Longitudinal associations of serum biomarkers with early cognitive, amyloid and grey matter changes.

Blood-based biomarkers have been extensively evaluated for their diagnostic potential in Alzheimer's disease. However, their relative prognostic and monitoring capabilities for cognitive decline, amyloid-ß (Aß) accumulation and grey matter loss in cognitively unimpaired elderly require further investigation over extended time periods. This prospective cohort study in cognitively unimpaired elderly [n = 185, mean age (range) = 69 (53-84) years, 48% female] examined the prognostic and monitoring capabilities of glial fibrillary acidic protein (GFAP), neurofilament light (NfL), Aß1-42/Aß1-40 and phosphorylated tau (pTau)181 through their quantification in serum. All participants underwent baseline Aß-PET, MRI and blood sampling as well as 2-yearly cognitive testing. A subset additionally underwent Aß-PET (n = 109), MRI (n = 106) and blood sampling (n = 110) during follow-up [median time interval (range) = 6.1 (1.3-11.0) years]. Matching plasma measurements were available for Aß1-42/Aß1-40 and pTau181 (both n = 140). Linear mixed-effects models showed that high serum GFAP and NfL predicted future cognitive decline in memory (ßGFAP×Time = -0.021, PFDR = 0.007 and ßNfL×Time = -0.031, PFDR = 0.002) and language (ßGFAP×Time = -0.021, PFDR = 0.002 and ßNfL×Time = -0.018, PFDR = 0.03) domains. Low serum Aß1-42/Aß1-40 equally but independently predicted memory decline (ßAß1-42/Aß1-40×Time = -0.024, PFDR = 0.02). Whole-brain voxelwise analyses revealed that low Aß1-42/Aß1-40 predicted Aß accumulation within the precuneus and frontal regions, high GFAP and NfL predicted grey matter loss within hippocampal regions and low Aß1-42/Aß1-40 predicted grey matter loss in lateral temporal regions. Serum GFAP, NfL and pTau181 increased over time, while Aß1-42/Aß1-40 decreased only in Aß-PET-negative elderly. NfL increases associated with declining memory (ßNfLchange×Time = -0.030, PFDR = 0.006) and language (ßNfLchange×Time = -0.021, PFDR = 0.02) function and serum Aß1-42/Aß1-40 decreases associated with declining language function (ßAß1-42/Aß1-40×Time = -0.020, PFDR = 0.04). GFAP increases associated with Aß accumulation within the precuneus and NfL increases associated with grey matter loss. Baseline and longitudinal serum pTau181 only associated with Aß accumulation in restricted occipital regions. In head-to-head comparisons, serum outperformed plasma Aß1-42/Aß1-40 (ΔAUC = 0.10, PDeLong, FDR = 0.04), while both plasma and serum pTau181 demonstrated poor performance to detect asymptomatic Aß-PET positivity (AUC = 0.55 and 0.63, respectively). However, when measured with a more phospho-specific assay, plasma pTau181 detected Aß-positivity with high performance (AUC = 0.82, PDeLong, FDR < 0.007). In conclusion, serum GFAP, NfL and Aß1-42/Aß1-40 are valuable prognostic and/or monitoring tools in asymptomatic stages providing complementary information in a time- and pathology-dependent manner.

Connecting dementia risk loci to the CSF proteome identifies pathophysiological leads for dementia.

