Faculty Bibliography

Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer's disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer's Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70-77% accuracy and 61-83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Neuropsychiatric symptoms (NPS) are common in older people with cognitive impairment and Alzheimer's disease (AD). No biomarkers to detect the related pathology or predict the clinical evolution of NPS are available yet. This study aimed to identify plasma proteins that may serve as biomarkers for NPS and NPS-related clinical disease progression. METHODS:A panel of 190 plasma proteins was quantified using Luminex xMAP in the Alzheimer's Disease Neuroimaging Initiative cohort. NPS and cognitive performance were assessed at baseline and after 1 and 2 years. Logistic regression, receiver operating characteristic analysis and cross-validation were used to address the relations of interest. RESULTS:A total of 507 participants with mild cognitive impairment (n=396) or mild AD dementia (n=111) were considered. Selected plasma proteins improved the prediction of NPS (area under the curve (AUC) from 0.61 to 0.76, p<0.001) and future NPS (AUC from 0.63 to 0.80, p<0.001) when added to a reference model. Distinct protein panels were identified for single symptoms. Among the selected proteins, ANGT, CCL1 and IL3 were associated with NPS at all three time points while CCL1, serum glutamic oxaloacetic transaminase and complement factor H were also associated with cognitive decline. The associations were independent of the presence of cerebral AD pathology as assessed using cerebrospinal fluid biomarkers. CONCLUSIONS:Plasma proteins are associated with NPS and improve prediction of future NPS.

White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating brain health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. Lesion network mapping (LNM) enables us to infer if brain networks are connected to lesions and could be a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed LNM to test the following hypotheses: (i) LNM-informed markers surpass WMH volumes in predicting cognitive performance; and (ii) WMH contributing to cognitive impairment map to specific brain networks. We analysed cross-sectional data of 3485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in four cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity to 480 atlas-based grey and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. We compared the capacity of total and regional WMH volumes and LNM scores in predicting cognitive function using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention/executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater connectivity to WMH, in grey and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Measures of WMH-related brain network connectivity significantly improve the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network integrity, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.

IMPORTANCE/UNASSIGNED:The lack of an in vivo measure for α-synuclein (α-syn) pathology until recently has limited thorough characterization of its brain atrophy pattern, especially during early disease stages. OBJECTIVE/UNASSIGNED:To assess the association of state-of-the-art cerebrospinal fluid (CSF) seed amplification assays (SAA) α-syn positivity (SAA α-syn+) with magnetic resonance imaging (MRI) structural measures, across the continuum from clinically unimpaired (CU) to cognitively impaired (CI) individuals, in 3 independent cohorts, and separately in CU and CI individuals, the latter reflecting a memory clinic population. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:Cross-sectional data were used from the Swedish BioFINDER-2 study (inclusion, 2017-2023) as the discovery cohort and the Swedish BioFINDER-1 study (inclusion, 2007-2015) and Alzheimer's Disease Neuroimaging Initiative (ADNI; inclusion 2005-2022) as replication cohorts. All cohorts are from multicenter studies, but the BioFINDER cohorts used 1 MRI scanner. CU and CI individuals fulfilling inclusion criteria and without missing data points in relevant metrics were included in the study. All analyses were performed from 2023 to 2024. EXPOSURES/UNASSIGNED:Presence of α-syn pathology, estimated by baseline CSF SAA α-syn. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The primary outcomes were cross-sectional structural MRI measures either through voxel-based morphometry (VBM) or regions of interest (ROI) including an automated pipeline for cholinergic basal forebrain nuclei CH4/4p (nucleus basalis of Meynert [NBM]) and CH1/2/3. Secondary outcomes were domain-specific cross-sectional cognitive measures. Analyses were adjusted for CSF biomarkers of Alzheimer pathology. RESULTS/UNASSIGNED:A total of 2961 participants were included in this study: 1388 (mean [SD] age, 71 [10] years; 702 female [51%]) from the BioFINDER-2 study, 752 (mean [SD] age, 72 [6] years; 406 female [54%]) from the BioFINDER-1 study, and 821 (mean [SD] age, 75 [8] years; 449 male [55%]) from ADNI. In the BioFINDER-2 study, VBM analyses in the whole cohort revealed a specific association between SAA α-syn+ and the cholinergic NBM, even when adjusting for Alzheimer copathology. ROI-based analyses in the BioFINDER-2 study focused on regions involved in the cholinergic system and confirmed that SAA α-syn+ was indeed independently associated with smaller NBM (β = -0.271; 95% CI, -0.399 to -0.142; P <.001) and CH1/2/3 volumes (β = -0.227; 95% CI, -0.377 to -0.076; P =.02). SAA α-syn+ was also independently associated with smaller NBM volumes in the separate CU (β = -0.360; 95% CI, -0.603 to -0.117; P =.03) and CI (β = -0.251; 95% CI, -0.408 to -0.095; P =.02) groups. Overall, the association between SAA α-syn+ and NBM volume was replicated in the BioFINDER-1 study and ADNI cohort. In CI individuals, NBM volumes partially mediated the association of SAA α-syn+ with attention/executive impairments in all cohorts (BioFINDER-2, β = -0.017; proportion-mediated effect, 7%; P =.04; BioFINDER-1, β = -0.096; proportion-mediated effect, 19%; P =.04; ADNI, β = -0.061; proportion-mediated effect, 20%; P =.007). CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this cohort study, SAA α-syn+ was consistently associated with NBM atrophy already during asymptomatic stages. Further, in memory clinic CI populations, SAA α-syn+ was associated with NBM atrophy, which partially mediated α-syn-induced attention/executive impairment.

