George Savulich

Dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia, pathologically defined by the presence of Lewy bodies. Peripheral and central inflammation are increasingly recognised in DLB in clinical, post-mortem, and animal studies. Finding clinically relevant biomarkers of inflammation in DLB will support identification of novel pathways for disease modifying therapies or use in clinical trials of immunomodulatory agents. Whilst there are cross-sectional studies of inflammation markers in DLB, there is limited evidence on the association between these markers and cognitive decline over time. Twenty participants with DLB underwent blood sampling for serum inflammatory markers, paired with PET imaging of the translocator protein (TSPO) and up to four years of longitudinal cognitive testing. Thirty participants with Alzheimer’s disease—comprising both Alzheimer’s dementia and/or Mild Cognitive Impairment with biomarker evidence of amyloid pathology (AD/MCI+) and twenty-eight controls were also recruited for group comparisons. Data from forty-two baseline cytokine immunoassays and TSPO PET were used as predictors of longitudinal cognitive scores in linear mixed effects models. Partial least squares regression was used to test the association between peripheral and central inflammation. Using peripheral inflammatory markers as single predictors we identified fourteen associated with either slower or faster rate of cognitive decline in DLB, whilst no single marker was predictive of decline in AD/MCI+. As many inflammatory markers were highly correlated, we used principal components analysis to identify a cytokine component associated with reduced cognitive decline in both DLB and AD/MCI+, which overlapped with the single markers identified in the previous analysis. A separate component was associated with cognitive decline in AD/MCI+, or DLB with Alzheimer’s dementia co-pathology (ascertained by amyloid PET). Widespread TSPO binding was associated with reduced cognitive decline in DLB, whilst a fronto-temporal pattern was associated with more rapid cognitive decline in both DLB and AD/MCI+. There were associations between peripheral cytokines and TSPO PET in AD/MCI+, but these were not significant in DLB. Overall peripheral and central inflammation predicted cognitive decline in DLB. Specific patterns associated with both faster and slower rates of decline were identified. These profiles had both overlapping and contrasting associations when compared to AD/MCI+. Collectively, these data add to a body of evidence suggesting clinically relevant levels of inflammation in DLB. Future studies in larger, multi-site cohorts with multiple biomarker sampling points are required to understand the impact and dynamics of inflammation across all stages of disease.

INTRODUCTION: Blood-based biomarkers have the potential to support early and accurate diagnosis of neurodegenerative diseases, which is sensitive to molecular pathology and predictive of outcome. We evaluated a novel multiplex proteomic method in people with diverse neurodegenerative diseases. METHODS: Serum from people with Alzheimer’s disease (N=36), Lewy body dementia (N=34), frontotemporal dementia (N=36) and progressive supranuclear palsy (N=36) and age-matched controls (N=30) was analysed with the NUcleic acid Linked Immuno-Sandwich Assay (NULISA) central nervous system panel (∼120 analytes) and inflammation panel (250 analytes). Biomarkers were compared across groups and included as predictors of survival. RESULTS: The NULISA panels demonstrated high sensitivity and reliability for detecting multiple biomarkers across neurodegenerative disorders. There were condition-specific proteomic biomarkers, while NfL, CRH, CD276 and S100A12 were significant transdiagnostic outcome predictors. DISCUSSION: The sensitive NULISA multiplex approach supports differential diagnosis and target identification, with prognostically informative dementia-related biomarkers.

The innate immune system plays an integral role in the progression of many neurodegenerative diseases. In addition to central innate immune cells (e.g., microglia), peripheral innate immune cells (e.g., blood monocytes, natural killer cells, and dendritic cells) may also differ in these conditions. However, the characterization of peripheral innate immune cell types across different neurodegenerative diseases remains incomplete. This study aimed to characterize peripheral innate immune profiles using flow cytometry for immunophenotyping of peripheral blood mononuclear cells in n = 148 people with Alzheimer’s disease (AD), frontotemporal dementia (FTD), corticobasal syndrome (CBS), progressive supranuclear palsy (PSP), Lewy body dementia (LBD) as compared to n = 37 healthy controls. To compare groups, we used multivariate dissimilarity analysis and principal component analysis across 19 innate immune cell types. We identified pro-inflammatory profiles that significantly differ between patients with all-cause dementia and healthy controls, with some significant differences between patient groups. Regression analysis confirmed that time to death following the blood test correlated with the individuals’ immune profile weighting, positively to TREM2+ and non-classical monocytes and negatively to classical monocytes. Taken together, these results describe transdiagnostic peripheral immune profiles and highlight the link between prognosis and the monocyte cellular subdivision and function (as measured by surface protein expression). The results suggest that blood-derived innate immune profiles can inform sub-populations of cells relevant for specific neurodegenerative diseases that are significantly linked to accelerated disease progression and worse survival outcomes across diagnoses. Blood-based innate immune profiles may contribute to enhanced precision medicine approaches in dementia, helping to identify and monitor therapeutic targets and stratify patients for candidate immunotherapies.