Genome-wide association studies have successfully identified many genetic risk loci for dementia, but exact biological mechanisms through which genetic risk factors contribute to dementia remains unclear. Integrating CSF proteomic data with dementia risk loci could reveal intermediate molecular pathways connecting genetic variance to the development of dementia. We tested to what extent effects of known dementia risk loci can be observed in CSF levels of 665 proteins [proximity extension-based (PEA) immunoassays] in a deeply-phenotyped mixed memory clinic cohort [n = 502, mean age (standard deviation, SD) = 64.1 (8.7) years, 181 female (35.4%)], including patients with Alzheimer's disease (AD, n = 213), dementia with Lewy bodies (DLB, n = 50) and frontotemporal dementia (FTD, n = 93), and controls (n = 146). Validation was assessed in independent cohorts (n = 99 PEA platform, n = 198, mass reaction monitoring-targeted mass spectroscopy and multiplex assay). We performed additional analyses stratified according to diagnostic status (AD, DLB, FTD and controls separately), to explore whether associations between CSF proteins and genetic variants were specific to disease or not. We identified four AD risk loci as protein quantitative trait loci (pQTL): CR1-CR2 (rs3818361, P = 1.65 × 10-8), ZCWPW1-PILRB (rs1476679, P = 2.73 × 10-32), CTSH-CTSH (rs3784539, P = 2.88 × 10-24) and HESX1-RETN (rs186108507, P = 8.39 × 10-8), of which the first three pQTLs showed direct replication in the independent cohorts. We identified one AD-specific association between a rare genetic variant of TREM2 and CSF IL6 levels (rs75932628, P = 3.90 × 10-7). DLB risk locus GBA showed positive trans effects on seven inter-related CSF levels in DLB patients only. No pQTLs were identified for FTD loci, either for the total sample as for analyses performed within FTD only. Protein QTL variants were involved in the immune system, highlighting the importance of this system in the pathophysiology of dementia. We further identified pQTLs in stratified analyses for AD and DLB, hinting at disease-specific pQTLs in dementia. Dissecting the contribution of risk loci to neurobiological processes aids in understanding disease mechanisms underlying dementia.

Methods to Discover and Validate Biofluid-Based Biomarkers in Neurodegenerative Dementias.

Neurodegenerative dementias are progressive diseases that cause neuronal network breakdown in different brain regions often because of accumulation of misfolded proteins in the brain extracellular matrix, such as amyloids or inside neurons or other cell types of the brain. Several diagnostic protein biomarkers in body fluids are being used and implemented, such as for Alzheimer's disease. However, there is still a lack of biomarkers for co-pathologies and other causes of dementia. Such biofluid-based biomarkers enable precision medicine approaches for diagnosis and treatment, allow to learn more about underlying disease processes, and facilitate the development of patient inclusion and evaluation tools in clinical trials. When designing studies to discover novel biofluid-based biomarkers, choice of technology is an important starting point. But there are so many technologies to choose among. To address this, we here review the technologies that are currently available in research settings and, in some cases, in clinical laboratory practice. This presents a form of lexicon on each technology addressing its use in research and clinics, its strengths and limitations, and a future perspective.

Structural flexibility and heterogeneity of recombinant human glial fibrillary acidic protein (GFAP).

Glial fibrillary acidic protein (GFAP) is a promising biomarker for brain and spinal cord disorders. Recent studies have highlighted the differences in the reliability of GFAP measurements in different biological matrices. The reason for these discrepancies is poorly understood as our knowledge of the protein's 3-dimensional conformation, proteoforms, and aggregation remains limited. Here, we investigate the structural properties of GFAP under different conditions. For this, we characterized recombinant GFAP proteins from various suppliers and applied hydrogen-deuterium exchange mass spectrometry (HDX-MS) to provide a snapshot of the conformational dynamics of GFAP in artificial cerebrospinal fluid (aCSF) compared to the phosphate buffer. Our findings indicate that recombinant GFAP exists in various conformational species. Furthermore, we show that GFAP dimers remained intact under denaturing conditions. HDX-MS experiments show an overall decrease in H-bonding and an increase in solvent accessibility of GFAP in aCSF compared to the phosphate buffer, with clear indications of mixed EX2 and EX1 kinetics. To understand possible structural interface regions and the evolutionary conservation profiles, we combined HDX-MS results with the predicted GFAP-dimer structure by AlphaFold-Multimer. We found that deprotected regions with high structural flexibility in aCSF overlap with predicted conserved dimeric 1B and 2B domain interfaces. Structural property predictions combined with the HDX data show an overall deprotection and signatures of aggregation in aCSF. We anticipate that the outcomes of this research will contribute to a deeper understanding of the structural flexibility of GFAP and ultimately shed light on its behavior in different biological matrices.

