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  • 1
    In: Brain, Oxford University Press (OUP), ( 2023-06-07)
    Kurzfassung: A clinical diagnosis of Alzheimer’s disease dementia (ADD) encompasses considerable pathological and clinical heterogeneity. While Alzheimer’s disease patients typically show a characteristic temporo-parietal pattern of glucose hypometabolism on 18F-fluorodeoxyglucose (FDG)-PET imaging, previous studies have identified a subset of patients showing a distinct posterior-occipital hypometabolism pattern associated with Lewy body pathology. Here, we aimed to improve the understanding of the clinical relevance of these posterior-occipital FDG-PET patterns in patients with Alzheimer’s disease-like amnestic presentations. Our study included 1214 patients with clinical diagnoses of ADD (n = 305) or amnestic mild cognitive impairment (aMCI, n = 909) from the Alzheimer’s Disease Neuroimaging Initiative, who had FDG-PET scans available. Individual FDG-PET scans were classified as being suggestive of Alzheimer’s (AD-like) or Lewy body (LB-like) pathology by using a logistic regression classifier trained on a separate set of patients with autopsy-confirmed Alzheimer’s disease or Lewy body pathology. AD- and LB-like subgroups were compared on amyloid-β and tau-PET, domain-specific cognitive profiles (memory versus executive function performance), as well as the presence of hallucinations and their evolution over follow-up (≈6 years for aMCI, ≈3 years for ADD). Around 12% of the aMCI and ADD patients were classified as LB-like. For both aMCI and ADD patients, the LB-like group showed significantly lower regional tau-PET burden than the AD-like subgroup, but amyloid-β load was only significantly lower in the aMCI LB-like subgroup. LB- and AD-like subgroups did not significantly differ in global cognition (aMCI: d = 0.15, P = 0.16; ADD: d = 0.02, P = 0.90), but LB-like patients exhibited a more dysexecutive cognitive profile relative to the memory deficit (aMCI: d = 0.35, P = 0.01; ADD: d = 0.85 P & lt; 0.001), and had a significantly higher risk of developing hallucinations over follow-up [aMCI: hazard ratio = 1.8, 95% confidence interval = (1.29, 3.04), P = 0.02; ADD: hazard ratio = 2.2, 95% confidence interval = (1.53, 4.06) P = 0.01]. In summary, a sizeable group of clinically diagnosed ADD and aMCI patients exhibit posterior-occipital FDG-PET patterns typically associated with Lewy body pathology, and these also show less abnormal Alzheimer’s disease biomarkers as well as specific clinical features typically associated with dementia with Lewy bodies.
    Materialart: Online-Ressource
    ISSN: 0006-8950 , 1460-2156
    RVK:
    Sprache: Englisch
    Verlag: Oxford University Press (OUP)
    Publikationsdatum: 2023
    ZDB Id: 1474117-9
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 2
    In: Brain, Oxford University Press (OUP), Vol. 146, No. 9 ( 2023-09-01), p. 3719-3734
    Kurzfassung: 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.
    Materialart: Online-Ressource
    ISSN: 0006-8950 , 1460-2156
    RVK:
    Sprache: Englisch
    Verlag: Oxford University Press (OUP)
    Publikationsdatum: 2023
    ZDB Id: 1474117-9
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 3
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 2 ( 2023-01-10)
    Kurzfassung: 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.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    RVK:
    RVK:
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2023
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 4
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 39 ( 2016-09-27)
    Kurzfassung: 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.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    RVK:
    RVK:
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2016
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 5
    In: Clinical Infectious Diseases, Oxford University Press (OUP), Vol. 69, No. 5 ( 2019-08-16), p. 769-776
    Kurzfassung: We evaluated the association between mortality and colistin resistance in Acinetobacter baumannii infections and the interaction with antibiotic therapy. Methods This is a secondary analysis of a randomized controlled trial of patients with carbapenem-resistant gram-negative bacterial infections treated with colistin or colistin-meropenem combination. We evaluated patients with infection caused by carbapenem-resistant A. baumannii (CRAB) identified as colistin susceptible (CoS) at the time of treatment and compared patients in which the isolate was confirmed as CoS with those whose isolates were retrospectively identified as colistin resistant (CoR) when tested by broth microdilution (BMD). The primary outcome was 28-day mortality. Results Data were available for 266 patients (214 CoS and 52 CoR isolates). Patients with CoR isolates had higher baseline functional capacity and lower rates of mechanical ventilation than patients with CoS isolates. All-cause 28-day mortality was 42.3% (22/52) among patients with CoR strains and 52.8% (113/214) among patients with CoS isolates (P = .174). After adjusting for variables associated with mortality, the mortality rate was lower among patients with CoR isolates (odds ratio [OR], 0.285 [95% confidence interval {CI}, .118–.686] ). This difference was associated with treatment arm: Mortality rates among patients with CoR isolates were higher in those randomized to colistin-meropenem combination therapy compared to colistin monotherapy (OR, 3.065 [95% CI, 1.021–9.202]). Conclusions Colistin resistance determined by BMD was associated with lower mortality among patients with severe CRAB infections. Among patients with CoR isolates, colistin monotherapy was associated with a better outcome compared to colistin-meropenem combination therapy. Clinical Trials Registration NCT01732250
