Citations

Purpose of review Increasing evidence suggests that epigenetic regulation plays a central role in chronic rhinosinusitis pathogenesis, heterogeneity, and treatment response. This review summarizes current knowledge of epigenetics in CRS pathogenesis, their role in endotype differentiation, and potential as diagnostic and therapeutic targets. Recent findings Distinct epigenetic signatures have been identified across CRS subtypes. Hypermethylation of TSLP and differential regulation of FZD5, IL8, and EMT-related genes distinguish eosinophilic CRSwNP from other phenotypes. Specific microRNAs (miR-941, miR-21, miR-125b, miR-155) correlate with disease severity, tissue eosinophilia, and corticosteroid responsiveness, highlighting their utility as noninvasive biomarkers. Experimental data suggest that targeting DNMTs or HDACs may reverse pathogenic remodeling. Emerging therapeutic approaches – such as biologics modulating epigenetically controlled cytokines (e.g. tezepelumab) and engineered extracellular vesicle-based miRNA delivery – illustrate translational promise. Summary Epigenetic mechanisms critically influence CRS pathogenesis and clinical variability. Their modulation offers novel opportunities for biomarker discovery, disease stratification, and personalized therapy. Future research should focus on standardizing epigenetic profiling methodologies, validating candidate biomarkers in diverse populations, and integrating multiomics and single-cell approaches to uncover cell-specific regulatory networks. These advances may enable precision medicine in CRS, bridging the gap between molecular mechanisms and targeted clinical management.

Abstract Background Aging and dementia are generally associated with lower metabolism in gray matter on FDG‐PET and have been widely studied. However, white matter (WM) metabolic changes remain understudied. We investigated the metabolic changes in WM associated with aging and dementia and their relationships with established Alzheimer's Disease (AD) biomarkers and cognitive outcomes. Method We analyzed data from 3,169 participants (72 ± 9 years; 53% male; 65% cognitively unimpaired) enrolled in the Mayo Clinic Study of Aging (MCSA) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). All participants underwent baseline MRI, amyloid‐PET, and FDG‐PET scans, as well as neuropsychological evaluations, with at least one clinical follow‐up. Voxel‐wise multiple regression analysis identified WM metabolic changes associated with global cognition in cognitively unimpaired MCSA participants ( n = 1,754). Univariate analyses and structural equation models were applied to elucidate the driving factors underlying the WM metabolic changes in MCSA data. Multiple regression and linear mixed‐effects models evaluated the explanatory utility of WM metabolism for baseline global cognition and cognitive decline in both cohorts. In a subset of MCSA participants, we evaluated neurite density index from diffusion MRI as a surrogate of WM health and glial fibrillary acidic protein (GFAP) as a surrogate of neuroinflammation to understand underlying mechanisms. Result We identified an atypical WM signature (AWM‐Signature) in the anterior and superior corona radiata, where glucose metabolism increased as cognitive performance worsened (Figure 1). Hypermetabolism in AWM‐Signature was related to increased age, amyloidosis, vascular disease, and neuroinflammation, as well as decreasing WM neurite density in the same regions (Figure 2). Hypermetabolism in AWM‐Signature regions predicted faster future cognitive decline, even after accounting for demographics, amyloid, and vascular disease metrics. The results observed in the AWM‐Signature regions were consistently in the opposite direction of the associations seen with gray matter and typical WM regions. Conclusion We found unexpected metabolism increases in corona radiata, a hub that carries significant portion of the brain's neural traffic, with aging and disease which likely indicates a compensatory response. These changes may be useful cognitive resilience measures and require further investigation to understand their role in maintaining cognitive function.