The GFAP proteoform puzzle: How to advance GFAP as a fluid biomarker in neurological diseases.

Glial fibrillary acidic protein (GFAP) is a well-established biomarker of reactive astrogliosis in the central nervous system because of its elevated levels following brain injury and various neurological disorders. The advent of ultra-sensitive methods for measuring low-abundant proteins has significantly enhanced our understanding of GFAP levels in the serum or plasma of patients with diverse neurological diseases. Clinical studies have demonstrated that GFAP holds promise both as a diagnostic and prognostic biomarker, including but not limited to individuals with Alzheimer's disease. GFAP exhibits diverse forms and structures, herein referred to as its proteoform complexity, encompassing conformational dynamics, isoforms and post-translational modifications (PTMs). In this review, we explore how the proteoform complexity of GFAP influences its detection, which may affect the differential diagnostic performance of GFAP in different biological fluids and can provide valuable insights into underlying biological processes. Additionally, proteoforms are often disease-specific, and our review provides suggestions and highlights areas to focus on for the development of new assays for measuring GFAP, including isoforms, PTMs, discharge mechanisms, breakdown products, higher-order species and interacting partners. By addressing the knowledge gaps highlighted in this review, we aim to support the clinical translation and interpretation of GFAP in both CSF and blood and the development of reliable, reproducible and specific prognostic and diagnostic tests. To enhance disease pathology comprehension and optimise GFAP as a biomarker, a thorough understanding of detected proteoforms in biofluids is essential.

Prospective trial of natalizumab personalised extended interval dosing by therapeutic drug monitoring in relapsing-remitting multiple sclerosis (NEXT-MS).

BACKGROUND: Extended interval dosing (EID) of natalizumab is a promising strategy to optimise treatment in multiple sclerosis (MS). Personalised EID by therapeutic drug monitoring can enable further extension of treatment intervals. METHODS: The NEXT-MS trial is an investigator-initiated prospective phase IV non-randomised study. Adults with a diagnosis of relapsing-remitting MS who received ≥6 natalizumab infusions were included in three groups: personalised EID with a target drug trough concentration of 10 µg/mL (EID10), an exploratory group of personalised EID with a target of 5 µg/mL (EID5) and standard interval dosing (SID) of 4 weeks. The primary outcome is radiological disease activity (new/newly enlarged T2 lesions) comparing the EID10 group to a historical cohort of SID (HSID). RESULTS: Results of the first phase of the NEXT-MS trial are reported here (n=376) as the study will continue with an amended protocol. In the EID10 group (n=251), incidence rate of radiological activity was 10.0 per 1000 person-years, which was non-inferior to the HSID cohort (24.7 per 1000 person-years (n=87), incidence rate difference 14.7, 90% CI -4.5 to 34.0). Incidence rate of radiological activity was 10.0 per 1000 person-years in the EID5 group (n=65), and 47.0 per 1000 person-years in the SID group (n=60). Serum neurofilament light levels did not increase over time within the EID groups. There were no cases of progressive multifocal leukoencephalopathy. CONCLUSIONS: MS disease activity is adequately controlled with personalised natalizumab EID. Interval extension to a drug trough concentration of 5 µg/mL is likely a safe target to extend natalizumab treatment intervals >6 weeks. TRIAL REGISTRATION NUMBER: NCT04225312.

Depressive Symptoms and Plasma Markers of Alzheimer's Disease and Neurodegeneration: A Coordinated Meta-Analysis of 8 Cohort Studies.

