Kantarci, Kejal

ImportanceIncreased white matter hyperintensity (WMH) volume is a common magnetic resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) and late-onset Alzheimer disease (LOAD), but it remains unclear whether increased WMH along the AD continuum is reflective of AD-intrinsic processes or secondary to elevated systemic vascular risk factors.ObjectiveTo estimate the associations of neurodegeneration and parenchymal and vessel amyloidosis with WMH accumulation and investigate whether systemic vascular risk is associated with WMH beyond these AD-intrinsic processes.Design, Setting, and ParticipantsThis cohort study used data from 3 longitudinal cohort studies conducted in tertiary and community-based medical centers—the Dominantly Inherited Alzheimer Network (DIAN; February 2010 to March 2020), the Alzheimer’s Disease Neuroimaging Initiative (ADNI; July 2007 to September 2021), and the Harvard Aging Brain Study (HABS; September 2010 to December 2019).Main Outcome and MeasuresThe main outcomes were the independent associations of neurodegeneration (decreases in gray matter volume), parenchymal amyloidosis (assessed by amyloid positron emission tomography), and vessel amyloidosis (evidenced by cerebral microbleeds [CMBs]) with cross-sectional and longitudinal WMH.ResultsData from 3960 MRI sessions among 1141 participants were included: 252 pathogenic variant carriers from DIAN (mean [SD] age, 38.4 [11.2] years; 137 [54%] female), 571 older adults from ADNI (mean [SD] age, 72.8 [7.3] years; 274 [48%] female), and 318 older adults from HABS (mean [SD] age, 72.4 [7.6] years; 194 [61%] female). Longitudinal increases in WMH volume were greater in individuals with CMBs compared with those without (DIAN: t = 3.2 [P = .001]; ADNI: t = 2.7 [P = .008]), associated with longitudinal decreases in gray matter volume (DIAN: t = −3.1 [P = .002]; ADNI: t = −5.6 [P < .001]; HABS: t = −2.2 [P = .03]), greater in older individuals (DIAN: t = 6.8 [P < .001]; ADNI: t = 9.1 [P < .001]; HABS: t = 5.4 [P < .001]), and not associated with systemic vascular risk (DIAN: t = 0.7 [P = .40]; ADNI: t = 0.6 [P = .50]; HABS: t = 1.8 [P = .06]) in individuals with ADAD and LOAD after accounting for age, gray matter volume, CMB presence, and amyloid burden. In older adults without CMBs at baseline, greater WMH volume was associated with CMB development during longitudinal follow-up (Cox proportional hazards regression model hazard ratio, 2.63; 95% CI, 1.72-4.03; P < .001).Conclusions and RelevanceThe findings suggest that increased WMH volume in AD is associated with neurodegeneration and parenchymal and vessel amyloidosis but not with elevated systemic vascular risk. Additionally, increased WMH volume may represent an early sign of vessel amyloidosis preceding the emergence of CMBs.

Abstract Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer’s disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging’s use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.

Abstract Sex and gender influence every aspect of human health; thus, sex- and gender-related topics should be incorporated in all aspects of health education curricula. Sex and gender health education (SGHE) is the rigorous, intersectional, data-driven integration of sex and gender into all elements of health education. A multisectoral group of thought leaders has collaborated to advance SGHE since 2012. This cross-sector collaboration to advance SGHE has been successful on several fronts, primarily developing robust interprofessional SGHE programs, hosting a series of international SGHE summits, developing sex- and gender-specific resources, and broadening the collaboration beyond medical education. However, other deeply entrenched challenges have proven more difficult to address, including accurate and consistent sex and gender reporting in research publications, broadening institutional support for SGHE, and the development and implementation of evaluation plans for assessing learner outcomes and the downstream effects of SGHE on patient care. This commentary reflects on progress made in SGHE over the first decade of the current collaboration (2012–2022), articulates a vision for next steps to advance SGHE, and proposes 4 benchmarks to guide the next decade of SGHE: (1) integrate sex, gender, and intersectionality across health curricula; (2) develop sex- and gender-specific resources for health professionals; (3) improve sex and gender reporting in research publications; and (4) develop evaluation plans to assess learner and patient outcomes.