Abstract Background Chronic disease conditions lead to brain changes elevating dementia risk. We hypothesized that tissue microstructural changes caused by type 2 diabetes mellitus (T2DM) and hypertension could be effectively captured using an advanced diffusion MRI technique, Neurite Orientation Dispersion and Density Imaging (NODDI). Our goal was to evaluate the usefulness of composite NODDI scores, customized for increased hemoglobin (Hb) A1c and systolic blood pressure as predictors of cognition and compare their performance to other measures typically used to assess dementia risk. Method We collected multi‐shell diffusion MR on 1024 Mayo Clinic Study of Aging participants. NODDI measures (neurite density index (NDI), orientation dispersion index (ODI), and free water fraction (FWF)) in gray matter (GM) and white matter (WM) regions were estimated. To identify brain regions susceptible to both conditions, a multiple linear regression model was fitted for each NODDI metric, using hemoglobin (Hb) A1c (in N = 305 participants) or systolic blood pressure ( N = 906) as predictor, with age, sex, and body mass index (BMI) as covariates. Event‐based modeling was performed with the identified NODDI metrics to investigate the chronological pattern along the course of chronic condition development from this cross‐sectional dataset. Composite metrics were created as a weighted sum of susceptible NODDI metrics. We evaluated the impact of both conditions on cognition using gradient boosting models incorporating composite metrics, additional brain measurements, and demographics. Result Increased HbA1c impacts both GM and WM NODDI relatively evenly, whereas increased systolic blood pressure related NODDI changes were mainly seen in WM (data not shown). With increased HbA1c, the earliest changes were observed in GM ODI, followed by changes in the pons and cortical FWF (Figure 1A). With increased systolic blood pressure, the earliest changes occurred in association fibers and middle cerebellar peduncle, followed by FWF change in lobar and projection WM fibers (Figure 1B). Average feature importance from 100 gradient boosting models for cognition prediction suggests that diabetes‐induced GM changes play a moderately important role in cognitive decline (Figure 2). Conclusion Chronic medical conditions, especially T2DM, result in brain changes that are captured by NODDI and contribute moderately to cognitive performance.

Abstract Background Clinically available plasma p ‐tau217 assays may be utilized in the determination of eligibility for amyloid‐lowering therapies. Our institution recently introduced a plasma p ‐tau217 assay in clinical practice using a two‐cutpoint approach that optimizes the accuracy while minimizing false positive risk and categorizing ≤20% of results as intermediate. In this study, we prospectively evaluate the performance of a plasma p ‐tau217 assay for detection of amyloid pathology using these predefined cutpoints. Method Patients recruited were being considered for lecanemab therapy at a tertiary care subspecialty clinic. Plasma p ‐tau217 was measured using the clinically available Fujirebio Lumipulse p ‐tau217 assay at Mayo Clinic, and results (pg/mL) were classified as either negative (≤0.185), intermediate (0.186–0.324) or positive (≥0.325). Amyloid pathology was determined by amyloid‐PET and/or CSF p ‐tau181/Aβ42. Result Ninety‐three patients were recruited between November 2023 and December 2024. Of these, 49 underwent amyloid‐PET, 4 had CSF p ‐tau181/Aβ42 measurements, and 40 had both PET and CSF results (with 3/40 discordant cases), for use in the assessment of amyloid pathology. The three discordant cases were considered amyloid positive for purposes of plasma p ‐tau217 comparison. Overall amyloid positivity was 90%. Plasma p ‐tau217 results were positive in 83% (77/93), negative in 6% (6/93), and intermediate in 11% (10/93) of patients. An elevated p ‐tau217 predicted the presence of amyloid positivity with a diagnostic accuracy of 96% (95% CI 90% − 99%). In the intermediate range, 80% of patients were positive for amyloid pathology. In patients with a definitive p ‐tau217 result (positive or negative), the positive and negative predictive values were 97% and 83%. There were three patients with discordant results: one PET+/p‐tau217‐, one PET‐/p‐tau217+, and one CSF‐/p‐tau217+. Clinical presentation of these discordant cases was examined, and relevant findings will be discussed. Conclusion The Lumipulse plasma p ‐tau217 assay exhibited acceptable diagnostic accuracy for the determination of amyloid pathology when compared to either amyloid‐PET or CSF p ‐tau181/Aβ42. This prospective study confirms the utility a two‐cutpoint approach for interpreting plasma p ‐tau217 for the assessment of amyloid pathology eligibility for amyloid‐lowering therapies in a heterogenous clinical cohort.

