Faculty Bibliography
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69
Intracranial artery stenosis is associated with cortical thinning in stroke-free individuals of two longitudinal cohorts
BACKGROUND:We examined the association between asymptomatic intracranial artery stenosis (aICAS) and cortical thickness using brain magnetic resonance morphometry in two cohorts. METHODS:This cross-sectional study included stroke-free participants from the Northern Manhattan Study (NOMAS) and the National Alzheimer's Coordinating Center (NACC). We represented the predictor aICAS in NOMAS as a continuous global stenosis score reflecting an overall burden of stenosis (possible range 0-44) assessed by magnetic resonance angiography and in NACC as a dichotomous autopsy-determined Circle of Willis (CoW) atherosclerosis (none-mild vs moderate-severe). The primary outcome of interest was total cortical thickness. We analyzed each dataset separately using multivariable linear regression. RESULTS:The analysis included 1209 NOMAS (46% had any stenosis, 5% had ≥70% stenosis of at least one vessel; stenosis score range 0-11) and 392 NACC (36% moderate-severe CoW atherosclerosis) participants. We found an inverse relationship between stenosis score and total cortical thickness (β-estimate [95% confidence interval (CI)]: -2.98 [-5.85, -0.11]) in adjusted models. We replicated these results in NACC (β-estimate [95% CI]: -0.06 [-0.11, -0.003]). Post-hoc, we segregated stenosis scores by location and only posterior circulation stenosis score was associated with total cortical thickness (anterior β-estimate [95% CI]: -0.90 [-5.16, 3.36], posterior β-estimate [95% CI]: -7.25 [-14.30, -0.20]). CONCLUSION/CONCLUSIONS:We found both radiographically and neuropathologically determined aICAS to be associated with global cortical thinning. Interestingly, posterior circulation stenoses appeared to drive this association with global cortical thinning, raising the possibility of pathophysiologic mechanisms for cortical thinning other than impaired hemodynamics.
PMCID:9880900
PMID: 36577280
ISSN: 1878-5883
CID: 5409642
On gaps of clinical diagnosis of dementia subtypes: A study of Alzheimer"™s disease and Lewy body disease
Introduction: Alzheimer"™s disease (AD) and Lewy body disease (LBD) are the two most common neurodegenerative dementias and can occur in combination (AD+LBD). Due to overlapping biomarkers and symptoms, clinical differentiation of these subtypes could be difficult. However, it is unclear how the magnitude of diagnostic uncertainty varies across dementia spectra and demographic variables. We aimed to compare clinical diagnosis and post-mortem autopsy-confirmed pathological results to assess the clinical subtype diagnosis quality across these factors. Methods: We studied data of 1,920 participants recorded by the National Alzheimer"™s Coordinating Center from 2005 to 2019. Selection criteria included autopsy-based neuropathological assessments for AD and LBD, and the initial visit with Clinical Dementia Rating (CDR) stage of normal, mild cognitive impairment, or mild dementia. Longitudinally, we analyzed the first visit at each subsequent CDR stage. This analysis included positive predictive values, specificity, sensitivity and false negative rates of clinical diagnosis, as well as disparities by sex, race, age, and education. If autopsy-confirmed AD and/or LBD was missed in the clinic, the alternative clinical diagnosis was analyzed. Findings: In our findings, clinical diagnosis of AD+LBD had poor sensitivities. Over 61% of participants with autopsy-confirmed AD+LBD were diagnosed clinically as AD. Clinical diagnosis of AD had a low sensitivity at the early dementia stage and low specificities at all stages. Among participants diagnosed as AD in the clinic, over 32% had concurrent LBD neuropathology at autopsy. Among participants diagnosed as LBD, 32% to 54% revealed concurrent autopsy-confirmed AD pathology. When three subtypes were missed by clinicians, "No cognitive impairment" and "primary progressive aphasia or behavioral variant frontotemporal dementia" were the leading primary etiologic clinical diagnoses. With increasing dementia stages, the clinical diagnosis accuracy of black participants became significantly worse than other races, and diagnosis quality significantly improved for males but not females. Discussion: These findings demonstrate that clinical diagnosis of AD, LBD, and AD+LBD are inaccurate and suffer from significant disparities on race and sex. They provide important implications for clinical management, anticipatory guidance, trial enrollment and applicability of potential therapies for AD, and promote research into better biomarker-based assessment of LBD pathology.
