Comparative Analysis of Alzheimer's Disease Cerebrospinal Fluid Biomarkers Measurement by Multiplex SOMAscan Platform and Immunoassay-Based Approach

CSF Proteomics in Patients With Progressive Supranuclear Palsy

BACKGROUND AND OBJECTIVES

Identification of fluid biomarkers for progressive supranuclear palsy (PSP) is critical to enhance therapeutic development. We implemented unbiased DNA aptamer (SOMAmer) proteomics to identify novel CSF PSP biomarkers.

METHODS

This is a cross-sectional study in original (18 clinically diagnosed PSP-Richardson syndrome [PSP-RS], 28 cognitively healthy controls]), validation (23 PSP-RS, 26 healthy controls), and neuropathology-confirmed (21 PSP, 52 non-PSP frontotemporal lobar degeneration) cohorts. Participants were recruited through the University of California, San Francisco, and the 4-Repeat Neuroimaging Initiative. The original and neuropathology cohorts were analyzed with the SomaScan platform version 3.0 (5026-plex) and the validation cohort with version 4.1 (7595-plex). Clinical severity was measured with the PSP Rating Scale (PSPRS). CSF proteomic data were analyzed to identify differentially expressed targets, implicated biological pathways using enrichment and weighted consensus gene coexpression analyses, diagnostic value of top targets with receiver-operating characteristic curves, and associations with disease severity with linear regressions.

RESULTS

A total of 136 participants were included (median age 70.6 ± 8 years, 68 [50%] women). One hundred fifty-five of 5,026 (3.1%), 959 of 7,595 (12.6%), and 321 of 5,026 (6.3%) SOMAmers were differentially expressed in PSP compared with controls in original, validation, and neuropathology-confirmed cohorts, with most of the SOMAmers showing reduced signal (83.1%, 95.1%, and 73.2%, respectively). Three coexpression modules were associated with PSP across cohorts: (1) synaptic function/JAK-STAT (β = -0.044, corrected p = 0.002), (2) vesicle cytoskeletal trafficking (β = 0.039, p = 0.007), and (3) cytokine-cytokine receptor interaction (β = -0.032, p = 0.035) pathways. Axon guidance was the top dysregulated pathway in PSP in original (strength = 1.71, p < 0.001), validation (strength = 0.84, p < 0.001), and neuropathology-confirmed (strength = 0.78, p < 0.001) cohorts. A panel of axon guidance pathway proteins discriminated between PSP and controls in original (area under the curve [AUC] = 0.924), validation (AUC = 0.815), and neuropathology-confirmed (AUC = 0.932) cohorts. Two inflammatory proteins, galectin-10 and cytotoxic T lymphocyte-associated protein-4, correlated with PSPRS scores across cohorts.

DISCUSSION

Axon guidance pathway proteins and several other molecular pathways are downregulated in PSP, compared with controls. Proteins in these pathways may be useful targets for biomarker or therapeutic development.

Crossing the Halfway Point: Aptamer-Based, Highly Multiplexed Assay for the Assessment of the Proteome

Measuring responses in the proteome to various perturbations improves our understanding of biological systems. The value of information gained from such studies is directly proportional to the number of proteins measured. To overcome technical challenges associated with highly multiplexed measurements, we developed an affinity reagent-based method that uses aptamers with protein-like side chains along with an assay that takes advantage of their unique properties. As hybrid affinity reagents, modified aptamers are fully comparable to antibodies in terms of binding characteristics toward proteins, including epitope size, shape complementarity, affinity and specificity. Our assay combines these intrinsic binding properties with serial kinetic proofreading steps to allow highly effective partitioning of stable specific complexes from unstable nonspecific complexes. The use of these orthogonal methods to enhance specificity effectively overcomes the severe limitation to multiplexing inherent to the use of sandwich-based methods. Our assay currently measures half of the unique proteins encoded in the human genome with femtomolar sensitivity, broad dynamic range and exceptionally high reproducibility. Using machine learning to identify patterns of change, we have developed tests based on measurement of multiple proteins predictive of current health states and future disease risk to guide a holistic approach to precision medicine.