BACKGROUND: Depressive symptoms are associated with an increased risk of Alzheimer's disease (AD). There has been a recent emergence in plasma biomarkers for AD pathophysiology, such as amyloid-beta (Aß) and phosphorylated tau (p-tau), as well as for axonal damage (neurofilament light, NfL) and astrocytic activation (glial fibrillary acidic protein, GFAP). Hypothesizing that depressive symptoms may occur along the AD process, we investigated associations between plasma biomarkers of AD with depressive symptoms in individuals without dementia. METHODS: A two-stage meta-analysis was performed on 2 clinic-based and 6 population-based cohorts (N = 7210) as part of the Netherlands Consortium of Dementia Cohorts. Plasma markers (Aß42/40, p-tau181, NfL, and GFAP) were measured using Single Molecular Array (Simoa; Quanterix) assays. Depressive symptoms were measured with validated questionnaires. We estimated the cross-sectional association of each standardized plasma marker (determinants) with standardized depressive symptoms (outcome) using linear regressions, correcting for age, sex, education, and APOE ε4 allele presence, as well as subgrouping by sex and APOE ε4 allele. Effect estimates were entered into a random-effects meta-analysis. RESULTS: Mean age of participants was 71 years. The prevalence of clinically relevant depressive symptoms ranged from 1% to 22%. None of the plasma markers were associated with depressive symptoms in the meta-analyses. However, NfL was associated with depressive symptoms only in APOE ε4 carriers (ß 0.11; 95% CI: 0.05-0.17). CONCLUSIONS: Late-life depressive symptoms did not show an association to plasma biomarkers of AD pathology. However, in APOE ε4 allele carriers, a more profound role of neurodegeneration was suggested with depressive symptoms.

Neurofilament light protein as a biomarker for spinal muscular atrophy: a review and reference ranges.

Spinal muscular atrophy (SMA) is the leading genetic cause of infant mortality, characterized by progressive neuromuscular degeneration resulting from mutations in the survival motor neuron (SMN1) gene. The availability of disease-modifying therapies for SMA therapies highlights the pressing need for easily accessible and cost-effective blood biomarkers to monitor treatment response and for better disease management. Additionally, the wide implementation of newborn genetic screening programs in Western countries enables presymptomatic diagnosis of SMA and immediate treatment administration. However, the absence of monitoring and prognostic blood biomarkers for neurodegeneration in SMA hinders effective disease management. Neurofilament light protein (NfL) is a promising biomarker of neuroaxonal damage in SMA and reflects disease progression in children with SMA undergoing treatment. Recently, the European Medicines Agency issued a letter of support endorsing the potential utilization of NfL as a biomarker of pediatric neurological diseases, including SMA. Within this review, we comprehensively assess the potential applications of NfL as a monitoring biomarker for disease severity and treatment response in pediatric-onset SMA. We provide reference ranges for normal levels of serum based NfL in neurologically healthy children aged 0-18 years. These reference ranges enable accurate interpretation of NfL levels in children and can accelerate the implementation of NfL into clinical practice.

Predicting progression to Alzheimer's disease with human hippocampal progenitors exposed to serum.

Adult hippocampal neurogenesis is important for learning and memory and is altered early in Alzheimer's disease. As hippocampal neurogenesis is modulated by the circulatory systemic environment, evaluating a proxy of how hippocampal neurogenesis is affected by the systemic milieu could serve as an early biomarker for Alzheimer's disease progression. Here, we used an in vitro assay to model the impact of systemic environment on hippocampal neurogenesis. A human hippocampal progenitor cell line was treated with longitudinal serum samples from individuals with mild cognitive impairment, who either progressed to Alzheimer's disease or remained cognitively stable. Mild cognitive impairment to Alzheimer's disease progression was characterized most prominently with decreased proliferation, increased cell death and increased neurogenesis. A subset of 'baseline' cellular readouts together with education level were able to predict Alzheimer's disease progression. The assay could provide a powerful platform for early prognosis, monitoring disease progression and further mechanistic studies.

