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Abstract The microbial communities of the oral cavity are important elements of oral and systemic health. With emerging evidence highlighting the heritability of oral bacterial microbiota, this study aimed to identify host genome variants that influence oral microbial traits. Using data from 16S rRNA gene amplicon sequencing, we performed genome-wide association studies with univariate and multivariate traits of the salivary microbiota from 610 unrelated adults from the Danish ADDITION-PRO cohort. We identified six single nucleotide polymorphisms (SNPs) in human genomes that showed associations with abundance of bacterial taxa at different taxonomical tiers (P

Abstract Background Disease prevalence and mean phenotype values differ between many populations, including Inuit and Europeans. Whether these differences are partly explained by genetic differences or solely due to differences in environmental exposures is still unknown, because estimates of the genetic contribution to these means, which we will here refer to as mean genotypic values, are easily confounded, and because studies across genetically diverse populations are lacking. Methods Leveraging the unique genetic properties of the small, admixed and historically isolated Greenlandic population, we estimated the differences in mean genotypic value between Inuit and European genetic ancestry using an admixed sibling design. Analyses were performed across 26 metabolic phenotypes, in 1474 admixed sibling pairs present in a cohort of 5996 Greenlanders. Results After FDR correction for multiple testing, we found significantly lower mean genotypic values in Inuit genetic ancestry compared to European genetic ancestry for body weight (effect size per percentage of Inuit genetic ancestry (se), −0.51 (0.16) kg/%), body mass index (−0.20 (0.06) kg/m2/%), fat percentage (−0.38 (0.13) %/%), waist circumference (−0.42 (0.16) cm/%), hip circumference (−0.38 (0.11) cm/%) and fasting serum insulin levels (−1.07 (0.51) pmol/l/%). The direction of the effects was consistent with the observed mean phenotype differences between Inuit and European genetic ancestry. No difference in mean genotypic value was observed for height, markers of glucose homeostasis, or circulating lipid levels. Conclusions We show that mean genotypic values for some metabolic phenotypes differ between two human populations using a method not easily confounded by possible differences in environmental exposures. Our study illustrates the importance of performing genetic studies in diverse populations.

Abstract Latent autoimmune diabetes in adults (LADA) is a heterogeneous disease characterized by autoantibodies against insulin producing pancreatic beta cells and initial lack of need for insulin treatment. The aim of the present study was to investigate if individuals with LADA have an altered gut microbiota relative to non-diabetic control subjects, individuals with type 1 diabetes (T1D), and individuals with type 2 diabetes (T2D). Bacterial community profiling was performed with primers targeting the variable region 4 of the 16S rRNA gene and sequenced. Amplicon sequence variants (ASVs) were generated with DADA2 and annotated to the SILVA database. The gut virome was sequenced, using a viral particle enrichment and metagenomics approach, assembled, and quantified to describe the composition of the viral community. Comparison of the bacterial alpha- and beta-diversity measures revealed that the gut bacteriome of individuals with LADA resembled that of individuals with T2D. Yet, specific genera were found to differ in abundance in individuals with LADA compared with T1D and T2D, indicating that LADA has unique taxonomical features. The virome composition reflected the stability of the most dominant order Caudovirales and the families Siphoviridae, Podoviridae, and Inoviridae, and the dominant family Microviridae. Further studies are needed to confirm these findings.

Abstract Background The emerging use of biomarkers in research and tailored care introduces a need for information about the association between biomarkers and basic demographics and lifestyle factors revealing expectable concentrations in healthy individuals while considering general demographic differences. Methods A selection of 47 biomarkers, including markers of inflammation and vascular stress, were measured in plasma samples from 9876 Danish Blood Donor Study participants. Using regression models, we examined the association between biomarkers and sex, age, Body Mass Index (BMI), and smoking. Results Here we show that concentrations of inflammation and vascular stress biomarkers generally increase with higher age, BMI, and smoking. Sex-specific effects are observed for multiple biomarkers. Conclusion This study provides comprehensive information on concentrations of 47 plasma biomarkers in healthy individuals. The study emphasizes that knowledge about biomarker concentrations in healthy individuals is critical for improved understanding of disease pathology and for tailored care and decision support tools.

Abstract To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.

Abstract Background Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analyses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank. Results Large-scale growth modeling enables an unprecedented view of adolescent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide significant loci and leverage trans-ancestry data to perform fine-mapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with different growth trajectories correlated with different outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fibrillation. Conclusion We report novel genetic associations with the tempo of pubertal growth and find that genetic determinants of growth are correlated with reproductive, glycemic, respiratory, and cardiac traits in adulthood. These results aid in identifying specific growth trajectories impacting lifelong health and show that there may not be a single “optimal” pubertal growth pattern.

Background & Aims: Infections are frequent in patients with cirrhosis and worsen prognosis. We evaluated the incidence of infections and their impact on decompensation and death in patients with early alcohol-related liver disease (ALD) during long-term follow-up. Methods: We performed a prospective cohort study of patients in secondary care with a history of excess alcohol intake, no prior decompensation, and with liver biopsies along with clinical investigations conducted at baseline. During follow-up, we reviewed the patients’ electronic healthcare records for cases of infections, hospitalizations, transient elastography measurements, decompensations, all-cause mortality, and alcohol intake. Results: We included 461 patients with a mean age of 56±10 years (76% males; fibrosis stage F0-1/F2/F3-4 = 259/107/93 [56%/23%/20%]). During a median follow-up of 4.5 years (IQR 2.9-6.3), 134 patients (29%) developed a total of 312 infections, most frequently pneumonia (106/312, 34%) and urinary tract infections (57/312, 18%). Excessive alcohol intake during follow-up, smoking ≥30 pack years, MELD score and elevated liver stiffness during follow-up were independent predictors of infections. Patients who developed at least one infection had a significantly increased risk of subsequent decompensation (hazard ratio 4.98, 95% CI 2.47-10.03) and death (hazard ratio 8.24, 95% CI 4.65-14.59). Infections increased the risk of decompensation and death independently of baseline fibrosis stage, age, gender, and MELD score. Conclusions: Almost one-third of patients with early ALD develop an infection, which worsens their prognosis by increasing the risk of decompensation and death. The risk of infections increases with liver disease severity and ongoing harmful use of alcohol. Impact and implications: This study reveals that infections significantly worsen the prognosis of patients with early alcohol-related liver disease (ALD), increasing the likelihood of decompensation and death by up to eight times. These findings, pertinent to healthcare providers, researchers, and policymakers, emphasize the importance of early prevention and management of infections in patients with ALD, even those in early stages who may be asymptomatic. It was observed that nearly one-third of patients with early-stage ALD developed infections over 4.5 years, with risk factors including alcohol overuse, smoking, and higher MELD scores. The research underscores the critical need to incorporate these insights into clinical practice and public health policies to improve patient outcomes and mitigate the impact of infections in patients with ALD.