Genetic and multi-omic resources for Alzheimer disease and related dementia from the Knight Alzheimer Disease Research Center

The Knight-Alzheimer Disease Research Center (Knight-ADRC) at Washington University in St. Louis has pioneered and led worldwide seminal studies that have expanded our clinical, social, pathological, and molecular understanding of Alzheimer Disease. Over more than 40 years, research volunteers have been recruited to participate in cognitive, neuropsychologic, imaging, fluid biomarkers, genomic and multi-omic studies. Tissue and longitudinal data collected to foster, facilitate, and support research on dementia and aging. The Genetics and high throughput -omics core (GHTO) have collected of more than 26,000 biological samples from 6,625 Knight-ADRC participants. Samples available include longitudinal DNA, RNA, non-fasted plasma, cerebrospinal fluid pellets, and peripheral blood mononuclear cells. The GHTO has performed deep molecular profiling (genomic, transcriptomic, epigenomic, proteomic, and metabolomic) from large number of brain (n = 2,117), CSF (n = 2,012) and blood/plasma (n = 8,265) samples with the goal of identifying novel risk and protective variants, identify novel molecular biomarkers and causal and druggable targets. Overall, the resources available at GHTO support the increase of our understanding of Alzheimer Disease.

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.

Blood-Based Proteomics for Adult-Onset Focal Dystonias

OBJECTIVES

The adult-onset focal dystonias are characterized by over-active muscles leading to abnormal movements. For most cases, the etiology and pathogenesis remain unknown. In the current study, unbiased proteomics methods were used to identify potential changes in blood plasma proteins.

METHODS

A large-scale unbiased proteomics screen was used to compare proteins (N = 6,345) in blood plasma of normal healthy controls (N = 49) with adult-onset focal dystonia (N = 143) consisting of specific subpopulations of cervical dystonia (N = 45), laryngeal dystonia (N = 49), and blepharospasm (N = 49). Pathway analyses were conducted to identify relevant biological pathways. Finally, protein changes were used to build a prediction model for dystonia.

RESULTS

After correction for multiple comparisons, 15 proteins were associated with adult-onset focal dystonia. Subgroup analyses revealed some proteins were shared across the dystonia subgroups while others were unique to 1 subgroup. The top biological pathways involved changes in the immune system, metal ion transport, and reactive oxygen species. A 4-protein model showed high accuracy in discriminating control individuals from dystonia cases [average area under the curve (AUC) = 0.89].

INTERPRETATION

These studies provide novel insights into the etiopathogenesis of dystonia, as well as novel potential biomarkers. ANN NEUROL 2024;96:110-120.

Sex and aging signatures of proteomics in human cerebrospinal fluid identify distinct clusters linked to neurodegeneration

Sex and age are major risk factors for chronic diseases. Recent studies examining age-related molecular changes in plasma provided insights into age-related disease biology. Cerebrospinal fluid (CSF) proteomics can provide additional insights into brain aging and neurodegeneration. By comprehensively examining 7,006 aptamers targeting 6,139 proteins in CSF obtained from 660 healthy individuals aged from 43 to 91 years old, we subsequently identified significant sex and aging effects on 5,097 aptamers in CSF. Many of these effects on CSF proteins had different magnitude or even opposite direction as those on plasma proteins, indicating distinctive CSF-specific signatures. Network analysis of these CSF proteins revealed not only modules associated with healthy aging but also modules showing sex differences. Through subsequent analyses, several modules were highlighted for their proteins implicated in specific diseases. Module 2 and 6 were enriched for many aging diseases including those in the circulatory systems, immune mechanisms, and neurodegeneration. Together, our findings fill a gap of current aging research and provide mechanistic understanding of proteomic changes in CSF during a healthy lifespan and insights for brain aging and diseases.

