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BackgroundPrecision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D).MethodsWe conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that could improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies.Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination on internal validation, with lower performance on external validation.ConclusionsDespite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.Plain Language SummaryPatients with T2D are at high risk for CVD but predicting who will experience a cardiac event is challenging. Current risk tools and prognostic factors, such as laboratory tests, may not accurately predict risk in different patient populations. There is a need for personalized risk prediction tools to identify patients more accurately so that CVD prevention can be targeted to those who need it most. This study examined novel biomarkers, genetic markers, and risk scores on the prediction of CVD in individuals with T2D. We found that four laboratory markers and a genetic risk score for CHD had high predictive utility beyond traditional CVD risk factors and that risk scores had modest predictive utility when tested in diverse populations, but more studies are needed to determine their usefulness in clinical practice. The highest strength of evidence was observed for NT-proBNP, a laboratory test currently used to monitor patients with heart failure but not currently used in clinical practice for the purpose of CVD prediction in T2D.

Data analyses from Swedish individuals with newly diagnosed diabetes have suggested that diabetes could be classified into five subtypes that differ with respect to the progression of dysglycaemia and the incidence of diabetes consequences. We assessed this classification in a multiethnic cohort of participants with established and newly diagnosed diabetes, randomly allocated to insulin glargine vs standard care. In total, 7017 participants from the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial were assigned to the five predefined diabetes subtypes (namely, severe auto-immune diabetes, severe insulin-deficient diabetes, severe insulin-resistant diabetes, mild obesity-related diabetes, mild age-related diabetes) based on the age at diabetes diagnosis, BMI, HbA1c, fasting C-peptide levels and the presence of glutamate decarboxylase antibodies at baseline. Differences between diabetes subtypes in cardiovascular and renal outcomes were investigated using Cox regression models for a median follow-up of 6.2 years. We also compared the effect of glargine vs standard care on hyperglycaemia, defined by having a mean post-randomisation HbA1c ≥6.5%, between subtypes. The five diabetes subtypes were replicated in the ORIGIN trial and exhibited similar baseline characteristics in Europeans and Latin Americans, compared with the initially described clusters in the Swedish cohort. We confirmed differences in renal outcomes, with a higher incidence of events in the severe insulin-resistant diabetes subtype compared with the mild age-related diabetes subtype (i.e., chronic kidney disease stage 3A: HR 1.49 [95% CI 1.31, 1.71]; stage 3B: HR 2.25 [1.82, 2.78]; macroalbuminuria: HR 1.56 [1.22, 1.99]). No differences were observed in the incidence of retinopathy and cardiovascular diseases after adjusting for multiple hypothesis testing. Diabetes subtypes also differed in glycaemic response to glargine, with a particular benefit of receiving glargine (vs standard care) in the severe insulin-deficient diabetes subtype compared with the mild age-related diabetes subtype, with a decreased occurrence of hyperglycaemia by 13% (OR 1.36 [1.30, 1.41] on glargine; OR 1.49 [1.43, 1.57] on standard care; p for interaction subtype × intervention = 0.001). Cluster analysis enabled the characterisation of five subtypes of diabetes in a multiethnic cohort. Both the incidence of renal outcomes and the response to insulin varied between diabetes subtypes. These findings reinforce the clinical utility of applying precision medicine to predict comorbidities and treatment responses in individuals with diabetes. ORIGIN trial, ClinicalTrials.gov NCT00069784.

BackgroundWhile the incidence of newly diagnosed early-onset colorectal cancer has been increasing, age-related disparity of survival outcome and treatment-related adverse events in patients with metastatic CRC (mCRC) has been inadequately studied with inconclusive findings. In this study, we aimed to evaluate such age-related disparity in this patient population.MethodsWe used individual patient data from three clinical trials (Study 1:NCT00272051, NCT 00305188 and Study 2:NCT00364013) in Project Data Sphere. All patients were diagnosed with mCRC and received first-line 5-fluorouracil and oxaliplatin. Clinical and genomic data of 763 patients with mCRC from Moffitt Cancer Center were used to assess genomic alterations and serve as an external and real-world validation cohort to evaluate overall survival (OS) disparity. Survival outcomes and treatment-related adverse events were estimated and compared in patients among three age groups: 65 years.ResultsAmong 1223 patients from previous clinical trials, 179 (14.6%) were younger than 50 years. These patients had significantly shorter progression-free survival (PFS) (HR=1.46; 95%CI=1.22–1.76;ppp=0.019), severe abdominal pain (8.4% vs 3.4% vs 3.5%,p=0.018), severe anemia (6.1% vs 1.0% vs 1.5%,pp=0.047), but significantly lower incidence of fatigue, severe diarrhea, severe fatigue, and severe neutropenia. The p=0.012), mucositis (3.6 vs 5.1 vs 5.7 weeks,p=0.051), and neutropenia (8.0 vs 9.4 vs 8.4 weeks,p=0.043), and shorter duration of mucositis (0.6 vs 0.9 vs 1.0 weeks,p=0.006). In the CTNNB1mutation (6.6% vs 3.1% vs 2.3%,p=0.047),ERBB2amplification (5.1% vs 0.6% vs 2.3%,p=0.005), andCREBBPmutation (3.1% vs 0.9% vs 0.5%,p=0.050), but lower prevalence ofBRAFmutation (7.7% vs 8.5% vs 16.7%,p=0.002).ConclusionsPatients with early-onset mCRC had worse survival outcome and unique adverse-event patterns, which could be partially attributed to distinct genomic profiles. Our findings might improve an individualized approach to chemotherapy, counseling, and management of treatment-related adverse events in this patient population.