Neuroinflammation is an important pathogenic mechanism in many neurodegenerative diseases, including those caused by frontotemporal lobar degeneration. Post-mortem and in vivo imaging studies have shown brain inflammation early in these conditions, proportional to symptom severity and rate of progression. However, evidence for corresponding blood markers of inflammation and their relationships to central inflammation and clinical outcome are limited. There is a pressing need for such scalable, accessible and mechanistically relevant blood markers because these will reduce the time, risk and costs of experimental medicine trials. We therefore assessed inflammatory patterns of serum cytokines from 214 patients with clinical syndromes associated with frontotemporal lobar degeneration in comparison to healthy controls, including their correlation with brain regional microglial activation and disease progression. Serum assays used the MesoScale Discovery V-Plex-Human Cytokine 36 plex panel plus five additional cytokine assays. A subgroup of patients underwent ¹¹C-PK11195 mitochondrial translocator protein PET imaging, as an index of microglial activation. A principal component analysis was used to reduce the dimensionality of cytokine data, excluding cytokines that were undetectable in >50% of participants. Frequentist and Bayesian analyses were performed on the principal components to compare each patient cohort with controls and test for associations with central inflammation, neurodegeneration-related plasma markers and survival. The first component identified by the principal component analysis (explaining 21.5% variance) was strongly loaded by pro-inflammatory cytokines, including TNF-α, TNF-R1, M-CSF, IL-17A, IL-12, IP-10 and IL-6. Individual scores of the component showed significant differences between each patient cohort and controls. The degree to which a patient expressed this peripheral inflammatory profile at baseline was correlated negatively with survival (higher inflammation, shorter survival), even when correcting for baseline clinical severity. Higher pro-inflammatory profile scores were associated with higher microglial activation in frontal and brainstem regions, as quantified with ¹¹C-PK11195 mitochondrial translocator protein PET. A permutation-based canonical correlation analysis confirmed the association between the same cytokine-derived pattern and central inflammation across brain regions in a fully data-based manner. This data-driven approach identified a pro-inflammatory profile across the frontotemporal lobar degeneration clinical spectrum, which is associated with central neuroinflammation and worse clinical outcome. Blood-based markers of inflammation could increase the scalability and access to neuroinflammatory assessment of people with dementia, to facilitate clinical trials and experimental medicine studies.

Neuroinflammation is an important pathogenic mechanism in many neurodegenerative diseases, including those caused by frontotemporal lobar degeneration (FTLD). There is a pressing need for scalable and mechanistically relevant blood markers of inflammation to facilitate drug development and experimental medicine. We assessed inflammatory profiles of serum cytokines from 214 patients with FTLD-associated syndromes (behavioural and language variants of frontotemporal dementia, progressive supranuclear palsy, corticobasal syndrome). We tested the association with brain microglial activation (by positron emission tomography) and survival. A pro-inflammatory profile across the FTLD spectrum (including TNF-α, TNF-R1, M-CSF, IL-17A, IL-12, IP-10 and IL-6) differentiated patients (all syndromes) from controls. A higher pro-inflammatory profile scores was associated with higher microglial activation in frontal and brainstem regions, and with lower survival. Blood-based markers of inflammation could increase the scalability and access to neuroinflammatory assessment of people with dementia, to facilitate clinical trials and experimental medicine studies.

Background: There is growing evidence for early and extensive synaptic loss in frontotemporal lobar degeneration syndromes from in vivo and post‐mortem studies. We proposed that synaptic loss would affect behaviour, in relation to changes in functional connectivity.Method: We recruited 29 participants with progressive supranuclear palsy, 16 participants with amyloid‐negative corticobasal syndrome, 8 participants with behavioural variant frontotemporal dementia and 24 similarly‐aged healthy volunteers. All participants underwent resting‐state functional 3T MRI and positron emission tomography with [¹¹C]UCB‐J, that binds synaptic vesicle 2A. We compared the connectivity metrics of nodal weighted degree and voxelwise regional homogeneity with [¹¹C]UCB‐J non‐displaceable binding potential (BP_ND), in associative and commonality analyses. We then used independent component analysis to extract [¹¹C]UCB‐J BP_ND signal variance across participants, followed by derivation of participant‐specific scores of functional spatial covariance with the [¹¹C]UCB‐J components. We applied model selection to assess whether connectivity scores would improve prediction of and moderate the effect of synaptic loss on clinical severity.Result: Reduced [¹¹C]UCB‐J BP_ND was associated with reduced connectivity, with synaptic density predicting both measures of connectivity over and above grey matter volume (Figure 1). The anatomical distribution of synaptic loss partially overlapped in PSP, bvFTD and CBS, but there were also disease‐specific effects (Figure 2). The effect of synaptic loss on functional connectivity was expressed local to the regions of severe synaptic loss, and in remote regions. Moreover, functional connectivity explained additional variance and moderated the relationship between synaptic density and clinical severity (Figure 3).Conclusion: In vivo synaptic loss is associated with reduced connectivity, and changes in behaviour, with implications for modelling disease pathogenesis and translational studies.

