Brain network decoupling with increased serum neurofilament and reduced cognitive function in Alzheimer's disease.

Neurofilament light chain, a putative measure of neuronal damage, is measurable in blood and CSF and is predictive of cognitive function in individuals with Alzheimer's disease. There has been limited prior work linking neurofilament light and functional connectivity, and no prior work has investigated neurofilament light associations with functional connectivity in autosomal dominant Alzheimer's disease. Here, we assessed relationships between blood neurofilament light, cognition, and functional connectivity in a cross-sectional sample of 106 autosomal dominant Alzheimer's disease mutation carriers and 76 non-carriers. We employed an innovative network-level enrichment analysis approach to assess connectome-wide associations with neurofilament light. Neurofilament light was positively correlated with deterioration of functional connectivity within the default mode network and negatively correlated with connectivity between default mode network and executive control networks, including the cingulo-opercular, salience, and dorsal attention networks. Further, reduced connectivity within the default mode network and between the default mode network and executive control networks was associated with reduced cognitive function. Hierarchical regression analysis revealed that neurofilament levels and functional connectivity within the default mode network and between the default mode network and the dorsal attention network explained significant variance in cognitive composite scores when controlling for age, sex, and education. A mediation analysis demonstrated that functional connectivity within the default mode network and between the default mode network and dorsal attention network partially mediated the relationship between blood neurofilament light levels and cognitive function. Our novel results indicate that blood estimates of neurofilament levels correspond to direct measurements of brain dysfunction, shedding new light on the underlying biological processes of Alzheimer's disease. Further, we demonstrate how variation within key brain systems can partially mediate the negative effects of heightened total serum neurofilament levels, suggesting potential regions for targeted interventions. Finally, our results lend further evidence that low-cost and minimally invasive blood measurements of neurofilament may be a useful marker of brain functional connectivity and cognitive decline in Alzheimer's disease.

Accelerated longitudinal changes and ordering of Alzheimer disease biomarkers across the adult lifespan.

The temporal evolutions and relative orderings of Alzheimer disease biomarkers, including CSF amyloid-ß42 (Aß42), Aß40, total tau (Tau) and phosphorylated tau181 (pTau181), standardized uptake value ratio (SUVR) from the molecular imaging of cerebral fibrillar amyloid-ß with PET using the 11C-Pittsburgh Compound-B (PiB), MRI-based hippocampal volume and cortical thickness and cognition have been hypothesized but not yet fully tested with longitudinal data for all major biomarker modalities among cognitively normal individuals across the adult lifespan starting from 18 years. By leveraging a large harmonized database from 8 biomarker studies with longitudinal data from 2609 participants in cognition, 873 in MRI biomarkers, 519 in PET PiB imaging and 475 in CSF biomarkers for a median follow-up of 5-6 years, we estimated the longitudinal trajectories of all major Alzheimer disease biomarkers as functions of baseline age that spanned from 18 to 103 years, located the baseline age window at which the longitudinal rates of change accelerated and further examined possible modifying effects of apolipoprotein E (APOE) genotype. We observed that participants 18-45 years at baseline exhibited learning effects on cognition and unexpected directions of change on CSF and PiB biomarkers. The earliest acceleration of longitudinal change occurred for CSF Aß42 and Aß42/Aß40 ratio (with an increase) and for Tau, and pTau181 (with a decrease) at the next baseline age interval of 45-50 years, followed by an accelerated increase for PiB SUVR at the baseline age of 50-55 years and an accelerated decrease for hippocampal volume at the baseline age of 55-60 years and finally by an accelerated decline for cortical thickness and cognition at the baseline age of 65-70 years. Another acceleration in the rate of change occurred at the baseline age of 65-70 years for Aß42/Aß40 ratio, Tau, pTau181, PiB SUVR and hippocampal volume. Accelerated declines in hippocampal volume and cognition continued after 70 years. For participants 18-45 years at baseline, significant increases in Aß42 and Aß42/Aß40 ratio and decreases in PiB SUVR occurred in APOE ɛ4 non-carriers but not carriers. After age 45 years, APOE ɛ4 carriers had greater magnitudes than non-carriers in the rates of change for all CSF biomarkers, PiB SUVR and cognition. Our results characterize the temporal evolutions and relative orderings of Alzheimer disease biomarkers across the adult lifespan and the modification effect of APOE ɛ4. These findings may better inform the design of prevention trials on Alzheimer disease.

