Sudden cardiac death after myocardial infarction: individual participant data from pooled cohorts.

BACKGROUND AND AIMS: Risk stratification of sudden cardiac death after myocardial infarction and prevention by defibrillator rely on left ventricular ejection fraction (LVEF). Improved risk stratification across the whole LVEF range is required for decision-making on defibrillator implantation. METHODS: The analysis pooled 20 data sets with 140 204 post-myocardial infarction patients containing information on demographics, medical history, clinical characteristics, biomarkers, electrocardiography, echocardiography, and cardiac magnetic resonance imaging. Separate analyses were performed in patients (i) carrying a primary prevention cardioverter-defibrillator with LVEF ≤ 35% [implantable cardioverter-defibrillator (ICD) patients], (ii) without cardioverter-defibrillator with LVEF ≤ 35% (non-ICD patients ≤ 35%), and (iii) without cardioverter-defibrillator with LVEF > 35% (non-ICD patients >35%). Primary outcome was sudden cardiac death or, in defibrillator carriers, appropriate defibrillator therapy. Using a competing risk framework and systematic internal-external cross-validation, a model using LVEF only, a multivariable flexible parametric survival model, and a multivariable random forest survival model were developed and externally validated. Predictive performance was assessed by random effect meta-analysis. RESULTS: There were 1326 primary outcomes in 7543 ICD patients, 1193 in 25 058 non-ICD patients ≤35%, and 1567 in 107 603 non-ICD patients >35% during mean follow-up of 30.0, 46.5, and 57.6 months, respectively. In these three subgroups, LVEF poorly predicted sudden cardiac death (c-statistics between 0.50 and 0.56). Considering additional parameters did not improve calibration and discrimination, and model generalizability was poor. CONCLUSIONS: More accurate risk stratification for sudden cardiac death and identification of low-risk individuals with severely reduced LVEF or of high-risk individuals with preserved LVEF was not feasible, neither using LVEF nor using other predictors.

Multi-omics analysis reveals the key factors involved in the severity of the Alzheimer's disease.

Alzheimer's disease (AD) is a debilitating neurodegenerative disorder with a global impact, yet its pathogenesis remains poorly understood. While age, metabolic abnormalities, and accumulation of neurotoxic substances are potential risk factors for AD, their effects are confounded by other factors. To address this challenge, we first utilized multi-omics data from 87 well phenotyped AD patients and generated plasma proteomics and metabolomics data, as well as gut and saliva metagenomics data to investigate the molecular-level alterations accounting the host-microbiome interactions. Second, we analyzed individual omics data and identified the key parameters involved in the severity of the dementia in AD patients. Next, we employed Artificial Intelligence (AI) based models to predict AD severity based on the significantly altered features identified in each omics analysis. Based on our integrative analysis, we found the clinical relevance of plasma proteins, including SKAP1 and NEFL, plasma metabolites including homovanillate and glutamate, and Paraprevotella clara in gut microbiome in predicting the AD severity. Finally, we validated the predictive power of our AI based models by generating additional multi-omics data from the same group of AD patients by following up for 3 months. Hence, we observed that these results may have important implications for the development of potential diagnostic and therapeutic approaches for AD patients.

Geometric Changes in Mitral Valve Apparatus during Long-term Cardiac Resynchronization Therapy as Assessed with Cardiac CT.