Abstract Background The amygdala is closely connected to the olfactory bulb and involved in olfactory processing as well. It is a particularly susceptible region that accumulates a‐synuclein pathology in Parkinson's disease (PD). Our previous work revealed olfactory bulb gene alterations related to neuroinflammation, and neurotransmitter dysfunction to be associated with olfactory function. We aimed to extend this work and assess gene expression changes, affected pathways and co‐expression networks by transcriptomic profiling of the amygdala in subjects with and without clinicopathologically defined PD. Method Bulk RNA sequencing was performed on frozen human amygdala of 20 PD and 20 controls without dementia or any other neurodegenerative disorder, from the Arizona Study of Aging and Neurodegenerative Disorders. Result Differential expression analysis, corrected for age, sex and post‐mortem interval revealed 40 significantly differentially expressed genes (DEGs) in PD. Downregulated genes were mainly related to altered hemoglobin expression while upregulated genes included inflammatory markers and glutamine transporter. Significantly enriched pathways were involved in oxygen and carbon dioxide transport, cellular oxidant detoxification and regulation of glutamine secretion. Cell enrichment revealed these genes to be mainly expressed in neurons. Co‐expression network analysis using Weighted correlation network analysis (WGCNA ) subsequently identified four significant modules correlated with both PD and premortem olfactory dysfunction which were involved in pathways related to neuroinflammatory processes, mitochondrial, endoplasmic reticulum and lysosomal dysfunction. Conclusion These preliminary results suggest cellular alterations in the amygdala related to mitochondrial dysfunction, altered oxygen homeostasis, oxidative stress, inflammation as well as glutamatergic neurotransmitter dysfunction that may contribute to neurodegeneration in PD.

Abstract Background Recent technological advances have enhanced the precision of blood‐based multiplex proteomics and their application in Alzheimer's disease. However, these approaches remain underutilized in frontotemporal lobar degeneration (FTLD). Familial FTLD cohorts offer a unique opportunity to study presymptomatic periods of disease that cannot be studied in sporadic cases. We leveraged NUcleic acid Linked Immuno‐Sandwich Assay (NULISAseq) to identify blood‐detectable proteins that change prior to symptom onset in familial FTLD. Method 120 FTLD mutation carriers (40 C9orf72 , 40 GRN , 40 MAPT ) and 40 age and sex‐matched noncarrier controls from the ALLFTD Consortium completed blood draws and clinical assessment. Targeted plasma proteomics was performed via NUcleic acid Linked Immuno‐Sandwich Assay (NULISAseq; 132 proteins). Disease age estimates measuring predicted symptom onset were derived from a validated model incorporating FTLD gene‐specific clinical, neuroimaging, and biomarker data. Mass linear regression models identified disease age ‘thresholds’ where individual proteins significantly diverged between each mutation carrier group and controls. NULISAseq targets were validated against orthogonal assays, specifically Simoa (plasma) and SomaScan (cerebrospinal fluid [CSF]). Result Compared to controls, 14 plasma proteins significantly diverged ( p <.05) in C9orf72 , 24 in GRN , and 13 in MAPT . Beyond NEFL, 10 additional proteins significantly diverged in more than one mutation group, including markers of synaptic function (NPTX2, NPTXR) and vascular integrity (PGF) that deviated prior to estimated symptom onset (disease age range: ‐30 to 0). Proteins with gene‐specific signals included GFAP (increased in GRN at disease age ‐17), ENO2 (decreased in C9orf72 at disease age ‐7), and FLT1 (increased in MAPT at disease age ‐6). Plasma NULISA‐based NEFL and GFAP showed strong concordance when measured via plasma Simoa ( r s>0.88) and were among 38 targets with significant concordance when measured via CSF SomaScan ( r range: 0.16 to 0.75, p s<.05). Conclusion Alterations in plasma protein abundance are measurable in familial FTLD prior to predicted symptom onset. The validity and brain‐based relevance of blood‐detectable NULISA targets is bolstered by the observed convergence with plasma Simoa and CSF SomaScan. Replication of top hits in larger familial and sporadic FTLD sample sizes is warranted to determine generalizability and suitability for clinical trials.