CSF Tau phosphorylation at Thr205 is associated with loss of white matter integrity in autosomal dominant Alzheimer disease.

BACKGROUND: Hyperphosphorylation of tau leads to conformational changes that destabilize microtubules and hinder axonal transport in Alzheimer's disease (AD). However, it remains unknown whether white matter (WM) decline due to AD is associated with specific Tau phosphorylation site(s). METHODS: In autosomal dominant AD (ADAD) mutation carriers (MC) and non-carriers (NC) we compared cerebrospinal fluid (CSF) phosphorylation at tau sites (pT217, pT181, pS202, and pT205) and total tau with WM measures, as derived from diffusion tensor imaging (DTI), and cognition. A WM composite metric, derived from a principal component analysis, was used to identify spatial decline seen in ADAD. RESULTS: The WM composite explained over 70% of the variance in MC. WM regions that strongly contributed to the spatial topography were located in callosal and cingulate regions. Loss of integrity within the WM composite was strongly associated with AD progression in MC as defined by the estimated years to onset (EYO) and cognitive decline. A linear regression demonstrated that amyloid, gray matter atrophy and phosphorylation at CSF tau site pT205 each uniquely explained a reduction in the WM composite within MC that was independent of vascular changes (white matter hyperintensities), and age. Hyperphosphorylation of CSF tau at other sites and total tau did not significantly predict WM composite loss. CONCLUSIONS: We identified a site-specific relationship between CSF phosphorylated tau and WM decline within MC. The presence of both amyloid deposition and Tau phosphorylation at pT205 were associated with WM composite loss. These findings highlight a primary AD-specific mechanism for WM dysfunction that is tightly coupled to symptom manifestation and cognitive decline.

Tau PET in autosomal dominant Alzheimer's disease: relationship with cognition, dementia and other biomarkers.

Tauopathy is a hallmark pathology of Alzheimer's disease with a strong relationship with cognitive impairment. As such, understanding tau may be a key to clinical interventions. In vivo tauopathy has been measured using cerebrospinal fluid assays, but these do not provide information about where pathology is in the brain. The introduction of PET ligands that bind to paired helical filaments provides the ability to measure the amount and distribution of tau pathology. The heritability of the age of dementia onset tied to the specific mutations found in autosomal dominant Alzheimer's disease families provides an elegant model to study the spread of tau across the course of the disease as well as the cross-modal relationship between tau and other biomarkers. To better understand the pathobiology of Alzheimer's disease we measured levels of tau PET binding in individuals with dominantly inherited Alzheimer's disease using data from the Dominantly Inherited Alzheimer Network (DIAN). We examined cross-sectional measures of amyloid-ß, tau, glucose metabolism, and grey matter degeneration in 15 cognitively normal mutation non-carriers, 20 asymptomatic carriers, and 15 symptomatic mutation carriers. Linear models examined the association of pathology with group, estimated years to symptom onset, as well as cross-modal relationships. For comparison, tau PET was acquired on 17 older adults with sporadic, late onset Alzheimer disease. Tau PET binding was starkly elevated in symptomatic DIAN individuals throughout the cortex. The brain areas demonstrating elevated tau PET binding overlapped with those seen in sporadic Alzheimer's disease, but with a greater cortical involvement and greater levels of binding despite similar cognitive impairment. Tau PET binding was elevated in the temporal lobe, but the most prominent loci of pathology were in the precuneus and lateral parietal regions. Symptomatic mutation carriers also demonstrated elevated tau PET binding in the basal ganglia, consistent with prior work with amyloid-ß. The degree of tau tracer binding in symptomatic individuals was correlated to other biomarkers, particularly markers of neurodegeneration. In addition to the differences seen with tau, amyloid-ß was increased in both asymptomatic and symptomatic groups relative to non-carriers. Glucose metabolism showed decline primarily in the symptomatic group. MRI indicated structural degeneration in both asymptomatic and symptomatic cohorts. We demonstrate that tau PET binding is elevated in symptomatic individuals with dominantly inherited Alzheimer's disease. Tau PET uptake was tied to the onset of cognitive dysfunction, and there was a higher amount, and different regional pattern of binding compared to late onset, non-familial Alzheimer's disease.

