Amyloid-Related Imaging Abnormalities and Other MRI Findings in a Cognitively Unimpaired Population With and Without Cerebral Amyloid.

BACKGROUND: Screening data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) and Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) studies provide a unique opportunity to compare magnetic resonance imaging (MRI) findings such as amyloid-related imaging abnormalities (ARIA) in cognitively unimpaired elderly with and without elevated cerebral amyloid. OBJECTIVES: To compare screening MRI findings, such as ARIA, in the cognitively unimpaired potential participants of a clinical trial with and without elevated cerebral amyloid. DESIGN: Cross-sectional analysis of structural MRI findings in screening data from the A4 and LEARN studies. SETTING: The A4 Study is a multi-center international clinical trial. The LEARN Study is a multi center observational study in the United States. PARTICIPANTS: Clinically normal older adults (65-85 years) with elevated cerebral amyloid (Aß+; n = 1250, A4) and without elevated cerebral amyloid (Aß-; n = 538, LEARN). MEASUREMENTS: Participants underwent florbetapir positron emission tomography for Aß+/- classification. A centrally read 3T MRI to assess for study eligibility was conducted on study qualified MRI scanners. RESULTS: No ARIA-effusions (ARIA-E) was detected on screening MRI in the Aß+ or Aß- cohorts. At least one ARIA-H (microhemorrhages [MCH] or superficial siderosis [SS]) was present in 18% of the Aß+ cohort compared with 8% in Aß- (P < 0.001). In the Aß+ cohort, approximately 2% of screening MRIs demonstrated MCH ≥4 compared with 0% in Aß-. The presence of two apolipoprotein E ε4 (APOEε4) alleles (vs no ε4 alleles) in the Aß+ cohort increased the odds for presence of MCH (odds ratio [OR] = 2.03; 95% CI, 1.23 to 3.27, P = 0.004). Cortical infarctions (4% vs 0%) and subcortical infarctions (10% vs 1%) were observed at statistically significantly higher prevalence in the Aß+ cohort compared with Aß- (P < 0.001). Females showed reduced odds of MCH in the Aß+ cohort by a factor of 0.63 (95% CI, 0.47 to 0.84, P = 0.002). CONCLUSIONS: ARIA-E is rare in cognitively unimpaired Aß+ and Aß- populations prior to anti-amyloid drug intervention. ARIA-H in Aß+ was greater than in Aß- populations.

Item-Level Investigation of Participant and Study Partner Report on the Cognitive Function Index from the A4 Study Screening Data.

BACKGROUND: Greater subjective cognitive changes on the Cognitive Function Index (CFI) was previously found to be associated with elevated amyloid (Aß) status in participants screening for the A4 Study, reported by study partners and the participants themselves. While the total score on the CFI related to amyloid for both sources respectively, potential differences in the specific types of cognitive changes reported by either participants or their study partners was not investigated. OBJECTIVES: To determine the specific types of subjective cognitive changes endorsed by participants and their study partners that are associated with amyloid status in individuals screening for an AD prevention trial. DESIGN, SETTING, PARTICIPANTS: Four thousand four hundred and eighty-six cognitively unimpaired (CDR=0; MMSE 25-30) participants (ages 65-85) screening for the A4 Study completed florbetapir (Aß) Positron Emission Tomography (PET) imaging. Participants were classified as elevated amyloid (Aß+; n=1323) or non-elevated amyloid (Aß-; n=3163). MEASUREMENTS: Prior to amyloid PET imaging, subjective report of changes in cognitive functioning were measured using the CFI (15 item questionnaire; Yes/Maybe/No response options) and administered separately to both participants and their study partners (i.e., a family member or friend in regular contact with the participant). The impact of demographic factors on CFI report was investigated. For each item of the CFI, the relationship between Aß and CFI response was investigated using an ordinal mixed effects model for participant and study partner report. RESULTS: Independent of Aß status, participants were more likely to report 'Yes' or 'Maybe' compared to the study partners for nearly all CFI items. Older age (r= 0.06, p<0.001) and lower education (r=-0.08, p<0.001) of the participant were associated with higher CFI. Highest coincident odds ratios related to Aß+ for both respondents included items assessing whether 'a substantial decline in memory' had occurred in the last year (ORsp= 1.35 [95% CI 1.11, 1.63]; ORp= 1.55 [95% CI 1.34, 1.79]) and whether the participant had 'seen a doctor about memory' (ORsp= 1.56 [95% CI 1.25, 1.95]; ORp =1.71 [95% CI 1.37, 2.12]). For two items, associations were significant for only study partner report; whether the participant 'Repeats questions' (ORsp = 1.30 [95% CI 1.07, 1.57]) and has 'trouble following the news' (ORsp= 1.46[95% CI 1.12, 1.91]). One question was significant only for participant report; 'trouble driving' (ORp= 1.25 [95% CI 1.04, 1.49]). CONCLUSIONS: Elevated Aß is associated with greater reporting of subjective cognitive changes as measured by the CFI in this cognitively unimpaired population. While participants were more likely than study partners to endorse change on most CFI items, unique CFI items were associated with elevated Aß for participants and their study partners, supporting the value of both sources of information in clinical trials.

