CSF proteome profiling across the Alzheimer's disease spectrum reflects the multifactorial nature of the disease and identifies specific biomarker panels

Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and implicates causal proteins for Alzheimer's disease

The integration of quantitative trait loci (QTLs) with disease genome-wide association studies (GWASs) has proven successful in prioritizing candidate genes at disease-associated loci. QTL mapping has been focused on multi-tissue expression QTLs or plasma protein QTLs (pQTLs). We generated a cerebrospinal fluid (CSF) pQTL atlas by measuring 6,361 proteins in 3,506 samples. We identified 3,885 associations for 1,883 proteins, including 2,885 new pQTLs, demonstrating unique genetic regulation in CSF. We identified CSF-enriched pleiotropic regions on chromosome (chr)3q28 near OSTN and chr19q13.32 near APOE that were enriched for neuron specificity and neurological development. We integrated our associations with Alzheimer's disease (AD) through proteome-wide association study (PWAS), colocalization and Mendelian randomization and identified 38 putative causal proteins, 15 of which have drugs available. Finally, we developed a proteomics-based AD prediction model that outperforms genetics-based models. These findings will be instrumental to further understand the biology and identify causal and druggable proteins for brain and neurological traits.

Large-scale proteomic analyses of incident Alzheimer's disease reveal new pathophysiological insights and potential therapeutic targets

Pathophysiological evolutions in early-stage Alzheimer's disease (AD) are not well understood. We used data of 2923 Olink plasma proteins from 51,296 non-demented middle-aged adults. During a follow-up of 15 years, 689 incident AD cases occurred. Cox-proportional hazard models were applied to identify AD-associated proteins in different time intervals. Through linking to protein categories, changing sequences of protein z-scores can reflect pathophysiological evolutions. Mendelian randomization using blood protein quantitative loci data provided causal evidence for potentially druggable proteins. We identified 48 AD-related proteins, with CEND1, GFAP, NEFL, and SYT1 being top hits in both near-term (HR:1.15-1.77; P:9.11 × 10-65-2.78 × 10-6) and long-term AD risk (HR:1.20-1.54; P:2.43 × 10-21-3.95 × 10-6). These four proteins increased 15 years before AD diagnosis and progressively escalated, indicating early and sustained dysfunction in synapse and neurons. Proteins related to extracellular matrix organization, apoptosis, innate immunity, coagulation, and lipid homeostasis showed early disturbances, followed by malfunctions in metabolism, adaptive immunity, and final synaptic and neuronal loss. Combining CEND1, GFAP, NEFL, and SYT1 with demographics generated desirable predictions for 10-year (AUC = 0.901) and over-10-year AD (AUC = 0.864), comparable to full model. Mendelian randomization supports potential genetic link between CEND1, SYT1, and AD as outcome. Our findings highlight the importance of exploring the pathophysiological evolutions in early stages of AD, which is essential for the development of early biomarkers and precision therapeutics.

CSF proteins of inflammation, proteolysis and lipid transport define preclinical AD and progression to AD dementia in cognitively unimpaired individuals

This preclinical AD CSF proteome study identified a panel of 12-CSF markers detecting amyloid positivity and clinical progression to AD with high accuracy; some of these CSF proteins related to immune function, neurotrophic processes, energy metabolism and endolysosomal functioning (e.g., ITGB2, CLEC5A, IGFBP-1, CST3) changed before amyloid positivity is established.

Isoform- and cell-state-specific APOE homeostasis and function

Apolipoprotein E is the major lipid transporter in the brain and an important player in neuron-astrocyte metabolic coupling. It ensures the survival of neurons under stressful conditions and hyperactivity by nourishing and detoxifying them. Apolipoprotein E polymorphism, combined with environmental stresses and/or age-related alterations, influences the risk of developing late-onset Alzheimer's disease. In this review, we discuss our current knowledge of how apolipoprotein E homeostasis, i.e. its synthesis, secretion, degradation, and lipidation, is affected in Alzheimer's disease.

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.

Proteomic changes in Alzheimer's disease associated with progressive Aβ plaque and tau tangle pathologies

Proteomics can shed light on the dynamic and multifaceted alterations in neurodegenerative disorders like Alzheimer's disease (AD). Combining radioligands measuring β-amyloid (Aβ) plaques and tau tangles with cerebrospinal fluid proteomics, we uncover molecular events mirroring different stages of AD pathology in living humans. We found 127 differentially abundant proteins (DAPs) across the AD spectrum. The strongest Aβ-related proteins were mainly expressed in glial cells and included SMOC1 and ITGAM. A dozen proteins linked to ATP metabolism and preferentially expressed in neurons were independently associated with tau tangle load and tau accumulation. Only 20% of the DAPs were also altered in other neurodegenerative diseases, underscoring AD's distinct proteome. Two co-expression modules related, respectively, to protein metabolism and microglial immune response encompassed most DAPs, with opposing, staggered trajectories along the AD continuum. We unveil protein signatures associated with Aβ and tau proteinopathy in vivo, offering insights into complex neural responses and potential biomarkers and therapeutics targeting different disease stages.

Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease

Recent expansion of proteomic coverage opens unparalleled avenues to unveil new biomarkers of Alzheimer's disease (AD). Among 6,361 cerebrospinal fluid (CSF) proteins analysed from the ADNI database, YWHAG performed best in diagnosing both biologically (AUC = 0.969) and clinically (AUC = 0.857) defined AD. Four- (YWHAG, SMOC1, PIGR and TMOD2) and five- (ACHE, YWHAG, PCSK1, MMP10 and IRF1) protein panels greatly improved the accuracy to 0.987 and 0.975, respectively. Their superior performance was validated in an independent external cohort and in discriminating autopsy-confirmed AD versus non-AD, rivalling even canonical CSF ATN biomarkers. Moreover, they effectively predicted the clinical progression to AD dementia and were strongly associated with AD core biomarkers and cognitive decline. Synaptic, neurogenic and infectious pathways were enriched in distinct AD stages. Mendelian randomization did not support the significant genetic link between CSF proteins and AD. Our findings revealed promising high-performance biomarkers for AD diagnosis and prediction, with implications for clinical trials targeting different pathomechanisms.

Integrative proteomics identifies a conserved Aβ amyloid responsome, novel plaque proteins, and pathology modifiers in Alzheimer's disease

Alzheimer's disease (AD) is a complex neurodegenerative disorder that develops over decades. AD brain proteomics reveals vast alterations in protein levels and numerous altered biologic pathways. Here, we compare AD brain proteome and network changes with the brain proteomes of amyloid β (Aβ)-depositing mice to identify conserved and divergent protein networks with the conserved networks identifying an Aβ amyloid responsome. Proteins in the most conserved network (M42) accumulate in plaques, cerebrovascular amyloid (CAA), and/or dystrophic neuronal processes, and overexpression of two M42 proteins, midkine (Mdk) and pleiotrophin (PTN), increases the accumulation of Aβ in plaques and CAA. M42 proteins bind amyloid fibrils in vitro, and MDK and PTN co-accumulate with cardiac transthyretin amyloid. M42 proteins appear intimately linked to amyloid deposition and can regulate amyloid deposition, suggesting that they are pathology modifiers and thus putative therapeutic targets. We posit that amyloid-scaffolded accumulation of numerous M42+ proteins is a central mechanism mediating downstream pathophysiology in AD.

Large-scale CSF proteome profiling identifies biomarkers for accurate diagnosis of Frontotemporal Dementia

Diagnosis of Frontotemporal dementia (FTD) and the specific underlying neuropathologies (frontotemporal lobar degeneration; FTLD- Tau and FTLD-TDP) is challenging, and thus fluid biomarkers are needed to improve diagnostic accuracy. We used proximity extension assays to analyze 665 proteins in cerebrospinal fluid (CSF) samples from a multicenter cohort including patients with FTD (n = 189), Alzheimer's Disease dementia (AD; n = 232), and cognitively unimpaired individuals (n = 196). In a subset, FTLD neuropathology was determined based on phenotype or genotype (FTLD-Tau = 87 and FTLD-TDP = 68). Forty three proteins were differentially regulated in FTD compared to controls and AD, reflecting axon development, regulation of synapse assembly, and cell-cell adhesion mediator activity pathways. Classification analysis identified a 14- and 13-CSF protein panel that discriminated FTD from controls (AUC: 0.96) or AD (AUC: 0.91). Custom multiplex panels confirmed the highly accurate discrimination between FTD and controls (AUCs > 0.96) or AD (AUCs > 0.88) in three validation cohorts, including one with autopsy confirmation (AUCs > 0.90). Six proteins were differentially regulated between FTLD-TDP and FTLD-Tau, but no reproducible classification model could be generated (AUC: 0.80). Overall, this study introduces novel FTD-specific biomarker panels with potential use in diagnostic setting.

Biomarkers in Alzheimer's disease

Alzheimer's disease (AD) is among the most common neurodegenerative disorders. AD is characterized by deposition of neurofibrillary tangles and amyloid plaques, leading to associated secondary pathologies, progressive neurodegeneration, and eventually death. Currently used diagnostics are largely image-based, lack accuracy and do not detect early disease, ie, prior to onset of symptoms, thus limiting treatment options and outcomes. Although biomarkers such as amyloid-β and tau protein in cerebrospinal fluid have gained much attention, these are generally limited to disease progression. Unfortunately, identification of biomarkers for early and accurate diagnosis remains a challenge. As such, body fluids such as sweat, serum, saliva, mucosa, tears, and urine are under investigation as alternative sources for biomarkers that can aid in early disease detection. This review focuses on biomarkers identified through proteomics in various biofluids and their potential for early and accurate diagnosis of AD.

