Kandimalla, Mahathi

Abstract INTRODUCTION Understanding neuroinflammation across the Alzheimer's disease (AD) spectrum is essential to elucidate disease mechanisms and individualize therapy. METHODS Human microglial translocator protein (TSPO) expression under inflammatory stimuli was assessed by immunoblot experiments. Ninety‐six participants were enrolled across four groups: cognitively unimpaired amyloid (CU A) + and −, mild cognitive impaired (MCI) A+, and Alzheimer's disease dementia (ADD) A+. Neuroinflammation using 11 C‐ER176 TSPO positron emission tomography (PET) was compared to amyloid and tau PET. Correlations between neuroinflammation, amyloid, and tau pathology were examined across disease stages. RESULTS TSPO was upregulated in human microglia under AD‐like inflammatory conditions. Neuroinflammation, defined by PET TSPO, increased in CU A+ participants and became more widespread with increasing disease severity, aligning with worsening amyloid and tau pathology. Associations with tau were particularly extensive in temporal and parietal regions. DISCUSSION These findings suggest probable amyloid association with early microglial activation, while tau pathology is closely tied to wider distribution of neuroinflammation. Highlights TSPO expression increases in human microglia under AD‐like inflammation. 11 C‐ER176 PET shows stage‐dependent neuroinflammation across the AD spectrum. Neuroinflammation overlaps with tau and is more widespread in amyloid‐positive individuals. Activity peaks in MCI, stabilizes later, and relates to vascular and neurodegenerative changes.

Abstract Background The tau PET imaging with 18F‐flortacipir (18F‐FTP) has focused interest in accurately tracking longitudinal tau changes in Alzheimer's disease [1]. Thus, minimizing variability is critical. Off‐target signal has the potential to complicate interpretation of tau‐PET imaging due to potential spillover or bleed‐in effects, with increased effects seen in later stages of Alzheimer's due to cerebral atrophy and proximity of off‐target areas to relevant cortical areas[2]. Previously, we demonstrated the effect of uptake period activity on 18F‐FTP signal. With increasing recent interest in demographic factors that may affect off‐target binding, we investigated the effect of age in extra‐cerebral off‐target signal in 18F‐FTP PET imaging. Method Standard 18F‐FTP PET protocol was performed in 330 participants. Two independent readers measured tau uptake in predetermined off‐target regions, including extraocular muscle, meninges, and occipital bone among others. Linear regression models assessed the relationship between participants’ age, sex, and tau uptake values (SUV and SUVr) (SUV = (Tissue radioactivity concentration / Injected dose) / Body weight & SUVr = SUV of target region/ SUV of reference region.) Result Sex had a significant effect on off‐target signal in most brain regions, with variable positive or negative correlation based on area. Notably, SUV in the eyeball‐retina, occipital bone, upper skull meninges all showed significant positive correlation with sex, with ‘male’ status generally associated with lower SUV. The greatest effect of sex was observed in superior skull meninges, occipital bone, and internal carotid artery ( p <0.001). Age showed minimally affected SUV and SUVr in off‐target regions. SUVr values show a significant correlation with SUV values of upper skull meninges in sex. Cognitive status did not significantly affect off‐target SUV. Conclusion We observed that sex significantly affected extra‐brain off‐target signal in 18F‐FTP PET imaging, while age has minimal effect, adding to previous evidence of off‐target binding within brain regions. Further evaluation is necessary to understand the age‐related effects on off‐target regions. As a result, the variability introduced by sex may pose challenges to studying tau accumulation.

