Highly BBB-permeable nanomedicine reverses neuroapoptosis and neuroinflammation to treat Alzheimer's disease.

The prevalence of Alzheimer's disease (AD) is increasing globally due to population aging. However, effective clinical treatment strategies for AD still remain elusive. The mechanisms underlying AD onset and the interplay between its pathological factors have so far been unclear. Evidence indicates that AD progression is ultimately driven by neuronal loss, which in turn is caused by neuroapoptosis and neuroinflammation. Therefore, the inhibition of neuroapoptosis and neuroinflammation could be a useful anti-AD strategy. Nonetheless, the delivery of active drug agents into the brain parenchyma is hindered by the blood-brain barrier (BBB). To address this challenge, we fabricated a black phosphorus nanosheet (BP)-based methylene blue (MB) delivery system (BP-MB) for AD therapy. After confirming the successful preparation of BP-MB, we proved that its BBB-crossing ability was enhanced under near-infrared light irradiation. In vitro pharmacodynamics analysis revealed that BP and MB could synergistically scavenge excessive reactive oxygen species (ROS) in okadaic acid (OA)-treated PC12 cells and lipopolysaccharide (LPS)-treated BV2 cells, thus efficiently reversing neuroapoptosis and neuroinflammation. To study in vivo pharmacodynamics, we established a mouse model of AD mice, and behavioral tests confirmed that BP-MB treatment could successfully improve cognitive function in these animals. Notably, the results of pathological evaluation were consistent with those of the in vitro assays. The findings demonstrated that BP-MB could scavenge excessive ROS and inhibit Tau hyperphosphorylation, thereby alleviating downstream neuroapoptosis and regulating the polarization of microglia from the pro-inflammatory M1 phenotype to the anti-inflammatory M2 phenotype. Overall, this study highlights the therapeutic potential of a smart nanomedicine with the capability of reversing neuroapoptosis and neuroinflammation for AD treatment.

Interval-specific likelihood ratios and probability-based models for interpreting combined CSF biomarkers for Alzheimer's disease.

BACKGROUND: In Alzheimer's disease (AD) diagnosis, a cerebrospinal fluid (CSF) biomarker panel is commonly interpreted with binary cutoff values. However, these values are not generic and do not reflect the disease continuum. We explored the use of interval-specific likelihood ratios (LRs) and probability-based models for AD using a CSF biomarker panel. METHODS: CSF biomarker (Aß1-42, tTau and pTau181) data for both a clinical discovery cohort of 241 patients (measured with INNOTEST) and a clinical validation cohort of 129 patients (measured with EUROIMMUN), both including AD and non-AD dementia/cognitive complaints were retrospectively retrieved in a single-center study. Interval-specific LRs for AD were calculated and validated for univariate and combined (Aß1-42/tTau and pTau181) biomarkers, and a continuous bivariate probability-based model for AD, plotting Aß1-42/tTau versus pTau181 was constructed and validated. RESULTS: LR for AD increased as individual CSF biomarker values deviated from normal. Interval-specific LRs of a combined biomarker model showed that once one biomarker became abnormal, LRs increased even further when another biomarker largely deviated from normal, as replicated in the validation cohort. A bivariate probability-based model predicted AD with a validated accuracy of 88% on a continuous scale. CONCLUSIONS: Interval-specific LRs in a combined biomarker model and prediction of AD using a continuous bivariate biomarker probability-based model, offer a more meaningful interpretation of CSF AD biomarkers on a (semi-)continuous scale with respect to the post-test probability of AD across different assays and cohorts.

Prevalence Estimation of Dementia/Alzheimer's Disease Using Health and Retirement Study Database in the United States.

