Neurology-related protein biomarkers are associated with cognitive ability and brain volume in older age

Prospective Investigation Unravels Plasma Proteomic Links to Dementia

Investigating plasma proteomic signatures of dementia offers insights into its pathology, aids biomarker discovery, supports disease monitoring, and informs drug development. Here, we analyzed data from 48,367 UK Biobank participants with proteomic profiling. Using Cox and generalized linear models, we examined the longitudinal associations between proteomic signatures and dementia-related phenotypes. Mendelian randomization analysis was employed to identify causal associations, and machine learning algorithms were applied to develop protein-based models for dementia prediction. We identified 74 proteins significantly associated with the risk of various types of dementia and cognitive functions after Bonferroni correction. Among these, strong associations were observed for growth/differentiation factor 15 (GDF15), glial fibrillary acidic protein (GFAP), and neurofilament light polypeptide (NEFL), across all types of dementia. Additionally, 15 proteins demonstrated significant associations with neuroimaging-defined dementia endophenotypes. Two-sample Mendelian randomization analyses further substantiated causal relationships between dementia-associated proteins and Alzheimer's disease, particularly involving GDF15, proto-oncogene tyrosine-protein kinase receptor Ret (RET), and GFAP. Moreover, we identified three protein modules associated with dementia, primarily linked to immune system processes, angiogenesis, and energy metabolism, providing insights into potential biological pathways underlying the disease. Furthermore, we proposed a ten-protein panel capable of forecasting dementia over a median follow-up period of 8.6 years, achieving an area under the curve (AUC) of 0.857 (95% confidence interval (CI), 0.837-0.876). Our results revealed dementia-associated plasma proteomic signatures, and their causal relationships, notably GDF15-RET signaling with Alzheimer's disease, and proposed a promising protein panel for high-risk dementia screening.

Profiling 92 circulating neurobiological proteins identifies novel candidate biomarkers of long-term cognitive outcome after ischemic stroke

The biological underpinnings of post-stroke cognitive function are largely unknown, and protein investigations can point towards important pathways for further study. We profiled plasma levels of 91 neurology-related proteins (Olink Neurology panel) and serum Neurofilament light chain (NfL) levels in 205 cases in the Sahlgrenska Academy Study on Ischemic Stroke. Blood was sampled in the acute and convalescent (3 months post-stroke) phase. Cognitive outcome was evaluated by the Barrow Neurological Institute Screen for Higher Cerebral Functions 7 years post-stroke. In linear regression models, 6 and 5 proteins in the acute and convalescent phase, respectively, were univariably associated with cognitive outcome at False Discovery Rate (FDR) < 0.05, and 9 and 8 at p < 0.05 after adjustment for age, sex, education and sampling day (model 1) and/or additional adjustment for stroke severity (model 2). Of these, 15 proteins contributed with information in multi-protein models on at least one time-point. These included brain-expressed proteoglycans (NCAN, BCAN, GPC5, SPOCK1); contactin-5 (CNTN5); metabolic enzymes (HAGH, NMNAT1); cluster of differentiation (CD)-proteins (SIGLEC1, CLEC10A, CD200R1); GDNF family receptor alpha-1 (GFR-alpha-1); brorin (VWC2); beta-nerve growth factor (beta-NGF); myostatin (GDF-8); and NfL. We identified novel candidate protein biomarkers of post-stroke cognitive outcome that likely reflect different biological processes, warranting further exploration.

Association between fibrinogen and cognitive impairment in patients with ischemic cerebrovascular disease

OBJECTIVES

Fibrinogen has been reported as a potential risk factor for vascular dementia (VaD). However, the association between fibrinogen and cognition in patients with ischemic cerebrovascular disease (ICVD) has not been studied adequately. We aimed to examine the association of fibrinogen with cognitive impairment among patients with ICVD and to test whether white matter hyperintensities (WMH) and brain atrophy play a role under the association.

METHODS

In this case-control study, ICVD patients were recruited from the Neurology Department. Cognitive function was assessed using the Montreal Cognitive Assessment. WMH and brain atrophy were quantified by brain magnetic resonance imaging (MRI). The associations of fibrinogen with cognition and MRI markers were investigated by conditional logistic regression models and generalized additive models.

RESULTS

The risk of cognitive impairment increased with each unit increase in fibrinogen (AOR = 1.92, 95 % CI = 1.06 - 3.48). Individuals with fibrinogen levels > 4 g/L presented a substantially higher risk of cognitive impairment than those with fibrinogen levels of 2-4 g/L (AOR = 5.72, 95 % CI = 1.22- 26.82). Fibrinogen was negatively correlated with global cognitive function (rs = -0.235) and visuospatial/executive function (rs = -0.251). A negative correlation between fibrinogen and normal-appearing white matter (NAWM) volume was observed (rs = -0.282).

CONCLUSIONS

Fibrinogen is associated with cognitive impairment among patients with ICVD, and significantly negatively impacts global cognitive function and visuospatial/executive function. Furthermore, the negative correlation between fibrinogen and NAWM volume supports further exploration of potential mechanistic paths.

Alzheimer's Disease polygenic risk, the plasma proteome, and dementia incidence among UK older adults

Alzheimer's Disease (AD) is a complex polygenic neurodegenerative disorder. Its genetic risk's relationship with all-cause dementia may be influenced by the plasma proteome. Up to 40,139 UK Biobank participants aged ≥ 50y at baseline assessment (2006-2010) were followed-up for ≤ 15 y for dementia incidence. Plasma proteomics were performed on a sub-sample of UK Biobank participants (k = 1,463 plasma proteins). AD polygenic risk scores (PRS) were used as the primary exposure and Cox proportional hazards models were conducted to examine the AD PRS-dementia relationship. A four-way decomposition model then partitioned the total effect (TE) of AD PRS on dementia into an effect due to mediation only, an effect due to interaction only, neither or both. The study found that AD PRS tertiles significantly increased the risk for all-cause dementia, particularly among women. The study specifically found that AD PRS was associated with a 79% higher risk for all-cause dementia for each unit increase (HR = 1.79, 95% CI: 1.70-1.87, P < 0.001). Eighty-six plasma proteins were significantly predicted by AD PRS, including a positive association with PLA2G7, BRK1, the glial acidic fibrillary protein (GFAP), neurofilament light chain (NfL), and negative with TREM2. Both GFAP and NfL significantly interacted synergistically with AD PRS to increase all-dementia risk (> 10% of TE is pure interaction), while GFAP was also an important consistent mediator in the AD PRS-dementia relationship. In summary, we detected significant interactions of NfL and GFAP with AD PRS, in relation to dementia incidence, suggesting potential for personalized dementia prevention and management.

Unraveling the role of proteins in dementia: insights from two UK cohorts with causal evidence

Population-based proteomics offers a groundbreaking avenue to predict future disease risks, enhance our understanding of disease mechanisms, and discover novel therapeutic targets and biomarkers. The role of plasma proteins in dementia, however, requires further exploration. This study investigated 276 protein-dementia associations in 229 incident all-cause dementia, 89 Alzheimer's disease, and 41 vascular dementia among 3249 participants (55% women, 97.2% white ethnicity) from the English Longitudinal Study of Ageing (ELSA) over a median 9.8-year follow-up. We used Cox proportional hazard regression for the analysis. Receiver operating characteristic analyses were conducted to assess the precision of the identified proteins from the fully adjusted Cox regression models in predicting incident all-cause dementia, both individually and in combination with demographic predictors, APOE genotype, and memory score, to estimate the area under the curve. Additionally, the eXtreme Gradient Boosting machine learning algorithm was used to identify the most important features predictive of future all-cause dementia onset. These associations were then validated in 1506 incident all-cause dementia, 732 Alzheimer's disease, 281 vascular dementia, and 111 frontotemporal dementia cases among 52 745 individuals (53.9% women, 93.3% White ethnicity) from the UK Biobank over a median 13.7-year follow-up. Two-sample bi-directional Mendelian randomization and drug target Mendelian randomization were further employed to determine the causal direction between protein concentration and dementia. NEFL (hazard ratio [HR] [95% confidence intervals (CIs)]: 1.54 [1.29, 1.84]) and RPS6KB1 (HR [95% CI]: 1.33 [1.16, 1.52]) were robustly associated with incident all-cause dementia; MMP12 (HR [95% CI]: 2.06 [1.41, 2.99]) was associated with vascular dementia in ELSA, after correcting for multiple testing. Additional markers EDA2R and KIM1 were identified from subgroup and sensitivity analyses. Combining NEFL and RPS6KB1 with other predictors yielded high predictive accuracy (area under the curve = 0.871) for incident all-cause dementia. The eXtreme Gradient Boosting machine learning algorithm also identified RPS6KB1, NEFL, and KIM1 as the most important protein features for predicting future all-cause dementia. Sex difference was evident for the association between RPS6KB1 and all-cause dementia, with stronger association in men (P for interaction = 0.037). Replication in the UK Biobank confirmed the associations between the identified proteins and various dementia subtypes. The results from Mendelian randomization in the reverse direction indicated that several proteins serve as early markers for dementia, rather than being direct causes of the disease. These findings provide insights into putative mechanisms for dementia. Future studies are needed to validate the findings on RPS6KB1 in relation to dementia risk.

