Precision mapping of schistosomiasis and soil-transmitted helminthiasis among school age children at the coastal region, Kenya.

BACKGROUND: Accurate mapping of schistosomiasis (SCH) and soil transmitted helminths (STH) is a prerequisite for effective implementation of the control and elimination interventions. A precision mapping protocol was developed and implemented in the coastal region of Kenya by applying the current World Health Organization (WHO) mapping guide at a much lower administrative level (ward). METHODS: A two-stage cluster survey design was undertaken, with 5 villages in each ward selected. From within each village 50 households were randomly selected, and a single child between the ages of 8 and 14 sampled following appropriate assent. The prevalence and intensity of infection of Schistosoma mansoni and STH were determined using the Kato-Katz method (single stool, duplicate slides) and urine filtration for S. haematobium. RESULTS: Of the 27,850 school age children sampled, 6.9% were infected with at least one Schistosoma species, with S. haematobium being the most common 6.1% (95% CI: 3.1-11.9), and Tana River County having highest prevalence 19.6% (95% CI: 11.6-31.3). Prevalence of any STH infection was 5.8% (95% CI: 3.7-8.9), with Lamu County having the highest prevalence at 11.9% (95% CI: 10.0-14.1). The most prevalent STH species in the region was Trichuris trichiura at 3.1% (95% CI: 2.0-4.8). According to the WHO threshold for MDA implementation, 31 wards (in 15 sub-Counties) had a prevalence of ≥10% for SCH and thus qualify for annual MDA of all age groups from 2 years old. On the other hand, using the stricter Kenya BTS MDA threshold of ≥2%, 72 wards (in 17 sub-Counties) qualified for MDA and were targeted for treatment in 2021. CONCLUSIONS: The precision mapping at the ward level demonstrated the variations of schistosomiasis prevalence and endemicity by ward even within the same sub-counties. The data collected will be utilized by the Kenyan Ministry of Health to improve targeting.

Responding to the cuts in UK AID to neglected tropical diseases control programmes in Africa.

The early termination of the Accelerating the Sustainable Control and Elimination of Neglected Tropical Diseases (Ascend) programme by the UK government in June 2021 was a bitter blow to countries in East and West Africa where no alternative source of funding existed. Here we assess the potential impact the cuts may have had if alternative funding had not been made available by new development partners and outline new strategies developed by affected countries to mitigate current and future disruptions to neglected tropical disease control programmes.

Modelling the impact of COVID-19-related control programme interruptions on progress towards the WHO 2030 target for soil-transmitted helminths.

BACKGROUND: On 1 April 2020, the WHO recommended an interruption of all activities for the control of neglected tropical diseases, including soil-transmitted helminths (STH), in response to the COVID-19 pandemic. This paper investigates the impact of this disruption on the progress towards the WHO 2030 target for STH. METHODS: We used two stochastic individual-based models to simulate the impact of missing one or more preventive chemotherapy (PC) rounds in different endemicity settings. We also investigated the extent to which this impact can be lessened by mitigation strategies, such as semiannual or community-wide PC. RESULTS: Both models show that without a mitigation strategy, control programmes will catch up by 2030, assuming that coverage is maintained. The catch-up time can be up to 4.5 y after the start of the interruption. Mitigation strategies may reduce this time by up to 2 y and increase the probability of achieving the 2030 target. CONCLUSIONS: Although a PC interruption will only temporarily impact the progress towards the WHO 2030 target, programmes are encouraged to restart as soon as possible to minimise the impact on morbidity. The implementation of suitable mitigation strategies can turn the interruption into an opportunity to accelerate progress towards reaching the target.

Association of TDP-43 proteinopathy, cerebral amyloid angiopathy, and Lewy bodies with cognitive impairment in individuals with or without Alzheimer's disease neuropathology.