Abstract The fetal insulin hypothesis proposes that low birthweight and type 2 diabetes (T2D) in adulthood may be two phenotypes of the same genotype. In this study we aimed to explore this theory further by testing the effects of GWAS-identified genetic variants related to insulin release and sensitivity on fetal growth and blood flow from week 20 of gestation to birth and on placental weight at birth. We calculated genetic risk scores (GRS) of first phase insulin release (FPIR), fasting insulin (FI), combined insulin resistance and dyslipidaemia (IR + DLD) and insulin sensitivity (IS) in a study population of 665 genotyped newborns. Two-dimensional ultrasound measurements with estimation of fetal weight and blood flow were carried out at week 20, 25, and 32 of gestation in all 665 pregnancies. Birthweight and placental weight were registered at birth. Associations between the GRSs and fetal growth, blood flow and placental weight were investigated using linear mixed models. The FPIR GRS was directly associated with fetal growth from week 20 to birth, and both the FI GRS, IR + DLD GRS, and IS GRS were associated with placental weight at birth. Our findings indicate that insulin-related genetic variants might primarily affect fetal growth via the placenta.

Abstract The inflammatory activity in cirrhosis is often pronounced and related to episodes of decompensation. Systemic markers of inflammation may contain prognostic information, and we investigated their possible correlation with admissions and mortality among patients with newly diagnosed liver cirrhosis. We collected plasma samples from 149 patients with newly diagnosed (within the past 6 months) cirrhosis, and registered deaths and hospital admissions within 180 days. Ninety-two inflammatory markers were quantified and correlated with clinical variables, mortality, and admissions. Prediction models were calculated by logistic regression. We compared the disease courses of our cohort with a validation cohort of 86 patients with cirrhosis. Twenty of 92 markers of inflammation correlated significantly with mortality within 180 days (q-values of 0.00–0.044), whereas we found no significant correlations with liver-related admissions. The logistic regression models yielded AUROCs of 0.73 to 0.79 for mortality and 0.61 to 0.73 for liver-related admissions, based on a variety of modalities (clinical variables, inflammatory markers, clinical scores, or combinations thereof). The models performed moderately well in the validation cohort and were better able to predict mortality than liver-related admissions. In conclusion, markers of inflammation can be used to predict 180-day mortality in patients with newly diagnosed cirrhosis. Prediction models for newly diagnosed cirrhotic patients need further validation before implementation in clinical practice. Trial registration: NCT04422223 (and NCT03443934 for the validation cohort), and Scientific Ethics Committee No.: H-19024348.

Abstract Atopic dermatitis (AD) is a common inflammatory skin condition and prior genome-wide association studies (GWAS) have identified 71 associated loci. In the current study we conducted the largest AD GWAS to date (discovery N = 1,086,394, replication N = 3,604,027), combining previously reported cohorts with additional available data. We identified 81 loci (29 novel) in the European-only analysis (which all replicated in a separate European analysis) and 10 additional loci in the multi-ancestry analysis (3 novel). Eight variants from the multi-ancestry analysis replicated in at least one of the populations tested (European, Latino or African), while two may be specific to individuals of Japanese ancestry. AD loci showed enrichment for DNAse I hypersensitivity and eQTL associations in blood. At each locus we prioritised candidate genes by integrating multi-omic data. The implicated genes are predominantly in immune pathways of relevance to atopic inflammation and some offer drug repurposing opportunities.

Abstract Background Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. Methods We searched PubMed and Embase for publications that used ‘simple subclassification’ approaches using simple categorisation of clinical characteristics, or ‘complex subclassification’ approaches which used machine learning or ‘omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches. Results Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes. Conclusion Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.

Introduction Human albumin is used in the treatment of complications of cirrhosis. However, the use of long-term human albumin administration is costly and resource demanding for both patients and healthcare systems. A precision medicine approach with biomarkers to predict human albumin treatment response, so-called predictive biomarkers, could make this a viable treatment option in patients with cirrhosis and ascites.Methods and analysis ALB-TRIAL is a multinational, double-blind, placebo-controlled randomised controlled trial. We aim to validate a predictive biomarker, consisting of a panel of circulating metabolites, to predict the treatment response to human albumin in patients with cirrhosis and ascites. All enrolled patients are stratified into a high-expected or low-expected effect stratum of human albumin based on the biomarker outcome. After stratification, patients in each group are randomised into either active treatment (20% human albumin) or corresponding placebo (0.9% NaCl) every 10th day for 6 months. The primary outcome is the cumulative number of liver-related events (composite of decompensation episodes, transjugular intrahepatic shunt insertion, liver transplantation and death). Key secondary outcomes include time-to-event analysis of primary outcome components, an analysis of the total healthcare burden and a health economic analysis.Ethics and dissemination The trial obtained ethical and regulatory approval in Denmark, Germany, the Netherlands, Belgium, Hungary and Spain through the Clinical Trials Information System (CTIS) from 13 February 2023, while UK approvals from the Health Regulatory Authority, Medicines and Healthcare products Regulatory Agency and Research Ethics Committee are pending. Findings will be published in peer-reviewed journals, presented at conferences, communicated to relevant stakeholders and in the public registry of CTIS, following trial completion.Trial registration number NCT05056220 EU CT: 2022-501006-34-01