BACKGROUND: Updated prevalence estimates along the continuum of Alzheimer's disease (AD) can foster a more nuanced and effective approach to managing AD within the current healthcare landscape. OBJECTIVES: This study aims to estimate the prevalence and severity distribution of dementia/AD (including mild, moderate, and severe stages) and all-cause mild cognitive impairment (MCI) in the United States using data from the Health and Retirement Study (HRS). DESIGN: Retrospective study. SETTING: Data from the bi-annual HRS surveys involving in-depth interviews of a representative sample of Americans aged >50 years. PARTICIPANTS: Dementia/AD and all-cause MCI patients from the 4 most recent HRS surveys (2014, 2016, 2018 and 2020). MEASUREMENTS: AD was identified based on diagnosis (self-report). Cognitive performance (modified Telephone Interview of Cognitive Status [TICS-m]) scores in the dementia/AD range were also captured; all-cause MCI was similarly identified using the TICS-m. Dementia/AD and MCI prevalence, as well as the distribution by dementia/AD stage (mild, moderate, or severe), were estimated. Sampling weights developed by HRS were applied to ensure the sample's representativeness of the target population and unbiased estimates for population parameters. RESULTS: Across the four HRS surveys, the total number of HRS respondents ranged from 15,000 to 21,000 (unweighted); 7,000 to 14,000 had TICS-m scores. The estimated prevalence of AD (all severity categories combined) in the 2014, 2016, 2018, and 2020 HRS surveys was 1.2%, 1.2%, 1.3% and 1.0%, respectively using the diagnosis-based approach; using the cognitive performance-based approach, 23-27% patients had scores in the dementia/AD ranges across the 4 surveys. The estimated prevalence of all-cause MCI was consistently 23% in each survey. In the 2020 survey, the distribution of mild, moderate, and severe disease stages was 34%, 45%, and 21%, respectively, in patients self-reporting an AD diagnosis, and 55%, 40%, and 5%, respectively in all patients meeting TICS-m threshold for dementia/AD. CONCLUSION: The prevalence of AD diagnosis based on self-report was approximately 1% across the 4 most recent HRS surveys and may reflect the proportion of patients who have actively sought healthcare for AD. Among HRS survey respondents with cognitive scores available, over 20% were in the dementia/AD range. The distribution of disease by stage differed for self-reported AD diagnosis vs dementia/AD based on cognitive scores. Discordance in estimates of dementia/AD and stage distributions underscores a need for better understanding of clinical practice patterns in AD diagnosis, use of clinical assessment tools, and severity classification in the United States. Accurate patient identification is needed, especially early in the AD disease continuum, to allow for timely and appropriate initiation of new anti-amyloid treatments.

A Statistical Framework for Assessing the Relationship between Biomarkers and Clinical Endpoints in Alzheimer's Disease.

Changes in biomarker levels of Alzheimer's disease (AD) reflect underlying pathophysiological changes in the brain and can provide evidence of direct and downstream treatment effects linked to disease modification. Recent results from clinical trials of anti-amyloid ß (Aß) treatments have raised the question of how to best characterize the relationship between AD biomarkers and clinical endpoints. Consensus methodology for assessing such relationships is lacking, leading to inconsistent evaluation and reporting. In this review, we provide a statistical framework for reporting treatment effects on early and late accelerating AD biomarkers and assessing their relationship with clinical endpoints at the subject and group levels. Amyloid positron emission tomography (PET), plasma p-tau, and tau PET follow specific trajectories during AD and are used as exemplar cases to contrast biomarkers with early and late progression. Subject-level correlation was assessed using change from baseline in biomarkers versus change from baseline in clinical endpoints, and interpretation of the correlation is dependent on the biomarker and disease stage. Group-level correlation was assessed using the placebo-adjusted treatment effects on biomarkers versus those on clinical endpoints in each trial. This correlation leverages the fundamental advantages of randomized placebo-controlled trials and assesses the predictivity of a treatment effect on a biomarker or clinical benefit. Harmonization in the assessment of treatment effects on biomarkers and their relationship to clinical endpoints will provide a wealth of comparable data across clinical trials and may yield new insights for the treatment of AD.

Plasma Biomarkers of Alzheimer's Disease and Neurodegeneration According to Sociodemographic Characteristics and Chronic Health Conditions.

Ultrasensitive assays have been developed which enable biomarkers of Alzheimer's disease pathology and neurodegeneration to be measured in blood. These biomarkers can aid in diagnosis, and have been used to predict risk of cognitive decline and Alzheimer's disease. The ease and cost-effectiveness of blood collections means that these biomarkers could be applied more broadly in population-based screening, however it is critical to first understand what other factors could affect blood biomarker levels. The aim of this review was to determine the extent that sociodemographic, lifestyle and health factors have been associated with blood biomarkers of Alzheimer's disease and neuropathology. Of the 32 studies included in this review, all but one measured biomarker levels in plasma, and age and sex were the most commonly investigated factors. The most consistent significant findings were a positive association between age and neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP), and females had higher GFAP than men. Apolipoprotein ε4 allele carriers had lower Aß42 and Aß42/40 ratio. Body mass index was negatively associated with GFAP and NfL, and chronic kidney disease with higher levels of all biomarkers. Too few studies have investigated other chronic health conditions and this requires further investigation. Given the potential for plasma biomarkers to enhance Alzheimer's disease diagnosis in primary care, it is important to understand how to interpret the biomarkers in light of factors that physiologically impact blood biomarker levels. This information will be critical for the establishment of reference ranges and thus the correct interpretation of these biomarkers in clinical screening.

Performance of Plasma Biomarkers Combined with Structural MRI to Identify Candidate Participants for Alzheimer's Disease-Modifying Therapy.

