Henrik Zetterberg’s research while affiliated with WWF United Kingdom and other places

INTRODUCTION Neuroinflammation may have sex‐specific effects on white matter injury and impact the development of dementia. METHODS Human chitinase‐3‐like protein‐1 (YKL‐40) concentrations at baseline were related to white matter hyperintensity (WMH) volume, free water (FW), and FW‐corrected fractional anisotropy using linear effects models (for cross‐sectional outcomes) and linear mixed‐effects models (for longitudinal outcomes), adjusting for demographic and medical risk factors. Models were repeated with a sex‐interaction term and then stratified by sex. RESULTS In stratified analyses, greater baseline YKL‐40 concentrations were associated with increased WMHs in females but not males in the parietal (females p = 0.04; males p = .34) and temporal lobes (females p = 0.005; males = p = 0.71) longitudinally. YKL‐40 associations with FW and FW‐corrected fractional anisotropy were null. DISCUSSION Results suggest that neuroinflammation is a sex‐specific driver of WMHs (but not FW) in females. Differential sequelae of neuroinflammation may be one reason that females have a greater burden of WMHs. Highlights ·Cerebrospinal fluid YKL‐40 is associated with white matter hyperintensities in females but not males cross‐sectionally and longitudinally. ·Longitudinally, cerebrospinal fluid YKL‐40 is associated with white matter hyperintensities in the parietal and temporal lobes, regions that exhibit early pathological changes in Alzheimer's disease . ·Cerebrospinal fluid YKL‐40 is not associated with white matter microstructural measures.

INTRODUCTION Cognitively unimpaired (CU) amyloid beta (Aβ)+ individuals with elevated plasma glial fibrillary acidic protein (GFAP) have an increased risk of Alzheimer's disease (AD)‐related progression. We tested the utility of plasma GFAP for population enrichment CU populations in clinical trials. METHODS We estimated longitudinal progression, effect size, and costs of hypothetical clinical trials designed to test an estimated 25% drug effect on reducing tau positron emission tomography (PET) accumulation in the medial temporal lobe (MTL) and temporal neocortical region (NEO‐T). RESULTS CU GFAP+/Aβ+ individuals present an increased annual rate of change and effect size in tau PETMTL and tau PETNEO‐T compared to the other groups. An enrichment strategy selecting CU GFAP+/Aβ+ individuals would require a smaller sample size (≈ 57% reduction) and fewer Aβ PET scans (≈ 74% reduction) than trials enriched with Aβ PET alone, reducing total clinical trial costs by up to 64%. DISCUSSION Our results suggest that clinical trials focusing on preclinical AD recruiting Aβ+ individuals with elevated GFAP levels would improve cost effectiveness. Highlights Cognitively unimpaired (CU) glial fibrillary acidic protein (GFAP)+/amyloid beta (Aβ)+ shows increased changes in tau positron emission tomography (PET) . CU GFAP+/Aβ+ enriched clinical trials require a reduced sample size compared to Aβ+ only. CU GFAP+/Aβ+ enrichment reduces Aβ PET scans required and costs. CU GFAP+/Aβ+ enrichment allows the selection of individuals at early stages of the Alzheimer's disease continuum.

The adaptive immune system and neurodegenerative Alzheimer’s disease (AD) are intertwined in multiple ways. Recent studies have reported alterations of the adaptive immune system in early AD stages, such as preclinical AD and mild cognitive impairment (MCI) due to AD. However, the identity of specific antigenic targets and whether the respective response is beneficial or detrimental during disease progression are still open questions. Herein, we describe cross-sectional analyses of blood and cerebrospinal fluid from three different study populations covering early AD stages. We employed high-dimensional mass cytometry, single-cell RNA-sequencing, ex vivo T-cell secretome analysis, and antigen presentation assays to achieve a comprehensive characterization of adaptive immune cell populations. Our results show that subjects at the stage of asymptomatic, preclinical AD can mount a CD4+ T helper cell response towards β-amyloid peptide and display an early enrichment of CD8+ T effector memory cells re-expressing CD45RA (TEMRA cells) in CSF, combined with a less immunosuppressive gene signature of peripheral regulatory T-cells. Conversely, in MCI we observed increased frequencies of CD8+ TEMRA/effector cells in the periphery characterized by a pro-inflammatory gene expression profile, and generally decreased antigen responsiveness. Our results demonstrate the complexity of adaptive immune changes in early AD and suggest that it may be beneficial to promote specific CD4+ T-cell responses in the preclinical stage, while in MCI it may be important to therapeutically target CD8+ T-cell responses if these prove to be harmful.