Biomarker A+T-: is this Alzheimer's disease or not? A combined CSF and pathology study.

The biological definition of Alzheimer's disease using CSF biomarkers requires abnormal levels of both amyloid (A) and tau (T). However, biomarkers and corresponding cutoffs may not always reflect the presence or absence of pathology. Previous studies suggest that up to 32% of individuals with autopsy-confirmed Alzheimer's disease show normal CSF p-tau levels in vivo, but these studies are sparse and had small sample sizes. Therefore, in three independent autopsy cohorts, we studied whether or not CSF A+T- excluded Alzheimer's disease based on autopsy. We included 215 individuals, for whom ante-mortem CSF collection and autopsy had been performed, from three cohorts: (i) the Amsterdam Dementia Cohort (ADC) [n = 80, 37 (46%) Alzheimer's disease at autopsy, time between CSF collection and death 4.5 ± 2.9 years]; (ii) the Antwerp Dementia Cohort (DEM) [n = 92, 84 (91%) Alzheimer's disease at autopsy, time CSF collection to death 1.7 ± 2.3 years]; and (iii) the Alzheimer's Disease Neuroimaging Initiative (ADNI) [n = 43, 31 (72%) Alzheimer's disease at autopsy, time CSF collection to death 5.1 ± 2.5 years]. Biomarker profiles were based on dichotomized CSF Aß1-42 and p-tau levels. The accuracy of CSF AT profiles to detect autopsy-confirmed Alzheimer's disease was assessed. Lastly, we investigated whether the concordance of AT profiles with autopsy diagnosis improved when CSF was collected closer to death in 9 (10%) DEM and 30 (70%) ADNI individuals with repeated CSF measurements available. In total, 50-73% of A+T- individuals and 100% of A+T+ individuals had Alzheimer's disease at autopsy. Amyloid status showed the highest accuracy to detect autopsy-confirmed Alzheimer's disease (accuracy, sensitivity and specificity in the ADC: 88%, 92% and 84%; in the DEM: 87%, 94% and 12%; and in the ADNI cohort: 86%, 90% and 75%, respectively). The addition of CSF p-tau did not further improve these estimates. We observed no differences in demographics or degree of Alzheimer's disease neuropathology between A+T- and A+T+ individuals with autopsy-confirmed Alzheimer's disease. All individuals with repeated CSF measurements remained stable in Aß1-42 status during follow-up. None of the Alzheimer's disease individuals with a normal p-tau status changed to abnormal; however, four (44%) DEM individuals and two (7%) ADNI individuals changed from abnormal to normal p-tau status over time, and all had Alzheimer's disease at autopsy. In summary, we found that up to 73% of A+T- individuals had Alzheimer's disease at autopsy. This should be taken into account in both research and clinical settings.

CSF proteomics in autosomal dominant Alzheimer's disease highlights parallels with sporadic disease.

