Influence of Temperature and Precipitation on the Effectiveness of Water, Sanitation, and Handwashing Interventions against Childhood Diarrheal Disease in Rural Bangladesh: A Reanalysis of the WASH Benefits Bangladesh Trial.

BACKGROUND: Diarrheal disease is a leading cause of childhood morbidity and mortality globally. Household water, sanitation, and handwashing (WASH) interventions can reduce exposure to diarrhea-causing pathogens, but meteorological factors may impact their effectiveness. Information about effect heterogeneity under different weather conditions is critical to refining these targeted interventions. OBJECTIVES: We aimed to determine whether temperature and precipitation modified the effect of low-cost, point-of-use WASH interventions on child diarrhea. METHODS: We analyzed data from a trial in rural Bangladesh that compared child diarrhea prevalence between clusters (N=720) that were randomized to different WASH interventions between 2012 and 2016 (NCT01590095). We matched temperature and precipitation measurements to diarrhea outcomes (N=12,440 measurements, 6,921 children) by geographic coordinates and date. We estimated prevalence ratios (PRs) using generative additive models and targeted maximum likelihood estimation to assess the effectiveness of each WASH intervention under different weather conditions. RESULTS: Generally, WASH interventions most effectively prevented diarrhea during monsoon season, particularly following weeks with heavy rain or high temperatures. The PR for diarrhea in the WASH interventions group compared with the control group was 0.49 (95% CI: 0.35, 0.68) after 1 d of heavy rainfall, with a less-protective effect [PR=0.87 (95% CI: 0.60, 1.25)] when there were no days with heavy rainfall. Similarly, the PR for diarrhea in the WASH intervention group compared with the control group was 0.60 (95% CI: 0.48, 0.75) following above-median temperatures vs. 0.91 (95% CI: 0.61, 1.35) following below-median temperatures. The influence of precipitation and temperature varied by intervention type; for precipitation, the largest differences in effectiveness were for the sanitation and combined WASH interventions. DISCUSSION: WASH intervention effectiveness was strongly influenced by precipitation and temperature, and nearly all protective effects were observed during the rainy season. Future implementation of these interventions should consider local environmental conditions to maximize effectiveness, including targeted efforts to maintain latrines and promote community adoption ahead of monsoon seasons. https://doi.org/10.1289/EHP13807.

Distribution of infectious and parasitic agents among three sentinel bee species across European agricultural landscapes.

Infectious and parasitic agents (IPAs) and their associated diseases are major environmental stressors that jeopardize bee health, both alone and in interaction with other stressors. Their impact on pollinator communities can be assessed by studying multiple sentinel bee species. Here, we analysed the field exposure of three sentinel managed bee species (Apis mellifera, Bombus terrestris and Osmia bicornis) to 11 IPAs (six RNA viruses, two bacteria, three microsporidia). The sentinel bees were deployed at 128 sites in eight European countries adjacent to either oilseed rape fields or apple orchards during crop bloom. Adult bees of each species were sampled before their placement and after crop bloom. The IPAs were detected and quantified using a harmonised, high-throughput and semi-automatized qPCR workflow. We describe differences among bee species in IPA profiles (richness, diversity, detection frequencies, loads and their change upon field exposure, and exposure risk), with no clear patterns related to the country or focal crop. Our results suggest that the most frequent IPAs in adult bees are more appropriate for assessing the bees' IPA exposure risk. We also report positive correlations of IPA loads supporting the potential IPA transmission among sentinels, suggesting careful consideration should be taken when introducing managed pollinators in ecologically sensitive environments.

Effects of the active amyloid beta immunotherapy CAD106 on PET measurements of amyloid plaque deposition in cognitively unimpaired APOE ε4 homozygotes.