Background Blood–brain barrier (BBB) dysfunction is an early event in neurodegenerative disorders. Pericytes are key cells for BBB maintenance. Upon pericyte injury, the platelet-derived growth factor receptor-β (PDGFRβ) is released in the cerebrospinal fluid (CSF). The relation of CSF PDGFRβ with markers of amyloid pathology, neuroinflammation, and axonal and synaptic damage across dementia remains unclear. Methods Retrospectively, we quantified CSF PDGFRβ and CSF core Alzheimer's disease (AD), astrocytic (GFAP), microglial (sTREM 2, YKL-40), axonal (NfL), and synaptic (GAP-43, neurogranin) biomarkers in 210 patients from the Cognitive Neurology Centre, Paris, France, including n = 23 neurological controls (NC), n = 84 patients with mild cognitive impairment (MCI) [AD, n = 41; non-AD, n = 43], and n = 103 patients with dementia (AD, n = 73; non-AD, n = 30). Findings Comparing clinical stages, CSF PDGFRβ levels were increased at the MCI stage (Cohen's d = 0.55 [CI95% 0.066, 1.0], P = 0.025) compared with NC. Non-AD MCI displayed higher levels than controls (Cohen's d = 0.74 [CI95% 0.22, 1.3], P = 0.042). No association was observed with CSF Aβ42/Aβ40 ratio but with p-tau 181 (β = 0.102 [CI95% 0.027, 0.176], P = 0.0080) and t-tau levels (β = 0.133 [0.054, 0.213], P = 0.0010). CSF PDGFRβ levels were positively associated with CSF neuroinflammation and synaptic markers levels. Higher CSF PDGFRβ levels were associated with lower MMSE scores at MCI (β = −1.23 [CI95% −2.33, −0.260], P = 0.015) and dementia stages (β = −2.24 [CI95% −3.62, −0.85], P = 0.0020). CSF neuroinflammation biomarkers mediated the association of CSF PDGFRβ with neurodegeneration and synaptic integrity markers. Interpretation CSF PDGFRβ, a candidate biomarker of BBB dysfunction, is increased in the early stages of neurodegenerative disorders, in association with neuroinflammation and axonal and synaptic damage. Funding Association des Anciens Internes des Hôpitaux de Paris, Edmond de Rothschild Program, 10.13039/100014808Fondation Vaincre Alzheimer, 10.13039/100010773Demensförbundet, Gamla Tjänarinnor, 10.13039/100010107Anna-Lisa och Bror Björnssons Stiftelse.

Background Little is known about the prognostic value of plasma biomarkers in mild cognitive impairment with Lewy bodies (MCI‐LB). Objectives To investigate the association of four plasma biomarkers with disease progression in MCI. Methods Plasma amyloid‐beta (Aβ) 42/40 , glial fibrillary acidic protein (GFAP), neurofilament light (NfL), and phosphorylated tau 181 (pTau181) were measured at baseline in a longitudinal MCI cohort (n = 131). Results Baseline plasma NfL was associated with increased risk of dementia/death in the entire cohort. In MCI‐LB, baseline plasma NfL, GFAP, and pTau181 were associated with increased risk of dementia/death and increased cognitive decline measured by the Addenbrooke's Cognitive Examination‐Revised. Conclusions pTau181, GFAP, and NfL are associated with more rapid disease progression in MCI‐LB and, with further validation, could be useful to support prognosis and stratification for clinical practice and treatment trials. Further work, including clinicopathological studies, is needed to understand the biological correlates of these markers in MCI‐LB. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

