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Observational studies in Alzheimer disease: bridging preclinical studies and clinical trials
Abstract
Recent high-profile failures of Alzheimer disease treatments at the clinical trial stage have led to renewed efforts to identify and test novel interventions for Alzheimer disease and related dementias (ADRD). In this Perspective, we highlight the importance of including well-designed observational studies as part of these efforts. Observational research is an important cornerstone for gathering evidence on risk factors and causes of ADRD; this evidence can then be combined with data from preclinical studies and randomized controlled trials to inform the development of effective interventions. Observational study designs can be particularly beneficial for hypothesis generation, posing questions that are unethical or impractical for a trial setting, studying life-course associations, research in populations typically not included in trials, and public health surveillance. Here, we discuss each of these situations in the specific context of ADRD research. We also highlight novel approaches to enhance causal inference and provide a timely discussion on how observational epidemiological studies help provide a bridge between preclinical studies and successful interventions for ADRD.
... Observational studies are currently a major source of evidence on risk factors and potential causes of dementia. [1][2][3] It is becoming increasingly clear that these real-world population-based studies need to work towards presenting robust evidence for inference of causality rather than reporting on associations alone to better inform effective prevention and treatment. [4] Furthermore, there is a push to combine evidence from diverse settings. ...
The Harmonized Cognitive Assessment Protocol (HCAP) is a detailed battery assessing cognition among older people used by studies across the world. Data harmonization is a key priority for HCAP studies. We used a mixed-methods approach using established theories from the existing literature detailing the methodologies of longitudinal studies and from the implementation of HCAP in four English-speaking studies adopting the same protocol. Through a detailed investigation involving the English Longitudinal Study of Ageing (ELSA), the Health and Retirement Study (HRS), The Irish Longitudinal Study on Ageing (TILDA), and the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA), we identified 60 factors contributing to the development of a conceptual framework for the evaluation and implementation of HCAP. We present this framework and a prototype checklist as a tool for providing a transparent and structured approach to improve data quality, cross-country comparability and for identifying, mitigating, and monitoring sources of bias. The framework consisting of four broad headings: (1) Organisation and design, (2) Competency of personnel and systems, (3) Implementation and outputs, and (4) Feedback and communication. Studies seeking to harmonize results in cross-national contexts should give operational aspects of fieldwork careful consideration as part of the harmonization process.
... Due to the random allocation of genetic variations during conception prior to disease onset, MR is considered superior to traditional RCT studies in identifying causal relationships by effectively controlling for confounding factors and obtaining more accurate conclusions [12]. RA is the result of interactions between genetic susceptibility, environmental factors, and immune factors, with genetic factors accounting for 50-60% of the risk for RA [13]. Therefore, many recent studies have used two-sample Mendelian randomization (TSMR) to investigate causal relationships between various exposure factors and RA outcomes. ...
Background
Immune factors are crucial in the pathogenesis of rheumatoid arthritis (RA), and immune cells play a key role in the development of RA. However, there is still disagreement regarding the specific roles of each type of immune cell in the pathological process of RA.
Methods
This study used bidirectional two-sample Mendelian randomization (MR) analysis to determine the causal relationship between immune cell characteristics and RA. Utilizing publicly available genetic data, we initially treated immune cell characteristics as exposures to investigate their causal effects on the risk of RA. Subsequently, we performed reverse two-sample MR using the positively selected cells from the initial analysis as outcomes, aiming to identify the core immune cells involved. Finally, a comprehensive sensitivity analysis was conducted to validate the robustness, heterogeneity, and horizontal pleiotropy of the results.
Results
Using data from 731 immune cells as exposures and cell SNPs as instruments, we independently conducted two-sample MR analysis for each patient with RA. The main analytical method used was the IVW method, with a significance level set at P < 0.05 for inclusion. In total, we identified 42 immune cell phenotypes that were causally associated with the onset of RA. For the reverse MR analysis, we used RA as the exposure factor and focused on 42 immune cell phenotypes as outcomes. Our analysis revealed causal relationships between the onset of RA and 7 immune cell phenotypes. Among these, 6 showed positive causal relationships, while 1 exhibited a negative causal relationship.
Conclusions
Our study emphasized the causal relationship between immune cells and RA through bidirectional two-sample MR analysis, identifying the immune cells causally associated with RA.
... Patients with dementia are typically excluded from RCTs and informed consent can be difficult to obtain. These patients are, however, likely medication users in the realworld setting [28]. Even RCTs of anti-dementia drugs do not adequately reflect the real-world setting of patients with dementia. ...
With ageing of the population worldwide and discovery of new medications for prevention and management of age-related conditions, there is increasing use of medications by older adults. There are international efforts to increase the representativeness of participants in clinical trials to match the intended real-world users of the medications across a range of characteristics including age, multimorbidity, polypharmacy and frailty. Currently, much of the data on medication-related harm in older adults are from pharmacovigilance studies. New methods in pre-clinical models have allowed for measurement of exposures (such as chronic exposure, polypharmacy and deprescribing) and outcomes (such as health span functional measures and frailty) that are highly relevant to geriatric pharmacotherapy. Here we describe opportunities for design and implementation of pre-clinical models that can better predict drug effects in geriatric patients. This could improve the translation of new drugs from bench to bedside and improve outcomes of pharmacotherapy in older adults.
Através de um percurso individual, este trabalho põe em evidência os principais avanços científicos da neurociência e sua contribuição para o tratamento das mais frequentes doenças neurológicas.
Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele. Meta-analysis of genome-wide association studies on Alzheimer’s disease and related dementias identifies new loci and enables generation of a new genetic risk score associated with the risk of future Alzheimer’s disease and dementia.
Objectives
There has been increasing epidemiological research examining the association between vision impairment (VI) and cognitive impairment and how poor vision may be a modifiable risk factor for cognitive decline. The objective of this systematic review is to synthesise the published literature on the association of VI with cognitive decline, cognitive impairment or dementia, to aid the development of interventions and guide public policies pertaining to the relationship between vision and cognition.
Methods
A literature search was performed with Embase, Medline and Cochrane library databases from inception to March 2020, and included abstracts and articles published in peer-reviewed journals in English. Our inclusion criteria included publications that contained subjective/objective measures of vision and cognition, or a diagnosis of VI, cognitive impairment or dementia. Longitudinal or cross-sectional studies with ≥100 participants aged >50 years were included. The search identified 11 805 articles whose abstracts underwent screening by three teams of study authors. Data abstraction and quality assessment using the Effective Public Health Practice Project Quality Assessment Tool were performed by one author (NN). 10% of the articles underwent abstraction and appraisal by a second author (LA/VV), results were compared between both and were in agreement.
Results
110 full-text articles were selected for data extraction, of which 53 were cross-sectional, 43 longitudinal and 14 were case–control studies. The mean age of participants was 73.0 years (range 50–93.1). Ninety-one (83%) of these studies reported that VI was associated with cognitive impairment.
Conclusion
Our systematic review indicates that a majority of studies examining the vision–cognition relationship report that VI is associated with more cognitive decline, cognitive impairment or dementia among older adults. This synthesis supports the need for additional research to understand the mechanisms underlying the association between VI and cognitive impairment and to test interventions that mitigate the cognitive consequences of VI.
Importance
Visual function is important for older adults. Interventions to preserve vision, such as cataract extraction, may modify dementia risk.
Objective
To determine whether cataract extraction is associated with reduced risk of dementia among older adults.
Design, Setting, and Participants
This prospective, longitudinal cohort study analyzed data from the Adult Changes in Thought study, an ongoing, population-based cohort of randomly selected, cognitively normal members of Kaiser Permanente Washington. Study participants were 65 years of age or older and dementia free at enrollment and were followed up biennially until incident dementia (all-cause, Alzheimer disease, or Alzheimer disease and related dementia). Only participants who had a diagnosis of cataract or glaucoma before enrollment or during follow-up were included in the analyses (ie, a total of 3038 participants). Data used in the analyses were collected from 1994 through September 30, 2018, and all data were analyzed from April 6, 2019, to September 15, 2021.
Exposures
The primary exposure of interest was cataract extraction. Data on diagnosis of cataract or glaucoma and exposure to surgery were extracted from electronic medical records. Extensive lists of dementia-related risk factors and health-related variables were obtained from study visit data and electronic medical records.
Main Outcomes and Measures
The primary outcome was dementia as defined by Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) criteria. Multivariate Cox proportional hazards regression analyses were conducted with the primary outcome. To address potential healthy patient bias, weighted marginal structural models incorporating the probability of surgery were used and the association of dementia with glaucoma surgery, which does not restore vision, was evaluated.