Purpose To assess long-term geometric changes of the mitral valve apparatus using cardiac CT in individuals who underwent cardiac resynchronization therapy (CRT). Materials and Methods Participants from a randomized controlled trial with cardiac CT examinations before CRT implantation and at 6 months follow-up (Clinicaltrials.gov identifier NCT01323686) were invited to undergo an additional long-term follow-up cardiac CT examination. The geometry of the mitral valve apparatus, including mitral valve annulus area, A2 leaflet angle, tenting height, and interpapillary muscle distances, were assessed. Geometric changes at the long-term follow-up examination were reported as mean differences (95% CI), and the Pearson correlation test was used to assess correlation between statistically significant geometric changes and left ventricular (LV) volumes and function. Results Thirty participants (mean age, 68 years ± 9 [SD]; 25 male participants) underwent cardiac CT imaging after a median long-term follow-up of 9.0 years (IQR, 8.4-9.4). There were reductions in end-systolic A2 leaflet angle (-4° [95% CI: -7, -2]), end-systolic tenting height (-1 mm [95% CI: -2, -1]), and end-systolic and end-diastolic interpapillary muscle distances (-4 mm [95% CI: -6, -2]) compared with pre-CRT implantation values. The mitral valve annulus area remained unchanged. LV end-diastolic and end-systolic volumes decreased (-68 mL [95% CI: -99, -37] and -67 mL [95% CI: -96, -39], respectively), and LV ejection fraction increased (13% [95% CI: 7, 19]) at the long-term follow-up examination. Changes in interpapillary muscle distances showed moderate to strong correlations with LV volumes (r = 0.42-0.72; P < .05), while A2 leaflet angle and tenting height were not correlated to LV volumes or function. Conclusion Among the various geometric changes in the mitral valve apparatus after long-term CRT, the reduction in interpapillary muscle distances correlated with LV volumes while the reduced A2 leaflet angle and tenting height did not correlate with LV volumes. Keywords: Mitral Valve Apparatus, Cardiac Resynchronization Therapy, Cardiac CT Supplemental material is available for this article. © RSNA, 2024.

De novo production of protoberberine and benzophenanthridine alkaloids through metabolic engineering of yeast.

Protoberberine alkaloids and benzophenanthridine alkaloids (BZDAs) are subgroups of benzylisoquinoline alkaloids (BIAs), which represent a diverse class of plant-specialized natural metabolites with many pharmacological properties. Microbial biosynthesis has been allowed for accessibility and scalable production of high-value BIAs. Here, we engineer Saccharomyces cerevisiae to de novo produce a series of protoberberines and BZDAs, including palmatine, berberine, chelerythrine, sanguinarine and chelirubine. An ER compartmentalization strategy is developed to improve vacuole protein berberine bridge enzyme (BBE) activity, resulting in >200% increase on the production of the key intermediate (S)-scoulerine. Another promiscuous vacuole protein dihydrobenzophenanthridine oxidase (DBOX) has been identified to catalyze two-electron oxidation on various tetrahydroprotoberberines at N7-C8 position and dihydrobenzophenanthridine alkaloids. Furthermore, cytosolically expressed DBOX can alleviate the limitation on BBE. This study highlights the potential of microbial cell factories for the biosynthesis of a diverse group of BIAs through engineering of heterologous plant enzymes.

Incidence of Staphylococcus aureus Bacteremia in Patients Following Implantation of Cardiac Implantable Electronic Devices: A Danish Nationwide Cohort Study.

Background: Staphylococcus aureus bacteremia (SAB) is a high-risk condition associated with high morbidity and mortality. In the presence of cardiac implantable electronic devices (CIEDs), SAB may cause or clinically indicate device infection. We aimed to estimate the 10-year absolute risk of SAB in adult Danish first-time CIED carriers. Secondary aims included identification of risk factors associated with SAB. Methods: A registry-based study utilizing Danish nationwide registers and including consecutive Danish patients undergoing first CIED implantation between 2000 and 2020 was conducted. The primary outcome was first-time SAB after CIED implantation. Results: A total of 87 257 patients with first CIED implantation in the study period were identified (median age, 75 years; 62.6% were male; median follow-up, 3.8 years). Patients with pacemakers (PMs) were older and with more noncardiovascular comorbidities compared to patients with implantable cardioverter defibrillators (ICDs) and cardiac resynchronization therapy devices with or without defibrillator capacity (CRTs). In total, 1366 patients (1.6%) developed SAB. The 10-year absolute risk (95% confidence interval) of SAB was 2.0% (1.9%-2.1%) for PM, 2.6% (2.2%-3.1%) for ICD, and 3.7% (3.0%-4.5%) for CRT. A multivariable Cox analysis identified hemodialysis (hazard ratio [HR], 8.51), SAB before CIED (HR, 2.76), liver disease (HR, 2.35), and carrying a CRT device (HR, 1.68) among the covariates associated with increased risk of SAB. Conclusions: The absolute risk of SAB in Danish CIED carriers increased with more advanced CIED systems. The risk was highest within the first 3 months after CIED implantation and increased with the presence of certain covariates including renal dialysis, SAB before CIED, male sex, and advancing age.