Background: The epigenetic mechanism of DNA methylation has been implicated in the pathophysiology of neurodegenerative disorders such as Lewy body dementia (LBD). DNA methylation profiling may help to identify novel treatment targets and early disease markers. We hypothesized that DNA methylation alterations are detectable in blood due the influence of genetic and environmental factors as well as immune system changes associated with LBD.Method: Genome‐wide DNA methylation profiling was carried out using reduced representation bisulfite sequencing in blood samples from 89 LBD patients and 67 controls. Fifty five LBD patients had amyloid PET imaging. Data processing was performed using FastQC, TrimGalore, Bismark and MethylKit. DNA methylation alterations at specific CpG sites as well as at promoter, CpG island and CpG shore regions were compared between LBD cases and controls. A log odds logistic regression was used to identify differential DNA methylation after adjusting for age, sex and smoking status. The false discovery rate (FDR) was used for correction for multiple testing. We also tested the diagnostic classification performance of the differentially methylated regions using receiver operating characteristic (ROC) curve analysis and examined the potential of DNA methylation as a predictor of amyloid PET positivity in LBD.Result: Two single CpG sites at TNFRSF1B and EMC6 and three CpG shore regions at ABCG5, ETAA1 and TENM4 reached genome‐wide significance in the differential DNA methylation analysis comparing LBD cases and controls. The combined panel of the top three differentially methylated CpG shores reached an area under the curve (AUC) of 0.91 for the diagnosis of LBD compared to controls (sensitivity 0.89, specificity 0.85). DNA methylation at TENM4 was associated with amyloid PET positivity in LBD with an AUC of 0.84 (sensitivity 0.99, specificity 0.55).Conclusion: Our data suggest that DNA methylation alterations in blood are observed in a cohort of LBD patients compared to controls. Our findings need to be replicated in larger cohorts and tested for specificity in LBD in order to explore their future potential as diagnostic markers and/or targets for novel therapeutics.

Background: Novel, validated imaging biomarkers for assessing disease severity and progression in dementia with Lewy Bodies (DLB) are needed as standard neuroimaging changes such as atrophy are not pronounced. Both multi‐modal MR and PET offer opportunities, for example cortical microstructure and dendritic imaging can be assessed using advanced MR diffusion weighted imaging (DWI) methods such as neurite orientation dispersion and density imaging (NODDI) and PET with UCB‐J can assess synaptic density. We applied these and other markers to people with DLB and controls.Method: In linked studies, people with probable DLB and similarly aged controls (n = 10‐30 per group depending on study) underwent multimodal 3T‐MRI (including structural, multi‐shell DWI and arterial spin labelling imaging) and PET imaging with AV1451 (for assessment of tau), PiB (for amyloid status) and [11C]UCB‐J PET/MR. For MR, T1‐MRI and DWI datasets were processed using FreeSurfer 7.2 and FSL 6.0.4 respectively with whole‐brain ODI derived from the Microstructure Diffusion Toolbox. The [11C]UCB‐J and [18F]AV1451 binding potentials (BPND) were assessed using a simplified reference tissue model (reference centrum semiovale for UCBJ and cerebellum for AV1451). Group differences in ODI, UCB‐J and AV1451 BPND were examined and correlated with structural changes and clinical and cognitive variables (ACE‐R score).Result: Compared to controls, people with DLB showed significantly thinner neocortex (T = ‐2.8, p = 0.01) in temporo‐parietal regions but more widespread reductions in cortical microstructure (ODI, T = ‐3.9, p < 0.001)(Figure 1). Within the DLB group, hippocampal ODI was positively correlated with cognitive performance (robust linear regression: p < 0.001)(Figure 2). Reduced synaptic density (UCB‐J BP_ND) was found for the DLB group in posterior regions (p<0.05, FWE corrected)(Figure 3), with a trend for greater reductions in those who were amyloid positive. ACE‐R scores significantly correlated with synaptic density (p<0.05, FWE corrected). There were no significant differences in AV1451 binding between DLB and controls.Conclusion: Extensive reductions in ODI and reduced synaptic density, both associated with cognitive impairment and occurring in regions without significant atrophy or tau deposition, suggests that NODDI and synaptic PET imaging are promising biomarkers for DLB which merit further investigation, including in longitudinal studies.