Blood Pressure and Memory: Novel Approaches to Modeling Nonlinear Effects in Longitudinal Studies.

BACKGROUND: Linear models cannot capture nonlinear associations when the relationships between cognition and risk factors vary across risk levels. We demonstrate a method of modelling nonlinear associations using the example of blood pressure (BP) and memory. METHODS: We measured memory and BP (in mm Hg) annually for 10 years in a population-based cohort (N=1982) aged 65+. We evaluated the relationship between BP and memory at the same time points using both linear mixed models and generalized additive mixed models with smoothing splines, adjusting for relevant covariates. RESULTS: Linear mixed models found no significant associations. Generalized additive mixed models detected different associations between BP and memory across baseline BP categories (normotensive, hypertensive, hypotensive). Among normotensives, systolic blood pressure (SBP)/diastolic blood pressure (DBP) around 140/80 was associated with the highest, while SBP/DBP around 110/60 was associated with the lowest, predicted memory scores. Among hypertensives, SBP/DBP around 130/85 was associated with the highest, while SBP/DBP around 150/65 was associated with the lowest, predicted memory scores. Among hypotensives, no significant association was found. Among both normotensives and hypertensives, a DBP >75 was associated with better memory. CONCLUSIONS: By modelling nonlinear associations, we showed that the relationship between BP and memory performance varied by baseline BP among normotensives and hypertensives.

Staging biomarkers in preclinical autosomal dominant Alzheimer's disease by estimated years to symptom onset.

INTRODUCTION: Staging preclinical Alzheimer disease (AD) by the expected years to symptom onset (EYO) in autosomal dominant AD (ADAD) through biomarker correlations is important. METHODS: We estimated the correlation matrix between EYO/cognition and imaging/CSF biomarkers, and searched for the EYO cutoff where a change in the correlations occurred before and after the cutoff among the asymptomatic mutation carriers of ADAD. We then estimated the longitudinal rate of change for biomarkers/cognition within each preclinical stage defined by the EYO. RESULTS: Based on the change in the correlations, the preclinical ADAD was divided by EYOs -7 and -13 years. Mutation carriers demonstrated a temporal ordering of biomarker/cognition changes across the three preclinical stages. DISCUSSION: Duration of each preclinical stage can be estimated in ADAD, facilitating better planning of prevention trials with the EYO cutoffs under the recently released FDA guidance. The generalization of these results to sporadic AD warrants further investigation.

A harmonized longitudinal biomarkers and cognition database for assessing the natural history of preclinical Alzheimer's disease from young adulthood and for designing prevention trials.

INTRODUCTION: Large longitudinal biomarkers database focusing on middle age is needed for Alzheimer's disease (AD) prevention. METHODS: Data for cerebrospinal fluid analytes, molecular imaging of cerebral fibrillar ß-amyloid with positron emission tomography, magnetic resonance imaging-based brain structures, and clinical/cognitive outcomes were harmonized across eight AD biomarker studies. Statistical power was estimated. RESULTS: The harmonized database included 7779 participants with clinical/cognitive data: 3542 were 18∼65 years at the baseline, 5865 had longitudinal cognitive data for a median of 4.7 years, 2473 participated in the cerebrospinal fluid studies (906 had longitudinal data), 2496 participated in the magnetic resonance imaging studies (1283 had longitudinal data), and 1498 participated in the positron emission tomography amyloid studies (849 had longitudinal data). The database provides adequate power for detecting early biomarker changes, and demonstrates the feasibility of AD prevention trials on middle-aged individuals. DISCUSSION: The harmonized database is an optimum resource to design AD prevention trials decades before symptomatic onset.

A novel cognitive disease progression model for clinical trials in autosomal-dominant Alzheimer's disease.