The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data. Funding Agencies|SciLifeLab; Swedish Research Council (Vetenskapsradet)Swedish Research Council [D0886501]; US National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [MH077139, MH1095320]; European UnionEuropean Commission [610307, 733161, 825843]; Swedish Cancer SocietySwedish Cancer Society; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2018-02837, 2014-03352, 2009-1039, 2018-03307]; Knut and Alice Wallenberg FoundationKnut & Alice Wallenberg Foundation; Karolinska Institutet, Karolinska University HospitalKarolinska Institutet; Radiumhemmets Forskningsfonder; European Research CouncilEuropean Research Council (ERC)European Commission [CoG-2015_681742_NASCENT]; Swedish Heart-Lung FoundationSwedish Heart-Lung Foundation [20160872]; Swedish Foundation for Strategic Research (IRC Center); Novo Nordisk FoundationNovo Nordisk FoundationNovocure Limited; ALF; Strategic Research Area Epidemiology at Karolinska Institutet; Swedish Rheumatism Association; Vth 80-year Foundation; Swedish Society of Medicine; Clinical Research Support (Avtal om Lakarutbildning och Forskning); Swedish government; county councils; ALF-agreement; Swedish Foundation for Strategic ResearchSwedish Foundation for Strategic Research [15-0067]; IMI2 Joint Undertaking [115974]; European Federation of Pharmaceutical Industries and Associations with JDRF; H2020 Program ERA PerMed JTC 2018 Call (VR) [2018-05619]

Background: Colorectal cancer (CRC) is a complex and heterogeneous disease characterized by distinct molecular features such as RAS and BRAF mutations. Assessing these molecular aberrations provides clinical guidance for selecting and predicting response with therapeutic modalities. Few reports have suggested that patient symptom burden at diagnosis differs across molecular subtypes of CRC. However, the association of RAS and BRAF mutations and symptom burden post-diagnosis in CRC patients has yet to be examined in a prospective cohort. Methods: We assessed CRC patients, stage I-IV, enrolled in the Moffitt ColoCare Study site with clinical molecular testing results and who completed a six-month questionnaire. Tumor mutation (MT) status (RAS/BRAF/Wildtype (WT)) was abstracted from the medical record. The MD Anderson Symptom Inventory (MDASI) was used to assess the severity of 13 cancer-related symptoms on a 1-to-10 scale. Mean scores in mutation subgroups were compared with one-way ANOVA. Linear regression analysis evaluated the association between symptom burden and mutation status. Multivariable regression models were adjusted for age, sex, stage at diagnosis, treatment, and microsatellite instability (MSI). Results: Among the 158 patients, the mean age at diagnosis was 60.9 ± 11.58 years. The prevalence of RAS and BRAF mutations was 30.4% (N=48) and 6.3% (N=10), respectively. Statistically significant mean differences between the mutation subgroups were distress (p=0.005), difficulty remembering (p=0.015), lack of appetite (p=0.042), and sadness (p=0.007). Patients with a BRAF-MT reported significantly more distress (p=0.001), difficulty remembering (p=0.029), and sadness (p=0.002) at six months compared to RAS-MT or RAS/BRAF-WT. Patients with a RAS-MT reported an increased lack of appetite (p=0.038) compared to BRAF-MT or RAS/BRAF-WT. Patients with a BRAF-MT reported higher severity of symptoms interfering with the enjoyment of life (p Conclusions: Tumors with BRAF-MT are molecularly classified into the serrated pathway, which has distinct clinical characteristics and risk factor profile. In this study, patients with tumors harboring BRAF-MT reported a higher symptom burden six months post-diagnosis than those with RAS-MT or RAS/BRAF-WT tumors. While the prevalence of BRAF-MT was low in this population, these findings warrant further investigation in a larger cohort. Citation Format: Gazelle Rouhani, Amanda M. Bloomer, Maria F. Gomez, Gillian K. Trujillo, Devon N. Conant, Seth I. Felder, Cornelia M. Ulrich, Christopher I. Li, Jane C. Figueiredo, Adetunji T. Toriola, Biljana Gigic, Martin Schneider, David Shibata, Erin M. Siegel. Profiling symptom burden of RAS and BRAF mutations in patients with colorectal cancer: Results from the ColoCare Study. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4205.

Background: The gut microbiome (GM) and the metabolites it produces and regulates, such as bile acids (BAs), may act individually or interact to influence colorectal cancer development. We used data from a multi-center screening study to investigate the associations of the normal colon tissue microbiome and circulating BAs with colorectal adenoma. Methods: We used data from the multi-center Colorectal Neoplasia Screening with Colonoscopy in Average-Risk Women Regional Navy/Army Medical Centers study (CONCeRN), comprising women undergoing complete colonoscopies. We individually matched women with adenoma (n=165 cases) to those without adenoma (n=311 controls). We extracted DNA using the Animal Tissue DNA Extraction Kit (AutoGene) and sequenced the V4 region of the 16S rRNA gene to characterize normal colonic mucosal bacteria, including alpha and beta diversity, taxonomic abundance, and co-abundance groups (CAGs). Fasting serum collected before colonoscopy underwent targeted quantitative liquid chromatography-tandem mass spectrometry to measure 13 primary and secondary BAs. We used multivariable conditional logistic regression, partial Pearson’s correlations, and linear regression to estimate interrelationships among the GM, BAs, and adenoma. Results: Multiple genera were statistically significantly associated with adenomas. For example, for the centered log-ratio transformed relative abundance of Phascolarctobacterium, Parvimonas, and Porphymonas, the ORs (95% CIs) were 0.75 (0.60-0.95, P=0.02), 0.71 (0.55-0.92; P=0.01), and 0.67 (0.49-0.93; P=0.02), respectively. A CAG comprising phylum Firmicutes, Actinobacteria, Proteobacteria, and Fusobacteria was less abundant among cases than controls (log2folddiff=-0.80, P=0.002). Alpha and beta diversity associations were close to null and not statistically significant. However, alpha diversity metrics were inversely associated with primary BAs [e.g., for Shannon (R2=-0.13, P=0.01)] and positively associated with secondary BAs [e.g., for Shannon (R2=0.16, P=0.001)]. Though no circulating BAs were statistically significantly associated with adenomas, those in the highest relative to lowest tertile of taurine-conjugated (TC) BAs, primary BAs, and secondary BAs had a 44% (95% CI: 0.85-2.46), 24% (95% CI: 0.73-2.12), and 11% (95% CI: 0.61-2.01) higher odds of adenoma, respectively. We found that TCBAs, primary BAs, and secondary BAs were inversely associated with the abundance of Parvimonas [e.g., for TCBAs (R2=-0.11, P=0.02)] and Porphyromonas [e.g., for TCBAs (R2=-0.11, P=0.02)]. Conclusions: We found short-chain fatty acid-producing and oral-originating bacteria were inversely associated with adenomas. Our oral bacteria findings are contrary to findings from prior studies. Our findings suggest potential interrelationships among the GM and BAs in adenoma development. Citation Format: Maria F. Gomez, Doratha A. Byrd, Stephanie R. Hogue, Jessica R. Burns, Nathan Smith, Joshua Sampson, Erikka Loftfield, Andrew Warner, Casey Dagnall, Kristine Jones, Belynda Hicks, Yunhu Wan, Youngchul Kim, Jin Xu, Rashmi Sinha, Emily Vogtmann. Associations of the mucosal microbiome and circulating bile acids with colorectal adenoma among average-risk women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3055.

Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called ‘long COVID’, are rising but little is known about prevalence, risk factors or whether it is possible to predict a protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app1. A total of 558 (13.3%) participants reported symptoms lasting ≥28 days, 189 (4.5%) for ≥8 weeks and 95 (2.3%) for ≥12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76-4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services.

Background and aims Dipeptidyl peptidase 4 (DPP-4) inhibitors have anti-inflammatory and atheroprotective effects. We evaluated the effects of the DPP-4 inhibitor linagliptin on atherosclerotic plaque and hepatic inflammation using histology and 2-deoxy-2-[18F]-fluoro- d -glucose (18F-FDG), a positron emission tomography tracer of inflammation, in a mouse model of hypercholesterolemia and type 2 diabetes. Methods Igf2/Ldlr−/−Apob100/100 mice were fed a high-fat diet (HFD) for 8 weeks and then randomly allocated to receive HFD (n = 14), or HFD with added linagliptin (n = 15) for additional 12 weeks. Five mice fed a chow diet were studied as an additional control. At the end of the study, glucose tolerance, aortic and liver uptake of 18F-FDG, and histology were studied. Results Mice in linagliptin and HFD groups had similar fasting glucose concentrations, but linagliptin improved glucose tolerance. Aortas of linagliptin and HFD groups showed advanced atherosclerotic plaques with no difference in the mean intima-to-media ratio or number of macrophages in the plaques. Autoradiography showed similar 18F-FDG uptake by atherosclerotic plaques in linagliptin and HFD groups (plaque-to-wall ratio: 1.7 ± 0.25 vs. 1.6 ± 0.21; p = 0.24). In the liver, linagliptin reduced the histologic inflammation score but had no effect on 18F-FDG uptake. Compared with chow diet, uptake of 18F-FDG was similar in the aorta, but higher in the liver after HFD. Conclusions Linagliptin therapy improved glucose tolerance and reduced hepatic inflammation but had no effect on plaque burden or atherosclerotic inflammation, as determined by histology and 18F-FDG uptake, in atherosclerotic mice with type 2 diabetes.

The QUIJOTE Experiment was developed to study the polarization in the Cosmic Microwave Background (CMB) over the frequency range of 10-50 GHz. Its first instrument, the Multi Frequency Instrument (MFI), measures in the range 10-20 GHz which coincides with one of the naturally transparent windows in the atmosphere. The Tenerife Microwave Spectrometer (TMS) has been designed to investigate the spectrum between 10-20 GHz in more detail. The MFI bands are 2 GHz wide whereas the TMS bands will be 250 MHz wide covering the complete 10-20 GHz range with one receiver chain and Fourier spectral filter bank. It is expected that the relative calibration between frequency bands will be better known than the MFI channels and that the higher resolution will provide essential information on narrow band interference and features such as ozone. The TMS will study the atmospheric spectra as well as provide key information on the viability of ground-based absolute spectral measurements. Here the novel Fourier transform spectrometer design is described showing its suitability to wide band measurement and $\sqrt{N}$ advantage over the usual scanning techniques., 8 pages, 10 figures. Accepted for publication in TIM

Central to the development of diabetic macro- and microvascular disease is endothelial dysfunction, which appears well before any clinical sign but, importantly, is potentially reversible. We previously demonstrated that hyperglycemia activates nuclear factor of activated T cells (NFAT) in conduit and medium-sized resistance arteries and that NFAT blockade abolishes diabetes-driven aggravation of atherosclerosis. In this study, we test whether NFAT plays a role in the development of endothelial dysfunction in diabetes. NFAT-dependent transcriptional activity was elevated in skin microvessels of diabetic Akita (Ins2+/−) mice when compared with nondiabetic littermates. Treatment of diabetic mice with the NFAT blocker A-285222 reduced NFATc3 nuclear accumulation and NFAT-luciferase transcriptional activity in skin microvessels, resulting in improved microvascular function, as assessed by laser Doppler imaging and iontophoresis of acetylcholine and localized heating. This improvement was abolished by pretreatment with the nitric oxide (NO) synthase inhibitor l-NG-nitro-l-arginine methyl ester, while iontophoresis of the NO donor sodium nitroprusside eliminated the observed differences. A-285222 treatment enhanced dermis endothelial NO synthase expression and plasma NO levels of diabetic mice. It also prevented induction of inflammatory cytokines interleukin-6 and osteopontin, lowered plasma endothelin-1 and blood pressure, and improved mouse survival without affecting blood glucose. In vivo inhibition of NFAT may represent a novel therapeutic modality to preserve endothelial function in diabetes.

Exocytosis in excitable cells is essential for their physiological functions. Although the exocytotic machinery controlling cellular secretion has been well investigated, the function of the vesicular cargo, i.e. secretory granular content remains obscure. Here we combine dSTORM imaging and single-domain insulin antibody, to dissect the in situ structure of insulin granule cores (IGCs) at nano level. We demonstrate that the size and shape of the IGCs can be regulated by the juxta-granular molecules Nucleobindin-2 and Enolase-1, that further contribute to the stimulated insulin secretion. IGCs located at the plasma membrane are larger than those in the cytosol. The IGCs size is decreased by ∼20% after glucose stimulation due to the release of the peripheral part of IGCs through incomplete granule fusion. Importantly, the reduction of the IGCs size is also observed in non-stimulatory pancreatic β-cells from diabetic db/db mice, Akita (Ins2+/-) mice and human Type-2 diabetic donors, in accordance with impaired secretion. These findings overall highlight the structure of exocytotic insulin cores as a novel modality amenable to targeting in the stimulated exocytosis in β-cells with impaired insulin secretion.