Results
In total, 3038 participants were included (mean [SD] age at first cataract diagnosis, 74.4 (6.2) years; 1800 women (59%) and 1238 men (41%); and 2752 (91%) self-reported White race). Based on 23 554 person-years of follow-up, cataract extraction was associated with significantly reduced risk (hazard ratio, 0.71; 95% CI, 0.62-0.83; P < .001) of dementia compared with participants without surgery after controlling for years of education, self-reported White race, and smoking history and stratifying by apolipoprotein E genotype, sex, and age group at cataract diagnosis. Similar results were obtained in marginal structural models after adjusting for an extensive list of potential confounders. Glaucoma surgery did not have a significant association with dementia risk (hazard ratio, 1.08; 95% CI, 0.75-1.56; P = .68). Similar results were found with the development of Alzheimer disease dementia.
Conclusions and Relevance
This cohort study found that cataract extraction was significantly associated with lower risk of dementia development. If validated in future studies, cataract surgery may have clinical relevance in older adults at risk of developing dementia.
Importance
Low socioeconomic status (SES) has been identified as a risk factor for the development of dementia. However, few studies have focused on the association between SES and dementia diagnostic evaluation on a population level.
Objective
To investigate whether household income (HHI) is associated with dementia diagnosis and cognitive severity at the time of diagnosis.
Design, Setting, and Participants
This population- and register-based cross-sectional study analyzed health, social, and economic data obtained from various Danish national registers. The study population comprised individuals who received a first-time referral for a diagnostic evaluation for dementia to the secondary health care sector of Denmark between January 1, 2017, and December 17, 2018. Dementia-related health data were retrieved from the Danish Quality Database for Dementia. Data analysis was conducted from October 2019 to December 2020.
Exposures
Annual HHI (used as a proxy for SES) for 2015 and 2016 was obtained from Statistics Denmark and categorized into upper, middle, and lower tertiles within 5-year interval age groups.
Main Outcomes and Measures
Dementia diagnoses (Alzheimer disease, vascular dementia, mixed dementia, dementia with Lewy bodies, Parkinson disease dementia, or other) and cognitive stages at diagnosis (cognitively intact; mild cognitive impairment but not dementia; or mild, moderate, or severe dementia) were retrieved from the database. Univariable and multivariable logistic and linear regressions adjusted for age group, sex, region of residence, household type, period (2017 and 2018), medication type, and medical conditions were analyzed for a possible association between HHI and receipt of dementia diagnosis.
Results
Among the 10 191 individuals (mean [SD] age, 75 [10] years; 5476 women [53.7%]) included in the study, 8844 (86.8%) were diagnosed with dementia. Individuals with HHI in the upper tertile compared with those with lower-tertile HHI were less likely to receive a dementia diagnosis after referral (odds ratio, 0.65; 95% CI, 0.55-0.78) and, if diagnosed with dementia, had less severe cognitive stage (β, −0.16; 95% CI, −0.21 to −0.10). Individuals with middle-tertile HHI did not significantly differ from those with lower-tertile HHI in terms of dementia diagnosis (odds ratio, 0.92; 95% CI, 0.77-1.09) and cognitive stage at diagnosis (β, 0.01; 95% CI, −0.04 to 0.06).
Conclusions and Relevance
The results of this study revealed a social inequality in dementia diagnostic evaluation: in Denmark, people with higher income seem to receive an earlier diagnosis. Public health strategies should target people with lower SES for earlier dementia detection and intervention.
Objective
To investigate whether Cholinesterase inhibitors (ChEIs) are associated with slower cognitive decline in Alzheimer’s dementia, and decreased risk of severe dementia or death.
Methods
Alzheimer’s dementia patients from the Swedish Dementia Registry (SveDem) starting on ChEIs within three months of the dementia diagnosis were included and compared to non-treated Alzheimer’s dementia patients. In a propensity score matched cohort, the association between ChEI-use and cognitive trajectories assessed by MMSE scores were examined with a mixed model, and severe dementia (MMSE<10) or death as outcomes with Cox proportional hazards models.
Results
The matched cohort included 11,652 ChEI-users and 5,826 non-users. During an average of 5 years follow up, 255 cases developed severe dementia and 6,055 (35%) died. ChEI-use was associated with higher MMSE at each visit (0.13 MMSE points/year; 95% confidence interval-CI 0.06, 0.20). ChEI-use had a 27% lower risk of death (0.73; CI 0.69, 0.77) compared with non-users. Galantamine was associated with lower risk of death (0.71; CI 0.65, 0.76), lower risk of severe dementia (0.69; CI 0.47-1.00), and had the strongest effect on cognitive decline of all the ChEIs (0.18 MMSE points/year, CI 0.07, 0.28).
Conclusions
ChEIs are associated with cognitive benefits which are modest but persist over time and with reduced mortality risk, which could be explained partly by their cognitive effects. Galantamine was the only ChEI demonstrating a significant reduction in the risk of developing severe dementia.
Classification of Evidence
This study provides Class III evidence that for patients with Alzheimer’s dementia, ChEIs decrease long term cognitive decline and risk of death, and that galantamine decreases the risk of severe dementia.
Vitamin B12 is often used to improve cognitive function, depressive symptoms, and fatigue. In most cases, such complaints are not associated with overt vitamin B12 deficiency or advanced neurological disorders and the effectiveness of vitamin B12 supplementation in such cases is uncertain. The aim of this systematic review and meta-analysis of randomized controlled trials (RCTs) is to assess the effects of vitamin B12 alone (B12 alone), in addition to vitamin B12 and folic acid with or without vitamin B6 (B complex) on cognitive function, depressive symptoms, and idiopathic fatigue in patients without advanced neurological disorders or overt vitamin B12 deficiency. Medline, Embase, PsycInfo, Cochrane Library, and Scopus were searched. A total of 16 RCTs with 6276 participants were included. Regarding cognitive function outcomes, we found no evidence for an effect of B12 alone or B complex supplementation on any subdomain of cognitive function outcomes. Further, meta-regression showed no significant associations of treatment effects with any of the potential predictors. We also found no overall effect of vitamin supplementation on measures of depression. Further, only one study reported effects on idiopathic fatigue, and therefore, no analysis was possible. Vitamin B12 supplementation is likely ineffective for improving cognitive function and depressive symptoms in patients without advanced neurological disorders.
Introduction:
The aged brain frequently exhibits multiple pathologies, rather than a single hallmark pathology (pure pathology [PurP]), ranging from low/intermediate levels of additional pathology (LowP) to mixed severe pathology (mixed SevP). We investigated the frequency of PurP, LowP, and mixed SevP, and the impact of additional LowP on cognition.
Methods:
Data came from 670 cases from the Brains for Dementia research program. Cases were categorized into PurP, mixed SevP, or a main disease with additional LowP; 508 cases had a clinical dementia rating.
Results:
69.9% of cases had LowP, 22.7% had PurP, and 7.5% had mixed SevP. Additional LowP increased the likelihood of having mild dementia versus mild cognitive impairment (MCI) by almost 20-fold (odds ratio = 19.5).
Discussion:
Most aged individuals have multiple brain pathologies. The presence of one additional LowP can significantly worsen cognitive decline, increasing the risk of transitioning from MCI to dementia 20-fold. Multimorbidity should be considered in dementia research and clinical studies.
Objective
To evaluate trials of drugs that target amyloid to determine whether reductions in amyloid levels are likely to improve cognition.
Design
Instrumental variable meta-analysis.
Setting
14 randomized controlled trials of drugs for the prevention or treatment of Alzheimer’s disease that targeted an amyloid mechanism, identified from ClinicalTrials.gov.
Population
Adults 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 measures
Analyses 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.
Results
Pooled 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.
Conclusions
Pooled evidence from available trials reporting both reduction in amyloid levels and change in cognition suggests that amyloid reduction strategies do not substantially improve cognition.
Introduction:
Herpesviruses, including Herpes simplex virus type 1 (HSV1) and varicella zoster-virus (VZV), have been implicated in Alzheimer's disease (AD) development. Likewise, antiviral treatment has been suggested to protect against dementia development in herpes-infected individuals.
Methods:
The study enrolled 265,172 subjects aged ≥ 50 years, with diagnoses of VZV or HSV, or prescribed antiviral drugs between 31 December 2005 and 31 December 2017. Controls were matched in a 1:1 ratio by sex and birth year.
Results:
Antiviral treatment was associated with decreased risk of dementia (adjusted hazard ratio [HR] 0.89, 95% confidence interval [CI] 0.86 to 0.92), while herpes infection without antiviral drugs increased the risk of dementia (adjusted HR 1.50, 95% CI 1.29 to 1.74).