Clinical trial outcomes for Alzheimer's disease are typically analyzed by using the mixed model for repeated measures (MMRM) or similar models that compare an efficacy scale change from baseline between treatment arms with or without participants' disease stage as a covariate. The MMRM focuses on a single-point fixed follow-up duration regardless of the exposure for each participant. In contrast to these typical models, we have developed a novel semiparametric cognitive disease progression model (DPM) for autosomal dominant Alzheimer's disease based on the Dominantly Inherited Alzheimer Network (DIAN) observational study. This model includes 3 novel features, in which the DPM (1) aligns and compares participants by disease stage, (2) uses a proportional treatment effect similar to the concept of the Cox proportional hazard ratio, and (3) incorporates extended follow-up data from participants with different follow-up durations using all data until last participant visit. We present the DPM model developed by using the DIAN observational study data and demonstrate through simulation that the cognitive DPM used in hypothetical intervention clinical trials produces substantial gains in power compared with the MMRM.

The DIAN-TU Next Generation Alzheimer's prevention trial: Adaptive design and disease progression model.

INTRODUCTION: The Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) trial is an adaptive platform trial testing multiple drugs to slow or prevent the progression of Alzheimer's disease in autosomal dominant Alzheimer's disease (ADAD) families. With completion of enrollment of the first two drug arms, the DIAN-TU now plans to add new drugs to the platform, designated as the Next Generation (NexGen) prevention trial. METHODS: In collaboration with ADAD families, philanthropic organizations, academic leaders, the DIAN-TU Pharma Consortium, the National Institutes of Health, and regulatory colleagues, the DIAN-TU developed innovative clinical study designs for the DIAN-TU NexGen prevention trial. RESULTS: Our expanded trial toolbox consists of a disease progression model for ADAD, primary end point DIAN-TU cognitive performance composite, biomarker development, self-administered cognitive assessments, adaptive dose adjustments, and blinded data collection through the last participant completion. CONCLUSION: These steps represent elements to improve efficacy of the adaptive platform trial and a continued effort to optimize prevention and treatment trials in ADAD.

In vivo assessment of amyloid-ß deposition in nondemented very elderly subjects.

OBJECTIVE: This study examined amyloid-ß (Aß) deposition in 190 nondemented subjects aged ≥82 years to determine the proportion of Aß-positive scans and associations with cognition, apolipoprotein E (APOE) status, brain volume, and Ginkgo biloba (Gb) treatment. METHODS: Subjects who agreed to participate had a brain magnetic resonance imaging and positron emission tomography scan with (11) C-labeled Pittsburgh compound B (PiB) following completion of a Gb treatment clinical trial. The youngest subject in this imaging study was 82 years, and the mean age of the subjects was 85.5 years at the time of the scans; 152 (80%) were cognitively normal, and 38 (20%) were diagnosed with mild cognitive impairment (MCI) at the time of the PiB study. RESULTS: A high proportion of the cognitively normal subjects (51%) and MCI subjects (68%) were PiB-positive. The APOE*4 allele was more prevalent in PiB-positive than in PiB-negative subjects (30% vs 6%). Measures of memory, language, and attentional functions were worse in PiB-positive than in PiB-negative subjects, when both normal and MCI cases were analyzed together; however, no significant associations were observed within either normal or MCI subject groups alone. There was no relationship between Gb treatment and Aß deposition as determined by PiB. INTERPRETATION: The data revealed a 55% prevalence of PiB positivity in nondemented subjects age >80 years and 85% PiB positivity in the APOE*4 nondemented elderly subjects. The findings also showed that long-term exposure to Gb did not affect the prevalence of cerebral Aß deposition.

How well do MCI criteria predict progression to severe cognitive impairment and dementia?

BACKGROUND: The International Working Group (IWG) criteria for mild cognitive impairment have variable utility in predicting progression to dementia, partly depending on the setting. We explored an empiric approach to optimize the criteria and cutoff points in a population study. METHODS: In a cohort of adults aged 65 years or older, we identified 1129 individuals with normal or only mildly impaired cognition by cognitive classification, and 1146 individuals without dementia (Clinical Dementia Rating <1). Operationally defining the IWG criterion set, we examined its sensitivity and specificity for the development of severe cognitive impairment and dementia (Clinical Dementia Rating ≥1) over 4 years. We then disaggregated the criteria and used Classification and Regression Tree analyses to identify the optimal predictive model. RESULTS: The operational IWG criteria had 49% sensitivity and 86% specificity for the outcome of severe cognitive impairment, and 40% sensitivity and 84% specificity for the outcome of dementia. Classification and Regression Tree modeling improved sensitivity to 82% for the cognitive outcome and 76% for the dementia outcome; specificity remained high. Memory scores were the most important predictors for both outcomes. The optimal cutoff points were around 1.0 SD below the age-education mean. The best fit was observed when prediction was modeled separately for each age-education group. CONCLUSIONS: Objective cognitive measurements contributed more to the prediction of dementia than subjective and functional measures. Those with less education only required memory testing, whereas those with more education required assessment of several cognitive domains. In cases in which only overall norms are available, the appropriate threshold will vary according to the individual's age and education.

