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Background and ObjectivesThe menopause transition is increasingly recognized as a time of importance for women's brain health. A growing body of work indicates that the classic menopausal symptom, vasomotor symptom (VMS), may be associated with poorer cardiovascular health. Other work links VMS to poorer cognition. We investigate whether VMS, when rigorously assessed using physiologic measures, are associated with greater white matter hyperintensity volume (WMHV) among midlife women. We consider a range of potential explanatory factors in these associations and explore whether VMS are associated with the spatial distribution of WMHV.MethodsWomen aged 45–67 years and free of hormone therapy underwent 24 hours of physiologic VMS monitoring (sternal skin conductance), actigraphy assessment of sleep, physical measures, phlebotomy, and 3 Tesla neuroimaging. Associations between VMS (24-hour, wake, and sleep VMS, with wake and sleep intervals defined by actigraphy) and whole brain WMHV were considered in linear regression models adjusted for age, race, education, smoking, body mass index, blood pressure, insulin resistance, and lipids. Secondary models considered WMHV in specific brain regions (deep, periventricular, frontal, temporal, parietal, and occipital) and additional covariates including sleep.ResultsThe study sample included 226 women. Physiologically assessed VMS were associated with greater whole brain WMHV in multivariable models, with the strongest associations observed for sleep VMS (24-hour VMS, B[SE] = 0.095 [0.045],p= 0.032; Wake VMS, B[SE] = 0.078 [0.046],p= 0.089, Sleep VMS, B[SE] = 0.173 [0.060],p= 0.004). Associations were not accounted for by additional covariates including actigraphy-assessed sleep (wake after sleep onset). When considering the spatial distribution of WMHV, sleep VMS were associated with both deep WMHV, periventricular WMHV, and frontal lobe WMHV.DiscussionVMS, particularly VMS occurring during sleep, were associated with greater WMHV. Identification of female-specific midlife markers of poor brain health later in life is critical to identify women who warrant early intervention and prevention. VMS have the potential to serve as female-specific midlife markers of brain health in women.

We previously developed a novel machine-learning-based brain age model that was sensitive to amyloid. We aimed to independently validate it and to demonstrate its utility using independent clinical data. We recruited 650 participants from South Korean memory clinics to undergo magnetic resonance imaging and clinical assessments. We employed a pretrained brain age model that used data from an independent set of largely Caucasian individuals (n = 757) who had no or relatively low levels of amyloid as confirmed by positron emission tomography (PET). We investigated the association between brain age residual and cognitive decline. We found that our pretrained brain age model was able to reliably estimate brain age (mean absolute error = 5.68 years, r(650) = 0.47, age range = 49–89 year) in the sample with 71 participants with subjective cognitive decline (SCD), 375 with mild cognitive impairment (MCI), and 204 with dementia. Greater brain age was associated with greater amyloid and worse cognitive function [Odds Ratio, (95% Confidence Interval {CI}): 1.28 (1.06–1.55), p = 0.030 for amyloid PET positivity; 2.52 (1.76–3.61), p p = 0.001 for total 336 follow-up sample; 2.31 (1.44–3.71), p = 0.001 for 284 subsample with baseline Clinical Dementia Rating ≤ 0.5; 2.40 (1.43–4.03), p = 0.001 for 240 subsample with baseline SCD or MCI]. In independent data set, these results replicate our previous findings using this model, which was able to delineate significant differences in brain age according to the diagnostic stages of dementia as well as amyloid deposition status. Brain age models may offer benefits in discriminating and tracking cognitive impairment in older adults.

OBJECTIVE: The dysregulation of stress-related networks due to chronic symptoms such as severe worry and/or rumination is one of the putative pathways linking anxiety in late-life with cognitive decline and increased cardiovascular burden. Symptoms such as severe worry or rumination respond poorly to standard treatment and drive the morbidity associated with anxiety in older adults. We assessed if any of the neural networks anchored in the stressrelated regions of interest (ROIs) are associated with distinct anxiety phenotypes (worry, rumination and global anxiety). METHODS: We recruited older participants (over 50 years of age) with varying levels of worry (N=91) to undergo resting state fMRI. We computed seed-based connectivity for each ROI: the bed nucleus of the stria terminalis (BNST), the paraventricular nucleus of the hypothalamus (PVN), habenula, and amygdala. We limited our connectivity analyses to extracted regions for each seeded ROI-based network based on their canonical networks in 1000 participants (Neurosynth). Using connectivity and clinical factors, we fit cross-validated elastic net models to predict scores on Penn State Worry Questionnaire, Rumination Subscale Questionnaire, Hamilton Anxiety Rating Scale, and Perceived Stress Scale. RESULTS: We identified several distinct connectivity patterns that predict anxiety phenotypes’ severity. Greater worry was associated with greater PVN-subgenual anterior cingulate cortex, parahippocampal (PHC), and olfactory and amygdala-PHC connectivity. Greater global anxiety was associated with lower amygdala-superior temporal gyrus connectivity. Greater perceived stress was associated with lower amygdala-inferior temporal gyrus and amygdala-fusiform gyrus connectivity. CONCLUSIONS: Our study suggests that various late-life anxiety phenotypes (worry, global anxiety, rumination) may be associated with varying functional connectivity related to stress and emotion regulation. This may aid in the development of future targeted interventions.

An unresolved question for the understanding of Alzheimer’s disease (AD) pathophysiology is why a significant percentage of amyloid-β (Aβ)-positive cognitively unimpaired (CU) individuals do not develop detectable downstream tau pathology and, consequently, clinical deterioration. In vitro evidence suggests that reactive astrocytes unleash Aβ effects in pathological tau phosphorylation. Here, in a biomarker study across three cohorts (n = 1,016), we tested whether astrocyte reactivity modulates the association of Aβ with tau phosphorylation in CU individuals. We found that Aβ was associated with increased plasma phosphorylated tau only in individuals positive for astrocyte reactivity (Ast+). Cross-sectional and longitudinal tau–positron emission tomography analyses revealed an AD-like pattern of tau tangle accumulation as a function of Aβ only in CU Ast+ individuals. Our findings suggest astrocyte reactivity as an important upstream event linking Aβ with initial tau pathology, which may have implications for the biological definition of preclinical AD and for selecting CU individuals for clinical trials.