Discussion:
Antiviral treatment was associated with a reduced long-term risk of dementia among individuals with overt signs of herpes infection. This is consistent with earlier findings indicating that herpesviruses are involved in the pathogenesis of AD.
Background: This study aims to examine if risk of dementia differs between adult- and late-onset depression.
Methods: 16,608 community-living dementia-free older adults were followed for 6 years to the outcome of incident dementia. Depression was diagnosed according to international diagnostic guidelines. Depression in adulthood or late life was categorized using age 65 as cutoff. Hazard ratio for dementia was estimated using Cox regression analysis.
Results: People with depression in adulthood only did not have higher dementia incidence, suggesting those in remission from adult-onset depression are not at greater risk of dementia. Conversely, having depression in both adulthood and late life was associated with higher dementia risk, and improvement in depression in late life was associated with lower risk, suggesting persistent or recurrent lifetime depression is a risk factor for dementia. Those with depression in late life only were not associated with higher dementia risk after controlling for the longitudinal changes in depressive symptoms, consistent with late-onset depression being a prodrome of dementia.
Limitations: Reverse causation is a potential limitation. This was minimized by careful ascertainment of depression and dementia cases, exclusion of individuals with suspected dementia at baseline and those who developed dementia within 3 years after baseline, and controlling for various important confounders.
Conclusions: Risk of incident dementia varies with presence and resolution of depression at different ages. Further studies are needed to test whether treating adult-onset depression may prevent dementia. Older adults with a history of depression present for an extended time should be monitored for cognitive decline.
Intervening on modifiable risk factors to prevent dementia is of key importance since progress-modifying treatments are not available. Education is inversely associated with dementia risk, but causality and mechanistic pathways remain unclear. We aimed to examine causality of this relationship in Sweden using a compulsory schooling reform that extended education by 1 year for 70 percent of the population as a natural experiment. The reform introduced substantial exogenous variation in education unrelated to pupils’ characteristics. We followed 18 birth cohorts (n=1,341,842) from 1985 to 2016 (until 79-96 years) for dementia diagnosis in the National Inpatient and Cause of Death Registers and estimated Cox survival models with stratified baseline hazards at the school-district level, chronological age as the time scale, and cohort indicators. Analyses indicated very small or negligible causal effects of education on dementia risk (main HR = 1.01; 95% CI: 0.98, 1.04). Multiple sensitivity checks considering only compliers, pre-post design, differences in healthcare-seeking behavior, and impact of exposure misclassification left the results essentially unaltered. The reform had limited effects on further adult socio-economic outcomes, such as income. Our findings suggest that without mediation through adult socioeconomic position, education cannot be uncritically considered as a modifiable risk factor for dementia.
Importance
Observational studies consistently report inverse associations between cancer and Alzheimer disease (AD). Shared inverse etiological mechanisms might explain this phenomenon, but a systematic evaluation of methodological biases in existing studies is needed.
Objectives
To systematically review and meta-analyze evidence on the association between cancer and subsequent AD, systematically identify potential methodological biases in studies, and estimate the influence of these biases on the estimated pooled association between cancer and AD.
Data Sources
All-language publications were identified from PubMed, Embase, and PsycINFO databases through September 2, 2020.
Study Selection
Longitudinal cohort studies and case-control studies on the risk of AD in older adults with a history of any cancer type, prostate cancer, breast cancer, colorectal cancer, or nonmelanoma skin cancer, relative to those with no cancer history.
Data Extraction and Synthesis
Two reviewers independently abstracted the data and evaluated study biases related to confounding, diagnostic bias, competing risks, or survival bias. Random-effects meta-analysis was used to provide pooled estimates of the association between cancer and AD. Metaregressions were used to evaluate whether the observed pooled estimate could be attributable to each bias. The study was designed and conducted according to the Preferring Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline.
Main Outcomes and Measures
Incidence, hazard, or odds ratios for AD comparing older adults with vs without a previous cancer diagnosis.
Results
In total, 19 cohort studies and 3 case-control studies of the associations between any cancer type (n = 13), prostate cancer (n = 5), breast cancer (n = 1), and nonmelanoma skin cancer (n = 3) with AD were identified, representing 9 630 435 individuals. In all studies combined, cancer was associated with decreased AD incidence (cohort studies: random-effects hazard ratio, 0.89; 95% CI, 0.79-1.00; case-control studies: random-effects odds ratio, 0.75; 95% CI, 0.61-0.93). Studies with insufficient or inappropriate confounder control or greater likelihood of AD diagnostic bias had mean hazard ratios closer to the null value, indicating that these biases could not explain the observed inverse association. Competing risks bias was rare. Studies with greater likelihood of survival bias had mean hazard ratios farther from the null value.
Conclusions and Relevance
The weak inverse association between cancer and AD may reflect shared inverse etiological mechanisms or survival bias but is not likely attributable to diagnostic bias, competing risks bias, or insufficient or inappropriate control for potential confounding factors.
Objectives
To examine the association between cognitive stimulating activities (CSA) in later life (internet/email use, employment, volunteering, evening classes, social club membership and newspaper reading) and risk of cognitive impairment or dementia using marginal structural models to account for time-varying confounding affected by prior exposure.
Methods
Data were used from the English Longitudinal Study of Ageing waves 1 (2002) to 7 (2014), a nationally representative sample of adults in England aged ≥50. Self-reported participation in CSAs were measured as binary exposures from waves 2 (2004) to 6 (2012), with final sample sizes between n=3937 and n=2530 for different CSAs. Baseline exposure and covariates were used to create inverse probability of treatment and censoring weights (IPTCW). IPTCW repeated measures Poisson and linear regression were used to estimate each CSAs effect on risk of probable cognitive impairment or dementia at wave 7 (defined as a score of ≤11/27 on a modified telephone interview for cognitive status (TICS-27)). Results were compared to standard regression adjustment.
Results
Internet use at any wave (Risk ratios between 0.62 and 0.69) and volunteering in waves 3 to 6 (RRs between 0.516 and 0.633) were associated with reduced risk of cognitive impairment in IPTCW models. Standard estimates were similar for both internet use and volunteering.
Newspaper reading (RR 95% Confidence interval 0.74-0.99) and social club membership (RR 95% CI 0.54-0.86) at wave 6 were significantly associated with risk of cognitive impairment in standard models, but not in the IPTCW models (RR 95% CI 0.82-1.11 and 0.60-1.08 respectively). Employment and evening classes were not associated with cognitive impairment in either model.
Conclusions
We found that volunteering and internet use were associated with reduced risk of cognitive impairment. Associations between newspaper reading or social club membership and cognitive impairment may be due to time-varying confounding affected by prior exposure.
Introduction:
We hypothesized that frequent experiences of racism among African American women would adversely affect subjective cognitive function (SCF), based on the established association of psychological stress with memory decline.
Methods:
We used multinomial logistic regression to quantify the association between experiences of racism and SCF, based on six questions, among 17,320 participants in the prospective Black Women's Health Study.
Results:
The multivariable odds ratio (OR, 95% confidence interval [CI]) for poor compared to good SCF among women at the highest versus the lowest level of daily racism (eg, poorer service in stores) was 2.75 (2.34 to 3.23); for the same comparison among women at the highest level of institutional racism (eg, discriminated against in housing) relative to the lowest, the OR was 2.66 (2.24 to 3.15). The associations were mediated, in part, by depression and insomnia.
Discussion:
Experiences of racism, a highly prevalent psychosocial stressor among African Americans, were associated with lower SCF.
Background
Evidence on preventing Alzheimer’s disease (AD) is challenging to interpret due to varying study designs with heterogeneous endpoints and credibility. We completed a systematic review and meta-analysis of current evidence with prospective designs to propose evidence-based suggestions on AD prevention.
Methods
Electronic databases and relevant websites were searched from inception to 1 March 2019. Both observational prospective studies (OPSs) and randomised controlled trials (RCTs) were included. The multivariable-adjusted effect estimates were pooled by random-effects models, with credibility assessment according to its risk of bias, inconsistency and imprecision. Levels of evidence and classes of suggestions were summarised.
