Vascular burden and cognition: Mediating roles of neurodegeneration and amyloid PET.

It remains unclear to what extent cerebrovascular burden relates to amyloid beta (Aß) deposition, neurodegeneration, and cognitive dysfunction in mixed disease populations with small vessel disease and Alzheimer's disease (AD) pathology. In 120 subjects, we investigated the association of vascular burden (white matter hyperintensity [WMH] volumes) with cognition. Using mediation analyses, we tested the indirect effects of WMH on cognition via Aß deposition (18 F-AV45 positron emission tomography [PET]) and neurodegeneration (cortical thickness or 18 F fluorodeoxyglucose PET) in AD signature regions. We observed that increased total WMH volume was associated with poorer performance in all tested cognitive domains, with the strongest effects observed for semantic fluency. These relationships were mediated mainly via cortical thinning, particularly of the temporal lobe, and to a lesser extent serially mediated via Aß and cortical thinning of AD signature regions. WMH volumes differentially impacted cognition depending on lobar location and Aß status. In summary, our study suggests mainly an amyloid-independent pathway in which vascular burden affects cognitive function via localized neurodegeneration. HIGHLIGHTS: Alzheimer's disease often co-exists with vascular pathology. We studied a unique cohort enriched for high white matter hyperintensities (WMH). High WMH related to cognitive impairment of semantic fluency and executive function. This relationship was mediated via temporo-parietal atrophy rather than metabolism. This relationship was, to lesser extent, serially mediated via amyloid beta and atrophy.

Linguistic changes in neurodegenerative diseases relate to clinical symptoms.

Background: The detection and characterization of speech changes may help in the identification and monitoring of neurodegenerative diseases. However, there is limited research validating the relationship between speech changes and clinical symptoms across a wide range of neurodegenerative diseases. Method: We analyzed speech recordings from 109 patients who were diagnosed with various neurodegenerative diseases, including Alzheimer's disease, Frontotemporal Dementia, and Vascular Cognitive Impairment, in a cognitive neurology memory clinic. Speech recordings of an open-ended picture description task were processed using the Winterlight speech analysis platform which generates >500 speech features, including the acoustics of speech and linguistic properties of spoken language. We investigated the relationship between the speech features and clinical assessments including the Mini Mental State Examination (MMSE), Mattis Dementia Rating Scale (DRS), Western Aphasia Battery (WAB), and Boston Naming Task (BNT) in a heterogeneous patient population. Result: Linguistic features including lexical and syntactic features were significantly correlated with clinical assessments in patients, across diagnoses. Lower MMSE and DRS scores were associated with the use of shorter words and fewer prepositional phrases. Increased impairment on WAB and BNT was correlated with the use of fewer nouns but more pronouns. Patients also differed from healthy adults as their speech duration was significantly shorter with more pauses. Conclusion: Linguistic changes such as the use of simpler vocabularies and syntax were detectable in patients with different neurodegenerative diseases and correlated with cognitive decline. Speech has the potential to be a sensitive measure for detecting cognitive impairments across various neurodegenerative diseases.

Amyloid-PET of the white matter: Relationship to free water, fiber integrity, and cognition in patients with dementia and small vessel disease.

White matter (WM) injury is frequently observed along with dementia. Positron emission tomography with amyloid-ligands (Aß-PET) recently gained interest for detecting WM injury. Yet, little is understood about the origin of the altered Aß-PET signal in WM regions. Here, we investigated the relative contributions of diffusion MRI-based microstructural alterations, including free water and tissue-specific properties, to Aß-PET in WM and to cognition. We included a unique cohort of 115 participants covering the spectrum of low-to-severe white matter hyperintensity (WMH) burden and cognitively normal to dementia. We applied a bi-tensor diffusion-MRI model that differentiates between (i) the extracellular WM compartment (represented via free water), and (ii) the fiber-specific compartment (via free water-adjusted fractional anisotropy [FA]). We observed that, in regions of WMH, a decrease in Aß-PET related most closely to higher free water and higher WMH volume. In contrast, in normal-appearing WM, an increase in Aß-PET related more closely to higher cortical Aß (together with lower free water-adjusted FA). In relation to cognitive impairment, we observed a closer relationship with higher free water than with either free water-adjusted FA or WM PET. Our findings support free water and Aß-PET as markers of WM abnormalities in patients with mixed dementia, and contribute to a better understanding of processes giving rise to the WM PET signal.