Mood symptoms and disorders are common in dementia caregivers, who can be exposed to a myriad of potential stressors including their care recipient’s neuropsychiatric symptoms. Existing evidence indicates that the effects of potentially stressful exposures on mental health depend on the caregiver’s individual characteristics and responses. Specifically, prior studies indicate that risk factors measured on psychological (e.g., emotion-focused/behaviorally disengaged coping responses) and behavioral (e.g., sleep and activity restriction) levels of analysis may confer the effects of caregiving exposures on mental health. Theoretically, this process from caregiving stressors and other risk factors to mood symptoms is neurobiologically mediated. This article reviews recent studies that used brain imaging to identify neurobiological factors that are related to psychological outcomes in caregivers. Available observational data indicate that psychological outcomes in caregivers are related to differences in the structure/function of regions involved in socio-affective information processing (prefrontal), autobiographical memory (the posterior cingulate), and stress (amygdala). In addition, two small randomized controlled trials using repeated brain imaging showed that Mentalizing Imagery Therapy (a mindfulness program) increased prefrontal network connectivity and reduced mood symptoms. These studies raise the possibility that, in the future, brain imaging may be useful to detect the neurobiological basis of a given caregiver’s mood vulnerability and guide the selection of interventions that are known to modify it. However, there remains a need for evidence on whether brain imaging improves on simpler/inexpensive measurement modalities like self-report for identifying vulnerable caregivers and matching them with efficacious interventions. In addition, to target interventions, more evidence is needed regarding the effects that both risk factors and interventions have on mood neurobiology (e.g., how persistent emotion-focused coping, sleep disruption, and mindfulness affect brain function).

While stress may be a potential mechanism by which childhood threat and deprivation influence mental health, few studies have considered specific stress‐related white matter pathways, such as the stria terminalis (ST) and medial forebrain bundle (MFB). Our goal was to examine the relationships between childhood adversity and ST and MFB structural integrity and whether these pathways may provide a link between childhood adversity and affective symptoms and disorders. Participants were young adults (n = 100) with a full distribution of maltreatment history and affective symptom severity. Threat was determined by measures of childhood abuse and repeated traumatic events. Socioeconomic deprivation (SED) was determined by a measure of childhood socioeconomic status (parental education). Participants underwent diffusion spectrum imaging. Human Connectome Project data was used to perform ST and MFB tractography; these tracts were used as ROIs to extract generalized fractional anisotropy (gFA) from each participant. Childhood threat was associated with ST gFA, such that greater threat was associated with less ST gFA. SED was also associated with ST gFA, however, conversely to threat, greater SED was associated with greater ST gFA. Additionally, threat was negatively associated with MFB gFA, and MFB gFA was negatively associated with post‐traumatic stress symptoms. Our results suggest that childhood threat and deprivation have opposing influences on ST structural integrity, providing new evidence that the context of childhood adversity may have an important influence on its neurobiological effects, even on the same structure. Further, the MFB may provide a novel link between childhood threat and affective symptoms., This study provides the first evidence that childhood threat and deprivation have opposing influences on stria terminalis generalized fractional anisotropy (gFA), and novel evidence that different dimensions of childhood adversity may have differential influences on structural integrity or underlying microstructure, even within the same region. Further, our results demonstrate that the medial forebrain bundle may provide a novel link between childhood threat and affective symptoms. Examining how these stress‐related, visceral circuits link childhood adversity to affective symptoms could improve our understanding of mechanisms underlying affective disorders and provide novel targets for intervention.

Small Vessel Disease (SVD) is known to be associated with higher AD risk, but its relationship to amyloidosis in the progression of AD is unclear. In this cross-sectional study of cognitively normal older adults, we explored the interactive effects of SVD and amyloid-beta (Aβ) pathology on hippocampal functional connectivity during an associative encoding task and on hippocampal volume.This study included 61 cognitively normal older adults (age range: 65-93 years, age mean ± standard deviation: 75.8 ± 6.4, 41 [67.2%] female). PiB PET, T2-weighted FLAIR, T1-weighted and face-name fMRI images were acquired on each participant to evaluate brain Aβ, white matter hyperintensities (WMH+/- status), gray matter density, and hippocampal functional connectivity.We found that, in WMH (+) older adults greater Aβ burden was associated with greater hippocampal local connectivity (i.e., hippocampal-parahippocampal connectivity) and lower gray matter density in medial temporal lobe (MTL), whereas in WMH (-) older adults greater Aβ burden was associated with greater hippocampal distal connectivity (i.e., hippocampal-prefrontal connectivity) and no changes in MTL gray matter density. Moreover, greater hippocampal local connectivity was associated with MTL atrophy.These observations support a hippocampal excitotoxicity model linking SVD to neurodegeneration in preclinical AD. This may explain how SVD may accelerate the progression from Aβ positivity to neurodegeneration, and subsequent AD.

In this review we examine, in the context of the amyloid, tau, and neurodegeneration framework, the available evidence and potential alternatives on how to establish tau positivity (T+) for multiple tau-imaging tracers in order to reach a consensus on normal and abnormal tau imaging values that can be universally implemented in clinical research and therapeutic trials.

To characterize the influence of APOE genotype on cerebral Aβ load and longitudinal Aβ trajectories, [(11)C]PiB PET imaging studies were performed in a cohort of 428 participants with known APOE genotype and a range of clinical diagnoses from cognitively normal elderly to Alzheimer’s disease (AD). [(11)C]PiB PET imaging was used to assess amyloid load in a clinically heterogeneous cohort of 428 elderly participants. Serial [(11)C]PiB data and a repeated measures model were used to model amyloid trajectories in a subset of 235 participants classified on the basis of APOE genotype. We found that APOE-ε4 was associated with increased Aβ burden and an earlier age of onset of Aβ positivity, whereas APOE-ε2 appeared to have modest protective effects against Aβ. APOE class did not predict rates of Aβ accumulation. The present study suggests that APOE modifies AD risk through a direct influence on amyloidogenic processes, which manifests as an earlier age-of-onset of Aβ positivity, although it is likely that other genetic, environmental, and lifestyle factors are important.

Purpose of review This narrative review seeks to ascertain the challenges older patients face with participation in mental health clinical research studies and suggests creative strategies to minimize these obstacles. Recent findings Challenges to older adults’ engagement in mental health research include practical, institutional, and collaboration-related barriers applicable to all clinical trials as well as more personal, cultural, and age-related patient barriers specific to geriatric mental health research. Universal research challenges include (1) institutional barriers of lack of funding and researchers, inter-researcher conflict, and sampling bias; (2) collaboration-related barriers involving miscommunication and clinician concerns; and (3) practical patient barriers such as scheduling issues, financial constraints, and transportation difficulties. Challenges unique to geriatric mental health research include (1) personal barriers such as no perceived need for treatment, prior negative experience, and mistrust of mental health research; (2) cultural barriers involving stigma and lack of bilingual or culturally matched staff; and (3) chronic medical issues and concerns about capacity. Summary Proposed solutions to these barriers include increased programmatic focus on and funding of geriatric psychiatry research grants, meeting with clinical staff to clarify study protocols and eligibility criteria, and offering transportation for participants. To minimize stigma and mistrust of psychiatric research, studies should devise community outreach efforts, employ culturally competent bilingual staff, and provide patient and family education about the study and general information about promoting mental health.

