A Framework for the Administration of Anti-amyloid Monoclonal Antibody Treatments in Early-Stage Alzheimer's Disease.

The US Food and Drug Administration (FDA) approval of lecanemab for early-stage Alzheimer's disease (AD) represents an exciting new chapter in the management of neurodegenerative disease, but likewise presents numerous clinical, technical, and financial logistical challenges for both academic and non-academic medical institutions hoping to administer this drug. Minimal resources exist that provide guidance for establishing and maintaining a lecanemab treatment program at the institutional level. The current report aims to provide healthcare institutions a framework for the planning, onboarding, and longitudinal treatment of AD with anti-amyloid monoclonal antibody treatments. We present an implementation study involving three stages: (1) feasibility assessment, (2) operations and going live, and (3) monitoring assessment. We found that implementation of lecanemab in clinical practice was feasible due to the assignment of an enterprise-wide project manager to facilitate the planning phase, a cost analysis showing that lecanemab was financially sustainable, and the development of electronic medical record tools to support operational efficiency.

Epidemiology and prevalence of dementia and Alzheimer's disease in American Indians: Data from the Strong Heart Study.

INTRODUCTION: Accurate epidemiologic estimates for dementia are lacking for American Indians, despite substantive social and health disparities. METHODS: The Strong Heart Study, a population-based cohort of 11 American Indian tribes, conducted detailed cognitive testing and examinations over two visits approximately 7 years apart. An expert panel reviewed case materials for consensus adjudication of cognitive status (intact; mild cognitive impairment [MCI]; dementia; other impaired/not MCI) and probable etiology (Alzheimer's disease [AD], vascular bain injury [VBI], traumatic brain injury [TBI], other). RESULTS: American Indians aged 70-95 years had 54% cognitive impairment including 10% dementia. VBI and AD were primary etiology approximately equal proportions (>40%). Apolipoprotein (APO) Eε4 carriers were more common among those with dementia (p = 0.040). Plasma pTau, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) were higher among those with cognitive impairment, but not amyloid beta (Aß). Cognitive intact had mean 3MSE 92.2 (SD 6.4) and mean Montreal Cognitive Assessment (MoCA) score of 21.3 (SD 3.2). DISCUSSION: This is the first population-based study to estimate the prevalence of vascular and Alzheimer's dementias in a population-based study of American Indians. HIGHLIGHTS: The Strong Heart Study is a population-based cohort of American Indian tribes, conducted over 30+ years and three US geographic regions (Northern Plains, Southern Plains, Southwest). Our teams conducted detailed cognitive testing, neurological examination, and brain imaging over two visits approximately 7 years apart. An expert panel reviewed collected materials for consensus-based adjudication of cognitive status (intact; MCI; dementia; other impaired/not MCI) and probable underlying etiology (AD; VBI; TBI; other). In this cohort of American Indians aged 70-95, 54% were adjudicated with cognitive impairment, including approximately 35% MCI and 10% dementia. These data expand on prior reports from studies using electronic health records, which had suggested prevalence, and incidence of dementia in American Indians to be more comparable to the majority population or non-Hispanic White individuals, perhaps due to latent case undercounts in clinical settings. Vascular and neurodegenerative injuries were approximately equally responsible for cognitive impairment, suggesting that reduction of cardiovascular disease is needed for primary prevention. Traumatic injury was more prevalent than in other populations, and common among those in the "other/not MCI" cognitive impairment category. Mean scores for common dementia screening instruments-even among those adjudicated as unimpaired-were relatively low compared to other populations (mean unimpaired 3MSE 92.2, SD 6.4; mean unimpaired MoCA 21.3, SD 3.2), suggesting the need for cultural and environmental adaptation of common screening and evaluation instruments.

Protocol for the Systematic Fixation, Circuit-Based Sampling, and Qualitative and Quantitative Neuropathological Analysis of Human Brain Tissue.