Autosomal dominant Alzheimer's disease (ADAD) offers a unique opportunity to study pathophysiological changes in a relatively young population with few comorbidities. A comprehensive investigation of proteome changes occurring in ADAD could provide valuable insights into AD-related biological mechanisms and uncover novel biomarkers and therapeutic targets. Furthermore, ADAD might serve as a model for sporadic AD, but in-depth proteome comparisons are lacking. We aimed to identify dysregulated CSF proteins in ADAD and determine the degree of overlap with sporadic AD. We measured 1472 proteins in CSF of PSEN1 or APP mutation carriers (n = 22) and age- and sex-matched controls (n = 20) from the Amsterdam Dementia Cohort using proximity extension-based immunoassays (PEA). We compared protein abundance between groups with two-sided t-tests and identified enriched biological pathways. Using the same protein panels in paired plasma samples, we investigated correlations between CSF proteins and their plasma counterparts. Finally, we compared our results with recently published PEA data from an international cohort of sporadic AD (n = 230) and non-AD dementias (n = 301). All statistical analyses were false discovery rate-corrected. We detected 66 differentially abundant CSF proteins (65 increased, 1 decreased) in ADAD compared to controls (q < 0.05). The most strongly upregulated proteins (fold change >1.8) were related to immunity (CHIT1, ITGB2, SMOC2), cytoskeletal structure (MAPT, NEFL) and tissue remodelling (TMSB10, MMP-10). Significant CSF-plasma correlations were found for the upregulated proteins SMOC2 and LILR1B. Of the 66 differentially expressed proteins, 36 had been measured previously in the sporadic dementias cohort, 34 of which (94%) were also significantly upregulated in sporadic AD, with a strong correlation between the fold changes of these proteins in both cohorts (rs = 0.730, P < 0.001). Twenty-nine of the 36 proteins (81%) were also upregulated among non-AD patients with suspected AD co-pathology. This CSF proteomics study demonstrates substantial biochemical similarities between ADAD and sporadic AD, suggesting involvement of the same biological processes. Besides known AD-related proteins, we identified several relatively novel proteins, such as TMSB10, MMP-10 and SMOC2, which have potential as novel biomarkers. With shared pathophysiological CSF changes, ADAD study findings might be translatable to sporadic AD, which could greatly expedite therapy development.

Neurofilament light chain but not glial fibrillary acidic protein is a potential biomarker of overt hepatic encephalopathy in patients with cirrhosis.

INTRODUCTION AND OBJECTIVES: Hepatic encephalopathy (HE) is a frequent complication of cirrhosis and may cause cerebral damage. Neurodegenerative diseases can induce the release of neuroproteins like neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in body fluids, including blood plasma. We investigated whether NfL and GFAP could serve as potential diagnostic plasma biomarkers for overt HE (oHE). MATERIALS AND METHODS: We included 85 patients from three prospective cohorts with different stages of liver disease and HE severity. The following patients were included: 1) 34 patients with primary sclerosing cholangitis (PSC) with compensated disease; 2) 17 patients with advanced liver disease without oHE before elective transjugular intrahepatic portosystemic shunt (TIPS) placement; 3) 17 intensive care unit (ICU) patients with oHE and 17 ICU patients without cirrhosis or oHE. Plasma NfL and GFAP were measured using single molecule assays. RESULTS: ICU oHE patients had higher NfL concentrations compared to pre-TIPS patients or ICU controls (p < 0.05, each). Median GFAP concentrations were equal in the ICU oHE and pre-TIPS patients or ICU controls. Plasma NfL and GFAP concentrations correlated with Model for End-Stage Liver Disease (MELD) scores (R = 0.58 and R = 0.40, p < 0.001, each). CONCLUSIONS: Plasma NfL deserves further evaluation as potential diagnostic biomarker for oHE and correlates with the MELD score.

Revised criteria for diagnosis and staging of Alzheimer's disease: Alzheimer's Association Workgroup.