Results
A total of 44 676 reports were identified, and 243 OPSs and 153 RCTs were eligible for analysis after exclusion based on pre-decided criteria, from which 104 modifiable factors and 11 interventions were included in the meta-analyses. Twenty-one suggestions are proposed based on the consolidated evidence, with Class I suggestions targeting 19 factors: 10 with Level A strong evidence (education, cognitive activity, high body mass index in latelife, hyperhomocysteinaemia, depression, stress, diabetes, head trauma, hypertension in midlife and orthostatic hypotension) and 9 with Level B weaker evidence (obesity in midlife, weight loss in late life, physical exercise, smoking, sleep, cerebrovascular disease, frailty, atrial fibrillation and vitamin C). In contrast, two interventions are not recommended: oestrogen replacement therapy (Level A2) and acetylcholinesterase inhibitors (Level B).
Interpretation
Evidence-based suggestions are proposed, offering clinicians and stakeholders current guidance for the prevention of AD.
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 in seven 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 non-overlapping 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% CI: 7%-19%), consistently across studies, and somewhat more pronouncedly in men than in women (24% [95% CI 14%-32%] versus 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.
Importance
Black individuals are more likely than white individuals to develop dementia. Whether higher blood pressure (BP) levels in black individuals explain differences between black and white individuals in dementia risk is uncertain.
Objective
To determine whether cumulative BP levels explain racial differences in cognitive decline.
Design, Setting, and Participants
Individual participant data from 5 cohorts (January 1971 to December 2017) were pooled from the Atherosclerosis Risk in Communities Study, Coronary Artery Risk Development in Young Adults Study, Cardiovascular Health Study, Framingham Offspring Study, and Northern Manhattan Study. Outcomes were standardized as t scores (mean [SD], 50 [10]); a 1-point difference represented a 0.1-SD difference in cognition. The median (interquartile range) follow-up was 12.4 (5.9-21.0) years. Analysis began September 2018.
Main Outcomes and Measures
The primary outcome was change in global cognition, and secondary outcomes were change in memory and executive function.
Exposures
Race (black vs white).
Results
Among 34 349 participants, 19 378 individuals who were free of stroke and dementia and had longitudinal BP, cognitive, and covariate data were included in the analysis. The mean (SD) age at first cognitive assessment was 59.8 (10.4) years and ranged from 5 to 95 years. Of 19 378 individuals, 10 724 (55.3%) were female and 15 526 (80.1%) were white. Compared with white individuals, black individuals had significantly faster declines in global cognition (−0.03 points per year faster [95% CI, −0.05 to −0.01]; P = .004) and memory (−0.08 points per year faster [95% CI, −0.11 to −0.06]; P < .001) but significantly slower declines in executive function (0.09 points per year slower [95% CI, 0.08-0.10]; P < .001). Time-dependent cumulative mean systolic BP level was associated with significantly faster declines in global cognition (−0.018 points per year faster per each 10–mm Hg increase [95% CI, −0.023 to −0.014]; P < .001), memory (−0.028 points per year faster per each 10–mm Hg increase [95% CI, −0.035 to −0.021]; P < .001), and executive function (−0.01 points per year faster per each 10–mm Hg increase [95% CI, −0.014 to −0.007]; P < .001). After adjusting for cumulative mean systolic BP, differences between black and white individuals in cognitive slopes were attenuated for global cognition (−0.01 points per year [95% CI, −0.03 to 0.01]; P = .56) and memory (−0.06 points per year [95% CI, −0.08 to −0.03]; P < .001) but not executive function (0.10 points per year [95% CI, 0.09-0.11]; P < .001).
Conclusions and Relevance
These results suggest that black individuals’ higher cumulative BP levels may contribute to racial differences in later-life cognitive decline.
Introduction:
Machine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer Disease (AD). Here we set out to test the performance of metabolites in blood to categorize AD when compared to CSF biomarkers.
Methods:
This study analyzed samples from 242 cognitively normal (CN) people and 115 with AD-type dementia utilizing plasma metabolites (n = 883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV).
Results:
On the test data, DL produced the AUC of 0.85 (0.80-0.89), XGBoost produced 0.88 (0.86-0.89) and RF produced 0.85 (0.83-0.87). By comparison, CSF measures of amyloid, p-tau and t-tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively.
Discussion:
This study showed that plasma metabolites have the potential to match the AUC of well-established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders.
Background:
Evidence concerning the potential repurposing of antihypertensives for Alzheimer's disease prevention is inconclusive. We used Mendelian randomization, which can be more robust to confounding by indication and patient characteristics, to investigate the effects of lowering systolic blood pressure, via the protein targets of different antihypertensive drug classes, on Alzheimer's disease.
Methods:
We used summary statistics from genome-wide association studies of systolic blood pressure and Alzheimer's disease in a two-sample Mendelian randomization analysis. We identified single-nucleotide polymorphisms (SNPs) that mimic the action of antihypertensive protein targets and estimated the effect of lowering systolic blood pressure on Alzheimer's disease in three ways: (i) combining the protein targets of antihypertensive drug classes, (ii) combining all protein targets and (iii) without consideration of the protein targets.
Results:
There was limited evidence that lowering systolic blood pressure, via the protein targets of antihypertensive drug classes, affected Alzheimer's disease risk. For example, the protein targets of calcium channel blockers had an odds ratio (OR) per 10 mmHg lower systolic blood pressure of 1.53 [95% confidence interval (CI): 0.94 to 2.49; p = 0.09; SNPs = 17]. We also found limited evidence for an effect when combining all protein targets (OR per 10 mmHg lower systolic blood pressure: 1.14; 95% CI: 0.83 to 1.56; p = 0.41; SNPs = 59) and without consideration of the protein targets (OR per 10 mmHg lower systolic blood pressure: 1.04; 95% CI: 0.95 to 1.13; p = 0.45; SNPs = 153).
Conclusions:
Mendelian randomization suggests that lowering systolic blood pressure via the protein targets of antihypertensive drugs is unlikely to affect the risk of developing Alzheimer's disease. Consequently, if specific antihypertensive drug classes do affect the risk of Alzheimer's disease, they may not do so via systolic blood pressure.
Background:
Short and long sleep duration have been linked with poorer cognitive outcomes, but it remains unclear whether these associations are causal.
Methods:
We conducted the first Mendelian randomization (MR) study with 77 single-nucleotide polymorphisms (SNPs) for sleep duration using individual-participant data from the UK Biobank cohort (N = 395 803) and summary statistics from the International Genomics of Alzheimer's Project (N cases/controls = 17 008/37 154) to investigate the potential impact of sleep duration on cognitive outcomes.
Results:
Linear MR suggested that each additional hour/day of sleep was associated with 1% [95% confidence interval (CI) = 0-2%; P = 0.008] slower reaction time and 3% more errors in visual-memory test (95% CI = 0-6%; P = 0.05). There was little evidence to support associations of increased sleep duration with decline in visual memory [odds ratio (OR) per additional hour/day of sleep = 1.10 (95% CI = 0.76-1.57); P = 0.62], decline in reaction time [OR = 1.28 (95% CI = 0.49-3.35); P = 0.61], all-cause dementia [OR = 1.19 (95% CI = 0.65-2.19); P = 0.57] or Alzheimer's disease risk [OR = 0.89 (95% CI = 0.67-1.18); P = 0.41]. Non-linear MR suggested that both short and long sleep duration were associated with poorer visual memory (P for non-linearity = 3.44e-9) and reaction time (P for non-linearity = 6.66e-16).
Conclusions:
Linear increase in sleep duration has a small negative effect on reaction time and visual memory, but the true association might be non-linear, with evidence of associations for both short and long sleep duration. These findings suggest that sleep duration may represent a potential causal pathway for cognition.
Introduction:
We estimated the age-specific duration of the preclinical, prodromal, and dementia stages of Alzheimer's disease (AD) and the influence of sex, setting, apolipoprotein E (APOE) genotype, and cerebrospinal fluid tau on disease duration.
Methods:
We performed multistate modeling in a combined sample of 6 cohorts (n = 3268) with death as the end stage and estimated the preclinical, prodromal, and dementia stage duration.
Results:
The overall AD duration varied between 24 years (age 60) and 15 years (age 80). For individuals presenting with preclinical AD, age 70, the estimated preclinical AD duration was 10 years, prodromal AD 4 years, and dementia 6 years. Male sex, clinical setting, APOE ε4 allele carriership, and abnormal cerebrospinal fluid tau were associated with a shorter duration, and these effects depended on disease stage.
Discussion:
Estimates of AD disease duration become more accurate if age, sex, setting, APOE, and cerebrospinal fluid tau are taken into account. This will be relevant for clinical practice and trial design.
Background:
Nine potentially modifiable risk factors (less childhood education, midlife hearing loss, hypertension, and obesity, and later-life smoking, depression, physical inactivity, social isolation, and diabetes) account for 35% of worldwide dementia, but most data to calculate these risk factors come from high-income countries only. We aimed to calculate population attributable fractions (PAFs) for dementia in selected low-income and middle-income countries (LMICs) to identify potential dementia prevention targets in these countries.