Metabolic engineering of Saccharomyces cerevisiae for enhanced taxadiene production.

BACKGROUND: Metabolic engineering enables the sustainable and cost-efficient production of complex chemicals. Efficient production of terpenes in Saccharomyces cerevisiae can be achieved by recruiting an intermediate of the mevalonate pathway. The present study aimed to evaluate the engineering strategies of S. cerevisiae for the production of taxadiene, a precursor of taxol, an antineoplastic drug. RESULT: SCIGS22a, a previously engineered strain with modifications in the mevalonate pathway (MVA), was used as a background strain. This strain was engineered to enable a high flux towards farnesyl diphosphate (FPP) and the availability of NADPH. The strain MVA was generated from SCIGS22a by overexpressing all mevalonate pathway genes. Combining the background strains with 16 different episomal plasmids, which included the combination of 4 genes: tHMGR (3-hydroxy-3-methylglutaryl-CoA reductase), ERG20 (farnesyl pyrophosphate synthase), GGPPS (geranyl diphosphate synthase) and TS (taxadiene synthase) resulted in the highest taxadiene production in S. cerevisiae of 528 mg/L. CONCLUSION: Our study highlights the critical role of pathway balance in metabolic engineering, mainly when dealing with toxic molecules like taxadiene. We achieved significant improvements in taxadiene production by employing a combinatorial approach and focusing on balancing the downstream and upstream pathways. These findings emphasize the importance of minor gene expression modification levels to achieve a well-balanced pathway, ultimately leading to enhanced taxadiene accumulation.

The Danish Centre for Strategic Research in Type 2 Diabetes (DD2) Project Cohort and Biobank from 2010 Through 2023-A Cohort Profile Update.

Purpose: This paper provides an overview of the Danish Centre for Strategic Research in Type 2 Diabetes (DD2) cohort and biobank, including baseline characteristics of participants enrolled up to 2023, and post-enrollment rates of cardiovascular disease outcomes and mortality. Methods: Since 2010, the DD2 project has enrolled individuals with type 2 diabetes mellitus (T2DM) recently diagnosed by general practitioners and by hospital-based clinicians across Denmark. Data from questionnaires, clinical examinations, and biological samples are collected at enrollment. Additional baseline and longitudinal follow-up data are accessed via linkage to health registries. Results: Between 2010 and 2023, the DD2 project enrolled 11,369 participants (41.3% women, median age 61.4 years). Median T2DM duration at enrollment was 1.3 years, and median BMI was 31.6 kg/m2 for women and 30.5 kg/m2 for men. 18.3% were smokers, 5.7% consumed more than 14/21 units of alcohol weekly (women/men), and 17.9% reported leisure-time physical inactivity. Original midwife records dating back >80 years revealed that 20.2% of cohort participants had birth weights <3000 g. Based on complete hospital contact history 10 years before enrollment, 20.7% of cohort participants had macrovascular complications, 17.0% had microvascular complications, and 21.7% had kidney disease based on eGFR or urine albumin-creatinine measurements. At enrollment, statins were used by 68.2%, antihypertensive drugs by 69.9%, and glucose-lowering drugs by 86.5% of individuals. Median HbA1c was 48 mmol/mol and median LDL cholesterol 2.2 mmol/L. Genome-wide genotyping and biomarker data have been analyzed for over 9000 individuals. During the current follow-up time from the enrollment date (median 7.9 years), incident cardiovascular disease rate has been 13.8 per 1000 person-years and the mortality rate has been 17.6 per 1000 person-years. Conclusion: The DD2 cohort, with its detailed information and long-term follow up, can improve our understanding of the progression and prevention of complications among individuals with newly diagnosed T2DM.

