Citations

AbstractBackgroundTwo main risk factors of Alzheimer’s disease (AD) are aging and APOE‐ε4. However, some individuals remain cognitively normal despite having these risk factors. They are considered “cognitively resilient”. This study aimed to identify molecular factors that confer cognitive resilience in APOE‐ε4 carriers ≥ 80 years of age and may serve as biomarkers.MethodWe applied weighted gene co‐expression network analysis (WGCNA) to generate consensus co‐expression networks from blood of participants in two antemortem cohorts, the Mayo Clinic Study of Aging (MCSA, n=105), and the Alzheimer’s Disease Neuroimaging Initiative (ADNI, n=91), using RNA‐sequencing and microarray data, respectively. We associated these networks with resilience (resilient vs non‐resilient), cognitive endophenotypes and hippocampal volume. Preservation between consensus networks from blood and those derived from postmortem brain tissues of AD and control donors from AMP‐AD (n=1174) was evaluated. We validated the human findings in four AD mouse models. Finally, machine learning models were utilized to discriminate cases (AD+mild cognitive impairment (MCI)) from controls in MCSA, ADNI and ANMerge antemortem cohorts.ResultFour consensus networks were significantly correlated with a memory phenotype (logical memory delayed recall=LMDR) and hippocampal volume in both MCSA and ADNI. Among these, blood expression module M3 was most preserved with the brain transcriptome. M3 was enriched with NDUF hub genes that are involved in the mitochondrial respiratory chain. Expression levels of M3 and many blood NDUFs had significant associations with better LMDR and hippocampal volume. In brain, NDUFs were upregulated in controls compared to AD, and their expression levels were associated with better global cognition and decreased AD neuropathology. Many NDUFs were significantly downregulated in the hippocampus or cortex of AD mice compared to wild‐types. Lastly, models that included blood NDUFs improved diagnostic accuracy of AD+MCI compared to models that only included demographic and risk variables (age, sex, APOE‐ε4) in MCSA, ADNI and ANMerge. In MCSA and ADNI, adding NDUFs’ expression to models that included established blood biomarkers (Aβ42/40, ptau181, NFL) further improved diagnostic accuracy.ConclusionOur results suggest that mitochondrial NDUFs are centrally‐linked peripheral molecular signatures that may be resilience factors against AD and serve as both therapeutic targets and novel diagnostic biomarkers.

AbstractBackgroundUnderstanding the relationship between AβPET and AβCSF biomarkers will define their potential utility in Aβ treatment. Few longitudinal or neuropathological comparisons have been reported. We assessed the relationship of AβPET and AβCSF biomarkers in a large community cohort.MethodParticipants 50+ years with coincident AβPET and AβCSF biomarkers (pTau181/Aβ42, n=505, and Aβ42/40, n=54) were included. Of these participants, a subgroup was identified that had neuropathology data (n=47) of which many had longitudinal AβPET and CSF testing. The relationships of AβPET and CSF biomarkers were assessed cross‐sectionally in all participants and longitudinally in those with autopsy data. Analyses were performed using AβPET Meta‐ROI and AβPET early‐Aβ‐deposition ROIs (ROIs with early Aβ deposition: fusiform, angular, inferior temporal, middle temporal, middle occipital, and calcarine).ResultIn biomarker tests performed at the same time, more participants were AβPET+ and CSF‐ than AβPET‐ and CSF+ using Meta‐ROI AβPET. This discordance occurred more frequently when using early‐Aβ‐deposition regions (Figure 1). Of 47 participants with autopsy data, 35 had Thal stage ≥1. The sensitivity for earliest detection of cortical Aβ neuropathology by AβPET was 89% (31/35) and by CSF was 66%, (23/35). Eight of these 35 had positive AβPET findings and negative coincident CSF tests at the first time tested. Of these, 5/8 were Meta‐ROI and early AβPET ROI positive. The other 3/8 were only positive on early‐Aβ AβPET ROIs. Four of the 8 with negative CSF and positive AβPET had subsequent testing and 2/4 became positive on CSF tests after 1.5 years while 2/4 continued to be negative on subsequent testing.ConclusionAβPET is more sensitive for detection of early cortical Aβ deposition than CSF biomarkers in cross‐sectional or autopsy data. While the assessment of AβPET by standard Meta‐ROI AβPET methods showed cortical Aβ deposition occurring when not indicated by CSF biomarkers, AβPET ROIs for early Aβ deposition detected additional participants that were AβPET positive and AβCSF negative. These findings have implications for detecting early Aβ neuropathology among CU participants in Aβ prevention trials when robust detection is needed. Further work is needed to compare Aβ plasma biomarkers and AβPET using these methods.