Methods:
The study was an analysis of cross-sectional data obtained from the 10/66 Dementia Research surveys of representative populations in India, China, and six Latin America countries (Cuba, Dominican Republic, Mexico, Peru, Puerto Rico, and Venezuela), which used identical risk factor ascertainment methods in each country. Between 2004 and 2006 (and between 2007 and 2010 for Puerto Rico), all residents aged 65 years and older in predefined catchment areas were invited to participate in the survey. We used risk factor prevalence estimates from this 10/66 survey data, and relative risk estimates from previous meta-analyses, to calculate PAFs for each risk factor. To account for individuals having overlapping risk factors, we adjusted PAF for communality between risk factors, and used these values to calculate overall weighted PAFs for India, China, and the Latin American sample.
Findings:
The overall weighted PAF for potentially modifiable risk factors for dementia was 39·5% (95% CI 37·5-41·6) in China (n=2162 participants), 41·2% (39·1-43·4) in India (n=2004), and 55·8% (54·9-56·7) in our Latin American sample (n=12 865). Five dementia risk factors were more prevalent in these LMICs than worldwide estimates, leading to higher PAFs for dementia: less childhood education (weighted PAF of 10·8% in China, 13·6% in India, and 10·9% in Latin America vs 7·5% worldwide), smoking (14·7%, 6·4%, and 5·7%, respectively, vs 5·5% worldwide), hypertension (6·4%, 4·0%, and 9·3%, vs 2·0%), obesity (5·6%, 2·9%, and 7·9%, vs 0·8%), and diabetes (1·6%, 1·7%, and 3·2%, vs 1·2%).
Interpretation:
The dementia prevention potential in India, China, and this sample of Latin American countries is large, and greater than in high-income countries. Less education in early life, hypertension, hearing loss, obesity, and physical inactivity have particularly high PAFs and could be initial targets for dementia prevention strategies.
Funding:
No funding.
Background
Cognitive complaints are common in cancer survivors. We aimed to assess cognitive complaints in cancer survivors and the associated factors using a large web–based survey.
Methods
This online survey was proposed to cancer survivors. Participants completed several questions on cognitive complaints experience, expectations for support of cognitive difficulties, preexisting knowledge about chemotherapy–associated cognitive problems and demographic and medical variables. We used multivariable logistic regression models to estimate Odds Ratios and 95% confidence intervals to estimate associations.
Results
Among 1610 eligible participants (median age 52 [21‐84]), >85% (n = 1393) were breast cancer survivors. Median postcancer treatment time (excluding hormone therapy) was 2.83 years [0.8‐33]. Seventy five percent of the participants (n = 1214) reported cognitive complaints related to cancer treatments. Cognitive difficulties had an impact on work resumption for 76% of the participants (n = 754/982). Most cancer survivors would like to receive support (75%, n = 909) and especially cognitive training (72%, n = 658). Chemotherapy was strongly associated with cognitive complaints (multivariable OR = 3.67, 95% CI: 2.80‐4.82). Self–reported sleep difficulties (ORoften vs. never = 2.84, 95% CI: 1.80‐4.47), preexisting knowledge about chemotherapy–associated cognitive problems (ORNo vs. Yes = 1.69, 95% CI: 1‐29‐2.22) and age (OR21‐64 vs. ≥65 = 0.37, 95% CI: 0.23‐0.58) were also associated with cancer–related cognitive complaints.
Conclusions
According to this large web–based survey including mainly breast cancer survivors, cognitive complaints were reported by three quarters of participants, which reinforces that cognitive difficulties are a major issue in cancer survivors. Chemotherapy, self–reported sleep difficulties and preexisting knowledge about chemotherapy–associated cognitive problems were strongly associated with cancer–related cognitive complaints. Most cancer survivors wished to receive support and especially cognitive training.
Risk for late-onset Alzheimer’s disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer’s or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer’s disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10⁻⁷), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.
Dysfunction in 24-h circadian rhythms is a common occurrence in ageing adults; however, circadian rhythm disruptions are more severe in people with age-related neurodegenerative diseases, including Alzheimer's disease and related dementias, and Parkinson's disease. Manifestations of circadian rhythm disruptions differ according to the type and severity of neurodegenerative disease and, for some patients, occur before the onset of typical clinical symptoms of neurodegeneration. Evidence from preliminary studies suggest that circadian rhythm disruptions, in addition to being a symptom of neurodegeneration, might also be a potential risk factor for developing Alzheimer's disease and related dementias, and Parkinson's disease, although large, longitudinal studies are needed to confirm this relationship. The mechanistic link between circadian rhythms and neurodegeneration is still not fully understood, although proposed underlying pathways include alterations of protein homoeostasis and immune and inflammatory function. While preliminary clinical studies are promising, more studies of circadian rhythm disruptions and its mechanisms are required. Furthermore, clinical trials are needed to determine whether circadian interventions could prevent or delay the onset of neurodegenerative diseases.
Dysregulation of the gut microbiome is associated with several life-threatening conditions and thus might represent a useful target for the prevention of dementia. However, the relationship between the gut microbial population and dementia has not yet been fully clarified. We recruited outpatients visiting our memory clinic to participate in this study. Information on patient demographics, risk factors, and activities of daily living was collected, and cognitive function was assessed using neuropsychological tests and brain magnetic resonance imaging scans. Faecal samples were obtained, and the gut microbiome was assessed by terminal restriction fragment length polymorphism (T-RFLP) analysis, one of the most well-established and reliable 16S ribosomal RNA-based methods for classifying gut microbiota. Patients were divided into two groups, demented and non-demented. Multivariable logistic regression models were used to identify the variables independently associated with dementia. The T-RFLP analysis revealed differences in the composition of the gut microbiome: the number of Bacteroides (enterotype I) was lower and the number of ‘other’ bacteria (enterotype III) was higher in demented than non-demented patients. Multivariable analyses showed that the populations of enterotype I and enterotype III bacteria were strongly associated with dementia, independent of the traditional dementia biomarkers. Further studies of the metabolites of gut microbes are needed to determine the mechanism underlying this association.
Importance:
There are currently no proven treatments to reduce the risk of mild cognitive impairment and dementia.
Objective:
To evaluate the effect of intensive blood pressure control on risk of dementia.
Design, setting, and participants:
Randomized clinical trial conducted at 102 sites in the United States and Puerto Rico among adults aged 50 years or older with hypertension but without diabetes or history of stroke. Randomization began on November 8, 2010. The trial was stopped early for benefit on its primary outcome (a composite of cardiovascular events) and all-cause mortality on August 20, 2015. The final date for follow-up of cognitive outcomes was July 22, 2018.
Interventions:
Participants were randomized to a systolic blood pressure goal of either less than 120 mm Hg (intensive treatment group; n = 4678) or less than 140 mm Hg (standard treatment group; n = 4683).
Main outcomes and measures:
The primary cognitive outcome was occurrence of adjudicated probable dementia. Secondary cognitive outcomes included adjudicated mild cognitive impairment and a composite outcome of mild cognitive impairment or probable dementia.
Results:
Among 9361 randomized participants (mean age, 67.9 years; 3332 women [35.6%]), 8563 (91.5%) completed at least 1 follow-up cognitive assessment. The median intervention period was 3.34 years. During a total median follow-up of 5.11 years, adjudicated probable dementia occurred in 149 participants in the intensive treatment group vs 176 in the standard treatment group (7.2 vs 8.6 cases per 1000 person-years; hazard ratio [HR], 0.83; 95% CI, 0.67-1.04). Intensive BP control significantly reduced the risk of mild cognitive impairment (14.6 vs 18.3 cases per 1000 person-years; HR, 0.81; 95% CI, 0.69-0.95) and the combined rate of mild cognitive impairment or probable dementia (20.2 vs 24.1 cases per 1000 person-years; HR, 0.85; 95% CI, 0.74-0.97).
Conclusions and relevance:
Among ambulatory adults with hypertension, treating to a systolic blood pressure goal of less than 120 mm Hg compared with a goal of less than 140 mm Hg did not result in a significant reduction in the risk of probable dementia. Because of early study termination and fewer than expected cases of dementia, the study may have been underpowered for this end point.
Trial registration:
ClinicalTrials.gov Identifier: NCT01206062.
Background
Cholinesterase inhibitors and memantine have been approved for management of Alzheimer’s disease (AD), but there has been no consensus about the choice of various types and doses of drugs at different stages. Hence, we compared and ranked the efficacy and tolerability of these available drugs.
