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  • 1
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 2 ( 2023-01-10)
    Abstract: The gap between chronological age (CA) and biological brain age, as estimated from magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging deviate from their typical trajectories. MRI-derived brain age (BA) estimates are often obtained using deep learning models that may perform relatively poorly on new data or that lack neuroanatomic interpretability. This study introduces a convolutional neural network (CNN) to estimate BA after training on the MRIs of 4,681 cognitively normal (CN) participants and testing on 1,170 CN participants from an independent sample. BA estimation errors are notably lower than those of previous studies. At both individual and cohort levels, the CNN provides detailed anatomic maps of brain aging patterns that reveal sex dimorphisms and neurocognitive trajectories in adults with mild cognitive impairment (MCI, N  = 351) and Alzheimer’s disease (AD, N  = 359). In individuals with MCI (54% of whom were diagnosed with dementia within 10.9 y from MRI acquisition), BA is significantly better than CA in capturing dementia symptom severity, functional disability, and executive function. Profiles of sex dimorphism and lateralization in brain aging also map onto patterns of neuroanatomic change that reflect cognitive decline. Significant associations between BA and neurocognitive measures suggest that the proposed framework can map, systematically, the relationship between aging-related neuroanatomy changes in CN individuals and in participants with MCI or AD. Early identification of such neuroanatomy changes can help to screen individuals according to their AD risk.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    RVK:
    RVK:
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2023
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  • 2
    In: Brain, Oxford University Press (OUP), Vol. 147, No. 4 ( 2024-04-04), p. 1497-1510
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0006-8950 , 1460-2156
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    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2024
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  • 3
    In: Journal of the Royal Statistical Society Series B: Statistical Methodology, Oxford University Press (OUP), ( 2024-03-22)
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 1369-7412 , 1467-9868
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2024
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  • 4
    In: Brain, Oxford University Press (OUP), Vol. 147, No. 5 ( 2024-05-03), p. 1680-1695
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0006-8950 , 1460-2156
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    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2024
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  • 5
    In: Brain, Oxford University Press (OUP), Vol. 146, No. 9 ( 2023-09-01), p. 3719-3734
    Abstract: Mechanisms of resilience against tau pathology in individuals across the Alzheimer’s disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer’s disease dementia with baseline 18F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = −0.062, P = 0.032), higher education level (Stβinteraction = −0.072, P = 0.011) and higher intracranial volume (Stβinteraction = −0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer’s disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences.
    Type of Medium: Online Resource
    ISSN: 0006-8950 , 1460-2156
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    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
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  • 6
    In: Journal of Instrumentation, IOP Publishing, Vol. 17, No. 01 ( 2022-01-01), p. P01013-
    Abstract: The semiconductor tracker (SCT) is one of the tracking systems for charged particles in the ATLAS detector. It consists of 4088 silicon strip sensor modules. During Run 2 (2015–2018) the Large Hadron Collider delivered an integrated luminosity of 156 fb -1 to the ATLAS experiment at a centre-of-mass proton-proton collision energy of 13 TeV. The instantaneous luminosity and pile-up conditions were far in excess of those assumed in the original design of the SCT detector. Due to improvements to the data acquisition system, the SCT operated stably throughout Run 2. It was available for 99.9% of the integrated luminosity and achieved a data-quality efficiency of 99.85%. Detailed studies have been made of the leakage current in SCT modules and the evolution of the full depletion voltage, which are used to study the impact of radiation damage to the modules.