The Computerized Cognitive Composite (C3) in an Alzheimer's Disease Secondary Prevention Trial.

BACKGROUND: Computerized cognitive assessments may improve Alzheimer's disease (AD) secondary prevention trial efficiency and accuracy. However, they require validation against standard outcomes and relevant biomarkers. OBJECTIVE: To assess the feasibility and validity of the tablet-based Computerized Cognitive Composite (C3). DESIGN: Cross-sectional analysis of cognitive screening data from the A4 study (Anti-Amyloid in Asymptomatic AD). SETTING: Multi-center international study. PARTICIPANTS: Clinically normal (CN) older adults (65-85; n=4486). MEASUREMENTS: Participants underwent florbetapir-Positron Emission Tomography for Aß+/- classification. They completed the C3 and standard paper and pencil measures included in the Preclinical Alzheimer's Cognitive Composite (PACC). The C3 combines memory measures sensitive to change over time (Cogstate Brief Battery-One Card Learning) and measures shown to be declining early in AD including pattern separation (Behavioral Pattern Separation Test- Object- Lure Discrimination Index) and associative memory (Face Name Associative Memory Exam- Face-Name Matching). C3 acceptability and completion rates were assessed using qualitative and quantitative methods. C3 performance was explored in relation to Aß+/- groups (n=1323/3163) and PACC. RESULTS: C3 was feasible for CN older adults to complete. Rates of incomplete or invalid administrations were extremely low, even in the bottom quartile of cognitive performers (PACC). C3 was moderately correlated with PACC (r=0.39). Aß+ performed worse on C3 compared with Aß- [unadjusted Cohen's d=-0.22 (95%CI: -0.31,-0.13) p<0.001] and at a magnitude comparable to the PACC [d=-0.32 (95%CI: -0.41,-0.23) p<0.001]. Better C3 performance was observed in younger, more educated, and female participants. CONCLUSIONS: These findings provide support for both the feasibility and validity of C3 and computerized cognitive outcomes more generally in AD secondary prevention trials.

Model-based reconstruction of an epidemic using multiple datasets: understanding influenza A/H1N1 pandemic dynamics in Israel.

Intensified surveillance during the 2009 A/H1N1 influenza pandemic in Israel resulted in large virological and serological datasets, presenting a unique opportunity for investigating the pandemic dynamics. We employ a conditional likelihood approach for fitting a disease transmission model to virological and serological data, conditional on clinical data. The model is used to reconstruct the temporal pattern of the pandemic in Israel in five age-groups and evaluate the factors that shaped it. We estimate the reproductive number at the beginning of the pandemic to beR= 1.4. We find that the combined effect of varying absolute humidity conditions and school vacations (SVs) is responsible for the infection pattern, characterized by three epidemic waves. Overall attack rate is estimated at 32% (28-35%) with a large variation among the age-groups: the highest attack rates within school children and the lowest within the elderly. This pattern of infection is explained by a combination of the age-group contact structure and increasing immunity with age. We assess that SVs increased the overall attack rates by prolonging the pandemic into the winter. Vaccinating school children would have been the optimal strategy for minimizing infection rates in all age-groups.

Bridging the Gap between Research and Clinical Practice in Asymptomatic Alzheimer's Disease.

Due to the growing global health impact of Alzheimer's disease (AD), there is a greater need for interventions that prevent or delay the onset of clinical symptoms of this debilitating disease. Clinical trials for disease-modifying compounds in AD have shifted towards earlier stages in the spectrum of illness, including the stage prior to cognitive symptoms. A population of specific interest for clinical research includes individuals with evidence of Alzheimer's disease pathology who are asymptomatic (ADPa). The challenges and barriers regarding medical treatment of ADPa must be identified and addressed prior to the completion of a positive clinical trial in order to accelerate the translation of research findings to clinical practice. This report applies an existing public health impact model from Spencer and colleagues (2013) to evaluate the readiness of the clinical practice environment to treat ADPa individuals if a disease-modifying agent achieves approval. We contrast the current clinical practice environment with a potential future state through investigating the effectiveness, reach, feasibility, sustainability, and transferability of the practice of treating ADPa individuals.

