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AbstractObjectiveTo evaluate trials of drugs that target amyloid to determine whether reductions in amyloid levels are likely to improve cognition.DesignInstrumental variable meta-analysis.Setting14 randomized controlled trials of drugs for the prevention or treatment of Alzheimer’s disease that targeted an amyloid mechanism, identified from ClinicalTrials.gov.PopulationAdults enrolled in randomized controlled trials of amyloid targeting drugs. Inclusion criteria for trials vary, but typically include adults aged 50 years or older with a diagnosis of mild cognitive impairment or Alzheimer’s disease, and amyloid positivity at baseline.Main outcome measuresAnalyses included trials for which information could be obtained on both change in brain amyloid levels measured with amyloid positron emission tomography and change in at least one cognitive test score reported for each randomization arm.ResultsPooled results from the 14 randomized controlled trials were more precise than estimates from any single trial. The pooled estimate for the effect of reducing amyloid levels by 0.1 standardized uptake value ratio units was an improvement in the mini-mental state examination score of 0.03 (95% confidence interval −0.06 to 0.1) points. This study provides a web application that allows for the re-estimation of the results when new data become available and illustrates the magnitude of the new evidence that would be necessary to achieve a pooled estimate supporting the benefit of reducing amyloid levels.ConclusionsPooled evidence from available trials reporting both reduction in amyloid levels and change in cognition suggests that amyloid reduction strategies do not substantially improve cognition.

The associations between muscle strength and cognitive outcomes have sparked interest in interventions that increase muscle strength for prevention of dementia, but the associations between muscle strength and cognitive aging are unclear, particularly among middle-aged adults. To evaluate the association between handgrip strength (HGS) and dementia, reduced cognition, and poorer neuroimaging outcomes in a UK population of middle-aged adults. This cohort study evaluated UK Biobank participants aged 39 to 73 years enrolled from 2006 to 2010 with measured HGS and prospectively followed up for dementia diagnosis. Data were analyzed from October 2021 to April 2022. HGS assessed in both hands via dynamometer. Outcomes included cognitive test scores (fluid intelligence and prospective memory), brain magnetic resonance imaging measures (total brain volume, white matter hyperintensity, and hippocampal volume), and incident dementia (all-cause, vascular, and Alzheimer disease [AD] from primary care, hospital, or death records) over a median (IQR) of 11.7 (11.0-12.4) years of follow-up. Mixed-effects linear and logistic regressions and Cox proportional-hazard models were used to estimate associations, stratified by gender and adjusted for covariates. Estimates are presented per 5-kg decrement in HGS. To evaluate reverse causation, we assessed whether a polygenic risk score for AD is associated with HGS. A subsample of 190 406 adult participants in the UK Biobank (mean [SD] age, 56.5 [8.1] years; 102 735 women [54%]) were evaluated. A 5-kg decrement in HGS was associated with lower fluid intelligence scores in men (β, -0.007; 95% CI, -0.010 to -0.003) and women (β, -0.04; 95% CI, -0.05 to -0.04. A 5-kg decrement in HGS was associated with worse odds of correctly responding to a prospective memory task for men (odds ratio, 0.91; 95% CI, 0.90 to 0.92) and women (odds ratio, 0.88; 95% CI, 0.87 to 0.90). A 5-kg decrement in HGS was associated with greater white matter hyperintensity volume in men (β, 92.22; 95% CI, 31.09 to 153.35) and women (β, 83.56; 95% CI, 13.54 to 153.58). A 5-kg decrement in HGS was associated with incident dementia for men (hazard ratio, 1.20; 95% CI, 1.12 to 1.28) and women (hazard ratio, 1.12; 95% CI, 1.00 to 1.26). The AD genetic risk score was not significantly associated with HGS. These findings suggest that HGS is associated with measures of neurocognitive brain health among men and women and they add to a growing body of research indicating that interventions designed to increase muscle strength, particularly among middle-aged adults, may hold promise for the maintenance of neurocognitive brain health.