AbstractBackgroundCorticobasal syndrome (CBS) is a progressive neurodegenerative syndrome that can result from several underlying neuropathologies, including Alzheimer’s disease (AD). Little is known about the utility of blood plasma measures to predict PET biomarker confirmed AD in CBS.MethodEighteen CBS patients (8 PET Aβ+; 10 PET Aβ‐) and 8 cognitively unimpaired Aβ‐ individuals (CU) were recruited by the Neurodegenerative Research group from the Department of Neurology, Mayo Clinic, Rochester, MN, underwent Aβ (Pittsburgh Compound‐B) and tau (18F‐flortaucipir) PET and provided a blood sample. Blood plasma analysis was performed to assess p‐tau 181, total tau, Aβ 42/40, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) using the Quanterix Simoa platform. Plasma concentrations were compared between Aβ‐, and Aβ+ CBS and controls using Kruskal‐Wallis corrected for multiple comparisons using Dunn’s test, with effect size measured with area under the receiver operating characteristic curve (AUROC) analysis. Spearman correlations were calculated to assess relationships between plasma concentrations and Aβ and tau PET uptake.ResultThe CBS Aβ+ group showed reduced Aβ42/40 ratio, with elevated p‐tau 181, GFAP and NfL plasma concentrations compared to CU, while the CBS Aβ‐ group only showed elevated NfL concentration compared to CU (Figure 1). Both p‐tau 181 (AUROC=0.95) and GFAP (AUROC=0.91) plasma concentrations were able to differentiate CBS Aβ‐ from CBS Aβ+. Plasma p‐tau 181 and GFAP concentrations showed a positive correlation to both Aβ and tau PET uptake, and the Aβ42/40 ratio showed a negative correlation to Aβ PET uptake (Figure 2). No correlations were observed between NfL and Aβ and tau PET.ConclusionThis study supports the use of plasma p‐tau 181 and GFAP to detect AD in CBS, while NfL shows potential as a nonspecific disease biomarker of CBS regardless of underlying pathology. Plasma concentrations of these biomarkers may potentially be incorporated into clinical trials targeting CBS patients with underlying AD pathology.

AbstractBackgroundBlood plasma metrics provide excellent biomarkers of the presence of Alzheimer’s disease (AD) pathology in population cohorts. However, it is less clear whether plasma metrics correlate with PET measures of AD pathology in cohorts of patients with advanced AD disease, particularly in those with atypical clinical presentations of AD.MethodSeventy‐seven patients (visual variant=43, language variant=32, motor variant=1 and dysexecutive variant=1) with PET biomarker‐confirmed atypical AD were recruited by the Neurodegenerative Research group at Mayo Clinic, Rochester, MN, underwent Aβ (Pittsburgh Compound‐B) and tau (18F‐flortaucipir) PET and provided a blood sample. Blood plasma analysis was performed to assess p‐tau 181 and Aβ42/40 ratio concentrations using the Quanterix Simoa platform. Multivariate linear regression models assessed the relationship between plasma concentrations and both global Aβ, atypical AD summary and regional tau PET measures. For each PET measure, two separate models were fit to assess the influence of each plasma biomarker separately, while the third model included all plasma measures to assess the combined influence of all biomarkers on PET uptake. To investigate differences in plasma concentrations between atypical AD phenotypes, we performed Mann‐Whitney’s test across the visual and language variants of AD.ResultPlasma Aβ42/40 ratio showed positive associations with tau PET uptake, specifically within precuneus, parietal and temporal regions and was not associated with Aβ PET. There was no relationship between plasma p‐tau 181 and Aβ or tau PET uptake. However, the model that included both plasma biomarkers showed that with the addition of p‐tau 181, all significant associations between Aβ42/40 ratio and regional tau uptake were weakened to trends. The Aβ42/40 ratio continued to show no relationship with global Aβ‐PET uptake and plasma p‐tau 181 showed no relationship to PET measures (Figure 1). Lastly, no significant difference in plasma Aβ42/40 and p‐tau 181 levels was noted between the visual and language variants of AD (Figure 2).ConclusionThe lack of associations between plasma concentrations and PET measures of Aβ and tau in this relatively advanced AD cohort may suggest that plasma concentrations have greater utility as diagnostic biomarkers of early AD as compared to advanced AD.