INTRODUCTION Elevated cardiovascular rate pressure product (RPP) has been shown to predict cardiovascular mortality and is associated with poor cognitive test performance among older adults. However, it is unclear how RPP is related to the cerebrospinal fluid (CSF) biomarkers of neurodegeneration and neuroinflammation. METHODS RPP was cross‐sectionally evaluated as a predictor of CSF biomarker levels in a cohort of 310 cognitively unimpaired late‐middle‐aged adults at risk for Alzheimer's disease. The primary outcomes were CSF levels of α‐Synuclein, glial fibrillary acidic protein, neurofilament light (NfL), soluble triggering receptor expressed in myeloid cells 2, and total tau. Further analyses examined amyloid beta (Aβ)42/Aβ40, phosphorylated tau 181 (pTau181), and pTau181/Aβ4. RESULTS RPP was positively associated with NfL (β = 0.006, R² = 0.411, p = 0.012, but Bonferroni‐corrected p ≤ 0.006) and not with other CSF biomarkers of neurodegeneration and neuroinflammation investigated in this sample. DISCUSSION A high myocardial oxygen demand at rest may be related to neuronal death and axonal degeneration in cognitively unimpaired late‐middle‐aged adults. Highlights We explored the relationship between RPP and CSF analytes. Higher RPP was associated with higher NfL but not other measured CSF biomarkers. HR was positively associated with NfL, whereas SBP was not.

Background and objectives: Plasma biomarkers of Alzheimer disease (AD), neuroinflammation, and neurodegeneration are increasingly being used in clinical trials for diagnosis and monitoring of dementia. However, their association with longitudinal structural brain MRI changes, an important outcome measure across neurodegenerative and cerebrovascular diseases, is less known. We investigated how baseline plasma biomarkers reflect MRI markers of progression over time in patients with neurodegenerative and cerebrovascular diseases. Methods: This longitudinal cohort study included patients from the Ontario Neurodegenerative Disease Research Initiative diagnosed with AD or mild cognitive impairment (AD/MCI), Parkinson disease (PD), frontotemporal dementia spectrum disorders (FTD), or cerebrovascular disease (CVD), followed annually for 2 years. Recruitment took place at specialized university-based dementia, movement disorders, and/or stroke clinics in the province of ON, Canada. MRI outcomes included markers of cerebral atrophy (ventricular CSF and regional gray matter volumes) and of small vessel disease pathology (white matter hyperintensity [WMH], perivascular spaces, and lacunar volumes). Hemorrhagic markers at baseline were also included. Plasma levels of glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), phosphorylated tau181 and tau217 (p-tau181, p-tau217), and β-amyloid (Aβ42/40) were quantified from blood samples collected at baseline using Simoa and used as predictors in linear mixed models adjusted for time (months), age, sex, apolipoprotein E (APOE)-ε4 carrier status, kidney function, vascular risk factors, microtubule-associated protein tau (MAPT) diplotypes, waist-hip circumference ratio, and disease duration. Results: We analyzed 1,240 MRIs from 473 patients (age: 69.2 ± 7.4 [range: 49-87]; 32.8% women). Elevated baseline levels of GFAP, NfL, p-tau181, and p-tau217, and to a lesser extent decreased levels of Aβ42/40, were significantly associated with more cerebral atrophy and WMH burden at baseline (|B| = 0.02 to 1.69, p = 0.044 to <0.001) and with progression over time (|B| = 0.001 to 0.028, p = 0.049 to <0.001) in the pooled disease-agnostic group. Within disease-specific cohorts, GFAP and NfL were associated with cerebral atrophy and/or small vessel disease copathology in AD/MCI, PD, FTD, or CVD. P-tau181 and p-tau217 were associated with cerebral atrophy and/or small vessel disease copathology in AD/MCI, CVD, PD-MCI, or PD-dementia. Discussion: Selected plasma biomarkers seem useful as prognosis and monitoring tools of longitudinal imaging changes within real-world populations of neurodegenerative and/or cerebrovascular diseases, and provide insight into overlap across diseases in shared pathologic burden.