Alzheimer's disease patients typically present with multiple co-morbid neuropathologies at autopsy, but the impact of these pathologies on cognitive impairment during life is poorly understood. In this study, we developed cognitive trajectories for patients with common co-pathologies in the presence and absence of Alzheimer's disease neuropathology. Cognitive trajectories were modelled in a Bayesian hierarchical regression framework to estimate the effects of each neuropathology on cognitive decline as assessed by the mini-mental state examination and the clinical dementia rating scale sum of boxes scores. We show that both TDP-43 proteinopathy and cerebral amyloid angiopathy associate with cognitive impairment of similar magnitude to that associated with Alzheimer's disease neuropathology. Within our study population, 63% of individuals given the 'gold-standard' neuropathological diagnosis of Alzheimer's disease in fact possessed either TDP-43 proteinopathy or cerebral amyloid angiopathy of sufficient severity to independently explain the majority of their cognitive impairment. This suggests that many individuals diagnosed with Alzheimer's disease may actually suffer from a mixed dementia, and therapeutics targeting only Alzheimer's disease-related processes may have severely limited efficacy in these co-morbid populations.

Twenty-seven-year time trends in dementia incidence in Europe and the United States: The Alzheimer Cohorts Consortium.

OBJECTIVE: To determine changes in the incidence of dementia between 1988 and 2015. METHODS: This analysis was performed in aggregated data from individuals >65 years of age in 7 population-based cohort studies in the United States and Europe from the Alzheimer Cohort Consortium. First, we calculated age- and sex-specific incidence rates for all-cause dementia, and then defined nonoverlapping 5-year epochs within each study to determine trends in incidence. Estimates of change per 10-year interval were pooled and results are presented combined and stratified by sex. RESULTS: Of 49,202 individuals, 4,253 (8.6%) developed dementia. The incidence rate of dementia increased with age, similarly for women and men, ranging from about 4 per 1,000 person-years in individuals aged 65-69 years to 65 per 1,000 person-years for those aged 85-89 years. The incidence rate of dementia declined by 13% per calendar decade (95% confidence interval [CI], 7%-19%), consistently across studies, and somewhat more pronouncedly in men than in women (24% [95% CI 14%-32%] vs 8% [0%-15%]). CONCLUSION: The incidence rate of dementia in Europe and North America has declined by 13% per decade over the past 25 years, consistently across studies. Incidence is similar for men and women, although declines were somewhat more profound in men. These observations call for sustained efforts to finding the causes for this decline, as well as determining their validity in geographically and ethnically diverse populations.

The dynamics of biomarkers across the clinical spectrum of Alzheimer's disease.

BACKGROUND: Quantifying changes in the levels of biological and cognitive markers prior to the clinical presentation of Alzheimer's disease (AD) will provide a template for understanding the underlying aetiology of the clinical syndrome and, concomitantly, for improving early diagnosis, clinical trial recruitment and treatment assessment. This study aims to characterise continuous changes of such markers and determine their rate of change and temporal order throughout the AD continuum. METHODS: The methodology is founded on the development of stochastic models to estimate the expected time to reach different clinical disease states, for different risk groups, and synchronise short-term individual biomarker data onto a disease progression timeline. Twenty-seven markers are considered, including a range of cognitive scores, cerebrospinal (CSF) and plasma fluid proteins, and brain structural and molecular imaging measures. Data from 2014 participants in the Alzheimer's Disease Neuroimaging Initiative database is utilised. RESULTS: The model suggests that detectable memory dysfunction could occur up to three decades prior to the onset of dementia due to AD (ADem). This is closely followed by changes in amyloid-ß CSF levels and the first cognitive decline, as assessed by sensitive measures. Hippocampal atrophy could be observed as early as the initial amyloid-ß accumulation. Brain hypometabolism starts later, about 14 years before onset, along with changes in the levels of total and phosphorylated tau proteins. Loss of functional abilities occurs rapidly around ADem onset. Neurofilament light is the only protein with notable early changes in plasma levels. The rate of change varies, with CSF, memory, amyloid PET and brain structural measures exhibiting the highest rate before the onset of ADem, followed by a decline. The probability of progressing to a more severe clinical state increases almost exponentially with age. In accordance with previous studies, the presence of apolipoprotein E4 alleles and amyloid-ß accumulation can be associated with an increased risk of developing the disease, but their influence depends on age and clinical state. CONCLUSIONS: Despite the limited longitudinal data at the individual level and the high variability observed in such data, the study elucidates the link between the long asynchronous pathophysiological processes and the preclinical and clinical stages of AD.