Subtle gait changes in patients with REM sleep behavior disorder.

Many people with rapid eye movement (REM) sleep behavior disorder (RBD) have an underlying synucleinopathy, the most common of which is Lewy body disease. Identifying additional abnormal clinical features may help in identifying those at greater risk of evolving to a more severe syndrome. Because gait disorders are common in the synucleinopathies, early abnormalities in gait in those with RBD could help in identifying those at increased risk of developing overt parkinsonism and/or cognitive impairment. We identified 42 probable RBD subjects and 492 controls using the Mayo Sleep Questionnaire and assessed gait velocity, cadence, and stride dynamics with an automated gait analysis system. Cases and controls were similar in age (79.9 ± 4.7 and 80.1 ± 4.7, P = 0.74), Unified Parkinson's Disease Rating Scale Part III (UPDRS) score (3.3 ± 5.5 and 1.9 ± 4.1, P = 0.21) and Mini-Mental State Examination scores (27.2 ± 1.9 and 27.7 ± 1.6, P = 0.10). A diagnosis of probable RBD was associated with decreased velocity (-7.9 cm/s; 95% confidence interval [CI], -13.8 to -2.0; P < 0.01), cadence (-4.4 steps/min; 95% CI, -7.6 to -1.3; P < 0.01), significantly increased double limb support variability (30%; 95% CI, 6-60; P = 0.01), and greater stride time variability (29%; 95% CI, 2-63; P = 0.03) and swing time variability (46%; 95% CI, 15-84; P < 0.01). Probable RBD is associated with subtle gait changes prior to overt clinical parkinsonism. Diagnosis of probable RBD supplemented by gait analysis may help as a screening tool for disorders of α-synuclein.

Advanced structural brain aging in preclinical autosomal dominant Alzheimer disease.

BACKGROUND: "Brain-predicted age" estimates biological age from complex, nonlinear features in neuroimaging scans. The brain age gap (BAG) between predicted and chronological age is elevated in sporadic Alzheimer disease (AD), but is underexplored in autosomal dominant AD (ADAD), in which AD progression is highly predictable with minimal confounding age-related co-pathology. METHODS: We modeled BAG in 257 deeply-phenotyped ADAD mutation-carriers and 179 non-carriers from the Dominantly Inherited Alzheimer Network using minimally-processed structural MRI scans. We then tested whether BAG differed as a function of mutation and cognitive status, or estimated years until symptom onset, and whether it was associated with established markers of amyloid (PiB PET, CSF amyloid-ß-42/40), phosphorylated tau (CSF and plasma pTau-181), neurodegeneration (CSF and plasma neurofilament-light-chain [NfL]), and cognition (global neuropsychological composite and CDR-sum of boxes). We compared BAG to other MRI measures, and examined heterogeneity in BAG as a function of ADAD mutation variants, APOE Îµ4 carrier status, sex, and education. RESULTS: Advanced brain aging was observed in mutation-carriers approximately 7 years before expected symptom onset, in line with other established structural indicators of atrophy. BAG was moderately associated with amyloid PET and strongly associated with pTau-181, NfL, and cognition in mutation-carriers. Mutation variants, sex, and years of education contributed to variability in BAG. CONCLUSIONS: We extend prior work using BAG from sporadic AD to ADAD, noting consistent results. BAG associates well with markers of pTau, neurodegeneration, and cognition, but to a lesser extent, amyloid, in ADAD. BAG may capture similar signal to established MRI measures. However, BAG offers unique benefits in simplicity of data processing and interpretation. Thus, results in this unique ADAD cohort with few age-related confounds suggest that brain aging attributable to AD neuropathology can be accurately quantified from minimally-processed MRI.