Abstract Background Cerebral amyloid angiopathy (CAA), characterized by the accumulation of amyloid‐beta in the cerebrovasculature, affects blood vessel integrity leading to brain hemorrhages and an accelerated cognitive decline in Alzheimer's Disease (AD) patients. Our previous genome‐wide association study (GWAS) identified a LINC‐PINT splice variant associated with lower CAA levels in individuals without the APOE e4 allele and higher levels of LINC‐PINT expression in the brain of AD donors. In this study, we expand our GWAS to include additional donors with AD and those lacking significant AD neuropathology (non‐AD), with available CAA scores. Method In our prior study we assessed 853 AD donors. We expanded this by addition of genetic data from 550 AD and 502 non‐AD donors from the Mayo Clinic Brain Bank, scored for CAA. We performed QC and imputation (TOPMED) of all datasets. We conducted GWAS in AD only ( N = 1,363), non‐AD only, and all donors ( N = 1,865) by testing imputed variant dosages for association with square root transformed CAA using linear regression, adjusting for relevant covariates. To assess associations in the context of major CAA risk factors, we performed interaction analysis with APOEe4 presence and sex; and pursued stratified analyses. Result Variants at the APOE locus were identified as the most significant in our study. In addition, several other variants approached genome‐wide significance after adjusting for AD neuropathology (Braak stage and Thal phase). The LINC‐PINT splice variant remained associated with lower CAA scores in AD donors without the APOEe4 risk allele . To enhance the robustness of our findings, we are pursuing further expansion of our study cohort to include other available datasets. To explore putative functional consequences of key variants we are collecting peripheral gene expression measures in participants from Mayo Clinic with neuroimaging measures including microhemorrhages. Conclusion We expect this study will provide further insights into the genetic architecture underlying risk for CAA, both in the context of significant AD pathology, and without. Characterization of genetic variants and their functional outcomes may lead to new avenues of research aimed at identifying biomarkers and therapies to treat CAA, a common co‐pathology in those with and without AD.

Abstract Background Alzheimer's disease (AD) blood biomarkers (BBMs) are increasingly used in clinical trials and clinical practice. However, widespread adoption of BBMs requires further understanding of factors that might influence the interpretation of these biomarkers which would allow for the development of standardized sample collection protocols. For example, studies of the effect of fasting on AD BBM concentrations have yielded inconsistent findings. In this study, we evaluated plasma concentrations of amyloid‐beta(Aβ) 42, Aβ40, phosphorylated Tau ( p ‐tau) 181, p ‐tau217, and neurofilament light chain (NfL) in cognitively normal individuals under fasting and non‐fasting conditions. Method EDTA‐plasma was collected from healthy donors ( n = 14; age >55yrs old) two weeks apart, at the same time of day. The first sample collection was under fasting conditions in which donors did not eat or drink (except water) for at least 12 hours prior to collection. The second sample collection was under non‐fasting conditions in which donors were instructed to eat a meal in the morning, approximately half an hour prior to collection. Plasma Aβ42, Aβ40, p ‐tau181, p ‐tau217, and NfL concentrations were measured on the Fujirebio Lumipulse G1200 analyzer. Wilcoxon signed‐rank test was used to compare values between the fasting and non‐fasting results. Spearman's rank correlation was used to assess biomarker correlation between fasting status. Result Moderate to strong correlation was observed between the fasting and non‐fasting measurements: p ‐tau217 (r s : 0.86), p ‐tau181 (r s : 0.89), NfL (r s : 0.94), p ‐tau217/Aβ42 (r s : 0.80), Aβ42/40 (r s : 0.66), Aβ42 (r s : 0.77), and Aβ40 (r s : 0.92). Average percent difference between the 2 conditions was: p ‐tau217 27%, p ‐tau181 6%, NfL 9%, p ‐tau217/ Aβ42 25%, Aβ42/40 4%, Aβ42 2%, and Aβ40 ‐6%. Statistically significant differences ( p ≤ 0.05) between fasting and non‐fasting measurements were observed for p ‐tau217, NfL, p ‐tau217/Aβ42, Aβ42/Aβ40, and Aβ42; but not for Aβ40 or p ‐tau181. Conclusion This data suggests that for some AD BBMs, there may be statistically significant differences in concentrations of samples collected in fasting versus non‐fasting conditions. However, further studies are needed to determine if the observed differences may affect the clinical interpretation of these BBMs in individuals with amyloid related pathology.