Plasma tau, neurofilament light chain and amyloid-ß levels and risk of dementia; a population-based cohort study.

CSF biomarkers, including total-tau, neurofilament light chain (NfL) and amyloid-ß, are increasingly being used to define and stage Alzheimer's disease. These biomarkers can be measured more quickly and less invasively in plasma and may provide important information for early diagnosis of Alzheimer's disease. We used stored plasma samples and clinical data obtained from 4444 non-demented participants in the Rotterdam study at baseline (between 2002 and 2005) and during follow-up until January 2016. Plasma concentrations of total-tau, NfL, amyloid-ß40 and amyloid-ß42 were measured using the Simoa NF-light® and N3PA assays. Associations between biomarker plasma levels and incident all-cause and Alzheimer's disease dementia during follow-up were assessed using Cox proportional-hazard regression models adjusted for age, sex, education, cardiovascular risk factors and APOE ε4 status. Moreover, biomarker plasma levels and rates of change over time of participants who developed Alzheimer's disease dementia during follow-up were compared with age and sex-matched dementia-free control subjects. During up to 14 years follow-up, 549 participants developed dementia, including 374 cases with Alzheimer's disease dementia. A log2 higher baseline amyloid-ß42 plasma level was associated with a lower risk of developing all-cause or Alzheimer's disease dementia, adjusted hazard ratio (HR) 0.61 [95% confidence interval (CI), 0.47-0.78; P < 0.0001] and 0.59 (95% CI, 0.43-0.79; P = 0.0006), respectively. Conversely, a log2 higher baseline plasma NfL level was associated with a higher risk of all-cause dementia [adjusted HR 1.59 (95% CI, 1.38-1.83); P < 0.0001] or Alzheimer's disease [adjusted HR 1.50 (95% CI, 1.26-1.78); P < 0.0001]. Combining the lowest quartile group of amyloid-ß42 with the highest of NfL resulted in a stronger association with all-cause dementia [adjusted HR 9.5 (95% CI, 2.3-40.4); P < 0.002] and with Alzheimer's disease [adjusted HR 15.7 (95% CI, 2.1-117.4); P < 0.0001], compared to the highest quartile group of amyloid-ß42 and lowest of NfL. Total-tau and amyloid-ß40 levels were not associated with all-cause or Alzheimer's disease dementia risk. Trajectory analyses of biomarkers revealed that mean NfL plasma levels increased 3.4 times faster in participants who developed Alzheimer's disease compared to those who remained dementia-free (P < 0.0001), plasma values for cases diverged from controls 9.6 years before Alzheimer's disease diagnosis. Amyloid-ß42 levels began to decrease in Alzheimer's disease cases a few years before diagnosis, although the decline did not reach significance compared to dementia-free participants. In conclusion, our study shows that low amyloid-ß42 and high NfL plasma levels are each independently and in combination strongly associated with risk of all-cause and Alzheimer's disease dementia. These data indicate that plasma NfL and amyloid-ß42 levels can be used to assess the risk of developing dementia in a non-demented population. Plasma NfL levels, although not specific, may also be useful in monitoring progression of Alzheimer's disease dementia.

Alzheimer's disease progression and risk factors: A standardized comparison between six large data sets.