Alzheimer Disease.

PURPOSE OF REVIEW: Alzheimer disease (AD) is the most common cause of dementia in adults (mid to late life), highlighting the importance of understanding the risk factors, clinical manifestations, and recent developments in diagnostic testing and therapeutics. RECENT FINDINGS: Advances in fluid (CSF and blood-based) and imaging biomarkers are allowing for a more precise and earlier diagnosis of AD (relative to non-AD dementias) across the disease spectrum and in patients with atypical clinical features. Specifically, tau- and amyloid-related AD pathologic changes can now be measured by CSF, plasma, and positron emission tomography (PET) with good precision. Additionally, a better understanding of risk factors for AD has highlighted the need for clinicians to address comorbidities to maximize prevention of cognitive decline in those at risk or to slow decline in patients who are symptomatic. Recent clinical trials of amyloid-lowering drugs have provided not only some optimism that amyloid reduction or prevention may be beneficial but also a recognition that addressing additional targets will be necessary for significant disease modification. SUMMARY: Recent developments in fluid and imaging biomarkers have led to the improved understanding of AD as a chronic condition with a protracted presymptomatic phase followed by the clinical stage traditionally recognized by neurologists. As clinical trials of potential disease-modifying therapies continue, important developments in the understanding of the disease will improve clinical care now and lead to more effective therapies in the near future.

Sequence of Alzheimer disease biomarker changes in cognitively normal adults: A cross-sectional study.

OBJECTIVE: To determine the ordering of changes in Alzheimer disease (AD) biomarkers among cognitively normal individuals. METHODS: Cross-sectional data, including CSF analytes, molecular imaging of cerebral fibrillar ß-amyloid (Aß) with PET using the [11C] benzothiazole tracer Pittsburgh compound B (PiB), MRI-based brain structures, and clinical/cognitive outcomes harmonized from 8 studies, collectively involving 3,284 cognitively normal individuals 18 to 101 years of age, were analyzed. The age at which each marker exhibited an accelerated change (called the change point) was estimated and compared across the markers. RESULTS: Accelerated changes in CSF Aß1-42 (Aß42) occurred at 48.28 years of age and in Aß42/Aß40 ratio at 46.02 years, followed by PiB mean cortical standardized uptake value ratio (SUVR) with a change point at 54.47 years. CSF total tau (Tau) and tau phosphorylated at threonine 181 (Ptau) had a change point at ≈60 years, similar to those for MRI hippocampal volume and cortical thickness. The change point for a cognitive composite occurred at 62.41 years. The change points for CSF Aß42 and Aß42/Aß40 ratio, albeit not significantly different from that for PiB SUVR, occurred significantly earlier than that for CSF Tau, Ptau, MRI markers, and the cognitive composite. Adjusted analyses confirmed that accelerated changes in CSF Tau, Ptau, MRI markers, and the cognitive composite occurred at ages not significantly different from each other. CONCLUSIONS: Our findings support the hypothesized early changes of amyloid in preclinical AD and suggest that changes in neuronal injury and neurodegeneration markers occur close in time to cognitive decline.

Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease.

Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease.

Neurofilament light chain (NfL) is a promising fluid biomarker of disease progression for various cerebral proteopathies. Here we leverage the unique characteristics of the Dominantly Inherited Alzheimer Network and ultrasensitive immunoassay technology to demonstrate that NfL levels in the cerebrospinal fluid (n = 187) and serum (n = 405) are correlated with one another and are elevated at the presymptomatic stages of familial Alzheimer's disease. Longitudinal, within-person analysis of serum NfL dynamics (n = 196) confirmed this elevation and further revealed that the rate of change of serum NfL could discriminate mutation carriers from non-mutation carriers almost a decade earlier than cross-sectional absolute NfL levels (that is, 16.2 versus 6.8 years before the estimated symptom onset). Serum NfL rate of change peaked in participants converting from the presymptomatic to the symptomatic stage and was associated with cortical thinning assessed by magnetic resonance imaging, but less so with amyloid-ß deposition or glucose metabolism (assessed by positron emission tomography). Serum NfL was predictive for both the rate of cortical thinning and cognitive changes assessed by the Mini-Mental State Examination and Logical Memory test. Thus, NfL dynamics in serum predict disease progression and brain neurodegeneration at the early presymptomatic stages of familial Alzheimer's disease, which supports its potential utility as a clinically useful biomarker.