Proteomic analysis of Alzheimer's disease cerebrospinal fluid reveals alterations associated with APOE ε4 and atomoxetine treatment

Alzheimer's disease (AD) is currently defined by the aggregation of amyloid-β (Aβ) and tau proteins in the brain. Although biofluid biomarkers are available to measure Aβ and tau pathology, few markers are available to measure the complex pathophysiology that is associated with these two cardinal neuropathologies. Here, we characterized the proteomic landscape of cerebrospinal fluid (CSF) changes associated with Aβ and tau pathology in 300 individuals using two different proteomic technologies-tandem mass tag mass spectrometry and SomaScan. Integration of both data types allowed for generation of a robust protein coexpression network consisting of 34 modules derived from 5242 protein measurements, including disease-relevant modules associated with autophagy, ubiquitination, endocytosis, and glycolysis. Three modules strongly associated with the apolipoprotein E ε4 (APOE ε4) AD risk genotype mapped to oxidant detoxification, mitogen-associated protein kinase signaling, neddylation, and mitochondrial biology and overlapped with a previously described lipoprotein module in serum. Alterations of all three modules in blood were associated with dementia more than 20 years before diagnosis. Analysis of CSF samples from an AD phase 2 clinical trial of atomoxetine (ATX) demonstrated that abnormal elevations in the glycolysis CSF module-the network module most strongly correlated to cognitive function-were reduced by ATX treatment. Clustering of individuals based on their CSF proteomic profiles revealed heterogeneity of pathological changes not fully reflected by Aβ and tau.

Utilization of fluid-based biomarkers as endpoints in disease-modifying clinical trials for Alzheimer's disease: a systematic review

BACKGROUND

Clinical trials in Alzheimer's disease (AD) had high failure rates for several reasons, including the lack of biological endpoints. Fluid-based biomarkers may present a solution to measure biologically relevant endpoints. It is currently unclear to what extent fluid-based biomarkers are applied to support drug development.

METHODS

We systematically reviewed 272 trials (clinicaltrials.gov) with disease-modifying therapies starting between 01-01-2017 and 01-01-2024 and identified which CSF and/or blood-based biomarker endpoints were used per purpose and trial type.

RESULTS

We found that 44% (N = 121) of the trials employed fluid-based biomarker endpoints among which the CSF ATN biomarkers (Aβ (42/40), p/tTau) were used most frequently. In blood, inflammatory cytokines, NFL, and pTau were most frequently employed. Blood- and CSF-based biomarkers were used approximately equally. Target engagement biomarkers were used in 26% (N = 72) of the trials, mainly in drugs targeting inflammation and amyloid. Lack of target engagement markers is most prominent in synaptic plasticity/neuroprotection, neurotransmitter receptor, vasculature, epigenetic regulators, proteostasis and, gut-brain axis targeting drugs. Positive biomarker results did not always translate to cognitive effects, most commonly the small significant reductions in CSF tau isoforms that were seen following anti-Tau treatments. On the other hand, the positive anti-amyloid trials results on cognitive function were supported by clear effect in most fluid markers.

CONCLUSIONS

As the field moves towards primary prevention, we expect an increase in the use of fluid-based biomarkers to determine disease modification. Use of blood-based biomarkers will rapidly increase, but CSF markers remain important to determine brain-specific treatment effects. With improving techniques, new biomarkers can be found to diversify the possibilities in measuring treatment effects and target engagement. It remains important to interpret biomarker results in the context of the trial and be aware of the performance of the biomarker. Diversifying biomarkers could aid in the development of surrogacy biomarkers for different drug targets.

CSF biomarkers of immune activation and Alzheimer's disease for predicting cognitive impairment risk in the elderly

The immune system substantially influences age-related cognitive decline and Alzheimer's disease (AD) progression, affected by genetic and environmental factors. In a Mayo Clinic Study of Aging cohort, we examined how risk factors like APOE genotype, age, and sex affect inflammatory molecules and AD biomarkers in cerebrospinal fluid (CSF). Among cognitively unimpaired individuals over 65 (N = 298), we measured 365 CSF inflammatory molecules, finding age, sex, and diabetes status predominantly influencing their levels. We observed age-related correlations with AD biomarkers such as total tau, phosphorylated tau-181, neurofilament light chain (NfL), and YKL40. APOE4 was associated with lower Aβ42 and higher SNAP25 in CSF. We explored baseline variables predicting cognitive decline risk, finding age, CSF Aβ42, NfL, and REG4 to be independently correlated. Subjects with older age, lower Aβ42, higher NfL, and higher REG4 at baseline had increased cognitive impairment risk during follow-up. This suggests that assessing CSF inflammatory molecules and AD biomarkers could predict cognitive impairment risk in the elderly.

