Neuroimaging and biomarker evidence of neurodegeneration in asthma

Background: Epidemiological studies have shown that Alzheimer’s disease and related dementias (ADRD) are seen more frequently with asthma, especially with greater asthma severity or exacerbation frequency. // Objective: To examine the changes in brain structure that may underlie this phenomenon, we examined diffusion-weighted magnetic resonance imaging (dMRI) and blood-based biomarkers of AD (p-Tau181), neurodegeneration (NfL) and glial activation (GFAP). // Methods: dMRI data were obtained in 111 individuals with asthma, ranging in disease severity from mild to severe, and 135 healthy controls. Regression analyses were used to test the relationships between asthma severity and neuroimaging measures, as well as AD pathology, neurodegeneration and glial activation, indexed by plasma p-Tau181, NfL and GFAP respectively. Additional relationships were tested with cognitive function. // Results: Asthma participants had widespread and large magnitude differences in several dMRI metrics, which were indicative of neuroinflammation and neurodegeneration, and robustly associated with GFAP and to a lesser extent, with NfL. The AD biomarker p-Tau181 was only minimally associated with neuroimaging outcomes. Further, asthma severity was associated with deleterious changes in neuroimaging outcomes, which in turn, were associated with slower processing speed, a test of cognitive performance. // Conclusion: These data suggest that asthma, particularly when severe, is associated with characteristics of neuroinflammation and neurodegeneration and may be a potential risk factor for neural injury and cognitive dysfunction. The results suggest a need to determine how asthma may affect brain health and whether treatment directed toward characteristics of asthma associated with these risks can mitigate these effects

Alzheimer's disease biomarkers in Black and non-Hispanic White cohorts: A contextualized review of the evidence

Black Americans are disproportionately affected by dementia. To expand our understanding of mechanisms of this disparity, we look to Alzheimer's disease (AD) biomarkers. In this review, we summarize current data, comparing the few studies presenting these findings. Further, we contextualize the data using two influential frameworks: the National Institute on Aging–Alzheimer's Association (NIA-AA) Research Framework and NIA's Health Disparities Research Framework. The NIA-AA Research Framework provides a biological definition of AD that can be measured in vivo. However, current cut-points for determining pathological versus non-pathological status were developed using predominantly White cohorts—a serious limitation. The NIA's Health Disparities Research Framework is used to contextualize findings from studies identifying racial differences in biomarker levels, because studying biomakers in isolation cannot explain or reduce inequities. We offer recommendations to expand study beyond initial reports of racial differences. Specifically, life course experiences associated with racialization and commonly used study enrollment practices may better account for observations than exclusively biological explanations

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

Association of Amyloid Pathology With Myelin Alteration in Preclinical Alzheimer Disease

IMPORTANCE: The accumulation of aggregated β-amyloid and tau proteins into plaques and tangles is a central feature of Alzheimer disease (AD). While plaque and tangle accumulation likely contributes to neuron and synapse loss, disease-related changes to oligodendrocytes and myelin are also suspected of playing a role in development of AD dementia. Still, to our knowledge, little is known about AD-related myelin changes, and even when present, they are often regarded as secondary to concomitant arteriosclerosis or related to aging. OBJECTIVE: To assess associations between hallmark AD pathology and novel quantitative neuroimaging markers while being sensitive to white matter myelin content. DESIGN, SETTING AND PARTICIPANTS: Magnetic resonance imaging was performed at an academic research neuroimaging center on a cohort of 71 cognitively asymptomatic adults enriched for AD risk. Lumbar punctures were performed and assayed for cerebrospinal fluid (CSF) biomarkers of AD pathology, including β-amyloid 42, total tau protein, phosphorylated tau 181, and soluble amyloid precursor protein. We measured whole-brain longitudinal and transverse relaxation rates as well as the myelin water fraction from each of these individuals. MAIN OUTCOMES AND MEASURES: Automated brain mapping algorithms and statistical models were used to evaluate the relationships between age, CSF biomarkers of AD pathology, and quantitative magnetic resonance imaging relaxometry measures, including the longitudinal and transverse relaxation rates and the myelin water fraction. RESULTS: The mean (SD) age for the 19 male participants and 52 female participants in the study was 61.6 (6.4) years. Widespread age-related changes to myelin were observed across the brain, particularly in late myelinating brain regions such as frontal white matter and the genu of the corpus callosum. Quantitative relaxometry measures were negatively associated with levels of CSF biomarkers across brain white matter and in areas preferentially affected in AD. Furthermore, significant age-by-biomarker interactions were observed between myelin water fraction and phosphorylated tau 181/β-amyloid 42, suggesting that phosphorylated tau 181/β-amyloid 42 levels modulate age-related changes in myelin water fraction. CONCLUSIONS AND RELEVANCE: These findings suggest amyloid pathologies significantly influence white matter and that these abnormalities may signify an early feature of the disease process. We expect that clarifying the nature of myelin damage in preclinical AD may be informative on the disease’s course and lead to new markers of efficacy for prevention and treatment trials