Linking obesity-associated genotype to child language development: the role of early-life neurology-related proteomics and brain myelination

BACKGROUND

The association between childhood obesity and language development may be confounded by socio-environmental factors and attributed to comorbid pathways.

METHODS

In a longitudinal Singaporean mother-offspring cohort, we leveraged trans-ancestry polygenic predictions of body mass index (BMI) to interrogate the causal effects of early-life BMI on child language development and its effects on molecular and neuroimaging measures. Leveraging large genome-wide association studies, we examined whether the link between obesity and language development is causal or due to a shared genetic basis.

FINDINGS

We found an inverse association between polygenic risk for obesity, which is less susceptible to confounding, and language ability assessed at age 9. Our findings suggested a shared genetic basis between obesity and language development rather than a causal effect of obesity on language development. Interrogating early-life mechanisms including neurology-related proteomics and language-related white matter microstructure, we found that EFNA4 and VWC2 expressions were associated with language ability as well as fractional anisotropy of language-related white matter tracts, suggesting a role in brain myelination. Additionally, the expression of the EPH-Ephrin signalling pathway in the hippocampus might contribute to language development. Polygenic risk for obesity was nominally associated with EFNA4 and VWC2 expression. However, we did not find support for mediating mechanisms via these proteins.

INTERPRETATION

This study demonstrates the potential of examining early-life proteomics in conjunction with deep genotyping and phenotyping and provides biological insights into the shared genomic links between obesity and language development.

FUNDING

Singapore National Research Foundation and Agency for Science, Technology and Research.

Serum proteomic correlates of mental health symptoms in a representative UK population sample

Poor mental health constitutes a public health crisis due to its high prevalence, unmet need and its mechanistic heterogeneity. A comprehensive understanding of the biological correlates of poor mental health in the population could enhance epidemiological research and eventually help guide treatment strategies. The human bloodstream contains many proteins, several of which have been linked to diagnosed mental health conditions but not to population mental health symptoms, however recent technological advances have made this possible. Here we perform exploratory factor analyses of 184 proteins from two panels (cardiometabolic and neurology-related) measured using proximity extension assays from Understanding Society (the UK Household Longitudinal Study; UKHLS). Data reduction results in 28 factors that explain 55-59% of the variance per panel. We perform multiple linear regressions in up to 5304 participants using two mental health symptom-based outcomes: psychological distress assessed with the general health questionnaire (GHQ-12) and mental health functioning assessed with the 12-Item Short Form Survey, Mental Component Summary (SF12-MCS) using the proteomic factors as explanatory variables and adjusting for demographic covariates. We use backward selection to discard non-significant proteomic factors from the models. Ten factors are independently associated with population mental health symptoms, three of which are immune-related (immunometabolism, immune cell-mediated processes, acute phase processes), three brain-related (neurodevelopment, synaptic processes, neuroprotective processes), two proteolysis-related (proteolysis & the kynurenine pathway, haemostasis & proteolysis), growth factors & muscle, and oxidative stress & the cytoskeleton. Associations partially overlap across the two outcomes, and a sensitivity analysis excluding people taking antidepressants or other central nervous system medications suggestively implicates some of the factors in treatment-resistant poor mental health. Our findings replicate those of case-control studies and expand these to underlie mental health symptomatology in the adult population. More work is needed to understand the direction of causality in these associations.

Exploratory analysis of the proteomic profile in plasma in adults with Down syndrome in the context of Alzheimer's disease

INTRODUCTION

Adults with Down syndrome (DS) show increased risk for Alzheimer's disease (AD) due to the triplication of chromosome 21 encoding the amyloid precursor protein gene. Further, this triplication possibly contributes to dysregulation of the immune system, furthering AD pathophysiology.

METHODS

Using Olink Explore 3072, we measured ∼3000 proteins in plasma from 73 adults with DS and 15 euploid, healthy controls (HC). Analyses for differentially expressed proteins (DEP) were carried out, and pathway and protein network enrichment using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG), and STRING database was investigated. Within DS, the LASSO (least absolute shrinkage and selection operator) feature selection was applied.

RESULTS

We identified 253 DEP between DS and HC and 142 DEP between symptomatic and asymptomatic DS. Several pathways regarding inflammatory and neurodevelopmental processes were dysregulated in both analyses. LASSO feature selection within DS returned 15 proteins as potential blood markers.

DISCUSSION

This exploratory proteomic analysis found potential new blood biomarkers for diagnosing DS-AD in need of further investigation.

HIGHLIGHTS

Inflammatory pathways are dysregulated in symptomatic versus asymptomatic DS. NFL and GFAP are confirmed as powerful biomarkers in DS with clinical and/or cognitive decline. Further circulating proteins were identified as potential blood biomarkers for symptomatic DS.

Large-Scale Plasma Proteomics Profiles for Predicting Ischemic Stroke Risk in the General Population

BACKGROUND

We aimed to develop and validate a protein risk score for ischemic stroke (IS) risk prediction and to compare its predictive capability with IS clinical risk factors and IS polygenic risk score.

METHODS

The prospective cohort study included 53 029 participants from UKB-PPP (UK Biobank Pharmaceutical Proteomics Project). IS protein risk score was calculated as the weighted sum of proteins selected by the least absolute shrinkage and selection operator regression. The discrimination ability of models was assessed by C statistic. IS risk factors included age, sex, smoking, waist-to-hip ratio, antihypertensive medication use, systolic and diastolic blood pressure, coronary heart disease, diabetes, total cholesterol/high-density lipoprotein cholesterol ratio, and estimated glomerular filtration rate. Polygenic risk score was computed using identified susceptibility variants.

RESULTS

After exclusions, 38 060 participants from England were randomly divided into the training set and the internal validation set in a 7:3 ratio, and 4970 participants from Scotland/Wales were assigned as the external validation set. Of 43 030 participants included (mean age, 59.0 years; 54.0% female), 989 incident IS occurred during a median follow-up of 13.6 years. In the training set, IS protein risk score was constructed using 17 out of 2911 proteins. In the internal validation set, compared with the basic model (age and sex: C statistic,0.720 [95% CI, 0.691-0.749]), IS protein risk score had the highest predictive performance for IS risk (C statistic, 0.765 [95% CI, 0.736-0.793]), followed by clinical risk factors of IS (C statistic, 0.753 [95% CI, 0.725-0.781]), and IS polygenic risk score (C statistic, 0.730 [95% CI, 0.701-0.759]). The top 5 proteins with the largest absolute coefficients in the IS protein risk score, including GDF15 (growth/differentiation factor 15), PLAUR (urokinase plasminogen activator surface receptor), NT-proBNP (N-terminal pro-B-type natriuretic peptide), IGFBP4 (insulin-like growth factor-binding protein 4), and BCAN (brevican core protein), contributed most of the predictive ability of the IS protein risk score, with a cumulative C statistic of 0.761 (95% CI, 0.733-0.790). These results were verified in the external validation cohort.

CONCLUSIONS

A simple model, including age, sex, and the IS protein risk score (or only the top 5 proteins) had a good predictive performance for IS risk.

Mediating and moderating effects of plasma proteomic biomarkers on the association between poor oral health problems and brain white matter microstructural integrity: the UK Biobank study

The plasma proteome can mediate associations between periodontal disease (Pd) and brain white matter integrity (WMI). We screened 5089 UK Biobank participants aged 40-70 years for poor oral health problems (POHP). We examined the association between POHP and WMI (fractional anisotropy (FA), mean diffusivity (MD), Intracellular Volume Fraction (ICVF), Isotropic Volume Fraction (ISOVF) and Orientation Diffusion (OD)), decomposing the total effect through the plasma proteome of 1463 proteins into pure mediation, pure interaction, neither, while adjusting for socio-demographic and cardiovascular health factors. Similarly, structural equations modeling (SEM) was conducted. POHP was more prevalent among men (12.3% vs. 9.6%), and was associated with lower WMI on most metrics, in a sex-specific manner. Of 15 proteins strongly associated with POHP, growth differentiation factor 15 (GDF15) and WAP four-disulfide core domain 2 (WFDC2; also known as human epididymis protein 4; HE4) were consistent mediators. Both proteins mediated 7-8% of total POHP effect on FAmean. SEM yielded significant total effects for FAmean, MDmean and ISOVFmean in full models, with %mediated by common latent factor (GDF15 and WFDC2) ranging between 13% (FAmean) and 19% (ISOVFmean). For FA, mediation by this common factor was found for 16 of 49 tract-specific and global mean metrics. Protein metabolism, immune system, and signal transduction were the most common pathways for mediational effects. POHP was associated with poorer WMI, which was partially mediated by GDF15 and WFDC2.

Plasma proteomic biomarkers as mediators or moderators for the association between poor cardiovascular health and white matter microstructural integrity: The UK Biobank study

INTRODUCTION

The plasma proteome's mediating or moderating roles in the association between poor cardiovascular health (CVH) and brain white matter (WM) microstructural integrity are largely unknown.