    Materialart: Online-Ressource
    ISSN: 1058-4838 , 1537-6591
    RVK:
    Sprache: Englisch
    Verlag: Oxford University Press (OUP)
    Publikationsdatum: 2019
    ZDB Id: 2002229-3
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 6
    In: Clinical Infectious Diseases, Oxford University Press (OUP), Vol. 71, No. 10 ( 2020-12-17), p. 2599-2607
    Kurzfassung: We evaluated whether carbapenem-colistin combination therapy reduces the emergence of colistin resistance, compared to colistin monotherapy, when given to patients with infections due to carbapenem-resistant Gram-negative organisms. Methods This is a pre-planned analysis of a secondary outcome from a randomized, controlled trial comparing colistin monotherapy with colistin-meropenem combination for the treatment of severe infections caused by carbapenem-resistant, colistin-susceptible Gram-negative bacteria. We evaluated rectal swabs taken on Day 7 or later for the presence of new colistin-resistant (ColR) isolates. We evaluated the emergence of any ColR isolate and the emergence of ColR Enterobacteriaceae (ColR-E). Results Data were available for 214 patients for the primary analysis; emergent ColR organisms were detected in 22 (10.3%). No difference was observed between patients randomized to treatment with colistin monotherapy (10/106, 9.4%) versus patients randomized to colistin-meropenem combination therapy (12/108, 11.1%; P = .669). ColR-E organisms were detected in 18/249 (7.2%) patients available for analysis. No difference was observed between the 2 treatment arms (colistin monotherapy 6/128 [4.7%] vs combination therapy 12/121 [9.9%] ; P = .111). Enterobacteriaceae, as the index isolate, was found to be associated with development of ColR-E (hazard ratio, 3.875; 95% confidence interval, 1.475–10.184; P = .006). Conclusions Carbapenem-colistin combination therapy did not reduce the incidence of colistin resistance emergence in patients with infections due to carbapenem-resistant organisms. Further studies are necessary to elucidate the development of colistin resistance and methods for its prevention.
    Materialart: Online-Ressource
    ISSN: 1058-4838 , 1537-6591
    RVK:
    Sprache: Englisch
    Verlag: Oxford University Press (OUP)
    Publikationsdatum: 2020
    ZDB Id: 2002229-3
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 7
    In: Microbiology Spectrum, American Society for Microbiology, Vol. 11, No. 3 ( 2023-06-15)
    Kurzfassung: Colistin heteroresistance (HR) refers to a bacterial population comprised of several subpopulations with different levels of resistance to colistin. In this study, we discuss the classic form of HR, in which a resistant subpopulation exists within a predominantly susceptible population. We investigated the prevalence of colistin HR and its evolution into full resistance among 173 clinical carbapenem-resistant Acinetobacter baumannii isolates and examined the effect of HR on clinical outcomes. To determine HR, we performed population analysis profiling. Our results showed a high prevalence of HR (67.1%). To examine evolution of HR strains into full resistance, the HR strains were grown in colistin-containing broth, transferred onto colistin-containing plates, and colonies on these plates were transferred into colistin-free broth. Many of the HR strains (80.2%) evolved into full resistance, 17.2% reverted to HR, and 2.6% were borderline. We used logistic regression to compare 14-day clinical failure and 14-day mortality between patients infected by HR versus susceptible non-HR carbapenem-resistant A. baumannii . In the subgroup of patients with bacteremia, HR was significantly associated with 14-day mortality. IMPORTANCE To our knowledge, this is the first large-scale study to report on HR in Gram-negative bacteria. We described the prevalence of colistin HR in a large sample of carbapenem-resistant A. baumannii isolates, the evolution of many colistin HR isolates to a resistant phenotype following colistin exposure and withdrawal, and the clinical consequences of colistin HR. We found a high prevalence of HR among clinical carbapenem-resistant A. baumannii isolates; most evolved into a resistant phenotype following colistin exposure and withdrawal. In patients treated with colistin, evolution of HR A. baumannii into full resistance could lead to higher rates of treatment failure and contribute to the reservoir of colistin-resistant pathogens in health care settings.