Human brain tissue has long been a critical resource for neuroanatomy and neuropathology, but with the advent of advanced imaging and molecular sequencing techniques, it has become possible to use human brain tissue to study, in great detail, the structural, molecular, and even functional underpinnings of human brain disease. In the century following the first description of Alzheimer's disease (AD), numerous technological advances applied to human tissue have enabled novel diagnostic approaches using diverse physical and molecular biomarkers, and many drug therapies have been tested in clinical trials (Schachter and Davis, Dialogues Clin Neurosci 2:91-100, 2000). The methods for brain procurement and tissue stabilization have remained somewhat consistently focused on formalin fixation and freezing. Although these methods have enabled research protocols of multiple modalities, new, more advanced technologies demand improved methodologies for the procurement, characterization, stabilization, and preparation of both normal and diseased human brain tissues. Here, we describe our current protocols for the procurement and characterization of fixed brain tissue, to enable systematic and precisely targeted diagnoses, and describe the novel, quantitative molecular, and neuroanatomical studies that broadly expand the use of formalin-fixed, paraffin-embedded (FFPE) tissue that will further our understanding of the mechanisms underlying human neuropathologies.

Educational and Clinical Associations With Longitudinal Cognitive Function and Brain Imaging in American Indians: The Strong Heart Study.

BACKGROUND: Little is known about incidence of vascular and Alzheimer's dementias in American Indians. METHODS We conducted a large, heterogeneous, population-based, longitudinal cohort study of brain aging in community-dwelling American Indians aged 64-95 years from 11 tribes across 3 states, with neurological examinations, 1.5T magnetic resonance imaging (MRI), and extensive cognitive testing. Visit 1 in 2010-2013 (n=817) and Visit 2 in 2017-2019 (n=403) included all willing, surviving participants. Standardized cognitive tests at both visits included Modified Mini Mental Status Examination (3MSE), Wechsler Adult Intelligence Scale digit symbol coding (WAIS), Controlled Oral Word Association fas (COWA), California Verbal Learning Test short form (CVLT). Test materials added at follow-up included Wide Range Achievement (reading) Test (WRAT) and National Alzheimer's Coordinating Center Uniform Data Set cognitive battery (v3 form C2) , including Montreal Cognitive Assessment (MoCA). MRI neuroradiologists coded infarcts, hemorrhages, white matter hyperintensities, sulcal atrophy, and ventricle enlargement. RESULTS Mean time between exams was 6.7 years (SD 1.1, range 3.8-9.1). Years of formal education had modest correlation with WRAT reading score (r=0.45). Prevalence and incidence of infarcts were (respectively) 32% and 12.8/1000 person-years (PY); hemmorhages 6% and 4.4/1000 PY; worsening sulci 74% and 19.0/1000 PY; wosening ventricle 79% and 30.1/1000 PY; worsening leukoaraiosis 44% and 26.1/1000 PY. Linear losses per year in cognitive scores were 0.6% 3MSE, 1.2% WAIS, 0.6% COWA, 2.2% CVLT. Mean MoCA scores were 18.9 (SD 4.3). DISCUSSION These are the first data on longitudinal cognitive and imaging changes in American Indians, as well as first reports of AD related features. Mean scores in MoCA were similar or lower than standard cutoffs used to diagnose dementia in other racial/ethnic groups, suggesting that standardized cognitive tests may not perform well in this population. Test validation, adaptation, and score adjustment are warranted. Years of education was a poor proxy for premorbid function, suggesting novel methods for cognitive score contextualization is also needed in this population. Evaluation of selective survival suggests attrition from death and frailty should be accounted for in causal analyses. Overall, these data represent a unique opportunity to examine neurology topics of critical importance to an understudied population.

Increased Basal Ganglia Modulatory Effective Connectivity Observed in Resting-State fMRI in Individuals With Parkinson's Disease.

