From SOMAmer-based biomarker discovery to diagnostic and clinical applications: a SOMAmer-based, streamlined multiplex proteomic assay

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.

Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using plasma proteomics profiling

AIMS

Atrial fibrillation (AF) is the most common sustained arrhythmia among patients with hypertrophic cardiomyopathy (HCM), increasing symptom burden and stroke risk. We aimed to construct a plasma proteomics-based model to predict new-onset AF in patients with HCM and determine dysregulated signalling pathways.

METHODS AND RESULTS

In this prospective, multi-centre cohort study, we conducted plasma proteomics profiling of 4986 proteins at enrolment. We developed a proteomics-based machine learning model to predict new-onset AF using samples from one institution (training set) and tested its predictive ability using independent samples from another institution (test set). We performed a survival analysis to compare the risk of new-onset AF among high- and low-risk groups in the test set. We performed pathway analysis of proteins significantly (univariable P < 0.05) associated with new-onset AF using a false discovery rate (FDR) threshold of 0.001. The study included 284 patients with HCM (training set: 193, test set: 91). Thirty-seven (13%) patients developed AF during median follow-up of 3.2 years [25-75 percentile: 1.8-5.2]. Using the proteomics-based prediction model developed in the training set, the area under the receiver operating characteristic curve was 0.89 (95% confidence interval 0.78-0.99) in the test set. In the test set, patients categorized as high risk had a higher rate of developing new-onset AF (log-rank P = 0.002). The Ras-MAPK pathway was dysregulated in patients who developed incident AF during follow-up (FDR < 1.0 × 10-6).

CONCLUSION

This is the first study to demonstrate the ability of plasma proteomics to predict new-onset AF in HCM and identify dysregulated signalling pathways.

Proteomic and transcriptomic analyses identify apo-transcobalamin-II as a biomarker of overall survival in osteosarcoma

Background

The large-scale proteomic platform known as the SomaScan® assay is capable of simultaneously measuring thousands of proteins in patient specimens through next-generation aptamer-based multiplexed technology. While previous studies have utilized patient peripheral blood to suggest serum biomarkers of prognostic or diagnostic value in osteosarcoma (OSA), the most common primary pediatric bone cancer, they have ultimately been limited in the robustness of their analyses. We propose utilizing this aptamer-based technology to describe the systemic proteomic milieu in patients diagnosed with this disease.

Methods

To determine novel biomarkers associated with overall survival in OSA, we deployed the SomaLogic SomaScan® 7k assay to investigate the plasma proteomic profile of naive primary, recurrent, and metastatic OSA patients. Following identification of differentially expressed proteins (DEPs) between 2-year deceased and survivor cohorts, publicly available databases including Survival Genie, TIGER, and KM Plotter Immunotherapy, among others, were utilized to investigate the significance of our proteomic findings.

Results

Apo-transcobalamin-II (APO-TCN2) was identified as the most DEP between 2-year deceased and survivor cohorts (Log2 fold change = 6.8, P-value = 0.0017). Survival analysis using the Survival Genie web-based platform indicated that increased intratumoral TCN2 expression was associated with better overall survival in both OSA (TARGET-OS) and sarcoma (TCGA-SARC) datasets. Cell-cell communication analysis using the TIGER database suggested that TCN2+ Myeloid cells likely interact with marginal zone and immunoglobin-producing B lymphocytes expressing the TCN2 receptor (CD320) to promote their proliferation and survival in both non-small cell lung cancer and melanoma tumors. Analysis of publicly available OSA scRNA-sequencing datasets identified similar populations in naive primary tumors. Furthermore, circulating APO-TCN2 levels in OSA were then associated with a plasma proteomic profile likely necessary for robust B lymphocyte proliferation, infiltration, and formation of intratumoral tertiary lymphoid structures for improved anti-tumor immunity.

Conclusions

Overall, APO-TCN2, a circulatory protein previously described in various lymphoproliferative disorders, was associated with 2-year survival status in patients diagnosed with OSA. The relevance of this protein and apparent immunological function (anti-tumor B lymphocyte responses) was suggested using publicly available solid tumor RNA-sequencing datasets. Further studies characterizing the biological function of APO-TCN2 and its relevance in these diseases is warranted.

Fluorogenic RNA-Based Biosensors of Small Molecules: Current Developments, Uses, and Perspectives

Small molecules are highly relevant targets for detection and quantification. They are also used to diagnose and monitor the progression of disease and infectious processes and track the presence of contaminants. Fluorogenic RNA-based biosensors (FRBs) represent an appealing solution to the problem of detecting these targets. They combine the portability of molecular systems with the sensitivity and multiplexing capacity of fluorescence, as well as the exquisite ligand selectivity of RNA aptamers. In this review, we first present the different sensing and reporting aptamer modules currently available to design an FRB, together with the main methodologies used to discover modules with new specificities. We next introduce and discuss how both modules can be functionally connected prior to exploring the main applications for which FRB have been used. Finally, we conclude by discussing how using alternative nucleotide chemistries may improve FRB properties and further widen their application scope.

Data acquisition approaches for single cell proteomics

Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.

Anemia, Iron Deficiency, and Cause-Specific Mortality: The Atherosclerosis Risk in Communities Study

INTRODUCTION

Anemia is a risk factor for all-cause mortality in older adults. Iron deficiency may also be associated with adverse outcomes, independent of its role in causing anemia. This study tested the hypotheses that anemia, and low ferritin among non-anemic participants, were associated with all-cause and cause-specific mortality in a community-based cohort of older adults.

METHODS

Fasting blood was obtained from 5,070 ARIC participants (median age: 75 years) in 2011-2013. Anemia was defined by hemoglobin concentrations <12 g/dL in women and <13 g/dL in men. We classified 4,020 non-anemic participants by quartiles of plasma ferritin, measured by the SomaScan proteomics platform. Cox proportional hazards regression was used. Mortality was ascertained via phone calls with proxies as part of twice-yearly cohort follow-up, surveillance of local hospital discharge indexes, state death records, and linkage to the National Death Index.

RESULTS

Of the total participants, 21% had anemia at baseline. Over a median of 7.5 years, there were 1,147 deaths, including 357 due to cardiovascular disease (CVD), 302 to cancer, and 132 to respiratory disease. Compared to those with normal hemoglobin, participants with anemia had a higher risk of all-cause mortality (hazard ratio 1.81 [95% CI: 1.60-2.06]), and mortality due to CVD (1.77 [1.41-2.22]), cancer (1.81 [1.41-2.33]), and respiratory disease (1.72 [1.18-2.52]) in demographics-adjusted models. In fully adjusted models, associations with all-cause mortality (1.37 [1.19-1.58]) and cause-specific mortality were attenuated. In non-anemic participants, lower ferritin levels were not associated with all-cause or cause-specific mortality, though associations were observed among participants with lesser evidence of inflammation (CRP below the median level of 1.9 mg/L) and for cancer mortality in men only.

CONCLUSION

Anemia is common among older adults and is associated with all-cause mortality, as well as mortality due to CVD, cancer, and respiratory disease. Our results do not provide evidence that iron deficiency, independent of anemia, is associated with mortality in this population.

Identifying plasma proteomic signatures from health to heart failure, across the ejection fraction spectrum

Circulating proteins may provide insights into the varying biological mechanisms involved in heart failure (HF) with preserved ejection fraction (HFpEF) and reduced ejection fraction (HFrEF). We aimed to identify specific proteomic patterns for HF, by comparing proteomic profiles across the ejection fraction spectrum. We investigated 4210 circulating proteins in 739 patients with normal (Stage A/Healthy) or elevated (Stage B) filling pressures, HFpEF, or ischemic HFrEF (iHFrEF). We found 2122 differentially expressed proteins between iHFrEF-Stage A/Healthy, 1462 between iHFrEF-HFpEF and 52 between HFpEF-Stage A/Healthy. Of these 52 proteins, 50 were also found in iHFrEF vs. Stage A/Healthy, leaving SLITRK6 and NELL2 expressed in lower levels only in HFpEF. Moreover, 108 proteins, linked to regulation of cell fate commitment, differed only between iHFrEF-HFpEF. Proteomics across the HF spectrum reveals overlap in differentially expressed proteins compared to stage A/Healthy. Multiple proteins are unique for distinguishing iHFrEF from HFpEF, supporting the capacity of proteomics to discern between these conditions.

A Cross-Sectional Exploratory Study of Cardiovascular Risk Biomarkers in Non-Obese Women with and without Polycystic Ovary Syndrome: Association with Vitamin D

Vitamin D is proposed to have a protective effect against cardiovascular disease, though the mechanism is unclear. Vitamin D deficiency is common in polycystic ovary syndrome (PCOS), where it is strongly related to obesity, insulin resistance (IR) and risk of cardiovascular disease. To determine if the inherent pathophysiology of PCOS or vitamin D levels are linked to dysregulation of cardiovascular risk proteins (CVRPs), a study in non-obese women with PCOS and without IR was undertaken. Our hypothesis was that the levels of vitamin D3 and its active metabolite would be associated with CVRPs comparably in women with and without PCOS. In women with PCOS (n = 29) and controls (n = 29), 54 CVRPs were determined by Slow Off-rate Modified Aptamer (SOMA)-scan plasma protein measurement and correlated to 25-hydroxyvitamin D3 (25(OH)D3) and the active 1,25-dihydroxyvitamin D3 (1,25(OH)2D3) measured by gold standard isotope-dilution liquid chromatography tandem mass spectrometry. Women with PCOS had comparable IR and systemic inflammation (normal C-reactive protein) to control women, though had higher free androgen index and anti-Mullerian hormone levels. 25(OH)D3 and 1,25(OH)2D3 levels did not differ between groups. Nine CVRPs were higher in PCOS (p < 0.05) (Galectin-9, Brother of CDO, C-motif chemokine 3, Interleukin-18 receptor-1, Thrombopoietin, Interleukin-1 receptor antagonist protein, Programmed cell death 1 ligand-2, Low-affinity immunoglobulin gamma Fc-region receptor II-b and human growth hormone), whilst 45 CVRPs did not differ. 25(OH)D3 correlated with five CVRPs in PCOS and one in controls (p < 0.05). Despite the women with PCOS not exhibiting overt systemic inflammation, 9 of 54 CVRPs were elevated, all relating to inflammation, and 5 of these correlated with 25(OH)D3, suggesting an ongoing underlying inflammatory process in PCOS even in the absence of obesity/IR.