    Type of Medium: Online Resource
    ISSN: 1748-0221
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 2022
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  • 7
    In: JAMA Network Open, American Medical Association (AMA), Vol. 6, No. 7 ( 2023-07-13), p. e2323349-
    Abstract: Current data identifying COVID-19 risk factors lack standardized outcomes and insufficiently control for confounders. Objective To identify risk factors associated with COVID-19, severe COVID-19, and SARS-CoV-2 infection. Design, Setting, and Participants This secondary cross-protocol analysis included 4 multicenter, international, randomized, blinded, placebo-controlled, COVID-19 vaccine efficacy trials with harmonized protocols established by the COVID-19 Prevention Network. Individual-level data from participants randomized to receive placebo within each trial were combined and analyzed. Enrollment began July 2020 and the last data cutoff was in July 2021. Participants included adults in stable health, at risk for SARS-CoV-2, and assigned to the placebo group within each vaccine trial. Data were analyzed from April 2022 to February 2023. Exposures Comorbid conditions, demographic factors, and SARS-CoV-2 exposure risk at the time of enrollment. Main Outcomes and Measures Coprimary outcomes were COVID-19 and severe COVID-19. Multivariate Cox proportional regression models estimated adjusted hazard ratios (aHRs) and 95% CIs for baseline covariates, accounting for trial, region, and calendar time. Secondary outcomes included severe COVID-19 among people with COVID-19, subclinical SARS-CoV-2 infection, and SARS-CoV-2 infection. Results A total of 57 692 participants (median [range] age, 51 [18-95] years; 11 720 participants [20.3%] aged ≥65 years; 31 058 participants [53.8%] assigned male at birth) were included. The analysis population included 3270 American Indian or Alaska Native participants (5.7%), 7849 Black or African American participants (13.6%), 17 678 Hispanic or Latino participants (30.6%), and 40 745 White participants (70.6%). Annualized incidence was 13.9% (95% CI, 13.3%-14.4%) for COVID-19 and 2.0% (95% CI, 1.8%-2.2%) for severe COVID-19. Factors associated with increased rates of COVID-19 included workplace exposure (high vs low: aHR, 1.35 [95% CI, 1.16-1.58]; medium vs low: aHR, 1.41 [95% CI, 1.21-1.65] ; P   & amp;lt; .001) and living condition risk (very high vs low risk: aHR, 1.41 [95% CI, 1.21-1.66]; medium vs low risk: aHR, 1.19 [95% CI, 1.08-1.32] ; P   & amp;lt; .001). Factors associated with decreased rates of COVID-19 included previous SARS-CoV-2 infection (aHR, 0.13 [95% CI, 0.09-0.19]; P   & amp;lt; .001), age 65 years or older (aHR vs age & amp;lt;65 years, 0.57 [95% CI, 0.50-0.64]; P   & amp;lt; .001) and Black or African American race (aHR vs White race, 0.78 [95% CI, 0.67-0.91]; P  = .002). Factors associated with increased rates of severe COVID-19 included race (American Indian or Alaska Native vs White: aHR, 2.61 [95% CI, 1.85-3.69]; multiracial vs White: aHR, 2.19 [95% CI, 1.50-3.20] ; P   & amp;lt; .001), diabetes (aHR, 1.54 [95% CI, 1.14-2.08]; P  = .005) and at least 2 comorbidities (aHR vs none, 1.39 [95% CI, 1.09-1.76]; P  = .008). In analyses restricted to participants who contracted COVID-19, increased severe COVID-19 rates were associated with age 65 years or older (aHR vs & amp;lt;65 years, 1.75 [95% CI, 1.32-2.31]; P   & amp;lt; .001), race (American Indian or Alaska Native vs White: aHR, 1.98 [95% CI, 1.38-2.83]; Black or African American vs White: aHR, 1.49 [95% CI, 1.03-2.14] ; multiracial: aHR, 1.81 [95% CI, 1.21-2.69]; overall P  = .001), body mass index (aHR per 1-unit increase, 1.03 [95% CI, 1.01-1.04]; P  = .001), and diabetes (aHR, 1.85 [95% CI, 1.37-2.49]; P   & amp;lt; .001). Previous SARS-CoV-2 infection was associated with decreased severe COVID-19 rates (aHR, 0.04 [95% CI, 0.01-0.14]; P   & amp;lt; .001). Conclusions and Relevance In this secondary cross-protocol analysis of 4 randomized clinical trials, exposure and demographic factors had the strongest associations with outcomes; results could inform mitigation strategies for SARS-CoV-2 and viruses with comparable epidemiological characteristics.
    Type of Medium: Online Resource
    ISSN: 2574-3805
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2023
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  • 8
    In: Cell Reports, Elsevier BV, Vol. 23, No. 1 ( 2018-04), p. 270-281.e3
    Type of Medium: Online Resource
    ISSN: 2211-1247
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2018
    detail.hit.zdb_id: 2649101-1
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  • 9
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 39 ( 2016-09-27)
    Abstract: Complex physiological and behavioral traits, including neurological and psychiatric disorders, often associate with distributed anatomical variation. This paper introduces a global metric, called morphometricity, as a measure of the anatomical signature of different traits. Morphometricity is defined as the proportion of phenotypic variation that can be explained by macroscopic brain morphology. We estimate morphometricity via a linear mixed-effects model that uses an anatomical similarity matrix computed based on measurements derived from structural brain MRI scans. We examined over 3,800 unique MRI scans from nine large-scale studies to estimate the morphometricity of a range of phenotypes, including clinical diagnoses such as Alzheimer’s disease, and nonclinical traits such as measures of cognition. Our results demonstrate that morphometricity can provide novel insights about the neuroanatomical correlates of a diverse set of traits, revealing associations that might not be detectable through traditional statistical techniques.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2016
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    detail.hit.zdb_id: 1461794-8
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  • 10
    In: Annals of Internal Medicine, American College of Physicians, Vol. 175, No. 7 ( 2022-07), p. 952-960
    Type of Medium: Online Resource
    ISSN: 0003-4819 , 1539-3704
    RVK:
    Language: English
    Publisher: American College of Physicians
    Publication Date: 2022
    detail.hit.zdb_id: 2003473-8
    detail.hit.zdb_id: 336-0
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