SCOPUS:85151542204
ISSN: 1663-4365
CID: 5460452
Gait dysfunction in Alzheimer disease
Alzheimer's disease (AD) is the most common cause of age-associated dementia and will exponentially rise in prevalence in the coming decades, supporting the parallel development of the early stage detection and disease-modifying strategies. While primarily considered as a cognitive disorder, AD also features motor symptoms, primarily gait dysfunction. Such gait abnormalities can be phenotyped across classic clinical syndromes as well as by quantitative kinematic assessments to address subtle dysfunction at preclinical and prodromal stages. As such, certain measures of gait can predict the future cognitive and functional decline. Moreover, cross-sectional and longitudinal studies have associated gait abnormalities with imaging, biofluid, and genetic markers of AD across all stages. This suggests that gait assessment is an important tool in the clinical assessment of patients across the AD spectrum, especially to help identify at-risk individuals.
PMID: 37620073
ISSN: 0072-9752
CID: 5598022
Local and long-range GABAergic circuits in hippocampal area CA1 and their link to Alzheimer's disease
GABAergic inhibitory neurons are the principal source of inhibition in the brain. Traditionally, their role in maintaining the balance of excitation-inhibition has been emphasized. Beyond homeostatic functions, recent circuit mapping and functional manipulation studies have revealed a wide range of specific roles that GABAergic circuits play in dynamically tilting excitation-inhibition coupling across spatio-temporal scales. These span from gating of compartment- and input-specific signaling, gain modulation, shaping input-output functions and synaptic plasticity, to generating signal-to-noise contrast, defining temporal windows for integration and rate codes, as well as organizing neural assemblies, and coordinating inter-regional synchrony. GABAergic circuits are thus instrumental in controlling single-neuron computations and behaviorally-linked network activity. The activity dependent modulation of sensory and mnemonic information processing by GABAergic circuits is pivotal for the formation and maintenance of episodic memories in the hippocampus. Here, we present an overview of the local and long-range GABAergic circuits that modulate the dynamics of excitation-inhibition and disinhibition in the main output area of the hippocampus CA1, which is crucial for episodic memory. Specifically, we link recent findings pertaining to GABAergic neuron molecular markers, electrophysiological properties, and synaptic wiring with their function at the circuit level. Lastly, given that area CA1 is particularly impaired during early stages of Alzheimer's disease, we emphasize how these GABAergic circuits may contribute to and be involved in the pathophysiology.
PMCID:10570439
PMID: 37841892
ISSN: 1662-5110
CID: 5605472
Clinical Implications of Internal Carotid Arterial Tortuosity in Patients with White Matter Hyperintensities
Background: White matter hyperintensities (WMHs) are observed frequently on MRI in elderly and associated with cognitive dysfunction. Many studies focused on intracranial small vessel disease (SVD), however, few studies linked WMHs with changes of extracranial large feeding arteries. We aimed to investigate the effects of internal carotid artery (ICA) tortuosity changes through quantitative MR Angiography. Method: Fifty-seven patients (age: 72.98±5.62; 32 females/25 males) with WMHs were included. WMHs lesions were semi-automatically segmented on FLAIR images. ICAs were segmented on the TOF images to generate tortuosity quantitative metrics, including tortuosity index (TI), inflection count metric (ICM), and ICA angle (Figure 1). According to the Fazekas scores, patients were categorized into mild, moderate and severe groups as summarized in Table 1. One-way ANOVA analyses were applied to reveal the difference of averaged bilateral ICAs' tortuosity measurements. Pearson's correlation coefficients were calculated to quantitatively investigate the relationship between tortuosity and volumes of lesions that are apart from the ventricle in subcortical white matter, i.e., deep white matter lesions (DWMLs), as well as the lesions attached with the ventricular system, i.e., periventricular white matter lesions (PVWMLs). Result: Patients with higher Fazekas scores have higher TI and ICM, indicating higher tortuosity (Figure 2). The correlation results showed that TI and ICM were positively correlated with DWMLs volumes (r = 0.33, P< 0.05; r = 0.4, P< 0.01), however, they did not show associations with PVWMLs. While there's no correlation between averaged bilateral ICA angles and DWMLs or PVWMLs, we found significant correlations between left ICA angles and DWML volumes on left brain (r =0.56, P < 0.005) as well as between right ICA angles and DWML volumes on right brain (r = 0.49, P < 0.05) (Figure 3). Conclusion: Tortuosity measurements derived from TOF images showed that subjects with higher degree of ICA tortuosity had higher lesion volumes of DWMLs not PVWMLs, indicating DWMLs may have different etiologies such as ischemic origin. The findings also highlight the importance of ICA angle as a risk factor for WMHs development which might be associated with the local hemodynamic shear stress at the bulb, where the ICA plaques are often developed.