Objective We sought to determine whether the aspects of white matter connectivity implicated in major depression also relate to mild depressive symptoms in family dementia caregivers (dCGs). Methods Forty-one dCGs (average age=69 years, standard deviation=6.4) underwent a 7 Tesla 64-direction (12-minute) diffusion-weighted imaging sequence. We compared the fractional anisotropy (FA) of 11 white matter features between dCGs with (n=20) and without (n=21) depressive symptoms (Patient Health Questionnaire-9 scores ≥5). Results Caregivers reporting depression symptoms had lower FA in tracts connecting to the posterior cingulate cortex (Cohen's d = −0.9) and connecting dorsolateral prefrontal with rostral cingulate regions (Cohen's d = −1.2). Conclusions Posterior cingulate and dorsolateral prefrontal-to-rostral cingulate white matter, implicated in prior studies of major depression, appear relevant to mild depression in dCGs.

Brain age prediction is a machine learning method that estimates an individual’s chronological age from their neuroimaging scans. Brain age indicates whether an individual’s brain appears “older” than age-matched healthy peers, suggesting that they may have experienced a higher cumulative exposure to brain insults or were more impacted by those pathological insults. However, contemporary brain age models include older participants with amyloid pathology in their training sets and thus may be confounded when studying Alzheimer’s disease (AD). We showed that amyloid status is a critical feature for brain age prediction models. We trained a model on T1-weighted MRI images participants without amyloid pathology. MRI data were processed to estimate gray matter density voxel-wise, which were then used to predict chronological age. Our model performed accurately comparable to previous models. Notably, we demonstrated more significant differences between AD diagnostic groups than other models. Additionally, our model was able to delineate significant differences in brain age relative to chronological age between cognitively normal individuals with and without amyloid. Incorporation of amyloid status in brain age prediction models ultimately improves the utility of brain age as a biomarker for AD.

Objectives We examined the extent to which measures of neurodegeneration and cerebrovascular disease explain the rest-activity rhythm (RAR)-cognition link. Methods Seventy participants (mean age at MRI = 86, standard deviation (SD) = 2.6; 53% female) had cognitive, MRI, and accelerometer data. The slope of cognitive decline was defined applying a mixed model to 10 repeated Modified Mini Mental Status Test (3MS) measures over 14 years. Regional gray matter volume (GMV), white matter hyperintensities, and RARs were measured around year 12. Results Past 3MS decline was related to RAR fragmentation (per SD β = −0.43, 95% confidence interval: −0.73, −0.14) and lower posterior parietal GMV (per standard deviation β = 0.47, 95% confidence interval: 0.14, 0.79). Higher RAR fragmentation was related to lower posterior parietal GMV (Pearson r = −0.39, n = 70, p = 0.0007), which attenuated the association of RAR fragmentation and past cognitive decline by 17%. Conclusions Longitudinal studies are warranted to understand the temporal relations and mechanisms linking RAR fragmentation and neurodegeneration.

Important insights into the early pathogenesis of Alzheimer's disease can be provided by studies of autosomal dominant Alzheimer's disease and Down syndrome. However, it is unclear whether the timing and spatial distribution of amyloid accumulation differs between people with autosomal dominant Alzheimer's disease and those with Down syndrome. We aimed to directly compare amyloid changes between these two groups of people.In this cross-sectional study, we included participants (aged ≥25 years) with Down syndrome and sibling controls who had MRI and amyloid PET scans in the first data release (January, 2020) of the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study. We also included carriers of autosomal dominant Alzheimer's disease genetic mutations and non-carrier familial controls who were within a similar age range to ABC-DS participants (25-73 years) and had MRI and amyloid PET scans at the time of a data freeze (December, 2020) of the Dominantly Inherited Alzheimer Network (DIAN) study. Controls from the two studies were combined into a single group. All DIAN study participants had genetic testing to determine PSEN1, PSEN2, or APP mutation status. APOE genotype was determined from blood samples. CSF samples were collected in a subset of ABC-DS and DIAN participants and the ratio of amyloid β42 (Aβ42) to Aβ40 (Aβ42/40) was measured to evaluate its Spearman's correlation with amyloid PET. Global PET amyloid burden was compared with regards to cognitive status, APOE ɛ4 status, sex, age, and estimated years to symptom onset. We further analysed amyloid PET deposition by autosomal dominant mutation type. We also assessed regional patterns of amyloid accumulation by estimated number of years to symptom onset. Within a subset of participants the relationship between amyloid PET and CSF Aβ42/40 was evaluated.192 individuals with Down syndrome and 33 sibling controls from the ABC-DS study and 265 carriers of autosomal dominant Alzheimer's disease mutations and 169 non-carrier familial controls from the DIAN study were included in our analyses. PET amyloid centiloid and CSF Aβ42/40 were negatively correlated in carriers of autosomal dominant Alzheimer's disease mutations (n=216; r=-0·565; p0·0001) and in people with Down syndrome (n=32; r=-0·801; p0·0001). There was no difference in global PET amyloid burden between asymptomatic people with Down syndrome (mean 18·80 centiloids [SD 28·33]) versus asymptomatic mutation carriers (24·61 centiloids [30·27]; p=0·11) and between symptomatic people with Down syndrome (77·25 centiloids [41·76]) versus symptomatic mutation carriers (69·15 centiloids [51·10]; p=0·34). APOE ɛ4 status and sex had no effect on global amyloid PET deposition. Amyloid deposition was elevated significantly earlier in mutation carriers than in participants with Down syndrome (estimated years to symptom onset -23·0 vs -17·5; p=0·0002). PSEN1 mutations primarily drove this difference. Early amyloid accumulation occurred in striatal and cortical regions for both mutation carriers (n=265) and people with Down syndrome (n=128). Although mutation carriers had widespread amyloid accumulation in all cortical regions, the medial occipital regions were spared in people with Down syndrome.Despite minor differences, amyloid PET changes were similar between people with autosomal dominant Alzheimer's disease versus Down syndrome and strongly supported early amyloid dysregulation in individuals with Down syndrome. Individuals with Down syndrome aged at least 35 years might benefit from early intervention and warrant future inclusion in clinical trials, particularly given the relatively high incidence of Down syndrome.The National Institute on Aging, Riney and Brennan Funds, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the German Center for Neurodegenerative Diseases, and the Japan Agency for Medical Research and Development.