The National Institute on Aging and the Alzheimer's Association convened three separate work groups in 2011 and single work groups in 2012 and 2018 to create recommendations for the diagnosis and characterization of Alzheimer's disease (AD). The present document updates the 2018 research framework in response to several recent developments. Defining diseases biologically, rather than based on syndromic presentation, has long been standard in many areas of medicine (e.g., oncology), and is becoming a unifying concept common to all neurodegenerative diseases, not just AD. The present document is consistent with this principle. Our intent is to present objective criteria for diagnosis and staging AD, incorporating recent advances in biomarkers, to serve as a bridge between research and clinical care. These criteria are not intended to provide step-by-step clinical practice guidelines for clinical workflow or specific treatment protocols, but rather serve as general principles to inform diagnosis and staging of AD that reflect current science. HIGHLIGHTS: We define Alzheimer's disease (AD) to be a biological process that begins with the appearance of AD neuropathologic change (ADNPC) while people are asymptomatic. Progression of the neuropathologic burden leads to the later appearance and progression of clinical symptoms. Early-changing Core 1 biomarkers (amyloid positron emission tomography [PET], approved cerebrospinal fluid biomarkers, and accurate plasma biomarkers [especially phosphorylated tau 217]) map onto either the amyloid beta or AD tauopathy pathway; however, these reflect the presence of ADNPC more generally (i.e., both neuritic plaques and tangles). An abnormal Core 1 biomarker result is sufficient to establish a diagnosis of AD and to inform clinical decision making throughout the disease continuum. Later-changing Core 2 biomarkers (biofluid and tau PET) can provide prognostic information, and when abnormal, will increase confidence that AD is contributing to symptoms. An integrated biological and clinical staging scheme is described that accommodates the fact that common copathologies, cognitive reserve, and resistance may modify relationships between clinical and biological AD stages.

Development of thresholds and a visualization tool for use of a blood test in routine clinical dementia practice.

INTRODUCTION: We developed a multimarker blood test result interpretation tool for the clinical dementia practice, including phosphorylated (P-)tau181, amyloid-beta (Abeta)42/40, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL). METHODS: We measured the plasma biomarkers with Simoa (n = 1199), applied LASSO regression for biomarker selection and receiver operating characteristics (ROC) analyses to determine diagnostic accuracy. We validated our findings in two independent cohorts and constructed a visualization approach. RESULTS: P-tau181, GFAP, and NfL were selected. This combination had area under the curve (AUC) = 83% to identify amyloid positivity in pre-dementia stages, AUC = 87%-89% to differentiate Alzheimer's or controls from frontotemporal dementia, AUC = 74%-76% to differentiate Alzheimer's or controls from dementia with Lewy bodies. Highly reproducible AUCs were obtained in independent cohorts. The resulting visualization tool includes UpSet plots to visualize the stand-alone biomarker results and density plots to visualize the biomarker results combined. DISCUSSION: Our multimarker blood test interpretation tool is ready for testing in real-world clinical dementia settings. HIGHLIGHTS: We developed a multimarker blood test interpretation tool for clinical dementia practice. Our interpretation tool includes plasma biomarkers P-tau, GFAP, and NfL. Our tool is particularly useful for Alzheimer's and frontotemporal dementia diagnosis.

CSF proteomic profiles of neurodegeneration biomarkers in Alzheimer's disease.

INTRODUCTION: We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics. METHODS: Individuals without dementia were classified as A+ (CSF amyloid beta [Aß]42), T+ (CSF phosphorylated tau181), and N+ or N- based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance. RESULTS: Only a few individuals were A+T+Ng-. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng- and A+T+NfL-, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV-, A+T+HCV+ showed few proteomic changes, associated with oxidative stress. DISCUSSION: Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology. HIGHLIGHTS: In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau.

Novel avenues of tau research.

INTRODUCTION: The pace of innovation has accelerated in virtually every area of tau research in just the past few years. METHODS: In February 2022, leading international tau experts convened to share selected highlights of this work during Tau 2022, the second international tau conference co-organized and co-sponsored by the Alzheimer's Association, CurePSP, and the Rainwater Charitable Foundation. RESULTS: Representing academia, industry, and the philanthropic sector, presenters joined more than 1700 registered attendees from 59 countries, spanning six continents, to share recent advances and exciting new directions in tau research. DISCUSSION: The virtual meeting provided an opportunity to foster cross-sector collaboration and partnerships as well as a forum for updating colleagues on research-advancing tools and programs that are steadily moving the field forward.

Blood DNA methylomic signatures associated with CSF biomarkers of Alzheimer's disease in the EMIF-AD study.

INTRODUCTION: We investigated blood DNA methylation patterns associated with 15 well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) pathophysiology, neuroinflammation, and neurodegeneration. METHODS: We assessed DNA methylation in 885 blood samples from the European Medical Information Framework for Alzheimer's Disease (EMIF-AD) study using the EPIC array. RESULTS: We identified Bonferroni-significant differential methylation associated with CSF YKL-40 (five loci) and neurofilament light chain (NfL; seven loci) levels, with two of the loci associated with CSF YKL-40 levels correlating with plasma YKL-40 levels. A co-localization analysis showed shared genetic variants underlying YKL-40 DNA methylation and CSF protein levels, with evidence that DNA methylation mediates the association between genotype and protein levels. Weighted gene correlation network analysis identified two modules of co-methylated loci correlated with several amyloid measures and enriched in pathways associated with lipoproteins and development. DISCUSSION: We conducted the most comprehensive epigenome-wide association study (EWAS) of AD-relevant CSF biomarkers to date. Future work should explore the relationship between YKL-40 genotype, DNA methylation, and protein levels in the brain. HIGHLIGHTS: Blood DNA methylation was assessed in the EMIF-AD MBD study. Epigenome-wide association studies (EWASs) were performed for 15 Alzheimer's disease (AD)-relevant cerebrospinal fluid (CSF) biomarker measures. Five Bonferroni-significant loci were associated with YKL-40 levels and seven with neurofilament light chain (NfL). DNA methylation in YKL-40 co-localized with previously reported genetic variation. DNA methylation potentially mediates the effect of single-nucleotide polymorphisms (SNPs) in YKL-40 on CSF protein levels.

Blood-based multivariate methylation risk score for cognitive impairment and dementia.

INTRODUCTION: The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood-derived DNA methylation as a promising tool for early dementia risk detection. METHODS: In conjunction with an extensive array of machine learning techniques, we employed whole blood genome-wide DNA methylation data as a surrogate for 14 modifiable and non-modifiable factors in the assessment of dementia risk in independent dementia cohorts. RESULTS: We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross-sectionally, independent of age and sex (P = 2.0 × 10-3). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)-Learning = 2.47) and Parkinson's disease (hazard ratio for MCI/dementia = 2.59). DISCUSSION: Our work shows the potential of employing blood-derived DNA methylation data in the assessment of dementia risk. HIGHLIGHTS: We used whole blood DNA methylation as a surrogate for 14 dementia risk factors. Created a multivariate methylation risk score for predicting cognitive impairment. Emphasized the role of machine learning and omics data in predicting dementia. The score predicts cognitive impairment development at the population level.

Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients.

INTRODUCTION: White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-ß1-42 (Aß42)-positive status. METHODS: Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume. RESULTS: VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001). DISCUSSION: Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter. HIGHLIGHTS: Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aß42 status in 11 memory clinic cohorts. Aß42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.

Deciphering Protein Secretion from the Brain to Cerebrospinal Fluid for Biomarker Discovery.

Cerebrospinal fluid (CSF) is an essential matrix for the discovery of neurological disease biomarkers. However, the high dynamic range of protein concentrations in CSF hinders the detection of the least abundant protein biomarkers by untargeted mass spectrometry. It is thus beneficial to gain a deeper understanding of the secretion processes within the brain. Here, we aim to explore if and how the secretion of brain proteins to the CSF can be predicted. By combining a curated CSF proteome and the brain elevated proteome of the Human Protein Atlas, brain proteins were classified as CSF or non-CSF secreted. A machine learning model was trained on a range of sequence-based features to differentiate between CSF and non-CSF groups and effectively predict the brain origin of proteins. The classification model achieves an area under the curve of 0.89 if using high confidence CSF proteins. The most important prediction features include the subcellular localization, signal peptides, and transmembrane regions. The classifier generalized well to the larger brain detected proteome and is able to correctly predict novel CSF proteins identified by affinity proteomics. In addition to elucidating the underlying mechanisms of protein secretion, the trained classification model can support biomarker candidate selection.