Abstract Background Neuroinflammation plays a crucial role in neuronal damage, synaptic dysfunction, and impaired neurogenesis, significantly contributing to Alzheimer's Disease (AD) progression. To address this, we assessed ER176's effectiveness in detecting neuroinflammation in cognitively unimpaired (CU) A–, CU A+, mild cognitive impairment (MCI), and AD participants, with a particular focus on their amyloid and tau status. This research aims to help identify suitable candidates for specialized treatment when adversely impacted by neuroinflammation. Method Participants from the Mayo Clinic Study of Aging were recruited for this study. The study included four participant groups: CU A– ( n = 25), CU A+ ( n = 25), MCI A+ ( n = 25), and AD ( n = 15). We explored the variations in neuroinflammation PET results among different groups. Result When compared to CU A–, both CU A+ and MCI A+ groups (Figure 1) showed greater regional neuroinflammation. AD exhibited more widely affected regions with neuroinflammation (temporal, occipital, and parietal lobes) than CU A‐ over the PVC spectrum (Figure 1). Minimally more neuroinflammation was seen (temporal lobes) in MCI A+ than CU A+ (Figure 1). AD had more widespread regional neuroinflammation vs CU A+ (Figure 1) than in MCI A+ vs CU+. The least difference in neuroinflammation is seen in MCI A+ vs AD (Figure 1). For A+ vs A‐, A+ showed more widespread neuroinflammation (Figure 2). T+ (tau>=1.29) vs T‐ (tau<1.29) showed more neuro inflammation with T+ (Figure 2). Comparisons varied modestly in significance level with PVC method (Figures 1 and 2). Conclusion The findings demonstrate that neuroinflammatory changes are associated with AD pathology. Even at early stages, neuroinflammation is associated with CU+. As the condition progresses, neuroinflammation extends to more brain regions and is associated with increased A+ and T+ pathology in MCI A+ and AD. These results suggest an early and persistent role of neuroinflammation in the progression AD pathology, indicating that therapy options could include early anti‐inflammatory intervention, even prior to clinical symptoms, along with treatment during clinical manifestations. PVC methods used may provide somewhat variable results.

Abstract Background Some data suggest that neuroinflammation may be associated with pro‐inflammatory states in the body. Systemic, proinflammatory cytokines (TNFα, IL‐1, IL‐6, etc.) are produced by a variety of comorbidities. Neuroinflammation has been shown to be associated with the accumulation of amyloid in the brain (Becher, Heneka). We hypothesized that systemic cytokine production could be associated with neuroinflammation and thereby be related to brain amyloid accumulation. This study aims to evaluate the relationship between neuroinflammation, amyloid accumulation and systemic cytokines. Method 90 participants from the Mayo Clinic Study of Aging (MCSA) received a fasting cytokine panel over a 5‐year span where IL‐1, IL‐6, IL‐10, TNFa levels were measured. Participants were divided into four groups: cognitively unimpaired with normal levels of amyloid (CU A‐, n = 25), cognitively unimpaired with elevated amyloid (CU A+, n = 25), and mild cognitively impaired (MCI) with amyloid positive (MCI A+, n = 25), and Alzheimer's disease (AD) with elevated amyloid (AD A+, n = 15). To compare regional standardized uptake value ratio (SUVr) from neuroinflammation PET based on amyloid status (A+ vs A‐) and the four cytokines, Spearman's rank correlation and Fishers r‐to‐z transformations were used to assess pairwise group differences. Result Using Spearman's rank correlation and Fishers r‐to‐z transformations, no strong relationship was found between systemic inflammation and neuroinflammation. While comparing CUA‐ vs CUA+ in Figure 1, three regions (supplementary motor area, frontal superior medial lobe, and middle cingulate cortex) showed a significant difference ( p < 0.05). However, Figure 2 showed an overarching trend bias towards significance across most regions in IL10, IL6, and TNFa. Conclusion Although significant relationships between systemic inflammation, brain amyloid and neuroinflammation were limited, the data show an overarching trend bias in broad brain regions, suggesting that further analyses are needed, possibly with larger sample sizes, to assess the relationship of regional neuroinflammation and amyloid to systemic inflammation. Future analyses could also regress out factors like sex, age, and genotype to further proinflammatory cytokine research.