    Materialart: Online-Ressource
    ISSN: 2165-0497
    Sprache: Englisch
    Verlag: American Society for Microbiology
    Publikationsdatum: 2023
    ZDB Id: 2807133-5
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 8
    Online-Ressource
    Online-Ressource
    Proceedings of the National Academy of Sciences ; 2009
    In:  Proceedings of the National Academy of Sciences Vol. 106, No. 49 ( 2009-12-08), p. 20954-20959
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 106, No. 49 ( 2009-12-08), p. 20954-20959
    Kurzfassung: Regions of the temporal and parietal lobes are particularly damaged in Alzheimer's disease (AD), and this leads to a predictable pattern of brain atrophy. In vivo quantification of subregional atrophy, such as changes in cortical thickness or structure volume, could lead to improved diagnosis and better assessment of the neuroprotective effects of a therapy. Toward this end, we have developed a fast and robust method for accurately quantifying cerebral structural changes in several cortical and subcortical regions using serial MRI scans. In 169 healthy controls, 299 subjects with mild cognitive impairment (MCI), and 129 subjects with AD, we measured rates of subregional cerebral volume change for each cohort and performed power calculations to identify regions that would provide the most sensitive outcome measures in clinical trials of disease-modifying agents. Consistent with regional specificity of AD, temporal-lobe cortical regions showed the greatest disease-related changes and significantly outperformed any of the clinical or cognitive measures examined for both AD and MCI. Global measures of change in brain structure, including whole-brain and ventricular volumes, were also elevated in AD and MCI, but were less salient when compared to changes in normal subjects. Therefore, these biomarkers are less powerful for quantifying disease-modifying effects of compounds that target AD pathology. The findings indicate that regional temporal lobe cortical changes would have great utility as outcome measures in clinical trials and may also have utility in clinical practice for aiding early diagnosis of neurodegenerative disease.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    RVK:
    RVK:
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2009
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 9
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 2, No. 1 ( 2022-06-20)
    Kurzfassung: Alzheimer’s disease, the most common cause of dementia, causes a progressive and irreversible deterioration of cognition that can sometimes be difficult to diagnose, leading to suboptimal patient care. Methods We developed a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted MRI scans, with or without cognitive scores. For each patient, a biomarker called “Alzheimer’s Predictive Vector” (ApV) was derived using a two-stage least absolute shrinkage and selection operator (LASSO). Results The ApV reliably discriminates between people with (ADrp) and without (nADrp) Alzheimer’s related pathologies (98% and 81% accuracy between ADrp - including the early form, mild cognitive impairment - and nADrp in internal and external hold-out test sets, respectively), without any a priori assumptions or need for neuroradiology reads. The new test is superior to standard hippocampal atrophy (26% accuracy) and cerebrospinal fluid beta amyloid measure (62% accuracy). A multiparametric analysis compared DTI-MRI derived fractional anisotropy, whose readout of neuronal loss agrees with ADrp phenotype, and SNPrs2075650 is significantly altered in patients with ADrp-like phenotype. Conclusions This new data analytic method demonstrates potential for increasing accuracy of Alzheimer diagnosis.
    Materialart: Online-Ressource
    ISSN: 2730-664X
    Sprache: Englisch
    Verlag: Springer Science and Business Media LLC
    Publikationsdatum: 2022
    ZDB Id: 3096949-9
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 10
    In: Communications Medicine, Springer Science and Business Media LLC, Vol. 3, No. 1 ( 2023-07-20)
    Kurzfassung: Identifying prediagnostic neurodegenerative disease is a critical issue in neurodegenerative disease research, and Alzheimer’s disease (AD) in particular, to identify populations suitable for preventive and early disease-modifying trials. Evidence from genetic and other studies suggests the neurodegeneration of Alzheimer’s disease measured by brain atrophy starts many years before diagnosis, but it is unclear whether these changes can be used to reliably detect prediagnostic sporadic disease. Methods We trained a Bayesian machine learning neural network model to generate a neuroimaging phenotype and AD score representing the probability of AD using structural MRI data in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Cohort (cut-off 0.5, AUC 0.92, PPV 0.90, NPV 0.93). We go on to validate the model in an independent real-world dataset of the National Alzheimer’s Coordinating Centre (AUC 0.74, PPV 0.65, NPV 0.80) and demonstrate the correlation of the AD-score with cognitive scores in those with an AD-score above 0.5. We then apply the model to a healthy population in the UK Biobank study to identify a cohort at risk for Alzheimer’s disease. Results We show that the cohort with a neuroimaging Alzheimer’s phenotype has a cognitive profile in keeping with Alzheimer’s disease, with strong evidence for poorer fluid intelligence, and some evidence of poorer numeric memory, reaction time, working memory, and prospective memory. We found some evidence in the AD-score positive cohort for modifiable risk factors of hypertension and smoking. Conclusions This approach demonstrates the feasibility of using AI methods to identify a potentially prediagnostic population at high risk for developing sporadic Alzheimer’s disease.
    Materialart: Online-Ressource
    ISSN: 2730-664X
    Sprache: Englisch
    Verlag: Springer Science and Business Media LLC
    Publikationsdatum: 2023
    ZDB Id: 3096949-9
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
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