BACKGROUND: Recently, two monoclonal antibodies that lower amyloid plaques have shown promising results for the treatment of Mild Cognitive Impairment (MCI) and mild dementia due to Alzheimer's disease (AD). These treatments require the identification of cognitively impaired older adults with biomarker evidence of AD pathology using CSF biomarkers or amyloid-PET. Previous studies showed plasma biomarkers (plasma Aß42/Aß40 and p-tau181) and hippocampal volume from structural MRI correlated with brain amyloid pathology. We hypothesized plasma biomarkers with hippocampal volume would identify patients who are suitable candidates for disease-modifying therapy. OBJECTIVES: To evaluate the performance of plasma AD biomarkers and hippocampal atrophy to detect MCI or AD with amyloid pathology confirmed by amyloid-PET or CSF biomarkers in ADNI. DESIGN: A cross-sectional and longitudinal study. SETTING AND PARTICIPANTS: Data were from the Alzheimer's Disease Neuroimaging Initiative. Participants were aged 55-90 years old with plasma biomarker and structural MRI brain data. MEASUREMENTS: The optimum cut-off point for plasma Aß42/Aß40, p-tau181, and NFL and the performance of combined biomarkers and hippocampal atrophy for detecting cognitive impairment with brain amyloid pathology were evaluated. The association between baseline plasma biomarkers and clinical progression, defined by CDR-Sum of Boxes (CDR-SB) and diagnostic conversion over two years, was evaluated using a Weibull time-to-event analysis. RESULTS: A total of 428 participants were included; 167 had normal cognition, 245 had MCI, and 16 had mild AD. Among MCI and AD, 140 participants had elevated amyloid levels by PET or CSF. Plasma Aß42/Aß40 provided the best accuracy (sensitivity 79%, specificity 66%, AUC 0.73, 95% CI 0.68-0.77) to detect drug candidate participants at baseline. Combined plasma Aß42/40, p-tau181, and hippocampal atrophy increased the specificity for diagnosis (96%), but had lower sensitivity (34%), and AUC (0.65). Hippocampal atrophy combined with the abnormal plasma p-tau181 or hippocampal atrophy alone showed high sensitivity to detect clinical progression (by CDR-SB worsening) of the drug-candidate participants within the next 2 years (sensitivity 93% and 89%, respectively). CONCLUSION: Plasma biomarkers and structural MRI can help identify patients who are currently eligible for anti-amyloid treatment and are likely to progress clinically, in cases where amyloid-PET or CSF biomarkers are not available.

Progress in the Treatment of Alzheimer's Disease Is Needed - Position Statement of European Alzheimer's Disease Consortium (EADC) Investigators.

ß-amyloid-targeting antibodies represent the first generation of effective causal treatment of Alzheimer's disease (AD) and can be considered historical research milestones. Their effect sizes, side effects, implementation challenges and costs, however, have stimulated debates about their overall value. In this position statement academic clinicians of the European Alzheimer's Disease Consortium (EADC) discuss the critical relevance of introducing these new treatments in clinical care now. Given the complexity of AD it is unlikely that molecular single-target treatments will achieve substantially larger effects than those seen with current ß-amyloid-targeting antibodies. Larger effects will most likely only be achieved incrementally by continuous optimization of molecular approaches, patient selection and combinations therapies. To be successful in this regard, drug development must be informed by the use of innovative treatments in real world practice, because full understanding of all facets of novel treatments requires experience and data of real-world care beyond those of clinical trials. Regarding the antibodies under discussion we consider their effects meaningful and potential side effects manageable. We assume that the number of eventually treated patient will only be a fraction of all early AD patients due to narrow eligibility criteria and barriers of access. We strongly endorse the use of these new compound in clinical practice in selected patients with treatment documentation in registries. We understand this as a critical step in advancing the field of AD treatment, and in shaping the health care systems for the new area of molecular-targeted treatment of neurodegenerative diseases.

Japanese Subgroup Analyses from EMERGE and ENGAGE, Phase 3 Clinical Trials of Aducanumab in Patients with Early Alzheimer's Disease.