Methods
We searched PubMed, the Cochrane Central Register of Controlled Trials, and Embase for randomized controlled trials (RCTs) published from database inception to July 21, 2017. The primary outcomes were the mean overall changes in cognitive function and responders who had any adverse events. We conducted a random-effects network meta-analysis.
Results
Forty-one RCTs were included in this study. Compared with placebo, galantamine 32 mg daily (standardized mean difference – 0.51, 95% credible interval – 0.67 to − 0.35), galantamine 24 mg daily (− 0.50, − 0.61 to − 0.40), and donepezil 10 mg daily (− 0.40, − 0.51 to − 0.29) were probably the most effective agents on cognition for mild to moderate AD, and memantine 20 mg combined with donepezil 10 mg (0.76, 0.39 to 1.11) was recommended for moderate to severe patients. Memantine showed the best profile of acceptability. Rivastigmine transdermal 15-cm² patch was the best optional treatment both in function and global changes. None of the medicines was likely to improve neuropsychiatric symptoms through this analysis.
Conclusions
Pharmacological interventions have beneficial effects on cognition, function, and global changes, but not on neuropsychiatric symptoms, through current network meta-analysis. The choice of drugs may mainly depend on the disease severity and clinical symptoms.
Electronic supplementary material
The online version of this article (10.1186/s13195-018-0457-9) contains supplementary material, which is available to authorized users.
Background: The number of individuals living with dementia is increasing, negatively affecting families, communities, and healthcare systems around the world. A successful response to these challenges requires an accurate understanding of the dementia disease burden. We aimed to present the first detailed analysis of the global prevalence, mortality, and overall burden of dementia as captured by the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016 and highlight the most important messages for clinicians and neurologists. Methods: GBD 2016 obtained data on dementia from vital registration systems, published scientific literature and surveys, and data from health-service encounters on deaths, excess mortality, prevalence, and incidence from 195 countries and territories from 1990 to 2016, through systematic review and additional data-seeking efforts. To correct for differences in cause of death coding across time and locations, we modeled mortality due to dementia using prevalence data and estimates of excess mortality derived from countries that were most likely to code deaths to dementia relative to prevalence. Data were analyzed by standardized methods to estimate deaths, prevalence, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs; computed as the sum of YLLs and YLDs), and the fractions of these metrics that were attributable to four risk factors that met GBD criteria for assessment (high body-mass index [BMI], high fasting plasma glucose, smoking, and a diet high in sugar-sweetened beverages). Findings: In 2016, the global number of individuals who lived with dementia was 43·8 million (95% uncertainty interval [UI] 37·8-51·0), increased from 20.2 million (17·4-23·5) in 1990. This increase of 117% (95% UI 114-121) contrasted with a minor increase in age-standardised prevalence of 1·7% (1·0-2·4), from 701 cases (95% UI 602-815) per 100 000 population in 1990 to 712 cases (614-828) per 100 000 population in 2016. More women than men had dementia in 2016 (27·0 million, 95% UI 23·3-31·4, vs 16.8 million, 14.4-19.6), and dementia was the fifth leading cause of death globally, accounting for 2·4 million (95% UI 2·1-2·8) deaths. Overall, 28·8 million (95% UI 24·5-34·0) DALYs were attributed to dementia; 6·4 million (95% UI 3·4-10·5) of these could be attributed to the modifiable GBD risk factors of high BMI, high fasting plasma glucose, smoking, and a high intake of sugar-sweetened beverages. Interpretation: The global number of people living with dementia more than doubled from 1990 to 2016, mainly due to increases in population aging and growth. Although differences in coding for causes of death and the heterogeneity in case-ascertainment methods constitute major challenges to the estimation of the burden of dementia, future analyses should improve on the methods for the correction of these biases. Until breakthroughs are made in prevention or curative treatment, dementia will constitute an increasing challenge to healthcare systems worldwide. Funding: Bill & Melinda Gates Foundation.
This article describes the protocol for the Systematic Multi-domain Alzheimer's Risk Reduction Trial (SMARRT), a single-blind randomized pilot trial to test a personalized, pragmatic, multi-domain Alzheimer's disease (AD) risk reduction intervention in a US integrated healthcare delivery system. Study participants will be 200 higher-risk older adults (age 70-89 years with subjective cognitive complaints, low normal performance on cognitive screen, and ≥ two modifiable risk factors targeted by our intervention) who will be recruited from selected primary care clinics of Kaiser Permanente Washington, oversampling people with non-white race or Hispanic ethnicity. Study participants will be randomly assigned to a two-year Alzheimer's risk reduction intervention (SMARRT) or a Health Education (HE) control. Randomization will be stratified by clinic, race/ethnicity (non-Hispanic white versus non-white or Hispanic), and age (70-79, 80-89). Participants randomized to the SMARRT group will work with a behavioral coach and nurse to develop a personalized plan related to their risk factors (poorly controlled hypertension, diabetes with evidence of hyper or hypoglycemia, depressive symptoms, poor sleep quality, contraindicated medications, physical inactivity, low cognitive stimulation, social isolation, poor diet, smoking). Participants in the HE control group will be mailed general health education information about these risk factors for AD. The primary outcome is two-year cognitive change on a cognitive test composite score. Secondary outcomes include: 1) improvement in targeted risk factors, 2) individual cognitive domain composite scores, 3) physical performance, 4) functional ability, 5) quality of life, and 6) incidence of mild cognitive impairment, AD, and dementia. Primary and secondary outcomes will be assessed in both groups at baseline and 6, 12, 18, and 24 months.
Background:
Imaging agents capable of quantifying the brain's tau aggregates will allow a more precise staging of Alzheimer's disease (AD). The aim of the present study was to examine the in vitro properties as well as the in vivo kinetics, using gold standard methods, of the novel positron emission tomography (PET) tau imaging agent [18F]MK-6240.
Methods:
In vitro properties of [18F]MK-6240 were estimated with autoradiography in postmortem brain tissues of 14 subjects (seven AD patients and seven age-matched controls). In vivo quantification of [18F]MK-6240 binding was performed in 16 subjects (four AD patients, three mild cognitive impairment patients, six healthy elderly individuals, and three healthy young individuals) who underwent 180-min dynamic scans; six subjects had arterial sampling for metabolite correction. Simplified approaches for [18F]MK-6240 quantification were validated using full kinetic modeling with metabolite-corrected arterial input function. All participants also underwent amyloid-PET and structural magnetic resonance imaging.
Results:
In vitro [18F]MK-6240 uptake was higher in AD patients than in age-matched controls in brain regions expected to contain tangles such as the hippocampus, whereas no difference was found in the cerebellar gray matter. In vivo, [18F]MK-6240 displayed favorable kinetics with rapid brain delivery and washout. The cerebellar gray matter had low binding across individuals, showing potential for use as a reference region. A reversible two-tissue compartment model well described the time-activity curves across individuals and brain regions. Distribution volume ratios using the plasma input and standardized uptake value ratios (SUVRs) calculated after the binding approached equilibrium (90 min) were correlated and higher in mild cognitive impairment or AD dementia patients than in controls. Reliability analysis revealed robust SUVRs calculated from 90 to 110 min, while earlier time points provided inaccurate estimates.
Conclusions:
This evaluation shows an [18F]MK-6240 distribution in concordance with postmortem studies and that simplified quantitative approaches such as the SUVR offer valid estimates of neurofibrillary tangle load 90 min post injection. [18F]MK-6240 is a promising tau tracer with the potential to be applied in the disease diagnosis and assessment of therapeutic interventions.
Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel’s laws of inheritance and instrumental variable estimation methods, which enable the inference of causal effects in the presence of unobserved confounding. In this Primer, we outline the principles of MR, the instrumental variable conditions underlying MR estimation and some of the methods used for estimation. We go on to discuss how the assumptions underlying an MR study can be assessed and describe methods of estimation that are robust to certain violations of these assumptions. We give examples of a range of studies in which MR has been applied, the limitations of current methods of analysis and the outlook for MR in the future. The differences between the assumptions required for MR analysis and other forms of epidemiological studies means that MR can be used as part of a triangulation across multiple sources of evidence for causal inference. Mendelian randomization is a technique for using genetic variation to examine the causal effect of a modifiable exposure on an outcome such as disease status. This Primer by Sanderson et al. explains the concepts of and the conditions required for Mendelian randomization analysis, describes key examples of its application and looks towards applying the technique to growing genomic datasets.
Background:
Identification of factors that may help to preserve cognitive function in late life could elucidate mechanisms and facilitate interventions to improve the lives of millions of people. However, the large number of potential factors associated with cognitive function poses an analytical challenge.