Exploratory Assessment of K-means Clustering to Classify 18F-Flutemetamol Brain PET as Positive or Negative.

RATIONALE: We evaluated K-means clustering to classify amyloid brain PETs as positive or negative. PATIENTS AND METHODS: Sixty-six participants (31 men, 35 women; age range, 52-81 years) were recruited through a multicenter observational study: 19 cognitively normal, 25 mild cognitive impairment, and 22 dementia (11 Alzheimer disease, 3 subcortical vascular cognitive impairment, and 8 Parkinson-Lewy Body spectrum disorder). As part of the neurocognitive and imaging evaluation, each participant had an 18F-flutemetamol (Vizamyl, GE Healthcare) brain PET. All studies were processed using Cortex ID software (General Electric Company, Boston, MA) to calculate SUV ratios in 19 regions of interest and clinically interpreted by 2 dual-certified radiologists/nuclear medicine physicians, using MIM software (MIM Software Inc, Cleveland, OH), blinded to the quantitative analysis, with final interpretation based on consensus. K-means clustering was retrospectively used to classify the studies from the quantitative data. RESULTS: Based on clinical interpretation, 46 brain PETs were negative and 20 were positive for amyloid deposition. Of 19 cognitively normal participants, 1 (5%) had a positive 18F-flutemetamol brain PET. Of 25 participants with mild cognitive impairment, 9 (36%) had a positive 18F-flutemetamol brain PET. Of 22 participants with dementia, 10 (45%) had a positive 18F-flutemetamol brain PET; 7 of 11 participants with Alzheimer disease (64%), 1 of 3 participants with vascular cognitive impairment (33%), and 2 of 8 participants with Parkinson-Lewy Body spectrum disorder (25%) had a positive 18F-flutemetamol brain PET. Using clinical interpretation as the criterion standard, K-means clustering (K = 2) gave sensitivity of 95%, specificity of 98%, and accuracy of 97%. CONCLUSIONS: K-means clustering may be a powerful algorithm for classifying amyloid brain PET.

Jalili Syndrome: Cross-sectional and Longitudinal Features of Seven Patients With Cone-Rod Dystrophy and Amelogenesis Imperfecta.

PURPOSE: To characterize a series of 7 patients with cone-rod dystrophy (CORD) and amelogenesis imperfecta (AI) owing to confirmed mutations in CNNM4, first described as "Jalili Syndrome." DESIGN: Retrospective observational case series. METHODS: Seven patients from 6 families with Jalili Syndrome were identified at 3 tertiary referral centers. We systematically reviewed their available medical records, spectral-domain optical coherence tomography (SD-OCT), fundus autofluorescence imaging (FAF), color fundus photography, and electrophysiological assessments. RESULTS: The mean age at presentation was 6.7 years (range 3-16 years), with 6 male and 1 female patient. CNNM4 mutations were identified in all patients. The mean Snellen best-corrected visual acuity (BCVA) at presentation was 20/246 (range 20/98 to 20/399) in the right eye and 20/252 (range 20/98 to 20/480) in the left. Nystagmus was observed in all 7 patients, and photophobia was present in 6. Funduscopic findings at presentation were variable, ranging from only mild disc pallor to retinal vascular attenuation and macular atrophy. Multimodal imaging demonstrated disease progression in all 7 patients over time. Electroretinography uniformly revealed progressive cone-rod dysfunction. CONCLUSIONS: Jalili Syndrome is a rare CORD associated with AI. We have further characterized its ocular phenotype, including describing SD-OCT, FAF, and electrophysiological features; and report several novel disease-causing sequence variants. Moreover, this study presents novel longitudinal data demonstrating structural and functional progression over time, allowing better informed advice on prognosis.