Background Measles cases continue to occur among susceptible individuals despite the elimination of endemic measles transmission in the United States. Clustering of disease susceptibility can threaten herd immunity and impact the likelihood of disease outbreaks in a highly vaccinated population. Previous studies have examined the role of contact tracing to control infectious diseases among clustered populations, but have not explicitly modeled the public health response using an agent-based model. Methods We developed an agent-based simulation model of measles transmission using the Framework for Reconstructing Epidemiological Dynamics (FRED) and the Synthetic Population Database maintained by RTI International. The simulation of measles transmission was based on interactions among individuals in different places: households, schools, daycares, workplaces, and neighborhoods. The model simulated different levels of immunity clustering, vaccination coverage, and contact investigations with delays caused by individuals’ behaviors and/or the delay in a health department’s response. We examined the effects of these characteristics on the probability of uncontrolled measles outbreaks and the outbreak size in 365 days after the introduction of one index case into a synthetic population. Results We found that large measles outbreaks can be prevented with contact investigations and moderate contact rates by having (1) a very high vaccination coverage (≥ 95%) with a moderate to low level of immunity clustering (≤ 0.5) for individuals aged less than or equal to 18 years, or (2) a moderate vaccination coverage (85% or 90%) with no immunity clustering for individuals (≤18 years of age), a short intervention delay, and a high probability that a contact can be traced. Without contact investigations, measles outbreaks may be prevented by the highest vaccination coverage with no immunity clustering for individuals (≤18 years of age) with moderate contact rates; but for the highest contact rates, even the highest coverage with no immunity clustering for individuals (≤18 years of age) cannot completely prevent measles outbreaks. Conclusions The simulation results demonstrated the importance of vaccination coverage, clustering of immunity, and contact investigations in preventing uncontrolled measles outbreaks.

ObjectivesEvidence on adverse childhood experiences (ACEs) and late-life cognitive outcomes is inconsistent, with little research among diverse racial/ethnic groups. We investigated whether ACE exposures were associated with worse late-life cognition for all racial/ethnic groups and at different ages of exposure.DesignCovariate-adjusted mixed-effects linear regression models estimated associations of: (1) total number of ACEs experienced, (2) earliest age when ACE occurred and (3) type of ACE with overall cognition.SettingKaiser Permanente Northern California members aged 65 years and older, living in Northern California.ParticipantsKaiser Healthy Aging and Diverse Life Experiences study baseline participants, aged 65 years and older (n=1661; including 403 Asian-American, 338 Latino, 427 Black and 493 white participants).ResultsMost respondents (69%) reported one or more ACE, most frequently family illness (36%), domestic violence (23%) and parental divorce (22%). ACE count was not adversely associated with cognition overall (β=0.01; 95% CI −0.01 to 0.03), in any racial/ethnic group or for any age category of exposure. Pooling across all race/ethnicities, parent’s remarriage (β=−0.11; 95% CI −0.20 to −0.03), mother’s death (β=−0.18; 95% CI −0.30 to −0.07) and father’s death (β=−0.11; 95% CI −0.20 to −0.01) were associated with worse cognition.ConclusionAdverse childhood exposures overall were not associated with worse cognition in older adults in a diverse sample, although three ACEs were associated with worse cognitive outcomes.