Pricing weekly motor insurance drivers' with behavioral and contextual telematics data.

Telematics boxes integrated into vehicles are instrumental in capturing driving data encompassing behavioral and contextual information, including speed, distance travelled by road type, and time of day. These data can be amalgamated with drivers' individual attributes and reported accident occurrences to their respective insurance providers. Our study analyzes a substantial sample size of 19,214 individual drivers over a span of 55 weeks, covering a cumulative distance of 181.4 million kilometers driven. Utilizing this dataset, we develop predictive models for weekly accident frequency. As anticipated based on prior research with yearly data, our findings affirm that behavioral traits, such as instances of excessive speed, and contextual data pertaining to road type and time of day significantly aid in ratemaking design. The predictive models enable the creation of driving scores and personalized warnings, presenting a potential to enhance traffic safety by alerting drivers to perilous conditions. Our discussion delves into the construction of multiplicative scores derived from Poisson regression, contrasting them with additive scores resulting from a linear probability model approach, which offer greater communicability. Furthermore, we demonstrate that the inclusion of lagged behavioral and contextual factors not only enhances prediction accuracy but also lays the foundation for a diverse range of usage-based insurance schemes for weekly payments.

Implantable cardioverter defibrillator therapy in paediatric patients for primary vs. secondary prevention.

AIMS: The decisions about placing an ICD in a child are more difficult than in an adult due to longer expected lifespan and the complication risk. Young patients gain the most years from ICDs, despite higher risk of device-related complications. The secondary prevention ICD indication is clear, and device is implanted regardless of potential complications. For primary prevention, risk of sudden cardiac death and complications need to be evaluated. We aimed to compare outcomes for primary and secondary prevention ICDs. METHODS AND RESULTS: Retrospective nationwide cohort study including paediatric patients identified from the Danish ICD registry with ICD implanted at an age ≤ 15 from 1982-21. Demographics, complications (composite of device-related infections or lead-failure requiring re-operation, mortality because of arrhythmia, or unknown cause), and mortality were retrieved from medical charts. Endpoint was appropriate therapy (shock or anti-tachycardia pacing for ventricular tachycardia or fibrillation). Of 72 receiving an ICD, the majority had channelopathies (n = 34) or structural heart diseases (n = 28). ICDs were implanted in 23 patients for primary prevention and 49 for secondary prevention, at median ages of 13.8 and 11.6 years (P-value 0.01), respectively. Median follow-up was 9.0 (interquartile ranges: 4.7-13.5) years. The 10-year cumulative incidence of first appropriate therapy was 70%, with complication and inappropriate therapy rates at 41% and 15%, respectively. No difference was observed between prevention groups for all outcomes. Six patients died during follow-up. CONCLUSION: In children, two-thirds are secondary prevention ICDs. Children have higher appropriate therapy and complication rates than adults, while the inappropriate therapy rate was low.

Discriminating Benign from Malignant Lung Diseases Using Plasma Glycosaminoglycans and Cell-Free DNA.