White matter hyperintensities (WMHs) are associated with cognitive decline. Assessing the effect of WMH on WM microstructural changes and its relationships with structural and functional connectivity to multiple cognitive domains are helpful to better understand the pathophysiological processes of cognitive impairment. 65 participants (49 normal and 16 MCI subjects, age: 67.4 ± 8.3 years, 44 females) were studied at 3T. The WMHs and fifty fiber tracts were automatically segmented from the T1/T2-weighted images and diffusion-weighted images, respectively. Tract-profiles of WMH were compared with those of apparent fiber density (AFD). The relationship between AFD and tract connectivity (TC) was assessed. Functional connectivity (FC) between tract ends obtained from resting-state functional MRI was examined in relation to TC. Tract-specific relationships of WMH, TC and FC with a multi-domain neuropsychological test battery and Montreal Cognitive Assessment (MoCA) were also separately assessed by lasso linear regression. Indirect pathways of TC and FC between WMH and multiple cognitive measures were tested using the mediation analysis. Higher WMH loads in WM tracts were locally matched with the reduced AFD, which was related to decrease in TC. However, no direct relationship was found between TC and FC. Tract-specific changes on WMH, TC and FC for each cognitive performance may explain that macro- and microstructural and functional changes are associated differently with each cognitive domain in a fiber specific manner. In these identified tracts, the differences between normal and MCI for WMH and TC were increased, and the relationships of WMH, TC and FC with cognitive outcomes were more significant, compared to the results from all tracts. Indirect pathways of two-step (TC-FC) between WMH and all cognitive domains were significant (p < 0.0083 with Bonferroni correction), while the separated indirect pathways through TC and through FC were different depending on cognitive domain. Deterioration in specific cognitive domains may be affected by alterations in a set of different tracts that are differently associated with macrostructural, microstructural, and function changes. Thus, assessments of WMH and its associated changes on specific tracts help for better understanding of the interrelationships of multiple changes in cognitive impairment.

This study examined the temporal relationship among depression, anxiety, insomnia, perceived stress, and physical activity in adults aged 60+ years with a history of major depressive disorder. We conducted a longitudinal study with 12 weeks of follow-up. Assessments consisted of phone or video interviews and included questionnaires evaluating depression, anxiety, insomnia, perceived stress, and physical activity. Our analytic approach consisted of a depression-focused cross-lagged panel model (CLPM) to examine week-to-week correlations among the five measures. The depression-focused CLPM identified statistically significant week-to-week self-predictive effects for each of the five measures. Higher depressive symptom burden was a strong predictor of increased stress, greater insomnia, and less physical activity the following week. No other cross-measure predictions were statistically significant. Our analytical approach clarifies the directional relationship among variables that typically co-occur with depression showing that higher depression symptom burden predisposes older adults to poor sleep, a reduced level of daytime activity, and a greater sense of stress. These findings support the need for longitudinal assessments and targeted interventions for reducing symptoms of depression in older adults.

Typical machine learning frameworks heavily rely on an underlying assumption that training and test data follow the same distribution. In medical imaging which increasingly begun acquiring datasets from multiple sites or scanners, this identical distribution assumption often fails to hold due to systematic variability induced by site or scanner dependent factors. Therefore, we cannot simply expect a model trained on a given dataset to consistently work well, or generalize, on a dataset from another distribution. In this work, we address this problem, investigating the application of machine learning models to unseen medical imaging data. Specifically, we consider the challenging case of Domain Generalization (DG) where we train a model without any knowledge about the testing distribution. That is, we train on samples from a set of distributions (sources) and test on samples from a new, unseen distribution (target). We focus on the task of white matter hyperintensity (WMH) prediction using the multi-site WMH Segmentation Challenge dataset and our local in-house dataset. We identify how two mechanically distinct DG approaches, namely domain adversarial learning and mix-up, have theoretical synergy. Then, we show drastic improvements of WMH prediction on an unseen target domain., IEEE International Symposium on Biomedical Imaging 2021

Childhood adversity is associated with altered or dysregulated stress reactivity; these altered patterns of physiological functioning persist into adulthood. Evidence from both preclinical animal models and human neuroimaging studies indicates that early life experience differentially influences stressor-evoked activity within central visceral neural circuits proximally involved in the control of stress responses, including the subgenual anterior cingulate cortex (sgACC), paraventricular nucleus of the hypothalamus (PVN), bed nucleus of the stria terminalis (BNST) and amygdala. However, the relationship between childhood adversity and the resting-state connectivity of this central visceral network remains unclear. To this end, we examined relationships between childhood threat and childhood socioeconomic deprivation, the resting-state connectivity between our regions of interest (ROIs), and affective symptom severity and diagnoses. We recruited a transdiagnostic sample of young adult males and females (n = 100; mean age = 27.28, SD = 3.99; 59 females) with a full distribution of maltreatment history and symptom severity across multiple affective disorders. Resting-state data were acquired using a 7.2-min functional magnetic resonance imaging (fMRI) sequence; noted ROIs were applied as masks to determine ROI-to-ROI connectivity. Threat was determined by measures of childhood traumatic events and abuse. Socioeconomic deprivation (SED) was determined by a measure of childhood socioeconomic status (parental education level). Covarying for age, race and sex, greater childhood threat was significantly associated with lower BNST-PVN, amygdala-sgACC and PVN-sgACC connectivity. No significant relationships were found between SED and resting-state connectivity. BNST-PVN connectivity was associated with the number of lifetime affective diagnoses. Exposure to threat during early development may entrain altered patterns of resting-state connectivity between these stress-related ROIs in ways that contribute to dysregulated neural and physiological responses to stress and subsequent affective psychopathology.

Severe worry is a complex transdiagnostic phenotype independently associated with increased morbidity, including cognitive impairment and cardiovascular diseases. We investigated the neurobiological basis of worry in older adults by analyzing resting state fMRI using a large-scale network-based approach. We collected resting fMRI on 77 participants (>50 years old) with varying worry severity. We computed region-wise connectivity across the default mode network (DMN), anterior salience network, and left executive control network. All 22,366 correlations were regressed on worry severity and adjusted for age, sex, race, education, disease burden, depression, anxiety, rumination, and neuroticism. We employed higher criticism, a second-level method of significance testing for rare and weak features, to reveal the functional connectivity patterns associated with worry. The analysis suggests that worry has a complex, yet distinct signature associated with resting state functional connectivity. Intra-connectivities and inter-connectivities of the DMN comprise the dominant contribution. The anterior cingulate, temporal lobe, and thalamus are heavily represented with overwhelmingly negative association with worry. The prefrontal regions are also strongly represented with a mix of positive and negative associations with worry. Identifying the most salient connections may be useful for targeted interventions for reducing morbidity associated with severe worry in older adults.