Prediction of cardiac death in patients with hypertrophic cardiomyopathy using plasma adipokine levels

BACKGROUNDS AND AIMS

Hypertrophic cardiomyopathy (HCM) causes cardiac death through both sudden cardiac death (SCD) and death due to heart failure (HF). Although adipokines lead to adverse cardiac remodeling in HCM, the prognostic value of plasma adipokines in HCM remains unknown. We aimed to predict cardiac death in patients with HCM using plasma adipokines.

METHODS AND RESULTS

We performed a multicenter prospective cohort study of patients with HCM. The outcome was cardiac death including heart transplant, death due to HF, and SCD. With data from 1 institution (training set), a prediction model was developed using random forest classification algorithm based on 10 plasma adipokines. The performance of the prediction model adjusted for 8 clinical parameters was examined in samples from another institution (test set). Time-to-event analysis was performed in the test set to compare the rate of outcome events between the low-risk and high-risk groups determined by the prediction model. In total, 389 (267 in the training set; 122 in the test set) patients with HCM were included. During the median follow-up of 2.7 years, 21 patients experienced the outcome event. The area under the covariates-adjusted receiver-operating characteristics curve was 0.89 (95 % confidence interval [CI] 0.71-0.99) in the test set. revealed the high-risk group had a significantly higher risk of cardiac death (hazard ratio 17.8, 95 % CI 2.1-148.3, P = 0.008).

CONCLUSION

The present multicenter prospective study demonstrated that a panel of plasma adipokines predicts cardiac death in patients with HCM.

Effect of Hypoglycemia and Rebound Hyperglycemia on Proteomic Cardiovascular Risk Biomarkers

Introduction: Hypoglycemia has been associated with cardiovascular events, and glucose variability has been suggested to be associated with increased cardiovascular risk. Therefore, in this study, we examined the effect on proteomic cardiovascular risk protein markers of (i) mild iatrogenic hypoglycemia and (ii) severe iatrogenic hypoglycemia followed by rebound hyperglycemia. Methods: Two iatrogenic hypoglycemia studies were compared; firstly, mild hypoglycemia in 18 subjects (10 type 2 diabetes (T2D), 8 controls; blood glucose to 2.8 mmoL/L (50 mg/dL) for 1 h), and secondly, severe hypoglycemia in 46 subjects (23 T2D, 23 controls; blood glucose to <2.2 mmoL/L (<40 mg/dL) transiently followed by intravenous glucose reversal giving rebound hyperglycemia). A SOMAscan assay was used to measure 54 of the 92 cardiovascular protein biomarkers that reflect biomarkers involved in inflammation, cellular metabolic processes, cell adhesion, and immune response and complement activation. Results: Baseline to euglycemia showed no change in any of the proteins measured in the T2D cohort. With severe hypoglycemia, the study controls showed an increase in Angiopoietin 1 (ANGPT1) (p < 0.01) and Dickkopf-1 (DKK1) (p < 0.01), but no changes were seen with mild hypoglycemia. In both the mild and severe hypoglycemia studies, at the point of hypoglycemia, T2D subjects showed suppression of Brother of CDO (BOC) (p < 0.01). At 1 h post-hypoglycemia, the changes in ANGPT1, DKK1, and BOC had resolved, with no additional protein biomarker changes despite rebound hyperglycemia from 1.8 ± 0.1 to 12.2 ± 2.0 mmol/L. Conclusions: Proteomic biomarkers of cardiovascular disease showed changes at hypoglycemia that resolved within 1 h following the hypoglycemic event and with no changes following hyperglycemia rebound, suggesting that any cardiovascular risk increase is due to the hypoglycemia and not due to glucose fluctuation per se.

Proteomic alterations in patients with atopic dermatitis

INTRODUCTION

Atopic Dermatitis (AD) is the most common inflammatory skin disease with a complex and multifactorial pathogenesis. The use of proteomics in understanding AD has yielded the discovery of novel biomarkers and may further expand therapeutic options.

AREAS COVERED

This review summarizes the most recent proteomic studies and the methodologies used in AD. It describes novel biomarkers that may monitor disease course and therapeutic response. The review also highlights skin and blood biomarkers characterizing different AD phenotypes and differentiates AD from other inflammatory skin disorders. A literature search was conducted by querying Scopus, Google Scholar, Pubmed/Medline, and Clinicaltrials.gov up to June 2023.

EXPERT OPINION

The integration of proteomics into research efforts in atopic dermatitis has broadened our understanding of the molecular profile of AD through the discovery of new biomarkers. In addition, proteomics may contribute to the development of targeted treatments ultimately improving personalized medicine. An increasing number of studies are utilizing proteomics to explore this heterogeneous disease.

A Cross-Sectional Study of Glomerular Hyperfiltration in Polycystic Ovary Syndrome

Glomerular hyperfiltration (GH) has been reported to be higher in women with polycystic ovary syndrome (PCOS) and is an independent risk factor for renal function deterioration, metabolic, and cardiovascular disease. The aim of this study was to determine GH in type A PCOS subjects and to identify whether inflammatory markers, markers of CKD, renal tubule injury markers, and complement system proteins were associated. In addition, a secondary cohort study was performed to determine if the eGFR had altered over time. In this comparative cross-sectional analysis, demographic, metabolic, and proteomic data from Caucasian women aged 18-40 years from a PCOS Biobank (137 with PCOS, 97 controls) was analyzed. Slow Off-rate Modified Aptamer (SOMA)-scan plasma protein measurement was undertaken for inflammatory proteins, serum markers of chronic kidney disease (CKD), tubular renal injury markers, and complement system proteins. A total of 44.5% of the PCOS cohort had GH (eGFR ≥ 126 mL/min/1.73 m2 (n = 55)), and 12% (n = 17) eGFR ≥ 142 mL/min/1.73 m2 (super-GH(SGH)). PCOS-GH women were younger and had lower creatinine and urea versus PCOS-nonGH. C-reactive protein (CRP), white cell count (WCC), and systolic blood pressure (SBP) were higher in PCOS versus controls, but CRP correlated only with PCOS-SGH alone. Complement protein changes were seen between controls and PCOS-nonGH, and decay-accelerator factor (DAF) was decreased between PCOS-nonGH and PCOS-GSGH (p < 0.05). CRP correlated with eGFR in the PCOS-SGH group, but not with other inflammatory or complement parameters. Cystatin-c (a marker of CKD) was reduced between PCOS-nonGH and PCOS-GSGH (p < 0.05). No differences in tubular renal injury markers were found. A secondary cohort notes review of the biobank subjects 8.2-9.6 years later showed a reduction in eGFR: controls -6.4 ± 12.6 mL/min/1.73 m2 (-5.3 ± 11.5%; decrease 0.65%/year); PCOS-nonGH -11.3 ± 13.7 mL/min/1.73 m2 (-9.7 ± 12.2%; p < 0.05, decrease 1%/year); PCOS-GH (eGFR 126-140 mL/min/17.3 m2) -27.1 ± 12.8 mL/min/1.73 m2 (-19.1 ± 8.7%; p < 0.0001, decrease 2%/year); PCOS-SGH (eGFR ≥ 142 mL/min/17.3 m2) -33.7 ± 8.9 mL/min/17.3 m2 (-22.8 ± 6.0%; p < 0.0001, decrease 3.5%/year); PCOS-nonGH eGFR versus PCOS-GH and PCOS-SGH, p < 0.001; no difference PCOS-GH versus PCOS-SGH. GH was associated with PCOS and did not appear mediated through tubular renal injury; however, cystatin-c and DAF were decreased, and CRP correlated positively with PCOS-SGH, suggesting inflammation may be involved at higher GH. There were progressive eGFR decrements for PCOS-nonGH, PCOS-GH, and PCOS-SGH in the follow-up period which, in the presence of additional factors affecting renal function, may be clinically important in the development of CKD in PCOS.

Development of Better Aptamers: Structured Library Approaches, Selection Methods, and Chemical Modifications

Systematic evolution of ligands by exponential enrichment (SELEX) has been used to discover thousands of aptamers since its development in 1990. Aptamers are short single-stranded oligonucleotides capable of binding to targets with high specificity and selectivity through structural recognition. While aptamers offer advantages over other molecular recognition elements such as their ease of production, smaller size, extended shelf-life, and lower immunogenicity, they have yet to show significant success in real-world applications. By analyzing the importance of structured library designs, reviewing different SELEX methodologies, and the effects of chemical modifications, we provide a comprehensive overview on the production of aptamers for applications in drug delivery systems, therapeutics, diagnostics, and molecular imaging.

MoS2-Based Sensor Array for Accurate Identification of Cancer Cells with Ensemble-Modified Aptamers

In this work, we present an array-based chemical nose sensor that utilizes a set of ensemble-modified aptamer (EMAmer) probes to sense subtle physicochemical changes on the cell surface for cancer cell identification. The EMAmer probes are engineered by domain-selective incorporation of different types and/or copies of positively charged functional groups into DNA scaffolds, and their differential interactions with cancer cells can be transduced through competitive adsorption of fluorophore-labeled EMAmer probes loaded on MoS2 nanosheets. We demonstrate that this MoS2-EMAmer-based sensor array enables rapid and effective discrimination among six types of cancer cells and their mixtures with a concentration of 104 cells within 60 min, achieving a 94.4% accuracy in identifying blinded unknown cell samples. The established MoS2-EMAmer sensing platform is anticipated to show significant promise in the advancement of cancer diagnostics.

Shaping the future of oral cancer diagnosis: advances in salivary proteomics

INTRODUCTION

Saliva has gained increasing attention in the quest for disease biomarkers. Because it is a biological fluid that can be collected is an easy, painless, and safe way, it has been increasingly studied for the identification of oral cancer biomarkers. This is particularly important because oral cancer is often diagnosed at late stages with a poor prognosis.

AREAS COVERED

The review addresses the evolution of the experimental approaches used in salivary proteomics studies of oral cancer over the years and outlines advantages and pitfalls related to each one. In addition, examines the current landscape of oral cancer biomarker discovery and translation focusing on salivary proteomic studies. This discussion is based on an extensive literature search (PubMed, Scopus and Google Scholar).

EXPERT OPINION

The introduction of mass spectrometry has revolutionized the study of salivary proteomics. In the future, the focus will be on refining existing methods and introducing powerful experimental techniques such as mass spectrometry with selected reaction monitoring, which, despite their effectiveness, are still underutilized due to their high cost. In addition, conducting studies with larger cohorts and establishing standardized protocols for salivary proteomics are key challenges that need to be addressed in the coming years.

Nucleic Acid Therapeutics: Successes, Milestones, and Upcoming Innovation

Nucleic acid-based therapies have become the third major drug class after small molecules and antibodies. The role of nucleic acid-based therapies has been strengthened by recent regulatory approvals and tremendous clinical success. In this review, we look at the major obstacles that have hindered the field, the historical milestones that have been achieved, and what is yet to be resolved and anticipated soon. This review provides a view of the key innovations that are expanding nucleic acid capabilities, setting the stage for the future of nucleic acid therapeutics.

Plasma Proteome-Based Test for First-Line Treatment Selection in Metastatic Non-Small Cell Lung Cancer

PURPOSE

Current guidelines for the management of metastatic non-small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions.

PATIENTS AND METHODS

We conducted a multicenter observational trial (ClinicalTrials.gov identifier: NCT04056247) of patients undergoing PD-1/PD-L1 inhibitor-based therapy (n = 540) and an additional patient cohort receiving chemotherapy (n = 85) who consented to pretreatment plasma and clinical data collection. Plasma proteome profiling was performed using SomaScan Assay v4.1.

RESULTS

Our test demonstrates a strong association between model output and clinical benefit (CB) from PD-1/PD-L1 inhibitor-based treatments, evidenced by high concordance between predicted and observed CB (R2 = 0.98, P < .001). The test categorizes patients as either PROphet-positive or PROphet-negative and further stratifies patient outcomes beyond PD-L1 expression levels. The test successfully differentiates between PROphet-negative patients exhibiting high tumor PD-L1 levels (≥50%) who have enhanced overall survival when treated with a combination of immunotherapy and chemotherapy compared with immunotherapy alone (hazard ratio [HR], 0.23 [95% CI, 0.1 to 0.51], P = .0003). By contrast, PROphet-positive patients show comparable outcomes when treated with immunotherapy alone or in combination with chemotherapy (HR, 0.78 [95% CI, 0.42 to 1.44], P = .424).

CONCLUSION

Plasma proteome-based testing of individual patients, in combination with standard PD-L1 testing, distinguishes patient subsets with distinct differences in outcomes from PD-1/PD-L1 inhibitor-based therapies. These data suggest that this approach can improve the precision of first-line treatment for metastatic NSCLC.

A Cross-Sectional Study of Protein Changes Associated with Dementia in Non-Obese Weight Matched Women with and without Polycystic Ovary Syndrome

Dysregulated Alzheimer's disease (AD)-associated protein expression is reported in polycystic ovary syndrome (PCOS), paralleling the expression reported in type 2 diabetes (T2D). We hypothesized, however, that these proteins would not differ between women with non-obese and non-insulin resistant PCOS compared to matched control subjects. We measured plasma amyloid-related proteins levels (Amyloid-precursor protein (APP), alpha-synuclein (SNCA), amyloid P-component (APCS), Pappalysin (PAPPA), Microtubule-associated protein tau (MAPT), apolipoprotein E (apoE), apoE2, apoE3, apoE4, Serum amyloid A (SAA), Noggin (NOG) and apoA1) in weight and aged-matched non-obese PCOS (n = 24) and control (n = 24) women. Dementia-related proteins fibronectin (FN), FN1.3, FN1.4, Von Willebrand factor (VWF) and extracellular matrix protein 1 (ECM1) were also measured. Protein levels were determined by Slow Off-rate Modified Aptamer (SOMA)-scan plasma protein measurement. Only APCS differed between groups, being elevated in non-obese PCOS women (p = 0.03) relative to the non-obese control women. This differed markedly from the elevated APP, APCS, ApoE, FN, FN1.3, FN1.4 and VWF reported in obese women with PCOS. Non-obese, non-insulin resistant PCOS subjects have a lower AD-associated protein pattern risk profile versus obese insulin resistant PCOS women, and are not dissimilar to non-obese controls, indicating that lifestyle management to maintain optimal body weight could be beneficial to reduce the long-term AD-risk in women with PCOS.

Mechanistically based blood proteomic markers in the TGF-β pathway stratify risk of hepatocellular cancer in patients with cirrhosis

Hepatocellular carcinoma (HCC) is the third leading cause of death from cancer worldwide but is often diagnosed at an advanced incurable stage. Yet, despite the urgent need for blood-based biomarkers for early detection, few studies capture ongoing biology to identify risk-stratifying biomarkers. We address this gap using the TGF-β pathway because of its biological role in liver disease and cancer, established through rigorous animal models and human studies. Using machine learning methods with blood levels of 108 proteomic markers in the TGF-β family, we found a pattern that differentiates HCC from non-HCC in a cohort of 216 patients with cirrhosis, which we refer to as TGF-β based Protein Markers for Early Detection of HCC (TPEARLE) comprising 31 markers. Notably, 20 of the patients with cirrhosis alone presented an HCC-like pattern, suggesting that they may be a group with as yet undetected HCC or at high risk for developing HCC. In addition, we found two other biologically relevant markers, Myostatin and Pyruvate Kinase M2 (PKM2), which were significantly associated with HCC. We tested these for risk stratification of HCC in multivariable models adjusted for demographic and clinical variables, as well as batch and site. These markers reflect ongoing biology in the liver. They potentially indicate the presence of HCC early in its evolution and before it is manifest as a detectable lesion, thereby providing a set of markers that may be able to stratify risk for HCC.

Proteomic insights into the pathophysiology of periodic limb movements and restless legs syndrome

OBJECTIVES

We used a high-throughput assay of 5000 plasma proteins to identify biomarkers associated with periodic limb movements (PLM) and restless legs syndrome (RLS) in adults.

METHODS

Participants (n = 1410) of the Stanford Technology Analytics and Genomics in Sleep (STAGES) study had blood collected, completed a sleep questionnaire, and underwent overnight polysomnography with the scoring of PLMs. An aptamer-based array (SomaScan) was used to quantify 5000 proteins in plasma. A second cohort (n = 697) that had serum assayed using a previous iteration of SomaScan (1300 proteins) was used for replication and in a combined analysis (n = 2107). A 5% false discovery rate was used to assess significance.

RESULTS

Multivariate analyses in STAGES identified 68 proteins associated with the PLM index after correction for multiple testing (ie, base model). Most significantly decreased proteins were iron-related and included Hepcidin (LEAP-1), Ferritin, and Ferritin light chain. Most significantly increased proteins included RANTES, Cathepsin A, and SULT 1A3. Of 68 proteins significant in the base model, 17 were present in the 1300 panel, and 15 of 17 were replicated. The most significant proteins in the combined model were Hepcidin (LEAP-1), Cathepsin A, Ferritin, and RANTES. Exploration of proteins in RLS versus non-RLS identified Cathepsin Z, Heme oxygenase 2 (HO-2), Interleukin-17A (upregulated in the combined cohort), and Megalin (upregulated in STAGES only) although results were less significant than for proteins associated with PLM index.

CONCLUSIONS

These results confirm the association of PLM with low iron status and suggest the involvement of catabolic enzymes in PLM/RLS.

Plasma SOMAmer proteomics of postoperative delirium

BACKGROUND

Postoperative delirium is prevalent in older adults and has been shown to increase the risk of long-term cognitive decline. Plasma biomarkers to identify the risk for postoperative delirium and the risk of Alzheimer's disease and related dementias are needed.

METHODS

This biomarker discovery case-control study aimed to identify plasma biomarkers associated with postoperative delirium. Patients aged ≥65 years undergoing major elective noncardiac surgery were recruited. The preoperative plasma proteome was interrogated with SOMAmer-based technology targeting 1433 biomarkers.

RESULTS

In 40 patients (20 with vs. 20 without postoperative delirium), a preoperative panel of 12 biomarkers discriminated patients with postoperative delirium with an accuracy of 97.5%. The final model of five biomarkers delivered a leave-one-out cross-validation accuracy of 80%. Represented biological pathways included lysosomal and immune response functions.

CONCLUSION

In older patients who have undergone major surgery, plasma SOMAmer proteomics may provide a relatively non-invasive benchmark to identify biomarkers associated with postoperative delirium.

Proteomics for heart failure risk stratification: a systematic review

BACKGROUND

Heart failure (HF) is a complex clinical syndrome with persistently high mortality. High-throughput proteomic technologies offer new opportunities to improve HF risk stratification, but their contribution remains to be clearly defined. We aimed to systematically review prognostic studies using high-throughput proteomics to identify protein signatures associated with HF mortality.

METHODS

We searched four databases and two clinical trial registries for articles published from 2012 to 2023. HF proteomics studies measuring high numbers of proteins using aptamer or antibody-based affinity platforms on human plasma or serum with outcomes of all-cause or cardiovascular death were included. Two reviewers independently screened articles, extracted data, and assessed the risk of bias. A third reviewer resolved conflicts. We assessed the risk of bias using the Risk Of Bias In Non-randomized Studies-of Exposure tool.

RESULTS

Out of 5131 unique articles identified, nine articles were included in the review. The nine studies were observational; three used the aptamer platform, and six used the antibody platform. We found considerable heterogeneity across studies in measurement panels, HF definitions, ejection fraction categorization, follow-up duration, and outcome definitions, and a lack of risk estimates for most protein associations. Hence, we proceeded with a systematic review rather than a meta-analysis. In two comparable aptamer studies in patients with HF with reduced ejection fraction, 21 proteins were identified in common for the association with all-cause death. Among these, one protein, WAP four-disulfide core domain protein 2 was also reported in an antibody study on HFrEF and for the association with CV death. We proposed standardized reporting criteria to facilitate the interpretation of future studies.

CONCLUSIONS

In this systematic review of nine studies evaluating the association of proteomics with mortality in HF, we identified a limited number of proteins common across several studies. Heterogeneity across studies compromised drawing broad inferences, underscoring the importance of standardized approaches to reporting.

Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases

Spatial multi-omic studies have emerged as a promising approach to comprehensively analyze cells in tissues, enabling the joint analysis of multiple data modalities like transcriptome, epigenome, proteome, and metabolome in parallel or even the same tissue section. This review focuses on the recent advancements in spatial multi-omics technologies, including novel data modalities and computational approaches. We discuss the advancements in low-resolution and high-resolution spatial multi-omics methods which can resolve up to 10,000 of individual molecules at subcellular level. By applying and integrating these techniques, researchers have recently gained valuable insights into the molecular circuits and mechanisms which govern cell biology along the cardiovascular disease spectrum. We provide an overview of current data analysis approaches, with a focus on data integration of multi-omic datasets, highlighting strengths and weaknesses of various computational pipelines. These tools play a crucial role in analyzing and interpreting spatial multi-omics datasets, facilitating the discovery of new findings, and enhancing translational cardiovascular research. Despite nontrivial challenges, such as the need for standardization of experimental setups, data analysis, and improved computational tools, the application of spatial multi-omics holds tremendous potential in revolutionizing our understanding of human disease processes and the identification of novel biomarkers and therapeutic targets. Exciting opportunities lie ahead for the spatial multi-omics field and will likely contribute to the advancement of personalized medicine for cardiovascular diseases.

A Cross-Sectional Study of Alzheimer-Related Proteins in Women with Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is the most common endocrine condition in women of reproductive age, and several risk factors found in PCOS are associated with an increased risk of Alzheimer's disease (AD). Proteins increased in AD have been reported to include fibronectin (FN) fragments 3 and 4 (FN1.3 and FN1.4, respectively) and ApoE. We hypothesized that Alzheimer-related proteins would be dysregulated in PCOS because of associated insulin resistance and obesity. In this comparative cross-sectional analysis, aptamer-based SomaScan proteomic analysis for the detection of plasma Alzheimer-related proteins was undertaken in a PCOS biobank of 143 women with PCOS and 97 control women. Amyloid precursor protein (APP) (p < 0.05) and amyloid P-component (APCS) (p < 0.001) were elevated in PCOS, while alpha-synuclein (SNCA) (p < 0.05) was reduced in PCOS. Associations with protective heat shock proteins (HSPs) showed that SNCA positively correlated with HSP90 (p < 0.0001) and HSP60 (p < 0.0001) in both the PCOS and control women. Correlations with markers of inflammation showed that APCS correlated with interleukin 6 (IL6) (p = 0.04), while Apolipoprotein (Apo) E3 correlated with TNF-alpha (p = 0.02). FN, FN1.3, FN1.4 and ApoE were all elevated significantly (p < 0.05). An AD-associated protein pattern with elevated FN, FN1.3, FN1.4 and ApoE was found in PCOS, in addition to elevated APP and reduced SNCA, which was the same as reported for type 2 diabetes (T2D) with, additionally, an elevation in APCS. With the AD biomarker pattern in PCOS being very similar to that in T2D, where there is an association between AD and T2D, this suggests that larger prospective cohort studies are needed in women with PCOS to determine if there is a causal association with AD.

Development and Validation of a Protein Risk Score for Mortality in Heart Failure : A Community Cohort Study

BACKGROUND

Heart failure (HF) is a complex clinical syndrome with high mortality. Current risk stratification approaches lack precision. High-throughput proteomics could improve risk prediction. Its use in clinical practice to guide the management of patients with HF depends on validation and evidence of clinical benefit.

OBJECTIVE

To develop and validate a protein risk score for mortality in patients with HF.

DESIGN

Community-based cohort.

SETTING

Southeast Minnesota.

PARTICIPANTS

Patients with HF enrolled between 2003 and 2012 and followed through 2021.

MEASUREMENTS

A total of 7289 plasma proteins in 1351 patients with HF were measured using the SomaScan Assay (SomaLogic). A protein risk score was derived using least absolute shrinkage and selection operator regression and temporal validation in patients enrolled between 2003 and 2007 (development cohort) and 2008 and 2012 (validation cohort). Multivariable Cox regression was used to examine the association between the protein risk score and mortality. The performance of the protein risk score to predict 5-year mortality risk was assessed using calibration plots, decision curves, and relative utility analyses and compared with a clinical model, including the Meta-Analysis Global Group in Chronic Heart Failure mortality risk score and N-terminal pro-B-type natriuretic peptide.

RESULTS

The development (n = 855; median age, 78 years; 50% women; 29% with ejection fraction <40%) and validation cohorts (n = 496; median age, 76 years; 45% women; 33% with ejection fraction <40%) were mostly similar. In the development cohort, 38 unique proteins were selected for the protein risk score. Independent of ejection fraction, the protein risk score demonstrated good calibration, reclassified mortality risk particularly at the extremes of the risk distribution, and showed greater clinical utility compared with the clinical model.

LIMITATION

Participants were predominantly of European ancestry, potentially limiting the generalizability of the findings to different patient populations.

CONCLUSION

Validation of the protein risk score demonstrated good calibration and evidence of predicted benefits to stratify the risk for death in HF superior to that of clinical methods. Further studies are needed to prospectively evaluate the score's performance in diverse populations and determine risk thresholds for interventions.

PRIMARY FUNDING SOURCE

Division of Intramural Research at the National Heart, Lung, and Blood Institute of the National Institutes of Health.

Identification and functional analysis of senescent cells in the cardiovascular system using omics approaches

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide, and senescent cells have emerged as key contributors to its pathogenesis. Senescent cells exhibit cell cycle arrest and secrete a range of proinflammatory factors, termed the senescence-associated secretory phenotype (SASP), which promotes tissue dysfunction and exacerbates CVD progression. Omics technologies, specifically transcriptomics and proteomics, offer powerful tools to uncover and define the molecular signatures of senescent cells in cardiovascular tissue. By analyzing the comprehensive molecular profiles of senescent cells, omics approaches can identify specific genetic alterations, gene expression patterns, protein abundances, and metabolite levels associated with senescence in CVD. These omics-based discoveries provide insights into the mechanisms underlying senescence-induced cardiovascular damage, facilitating the development of novel diagnostic biomarkers and therapeutic targets. Furthermore, integration of multiple omics data sets enables a systems-level understanding of senescence in CVD, paving the way for precision medicine approaches to prevent or treat cardiovascular aging and its associated complications.

Alternative splicing in lung influences COVID-19 severity and respiratory diseases

Alternative splicing generates functional diversity in isoforms, impacting immune response to infection. Here, we evaluate the causal role of alternative splicing in COVID-19 severity and susceptibility by applying two-sample Mendelian randomization to cis-splicing quantitative trait loci and the results from COVID-19 Host Genetics Initiative. We identify that alternative splicing in lung, rather than total expression of OAS1, ATP11A, DPP9 and NPNT, is associated with COVID-19 severity. MUC1 and PMF1 splicing is associated with COVID-19 susceptibility. Colocalization analyses support a shared genetic mechanism between COVID-19 severity with idiopathic pulmonary fibrosis at the ATP11A and DPP9 loci, and with chronic obstructive lung diseases at the NPNT locus. Last, we show that ATP11A, DPP9, NPNT, and MUC1 are highly expressed in lung alveolar epithelial cells, both in COVID-19 uninfected and infected samples. These findings clarify the importance of alternative splicing in lung for COVID-19 and respiratory diseases, providing isoform-based targets for drug discovery.

Circulating Proteins and Mortality in CKD: A Proteomics Study of the AASK and ARIC Cohorts

Rationale & Objective

Proteomics could provide pathophysiologic insight into the increased risk of mortality in patients with chronic kidney disease (CKD). This study aimed to investigate associations between the circulating proteome and all-cause mortality among patients with CKD.

Study Design

Observational cohort study.

Setting & Participants

Primary analysis in 703 participants in the African American Study of Kidney Disease and Hypertension (AASK) and validation in 1,628 participants with CKD in the Atherosclerosis Risk in Communities (ARIC) study who attended visit 5.

Exposure

Circulating proteins.

Outcome

All-cause mortality.

Analytical Approach

Among AASK participants, we evaluated the associations of 6,790 circulating proteins with all-cause mortality using multivariable Cox proportional hazards models. Proteins with significant associations were further studied in ARIC Visit 5 participants with CKD.

Results

In the AASK cohort, the mean age was 54.5 years, 271 (38.5%) were women, and the mean measured glomerular filtration rate (GFR) was 46 mL/min/1.73 m2. The median follow-up was 9.6 years, and 7 distinct proteins were associated with all-cause mortality at the Bonferroni-level threshold (P < 0.05 of the 6,790) after adjustment for demographics and clinical factors, including baseline measured estimated GFR and proteinuria. In the ARIC visit 5 cohort, the mean age was 77.2 years, 903 (55.5%) were women, the mean estimated GFR was 54 mL/min/1.73 m2 and median follow-up was 6.9 years. Of the 7 proteins found in AASK, 3 (β2-microglobulin, spondin-1, and N-terminal pro-brain natriuretic peptide) were available in the ARIC data, with all 3 significantly associated with death in ARIC.

Limitations

Possibility of unmeasured confounding. Cause of death was not known.

Conclusions

Using large-scale proteomic analysis, proteins were reproducibly associated with mortality in 2 cohorts of participants with CKD.

Plain-Language Summary

Patients with chronic kidney disease (CKD) have a high risk of premature death, with various pathophysiological processes contributing to this increased risk of mortality. This observational cohort study aimed to investigate the associations between circulating proteins and all-cause mortality in patients with CKD using large-scale proteomic analysis. The study analyzed data from the African American Study of Kidney Disease and Hypertension (AASK) study and validated the findings in the Atherosclerosis Risk in Communities (ARIC) Study. A total of 6,790 circulating proteins were evaluated in AASK, and 7 proteins were significantly associated with all-cause mortality. Three of these proteins (β2-microglobulin, spondin-1, and N-terminal pro-brain natriuretic peptide (BNP)) were also measured in ARIC and were significantly associated with death. Additional studies assessing biomarkers associated with mortality among patients with CKD are needed to evaluate their use in clinical practice.

Proteomics evaluation of five economical commercial abundant protein depletion kits for enrichment of diseases-specific biomarkers from blood serum

Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease-specific biomarkers in human serum using bottom-up proteomics. As expected, the IgG removal efficiency among the SAPD kits is highly variable, ranging from 70% to 93%. A pairwise comparison of database search results showed a 10%-19% variation in protein identification among the kits. Immunocapturing-based SAPD kits against IgG and albumin outperformed the others in the removal of these two abundant proteins. Conversely, non-antibody-based methods (i.e., kits using ion exchange resins) and kits leveraging a multi-antibody approach were proven to be less efficient in depleting IgG/albumin from samples but led to the highest number of identified peptides. Notably, our results indicate that different cancer biomarkers could be enriched up to 10% depending on the utilized SAPD kit compared with the undepleted sample. Additionally, functional analysis of the bottom-up proteomic results revealed that different SAPD kits enrich distinct disease- and pathway-specific protein sets. Overall, our study emphasizes that a careful selection of the appropriate commercial SAPD kit is crucial for the analysis of disease biomarkers in serum by shotgun proteomics.

Selection of optimised ligands by fluorescence-activated bead sorting

The chemistry of aptamers is largely limited to natural nucleotides, and although modifications of nucleic acids can enhance target aptamer affinity, there has not yet been a technology for selecting the right modifications in the right locations out of the vast number of possibilities, because enzymatic amplification does not transmit sequence-specific modification information. Here we show the first method for the selection of specific nucleoside modifications that increase aptamer binding efficacy, using the oncoprotein EGFR as a model target. Using fluorescence-activated bead sorting (FABS), we have successfully selected optimized aptamers from a library of >65 000 variations. Hits were identified by tandem mass spectrometry and validated by using an EGFR binding assay and computational docking studies. Our results provide proof of concept for this novel strategy for the selection of chemically optimised aptamers and offer a new method for rapidly synthesising and screening large aptamer libraries to accelerate diagnostic and drug discovery.

Non-invasive candidate protein signature predicts hepatic venous pressure gradient reduction in cirrhotic patients after sustained virologic response

BACKGROUND AND AIMS

A reduction in hepatic venous pressure gradient (HVPG) is the most accurate marker for assessing the severity of portal hypertension and the effectiveness of intervention treatments. This study aimed to evaluate the prognostic potential of blood-based proteomic biomarkers in predicting HVPG response amongst cirrhotic patients with portal hypertension due to Hepatitis C virus (HCV) and had achieved sustained virologic response (SVR).

METHODS

The study comprised 59 patients from two cohorts. Patients underwent paired HVPG (pretreatment and after SVR), liver stiffness (LSM), and enhanced liver fibrosis scores (ELF) measurements, as well as proteomics-based profiling on serum samples using SomaScan® at baseline (BL) and after SVR (EOS). Machine learning with feature selection (Caret, Random Forest and RPART) methods were performed to determine the proteins capable of classifying HVPG responders. Model performance was evaluated using AUROC (pROC R package).

RESULTS

Patients were stratified by a change in HVPG (EOS vs. BL) into responders (greater than 20% decline in HVPG from BL, or <10 mmHg at EOS with >10 mmHg at BL) and non-responders. LSM and ELF decreased markedly after SVR but did not correlate with HVPG response. SomaScan (SomaLogic, Inc., Boulder, CO) analysis revealed a substantial shift in the peripheral proteome composition, reflected by 82 significantly differentially abundant proteins. Twelve proteins accurately distinguished responders from non-responders, with an AUROC of .86, sensitivity of 83%, specificity of 83%, accuracy of 83%, PPV of 83%, and NPV of 83%.

CONCLUSIONS

A combined non-invasive soluble protein signature was identified, capable of accurately predicting HVPG response in HCV liver cirrhosis patients after achieving SVR.

Harnessing Nucleic Acids Nanotechnology for Bone/Cartilage Regeneration

The effective regeneration of weight-bearing bone defects and critical-sized cartilage defects remains a significant clinical challenge. Traditional treatments such as autologous and allograft bone grafting have not been successful in achieving the desired outcomes, necessitating the need for innovative therapeutic approaches. Nucleic acids have attracted significant attention due to their ability to be designed to form discrete structures and programmed to perform specific functions at the nanoscale. The advantages of nucleic acid nanotechnology offer numerous opportunities for in-cell and in vivo applications, and hold great promise for advancing the field of biomaterials. In this review, the current abilities of nucleic acid nanotechnology to be applied in bone and cartilage regeneration are summarized and insights into the challenges and future directions for the development of this technology are provided.

Complement Dysregulation in Obese Versus Nonobese Polycystic Ovary Syndrome Patients

INTRODUCTION

Upregulation of complement system factors are reported to be increased in polycystic ovary syndrome (PCOS) and may be due to obesity and insulin resistance rather than inherently due to PCOS. We directly compared complement factors from an obese, insulin-resistant PCOS population to a nonobese, non-insulin-resistant PCOS population in a proteomic analysis to investigate this.

METHODS

Plasma was collected from 234 women (137 with PCOS and 97 controls) from a biobank cohort and compared to a nonobese, non-insulin-resistant population (24 with PCOS and 24 controls). Slow off-rate modified aptamer (SOMA) scan plasma protein measurement was undertaken for the following complement system proteins: C1q, C1r, C2, C3, C3a, iC3b, C3b, C3d, C3adesArg, C4, C4a, C4b, C5, C5a, C5b-6 complex, C8, properdin, factor B, factor D, factor H, factor I, Mannose-binding protein C (MBL), complement decay-accelerating factor (DAF) and complement factor H-related protein 5 (CFHR5).

RESULTS

The alternative pathway of the complement system was overexpressed in both obese and nonobese PCOS, with increased C3 (p < 0.05) and properdin (p < 0.01); additionally, factor B increased in obese PCOS (p < 0.01). For inhibitors of this pathway, factor I was increased (p < 0.01) in both slim and obese PCOS, with an increase in CFHR5 and factor H in obese PCOS (p < 0.01). Complement factors iC3b, C3d and C5a, associated with an enhanced B cell response and inflammatory cytokine release, were increased in both slim and obese PCOS (p < 0.05). C3a and its product, C3adesArg, were both significantly elevated in nonobese PCOS (<0.01) but not altered in obese PCOS. Hyperandrogenemia correlated positively with properdin and iC3b in obese PCOS (p < 0.05) but not in nonobese PCOS. There was no association with insulin resistance. BMI correlated positively in both groups with factor B, factor H and C5a. Additionally, in obese PCOS, BMI correlated with C3d, factor D, factor I, CFHR5 and C5a (p < 0.05), and in nonobese PCOS, BMI correlated with properdin, iC3b, C3, C3adesArg, C3a, C4, C5, C5a and C1q. In obese controls, BMI correlated with C3, C3desArg, C3a, C3d, C4, factor I, factor B, C5a and C5, whilst in nonobese controls, BMI only correlated negatively with C1q. Comparison of nonobese and obese PCOS showed that properdin, C3b, iC3b, C4A, factor D, factor H and MBL differed.