We aimed to investigate the use of free glycosaminoglycan profiles (GAGomes) and cfDNA in plasma to differentiate between lung cancer and benign lung disease, in a cohort of 113 patients initially suspected of lung cancer. GAGomes were analyzed in all samples using the MIRAM® Free Glycosaminoglycan Kit with ultra-high-performance liquid chromatography and electrospray ionization triple quadrupole mass spectrometry. In a subset of samples, cfDNA concentration and NGS-data was available. We detected two GAGome features, 0S chondroitin sulfate (CS), and 4S CS, with cancer-specific changes. Based on the observed GAGome changes, we devised a model to predict lung cancer. The model, named the GAGome score, could detect lung cancer with 41.2% sensitivity (95% CI: 9.2-54.2%) at 96.4% specificity (95% CI: 95.2-100.0%, n = 113). When we combined the GAGome score with a cfDNA-based model, the sensitivity increased from 42.6% (95% CI: 31.7-60.6%, cfDNA alone) to 70.5% (95% CI: 57.4-81.5%) at 95% specificity (95% CI: 75.1-100%, n = 74). Notably, the combined GAGome and cfDNA testing improved the sensitivity, compared to cfDNA alone, especially in ASCL stage I (55.6% vs 11.1%). Our findings show that plasma GAGome profiles can enhance cfDNA testing performance, highlighting the applicability of a multiomics approach in lung cancer diagnostics.

Urinary Free Glycosaminoglycans Identify Adults at High Risk of Developing Early-stage High-grade Bladder Cancer.

Background and objective: Screening for bladder cancer (BCa) could reduce mortality via early detection of early-stage high-grade (Ta/T1 N0 M0 grade 2-3) disease. Noninvasive biomarkers could aid in screening, but current markers lack the specificity required. The urinary free glycosaminoglycan profile (GAGome) is a promising biomarker for early detection of BCa metabolism. Methods: In a prospective case-control development study, we included patients with BCa or no evidence of disease (NED) and measured the urinary GAGome. We then developed a score to predict the probability of BCa using GAGome features that correlated with BCa versus NED according to Bayesian regression. Next, in a retrospective, population-based, case-control study, we included adults from the Lifelines Cohort Study who were presumed healthy at baseline. All cases with BCa confirmed in the cancer registry by the 2-yr or 6-yr study visit were matched to randomly selected control subjects. We developed a reference logistic regression model using age and sex to predict BCa at 7 yr after baseline. We then added the GAGome score to the model and assessed model improvement using the likelihood ratio test. We dichotomized outputs for the reference model and saturated model (reference + GAGome score) into high-risk versus low-risk categories using a 99% specificity cutoff and estimated the sensitivity for association with BCa at 7 yr. Key findings and limitations: We prospectively included 51 individuals with BCa and 38 with NED and observed alterations in three GAGome features compatible with BCa. We developed a score that discriminated BCa with an area under the receiver operating characteristic curve of 0.77 (95% confidence interval [CI] 0.67-0.87). We retrospectively selected a cohort of 1088 presumed healthy adults (median age 48 yr, 56% females), of whom 48 had developed BCa by 7 yr after baseline (median time to diagnosis 1.4 yr). The GAGome score was an independent predictor of BCa at 7 yr when added to the reference model (p < 0.001). The sensitivity for BCa at 7 yr for high-risk subjects was 31% (95% CI 20-43%) using the saturated model and 17% (95% CI 4.7-29%) using the reference model at 99% specificity (95% CI 98-99%). Conclusions and clinical implications: The urinary free GAGome is specifically altered in BCa and can be used for noninvasive identification of adults at high risk of developing BCa, independent of age and sex. This information could be useful for the design of risk-stratified targeted screening programs for BCa. Patient summary: We tested whether measurement of a class of sugars called glycosaminoglycans (GAGs) in urine could be used for early detection of bladder cancer. Our results show that GAG levels in urine can distinguish people at high risk of developing bladder cancer within 7 years, even if they are healthy at the time of the urine sampling.

Task difficulty of visually guided gait modifications involves differences in central drive to spinal motor neurons.