METHODS

Data from 3953 UK Biobank participants were used (40-70 years, 2006-2010), with a neuroimaging visit between 2014 and 2021. Poor CVH was determined using Life's Essential 8 (LE8) and reversing standardized z-scores (LE8z _rev). The plasma proteome was examined as a potential mediator or moderator of LE8z _rev's effects on quantitative diffusion-weighted magnetic resonance imaging (dMRI) metrics.

RESULTS

LE8z_rev was significantly associated with deteriorated WM microstructural integrity, as reflected by lower tract-averaged fractional anisotropy (dMRI-FAmean), (β ± standared error (SE): -0.00152 ± 0.0003, p < 0.001) and higher tract-averaged orientation dispersion (dMRI-ODmean), (β ± SE:+0.00081 ± 0.00017, p < 0.001). Ten strongly mediating plasma proteins of 1463 were identified, with leptin as the principal driver.

DISCUSSION

Poor CVH is linked to poor WM microstructural integrity measures (lower FAmean and higher ODmean), mostly mediated through leptin.

HIGHLIGHTS

Up to 3953 UK Biobank participants were selected for this study. Poor cardiovascular health (CVH) was determined using Life's Essential 8. The plasma proteome was examined as a potential mediator or moderator of poor CVH's effect on dMRI metrics. Ten plasma proteins were identified with strong mediating effects, with leptin being the principal driver.

Plasma protein-based identification of neuroimage-driven subtypes in mild cognitive impairment via protein-protein interaction aware explainable graph propagational network

As an early indicator of dementia, mild cognitive impairment (MCI) requires specialized treatment according to its subtypes for the effective prevention and management of dementia progression. Based on the neuropathological characteristics, MCI can be classified into Alzheimer's disease (AD)-related cognitive impairment (ADCI) and subcortical vascular cognitive impairment (SVCI), being more likely to progress to AD and subcortical vascular dementia (SVD), respectively. For identifying MCI subtypes, plasma protein biomarkers are recently seen as promising tools due to their minimal invasiveness and cost-effectiveness in diagnostic procedures. Furthermore, the application of machine learning (ML) has led the preciseness in the biomarker discovery and the resulting diagnostics. Nevertheless, previous ML-based studies often fail to consider interactions between proteins, which are essential in complex neurodegenerative disorders such as MCI and dementia. Although protein-protein interactions (PPIs) have been employed in network models, these models frequently do not fully capture the diverse properties of PPIs due to their local awareness. This limitation increases the likelihood of overlooking critical components and amplifying the impact of noisy interactions. In this study, we introduce a new graph-based ML model for classifying MCI subtypes, called eXplainable Graph Propagational Network (XGPN). The proposed method extracts the globally interactive effects between proteins by propagating the independent effect of plasma proteins on the PPI network, and thereby, MCI subtypes are predicted by estimation of the risk effect of each protein. Moreover, the process of model training and the outcome of subtype classification are fully explainable due to the simplicity and transparency of XGPN's architecture. The experimental results indicated that the interactive effect between proteins significantly contributed to the distinct differences between MCI subtype groups, resulting in an enhanced classification performance with an average improvement of 10.0 % compared to existing methods, also identifying key biomarkers and their impact on ADCI and SVCI.

The genetic landscape of neuro-related proteins in human plasma

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. At the cis-pQTL, multiple proteins shared a genetic basis with human behavioural traits such as alcohol and food intake, smoking and educational attainment, as well as neurological conditions and psychiatric disorders such as pain, neuroticism and schizophrenia. Integrating with established drug information, the causal inference analysis validated 52 out of 66 matched combinations of protein targets and diseases or side effects with available drugs while suggesting hundreds of repurposing and new therapeutic targets.

Mediating and moderating effects of plasma proteomic biomarkers on the association between poor oral health problems and incident dementia: The UK Biobank study

The plasma proteome can mediate poor oral health problems (POHP)'s link to incident dementia. We screened 37,269 UK Biobank participants 50-74 years old (2006-2010) for prevalent POHP, further tested against 1463 plasma proteins and incident dementia over up to 15 years of follow-up. Total effect (TE) of POHP-dementia through plasma proteomic markers was decomposed into pure indirect effect (PIE), interaction referent (INTREF), controlled direct effect (CDE), or mediated interaction (INTMED). POHP increased the risk of all-cause dementia by 17% (P < 0.05). Growth differentiation factor 15 (GDF15) exhibited the strongest mediating effects (PIE > 0, P < 0.001), explaining 28% the total effect of POHP on dementia, as a pure indirect effect. A first principal component encompassing top 4 mediators (GDF15, IL19, MMP12, and ACVRL1), explained 11% of the POHP-dementia effect as a pure indirect effect. Pathway analysis including all mediators (k = 173 plasma proteins) revealed the involvement of the immune system, signal transduction, metabolism, disease, and gene expression, while STRING analysis indicated that top mediators within the first principal component were also represented in the two largest proteomic clusters. The dominant biological GO pathway for the GDF15 cluster was GO:0007169 labeled as "transmembrane receptor protein tyrosine kinase signaling pathway." Dementia is linked to POHP mediated by GDF15 among several proteomic markers.

Transcriptional Patterns in Stages of Alzheimer's Disease Are Cell-Type-Specific and Partially Converge with the Effects of Alcohol Use Disorder in Humans

Advances in single-cell technologies have led to the discovery and characterization of new brain cell types, which in turn lead to a better understanding of the pathogenesis of Alzheimer's disease (AD). Here, we present a detailed analysis of single-nucleus (sn)RNA-seq data for three stages of AD from middle temporal gyrus and compare it with snRNA-seq data from the prefrontal cortices from individuals with alcohol use disorder (AUD). We observed a significant decrease in both inhibitory and excitatory neurons, in general agreement with previous reports. We observed several cell-type-specific gene expressions and pathway dysregulations that delineate AD stages. Endothelial and vascular leptomeningeal cells showed the greatest degree of gene expression changes. Cell-type-specific evidence of neurodegeneration was seen in multiple neuronal cell types particularly in somatostatin and Layer 5 extratelencephalic neurons, among others. Evidence of inflammatory responses was seen in non-neuronal cells, particularly in intermediate and advanced AD. We observed common perturbations in AD and AUD, particularly in pathways, like transcription, translation, apoptosis, autophagy, calcium signaling, neuroinflammation, and phosphorylation, that imply shared transcriptional pathogenic mechanisms and support the role of excessive alcohol intake in AD progression. Major AUD gene markers form and perturb a network of genes significantly associated with intermediate and advanced AD. Master regulator analysis from AUD gene markers revealed significant correlation with advanced AD of transcription factors that have implications in intellectual disability, neuroinflammation, and other neurodegenerative conditions, further suggesting a shared nexus of transcriptional changes between AD and AUD.

Exploratory study of blood biomarkers in patients with post-stroke epilepsy

INTRODUCTION

In addition to clinical factors, blood-based biomarkers can provide useful information on the risk of developing post-stroke epilepsy (PSE). Our aim was to identify serum biomarkers at stroke onset that could contribute to predicting patients at higher risk of PSE.

PATIENTS AND METHODS

From a previous study in which 895 acute stroke patients were followed-up, 51 patients developed PSE. We selected 15 patients with PSE and 15 controls without epilepsy. In a biomarker discovery setting, 5 Olink panels of 96 proteins each, were used to determine protein levels. Biomarkers that were down-regulated and overexpressed in PSE patients, and those that showed the strongest interactions with other proteins were validated using an enzyme-linked immunosorbent assay in samples from 50 PSE patients and 50 controls. A ROC curve analysis was used to evaluate the predictive ability of significant biomarkers to develop PSE.

RESULTS

Mean age of the PSE discovery cohort was 68.56 ± 15.1, 40% women and baseline NIHSS 12 [IQR 1-25]. Nine proteins were down-expressed: CASP-8, TNFSF-14, STAMBP, ENRAGE, EDA2R, SIRT2, TGF-alpha, OSM and CLEC1B. VEGFa, CD40 and CCL4 showed greatest interactions with the remaining proteins. In the validation analysis, TNFSF-14 was the single biomarker showing statistically significant downregulated levels in PSE patients (p = 0.006) and it showed a good predictive capability to develop PSE (AUC 0.733, 95% CI 0.601-0.865).

DISCUSSION AND CONCLUSION

Protein expression in PSE patients differs from that of non-epileptic stroke patients, suggesting the involvement of several different proteins in post-stroke epileptogenesis. TNFSF-14 emerges as a potential biomarker for predicting PSE.

