Leveraging large multi-center cohorts of Alzheimer disease endophenotypes to understand the role of Klotho heterozygosity on disease risk

Patient stratification by genetic risk in Alzheimer's disease is only effective in the presence of phenotypic heterogeneity

Case-only designs in longitudinal cohorts are a valuable resource for identifying disease-relevant genes, pathways, and novel targets influencing disease progression. This is particularly relevant in Alzheimer's disease (AD), where longitudinal cohorts measure disease "progression," defined by rate of cognitive decline. Few of the identified drug targets for AD have been clinically tractable, and phenotypic heterogeneity is an obstacle to both clinical research and basic science. In four cohorts (n = 7241), we performed genome-wide association studies (GWAS) and Mendelian randomization (MR) to discover novel targets associated with progression and assess causal relationships. We tested opportunities for patient stratification by deriving polygenic risk scores (PRS) for AD risk and severity and tested the value of these scores in predicting progression. Genome-wide association studies identified no loci associated with progression at genome-wide significance (α = 5×10-8); MR analyses provided no significant evidence of an association between cognitive decline in AD patients and protein levels in brain, cerebrospinal fluid (CSF), and plasma. Polygenic risk scores for AD risk did not reliably stratify fast from slow progressors; however, a deeper investigation found that APOE ε4 status predicts amyloid-β and tau positive versus negative patients (odds ratio for an additional APOE ε4 allele = 5.78 [95% confidence interval: 3.76-8.89], P<0.001) when restricting to a subset of patients with available CSF biomarker data. These results provided no evidence for large-effect, common-variant loci involved in the rate of memory decline, suggesting that patient stratification based on common genetic risk factors for progression may have limited utility. Where clinically relevant biomarkers suggest diagnostic heterogeneity, there is evidence that a priori identified genetic risk factors may have value in patient stratification. Mendelian randomization was less tractable due to the lack of large-effect loci, and future analyses with increased samples sizes are needed to replicate and validate our results.

CSF proteomics identifies early changes in autosomal dominant Alzheimer's disease

In this high-throughput proteomic study of autosomal dominant Alzheimer's disease (ADAD), we sought to identify early biomarkers in cerebrospinal fluid (CSF) for disease monitoring and treatment strategies. We examined CSF proteins in 286 mutation carriers (MCs) and 177 non-carriers (NCs). The developed multi-layer regression model distinguished proteins with different pseudo-trajectories between these groups. We validated our findings with independent ADAD as well as sporadic AD datasets and employed machine learning to develop and validate predictive models. Our study identified 137 proteins with distinct trajectories between MCs and NCs, including eight that changed before traditional AD biomarkers. These proteins are grouped into three stages: early stage (stress response, glutamate metabolism, neuron mitochondrial damage), middle stage (neuronal death, apoptosis), and late presymptomatic stage (microglial changes, cell communication). The predictive model revealed a six-protein subset that more effectively differentiated MCs from NCs, compared with conventional biomarkers.

Multifaceted roles of APOE in Alzheimer disease

For the past three decades, apolipoprotein E (APOE) has been known as the single greatest genetic modulator of sporadic Alzheimer disease (AD) risk, influencing both the average age of onset and the lifetime risk of developing AD. The APOEε4 allele significantly increases AD risk, whereas the ε2 allele is protective relative to the most common ε3 allele. However, large differences in effect size exist across ethnoracial groups that are likely to depend on both global genetic ancestry and local genetic ancestry, as well as gene-environment interactions. Although early studies linked APOE to amyloid-β - one of the two culprit aggregation-prone proteins that define AD - in the past decade, mounting work has associated APOE with other neurodegenerative proteinopathies and broader ageing-related brain changes, such as neuroinflammation, energy metabolism failure, loss of myelin integrity and increased blood-brain barrier permeability, with potential implications for longevity and resilience to pathological protein aggregates. Novel mouse models and other technological advances have also enabled a number of therapeutic approaches aimed at either attenuating the APOEε4-linked increased AD risk or enhancing the APOEε2-linked AD protection. This Review summarizes this progress and highlights areas for future research towards the development of APOE-directed therapeutics.

Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures for asymptomatic and symptomatic Alzheimer's disease

Changes in Amyloid-β (A), hyperphosphorylated Tau (T) in brain and cerebrospinal fluid (CSF) precedes AD symptoms, making CSF proteome a potential avenue to understand the pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 proteins dysregulated in AD, that were further validated in a third totally independent cohort. Machine learning was implemented to create and validate highly accurate and replicable (AUC>0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD and those AD cases with faster progression. The associated proteins cluster in four different protein pseudo-trajectories groups spanning the AD continuum and were enrichment in specific pathways including neuronal death, apoptosis and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfuncton(mid-stages), brain plasticity and longevity (mid-stages) and late microglia-neuron crosstalk (late stages).

Systematic proteomics in Autosomal dominant Alzheimer's disease reveals decades-early changes of CSF proteins in neuronal death, and immune pathways

Background

To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies.

Methods

We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models.

Findings

We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aβ42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89).

Interpretation

Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs.

Funding

Proteomic data generation was supported by NIH: RF1AG044546.