Walking in natural environments requires visually guided modifications, which can be more challenging when involving sideways steps rather than longer steps. This exploratory study investigated whether these two types of modifications involve different changes in the central drive to spinal motor neurons of leg muscles. Fifteen adults [age: 36 ± 6 (SD) years] walked on a treadmill (4 km/h) while observing a screen displaying the real-time position of their toes. At the beginning of the swing phase, a visual target appeared in front (forward) or medial-lateral (sideways) of the ground contact in random step cycles (approximately every third step). We measured three-dimensional kinematics and electromyographic activity from leg muscles bilaterally. Intermuscular coherence was calculated in the alpha (5-15 Hz), beta (15-30 Hz), and gamma bands (30-45 Hz) approximately 230 ms before and after ground contact in control and target steps. Results showed that adjustments toward sideways targets were associated with significantly higher error, lower foot lift, and higher cocontraction between antagonist ankle muscles. Movements toward sideways targets were associated with larger beta-band soleus (SOL): medial gastrocnemius (MG) coherence and a more narrow and larger peak of synchronization in the cumulant density before ground contact. In contrast, movements toward forward targets showed no significant differences in coherence or synchronization compared with control steps. Larger SOL:MG beta-band coherence and short-term synchronization were observed during sideways, but not forward, gait modifications. This suggests that visually guided gait modifications may involve differences in the central drive to spinal ankle motor neurons dependent on the level of task difficulty.NEW & NOTEWORTHY This exploratory study suggests a specific and temporally restricted increase of central (likely corticospinal) drive to ankle muscles in relation to visually guided gait modifications. The findings indicate that a high level of visual attention to control the position of the ankle joint precisely before ground contact may involve increased central drive to ankle muscles. These findings are important for understanding the neural mechanisms underlying visually guided gait and may help develop rehabilitation interventions.

Yeast9: a consensus genome-scale metabolic model for S. cerevisiae curated by the community.

Genome-scale metabolic models (GEMs) can facilitate metabolism-focused multi-omics integrative analysis. Since Yeast8, the yeast-GEM of Saccharomyces cerevisiae, published in 2019, has been continuously updated by the community. This has increased the quality and scope of the model, culminating now in Yeast9. To evaluate its predictive performance, we generated 163 condition-specific GEMs constrained by single-cell transcriptomics from osmotic pressure or reference conditions. Comparative flux analysis showed that yeast adapting to high osmotic pressure benefits from upregulating fluxes through central carbon metabolism. Furthermore, combining Yeast9 with proteomics revealed metabolic rewiring underlying its preference for nitrogen sources. Lastly, we created strain-specific GEMs (ssGEMs) constrained by transcriptomics for 1229 mutant strains. Well able to predict the strains' growth rates, fluxomics from those large-scale ssGEMs outperformed transcriptomics in predicting functional categories for all studied genes in machine learning models. Based on those findings we anticipate that Yeast9 will continue to empower systems biology studies of yeast metabolism.

Anthropometric measures and long-term mortality in non-ischaemic heart failure with reduced ejection fraction: Questioning the obesity paradox.

AIMS: Although body mass index (BMI) is the most commonly used anthropometric measure to assess adiposity, alternative indices such as the waist-to-height ratio may better reflect the location and amount of ectopic fat as well as the weight of the skeleton. METHODS AND RESULTS: The prognostic value of several alternative anthropometric measures was compared with that of BMI in 1116 patients with non-ischaemic heart failure with reduced ejection fraction (HFrEF) enrolled in DANISH. The association between anthropometric measures and all-cause death was adjusted for prognostic variables, including natriuretic peptides. Median follow-up was 9.5 years (25th-75th percentile, 7.9-10.9). Compared to patients with a BMI 18.5-24.9 kg/m2 (n = 363), those with a BMI ≥25 kg/m2 had a higher risk of all-cause and cardiovascular death, although this association was only statistically significant for a BMI ≥35 kg/m2 (n = 91) (all-cause death: hazard ratio [HR] 1.78, 95% confidence interval [CI] 1.28-2.48; cardiovascular death: HR 2.46, 95% CI 1.69-3.58). Compared to a BMI 18.5-24.9 kg/m2, a BMI <18.5 kg/m2 (n = 24) was associated with a numerically, but not a significantly, higher risk of all-cause and cardiovascular death. Greater waist-to-height ratio (as an exemplar of indices not incorporating weight) was also associated with a higher risk of all-cause and cardiovascular death (HR for the highest vs. the lowest quintile: all-cause death: HR 2.11, 95% CI 1.53-2.92; cardiovascular death: HR 2.17, 95% CI 1.49-3.15). CONCLUSION: In patients with non-ischaemic HFrEF, there was a clear association between greater adiposity and higher long-term mortality. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT00542945.