Benchmarking of a multi-biomarker low-volume panel for Alzheimer's Disease and related dementia research

Alzheimer's Disease (AD) biomarker measurement is key to aid in the diagnosis and prognosis of the disease. In the research setting, participant recruitment and retention and optimization of sample use, is one of the main challenges that observational studies face. Thus, obtaining accurate established biomarker measurements for stratification and maximizing use of the precious samples is key. Accurate technologies are currently available for established biomarkers, mainly immunoassays and immunoprecipitation liquid chromatography-mass spectrometry (IP-MS), and some of them are already being used in clinical settings. Although some immunoassays- and IP-MS based platforms provide multiplexing for several different coding proteins there is not a current platform that can measure all the stablished and emerging biomarkers in one run. The NUcleic acid Linked Immuno-Sandwich Assay (NULISA™) is a mid-throughput platform with antibody-based measurements with a sequencing output that requires 15μL of sample volume to measure more than 100 analytes, including those typically assayed for AD. Here we benchmarked and compared the AD-relevant biomarkers including in the NULISA against validated assays, in both CSF and plasma. Overall, we have found that CSF measures of Aß42/40, NfL, GFAP, and p-tau217 are highly correlated and have similar predictive performance when measured by immunoassay, mass-spectrometry or NULISA. In plasma, p-tau217 shows a performance similar to that reported with other technologies when predicting amyloidosis. Other established and exploratory biomarkers (total tau, p-tau181, NRGN, YKL40, sTREM2, VILIP1 among other) show a wide range of correlation values depending on the fluid and the platform. Our results indicate that the multiplexed immunoassay platform produces reliable results for established biomarkers in CSF that are useful in research settings, with the advantage of measuring additional novel biomarkers using minimal sample volume.

The dynamic impact of location and resection on the glioma CSF proteome

While serial sampling of glioma tissue is rarely performed prior to recurrence, cerebrospinal fluid (CSF) is an underutilized longitudinal source of candidate glioma biomarkers for understanding therapeutic impacts. However, the impact of key variables to consider in longitudinal CSF samples, including anatomical location and post-surgical changes, remains unknown. To that end, pre- versus post-resection intracranial CSF samples were obtained at early (1-16 days; n=20) or delayed (86-153 days; n=11) timepoints for patients with glioma. Paired lumbar-versus-intracranial glioma CSF samples were also obtained (n=14). Using aptamer-based proteomics, we identify significant differences in the CSF proteome between lumbar, subarachnoid, and ventricular CSF. Our analysis of serial intracranial CSF samples suggests the early potential for disease monitoring and evaluation of pharmacodynamic impact of targeted therapies. Importantly, we found that resection had a significant, evolving longitudinal impact on the CSF proteome. Proteomic data are provided with individual clinical annotations as a resource for the field.

One Sentence Summary

Glioma cerebrospinal fluid (CSF) accessed intra-operatively and longitudinally via devices can reveal impacts of treatment and anatomical location.

CSF proteomic profiling with amyloid/tau positivity identifies distinctive sex-different alteration of multiple proteins involved in Alzheimer's disease

In Alzheimer's disease (AD), the most common cause of dementia, females have higher prevalence and faster progression, but sex-specific molecular findings in AD are limited. Here, we comprehensively examined and validated 7,006 aptamers targeting 6,162 proteins in cerebral spinal fluid (CSF) from 2,077 amyloid/tau positive cases and controls to identify sex-specific proteomic signatures of AD. In discovery (N=1,766), we identified 330 male-specific and 121 female-specific proteomic alternations in CSF (FDR <0.05). These sex-specific proteins strongly predicted amyloid/tau positivity (AUC=0.98 in males; 0.99 in females), significantly higher than those with age, sex, and APOE-ε4 (AUC=0.85). The identified sex-specific proteins were well validated (r≥0.5) in the Stanford study (N=108) and Emory study (N=148). Biological follow-up of these proteins led to sex differences in cell-type specificity, pathways, interaction networks, and drug targets. Male-specific proteins, enriched in astrocytes and oligodendrocytes, were involved in postsynaptic and axon-genesis. The male network exhibited direct connections among 152 proteins and highlighted PTEN, NOTCH1, FYN, and MAPK8 as hubs. Drug target suggested melatonin (used for sleep-wake cycle regulation), nabumetone (used for pain), daunorubicin, and verteporfin for treating AD males. In contrast, female-specific proteins, enriched in neurons, were involved in phosphoserine residue binding including cytokine activities. The female network exhibits strong connections among 51 proteins and highlighted JUN and 14-3-3 proteins (YWHAG and YWHAZ) as hubs. Drug target suggested biperiden (for muscle control of Parkinson's disease), nimodipine (for cerebral vasospasm), quinostatin and ethaverine for treating AD females. Together, our findings provide mechanistic understanding of sex differences for AD risk and insights into clinically translatable interventions.