Cerebrospinal fluid protein biomarkers in Parkinson's disease

Proteomic profiling is an effective way to identify biomarkers for Parkinson's disease (PD). Cerebrospinal fluid (CSF) has direct connectivity with the brain and could be a source of finding biomarkers and their clinical implications. Comparative proteomic profiling has shown that a group of differentially displayed proteins exist. The studies performed using conventional and classical tools also supported the occurrence of these proteins. Many studies have highlighted the potential of CSF proteomic profiling for biomarker identification and their clinical applications. Some of these proteins are useful for disease diagnosis and prediction. Proteomic profiling of CSF also has immense potential to distinguish PD from similar neurodegenerative disorders. A few protein biomarkers help in fundamental knowledge generation and clinical interpretation. However, the specific biomarker of PD is not yet known. The use of proteomic approaches in clinical settings is also rare. A large-scale, multi-centric, multi-population and multi-continental study using multiple proteomic tools is warranted. Such a study can provide valuable, comprehensive and reliable information for a better understanding of PD and the development of specific biomarkers. The current article sheds light on the role of CSF proteomic profiling in identifying biomarkers of PD and their clinical implications. The article also explains the achievements, obstacles and hopes for future directions of this approach.

Proximity extension assay-based proteomics studies in neurodegenerative disorders and multiple sclerosis

Neurodegenerative diseases impact the structure and operation of the nervous system, causing progressive and irreparable harm. Efforts for distinguishing neurodegenerative diseases in their early stages are continuing. Despite several biomarkers being identified, there is always search for more accurate and abundant ones. Additionally, it can be difficult to pinpoint the precise neurodegenerative disorder affecting a patient as the symptoms of these conditions frequently overlap. Numerous studies have shown that pathological changes occur years before clinical signs appear. Therefore, it is crucial to discover blood-based biomarkers for neurodegenerative diseases for easier and earlier diagnosis. Proximity extension assay is a unique proteomics method that uses antibodies linked to oligonucleotides for quantifying proteins with real-time PCR. Proximity extension assay can identify even low-quantity proteins using a small volume of specimens with increased sensitivity compared to conventional methods. In this article, we reviewed the employment of proximity extension assay technology to detect biomarkers or protein profiles for several neurodegenerative diseases.

Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures for asymptomatic and symptomatic Alzheimer's disease

Changes in Amyloid-β (A), hyperphosphorylated Tau (T) in brain and cerebrospinal fluid (CSF) precedes AD symptoms, making CSF proteome a potential avenue to understand the pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 proteins dysregulated in AD, that were further validated in a third totally independent cohort. Machine learning was implemented to create and validate highly accurate and replicable (AUC>0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD and those AD cases with faster progression. The associated proteins cluster in four different protein pseudo-trajectories groups spanning the AD continuum and were enrichment in specific pathways including neuronal death, apoptosis and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfuncton(mid-stages), brain plasticity and longevity (mid-stages) and late microglia-neuron crosstalk (late stages).

Plasma Biomarker Strategy for Selecting Patients With Alzheimer Disease for Antiamyloid Immunotherapies

Importance

Antiamyloid immunotherapies against Alzheimer disease (AD) are emerging. Scalable, cost-effective tools will be needed to identify amyloid β (Aβ)-positive patients without an advanced stage of tau pathology who are most likely to benefit from these therapies. Blood-based biomarkers might reduce the need to use cerebrospinal fluid (CSF) or positron emission tomography (PET) for this.

Objective

To evaluate plasma biomarkers for identifying Aβ positivity and stage of tau accumulation.

Design, Setting, and Participants

The cohort study (BioFINDER-2) was a prospective memory-clinic and population-based study. Participants with cognitive concerns were recruited from 2017 to 2022 and divided into a training set (80% of the data) and test set (20%).

Exposure

Baseline values for plasma phosphorylated tau 181 (p-tau181), p-tau217, p-tau231, N-terminal tau, glial fibrillary acidic protein, and neurofilament light chain.

Main Outcomes and Measures

Performance to classify participants by Aβ status (defined by Aβ-PET or CSF Aβ42/40) and tau status (tau PET). Number of hypothetically saved PET scans in a plasma biomarker-guided workflow.

Results

Of a total 912 participants, there were 499 males (54.7%) and 413 females (45.3%), and the mean (SD) age was 71.1 (8.49) years. Among the biomarkers, plasma p-tau217 was most strongly associated with Aβ positivity (test-set area under the receiver operating characteristic curve [AUC] = 0.94; 95% CI, 0.90-0.97). A 2-cut-point procedure was evaluated, where only participants with ambiguous plasma p-tau217 values (17.1% of the participants in the test set) underwent CSF or PET to assign definitive Aβ status. This procedure had an overall sensitivity of 0.94 (95% CI, 0.90-0.98) and a specificity of 0.86 (95% CI, 0.77-0.95). Next, plasma biomarkers were used to differentiate low-intermediate vs high tau-PET load among Aβ-positive participants. Plasma p-tau217 again performed best, with the test AUC = 0.92 (95% CI, 0.86-0.97), without significant improvement when adding any of the other plasma biomarkers. At a false-negative rate less than 10%, the use of plasma p-tau217 could avoid 56.9% of tau-PET scans needed to identify high tau PET among Aβ-positive participants. The results were validated in an independent cohort (n = 118).