Associations of plasma proteomics and age-related outcomes with brain age in a diverse cohort

Machine learning models are increasingly being used to estimate "brain age" from neuroimaging data. The gap between chronological age and the estimated brain age gap (BAG) is potentially a measure of accelerated and resilient brain aging. Brain age calculated in this fashion has been shown to be associated with mortality, measures of physical function, health, and disease. Here, we estimate the BAG using a voxel-based elastic net regression approach, and then, we investigate its associations with mortality, cognitive status, and measures of health and disease in participants from Atherosclerosis Risk in Communities (ARIC) study who had a brain MRI at visit 5 of the study. Finally, we used the SOMAscan assay containing 4877 proteins to examine the proteomic associations with the MRI-defined BAG. Among N = 1849 participants (age, 76.4 (SD 5.6)), we found that increased values of BAG were strongly associated with increased mortality and increased severity of the cognitive status. Strong associations with mortality persisted when the analyses were performed in cognitively normal participants. In addition, it was strongly associated with BMI, diabetes, measures of physical function, hypertension, prevalent heart disease, and stroke. Finally, we found 33 proteins associated with BAG after a correction for multiple comparisons. The top proteins with positive associations to brain age were growth/differentiation factor 15 (GDF-15), Sushi, von Willebrand factor type A, EGF, and pentraxin domain-containing protein 1 (SEVP 1), matrilysin (MMP7), ADAMTS-like protein 2 (ADAMTS), and heat shock 70 kDa protein 1B (HSPA1B) while EGF-receptor (EGFR), mast/stem-cell-growth-factor-receptor (KIT), coagulation-factor-VII, and cGMP-dependent-protein-kinase-1 (PRKG1) were negatively associated to brain age. Several of these proteins were previously associated with dementia in ARIC. These results suggest that circulating proteins implicated in biological aging, cellular senescence, angiogenesis, and coagulation are associated with a neuroimaging measure of brain aging.

Eleven neurology-related proteins measured in serum are positively correlated to the severity of diabetic neuropathy

About 20% of patients with diabetes suffer from chronic pain with neuropathic characteristics. We investigated the multivariate associations between 92 neurology-related proteins measured in serum from 190 patients with painful and painless diabetic neuropathy. Participants were recruited from the Pain in Neuropathy Study, an observational cross-sectional multicentre study in which participants underwent deep phenotyping. In the exploration cohort, two groups were defined by hierarchical cluster analyses of protein data. The proportion of painless vs painful neuropathy did not differ between the two groups, but one group had a significantly higher grade of neuropathy as measured by the Toronto Clinical Scoring System (TCSS). This finding was replicated in the replication cohort. Analyzing both groups together, we found that a group of 11 inter-correlated proteins (TNFRSF12A, SCARB2, N2DL-2, SKR3, EFNA4, LAYN, CLM-1, CD38, UNC5C, GFR-alpha-1, and JAM-B) were positively associated with TCSS values. Notably, EFNA4 and UNC5C are known to be part of axon guidance pathways. To conclude, although cluster analysis of 92 neurology-related proteins did not distinguish painful from painless diabetic neuropathy, we identified 11 proteins which positively correlated to neuropathy severity and warrant further investigation as potential biomarkers.

Plasma proteomic biomarkers and the association between poor cardiovascular health and incident dementia: The UK Biobank study

BACKGROUND

The study examined how plasma proteome indicators may explain the link between poor cardiovascular health (CVH) and dementia risk.

METHODS

The present study involved 28,974 UK Biobank participants aged 50-74y at baseline (2006-2010) who were followed-up for ≤ 15 y for incidence of dementia. CVH was calculated using Life's Essential 8 (LE8) total scores. The scores were standardized and reverse coded to reflect poor CVH (LE8z_rev). OLINK proteomics was available on this sample (k = 1,463 plasma proteins). The study primarily tested the mediating effects of the plasma proteome in LE8z_rev-dementia effect. The total effect was decomposed into "mediation only" or pure indirect effect (PIE), "interaction only" or interaction referent (INTREF), "neither mediation nor interaction" or controlled direct effect (CDE), and "both mediation and interaction" or mediated interaction (INTMED).

RESULTS

The study found poorer CVH assessed by LE8z_rev increased the risk of all-cause dementia by 11 % [per 1 SD, hazard ratio, (HR) = 1.11, 95 % CI: 1.03-1.20, p = 0.005). The study identified 11 plasma proteins with strong mediating effects, with GDF15 having the strongest association with dementia risk (per 1 SD, HR = 1.24, 95 % CI: 1.16, 1.33, P < 0.001 when LE8z_rev is set at its mean value) and the largest proportion mediated combining PIE and INTMED (62.6 %; 48 % of TE is PIE), followed by adrenomedullin or ADM. A first principal component with 10 top mediators (TNFRSF1A, GDF15, FSTL3, COL6A3, PLAUR, ADM, GFRAL, ACVRL1, TNFRSF6B, TGFA) mediated 53.6 % of the LE8z_rev-dementia effect. Using all the significant PIE (k = 526) proteins, we used OLINK Insight pathway analysis to identify key pathways, which revealed the involvement of the immune system, signal transduction, metabolism, disease, protein metabolism, hemostasis, membrane trafficking, extracellular matrix organization, developmental biology, and gene expression among others. STRING analysis revealed that five top consistent proteomic mediators were represented in two larger clusters reflecting numerous interconnected biological gene ontology pathways, most notably cytokine-mediated signaling pathway for GDF15 cluster (GO:0019221) and regulation of peptidyl-tyrosine phosphorylation for the ADM cluster (GO:0050730).

CONCLUSION

Dementia is linked to poor CVH mediated by GDF15 and ADM among several key proteomic markers which collectively explained ∼ 54 % of the total effect.

Unraveling the role of plasma proteins in dementia: insights from two cohort studies in the UK, with causal evidence from Mendelian randomization

Population-based proteomics offer a groundbreaking avenue to predict dementia onset. This study employed a proteome-wide, data-driven approach to investigate protein-dementia associations in 229 incident all-cause dementia (ACD) among 3,249 participants from the English Longitudinal Study of Ageing (ELSA) over a median 9.8-year follow-up, then validated in 1,506 incident ACD among 52,745 individuals from the UK Biobank (UKB) over median 13.7 years. NEFL and RPS6KB1 were robustly associated with incident ACD; MMP12 was associated with vascular dementia in ELSA. Additional markers EDA2R and KIM1 (HAVCR1) were identified from sensitivity analyses. Combining NEFL and RPS6KB1 with other factors yielded high predictive accuracy (area under the curve (AUC)=0.871) for incident ACD. Replication in the UKB confirmed associations between identified proteins with various dementia subtypes. Results from reverse Mendelian Randomization also supported the role of several proteins as early dementia biomarkers. These findings underscore proteomics' potential in identifying novel risk screening targets for dementia.

A Search for New Biological Pathways in Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy by Proteomic Research

Background/Objectives: Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is a hereditary small vessel disease leading to significant morbidity and mortality. Despite advances in genetic diagnosis, the underlying pathophysiology remains incompletely understood. Proteomic studies offer insights into disease mechanisms by identifying altered protein expression patterns. Here, we conducted a proteomic analysis to elucidate molecular pathways associated with CADASIL. Methods: We enrolled genetically diagnosed CADASIL patients and healthy, genetically related controls. Plasma samples were subjected to proteomic analysis using the Olink platform, measuring 552 proteins across six panels. The data were analyzed from several approaches by using three different statistical methods: Exploratory Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA), differential expression with moderated t-test, and gene set enrichment analysis (GSEA). In addition, bioinformatics analysis, including volcano plot, heatmap, and Variable Importance on Projection (VIP) scores from the PLS-DA model were drawn. Results: Significant differences in protein expression were observed between CADASIL patients and controls. RSPO1 and FGF-19 exhibited elevated levels (p < 0.05), while PPY showed downregulation (p < 0.05) in CADASIL patients, suggesting their involvement in disease pathogenesis. Furthermore, MIC-A/B expression varied significantly between patients with mutations in exon 4 versus exon 11 of the NOTCH3 gene (p < 0.05), highlighting potential immunological mechanisms underlying CADASIL. We identified altered pathways using GSEA, applied after ranking the study data. Conclusions: Our study provides novel insights into the proteomic profile of CADASIL, identifying dysregulated proteins associated with vascular pathology, metabolic dysregulation, and immune activation. These findings contribute to a deeper understanding of CADASIL pathophysiology and may inform the development of targeted therapeutic strategies. Further research is warranted to validate these biomarkers and elucidate their functional roles in disease progression.

The circulating proteome and brain health: Mendelian randomisation and cross-sectional analyses

Decline in cognitive function is the most feared aspect of ageing. Poorer midlife cognitive function is associated with increased dementia and stroke risk. The mechanisms underlying variation in cognitive function are uncertain. Here, we assessed associations between 1160 proteins' plasma levels and two measures of cognitive function, the digit symbol substitution test (DSST) and the Montreal Cognitive Assessment in 1198 PURE-MIND participants. We identified five DSST performance-associated proteins (NCAN, BCAN, CA14, MOG, CDCP1), with NCAN and CDCP1 showing replicated association in an independent cohort, GS (N = 1053). MRI-assessed structural brain phenotypes partially mediated (8-19%) associations between NCAN, BCAN, and MOG, and DSST performance. Mendelian randomisation analyses suggested higher CA14 levels might cause larger hippocampal volume and increased stroke risk, whilst higher CDCP1 levels might increase intracranial aneurysm risk. Our findings highlight candidates for further study and the potential for drug repurposing to reduce the risk of stroke and cognitive decline.

