2018

Multi-modal Latent Factor Exploration of Atrophy, Cognitive and Tau Heterogeneity in Typical Late-Onset Alzheimer’s Disease

Individuals with Alzheimers disease (AD) dementia exhibit significant heterogeneity across clinical symptoms, atrophy patterns, and spatial distribution of Tau deposition. Most previous studies of AD heterogeneity have focused on atypical clinical subtypes, defined subtypes with a single modality, or restricted their analyses to a priori brain regions and cognitive tests. Here, we considered a data-driven hierarchical Bayesian model to identify latent factors from atrophy patterns and cognitive deficits simultaneously, thus exploiting the rich dimensionality within each modality. Unlike most previous studies, our model allows each factor to be expressed to varying degrees within an individual, in order to reflect potential multiple co-existing pathologies.\n\nBy applying our model to ADNI-GO/2 AD dementia participants, we found three atrophy-cognitive factors. The first factor was associated with medial temporal lobe atrophy, episodic memory deficits and disorientation to time/place (\"MTL-Memory\"). The second factor was associated with lateral temporal atrophy and language deficits (\"Lateral Temporal-Language\"). The third factor was associated with atrophy in posterior bilateral cortex, and visuospatial executive function deficits (\"Posterior Cortical-Executive\"). While the MTL-Memory and Posterior Cortical-Executive factors were discussed in previous literature, the Lateral Temporal-Language factor is novel and emerged only by considering atrophy and cognition jointly. Several analyses were performed to ensure generalizability, replicability and stability of the estimated factors. First, the factors generalized to new participants within a 10-fold cross-validation of ADNI-GO/2 AD dementia participants. Second, the factors were replicated in an independent ADNI-1 AD dementia cohort. Third, factor loadings of ADNI-GO/2 AD dementia participants were longitudinally stable, suggesting that these factors capture heterogeneity across patients, rather than longitudinal disease progression. Fourth, the model outperformed canonical correlation analysis at capturing associations between atrophy patterns and cognitive deficits.\n\nTo explore the influence of the factors early in the disease process, factor loadings were estimated in ADNI-GO/2 mild cognitively impaired (MCI) participants. Although the associations between the atrophy patterns and cognitive profiles were weak in MCI compared to AD, we found that factor loadings were associated with inter-individual regional variation in Tau uptake. Taken together, these results suggest that distinct atrophy-cognitive patterns exist in typical Alzheimers disease, and are associated with distinct patterns of Tau depositions before clinical dementia emerges.\n\nHighlightsO_LIBayesian model reveals 3 atrophy-cognitive factors in typical AD from ADNI-GO/2\nC_LIO_LIReplicated in independent ADNI-1 cohort; longitudinally stable within individuals\nC_LIO_LITriple cognitive dissociations among atrophy patterns suggest subtypes, not stages\nC_LIO_LIOutperforms canonical correlation analysis\nC_LIO_LIFactor loadings associated with spatial patterns of Tau uptake in MCI\nC_LI

neuroscience↗

bioRxiv2017

Polygenic hazard score: an enrichment marker for Alzheimer’s associated amyloid and tau deposition

BackgroundThere is an urgent need for the early identification of nondemented individuals at the highest risk of progressing to Alzheimers disease (AD) dementia for early therapeutic interventions. Our goal was to evaluate whether a recently validated polygenic hazard score (PHS) can be integrated with known in vivo CSF or PET biomarkers of amyloid or tau pathology to prospectively predict cognitive decline and clinical progression to AD dementia in nondemented older individuals.\n\nMethodsWe evaluated 347 cognitive normal (CN) and 599 mild cognitively impaired (MCI) individuals. We first investigated whether PHS can predict CSF or PET amyloid and tau deposition. We evaluated differences in positive and negative predictive values of biomarker status, as a function of PHS risk. Next, we used linear mixed-effects (LME) to examine if PHS and biomarker status in conjunction, best predict longitudinal cognitive and clinical progression. Lastly, we used survival analysis to investigate whether a combination of PHS and biomarker positivity predicts progression to AD dementia better than using PHS or biomarker positivity alone.\n\nFindingsIn CN and MCI individuals, we found that amyloid and total tau positivity systematically varies as a function of PHS. For individuals in greater than the 50th percentile PHS, the positive predictive value for amyloid approached 100%. Similarly, for individuals in less than the 25th percentile PHS, the negative predictive value for total tau approached 85%. Beyond APOE, high PHS individuals with amyloid and tau pathology showed the fastest rate of longitudinal cognitive decline and time to AD dementia progression. Among the CN subgroup, we similarly found that PHS was strongly associated with amyloid positivity and the combination of PHS and biomarker status significantly predicted longitudinal clinical progression.\n\nInterpretationAmong asymptomatic and mildly symptomatic older individuals, PHS considerably improves the predictive value of CSF or PET amyloid and tau biomarkers. Beyond APOE, PHS may be useful for risk stratification and cohort enrichment for MCI and preclinical AD therapeutic trials.

genetics↗