Simultaneously evaluating the effect of baseline levels and longitudinal changes in disease biomarkers on cognition in dominantly inherited Alzheimer's disease.

INTRODUCTION: As the role of biomarkers is increasing in Alzheimer's disease (AD) clinical trials, it is critical to use a comprehensive temporal biomarker profile that reflects both baseline and longitudinal assessments to establish a more precise association between the change in biomarkers and change in cognition. Because age of onset of dementia symptoms is highly predictable, and there are relatively few age-related comorbidities, the Dominantly Inherited Alzheimer Network autosomal dominant AD population affords a unique opportunity to investigate these relationships in a well-characterized population. METHODS: A novel joint statistical model was used to simultaneously evaluate how a comprehensive AD biomarker profile predicts change in cognition using amyloid positron emission tomography (PET), CSF Aß42, CSF total tau and Ptau181, cortical metabolism using [F-18] fluorodeoxyglucose-PET, and hippocampal volume from participants enrolled in the Dominantly Inherited Alzheimer Network (n = 262) with mean (SD) duration of follow-up of 2.7 (1.2) years. RESULTS: Baseline amyloid PET levels and CSF biomarkers were associated with change in cognition in contrast to the rate of change of brain metabolism and hippocampal volume, which predicted change in cognition. CONCLUSIONS: This study suggests that the baseline value of amyloid PET and CSF Aß42 measures may be useful for screening participants for AD trials; however, brain hippocampus atrophy and hypometabolism are only useful as repeated longitudinal assessments for tracking cognition and disease progression. This suggests that measures of amyloid plaques predict future cognitive decline, but only longitudinal measures of neurodegeneration correlate with cognitive decline. The novel statistical model used in this study can be easily applied to any pair of outcomes and has potential to be widely used by the AD research community.

Rapidly-progressive catatonia responsive to zolpidem in a patient with ovarian teratoma-associated paraneoplastic encephalitis.

Psychiatric symptoms and catatonia are key components of the clinical presentation of paraneoplastic encephalitis; additionally symptoms can be long-lasting and often difficult to treat. We report a 73-year-old patient with rapidly progressive catatonia not responsive to immunotherapy, tumor resection, electroconvulsive therapy, or benzodiazepines who had significant improvement after zolpidem administration. This report suggests that zolpidem is an option in the treatment of patients with refractory catatonia and paraneoplastic encephalitis.

The Dynamic Gait Index in Evaluating Patients with Normal Pressure Hydrocephalus for Cerebrospinal Fluid Diversion.

BACKGROUND: Diagnosing normal pressure hydrocephalus (NPH) remains challenging. Most clinical tests currently used to evaluate suspected NPH patients for shunt surgery are invasive, require inpatient admission, and are not without complications. An objective, noninvasive, and low-cost alternative would be ideal. METHODS: A retrospective review was performed of prospectively collected dynamic gait index (DGI) scores, obtained at baseline and on every day of a 3- to 5-day lumbar cerebrospinal fluid (CSF) drainage trial on patients with suspected NPH at our institution. RESULTS: Between 2003 and 2014, 170 patients were suspected to have primary NPH (166, 97.6%) or secondary NPH (4, 2.4%). Using responsiveness to lumbar CSF drainage and subsequent shunting as the reference standard, we found that a baseline DGI ≥ 7 was found to have significant ability in selecting patients for permanent CSF diverting shunt surgery: sensitivity of 84.2% (95% confidence interval [95% CI]: 75.6%-90.2%), specificity of 80.6% (95% CI 70.0%-88.0%), and diagnostic odds ratio of 22.1 (95% CI 9.9-49.3). CONCLUSIONS: A baseline DGI ≥ 7 appears to provide an objective, low-cost, noninvasive measure to select patients with suspected NPH for a positive response to CSF diversion with high sensitivity, specificity and diagnostic odds ratio.