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).

Systematic proteomics in Autosomal dominant Alzheimer's disease reveals decades-early changes of CSF proteins in neuronal death, and immune pathways

Background

To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies.

Methods

We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models.

Findings

We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aβ42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89).

Interpretation

Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs.

Funding

Proteomic data generation was supported by NIH: RF1AG044546.

Proteo-genomics of soluble TREM2 in cerebrospinal fluid provides novel insights and identifies novel modulators for Alzheimer's disease

Triggering receptor expressed on myeloid cells 2 (TREM2) plays a critical role in microglial activation, survival, and apoptosis, as well as in Alzheimer's disease (AD) pathogenesis. We previously reported the MS4A locus as a key modulator for soluble TREM2 (sTREM2) in cerebrospinal fluid (CSF). To identify additional novel genetic modifiers of sTREM2, we performed the largest genome-wide association study (GWAS) and identified four loci for CSF sTREM2 in 3,350 individuals of European ancestry. Through multi-ethnic fine mapping, we identified two independent missense variants (p.M178V in MS4A4A and p.A112T in MS4A6A) that drive the association in MS4A locus and showed an epistatic effect for sTREM2 levels and AD risk. The novel TREM2 locus on chr 6 contains two rare missense variants (rs75932628 p.R47H, P=7.16×10-19; rs142232675 p.D87N, P=2.71×10-10) associated with sTREM2 and AD risk. The third novel locus in the TGFBR2 and RBMS3 gene region (rs73823326, P=3.86×10-9) included a regulatory variant with a microglia-specific chromatin loop for the promoter of TGFBR2. Using cell-based assays we demonstrate that overexpression and knock-down of TGFBR2, but not RBMS3, leads to significant changes of sTREM2. The last novel locus is located on the APOE region (rs11666329, P=2.52×10-8), but we demonstrated that this signal was independent of APOE genotype. This signal colocalized with cis-eQTL of NECTIN2 in the brain cortex and cis-pQTL of NECTIN2 in CSF. Overexpression of NECTIN2 led to an increase of sTREM2 supporting the genetic findings. To our knowledge, this is the largest study to date aimed at identifying genetic modifiers of CSF sTREM2. This study provided novel insights into the MS4A and TREM2 loci, two well-known AD risk genes, and identified TGFBR2 and NECTIN2 as additional modulators involved in TREM2 biology.

Mapping the human brain proteome: opportunities, challenges, and clinical potential

INTRODUCTION

Due to the segmented functions and complexity of the human brain, the characterization of molecular profiles within specific areas such as brain structures and biofluids is essential to unveil the molecular basis for structure specialization as well as the molecular imbalance associated with neurodegenerative and psychiatric diseases.

AREAS COVERED

Much of our knowledge about brain functionality derives from neurophysiological, anatomical, and transcriptomic approaches. More recently, laser capture and imaging proteomics, technological and computational developments in LC-MS/MS, as well as antibody/aptamer-based platforms have allowed the generation of novel cellular, spatial, and posttranslational dimensions as well as innovative facets in biomarker validation and druggable target identification.

EXPERT OPINION

Proteomics is a powerful toolbox to functionally characterize, quantify, and localize the extensive protein catalog of the human brain across physiological and pathological states. Brain function depends on multi-dimensional protein homeostasis, and its elucidation will help us to characterize biological pathways that are essential to properly maintain cognitive functions. In addition, comprehensive human brain pathological proteomes may be the basis in computational drug-repositioning methods as a strategy for unveiling potential new therapies in neurodegenerative and psychiatric disorders.

Evaluation of a New Aptamer-Based Array for Soluble Suppressor of Tumorgenicity (ST2) and N-terminal Pro-B-Type Natriuretic Peptide (NTproBNP) in Heart Failure Patients

BACKGROUND

Recent advances in multi-marker platforms offer faster data generation, but the fidelity of these methods compared to the ELISA is not established. We tested the correlation and predictive performance of SOMAscan vs. ELISA methods for NTproBNP and ST2.

METHODS

Patients ≥ 18 years with heart failure and ejection fraction < 50% were enrolled. We tested the correlation between SOMA and ELISA for each biomarker and their association with outcomes.