INTRODUCTION: Alzheimer's Prevention Initiative Generation Study 1 evaluated amyloid beta (Aß) active immunotherapy (vaccine) CAD106 and BACE-1 inhibitor umibecestat in cognitively unimpaired 60- to 75-year-old participants at genetic risk for Alzheimer's disease (AD). The study was reduced in size and terminated early. Results from the CAD106 cohort are presented. METHODS: Sixty-five apolipoprotein E ε4 homozygotes with/without amyloid deposition received intramuscular CAD106 450 µg (n = 42) or placebo (n = 23) at baseline; Weeks 1, 7, 13; and quarterly; 51 of them had follow-up Aß positron emission tomography (PET) scans at 18 to 24 months. RESULTS: CAD106 induced measurable serum Aß immunoglobulin G titers in 41/42 participants, slower rates of Aß plaque accumulation (mean [standard deviation] annualized change from baseline in amyloid PET Centiloid: -0.91[5.65] for CAD106 versus 8.36 [6.68] for placebo; P < 0.001), and three amyloid-related imaging abnormality cases (one symptomatic). DISCUSSION: Despite early termination, these findings support the potential value of conducting larger prevention trials of Aß active immunotherapies in individuals at risk for AD. HIGHLIGHTS: This was the first amyloid-lowering prevention trial in persons at genetic risk of late-onset Alzheimer's disease (AD). Active immunotherapy targeting amyloid (CAD106) was tested in this prevention trial. CAD106 significantly slowed down amyloid plaque deposition in apolipoprotein E homozygotes. CAD106 was generally safe and well tolerated, with only three amyloid-related imaging abnormality cases (one symptomatic). Such an approach deserves further evaluation in larger AD prevention trials.

Cumulative and potential synergistic effects of seven different bisphenols on human granulosa cells in vitro?

Bisphenol (BP) structural analogues of BPA are widely used. Previous studies showed similar effects of BPA and BPS on reproduction in several species including human. We hypothesised that the similar effects of several bisphenols (BPs) could accumulate in granulosa cells (GCs) and affects steroidogenesis. This study investigated the effects of seven BP analogues and their equimolar cocktail on human granulosa cells (hGC) and assessed BPA, BPS, BPF and BPAF level exposures in the follicular fluid of 277 women undergoing Assisted Reproductive Technology. The hGCs were recovered after women oocyte punctures and treated with the seven BP analogues (BPS, BPA, BPAF, BPF, BPAP, BPE and BPB) or their equimolar cocktail of 7 × 1.43 or 7 × 7.14 µM for each of the seven BPs, the sum of BPs reaching 10 ("∑BPs 10 µM"), or 50 µM ("∑BPs 50 µM"), respectively. Oestradiol and progesterone secretion, cell proliferation, viability and expression of steroidogenic enzymes were investigated. Progesterone secretion was decreased by 6 BPs 10 µM and the cocktail "∑BPs 10 µM", (-17.8 to -41.3%) and by all seven BPs 50 µM and "∑BPs 50 µM" (-21.8 to -84.2%). Oestradiol secretion was decreased only by 50 µM BPAF and BPAP (-37.8% and -44%, respectively), with corresponding decreases in CYP17A1 and CYP19A1 gene expression. Cellular proliferation was decreased after treatment with 50 µM BPAF (-32.2%), BPAP (-29%), BPB (-24%) and the equimolar cocktail "∑BPs 50 µM" (-33.1%). BPB (50 µM) and the cocktail "∑BPs 50 µM" increased HSD3B2 mRNA expression. At least one BP was detected in 64 of 277 (23.1%) women follicular fluids. Similar effects of the seven BPs or their cocktail were observed on progesterone secretion and/or on cell proliferation, suggesting cumulative effects of BPs. Our results highlight the urge to consider all BPs simultaneously and to further investigate the potential additive or synergistic effects of several BPs.

Rationale for the selection of dual primary endpoints in prevention studies of cognitively unimpaired individuals at genetic risk for developing symptoms of Alzheimer's disease.

