Age-Related Tau Burden and Cognitive Deficits Are Attenuated in KLOTHO KL-VS Heterozygotes

Background: Identification of new genetic variants that modify Alzheimer’s disease (AD) risk will elucidate novel targets for curbing the disease progression or delaying symptom onset. Objective: To examine whether the functionally advantageous KLOTHO gene KL-VS variant attenuates age-related alteration in cerebrospinal fluid (CSF) biomarkers or cognitive function in middle-aged and older adults enriched for AD risk. Methods: Sample included non-demented adults (N = 225, mean age = 63±8, 68% women) from the Wisconsin Registry for Alzheimer’s Prevention and the Wisconsin Alzheimer’s Disease Research Center who were genotyped for KL-VS, underwent CSF sampling and had neuropsychological testing data available proximal to CSF draw. Covariate-adjusted multivariate regression examined relationships between age group (Younger versus Older; mean split at 63 years), AD biomarkers, and neuropsychological performance tapping memory and executive function, and whether these relationships differed between KL-VS non-carriers (KL-VSNC) and heterozygote (KL-VSHET). Results: In the pooled analyses, older age was associated with higher levels of total tau (tTau), phosphorylated tau (pTau), and their respective ratios to amyloid-β (Aβ)42 (ps ≤ 0.002), and with poorer performance on neuropsychological tests (ps ≤ 0.001). In the stratified analyses, KL-VSNC exhibited this age-related pattern of associations with CSF biomarkers (all ps ≤ 0.001), and memory and executive function (ps ≤ 0.003), which were attenuated in KL-VSHET (ps ≥ 0.14). Conclusion: Worse memory and executive function, and higher tau burden with age were attenuated in carriers of a functionally advantageous KLOTHO variant. KL-VS heterozygosity seems to be protective against age-related cognitive and biomolecular alterations that confer risk for AD

Comparative Evaluation of MS-based Metabolomics Software and Its Application to Preclinical Alzheimer's Disease

Mass spectrometry-based metabolomics has undergone significant progresses in the past decade, with a variety of software packages being developed for data analysis. However, systematic comparison of different metabolomics software tools has rarely been conducted. In this study, several representative software packages were comparatively evaluated throughout the entire pipeline of metabolomics data analysis, including data processing, statistical analysis, feature selection, metabolite identification, pathway analysis, and classification model construction. LC-MS-based metabolomics was applied to preclinical Alzheimer’s disease (AD) using a small cohort of human cerebrospinal fluid (CSF) samples (N = 30). All three software packages, XCMS Online, SIEVE, and Compound Discoverer, provided consistent and reproducible data processing results. A hybrid method combining statistical test and support vector machine feature selection was employed to screen key metabolites, achieving a complementary selection of candidate biomarkers from three software packages. Machine learning classification using candidate biomarkers generated highly accurate and predictive models to classify patients into preclinical AD or control category. Overall, our study demonstrated a systematic evaluation of different MS-based metabolomics software packages for the entire data analysis pipeline which was applied to the candidate biomarker discovery of preclinical AD

Biomarker clusters are differentially associated with longitudinal cognitive decline in late midlife

The ability to detect preclinical Alzheimer’s disease is of great importance, as this stage of the Alzheimer’s continuum is believed to provide a key window for intervention and prevention. As Alzheimer’s disease is characterized by multiple pathological changes, a biomarker panel reflecting co-occurring pathology will likely be most useful for early detection. Towards this end, 175 late middle-aged participants (mean age 55.9 ± 5.7 years at first cognitive assessment, 70% female) were recruited from two longitudinally followed cohorts to undergo magnetic resonance imaging and lumbar puncture. Cluster analysis was used to group individuals based on biomarkers of amyloid pathology (cerebrospinal fluid amyloid-β42/amyloid-β40 assay levels), magnetic resonance imaging-derived measures of neurodegeneration/atrophy (cerebrospinal fluid-to-brain volume ratio, and hippocampal volume), neurofibrillary tangles (cerebrospinal fluid phosphorylated tau181 assay levels), and a brain-based marker of vascular risk (total white matter hyperintensity lesion volume). Four biomarker clusters emerged consistent with preclinical features of (i) Alzheimer’s disease; (ii) mixed Alzheimer’s disease and vascular aetiology; (iii) suspected non-Alzheimer’s disease aetiology; and (iv) healthy ageing. Cognitive decline was then analysed between clusters using longitudinal assessments of episodic memory, semantic memory, executive function, and global cognitive function with linear mixed effects modelling. Cluster 1 exhibited a higher intercept and greater rates of decline on tests of episodic memory. Cluster 2 had a lower intercept on a test of semantic memory and both Cluster 2 and Cluster 3 had steeper rates of decline on a test of global cognition. Additional analyses on Cluster 3, which had the smallest hippocampal volume, suggest that its biomarker profile is more likely due to hippocampal vulnerability and not to detectable specific volume loss exceeding the rate of normal ageing. Our results demonstrate that pathology, as indicated by biomarkers, in a preclinical timeframe is related to patterns of longitudinal cognitive decline. Such biomarker patterns may be useful for identifying at-risk populations to recruit for clinical trials