Objective:
We used data from the longitudinal Women's Health Initiative Memory Study (WHIMS) and machine learning to investigate 50 demographic, biomedical, behavioral, social, and psychological predictors of preserved cognitive function in later life.
Methods:
Participants in WHIMS and two consecutive follow up studies who were at least 80 years old and had at least one cognitive assessment following their 80th birthday were classified as cognitively preserved. Preserved cognitive function was defined as having a score ≥39 on the most recent administration of the modified Telephone Interview for Cognitive Status (TICSm) and a mean score across all assessments ≥39. Cognitively impaired participants were those adjudicated by experts to have probable dementia or at least two adjudications of mild cognitive impairment within the 14 years of follow-up and a last TICSm score < 31. Random Forests was used to rank the predictors of preserved cognitive function.
Results:
Discrimination between groups based on area under the curve was 0.80 (95%-CI-0.76-0.85). Women with preserved cognitive function were younger, better educated, and less forgetful, less depressed, and more optimistic at study enrollment. They also reported better physical function and less sleep disturbance, and had lower systolic blood pressure, hemoglobin, and blood glucose levels.
Conclusion:
The predictors of preserved cognitive function include demographic, psychological, physical, metabolic, and vascular factors suggesting a complex mix of potential contributors.
The US Food and Drug Administration (FDA) recently provided accelerated approval for aducanumab to treat Alzheimer disease (AD). The decision was controversial within and outside the FDA because of inadequate evidence of medication efficacy. The Peripheral and Central Nervous System Drugs Advisory Committee voted against recommendation of aducanumab and several committee members resigned after approval. FDA approval was based on trials that were not inclusive of the people who bear a disproportionate burden of disease.¹ Only 0.6% (ie, 19 individuals) of participants identified as Black, 3% as Hispanic, 0.03% (1 person) as American Indian or Alaska Native, and 0.03% as Native Hawaiian or Pacific Islander. Of the 9% identified as Asian, 94% were recruited in Asia.² Older Black adults are estimated to have AD incidence up to double the rates in older White people. Despite this, Biogen reported that only 6 Black people were randomized to the treatment dose approved by the FDA.
In June 2021, the US Food and Drug Administration (FDA) granted accelerated approval for aducanumab to treat patients with mild cognitive impairment (MCI) or mild dementia due to Alzheimer disease (AD), despite limited evidence of clinical benefit. The 2 phase 3 clinical trials of aducanumab, EMERGE and ENGAGE, were stopped prematurely based on prespecified futility thresholds.¹ Both trials also showed an increased risk of adverse events with aducanumab, including microhemorrhages and vasogenic brain edema, headache, and possibly falls.¹ Though both trials excluded patients based on age, certain chronic diseases, and use of antiplatelet agents and anticoagulants, FDA approval was granted without contraindications or precautions for these unstudied patient populations. We evaluated whether patients enrolled in the trials of aducanumab were representative of patients with dementia enrolled in Medicare by estimating the proportions of Medicare beneficiaries with AD or MCI who would have been excluded from the trials.
Audio Interview
Interview with Dr. Gil Rabinovici on the FDA’s controversial approval of a new treatment for Alzheimer’s disease. (16:39)Download
Given the scientific, regulatory, and clinical implications of the accelerated FDA approval of aducanumab for Alzheimer’s disease, it’s essential to consider beta-amyloid’s suitability as a surrogate end point. Doing so casts doubt on the wisdom of the decision.
Growing evidence relates Body Mass index (BMI) to poorer health outcomes; however, results across studies associating BMI and dementia are conflicting. A total of 3632 Framingham Offspring participants aged 20 to 60 years at their second health exam (1979-1982) were included in this study with 190 cases of incident dementia identified by 2017. Cox proportional hazards regression models were performed to investigate the association of BMI at each of their 8 exams as a baseline for dementia risk, and the associations between obesity and dementia across age groups. Spline models were fitted to investigate non-linear associations between BMI and dementia. Each 1 kg/m2 increase in BMI at 40-49 years was associated with higher risk of dementia, but lower risk after 70 years. Obesity at 40-49 years was associated with higher risk of dementia. Overall, the relationship between BMI and dementia risk was heterogeneous across the adult age range. Monitoring BMI at different age may mediate risk for dementia across an individual’s lifetime.
Praise for the First Edition of Statistical Analysis with Missing Data “An important contribution to the applied statistics literature.... I give the book high marks for unifying and making accessible much of the past and current work in this important area.”—William E. Strawderman, Rutgers University “This book...provide[s] interesting real-life examples, stimulating end-of-chapter exercises, and up-to-date references. It should be on every applied statistician’s bookshelf.”—The Statistician “The book should be studied in the statistical methods department in every statistical agency.”—Journal of Official Statistics Statistical analysis of data sets with missing values is a pervasive problem for which standard methods are of limited value. The first edition of Statistical Analysis with Missing Data has been a standard reference on missing-data methods. Now, reflecting extensive developments in Bayesian methods for simulating posterior distributions, this Second Edition by two acknowledged experts on the subject offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing-data problems. Blending theory and application, authors Roderick Little and Donald Rubin review historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values. They then provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing-data mechanism and apply the theory to a wide range of important missing-data problems. The new edition now enlarges its coverage to include: Expanded coverage of Bayesian methodology, both theoretical and computational, and of multiple imputation Analysis of data with missing values where inferences are based on likelihoods derived from formal statistical models for the data-generating and missing-data mechanisms Applications of the approach in a variety of contexts including regression, factor analysis, contingency table analysis, time series, and sample survey inference Extensive references, examples, and exercises Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Statistical Analysis With Missing Data was among those chosen.
The development of the next generation therapy for Alzheimer’s disease (AD) presents a huge challenge given the number of promising treatment candidates that failed in trials, despite recent advancements in understanding of genetic, pathophysiologic and clinical characteristics of the disease. This review reflects some of the most current concepts and controversies in developing disease-modifying and new symptomatic treatments. It elaborates on recent changes in the AD research strategy for broadening drug targets, and potentials of emerging non-pharmacological treatment interventions. Established and novel biomarkers are discussed, including emerging cerebrospinal fluid and plasma biomarkers reflecting tau pathology, neuroinflammation and neurodegeneration. These fluid biomarkers together with neuroimaging findings can provide innovative objective assessments of subtle changes in brain reflecting disease progression. A particular emphasis is given to neurophysiological biomarkers which are well-suited for evaluating the brain overall neural network integrity and function. Combination of multiple biomarkers, including target engagement and outcome biomarkers will empower translational studies and facilitate successful development of effective therapies.
Background: This study aims to examine if risk of dementia differs between adult- and late-onset depression. Methods: 16,608 community-living dementia-free older adults were followed for 6 years to the outcome of incident dementia. Depression was diagnosed according to international diagnostic guidelines. Depression in adulthood or late life was categorized using age 65 as cutoff. Hazard ratio for dementia was estimated using Cox regression analysis. Results: People with depression in adulthood only did not have higher dementia incidence, suggesting those in remission from adult-onset depression are not at greater risk of dementia. Conversely, having depression in both adulthood and late life was associated with higher dementia risk, and improvement in depression in late life was associated with lower risk, suggesting persistent or recurrent lifetime depression is a risk factor for dementia. Those with depression in late life only were not associated with higher dementia risk after controlling for the longitudinal changes in depressive symptoms, consistent with late-onset depression being a prodrome of dementia. Limitations: Reverse causation is a potential limitation. This was minimized by careful ascertainment of depression and dementia cases, exclusion of individuals with suspected dementia at baseline and those who developed dementia within 3 years after baseline, and controlling for various important confounders. Conclusions: Risk of incident dementia varies with presence and resolution of depression at different ages. Further studies are needed to test whether treating adult-onset depression may prevent dementia. Older adults with a history of depression present for an extended time should be monitored for cognitive decline.