BACKGROUND: There is a critical need for novel primary endpoints designed to detect early and subtle changes in cognition in clinical trials targeting the asymptomatic (preclinical) phase of Alzheimer's disease (AD). The Alzheimer's Prevention Initiative (API) Generation Program, conducted in cognitively unimpaired individuals at risk of developing AD (e.g., enriched by the apolipoprotein E (APOE) genotype), used a novel dual primary endpoints approach, whereby demonstration of treatment effect in one of the two endpoints is sufficient for trial success. The two primary endpoints were (1) time to event (TTE)-with an event defined as a diagnosis of mild cognitive impairment (MCI) due to AD and/or dementia due to AD-and (2) change from baseline to month 60 in the API Preclinical Composite Cognitive (APCC) test score. METHODS: Historical observational data from three sources were used to fit models to describe the TTE and the longitudinal APCC decline, both in people who do and do not progress to MCI or dementia due to AD. Clinical endpoints were simulated based on the TTE and APCC models to assess the performance of the dual endpoints versus each of the two single endpoints, with the selected treatment effect ranging from a hazard ratio (HR) of 0.60 (40% risk reduction) to 1 (no effect). RESULTS: A Weibull model was selected for TTE, and power and linear models were selected to describe the APCC score for progressors and non-progressors, respectively. Derived effect sizes in terms of reduction of the APCC change from baseline to year 5 were low (0.186 for HR = 0.67). The power for the APCC alone was consistently lower compared to the power of TTE alone (58% [APCC] vs 84% [TTE] for HR = 0.67). Also, the overall power was higher for the 80%/20% distribution (82%) of the family-wise type 1 error rate (alpha) between TTE and APCC compared to 20%/80% (74%). CONCLUSIONS: Dual endpoints including TTE and a measure of cognitive decline perform better than the cognitive decline measure as a single primary endpoint in a cognitively unimpaired population at risk of AD (based on the APOE genotype). Clinical trials in this population, however, need to be large, include older age, and have a long follow-up period of at least 5 years to be able to detect treatment effects.

Bisphenol A and bisphenol S both disrupt ovine granulosa cell steroidogenesis but through different molecular pathways.

BACKGROUND: Ovarian granulosa cells (GC) are essential for the development and maturation of a proper oocyte. GC are sensitive to endocrine disruptors, including bisphenol A (BPA) and its analogue bisphenol S (BPS), plasticisers present in everyday consumer products. BPA exhibits greater binding affinity for the membrane oestrogen receptor (GPER) than for the nuclear oestrogen receptors (ERα and ERß). Here, we analysed the effects of BPA and BPS on the steroidogenesis of ovine GC in vitro, as well as their early mechanisms of action, the ovine being a relevant model to study human reproductive impairment. Disruption of GC steroidogenesis might alter oocyte quality and consequently fertility rate. In addition, we compared the effects of a specific GPER agonist (G-1) and antagonist (G-15) to those of BPA and BPS. Ewe GC were cultured with BPA or BPS (10 or 50 µM) or G-1 (1 µM) and/or G-15 (10 µM) for 48 h to study steroidogenesis. RESULTS: Both BPA and BPS (10 µM) altered the secretion of progesterone, however, only BPS (10 µM) affected oestradiol secretion. RNA-seq was performed on GC after 1 h of culture with BPA or BPS (50 µM) or G-1 (10 µM), followed by real-time PCR analyses of differentially expressed genes after 12, 24 and 48 h of culture. The absence of induced GPER target genes showed that BPA and BPS did not activate GPER in GC after 1 h of treatment. These molecules exhibited mainly independent early mechanisms of action. Gene ontology analysis showed that after 1 h of treatment, BPA mainly disrupted the expression of the genes involved in metabolism and transcription, while BPS had a smaller effect and impaired cellular communications. BPA had a transient effect on the expression of CHAC1 (NOTCH signalling and oxidative balance), JUN (linked to MAPK pathway), NR4A1 (oestradiol secretion inhibition), ARRDC4 (endocytose of GPCR) and KLF10 (cell growth, differentiation and apoptosis), while expression changes were maintained over time for the genes LSMEM1 (linked to MAPK pathway), TXNIP (oxidative stress) and LIF (cell cycle regulation) after 12 and 48 h, respectively. CONCLUSION: In conclusion, although they exhibited similar effects, BPA and BPS impaired different molecular pathways in GC in vitro. New investigations will be necessary to follow the temporal changes of these genes over time, as well as the biological processes involved.

Effect of medical staff training on vaccination coverage in outpatients with cancer: An interventional multicenter before-and-after study.