Background This article investigates the impact of a non-mandatory and age-specific social distancing recommendation on isolation behaviours and disease outcomes in Sweden during the first wave of the coronavirus disease 2019 (COVID-19) pandemic (March to July 2020). The policy stated that people aged 70 years or older should avoid crowded places and contact with people outside the household. Methods We used a regression discontinuity design—in combination with self-reported isolation data from COVID Symptom Study Sweden (n = 96 053; age range: 39–79 years) and national register data (age range: 39–100+ years) on severe COVID-19 disease (hospitalization or death, n = 21 804) and confirmed cases (n = 48 984)—to estimate the effects of the policy. Results Our primary analyses showed a sharp drop in the weekly number of visits to crowded places (−13%) and severe COVID-19 cases (−16%) at the 70-year threshold. These results imply that the age-specific recommendations prevented approximately 1800–2700 severe COVID-19 cases, depending on model specification. Conclusions It seems that the non-mandatory, age-specific recommendations helped control COVID-19 disease during the first wave of the pandemic in Sweden, as opposed to not implementing a social distancing policy aimed at older adults. Our study provides empirical data on how populations may react to non-mandatory, age-specific social distancing policies in the face of a novel virus.

Skeletal muscle fiber composition and capillary density influence physical performance and whole-body metabolic properties. ~45% of the variance in fiber type is heritable, which motivated us to perform a genome-wide association study of skeletal muscle histology from 656 Swedish men. Four independent variants were associated (p − 8) with proportion of type IIx fibers or capillary-to-fiber ratio (C:F). The strongest signal localized to the rs115660502 variant, where the G-allele corresponded with increased C:F and reduced skeletal muscle expression of the proximal gene, RAB3 GTPase Activating Non-Catalytic Protein Subunit 2 (RAB3GAP2). The G-allele was less frequent in elite short-track sprinters and more frequent in endurance athletes than in matched non-athlete (population) controls; RAB3GAP2 expression was reduced by high-intensity intermittent training. RAB3GAP2 protein was not uniformly expressed in muscle tissue but localized to the endothelium and capillaries. Experimental reduction of RAB3GAP2 in human endothelial cells led to increased tube formation in vitro, to regulation of secreted factors promoting angiogenesis and T-cell activation, to reduced intracellular levels of von Willebrand factor (VWF) and, post-implantation, to increased endothelial cell density in vivo in mice. The amount of RAB3GAP2 in skeletal muscle was positively associated with exercise-induced release of VWF in vivo in humans. By regulating the release of protein factors (VWF, CD70, TNC, TNXB, MCP1, IGFBP3, COL1A1, TFPI2 and tPA), RAB3GAP2 influences fitness adaptation after exercise by improving muscle healing and promotion of capillary formation.

Clinical risk factors explain only a fraction of the variability of estimated glomerular filtration rate (eGFR) decline in people with type 2 diabetes. Cross-omics technologies by virtue of a wide spectrum screening of plasma samples have the potential to identify biomarkers for the refinement of prognosis in addition to clinical variables. Here we utilized proteomics, metabolomics and lipidomics panel assay measurements in baseline plasma samples from the multinational PROVALID study (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers) of patients with incident or early chronic kidney disease (median follow-up 35 months, median baseline eGFR 84 mL/min/1.73 m(2), urine albumin-to-creatinine ratio 8.1 mg/g). In an accelerated case-control study, 258 individuals with a stable eGFR course (median eGFR change 0.1 mL/min/year) were compared to 223 individuals with a rapid eGFR decline (median eGFR decline -6.75 mL/min/year) using Bayesian multivariable logistic regression models to assess the discrimination of eGFR trajectories. The analysis included 402 candidate predictors and showed two protein markers (KIM-1, NTproBNP) to be relevant predictors of the eGFR trajectory with baseline eGFR being an important clinical covariate. The inclusion of metabolomic and lipidomic platforms did not improve discrimination substantially. Predictions using all available variables were statistically indistinguishable from predictions using only KIM-1 and baseline eGFR (area under the receiver operating characteristic curve 0.63). Thus, the discrimination of eGFR trajectories in patients with incident or early diabetic kidney disease and maintained baseline eGFR was modest and the protein marker KIM-1 was the most important predictor.

Fecal specimen collection in the clinical setting is often unfeasible for large population studies, especially because cancer patients on immunotherapy often experience constipation. A method for constructing and using an at-home stool collection kit designed for epidemiological studies in cancer patients is presented. Participation and compliance rates of the collection kit among late-stage cancer patients from an ongoing, longitudinal study are also discussed. The kit includes three different media on which samples are introduced. Using one stool sample, patients collect specimens by smearing stool onto a fecal occult blood test (FOBT) card, containing three slides for collection. Additional specimens from the same stool sample are added to one tube containing 8 mL of RNAlater preservative and one tube containing 8 mL of 95% ethanol. Stool specimens are stored at room temperature and returned to researchers within 3 days of collection. The purpose of this kit is to yield stool specimens on a variety of media that can be preserved for extended periods of time at room temperature and are compatible with multi-omics approaches for specimen analysis. According to leading microbiome researchers and published literature, each collection method is considered optimal for use in large epidemiological studies. Moreover, the kit is comprised of various components that make stool collection easy, so as not to burden the patient and hence maximize overall compliance. Use of this kit in a study of late-stage lung cancer patients had a participation rate of 83% and baseline compliance rate of 58%. Electronic supplementary material The online version of this article (10.1007/s00248-019-01346-2) contains supplementary material, which is available to authorized users.

BackgroundThe response of the Swedish authorities to the COVID-19 pandemic was less restrictive than in most countries during the first year, with infection and death rates substantially higher than in neighbouring Nordic countries. Because access to PCR testing was limited during the first wave (February to June 2020) and regional data were reported with delay, adequate monitoring of community disease spread was hampered. The app-based COVID Symptom Study was launched in Sweden to disseminate real-time estimates of disease spread and to collect prospective data for research. The aim of this study was to describe the research project, develop models for estimation of COVID-19 prevalence and to evaluate it for prediction of hospital admissions for COVID-19. MethodsWe enrolled 143 531 study participants ([≥]18 years) throughout Sweden, who contributed 10{middle dot}6 million daily symptom reports between April 29, 2020 and February 10, 2021. Data from 19 161 self-reported PCR tests were used to create a symptom-based algorithm to estimate daily prevalence of symptomatic COVID-19. The prediction model was validated using external datasets. We further utilized the model estimates to forecast subsequent new hospital admissions. FindingsA prediction model for symptomatic COVID-19 based on 17 symptoms, age, and sex yielded an area under the ROC curve of 0{middle dot}78 (95% CI 0{middle dot}74-0{middle dot}83) in an external validation dataset of 943 PCR-tested symptomatic individuals. App-based surveillance proved particularly useful for predicting hospital trends in times of insufficient testing capacity and registration delays. During the first wave, our prediction model estimates demonstrated a lower mean error (0{middle dot}38 average new daily hospitalizations per 100 000 inhabitants per week (95% CI 0{middle dot}32, 0{middle dot}45)) for subsequent hospitalizations in the ten most populated counties, than a model based on confirmed case data (0{middle dot}72 (0{middle dot}64, 0{middle dot}81)). The model further correctly identified on average three out of five counties (95% CI 2{middle dot}3, 3{middle dot}7) with the highest rates of hospitalizations the following week during the first wave and four out of five (3{middle dot}0, 4{middle dot}6) during the second wave. InterpretationThe experience of the COVID Symptom Study highlights the important role citizens can play in real-time monitoring of infectious diseases, and how app-based data collection may be used for data-driven rapid responses to public health challenges. FundingSwedish Heart-Lung Foundation (20190470, 20140776), Swedish Research Council (EXODIAB, 2009-1039; 2014-03529), European Commission (ERC-2015-CoG - 681742 NASCENT), and Swedish Foundation for Strategic Research (LUDC-IRC, 15-0067) to MG or PF. European Research Council Starting Grant (801965) to TF. NO was financially supported by the Knut and Alice Wallenberg Foundation as part of the National Bioinformatics Infrastructure Sweden at SciLifeLab. ATC was supported in this work through the Massachusetts Consortium on Pathogen Readiness (MassCPR). ZOE Limited provided in-kind support for all aspects of building, running and supporting the app and service to all users worldwide. Support for this study for KCL researchers was provided by the National Institute for Health Research (NIHR)-funded Biomedical Research Centre based at Guys and St Thomas (GSTT) NHS Foundation Trust. This work was supported by the UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value-Based Healthcare. Investigators also received support from the Wellcome Trust, Medical Research Council (MRC), British Heart Foundation (BHF), Alzheimers Society, European Union, NIHR, COVID-19 Driver Relief Fund (CDRF) and the NIHR-funded BioResource, Clinical Research Facility and Biomedical Research Centre (BRC) based at GSTT NHS Foundation Trust in partnership with KCL. ZOE Limited developed the app for data collection as a not-for-profit endeavour. None of the funding entities had any role in study design, data analysis, data interpretation, or the writing of this manuscript.

Early reports raised concern that use of non-steroidal anti-inflammatory drugs (NSAIDs) may increase risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19). Users of the COVID Symptom Study smartphone application reported use of aspirin and other NSAIDs between March 24 and May 8, 2020. Users were queried daily about symptoms, COVID-19 testing, and healthcare seeking behavior. Cox proportional hazards regression was used to determine the risk of COVID-19 among according to aspirin or non-aspirin NSAID users. Among 2,736,091 individuals in the U.S., U.K., and Sweden, we documented 8,966 incident reports of a positive COVID-19 test over 60,817,043 person-days of follow-up. Compared to non-users and after stratifying by age, sex, country, day of study entry, and race/ethnicity, non-aspirin NSAID use was associated with a modest risk for testing COVID-19 positive (HR 1.23 [1.09, 1.32]), but no significant association was observed among aspirin users (HR 1.13 [0.92, 1.38]). After adjustment for lifestyle factors, comorbidities and baseline symptoms, any NSAID use was not associated with risk (HR 1.02 [0.94, 1.10]). Results were similar for those seeking healthcare for COVID-19 and were not substantially different according to lifestyle and sociodemographic factors or after accounting for propensity to receive testing. Our results do not support an association of NSAID use, including aspirin, with COVID-19 infection. Previous reports of a potential association may be due to higher rates of comorbidities or use of NSAIDs to treat symptoms associated with COVID-19.One Sentence SummaryNSAID use is not associated with COVID-19 risk.

Individuals with cancer may be at high risk for coronavirus disease 2019 (COVID-19) and adverse outcomes. However, evidence from large population-based studies examining whether cancer and cancer-related therapy exacerbates the risk of COVID-19 infection is still limited. Data were collected from the COVID Symptom Study smartphone application since March 29 through May 8, 2020. Among 23,266 participants with cancer and 1,784,293 without cancer, we documented 10,404 reports of a positive COVID-19 test. Compared with participants without cancer, those living with cancer had a 60% increased risk of a positive COVID-19 test. Among patients with cancer, current treatment with chemotherapy or immunotherapy was associated with a 2.2-fold increased risk of a positive test. The association between cancer and COVID-19 infection was stronger among participants >65 years and males. Future studies are needed to identify subgroups by tumor types and treatment regimens who are particularly at risk for COVID-19 infection and adverse outcomes.

BackgroundAs many countries seek to slow the spread of COVID-19 without reimposing national restrictions, it has become important to track the disease at a local level to identify areas in need of targeted intervention.MethodsWe performed modelling on longitudinal, self-reported data from users of the COVID Symptom Study app in England between 24 March and 29 September, 2020. Combining a symptom-based predictive model for COVID-19 positivity and RT-PCR tests provided by the Department of Health we were able to estimate disease incidence, prevalence and effective reproduction number. Geographically granular estimates were used to highlight regions with rapidly increasing case numbers, or hotspots.FindingsMore than 2.8 million app users in England provided 120 million daily reports of their symptoms, and recorded the results of 170,000 PCR tests. On a national level our estimates of incidence and prevalence showed similar sensitivity to changes as two national community surveys: the ONS and REACT-1 studies. On 28 September 2020 we estimated 15,841 (95% CI 14,023-17,885) daily cases, a prevalence of 0.53% (95% CI 0.45-0.60), and R(t) of 1.17 (95% credible interval 1.15-1.19) in England. On a geographically granular level, on 28 September 2020 we detected 15 of the 20 regions with highest incidence according to Government test data, with indications that our method may be able to detect rapid case increases in regions where Government testing provision is more limited.InterpretationSelf-reported data from mobile applications can provide an agile resource to inform policymakers during a fast-moving pandemic, serving as an independent and complementary resource to more traditional instruments for disease surveillance.FundingZoe Global Limited, Department of Health, Wellcome Trust, EPSRC, NIHR, MRC, Alzheimer’s Society.Research in contextEvidence before this studyTo identify instances of the use of digital tools to perform COVID-19 surveillance, we searched PubMed for peer-reviewed articles between 1 January and 14 October 2020, using the keywords COVID-19 AND ((mobile application) OR (web tool) OR (digital survey)). Of the 382 results, we found eight that utilised user-reported data to ascertain a user’s COVID-19 status. Of these, none sought to provide disease surveillance on a national level, or to compare these predictions to other tools to ascertain their accuracy. Furthermore, none of these papers sought to use their data to highlight geographical areas of concern.Added value of this studyTo our knowledge, we provide the first demonstration of mobile technology to provide national-level disease surveillance. Using over 120 million reports from more than 2.8 million users across England, we estimate incidence, prevalence, and the effective reproduction number. We compare these estimates to those from national community surveys to understand the effectiveness of these digital tools. Furthermore, we demonstrate the large number of users can be used to provide disease surveillance with high geographical granularity, potentially providing a valuable source of information for policymakers seeking to understand the spread of the disease.Implications of all the available evidenceOur findings suggest that mobile technology can be used to provide real-time data on the national and local state of the pandemic, enabling policymakers to make informed decisions in a fast-moving pandemic.

Longitudinal clustering of symptoms can predict the need for respiratory support in severe COVID-19., As no one symptom can predict disease severity or the need for dedicated medical support in coronavirus disease 2019 (COVID-19), we asked whether documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations. Clustering was validated on an independent replication dataset between 1 and 28 May 2020. Using the first 5 days of symptom logging, the ROC-AUC (receiver operating characteristic – area under the curve) of need for respiratory support was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required.

In parallel with an unprecedented progress in vascular and stem cell biology during the past two decades, our understanding of vascular calcification has evolved from being perceived as a harmless, passive deposition of minerals to what we now consider a highly regulated, cell-mediated process that is strongly associated with chronic kidney disease (CKD) and confers increased risk for incident cardiovascular disease. A PubMed search of the term “vascular calcification” reveals an impressive exponential growth in the number of original articles published between 2000-2015, but this trend seems to have slowed down in the past 5-6 years. Studies have helped us understand that vascular calcification can engage a large number of key mediators and signalling pathways and that its anatomical and histological location can determine the type and severity of the clinical outcomes. Despite this significantly increased knowledge regarding the underlying pathophysiology, very little progress has been made when it comes to therapies and only a handful of interventional studies have documented any impact on vascular calcification other than modest effects in slowing down the process. The reasons for this lack of translational progress are many, including a somewhat conventional view of vascular calcification with most interventions aiming at restoring or reverting the uremic environment or targeting calcification too late in the process. In this issue of Function, Cazana-Perez et al provide new mechanistic insight in the regulation of vascular calcification, directing our attention to the vascular smooth muscle cell (VSMC), one of the main drivers in both medial and intimal calcification. (Less)

The Tenerife Microwave Spectrometer (TMS) is a new 10-20 GHz experiment that will be installed at the Teide Observatory (Tenerife, Spain), next to the QUIJOTE CMB experiment. The main TMS scientific driver is to accurately measure absolute distortions of the sky spectrum in the 10-20 GHz frequency range, with special emphasis on the characterization of the absolute synchrotron monopole from our Galaxy, and the possible deviations of the CMB spectrum from a pure blackbody law. TMS will provide an absolute calibration for the QUIJOTE experiment, and it will also serve as a prototype for future instruments of its type, both ground-based and satellites. Among its new instrumental design is an octave bandwidth high quality cryogenic front-end, a thermally stabilized cold black body and a new design of wide-band Fourier transform spectrometer. The spectrometer will have a resolution of 250 MHz, giving 40 spectrally stable sub-bands.

ObjectivesDietary supplements may provide nutrients of relevance to ameliorate SARS-CoV-2 infection, although scientific evidence to support a role is lacking. We investigate whether the regular use of dietary supplements can reduce the risk of testing positive for SARS-CoV-2 infection in around 1.4M users of the COVID Symptom Study App who completed a supplement use questionnaire.DesignLongitudinal app-based community survey and nested case control study.SettingSubscribers to an app that was launched to enable self-reported information related to SARS-CoV-2 infection for use in the general population in three countries.Main ExposureSelf-reported regular dietary supplement usage since the beginning of the pandemic.Main Outcome MeasuresSARS-CoV-2 infection confirmed by viral RNA polymerase chain reaction test (RT-PCR) or serology test. A secondary outcome was new-onset anosmia.ResultsIn an analysis including 327,720 UK participants, the use of probiotics, omega-3 fatty acids, multivitamins or vitamin D was associated with a lower risk of SARS-CoV-2 infection by 14%(95%CI: [8%,19%]), 12%(95%CI: [8%,16%]), 13%(95%CI: [10%,16%]) and 9%(95%CI: [6%,12%]), respectively, after adjusting for potential confounders. No effect was observed for vitamin C, zinc or garlic supplements. When analyses were stratified by sex, age and body mass index (BMI), the protective associations for probiotics, omega-3 fatty acids, multivitamins and vitamin D were observed in females across all ages and BMI groups, but were not seen in men. The same overall pattern of association was observed in both the US and Swedish cohorts. Results were further confirmed in a sub-analysis of 993,365 regular app users who were not tested for SARS-CoV-2 with cases (n= 126,556) defined as those with new onset anosmia (the strongest COVID-19 predictor).ConclusionWe observed a modest but significant association between use of probiotics, omega-3 fatty acid, multivitamin or vitamin D supplements and lower risk of testing positive for SARS-CoV-2 in women. No clear benefits for men were observed nor any effect of vitamin C, garlic or zinc for men or women. Randomised controlled trials of selected supplements would be required to confirm these observational findings before any therapeutic recommendations can be made.

We tested whether pregnant and non-pregnant women differ in COVID-19 symptom profile and severity, and we extended previous investigations on hospitalized pregnant women to those who did not require hospitalization. Two female community-based cohorts (18–44 years) provided longitudinal (smartphone application, N = 1,170,315, n = 79 pregnant tested positive) and cross-sectional (web-based survey, N = 1,344,966, n = 134 pregnant tested positive) data, prospectively collected through self-participatory citizen surveillance in UK, Sweden and USA. Pregnant and non-pregnant were compared for frequencies of events, including SARS-CoV-2 testing, symptoms and hospitalization rates. Multivariable regression was used to investigate symptoms severity and comorbidity effects. Pregnant and non-pregnant women positive for SARS-CoV-2 infection were not different in syndromic severity, except for gastrointestinal symptoms. Pregnant were more likely to have received testing, despite reporting fewer symptoms. Pre-existing lung disease was most closely associated with syndromic severity in pregnant hospitalized. Heart and kidney diseases and diabetes increased risk. The most frequent symptoms among non-hospitalized women were anosmia [63% pregnant, 92% non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant who were hospitalized. Consistent with observations in non-pregnant populations, lung disease and diabetes were associated with increased risk of more severe SARS-CoV-2 infection during pregnancy.

Objective: While existing evidence supports beneficial cardiovascular effects of glucagon-like peptide-1 (GLP-1), emerging studies suggest that glucose-dependent insulinotropic peptide (GIP) and/or signaling via the GIP receptor may have untoward cardiovascular effects. Indeed, recent studies show that fasting physiological GIP levels are associated with total mortality and cardiovascular mortality, and it was suggested that GIP plays a role in pathogenesis of coronary artery disease.. We investigated the associations between fasting and post-challenge GIP and GLP-1 concentrations and subclinical atherosclerosis as measured by intima-media thickness in the common carotid artery (IMTmeanCCA), and intima-media thickness in the carotid bifurcation (IMTmaxBulb). Research design and methods: Participants at re-examination within the Malmö Diet and Cancer cardiovascular cohort study (n=3734, mean age 72.5 years; 59.3% women; 10.8% subjects with diabetes; fasting GIP available for 3342 subjects; fasting GLP-1 available for 3299 subjects) underwent oral glucose tolerance testing and carotid ultrasound. Results: In linear regression analyses, each 1 SD increment of fasting GIP was associated with increased (per mm) IMTmeanCCA (β=0.010, p=0.010) and IMTmaxBulb (β=0.014; p=0.040) in models adjusted for known risk factors and glucose metabolism. In contrast, each 1 SD increment of fasting GLP-1 was associated with decreased IMTmaxBulb (per mm; β=-0.016, p=0.014). These associations remained significant when subjects with diabetes were excluded from analyses. Conclusion In a Swedish elderly population, physiologically elevated levels of fasting GIP are associated with increased IMTmeanCCA, while GLP-1 is associated with decreased IMTmaxBulb, further emphasizing diverging cardiovascular effects of these two incretin hormones.

Reports of “Long-COVID”, are rising but little is known about prevalence, risk factors, or whether it is possible to predict a protracted course early in the disease. We analysed data from 4182 incident cases of COVID-19 who logged their symptoms prospectively in the COVID Symptom Study app. 558 (13.3%) had symptoms lasting >=28 days, 189 (4.5%) for >=8 weeks and 95 (2.3%) for >=12 weeks. Long-COVID was characterised by symptoms of fatigue, headache, dyspnoea and anosmia and was more likely with increasing age, BMI and female sex. Experiencing more than five symptoms during the first week of illness was associated with Long-COVID, OR=3.53 [2.76;4.50]. A simple model to distinguish between short and long-COVID at 7 days, which gained a ROC-AUC of 76%, was replicated in an independent sample of 2472 antibody positive individuals. This model could be used to identify individuals for clinical trials to reduce long-term symptoms and target education and rehabilitation services.

BackgroundFrom the beginning of COVID-19 pandemic, pregnant women have been considered at greater risk of severe morbidity and mortality. However, data on hospitalized pregnant women show that the symptom profile and risk factors for severe disease are similar to those among women who are not pregnant, although preterm birth, Cesarean delivery, and stillbirth may be more frequent and vertical transmission is possible. Limited data are available for the cohort of pregnant women that gave rise to these hospitalized cases, hindering our ability to quantify risk of COVID-19 sequelae for pregnant women in the community.ObjectiveTo test the hypothesis that pregnant women in community differ in their COVID-19 symptoms profile and disease severity compared to non-pregnant women. This was assessed in two community-based cohorts of women aged 18-44 years in the United Kingdom, Sweden and the United States of America.Study designThis observational study used prospectively collected longitudinal (smartphone application interface) and cross-sectional (web-based survey) data. Participants in the discovery cohort were drawn from 400,750 UK, Sweden and US women (79 pregnant who tested positive) who self-reported symptoms and events longitudinally via their smartphone, and a replication cohort drawn from 1,344,966 USA women (162 pregnant who tested positive) cross-sectional self-reports samples from the social media active user base. The study compared frequencies of symptoms and events, including self-reported SARS-CoV-2 testing and differences between pregnant and non-pregnant women who were hospitalized and those who recovered in the community. Multivariable regression was used to investigate disease severity and comorbidity effects.ResultsPregnant and non-pregnant women positive for SARS-CoV-2 infection drawn from these community cohorts were not different with respect to COVID-19-related severity. Pregnant women were more likely to have received SARS-CoV-2 testing than non-pregnant, despite reporting fewer clinical symptoms. Pre-existing lung disease was most closely associated with the severity of symptoms in pregnant hospitalized women. Heart and kidney diseases and diabetes were additional factors of increased risk. The most frequent symptoms among all non-hospitalized women were anosmia [63% in pregnant, 92% in non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant women who were hospitalized. Gastrointestinal symptoms, including nausea and vomiting, were different among pregnant and non-pregnant women who developed severe outcomes.ConclusionsAlthough pregnancy is widely considered a risk factor for SARS-CoV-2 infection and outcomes, and was associated with higher propensity for testing, the profile of symptom characteristics and severity in our community-based cohorts were comparable to those observed among non-pregnant women, except for the gastrointestinal symptoms. Consistent with observations in non-pregnant populations, comorbidities such as lung disease and diabetes were associated with an increased risk of more severe SARS-CoV-2 infection during pregnancy. Pregnant women with pre-existing conditions require careful monitoring for the evolution of their symptoms during SARS-CoV-2 infection.

Background Diabetic kidney disease (DKD) remains one of the leading causes of premature death in diabetes. DKD is classified on albuminuria and reduced kidney function (estimated glomerular filtration rate (eGFR)) but these have modest value for predicting future renal status. There is an unmet need for biomarkers that can be used in clinical settings which also improve prediction of renal decline on top of routinely available data, particularly in the early stages. The iBEAt study of the BEAt-DKD project aims to determine whether renal imaging biomarkers (magnetic resonance imaging (MRI) and ultrasound (US)) provide insight into the pathogenesis and heterogeneity of DKD (primary aim) and whether they have potential as prognostic biomarkers in DKD (secondary aim). Methods iBEAt is a prospective multi-centre observational cohort study recruiting 500 patients with type 2 diabetes (T2D) and eGFR ≥30 ml/min/1.73m2. At baseline, blood and urine will be collected, clinical examinations will be performed, and medical history will be obtained. These assessments will be repeated annually for 3 years. At baseline each participant will also undergo quantitative renal MRI and US with central processing of MRI images. Biological samples will be stored in a central laboratory for biomarker and validation studies, and data in a central data depository. Data analysis will explore the potential associations between imaging biomarkers and renal function, and whether the imaging biomarkers improve the prediction of DKD progression. Ancillary substudies will: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI based renal blood flow measurements against H2O15 positron-emission tomography (PET); (3) validate methods for (semi-)automated processing of renal MRI; (4) examine longitudinal changes in imaging biomarkers; (5) examine whether glycocalyx and microvascular measures are associated with imaging biomarkers and eGFR decline; (6) explore whether the findings in T2D can be extrapolated to type 1 diabetes. Discussion iBEAt is the largest DKD imaging study to date and will provide valuable insights into the progression and heterogeneity of DKD. The results may contribute to a more personalised approach to DKD management in patients with T2D. Trial registration Clinicaltrials.gov (NCT03716401).

Aims/hypothesis Evidence that glucose-dependent insulinotropic peptide (GIP) and/or the GIP receptor (GIPR) are involved in cardiovascular biology is emerging. We hypothesised that GIP has untoward effects on cardiovascular biology, in contrast to glucagon-like peptide 1 (GLP-1), and therefore investigated the effects of GIP and GLP-1 concentrations on cardiovascular disease (CVD) and mortality risk. Methods GIP concentrations were successfully measured during OGTTs in two independent populations (Malmö Diet Cancer–Cardiovascular Cohort [MDC-CC] and Prevalence, Prediction and Prevention of Diabetes in Botnia [PPP-Botnia]) in a total of 8044 subjects. GLP-1 (n = 3625) was measured in MDC-CC. The incidence of CVD and mortality was assessed via national/regional registers or questionnaires. Further, a two-sample Mendelian randomisation (2SMR) analysis between the GIP pathway and outcomes (coronary artery disease [CAD] and myocardial infarction) was carried out using a GIP-associated genetic variant, rs1800437, as instrumental variable. An additional reverse 2SMR was performed with CAD as exposure variable and GIP as outcome variable, with the instrumental variables constructed from 114 known genetic risk variants for CAD. Results In meta-analyses, higher fasting levels of GIP were associated with risk of higher total mortality (HR[95% CI] = 1.22 [1.11, 1.35]; p = 4.5 × 10−5) and death from CVD (HR[95% CI] 1.30 [1.11, 1.52]; p = 0.001). In accordance, 2SMR analysis revealed that increasing GIP concentrations were associated with CAD and myocardial infarction, and an additional reverse 2SMR revealed no significant effect of CAD on GIP levels, thus confirming a possible effect solely of GIP on CAD. Conclusions/interpretation In two prospective, community-based studies, elevated levels of GIP were associated with greater risk of all-cause and cardiovascular mortality within 5–9 years of follow-up, whereas GLP-1 levels were not associated with excess risk. Further studies are warranted to determine the cardiovascular effects of GIP per se.

OBJECTIVE While existing evidence supports beneficial cardiovascular effects of glucagon-like peptide 1 (GLP-1), emerging studies suggest that glucose-dependent insulinotropic peptide (GIP) and/or signaling via the GIP receptor may have untoward cardiovascular effects. Indeed, recent studies show that fasting physiological GIP levels are associated with total mortality and cardiovascular mortality, and it was suggested that GIP plays a role in pathogenesis of coronary artery disease. We investigated the associations between fasting and postchallenge GIP and GLP-1 concentrations and subclinical atherosclerosis as measured by mean intima-media thickness in the common carotid artery (IMTmeanCCA) and maximal intima-media thickness in the carotid bifurcation (IMTmaxBulb). RESEARCH DESIGN AND METHODS Participants at reexamination within the Malmö Diet and Cancer–Cardiovascular Cohort study (n = 3,734, mean age 72.5 years, 59.3% women, 10.8% subjects with diabetes, fasting GIP available for 3,342 subjects, fasting GLP-1 available for 3,299 subjects) underwent oral glucose tolerance testing and carotid ultrasound. RESULTS In linear regression analyses, each 1-SD increment of fasting GIP was associated with increased (per mm) IMTmeanCCA (β = 0.010, P = 0.010) and IMTmaxBulb (β = 0.014; P = 0.040) in models adjusted for known risk factors and glucose metabolism. In contrast, each 1-SD increment of fasting GLP-1 was associated with decreased IMTmaxBulb (per mm, β = −0.016, P = 0.014). These associations remained significant when subjects with diabetes were excluded from analyses. CONCLUSIONS In a Swedish elderly population, physiologically elevated levels of fasting GIP are associated with increased IMTmeanCCA, while GLP-1 is associated with decreased IMTmaxBulb, further emphasizing diverging cardiovascular effects of these two incretin hormones.

BackgroundPressure overload of the heart occurs in patients with hypertension or valvular stenosis and induces cardiac fibrosis because of excessive production of extracellular matrix by activated cardiac fibroblasts. This initially provides essential mechanical support to the heart, but eventually compromises function. Osteopontin is associated with fibrosis; however, the underlying signaling mechanisms are not well understood. Herein, we examine the effect of thrombin‐cleaved osteopontin on fibrosis in the heart and explore the role of syndecan‐4 in regulating cleavage of osteopontin.Methods and ResultsOsteopontin was upregulated and cleaved by thrombin in the pressure‐overloaded heart of mice subjected to aortic banding. Cleaved osteopontin was higher in plasma from patients with aortic stenosis receiving crystalloid compared with blood cardioplegia, likely because of less heparin‐induced inhibition of thrombin. Cleaved osteopontin and the specific osteopontin peptide sequenceRGDSLAYGLRthat is exposed after thrombin cleavage both induced collagen production in cardiac fibroblasts. Like osteopontin, the heparan sulfate proteoglycan syndecan‐4 was upregulated after aortic banding. Consistent with a heparan sulfate binding domain in the osteopontin cleavage site, syndecan‐4 was found to bind to osteopontin in left ventricles and cardiac fibroblasts and protected osteopontin from cleavage by thrombin. Shedding of the extracellular part of syndecan‐4 was more prominent at later remodeling phases, at which time levels of cleaved osteopontin were increased.ConclusionsThrombin‐cleaved osteopontin induces collagen production by cardiac fibroblasts. Syndecan‐4 protects osteopontin from cleavage by thrombin, but this protection is lost when syndecan‐4 is shed in later phases of remodeling, contributing to progression of cardiac fibrosis.