Cell factory design with advanced metabolic modelling empowered by artificial intelligence.

Advances in synthetic biology and artificial intelligence (AI) have provided new opportunities for modern biotechnology. High-performance cell factories, the backbone of industrial biotechnology, are ultimately responsible for determining whether a bio-based product succeeds or fails in the fierce competition with petroleum-based products. To date, one of the greatest challenges in synthetic biology is the creation of high-performance cell factories in a consistent and efficient manner. As so-called white-box models, numerous metabolic network models have been developed and used in computational strain design. Moreover, great progress has been made in AI-powered strain engineering in recent years. Both approaches have advantages and disadvantages. Therefore, the deep integration of AI with metabolic models is crucial for the construction of superior cell factories with higher titres, yields and production rates. The detailed applications of the latest advanced metabolic models and AI in computational strain design are summarized in this review. Additionally, approaches for the deep integration of AI and metabolic models are discussed. It is anticipated that advanced mechanistic metabolic models powered by AI will pave the way for the efficient construction of powerful industrial chassis strains in the coming years.

Apixaban vs Aspirin According to CHA2DS2-VASc Score in Subclinical Atrial Fibrillation: Insights From ARTESiA.

BACKGROUND: ARTESiA (Apixaban for the Reduction of Thrombo-Embolism in Patients With Device-Detected Sub-Clinical Atrial Fibrillation) demonstrated that apixaban, compared with aspirin, significantly reduced stroke and systemic embolism (SE) but increased major bleeding in patients with subclinical atrial fibrillation. OBJECTIVES: To help inform decision making, the authors evaluated the efficacy and safety of apixaban according to baseline CHA2DS2-VASc score. METHODS: We performed a subgroup analysis according to baseline CHA2DS2-VASc score and assessed both the relative and absolute differences in stroke/SE and major bleeding. RESULTS: Baseline CHA2DS2-VASc scores were <4 in 1,578 (39.4%) patients, 4 in 1,349 (33.6%), and >4 in 1,085 (27.0%). For patients with CHA2DS2-VASc >4, the rate of stroke was 0.98%/year with apixaban and 2.25%/year with aspirin; compared with aspirin, apixaban prevented 1.28 (95% CI: 0.43-2.12) strokes/SE per 100 patient-years and caused 0.68 (95% CI: -0.23 to 1.57) major bleeds. For CHA2DS2-VASc <4, the stroke/SE rate was 0.85%/year with apixaban and 0.97%/year with aspirin. Apixaban prevented 0.12 (95% CI: -0.38 to 0.62) strokes/SE per 100 patient-years and caused 0.33 (95% CI: -0.27 to 0.92) major bleeds. For patients with CHA2DS2-VASc =4, apixaban prevented 0.32 (95% CI: -0.16 to 0.79) strokes/SE per 100 patient-years and caused 0.28 (95% CI: -0.30 to 0.86) major bleeds. CONCLUSIONS: One in 4 patients in ARTESiA with subclinical atrial fibrillation had a CHA2DS2-VASc score >4 and a stroke/SE risk of 2.2% per year. For these patients, the benefits of treatment with apixaban in preventing stroke/SE are greater than the risks. The opposite is true for patients with CHA2DS2-VASc score <4. A substantial intermediate group (CHA2DS2-VASc =4) exists in which patient preferences will inform treatment decisions. (Apixaban for the Reduction of Thrombo-Embolism in Patients With Device-Detected Sub-Clinical Atrial Fibrillation; NCT01938248).

Machine-Learning-Guided Peptide Drug Discovery: Development of GLP-1 Receptor Agonists with Improved Drug Properties.