Purpose: Despite widely disseminated guidelines, pneumococcal and influenza vaccination coverage (VC) remains insufficient in patients with cancer receiving cancer treatment. We performed an interventional study to evaluate VC in patients with cancer treated at the medical oncology departments of three North-of-France hospitals and to assess the effect of medical staff training on VC in these patients. Methods: A standardized questionnaire assessed VC in adult patients with cancer receiving anticancer treatment at three day hospitals during December 2-7, 2019. Subsequently (January 2020), we organized educational training sessions for medical staff from each hospital to discuss the current vaccination guidelines. To assess the impact of training on pneumococcal and influenza VC, we re-administered the same questionnaire in March 2020. Because there are no specific guidelines on Diphtheria-Tetanus-Pertussis (DTP) vaccination and no improvement was expected, DTP VC acted as an internal control. Results: In total, 272 patients from all three hospitals were enrolled in the "before study"; 156 patients from only two hospitals were enrolled in the "after study" as medical training and data collection at the third were impossible because of administrative reasons and COVID-19 pandemic. The predictors were age for DTP VC; treatment center for pneumococcal VC; and age, sex, and tumor histology (adenocarcinoma vs. others) for influenza VC. Neither influenza VC (42.6% vs. 55.1%, p = 0.08), nor pneumococcal VC were significantly improved post-intervention (11.8% vs. 15.4%, p = 1). There seems to be a small effect in the most fragile for influenza VC. Conclusion: As expected, VC was very low in patients with cancer, consistent with the literature. There was no impact of the intervention for pneumococcal and influenza VC.

Specific detection and quantification of three microsporidia infecting bees, Nosema apis, Nosema ceranae, and Nosema bombi, using probe-based real-time PCR.

Among stressors affecting bee health, Nosema microsporidia are prevalent intracellular parasites. Nosema apis and Nosema ceranae have been described in honey bees (Apis spp.), while Nosema bombi has been described in bumble bees (Bombus spp.). Although available molecular methods serve as a complement to microscopic diagnosis of nosemosis, they do not enable accurate quantification of these three Nosema species. We developed three quantitative real-time PCRs (qPCRs) starting from in silico design of specific primers, probes, and recombinant plasmids, to target the RNA polymerase II subunit B1 (RPB1) gene in the three species. The complete methods, including bee grinding, DNA purification, and qPCR, were validated in honey bee (Apis mellifera) homogenate. Specificity was assessed in silico and in vitro with several types of bee samples. The limit of detection was estimated at 4 log10 copies/honey bee. A small, systematic method bias was corrected for accurate quantification up to 10 log10 copies/honey bee. Method accuracy was also verified in bumble bee (Bombus terrestris) and mason bee (Osmia bicornis) homogenates in the range of 5 to 10 log10 copies/bee. These validated qPCR methods open perspectives in nosemosis diagnosis and in the study of the parasite's eco-dynamics in managed and wild bees.

Bisphenol S Alters the Steroidome in the Preovulatory Follicle, Oviduct Fluid and Plasma in Ewes With Contrasted Metabolic Status.

Bisphenol A (BPA), a plasticizer and endocrine disruptor, has been substituted by bisphenol S (BPS), a structural analogue that had already shown adverse effects on granulosa cell steroidogenesis. The objective of this study was to assess the effect of chronic exposure to BPS, a possible endocrine disruptor, on steroid hormones in the ovary, oviduct and plasma using the ewe as a model. Given the interaction between steroidogenesis and the metabolic status, the BPS effect was tested according to two diet groups. Eighty adult ewes were allotted to restricted (R) and well-fed (WF) groups, that were further subdivided into two subgroups. Ewes were exposed to 50 µg BPS/kg/day in their diet (R50 and WF50 groups) or were unexposed controls (R0 and WF0 groups). After at least 3 months of BPS exposure, preovulatory follicular fluid, oviduct fluid and plasma were collected and steroid hormones were analyzed by gas chromatography coupled with tandem mass spectrometry (GC-MS/MS). A deleterious effect of restricted diet on the volume of oviduct fluid and numbers of pre-ovulatory follicles was observed. Exposure to BPS impaired estradiol concentrations in both follicular and oviduct fluids of well-fed ewes and progesterone, estradiol and estrone concentrations in plasma of restricted ewes. In addition, a significant interaction between metabolic status and BPS exposure was observed for seven steroids, including estradiol. In conclusion, BPS acts in ewes as an endocrine disruptor with differential actions according to metabolic status.

Return of genomic results does not motivate intent to participate in research for all: Perspectives across 22 countries.