Pathway-Specific Polygenic Risk Scores as Predictors of Amyloid-beta Deposition and Cognitive Function in a Sample at Increased Risk for Alzheimer's Disease

Polygenic risk scores (PRSs) have been used to combine the effects of variants with small effects identified by genome-wide association studies. We explore the potential for using pathway-specific PRSs as predictors of early changes in Alzheimer’s disease (AD)-related biomarkers and cognitive function. Participants were from the Wisconsin Registry for Alzheimer’s Prevention, a longitudinal study of adults who were cognitively asymptomatic at enrollment and enriched for a parental history of AD. Using genes associated with AD in the International Genomics of Alzheimer’s Project’s meta-analysis, we identified clusters of genes that grouped into pathways involved in amyloid-β (Aβ) deposition and neurodegeneration: Aβ clearance, cholesterol metabolism, and immune response. Weighted pathway-specific and overall PRSs were developed and compared to APOE alone. Mixed models were used to assess whether each PRS was associated with cognition in 1,200 individuals, cerebral Aβ deposition measured using amyloid ligand (Pittsburgh compound B) positron emission imaging in 168 individuals, and cerebrospinal fluid Aβ deposition, neurodegeneration, and tau pathology in 111 individuals, with replication performed in an independent sample. We found that PRSs including APOE appeared to be driven by the inclusion of APOE, suggesting that the pathway-specific PRSs used here were not more predictive than an overall PRS or APOE alone. However, pathway-specific PRSs could prove to be useful as more knowledge is gained on the genetic variants involved in specific biological pathways of AD

Measurement batch differences and between-batch conversion of Alzheimer's disease cerebrospinal fluid biomarker values

Introduction: Batch differences in cerebrospinal fluid (CSF) biomarker measurement can introduce bias into analyses for Alzheimer's disease studies. We evaluated and adjusted for batch differences using statistical methods. Methods: A total of 792 CSF samples from 528 participants were assayed in three batches for 12 biomarkers and 3 biomarker ratios. Batch differences were assessed using Bland-Altman plot, paired t test, Pitman-Morgan test, and linear regression. Generalized linear models were applied to convert CSF values between batches. Results: We found statistically significant batch differences for all biomarkers and ratios, except that neurofilament light was comparable between batches 1 and 2. The conversion models generally had high R2 except for converting P-tau between batches 1 and 3. Discussion: Between-batch conversion allows harmonized CSF values to be used in the same analysis. Such method may be applied to adjust for other sources of variability in measuring CSF or other types of biomarkers

Cardiorespiratory Fitness Modifies Influence of Sleep Problems on Cerebrospinal Fluid Biomarkers in an At-Risk Cohort

Background: Previous studies indicate that cardiorespiratory fitness (CRF) and sleep are each favorably associated with Alzheimer’s disease (AD) pathophysiology, including reduced amyloid-β (Aβ) and tau pathology. However, few studies have examined CRF and sleep in the same analysis. Objective: To examine the relationship between sleep and core AD cerebrospinal fluid (CSF) biomarkers among at-risk healthy late-middle-aged adults and determine whether CRF modifies this association. Methods: Seventy-four adults (age = 64.38±5.48, 68.9% female) from the Wisconsin Registry for Alzheimer’s Prevention participated. Sleep was evaluated using the Medical Outcomes Study Sleep Scale, specifically the Sleep Problems Index I (SPI), which incorporates domains of sleep disturbance, somnolence, sleep adequacy, and shortness of breath. Higher scores indicate greater sleep problems. To assess CRF, participants underwent a graded exercise test. CSF was collected via lumbar puncture, from which Aβ42, total-tau (t-tau), and phosphorylated-tau (p-tau) were immunoassayed. Regression analyses examined the association between SPI and CSF biomarkers, and the interaction between SPI and CRF on these same biomarkers, adjusting for relevant covariates. Results: Higher SPI scores were associated with greater p-tau (p = 0.027) and higher t-tau/Aβ42 (p = 0.021) and p-tau/Aβ42 (p = 0.009) ratios. Analyses revealed significant SPI*CRF interactions for t-tau (p = 0.016), p-tau (p = 0.008), and p-tau/Aβ42 (p = 0.041); with a trend for t-tau/Aβ42 (p = 0.061). Specifically, the relationship between poorer sleep and these biomarkers was significant among less fit individuals, but not among those who were more fit. Conclusion: In a late-middle-aged at-risk cohort, CRF attenuated the association between poor sleep and levels of select CSF biomarkers. This suggests fitness may play an important role in preventing AD by protecting against pathology, even in impaired sleep