There exist a large number of cohort studies that have been used to identify genetic and biological risk factors for developing Alzheimer's disease (AD). However, there is a disagreement between studies as to how strongly these risk factors affect the rate of progression through diagnostic groups toward AD. We have calculated the probability of transitioning through diagnostic groups in six studies and considered how uncertainty around the strength of the effect of these risk factors affects estimates of the distribution of individuals in each diagnostic group in an AD clinical trial simulator. In this work, we identify the optimal choice of widely collected variables for comparing data sets and calculating probabilities of progression toward AD. We use the estimated transition probabilities to inform stochastic simulations of AD progression that are based on a Markov model and compare predicted incidence rates to those in a community-based study, the Cardiovascular Health Study.

Perspective: Clinical relevance of the dichotomous classification of Alzheimer's disease biomarkers: Should there be a "gray zone"?

The 2018 National Institute on Aging and the Alzheimer's Association (NIA-AA) research framework recently redefined Alzheimer's disease (AD) as a biological construct, based on in vivo biomarkers reflecting key neuropathologic features. Combinations of normal/abnormal levels of three biomarker categories, based on single thresholds, form the AD signature profile that defines the biological disease state as a continuum, independent of clinical symptomatology. While single thresholds may be useful in defining the biological signature profile, we provide evidence that their use in studies with cognitive outcomes merits further consideration. Using data from the Alzheimer's Disease Neuroimaging Initiative with a focus on cortical amyloid binding, we discuss the limitations of applying the biological definition of disease status as a tool to define the increased likelihood of the onset of the Alzheimer's clinical syndrome and the effects that this may have on trial study design. We also suggest potential research objectives going forward and what the related data requirements would be.

Potential Factors Associated with Cognitive Improvement of Individuals Diagnosed with Mild Cognitive Impairment or Dementia in Longitudinal Studies.

Despite the progressive nature of Alzheimer's disease and other dementias, it is observed that many individuals that are diagnosed with mild cognitive impairment (MCI) in one clinical assessment, may return back to normal cognition (CN) in a subsequent assessment. Less frequently, such 'back-transitions' are also observed in people that had already been diagnosed with later stages of dementia. In this study, an analysis was performed on two longitudinal cohort datasets provided by 1) the Alzheimer's Disease Neuroimaging Initiative (ADNI) and 2) the National Alzheimer's Coordinating Centre (NACC). The focus is on the observed improvement of individuals' clinical condition recorded in these datasets to explore potential associations with different factors. It is shown that, in both datasets, transitions from MCI to CN are significantly associated with younger age, better cognitive function, and the absence of ApoE ɛ4 alleles. Better cognitive function and in some cases the absence of ApoE ɛ4 alleles are also significantly associated with transitions from types of dementia to less severe clinical states. The effect of gender and education is not clear-cut in these datasets, although highly educated people who reach MCI tend to be more likely to show an improvement in their clinical state. The potential effect of other factors such as changes in symptoms of depression is also discussed. Although improved clinical outcomes can be associated with many factors, better diagnostic tools are required to provide insight into whether such improvements are a result of misdiagnosis, and if they are not, whether they are linked to improvements in the underlying neuropathological condition.

The importance of endpoint selection: How effective does a drug need to be for success in a clinical trial of a possible Alzheimer's disease treatment?

To date, Alzheimer's disease (AD) clinical trials have been largely unsuccessful. Failures have been attributed to a number of factors including ineffective drugs, inadequate targets, and poor trial design, of which the choice of endpoint is crucial. Using data from the Alzheimer's Disease Neuroimaging Initiative, we have calculated the minimum detectable effect size (MDES) in change from baseline of a range of measures over time, and in different diagnostic groups along the AD development trajectory. The Functional Activities Questionnaire score had the smallest MDES for a single endpoint where an effect of 27% could be detected within 3 years in participants with Late Mild Cognitive Impairment (LMCI) at baseline, closely followed by the Clinical Dementia Rating Sum of Boxes (CDRSB) score at 28% after 2 years in the same group. Composite measures were even more successful than single endpoints with an MDES of 21% in 3 years. Using alternative cognitive, imaging, functional, or composite endpoints, and recruiting patients that have LMCI could improve the success rate of AD clinical trials.