Carbon fiber nanotip electrodes (CFNEs) are essential for electrochemical recordings of neurotransmitter release in confined spaces like synapses and for intracellular measurements through cytoplasm insertion. However, fabricating CFNEs with small surface areas to reduce noise remains challenging. Conventional methods struggle in controlling electrode tip size and length, reproducibility and success rate of fabrication. Here, we established a reliable, straightforward and user-friendly method to fabricate and shape CFNEs, enabling control over tip diameter, length, and tailor tip geometry. This method utilizes real-time microscopy imaging for positioning cylindrical carbon fiber microelectrodes (CFMEs) into a potassium hydroxide droplet, where a series of time- and voltage- controlled pulses enables a gentle, stepwise electrochemical etching of the CFME tips. The microscope-guided electrode positioning determines the etched region, while voltage pulse size and number control the extent of CFME tip removal. Hence, real-time adjustments to electrode positioning at the droplet’s liquid-air interface and incremental voltage pulses enable precise electrode sculpturing, akin to woodcarving with a knife. Using this method, we demonstrate the successful fabrication of short (10 μm) CFNEs with tip diameters of ~100 nm and sculptured into two distinct geometries: cone and needle shaped electrodes. These CFNEs exhibited excellent electrochemical properties and were employed for low-current noise electroanalysis of dopamine (DA) released from individual ~200 nm liposomes preloaded with DA. The data, supported by in silico simulation, suggest that electrode shape influences detection efficiency of liposome sub-populations based on their size, thus highlighting the critical role of electrode geometry in vesicle-based electroanalysis studies.

Purpose This study explores the application of machine learning to high-dimensional proteomics datasets for identifying Alzheimer’s disease (AD) biomarkers. AD, a neurodegenerative disorder affecting millions worldwide, necessitates early and accurate diagnosis for effective management. Methods We leverage Tandem Mass Tag (TMT) proteomics data from the cerebrospinal fluid (CSF) samples from the frontal cortex of patients with idiopathic normal pressure hydrocephalus (iNPH), a condition often comorbid with AD, with rare access to both lumbar and ventricular samples. Our methodology includes extensive data preprocessing to address batch effects and missing values, followed by the use of the Synthetic Minority Over-sampling Technique (SMOTE) for data augmentation to overcome the small sample size. We apply linear, and non-linear machine learning models, and ensemble methods, to compare iNPH patients with and without biomarker evidence of AD pathology ($A\beta ^-T^-$ or $A\beta ^+T^+$) in a classification task. Results We present a machine learning workflow for working with high-dimensional TMT proteomics data that addresses their inherent data characteristics. Our results demonstrate that batch effect correction has no or minor impact on the models’ performance and robust feature selection is critical for model stability and performance, especially in the high-dimensional proteomics data setting for AD diagnostics. The results further indicated that removing features with missing values produced stronger models than imputing them, and the batch effect had minimal impact on the models Our best-performing disease-progression detection model, a random forest, achieves an AUC of 0.84 (± 0.03). Conclusion We identify several novel protein biomarkers candidates, such as FABP3 and GOT1, with potential diagnostic value for AD pathology detection, suggesting the necessity of different biomarkers for AD diagnoses for patients with iNPH, and considering different biomarkers for ventricular and lumbar CSF samples. This work underscores the importance of a meticulous machine learning process in enhancing biomarker discovery. Our study also provides insights in translating biomarkers from other central nervous system diseases like iNPH, and both ventricular and lumbar CSF samples for biomarker discovery, providing a foundation for future research and clinical applications.