BACKGROUND: Global prevalence and incidence of dementia continue to rise at a rapid rate. There is a need for new Alzheimer's disease (AD) treatments globally. Aducanumab is a human monoclonal antibody that selectively targets aggregated soluble amyloid beta oligomers and insoluble amyloid beta fibrils. In June 2021, aducanumab was approved by the US Food and Drug Administration for the treatment of AD under the accelerated approval pathway. OBJECTIVES: We evaluated the efficacy, safety, biomarker and pharmacokinetics (PK) of aducanumab in Japanese subgroups in EMERGE and ENGAGE studies. DESIGN: EMERGE and ENGAGE were two randomized, double-blind, placebo-controlled, global, phase 3 studies of aducanumab in patients with early AD (mild cognitive impairment due to AD or mild AD dementia). SETTING: These studies involved 348 sites in 20 countries. PARTICIPANTS: Participants enrolled in Japan included 121 (7.4% of total 1638 in EMERGE) and 100 (6.1% of total 1647 in ENGAGE) patients (aged 50-85 years with confirmed amyloid pathology) who met clinical criteria for mild cognitive impairment due to AD or mild AD dementia. INTERVENTION: Participants were randomly assigned 1:1:1 to receive aducanumab low dose (3 or 6 mg/kg target dose), high dose (6 or 10 mg/kg target dose) or placebo via IV infusion once every 4 weeks over 76 weeks. MEASUREMENTS: The primary outcome measure was change from baseline to Week 78 on the Clinical Dementia Rating Sum of Boxes (CDR-SB), an integrated scale that assesses both function and cognition. Other measures included safety assessments; secondary and tertiary clinical outcomes that assessed cognition, function, and behavior; biomarker endpoints (amyloid PET and plasma p-tau181); serum PK profiles and immunogenicity. RESULTS: Results from the Japanese subgroup analyses were generally consistent with those of the overall study population across endpoints, while a lower mean body weight (kg) and a smaller proportion of ApoE ε4 carriers were observed in the Japanese subgroup population. A treatment effect was observed in favor of aducanumab on the primary and secondary efficacy endpoints at Week 78 in EMERGE, but not ENGAGE. The incidence and type of adverse events in the Japanese subgroups were generally comparable to those observed in the overall study population; amyloid related imaging abnormalities (ARIA) were common treatment-related adverse events that appeared to be related to the aducanumab dose. ARIA incidence was generally lower in the Japanese subgroup compared with the overall population. Consistent with the overall data set, a robust dose-dependent decrease in amyloid beta levels as assessed with amyloid-PET and plasma p-tau181 was observed. Serum PK profiles and immunogenicity of aducanumab in Japanese population were consistent with the non-Japanese population. CONCLUSION: Efficacy, safety, biomarker, and PK profiles of aducanumab were consistent between the Japanese subgroup and the overall population. A positive treatment effect of aducanumab on efficacy endpoints was observed in EMERGE, but not in ENGAGE.

Estimating Socio-Economic Status for Alzheimer's Disease Trials.

INTRODUCTION: Metrics of a participant's socioeconomic status (SES) are not routinely collected or standardized in clinical trials. This omission limits the ability to evaluate the generalizability of trial results and restricts clinicians from confidently interpreting the efficacy of new treatments across important sub-populations. METHODS: We adapted an SES measure of social disparity; the Hollingshead Two Factor Index of Social Position, which combines education and occupation into a single metric. We modernized the 1965 occupations to reflect the 2017 careers tabulated by the US Bureau of Labor Statistics. We currently use this adapted measure in Alzheimer's Clinical Trials Consortium studies. RESULTS: We present the revised table of occupations. We found that the collection of SES data using the modified Hollingshead was feasible in a multi-site clinical trial and scores were distributed across all SES strata. DISCUSSION: The modified Hollingshead provides a standardized method for collecting SES information, enabling data aggregation, monitoring, and reporting.

Lower Incidence of Dementia Following Cancer Diagnoses: Evidence from a Large Cohort and Mendelian Randomization Study.

BACKGROUND: The reported inverse association between cancer and subsequent Alzheimer's disease and related dementias (ADRD) remains uncertain. OBJECTIVES: To investigate the association between these common conditions of old age and explore possible causal factors. DESIGN, SETTING, PARTICIPANTS AND MEASUREMENTS: We conducted a large population-based cohort analysis using data from 3,021,508 individuals aged 60 and over in the UK Clinical Practice Research Datalink (CPRD), over a period up to 30 years (1988-2018). Cox proportional hazards models were fitted to estimate hazard ratios (HR) for risk of dementia associated with previous cancer diagnosis. Competing risk models were employed to account for competing risk of death. Two-sample Mendelian Randomization analysis based on meta-analysis data from large-scale GWAS studies was also conducted. RESULTS: In the CPRD cohort, 412,903 participants had cancer diagnosis and 230,558 were subsequently diagnosed with dementia over a median follow-up period of 7.9 years. Cancer survivors had a 25% lower risk of developing dementia (HR=0.75, 95% CI:0.74-0.76) after adjustment for potential confounders. Accounting for competing risk of death provided a sub-distribution HR of 0.56 (95% CI:0.55-0.56). Results were consistent for prevalent and incident cancer and different common cancer types. Two-sample Mendelian Randomization analysis, using 357 cancer-related instrumental single-nucleotide polymorphisms (SNPs) revealed evidence of vertical pleiotropy between genetically predicted cancer and reduced risk of Alzheimer's disease (OR=0.97,95% CI:0.95-0.99). CONCLUSION: Our results provide strong epidemiological evidence of the inverse association between cancer and risk of ADRD and support the potential causal nature of this association via genetic instruments. Further investigations into the precise underlying biological mechanisms may reveal valuable information for new therapeutic approaches.