PURPOSE: The aim of this study was to determine how attitudes toward the return of genomic research results vary internationally. METHODS: We analyzed the "Your DNA, Your Say" online survey of public perspectives on genomic data sharing including responses from 36,268 individuals across 22 low-, middle-, and high-income countries, and these were gathered in 15 languages. We analyzed how participants responded when asked whether return of results (RoR) would motivate their decision to donate DNA or health data. We examined variation across the study countries and compared the responses of participants from other countries with those from the United States, which has been the subject of the majority of research on return of genomic results to date. RESULTS: There was substantial variation in the extent to which respondents reported being influenced by RoR. However, only respondents from Russia were more influenced than those from the United States, and respondents from 20 countries had lower odds of being partially or wholly influenced than those from the United States. CONCLUSION: There is substantial international variation in the extent to which the RoR may motivate people's intent to donate DNA or health data. The United States may not be a clear indicator of global attitudes. Participants' preferences for return of genomic results globally should be considered.

Bayesian dose regimen assessment in early phase oncology incorporating pharmacokinetics and pharmacodynamics.

Phase I dose-finding trials in oncology seek to find the maximum tolerated dose of a drug under a specific schedule. Evaluating drug schedules aims at improving treatment safety while maintaining efficacy. However, while we can reasonably assume that toxicity increases with the dose for cytotoxic drugs, the relationship between toxicity and multiple schedules remains elusive. We proposed a Bayesian dose regimen assessment method (DRtox) using pharmacokinetics/pharmacodynamics (PK/PD) to estimate the maximum tolerated dose regimen (MTD-regimen) at the end of the dose-escalation stage of a trial. We modeled the binary toxicity via a PD endpoint and estimated the dose regimen toxicity relationship through the integration of a dose regimen PD model and a PD toxicity model. For the first model, we considered nonlinear mixed-effects models, and for the second one, we proposed the following two Bayesian approaches: a logistic model and a hierarchical model. In an extensive simulation study, the DRtox outperformed traditional designs in terms of proportion of correctly selecting the MTD-regimen. Moreover, the inclusion of PK/PD information helped provide more precise estimates for the entire dose regimen toxicity curve; therefore the DRtox may recommend alternative untested regimens for expansion cohorts. The DRtox was developed to be applied at the end of the dose-escalation stage of an ongoing trial for patients with relapsed or refractory acute myeloid leukemia (NCT03594955) once all toxicity and PK/PD data are collected.

Bayesian modeling of a bivariate toxicity outcome for early phase oncology trials evaluating dose regimens.

Most phase I trials in oncology aim to find the maximum tolerated dose (MTD) based on the occurrence of dose limiting toxicities (DLT). Evaluating the schedule of administration in addition to the dose may improve drug tolerance. Moreover, for some molecules, a bivariate toxicity endpoint may be more appropriate than a single endpoint. However, standard dose-finding designs do not account for multiple dose regimens and bivariate toxicity endpoint within the same design. In this context, following a phase I motivating trial, we proposed modeling the first type of DLT, cytokine release syndrome, with the entire dose regimen using pharmacokinetics and pharmacodynamics (PK/PD), whereas the other DLT (DLTo ) was modeled with the cumulative dose. We developed three approaches to model the joint distribution of DLT, defining it as a bivariate binary outcome from the two toxicity types, under various assumptions about the correlation between toxicities: an independent model, a copula model and a conditional model. Our Bayesian approaches were developed to be applied at the end of the dose-allocation stage of the trial, once all data, including PK/PD measurements, were available. The approaches were evaluated through an extensive simulation study that showed that they can improve the performance of selecting the true MTD-regimen compared to the recommendation of the dose-allocation method implemented. Our joint approaches can also predict the DLT probabilities of new dose regimens that were not tested in the study and could be investigated in further stages of the trial.

Demonstrating trustworthiness when collecting and sharing genomic data: public views across 22 countries.