We introduce a novel framework for the classification of functional data supported on nonlinear, and possibly random, manifold domains. The motivating application is the identification of subjects with Alzheimer's disease from their cortical surface geometry and associated cortical thickness map. The proposed model is based upon a reformulation of the classification problem as a regularized multivariate functional linear regression model. This allows us to adopt a direct approach to the estimation of the most discriminant direction while controlling for its complexity with appropriate differential regularization. Our approach does not require prior estimation of the covariance structure of the functional predictors, which is computationally prohibitive in our application setting. We provide a theoretical analysis of the out-of-sample prediction error of the proposed model and explore the finite sample performance in a simulation setting. We apply the proposed method to a pooled dataset from Alzheimer's Disease Neuroimaging Initiative and Parkinson's Progression Markers Initiative. Through this application, we identify discriminant directions that capture both cortical geometric and thickness predictive features of Alzheimer's disease that are consistent with the existing neuroscience literature.

Alzheimer's disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (-). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimer's disease. Here, we investigate whether genetic risk for Alzheimer's disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A-T- status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T- status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T- status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A-T- to A+T-, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70-4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84-1.42; P = 0.53). Conversely, for the transition from A+T- to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05-2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27-2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05-6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87-3.49; P = 0.12). The genetic risk for late-onset Alzheimer's disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of the transition between ATN stages and a better understanding of the molecular processes leading to Alzheimer's disease, in addition to opening therapeutic windows for targeted interventions.

Alzheimer's disease (AD) is a devastating disorder with a global prevalence estimated at 55 million people. In clinical studies administering certain anti-beta-amyloid (Aβ) antibodies, amyloid-related imaging abnormalities (ARIAs) have emerged as major adverse events. The frequency of these events is higher among apolipoprotein ε4 allele carriers (APOE4) compared to non-carriers. To reflect patients most at risk for vascular complications of anti-Aβ immunotherapy, we selected an APPswe/PS1dE9 transgenic mouse model bearing the human APOE4 gene (APPPS1:E4) and compared it with the same APP/PS1 mouse model bearing the human APOE3 gene (APOE ε3 allele; APPPS1:E3). Using histological and biochemical analyses, we characterized mice at three ages: 8, 12, and 16 months. Female and male mice were assayed for general cerebral fibrillar and pyroglutamate (pGlu-3) Aβ deposition, cerebral amyloid angiopathy (CAA), microhemorrhages, apoE and cholesterol composition, astrocytes, microglia, inflammation, lysosomal dysfunction, and neuritic dystrophy. Amyloidosis, lipid deposition, and astrogliosis increased with age in APPPS1:E4 mice, while inflammation did not reveal significant changes with age. In general, APOE4 carriers showed elevated Aβ, apoE, reactive astrocytes, pro-inflammatory cytokines, microglial response, and neuritic dystrophy compared to APOE3 carriers at different ages. These results highlight the potential of the APPPS1:E4 mouse model as a valuable tool in investigating the vascular side effects associated with anti-amyloid immunotherapy.