Alterations to interactions between networked brain regions underlie cognitive impairment in many neurodegenerative diseases, providing an important physiological link between brain structure and cognitive function. Previous attempts to characterize the effects of Parkinson's disease (PD) on network functioning using resting-state functional magnetic resonance imaging (rs-fMRI), however, have yielded inconsistent and contradictory results. Potential problems with prior work arise in the specifics of how the area targeted by the diseases (the basal ganglia) interacts with other brain regions. Specifically, current computational models point to the fact that the basal ganglia contributions should be captured with modulatory (i.e., second-order) rather than direct (i.e., first-order) functional connectivity measures. Following this hypothesis, a principled but manageable large-scale brain architecture, the Common Model of Cognition, was used to identify differences in basal ganglia connectivity in PD by analyzing resting-state fMRI data from 111 participants (70 patients with PD; 41 healthy controls) using Dynamic Causal Modeling (DCM). Specifically, the functional connectivity of the basal ganglia was modeled as two second-level, modulatory connections that control projections from sensory cortices to the prefrontal cortex, and from the hippocampus and medial temporal lobe to the prefrontal cortex. We then examined group differences between patients with PD and healthy controls in estimated modulatory effective connectivity in these connections. The Modulatory variant of the Common Model of Cognition outperformed the Direct model across all subjects. It was also found that these second-level modulatory connections had higher estimates of effective connectivity in the PD group compared to the control group, and that differences in effective connectivity were observed for all direct connections between the PD and control groups.We make the case that accounting for modulatory effective connectivity better captures the effects of PD on network functioning and influences the interpretation of the directionality of the between-group results. Limitations include that the PD group was scanned on dopaminergic medication, results were derived from a reasonable but small number of individuals and the ratio of PD to healthy control participants was relatively unbalanced. Future research will examine if the observed effect holds for individuals with PD scanned off their typical dopaminergic medications.

Association of Performance on Dichotic Auditory Tests With Risk for Incident Dementia and Alzheimer Dementia.

Importance: Age-related hearing difficulties can include problems with signal audibility and central auditory processing. Studies have demonstrated associations between audibility and dementia risk. To our knowledge, limited data exist to determine whether audibility, central processing, or both drive these associations. Objective: To determine the associations between signal sensitivity, central auditory processing, and dementia and Alzheimer dementia (AD) risk. Design, Setting, and Participants: This follow-up observational study of a sample from the prospective Adult Changes in Thought study of dementia risk was conducted at Kaiser Permanente Washington, a western Washington health care delivery system, and included 280 volunteer participants without dementia who were evaluated from October 2003 to February 2006 with follow-up through September 2018. Analyses began in 2019 and continued through 2021. Exposures: Hearing tests included pure tone signal audibility, a monaural word recognition test, and 2 dichotic tests: the Dichotic Sentence Identification (DSI) test and the Dichotic Digits test (DDT). Main Outcomes and Measures: Cognition was assessed biennially with the Cognitive Abilities Screening Instrument (range, 1-100; higher scores are better), and scores of less than 86 prompted clinical and neuropsychological evaluations. All data were reviewed at multidisciplinary consensus conferences, and standardized criteria were used to define incident cases of dementia and probable or possible AD. Cox proportional hazard models were used to determine associations with hearing test performance. Results: A total of 280 participants (177 women [63%]; mean [SD] age, 79.5 [5.2] years). As of September 2018, there were 2196 person-years of follow-up (mean, 7.8 years) and 89 incident cases of dementia (66 not previously analyzed), of which 84 (94.4%) were AD (63 not previously analyzed). Compared with people with DSI scores of more than 80, the dementia adjusted hazard ratio (aHR) for DSI scores of less than 50 was 4.18 (95% CI, 2.37-7.38; P < .001); for a DSI score of 50 to 80, it was 1.82 (95% CI, 1.10-3.04; P = .02). Compared with people with DDT scores of more than 80, the dementia aHR for DDT scores of less than 50 was 2.66 (95% CI, 1.31-5.42; P = .01); for a DDT score of 50 to 80, it was 2.40 (95% CI, 1.45-3.98; P = .001). The AD results were similar. Pure tone averages were weakly and insignificantly associated with dementia and AD, and associations were null when controlling for DSI scores. Conclusions and Relevance: In this cohort study, abnormal central auditory processing as measured by dichotic tests was independently associated with dementia and AD risk.

Leveraging Neuroimaging Tools to Assess Precision and Accuracy in an Alzheimer's Disease Neuropathologic Sampling Protocol.