Multiplex proteomics identifies inflammation-related plasma biomarkers for aging and cardio-metabolic disorders

BACKGROUND

Cardio-metabolic disorders (CMDs) are common in aging people and are pivotal risk factors for cardiovascular diseases (CVDs). Inflammation is involved in the pathogenesis of CVDs and aging, but the underlying inflammatory molecular phenotypes in CMDs and aging are still unknown.

METHOD

We utilized multiple proteomics to detect 368 inflammatory proteins in the plasma of 30 subjects, including healthy young individuals, healthy elderly individuals, and elderly individuals with CMDs, by Proximity Extension Assay technology (PEA, O-link). Protein-protein interaction (PPI) network and functional modules were constructed to explore hub proteins in differentially expressed proteins (DEPs). The correlation between proteins and clinical traits of CMDs was analyzed and diagnostic value for CMDs of proteins was evaluated by ROC curve analysis.

RESULT

Our results revealed that there were 161 DEPs (adjusted p < 0.05) in normal aging and EGF was the most differentially expressed hub protein in normal aging. Twenty-eight DEPs were found in elderly individuals with CMDs and MMP1 was the most differentially expressed hub protein in CMDs. After the intersection of DEPs in aging and CMDs, there were 10 overlapping proteins: SHMT1, MVK, EGLN1, SLC39A5, NCF2, CXCL6, IRAK4, REG4, PTPN6, and PRDX5. These proteins were significantly correlated with the level of HDL-C, TG, or FPG in plasma. They were verified to have good diagnostic value for CMDs in aging with an AUC > 0.7. Among these, EGLN1, NCF2, REG4, and SLC39A2 were prominently increased both in normal aging and aging with CMDs.

CONCLUSION

Our results could reveal molecular markers for normal aging and CMDs, which need to be further expanded the sample size and to be further investigated to predict their significance for CVDs.

Associations of Folate/Folic Acid Supplementation Alone and in Combination With Other B Vitamins on Dementia Risk and Brain Structure: Evidence From 466 224 UK Biobank Participants

Previous researchers have tried to explore the association between folate/folic acid intake and dementia incidence, but the results remain controversial. We evaluated the associations of folate/folic acid supplementation alone and in combination with other B vitamins on dementia risk and brain structure. A total of 466 224 UK Biobank participants were investigated. Cox proportional hazards models were used to assess the associations between folate/folic acid supplementation status and the risk of Alzheimer's disease (AD) and vascular dementia (VD). Multivariable linear regression models were employed to evaluate the association between folate/folic acid supplementation status and brain structure. In the final model, folate/folic acid supplementation alone was significantly associated with a higher risk of AD (hazard ratio [HR] = 1.34, 95% confidence interval [CI] = 1.06-1.69, p = .015) and VD (HR = 1.61, 95% CI = 1.21-2.13, p = .001). Folate/folic acid supplementation alone was associated with a reduction in the hippocampus (β = -95.25 mm3, 95% CI = -165.31 to -25.19 mm3, p = .014) and amygdala (β = -51.85 mm3, 95% CI = -88.02 to -15.68 mm3, p = .012). The risk of AD and VD, as well as brain structure, in the group with combined folate/folic acid supplementation and other B vitamins did not show a statistically significant difference compared to the reference group (all p > .05). Folate/folic acid supplementation alone is significantly associated with a higher risk of AD and VD, as well as adverse alterations in brain structure. However, when combined with other B vitamins, these detrimental effects can be counteracted.

Hospital-treated prevalent infections, the plasma proteome and incident dementia among UK older adults

The plasma proteome can mediate the association of hospital-treated infections with dementia incidence. We screened up to 37,269 UK Biobank participants aged 50-74 years for the presence of a prevalent hospital-treated infection, subsequently tested as a predictor for ≤1,463 plasma proteins and dementia incidence. Four-way decomposition models decomposed infection-dementia total effect into pure mediation, pure interaction, neither or both through the plasma proteome. Hospital-treated infections increased dementia two-fold. The strongest mediation effect was through the growth differentiation factor 15 (GDF15) protein. Top 17 proteomic mediators explained collectively 5% of the total effect, while pathway analysis of all mediators (k = 221 plasma proteins) revealed top pathways including the immune system, signal transduction, metabolism, disease and metabolism of proteins, with the GDF15 cluster reflecting most strongly the "transmembrane receptor protein tyrosine kinase signaling pathway". The association of hospital-treated infections with dementia was partially mediated through GDF15 and other plasma proteomic markers.

Plasma proteomic profiles predict individual future health risk

Developing a single-domain assay to identify individuals at high risk of future events is a priority for multi-disease and mortality prevention. By training a neural network, we developed a disease/mortality-specific proteomic risk score (ProRS) based on 1461 Olink plasma proteins measured in 52,006 UK Biobank participants. This integrative score markedly stratified the risk for 45 common conditions, including infectious, hematological, endocrine, psychiatric, neurological, sensory, circulatory, respiratory, digestive, cutaneous, musculoskeletal, and genitourinary diseases, cancers, and mortality. The discriminations witnessed high accuracies achieved by ProRS for 10 endpoints (e.g., cancer, dementia, and death), with C-indexes exceeding 0.80. Notably, ProRS produced much better or equivalent predictive performance than established clinical indicators for almost all endpoints. Incorporating clinical predictors with ProRS enhanced predictive power for most endpoints, but this combination only exhibited limited improvement when compared to ProRS alone. Some proteins, e.g., GDF15, exhibited important discriminative values for various diseases. We also showed that the good discriminative performance observed could be largely translated into practical clinical utility. Taken together, proteomic profiles may serve as a replacement for complex laboratory tests or clinical measures to refine the comprehensive risk assessments of multiple diseases and mortalities simultaneously. Our models were internally validated in the UK Biobank; thus, further independent external validations are necessary to confirm our findings before application in clinical settings.

Identification of circulating proteins associated with general cognitive function among middle-aged and older adults

Identifying circulating proteins associated with cognitive function may point to biomarkers and molecular process of cognitive impairment. Few studies have investigated the association between circulating proteins and cognitive function. We identify 246 protein measures quantified by the SomaScan assay as associated with cognitive function (p < 4.9E-5, n up to 7289). Of these, 45 were replicated using SomaScan data, and three were replicated using Olink data at Bonferroni-corrected significance. Enrichment analysis linked the proteins associated with general cognitive function to cell signaling pathways and synapse architecture. Mendelian randomization analysis implicated higher levels of NECTIN2, a protein mediating viral entry into neuronal cells, with higher Alzheimer's disease (AD) risk (p = 2.5E-26). Levels of 14 other protein measures were implicated as consequences of AD susceptibility (p < 2.0E-4). Proteins implicated as causes or consequences of AD susceptibility may provide new insight into the potential relationship between immunity and AD susceptibility as well as potential therapeutic targets.

Molecular Mechanisms for Changing Brain Connectivity in Mice and Humans

The goal of this study was to examine commonalities in the molecular basis of learning in mice and humans. In previous work we have demonstrated that the anterior cingulate cortex (ACC) and hippocampus (HC) are involved in learning a two-choice visuospatial discrimination task. Here, we began by looking for candidate genes upregulated in mouse ACC and HC with learning. We then determined which of these were also upregulated in mouse blood. Finally, we used RT-PCR to compare candidate gene expression in mouse blood with that from humans following one of two forms of learning: a working memory task (network training) or meditation (a generalized training shown to change many networks). Two genes were upregulated in mice following learning: caspase recruitment domain-containing protein 6 (Card6) and inosine monophosphate dehydrogenase 2 (Impdh2). The Impdh2 gene product catalyzes the first committed step of guanine nucleotide synthesis and is tightly linked to cell proliferation. The Card6 gene product positively modulates signal transduction. In humans, Card6 was significantly upregulated, and Impdh2 trended toward upregulation with training. These genes have been shown to regulate pathways that influence nuclear factor kappa B (NF-κB), a factor previously found to be related to enhanced synaptic function and learning.

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.

Plasma levels of neurology-related proteins are associated with cognitive performance in an older population with overweight/obesity and metabolic syndrome

Cognitive impairment is present in a broad spectrum of medical conditions and in aging. Here, we aimed to identify plasma proteins related to cognitive function in a sample of older adults with overweight/obesity and metabolic syndrome. A total of 129 subjects (mean age 64.7 years; 36% females) were grouped according to low (l-GCF, N=65) or high (h-GCF, N=64) global cognitive function and matched according to education, sex, age, and body mass index. Cognitive performance was assessed using neuropsychological tests. Plasma levels of 92 neurology-related proteins were assessed using a proximity extension assay. An elastic net regression analysis was used to identify proteins more associated with cognitive performance. Additionally, the protein expression levels were compared between the two groups by means of a t-test with false discovery rate correction. Pearson correlations were used to assess associations between the protein levels and scores from the neurocognitive tests. Six proteins (alpha-2-MRAP, HAGH, Siglec-9, MDGA1, IL12, and EDA2R) were identified as potential contributors to cognitive performance, remaining significantly increased in l-GCF compared to h-GCF participants after correction for multiple testing. Negative correlations (r= -0.23 to -0.18, i.e., lower protein levels, higher cognitive function) were found between global cognitive function and Siglec-9, NMNAT1, HAGH, LXN, gal-8, alpha-2-MRAP, IL12, PDGF-R-alpha, NAAA, EDA2R, CLEC1B, and LAT. Mini-mental state examination z scores showed the strongest correlations with protein levels, specifically negative correlations with CLEC1b, LXN, LAT, PLXNB3, NMNAT1, gal-8, HAGH, NAAA, CTSS, EZR, KYNU, MANF (r=-0.38 to -0.26) and a positive correlation with ADAM23 (r= 0.26). In summary, we identified several plasma proteins that were significantly associated with cognitive performance in older adults with obesity and metabolic syndrome, although further research is needed to replicate the results in larger samples and to include a predictive perspective.