Insulin, insulin-like growth factors (IGF) and their receptors are highly expressed in the adult hippocampus. Thus, disturbances in the insulin-IGF signalling pathway may account for the selective vulnerability of the hippocampus to nascent Alzheimer's disease (AD) pathology. In the present study, we examined the predominant IGF-binding protein in the CSF, IGFBP2. CSF was collected from 109 asymptomatic members of the parental history-positive PREVENT-AD cohort. CSF levels of IGFBP2, core AD and synaptic biomarkers were measured using proximity extension assay, ELISA and mass spectrometry. Cortical amyloid-beta (Aβ) and tau deposition were examined using 18F-NAV4694 and flortaucipir. Cognitive assessments were performed during up to 8 years of follow-up, using the Repeatable Battery for the Assessment of Neuropsychological Status. T1-weighted structural MRI scans were acquired, and neuroimaging analyses were performed on pre-specified temporal and parietal brain regions. Next, in an independent cohort, we allocated 241 dementia-free ADNI-1 participants into four stages of AD progression based on the biomarkers CSF Aβ42 and total-tau (t-tau). In this analysis, differences in CSF and plasma IGFBP2 levels were examined across the pathological stages. Finally, IGFBP2 mRNA and protein levels were examined in the frontal cortex of 55 autopsy-confirmed AD and 31 control brains from the Quebec Founder Population (QFP) cohort, a unique population isolated from Eastern Canada. CSF IGFBP2 progressively increased over 5 years in asymptomatic PREVENT-AD participants. Baseline CSF IGFBP2 was positively correlated with CSF AD biomarkers and synaptic biomarkers, and negatively correlated with longitudinal changes in delayed memory (P = 0.024) and visuospatial abilities (P = 0.019). CSF IGFBP2 was negatively correlated at a trend-level with entorhinal cortex volume (P = 0.082) and cortical thickness in the piriform (P = 0.039), inferior temporal (P = 0.008), middle temporal (P = 0.014) and precuneus (P = 0.033) regions. In ADNI-1, CSF (P = 0.009) and plasma (P = 0.001) IGFBP2 were significantly elevated in Stage 2 [CSF Aβ(+)/t-tau(+)]. In survival analyses in ADNI-1, elevated plasma IGFBP2 was associated with a greater rate of AD conversion (hazard ratio = 1.62, P = 0.021). In the QFP cohort, IGFBP2 mRNA was reduced (P = 0.049); however, IGFBP2 protein levels did not differ in the frontal cortex of autopsy-confirmed AD brains (P = 0.462). Nascent AD pathology may induce an upregulation in IGFBP2 in asymptomatic individuals. CSF and plasma IGFBP2 may be valuable markers for identifying CSF Aβ(+)/t-tau(+) individuals and those with a greater risk of AD conversion.

Females are disproportionately affected by dementia due to Alzheimer's disease. Despite a similar amyloid-β (Aβ) load, a higher load of neurofibrillary tangles (NFTs) is seen in females than males. Previous literature has proposed that Aβ and phosphorylated-tau (p-tau) synergism accelerates tau tangle formation, yet the effect of biological sex in this process has been overlooked. In this observational study, we examined longitudinal neuroimaging data from the TRIAD and ADNI cohorts from Canada and USA, respectively. We assessed 457 participants across the clinical spectrum of Alzheimer's disease. All participants underwent baseline multimodal imaging assessment, including MRI and PET, with radioligands targeting Aβ plaques and tau tangles, respectively. CSF data were also collected. Follow-up imaging assessments were conducted at 1- and 2-year intervals for the TRIAD cohort and 1-, 2- and 4-year intervals for the ADNI cohort. The upstream pathological events contributing to faster tau progression in females were investigated-specifically, whether the contribution of Aβ and p-tau synergism to accelerated tau tangle formation is modulated by biological sex. We hypothesized that cortical Aβ predisposes tau phosphorylation and tangle accumulation in a sex-specific manner. Findings revealed that Aβ-positive females presented higher CSF p-tau181 concentrations compared with Aβ-positive males in both the TRIAD (P = 0.04, Cohen's d = 0.51) and ADNI (P = 0.027, Cohen's d = 0.41) cohorts. In addition, Aβ-positive females presented faster NFT accumulation compared with their male counterparts (TRIAD: P = 0.026, Cohen's d = 0.52; ADNI: P = 0.049, Cohen's d = 1.14). Finally, the triple interaction between female sex, Aβ and CSF p-tau181 was revealed as a significant predictor of accelerated tau accumulation at the 2-year follow-up visit (Braak I: P = 0.0067, t = 2.81; Braak III: P = 0.017, t = 2.45; Braak IV: P = 0.002, t = 3.17; Braak V: P = 0.006, t = 2.88; Braak VI: P = 0.0049, t = 2.93). Overall, we report sex-specific modulation of cortical Aβ in tau phosphorylation, consequently facilitating faster NFT progression in female individuals over time. This presents important clinical implications and suggests that early intervention that targets Aβ plaques and tau phosphorylation may be a promising therapeutic strategy in females to prevent the further accumulation and spread of tau aggregates.

Primary neuronal cultures are commonly used to study genetic and exogenous factors influencing neuronal development and maturation. During development, neurons undergo robust morphological changes involving expansion of dendritic arbor, formation of dendritic spines, and expression of synaptic proteins. In this chapter, we will cover methodological approaches allowing quantitative assessment of in vitro cultured neurons. Various quantitative characteristics of dendritic arbor can be derived based on immunostaining against anti-microtubule-associated protein 2 followed by dendrite tracing with the SNT plug-in of the FIJI software package. The number and subtypes of dendritic spines can be assessed by double labeling with DiI and Phalloidin iFluor448 followed by laser scanning confocal microscopy analysis. Finally, expression of presynaptic and postsynaptic proteins can be determined by immunohistochemistry and quantification using several available software packages including FIJI and Imaris, which also allows for 3D rendering and statistical displaying of the expression level of synaptic proteins.