Conclusions and Relevance

This study found that algorithms using plasma p-tau217 can accurately identify most Aβ-positive individuals, including those likely to have a high tau load who would require confirmatory tau-PET imaging. Plasma p-tau217 measurements may substantially reduce the number of invasive and costly confirmatory tests required to identify individuals who would likely benefit from antiamyloid therapies.

Aβ Amyloid Scaffolds the Accumulation of Matrisome and Additional Proteins in Alzheimer's Disease

We report a highly significant correlation in brain proteome changes between Alzheimers disease (AD) and CRND8 APP695NL/F transgenic mice. However, integrating protein changes observed in the CRND8 mice with co-expression networks derived from human AD, reveals both conserved and divergent module changes. For the most highly conserved module (M42, matrisome) we find many proteins accumulate in plaques, cerebrovascular amyloid (CAA), dystrophic processes, or a combination thereof. Overexpression of two M42 proteins, midkine (Mdk) and pleiotrophin (PTN), in CRND8 mice brains leads to increased accumulation of A β ; in plaques and in CAA; further, recombinant MDK and PTN enhance A β ; aggregation into amyloid. Multiple M42 proteins, annotated as heparan sulfate binding proteins, bind to fibrillar A β 42 and a non-human amyloid fibril in vitro. Supporting this binding data, MDK and PTN co-accumulate with transthyretin (TTR) amyloid in the heart and islet amyloid polypeptide (IAPP) amyloid in the pancreas. Our findings establish several critical insights. Proteomic changes in modules observed in human AD brains define an A β ; amyloid responsome that is well conserved from mouse model to human. Further, distinct amyloid structures may serve as scaffolds, facilitating the co-accumulation of proteins with signaling functions. We hypothesize that this co-accumulation may contribute to downstream pathological sequalae. Overall, this contextualized understanding of proteomic changes and their interplay with amyloid deposition provides valuable insights into the complexity of AD pathogenesis and potential biomarkers and therapeutic targets.

LRPAP1 is released from activated microglia and inhibits microglial phagocytosis and amyloid beta aggregation

Low-density lipoprotein receptor-related protein-associated protein 1 (LRPAP1), also known as receptor associated protein (RAP), is an endoplasmic reticulum (ER) chaperone and inhibitor of LDL receptor related protein 1 (LRP1) and related receptors. These receptors have dozens of physiological ligands and cell functions, but it is not known whether cells release LRPAP1 physiologically at levels that regulate these receptors and cell functions. We used mouse BV-2 and human CHME3 microglial cell lines, and found that microglia released nanomolar levels of LRPAP1 when inflammatory activated by lipopolysaccharide or when ER stressed by tunicamycin. LRPAP1 was found on the surface of live activated and non-activated microglia, and anti-LRPAP1 antibodies induced internalization. Addition of 10 nM LRPAP1 inhibited microglial phagocytosis of isolated synapses and cells, and the uptake of Aβ. LRPAP1 also inhibited Aβ aggregation in vitro. Thus, activated and stressed microglia release LRPAP1 levels that can inhibit phagocytosis, Aβ uptake and Aβ aggregation. We conclude that LRPAP1 release may regulate microglial functions and Aβ pathology, and more generally that extracellular LRPAP1 may be a physiological and pathological regulator of a wide range of cell functions.

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.

Thimet oligopeptidase (THOP 1) distribution in cane toad (Bufo Marinus, Linnaeus, 1758) brain

Thimet oligopeptides (THOP 1) is a metal-dependent peptidase involved in the metabolism of neuropeptides and the presentation of peptides via MHC-1. It has been shown to play a role in the regulation of protein-protein interactions and the metabolism of intracellular peptides. THOP 1 is associated with important biological processes such as metabolism and neurodegenerative diseases, among others. The objective of this study is to elucidate the distribution of THOP 1 in the Bufo marinus brain. The analysis of THOP 1 amino acid sequences indicates that they have been conserved throughout evolution, with significant homology observed across various phyla. When comparing amphibians with other species, more than 70% identity can be identified. Immunohistochemistry analysis of the toad's brain has demonstrated that the enzyme has a ubiquitous distribution, consistent with previous findings in mammals. THOP 1 can be found in important areas of the brain, such as bulb, thalamic nuclei, striatum, hypothalamus, and among others. Nonetheless, THOP 1 is consistently localized within the nucleus, a pattern also observed in the rat brain. Therefore, based on these results, the toad appears to be an excellent model for studying the general biology of THOP 1, given the substantial homology of this enzyme with mammals and its similarity in distribution within the brain.