RESULTS

There was good correlation of SOMA vs. ELISA for ST2 (ρ = 0.71) and excellent correlation for NTproBNP (ρ = 0.94). The two versions of both markers were not significantly different regarding survival association. The two ST2 assays and NTproBNP assays were similarly associated with all-cause mortality and cardiovascular mortality. These associations remained statistically significant when adjusted for MAGGIC risk score (all p < 0.05).

CONCLUSION

SOMAscan quantifications of ST2 and NTproBNP correlate to ELISA versions and carry similar prognosis.

Exploring the Potential of Aptamers in Targeting Neuroinflammation and Neurodegenerative Disorders: Opportunities and Challenges

Neuroinflammation is the precursor for several neurodegenerative diseases (NDDs), such as Alzheimer's disease (AD), Parkinson's disease (PD), and multiple sclerosis (MS). Targeting neuroinflammation has emerged as a promising strategy to address a wide range of CNS pathologies. These NDDs still present significant challenges in terms of limited and ineffective diagnosis and treatment options, driving the need to explore innovative and novel therapeutic alternatives. Aptamers are single-stranded nucleic acids that offer the potential for addressing these challenges through diagnostic and therapeutic applications. In this review, we summarize diagnostic and therapeutic aptamers for inflammatory biomolecules, as well as the inflammatory cells in NDDs. We also discussed the potential of short nucleotides for Aptamer-Based Targeted Brain Delivery through their unique features and modifications, as well as their ability to penetrate the blood-brain barrier. Moreover, the unprecedented opportunities and substantial challenges of using aptamers as therapeutic agents, such as drug efficacy, safety considerations, and pharmacokinetics, are also discussed. Taken together, this review assesses the potential of aptamers as a pioneering approach for target delivery to the CNS and the treatment of neuroinflammation and NDDs.

Proteome wide association studies of LRRK2 variants identify novel causal and druggable proteins for Parkinson's disease

Common and rare variants in the LRRK2 locus are associated with Parkinson's disease (PD) risk, but the downstream effects of these variants on protein levels remain unknown. We performed comprehensive proteogenomic analyses using the largest aptamer-based CSF proteomics study to date (7006 aptamers (6138 unique proteins) in 3107 individuals). The dataset comprised six different and independent cohorts (five using the SomaScan7K (ADNI, DIAN, MAP, Barcelona-1 (Pau), and Fundació ACE (Ruiz)) and the PPMI cohort using the SomaScan5K panel). We identified eleven independent SNPs in the LRRK2 locus associated with the levels of 25 proteins as well as PD risk. Of these, only eleven proteins have been previously associated with PD risk (e.g., GRN or GPNMB). Proteome-wide association study (PWAS) analyses suggested that the levels of ten of those proteins were genetically correlated with PD risk, and seven were validated in the PPMI cohort. Mendelian randomization analyses identified GPNMB, LCT, and CD68 causal for PD and nominate one more (ITGB2). These 25 proteins were enriched for microglia-specific proteins and trafficking pathways (both lysosome and intracellular). This study not only demonstrates that protein phenome-wide association studies (PheWAS) and trans-protein quantitative trail loci (pQTL) analyses are powerful for identifying novel protein interactions in an unbiased manner, but also that LRRK2 is linked with the regulation of PD-associated proteins that are enriched in microglial cells and specific lysosomal pathways.

Proteomics of brain, CSF, and plasma identifies molecular signatures for distinguishing sporadic and genetic Alzheimer's disease

Proteomic studies for Alzheimer's disease (AD) are instrumental in identifying AD pathways but often focus on single tissues and sporadic AD cases. Here, we present a proteomic study analyzing 1305 proteins in brain tissue, cerebrospinal fluid (CSF), and plasma from patients with sporadic AD, TREM2 risk variant carriers, patients with autosomal dominant AD (ADAD), and healthy individuals. We identified 8 brain, 40 CSF, and 9 plasma proteins that were altered in individuals with sporadic AD, and we replicated these findings in several external datasets. We identified a proteomic signature that differentiated TREM2 variant carriers from both individuals with sporadic AD and healthy individuals. The proteins associated with sporadic AD were also altered in patients with ADAD, but with a greater effect size. Brain-derived proteins associated with ADAD were also replicated in additional CSF samples. Enrichment analyses highlighted several pathways, including those implicated in AD (calcineurin and Apo E), Parkinson's disease (α-synuclein and LRRK2), and innate immune responses (SHC1, ERK-1, and SPP1). Our findings suggest that combined proteomics across brain tissue, CSF, and plasma can be used to identify markers for sporadic and genetically defined AD.