Harmonization of CSF and imaging biomarkers in Alzheimer's disease: Need and practical applications for genetics studies and preclinical classification

In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers, leading to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS results using this approach with currently accepted methods. We also used a generalized mixture model to calculate the threshold for biomarker-positivity. Based on our findings, our normalization approach performed as well as meta-analysis and did not lead to any spurious results. In terms of dichotomization, cutoffs calculated with this approach were very similar to those reported previously. These findings show that the Z-score based harmonization approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.

Non-Pharmacological Exercise Randomized Controlled Trials in Alzheimer's Disease

This narrative review aimed to summarize evidence on responses to exercise in pre-clinical Alzheimer's disease (AD) and on how long-term exercise programs work to improve neuropsychiatric symptoms and cognitive performance. We conducted a narrative review of the body of research on the benefits of long-term exercise programs in improving cognitive performance and reducing neuropsychiatric scores in patients with AD. Long-term exercise therapy appears to improve blood flow, increase hippocampal volume, and promote neurogenesis in patients with AD. Higher levels of physical activity are associated with a lower chance of developing the disease, and most prospective studies have shown that physical inactivity is one of the most prevalent modifiable risk factors for the development of AD. Exercise appears to be beneficial in improving cognitive function, a neuropsychiatric symptom of AD. Exercise has been shown to have fewer side effects, such as non-pharmacological effects and better adherence than medication. In this review, experts provided a snapshot and authoritative summary of evidence for non-pharmacological exercise in patients with AD based on the best synthesis efforts, identified the main knowledge gaps and relevant barriers, and provided directions for future research. Furthermore, experts in randomized trial designs provided practical details and recommendations for researchers working in this area, underscoring the importance of relevant topics.

Targeting neuroendocrine abnormalities in Parkinson's disease with exercise

Parkinson's Disease (PD) is a prevalent and complex age-related neurodegenerative condition for which there are no disease-modifying treatments currently available. The pathophysiological process underlying PD remains incompletely understood but increasing evidence points to multiple system dysfunction. Interestingly, the past decade has produced evidence that exercise not only reduces signs and symptoms of PD but is also potentially neuroprotective. Characterizing the mechanistic pathways that are triggered by exercise and lead to positive outcomes will improve understanding of how to counter disease progression and symptomatology. In this review, we highlight how exercise regulates the neuroendocrine system, whose primary role is to respond to stress, maintain homeostasis and improve resilience to aging. We focus on a group of hormones - cortisol, melatonin, insulin, klotho, and vitamin D - that have been shown to associate with various non-motor symptoms of PD, such as mood, cognition, and sleep/circadian rhythm disorder. These hormones may represent important biomarkers to track in clinical trials evaluating effects of exercise in PD with the aim of providing evidence that patients can exert some behavioral-induced control over their disease.

The Early-Onset Alzheimer's Disease Whole-Genome Sequencing Project: Study design and methodology

INTRODUCTION

Sequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late-onset AD although early-onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations, resulting in a lack of understanding of its molecular etiology.

METHODS

Whole-genome sequencing and harmonization of clinical, neuropathological, and biomarker data of over 5000 EOAD cases of diverse ancestries.

RESULTS

A publicly available genomics resource for EOAD with extensive harmonized phenotypes. Primary analysis will (1) identify novel EOAD risk loci and druggable targets; (2) assess local-ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits.

DISCUSSION

This novel resource complements over 50,000 control and late-onset AD samples generated through the Alzheimer's Disease Sequencing Project (ADSP). The harmonized EOAD/ADSP joint call will be available through upcoming ADSP data releases and will allow for additional analyses across the full onset range.

HIGHLIGHTS

Sequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late-onset AD although early-onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations. This results in a significant lack of understanding of the molecular etiology of this devastating form of the disease. The Early-Onset Alzheimer's Disease Whole-genome Sequencing Project is a collaborative initiative to generate a large-scale genomics resource for early-onset Alzheimer's disease with extensive harmonized phenotype data. Primary analyses are designed to (1) identify novel EOAD risk and protective loci and druggable targets; (2) assess local-ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits. The harmonized genomic and phenotypic data from this initiative will be available through NIAGADS.

Longevity factor klotho enhances cognition in aged nonhuman primates

Cognitive dysfunction in aging is a major biomedical challenge. Whether treatment with klotho, a longevity factor, could enhance cognition in human-relevant models such as in nonhuman primates is unknown and represents a major knowledge gap in the path to therapeutics. We validated the rhesus form of the klotho protein in mice showing it increased synaptic plasticity and cognition. We then found that a single administration of low-dose, but not high-dose, klotho enhanced memory in aged nonhuman primates. Systemic low-dose klotho treatment may prove therapeutic in aging humans.