Peptide-based drug discovery has surged with the development of peptide hormone-derived analogs for the treatment of diabetes and obesity. Machine learning (ML)-enabled quantitative structure-activity relationship (QSAR) approaches have shown great promise in small molecule drug discovery but have been less successful in peptide drug discovery due to limited data availability. We have developed a peptide drug discovery platform called streaMLine, enabling rigorous design, synthesis, screening, and ML-driven analysis of large peptide libraries. Using streaMLine, this study systematically explored secretin as a peptide backbone to generate potent, selective, and long-acting GLP-1R agonists with improved physicochemical properties. We synthesized and screened a total of 2688 peptides and applied ML-guided QSAR to identify multiple options for designing stable and potent GLP-1R agonists. One candidate, GUB021794, was profiled in vivo (S.C., 10 nmol/kg QD) and showed potent body weight loss in diet-induced obese mice and a half-life compatible with once-weekly dosing.

Coronary Artery Disease Is A Stronger Predictor of All-Cause Mortality Than Left Ventricular Ejection Fraction Among Patients With Newly Diagnosed Heart Failure: Insights From the WDHR.

BACKGROUND: In patients with newly diagnosed heart failure (HF) and left ventricular ejection fraction (LVEF) <50%, little is known whether LVEF per se or presence of coronary artery disease (CAD) provides independent prognostic information on all-cause mortality. METHODS AND RESULTS: Using the WDHR (Western Denmark Heart Registry), we identified 3620 patients with newly diagnosed HF and LVEF 10% to 49% referred for first-time coronary angiography as part of general workup of HF. Patients were stratified by LVEF (10%-35% versus 36%-49%) and presence of CAD. We estimated 10-year all-cause mortality risk and calculated hazard ratios adjusted for relevant comorbidities and risk factors (aHRs). CAD was present in 1592 (44%) patients. Lower LVEF was associated with a relative 15% increased 10-year mortality: 37% for LVEF 36% to 49% versus 42% for LVEF 10% to 35% (aHR, 1.15 [95% CI, 0.99-1.34]). This result did not change when stratified into those with CAD (52% versus 56%; aHR, 1.11 [95% CI, 0.91-1.35]) and those without CAD (27% versus 33%; aHR, 1.24 [95% CI, 0.97-1.57]). In comparison, presence and extent of CAD were associated with a relative 43% increased 10-year mortality (CAD versus no CAD, 55.0% versus 31.5%; aHR, 1.43 [95% CI, 1.25-1.64]). Compared with a matched general population, excess mortality risk was higher for patients with HF and CAD (54.7% versus 26.3%; aHR, 2.10 [95% CI, 1.85-2.39]) versus those with HF and no CAD (31.4% versus 17.2%; aHR, 1.76 [95% CI, 1.52-2.02]). CONCLUSIONS: Among newly diagnosed patients with HF and LVEF <50%, presence and extent of CAD are associated with substantial higher all-cause mortality risk than lower LVEF.

Global compositional and functional states of the human gut microbiome in health and disease.

The human gut microbiota is of increasing interest, with metagenomics a key tool for analyzing bacterial diversity and functionality in health and disease. Despite increasing efforts to expand microbial gene catalogs and an increasing number of metagenome-assembled genomes, there have been few pan-metagenomic association studies and in-depth functional analyses across different geographies and diseases. Here, we explored 6014 human gut metagenome samples across 19 countries and 23 diseases by performing compositional, functional cluster, and integrative analyses. Using interpreted machine learning classification models and statistical methods, we identified Fusobacterium nucleatum and Anaerostipes hadrus with the highest frequencies, enriched and depleted, respectively, across different disease cohorts. Distinct functional distributions were observed in the gut microbiomes of both westernized and nonwesternized populations. These compositional and functional analyses are presented in the open-access Human Gut Microbiome Atlas, allowing for the exploration of the richness, disease, and regional signatures of the gut microbiota across different cohorts.