Introduction The population-based Inter99 cohort has contributed extensively to our understanding of effects of a systematic screening and lifestyle intervention, as well as the multifactorial aetiology of type 2 diabetes (T2D) and cardiovascular disease. To understand causes, trajectories and patterns of early and overt cardiometabolic disease manifestations, we will perform a combined clinical deep phenotyping and registry follow-up study of the now 50–80 years old Inter99 participants.Methods and analysis The Inter99 cohort comprises individuals aged 30–60 years, who lived in a representative geographical area of greater Copenhagen, Denmark, in 1999. Age-stratified and sex-stratified random subgroups were invited to participate in either a lifestyle intervention (N=13 016) or questionnaires (N=5264), while the rest served as a reference population (N=43 021). Of the 13 016 individuals assigned to the lifestyle intervention group, 6784 (52%) accepted participation in a baseline health examination in 1999, including screening for cardiovascular risk factors and prediabetic conditions. In total, 6004 eligible participants, who participated in the baseline examination, will be invited to participate in the deep phenotyping 20-year follow-up clinical examination including measurements of anthropometry, blood pressure, arterial stiffness, cardiometabolic biomarkers, coronary artery calcification, heart rate variability, heart rhythm, liver stiffness, fundus characteristics, muscle strength and mass, as well as health and lifestyle questionnaires. In a subsample, 10-day monitoring of diet, physical activity and continuous glucose measurements will be performed. Fasting blood, urine and faecal samples to be stored in a biobank. The established database will form the basis of multiple analyses. A main purpose is to investigate whether low birth weight independent of genetics, lifestyle and glucose tolerance predicts later common T2D cardiometabolic comorbidities.Ethics and dissemination The study was approved by the Medical Ethics Committee, Capital Region, Denmark (H-20076231) and by the Danish Data Protection Agency through the Capital Region of Denmark’s registration system (P-2020-1074). Informed consent will be obtained before examinations. Findings will be disseminated in peer-reviewed journals, at conferences and via presentations to stakeholders, including patients and public health policymakers.Trial registration number NCT05166447.

Abstract The host-microbiota co-metabolite trimethylamine N-oxide (TMAO) is linked to increased cardiovascular risk but how its circulating levels are regulated remains unclear. We applied “explainable” machine learning, univariate, multivariate and mediation analyses of fasting plasma TMAO concentration and a multitude of phenotypes in 1,741 adult Europeans of the MetaCardis study. Here we show that next to age, kidney function is the primary variable predicting circulating TMAO, with microbiota composition and diet playing minor, albeit significant, roles. Mediation analysis suggests a causal relationship between TMAO and kidney function that we corroborate in preclinical models where TMAO exposure increases kidney scarring. Consistent with our findings, patients receiving glucose-lowering drugs with reno-protective properties have significantly lower circulating TMAO when compared to propensity-score matched control individuals. Our analyses uncover a bidirectional relationship between kidney function and TMAO that can potentially be modified by reno-protective anti-diabetic drugs and suggest a clinically actionable intervention for decreasing TMAO-associated excess cardiovascular risk.

Abstract Background Since 1972 The National Child Odontology Registry has collected data on the oral health of most of all Danish children and adolescents. However, comprehensive information on the registry has not previously been available, making it difficult to approach and use the registry for research purposes. Methods By combining historical documentation and simple descriptive statistics we provide an overview of major events in the timeline of The National Child Odontology Registry and discuss how they impact the available data. We provide a broad overview of the dental variables in the registry, and how the registration criteria for some of the core dental variables (gingivitis, periodontitis, and dental caries) have changed over time. We then provide examples of how aggregate variables for the core dental diseases, allowing for comparison across registration criteria, can be created. Results Most of the Danish population born during or after 1965 have a least one entry in the National Child Odontology Registry, with 68% having entries spanning their entire childhood and adolescence. The prevalence of gingivitis and periodontitis seem to increase significantly in the years immediately following changes in how registration criteria for these variables, raising questions as to whether these diseases are generally underreported, or subject to overreporting in the years following the registration changes. The mandatory ages of registration instituted in 2003, do not appear to have had a strong impact on the ages at which registrations are made. For variables not directly comparable across datasets due to changes in registration criteria aggregate variables of measurements can be computed in most cases. Conclusions The National Child Odontology Registry provides a unique opportunity to study the impact of childhood oral health on life trajectories, but using the registry is not without issues, and we strongly recommend consulting with experts in the field of odontology to ensure the best use of available data.

Abstract We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Abstract Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.

Abstract Background Glucokinase (GCK) regulates insulin secretion to maintain appropriate blood glucose levels. Sequence variants can alter GCK activity to cause hyperinsulinemic hypoglycemia or hyperglycemia associated with GCK-maturity-onset diabetes of the young (GCK-MODY), collectively affecting up to 10 million people worldwide. Patients with GCK-MODY are frequently misdiagnosed and treated unnecessarily. Genetic testing can prevent this but is hampered by the challenge of interpreting novel missense variants. Result Here, we exploit a multiplexed yeast complementation assay to measure both hyper- and hypoactive GCK variation, capturing 97% of all possible missense and nonsense variants. Activity scores correlate with in vitro catalytic efficiency, fasting glucose levels in carriers of GCK variants and with evolutionary conservation. Hypoactive variants are concentrated at buried positions, near the active site, and at a region of known importance for GCK conformational dynamics. Some hyperactive variants shift the conformational equilibrium towards the active state through a relative destabilization of the inactive conformation. Conclusion Our comprehensive assessment of GCK variant activity promises to facilitate variant interpretation and diagnosis, expand our mechanistic understanding of hyperactive variants, and inform development of therapeutics targeting GCK.

Background: Schizophrenia (SCZ) is a heterogeneous neuropsychiatric disorder for which current treatment has insufficient efficacy and severe adverse effects. The modifiable gut microbiome might be a potential target for intervention to improve neurobiological functions through the gut-microbiome-brain axis. Methods: In this case-control study, gut microbiota of 132 patients with SCZ and increased waist circumference were compared with gut microbiota of two age- and sex-matched control groups, composed of 132 healthy individuals and 132 individuals with metabolic syndrome. Shotgun sequencing was used to characterize fecal samples at the taxonomic and functional levels. Cognition of the patients with SCZ was evaluated using the Brief Assessment of Cognition instrument. Results: SCZ gut microbiota differed significantly from those of healthy control subjects and individuals with metabolic syndrome in terms of richness and global composition. SCZ gut microbiota were notably enriched in Flavonifractor plautii, Collinsella aerofaciens, Bilophila wadsworthia, and Sellimonas intestinalis, while depleted in Faecalibacterium prausnitzii, Ruminococcus lactaris, Ruminococcus bicirculans, and Veillonella rogosae. Functional potential of the gut microbiota accounted for 11% of cognition variability. In particular, the bacterial functional module for synthesizing tyrosine, a precursor for dopamine, was in SCZ cases positively associated with cognitive score (ρ = 0.34, q ≤ .1). Conclusions: Overall, this study shows that the gut microbiome of patients with SCZ differs greatly from that of healthy control subjects or individuals with metabolic syndrome. Cognitive function of patients with SCZ is associated with the potential for gut bacterial biosynthesis of tyrosine, a precursor for dopamine, suggesting that gut microbiota might be an intervention target for alleviation of cognitive dysfunction in SCZ.