Proteomic Network Analysis of Alzheimer's Disease Cerebrospinal Fluid Reveals Alterations Associated with APOE ε4 Genotype and Atomoxetine Treatment

Alzheimer's disease (AD) is currently defined at the research level by the aggregation of amyloid-β (Aβ) and tau proteins in brain. While biofluid biomarkers are available to measure Aβ and tau pathology, few biomarkers are available to measure the complex pathophysiology that is associated with these two cardinal neuropathologies. Here we describe the proteomic landscape of cerebrospinal fluid (CSF) changes associated with Aβ and tau pathology in 300 individuals as assessed by two different proteomic technologies-tandem mass tag (TMT) mass spectrometry and SomaScan. Harmonization and integration of both data types allowed for generation of a robust protein co-expression network consisting of 34 modules derived from 5242 protein measurements, including disease-relevant modules associated with autophagy, ubiquitination, endocytosis, and glycolysis. Three modules strongly associated with the apolipoprotein E ε4 (APOE ε4) AD risk genotype mapped to oxidant detoxification, mitogen associated protein kinase (MAPK) signaling, neddylation, and mitochondrial biology, and overlapped with a previously described lipoprotein module in serum. Neddylation and oxidant detoxification/MAPK signaling modules had a negative association with APOE ε4 whereas the mitochondrion module had a positive association with APOE ε4. The directions of association were consistent between CSF and blood in two independent longitudinal cohorts, and altered levels of all three modules in blood were associated with dementia over 20 years prior to diagnosis. Dual-proteomic platform analysis of CSF samples from an AD phase 2 clinical trial of atomoxetine (ATX) demonstrated that abnormal elevations in the glycolysis CSF module-the network module most strongly correlated to cognitive function-were reduced by ATX treatment. Individuals who had more severe glycolytic changes at baseline responded better to ATX. Clustering of individuals based on their CSF proteomic network profiles revealed ten groups that did not cleanly stratify by Aβ and tau status, underscoring the heterogeneity of pathological changes not fully reflected by Aβ and tau. AD biofluid proteomics holds promise for the development of biomarkers that reflect diverse pathologies for use in clinical trials and precision medicine.

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.

CSF proteome profiling reveals biomarkers to discriminate dementia with Lewy bodies from Alzheimer´s disease

Diagnosis of dementia with Lewy bodies (DLB) is challenging and specific biofluid biomarkers are highly needed. We employed proximity extension-based assays to measure 665 proteins in the cerebrospinal fluid (CSF) from patients with DLB (n = 109), Alzheimer´s disease (AD, n = 235) and cognitively unimpaired controls (n = 190). We identified over 50 CSF proteins dysregulated in DLB, enriched in myelination processes among others. The dopamine biosynthesis enzyme DDC was the strongest dysregulated protein, and could efficiently discriminate DLB from controls and AD (AUC:0.91 and 0.81 respectively). Classification modeling unveiled a 7-CSF biomarker panel that better discriminate DLB from AD (AUC:0.93). A custom multiplex panel for six of these markers (DDC, CRH, MMP-3, ABL1, MMP-10, THOP1) was developed and validated in independent cohorts, including an AD and DLB autopsy cohort. This DLB CSF proteome study identifies DLB-specific protein changes and translates these findings to a practicable biomarker panel that accurately identifies DLB patients, providing promising diagnostic and clinical trial testing opportunities.

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.

Protein disulfide isomerases as CSF biomarkers for the neuronal response to tau pathology

INTRODUCTION

Cerebrospinal fluid (CSF) biomarkers for specific cellular disease processes are lacking for tauopathies. In this translational study we aimed to identify CSF biomarkers reflecting early tau pathology-associated unfolded protein response (UPR) activation.

METHODS

We employed mass spectrometry proteomics and targeted immunoanalysis in a combination of biomarker discovery in primary mouse neurons in vitro and validation in patient CSF from two independent large multicentre cohorts (EMIF-AD MBD, n = 310; PRIDE, n = 771).

RESULTS

First, we identify members of the protein disulfide isomerase (PDI) family in the neuronal UPR-activated secretome and validate secretion upon tau aggregation in vitro. Next, we demonstrate that PDIA1 and PDIA3 levels correlate with total- and phosphorylated-tau levels in CSF. PDIA1 levels are increased in CSF from AD patients compared to controls and patients with tau-unrelated frontotemporal and Lewy body dementia (LBD).

HIGHLIGHTS

Neuronal unfolded protein response (UPR) activation induces the secretion of protein disulfide isomerases (PDIs) in vitro. PDIA1 is secreted upon tau aggregation in neurons in vitro. PDIA1 and PDIA3 levels correlate with total and phosphorylated tau levels in CSF. PDIA1 levels are increased in CSF from Alzheimer's disease (AD) patients compared to controls. PDIA1 levels are not increased in CSF from tau-unrelated frontotemporal dementia (FTD) and Lewy body dementia (LBD) patients.