Moderate intensity physical activity associates with CSF biomarkers in a cohort at risk for Alzheimer's disease

INTRODUCTION: Alzheimer's disease (AD) is characterized by the presence of amyloid β (Aβ) plaques, neurofibrillary tangles, and neurodegeneration, evidence of which may be detected in vivo via cerebrospinal fluid (CSF) sampling. Physical activity (PA) has emerged as a possible modifier of these AD-related pathological changes. Consequently, the aim of this study was to cross-sectionally examine the relationship between objectively measured PA and CSF levels of Aβ42 and tau in asymptomatic late-middle-aged adults at risk for AD. METHODS: Eighty-five cognitively healthy late-middle-aged adults (age = 64.31 years, 61.2% female) from the Wisconsin Registry for Alzheimer's Prevention participated in this study. They wore an accelerometer (ActiGraph GT3X+) for one week to record free-living PA, yielding measures of sedentariness and various intensities of PA (i.e., light, moderate, and vigorous). They also underwent lumbar puncture to collect CSF, from which Aβ42, total tau, and phosphorylated tau were immunoassayed. Regression analyses were used to examine the association between accelerometer measures and CSF biomarkers, adjusting for age, sex, and other relevant covariates. RESULTS: Engagement in moderate PA was associated with higher Aβ42 (P = .008), lower total tau/Aβ42 (P = .006), and lower phosphorylated tau/Aβ42 (P = .030). In contrast, neither light nor vigorous PA was associated with any of the biomarkers. Increased sedentariness was associated with reduced Aβ42 (P = .014). DISCUSSIONS: In this cohort, moderate PA, but not light or vigorous, was associated with a favorable AD biomarker profile, while sedentariness was associated with greater Aβ burden. These findings suggest that a physically active lifestyle may play a protective role against the development of AD

Cardiorespiratory fitness alters the influence of a polygenic risk score on biomarkers of AD

OBJECTIVE: To examine whether a polygenic risk score (PRS) derived from APOE4, CLU, and ABCA7 is associated with CSF biomarkers of Alzheimer disease (AD) pathology and whether higher cardiorespiratory fitness (CRF) modifies the association between the PRS and CSF biomarkers. METHODS: Ninety-five individuals from the Wisconsin Registry for Alzheimer's Prevention were included in these cross-sectional analyses. They were genotyped for APOE4, CLU, and ABCA7, from which a PRS was calculated for each participant. The participants underwent lumbar puncture for CSF collection. β-Amyloid 42 (Aβ42), Aβ40, total tau (t-tau), and phosphorylated tau (p-tau) were quantified by immunoassays, and Aβ42/Aβ40 and tau/Aβ42 ratios were computed. CRF was estimated from a validated equation incorporating sex, age, body mass index, resting heart rate, and self-reported physical activity. Covariate-adjusted regression analyses were used to test for associations between the PRS and CSF biomarkers. In addition, by including a PRS×CRF term in the models, we examined whether these associations were modified by CRF. RESULTS: A higher PRS was associated with lower Aβ42/Aβ40 (p < 0.001), higher t-tau/Aβ42 (p = 0.012), and higher p-tau/Aβ42 (p = 0.040). Furthermore, we observed PRS × CRF interactions for Aβ42/Aβ40 (p = 0.003), t-tau/Aβ42 (p = 0.003), and p-tau/Aβ42 (p = 0.001). Specifically, the association between the PRS and these CSF biomarkers was diminished in those with higher CRF. CONCLUSIONS: In a late-middle-aged cohort, CRF attenuates the adverse influence of genetic vulnerability on CSF biomarkers. These findings support the notion that increased cardiorespiratory fitness may be beneficial to those at increased genetic risk for AD