Background
Smoking starts in early adulthood and persists throughout the life course, but the association between these trajectories and midlife cognition remains unclear.Objective
Determine the association between early to midlife smoking trajectories and midlife cognition.DesignProspective cohort study.ParticipantsParticipants were 3364 adults (mean age = 50.1 ± 3.6, 56% female, 46% Black) from the Coronary Artery Risk Development in Young Adults (CARDIA) study: 1638 ever smokers and 1726 never smokers.Main MeasuresSmoking trajectories were identified in latent class analysis among 1638 ever smokers using smoking measures every 2–5 years from baseline (age 18–30 in 1985–1986) through year 25 (2010–2011). Poor cognition was based on cognitive domain scores ≥ 1 SD below the mean on tests of processing speed (Digit Symbol Substitution Test), executive function (Stroop), and memory (Rey Auditory Verbal Learning Test) at year 25.ResultsFive smoking trajectories emerged over 25 years: quitters (19%), and minimal stable (40%), moderate stable (20%), heavy stable (15%), and heavy declining smokers (5%). Heavy stable smokers showed poor cognition on all 3 domains compared to never smoking (processing speed AOR = 2.22 95% CI 1.53–3.22; executive function AOR = 1.58 95% CI 1.05–2.36; memory AOR = 1.48 95% CI 1.05–2.10). Compared to never smoking, both heavy declining (AOR = 1.95 95% CI 1.06–3.68) and moderate stable smokers (AOR = 1.56 95% CI 1.11–2.19) exhibited slower processing speed, and heavy declining smokers additionally had poor executive function. For minimal stable smokers (processing speed AOR = 1.12 95% CI 0.85–1.51; executive function AOR = 0.97 95% CI 0.71–1.31; memory AOR = 1.21 95% CI 0.94–1.55) and quitters (processing speed AOR = 0.96 95% CI 0.63–1.48; executive function AOR = 0.98 95% CI 0.63–1.52; memory AOR = 0.97 95% CI 0.67–1.39), no association was observed.Conclusions
The association between early to midlife smoking trajectories and midlife cognition was dose-dependent. Results underscore the cognitive health risk of moderate and heavy smoking and the potential benefits of quitting on cognition, even in midlife.
Growing evidence has suggested an association between sleep duration and Alzheimer's disease (AD), but it is unclear if sleep duration is a manifestation of AD disease process. We studied whether genetic liability for AD predicts sleep duration using a genetic risk score for AD (AD-GRS), in 406,536 UK Biobank participants with European ancestry and without dementia at enrollment. Higher AD-GRS score was associated with shorter sleep (b= -0.014,95%CI:-0.022,-0.006), especially in those aged 55+. Using AD-GRS as an instrumental variable for AD diagnosis, incipient AD reduced sleep duration by 1.87 hours (95%CI:0.96, 2.78). Short sleep duration might be an early marker of AD. This article is protected by copyright. All rights reserved.
Introduction:
Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging database (11 studies; 10,216 subjects).
Methods:
Three brain signatures were calculated: Brain-age, AD-like neurodegeneration, and white matter hyperintensities (WMHs). Brain Charts measured and displayed the relationships of these signatures to cognition and molecular biomarkers of AD.
Results:
WMHs were associated with advanced brain aging, AD-like atrophy, poorer cognition, and AD neuropathology in mild cognitive impairment (MCI)/AD and cognitively normal (CN) subjects. High WMH volume was associated with brain aging and cognitive decline occurring in an ≈10-year period in CN subjects. WMHs were associated with doubling the likelihood of amyloid beta (Aβ) positivity after age 65. Brain aging, AD-like atrophy, and WMHs were better predictors of cognition than chronological age in MCI/AD.
Discussion:
A Brain Chart quantifying brain-aging trajectories was established, enabling the systematic evaluation of individuals' brain-aging patterns relative to this large consortium.
This article describes the public health impact of Alzheimer's disease (AD), including incidence and prevalence, mortality and morbidity, use and costs of care, and the overall impact on caregivers and society. The Special Report discusses the future challenges of meeting care demands for the growing number of people living with Alzheimer's dementia in the United States with a particular emphasis on primary care. By mid‐century, the number of Americans age 65 and older with Alzheimer's dementia may grow to 13.8 million. This represents a steep increase from the estimated 5.8 million Americans age 65 and older who have Alzheimer's dementia today. Official death certificates recorded 122,019 deaths from AD in 2018, the latest year for which data are available, making Alzheimer's the sixth leading cause of death in the United States and the fifth leading cause of death among Americans age 65 and older. Between 2000 and 2018, deaths resulting from stroke, HIV and heart disease decreased, whereas reported deaths from Alzheimer's increased 146.2%. In 2019, more than 16 million family members and other unpaid caregivers provided an estimated 18.6 billion hours of care to people with Alzheimer's or other dementias. This care is valued at nearly 305 billion. As the population of Americans living with Alzheimer's dementia increases, the burden of caring for that population also increases. These challenges are exacerbated by a shortage of dementia care specialists, which places an increasing burden on primary care physicians (PCPs) to provide care for people living with dementia. Many PCPs feel underprepared and inadequately trained to handle dementia care responsibilities effectively. This report includes recommendations for maximizing quality care in the face of the shortage of specialists and training challenges in primary care.
Objective:
Income volatility presents a growing public health threat. To our knowledge, no previous study examined the relationship among income volatility, cognitive function, and brain integrity.
Methods:
We studied 3,287 participants aged 23-35 years in 1990 from the Coronary Artery Risk Development in Young Adults prospective cohort study. Income volatility data were created using income data collected from 1990 to 2010 and defined as SD of percent change in income and number of income drops ≥25% (categorized as 0, 1, or 2+). In 2010, cognitive tests (n = 3,287) and brain scans (n = 716) were obtained.
Results:
After covariate adjustment, higher income volatility was associated with worse performance on processing speed (β = -1.09, 95% confidence interval [CI] -1.73 to -0.44) and executive functioning (β = 2.53, 95% CI 0.60-4.50) but not on verbal memory (β = -0.02, 95% CI -0.16 to 0.11). Similarly, additional income drops were associated with worse performance on processing speed and executive functioning. Higher income volatility and more income drops were also associated with worse microstructural integrity of total brain and total white matter. All findings were similar when restricted to those with high education, suggesting reverse causation may not explain these findings.
Conclusion:
Income volatility over a 20-year period of formative earning years was associated with worse cognitive function and brain integrity in midlife.
Alzheimer disease (AD) is a heterogeneous disease with a complex pathobiology. The presence of extracellular β-amyloid deposition as neuritic plaques and intracellular accumulation of hyperphosphorylated tau as neurofibrillary tangles remains the primary neuropathologic criteria for AD diagnosis. However, a number of recent fundamental discoveries highlight important pathological roles for other critical cellular and molecular processes. Despite this, no disease-modifying treatment currently exists, and numerous phase 3 clinical trials have failed to demonstrate benefits. Here, we review recent advances in our understanding of AD pathobiology and discuss current treatment strategies, highlighting recent clinical trials and opportunities for developing future disease-modifying therapies.
Machine learning is a branch of computer science that has the potential to transform epidemiological sciences. Amid a growing focus on "Big Data," it offers epidemiologists new tools to tackle problems for which classical methods are not well-suited. In order to critically evaluate the value of integrating machine learning algorithms and existing methods, however, it is essential to address language and technical barriers between the two fields that can make it difficult for epidemiologists to read and assess machine learning studies. Here, we provide an overview of the concepts and terminology used in machine learning literature, which encompasses a diverse set of tools with goals ranging from prediction, to classification, to clustering. We provide a brief introduction to five common machine learning algorithms and four ensemble-based approaches. We then summarize epidemiological applications of machine learning techniques in the published literature. We recommend approaches to incorporate machine learning in epidemiological research and discuss opportunities and challenges for integrating machine learning and existing epidemiological research methods.
Objective:
To assess the onset, sequence, and rate of progression of comprehensive biomarker and clinical measures across the spectrum of Alzheimer disease (AD) using the Dominantly Inherited Alzheimer Network (DIAN) study and compare these to cross-sectional estimates.
Methods:
We conducted longitudinal clinical, cognitive, CSF, and neuroimaging assessments (mean of 2.7 [±1.1] visits) in 217 DIAN participants. Linear mixed effects models were used to assess changes in each measure relative to individuals' estimated years to symptom onset and to compare mutation carriers and noncarriers.
Results:
Longitudinal β-amyloid measures changed first (starting 25 years before estimated symptom onset), followed by declines in measures of cortical metabolism (approximately 7-10 years later), then cognition and hippocampal atrophy (approximately 20 years later). There were significant differences in the estimates of CSF p-tau181 and tau, with elevations from cross-sectional estimates preceding longitudinal estimates by over 10 years; further, longitudinal estimates identified a significant decline in CSF p-tau181 near symptom onset as opposed to continued elevations.
Conclusion:
These longitudinal estimates clarify the sequence and temporal dynamics of presymptomatic pathologic changes in autosomal dominant AD, information critical to a better understanding of the disease. The pattern of biomarker changes identified here also suggests that once β-amyloidosis begins, additional pathologies may begin to develop less than 10 years later, but more than 15 years before symptom onset, an important consideration for interventions meant to alter the disease course.