INTRODUCTION: The study of Alzheimer's disease investigates topographic patterns of degeneration in the context of connected networks comprised of functionally distinct domains using increasingly sophisticated molecular techniques. Therefore, obtaining high precision and accuracy of neuropathologic tissue sampling will enhance the reliability of molecular studies and contribute to the understanding of Alzheimer's disease pathology. Neuroimaging tools can help assess these aspects of current sampling protocols as well as contribute directly to their improvement. METHODS: Using a virtual sampling method on magnetic resonance images (MRIs) from 35 participants (21 women), we compared the precision and accuracy of traditional neuropathologic vs. neuroimaging-guided sampling. The impact of the resulting differences was assessed by evaluating the functional connectivity pattern of regions selected by each approach. RESULTS: Virtual sampling using the traditional neuropathologic approach had low neuroanatomical precision and accuracy for all cortical regions tested. Neuroimaging-guided strategies narrowed these gaps. Discrepancies in the location of traditional and neuroimaging-guided samples corresponded to differences in fMRI measures of functional connectivity. DISCUSSION: Integrating neuroimaging tools with the neuropathologic assessment will improve neuropathologic-neuroimaging correlations by helping to ensure specific functional domains are accurately sampled for quantitative molecular neuropathologic applications. Our neuroimaging-based simulation of current sampling practices provides a benchmark of precision and accuracy against which to measure improvements when using novel tissue sampling approaches. Our results suggest that relying on gross landmarks alone to select samples at autopsy leads to significant variability, even when sampled by the same neuropathologist. Further, this exercise highlights how sampling precision could be enhanced if neuroimaging were integrated with the standard neuropathologic assessment. More accurate targeting and improved biological homogeneity of sampled brain tissue will facilitate the interpretation of neuropathological analyses in AD and the downstream research applications of brain tissue from biorepositories.

Alzheimer's Disease-Related Neuropathology Among Patients with Medication Treated Type 2 Diabetes in a Community-Based Autopsy Cohort.

BACKGROUND: Diabetes is a risk factor for Alzheimer's disease and related dementias (ADRD). Epidemiologic evidence shows an association between diabetes medications and ADRD risk; cell and mouse models show diabetes medication association with AD-related neuropathologic change (ADNC). OBJECTIVE: This hypothesis-generating analysis aimed to describe autopsy-measured ADNC for individuals who used diabetes medications. METHODS: Descriptive analysis of ADNC for Adult Changes in Thought (ACT) Study autopsy cohort who used diabetes medications, including sulfonylureas, insulin, and biguanides; total N = 118. ADNC included amyloid plaque distribution (Thal phasing), neurofibrillary tangle (NFT) distribution (Braak stage), and cortical neuritic plaque density (CERAD score). We also examined quantitative measures of ADNC using the means of standardized Histelide measures of cortical PHF-tau and Aß1-42. Adjusted analyses control for age at death, sex, education, APOE genotype, and diabetes complication severity index. RESULTS: Adjusted analyses showed no significant association between any drug class and traditional neuropathologic measures compared to nonusers of that class. In adjusted Histelide analyses, any insulin use was associated with lower mean levels of Aß1-42 (-0.57 (CI: -1.12, -0.02)) compared to nonusers. Five years of sulfonylureas and of biguanides use was associated with lower levels of Aß1-42 compared to nonusers (-0.15 (CI: -0.28, -0.02), -0.31 (CI: -0.54, -0.07), respectively). CONCLUSION: Some evidence exists that diabetes medications are associated with lower levels of Aß1-42, but not traditional measures of neuropathology. Future studies are needed in larger samples to build understanding of the mechanisms between diabetes, its medications, and ADRD, and to potentially repurpose existing medications for prevention or delay of ADRD.

Reassessing relationships between appetite and adiposity in people at risk of obesity: A twin study using fMRI.