ABSTRACTThe aim of this study was to examine the effect of diabetes and the diabetogenic TBC1D4 variant on kidney function in Greenland in a population-based setting. Health survey data and TBC1D4 genotypes from 5,336 Greenlanders were used to estimate odds ratios (ORs) of albuminuria (>30 mg/g creatinine) and chronic kidney disease (CKD, eGFR

ABSTRACTIn Greenland, traditional marine foods are increasingly being replaced by sucrose- and starch-rich foods. A knock-out c.273_274delAG variant in the sucrase-isomaltase (SI) gene is relatively common in Greenland, with homozygous carriers being unable to digest sucrose and some starch. The variant is associated with a healthier metabolic phenotype in Greenlanders, which is confirmed by SI-knockout mice. We aim to assess if the healthy phenotype is explained by metabolic and microbial differences and if food and taste preferences differ between SI-genotypes. This paper describes the protocol for a randomised cross-over trial conducted in Greenland in 2022 with two dietary interventions of three days; a traditional meat- and fish-rich diet and a starch-rich Western diet with 11 energy% sucrose. The power calculation showed that 22 homozygous SI-carriers and 22 non-carriers were sufficient to detect a 0.5 mmol/L difference in glycaemic variability (80% power, α=0.05). We enrolled 18 carriers and 20 non-carriers. We examined food preferences at baseline and collected samples before and after each intervention for metabolic, metabolome, and microbiome profiling. Analyses of samples have not been completed yet. The Ethics Committee of Greenland approved the study. Results will be disseminated in international peer-reviewed journals and to the general Greenlandic population. NCT05375656.

The spatial and frontal QRS-T angles are electrocardiographic (ECG) predictors for arrhythmia. This work used genetic analyses to identify associated loci and pathways, and explore their relationships with other ECG traits and cardiovascular disease.

Abstract Background Multiple sclerosis is a chronic immune-mediated disease of the brain and spinal cord resulting in physical and cognitive impairment in young adults. It is hypothesized that a disrupted bacterial and viral gut microbiota is a part of the pathogenesis mediating disease impact through an altered gut microbiota-brain axis. The aim of this study is to explore the characteristics of gut microbiota in multiple sclerosis and to associate it with disease variables, as the etiology of the disease remains only partially known. Methods Here, in a case-control setting involving 148 Danish cases with multiple sclerosis and 148 matched healthy control subjects, we performed shotgun sequencing of fecal microbial DNA and associated bacterial and viral microbiota findings with plasma cytokines, blood cell gene expression profiles, and disease activity. Results We found 61 bacterial species that were differentially abundant when comparing all multiple sclerosis cases with healthy controls, among which 31 species were enriched in cases. A cluster of inflammation markers composed of blood leukocytes, CRP, and blood cell gene expression of IL17A and IL6 was positively associated with a cluster of multiple sclerosis-related species. Bacterial species that were more abundant in cases with disease-active treatment-naïve multiple sclerosis were positively linked to a group of plasma cytokines including IL-22, IL-17A, IFN-β, IL-33, and TNF-α. The bacterial species richness of treatment-naïve multiple sclerosis cases was associated with number of relapses over a follow-up period of 2 years. However, in non-disease-active cases, we identified two bacterial species, Faecalibacterium prausnitzii and Gordonibacter urolithinfaciens, whose absolute abundance was enriched. These bacteria are known to produce anti-inflammatory metabolites including butyrate and urolithin. In addition, cases with multiple sclerosis had a higher viral species diversity and a higher abundance of Caudovirales bacteriophages. Conclusions Considerable aberrations are present in the gut microbiota of patients with multiple sclerosis that are directly associated with blood biomarkers of inflammation, and in treatment-naïve cases bacterial richness is positively associated with disease activity. Yet, the finding of two symbiotic bacterial species in non-disease-active cases that produce favorable immune-modulating compounds provides a rationale for testing these bacteria as adjunct therapeutics in future clinical trials.

Mucopolysaccharidoses (MPSs) are inherited lysosomal storage disorders (LSDs). MPSs are caused by excessive accumulation of mucopolysaccharides due to missing or deficiency of enzymes required for the degradation of specific macromolecules. MPS I-IV, MPS VI, MPS VII, and MPS IX are sub-types of mucopolysaccharidoses. Among these, MPS III (also known as Sanfilippo) and MPS IV (Morquio) syndromes are lethal and prevalent sub-types. This study aimed to identify causal genetic variants in cases of MPS III and MPS IV and characterize genotype-phenotype relations in Pakistan. We performed clinical, biochemical and genetic analysis using Whole Genome Sequencing (WGS) in 14 Pakistani families affected with MPS III or MPS IV. Patients were classified into MPS III by history of aggressive behaviors, dementia, clear cornea and into MPS IV by short trunk, short stature, reversed ratio of upper segment to lower segment with a short upper segment. Data analysis and variant selections were made based on segregation analysis, examination of known MPS III and MPS IV genes, gene function, gene expression, the pathogenicity of variants based on ACMG guidelines and in silico analysis. In total, 58 individuals from 14 families were included in the present study. Six families were clinically diagnosed with MPS III and eight families with MPS IV. WGS revealed variants in MPS-associated genes including NAGLU, SGSH, GALNS, GNPTG as well as the genes VWA3B, BTD, and GNPTG which have not previously associated with MPS. One family had causal variants in both GALNS and BTD. Accurate and early diagnosis of MPS in children represents a helpful step for designing therapeutic strategies to protect different organs from permanent damage. In addition, pre-natal screening and identification of genetic etiology will facilitate genetic counselling of the affected families. Identification of novel causal MPS genes might help identifying new targeted therapies to treat LSDs.

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

The QT interval is a heritable electrocardiographic measure associated with arrhythmia risk when prolonged. Here, the authors used a series of genetic analyses to identify genetic loci, pathways, therapeutic targets, and relationships with cardiovascular disease.