Neuro-PASC is characterized by enhanced CD4+ and diminished CD8+ T cell responses to SARS-CoV-2 Nucleocapsid protein

Introduction

Many people with long COVID symptoms suffer from debilitating neurologic post-acute sequelae of SARS-CoV-2 infection (Neuro-PASC). Although symptoms of Neuro-PASC are widely documented, it is still unclear whether PASC symptoms impact virus-specific immune responses. Therefore, we examined T cell and antibody responses to SARS-CoV-2 Nucleocapsid protein to identify activation signatures distinguishing Neuro-PASC patients from healthy COVID convalescents.

Results

We report that Neuro-PASC patients exhibit distinct immunological signatures composed of elevated CD4+ T cell responses and diminished CD8+ memory T cell activation toward the C-terminal region of SARS-CoV-2 Nucleocapsid protein when examined both functionally and using TCR sequencing. CD8+ T cell production of IL-6 correlated with increased plasma IL-6 levels as well as heightened severity of neurologic symptoms, including pain. Elevated plasma immunoregulatory and reduced pro-inflammatory and antiviral response signatures were evident in Neuro-PASC patients compared with COVID convalescent controls without lasting symptoms, correlating with worse neurocognitive dysfunction.

Discussion

We conclude that these data provide new insight into the impact of virus-specific cellular immunity on the pathogenesis of long COVID and pave the way for the rational design of predictive biomarkers and therapeutic interventions.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways

Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

Consolidation of metabolomic, proteomic, and GWAS data in connective model of schizophrenia

Despite of multiple systematic studies of schizophrenia based on proteomics, metabolomics, and genome-wide significant loci, reconstruction of underlying mechanism is still a challenging task. Combination of the advanced data for quantitative proteomics, metabolomics, and genome-wide association study (GWAS) can enhance the current fundamental knowledge about molecular pathogenesis of schizophrenia. In this study, we utilized quantitative proteomic and metabolomic assay, and high throughput genotyping for the GWAS study. We identified 20 differently expressed proteins that were validated on an independent cohort of patients with schizophrenia, including ALS, A1AG1, PEDF, VTDB, CERU, APOB, APOH, FASN, GPX3, etc. and almost half of them are new for schizophrenia. The metabolomic survey revealed 18 group-specific compounds, most of which were the part of transformation of tyrosine and steroids with the prevalence to androgens (androsterone sulfate, thyroliberin, thyroxine, dihydrotestosterone, androstenedione, cholesterol sulfate, metanephrine, dopaquinone, etc.). The GWAS assay mostly failed to reveal significantly associated loci therefore 52 loci with the smoothened p < 10^-5 were fractionally integrated into proteome-metabolome data. We integrated three omics layers and powered them by the quantitative analysis to propose a map of molecular events associated with schizophrenia psychopathology. The resulting interplay between different molecular layers emphasizes a strict implication of lipids transport, oxidative stress, imbalance in steroidogenesis and associated impartments of thyroid hormones as key interconnected nodes essential for understanding of how the regulation of distinct metabolic axis is achieved and what happens in the conditioned proteome and metabolome to produce a schizophrenia-specific pattern.

Perinatal mood and anxiety disorders: biomarker discovery using plasma proteomics

BACKGROUND

Perinatal mood and anxiety disorders encompass a range of mental health disorders that occur during pregnancy and up to 1 year postpartum, affecting approximately 20% of women. Traditional risk factors, such as a history of depression and pregnancy complications including preeclampsia, are known. Their predictive utility, however, is not specific or sensitive enough to inform clinical decision-making or prevention strategies for perinatal mood and anxiety disorders. Better diagnostic and prognostic models are needed for early identification and referral to treatment.