Background Traumatic experiences have been linked to poor mental and physical health. However, there has been little examination of their relationship to neuroimaging markers of cerebrovascular risk. White matter hyperintensities (WMHs) are markers of brain small vessel disease. WMHs can be detected decades before the onset of dementia and other disorders and can serve as early markers for these brain disorders. We tested whether traumatic experiences were associated with brain WMH volume among midlife women. Methods In the MsBrain study, 145 women (mean age = 59 years) without cardiovascular disease, stroke, or dementia were recruited. Women completed questionnaires [trauma checklist, depression, post-traumatic stress measures]; physical measures [body mass index (BMI), blood pressure (BP)]; phlebotomy; actigraphy sleep measurement, and 3 Tesla magnetic resonance brain imaging for WMHs. Cross-sectional associations between traumatic experiences and WMH volume were assessed in linear regression models. Covariates were age, race/ethnicity, education, BMI, BP, lipids, preeclampsia, sleep, and additionally depressive and post-traumatic stress disorder symptoms. Results 68% of women endorsed at least one of the traumas assessed. The most common trauma was sexual assault (23% of women). Women with trauma exposure had greater WMH volume than women without trauma [B(SE) = .24 (.09), p = .01, multivariable]. The single trauma most associated with WMH was sexual assault [B(SE) = .25 (.11), p = .02, multivariable]. Results persisted adjusting for depressive or post-traumatic stress symptoms. Conclusions A trauma history, particularly sexual assault, was associated with greater WMH volume controlling for covariates, including depressive and post-traumatic symptoms. Sexual assault may place women at risk for poor brain health.

The Alzheimer’s Disease Neuroimaging Initiative showed that Japanese had significantly lower brain Aβ burden than Americans among a cognitively normal population. This cross-sectional study aimed to compare vascular disease burden, Aβ burden, and neurodegeneration between cognitively normal elderly Japanese and Americans. Japanese and American participants were matched for age (±4-year-old), sex, and Apolipoprotein E (APOE) genotype. Brain vascular disease burden and brain Aβ burden were measured using white matter lesions (WMLs) and 11C-labeled Pittsburgh Compound B (PiB) retention, respectively. Neurodegeneration was measured using hippocampal volumes and cortical thickness. A total of 95 Japanese and 95 Americans were recruited (50.5% men, mean age = 82). Compared to Americans, Japanese participants had larger WMLs, and a similar global Aβ standardized uptake value ratio (SUVR), cortical thickness and hippocampal volumes. Japanese had significantly lower regional Aβ SUVR in the anterior ventral striatum, posterior cingulate cortex, and precuneus. Cognitively normal elderly Japanese and Americans had different profiles regarding vascular disease and Aβ burden. This suggests that multiple risk factors are likely to be involved in the development of dementia. Additionally, Japanese might have a lower risk of dementia due to lower Aβ burden than Americans. Longitudinal follow-up of these cohorts is warranted to ascertain the predictive accuracy of these findings.

Purpose Partial-volume correction (PVC) using the Geometric Transfer Matrix (GTM) method is used in positron emission tomography (PET) to compensate for the effects of spatial resolution on quantitation. We evaluate the effect of misspecification of scanner point-spread function (PSF) on GTM results in amyloid imaging, including the effect on amyloid status classification (positive or negative). Methods Twenty-nine subjects with Pittsburgh Compound B ([11C]PiB) PET and structural T1 MR imaging were analyzed. FreeSurfer 5.3 (FS) was used to parcellate MR images into regions-of-interest (ROIs) that were used to extract radioactivity concentration values from the PET images. GTM PVC was performed using our “standard” PSF parameterization [3D Gaussian, full-width at half-maximum (w) of approximately 5 mm]. Additional GTM PVC was performed with “incorrect” parameterizations, taken around the correct value. The result is a set of regional activity values for each of the GTM applications. For each case, activity values from various ROIs were combined and normalized to produce standardized uptake value ratios (SUVRs) for nine standard [11C]PiB quantitation ROIs and a global region. GTM operating-point characteristics were determined from the slope of apparent SUVR versus w curves. Results Errors in specification of w on the order of 1 mm (3D) mainly produce only modest errors of up to a few percent. An exception was the anterior ventral striatum in which fractional errors of up to 0.29 per millimeter (3D) of error in w were observed. Conclusion While this study does not address all the issues regarding the quantitative strengths and weakness of GTM PVC, we find that with reasonable caution, the unavoidable inaccuracies associated with PSF specification do not preclude its use in amyloid quantitation.

Objectives: Self-reported activity restriction is an established correlate of depression in dementia caregivers (dCGs). It is plausible that the daily distribution of objectively measured activity is also altered in dCGs with depression symptoms; if so, such activity characteristics could provide a passively measurable marker of depression or specific times to target preventive interventions. We therefore investigated how levels of activity throughout the day differed in dCGs with and without depression symptoms, then tested whether any such differences predicted changes in symptoms 6 months later. Design, setting, participants, and measurements: We examined 56 dCGs (mean age = 71, standard deviation (SD) = 6.7; 68% female) and used clustering to identify subgroups which had distinct depression symptom levels, leveraging baseline Center for Epidemiologic Studies of Depression Scale–Revised Edition and Patient Health Questionnaire-9 (PHQ-9) measures, as well as a PHQ-9 score from 6 months later. Using wrist activity (mean recording length = 12.9 days, minimum = 6 days), we calculated average hourly activity levels and then assessed when activity levels relate to depression symptoms and changes in symptoms 6 months later. Results: Clustering identified subgroups characterized by: (1) no/minimal symptoms (36%) and (2) depression symptoms (64%). After multiple comparison correction, the group of dCGs with depression symptoms was less active from 8 to 10 AM (Cohen’s d ≤ −0.9). These morning activity levels predicted the degree of symptom change on the PHQ-9 6 months later (per SD unit β = −0.8, 95% confidence interval: −1.6, −0.1, p = 0.03) independent of self-reported activity restriction and other key factors. Conclusions: These novel findings suggest that morning activity may protect dCGs from depression symptoms. Future studies should test whether helping dCGs get active in the morning influences the other features of depression in this population (i.e. insomnia, intrusive thoughts, and perceived activity restriction).

It remains challenging to integrate clinical neuroscience into clinical practice. Hindrances at the training level (e.g., lack of qualified faculty and curriculum) contribute to this impasse. To help address this, we present a model of training in clinical neuroscience. We expand on a growing literature on incorporating neuroscience into psychiatry training by emphasizing two points. That is, 1) we propose a training model designed for the geriatric-minded clinician; and 2) that extends across several phases of education and career development. Considering the relevance of dementia to our population of interest, and the potential impact expertise in clinical neuroscience can have in elders with cognitive impairment, we provide relevant curriculum examples at various training stages. Clinical research, both as a practitioner and consumer, figures prominently into our training model. We discuss two mentoring programs, T32 fellowships and Research Career Institute in the Mental Health of Aging, as ways to engage geriatric psychiatrists early in their training and transition them successfully to post-residency clinical investigator positions. Although there is increasing opportunity for geriatric psychiatrists and other clinicians to become leaders in the field of neuroscience, this remains a work in progress; ours and others' training programs continue to evolve based on input from trainers and trainees alike, as well as from the increasing literature on this important topic.