Abstract The aim of this study is to characterize cell type-specific transcriptional signatures in non-alcoholic steatohepatitis (NASH) to improve our understanding of the disease. We performed single-cell RNA sequencing on liver biopsies from 10 patients with NASH. We applied weighted gene co-expression network analysis and validated our findings using a publicly available RNA sequencing data set derived from 160 patients with non-alcoholic fatty liver disease (NAFLD) and 24 controls with normal liver histology. Our study provides a comprehensive single-cell analysis of NASH pathology in humans, describing 19,627 single-cell transcriptomes from biopsy-proven NASH patients. Our data suggest that the previous notion of ”NASH-associated macrophages” can be explained by an up-regulation of normally existing subpopulations of liver macrophages. Similarly, we describe two distinct populations of activated hepatic stellate cells, associated with the level of fibrosis. Finally, we find that the expression of several circulating markers of NAFLD are co-regulated in hepatocytes together with predicted effector genes from NAFLD genome-wide association studies (GWAS), coupled to abnormalities in the complement system. In sum, our single-cell transcriptomic data set provides insights into novel cell type-specific and general biological processes associated with inflammation and fibrosis, emphasizing the importance of studying cell type-specific biological processes in human NASH.

Abstract Genetic predisposition and unhealthy lifestyle are risk factors for nonalcoholic fatty liver disease (NAFLD). We investigated whether the genetic risk of NAFLD is modified by physical activity, muscular fitness, and/or adiposity. In up to 242,524 UK Biobank participants without excessive alcohol intake or known liver disease, we examined cross‐sectional interactions and joint associations of physical activity, muscular fitness, body mass index (BMI), and a genetic risk score (GRS) with alanine aminotransferase (ALT) levels and the proxy definition for suspected NAFLD of ALT levels > 30 U/L in women and >40 U/L in men. Genetic predisposition to NAFLD was quantified using a GRS consisting of 68 loci known to be associated with chronically elevated ALT. Physical activity was assessed using accelerometry, and muscular fitness was estimated by measuring handgrip strength. We found that increased physical activity and grip strength modestly attenuate genetic predisposition to elevation in ALT levels, whereas higher BMI markedly amplifies it (all p values < 0.001). Among those with normal weight and high level of physical activity, the odds of suspected NAFLD were 1.6‐fold higher in those with high versus low genetic risk (reference group). In those with high genetic risk, the odds of suspected NAFLD were 12‐fold higher in obese participants with low physical activity versus those with normal weight and high physical activity (odds ratio for NAFLD = 19.2 and 1.6, respectively, vs. reference group). Conclusion: In individuals with high genetic predisposition for NAFLD, maintaining a normal body weight and increased physical activity may reduce the risk of NAFLD.

Introduction Diabetic kidney disease is a severe complication of diabetes. The diagnosis is based on clinical characteristics such as persistently elevated albuminuria, hypertension and decline in kidney function, although this definition is not specific to kidney disease caused by diabetes. The only way to establish an accurate diagnosis—diabetic nephropathy—is by performing a kidney biopsy. The histological presentation of diabetic nephropathy can be associated with a heterogeneous range of histological features with many pathophysiological factors involved demonstrating the complexity of the condition. Current treatment strategies aim to slow disease progression and are not specific to the underlying pathological processes.This study will investigate the prevalence of diabetic nephropathy in individuals with type 2 diabetes (T2D) and severely elevated albuminuria. The deep molecular characterisation of the kidney biopsy and biological specimens may pave the way for improved diagnostic accuracy and a better understanding of the pathological processes involved and may also reveal new targets for individualised treatment.Methods and analysis In the PRecIsion MEdicine based on kidney TIssue Molecular interrogation in diabetic nEphropathy 2 study, research kidney biopsies will be performed in 300 participants with T2D, urine albumin/creatinine ratio ≥700 mg/g and estimated glomerular filtration ratio >30 mL/min/1.73 m2. Cutting-edge molecular technologies will be applied to the kidney, blood, urine, faeces and saliva samples for comprehensive multi-omics profiling. The associated disease course and clinical outcomes will be assessed by annual follow-up for 20 years.Ethics and dissemination The Danish Regional Committee on Health Research Ethics and the Knowledge Center on Data Protection (in the Capital Region of Denmark) have granted approval for the study. The results will be published in peer-reviewed journals.Trial registration number NCT04916132.

Background: Functionally disruptive variants in the glucokinase gene (GCK) cause a form of mild non-progressive hyperglycemia, which does not require pharmacological treatment. A substantial proportion of patients with type 2 diabetes (T2D) carry GCK variants. We aimed to investigate whether carriers of rare GCK variants diagnosed with T2D have a glycemic phenotype and treatment response consistent with GCK-diabetes. Methods: Eight patients diagnosed with T2D from the Danish DD2 cohort who had previously undergone sequencing of GCK participated. Clinical examinations at baseline included an oral glucose tolerance test and continuous glucose monitoring. Carriers with a glycemic phenotype consistent with GCK-diabetes took part in a three-month treatment withdrawal. Results: Carriers of pathogenic and likely pathogenic variants had lower median fasting glucose and C-peptide levels compared to carriers of variants of uncertain significance and benign variants (median fasting glucose: 7.3 (interquartile range: 0.4) mmol/l vs. 9.5 (1.6) mmol/l, p = 0.04; median fasting C-peptide 902 (85) pmol/l vs. 1535 (295) pmol/l, p = 0.03). Four participants who discontinued metformin treatment and one diet-treated participant were reevaluated after three months. There was no deterioration of HbA1c or fasting glucose (median baseline HbA1c: 49 (3) vs. 51 (6) mmol/mol after three months, p = 0.4; median baseline fasting glucose: 7.3 (0.4) mmol/l vs. 7.0 (0.6) mmol/l after three months, p = 0.5). Participants did not consistently fulfill best practice guidelines for GCK screening nor clinical criteria for monogenic diabetes. Discussion: Carriers of pathogenic or likely pathogenic GCK variants identified by unselected screening in T2D should be reported, as they have a glycemic phenotype and treatment response consistent with GCK-diabetes. Variants of uncertain significance should be interpreted with care. Systematic genetic screening of patients with common T2D receiving routine care can lead to the identification and precise care of patients with misclassified GCK-diabetes who are not identifiable through common genetic screening criteria.