Proteomic Analysis Identifies Circulating Proteins Associated With Plasma Amyloid-β and Incident Dementia

Background

Plasma amyloid-β (Aβ) (Aβ42, Aβ40, and Aβ42/Aβ40), biomarkers of the Alzheimer's form of dementia, are under consideration for clinical use. The associations of these peptides with circulating proteins may identify novel plasma biomarkers of dementia and inform peripheral factors influencing the levels of these peptides.

Methods

We analyzed the association of these 3 plasma Aβ measures with 4638 circulating proteins among a subset of the participants of the Atherosclerosis Risk in Communities (ARIC) study (midlife: n = 1955; late life: n = 2082), related the Aβ-associated proteins with incident dementia in the overall ARIC cohort (midlife: n = 11,069, late life: n = 4110) with external replication in the Age, Gene/Environment Susceptibility (AGES)-Reykjavik Study (n = 4973), estimated the proportion of Aβ variance explained, and conducted enrichment analyses to characterize the proteins associated with the plasma Aβ peptides.

Results

At midlife, of the 296 Aβ-associated proteins, 8 were associated with incident dementia from midlife and late life in the ARIC study, and NPPB, IBSP, and THBS2 were replicated in the AGES-Reykjavik Study. At late life, of the 34 Aβ-associated proteins, none were associated with incident dementia at midlife, and kidney function explained 10%, 12%, and 0.2% of the variance of Aβ42, Aβ40, and Aβ42/Aβ40, respectively. Aβ42-associated proteins at midlife were found to be enriched in the liver, and those at late life were found to be enriched in the spleen.

Conclusions

This study identifies circulating proteins associated with plasma Aβ levels and incident dementia and informs peripheral factors associated with plasma Aβ levels.

Synaptic resilience is associated with maintained cognition during ageing

INTRODUCTION

It remains unclear why age increases risk of Alzheimer's disease and why some people experience age-related cognitive decline in the absence of dementia. Here we test the hypothesis that resilience to molecular changes in synapses contribute to healthy cognitive ageing.

METHODS

We examined post-mortem brain tissue from people in mid-life (n = 15), healthy ageing with either maintained cognition (n = 9) or lifetime cognitive decline (n = 8), and Alzheimer's disease (n = 13). Synapses were examined with high resolution imaging, proteomics, and RNA sequencing. Stem cell-derived neurons were challenged with Alzheimer's brain homogenate.

RESULTS

Synaptic pathology increased, and expression of genes involved in synaptic signaling decreased between mid-life, healthy ageing and Alzheimer's. In contrast, brain tissue and neurons from people with maintained cognition during ageing exhibited decreases in synaptic signaling genes compared to people with cognitive decline.

DISCUSSION

Efficient synaptic networks without pathological protein accumulation may contribute to maintained cognition during ageing.

Proteomic characterization of atopic dermatitis blood from infancy to adulthood

BACKGROUND

Patients with atopic dermatitis (AD) have systemic biomarker dysregulation that differs by age group; however, the proteomic characteristics of these age-based changes are unknown.

OBJECTIVE

To profile blood proteins of patients with AD across different age groups versus age-appropriate controls.

METHODS

Using the Olink high-throughput proteomic platform, we profiled 375 serum proteins of 20 infants (age, 0-5 years), 39 children (age, 6-11 years), 21 adolescents (age, 12-17 years), and 20 adults (age, ≥18 years) with moderate-to-severe AD and 83 age-appropriate controls.

RESULTS

Each group presented a distinct systemic proteomic signature. Th2-related proteins were increased in infant AD and further intensified with age through adolescence and adulthood (interleukin 4/CCL13/CCL17). In contrast, Th1 axis down-regulation was detected in infants with AD and gradually reversed to increased Th1 products (interferon γ/CXCL9/CXCL10/CCL2) in patients with AD from childhood to adulthood. Despite their short disease duration, infants already had evidence of systemic inflammation, with significant upregulation of innate immunity (interleukin 17C/ interleukin-1RN), T-cell activation/migration (CCL19), Th2 (CCL13/CCL17), and Th17 (PI3) proteins. Adults with AD present unique upregulation of cardiovascular proteins related to coagulation and diabetes.

LIMITATIONS

Cross-sectional observational study with a single time point.

CONCLUSION

Systemic immune signatures of AD are age-specific beyond the shared Th2 immune activation. These data advocate for precision medicine approaches based on age-specific AD profiles.

Unraveling Neuro-Proteogenomic Landscape and Therapeutic Implications for Human Behaviors and Psychiatric Disorders

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioral traits and the disease etiology of neuropsychiatric disorders. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-related proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-related traits such as sleeping, smoking, feelings, alcohol intake, mental health, and psychiatric disorders. Integrating with established drug information, we validated 13 out of 13 matched combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets. This consortium effort provides a large-scale proteogenomic resource for biomedical research on human behaviors and other neuro-related phenotypes.

Circulatory proteins relate cardiovascular disease to cognitive performance: A mendelian randomisation study

Background and objectives: Mechanistic research suggests synergistic effects of cardiovascular disease (CVD) and dementia pathologies on cognitive decline. Interventions targeting proteins relevant to shared mechanisms underlying CVD and dementia could also be used for the prevention of cognitive impairment. Methods: We applied Mendelian randomisation (MR) and colocalization analysis to investigate the causal relationships of 90 CVD-related proteins measured by the Olink CVD I panel with cognitive traits. Genetic instruments for circulatory protein concentrations were obtained using a meta-analysis of genome-wide association studies (GWAS) from the SCALLOP consortium (N = 17,747) based on three sets of criteria: 1) protein quantitative trait loci (pQTL); 2) cis-pQTL (pQTL within ±500 kb from the coding gene); and 3) brain-specific cis-expression QTL (cis-eQTL) which accounts for coding gene expression based on GTEx8. Genetic associations of cognitive performance were obtained from GWAS for either: 1) general cognitive function constructed using Principal Component Analysis (N = 300,486); or, 2) g Factor constructed using genomic structural equation modelling (N = 11,263-331,679). Findings for candidate causal proteins were replicated using a separate protein GWAS in Icelanders (N = 35,559). Results: A higher concentration of genetically predicted circulatory myeloperoxidase (MPO) was nominally associated with better cognitive performance (p < 0.05) using different selection criteria for genetic instruments. Particularly, brain-specific cis-eQTL predicted MPO, which accounts for protein-coding gene expression in brain tissues, was associated with general cognitive function (βWald = 0.22, PWald = 2.4 × 10-4). The posterior probability for colocalization (PP.H4) of MPO pQTL with the g Factor was 0.577. Findings for MPO were replicated using the Icelandic GWAS. Although we did not find evidence for colocalization, we found that higher genetically predicted concentrations of cathepsin D and CD40 were associated with better cognitive performance and a higher genetically predicted concentration of CSF-1 was associated with poorer cognitive performance. Conclusion: We conclude that these proteins are involved in shared pathways between CVD and those for cognitive reserve or affecting cognitive decline, suggesting therapeutic targets able to reduce genetic risks conferred by cardiovascular disease.

Genetic mechanisms of 184 neuro-related proteins in human plasma

Understanding the genetic basis of neuro-related proteins is essential for dissecting the disease etiology of neuropsychiatric disorders and other complex traits and diseases. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-reiated proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-reiated traits as well as complex diseases such as hypertension, high cholesterol, immune-related disorders, and psychiatric disorders. Integrating with established drug information, we validated 13 combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets for diseases and comorbidities. This consortium effort provides a large-scale proteogenomic resource for biomedical research.

Cross-sectional and longitudinal assessment of the association between DDR1 variants and processing speed in patients with early psychosis and healthy controls

Recent evidence indicates that DDR1 participates in myelination and that variants of DDR1 are associated with decreased cognitive processing speed (PS) in schizophrenia (SZ). Here, we explored whether DDR1 variants were associated with PS in subjects diagnosed with an early psychosis (EP), a condition often preceding SZ. Data from two Spanish independent samples (from Reus and Santander) including patients with EP (n = 75 and n = 312, respectively) and healthy controls (HCs; n = 57 and n = 160) were analyzed. The Trail Making Test part A was used to evaluate PS. Participants underwent genotyping to identify DDR1 variants rs1264323 and rs2267641. Cross-sectional data were analyzed with general linear models and longitudinal data were analyzed using mixed models. We examined the combined rs1264323AA-rs2267641AC/CC genotypes (an SZ-risk combination) on PS. The SZ-risk combined genotypes were associated with increased PS in EP patients but not in HCs in the cross-sectional analysis. In the longitudinal analysis, the SZ-risk combined genotypes were significantly associated with increased PS in both HCs and EP patients throughout the 10-year follow-up but no genotype × time interaction was observed. These results provide further evidence that DDR1 is involved in cognition and should be replicated with other samples.