BACKGROUND: Neuroimaging studies suggest that appetitive drive is enhanced in obesity. OBJECTIVE: To test if appetitive drive varies in direct proportion to the level of body adiposity after accounting for genetic factors that contribute to both brain response and obesity risk. SUBJECTS/METHODS: Participants were adult monozygotic (n = 54) and dizygotic (n = 30) twins with at least one member of the pair with obesity. Body composition was assessed by dual-energy X-ray absorptiometry. Hormonal and appetite measures were obtained in response to a standardized meal that provided 20% of estimated daily caloric needs and to an ad libitum buffet meal. Pre- and post-meal functional magnetic resonance imaging (fMRI) assessed brain response to visual food cues in a set of a priori appetite-regulating regions. Exploratory voxelwise analyses outside a priori regions were performed with correction for multiple comparisons. RESULTS: In a group of 84 adults, the majority with obesity (75%), body fat mass was not associated with hormonal responses to a meal (glucose, insulin, glucagon-like peptide-1 and ghrelin, all P>0.40), subjective feelings of hunger (ß=-0.01 mm [95% CI -0.35, 0.34] P = 0.97) and fullness (ß=0.15 mm [-0.15, 0.44] P = 0.33), or buffet meal intake in relation to estimated daily caloric needs (ß=0.28% [-0.05, 0.60] P = 0.10). Body fat mass was also not associated with brain response to high-calorie food cues in appetite-regulating regions (Pre-meal ß=-0.12 [-0.32, 0.09] P = 0.26; Post-meal ß=0.18 [-0.02, 0.37] P = 0.09; Change by a meal ß=0.29 [-0.02, 0.61] P = 0.07). Conversely, lower fat mass was associated with being weight reduced (ß=-0.05% [-0.07, -0.03] P<0.001) and greater pre-meal activation to high-calorie food cues in the dorsolateral prefrontal cortex (Z = 3.63 P = 0.017). CONCLUSIONS: In a large study of adult twins, the majority with overweight or obesity, the level of adiposity was not associated with excess appetitive drive as assessed by behavioral, hormonal, or fMRI measures.

Relationships Between Sensorimotor Inhibition and Mobility in Older Adults With and Without Parkinson's Disease.

BACKGROUND: Reduced cortical sensorimotor inhibition is associated with mobility and cognitive impairments in people with Parkinson's disease (PD) and older adults (OAs). However, there is a lack of clarity regarding the relationships among sensorimotor, cognitive, and mobility impairments. The purpose of this study was to determine how cortical sensorimotor inhibition relates to impairments in mobility and cognition in people with PD and OAs. METHOD: Cortical sensorimotor inhibition was characterized with short-latency afferent inhibition (SAI) in 81 people with PD and 69 OAs. Six inertial sensors recorded single- and dual-task gait and postural sway characteristics during a 2-minute walk and a 1-minute quiet stance. Cognition was assessed across the memory, visuospatial, executive function, attention, and language domains. RESULTS: SAI was significantly impaired in the PD compared to the OA group. The PD group preformed significantly worse across all gait and postural sway tasks. In PD, SAI significantly correlated with single-task foot strike angle and stride length variability, sway area, and jerkiness of sway in the coronal and sagittal planes. In OAs, SAI significantly related to single-task gait speed and stride length, dual-task stride length, and immediate recall (memory domain). No relationship among mobility, cognition, and SAI was observed. CONCLUSIONS: Impaired SAI related to slower gait in OA and to increased gait variability and postural sway in people with PD, all of which have been shown to be related to increased fall risk.

Learning Cortical Parcellations Using Graph Neural Networks.

Deep learning has been applied to magnetic resonance imaging (MRI) for a variety of purposes, ranging from the acceleration of image acquisition and image denoising to tissue segmentation and disease diagnosis. Convolutional neural networks have been particularly useful for analyzing MRI data due to the regularly sampled spatial and temporal nature of the data. However, advances in the field of brain imaging have led to network- and surface-based analyses that are often better represented in the graph domain. In this analysis, we propose a general purpose cortical segmentation method that, given resting-state connectivity features readily computed during conventional MRI pre-processing and a set of corresponding training labels, can generate cortical parcellations for new MRI data. We applied recent advances in the field of graph neural networks to the problem of cortical surface segmentation, using resting-state connectivity to learn discrete maps of the human neocortex. We found that graph neural networks accurately learn low-dimensional representations of functional brain connectivity that can be naturally extended to map the cortices of new datasets. After optimizing over algorithm type, network architecture, and training features, our approach yielded mean classification accuracies of 79.91% relative to a previously published parcellation. We describe how some hyperparameter choices including training and testing data duration, network architecture, and algorithm choice affect model performance.

Sensorimotor Inhibition and Mobility in Genetic Subgroups of Parkinson's Disease.