Pushing the boundaries of brain organoids to study Alzheimer's disease

Progression of Alzheimer's disease (AD) entails deterioration or aberrant function of multiple brain cell types, eventually leading to neurodegeneration and cognitive decline. Defining how complex cell-cell interactions become dysregulated in AD requires novel human cell-based in vitro platforms that could recapitulate the intricate cytoarchitecture and cell diversity of the human brain. Brain organoids (BOs) are 3D self-organizing tissues that partially resemble the human brain architecture and can recapitulate AD-relevant pathology. In this review, we highlight the versatile applications of different types of BOs to model AD pathogenesis, including amyloid-β and tau aggregation, neuroinflammation, myelin breakdown, vascular dysfunction, and other phenotypes, as well as to accelerate therapeutic development for AD.

Potential diagnostic value of CSF metabolism-related proteins across the Alzheimer's disease continuum

BACKGROUND

Alzheimer's disease (AD) cerebrospinal fluid (CSF) core biomarkers (Aβ42/40 ratio, p-tau, and t-tau) provide high diagnostic accuracy, even at the earliest stage of disease. However, these markers do not fully reflect the complex AD pathophysiology. Recent large scale CSF proteomic studies revealed several new AD candidate biomarkers related to metabolic pathways. In this study we measured the CSF levels of four metabolism-related proteins not directly linked to amyloid- and tau-pathways (i.e., pyruvate kinase, PKM; aldolase, ALDO; ubiquitin C-terminal hydrolase L1, UCHL1, and fatty acid-binding protein 3, FABP3) across the AD continuum. We aimed at validating the potential value of these proteins as new CSF biomarkers for AD and their possible involvement in AD pathogenesis, with specific interest on the preclinical phase of the disease.

METHODS

CSF PKM and ALDO activities were measured with specific enzyme assays while UCHL1 and FABP3 levels were measured with immunoassays in a cohort of patients composed as follows: preclinical AD (pre-AD, n = 19, cognitively unimpaired), mild cognitive impairment due to AD (MCI-AD, n = 50), dementia due to AD (ADdem, n = 45), and patients with frontotemporal dementia (FTD, n = 37). Individuals with MCI not due to AD (MCI, n = 30) and subjective cognitive decline (SCD, n = 52) with negative CSF AD-profile, were enrolled as control groups.

RESULTS

CSF UCHL1 and FABP3 levels, and PKM activity were significantly increased in AD patients, already at the pre-clinical stage. CSF PKM activity was also increased in FTD patients compared with control groups, being similar between AD and FTD patients. No difference was found in ALDO activity among the groups. UCHL1 showed good performance in discriminating early AD patients (pre-AD and MCI-AD) from controls (AUC ~ 0.83), as assessed by ROC analysis. Similar results were obtained for FABP3. Conversely, PKM provided the best performance when comparing FTD vs. MCI (AUC = 0.80). Combination of PKM, FABP3, and UCHL1 improved the diagnostic accuracy for the detection of patients within the AD continuum when compared with single biomarkers.

CONCLUSIONS

Our study confirmed the potential role of UCHL1 and FABP3 as neurodegenerative biomarkers for AD. Furthermore, our results validated the increase of PKM activity in CSF of AD patients, already at the preclinical phase of the disease. Increased PKM activity was observed also in FTD patients, possibly underlining similar alterations in energy metabolism in AD and FTD.

Thimet oligopeptidase as a potential CSF biomarker for Alzheimer's disease: A cross-platform validation study

INTRODUCTION

Our previous antibody-based cerebrospinal fluid (CSF) proteomics study showed that Thimet oligopeptidase (THOP1), an amyloid beta (Aβ) neuropeptidase, was increased in mild cognitive impairment with amyloid pathology (MCI-Aβ+) and Alzheimer's disease (AD) dementia compared with controls and dementia with Lewy bodies (DLB), highlighting the potential of CSF THOP1 as an early specific biomarker for AD. We aimed to develop THOP1 immunoassays for large-scale analysis and validate our proteomics findings in two independent cohorts.

METHODS

We developed in-house CSF THOP1 immunoassays on automated Ella and Simoa platforms. The performance of the different assays were compared using Passing-Bablok regression analysis in a subset of CSF samples from the discovery cohort (n = 72). Clinical validation was performed in two independent cohorts (cohort 1: n = 200; cohort 2: n = 165) using the Ella platform.

RESULTS

THOP1 concentrations moderately correlated between proteomics analysis and our novel assays (Rho > 0.580). In both validation cohorts, CSF THOP1 was increased in MCI-Aβ+ (>1.3-fold) and AD (>1.2-fold) compared with controls; and between MCI-Aβ+ and DLB (>1.2-fold). Higher THOP1 concentrations were detected in AD compared with DLB only when both cohorts were analyzed together. In both cohorts, THOP1 correlated with CSF total tau (t-tau), phosphorylated tau (p-tau), and Aβ40 (Rho > 0.540) but not Aβ42.