Modelling seasonal influenza: the role of weather and punctuated antigenic drift.

Seasonal influenza appears as annual oscillations in temperate regions of the world, yet little is known as to what drives these annual outbreaks and what factors are responsible for their inter-annual variability. Recent studies suggest that weather variables, such as absolute humidity, are the key drivers of annual influenza outbreaks. The rapid, punctuated, antigenic evolution of the influenza virus is another major factor. We present a new framework for modelling seasonal influenza based on a discrete-time, age-of-infection, epidemic model, which allows the calculation of the model's likelihood function in closed form. This framework may be used to perform model inference and parameter estimation rigorously. The modelling approach allows us to fit 11 years of Israeli influenza data, with the best models fitting the data with unusually high correlations in which r > 0.9. We show that using actual weather to modulate influenza transmission rate gives better results than using the inter-annual means of the weather variables, providing strong support for the role of weather in shaping the dynamics of influenza. This conclusion remains valid even when incorporating a more realistic depiction of the decay of immunity at the population level, which allows for discrete changes in immunity from year to year.

Cerebrovascular risk factors and preclinical memory decline in healthy APOE ε4 homozygotes.

OBJECTIVE: To characterize the effects of cerebrovascular (CV) risk factors on preclinical memory decline in cognitively normal individuals at 3 levels of genetic risk for Alzheimer disease (AD) based on APOE genotype. METHODS: We performed longitudinal neuropsychological testing on an APOE ε4 enriched cohort, ages 21-97. The long-term memory (LTM) score of the Auditory Verbal Learning Test (AVLT) was the primary outcome measure. Any of 4 CV risk factors (CVany), including hypercholesterolemia (CHOL), prior cigarette use (CIG), diabetes mellitus (DM), and hypertension (HTN), was treated as a dichotomized variable. We estimated the longitudinal effect of age using statistical models that simultaneously modeled the cross-sectional and longitudinal effects of age on AVLT LTM by APOE genotype, CVany, and the interaction between the two. RESULTS: A total of 74 APOE ε4 homozygotes (HMZ), 239 ε4 heterozygotes (HTZ), and 494 ε4 noncarriers were included. APOE ε4 carrier status showed a significant quadratic effect with age-related LTM decline in all models as previously reported. CVany was associated with further longitudinal AVLT LTM decline in APOE ε4 carriers (p=0.02), but had no effect in noncarriers. When ε4 HTZ and HMZ were considered separately, there was a striking effect in HMZ (p<0.001) but not in HTZ. In exploratory analyses, significant deleterious effects were found for CIG (p=0.001), DM (p=0.03), and HTN (p=0.05) in APOE ε4 carriers only that remained significant only for CIG after correction for multiple comparisons. CONCLUSION: CV risk factors influence age-related memory decline in APOE ε4 HMZ.

Modelling the initial phase of an epidemic using incidence and infection network data: 2009 H1N1 pandemic in Israel as a case study.

This paper presents new computational and modelling tools for studying the dynamics of an epidemic in its initial stages that use both available incidence time series and data describing the population's infection network structure. The work is motivated by data collected at the beginning of the H1N1 pandemic outbreak in Israel in the summer of 2009. We formulated a new discrete-time stochastic epidemic SIR (susceptible-infected-recovered) model that explicitly takes into account the disease's specific generation-time distribution and the intrinsic demographic stochasticity inherent to the infection process. Moreover, in contrast with many other modelling approaches, the model allows direct analytical derivation of estimates for the effective reproductive number (R(e)) and of their credible intervals, by maximum likelihood and Bayesian methods. The basic model can be extended to include age-class structure, and a maximum likelihood methodology allows us to estimate the model's next-generation matrix by combining two types of data: (i) the incidence series of each age group, and (ii) infection network data that provide partial information of 'who-infected-who'. Unlike other approaches for estimating the next-generation matrix, the method developed here does not require making a priori assumptions about the structure of the next-generation matrix. We show, using a simulation study, that even a relatively small amount of information about the infection network greatly improves the accuracy of estimation of the next-generation matrix. The method is applied in practice to estimate the next-generation matrix from the Israeli H1N1 pandemic data. The tools developed here should be of practical importance for future investigations of epidemics during their initial stages. However, they require the availability of data which represent a random sample of the real epidemic process. We discuss the conditions under which reporting rates may or may not influence our estimated quantities and the effects of bias.