BACKGROUND: Public trust is central to the collection of genomic and health data and the sustainability of genomic research. To merit trust, those involved in collecting and sharing data need to demonstrate they are trustworthy. However, it is unclear what measures are most likely to demonstrate this. METHODS: We analyse the 'Your DNA, Your Say' online survey of public perspectives on genomic data sharing including responses from 36,268 individuals across 22 low-, middle- and high-income countries, gathered in 15 languages. We examine how participants perceived the relative value of measures to demonstrate the trustworthiness of those using donated DNA and/or medical information. We examine between-country variation and present a consolidated ranking of measures. RESULTS: Providing transparent information about who will benefit from data access was the most important measure to increase trust, endorsed by more than 50% of participants across 20 of 22 countries. It was followed by the option to withdraw data and transparency about who is using data and why. Variation was found for the importance of measures, notably information about sanctions for misuse of data-endorsed by 5% in India but almost 60% in Japan. A clustering analysis suggests alignment between some countries in the assessment of specific measures, such as the UK and Canada, Spain and Mexico and Portugal and Brazil. China and Russia are less closely aligned with other countries in terms of the value of the measures presented. CONCLUSIONS: Our findings highlight the importance of transparency about data use and about the goals and potential benefits associated with data sharing, including to whom such benefits accrue. They show that members of the public value knowing what benefits accrue from the use of data. The study highlights the importance of locally sensitive measures to increase trust as genomic data sharing continues globally.

Development and evaluation of a core genome multilocus sequence typing scheme for Paenibacillus larvae, the deadly American foulbrood pathogen of honeybees.

Paenibacillus larvae is the causative agent of the fatal American foulbrood disease in honeybees (Apis mellifera). Strain identification is vital for preventing the spread of the disease. To date, the most accessible and robust scheme to identify strains is the multilocus sequence typing (MLST) method. However, this approach has limited resolution, especially for epidemiological studies. As the cost of whole-genome sequencing has decreased and as it becomes increasingly available to most laboratories, an extended MLST based on the core genome (cgMLST) presents a valuable tool for high-resolution investigations. In this study, we present a standardized, robust cgMLST scheme for P. larvae typing using whole-genome sequencing. A total of 333 genomes were used to identify, validate and evaluate 2419 core genes. The cgMLST allowed fine-scale differentiation between samples that had the same profile using traditional MLST and allowed for the characterization of strains impossible by MLST. The scheme was successfully used to trace a localized Swedish outbreak, where a cluster of 38 isolates was linked to a country-wide beekeeping operation. cgMLST greatly enhances the power of a traditional typing scheme, while preserving the same stability and standardization for sharing results and methods across different laboratories.

Arabidopsis cell wall composition determines disease resistance specificity and fitness.

Plant cell walls are complex structures subject to dynamic remodeling in response to developmental and environmental cues and play essential functions in disease resistance responses. We tested the specific contribution of plant cell walls to immunity by determining the susceptibility of a set of Arabidopsis cell wall mutants (cwm) to pathogens with different parasitic styles: a vascular bacterium, a necrotrophic fungus, and a biotrophic oomycete. Remarkably, most cwm mutants tested (29/34; 85.3%) showed alterations in their resistance responses to at least one of these pathogens in comparison to wild-type plants, illustrating the relevance of wall composition in determining disease-resistance phenotypes. We found that the enhanced resistance of cwm plants to the necrotrophic and vascular pathogens negatively impacted cwm fitness traits, such as biomass and seed yield. Enhanced resistance of cwm plants is not only mediated by canonical immune pathways, like those modulated by phytohormones or microbe-associated molecular patterns, which are not deregulated in the cwm tested. Pectin-enriched wall fractions isolated from cwm plants triggered immune responses in wild-type plants, suggesting that wall-mediated defensive pathways might contribute to cwm resistance. Cell walls of cwm plants show a high diversity of composition alterations as revealed by glycome profiling that detect specific wall carbohydrate moieties. Mathematical analysis of glycome profiling data identified correlations between the amounts of specific wall carbohydrate moieties and disease resistance phenotypes of cwm plants. These data support the relevant and specific function of plant wall composition in plant immune response modulation and in balancing disease resistance/development trade-offs.

Global Public Perceptions of Genomic Data Sharing: What Shapes the Willingness to Donate DNA and Health Data?