Genetic architecture of plasma Alzheimer disease biomarkers

Genome-wide association studies (GWAS) of cerebrospinal fluid (CSF) Alzheimer's Disease (AD) biomarker levels have identified novel genes implicated in disease risk, onset and progression. However, lumbar punctures have limited availability and may be perceived as invasive. Blood collection is readily available and well accepted, but it is not clear whether plasma biomarkers will be informative for genetic studies. Here we perform genetic analyses on concentrations of plasma amyloid-β peptides Aβ40 (n = 1,467) and Aβ42 (n = 1,484), Aβ42/40 (n = 1467) total tau (n = 504), tau phosphorylated (p-tau181; n = 1079) and neurofilament light (NfL; n = 2,058). GWAS and gene-based analysis was used to identify single variant and genes associated with plasma levels. Finally, polygenic risk score and summary statistics were used to investigate overlapping genetic architecture between plasma biomarkers, CSF biomarkers and AD risk. We found a total of six genome-wide significant signals. APOE was associated with plasma Aβ42, Aβ42/40, tau, p-tau181 and NfL. We proposed 10 candidate functional genes on the basis of 12 single nucleotide polymorphism-biomarker pairs and brain differential gene expression analysis. We found a significant genetic overlap between CSF and plasma biomarkers. We also demonstrate that it is possible to improve the specificity and sensitivity of these biomarkers, when genetic variants regulating protein levels are included in the model. This current study using plasma biomarker levels as quantitative traits can be critical to identification of novel genes that impact AD and more accurate interpretation of plasma biomarker levels.

Harmonization of CSF and imaging biomarkers for Alzheimer's disease biomarkers: need and practical applications for genetics studies and preclinical classification

INTRODUCTION

In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers which leads to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values.

METHODS

We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS result using this method with currently accepted methods. We also used a generalized mixture modelling to calculate the threshold for biomarker-positivity.

RESULTS

Z-scores method performed as well as meta-analysis and did not lead to any spurious results. Cutoffs calculated with this approach were found to be very similar to those reported previously.

DISCUSSION

This approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.

Interaction between KLOTHO-VS Heterozygosity and APOE ε4 Allele Predicts Rate of Cognitive Decline in Late-Onset Alzheimer's Disease

KLOTHO-VS heterozygosity (KL-VShet+) promotes longevity and protects against cognitive decline in aging. To determine whether KL-VShet+ mitigates Alzheimer's disease (AD) progression, we used longitudinal linear-mixed models to compare the rate of change in multiple cognitive measures in AD patients stratified by APOE ε4 carrier status. We aggregated data on 665 participants (208 KL-VShet-/ε4-, 307 KL-VShet-/ε4+, 66 KL-VShet+/ε4-, and 84 KL-VShet+/ε4+) from two prospective cohorts, the National Alzheimer's Coordinating Center and the Alzheimer's Disease Neuroimaging Initiative. All participants were initially diagnosed with mild cognitive impairment, later developed AD dementia during the study, and had at least three subsequent visits. KL-VShet+ conferred slower cognitive decline in ε4 non-carriers (+0.287 MMSE points/year, p = 0.001; -0.104 CDR-SB points/year, p = 0.026; -0.042 ADCOMS points/year, p < 0.001) but not in ε4 carriers who generally had faster rates of decline than non-carriers. Stratified analyses showed that the protective effect of KL-VShet+ was particularly prominent in male participants, those who were older than the median baseline age of 76 years, or those who had an education level of at least 16 years. For the first time, our study provides evidence that KL-VShet+ status has a protective effect on AD progression and interacts with the ε4 allele.

Comparative Analysis of Alzheimer's Disease Cerebrospinal Fluid Biomarkers Measurement by Multiplex SOMAscan Platform and Immunoassay-Based Approach

BACKGROUND

The SOMAscan assay has an advantage over immunoassay-based methods because it measures a large number of proteins in a cost-effective manner. However, the performance of this technology compared to the routinely used immunoassay techniques needs to be evaluated.

OBJECTIVE

We performed comparative analyses of SOMAscan and immunoassay-based protein measurements for five cerebrospinal fluid (CSF) proteins associated with Alzheimer's disease (AD) and neurodegeneration: NfL, Neurogranin, sTREM2, VILIP-1, and SNAP-25.

METHODS

We compared biomarkers measured in ADNI (N = 689), Knight-ADRC (N = 870), DIAN (N = 115), and Barcelona-1 (N = 92) cohorts. Raw protein values were transformed using z-score in order to combine measures from the different studies. sTREM2 and VILIP-1 had more than one analyte in SOMAscan; all available analytes were evaluated. Pearson's correlation coefficients between SOMAscan and immunoassays were calculated. Receiver operating characteristic curve and area under the curve were used to compare prediction accuracy of these biomarkers between the two platforms.

RESULTS

Neurogranin, VILIP-1, and NfL showed high correlation between SOMAscan and immunoassay measures (r > 0.9). sTREM2 had a fair correlation (r > 0.6), whereas SNAP-25 showed weak correlation (r = 0.06). Measures in both platforms provided similar predicted performance for all biomarkers except SNAP-25 and one of the sTREM2 analytes. sTREM2 showed higher AUC for SOMAscan based measures.

CONCLUSION

Our data indicate that SOMAscan performs as well as immunoassay approaches for NfL, Neurogranin, VILIP-1, and sTREM2. Our study shows promise for using SOMAscan as an alternative to traditional immunoassay-based measures. Follow-up investigation will be required for SNAP-25 and additional established biomarkers.