Discovery and replication of blood-based proteomic signature of PTSD in 9/11 responders

Proteomics provides an opportunity to develop biomarkers for the early detection and monitoring of post-traumatic stress disorder (PTSD). However, research to date has been limited by small sample sizes and a lack of replication. This study performed Olink Proseek Multiplex Platform profiling of 81 proteins involved in neurological processes in 936 responders to the 9/11 disaster (mean age at blood draw = 55.41 years (SD = 7.93), 94.1% white, all men). Bivariate correlations and elastic net regressions were used in a discovery subsample to identify concurrent associations between PTSD symptom severity and the profiled proteins, and to create a multiprotein composite score. In hold-out subsamples, nine bivariate associations between PTSD symptoms and differentially expressed proteins were replicated: SKR3, NCAN, BCAN, MSR1, PVR, TNFRSF21, DRAXIN, CLM6, and SCARB2 (|r| = 0.08-0.17, p < 0.05). There were three replicated bivariate associations between lifetime PTSD diagnosis and differentially expressed proteins: SKR3, SIGLEC, and CPM (OR = 1.38-1.50, p < 0.05). The multiprotein composite score retained 38 proteins, including 10/11 proteins that replicated in bivariate tests. The composite score was significantly associated with PTSD symptom severity (β = 0.27, p < 0.001) and PTSD diagnosis (OR = 1.60, 95% CI: 1.17-2.19, p = 0.003) in the hold-out subsample. Overall, these findings suggest that PTSD is characterized by altered expression of several proteins implicated in neurological processes. Replicated associations with TNFRSF21, CLM6, and PVR support the neuroinflammatory signature of PTSD. The multiprotein composite score substantially increased associations with PTSD symptom severity over individual proteins. If generalizable to other populations, the current findings may inform the development of PTSD biomarkers.

Investigation of 91 proteins implicated in neurobiological processes identifies multiple candidate plasma biomarkers of stroke outcome

The inter-individual variation in stroke outcomes is large and protein studies could point to potential underlying biological mechanisms. We measured plasma levels of 91 neurobiological proteins in 209 cases included in the Sahlgrenska Academy Study on Ischemic Stroke using a Proximity Extension Assay, and blood was sampled in the acute phase and at 3-month and 7-year follow-ups. Levels were also determined once in 209 controls. Acute stroke severity and neurological outcome were evaluated by the National Institutes of Health Stroke Scale. In linear regression models corrected for age, sex, and sampling day, acute phase levels of 37 proteins were associated with acute stroke severity, and 47 with 3-month and/or 7-year outcome at false discovery rate < 0.05. Three-month levels of 8 proteins were associated with 7-year outcome, of which the associations for BCAN and Nr-CAM were independent also of acute stroke severity. Most proteins followed a trajectory with lower levels in the acute phase compared to the 3-month follow-up and the control sampling point. Conclusively, we identified multiple candidate plasma biomarkers of stroke severity and neurological outcome meriting further investigation. This study adds novel information, as most of the reported proteins have not been previously investigated in a stroke cohort.

Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health

Characterising associations between the methylome, proteome and phenome may provide insight into biological pathways governing brain health. Here, we report an integrated DNA methylation and phenotypic study of the circulating proteome in relation to brain health. Methylome-wide association studies of 4058 plasma proteins are performed (N = 774), identifying 2928 CpG-protein associations after adjustment for multiple testing. These are independent of known genetic protein quantitative trait loci (pQTLs) and common lifestyle effects. Phenome-wide association studies of each protein are then performed in relation to 15 neurological traits (N = 1,065), identifying 405 associations between the levels of 191 proteins and cognitive scores, brain imaging measures or APOE e4 status. We uncover 35 previously unreported DNA methylation signatures for 17 protein markers of brain health. The epigenetic and proteomic markers we identify are pertinent to understanding and stratifying brain health.

A Neuroimaging Signature of Cognitive Aging from Whole-Brain Functional Connectivity

Cognitive decline is amongst one of the most commonly reported complaints during normal aging. Despite evidence that age and cognition are linked with similar neural correlates, no previous studies have directly ascertained how these two constructs overlap in the brain in terms of neuroimaging-based prediction. Based on a long lifespan healthy cohort (CamCAN, aged 19-89 years, n = 567), it is shown that both cognitive function (domains spanning executive function, emotion processing, motor function, and memory) and human age can be reliably predicted from unique patterns of functional connectivity, with models generalizable in two external datasets (n = 533 and n = 453). Results show that cognitive decline and normal aging both manifest decrease within-network connections (especially default mode and ventral attention networks) and increase between-network connections (somatomotor network). Whereas dorsal attention network is an exception, which is highly predictive on cognitive ability but is weakly correlated with aging. Further, the positively weighted connections in predicting fluid intelligence significantly mediate its association with age. Together, these findings offer insights into why normal aging is often associated with cognitive decline in terms of brain network organization, indicating a process of neural dedifferentiation and compensational theory.

MSR1 and NEP Are Correlated with Alzheimer's Disease Amyloid Pathology and Apolipoprotein Alterations

BACKGROUND

In mouse models of amyloidosis, macrophage receptor 1 (MSR1) and neprilysin (NEP) have been shown to interact to reduce amyloid burden in the brain.

OBJECTIVE

The purpose of this study is to analyze these two gene products in combination with apolipoproteins and Aβ1-42 in the cerebrospinal fluid (CSF) and plasma of individuals at different stages of Alzheimer's disease (AD), as well as in autopsied brain samples from ROSMAP (Religious Orders Study and Memory and Aging Project).

METHODS

CSF/plasma levels of MSR1 and NEP were measured using the sensitive primer extension assay technology. CSF Aβ1-42 was assessed with ELISA, while CSF ApoE and ApoJ were measured with the Luminex's multiplex technology. Brain MSR1, APOE, and CLU (APOJ) mRNA levels were measured with RNA-Seq and contrasted to amyloid plaques pathology using CERAD staging.

RESULTS

While plasma and CSF MSR1 levels are significantly correlated, this correlation was not observed for NEP. In addition to be highly correlated to one another, CSF levels of both MSR1 and NEP are strongly correlated with AD status and CSF Aβ1-42, ApoE, and ApoJ levels. In the cortical tissues of subjects from ROSMAP, MSR1 mRNA levels are correlated with CLU mRNA levels and the CERAD scores but not with APOE mRNA levels.

CONCLUSION

The discrepancies observed between CSF/plasma levels of MSR1 and NEP with CSF Aβ1-42 and ApoE concentrations can be explained by many factors, such as the disease stage or the involvement of the blood-brain barrier breakdown that leads to the infiltration of peripheral monocytes or macrophages.

Blood-based epigenome-wide analyses of cognitive abilities

BACKGROUND

Blood-based markers of cognitive functioning might provide an accessible way to track neurodegeneration years prior to clinical manifestation of cognitive impairment and dementia.

RESULTS

Using blood-based epigenome-wide analyses of general cognitive function, we show that individual differences in DNA methylation (DNAm) explain 35.0% of the variance in general cognitive function (g). A DNAm predictor explains ~4% of the variance, independently of a polygenic score, in two external cohorts. It also associates with circulating levels of neurology- and inflammation-related proteins, global brain imaging metrics, and regional cortical volumes.

CONCLUSIONS

As sample sizes increase, the ability to assess cognitive function from DNAm data may be informative in settings where cognitive testing is unreliable or unavailable.

The cerebrospinal fluid proteome of preterm infants predicts neurodevelopmental outcome

BACKGROUND

Survival rate increases for preterm infants, but long-term neurodevelopmental outcome predictors are lacking. Our primary aim was to determine whether a specific proteomic profile in cerebrospinal fluid (CSF) of preterm infants differs from that of term infants and to identify novel biomarkers of neurodevelopmental outcome in preterm infants.

METHODS

Twenty-seven preterm infants with median gestational age 27 w + 4 d and ten full-term infants were enrolled prospectively. Protein profiling of CSF were performed utilizing an antibody suspension bead array. The relative levels of 178 unique brain derived proteins and inflammatory mediators, selected from the Human Protein Atlas, were measured.

RESULTS

The CSF protein profile of preterm infants differed from that of term infants. Increased levels of brain specific proteins that are associated with neurodevelopment and neuroinflammatory pathways made up a distinct protein profile in the preterm infants. The most significant differences were seen in proteins involved in neurodevelopmental regulation and synaptic plasticity, as well as components of the innate immune system. Several proteins correlated with favorable outcome in preterm infants at 18-24 months corrected age. Among the proteins that provided strong predictors of outcome were vascular endothelial growth factor C, Neurocan core protein and seizure protein 6, all highly important in normal brain development.

CONCLUSION

Our data suggest a vulnerability of the preterm brain to postnatal events and that alterations in protein levels may contribute to unfavorable neurodevelopmental outcome.