Analyzing genomic data across populations is central to understanding the role of genetic factors in health and disease. Successful data sharing relies on public support, which requires attention to whether people around the world are willing to donate their data that are then subsequently shared with others for research. However, studies of such public perceptions are geographically limited and do not enable comparison. This paper presents results from a very large public survey on attitudes toward genomic data sharing. Data from 36,268 individuals across 22 countries (gathered in 15 languages) are presented. In general, publics across the world do not appear to be aware of, nor familiar with, the concepts of DNA, genetics, and genomics. Willingness to donate one's DNA and health data for research is relatively low, and trust in the process of data's being shared with multiple users (e.g., doctors, researchers, governments) is also low. Participants were most willing to donate DNA or health information for research when the recipient was specified as a medical doctor and least willing to donate when the recipient was a for-profit researcher. Those who were familiar with genetics and who were trusting of the users asking for data were more likely to be willing to donate. However, less than half of participants trusted more than one potential user of data, although this varied across countries. Genetic information was not uniformly seen as different from other forms of health information, but there was an association between seeing genetic information as special in some way compared to other health data and increased willingness to donate. The global perspective provided by our "Your DNA, Your Say" study is valuable for informing the development of international policy and practice for sharing genomic data. It highlights that the research community not only needs to be worthy of trust by the public, but also urgent steps need to be taken to authentically communicate why genomic research is necessary and how data donation, and subsequent sharing, is integral to this.

Bayesian methods for the analysis of early-phase oncology basket trials with information borrowing across cancer types.

Research in oncology has changed the focus from histological properties of tumors in a specific organ to a specific genomic aberration potentially shared by multiple cancer types. This motivates the basket trial, which assesses the efficacy of treatment simultaneously on multiple cancer types that have a common aberration. Although the assumption of homogeneous treatment effects seems reasonable given the shared aberration, in reality, the treatment effect may vary by cancer type, and potentially only a subgroup of the cancer types respond to the treatment. Various approaches have been proposed to increase the trial power by borrowing information across cancer types, which, however, tend to inflate the type I error rate. In this article, we review some representative Bayesian information borrowing methods for the analysis of early-phase basket trials. We then propose a novel method called the Bayesian hierarchical model with a correlated prior (CBHM), which conducts more flexible borrowing across cancer types according to sample similarity. We did simulation studies to compare CBHM with independent analysis and three information borrowing approaches: the conventional Bayesian hierarchical model, the EXNEX approach, and Liu's two-stage approach. Simulation results show that all information borrowing approaches substantially improve the power of independent analysis if a large proportion of the cancer types truly respond to the treatment. Our proposed CBHM approach shows an advantage over the existing information borrowing approaches, with a power similar to that of EXNEX or Liu's approach, but the potential to provide substantially better control of type I error rate.

The Alzheimer's Prevention Initiative Composite Cognitive Test: a practical measure for tracking cognitive decline in preclinical Alzheimer's disease.

BACKGROUND: There is growing interest in identifying sensitive composite cognitive tests to serve as primary endpoints in preclinical Alzheimer's disease (AD) treatment trials. We reported previously a composite cognitive test score sensitive to tracking preclinical AD decline up to 5 years prior to clinical diagnosis. Here we expand upon and refine this work, empirically deriving a composite cognitive test score sensitive to tracking preclinical AD decline up to 11 years prior to diagnosis and suitable for use as a primary endpoint in a preclinical AD trial. METHODS: This study used a longitudinal approach to maximize sensitivity to tracking progressive cognitive decline in people who progressed to the clinical stages of AD (n = 868) compared to those who remained cognitively unimpaired during the same time period (n = 989), thereby correcting for normal aging and practice effects. Specifically, we developed the Alzheimer's Prevention Initiative Preclinical Composite Cognitive test (APCC) to measure very early longitudinal cognitive decline in older adults with preclinical AD. Data from three cohorts from Rush University were analyzed using a partial least squares (PLS) regression model to identify optimal composites within different time periods prior to diagnosis, up to 11 years prior to diagnosis. The mean-to-standard deviation ratio (MSDRs) is an indicator of sensitivity to change and was used to inform the final calculation of the composite score. RESULTS: The optimal composite, the APCC, is calculated: 0.26*Symbol Digit Modalities + 2.24*MMSE Orientation to Time + 2.14*MMSE Orientation to Place + 0.53*Logical Memory Delayed Recall + 1.36* Word List-Delayed Recall + 0.68*Judgment of Line Orientation + 1.39*Raven's Progressive Matrices Matrices (subset of 9 items from A and B). The MSDR of the APCC in a population of preclinical AD individuals who eventually progress to cognitive impairment, compared to those who remained cognitively unimpaired during the same time period, was - 1.10 over 1 year. CONCLUSIONS: The APCC is an empirically derived composite cognitive test score with high face validity that is sensitive to preclinical AD decline up to 11 years prior to diagnosis of the clinical stages of AD. The components of the APCC are supported by theoretical understanding of cognitive decline that occurs during preclinical AD. The APCC was used as a primary outcome in the API Generation Program trials.