AbstractBackgroundBlood‐based biomarkers show promise as a noninvasive, inexpensive method for measuring Alzheimer’s disease pathology throughout the lifecourse. However, the predictive and classification accuracy of these biomarkers at different stages of the lifecourse and among diverse, community‐dwelling populations requires further investigation.MethodBetween 2014 and 2015, 329 dementia‐free participants from the Atherosclerosis Risk in Communities Study underwent brain magnetic resonance imaging (MRI) and florbetapir positron emission tomography (PET). Amyloid positivity was defined as a global cortex standardized uptake value ratio greater than 1.2. Stored plasma samples collected in midlife (1993‐95, mean age 58.5 years) and late‐life (2011‐13, mean age 76.2 years) from a subsample of 259 participants were assayed in 2022 using Quanterix SiMoA. The assay quantified amyloid‐β (Aβ)42/40, phosphorylated tau at threonine 181 (p‐Tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). Unadjusted and covariate‐adjusted logistic regression models estimated the association between plasma biomarkers from midlife and late‐life and amyloid positivity in late‐life. Unadjusted receiver operating characteristic curves documented the classification accuracy of the plasma biomarkers separately and collectively.ResultThe sample (Table 1) included 151 women (58.1%), 105 Black participants (40.4%), and 136 (52.3%) participants with amyloid positivity. In models adjusted for demographics, lifestyle factors, cardiovascular factors, and the presence of APOE ε4 alleles, assays measured in midlife were not associated with amyloid positivity in late‐life (Table 2). However, late‐life measurements of Aβ42/40, p‐Tau181, and GFAP and change per decade from midlife to late‐life in p‐Tau181 and GFAP were associated with greater odds of amyloid positivity. The greatest classification accuracy (Figure 1) was achieved by using all assays measured in midlife and late‐life (AUC = 0.754), although the accuracy when using only late‐life measures was comparable (AUC = 0.737).ConclusionLate‐life plasma biomarkers of Alzheimer's disease neuropathology and astrogliosis were associated with late‐life amyloid positivity, but midlife plasma biomarkers obtained 16 to 20 years earlier did not exhibit a statistically significant association. Additional longitudinal research is needed to determine whether changes in plasma biomarkers measured before an individual is classified as amyloid positive can be used to identify individuals at risk of developing Alzheimer's disease.