Background: Mobility and sensorimotor inhibition impairments are heterogeneous in Parkinson's disease (PD). Genetics may contribute to this heterogeneity since the apolipoprotein (APOE) ε4 allele and glucocerebrosidase (GBA) gene variants have been related to mobility impairments in otherwise healthy older adult (OA) and PD cohorts. The purpose of this study is to determine if APOE or GBA genetic status affects sensorimotor inhibition and whether the relationship between sensorimotor inhibition and mobility differs in genetic sub-groups of PD. Methods: Ninety-three participants with idiopathic PD (53 non-carriers; 23 ε4 carriers; 17 GBA variants) and 72 OA (45 non-carriers; 27 ε4 carriers) had sensorimotor inhibition characterized by short-latency afferent inhibition. Mobility was assessed in four gait domains (pace/turning, rhythm, trunk, variability) and two postural sway domains (area/jerkiness and velocity) using inertial sensors. Results: Sensorimotor inhibition was worse in the PD than OA group, with no effect of genetic status. Gait pace/turning was slower and variability was higher (p < 0.01) in PD compared to OA. Postural sway area/jerkiness (p < 0.01) and velocity (p < 0.01) were also worse in the PD than OA group. Genetic status was not significantly related to any gait or postural sway domain. Sensorimotor inhibition was significantly correlated with gait variability (r = 0.27; p = 0.02) and trunk movement (r = 0.23; p = 0.045) in the PD group. In PD non-carriers, sensorimotor inhibition related to variability (r = 0.35; p = 0.010) and trunk movement (r = 0.31; p = 0.025). In the PD ε4 group, sensorimotor inhibition only related to rhythm (r = 0.47; p = 0.024), while sensorimotor inhibition related to pace/turning (r = -0.49; p = 0.046) and rhythm (r = 0.59; p = 0.013) in the PD GBA group. Sensorimotor inhibition was significantly correlated with gait pace/turning (r = -0.27; p = 0.04) in the OA group. There was no relationship between sensorimotor inhibition and postural sway. Conclusion: ε4 and GBA genetic status did not affect sensorimotor inhibition or mobility impairments in this PD cohort. However, worse sensorimotor inhibition was associated with gait variability in PD non-carriers, but with gait rhythm in PD ε4 carriers and with gait rhythm and pace in PD with GBA variants. Impaired sensorimotor inhibition had a larger effect on mobility in people with PD than OA and affected different domains of mobility depending on genetic status.

White Matter Lesions in Mild Cognitive Impairment and Idiopathic Parkinson's Disease: Multimodal Advanced MRI and Cognitive Associations.

Cerebrovascular disease is a common comorbidity in older adults, typically assessed in terms of white matter hyperintensities (WMHs) on MRI. While it is well known that WMHs exacerbate cognitive symptoms, the exact relation of WMHs with cognitive performance and other degenerative diseases is unknown. Furthermore, based on location, WMHs are often classified into periventricular and deep WMHs and are believed to have different pathological origins. Whether the two types of WMHs influence cognition differently is unclear. Using regression models, we assessed the independent association of these two types of WMHs with cognitive performance in two separate studies focused on distinct degenerative diseases, early Alzheimer's (mild cognitive impairment), and Parkinson's disease. We further tested if the two types of WMHs were differentially associated with reduced cortical cerebral blood flow (CBF) as measured by arterial spin labeling and increased mean diffusivity (MD, a marker of tissue injury) as measured by diffusion imaging. Our approach revealed that both deep and periventricular WMHs were associated with poor performance on tests of global cognition (Montreal cognitive Assessment, MoCA), task processing (Trail making test), and category fluency in the study of mild cognitive impairment. They were associated with poor performance in global cognition (MoCA) and category fluency in the Parkinson's disease study. Of note, more associations were detected between cognitive performance and deep WMHs than between cognitive performance and periventricular WMHs. Mechanistically, both deep and periventricular WMHs were associated with increased MD. Both deep and periventricular WMHs were also associated with reduced CBF in the gray matter.

Resting-State Cerebello-Cortical Dysfunction in Parkinson's Disease.