Robust designs in longitudinal studies accounting for parameter and model uncertainties - application to count data.

Nonlinear mixed effect models (NLMEMs) are widely used for the analysis of longitudinal data. To design these studies, optimal designs based on the expected Fisher information matrix (FIM) can be used. A method evaluating the FIM using Monte-Carlo Hamiltonian Monte-Carlo (MC-HMC) has been proposed and implemented in the R package MIXFIM using Stan. This approach, however, requires a priori knowledge of models and parameters, which leads to locally optimal designs. The objective of this work was to extend this MC-HMC-based method to evaluate the FIM in NLMEMs accounting for uncertainty in parameters and in models. When introducing uncertainty in the population parameters, we evaluated the robust FIM as the expectation of the FIM computed by MC-HMC over the distribution of these parameters. Then, the compound D-optimality criterion (CD optimality), corresponding to a weighted product of the D-optimality criteria of several candidate models, was used to find a common CD-optimal design for the set of candidate models. Finally, a compound DE-criterion (CDE optimality), corresponding to a weighted product of the normalized determinants of the robust FIMs of all the candidate models accounting for uncertainty in parameters, was calculated to find the CDE-optimal design which was robust on both parameters and model. These methods were applied in a longitudinal Poisson count model. We assumed prior distributions on the population parameters, as well as several candidate models describing the relationship between the logarithm of the event rate parameter and the dose. We found that assuming uncertainty in parameters could lead to different optimal designs, and misspecification of models could induce designs with low efficiencies. The CD- or CDE-optimal designs therefore provided a good compromise for different candidate models. Finally, the proposed approach allows for the first time optimization of designs for repeated discrete data accounting for parameter and model uncertainties.

The Alzheimer's Prevention Initiative Generation Program: Study design of two randomized controlled trials for individuals at risk for clinical onset of Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD) pathology, including the accumulation of amyloid beta (Aß) species and tau pathology, begins decades before the onset of cognitive impairment. This long preclinical period provides an opportunity for clinical trials designed to prevent or delay the onset of cognitive impairment due to AD. Under the umbrella of the Alzheimer's Prevention Initiative Generation Program, therapies targeting Aß, including CNP520 (umibecestat), a ß-site-amyloid precursor protein cleaving enzyme-1 (BACE-1) inhibitor, and CAD106, an active Aß immunotherapy, are in clinical development in preclinical AD. METHODS: The Alzheimer's Prevention Initiative Generation Program comprises two pivotal (phase 2/3) studies that assess the efficacy and safety of umibecestat and CAD106 in cognitively unimpaired individuals with high risk for developing symptoms of AD based on their age (60-75 years), APOE4 genotype, and, for heterozygotes (APOE ε2/ε4 or ε3/ε4), elevated brain amyloid. Approximately, 3500 individuals will be enrolled in either Generation Study 1 (randomized to cohort 1 [CAD106 injection or placebo, 5:3] or cohort 2 [oral umibecestat 50 mg or placebo, 3:2]) or Generation Study 2 (randomized to oral umibecestat 50 mg and 15 mg, or placebo [2:1:2]). Participants receive treatment for at least 60 months and up to a maximum of 96 months. Primary outcomes include time to event, with event defined as diagnosis of mild cognitive impairment due to AD and/or dementia due to AD, and the Alzheimer's Prevention Initiative preclinical composite cognitive test battery. Secondary endpoints include the Clinical Dementia Rating Sum of Boxes, Repeatable Battery for the Assessment of Neuropsychological Status total score, Everyday Cognition Scale, biomarkers, and brain imaging. DISCUSSION: The Generation Program is designed to assess the efficacy, safety, and biomarker effects of the two treatments in individuals at high risk for AD. It may also provide a plausible test of the amyloid hypothesis and further accelerate the evaluation of AD prevention therapies.