AbstractBackgroundScanning laser ophthalmoscopy (SLO) visualizes two important markers of cognitive dysfunction in the retina: vascular changes and amyloid plaque (AP) deposition. The relationship between retinal arteriolar versus venular changes and perivascular amyloid deposition across the continuum of neurodegeneration is imperfectly understood. We investigate the retinal perivascular AP distribution in relationship to cognitive and neuroimaging measures in a cohort of cognitively normal and impaired individuals.Method34 subjects with normal or impaired cognition underwent retinal SLO, brain magnetic resonance imaging and standard neuropsychometric testing. Retinal peri‐arteriolar and peri‐venular curcumin positive AP were quantified in the supero‐temporal retinal quadrant, in the first, second and third‐order retinal vascular branches. The peri‐venular and peri‐arteriolar AP count were compared between patients with normal and impaired cognition, and their correlation with brain volumes, white matter hyperintensities and cognitive Z‐scores was determined.ResultWe analyzed retinal para‐venous and para‐arteriolar amyloid count in 28 subjects, mean (SD) age 65 (7.3), 50% female, 19 (52.6%) with impaired cognition. Para‐arteriolar plaque count was higher than peri‐venular plaque in the entire cohort (p<0.0001). Secondary branch peri‐venular amyloid plaque count was higher in patients with MOCA ≤26. Tertiary branch perivascular AP count significantly and negatively correlated with hippocampal volume and positively correlated white matter hyperintensity lesion count.ConclusionRetinal AP deposit peri‐arteriolarly overall and peri‐venularly in the secondary branches in cognitively impaired. Perivascular amyloid burden in small retinal branches correlates with hippocampal volume and white matter hyperintensities.

Background Sinonasal mucosal melanoma has poor survival despite multimodality treatment. While the impact of immunotherapy (IT) on metastatic cutaneous melanoma is well-defined, there are relatively little data on sinonasal mucosal melanoma. Objective We sought to define immunotherapy outcomes in patients with sinonasal mucosal melanoma. Methods A retrospective cohort study evaluated patients treated with IT during their overall treatment strategy for SNMM. Patient demographics, treatment, and survival outcomes were recorded. Results 52 patients had IT treatment for SNMM from 2000 to 2022, with an average age of 69.1 ± 11.9 years. The most common treatment was surgery with radiation and IT ( n = 26, 50%). Most regimens consisted of a combination of Nivolumab and Ipilimumab ( n = 17, 32.7%) or pembrolizumab ( n = 14, 26.9%). 44.2% of patients experienced reported complications. Overall survival at 1-, 2-, and 5 years was 86.9%, 74.1%, and 39.1%, respectively. Conclusion Approximately half of patients will have a local response following immunotherapy, but it is rare to have improvement at metastatic locations. Further research within our group will assess optimal timing and markers that are predictive of response.

AbstractBackgroundCorticobasal syndrome (CBS) is a progressive neurodegenerative syndrome that can result from several underlying neuropathologies, including Alzheimer’s disease (AD). Little is known about the utility of blood plasma measures to predict PET biomarker confirmed AD in CBS.MethodEighteen CBS patients (8 PET Aß+; 10 PET Aß‐) and 8 cognitively unimpaired Aß‐ individuals (CU) were recruited by the Neurodegenerative Research group from the Department of Neurology, Mayo Clinic, Rochester, MN, underwent Aß (Pittsburgh Compound‐B) and tau (18F‐flortaucipir) PET and provided a blood sample. Blood plasma analysis was performed to assess p‐tau 181, total tau, Aß 42/40, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) using the Quanterix Simoa platform. Plasma concentrations were compared between Aß‐, and Aß+ CBS and controls using Kruskal‐Wallis corrected for multiple comparisons using Dunn’s test, with effect size measured with area under the receiver operating characteristic curve (AUROC) analysis. Spearman correlations were calculated to assess relationships between plasma concentrations and Aß and tau PET uptake.ResultThe CBS Aß+ group showed reduced Aß42/40 ratio, with elevated p‐tau 181, GFAP and NfL plasma concentrations compared to CU, while the CBS Aß‐ group only showed elevated NfL concentration compared to CU (Figure 1). Both p‐tau 181 (AUROC=0.95) and GFAP (AUROC=0.91) plasma concentrations were able to differentiate CBS Aß‐ from CBS Aß+. Plasma p‐tau 181 and GFAP concentrations showed a positive correlation to both Aß and tau PET uptake, and the Aß42/40 ratio showed a negative correlation to Aß PET uptake (Figure 2). No correlations were observed between NfL and Aß and tau PET.ConclusionThis study supports the use of plasma p‐tau 181 and GFAP to detect AD in CBS, while NfL shows potential as a nonspecific disease biomarker of CBS regardless of underlying pathology. Plasma concentrations of these biomarkers may potentially be incorporated into clinical trials targeting CBS patients with underlying AD pathology.