Purpose: Recently, the cerebellum's role in Parkinson's disease (PD) has been highlighted. Therefore, this study sought to test the hypothesis that functional connectivity (FC) between cerebellar and cortical nodes of the resting-state networks differentiates PD patients from controls by scanning participants at rest using functional magnetic resonance imaging (fMRI) and investigating connectivity of the cerebellar nodes of the resting-state networks. Materials and Methods: Sixty-two PD participants off medication for at least 12 h and 33 normal controls (NCs) were scanned at rest using blood oxygenation level-dependent fMRI scans. Motor and cognitive functions were assessed with the Movement Disorder Society's Revision of the Unified Parkinson's Disease Rating Scale III and Montreal Cognitive Assessment, respectively. Connectivity was investigated with cerebellar seeds defined by Buckner's 7-network atlas. Results: PD participants had significant differences in FC when compared to NC participants. Most notably, PD patients had higher FC between cerebellar nodes of the somatomotor network (SMN) and the corresponding cortical nodes. Cognitive functioning was differentially associated with connectivity of the cerebellar SMN and dorsal attention network. Further, cerebellar connectivity of frontoparietal and default mode networks correlated with the severity of motor function. Conclusion: Our study demonstrates altered cerebello-cortical FC in PD, as well as an association of this FC with PD-related motor and cognitive disruptions, thus providing additional evidence for the cerebellum's role in PD.

Correction: Genetic data and cognitively defined late-onset Alzheimer's disease subgroups.

This article was originally published under standard licence, but has now been made available under a [CC BY 4.0] license. The PDF and HTML versions of the paper have been modified accordingly.

Salience network connectivity is reduced by a meal and influenced by genetic background and hypothalamic gliosis.

BACKGROUND/OBJECTIVES: The salience network (SN) comprises brain regions that evaluate cues in the external environment in light of internal signals. We examined the SN response to meal intake and potential genetic and acquired influences on SN function. SUBJECTS/METHODS: Monozygotic (MZ; 40 pairs) and dizygotic (15 pairs) twins had body composition and plasma metabolic profile evaluated (glucose, insulin, leptin, ghrelin, and GLP-1). Twins underwent resting-state functional magnetic resonance imaging (fMRI) scans before and after a standardized meal. The strength of SN connectivity was analyzed pre- and post-meal and the percentage change elicited by a meal was calculated. A multi-echo T2 MRI scan measured T2 relaxation time, a radiologic index of gliosis, in the mediobasal hypothalamus (MBH) and control regions. Statistical approaches included intraclass correlations (ICC) to investigate genetic influences and within-pair analyses to exclude genetic confounders. RESULTS: SN connectivity was reduced by a meal ingestion (ß = -0.20; P < 0.001). Inherited influences on both pre- and post-meal connectivity were present (ICC MZ twins 26%, P < 0.05 and 47%, P < 0.001, respectively), but not percentage change in response to the meal. SN connectivity in response to a meal did not differ between participants with obesity and of normal weight (χ2(1) = 0.93; P = 0.33). However, when participants were classified as having high or low signs of MBH gliosis, the high MBH gliosis group failed to reduce the connectivity in response to a meal (z = -1.32; P = 0.19). Excluding genetic confounders, the percentage change in SN connectivity by a meal correlated to body fat percentage (r = 0.24; P < 0.01). CONCLUSIONS: SN connectivity was reduced by a meal, indicating potential participation of the SN in control of feeding. The strength of SN connectivity is inherited, but the degree to which SN connectivity is reduced by eating appears to be influenced by adiposity and the presence of hypothalamic gliosis.

Genetic data and cognitively defined late-onset Alzheimer's disease subgroups.

Categorizing people with late-onset Alzheimer's disease into biologically coherent subgroups is important for personalized medicine. We evaluated data from five studies (total n = 4050, of whom 2431 had genome-wide single-nucleotide polymorphism (SNP) data). We assigned people to cognitively defined subgroups on the basis of relative performance in memory, executive functioning, visuospatial functioning, and language at the time of Alzheimer's disease diagnosis. We compared genotype frequencies for each subgroup to those from cognitively normal elderly controls. We focused on APOE and on SNPs with p < 10-5 and odds ratios more extreme than those previously reported for Alzheimer's disease (<0.77 or >1.30). There was substantial variation across studies in the proportions of people in each subgroup. In each study, higher proportions of people with isolated substantial relative memory impairment had ≥1 APOE ε4 allele than any other subgroup (overall p = 1.5 × 10-27). Across subgroups, there were 33 novel suggestive loci across the genome with p < 10-5 and an extreme OR compared to controls, of which none had statistical evidence of heterogeneity and 30 had ORs in the same direction across all datasets. These data support the biological coherence of cognitively defined subgroups and nominate novel genetic loci.

Diagnostic Classification of ADHD Versus Control: Support Vector Machine Classification Using Brief Neuropsychological Assessment.