Background: Lysosomal storage disorders (LSDs) are a group of inherited metabolic diseases, which encompass more than 50 different subtypes of pathologies. These disorders are caused by defects in lysosomal enzymes, transporters, and other non-lysosomal proteins. Mucopolysaccharidosis (MPS) is the most common subgroup of lysosomal storage disorders in which the body is unable to properly breakdown mucopolysaccharides. The aim of the present study was to identify novel genes and pathogenic variants in families from diverse regions of Pakistan with clinically diagnosed mucopolysaccharidosis type I and mucopolysaccharidosis type II.Methods: Clinical diagnosis identified 12 with mucopolysaccharidosis I and 2 with mucopolysaccharidosis II in 14 families and whole genome sequencing (WGS) was performed to identify the causative variations in 15 affected individuals. Twenty-two unaffected individuals including parents or normal siblings of patients were also sequenced. Putative causal variants were identified by co-segregation and functional annotation.Results: Analysis of whole genome sequencing data revealed ten novel and six previously reported variants in lysosomal storage disorders-associated genes (IDUA, GALNS, SGSH, GAA, IDS, ALDOB, TRAPPC4, MASP1, SMARCAL, KIAA1109, HERC1, RRAS2) and a novel candidate gene (ABCA5) for lysosomal storage disorder-like phenotypes, which has previously been associated with symptoms strongly related with lysosomal storage disorder in animal models.Conclusion: Multigenic inheritance was found in several families highlighting the importance of searching for homozygous pathogenic variants in several genes also in families with a high degree of consanguinity.

Impaired mitochondrial function in liver tissue may contribute to the pathogenesis and disease progression of nonalcoholic fatty liver disease (NAFLD). Here the authors report that patients with obesity have lower mitochondrial capacity in adipose tissues but higher capacity in the liver, without overall associations to NAFLD severity, and that bariatric surgery increases hepatic mitochondrial respiration and mitochondrial biogenesis.

Background Lectin‐like oxidized low‐density lipoprotein (ox‐LDL) receptor‐1 is a scavenger receptor for oxidized low‐density lipoprotein. In adults, higher soluble lectin‐like ox‐LDL receptor‐1 (sLOX‐1) levels are associated with cardiovascular disease, type 2 diabetes, and obesity, but a similar link in pediatric overweight/obesity remains uncertain. Methods and Results Analyses were based on the cross‐sectional HOLBAEK Study, including 4‐ to 19‐year‐olds from an obesity clinic group with body mass index >90th percentile (n=1815) and from a population‐based group (n=2039). Fasting plasma levels of sLOX‐1 and inflammatory markers were quantified, cardiometabolic risk profiles were assessed, and linear and logistic regression analyses were performed. Pubertal/postpubertal children and adolescents from the obesity clinic group exhibited higher sLOX‐1 levels compared with the population (P

[This corrects the article DOI: 10.1371/journal.pone.0208645.].

Abstract The Faroese population isolate harbors epidemiological and genetic characteristics that likely differ from outbred populations. This population‐based register study found that the Faroese 2010–2020 crude incidence of amyotrophic lateral sclerosis (ALS) was 4.9/100,000 person‐years (95% confidence interval [CI], 3.3–7.0) and the age‐ and sex‐standardized incidence (US 2010 Census Population) was 4.1/100,000 person‐years (95% CI, 2.7–6.0), which is a 68% increase from the 1987–2009 estimate. The 2020 crude prevalence was 9.5/100,000 (95% CI, 3.0–19.6) in a population of 52,912 inhabitants. Incidence and prevalence estimates of ALS in the Faroes are high and further research is warranted to uncover the genetic or environmental determinants of ALS in this population.

Abstract High maternal body mass index (BMI) and smoking during pregnancy are risk factors for child overweight. Maternal smoking tends to reduce her BMI and the association of smoking with child overweight may be confounded by or interacting with maternal genetic predisposition to adiposity. In the Danish National Birth Cohort, we investigated whether smoking during pregnancy is associated with child BMI/overweight independent of pre-pregnancy BMI and maternal genetic predisposition to adiposity estimated as total, transmitted and non-transmitted genetic risk scores (GRSs) based on 941 common genetic variants associated with BMI. Smoking during pregnancy was associated with higher child BMI and higher odds of child overweight in a dose–response relationship. The odds ratio (95% CI) for smoking 11 + cigarettes in third trimester versus no smoking was 2.42 (1.30; 4.50), irrespective of maternal BMI and maternal GRSs (total, transmitted or non-transmitted). There were no statistically significant interactions between maternal GRSs and smoking (all p-values for interactions > 0.05). In conclusion, in this study, smoking during pregnancy exhibits a dose–response association with increased child BMI/overweight, independent of maternal pre-pregnancy BMI, maternal transmitted, and non-transmitted genetic predisposition to adiposity. Avoidance of smoking during pregnancy may help prevent childhood obesity irrespective of the mother–child genetic predisposition.

Bilirubin is the end product of heme catabolism, mainly produced by the breakdown of mature red blood cells. Due to its anti-inflammatory, antioxidant, antidiabetic, and antilipemic properties, circulating bilirubin concentrations are inversely associated with the risk of cardiovascular disease, type 2 diabetes, and all-cause mortality in adults. Some genetic loci associated with circulating bilirubin concentrations have been identified by genome-wide association studies in adults. We aimed to examine the relationship between circulating bilirubin, cardiometabolic risk factors, and inflammation in children and adolescents and the genetic architecture of plasma bilirubin concentrations. We measured fasting plasma bilirubin, cardiometabolic risk factors, and inflammatory markers in a sample of Danish children and adolescents with overweight or obesity (n = 1530) and in a population-based sample (n = 1820) of Danish children and adolescents. Linear and logistic regression analyses were performed to analyze the associations between bilirubin, cardiometabolic risk factors, and inflammatory markers. A genome-wide association study (GWAS) of fasting plasma concentrations of bilirubin was performed in children and adolescents with overweight or obesity and in a population-based sample. Bilirubin is associated inversely and significantly with a number of cardiometabolic risk factors, including body mass index (BMI) standard deviation scores (SDS), waist circumference, high-sensitivity C-reactive protein (hs-CRP), homeostatic model assessment for insulin resistance (HOMA-IR), hemoglobin A1c (HbA1c), low-density lipoprotein cholesterol (LDL-C), triglycerides, and the majority of measured inflammatory markers. In contrast, bilirubin was positively associated with fasting plasma concentrations of alanine transaminase (ALT), high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SDS), and the inflammatory markers GH, PTX3, THBS2, TNFRSF9, PGF, PAPPA, GT, CCL23, CX3CL1, SCF, and TRANCE. The GWAS showed that two loci were positively associated with plasma bilirubin concentrations at a p-value threshold of −8 (rs76999922: β = −0.65 SD; p = 4.3 × 10−8, and rs887829: β = 0.78 SD; p = 2.9 × 10−247). Approximately 25% of the variance in plasma bilirubin concentration was explained by rs887829. The rs887829 was not significantly associated with any of the mentioned cardiometabolic risk factors except for hs-CRP. Our findings suggest that plasma concentrations of bilirubin non-causally associates with cardiometabolic risk factors in children and adolescents.