Abstract Objective We examined the long-term effects of premenopausal bilateral oophorectomy (PBO) with or without concurrent or preceding hysterectomy on physical and cognitive function and on odds of chronic conditions. Methods We enrolled 274 women with PBO with or without concurrent or preceding hysterectomy and 240 referents aged 55 years and older who were residents of Olmsted County, MN as of the PBO or index date. Chronic conditions were assessed via medical record abstraction. Cognitive diagnoses were based on neurocognitive testing. A physical function assessment included measures of strength and mobility. Multivariable regression models compared characteristics for women with PBO <46 years, PBO 46–49 years, and referent women with adjustments for age and other confounders. Results The clinical visits (median age, 67 years) were a median of 22 years after the PBO or index date. Of 274 women with PBO, 161 (59%) were <46 years at PBO and 113 (41%) were 46–49 years. Compared with referents, women with a history of PBO <46 years had increased odds of arthritis (odds ratio [OR], 1.64; 95% confidence interval [CI], 1.06–2.55), asthma (OR, 1.74; 95% CI, 1.03–2.93), obstructive sleep apnea (OR, 2.00; 95% CI, 1.23–3.26), and bone fractures (OR, 2.86; 95% CI, 1.17–6.98), and walked a shorter mean distance on a 6-minute walk test ( b = −18.43; P = 0.034). Compared with referents, women with a history of PBO at age 46–49 years had increased odds of arthritis (OR, 1.92; 95% CI, 1.16–3.18) and obstructive sleep apnea (OR, 2.21; 95% CI, 1.33–3.66). There were no significant differences in cognitive status in women with PBO compared with referents. Conclusions Women with a history of PBO with or without concurrent or preceding hysterectomy, especially at age <46 years, have more chronic conditions in late mid-life compared with referents.

BACKGROUND: Cerebral microbleeds (CMBs) are associated with cognitive decline, but their importance outside of cerebral amyloid angiopathy and the mechanisms of their impact on cognition are poorly understood. We evaluated the cross-sectional association between CMB patterns and cerebral Aβ (amyloid-β) deposition, by florbetapir positron emission tomography. METHODS: The longitudinal ARIC study (Atherosclerosis Risk in Communities) recruited individuals from 4 US communities from 1987 to 1989. From 2012 to 2014, the ARIC-PET (Atherosclerosis Risk in Communities - Positron Emission Tomography) ancillary recruited 322 nondemented ARIC participants who completed 3T brain magnetic resonance imaging with T2*GRE as part of ARIC visit 5 to undergo florbetapir positron emission tomography imaging. Magnetic resonance imaging images were read for CMBs and superficial siderosis; on positron emission tomography, global cortical standardized uptake value ratio >1.2 was considered a positive Aβ scan. Multivariable logistic regression models evaluated CMB characteristics in association with Aβ positivity. Effect modification by sex, race, APOE status, and cognition was evaluated. RESULTS: CMBs were present in 24% of ARIC-PET participants. No significant associations were found between CMBs and Aβ positivity, but a pattern of isolated lobar CMBs or superficial siderosis was associated with over 4-fold higher odds of elevated Aβ when compared with those with no CMBs (odds ratio, 4.72 [95% CI, 1.16–19.16]). A similar elevated risk was not observed in those with isolated subcortical or mixed subcortical and either lobar CMBs or superficial siderosis. Although no significant interactions were found, effect estimates for elevated Aβ were nonsignificantly lower ( P >0.10, odds ratio, 0.4–0.6) for a mixed CMB pattern, and odds ratios were nonsignificantly higher for lobar-only CMBs for 4 subgroups: women (versus men); Black participants (versus White participants), APOE ε4 noncarriers (versus carriers), and cognitively normal (versus mild cognitive impairment). CONCLUSIONS: In this community-based cohort of nondemented adults, lobar-only pattern of CMBs or superficial siderosis is most strongly associated with brain Aβ, with no elevated risk for a mixed CMB pattern. Further studies are needed to understand differences in CMB patterns and their meaning across subgroups.

ObjectiveMicrotubule‐associated protein tau (MAPT) mutations cause frontotemporal lobar degeneration, and novel biomarkers are urgently needed for early disease detection. We used task‐free functional magnetic resonance imaging (fMRI) mapping, a promising biomarker, to analyze network connectivity in symptomatic and presymptomatic MAPT mutation carriers.MethodsWe compared cross‐sectional fMRI data between 17 symptomatic and 39 presymptomatic carriers and 81 controls with (1) seed‐based analyses to examine connectivity within networks associated with the 4 most common MAPT‐associated clinical syndromes (ie, salience, corticobasal syndrome, progressive supranuclear palsy syndrome, and default mode networks) and (2) whole‐brain connectivity analyses. We applied K‐means clustering to explore connectivity heterogeneity in presymptomatic carriers at baseline. Neuropsychological measures, plasma neurofilament light chain, and gray matter volume were compared at baseline and longitudinally between the presymptomatic subgroups defined by their baseline whole‐brain connectivity profiles.ResultsSymptomatic and presymptomatic carriers had connectivity disruptions within MAPT‐syndromic networks. Compared to controls, presymptomatic carriers showed regions of connectivity alterations with age. Two presymptomatic subgroups were identified by clustering analysis, exhibiting predominantly either whole‐brain hypoconnectivity or hyperconnectivity at baseline. At baseline, these two presymptomatic subgroups did not differ in neuropsychological measures, although the hypoconnectivity subgroup had greater plasma neurofilament light chain levels than controls. Longitudinally, both subgroups showed visual memory decline (vs controls), yet the subgroup with baseline hypoconnectivity also had worsening verbal memory and neuropsychiatric symptoms, and extensive bilateral mesial temporal gray matter decline.InterpretationNetwork connectivity alterations arise as early as the presymptomatic phase. Future studies will determine whether presymptomatic carriers' baseline connectivity profiles predict symptomatic conversion. ANN NEUROL 2023;94:632–646