Objective: Common methods for clinical diagnosis include clinical interview, behavioral questionnaires, and neuropsychological assessment. These methods rely on clinical interpretation and have variable reliability, sensitivity, and specificity. The goal of this study was to evaluate the utility of machine learning in the prediction and classification of children with ADHD-Combined presentation (ADHD-C) using brief neuropsychological measures (d2 Test of Attention, Children with ADHD-C and typically developing control children completed semi-structured clinical interviews and measures of attention/concentration and parents completed symptom severity questionnaires. Method: We used a forward feature selection method to identify the most informative neuropsychological features for support vector machine (SVM) classification and a decision tree model to derive a rule-based model. Results: The SVM model yielded excellent classification accuracy (100%) of individual children with and without ADHD (1.0). Decision tree algorithms identified individuals with and without ADHD-C with 100% sensitivity and specificity. Conclusion:This study observed highly accurate statistical diagnostic classification, at the individual level, in a sample of children with ADHD-C. The findings suggest data-driven behavioral algorithms based on brief neuropsychological data may present an efficient and accurate diagnostic tool for clinicians.

Cognitive associations with comprehensive gait and static balance measures in Parkinson's disease.

INTRODUCTION: Gait and balance impairments are cardinal features of Parkinson's disease (PD) that require cognitive input. However, the extent to which specific gait and balance characteristics relate to cognition in PD is unclear. In addition, independent models of gait and balance have not been developed from the same cohort. We aimed to i) develop models of gait and balance in a large PD cohort and ii) determine which gait and balance characteristics best related to cognition. METHODS: One hundred and ninety-eight people with PD were recruited to the Pacific Udall Center. Using six inertial sensors (APDM, Inc.), comprehensive gait measurements were collected over a 2-min continuous walk and comprehensive static balance measures were collected during a 60-second standing task. Six domains of cognition were assessed: global cognition, attention, executive function, language, memory, and visuospatial function. Correlations and hierarchical linear regression determined independent associations. RESULTS: Principal components analysis identified a gait model containing four domains accounting for 80.1% of total variance: pace/turning, rhythm, variability, and trunk. The balance model contained four independent domains accounting for 84.5% of total variance: sway area/jerkiness, sway velocity, sway frequency anteroposterior, and sway frequency mediolateral. Gait domains of pace/turning and variability were strongly associated with attention and executive function. Sway area and jerkiness of balance associated with attention and visuospatial function. CONCLUSIONS: Gait and balance characteristics were associated with specific types of cognition. The specific relationships between gait or balance with cognitive functions suggests shared cerebral cortical circuitry for mobility and cognitive functions.

Lifestyle Risk Factors and Findings on Brain Magnetic Resonance Imaging of Older Adult American Indians: The Strong Heart Study.

BACKGROUND: Clinical stroke is prevalent in American Indians, but the lifestyle risk factors for vascular brain injury have not been well-studied in this population. The purpose of this study was to correlate brain magnetic resonance imaging (MRI) findings with obesity, alcohol use, and smoking behaviors in elderly American Indians from the Strong Heart Study. METHODS: Cranial MRI scans (n = 789) were analyzed for dichotomous measures of infarcts, hemorrhages, white matter hyperintensities (WMH), and cerebral atrophy and continuous measures of total brain, WMH, and hippocampal volume. Poisson regression was used to estimate prevalence ratios, and linear regression was used to estimate measures of association for continuous outcomes. Models were adjusted for the risk factors of interest as well as age, sex, study site, income, education, hypertension, diabetes, and low-density lipoprotein cholesterol. RESULTS: Smoking was associated with increased hippocampal atrophy (p = 0.002) and increased prevalence of sulcal widening (p < 0.001). Relative to nonsmokers, smokers with more than 25 pack-years of smoking had a 27% (95% CI 7-47%) increased prevalence of high-grade sulci, p = 0.005. Body mass index was inversely associated with prevalence of nonlacunar infarcts and sulcal widening (all p = 0.004). Alcohol use was not significantly associated with any of the measured MRI findings. CONCLUSIONS: This study found similar associations between smoking and vascular brain injury among American Indians, as seen in other populations. In particular, these findings support the role of smoking as a key correlate for cerebral atrophy.