Background: Neuroinflammation is an important pathogenic mechanism in frontotemporal dementia (FTD) and related disorders. Postmortem and in vivo imaging studies have shown brain inflammation early in these conditions, and as proportionate to symptom severity and rate of progression. However, data on inflammation blood markers of inflammation and their relationship with central inflammation are limited. Here we assess inflammatory patterns of 41 serum cytokines from patients with FTD and related conditions, and their association with regional microglial activation (TSPO PET).Method: Blood samples were obtained from 29 healthy controls, and 214 patients with a clinical diagnosis of behavioural variant FTD (bvFTD = 52), primary progressive aphasia (PPA = 51), progressive supranuclear palsy (PSP = 58) and corticobasal syndrome (CBS = 53). Serum assays used the MesoScale Discovery V‐Plex‐Human Cytokine 36 plex panel plus five additional cytokine assays. A Principal Component Analysis (PCA) across all participants was used to reduce dimensionality of cytokine data. A sub‐group of patients (bvFTD = 10, PPA = 17, PSP = 17) underwent PET imaging with [¹¹C]PK11195 PET, as index of microglial activation. Kruskal‐Wallis and pairwise t‐tests were performed on the resulting components to compare each patient cohort to controls. [¹¹C]PK11195 non‐displaceable binding potential (BP_ND) was calculated in 83 regions of interest (ROIs) across the whole brain. Spearman correlations tested associations between cytokine components and regional [¹¹C]PK11195 BP_ND.Result: Sixteen cytokines were undetectable in >50% of participants and thus excluded. The first component identified by the PCA on the remaining 25 cytokines (explaining 19.7%) was strongly loaded by pro‐inflammatory cytokines (Figure 1, left). Kruskal–Wallis one‐way analyses of variance on detected significant differences across the groups (χ²(4) = 11.0, p = 0.027), and the pairwise t‐tests identified significant differences between each patient cohort and controls (Figure 1, right). Spearman correlations identified regional positive associations between individual cytokine‐component scores and microglial activation in frontal and brainstem regions across the whole group (R≥0.25), and syndrome‐specific regional patterns (Figure 2).Conclusion: This data‐driven approach identified a pro‐inflammatory profile across FTD and related conditions, which is positively associated with higher levels of microglial activation in syndrome‐related key brain regions. Blood‐based tests could greatly increase the scalability and access to neuroinflammatory assessment in dementia and experimental medicine studies.

Background: Neuroinflammation is an important pathogenic mechanism in frontotemporal dementia (FTD) and related disorders. Postmortem and in vivo imaging studies have shown brain inflammation early in these conditions, and as proportionate to symptom severity and rate of progression. However, data on inflammation blood markers of inflammation and their relationship with central inflammation are limited. Here we assess inflammatory patterns of 41 serum cytokines from patients with FTD and related conditions, and their association with regional microglial activation (TSPO PET).Method: Blood samples were obtained from 29 healthy controls, and 214 patients with a clinical diagnosis of behavioural variant FTD (bvFTD = 52), primary progressive aphasia (PPA = 51), progressive supranuclear palsy (PSP = 58) and corticobasal syndrome (CBS = 53). Serum assays used the MesoScale Discovery V‐Plex‐Human Cytokine 36 plex panel plus five additional cytokine assays. A Principal Component Analysis (PCA) across all participants was used to reduce dimensionality of cytokine data. A sub‐group of patients (bvFTD = 10, PPA = 17, PSP = 17) underwent PET imaging with [11C]PK11195 PET, as index of microglial activation. Kruskal‐Wallis and pairwise t‐tests were performed on the resulting components to compare each patient cohort to controls. [11C]PK11195 non‐displaceable binding potential (BPND) was calculated in 83 regions of interest (ROIs) across the whole brain. Spearman correlations tested associations between cytokine components and regional [11C]PK11195 BPND.Result: Sixteen cytokines were undetectable in >50% of participants and thus excluded. The first component identified by the PCA on the remaining 25 cytokines (explaining 19.7%) was strongly loaded by pro‐inflammatory cytokines (Figure 1, left). Kruskal–Wallis one‐way analyses of variance on detected significant differences across the groups (χ2(4) = 11.0, p = 0.027), and the pairwise t‐tests identified significant differences between each patient cohort and controls (Figure 1, right). Spearman correlations identified regional positive associations between individual cytokine‐component scores and microglial activation in frontal and brainstem regions across the whole group (R≥0.25), and syndrome‐specific regional patterns (Figure 2).Conclusion: This data‐driven approach identified a pro‐inflammatory profile across FTD and related conditions, which is positively associated with higher levels of microglial activation in syndrome‐related key brain regions. Blood‐based tests could greatly increase the scalability and access to neuroinflammatory assessment in dementia and experimental medicine studies.