Abstract Recent global developments underscore the prominent role big data have in modern medical science. But privacy issues constitute a prevalent problem for collecting and sharing data between researchers. However, synthetic data generated to represent real data carrying similar information and distribution may alleviate the privacy issue. In this study, we present generative adversarial networks (GANs) capable of generating realistic synthetic DeepFake 10-s 12-lead electrocardiograms (ECGs). We have developed and compared two methods, named WaveGAN* and Pulse2Pulse. We trained the GANs with 7,233 real normal ECGs to produce 121,977 DeepFake normal ECGs. By verifying the ECGs using a commercial ECG interpretation program (MUSE 12SL, GE Healthcare), we demonstrate that the Pulse2Pulse GAN was superior to the WaveGAN* to produce realistic ECGs. ECG intervals and amplitudes were similar between the DeepFake and real ECGs. Although these synthetic ECGs mimic the dataset used for creation, the ECGs are not linked to any individuals and may thus be used freely. The synthetic dataset will be available as open access for researchers at OSF.io and the DeepFake generator available at the Python Package Index (PyPI) for generating synthetic ECGs. In conclusion, we were able to generate realistic synthetic ECGs using generative adversarial neural networks on normal ECGs from two population studies, thereby addressing the relevant privacy issues in medical datasets.

Aims/hypothesisTo identify novel pathophysiological signatures of longstanding type 1 diabetes (T1D) with and without albuminuria we investigated the gut microbiome and blood metabolome in individuals with T1D and healthy controls (HC). We also mapped the functional underpinnings of the microbiome in relation to its metabolic role.MethodsOne hundred and sixty-one individuals with T1D and 50 HC were recruited at the Steno Diabetes Center Copenhagen, Denmark. T1D cases were stratified based on levels of albuminuria into normoalbuminuria, moderate and severely increased albuminuria. Shotgun sequencing of bacterial and viral microbiome in stool samples and circulating metabolites and lipids profiling using mass spectroscopy in plasma of all participants were performed. Functional mapping of microbiome into Gut Metabolic Modules (GMMs) was done using EggNog and KEGG databases. Multiomics integration was performed using MOFA tool.ResultsMeasures of the gut bacterial beta diversity differed significantly between T1D and HC, either with moderately or severely increased albuminuria. Taxonomic analyses of the bacterial microbiota identified 51 species that differed in absolute abundance between T1D and HC (17 higher, 34 lower). Stratified on levels of albuminuria, 10 species were differentially abundant for the moderately increased albuminuria group, 63 for the severely increased albuminuria group while 25 were common and differentially abundant both for moderately and severely increased albuminuria groups, when compared to HC. Functional characterization of the bacteriome identified 23 differentially enriched GMMs between T1D and HC, mostly involved in sugar and amino acid metabolism. No differences in relation to albuminuria stratification was observed. Twenty-five phages were differentially abundant between T1D and HC groups. Six of these varied with albuminuria status. Plasma metabolomics indicated differences in the steroidogenesis and sugar metabolism and circulating sphingolipids in T1D individuals. We identified association between sphingolipid levels and Bacteroides sp. abundances. MOFA revealed reduced interactions between gut microbiome and plasma metabolome profiles albeit polar metabolite, lipids and bacteriome compositions contributed to the variance in albuminuria levels among T1D individuals.ConclusionsIndividuals with T1D and progressive kidney disease stratified on levels of albuminuria show distinct signatures in their gut microbiome and blood metabolome.

Aims: To investigate the prevalence of pathogenic variants in monogenic diabetes genes in Emirati women with gestational diabetes (GDM) and examine the risk of developing hyperglycemia during follow-up in carriers and non-carriers. Methods: Female patients with GDM (n = 370) were identified. Selected monogenic diabetes genes, GCK, HNF1A, HNF4A, HNF1B, INS, ABCC8 and KCNJ1I, were examined by sequencing and identified variants were classified. Anthropometrics and subsequent diagnosis of diabetes were extracted from hospital records. Median follow-up time was 6-years. Results: A total of 34 variants were detected. Seven women (2%) were carriers of pathogenic variants in GCK, HNF1A, INS, ABCC8 or KCNJ11. A significantly larger fraction of women carrying pathogenic variants were diagnosed with any form of hyperglycemia or diabetes postpartum (risk ratio = 1.8 (1.1–2.9), p = 0.02) or 2.5 (1.3–4.8; p = 0.009), respectively) and they had a shorter disease-free period after GDM compared to women without such variants. There were no significant associations between carrying pathogenic variants and anthropometric measures or C-peptide. Conclusions: Pathogenic variants were found in known monogenic diabetes genes in two percent of Emirati women with GDM, allowing for precision medicine utilisation in these women both during and outside pregnancy. Carriers were at an increased risk of being diagnosed with hyperglycemia or type 2 diabetes mellitus within 5 years after pregnancy.

Since 1993, regular population health surveys in Greenland have supported and monitored the public health strategy of Greenland and have monitored cardiometabolic and lung diseases. The most recent of these surveys included 2539 persons aged 15+ from 20 communities spread over the whole country. The survey instruments included personal interviews, self-administered questionnaires, blood sampling, anthropometric measurements, blood pressure, ECG, oral glucose test, pulmonary function, hand grip strength and chair stand test. Blood samples were analysed for glucose, glycated haemoglobin (HbA1c), insulin, incretin hormones, cholesterol, kidney function, fatty acids in erythrocyte membranes and mercury, urine for albumin-creatinine ratio, and aliquots were stored at −80°C for future use. Data were furthermore collected for studies of the gut microbiome and diabetes complications. Survey participants were followed up with register data. The potential of the study is to contribute to the continued monitoring of risk factors and health conditions as part of Greenland’s public health strategy and to study the epidemiology of cardiometabolic diseases and other chronic diseases and behavioural risk factors. The next population health survey is planned for 2024. The emphasis of the article is on the methods of the study and results will be presented in other publications.