Compared to men, women are disproportionally affected by Alzheimer's disease (AD) and have an accelerated trajectory of cognitive decline and disease progression. Neurobiological factors underlying gender differences in AD remain unclear. This study investigated brain beta-amyloid (Aβ)-related neural system differences in cognitively normal older men and women (N = 61; 41 females, 65–93 years old). We found that men and women showed different associations between Aβ load and hippocampal functional connectivity. During associative memory encoding, in men greater Aβ burden was accompanied by greater hippocampus-prefrontal connectivity (i.e., more synchronized activities), whereas in women hippocampal connectivity did not vary by Aβ burden. For resting-state data, the interaction of gender × Aβ on hippocampal connectivity did not survive multiple comparison in the whole-brain analyses. In the region of interest–based analyses, resting-state hippocampal-prefrontal connectivity was positively correlated with Aβ load in men and was negatively correlated with Aβ load in women. The observed Aβ-related neural differences may explain the accelerated trajectory of cognitive decline and AD progression in women.

Background:Observational studies in Asia show that dietary intake of soy isoflavones had a significant inverse association with coronary heart disease (CHD). A recent randomized controlled trial (RCT) of soy isoflavones on atherosclerosis in the US, however, failed to show their benefit. The discrepancy may be due to the much lower prevalence of S-equol producers in Westerners: Only 20-30% of Westerners produce S-equol in contrast to 50-70% in Asians. S-equol is a metabolite of dietary soy isoflavone daidzein by gut microbiome and possesses the most antiatherogenic properties among all isoflavones. Several short-duration RCTs documented that soy isoflavones improves arterial stiffness. Accumulating evidence shows that both atherosclerosis and arterial stiffness are positively associated with cognitive decline/dementia. Therefore, potentially, soy isoflavones, especially S-equol, are protective against cognitive decline/dementia. Methods/Results: This narrative review of clinical and epidemiological studies provides an overview of the health benefits of soy isoflavones and introduces S-equol. Second, we review recent evidence on the association of soy isoflavones and S-equol with CHD, atherosclerosis, and arterial stiffness as well as the association of atherosclerosis and arterial stiffness with cognitive decline/ dementia. Third, we highlight recent studies that report the association of soy isoflavones and S-equol with cognitive decline/dementia. Lastly, we discuss the future directions of clinical and epidemiological research on the relationship of S-equol and CHD and dementia.Conclusions:Evidence from observational studies and short-term RCTs suggests that S-equol is anti-atherogenic and improves arterial stiffness and may prevent CHD and cognitive impairment/ dementia. Well-designed long-term (≥ 2years) RCTs should be pursued.

AIM To assess the prevalence of, and risk factors for, depressive symptoms, comparing a sample of middle-aged adults with and without juvenile-onset Type 1 diabetes mellitus, and to determine if depressive symptoms were associated with white matter hyperintensity volume among those with Type 1 diabetes. METHODS Depressive symptoms and white matter hyperintensities were compared between adults (age range 30-65 years) with juvenile-onset Type 1 diabetes (n=130) and adults without Type 1 diabetes (n=133). The association of Type 1 diabetes with depression was computed before and after adjustment for white matter hyperintensities. Among the Type 1 diabetes group, the primary associations of interest were between depressive symptoms (Beck Depression Inventory score ≥10) and white matter hyperintensities (n=71), hyperglycaemia and physical activity. Associations between depressive symptoms and diabetes-related complications, cognitive impairment, smoking and self-reported disability were examined. Analyses were controlled for education, sex, age and antidepressant use. RESULTS Depressive symptoms were more prevalent among those with vs those without Type 1 diabetes (28% vs 3%; P

Down syndrome (DS) predisposes individuals to early Alzheimer's disease (AD). Using Pittsburgh Compound B ([11C]PiB), a pattern of striatal amyloid beta (Aβ) that is elevated relative to neocortical binding has been reported, similar to that of nondemented autosomal dominant AD mutation carriers. However, it is not known whether changes in striatal and neocortical [11C]PiB retention differ over time in a nondemented DS population when compared to changes in a nondemented elderly (NDE) population. The purpose of this work was to assess longitudinal changes in trajectories of Aβ in a nondemented DS compared to an NDE cohort. The regional trajectories for anterior ventral striatum (AVS), frontal cortex, and precuneus [11C]PiB retention were explored over time using linear mixed effects models with fixed effects of time, cohort, and time-by-cohort interactions and subject as random effects. Significant differences between DS and NDE cohort trajectories for all 3 region of interests were observed (p < 0.05), with the DS cohort showing a faster accumulation in the AVS and slower accumulation in the frontal cortex and precuneus compared to the NDE cohort. These data add to the previously reported distinct pattern of early striatal deposition not commonly seen in sporadic AD by demonstrating that individuals with DS may also accumulate Aβ at a rate faster in the AVS when compared to NDE subjects.

We hypothesized that lower untreated systolic blood pressure (SBP) would be associated with a lower risk of dementia and death up to age 95.SBP measured between 2000 and 2006 was evaluated in relationship to dementia risk and brain biomarkers from 2009-2020 (n = 177) in the Gingko Evaluation of Memory Study (GEMS), mean age 95 in 2020. Participants had measurements of brain amyloid beta (Aβ) and repeat clinical-cognitive evaluations every 6 months.By 2020, only 9 of 177 patients (5%) were alive and cognitively unimpaired (CU). Mean SBP from 2000 to 2006 was 120 mm Hg for nine alive/CU, 125 mm Hg for alive/mild cognitive impairment (MCI), and 130 mm Hg for alive/dementia (P = .03). The amount of Aβ was directly related to SBP levels. In multivariate analysis, Aβ+ in 2009 and thinner cortex were significant predictors of dementia. Excluding Aβ, SBP became a significant predictor of dementia.Low SBP untreated by antihypertensive medications was associated with significant decreased risk of dementia and less Aβ.