Cohort study of electroencephalography markers of amyloid-tau-neurodegeneration pathology

Electroencephalography signatures of amyloid-β, tau and neurodegenerative pathologies would aid in screening for, tracking progression of, and critically, understanding the pathogenesis of dementia. We hypothesized that slowing of the alpha peak frequency, as a signature of hyperpolarization-activated cyclic nucleotide gated ‘pacemaker’ channel activity, would correlate with amyloid and tau pathology burden measured by amyloid (Pittsburgh Compound B) and tau (MK-6240) positron emission tomography or CSF biomarkers. We also hypothesized that EEG power would be associated with neurodegeneration (CSF neurofilament light and hippocampal volume). Wakeful high-density EEG data were collected from 53 subjects. Both amyloid-β and tau pathology were associated with slowing in the alpha peak frequency [Pittsburgh Compound B (+) vs. Pittsburgh Compound B (−) subjects, P = 0.039 and MK-6240 (+) vs. MK-6240 (−) subjects, P = 0.019]. Furthermore, slowing in the peak alpha frequency correlated with CSF Aβ42/40 ratio (r2 = 0.270; P = 0.003), phosphoTau (pTau181, r2 = 0.290; P = 0.001) and pTau181/Aβ42 (r2 = 0.343; P < 0.001). Alpha peak frequency was not associated with neurodegeneration. Higher CSF neurofilament light was associated with lower total EEG power (r2 = 0.136; P = 0.018), theta power (r2 = 0.148; P = 0.014) and beta power (r2 = 0.216; P = 0.002); the latter was also associated with normalized hippocampal volume (r2 = 0.196; P = 0.002). Amyloid-tau and neurodegenerative pathologies are associated with distinct electrophysiological signatures that may be useful as mechanistic tools and diagnostic/treatment effect biomarkers in 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

The gut microbiota-derived metabolite trimethylamine N-oxide is elevated in Alzheimer's disease

BACKGROUND: Trimethylamine N-oxide (TMAO), a small molecule produced by the metaorganismal metabolism of dietary choline, has been implicated in human disease pathogenesis, including known risk factors for Alzheimer's disease (AD), such as metabolic, cardiovascular, and cerebrovascular disease. METHODS: In this study, we tested whether TMAO is linked to AD by examining TMAO levels in cerebrospinal fluid (CSF) collected from a large sample (n = 410) of individuals with Alzheimer's clinical syndrome (n = 40), individuals with mild cognitive impairment (MCI) (n = 35), and cognitively-unimpaired individuals (n = 335). Linear regression analyses were used to determine differences in CSF TMAO between groups (controlling for age, sex, and APOE ε4 genotype), as well as to determine relationships between CSF TMAO and CSF biomarkers of AD (phosphorylated tau and beta-amyloid) and neuronal degeneration (total tau, neurogranin, and neurofilament light chain protein). RESULTS: CSF TMAO is higher in individuals with MCI and AD dementia compared to cognitively-unimpaired individuals, and elevated CSF TMAO is associated with biomarkers of AD pathology (phosphorylated tau and phosphorylated tau/Aβ42) and neuronal degeneration (total tau and neurofilament light chain protein). CONCLUSIONS: These findings provide additional insight into gut microbial involvement in AD and add to the growing understanding of the gut-brain axis

Differential effects of neurodegeneration biomarkers on subclinical cognitive decline

Introduction: Neurodegeneration appears to be the biological mechanism most proximate to cognitive decline in Alzheimer's disease. We test whether t-tau and alternative biomarkers of neurodegeneration—neurogranin and neurofilament light protein (NFL)—add value in predicting subclinical cognitive decline. Methods: One hundred fifty cognitively unimpaired participants received a lumbar puncture for cerebrospinal fluid and at least two neuropsychological examinations (mean age at first visit = 59.3 ± 6.3 years; 67% female). Linear mixed effects models were used with cognitive composite scores as outcomes. Neurodegeneration interactions terms were the primary predictors of interest: age × NFL or age × neurogranin or age × t-tau. Models were compared using likelihood ratio tests. Results: Age × NFL accounted for a significant amount of variation in longitudinal change on preclinical Alzheimer's cognitive composite scores, memory composite scores, and learning scores, whereas age × neurogranin and age × t-tau did not. Discussion: These data suggest that NFL may be more sensitive to subclinical cognitive decline compared to other proposed biomarkers for neurodegeneration

Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status

Background: Alzheimer’s disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical. Methods: Participants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination). Results: Using internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone. Conclusion: Using a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged