Genetics meets proteomics: perspectives for large population-based studies.

Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.

Elucidating the Interactome of G Protein-Coupled Receptors and Receptor Activity-Modifying Proteins.

G protein-coupled receptors (GPCRs) are known to interact with several other classes of integral membrane proteins that modulate their biology and pharmacology. However, the extent of these interactions and the mechanisms of their effects are not well understood. For example, one class of GPCR-interacting proteins, receptor activity-modifying proteins (RAMPs), comprise three related and ubiquitously expressed single-transmembrane span proteins. The RAMP family was discovered more than two decades ago, and since then GPCR-RAMP interactions and their functional consequences on receptor trafficking and ligand selectivity have been documented for several secretin (class B) GPCRs, most notably the calcitonin receptor-like receptor. Recent bioinformatics and multiplexed experimental studies suggest that GPCR-RAMP interactions might be much more widespread than previously anticipated. Recently, cryo-electron microscopy has provided high-resolution structures of GPCR-RAMP-ligand complexes, and drugs have been developed that target GPCR-RAMP complexes. In this review, we provide a summary of recent advances in techniques that allow the discovery of GPCR-RAMP interactions and their functional consequences and highlight prospects for future advances. We also provide an up-to-date list of reported GPCR-RAMP interactions based on a review of the current literature. SIGNIFICANCE STATEMENT: Receptor activity-modifying proteins (RAMPs) have emerged as modulators of many aspects of G protein-coupled receptor (GPCR)biology and pharmacology. The application of new methodologies to study membrane protein-protein interactions suggests that RAMPs interact with many more GPCRs than had been previously known. These findings, especially when combined with structural studies of membrane protein complexes, have significant implications for advancing GPCR-targeted drug discovery and the understanding of GPCR pharmacology, biology, and regulation.

Role of human plasma metabolites in prediabetes and type 2 diabetes from the IMI-DIRECT study.

AIMS/HYPOTHESIS: Type 2 diabetes is a chronic condition that is caused by hyperglycaemia. Our aim was to characterise the metabolomics to find their association with the glycaemic spectrum and find a causal relationship between metabolites and type 2 diabetes. METHODS: As part of the Innovative Medicines Initiative - Diabetes Research on Patient Stratification (IMI-DIRECT) consortium, 3000 plasma samples were measured with the Biocrates AbsoluteIDQ p150 Kit and Metabolon analytics. A total of 911 metabolites (132 targeted metabolomics, 779 untargeted metabolomics) passed the quality control. Multivariable linear and logistic regression analysis estimates were calculated from the concentration/peak areas of each metabolite as an explanatory variable and the glycaemic status as a dependent variable. This analysis was adjusted for age, sex, BMI, study centre in the basic model, and additionally for alcohol, smoking, BP, fasting HDL-cholesterol and fasting triacylglycerol in the full model. Statistical significance was Bonferroni corrected throughout. Beyond associations, we investigated the mediation effect and causal effects for which causal mediation test and two-sample Mendelian randomisation (2SMR) methods were used, respectively. RESULTS: In the targeted metabolomics, we observed four (15), 34 (99) and 50 (108) metabolites (number of metabolites observed in untargeted metabolomics appear in parentheses) that were significantly different when comparing normal glucose regulation vs impaired glucose regulation/prediabetes, normal glucose regulation vs type 2 diabetes, and impaired glucose regulation vs type 2 diabetes, respectively. Significant metabolites were mainly branched-chain amino acids (BCAAs), with some derivatised BCAAs, lipids, xenobiotics and a few unknowns. Metabolites such as lysophosphatidylcholine a C17:0, sum of hexoses, amino acids from BCAA metabolism (including leucine, isoleucine, valine, N-lactoylvaline, N-lactoylleucine and formiminoglutamate) and lactate, as well as an unknown metabolite (X-24295), were associated with HbA1c progression rate and were significant mediators of type 2 diabetes from baseline to 18 and 48 months of follow-up. 2SMR was used to estimate the causal effect of an exposure on an outcome using summary statistics from UK Biobank genome-wide association studies. We found that type 2 diabetes had a causal effect on the levels of three metabolites (hexose, glutamate and caproate [fatty acid (FA) 6:0]), whereas lipids such as specific phosphatidylcholines (PCs) (namely PC aa C36:2, PC aa C36:5, PC ae C36:3 and PC ae C34:3) as well as the two n-3 fatty acids stearidonate (18:4n3) and docosapentaenoate (22:5n3) potentially had a causal role in the development of type 2 diabetes. CONCLUSIONS/INTERPRETATION: Our findings identify known BCAAs and lipids, along with novel N-lactoyl-amino acid metabolites, significantly associated with prediabetes and diabetes, that mediate the effect of diabetes from baseline to follow-up (18 and 48 months). Causal inference using genetic variants shows the role of lipid metabolism and n-3 fatty acids as being causal for metabolite-to-type 2 diabetes whereas the sum of hexoses is causal for type 2 diabetes-to-metabolite. Identified metabolite markers are useful for stratifying individuals based on their risk progression and should enable targeted interventions.

Itch receptor MRGPRX4 interacts with the receptor activity-modifying proteins.

Cholestatic itch is a severe and debilitating symptom in liver diseases with limited treatment options. The class A G protein-coupled receptor (GPCR) Mas-related GPCR subtype X4 (MRGPRX4) has been identified as a receptor for bile acids, which are potential cholestatic pruritogens. An increasing number of GPCRs have been shown to interact with receptor activity-modifying proteins (RAMPs), which can modulate different aspects of GPCR biology. Using a combination of multiplexed immunoassay and proximity ligation assay, we show that MRGPRX4 interacts with RAMPs. The interaction of MRGPRX4 with RAMP2, but not RAMP1 or 3, causes attenuation of basal and agonist-dependent signaling, which correlates with a decrease of MRGPRX4 cell surface expression as measured using a quantitative NanoBRET pulse-chase assay. Finally, we use AlphaFold Multimer to predict the structure of the MRGPRX4-RAMP2 complex. The discovery that RAMP2 regulates MRGPRX4 may have direct implications for future drug development for cholestatic itch.

The impact of circulating protein levels identified by affinity proteomics on short-term, overall breast cancer risk.

OBJECTIVE: 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. SUBJECTS: In this study, we included 1577 women participating in the prospective KARMA mammographic screening cohort. RESULTS: 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. CONCLUSIONS: 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.

Microfluidic Device for Patient-Centric Multiplexed Assays with Readout in Centralized Laboratories.

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.

A wide scan of plasma proteins demonstrates thioredoxin reductase 1 as a potential new diagnostic biomarker for hepatocellular carcinoma.

BACKGROUND: Patients with liver cirrhosis are recommended ultrasonography screening for early detection of hepatocellular carcinoma to increase the chances of curative treatment. However, ultrasonography alone lacks in sensitivity. Adding plasma biomarkers may increase the detection rate. We performed a broad exploratory analysis to find new plasma proteins with potential applicability for HCC screening in patients with cirrhosis. METHODS: In a protein discovery cohort of 172 patients with cirrhosis or HCC, we screened for 481 proteins with suspension bead array or proximity extension assay. From these, 24 proteins were selected for further analysis in a protein verification cohort (n = 160), using ELISA, Luminex or an electrochemiluminescence platform. A cut-off model and a stepwise logistic regression model were used to find combinations of proteins with the best discriminatory performance between HCC and cirrhosis. RESULTS: Stepwise logistic regression revealed alpha-fetoprotein (AFP), decarboxy-prothrombin (DCP), thioredoxin reductase 1 (TXNRD1), and fibroblast growth factor 21 (FGF21) as the proteins with the best discriminatory performance between HCC and cirrhosis. Adding TXNRD1 to DCP and AFP increased the AUC from 0.844 to 0.878, and combining AFP, DCP and TXNRD1 with age and sex resulted in an AUC of 0.920. FGF21, however, did not further increase the performance when including age and sex. CONCLUSION: In the present study, TXNRD1 improves the sensitivity and specificity of AFP and DCP as HCC screening tools in patients with cirrhosis. We suggest that TXNRD1 should be validated in prospective settings as a new complementary HCC biomarker together with AFP and DCP.

A Longitudinal Study of Individual Radiation Responses in Pediatric Patients Treated with Proton and Photon Radiotherapy, and Interventional Cardiology: Rationale and Research Protocol of the HARMONIC Project.

The Health Effects of Cardiac Fluoroscopy and Modern Radiotherapy (photon and proton) in Pediatrics (HARMONIC) is a five-year project funded by the European Commission that aimed to improve the understanding of the long-term ionizing radiation (IR) risks for pediatric patients. In this paper, we provide a detailed overview of the rationale, design, and methods for the biological aspect of the project with objectives to provide a mechanistic understanding of the molecular pathways involved in the IR response and to identify potential predictive biomarkers of individual response involved in long-term health risks. Biological samples will be collected at three time points: before the first exposure, at the end of the exposure, and one year after the exposure. The average whole-body dose, the dose to the target organ, and the dose to some important out-of-field organs will be estimated. State-of-the-art analytical methods will be used to assess the levels of a set of known biomarkers and also explore high-resolution approaches of proteomics and miRNA transcriptomes to provide an integrated assessment. By using bioinformatics and systems biology, biological pathways and novel pathways involved in the response to IR exposure will be deciphered.

Combined metabolic activators therapy ameliorates liver fat in nonalcoholic fatty liver disease patients.

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 (CMAs) 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 metagenomic 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 showed that CMA can be used to develop a pharmacological treatment strategy in NAFLD patients.

Identification of Endothelial Proteins in Plasma Associated With Cardiovascular Risk Factors.

OBJECTIVE: Endothelial cell (EC) dysfunction is a well-established response to cardiovascular disease risk factors, such as smoking and obesity. Risk factor exposure can modify EC signaling and behavior, leading to arterial and venous disease development. Here, we aimed to identify biomarker panels for the assessment of EC dysfunction, which could be useful for risk stratification or to monitor treatment response. Approach and Results: We used affinity proteomics to identify EC proteins circulating in plasma that were associated with cardiovascular disease risk factor exposure. Two hundred sixteen proteins, which we previously predicted to be EC-enriched across vascular beds, were measured in plasma samples (N=1005) from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study) pilot. Thirty-eight of these proteins were associated with body mass index, total cholesterol, low-density lipoprotein, smoking, hypertension, or diabetes. Sex-specific analysis revealed that associations predominantly observed in female- or male-only samples were most frequently with the risk factors body mass index, or total cholesterol and smoking, respectively. We show a relationship between individual cardiovascular disease risk, calculated with the Framingham risk score, and the corresponding biomarker profiles. CONCLUSIONS: EC proteins in plasma could reflect vascular health status.

Advances and Utility of the Human Plasma Proteome.

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

Correction to: The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes: an IMI DIRECT study.

Unfortunately, 'Present address' was omitted from one of the addresses provided for Mark I. McCarthy (#26).

Circulating proteins associated with allergy development in infants-an exploratory analysis.

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.

Enhanced Validation of Antibodies Enables the Discovery of Missing Proteins.

The localization of proteins at a tissue- or cell-type-specific level is tightly linked to the protein function. To better understand each protein's role in cellular systems, spatial information constitutes an important complement to quantitative data. The standard methods for determining the spatial distribution of proteins in single cells of complex tissue samples make use of antibodies. For a stringent analysis of the human proteome, we used orthogonal methods and independent antibodies to validate 5981 antibodies that show the expression of 3775 human proteins across all major human tissues. This enhanced validation uncovered 56 proteins corresponding to the group of "missing proteins" and 171 proteins of unknown function. The presented strategy will facilitate further discussions around criteria for evidence of protein existence based on immunohistochemistry and serves as a useful guide to identify candidate proteins for integrative studies with quantitative proteomics methods.

The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes: an IMI DIRECT study.

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.

Systematic Development of Sandwich Immunoassays for the Plasma Secretome.

The plasma proteome offers a clinically useful window into human health. Recent advances from highly multiplexed assays now call for appropriate pipelines to validate individual candidates. Here, a workflow is developed to build dual binder sandwich immunoassays (SIA) and for proteins predicted to be secreted into plasma. Utilizing suspension bead arrays, ≈1800 unique antibody pairs are first screened against 209 proteins with recombinant proteins as well as EDTA plasma. Employing 624 unique antibodies, dilution-dependent curves in plasma and concentration-dependent curves of full-length proteins for 102 (49%) of the targets are obtained. For 22 protein assays, the longitudinal, interindividual, and technical performance is determined in a set of plasma samples collected from 18 healthy subjects every third month over 1 year. Finally, 14 of these assays are compared with with SIAs composed of other binders, proximity extension assays, and affinity-free targeted mass spectrometry. The workflow provides a multiplexed approach to screen for SIA pairs that suggests using at least three antibodies per target. This design is applicable for a wider range of targets of the plasma proteome, and the assays can be applied for discovery but also to validate emerging candidates derived from other platforms.

Screening a Resource of Recombinant Protein Fragments for Targeted Proteomics.

The availability of proteomics resources hosting protein and peptide standards, as well as the data describing their analytical performances, will continue to enhance our current capabilities to develop targeted proteomics methods for quantitative biology. This study describes the analysis of a resource of 26,840 individually purified recombinant protein fragments corresponding to more than 16,000 human protein-coding genes. The resource was screened to identify proteotypic peptides suitable for targeted proteomics efforts, and we report LC-MS/MS assay coordinates for more than 25,000 proteotypic peptides, corresponding to more than 10,000 unique proteins. Additionally, peptide formation and digestion kinetics were, for a subset of the standards, monitored using a time-course protocol involving parallel digestion of isotope-labeled recombinant protein standards and endogenous human plasma proteins. We show that the strategy by adding isotope-labeled recombinant proteins before trypsin digestion enables short digestion protocols (≤60 min) with robust quantitative precision. In a proof-of-concept study, we quantified 23 proteins in human plasma using assay parameters defined in our study and used the standards to describe distinct clusters of individuals linked to different levels of LPA, APOE, SERPINA5, and TFRC. In summary, we describe the use and utility of a resource of recombinant proteins to identify proteotypic peptides useful for targeted proteomics assay development.

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data.

The proteomic analysis of human blood and blood-derived products (e.g., plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g., interindividual variability) and analysis of biospecimens (e.g., sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing, and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest while enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.

Progress on Identifying and Characterizing the Human Proteome: 2019 Metrics from the HUPO Human Proteome Project.

The Human Proteome Project (HPP) annually reports on progress made throughout the field in credibly identifying and characterizing the complete human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2019-01-11 contains 17 694 proteins with strong protein-level evidence (PE1), compliant with HPP Guidelines for Interpretation of MS Data v2.1; these represent 89% of all 19 823 neXtProt predicted coding genes (all PE1,2,3,4 proteins), up from 17 470 one year earlier. Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), has been reduced from 2949 to 2129 since 2016 through efforts throughout the community, including the chromosome-centric HPP. PeptideAtlas is the source of uniformly reanalyzed raw mass spectrometry data for neXtProt; PeptideAtlas added 495 canonical proteins between 2018 and 2019, especially from studies designed to detect hard-to-identify proteins. Meanwhile, the Human Protein Atlas has released version 18.1 with immunohistochemical evidence of expression of 17 000 proteins and survival plots as part of the Pathology Atlas. Many investigators apply multiplexed SRM-targeted proteomics for quantitation of organ-specific popular proteins in studies of various human diseases. The 19 teams of the Biology and Disease-driven B/D-HPP published a total of 160 publications in 2018, bringing proteomics to a broad array of biomedical research.

Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium.

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.