BackgroundAlzheimer’s Disease (AD) is the most common form of dementia and is characterized by cognitive dysfunction that impacts daily functioning. Beta-amyloid (Aβ) is a cytotoxic protein that deposits in the brain many years prior to the onset of cognitive dysfunction. The preclinical period is a stage of AD in which significant pathology is present without clinical symptoms. Aβ has been shown to deposit asymmetrically early in the AD trajectory, which has shown to have functional consequences (e.g., asymmetric hypometabolism). We aimed to investigate whether markers of AD and cognitive function were correlated with neural activation asymmetry during memory encoding tasks.MethodsWe recruited participants who were cognitively normal to undergo functional magnetic resonance imaging (fMRI), positron emission tomography (PET) imaging, and cognitive testing. We conducted analyses to identify regions of significant activation during a well-established face-name pair memory encoding task, and to identify regions of significant asymmetry. We then computed hemispheric asymmetry (negative/positive values indicate left/right asymmetry, respectively) and absolute asymmetry (greater values indicate greater asymmetry in either hemisphere) and investigated their associations with age, sex, education, global cerebral amyloid, global cerebral metabolism, memory encoding task performance, white matter hyperintensities, and multiple domains of cognitive function.ResultsWe identified expected regions of significant activation, including the hippocampus, and identified four regions with significant left-hemisphere asymmetry: superior medial frontal gyrus, middle frontal gyrus, supplemental motor area, and medial orbitofrontal gyrus, and two regions with significant right hemisphere asymmetry: putamen and ventral posterolateral nucleus of the thalamus. We found that greater left-hemisphere asymmetry in the middle frontal gyrus was correlated with greater global cerebral glucose metabolism. We also found that better performance in memory, learning, and executive attention was associated with greater absolute symmetry in the thalamus, while better visuospatial performance was associated with greater putamen absolute symmetry.DiscussionFunctional asymmetry is correlated with functional markers (e.g., glucose metabolism) in older cognitively normal adults and may reflect metabolic and cognitive changes. Longitudinal studies may help us better understand these associations and the causal impact of neural activation asymmetry.

Background Despite the well-known clinical effects of midazolam and ketamine, including sedation and memory impairment, the neural mechanisms of these distinct drugs in humans are incompletely understood. The authors hypothesized that both drugs would decrease recollection memory, task-related brain activity, and long-range connectivity between components of the brain systems for memory encoding, pain processing, and fear learning. Methods In this randomized within-subject crossover study of 26 healthy adults, the authors used behavioral measures and functional magnetic resonance imaging to study these two anesthetics, at sedative doses, in an experimental memory paradigm using periodic pain. The primary outcome, recollection memory performance, was quantified with d′ (a difference of z scores between successful recognition versus false identifications). Secondary outcomes were familiarity memory performance, serial task response times, task-related brain responses, and underlying brain connectivity from 17 preselected anatomical seed regions. All measures were determined under saline and steady-state concentrations of the drugs. Results Recollection memory was reduced under midazolam (median [95% CI], d′ = 0.73 [0.43 to 1.02]) compared with saline (d′ = 1.78 [1.61 to 1.96]) and ketamine (d′ = 1.55 [1.12 to 1.97]; P < 0.0001). Task-related brain activity was detected under saline in areas involved in memory, pain, and fear, particularly the hippocampus, insula, and amygdala. Compared with saline, midazolam increased functional connectivity to 20 brain areas and decreased to 8, from seed regions in the precuneus, posterior cingulate, and left insula. Compared with saline, ketamine decreased connectivity to 17 brain areas and increased to 2, from 8 seed regions including the hippocampus, parahippocampus, amygdala, and anterior and primary somatosensory cortex. Conclusions Painful stimulation during light sedation with midazolam, but not ketamine, can be accompanied by increased coherence in brain connectivity, even though details are less likely to be recollected as explicit memories. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

Background: Subjective cognitive decline (SCD) may be an early manifestation of pre-clinical Alzheimer’s disease. Elevated amyloid-β (Aβ) is a correlate of SCD symptoms in some individuals. The underlying neural correlates of SCD symptoms and their association with Aβ is unknown. SCD is a heterogeneous condition, and cognitive reserve may explain individual differences in its neural correlates. Objective: We investigated the association between brain activation during memory encoding and SCD symptoms, as well as with Aβ, among older individuals. We also tested the moderating role of education (an index of cognitive reserve) on the associations. Methods: We measured brain activation during the “face-name” memory-encoding fMRI task and Aβ deposition with Pittsburgh Compound-B (PiB)-PET among cognitively normal older individuals (n = 63, mean age 73.1 ± 7.4 years). We tested associations between activation and SCD symptoms by self-report measures, Aβ, and interactions with education. Results: Activation was not directly associated with SCD symptoms or Aβ. However, education moderated the association between activation and SCD symptoms in the executive control network, salience network, and subcortical regions. Greater SCD symptoms were associated with greater activation in those with higher education, but with lower activation in those with lower education. Conclusion: SCD symptoms were associated with different patterns of brain activation in the extended memory system depending on level of cognitive reserve. Greater SCD symptoms may represent a saturation of neural compensation in individuals with greater cognitive reserve, while it may reflect diminishing neural resources in individuals with lower cognitive reserve.

Introduction Systemic inflammation has been increasingly implicated in the pathogenesis of Alzheimer’s disease (AD), yet the mechanistic and temporal specificity of this relationship is poorly understood. We aimed to characterize the cross-sectional and longitudinal associations between peripheral inflammatory biomarkers, cognition, and Aβ deposition in oldest-old cognitively unimpaired (CU) adults. Methods A large sample of 139 CU older adults (mean age (range) = 85.4 (82–95)) underwent neuropsychological testing, Pittsburgh compound-B (PiB)-PET imaging and structural MRI. Hierarchical regression models examined associations between circulating inflammatory biomarkers (Interleukin-6 (IL-6), soluble Tumor Necrosis Factor receptors 1 and 2 (sTNFr1 and sTNFr2), soluble cluster of differentiation 14 (sCD14), C-reactive protein (CRP)), cognition, and global and regional Aβ deposition at baseline and over follow-up. Indices of preclinical disease, including pathologic Aβ status and hippocampal volume, were incorporated to assess conditional associations. Results At baseline evaluation, higher concentrations of IL-6 and sTNFr2 were associated with greater global Aβ burden in those with lower hippocampal volume. In longitudinal models, IL-6 predicted subsequent conversion to MCI and both IL-6 and CRP predicted greater change in global and regional Aβ deposition specifically among participants PiB-positive at baseline. These relationships withstood adjustment for demographic factors, anti-hypertensive medication use, history of diabetes, heart disease, APOE e4 carrier status, and white matter lesions. Discussion In a large prospective sample of CU adults aged 80 and over, peripheral inflammatory biomarkers were associated with and predictive of the progression of Aβ deposition. This was specific to those with biomarker evidence of preclinical AD at baseline, supporting recent evidence of disease-state-dependent differences in inflammatory expression profiles. Chronic, low-level systemic inflammation may exacerbate the deposition of Aβ pathology among those with emerging disease processes, and place individuals at a higher risk of developing clinically significant cognitive impairment.