Abstract Background Individuals meeting neuropathological criteria for Alzheimer's disease (AD) can exhibit distinct clinical syndromes, suggesting region‐specific neuronal susceptibilities to tau pathology. Amnestic AD cases show greater tau burden in CA1, logopenic variant primary progressive aphasia (lvPPA) in the superior temporal gyrus (STG), and posterior cortical atrophy (PCA) in the occipital cortex. We hypothesize that by contrasting these AD variants and examining their respective pathological hotspots, we can identify the most vulnerable neuronal subpopulations ‐ those that exhibit the greatest reduction in their specific hotspot area compared to other regions. Using single‐nucleus RNA sequencing (snRNA‐seq), we investigate the molecular mechanisms driving this selective neuronal vulnerability. Methods We performed snRNA‐seq using the Chromium Single Cell 3′ (10X Genomics, USA) platform on nuclei extracted from the CA1 hippocampal sector, posterior STG, and occipital cortex of postmortem brain tissue from 68 individuals. The cohort included 24 amnestic AD cases, 11 lvPPA cases, and 6 PCA cases (all meeting A3B3C3 pathological criteria), along with 27 healthy controls (A≤1B≤1C≤1). Bioinformatics analysis was conducted using the Seurat library in R. Cell subpopulation comparisons were performed using the Wald statistical test, with p ‐values < .05 considered significant. Results Following quality control, we recovered over 1.58 million nuclei, with an average of 2,129 genes detected per nucleus. UMAP clustering identified 17 inhibitory and 16 excitatory neuronal subpopulations across all three regions. Among these, one excitatory subpopulation was highly enriched in CA1. We identified six excitatory subpopulations (Exc‐subs) exhibiting region‐specific vulnerability. Notably, the Ex L2/3 IT RORB GRIN1 subpopulation showed pronounced vulnerability in CA1 among amnestic cases, in STG among amnestic and lvPPA cases, and displayed a vulnerability trend in the occipital cortex among PCA cases, though not statistically significant. Conclusion Our findings suggest that a specific excitatory neuron subpopulation exhibits heightened susceptibility across highly tau‐affected regions in amnestic and atypical AD syndromes, including PCA. Ongoing validation using quantitative pathology aims to confirm these findings, and further case analyses will refine our understanding of the molecular drivers of neuronal vulnerability in AD.

Abstract Background Individuals with coexisting Alzheimer's disease (AD) and disorders of CSF dynamics such as normal‐pressure hydrocephalus (NPH) have lower CSF Aβ42 levels, which can confound interpretation of AD CSF‐biomarkers. However, little is known about how CSF dynamics influences plasma AD biomarkers. The objective of this study was to determine whether mass spectrometry‐based blood tests for AD are associated with disproportionately enlarged subarachnoid space hydrocephalus (DESH) on MRI. Method 509 Individuals from the Mayo Clinic Study of Aging, with MRI, 11C‐Pittsburgh compound B (Aβ) PET scans, and plasma phosphorylated‐tau protein 217, Aβ40 and Aβ42 were included. We performed an age‐adjusted logistic regression to determine whether abnormal values of p ‐Tau 217 (Abnormal if >1.55 pg/mL), %p‐tau217 defined as the ratio of phosphorylated Tau217 to non‐phosphorylated tau x 100% (Abnormal if >1.55%), Aβ42 (Abnormal if <41.5 pg/mL), and Aβ42/40 ratio (Abnormal if <0.094) were associated with the presence of DESH, as classified by a previously validated automated algorithm. Result Thirty‐two participants were classified as DESH‐positive. The median [IQR] age was 76.8 yrs [70.6, 82.9] for participants with DESH and 72.4 [59.3, 85.5] without DESH (Table 1). An abnormal plasma Aβ42 was associated with DESH (OR, 2.56 [1.19, 5.74], p = 0.018), but having an abnormal Aβ42/40 ratio (OR 2.01 [0.94, 4.56], p = 0.079) was not. There was no association between being DESH‐positive and an abnormal plasma p ‐tau217 (OR 1.30 [0.51, 3.09], p = 0.560) or with abnormal %plasma p ‐tau217 (OR 1.82 [0.74, 4.20], p = 0.17) (Figure 1). Subgroup analysis showed that only those participants who had an abnormal Aβ42 and positive amyloid PET (≥25 Centiloids) showed an association with DESH compared to biomarker‐ and PET‐negative participants (OR 3.10 [1.15, 8.43], p = 0.024 ) . Conclusion Understanding how CSF dynamics affect plasma biomarkers is critical for implementation. The relationship between lower Aβ42 and DESH is expected based on prior CSF studies, which can be addressed by using an amyloid ratio. p ‐tau217 shows robustness against DESH, making it a suitable biomarker in cases of abnormal cerebrospinal fluid dynamics although validation in a more severe CSF dynamics group is warranted.