AbstractBackgroundWhite matter signal abnormalities (WMSA) are frequently observed on magnetic resonance imaging (MRI) scans of people with frontotemporal dementia (FTD). We hypothesized that carriers of mutations in progranulin (GRN+), chromosome 9 open reading frame 72 (C9orf72+) and microtubule associated protein tau (MAPT+) have increased rates of progression of WMSA compared to non‐carrier individuals prior to onset of dementia, and that different mutations may have different rates of WMSA accumulation.MethodParticipants were recruited through the ARTFL‐LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) Study. We selected participants with Clinical Dementia Rating scale (CDR) scores of 0 and 0.5. If a participant developed FTD during the follow‐up, we only analyzed observations collected before the conversion. WMSA were defined as hyperintensities on FLAIR MRI. Total WMSA volumes were normalized to the respective intracranial volumes. We used a linear mixed effects model, with random intercepts and slopes, to compare the baseline burden and the longitudinal progression of total WMSA volumes between mutation carriers and controls. The model was adjusted for baseline age, sex, education, baseline Montreal Cognitive Assessment (MoCA) scores, and MRI acquisition sites.ResultWe analyzed MRI data from 199 participants who had at least two MRI visits (46 C9orf72+, 17 GRN+, 35 MAPT+, 101 non‐carrier controls; up to five years of follow‐up). We did not find significant group differences in baseline demographic features, except that MAPT+ was younger than non‐carrier controls (average age: C9orf72+ = 47, GRN+ = 56, MAPT+ = 40, controls = 47). Baseline WMSA volumes were not significantly different between mutation carriers and controls. Longitudinally, the rates of WMSA volume increase in C9orf72+ and MAPT+ were comparable to controls; whereas, GRN+ had higher rates of WMSA volume increases compared to controls (p = 0.01).ConclusionWMSA may accumulate at higher rates in GRN+ prior to the onset of FTD, which is consistent with the frequent presence of white matter diseases observed in symptomatic FTD patients with GRN mutations. Future work is warranted to investigate the association between white matter structural changes and cognitive/psychiatric changes in FTD mutation carriers.

AbstractBackgroundDementia with Lewy bodies (DLB) is the second most common neurodegenerative dementia, after Alzheimer’s disease (AD). While alpha‐synuclein pathology is the hallmark of DLB, AD and cerebrovascular pathologies are common in DLB patients. However, the contribution of these pathologies towards neurodegeneration in DLB is largely unknown. We investigated associations of amyloid‐beta, tau, and cerebrovascular biomarkers with regional gray matter (GM) volume in DLB patients and cognitively unimpaired (CU) controls.MethodWe included 30 DLB patients (69.3±10.2 years old, 87% men) and 100 CU individuals balanced on age and sex (Table 1). We used 11C‐Pittsburgh Compound‐B (PiB) and 18F‐Flortaucipir positron emission tomography (PET) to assess amyloid‐beta and tau in‐vivo. We used structural MRI to assess white matter hyperintensity (WMH) volume, a marker of cerebrovascular lesion load, and regional GM volume (a marker of neurodegeneration). We used correlations and ANCOVA in the whole dataset and structural equation modelling in the DLB patients to investigate associations of WMH volume and regional amyloid‐beta and tau PET standardized uptake value ratios (SUVRs) with regional GM volume.ResultDLB patients showed lower GM volume across all cortical and subcortical regions except for cuneus, putamen, and pallidum (Fig.1). Greater WMH volume was associated with lower volume in the medial and orbital frontal cortices, insula, fusiform cortex, and thalamus in DLB patients (Fig.2). Greater PiB SUVR was associated with lower volume in the inferior temporal cortex, while Flortaucipir SUVR did not correlate with GM volume (Fig.2). Structural equation modelling showed that higher age and positivity for the APOE e4 genotype were significant predictors of greater WMH, and WMH in turn was a significant predictor of GM volume in medial and orbital frontal cortices, insula, and inferior temporal cortex (Fig.3). In contrast, we observed two distinct paths for the fusiform cortex, with age having an effect through PiB and Flortaucipir SUVRs on the one path, and through WMH on the other path (Fig.3).ConclusionDLB patients have widespread cortical atrophy, most of which likely is influenced by alpha‐synuclein pathology. Although amyloid‐beta, tau, and cerebrovascular pathologies often coexist in DLB, their contributions to neurodegeneration seem to be region specific.