Late-life depression (LLD) is associated with an increased risk of developing dementia; however, it is not known whether individuals with a history of LLD exhibit a more rapid rate of cognitive decline. We aimed to determine whether those with LLD experienced faster cognitive decline compared with never-depressed control (NDC) participants from the community and whether stratification of LLD into early-onset depression (EOD) and late-onset depression (LOD) subtypes revealed differing rates and domain-specific expression of cognitive decline. We conducted a prospective, longitudinal study where 185 participants with LLD (remitted) and 114 NDC were followed for 5 years on average. EOD was defined as having first lifetime depressive episode at

Recently cleared by the FDA, 7 Tesla (7 T) MRI is a rapidly growing technology that can provide higher resolution and enhanced contrast in human MRI images. However, the increased operational frequency (~ 297 MHz) hinders its full potential since it causes inhomogeneities in the images and increases the power deposition in the tissues. This work describes the optimization of an innovative radiofrequency (RF) head coil coupled design, named Tic Tac Toe, currently used in large scale human MRI scanning at 7 T; to date, this device was used in more than 1,300 neuro 7 T MRI scans. Electromagnetic simulations of the coil were performed using the finite-difference time-domain method. Numerical optimizations were used to combine the calculated electromagnetic fields produced by these antennas, based on the superposition principle, resulting in homogeneous magnetic field distributions at low levels of power deposition in the tissues. The simulations were validated in-vivo using the Tic Tac Toe RF head coil system on a 7 T MRI scanner.

Chronic low back pain (CLBP) is a leading cause of disability and is associated with neurodegenerative changes in brain structure. These changes lead to impairments in cognitive function and are consistent with those seen in aging, suggesting an accelerated aging pattern. In this study we assessed this using machine-learning estimated brain age (BA) as a holistic metric of morphometric changes associated with aging. Structural imaging data from 31 non-depressed CLBP patients and 32 healthy controls from the Pain and Interoception Imaging Network were included. Using our previously developed algorithm, we estimated BA per individual based on grey matter density. We then conducted multivariable linear modeling for effects of group, chronological age, and their interaction on BA. We also performed two voxel-wise analyses comparing grey matter density between CLBP and control individuals and the association between gray matter density and BA. There was an interaction between CLBP and greater chronological age on BA such that the discrepancy in BA between healthy and CLBP individuals was greater for older individuals. In CLBP individuals, BA was not associated with sex, current level of pain, duration of CLBP, or mild to moderate depressive symptoms. CLBP individuals had lower cerebellar grey matter density compared to healthy individuals. Brain age was associated with lower gray matter density in numerous brain regions. CLBP was associated with greater BA, which was more profound in later life. BA as a holistic metric was sensitive to differences in gray matter density in numerous regions which eluded direct comparison between groups.

We consider a model-agnostic solution to the problem of Multi-Domain Learning (MDL) for multi-modal applications. Many existing MDL techniques are model-dependent solutions which explicitly require nontrivial architectural changes to construct domain-specific modules. Thus, properly applying these MDL techniques for new problems with well-established models, e.g. U-Net for semantic segmentation, may demand various low-level implementation efforts. In this paper, given emerging multi-modal data (e.g., various structural neuroimaging modalities), we aim to enable MDL purely algorithmically so that widely used neural networks can trivially achieve MDL in a model-independent manner. To this end, we consider a weighted loss function and extend it to an effective procedure by employing techniques from the recently active area of learning-to-learn (meta-learning). Specifically, we take inner-loop gradient steps to dynamically estimate posterior distributions over the hyperparameters of our loss function. Thus, our method is model-agnostic, requiring no additional model parameters and no network architecture changes; instead, only a few efficient algorithmic modifications are needed to improve performance in MDL. We demonstrate our solution to a fitting problem in medical imaging, specifically, in the automatic segmentation of white matter hyperintensity (WMH). We look at two neuroimaging modalities (T1-MR and FLAIR) with complementary information fitting for our problem., Comment: IEEE International Symposium on Biomedical Imaging 2021

Sickle cell disease (SCD) is an inherited hemoglobinopathy that causes organ dysfunction, including cerebral vasculopathy and neurological complications. Hippocampal segmentation with newer and advanced 7 Tesla (7T) MRI protocols has revealed atrophy in specific subregions in other neurodegenerative and neuroinflammatory diseases, however, there is limited evidence of hippocampal involvement in SCD. Thus, we explored whether SCD may be also associated with abnormalities in hippocampal subregions. We conducted 7T MRI imaging in individuals with SCD, including the HbSS, HbSC and HbS/beta thalassemia genotypes (n = 53), and healthy race and age-matched controls (n = 47), using a customized head coil. Both T1- and T2-weighted images were used for automatic segmentation of the hippocampal subfields. Individuals with SCD had, on average, significantly smaller volume of the region including the Dentate Gyrus and Cornu Ammonis (CA) 2 and 3 as compared to the control group. Other hippocampal subregions also showed a trend towards smaller volumes in the SCD group. These findings support and extend previous reports of reduced volume in the temporal lobe in SCD patients. Further studies are necessary to investigate the mechanisms that lead to structural changes in the hippocampus subfields and their relationship with cognitive performance in SCD patients.

BACKGROUND: Mobility is important for independence in older age. While brain health correlates of objectively measured mobility-related features like gait and balance have been reported, we aimed to test neuroimaging and cognitive correlates of subjective measures of mobility-related confidence. METHODS: We carried out a cross-sectional observational study comprised of N=29 cognitively unimpaired older adult participants, mean age 75.8±5.8, 52% female, 24% non-white. We measured cognition, hippocampal volume, white matter hyperintensities, cerebral amyloid-β (Aβ), and gait and balance confidence. We tested associations using unadjusted Spearman correlations and correlations partialling out covariates of interest one at a time. RESULTS: Greater gait confidence was associated with better attention (unadjusted ρ=0.37, p=0.05; partially attenuated by adjustment for age, APOE4, anxiety, motivation, gait speed, and Aβ); executive performance (unadjusted ρ=0.35, p=0.06; partially attenuated by adjustment for age, APOE4, gait speed, or Aβ); and lower Aβ levels (unadjusted ρ= −0.40, p=0.04; partially attenuated by adjustment for age, depressive symptoms, motivation, or gait speed). Greater balance confidence was associated with better global cognition (unadjusted ρ=0.41, p=0.03; partially attenuated by adjustment for APOE4, gait speed, or Aβ); attention (unadjusted ρ=0.46, p=0.01; robust to adjustment); and lower Aβ levels (unadjusted ρ= −0.35, p=0.07; partially attenuated by adjustment for age, education, APOE4, depressive symptoms, anxiety, motivation, or gait speed). CONCLUSIONS: Self-reported mobility-related confidence is associated with neuroimaging and cognitive measures and would be easy for providers to use in clinical evaluations. These associations should be further evaluated in larger samples, and longitudinal studies can help determine temporality of declines.