Human and animal trypanosomiasis, spread by tsetse flies (Glossina spp), is a major public health concern in much of sub-Saharan Africa. The basic reproduction number of vector-borne diseases, such as trypanosomiasis, is a function of vector mortality rate. Robust methods for estimating tsetse mortality are thus of interest for understanding population and disease dynamics and for optimal control. Existing methods for estimating mortality in adult tsetse, from ovarian dissection data, often use invalid assumptions of the existence of a stable age distribution, and age-invariant mortality and capture probability. We develop a dynamic model to estimate tsetse mortality from ovarian dissection data in populations where the age distribution is not necessarily stable. The models correspond to several hypotheses about how temperature affects mortality: no temperature dependence (model 1), identical temperature dependence for mature adults and immature stages, i.e., pupae and newly emerged adults (model 2), and differential temperature dependence for mature adults and immature stages (model 3). We fit our models to ovarian dissection data for G. pallidipes collected at Rekomitjie Research Station in the Zambezi Valley in Zimbabwe. We compare model fits to determine the most probable model, given the data, by calculating the Akaike Information Criterion (AIC) for each model. The model that allows for a differential dependence of temperature on mortality for immature stages and mature adults (model 3) performs significantly better than models 1 and 2. All models produce mortality estimates, for mature adults, of approximately 3% per day for mean daily temperatures below 25°C, consistent with those of mark-recapture studies performed in other settings. For temperatures greater than 25°C, mortality among immature classes of tsetse increases substantially, whereas mortality remains roughly constant for mature adults. As a sensitivity analysis, model 3 was simultaneously fit to both the ovarian dissection and trap data; while this fit also produces comparable mortality at temperatures below 25°C, it is not possible to obtain good fits to both data sources simultaneously, highlighting the uncertain correspondence between trap catches and population levels and/or the need for further improvements to our model. The modelling approach employed here could be applied to any substantial time series of age distribution data.

We conducted an expert survey of leprosy (Hansen's Disease) and neglected tropical disease experts in February 2016. Experts were asked to forecast the next year of reported cases for the world, for the top three countries, and for selected states and territories of India. A total of 103 respondents answered at least one forecasting question. We elicited lower and upper confidence bounds. Comparing these results to regression and exponential smoothing, we found no evidence that any forecasting method outperformed the others. We found evidence that experts who believed it was more likely to achieve global interruption of transmission goals and disability reduction goals had higher error scores for India and Indonesia, but lower for Brazil. Even for a disease whose epidemiology changes on a slow time scale, forecasting exercises such as we conducted are simple and practical. We believe they can be used on a routine basis in public health.

Distributions were derived from Holt-Winters, regression (ordinary least squares for the world data, linear mixed effects regression for the three countries), and expert survey. The median is indicated with a white dot; the bright central band (orange, yellow, green, respectively) corresponds to the interquartile region, and the remainder of the 95 percent central coverage region is indicated by the darker region (brown, olive, dark green, respectively).

Amyloid removal has been used as surrogate outcomes in clinical trials of Alzheimer's disease (AD) drugs, leading to approvals of aducanumab and lecanemab under the Accelerated Approval Program. While well-established epidemiologic and econometric methods exist to formally evaluate amyloid's validity as a surrogate outcome, their application has been hindered by restricted access to individual-level data from anti-amyloid drug trials. The newly available individual-level data from the A4 trial of solanezumab offers a unique opportunity to demonstrate how these untapped approaches can improve our understanding of the impact of amyloid removal on cognitive decline. We used data on 815 A4 study participants (Alzheimer's Clinical Trial Consortium A4/LEARN) with complete follow-up measures for florbetapir PET imaging and Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB) score. We estimated cognitive change using the trajectory of the CDR-SB score over 4.5 years. Instrumental-variable (IV) methods were used to evaluate the causal effect of amyloid reduction on cognitive changes using randomization as an instrument for amyloid reduction. Causal mediation analysis was conducted to estimate the extent to which changes in amyloid mediated the cognitive effects of solanezumab. Analyses were adjusted for sex, APOE-ε4 carrier status, and baseline age, cognition, and amyloid. Average between-group differences in amyloid change and cognitive trajectory were -0.05 (SD 0.16) SUVr and 0.002 (SD 0.028) CDR-SB points per month, respectively. Non-linear effects of amyloid on cognition were not supported (Figure 1). The IV-estimated effect of a 1 SUVr reduction on monthly CDR-SB change was -0.041, 95% CI: (-0.096, 0.014) (Figure 2). Mediation analysis suggests that amyloid change mediates 23% of solanezumab's effect on cognitive change, 95% CI: (-125%, 253%) (Figure 2). Using epidemiologic and econometric methods to analyze individual-level data from trials of amyloid-targeting drugs will improve our understanding of amyloid as a surrogate outcome for cognition. In this instance, results are imprecise because solanezumab did not effectively remove amyloid. However, reproducing these analyses using individual-level data from effective anti-amyloid trials has the potential to shape treatment strategies and inform use of surrogate outcomes in future approval processes.