SCOPUS:85144449727
ISSN: 1552-5260
CID: 5393902
Cortical Myelin Profile Variations in Healthy Aging Brain: A T1w/T2w Ratio Study
Demyelination is observed in both healthy aging and age-related neurodegenerative disorders. While the significance of myelin within the cortex is well acknowledged, studies focused on intracortical demyelination and depth-specific structural alterations in normal aging are lacking. Using the recently available Human Connectome Project Aging dataset, we investigated intracortical myelin in a normal aging population using the T1w/T2w ratio. To capture the fine changes across cortical depths, we employed a surface-based approach by constructing cortical profiles traveling perpendicularly through the cortical ribbon and sampling T1w/T2w values. The curvatures of T1w/T2w cortical profiles may be influenced by differences in local myeloarchitecture and other tissue properties, which are known to vary across cortical regions. To quantify the shape of these profiles, we parametrized the level of curvature using a nonlinearity index (NLI) that measures the deviation of the profile from a straight line. We showed that NLI exhibited a steep decline in aging that was independent of local cortical thinning. Further examination of the profiles revealed that lower T1w/T2w near the gray-white matter boundary and superficial cortical depths were major contributors to the apparent NLI variations with age. These findings suggest that demyelination and changes in other T1w/T2w related tissue properties in normal aging may be depth-specific and highlight the potential of NLI as a unique marker of microstructural alterations within the cerebral cortex.
PMID: 36368498
ISSN: 1095-9572
CID: 5357642
Generalizable deep learning model for early Alzheimer's disease detection from structural MRIs
Early diagnosis of Alzheimer's disease plays a pivotal role in patient care and clinical trials. In this study, we have developed a new approach based on 3D deep convolutional neural networks to accurately differentiate mild Alzheimer's disease dementia from mild cognitive impairment and cognitively normal individuals using structural MRIs. For comparison, we have built a reference model based on the volumes and thickness of previously reported brain regions that are known to be implicated in disease progression. We validate both models on an internal held-out cohort from The Alzheimer's Disease Neuroimaging Initiative (ADNI) and on an external independent cohort from The National Alzheimer's Coordinating Center (NACC). The deep-learning model is accurate, achieved an area-under-the-curve (AUC) of 85.12 when distinguishing between cognitive normal subjects and subjects with either MCI or mild Alzheimer's dementia. In the more challenging task of detecting MCI, it achieves an AUC of 62.45. It is also significantly faster than the volume/thickness model in which the volumes and thickness need to be extracted beforehand. The model can also be used to forecast progression: subjects with mild cognitive impairment misclassified as having mild Alzheimer's disease dementia by the model were faster to progress to dementia over time. An analysis of the features learned by the proposed model shows that it relies on a wide range of regions associated with Alzheimer's disease. These findings suggest that deep neural networks can automatically learn to identify imaging biomarkers that are predictive of Alzheimer's disease, and leverage them to achieve accurate early detection of the disease.
PMCID:9576679
PMID: 36253382
ISSN: 2045-2322
CID: 5352422
American journal of respiratory & critical care medicine. 2022:206(5):632-636.DOI: 10.1164/rccm.202201-0107LE
Obstructive Sleep Apnea and Hypertension with Longitudinal β-Amyloid Burden and Cognitive Changes
PMID: 35550019
ISSN: 1535-4970
CID: 5213082
Comparison of serum neurodegenerative biomarkers among hospitalized COVID-19 patients versus non-COVID subjects with normal cognition, mild cognitive impairment, or Alzheimer's dementia
INTRODUCTION/BACKGROUND:Neurological complications among hospitalized COVID-19 patients may be associated with elevated neurodegenerative biomarkers. METHODS:Among hospitalized COVID-19 patients without a history of dementia (N = 251), we compared serum total tau (t-tau), phosphorylated tau-181 (p-tau181), glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), ubiquitin carboxy-terminal hydrolase L1 (UCHL1), and amyloid beta (Aβ40,42) between patients with or without encephalopathy, in-hospital death versus survival, and discharge home versus other dispositions. COVID-19 patient biomarker levels were also compared to non-COVID cognitively normal, mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia controls (N = 161). RESULTS:Admission t-tau, p-tau181, GFAP, and NfL were significantly elevated in patients with encephalopathy and in those who died in-hospital, while t-tau, GFAP, and NfL were significantly lower in those discharged home. These markers correlated with severity of COVID illness. NfL, GFAP, and UCHL1 were higher in COVID patients than in non-COVID controls with MCI or AD. DISCUSSION/CONCLUSIONS:Neurodegenerative biomarkers were elevated to levels observed in AD dementia and associated with encephalopathy and worse outcomes among hospitalized COVID-19 patients.
PMID: 35023610
ISSN: 1552-5279
CID: 5116752
New insights into the genetic etiology of Alzheimer's disease and related dementias
Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele.
PMCID:9005347
PMID: 35379992
ISSN: 1546-1718
CID: 5213092