AbstractBackgroundImaging and plasma markers are used as key indicators of disease for Alzheimer’s disease (AD) but their usefulness in predicting regional tau pathology is relatively understudied. Our objective was to construct predictive models for regional tau pathology measured on postmortem brain tissue using multiple ante‐mortem AD biomarkers. We focused on hippocampal and parietal regions that were immunostained with AT8 and 2E9 that reflect early and advanced aspects of tangle maturity, respectively.MethodsUsing autopsy data from 63 participants enrolled in the Mayo Clinic Study of Aging (MCSA) where the last clinical visit is within three years of death, we analyzed three ante‐mortem plasma markers ‐ phosphorylated tau protein at the threonine 181 residue, glial fibrillary acidic protein, total ß‐amyloid Aß42 relative to Aß40 ratio (Quanterix Simoa HD‐X Analyzer), and three regional MRI markers computed using SPM12 ‐ parietal thickness, parietal volume relative to total intracranial volume ratio, and hippocampal volume adjusted for total intracranial volume. Based on eight separate cross‐sectional linear regression models weighted by the inverse of time from last visit to death, we estimated the multiple and partial R2 predicting post‐mortem pathology measures, including AT8 and 2E9 in both the hippocampal and parietal regions. All models were adjusted for age, sex, and cardiovascular and metabolic conditions score.ResultsThe MRI models (R2 of 0.26‐0.53) had greater predictive power compared to the plasma models (R2 of 0.17‐0.26). The best multiple R2 was 0.53 for prediction of hippocampal AT8 using antemortem hippocampal volume adjusted for total intracranial volume followed by R2 of 0.43 for prediction of hippocampal 2E9 using hippocampal volume adjusted for total intracranial volume. Though the model prediction of parietal AT8 and 2E9 measurements was low (R2 of 0.21‐0.26), parietal thickness exhibited better predictive performance than parietal volume relative to total intracranial volume ratio.ConclusionsThe data we presented here may be utilized to validate biomarkers using regional pathology. Our results support that regional MRI is sensitive to tau pathology. Newer MRI methods should be tested to examine the specificity of newer quantitative measurements to tau pathology.

AbstractBackgroundThe immune system is substantially involved in the development and progression of age‐related cognitive decline and Alzheimer’s disease (AD).MethodAs genetic and environmental factors interactively impact these conditions, we investigated how risk factors such as APOE genotype, age, and sex influence immune activation markers and AD biomarkers in cerebrospinal fluid (CSF) in elderly individuals enrolled in the Mayo Clinic Study of Aging cohort. Among cognitively unimpaired individuals aged over 65 at the baseline visit (N=298), we measured 365 CSF immune activation markers using the proximity extension assay.ResultWe found that age, sex, and diabetes status are associated with altered CSF levels of immune activation markers independently of other factors. For CSF AD biomarkers, we observed significant positive correlations between age and total tau, phosphorylated tau‐181 (p‐tau181), neurofilament light (NfL), and YKL40. APOE4 was also associated with lower Aß42 and higher SNAP25 in CSF. We further examined whether baseline visit variables can predict cognitive decline, represented by the conversion from CDR=0 to CDR>0. We found that age, Aß42, NfL, and REG4 were independently correlated with CDR conversion risk. When the cohort was dichotomized by their median values, older participants with lower Aß42, higher NfL, and higher REG4 at baseline developed cognitive impairment during the follow up with a c‐index of 0.762 while age alone had a c‐index of 0.699.ConclusionTogether, our results suggest that assessing CSF immune activation markers and AD biomarkers can improve the prediction of cognitive impairment risk in the elderly.