Open Circuit Potential as a Tool for the Assessment of Binding Kinetics and Reagentless Protein Quantitation

A microfluidic open circuit potential label-free protein assay was developed for the reagentless quantification of C-reactive protein (CRP), a model protein target, and further utilized to assess target-receptor binding kinetics. Generated sensors have very high baseline stabilities (<1% change in 100 min) and high levels of selectivity in complex media. Real-time assays are fast (<20 min), of high sensitivity (1 ng/mL limit of detection for CRP in serum), and resolve kinetic and thermodynamic characteristics that correlate well with those resolved optically. The assay shows excellent correlation with an enzyme-linked immunosorbent assay analysis of patient samples. The methodology has value in potentially underpinning a low-cost, rapid, and sensitive single-step biomarker quantification.

Advances and Utility of the Human Plasma Proteome

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.

Personalised predictive modelling with brain-inspired spiking neural networks of longitudinal MRI neuroimaging data and the case study of dementia

BACKGROUND

Longitudinal neuroimaging provides spatiotemporal brain data (STBD) measurement that can be utilised to understand dynamic changes in brain structure and/or function underpinning cognitive activities. Making sense of such highly interactive information is challenging, given that the features manifest intricate temporal, causal relations between the spatially distributed neural sources in the brain.

METHODS

The current paper argues for the advancement of deep learning algorithms in brain-inspired spiking neural networks (SNN), capable of modelling structural data across time (longitudinal measurement) and space (anatomical components). The paper proposes a methodology and a computational architecture based on SNN for building personalised predictive models from longitudinal brain data to accurately detect, understand, and predict the dynamics of an individual's functional brain state. The methodology includes finding clusters of similar data to each individual, data interpolation, deep learning in a 3-dimensional brain-template structured SNN model, classification and prediction of individual outcome, visualisation of structural brain changes related to the predicted outcomes, interpretation of results, and individual and group predictive marker discovery.

RESULTS

To demonstrate the functionality of the proposed methodology, the paper presents experimental results on a longitudinal magnetic resonance imaging (MRI) dataset derived from 175 older adults of the internationally recognised community-based cohort Sydney Memory and Ageing Study (MAS) spanning 6 years of follow-up.

SIGNIFICANCE

The models were able to accurately classify and predict 2 years ahead of cognitive decline, such as mild cognitive impairment (MCI) and dementia with 95% and 91% accuracy, respectively. The proposed methodology also offers a 3-dimensional visualisation of the MRI models reflecting the dynamic patterns of regional changes in white matter hyperintensity (WMH) and brain volume over 6 years.

CONCLUSION

The method is efficient for personalised predictive modelling on a wide range of neuroimaging longitudinal data, including also demographic, genetic, and clinical data. As a case study, it resulted in finding predictive markers for MCI and dementia as dynamic brain patterns using MRI data.

Uncovering the Depths of the Human Proteome: Antibody-based Technologies for Ultrasensitive Multiplexed Protein Detection and Quantification

Probing the human proteome in tissues and biofluids such as plasma is attractive for biomarker and drug target discovery. Recent breakthroughs in multiplex, antibody-based, proteomics technologies now enable the simultaneous quantification of thousands of proteins at as low as sub fg/ml concentrations with remarkable dynamic ranges of up to 10-log. We herein provide a comprehensive guide to the methodologies, performance, technical comparisons, advantages, and disadvantages of established and emerging technologies for the multiplexed ultrasensitive measurement of proteins. Gaining holistic knowledge on these innovations is crucial for choosing the right multiplexed proteomics tool for applications at hand to critically complement traditional proteomics methods. This can bring researchers closer than ever before to elucidating the intricate inner workings and cross talk that spans multitude of proteins in disease mechanisms.

The plasma peptides of Alzheimer's disease

Background

A practical strategy to discover proteins specific to Alzheimer’s dementia (AD) may be to compare the plasma peptides and proteins from patients with dementia to normal controls and patients with neurological conditions like multiple sclerosis or other diseases. The aim was a proof of principle for a method to discover proteins and/or peptides of plasma that show greater observation frequency and/or precursor intensity in AD. The endogenous tryptic peptides of Alzheimer’s were compared to normals, multiple sclerosis, ovarian cancer, breast cancer, female normal, sepsis, ICU Control, heart attack, along with their institution-matched controls, and normal samples collected directly onto ice.

Methods

Endogenous tryptic peptides were extracted from blinded, individual AD and control EDTA plasma samples in a step gradient of acetonitrile for random and independent sampling by LC–ESI–MS/MS with a set of robust and sensitive linear quadrupole ion traps. The MS/MS spectra were fit to fully tryptic peptides within proteins identified using the X!TANDEM algorithm. Observation frequency of the identified proteins was counted using SEQUEST algorithm. The proteins with apparently increased observation frequency in AD versus AD Control were revealed graphically and subsequently tested by Chi Square analysis. The proteins specific to AD plasma by Chi Square with FDR correction were analyzed by the STRING algorithm. The average protein or peptide log₁₀ precursor intensity was compared across disease and control treatments by ANOVA in the R statistical system.

Results

Peptides and/or phosphopeptides of common plasma proteins such as complement C2, C7, and C1QBP among others showed increased observation frequency by Chi Square and/or precursor intensity in AD. Cellular gene symbols with large Chi Square values (χ2 ≥ 25, p ≤ 0.001) from tryptic peptides included KIF12, DISC1, OR8B12, ZC3H12A, TNF, TBC1D8B, GALNT3, EME2, CD1B, BAG1, CPSF2, MMP15, DNAJC2, PHACTR4, OR8B3, GCK, EXOSC7, HMGA1 and NT5C3A among others. Similarly, increased frequency of tryptic phosphopeptides were observed from MOK, SMIM19, NXNL1, SLC24A2, Nbla10317, AHRR, C10orf90, MAEA, SRSF8, TBATA, TNIK, UBE2G1, PDE4C, PCGF2, KIR3DP1, TJP2, CPNE8, and NGF amongst others. STRING analysis showed an increase in cytoplasmic proteins and proteins associated with alternate splicing, exocytosis of luminal proteins, and proteins involved in the regulation of the cell cycle, mitochondrial functions or metabolism and apoptosis. Increases in mean precursor intensity of peptides from common plasma proteins such as DISC1, EXOSC5, UBE2G1, SMIM19, NXNL1, PANO, EIF4G1, KIR3DP1, MED25, MGRN1, OR8B3, MGC24039, POLR1A, SYTL4, RNF111, IREB2, ANKMY2, SGKL, SLC25A5, CHMP3 among others were associated with AD. Tryptic peptides from the highly conserved C-terminus of DISC1 within the sequence MPGGGPQGAPAAAGGGGVSHRAGSRDCLPPAACFR and ARQCGLDSR showed a higher frequency and highest intensity in AD compared to all other disease and controls.

Conclusion

Proteins apparently expressed in the brain that were directly related to Alzheimer’s including Nerve Growth Factor (NFG), Sphingomyelin Phosphodiesterase, Disrupted in Schizophrenia 1 (DISC1), the cell death regulator retinitis pigmentosa (NXNl1) that governs the loss of nerve cells in the retina and the cell death regulator ZC3H12A showed much higher observation frequency in AD plasma vs the matched control. There was a striking agreement between the proteins known to be mutated or dis-regulated in the brains of AD patients with the proteins observed in the plasma of AD patients from endogenous peptides including NBN, BAG1, NOX1, PDCD5, SGK3, UBE2G1, SMPD3 neuronal proteins associated with synapse function such as KSYTL4, VTI1B and brain specific proteins such as TBATA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-021-09320-2.

Arsenic Exposure and Cancer-Related Proteins in Urine of Indigenous Bolivian Women

Indigenous people living in the Bolivian Andes are exposed through their drinking water to inorganic arsenic, a potent carcinogen. However, the health consequences of arsenic exposure in this region are unknown. The aim of this study was to evaluate associations between arsenic exposure and changes in cancer-related proteins in indigenous women (n = 176) from communities around the Andean Lake Poopó, Bolivia. Arsenic exposure was assessed in whole blood (B-As) and urine (as the sum of arsenic metabolites, U-As) by inductively coupled plasma-mass spectrometry (ICP-MS). Cancer-related proteins (N = 92) were measured in urine using the proximity extension assay. The median B-As concentration was 2.1 (range 0.60-9.1) ng/g, and U-As concentration was 67 (12-399) μg/L. Using linear regression models adjusted for age, urinary osmolality, and urinary leukocytes, we identified associations between B-As and four putative cancer-related proteins: FASLG, SEZ6L, LYPD3, and TFPI2. Increasing B-As concentrations were associated with lower protein expression of SEZ6L, LYPD3, and TFPI2, and with higher expression of FASLG in urine (no association was statistically significant after correcting for multiple comparisons). The associations were similar across groups with different arsenic metabolism efficiency, a susceptibility factor for arsenic toxicity. In conclusion, arsenic exposure in this region was associated with changes in the expression of some cancer-related proteins in urine. Future research is warranted to understand if these proteins could serve as valid biomarkers for arsenic-related toxicity.