CONCLUSION

The upregulation of the alternative complement pathway was seen in nonobese PCOS and was further exacerbated in obese PCOS, indicating that this is an inherent feature of the pathophysiology of PCOS that is worsened by obesity and is reflected in the differences between the nonobese and obese PCOS phenotypes. However, the increase in the complement proteins associated with activation was counterbalanced by upregulation of complement inhibitors; this was evident in both PCOS groups, suggesting that insults, such as a cardiovascular event or infection, that cause activation of complement pathways may be amplified in PCOS.

Oxidative Stress Markers and Heat Shock Proteins in Non-Obese Women with Polycystic Ovary Syndrome Are Not Elevated and Show No Correlation with Vitamin D

INTRODUCTION

Oxidative stress (OS) is recognized in the pathophysiology of polycystic ovary syndrome (PCOS). OS results in intracellular reactive oxygen species generation, causing oxidative protein damage that is protected by heat shock proteins (HSPs). Vitamin D is thought to reduce and protect against OS; therefore, OS, HSP, and vitamin D levels may be associated with PCOS. However, their expression in PCOS without underlying inflammation is unknown.

METHODS

In this exploratory study, the plasma levels of 7 OS proteins and 10 HSPs that are affected by the OS process were measured using Slow Off-rate Modified Aptamer (SOMA)-scan plasma protein measurements in non-obese, non-insulin resistant women with PCOS (n = 24) without systemic inflammation and control (n = 24) women; the cohorts were matched for weight and age. The OS proteins and HSPs were correlated with 25-hydroxy vitamin D₃ (25(OH)D₃) and the active form, 1,25-dihydroxyvitamin D₃ (1,25(OH)₂D₃), as measured by isotope-dilution liquid chromatography tandem mass spectrometry.

RESULTS

The PCOS women versus the controls had comparable insulin resistance and systemic inflammation (C-reactive protein 2.0 mg/L vs. 2.3 mg/L, p > 0.05), but higher free androgen index and anti-mullerian hormone levels. Among the OS proteins, only esterase D (ESD; p < 0.01) was elevated in PCOS and the HSPs did not differ between the PCOS and control women. There was no correlation of 25(OH)D₃ or 1,25(OH)₂D₃ with any of the proteins.

CONCLUSIONS

In a PCOS population that was non-obese and without insulin resistance and systemic inflammation, only ESD was elevated in PCOS, whilst the other OS proteins and HSPs were not elevated. Further, none of the OS proteins or HSPs were correlated with either 25(OH)D₃ or 1,25(OH)₂D₃ in either cohort of women or when both cohorts were combined, indicating that the OS and HSP responses were largely absent and not affected by vitamin D in a non-obese PCOS population.

Magnetically Detected Protein Binding Using Spin-Labeled Slow Off-Rate Modified Aptamers

Recent developments in aptamer chemistry open up opportunities for new tools for protein biosensing. In this work, we present an approach to use immobilized slow off-rate modified aptamers (SOMAmers) site-specifically labeled with a nitroxide radical via azide-alkyne click chemistry as a means for detecting protein binding. Protein binding induces a change in rotational mobility of the spin label, which is detected via solution-state electron paramagnetic resonance (EPR) spectroscopy. We demonstrate the workflow and test the protocol using the SOMAmer SL5 and its protein target, platelet-derived growth factor B (PDGF-BB). In a complete site scan of the nitroxide over the SOMAmer, we determine the rotational mobility of the spin label in the absence and presence of target protein. Several sites with sufficiently tight affinity and large rotational mobility change upon protein binding are identified. We then model a system where the spin-labeled SOMAmer assay is combined with fluorescence detection via diamond nitrogen-vacancy (NV) center relaxometry. The NV center spin-lattice relaxation time is modulated by the rotational mobility of a proximal spin label and thus responsive to SOMAmer-protein binding. The spin label-mediated assay provides a general approach for transducing protein binding events into magnetically detectable signals.

Labeling approaches for DNA-PAINT super-resolution imaging

Super-resolution imaging is becoming a commonly employed tool to visualize biological targets in unprecedented detail. DNA-PAINT is one of the single-molecule localization microscopy-based super-resolution imaging modalities allowing the ultra-high-resolution imaging with superior multiplexing capabilities. We discuss the importance of patterned DNA nanostructures in demonstrating the capabilities of DNA-PAINT and the design of various combinations of imager-docking strand pairs for imaging. Central to the implementation of DNA-PAINT imaging in a biological context is the generation of docking strand-conjugated binders against the target molecules. Several researchers have developed a variety of labelling probes for improving resolution while also providing multiplexing capabilities for the broader application of DNA-PAINT. This review provides a comprehensive summary of the repertoire of labelling probes used for DNA-PAINT in cells and the strategies implemented to chemically modify them with a docking strand.

HDL-Associated Proteins in Subjects with Polycystic Ovary Syndrome: A Proteomic Study

Introduction. Serum lipoproteins, with the exception of high-density lipoprotein cholesterol (HDL-C), are increased in polycystic ovary syndrome (PCOS) and their levels may reflect the associated obesity and insulin resistance, but the nature of this association is not fully explained. Therefore, proteomic analysis of key proteins in lipoprotein metabolism was performed. Methods. In this cohort study, plasma was collected from 234 women (137 with PCOS and 97 controls without PCOS). Somalogic proteomic analysis was undertaken for the following 19 proteins involved in lipoprotein, and particularly HDL, metabolism: alpha-1-antichymotrypsin; alpha-1-antitrypsin; apolipoproteins A-1, B, D, E, E2, E3, E4, L1, and M; clusterin; complement C3; hemopexin; heparin cofactor II; kininogen-1; serum amyloid A-1; amyloid beta A-4; and paraoxonase-1. Results. The levels of apolipoprotein E were higher in PCOS (p = 0.012). However, the other isoforms of ApoE, ApoE2, E3, and E4, did not differ when compared with controls. ApoM was lower in PCOS (p = 0.000002). Complement C3 was higher in PCOS (p = 0.037), as was heparin cofactor II (HCFII) (p = 0.0004). The levels of the other proteins associated with lipoprotein metabolism did not differ between PCOS and controls. Conclusions. These data contribute to the concern of the deleterious dyslipidemia found in PCOS, with the novel combination reported here of higher levels of ApoE, C3 and HCFII together with lower ApoM. The dysregulation of these proteins could circumvent the protective effect of HDL-C and contribute to a more atherogenic profile that may increase cardiovascular risk.

Coagulation factor dysregulation in polycystic ovary syndrome is an epiphenomenon of obesity

OBJECTIVE

Obese women with polycystic ovary syndrome (PCOS) exhibit a hypercoagulable state, with the suggestion that this may be obesity-driven rather than an intrinsic facet of PCOS; however, this has not yet been definitively determined since body mass index (BMI) is so highly correlated with PCOS. Therefore, only a study design where obesity, insulin resistance and inflammation are matched can answer this question.

DESIGN

This was a cohort study. Patients Weight and aged-matched nonobese women with PCOS (n = 29) and control women (n = 29) were included. Measurements Plasma coagulation pathway protein levels were measured. Circulating levels of a panel of nine clotting proteins known to differ in obese women with PCOS were determined by Slow Off-rate Modified Aptamer (SOMA)-scan plasma protein measurement.

RESULTS

Women with PCOS showed a higher free androgen index (FAI) and anti-Müllerian hormone, but measures of insulin resistance, and C reactive protein (as a marker of inflammation), did not differ between the nonobese women with PCOS and the control women. Seven pro-coagulation proteins (plasminogen activator inhibitor-1, fibrinogen, fibrinogen gamma chain, fibronectin, d-dimer, P-selectin and plasma kallikrein) and two anticoagulant proteins (vitamin K-dependent protein-S and heparin cofactor-II) known to be elevated in obese women with PCOS did not differ from controls in this cohort.

CONCLUSIONS

This novel data show that clotting system abnormalities do not contribute to the intrinsic mechanisms underlying PCOS in this nonobese noninsulin resistant population of women with PCOS matched for age and BMI, and without evidence of underlying inflammation, but rather the clotting factor changes are an epiphenomenon coincident with obesity; therefore, increased coagulability is unlikely in these nonobese PCOS women.

Cross-sectional proteomic expression in Parkinson's disease-related proteins in drug-naïve patients vs healthy controls with longitudinal clinical follow-up

There is an urgent need to find reliable and accessible blood-based biomarkers for early diagnosis of Parkinson's disease (PD) correlating with clinical symptoms and displaying predictive potential to improve future clinical trials. This led us to a conduct large-scale proteomics approach using an advanced high-throughput proteomics technology to create a proteomic profile for PD. Over 1300 proteins were measured in serum samples from a de novo Parkinson's (DeNoPa) cohort made up of 85 deep clinically phenotyped drug-naïve de novo PD patients and 93 matched healthy controls (HC) with longitudinal clinical follow-up available of up to 8 years. The analysis identified 73 differentially expressed proteins (DEPs) of which 14 proteins were confirmed as stable potential diagnostic markers using machine learning tools. Among the DEPs identified, eight proteins-ALCAM, contactin 1, CD36, DUS3, NEGR1, Notch1, TrkB, and BTK- significantly correlated with longitudinal clinical scores including motor and non-motor symptom scores, cognitive function and depression scales, indicating potential predictive values for progression in PD among various phenotypes. Known functions of these proteins and their possible relation to the pathophysiology or symptomatology of PD were discussed and presented with a particular emphasis on the potential biological mechanisms involved, such as cell adhesion, axonal guidance and neuroinflammation, and T-cell activation. In conclusion, with the use of advance multiplex proteomic technology, a blood-based protein signature profile was identified from serum samples of a well-characterized PD cohort capable of potentially differentiating PD from HC and predicting clinical disease progression of related motor and non-motor PD symptoms. We thereby highlight the need to validate and further investigate these markers in future prospective cohorts and assess their possible PD-related mechanisms.

Aptamer-coated track-etched membranes with a nanostructured silver layer for single virus detection in biological fluids

Aptasensors based on surface-enhanced Raman spectroscopy (SERS) are of high interest due to the superior specificity and low limit of detection. It is possible to produce stable and cheap SERS-active substrates and portable equipment meeting the requirements of point-of-care devices. Here we combine the membrane filtration and SERS-active substrate in the one pot. This approach allows efficient adsorption of the viruses from the solution onto aptamer-covered silver nanoparticles. Specific determination of the viruses was provided by the aptamer to influenza A virus labeled with the Raman-active label. The SERS-signal from the label was decreased with a descending concentration of the target virus. Even several virus particles in the sample provided an increase in SERS-spectra intensity, requiring only a few minutes for the interaction between the aptamer and the virus. The limit of detection of the aptasensor was as low as 10 viral particles per mL (VP/mL) of influenza A virus or 2 VP/mL per probe. This value overcomes the limit of detection of PCR techniques (∼10³ VP/mL). The proposed biosensor is very convenient for point-of-care applications.

High density lipoprotein-associated proteins in non-obese women with and without polycystic ovary syndrome

Introduction

Dyslipidemia frequently occurs in women with polycystic ovary syndrome (PCOS), but it is unclear whether dyslipidemia is due to obesity and insulin resistance (IR) or is inherent to PCOS. To address this, proteomic analysis of proteins important in lipid metabolism, particularly for high-density lipoprotein cholesterol (HDL-C), was performed in non-obese, non-insulin resistant PCOS women compared to matched controls.

Methods

Weight and aged-matched non-obese subjects with PCOS (n=24) and without IR were compared with control women (n=24). 19 proteins were measured by Somalogic proteomic analysis: alpha-1-antichymotrypsin, alpha-1-antitrypsin, apolipoproteins A-1, B, D, E, E2, E3, E4, L1, M, clusterin, complement C3, hemopexin, heparin cofactor-II (HCFII), kininogen-1, serum amyloid A-1, amyloid beta A-4 and paraoxonase-1.

Results

Women with PCOS had a higher free androgen index (FAI) (p<0.001) and anti-Mullerian hormone (AMH) (p<0.001), but IR and C-reactive protein (CRP), a marker of inflammation, did not differ from controls (p>0.05). The triglyceride:HDL-cholesterol ratio was elevated (p=0.03) in PCOS. Alpha-1-antitrypsin levels were lower (p<0.05) and complement C3 levels were higher (p=0.001) in PCOS. C3 correlated with body mass index (BMI) (r=0.59, p=0.001), IR (r=0.63, p=0.0005) and CRP (r=0.42, p=0.04) in women with PCOS, though no correlations of these parameters with alpha-1-antitrypsin were found. Total cholesterol, triglycerides, HDL-cholesterol, LDL-cholesterol and levels of the other 17 lipoprotein metabolism-associated proteins did not differ between the two groups (p>0.05). However, in PCOS, alpha-1-antichymotrypsin correlated negatively with BMI (r=-0.40, p<0.04) and HOMA-IR (r=-0.42, p<0.03), apoM correlated positively with CRP (r=0.36, p<0.04) and HCFII correlated negatively with BMI (r=-0.34, p<0.04).

Conclusion

In PCOS subjects, when obesity, IR and inflammation confounders were absent, alpha-1-antitrypsin was lower and complement C3 was higher than in non-PCOS women, suggesting increased cardiovascular risk; however, subsequent obesity related IR/inflammation likely stimulates other HDL-associated protein abnormalities, thus increasing cardiovascular risk further.

Ensemble Modified Aptamer Based Pattern Recognition for Adaptive Target Identification

The difficulty of the molecular design and chemical synthesis of artificial sensing receptors restricts their diagnostic and proteomic applications. Herein, we report a concept of "ensemble modified aptamers" (EMAmers) that exploits the collective recognition abilities of a small set of protein-like side-chain-modified nucleic acid ligands for discriminative identification of molecular or cellular targets. Different types and numbers of hydrophobic functional groups were incorporated at designated positions on nucleic acid scaffolds to mimic amino acid side chains. We successfully assayed 18 EMAmer probes with differential binding affinities to seven proteins. We constructed an EMAmer-based chemical nose sensor and demonstrated its application in blinded unknown protein identification, giving a 92.9% accuracy. Additionally, the sensor is generalizable to the detection of blinded unknown bacterial and cellular samples, which enabled identification accuracies of 96.3% and 94.8%, respectively. This sensing platform offers a discriminative means for adaptive target identification and holds great potential for diverse applications.

Aptamer proteomics of serum exosomes from patients with Primary Raynaud's and patients with Raynaud's at risk of evolving into Systemic Sclerosis

BACKGROUND

A major unmet need for Systemic Sclerosis (SSc) clinical management is the lack of biomarkers for the early diagnosis of patients with Raynaud's Phenomenon at high risk of evolving into SSc.

OBJECTIVE

To identify proteins contained within serum exosomes employing an aptamer proteomic analysis that may serve to reveal patients with Raynaud's Phenomenon at risk of developing SSc.

METHODS

Exosomes were isolated from serum samples from patients with Primary Raynaud's Phenomenon and from patients with Raynaud's Phenomenon harbouring serum antinuclear antibodies (ANA) who may be at high risk of evolving into SSc. The expression of 1,305 proteins was quantified using SOMAscan aptamer proteomics, and associations of the differentially elevated or reduced proteins with the clinical subsets of Raynaud's Phenomenon were assessed.

RESULTS

Twenty one differentially elevated and one differentially reduced (absolute fold change >|1.3|) proteins were identified. Principal component analysis using these 22 most differentially expressed proteins resulted in excellent separation of the two Raynaud's Phenomenon clinical subsets. Remarkably, the most differentially elevated proteins are involved in enhanced inflammatory responses, immune cell activation and cell migration, and abnormal vascular functions.

CONCLUSION

Aptamer proteomic analysis of circulating exosomes identified differentially elevated or reduced proteins between Raynaud's Phenomenon at high risk of evolving into SSc and Primary Raynaud's Phenomenon patients. Some of these proteins are involved in relevant biological pathways that may play a role in SSc pathogenesis including enhanced inflammatory responses, immune cell activation, and endothelial cell and vascular abnormalities.

Prediction of Major Adverse Cardiovascular Events in Patients With Hypertrophic Cardiomyopathy Using Proteomics Profiling

BACKGROUND

Hypertrophic cardiomyopathy often causes major adverse cardiovascular events (MACE), for example, arrhythmias, stroke, heart failure, and sudden cardiac death. Currently, there are no models available to predict MACE. Furthermore, it remains unclear which signaling pathways mediate MACE. Therefore, we aimed to prospectively determine protein biomarkers that predict MACE in hypertrophic cardiomyopathy and to identify signaling pathways differentially regulated in patients who subsequently develop MACE.

METHODS

In this multi-centre prospective cohort study of patients with hypertrophic cardiomyopathy, we conducted plasma proteomics profiling of 4979 proteins upon enrollment. We developed a proteomics-based model to predict MACE using data from one institution (training set). We tested the predictive ability in independent samples from the other institution (test set) and performed time-to-event analysis. Additionally, we executed pathway analysis of predictive proteins using a false discovery rate threshold of <0.001.

RESULTS

The study included 245 patients (n=174 in the training set and n=71 in the test set). Using the proteomics-based model to predict MACE derived from the training set, the area under the receiver-operating-characteristic curve was 0.81 (95% CI, 0.68-0.93) in the test set. In the test set, the high-risk group determined by the proteomics-based predictive model had a significantly higher rate of developing MACE (hazard ratio, 13.6 [95% CI, 1.7-107]; P=0.01). The Ras-MAPK (mitogen-activated protein kinase) pathway was upregulated in patients who subsequently developed MACE (false discovery rate<1.0×10-7). Pathways involved in inflammation and fibrosis-for example, the TGF (transforming growth factor)-β pathway-were also upregulated.

CONCLUSIONS

This study serves as the first to demonstrate the ability of proteomics profiling to predict MACE in hypertrophic cardiomyopathy, exhibiting both novel (eg, Ras-MAPK) and known (eg, TGF-β) pathways differentially regulated in patients who subsequently experience MACE.

Perceptions and priorities for the development of multiplex rapid diagnostic tests for acute non-malarial fever in rural South and Southeast Asia: An international modified e-Delphi survey

Background

Fever is a common presenting symptom in low- and middle-income countries (LMICs). It was previously assumed that malaria was the cause in such patients, but its incidence has declined rapidly. The urgent need to develop point-of-care tests for the most important causes of non-malarial acute febrile illness is hampered by the lack of robust epidemiological data. We sought to obtain expert consensus on analytes which should be prioritized for inclusion in fingerprick blood-based multiplex lateral flow rapid diagnostic tests (LF-RDTs) targeted towards four categories of patients with acute non-malarial fever in South and Southeast Asian LMICs, stratified by age (paediatric vs. adult) and care setting (primary vs. secondary care).

Methodology/Principal findings

We conducted a two-round modified e-Delphi survey. A total of 84 panellists were invited, consisting of seven each from 12 countries, divided into three regional panels (Mainland Southeast Asia, Maritime Southeast Asia, and South Asia). Panellists were asked to rank their top seven analytes for inclusion in LF-RDTs to be used in each patient category, justify their choices, and indicate whether such LF-RDTs should be incorporated into algorithm-based clinical decision support tools. Thirty-six panellists (43%) participated in the first round and 44 (52%) in the second. There was consensus that such LF-RDTs should be incorporated into clinical decision support tools. At a minimum, these LF-RDTs should be able to diagnose dengue and enteric fever in all patient categories. There was a clear preference to develop LF-RDTs for pathogens not readily detected by existing technologies, and for direct diagnosis through antigen detection. Pathogen biomarkers were prioritized over host inflammatory biomarkers, with CRP being the only one ranked consistently highly.

Conclusions/Significance

Our results provide guidance on prioritizing analytes for inclusion in context-specific multiplex LF-RDTs and similar platforms for non-malarial acute febrile illness, for which there is an urgent unmet need.

In vitro evolution of ribonucleases from expanded genetic alphabets

The ability of nucleic acids to catalyze reactions (as well as store and transmit information) is important for both basic and applied science, the first in the context of molecular evolution and the origin of life and the second for biomedical applications. However, the catalytic power of standard nucleic acids (NAs) assembled from just four nucleotide building blocks is limited when compared with that of proteins. Here, we assess the evolutionary potential of libraries of nucleic acids with six nucleotide building blocks as reservoirs for catalysis. We compare the outcomes of in vitro selection experiments toward RNA-cleavage activity of two nucleic acid libraries: one built from the standard four independently replicable nucleotides and the other from six, with the two added nucleotides coming from an artificially expanded genetic information system (AEGIS). Results from comparative experiments suggest that DNA libraries with increased chemical diversity, higher information density, and larger searchable sequence spaces are one order of magnitude richer reservoirs of molecules that catalyze the cleavage of a phosphodiester bond in RNA than DNA libraries built from a standard four-nucleotide alphabet. Evolved AEGISzymes with nitro-carrying nucleobase Z appear to exploit a general acid–base catalytic mechanism to cleave that bond, analogous to the mechanism of the ribonuclease A family of protein enzymes and heavily modified DNAzymes. The AEGISzyme described here represents a new type of catalysts evolved from libraries built from expanded genetic alphabets.

Components of the Complement Cascade Differ in Polycystic Ovary Syndrome

Complement pathway proteins are reported to be increased in polycystic ovary syndrome (PCOS) and may be affected by obesity and insulin resistance. To investigate this, a proteomic analysis of the complement system was undertaken, including inhibitory proteins. In this cohort study, plasma was collected from 234 women (137 with PCOS and 97 controls). SOMALogic proteomic analysis was undertaken for the following complement system proteins: C1q, C1r, C2, C3, C3a, iC3b, C3b, C3d, C3adesArg, C4, C4a, C4b, C5, C5a, C5b-6 complex, C8, properdin, factor B, factor D, factor H, factor I, mannose-binding protein C (MBL), complement decay-accelerating factor (DAF) and complement factor H-related protein 5 (CFHR5). The alternative pathway of the complement system was primarily overexpressed in PCOS, with increased C3 (p < 0.05), properdin and factor B (p < 0.01). In addition, inhibition of this pathway was also seen in PCOS, with an increase in CFHR5, factor H and factor I (p < 0.01). Downstream complement factors iC3b and C3d, associated with an enhanced B cell response, and C5a, associated with an inflammatory cytokine release, were increased (p < 0.01). Hyperandrogenemia correlated positively with properdin and iC3b, whilst insulin resistance (HOMA-IR) correlated with iC3b and factor H (p < 0.05) in PCOS. BMI correlated positively with C3d, factor B, factor D, factor I, CFHR5 and C5a (p < 0.05). This comprehensive evaluation of the complement system in PCOS revealed the upregulation of components of the complement system, which appears to be offset by the concurrent upregulation of its inhibitors, with these changes accounted for in part by BMI, hyperandrogenemia and insulin resistance.

The severity and duration of Hypoglycemia affect platelet-derived protein responses in Caucasians

Objective

Severe hypoglycemia is associated with increased cardiovascular death risk, and platelet responses to hypoglycemia (hypo) have been described. However, the impact of deep transient hypo (deep-hypo) versus prolonged milder hypo (mild-hypo) on platelet response is unclear.

Research Design and methods

Two hypo studies were compared; firstly, mild-hypo in 18-subjects (10 type-2-diabetes (T2D), 8 controls), blood glucose to 2.8mmoL/L (50 mg/dL) for 1-hour; secondly deep-hypo in 46-subjects (23 T2D, 23 controls), blood glucose to < 2.2mmoL/L (< 40 mg/dL) transiently. Platelet-related protein (PRP) responses from baseline to after 1-hour of hypo (mild-hypo) or at deep-hypo were compared, and at 24-hours post-hypo. Slow Off-rate Modified Aptamer (SOMA)-scan plasma protein measurement was used to determine PRP changes for 13 PRPs.

Results

In controls, from baseline to hypo, differences were seen for four PRPs, three showing increased %change in deep-hypo (Plasminogen activator inhibitor-1(PAI-1), CD40 ligand (CD40LG) and Protein-S), one showing increased %change in mild-hypo (von Willebrand factor (vWF)); at 24-hours in controls, %change for Protein-S remained increased in deep-hypo, whilst % change for vWF and plasminogen were increased in mild-hypo. In T2D, from baseline to hypo, differences were seen for 4 PRPs, three showing increased %change in deep-hypo (PAI-1, platelet glycoprotein VI and Tissue factor), one showing increased %change in mild-hypo (CD40LG); at 24-hours in T2D, %change for CD40LG remained increased, together with vWF, in deep-hypo.

Conclusion

Both mild-hypo and deep-hypo showed marked PRP changes that continued up to 24-hours, showing that both the severity and duration of hypoglycemia are likely important and that any degree of hypoglycemia may be detrimental for increased cardiovascular risk events through PRP changes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01639-w.

Plasma Growth and Differentiation Factor 15 Predict Longitudinal Changes in Bone Parameters in Women, but Not in Men

Bone fragility can progress with aging, but biomarkers to detect emerging osteopenia have not been fully elucidated. Growth/differentiation factor 15 (GDF-15) has pleiotropic roles in a broad range of age-related conditions, but its association with osteopenia is unknown. We examined the relationship between plasma GDF-15 levels and rate of change in bone parameters over 9 years of follow-up in 596 adults in the InCHIANTI study (baseline age, 65-94 years; women, 52.4%; mean follow-up, 7.0 ± 3.0 years). Plasma GDF-15 concentrations were measured using the 1.3k HTS SOMAscan assay. Eight bone parameters were measured in the right tibia by peripheral quantitative computed tomography; total bone density, trabecular bone density, medullary plus trabecular bone density, cortical bone density, total bone area, cortical bone area, medullary bone area, and minimum moment of inertia (mMOI). We ran sex-specific linear mixed-effect models with random intercepts and slopes adjusted for age, age-squared, education, body mass index, the rate of change in weight, smoking, sedentary behavior, cross-sectional areas of calf muscles and fat, 25-hydroxyvitamin D, parathyroid hormone, calcium, diabetes mellitus, and follow-up time. We found a significant association of "baseline GDF-15 × time" in models predicting cortical bone density and the mMOI in women, suggesting that the rates of decline in these bone parameters increased with higher GDF-15 (false discovery rate <0.05). Higher plasma levels GDF-15 predicted an accelerated decline in bone parameters in women, but was less associated in men. Furthermore studies are needed to understand the mechanisms underlying these sex differences.

The dynamic changes and sex differences of 147 immune-related proteins during acute COVID-19 in 580 individuals

INTRODUCTION

Severe COVID-19 leads to important changes in circulating immune-related proteins. To date it has been difficult to understand their temporal relationship and identify cytokines that are drivers of severe COVID-19 outcomes and underlie differences in outcomes between sexes. Here, we measured 147 immune-related proteins during acute COVID-19 to investigate these questions.

METHODS

We measured circulating protein abundances using the SOMAscan nucleic acid aptamer panel in two large independent hospital-based COVID-19 cohorts in Canada and the United States. We fit generalized additive models with cubic splines from the start of symptom onset to identify protein levels over the first 14 days of infection which were different between severe cases and controls, adjusting for age and sex. Severe cases were defined as individuals with COVID-19 requiring invasive or non-invasive mechanical respiratory support.

RESULTS

580 individuals were included in the analysis. Mean subject age was 64.3 (sd 18.1), and 47% were male. Of the 147 proteins, 69 showed a significant difference between cases and controls (p < 3.4 × 10-4). Three clusters were formed by 108 highly correlated proteins that replicated in both cohorts, making it difficult to determine which proteins have a true causal effect on severe COVID-19. Six proteins showed sex differences in levels over time, of which 3 were also associated with severe COVID-19: CCL26, IL1RL2, and IL3RA, providing insights to better understand the marked differences in outcomes by sex.

CONCLUSIONS

Severe COVID-19 is associated with large changes in 69 immune-related proteins. Further, five proteins were associated with sex differences in outcomes. These results provide direct insights into immune-related proteins that are strongly influenced by severe COVID-19 infection.