Serological testing is essential to curb the consequences of the COVID-19 pandemic. However, most assays are still limited to single analytes and samples collected within healthcare. Thus, we ...establish a multianalyte and multiplexed approach to reliably profile IgG and IgM levels against several versions of SARS-CoV-2 proteins (S, RBD, N) in home-sampled dried blood spots (DBS). We analyse DBS collected during spring of 2020 from 878 random and undiagnosed individuals from the population in Stockholm, Sweden, and use classification approaches to estimate an accumulated seroprevalence of 12.5% (95% CI: 10.3%-14.7%). This includes 5.4% of the samples being IgG
IgM
against several SARS-CoV-2 proteins, as well as 2.1% being IgG
IgM
and 5.0% being IgG
IgM
for the virus' S protein. Subjects classified as IgG
for several SARS-CoV-2 proteins report influenza-like symptoms more frequently than those being IgG
for only the S protein (OR = 6.1; p < 0.001). Among all seropositive cases, 30% are asymptomatic. Our strategy enables an accurate individual-level and multiplexed assessment of antibodies in home-sampled blood, assisting our understanding about the undiagnosed seroprevalence and diversity of the immune response against the coronavirus.
Self-sampling of dried blood spots (DBS) offers new routes to gather valuable health-related information from the general population. Yet, the utility of using deep proteome profiling from ...home-sampled DBS to obtain clinically relevant insights about SARS-CoV-2 infections remains largely unexplored.
Our study involved 228 individuals from the general Swedish population who used a volumetric DBS sampling device and completed questionnaires at home during spring 2020 and summer 2021. Using multi-analyte COVID-19 serology, we stratified the donors by their response phenotypes, divided them into three study sets, and analyzed 276 proteins by proximity extension assays (PEA). After normalizing the data to account for variances in layman-collected samples, we investigated the association of DBS proteomes with serology and self-reported information.
Our three studies display highly consistent variance of protein levels and share associations of proteins with sex (e.g., MMP3) and age (e.g., GDF-15). Studying seropositive (IgG
) and seronegative (IgG
) donors from the first pandemic wave reveals a network of proteins reflecting immunity, inflammation, coagulation, and stress response. A comparison of the early-infection phase (IgM
IgG
) with the post-infection phase (IgM
IgG
) indicates several proteins from the respiratory system. In DBS from the later pandemic wave, we find that levels of a virus receptor on B-cells differ between seropositive (IgG
) and seronegative (IgG
) donors.
Proteome analysis of volumetric self-sampled DBS facilitates precise analysis of clinically relevant proteins, including those secreted into the circulation or found on blood cells, augmenting previous COVID-19 reports with clinical blood collections. Our population surveys support the usefulness of DBS, underscoring the role of timing the sample collection to complement clinical and precision health monitoring initiatives.
Precision medicine approaches aim to tackle diseases on an individual level through molecular profiling. Despite the growing knowledge about diseases and the reported diversity of molecular ...phenotypes, the descriptions of human health on an individual level have been far less elaborate.
To provide insights into the longitudinal protein signatures of well-being, we profiled blood plasma collected over one year from 101 clinically healthy individuals using multiplexed antibody assays. After applying an antibody validation scheme, we utilized > 700 protein profiles for in-depth analyses of the individuals’ short-term health trajectories.
We found signatures of circulating proteomes to be highly individual-specific. Considering technical and longitudinal variability, we observed that 49% of the protein profiles were stable over one year. We also identified eight networks of proteins in which 11–242 proteins covaried over time. For each participant, there were unique protein profiles of which some could be explained by associations to genetic variants.
This observational and non-interventional study identifyed noticeable diversity among clinically healthy subjects, and facets of individual-specific signatures emerged by monitoring the variability of the circulating proteomes over time. To enable more personal hence precise assessments of health states, longitudinal profiling of circulating proteomes can provide a valuable component for precision medicine approaches.
This work was supported by the Erling Persson Foundation, the Swedish Heart and Lung Foundation, the Knut and Alice Wallenberg Foundation, Science for Life Laboratory, and the Swedish Research Council.
The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment
. The ...origins of specific compounds are known, including metabolites that are highly heritable
, or those that are influenced by the gut microbiome
, by lifestyle choices such as smoking
, or by diet
. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites-in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts
that were not available to us when we trained the algorithms. We used feature attribution analysis
to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.
Patient-centric sampling strategies, where the patient performs self-sampling and ships the sample to a centralized laboratory for readout, are on the verge of widespread adaptation. However, the key ...to a successful patient-centric workflow is user-friendliness, with few noncritical user interactions, and simple, ideally biohazard-free shipment. Here, we present a capillary-driven microfluidic device designed to perform the critical biomarker capturing step of a multiplexed immunoassay at the time of sample collection. On-chip sample drying enables biohazard-free shipment and allows us to make use of advanced analytics of specialized laboratories that offer the needed analytical sensitivity, reliability, and affordability. Using C-Reactive Protein, MCP1, S100B, IGFBP1, and IL6 as model blood biomarkers, we demonstrate the multiplexing capability and applicability of the device to a patient-centric workflow. The presented quantification of a biomarker panel opens up new possibilities for e-doctor and e-health applications.
Current breast cancer risk prediction scores and algorithms can potentially be further improved by including molecular markers. To this end, we studied the association of circulating plasma proteins ...using Proximity Extension Assay (PEA) with incident breast cancer risk.
In this study, we included 1577 women participating in the prospective KARMA mammographic screening cohort.
In a targeted panel of 164 proteins, we found 8 candidates nominally significantly associated with short-term breast cancer risk (P < 0.05). Similarly, in an exploratory panel consisting of 2204 proteins, 115 were found nominally significantly associated (P < 0.05). However, none of the identified protein levels remained significant after adjustment for multiple testing. This lack of statistically significant findings was not due to limited power, but attributable to the small effect sizes observed even for nominally significant proteins. Similarly, adding plasma protein levels to established risk factors did not improve breast cancer risk prediction accuracy.
Our results indicate that the levels of the studied plasma proteins captured by the PEA method are unlikely to offer additional benefits for risk prediction of short-term overall breast cancer risk but could provide interesting insights into the biological basis of breast cancer in the future.
INTRODUCTION
We explored the variations of blood biomarkers of Alzheimer's disease (AD) by chronic diseases and systemic inflammation.
METHODS
We explored the association of AD blood biomarkers with ...chronic diseases and systemic inflammation (interleukin‐6 IL‐6), in 2366 dementia‐free participants of the Swedish National Study on Aging and Care‐in Kungsholmen, using quantile regression models.
RESULTS
A greater number of co‐occurring chronic diseases was associated with higher concentrations of phosphorylated‐tau 181 (p‐tau181), total‐tau (t‐tau), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) (p < 0.01). Anemia, kidney, cerebrovascular, and heart diseases were associated with variations in the levels of AD blood biomarkers. Participants in the highest (vs. lowest) interleukin‐6 (IL‐6) tertile had higher NfL concentration. Systemic inflammation amplified the associations between several chronic diseases and p‐tau181, t‐tau, NfL, and GFAP.
DISCUSSION
In the community, the concentration of AD blood biomarkers varies in relation to medical conditions and systemic inflammation. Recognizing these influences is crucial for the accurate interpretation and clinical implementation of blood biomarkers.
Highlights
Participants with a complex clinical profile (i.e., multiple co‐occurring diseases or specific disease combinations) display elevated levels of AD blood‐biomarkers.
Anemia, heart, cerebrovascular, and kidney diseases are associated with variations is the levels of AD blood biomarkers in cognitively intact older adults.
Systemic inflammation amplifies the association between several chronic diseases and AD blood biomarkers.
Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as ...this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning.
We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (<5% or ≥5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Another key limitation of this study is that the prediction was done on a binary outcome of liver fat quantity (<5% or ≥5%) rather than a continuous one.
In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community.
ClinicalTrials.gov NCT03814915.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Roux-en-Y gastric bypass surgery (RYGB) has been effective for inducing weight-loss and remission of diabetes in obese persons. Nonetheless, the response to RYGB and resulting improvements in ...glycemic control are heterogeneous and not well understood. To gain molecular insights into how individuals respond to RYGB, we monitored the longitudinal effects of RYGB surgery via circulating proteins. We quantified 368 proteins using multiplexed and sensitive immunoassays (Olink) in sera collected from 146 obese persons with T2D (BMI > 35 kg/m2) prior to, and at one and three months after surgery. We observed an overall longitudinal change in circulating levels for ∼50% of the proteins (FDR < 0.01). This included a post-RYGB increase in levels of GH, IGFBP-2, NT-proBNP, REGA1 and MMP-3, as well as a decrease in levels of SSC4D, SERPINA12, GIF, FBP1, CES1. To deconvolute the inter-individual heterogeneity of the circulating proteomes and protein-related longitudinal dynamics, we clustered the total of ∼44,000 protein profiles into 10 response patterns. Just 8% (28/368) of the proteins’ levels changed in a common manner across the majority of individuals, as these were grouped into 3 or fewer clusters. Among these were proteins related to adipogenesis (LEP, DLK1, GH), white adipocyte differentiation (LEP, FABP4), as well as innate immunity (CHIT1, PTX3, CSTB). However, out of these 28 proteins, only levels of VSIG2 were significantly associated (FDR < 0.01) with diabetes remission at 12 months (HbA1c < 6.5%, no diabetes medication). Overall, our results suggest a wide-reaching, individual-specific, but predominantly short-term impact of RYGB surgery on the circulating proteome. Current investigations examine how genetic variance and mRNA expression in adipose and liver tissue influence the donors’ circulating proteomes in order to explain the observed heterogeneity and its impact on a person’s molecular homeostasis.
Disclosure
C.E. Thomas: None. R.S. Häussler: None. M. Hong: None. V. Raverdy: None. M. Dale: None. M. Canouil: None. G. Mazzoni: None. A. Viñuela: None. P. Froguel: None. S. Brunak: Board Member; Self; Intomics A/S, Proscion A/S. Research Support; Self; Novo Nordisk Foundation. Stock/Shareholder; Self; Lundbeck, Novo Nordisk A/S. J.M. Schwenk: None.
Funding
Innovative Medicines Initiative Joint Undertaking (115317); European Union’s Seventh Framework Programme (FP7/2007-2013); Conseil Regional Nord-Pas-de-Calais; European Commission (FEDER 12003944); European Genomic Institute for Diabetes (ANR-10-LABX-46); Foundation Coeur et Arteres (R15112EE); Fonds hospitalier d’aide a l’emergence et a la structuration des activities et des equipes de recherche 2015 (CHRU Lille, France)
Membrane proteins on enveloped viruses play an important role in many biological functions involving virus attachment to target cell receptors, fusion of viral particles to host cells, host-virus ...interactions, and disease pathogenesis. Furthermore, viral membrane proteins on virus particles and presented on host cell surfaces have proven to be excellent targets for antivirals and vaccines. Here, we describe a protocol to investigate surface proteins on intact severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) particles using the dual-reporter flow cytometric system. The assay exploits multiplex technology to obtain a triple detection of viral particles by three independent affinity reactions. Magnetic beads conjugated to recombinant human angiotensin-converting enzyme-2 (ACE2) were used to capture viral particles from the supernatant of cells infected with SARS-CoV-2. Then, two detection reagents labeled with R-phycoerythrin (PE) or Brilliant Violet 421 (BV421) were applied simultaneously. As a proof-of-concept, antibody fragments targeting different epitopes of the SARS-CoV-2 surface protein Spike (S1) were used. The detection of viral particles by three independent affinity reactions provides strong specificity and confirms the capture of intact virus particles. Dose-dependency curves of SARS-CoV-2 infected cell supernatant were generated with replicate coefficient variances (mean/SD) ˂14%. Good assay performance in both channels confirmed that two virus surface target protein epitopes are detectable in parallel. The protocol described here could be applied for (i) high-multiplex, high-throughput profiling of surface proteins expressed on enveloped viruses; ii) detection of active intact viral particles; and (iii) assessment of specificity and affinity of antibodies and antiviral drugs for surface epitopes of viral antigens.The application can be potentially extended to any type of extracellular vesicles and bioparticles, exposing surface antigens in body fluids or other liquid matrices.
PDF