OBJECTIVE

This study aimed to determine if a panel of novel third-trimester plasma protein biomarkers in pregnant women can be used to identify those who have a high predisposed risk for perinatal mood and anxiety disorders within 3 months postpartum.

STUDY DESIGN

We studied 52 women (n=34 with a risk for perinatal mood and anxiety disorders and n=18 controls) among whom mental health screening was conducted at 2 time points, namely in the third trimester and again at 3 months postdelivery. An elevated perinatal mood and anxiety disorder risk was identified by screening individuals with above-validated cutoffs for depression (Edinburgh Postnatal Depression Scale ≥12), anxiety (Overall Anxiety Severity and Impairment Scale ≥7), and/or posttraumatic stress disorder (Impact of Events Scale >26) at both time points. Plasma samples collected in the third trimester were screened using the aptamer-based SomaLogic SomaScan proteomic assay technology to evaluate perinatal mood and anxiety disorder-associated changes in the expression of 1305 protein analytes. Ingenuity Pathway Analysis was conducted to highlight pathophysiological relationships between perinatal mood and anxiety disorder-specific proteins found to be significantly up- or down-regulated in all subjects with perinatal mood and anxiety disorder and in those with perinatal mood and anxiety disorders and no preeclampsia.

RESULTS

From a panel of 53 significant perinatal mood and anxiety disorder-associated proteins, a unique 20-protein signature differentiated perinatal mood and anxiety disorder cases from controls in a principal component analysis (P<.05). This protein signature included NCAM1, NRCAM, and NTRK3 that converge around neuronal signaling pathways regulating axonal guidance, astrocyte differentiation, and maintenance of GABAergic neurons. Interestingly, when we restricted the analysis to subjects without preeclampsia, a 30-protein signature differentiated perinatal mood and anxiety disorder cases from all controls without overlap on the principal component analysis (P<.001). In the nonpreeclamptic perinatal mood and anxiety disorder group, we observed increased expression of proteins, such as CXCL11, CXCL6, MIC-B, and B2MG, which regulate leucocyte migration, inflammation, and immune function.

CONCLUSION

Participants with perinatal mood and anxiety disorders had a unique and distinct plasma protein signature that regulated a variety of neuronal signaling and proinflammatory pathways. Additional validation studies with larger sample sizes are needed to determine whether some of these molecules can be used in conjunction with traditional risk factors for the early detection of perinatal mood and anxiety disorders.

Vascular endothelial-cadherin as a marker of endothelial injury in preclinical Alzheimer disease

OBJECTIVE

Endothelial dysfunction is an early and prevalent pathology in Alzheimer disease (AD). We here investigate the value of vascular endothelial-cadherin (VEC) as a cerebrospinal fluid (CSF) marker of endothelial injury in preclinical AD.

METHODS

Cognitively normal participants (Clinical Dementia Rating [CDR] 0) from the Knight Washington University-ADRC were included in this study (n = 700). Preclinical Alzheimer's Cognitive Composite (PACC) scores, CSF VEC, tau, p-tau181, Aβ42/Aβ40, neurofilament light-chain (NFL) levels, and magnetic resonance imaging (MRI) assessments of white matter injury (WMI) were obtained from all participants. A subset of participants underwent brain amyloid imaging using positron emission tomography (amyloid-PET) (n = 534). Linear regression examined associations of CSF VEC with PACC and individual cognitive scores in preclinical AD. Mediation analyses examined whether CSF VEC mediated effects of CSF amyloid and tau markers on cognition in preclinical AD.

RESULTS

CSF VEC levels significantly correlated with PACC and individual cognitive scores in participants with amyloid (A+T±N±; n = 558) or those with amyloid and tau pathologies (A+T+N±; n = 259), after adjusting for covariates. CSF VEC also correlated with CSF measures of amyloid, tau, and neurodegeneration and global amyloid burden on amyloid-PET scans in our cohort. Importantly, our findings suggest that CSF VEC mediates associations of CSF Aβ42/Aβ40, p-tau181, and global amyloid burden with cognitive outcomes in preclinical AD.

INTERPRETATION

Our results support the utility of CSF VEC as a marker of endothelial injury in AD and highlight the importance of endothelial injury as an early pathology that contributes to cognitive impairment in even the earliest preclinical stages.