Amyloid removal has been used as surrogate outcomes in clinical trials of Alzheimer's disease (AD) drugs, leading to approvals of aducanumab and lecanemab under the Accelerated Approval Program. While well-established epidemiologic and econometric methods exist to formally evaluate amyloid's validity as a surrogate outcome, their application has been hindered by restricted access to individual-level data from anti-amyloid drug trials. The newly available individual-level data from the A4 trial of solanezumab offers a unique opportunity to demonstrate how these untapped approaches can improve our understanding of the impact of amyloid removal on cognitive decline. We used data on 815 A4 study participants (Alzheimer's Clinical Trial Consortium A4/LEARN) with complete follow-up measures for florbetapir PET imaging and Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB) score. We estimated cognitive change using the trajectory of the CDR-SB score over 4.5 years. Instrumental-variable (IV) methods were used to evaluate the causal effect of amyloid reduction on cognitive changes using randomization as an instrument for amyloid reduction. Causal mediation analysis was conducted to estimate the extent to which changes in amyloid mediated the cognitive effects of solanezumab. Analyses were adjusted for sex, APOE-ε4 carrier status, and baseline age, cognition, and amyloid. Average between-group differences in amyloid change and cognitive trajectory were -0.05 (SD 0.16) SUVr and 0.002 (SD 0.028) CDR-SB points per month, respectively. Non-linear effects of amyloid on cognition were not supported (figure 1). The IV-estimated effect of a 1 SUVr reduction on monthly CDR-SB change was -0.041, 95% CI: (-0.096, 0.014) (figure 2). Mediation analysis suggests that amyloid change mediates 23% of solanezumab's effect on cognitive change, 95% CI: (-125%, 253%) (figure 2). Using epidemiologic and econometric methods to analyze individual-level data from trials of amyloid-targeting drugs will improve our understanding of amyloid as a surrogate outcome for cognition. In this instance, results are imprecise because solanezumab did not effectively remove amyloid. However, reproducing these analyses using individual-level data from effective anti-amyloid trials has the potential to shape treatment strategies and inform use of surrogate outcomes in future approval processes.

Most neuroimaging studies linking regional brain volumes with cognition correct for total intracranial volume (ICV), but methods used for this correction differ across studies. It is unknown whether different ICV correction methods yield consistent results. Using a brain‐wide association approach in the MRI substudy of UK Biobank (N = 41,964; mean age = 64.5 years), we used regression models to estimate the associations of 58 regional brain volumetric measures with eight cognitive outcomes, comparing no correction and four ICV correction approaches. Approaches evaluated included: no correction; dividing regional volumes by ICV (proportional approach); including ICV as a covariate in the regression (adjustment approach); and regressing the regional volumes against ICV in different normative samples and using calculated residuals to determine associations (residual approach). We used Spearman‐rank correlations and two consistency measures to quantify the extent to which associations were inconsistent across ICV correction approaches for each possible brain region and cognitive outcome pair across 2320 regression models. When the association between brain volume and cognitive performance was close to null, all approaches produced similar estimates close to the null. When associations between a regional volume and cognitive test were not null, the adjustment and residual approaches typically produced similar estimates, but these estimates were inconsistent with results from the crude and proportional approaches. For example, when using the crude approach, an increase of 0.114 (95% confidence interval [CI]: 0.103–0.125) in fluid intelligence was associated with each unit increase in hippocampal volume. However, when using the adjustment approach, the increase was 0.055 (95% CI: 0.043–0.068), while the proportional approach showed a decrease of −0.025 (95% CI: −0.035 to −0.014). Different commonly used methods to correct for ICV yielded inconsistent results. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations. Different commonly used methods to correct for intracranial volume (ICV) yielded inconsistent results, representing significant challenges for reproducibility in neuroimaging research. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations.