Clinical and proteomic profiles of chronic kidney disease in heart failure with reduced and preserved ejection fraction.

BACKGROUND: Chronic kidney disease (CKD) is prevalent and related to poor clinical outcomes in patients with heart failure (HF). The pathophysiology of CKD in HF with a reduced ejection fraction (HFrEF) and HF with a preserved ejection fraction (HFpEF) is not well defined. In this study we compared clinical and proteomic profiles of CKD between patients with HFrEF and HFpEF. METHODS: We included 478 patients of the Scottish BIOSTAT-CHF cohort, of which 246 had HFrEF and 232 had HFpEF. CKD was defined as an eGFR <60 mL/min/1.73m2. We compared HFrEF-patients with CKD to HFpEF-patients with CKD using logistic- and Cox-regression. We performed a differential expression analysis using 6376 proteins. RESULTS: The prevalence of CKD was 36 % and 32 % in patients with HFpEF and HFrEF, respectively. CKD patients were on average 7 years older. BMI, higher NT-proBNP, ACE-inhibitors, HDL-cholesterol and Stroke were associated with CKD- patients with HFrEF. In HFpEF, CKD was associated with MRA-use and higher platelet count. CKD was associated with increased risk of death or heart failure hospitalization (HR 1.82, p < 0.001), with similar effect in HFrEF and HFpEF. The pattern of differentially expressed proteins between patients with and without CKD was similar in both HF-groups. CONCLUSION: Clinical profiles related to CKD- patients with HFrEF were different from CKD-patients with HFrEF. CKD was associated with an increased risk of death or heart failure hospitalization, which was not different between HFpEF and HFrEF. Patterns of circulating proteins were similar between CKD-patients with HFpEF and HFrEF, suggesting no major differences in CKD-pathophysiology.

Levels of plasma 25-hydroxy vitamin D and risk of developing type 2 diabetes in a large Danish primary health care population.

AIMS: Plasma levels of Vitamin D (25(OH)D) have been suggested as a predictor for developing type 2 diabetes. The purpose of this study was therefore to investigate if a measurement of plasma 25(OH)D could predict the development of type 2 diabetes in a cohort of 222,311 individuals from primary healthcare in Denmark. METHODS: The CopD-study database containing data from the Copenhagen General Practitioners Laboratory on blood tests conducted from April 2004 to January 2012 was used for identification of the study population. Incident type 2 diabetes was then defined as having at least two redeemed prescriptions of antidiabetics or at least two hospital contacts due to type 2 diabetes or one redeemed prescription and one hospital contact regarding type 2 diabetes. RESULTS: A total of 222,311 individuals were included in the study, of whom 7652 (3.4%) developed type 2 diabetes during the follow-up period of minimum one year. Individuals who developed type 2 diabetes had a significantly lower median 25(OH)D level than persons in the non-diabetes group. The hazard ratio for development of type 2 diabetes increased by 15% per 10 n mol/L decrease in 25(OH)D level. CONCLUSION: In this study of 222,311 persons from primary health care in Denmark, we found a clear inverse relationship between 25(OH)D and the risk of developing type 2 diabetes. Further studies should be conducted to clarify the mechanisms behind the relationship between 25(OH)D and type 2 diabetes and the effect of oral vitamin D supplementation on the development of type 2 diabetes.

Cause-specific excess mortality in Denmark, Finland, Norway, and Sweden during the COVID-19 pandemic 2020-2022: a study using nationwide population data.

While there is substantial evidence on excess mortality in the first two years of the COVID-19 pandemic, no study has conducted a cause-specific analysis of excess mortality for the whole period 2020-2022 across multiple countries. We examined cause-specific excess mortality during 2020-2022 in Denmark, Finland, Norway, and Sweden-four countries with similar demographics and welfare provisions, which implemented different pandemic response policies. To this end, we utilized nationwide register-based information on annual cause-specific deaths stratified by age and sex, and applied linear regression models to predict mortality in 2020-2022 based on the reference period 2010-2019. Excess deaths were obtained by contrasting actual and expected deaths. Additional analyses employed standardization to a common population, as well as population adjustments to account for previous deaths. Our results showed that, besides deaths due to COVID-19 (a total of 32,491 during 2020-2022), all countries experienced excess deaths due to cardiovascular diseases (in total 11,610 excess deaths), and under-mortality due to respiratory diseases other than COVID-19 (in total 9878) and dementia (in total 8721). The excess mortality due to cardiovascular diseases was particularly pronounced in Finland and Norway in 2022, and the under-mortality due to dementia was particularly pronounced in Sweden in 2021-2022. In conclusion, while COVID-19 deaths emerge as the most apparent consequence of the pandemic, our findings suggest that mortality has also been influenced by substitutions between different causes of death and over time, as well as indirect consequences of COVID-19 infection and pandemic responses-albeit to different extents in the different countries.

GASP: A Pan-Specific Predictor of Family 1 Glycosyltransferase Acceptor Specificity Enabled by a Pipeline for Substrate Feature Generation and Large-Scale Experimental Screening.

Glycosylation represents a major chemical challenge; while it is one of the most common reactions in Nature, conventional chemistry struggles with stereochemistry, regioselectivity, and solubility issues. In contrast, family 1 glycosyltransferase (GT1) enzymes can glycosylate virtually any given nucleophilic group with perfect control over stereochemistry and regioselectivity. However, the appropriate catalyst for a given reaction needs to be identified among the tens of thousands of available sequences. Here, we present the glycosyltransferase acceptor specificity predictor (GASP) model, a data-driven approach to the identification of reactive GT1:acceptor pairs. We trained a random forest-based acceptor predictor on literature data and validated it on independent in-house generated data on 1001 GT1:acceptor pairs, obtaining an AUROC of 0.79 and a balanced accuracy of 72%. The performance was stable even in the case of completely new GT1s and acceptors not present in the training data set, highlighting the pan-specificity of GASP. Moreover, the model is capable of parsing all known GT1 sequences, as well as all chemicals, the latter through a pipeline for the generation of 153 chemical features for a given molecule taking the CID or SMILES as input (freely available at https://github.com/degnbol/GASP). To investigate the power of GASP, the model prediction probability scores were compared to GT1 substrate conversion yields from a newly published data set, with the top 50% of GASP predictions corresponding to reactions with >50% synthetic yields. The model was also tested in two comparative case studies: glycosylation of the antihelminth drug niclosamide and the plant defensive compound DIBOA. In the first study, the model achieved an 83% hit rate, outperforming a hit rate of 53% from a random selection assay. In the second case study, the hit rate of GASP was 50%, and while being lower than the hit rate of 83% using expert-selected enzymes, it provides a reasonable performance for the cases when an expert opinion is unavailable. The hierarchal importance of the generated chemical features was investigated by negative feature selection, revealing properties related to cyclization and atom hybridization status to be the most important characteristics for accurate prediction. Our study provides a GT1:acceptor predictor which can be trained on other data sets enabled by the automated feature generation pipelines. We also release the new in-house generated data set used for testing of GASP to facilitate the future development of GT1 activity predictors and their robust benchmarking.

Excess mortality in Denmark, Finland, Norway and Sweden during the COVID-19 pandemic 2020-2022.

BACKGROUND: The Nordic countries represent a unique case study for the COVID-19 pandemic due to socioeconomic and cultural similarities, high-quality comparable administrative register data and notable differences in mitigation policies during the pandemic. We aimed to compare weekly excess mortality in the Nordic countries across the three full pandemic years 2020-2022. METHODS: Using data on weekly all-cause mortality from official administrative registers in Denmark, Finland, Norway and Sweden, we employed time series regression models to assess mortality developments within each pandemic year, with the period 2010-2019 used as reference period. We then compared excess mortality across the countries in 2020-2022, taking differences in population size and age- and sex-distribution into account. Results were age- and sex-standardized to the Danish population of 2020. Robustness was examined with a variety of sensitivity analyses. RESULTS: While Sweden experienced excess mortality in 2020 [75 excess deaths per 100 000 population (95% prediction interval 29-122)], Denmark, Finland and Norway experienced excess mortality in 2022 [52 (14-90), 130 (83-177) and 88 (48-128), respectively]. Weekly death data reveal how mortality started to increase in mid-2021 in Denmark, Finland and Norway, and continued above the expected level through 2022. CONCLUSION: Although the Nordic countries experienced relatively low pandemic excess mortality, the impact and timing of excess mortality differed substantially. These estimates-arguably the most accurate available for any region in capturing pandemic-related excess deaths-may inform future research and policy regarding the complex mortality dynamics in times of a health crisis such as the COVID-19 pandemic.

Effects of Quinidine or Rifampin Co-administration on the Single-Dose Pharmacokinetics and Safety of Rilzabrutinib (PRN1008) in Healthy Participants.

This open-label, phase 1 study was conducted with healthy adult participants to evaluate the potential drug-drug interaction between rilzabrutinib and quinidine (an inhibitor of P-glycoprotein [P-gp] and CYP2D6) or rifampin (an inducer of CYP3A and P-gp). Plasma concentrations of rilzabrutinib were measured after a single oral dose of rilzabrutinib 400 mg administered on day 1 and again, following a wash-out period, after co-administration of rilzabrutinib and quinidine or rifampin. Specifically, quinidine was given at a dose of 300 mg every 8 hours for 5 days from day 7 to day 11 (N = 16) while rifampin was given as 600 mg once daily for 11 days from day 7 to day 17 (N = 16) with rilzabrutinib given in the morning of day 10 (during quinidine dosing) or day 16 (during rifampin dosing). Quinidine had no significant effect on rilzabrutinib pharmacokinetics. Rifampin decreased rilzabrutinib exposure (the geometric mean of Cmax and AUC0-∞ decreased by 80.5% and 79.5%, respectively). Single oral doses of rilzabrutinib, with or without quinidine or rifampin, appeared to be well tolerated. These findings indicate that rilzabrutinib is a substrate for CYP3A but not a substrate for P-gp.

Post-injury long-term sickness absence and risk of disability pension: The role of socioeconomic status.

INTRODUCTION: Previous research has identified low socioeconomic status (SES) as a risk factor for long-term sickness absence (LTSA) and disability pension (DP) following trauma. However, most studies lack information on medical diagnoses, limiting our understanding of the underlying factors. To address this gap, we retrieved information about diagnostic causes for receipt of welfare benefits to explore the role of SES in the transition from post-injury LTSA to permanent DP among the working population in Norway. MATERIALS AND METHODS: We conducted a population-based cohort study of all Norwegian residents aged 25-59 years registered with a spell of LTSA due to injury commencing in the period 2000-2003. This cohort was followed through 2014 by linking information on receipt of welfare benefits with sociodemographic data from administrative registers. SES was defined as a composite measure of educational attainment and income level. We used flexible parametric survival models to estimate hazard ratios (HR) with 95 % confidence intervals (CI) for all-cause and diagnosis-specific DP according to SES, adjusting for sex, age, marital status, immigrant status and healthcare region of residence. RESULTS: Of 53,937 adults with post-injury LTSA, 9,665 (18 %) transferred to DP during follow-up. The crude risk of DP was highest for LTSA spells due to poisoning and head injuries. Overall, individuals in the lowest SES category had twice the risk of DP compared to those in the highest SES category (HR = 2.25, 95 % CI 2.13-2.38). The difference by SES was greatest for LTSA due to poisoning and smallest for LTSA due to head injuries. A majority (75 %) of DP recipients had a non-injury diagnosis as the primary cause of DP. The socioeconomic gradient was more pronounced for non-injury causes of DP (HR = 2.47, 95 % CI 2.31-2.63) than for injury causes (HR = 1.73, 95 % CI 1.56-1.92) and was especially steep for DP due to musculoskeletal diseases and mental and behavioural disorders. CONCLUSIONS: The relationship between SES and DP varied by both the type of injury that caused LTSA and the diagnosis used to grant DP, highlighting the importance of taking diagnostic information into account when investigating long-term consequences of injuries.

The Cardioprotective Effects of Semaglutide Exceed Those of Dietary Weight Loss in Mice With HFpEF.

Obesity-related heart failure with preserved ejection fraction (HFpEF) has become a well-recognized HFpEF subphenotype. Targeting the unfavorable cardiometabolic profile may represent a rational treatment strategy. This study investigated semaglutide, a glucagon-like peptide-1 receptor agonist that induces significant weight loss in patients with obesity and/or type 2 diabetes mellitus and has been associated with improved cardiovascular outcomes. In a mouse model of HFpEF that was caused by advanced aging, female sex, obesity, and type 2 diabetes mellitus, semaglutide, compared with weight loss induced by pair feeding, improved the cardiometabolic profile, cardiac structure, and cardiac function. Mechanistically, transcriptomic, and proteomic analyses revealed that semaglutide improved left ventricular cytoskeleton function and endothelial function and restores protective immune responses in visceral adipose tissue. Strikingly, treatment with semaglutide induced a wide array of favorable cardiometabolic effects beyond the effect of weight loss by pair feeding. Glucagon-like peptide-1 receptor agonists may therefore represent an important novel therapeutic option for treatment of HFpEF, especially when obesity-related.

No gold standard for calculating excess mortality. / Ingen fasit for beregning av overdødelighet.

When observed mortality is higher than expected mortality, it is referred to as excess mortality. While observed mortality is easy to quantify, calculating expected mortality is challenging. Using different methods can sometimes lead to major differences in excess mortality estimates.

DeepPeptide predicts cleaved peptides in proteins using conditional random fields.

MOTIVATION: Peptides are ubiquitous throughout life and involved in a wide range of biological processes, ranging from neural signaling in higher organisms to antimicrobial peptides in bacteria. Many peptides are generated post-translationally by cleavage of precursor proteins and can thus not be detected directly from genomics data, as the specificities of the responsible proteases are often not completely understood. RESULTS: We present DeepPeptide, a deep learning model that predicts cleaved peptides directly from the amino acid sequence. DeepPeptide shows both improved precision and recall for peptide detection compared to previous methodology. We show that the model is capable of identifying peptides in underannotated proteomes. AVAILABILITY AND IMPLEMENTATION: DeepPeptide is available online at ku.biolib.com/DeepPeptide.

Contact with primary care physicians among adults with pre-existing common mental health problems during the COVID-19 pandemic: a registry-based study from Norway.

BACKGROUND: During the COVID-19 pandemic, individuals with pre-existing mental health problems may have experienced additional stress, which could worsen symptoms or trigger relapse. Thus, this study aimed to investigate if the number of consultations with general practitioners (GPs) among individuals with a pre-existing common mental health problem during the pandemic differed from pre-pandemic years. METHODS: Data on consultations with GPs among 18-65-year-olds registered with common mental health problems in 2017-2021 were retrieved from the Norwegian Control and Payment of Health Reimbursements Database. Based on data from the pre-pandemic years (2017-2019), we predicted the number of consultations per week for depression, anxiety disorder, phobia/obsessive-compulsive disorder (OCD), post-traumatic stress disorder (PTSD), and eating disorders during the pandemic (March 2020-December 2021) among individuals with pre-existing mental health problems. The forecasted and observed trends in GP consultations per week during the pandemic were stratified by diagnosis, gender, and age groups. RESULTS: The observed number of consultations for anxiety disorder, PTSD, and eating disorders were significantly higher than forecasted during extended periods of the two pandemic years. The differences were largest for PTSD (on average 37% higher in men and 47% higher in women during the pandemic), and for eating disorders among women (on average 87% higher during the pandemic). There were only minor differences between the predicted and observed number of consultations for depression and phobia/OCD. CONCLUSIONS: During the pandemic, individuals with a recent history of mental health problems were more likely to seek help for anxiety disorder, PTSD, and eating disorders, as compared to pre-pandemic years.

Incidence rates of treated mental disorders before and during the COVID-19 pandemic-a nationwide study comparing trends in the period 2015 to 2021.

BACKGROUND: There is a concern that exposure to psychosocial stressors during the COVID-19 pandemic may have led to a higher incidence of mental disorders. Thus, this study aimed to compare trends in incidence rates of depressive disorder, anxiety disorders, obsessive-compulsive disorder (OCD), post-traumatic stress disorder (PTSD), and eating disorders in primary- and specialist health care before (2015-2019) and during the COVID-19 pandemic (2020-2021). METHODS: We used aggregated population registry data to calculate incidence rates of mental disorders from primary- (The Norwegian Control and Payment of Health Reimbursements Registry (KUHR)) and specialist (The Norwegian Patient Registry (NPR)) health care. The analyses included all Norwegian residents aged 18-65 during the study period. Incident cases were defined as having no previous registration with the same mental disorder in KUHR (from 2006) or NPR (from 2008). We used linear prediction models and mean models to compare incidence rates and test trends before and during the pandemic. RESULTS: During the pandemic, the incidence rates among women were higher or as predicted for OCD in specialist health care and for eating disorders in both primary- and specialist health care. These findings were strongest among women aged 18-24 years. Incidence rates for depression and phobia/OCD among both genders in primary health care and phobic anxiety disorders among both genders in specialist health care were lower or as predicted. CONCLUSION: The COVID-19 pandemic may have led to more women needing treatment for OCD and eating disorders in the Norwegian population. The decreased incidence rates for some disorders might indicate that some individuals either avoided seeking help or had improved mental health during the pandemic.

Forearm fractures - are we counting them all? An attempt to identify and include the missing fractures treated in primary care.

OBJECTIVE: Norway has a high incidence of forearm fractures, however, the incidence rates based on secondary care registers can be underestimated, as some fractures are treated exclusively in primary care. We estimated the proportion of forearm fracture diagnoses registered exclusively in primary care and assessed the agreement between diagnosis for forearm fractures in primary and secondary care. DESIGN: Quality assurance study combining nationwide data from 2008 to 2019 on forearm fractures registered in primary care (Norwegian Control and Payment of Health Reimbursement) and secondary care (the Norwegian Patient Registry). SETTING AND PATIENTS: Forearm fracture diagnoses in patients aged ≥20 treated in primary care (n = 83,357) were combined with injury diagnoses for in- and outpatients in secondary care (n = 3,294,336). MAIN OUTCOME MEASURES: Proportion of forearm fractures registered exclusively in primary care, and corresponding injury diagnoses for those registered in both primary and secondary care. RESULTS: Of 189,105 forearm fracture registrations in primary and secondary care, 13,948 (7.4%) were registered exclusively in primary care. The proportion ranged from 4.9% to 13.5% on average between counties, but was higher in some municipalities (>30%). Of 66,747 primary care forearm fractures registered with a diagnosis in secondary care, 62% were incident forearm fractures, 28% follow-up controls, and 10% other fractures or non-fracture injuries. CONCLUSION: An overall small proportion of forearm fractures were registered only in primary care, but it was larger in some areas of Norway. Failing to include fractures exclusively treated in primary care could underestimate the incidence rates in these areas.

Norwegian forearm fracture incidence based on secondary care may be underestimated by not including fractures treated exclusively in primary care.The mean proportion of forearm fractures exclusively handled in primary care is 7% and varies from 5% to 14% between counties.Fractures treated in primary care can be considered for more accurate national incidence rates. Correct fracture diagnosis needs further investigation.

Deorphanizing Peptides Using Structure Prediction.

Many endogenous peptides rely on signaling pathways to exert their function, but identifying their cognate receptors remains a challenging problem. We investigate the use of AlphaFold-Multimer complex structure prediction together with transmembrane topology prediction for peptide deorphanization. We find that AlphaFold's confidence metrics have strong performance for prioritizing true peptide-receptor interactions. In a library of 1112 human receptors, the method ranks true receptors in the top percentile on average for 11 benchmark peptide-receptor pairs.

Migration mediated by the oxysterol receptor GPR183 depends on arrestin coupling but not receptor internalization.

The chemotactic G protein-coupled receptor GPR183 and its most potent endogenous oxysterol ligand 7α,25-dihydroxycholesterol (7α,25-OHC) are important for immune cell positioning in secondary lymphoid tissues. This receptor-ligand pair is associated with various diseases, in some cases contributing favorably and in other cases adversely, making GPR183 an attractive target for therapeutic intervention. We investigated the mechanisms underlying GPR183 internalization and the role of internalization in the main biological function of the receptor, chemotaxis. We found that the C terminus of the receptor was important for ligand-induced internalization but less so for constitutive (ligand-independent) internalization. ß-arrestin potentiated ligand-induced internalization but was not required for ligand-induced or constitutive internalization. Caveolin and dynamin were the main mediators of both constitutive and ligand-induced receptor internalization in a mechanism independent of G protein activation. Clathrin-mediated endocytosis also contributed to constitutive GPR183 internalization in a ß-arrestin-independent manner, suggesting the existence of different pools of surface-localized GPR183. Chemotaxis mediated by GPR183 depended on receptor desensitization by ß-arrestins but could be uncoupled from internalization, highlighting an important biological role for the recruitment of ß-arrestin to GPR183. The role of distinct pathways in internalization and chemotaxis may aid in the development of GPR183-targeting drugs for specific disease contexts.

Ancient DNA provides insights into 4,000 years of resource economy across Greenland.

The success and failure of past cultures across the Arctic was tightly coupled to the ability of past peoples to exploit the full range of resources available to them. There is substantial evidence for the hunting of birds, caribou and seals in prehistoric Greenland. However, the extent to which these communities relied on fish and cetaceans is understudied because of taphonomic processes that affect how these taxa are presented in the archaeological record. To address this, we analyse DNA from bulk bone samples from 12 archaeological middens across Greenland covering the Palaeo-Inuit, Norse and Neo-Inuit culture. We identify an assemblage of 42 species, including nine fish species and five whale species, of which the bowhead whale (Balaena mysticetus) was the most commonly detected. Furthermore, we identify a new haplotype in caribou (Rangifer tarandus), suggesting the presence of a distinct lineage of (now extinct) dwarfed caribou in Greenland 3,000 years ago.

Combining mass spectrometry and machine learning to discover bioactive peptides.

Peptides play important roles in regulating biological processes and form the basis of a multiplicity of therapeutic drugs. To date, only about 300 peptides in human have confirmed bioactivity, although tens of thousands have been reported in the literature. The majority of these are inactive degradation products of endogenous proteins and peptides, presenting a needle-in-a-haystack problem of identifying the most promising candidate peptides from large-scale peptidomics experiments to test for bioactivity. To address this challenge, we conducted a comprehensive analysis of the mammalian peptidome across seven tissues in four different mouse strains and used the data to train a machine learning model that predicts hundreds of peptide candidates based on patterns in the mass spectrometry data. We provide in silico validation examples and experimental confirmation of bioactivity for two peptides, demonstrating the utility of this resource for discovering lead peptides for further characterization and therapeutic development.

The Association of Cold Ambient Temperature With Fracture Risk and Mortality: National Data From Norway-A Norwegian Epidemiologic Osteoporosis Studies (NOREPOS) Study.

Norway is an elongated country with large variations in climate and duration of winter season. It is also a high-risk country for osteoporotic fractures, in particular hip fractures, which cause high mortality. Although most hip fractures occur indoors, there is a higher incidence of both forearm and hip fractures during wintertime, compared with summertime. In a nationwide longitudinal cohort study, we investigated whether cold ambient (outdoor) temperatures could be an underlying cause of this high incidence and mortality. Hospitalized/outpatient forearm fractures (International Classification of Diseases and Related Health Problems, 10th Revision [ICD-10] code S52) and hospitalized hip fractures (ICD-10 codes S72.0-S72.2) from 2008 to 2018 were retrieved from the Norwegian Patient Registry. Average monthly ambient temperatures (degrees Celsius, °C) from the years 2008 to 2018 were provided by the Norwegian Meteorological Institute and linked to the residential area of each inhabitant. Poisson models were fitted to estimate the association (incidence rate ratios [IRRs], 95% confidence intervals [CIs]) between temperature and monthly incidence of total number of forearm and hip fractures. Flexible parametric survival models (hazard ratios [HR], 95% CI) were used to estimate the association between temperature and post-hip fracture mortality, taking the population mortality into account. Monthly temperature ranged from -20.2°C to 22.0°C, with a median of -2.0°C in winter and 14.4°C in summer. At low temperatures (<0°C) compared to ≥0°C, there was a 53% higher risk of forearm fracture (95% CI, 51%-55%) and 21% higher risk of hip fracture (95% CI, 19%-22%), adjusting for age, gender, calendar year, urbanization, residential region, elevation, and coastal proximity. When taking the population mortality into account, the post-hip fracture mortality in both men (HR 1.08; 95% CI, 1.02-1.13) and women (HR 1.09; 95% CI, 1.04-1.14) was still higher at cold temperatures. There was a higher risk of forearm and hip fractures, and an excess post-hip fracture mortality at cold ambient temperatures. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).