DISCUSSION

Validation of our proteomics findings underpins the potential of CSF THOP1 as an early specific biomarker associated with AD pathology. The use of antibody-based platforms in both the discovery and validation phases facilitated the translation of proteomics findings, providing an additional workflow that may accelerate the development of biofluid-based biomarkers.

Neuroinflammatory CSF biomarkers MIF, sTREM1, and sTREM2 show dynamic expression profiles in Alzheimer's disease

BACKGROUND

There is a need for novel fluid biomarkers tracking neuroinflammatory responses in Alzheimer's disease (AD). Our recent cerebrospinal fluid (CSF) proteomics study revealed that migration inhibitory factor (MIF) and soluble triggering receptor expressed on myeloid cells 1 (sTREM1) increased along the AD continuum. We aimed to assess the potential use of these proteins, in addition to sTREM2, as CSF biomarkers to monitor inflammatory processes in AD.

METHODS

We included cognitively unimpaired controls (n = 67, 63 ± 9 years, 24% females, all amyloid negative), patients with mild cognitive impairment (MCI; n = 92, 65 ± 7 years, 47% females, 65% amyloid positive), AD (n = 38, 67 ± 6 years, 8% females, all amyloid positive), and DLB (n = 50, 67 ± 6 years, 5% females, 54% amyloid positive). MIF, sTREM1, and sTREM2 levels were measured by validated immunoassays. Differences in protein levels between groups were tested with analysis of covariance (corrected for age and sex). Spearman correlation analysis was performed to evaluate the association between these neuroinflammatory markers with AD-CSF biomarkers (Aβ42, tTau, pTau) and mini-mental state examination (MMSE) scores.

RESULTS

MIF levels were increased in MCI (p < 0.01), AD (p < 0.05), and DLB (p > 0.05) compared to controls. Levels of sTREM1 were specifically increased in AD compared to controls (p < 0.01), MCI (p < 0.05), and DLB patients (p > 0.05), while sTREM2 levels were increased specifically in MCI compared to all other groups (all p < 0.001). Neuroinflammatory proteins were highly correlated with CSF pTau levels (MIF: all groups; sTREM1: MCI, AD and DLB; sTREM2: controls, MCI and DLB). Correlations with MMSE scores were observed in specific clinical groups (MIF in controls, sTREM1 in AD, and sTREM2 in DLB).

CONCLUSION

Inflammatory-related proteins show diverse expression profiles along different AD stages, with increased protein levels in the MCI stage (MIF and sTREM2) and AD stage (MIF and sTREM1). The associations of these inflammatory markers primarily with CSF pTau levels indicate an intertwined relationship between tau pathology and inflammation. These neuroinflammatory markers might be useful in clinical trials to capture dynamics in inflammatory responses or monitor drug-target engagement of inflammatory modulators.

Synaptic biomarkers in the cerebrospinal fluid associate differentially with classical neuronal biomarkers in patients with Alzheimer's disease and frontotemporal dementia

BACKGROUND

Loss of synaptic functionality has been recently identified as an early-stage indicator of neurological diseases. Consequently, monitoring changes in synaptic protein levels may be relevant for observing disease evolution or treatment responses in patients. Here, we have studied the relationship between fluid biomarkers of neurodegeneration and synaptic dysfunction in patients with Alzheimer's disease (AD), frontotemporal dementia (FTD), and subjective cognitive decline (SCD).

METHODS

The exploratory cohort consisted of cerebrospinal fluid (CSF) samples (n = 60) from patients diagnosed with AD (n = 20), FTD (n = 20), and SCD (n = 20) from the Amsterdam Dementia Cohort. We developed two novel immunoassays for the synaptic proteins synaptosomal-associated protein-25 (SNAP25) and vesicle-associated membrane protein-2 (VAMP2). We measured the levels of these biomarkers in CSF, in addition to neuronal pentraxin-2 (NPTX2), glutamate ionotropic receptor-4 (GluR4), and neurogranin (Ng) for this cohort. All in-house immunoassays were validated and analytically qualified prior to clinical application. CSF neurogranin (Ng) was measured using a commercially available ELISA.

RESULTS

This pilot study indicated that SNAP25, VAMP2, and Ng may not be specific biomarkers for AD as their levels were significantly elevated in patients with both AD and FTD compared to SCD. Moreover, the strength of the correlations between synaptic proteins was lower in the AD and FTD clinical groups compared to SCD. SNAP25, VAMP2, and Ng correlated strongly with each other as well as with total Tau (Tau) and phosphorylated Tau (PTau) in all three clinical groups. However, this correlation was weakened or absent with NPTX2 and GluR4. None of the synaptic proteins correlated to neurofilament light (NfL) in any clinical group.

CONCLUSION

The correlation of the synaptic biomarkers with CSF Tau and PTau but the lack thereof with NfL implies that distinct pathological pathways may be involved in synaptic versus axonal degeneration. Our results reflect the diversity of synaptic pathology in neurodegenerative dementias.