IntroductionPrevious research indicates that the salivary microbiota may be a biomarker of oral as well as systemic disease. However, clarifying the potential bias from general health status and lifestyle-associated factors is a prerequisite of using the salivary microbiota for screening.Materials & MethodsADDDITION-PRO is a nationwide Danish cohort, nested within the Danish arm of the Anglo-Danish-Dutch Study of Intensive treatment in People with Screen-Detected Diabetes in Primary Care. Saliva samples from n=746 individuals from the ADDITION-PRO cohort were characterized using 16s rRNA sequencing. Alpha- and beta diversity as well as relative abundance of genera was examined in relation to general health and lifestyle-associated variables. Permutational multivariate analysis of variance (PERMANOVA) was performed on individual variables and all variables together. Classification models were created using sparse partial-least squares discriminant analysis (sPLSDA) for variables that showed statistically significant differences based on PERMANOVA analysis (p < 0.05).ResultsGlycemic status, hemoglobin-A1c (HbA1c) level, sex, smoking and weekly alcohol intake were found to be significantly associated with salivary microbial composition (individual variables PERMANOVA, p < 0.05). Collectively, these variables were associated with approximately 5.8% of the observed differences in the composition of the salivary microbiota. Smoking status was associated with 3.3% of observed difference, and smoking could be detected with good accuracy based on salivary microbial composition (AUC 0.95, correct classification rate 79.6%).ConclusionsGlycemic status, HbA1c level, sex, smoking and weekly alcohol intake were significantly associated with the composition of the salivary microbiota. Despite smoking only being associated with 3.3% of the difference in overall salivary microbial composition, it was possible to create a model for detection of smoking status with a high correct classification rate. However, the lack of information on the oral health status of participants serves as a limitation in the present study. Further studies in other cohorts are needed to validate the external validity of these findings.

Background Monocytes/macrophages participate in cardiovascular disease. CD163 (cluster of differentiation 163) is a monocyte/macrophage receptor, and the shed sCD163 (soluble CD163) reflects monocyte/macrophage activation. We examined the association of sCD163 with incident cardiovascular disease events and performed a genome‐wide association study to identify sCD163‐associated variants. Methods and Results We measured plasma sCD163 in 5214 adults (aged ≥65 years, 58.7% women, 16.2% Black) of the CHS (Cardiovascular Health Study). We used Cox regression models (associations of sCD163 with incident events and mortality); median follow‐up was 26 years. Genome‐wide association study analyses were stratified on race. Adjusted for age, sex, and race and ethnicity, sCD163 levels were associated with all‐cause mortality (hazard ratio [HR], 1.08 [95% CI, 1.04–1.12] per SD increase), cardiovascular disease mortality (HR, 1.15 [95% CI, 1.09–1.21]), incident coronary heart disease (HR, 1.10 [95% CI, 1.04–1.16]), and incident heart failure (HR, 1.18 [95% CI, 1.12–1.25]). When further adjusted (eg, cardiovascular disease risk factors), only incident coronary heart disease lost significance. In European American individuals, genome‐wide association studies identified 38 variants on chromosome 2 near MGAT5 (top result rs62165726, P=3.3×10−18),19 variants near chromosome 17 gene ASGR1 (rs55714927, P=1.5×10−14), and 18 variants near chromosome 11 gene ST3GAL4. These regions replicated in the European ancestry ADDITION‐PRO cohort, a longitudinal cohort study nested in the Danish arm of the Anglo‐Danish‐Dutch study of Intensive Treatment Intensive Treatment In peOple with screeNdetcted Diabetes in Primary Care. In Black individuals, we identified 9 variants on chromosome 6 (rs3129781 P=7.1×10−9) in the HLA region, and 3 variants (rs115391969 P=4.3×10−8) near the chromosome 16 gene MYLK3. Conclusions Monocyte function, as measured by sCD163, may be predictive of overall and cardiovascular‐specific mortality and incident heart failure.

Abstract Knowledge about in vivo effects of human circulating C-6 hydroxylated bile acids (BAs), also called muricholic acids, is sparse. It is unsettled if the gut microbiome might contribute to their biosynthesis. Here, we measured a range of serum BAs and related them to markers of human metabolic health and the gut microbiome. We examined 283 non-obese and obese Danish adults from the MetaHit study. Fasting concentrations of serum BAs were quantified using ultra-performance liquid chromatography-tandem mass-spectrometry. The gut microbiome was characterized with shotgun metagenomic sequencing and genome-scale metabolic modeling. We find that tauro- and glycohyocholic acid correlated inversely with body mass index (P = 4.1e-03, P = 1.9e-05, respectively), waist circumference (P = 0.017, P = 1.1e-04, respectively), body fat percentage (P = 2.5e-03, P = 2.3e-06, respectively), insulin resistance (P = 0.051, P = 4.6e-4, respectively), fasting concentrations of triglycerides (P = 0.06, P = 9.2e-4, respectively) and leptin (P = 0.067, P = 9.2e-4). Tauro- and glycohyocholic acids, and tauro-a-muricholic acid were directly linked with a distinct gut microbial community primarily composed of Clostridia species (P = 0.037, P = 0.013, P = 0.027, respectively). We conclude that serum conjugated C-6-hydroxylated BAs associate with measures of human metabolic health and gut communities of Clostridia species. The findings merit preclinical interventions and human feasibility studies to explore the therapeutic potential of these BAs in obesity and type 2 diabetes.

Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants.

Abstract Deep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors are ultimately responsible for clinical decision-making, any deep learning-based prediction should be accompanied by an explanation that a human can understand. We present an approach called electrocardiogram gradient class activation map (ECGradCAM), which is used to generate attention maps and explain the reasoning behind deep learning-based decision-making in ECG analysis. Attention maps may be used in the clinic to aid diagnosis, discover new medical knowledge, and identify novel features and characteristics of medical tests. In this paper, we showcase how ECGradCAM attention maps can unmask how a novel deep learning model measures both amplitudes and intervals in 12-lead electrocardiograms, and we show an example of how attention maps may be used to develop novel ECG features.