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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, Here, Roxhed et al. develop a multiplexed approach to screen IgG and IgM levels against several SARS-CoV-2 proteins in home-sampled dried blood spots and estimate seroprevalence of 12.5% in Stockholm in spring of 2020.

Self-sampled blood provided valuable information about the COVID-19 seroprevalence in the general population. To enable an even deeper understanding of pathophysiological processes following SARS-CoV-2 infections, 276 circulating proteins were quantified by proximity extension assays in dried blood spots (DBS). Samples from undiagnosed individuals collected during the first wave of the pandemic were selected based on their serological immune response and matched on self-reported symptoms. We stratified these as seropositive (IgM+IgG+; N = 41) or seronegative (IgM-IgG-; N = 37), and to represent the acute (IgM+IgG-; N = 26) and convalescent phases (IgM-IgG+; N = 40). This revealed proteins from a variety of clinical processes including inflammation and immune response (MBL2, MMP3, IL2RA, FCGR2A, CCL5), haemostasis (GP1BA, VWF), stress response (ANG), virus entry (SDC4) or nerve regeneration (CHL1). The presented approach complements clinical surveys and enables a deep molecular and population-wide analysis of COVID-19 from blood specimens collected outside a hospital setting.

Type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD) often co-occur. Defining causal pathways underlying this relationship may help optimize the prevention and treatment of both diseases. Thus, we assessed the strength and magnitude of the putative causal pathways linking dysglycemia and fatty liver, using a combination of causal inference methods.Measures of glycemia, insulin dynamics, magnetic resonance imaging (MRI)-derived abdominal and liver fat content, serological biomarkers, lifestyle, and anthropometry were obtained in participants from the IMI DIRECT cohorts (n=795 with new onset T2D and 2234 individuals free from diabetes). UK Biobank (n=3641) was used for modelling and replication purposes. Bayesian networks were employed to infer causal pathways, with causal validation using two-sample Mendelian randomization.Bayesian networks fitted to IMI DIRECT data identified higher basal insulin secretion rate (BasalISR) and MRI-derived excess visceral fat (VAT) accumulation as the features of dysmetabolism most likely to cause liver fat accumulation; the unconditional probability of fatty liver (>5%) increased significantly when conditioning on high levels of BasalISR and VAT (by 23%, 32% respectively; 40% for both). Analyses in UK Biobank yielded comparable results. MR confirmed most causal pathways predicted by the Bayesian networks.Here, BasalISR had the highest causal effect on fatty liver predisposition, providing mechanistic evidence underpinning the established association of NAFLD and T2D. BasalISR may represent a pragmatic biomarker for NAFLD prediction in clinical practice.

Aims/hypothesis It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). Methods We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. Results The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. Conclusions/interpretation These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.

Nonalcoholic fatty liver disease (NAFLD) refers to excess fat accumulation in the liver. In animal experiments and human kinetic study, we found that administration of combined metabolic activators (CMA) promotes the oxidation of fat, attenuates the resulting oxidative stress, activates mitochondria and eventually removes excess fat from the liver. Here, we tested the safety and efficacy of CMA in NAFLD patients in a placebo-controlled 10-week study. We found that CMA significantly decreased hepatic steatosis and levels of aspartate aminotransferase, alanine aminotransferase, uric acid, and creatinine, whereas found no differences on these variables in the placebo group after adjustment for weight loss. By integrating clinical data with plasma metabolomics and inflammatory proteomics as well as oral and gut metagenomics data, we revealed the underlying molecular mechanisms associated with the reduced hepatic fat and inflammation in NAFLD patients and identified the key players involved in the host-microbiome interactions. In conclusion, we observed that CMA can be used develop a pharmacological treatment strategy in NAFLD patients.

Highlights • Current risk prediction models use a variety of factors to identify women at risk of developing breast cancer. • Proteins circulating in blood represent an attractive but currently still underrepresented source of candidates serving as molecular risk factors. • Plasma samples from women participating in a prospective breast cancer cohort study were studied for proteomic risk factors related to a future breast cancer diagnosis. • Applying data-driven approaches on the levels of circulating proteins, women with future breast cancers and previous use of menopausal hormone therapy were identified. • Menopausal hormone therapy was found to alter components of the circulating proteomes even years after the treatment ended., Accessible risk predictors are crucial for improving the early detection and prognosis of breast cancer. Blood samples are widely available and contain proteins that provide important information about human health and disease, however, little is still known about the contribution of circulating proteins to breast cancer risk prediction. We profiled EDTA plasma samples collected before diagnosis from the Swedish KARMA breast cancer cohort to evaluate circulating proteins as molecular predictors. A data-driven analysis strategy was applied to the molecular phenotypes built on 700 circulating proteins to identify and annotate clusters of women. The unsupervised analysis of 183 future breast cancer cases and 366 age-matched controls revealed five stable clusters with distinct proteomic plasma profiles. Among these women, those in the most stable cluster (N = 19; mean Jaccard index: 0.70 ± 0.29) were significantly more likely to have used menopausal hormonal therapy (MHT), get a breast cancer diagnosis, and were older compared to the remaining clusters. The circulating proteins associated with this cluster (FDR < 0.001) represented physiological processes related to cell junctions (F11R, CLDN15, ITGAL), DNA repair (RBBP8), cell replication (TJP3), and included proteins found in female reproductive tissue (PTCH1, ZP4). Using a data-driven approach on plasma proteomics data revealed the potential long-lasting molecular effects of menopausal hormonal therapy (MHT) on the circulating proteome, even after women had ended their treatment. This provides valuable insights concerning proteomics efforts to identify molecular markers for breast cancer risk prediction.

Background Protein profiles that can predict allergy development in children are lacking and the ideal sampling age is unknown. By applying an exploratory proteomics approach in the prospective FARMFLORA birth cohort, we sought to identify previously unknown circulating proteins in early life that associate to protection or risk for development of allergy up to 8 years of age. Methods We analyzed plasma prepared from umbilical cord blood (n = 38) and blood collected at 1 month (n = 42), 4 months (n = 39), 18 months (n = 42), 36 months (n = 42) and 8 years (n = 44) of age. We profiled 230 proteins with a multiplexed assay and evaluated the global structure of the data with principal component analysis (PCA). Protein profiles informative to allergic disease at 18 months, 36 months and/or 8 years were evaluated using Lasso logistic regression and random forest. Results Two clusters emerged in the PCA analysis that separated samples obtained at birth and at 1 month of age from samples obtained later. Differences between the clusters were mostly driven by abundant plasma proteins. For the prediction of allergy, both Lasso logistic regression and random forest were most informative with samples collected at 1 month of age. A Lasso model with 27 proteins together with farm environment differentiated children who remained healthy from those developing allergy. This protein panel was primarily composed of antigen-presenting MHC class I molecules, interleukins and chemokines. Conclusion Sampled at one month of age, circulating proteins that reflect processes of the immune system may predict the development of allergic disease later in childhood.

Endothelial cell (EC) dysfunction is a well-established response to cardiovascular disease (CVD) risk factors, such as smoking and obesity. Risk factor exposure can modify EC signalling and behaviour, leading to arterial and venous disease development. Biomarker panels to assess EC dysfunction are lacking, but could be useful for risk stratification and to monitor treatment response. Here, we used affinity proteomics to identify EC-derived proteins circulating in plasma that were associated with CVD risk factor exposure. 216 proteins, known to be expressed in ECs across vascular beds, were measured in plasma samples (n=1005) from the population-based Swedish CArdioPulmonary bioImage Study (SCAPIS) pilot. We identified 38 EC-derived proteins that were associated with body mass index, total cholesterol, low density lipoprotein, smoking, hypertension or diabetes. Sex-specific analysis revealed female- and male-only associations were most frequently observed with BMI, or total cholesterol, respectively. We showed a relationship between individual CVD risk, calculated with the Framingham risk score, and the corresponding biomarker profiles; presenting the concept of measuring EC-derived proteins in plasma to infer vascular status.

OBJECTIVE We investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS A total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), β-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA1c deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression. RESULTS Faster HbA1c progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles (R2 = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8–10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07–0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role. CONCLUSIONS Deteriorating insulin sensitivity and β-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, β-cell function, and insulin clearance may be relevant to prevent progression.

Systematic exploration of the dynamic human plasma proteome enables the discovery of novel protein biomarkers. Using state-of-the-art technologies holds the promise to facilitate a better diagnosis and risk prediction of diseases. Cardiovascular disease (CVD) pathophysiology is characterized for unbalancing of processes such as vascular inflammation, endothelial dysfunction, or lipid profiles among others. Such processes have a direct impact on the dynamic and complex composition of blood and hence the plasma proteome. Therefore, the study of the plasma proteome comprises an excellent exploratory source of biomarker research particularly for CVD. We describe the protocol for performing the discovery of protein biomarker candidates using the suspension bead array technology. The process does not require depletion steps to remove abundant proteins and consumes only a few microliters of sample from the body fluid of interest. The approach is scalable to measure many analytes as well as large numbers of samples. Moreover, we describe a bead-assisted antibody-labeling process that helps to develop quantitative assays for validation purposes and facilitate the translation of the identified candidates into clinical studies.

We have previously found that combined metabolic cofactor supplementation (CMCS) promotes the oxidation of fat, attenuates the resulting oxidative stress, activates mitochondria and eventually removes excess fat from the liver. Here, we tested the safety and efficacy of CMCS in Nonalcoholic fatty liver disease (NAFLD) patients in a placebo-controlled 10-week study. We found that CMCS significantly decreased hepatic steatosis and levels of aspartate aminotransferase, alanine aminotransferase, uric acid, and creatinine whereas found no differences on these variables in the placebo group after adjustment for weight loss. By integrating clinical data with plasma metabolomics and inflammatory proteomics as well as oral and gut metagenomics data, we revealed the underlying molecular mechanisms associated with the reduced hepatic fat and inflammation in NAFLD patients and identified the key players involved in the host-microbiome interactions. In conclusion, we observed that CMCS could develop a pharmacological treatment strategy in NAFLD patients.

The hepatokine follistatin is elevated in patients with type 2 diabetes (T2D) and promotes hyperglycemia in mice. Here we explore the relationship of plasma follistatin levels with incident T2D and mechanisms involved. Adjusted hazard ratio (HR) per standard deviation (SD) increase in follistatin levels for T2D is 1.24 (CI: 1.04–1.47, p, Follistatin promotes in type 2 diabetes (T2D) pathogenesis in model animals and is elevated in patients with T2D. Here the authors report that plasma follistatin associates with increased risk of incident T2D in two longitudinal cohorts, and show that follistatin regulates insulin-induced suppression lipolysis in cultured human adipocytes.

Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (N = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA1c indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). β-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISRr), and insulin secretion potentiation (P < 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISRr (P < 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, P < 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.

It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435).We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively.The TC and TC-PA models showed better fit than null models (TC: χThese analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.

Background: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D. Methods: We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (Tpred) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous Tpred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models. Findings: A higher Tpred score was associated with healthier diets high in wholegrain (β=3.36 g, 95% CI 0.31, 6.40 and β=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (β=-75.53 kcal, 95% CI -144.71, -2.35 and β=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (β=-0.92 g, 95% CI -1.56, -0.28 and β=–0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher Tpred score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (β=0.07 mmol/L, 95% CI 0.03, 0.1), (β=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (β=-0.1 mmol/L, 95% CI -0.2, -0.03), (β=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the Tpred score was negatively associated with liver fat (β=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (β=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (β=-0.2 mmol/L, 95% CI -0.4, -0.05) and insulin (β=-11.0 pmol/mol, 95% CI -19.5, -2.6). Longitudinal analysis showed at 18-month follow up a higher Tpred score was also associated lower total body adiposity in both cohorts and lower fasting glucose (β=-0.2 mmol/L, 95% CI -0.3, -0.01) and insulin (β=-9.2 pmol/mol, 95% CI -17.9, -0.4) concentrations in cohort 2. Interpretation: Plasma dietary metabolite profiling provides objective measures of diet intake, showing a relationship to glycaemic deterioration and cardiometabolic health. Funding: This work was supported by the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115,317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007–2013) and EFPIA companies.

The COVID-19 pandemic has posed a tremendous challenge for the global community. We established a translational approach combining home blood sampling by finger-pricking with multiplexed serology to assess the exposure to the SARS-CoV-2 virus in a general population. The developed procedure determines the immune response in multiplexed assays against several spike (S, here denoted SPK), receptor binding domain (RBD) and nucleocapsid (NCP) proteins in eluates from dried capillary blood. The seroprevalence was then determined in two study sets by mailing 1000 blood sampling kits to random households in urban Stockholm during early and late April 2020, respectively. After receiving 55% (1097/2000) of the cards back within three weeks, 80% (878/1097) were suitable for the analyses of IgG and IgM titers. The data revealed diverse pattern of immune response, thus seroprevalence was dependent on the antigen, immunoglobulin class, stringency to include different antigens, as well as the required analytical performance. Applying unsupervised dimensionality reduction to the combined IgG and IgM data, 4.4% (19/435; 95% CI: 2.4%-6.3%) and 6.3% (28/443; 95% CI: 4.1%-8.6%) of the samples clustered with convalescent controls. Using overlapping scores from at least two SPK antigens, prevalence rates reached 10.1% (44/435; 95% CI: 7.3%-12.9%) in study set 1 and 10.8% (48/443; 95% CI: 7.9%-13.7%). Measuring the immune response against several SARS-CoV-2 proteins in a multiplexed workflow can provide valuable insights about the serological diversity and improve the certainty of the classification. Combining such assays with home-sampling of blood presents a viable strategy for individual-level diagnostics and towards an unbiased assessment of the seroprevalence in a population and may serve to improve our understanding about the diversity of COVID-19 etiology.One Sentence SummaryA multiplexed serology assay was developed to determine antibodies against SARS-CoV-2 proteins in home-sampled dried blood spots collected by finger pricking.

Aim Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D. Methods The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders. Results At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1–3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18–1.92) for subgroup 2 and 1.88 (-0.08–3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose. Conclusions Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk.

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)

BackgroundNon-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in type 2 diabetes (T2D) and beyond. Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and ultimately hepatocellular carcinomas.Methods and FindingsUtilizing the baseline data from the IMI DIRECT participants (n=1514) we sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. Multi-omic (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, and 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 (ConclusionsWe have developed clinically useful liver fat prediction models (see:www.predictliverfat.org) and identified biological features that appear to affect liver fat accumulation.

Objectives Cancer-testis antigens (CTAs) are defined as proteins that are specifically expressed in testis or placenta and their expression is frequently activated in cancer. Due to their ability to induce an immune response, CTAs may serve as suitable targets for immunotherapy. The aim of this study was to evaluate if there is reactivity against CTAs in the plasma of non-small cell lung cancer (NSCLC) patients through the detection of circulating antibodies. Materials and methods To comprehensively analyze autoantibodies against CTAs the multiplexing capacities of suspension bead array technology was used. Bead arrays were created with 120 protein fragments, representing 112 CTAs. Reactivity profiles were measured in plasma samples from 133 NSCLC patients and 57 cases with benign lung diseases. Results Altogether reactivity against 69 antigens, representing 81 CTAs, was demonstrated in at least one of the analyzed samples. Twenty-nine of the antigens (45 CTAs) demonstrated exclusive reactivity in NSCLC samples. Reactivity against cancer-testis antigen family 47; member A (CT47A) genes, P antigen family member 3 (PAGE3), variable charge X-linked (VCX), melanoma antigen family B1 (MAGEB1), lin-28 homolog B (LIN28B) and chromosome 12 open reading frame 54 (C12orf54) were only found in NSCLC patients at a frequency of 1%–4%. The presence of autoantibodies towards these six antigens was confirmed in an independent group of 34 NSCLC patients. Conclusion We identified autoantibodies against CTAs in the plasma of lung cancer patients. The reactivity pattern of autoantibodies was higher in cancer patients compared to the benign group, stable over time, but low in frequency of occurrence. The findings suggest that some CTAs are immunogenic and that these properties can be utilized as immune targets.

Aims/hypothesis Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up). Methods From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6–24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at ~18 months (both cohorts) and at ~48 months (cohort 1) or ~36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe. Results Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean ± SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m2; fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants’ clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following characteristics at baseline: age 62 (8.1) years; BMI 30.5 (5.0) kg/m2; fasting glucose 7.2 (1.4) mmol/l; 2 h glucose 8.6 (2.8) mmol/l. At the final follow-up examination, the participants’ clinical characteristics were as follows: fasting glucose 7.9 (2.0) mmol/l; 2 h mixed-meal tolerance test glucose 9.9 (3.4) mmol/l. Conclusions/interpretation The IMI DIRECT cohorts are intensely characterised, with a wide-variety of metabolically relevant measures assessed prospectively. We anticipate that the cohorts, made available through managed access, will provide a powerful resource for biomarker discovery, multivariate aetiological analyses and reclassification of patients for the prevention and treatment of type 2 diabetes. Electronic supplementary material The online version of this article (10.1007/s00125-019-4906-1) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

Plasma proteins can provide valuable insights on human health and disease states. Within the framework of the EU IMI project DIRECT (https://www.direct-diabetes.org), we used a set of affinity proteomic methods to profile > 3100 study participants at baseline. Multiplexed assays quantified more than 600 unique proteins in EDTA plasma from this multi-center cohort that included 2300 subjects at risk of developing T2D (HbA1c ~ 6-6.5%) as well as 800 with early T2D (HbA1c > 6.5%). Using extensive clinical and other omics metadata available, the aim of the investigation was to identify plasma proteins associated with baseline traits. An initial analysis highlighted the importance of considering sample-related and pre-analytical variables as possible confounders in the data analysis. Hence, we used linear mixed models that included several parameters such as age, sex, study center and collection date. Next, we defined proteins associating with any of the >50 quantitative clinical traits at baseline. We found more than 300 proteins in plasma that were associated with diabetes related traits (adjusted p-value < 0.0001), many of which were prominently associated with BMI. The shortlisted candidates included leptin which associates with waist circumference and BMI; IGFBP1 and IGFBP2 to Matsuda; adiponectin to basal insulin secretion rate and fasting HDL; LDL receptor proteins to fasting triglycerides; APOM to fasting cholesterol; or IL8 and MCP-1 to fasting AST. In addition, we performed pQTL analysis to assess any connection between the protein values in plasma and genetic variants. We observed >400 cis-pQTLs (q-value < 0.05), such as for APOM (rs2736163, p = 5.15 e-24), which illustrated that many of the studied protein profiles are affected by a genetic component. With follow-up samples collected 3-4 years after starting the study, the baseline values will serve as valuable indicators of progression and allow study of how each participant's disease phenotype changes over time or due to treatment. Disclosure M. Hong: None. A. Viñuela: None. R.S. Häussler: None. M. Dale: None. R.W. Koivula: None. J. Fernandez-Tajes: None. A. Mahajan: None. R. Bizzotto: Research Support; Self; GlaxoSmithKline plc. A. Mari: Consultant; Self; Eli Lilly and Company. Research Support; Self; Boehringer Ingelheim International GmbH. E. Dermitzakis: Advisory Panel; Self; DNAnexus LTD. Board Member; Self; Hybridstat LTD. M. McCarthy: Advisory Panel; Self; European Association for the Study of Diabetes, Pfizer Inc. Consultant; Self; Eli Lilly and Company, Merck & Co., Inc. Consultant; Spouse/Partner; Merck & Co., Inc. Research Support; Self; AbbVie Inc., Boehringer Ingelheim International GmbH. Research Support; Spouse/Partner; Diabetes UK. Research Support; Self; Janssen Pharmaceuticals, Inc., Merck & Co., Inc., National Institutes of Health. Research Support; Spouse/Partner; National Institutes of Health. Research Support; Self; Novo Nordisk A/S. Research Support; Spouse/Partner; Novo Nordisk A/S. Research Support; Self; Novo Nordisk Foundation, Roche Pharma, Sanofi-Aventis, Servier, Takeda Pharmaceutical Company Limited. P.W. Franks: Board Member; Self; Zoe Ltd. Research Support; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Lilly Diabetes, Novo Nordisk A/S, Novo Nordisk Foundation, Sanofi, Servier. E. Pearson: None. J.M. Schwenk: None. Funding Innovative Medicines Initiative Joint Undertaking (115317)

/SummaryBackground and aims:Understanding the aetiology, clinical presentation and prognosis of type 2 diabetes (T2D) and optimizing its treatment might be facilitated by biomarkers that help predict a person’s susceptibility to the risk factors that cause diabetes or its complications, or response to treatment. The IMI DIRECT (Diabetes Research on Patient Stratification) Study is a European Union (EU) Innovative Medicines Initiative (IMI) project that seeks to test these hypotheses in two recently established epidemiological cohorts. Here, we describe the characteristics of these cohorts at baseline and at the first main follow-up examination (18-months).Materials and methods:From a sampling-frame of 24,682 European-ancestry adults in whom detailed health information was available, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm and enrolled into a prospective cohort study (n=2127) undertaken at four study centres across Europe (Cohort 1: prediabetes). We also recruited people from clinical registries with recently diagnosed T2D (n=789) into a second cohort study (Cohort 2: diabetes). The two cohorts were studied in parallel with matched protocols. Endogenous insulin secretion and insulin sensitivity were modelled from frequently sampled 75g oral glucose tolerance (OGTT) in Cohort 1 and with mixed-meal tolerance tests (MMTT) in Cohort 2. Additional metabolic biochemistry was determined using blood samples taken when fasted and during the tolerance tests. Body composition was assessed using MRI and lifestyle measures through self-report and objective methods.Results:Using ADA-2011 glycaemic categories, 33% (n=693) of Cohort 1 (prediabetes) had normal glucose regulation (NGR), and 67% (n=1419) had impaired glucose regulation (IGR). 76% of the cohort was male, age=62(6.2) years; BMI=27.9(4.0) kg/m2; fasting glucose=5.7(0.6) mmol/l; 2-hr glucose=5.9(1.6) mmol/l [mean(SD)]. At follow-up, 18.6(1.4) months after baseline, fasting glucose=5.8(0.6) mmol/l; 2-hr OGTT glucose=6.1(1.7) mmol/l [mean(SD)]. In Cohort 2 (diabetes): 65% (n=508) were lifestyle treated (LS) and 35% (n=271) were lifestyle + metformin treated (LS+MET). 58% of the cohort was male, age=62(8.1) years; BMI=30.5(5.0) kg/m2; fasting glucose=7.2(1.4)mmol/l; 2-hr glucose=8.6(2.8) mmol/l [mean(SD)]. At follow-up, 18.2(0.6) months after baseline, fasting glucose=7.8(1.8) mmol/l; 2-hr MMTT glucose=9.5(3.3) mmol/l [mean(SD)].Conclusion:The epidemiological IMI DIRECT cohorts are the most intensely characterised prospective studies of glycaemic deterioration to date. Data from these cohorts help illustrate the heterogeneous characteristics of people at risk of or with T2D, highlighting the rationale for biomarker stratification of the disease - the primary objective of the IMI DIRECT consortium.Abbreviations:ASATAbdominal subcutaneous adipose tissueDIRECTDiabetes Research on Patient StratificationEUEuropean UnionMMTTMixed-meal tolerance testMRIMagnetic resonance imaginghpfVMHigh-pass filtered vector magnitudeIAATIntra-abdominal adipose tissueIGRImpaired glucose regulationIMIInnovative Medicines InitiativeMEmultiechoNGRNormal glucose regulationOGTTOral glucose tolerance testPAPhysical activityTAATTotal abdominal adipose tissueT2DType 2 Diabetes

The concept of antibody microarrays is one of the most versatile approaches within multiplexed immunoassay technologies. These types of arrays have increasingly become an attractive tool for the exploratory detection and study of protein abundance, function, pathways, and potential drug targets. Due to the properties of the antibody microarrays and their potential use in basic research and clinical analytics, various types of antibody microarrays have already been developed. In spite of the growing number of studies utilizing this technique, few reviews about antibody microarray technology have been presented to reflect the quality and future uses of the generated data. In this review, we provide a summary of the recent applications of antibody microarray techniques in basic biology and clinical studies, providing insights into the current trends and future of protein analysis. Electronic supplementary material The online version of this article (10.1186/s12014-018-9184-2) contains supplementary material, which is available to authorized users.

Visual Abstract, Highlights • Multiomics profiling of gene and protein expression in carotid plaques, together with protein expression in peripheral and “local” plasma sampled around the lesion, was performed using a large cohort of patients from BiKE in discovery analyses. • BLVRB was identified as a biomarker of intraplaque hemorrhage and plaque instability in carotid atherosclerosis that was further validated in population samples. • BLVRB was characterized as a hitherto unappreciated key enzyme, functionally linked with HMOX1, in the hemoglobin catabolism under pathological conditions. • The novel translational approach applied for biomarker discovery in this study permits causal interpretation of candidates directly in relation to the underlying disease and paves the way for similar investigations in other vascular territories., Summary Clinical tools to identify individuals with unstable atherosclerotic lesions are required to improve prevention of myocardial infarction and ischemic stroke. Here, a systems-based analysis of atherosclerotic plaques and plasma from patients undergoing carotid endarterectomy for stroke prevention was used to identify molecular signatures with a causal relationship to disease. Local plasma collected in the lesion proximity following clamping prior to arteriotomy was profiled together with matched peripheral plasma. This translational workflow identified biliverdin reductase B as a novel marker of intraplaque hemorrhage and unstable carotid atherosclerosis, which should be investigated as a potential predictive biomarker for cardiovascular events in larger cohorts.

Background Mammographic breast density is one of the strongest risk factors for breast cancer, but molecular understanding of how breast density relates to cancer risk is less complete. Studies of proteins in blood plasma, possibly associated with mammographic density, are well-suited as these allow large-scale analyses and might shed light on the association between breast cancer and breast density. Methods Plasma samples from 1329 women in the Swedish KARMA project, without prior history of breast cancer, were profiled with antibody suspension bead array (SBA) assays. Two sample sets comprising 729 and 600 women were screened by two different SBAs targeting a total number of 357 proteins. Protein targets were selected through searching the literature, for either being related to breast cancer or for being linked to the extracellular matrix. Association between proteins and absolute area-based breast density (AD) was assessed by quantile regression, adjusting for age and body mass index (BMI). Results Plasma profiling revealed linear association between 20 proteins and AD, concordant in the two sets of samples (p

We examined the immunologic effects of allogeneic hematopoietic stem cell transplantation (HSCT) in the treatment of pancreatic ductal adenocarcinoma, a deadly disease with a median survival of 24 months for resected tumors and a 5-year survival rate of 6%. After adjuvant chemotherapy, 2 patients with resected pancreatic ductal adenocarcinoma underwent HSCT with HLA-identical sibling donors. Comparable patients who underwent radical surgery, but did not have a donor, served as controls (n=6). Both patients developed humoral and cellular (ie, HLA-A*01:01-restricted) immune responses directed against 2 novel tumor-associated antigens (TAAs), INO80E and UCLH3 after HSCT. Both TAAs were highly expressed in the original tumor tissue suggesting that HSCT promoted a clinically relevant, long-lasting cellular immune response. In contrast to untreated controls, who succumbed to progressive disease, both patients are tumor-free 9 years after diagnosis. Radical surgery combined with HSCT may cure pancreatic adenocarcinoma and change the cellular immune repertoire capable of responding to clinically and biologically relevant TAAs.

Modeling the cancer transcriptome Recent initiatives such as The Cancer Genome Atlas have mapped the genome-wide effect of individual genes on tumor growth. By unraveling genomic alterations in tumors, molecular subtypes of cancers have been identified, which is improving patient diagnostics and treatment. Uhlen et al. developed a computer-based modeling approach to examine different cancer types in nearly 8000 patients. They provide an open-access resource for exploring how the expression of specific genes influences patient survival in 17 different types of cancer. More than 900,000 patient survival profiles are available, including for tumors of colon, prostate, lung, and breast origin. This interactive data set can also be used to generate personalized patient models to predict how metabolic changes can influence tumor growth. Science , this issue p. eaan2507

[Abstract] Currently there are no sufficiently sensitive biomarkers able to reflect changes in joint remodelling during osteoarthritis (OA). In this work, we took an affinity proteomic approach to profile serum samples for proteins that could serve as indicators for the diagnosis of radiographic knee OA. Antibody suspension bead arrays were applied to analyze serum samples from patients with OA (n = 273), control subjects (n = 76) and patients with rheumatoid arthritis (RA, n = 244). For verification, a focused bead array was built and applied to an independent set of serum samples from patients with OA (n = 188), control individuals (n = 83) and RA (n = 168) patients. A linear regression analysis adjusting for sex, age and body mass index (BMI) revealed that three proteins were significantly elevated (P

Objective Systemic Lupus Erythematosus (SLE) is a heterogeneous systemic autoimmune disease that is currently lacking specific diagnostic biomarkers. The diversity within the patients might obstruct clinical trials and could reflect differences in underlying pathogenesis. Our objective was to identify protein profiles that could be used for diagnosis and to identify molecular subgroups within SLE for patient stratification subjected to different treatment. Method In a cross-sectional study we performed protein profiling of 695 plasma samples from SLE patients and matched controls. This was achieved by utilising an antibody suspension bead array targeting 367 proteins. T-test and ROC analysis was performed to identify differences in the protein profiles between SLE and controls. Unsupervised K-means clustering was performed to identify data-driven SLE subgroups. Results We report that the novel proteins MMP1, SELE, and S100A12 can distinguish between SLE patients and controls with an area under curve of 0.80 in a ROC analysis. In addition, 28 proteins were found to show differences (corrected p-value Conclusion We have identified potential biomarkers of SLE that may be used to improve the diagnosis of SLE patients. Our suggested panel of biomarkers needs to be validated in an additional SLE cohort and also in relation to other systemic autoimmune diseases before it can be used as a diagnostic test. We have also identified subgroups characterised by different molecular patterns, indicating underlying pathogenic differences. These patient groups might benefit from different treatment strategies. Our work adds new information to today’s view of classifying the heterogeneous subgroups within SLE and the importance of personalised medicine.

OBJECTIVE: Amyotrophic lateral sclerosis (ALS) is the most common adult motor neuron disease leading to muscular paralysis and death within 3-5 years from onset. Currently, there are no reliable and sensitive markers able to substantially shorten the diagnosis delay. The objective of the study was to analyze a large number of proteins in plasma from patients with various clinical phenotypes of ALS in search for novel proteins or protein profiles that could serve as potential indicators of disease. METHODS: Affinity proteomics in the form of antibody suspension bead arrays were applied to profile plasma samples from 367 ALS patients and 101 controls. The plasma protein content was directly labeled and protein profiles obtained using 352 antibodies from the Human Protein Atlas targeting 278 proteins. A focused bead array was then built to further profile eight selected protein targets in all available samples. RESULTS: Disease-associated significant differences were observed and replicated for profiles from antibodies targeting the proteins: neurofilament medium polypeptide (NEFM), solute carrier family 25 (SLC25A20), and regulator of G-protein signaling 18 (RGS18). INTERPRETATION: Upon further validation in several independent cohorts with inclusion of a broad range of other neurological disorders as controls, the alterations of these three protein profiles in plasma could potentially provide new molecular markers of disease that contribute to the quest of understanding ALS pathology. QC 20150115

Background Immunological reactions may have a role in subgroups of patients suffering from psychiatric disorders. Possible markers for such subgroups may be autoantibodies of currently unknown nature. If identified, they could indicate which patients that would benefit from immunomodulatory treatment in addition to standard interventions. Modern proteomic methods allow analyses of antibody binding to thousands of different human proteins, facilitating the identification of currently undiscovered autoantibodies. Methods We have explored the association between any seroreactivity in plasma samples from first episode psychosis patients against more than 2000 randomly chosen protein fragments derived from human proteins, and the development of disorders characterized by chronic or relapsing psychotic symptoms. Plasma from 53 patients and 41 non-psychotic controls were assessed; the clinical course of the patients were followed for a mean duration of 7 years. The plasma samples were analyzed for IgG reactivity to 2304 fragments (approx 100 a.a. residues in length) of human proteins using a multiplexed affinity proteomic technique, and positive hits validated for binding in two additional assays. Results Thirty patients were diagnosed with schizophrenia, delusional disorder, schizoaffective disorder, bipolar disorder or a long-term unspecified nonorganic psychosis during follow-up, while 23 patients achieved complete remission. Eight patient samples showed autoreactivity to the N-terminal fragment of the PAGE protein family (PAGE2B/PAGE2/PAGE5), whereas no such autoreactivity was seen among the controls. PAGE autoreactivity was associated with a significantly increased risk of being diagnosed with schizophrenia during follow-up (odds ratio 6.7). An antisera raised against the N-terminal fragment stained an unknown extracellular target in human cortical brain tissue (Zandian et al., Transl Psychiatry 7: e1177; doi:10.1038/tp.2017.160). We are currently investigating the identity of this target. In addition, two other putative new autoantibodies found primarily among the patients, and rarely in the controls, will be discussed at the meeting. Discussion Our findings suggest that autoreactivity to the N-terminal portion of the PAGE protein family is associated with schizophrenia in a subset of patients with first-episode psychosis. In addition, we propose that searching for novel autoantibodies in an unbiased way may be feasible using state-of-the-art proteomic methods, and can yield useful biological markers for immune involvement in subgroups of individuals diagnosed with psychiatric disorders.

BACKGROUND: Blood-based proteomic profiling may aid and expand our understanding of diseases and their different phenotypes. The aim of the presented study was to profile serum samples from patients with malignant melanoma using affinity proteomic assays to describe proteins in the blood stream that are associated to stage or recurrence of melanoma. MATERIAL AND METHODS: Multiplexed protein analysis was conducted using antibody suspension bead arrays. A total of 232 antibodies against 132 proteins were selected from (i) a screening with 4595 antibodies and 32 serum samples from melanoma patients and controls, (ii) antibodies used for immunohistochemistry, (iii) protein targets previously related with melanoma. The analysis was performed with 149 serum samples from patients with malignant melanoma. Antibody selectivity was then assessed by Western blot, immunocapture mass spectrometry, and epitope mapping. Lastly, indicative antibodies were applied for IHC analysis of melanoma tissues. RESULTS: Serum levels of regucalcin (RGN) and syntaxin 7 (STX7) were found to be lower in patients with both recurring tumors and a high Breslow's thickness (T-stage 3/4) compared to low thickness (T-stage 1/2) without disease recurrence. Serum levels of methylenetetrahydrofolate dehydrogenase 1-like (MTHFD1L) were instead elevated in sera of T3/4 patients with recurrence. The analysis of tissue sections with S100A6 and MTHFD1L showed positive staining in a majority of patients with melanoma, and S100A6 was significantly associated to T-stage. CONCLUSIONS: Our findings provide a starting point to further study RGN, STX7, MTHFD1L and S100A6 in serum to elucidate their involvement in melanoma progression and to assess a possible contribution to support clinical indications.

Background & Aims The occurrence of drug‐induced liver injury (DILI) is a major issue in all phases of drug development. To identify novel biomarker candidates associated with DILI, we utilised an affinity proteomics strategy, where antibody suspension bead arrays were applied to profile plasma and serum samples from human DILI cases and controls. Methods An initial screening was performed using 4594 randomly selected antibodies, representing 3450 human proteins. Resulting candidate proteins together with proposed DILI biomarker candidates generated a DILI array of 251 proteins for subsequent target analysis and verifications. In total, 1196 samples from 241 individuals across four independent cohorts were profiled: healthy volunteers receiving acetaminophen, patients with human immunodeficiency virus and/or tuberculosis receiving treatment, DILI cases originating from a wide spectrum of drugs, and healthy volunteers receiving heparins. Results We observed elevated levels of cadherin 5, type 2 (CDH5) and fatty acid‐binding protein 1 (FABP1) in DILI cases. In the two longitudinal cohorts, CDH5 was elevated already at baseline. FABP1 was elevated after treatment initiation and seemed to respond more rapidly than alanine aminotransferase (ALT). The elevations were verified in the DILI cases treated with various drugs. In the heparin cohort, CDH5 was stable over time whereas FABP1 was elevated. Conclusions These results suggest that CDH5 may have value as a susceptibility marker for DILI. FABP1 was identified as a biomarker candidate with superior characteristics regarding tissue distribution and kinetics compared to ALT but likely with limited predictive value for the development of severe DILI. Further studies are needed to determine the clinical utility of the proposed markers.

Background Sarcoidosis is a granulomatous systemic inflammatory disease in which more than 90 % of all patients develop pulmonary manifestations. Several gene associations have previously been described, but established and clinically useful biomarkers are still absent. This study aimed to find proteins in bronchoalveolar lavage (BAL) fluid that can be associated with the disease. Methods We developed and performed profiling of 94 selected proteins in BAL fluid and serum samples obtained from newly diagnosed and non-treated patients with sarcoidosis. Using multiplexed immunoassays, a total of 317 BAL and 217 serum samples were analyzed, including asthmatic patients and healthy individuals as controls. Results Our analyses revealed increased levels of eight proteins in sarcoidosis patients compared to controls. Out of these, fibronectin (FN1) and C-C motif chemokine 2 (CCL2) revealed the strongest associations. In addition, cadherin 5 (CDH5) was found to correlate positively with lymphocyte cell numbers in BAL fluid. Conclusions Applying a high throughput proteomics screening technique, we found proteins of potential clinical relevance in the context of sarcoidosis. Electronic supplementary material The online version of this article (doi:10.1186/s12931-016-0381-0) contains supplementary material, which is available to authorized users.

s / Osteoarthritis and Cartilage 24 (2016) S8eS62 S23 knee criteria and included features related to osteophytes, cartilage damage, bone marrow lesions, subchondral cysts and labral lesions. Logistic regression analysis was used to evaluate the association of FAI with moderate cartilage damage ( 2), moderate BML ( 2) and MRI-OA. Analyses were adjusted for age, sex, body mass index and family history of OA and, in secondary analyses, also for physical activity. Results: Subjects in the MRI study (n 1⁄4 182) had mean age 43.5 years, mean BMI 26.8, mean WOMAC pain 14.4 and 65.4% were female. FAI was present in 48.9% and hip pain in 51.7%. Cartilage score 2, BML 2 and MRI-OA were present in 11.0%, 9.9% and 8.9%, respectively. FAI was not significantly associated with cartilage damage 2 (OR 2.0, 95% CI 0.7e5.5) and this relationship remained non-significant after adjustment for physical activity (OR 1.8, 95% CI 0.6e5.2). There was a statistically significant association of FAI with BML 2 (OR 4.7, 95% CI 1.4e16.0) and with MRI-OA (OR 3.4, 95% CI 1.1e12.3). Additional adjusting for physical activity did not change the findings for BML (OR 4.2, 95% CI 1.4e14.7) and MRI-OA (OR 2.9, 95% CI 0.9e10.6), although the latter was only of borderline statistical significance. Conclusions: In this population-based cross-sectional study of young adults, the risk of moderate BML and MRI-defined OA was significantly increased in subjects with radiographic FAI compared to those without radiographic FAI. No association was found for FAI with moderate cartilage damage. These findings suggest that FAI is linked to early osteoarthritic changes onMRI in young adults. Whether BML is a precursor to future cartilage damage and radiographic OA requires longitudinal evaluation of this cohort. 27 IDENTIFICATION OF A SERUM PROTEIN BIOMARKER PANEL FOR THE DIAGNOSIS OF KNEE OSTEOARTHRITIS L. Lourido y, B. Ayoglu z, J. Fern andez-Tajes x, F. Henjes z, J.M. Schwenk z, C. Ruiz-Romero y, P. Nilsson z, F.J. Blanco y. yRheumatology Div., ProteoRed/ISCIII Proteomics Group, INIBIC e Hospital Universitario de A Coru~ na, Spain; zAffinity Proteomics, SciLifeLab, Sch. of Biotechnology, KTH-Royal Institute of Technology, Stockholm, Sweden; xWellcome Trust Ctr. For Human Genetics, McCarthy's Group, University of Oxford, Oxford, United Kingdom Purpose: Osteoarthritis (OA) is the most common rheumatic disease. Despite the active research in the OA biomarker field, no single protein is sufficiently reliable for its use in OA diagnosis. This is mainly due to the lack of validation studies in large populations, making the findings questionable to be considered as robust biomarkers for the OA joint turnover. In this study we addressed a large-scale study with the aim of search for proteins that could serve as potential indicators of knee OA. Methods: Antibody suspension bead arrays were applied to profile serum samples from patients with knee OA (n 1⁄4 288) with different Kellgren-Lawrence (K/L) scores and compare to patients with rheumatoid arthritis (RA, n 1⁄4 288), psoriatic arthritis (PsA, n 1⁄4 288) and healthy control (n 1⁄4 96) subjects with non-radiographic knee osteoarthritis. The serum protein content was labelled and protein profiles obtained using 174 antibodies from the Human Protein Atlas targeting 78 different proteins. A focused bead array was then built to further profile 46 selected protein targets as a replication of the first findings and also to validate these results in an independent cohort of serum samples composed by patients with OA (n 1⁄4 196), RA (n 1⁄4 192), PsA (n1⁄4 192) and healthy control individuals (n1⁄4 92). The panel of proteins proposed and analysed for this study was selected based on previous internal protein profiling studies in the context of rheumatic diseases. For the statistical analysis, a lineal regression analysis adjusting by sex, age and body mass index (BMI) was applied to observe differences in protein profiles between compared groups and these were denoted statistically significant if they concordantly revealed p.values 2-fold increase in the risk of incident ROA, while sarcopenia alone had no increased risk, compared with those who were non-obese non-sarcopenic (Table 1). This association of obesity persisted after adjustment for body weight. Similar results were

There is a need to further characterize the antibody repertoire in relation to sarcoidosis and potentially related autoantigens.We investigated bronchoalveolar lavage (BAL) and serum samples from patients with sarcoidosis and healthy and diseased control subjects to discover sarcoidosis-associated autoantigens.Antigen microarrays built on 3,072 protein fragments were used to screen for IgG reactivity in 73 BAL samples from subjects with sarcoidosis, subjects with asthma, and healthy subjects. A set of 131 targets were selected for subsequent verification on suspension bead arrays using 272 additional BAL samples and 141 paired sera. Reactivity to four antigens was furthermore analyzed in 22 unprocessed BAL samples from patients with fibrosis and 269 plasma samples from patients diagnosed with myositis.Reactivity toward zinc finger protein 688 and mitochondrial ribosomal protein L43 were discovered with higher frequencies in patients with sarcoidosis, for mitochondrial ribosomal protein L43 especially in patients with non-Löfgren syndrome. Increased reactivity toward nuclear receptor coactivator 2 was also observed in patients with non-Löfgren syndrome as compared with patients with Löfgren syndrome. The antigen representing adenosine diphosphate-ribosylation factor GTPase activating protein 1 revealed high reactivity frequency in all sample groups but with significantly higher level of IgG reactivities in patients with sarcoidosis.Autoantigen reactivity was present in most BAL and serum samples analyzed, and the results revealed high interindividual heterogeneity, with most of the reactivities observed in single individuals only. Four proteins are here proposed as sarcoidosis-associated autoimmune targets and of interest for further validation in independent cohorts.

BackgroundCancer cachexia (CC) is linked to poor prognosis. Although the mechanisms promoting this condition are not known, several circulating proteins have been proposed to contribute. We analyzed the plasma proteome in cancer subjects in order to identify factors associated with cachexia.Design/subjectsPlasma was obtained from a screening cohort of 59 patients, newly diagnosed with suspected gastrointestinal cancer, with (n = 32) or without (n = 27) cachexia. Samples were subjected to proteomic profiling using 760 antibodies (targeting 698 individual proteins) from the Human Protein Atlas project. The main findings were validated in a cohort of 93 patients with verified and advanced pancreas cancer.ResultsOnly six proteins displayed differential plasma levels in the screening cohort. Among these, Carnosine Dipeptidase 1 (CNDP1) was confirmed by sandwich immunoassay to be lower in CC (p = 0.008). In both cohorts, low CNDP1 levels were associated with markers of poor prognosis including weight loss, malnutrition, lipid breakdown, low circulating albumin/IGF1 levels and poor quality of life. Eleven of the subjects in the discovery cohort were finally diagnosed with non-malignant disease but omitting these subjects from the analyses did not have any major influence on the results.ConclusionsIn gastrointestinal cancer, reduced plasma levels of CNDP1 associate with signs of catabolism and poor outcome. These results, together with recently published data demonstrating lower circulating CNDP1 in subjects with glioblastoma and metastatic prostate cancer, suggest that CNDP1 may constitute a marker of aggressive cancer and CC.

Despite the recent progress in the broad-scaled analysis of proteins in body fluids, there is still a lack in protein profiling approaches for biomarkers of rare diseases. Scarcity of samples is the main obstacle hindering attempts to apply discovery driven protein profiling in rare diseases. We addressed this challenge by combining samples collected within the BIO-NMD consortium from four geographically dispersed clinical sites to identify protein markers associated with muscular dystrophy using an antibody bead array platform with 384 antibodies. Based on concordance in statistical significance and confirmatory results obtained from analysis of both serum and plasma, we identified eleven proteins associated with muscular dystrophy, among which four proteins were elevated in blood from muscular dystrophy patients: carbonic anhydrase III (CA3) and myosin light chain 3 (MYL3), both specifically expressed in slow-twitch muscle fibers and mitochondrial malate dehydrogenase 2 (MDH2) and electron transfer flavo-protein A (ETFA). Using age-matched sub-cohorts, 9 protein profiles correlating with disease progression and severity were identified, which hold promise for the development of new clinical tools for management of dystrophinopathies. QC 20140819

With the increasing collection of affinity reagents, their validation in terms of functionality and binding specificity becomes a challenge. To match this growing need, miniaturized and parallelized platforms have become available to corroborate the applicability for a broad range of binder scaffolds. Among the -commonly used systems, planar microarrays have been a platform of choice for a long time but alternative systems are emerging, of which one is based on color-coded beads for the creation of arrays in suspension. The latter systems offer to perform a two-dimensional multiplexing by now analyzing up to 384 samples against up to 500 analytes in a single experiment. While the analyte parameter is flexible in terms of its composition, an extended screening can be facilitated without the need to set up a microarray production facility.

Background Osteoarthritis (OA) is the most common rheumatic disease. To date, the diagnostic methods of OA are very limited and low accurate to detect changes in the joint, what means to wait for a long time to get reliable information about the disease progression. Moreover, there are no available medications capable of halting its characteristic cartilage degradation. Therefore, there is a significant interest to find new biomarkers potentially useful for early diagnosis, prognosis and therapeutic monitoring. Objectives In the present study, we utilize different affinity proteomics approaches for profiling autoantibodies and proteins in a large number of serum samples from OA patients and compare this profile with that observed in control individuals and other rheumatic diseases. Our overall objective is to develop a novel diagnosis method for the high-throughput analysis of OA patients, applicable in clinical practice. Methods We analyzed a total of 960 serum samples from control individuals (Ctrl) and patients with osteoarthritis (OA), rheumatoid arthritis (RA) and psoriatic arthritis (PSA). On one hand, to characterize the autoantibody repertoire from each group of study, we used antigen arrays and NAPPA (Nucleic Acid Programmable Protein Arrays). In the first platform, a total of 3840 protein fragments were analysed and 373 were selected for further validation analysis. Using NAPPA, we studied autoantibodies towards 80 different proteins selected by their relevance in OA pathology. On the other hand, to characterize the different protein profile of these samples, 174 antibodies towards 78 different proteins included in Human Protein Atlas (HPA) were coupled to bead array and screened with the 960-sample set. Results Using antigen array and NAPPA, 15 autoantibodies were identified as potential candidates to distinguish between OA patients, RA patients and controls. In complementary efforts, using antibody arrays, we identified a panel of 12 serum proteins whose levels distinguish between OA patients and controls. Moreover, we identified 34 proteins significantly different between PSA and Ctrl, and a panel of 45 proteins, which distinguish between OA patients and PSA patients. Conclusions Broad-scaled protein profiling of autoantibody repertoires and protein levels in serum enables discovery of potential novel biomarkers in osteoarthritis. Using different protein array formats we have defined interesting marker candidates, which allow distinguishing serum samples from control individuals, OA patients and other rheumatic diseases. These proteins are now brought into the next level of verification where a new cohort of new serum samples will be utilized. Disclosure of Interest None declared