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Animals such as raccoon dogs, mink and muskrats are farmed for fur and are sometimes used as food or medicinal products1,2, yet they are also potential reservoirs of emerging pathogens3. Here we performed single-sample metatranscriptomic sequencing of internal tissues from 461 individual fur animals that were found dead due to disease. We characterized 125 virus species, including 36 that were novel and 39 at potentially high risk of cross-species transmission, including zoonotic spillover. Notably, we identified seven species of coronaviruses, expanding their known host range, and documented the cross-species transmission of a novel canine respiratory coronavirus to raccoon dogs and of bat HKU5-like coronaviruses to mink, present at a high abundance in lung tissues. Three subtypes of influenza A virus—H1N2, H5N6 and H6N2—were detected in the lungs of guinea pig, mink and muskrat, respectively. Multiple known zoonotic viruses, such as Japanese encephalitis virus and mammalian orthoreovirus4,5, were detected in guinea pigs. Raccoon dogs and mink carried the highest number of potentially high-risk viruses, while viruses from the Coronaviridae, Paramyxoviridaeand Sedoreoviridaefamilies commonly infected multiple hosts. These data also reveal potential virus transmission between farmed animals and wild animals, and from humans to farmed animals, indicating that fur farming represents an important transmission hub for viral zoonoses.

In response to the emergence of SARS-CoV-2 variants of concern, the global scientific community, through unprecedented effort, has sequenced and shared over 11 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info, a platform that currently tracks over 40 million combinations of Pango lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials and the general public. We describe the interpretable visualizations available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data and the server infrastructure that enables widespread data dissemination via a high-performance API that can be accessed using an R package. We show how outbreak.infocan be used for genomic surveillance and as a hypothesis-generation tool to understand the ongoing pandemic at varying geographic and temporal scales.

The cardiovascular benefits of intensive systolic blood pressure control vary across clinical populations tested in large randomised clinical trials. We aimed to evaluate the application of machine learning to clinical trials of patients without and with type 2 diabetes to define the personalised cardiovascular benefit of intensive control of systolic blood pressure.

The SARS-CoV-2 Delta (Pango lineage B.1.617.2) variant of concern spread globally, causing resurgences of COVID-19 worldwide1,2. The emergence of the Delta variant in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 SARS-CoV-2 genomes from England together with 93,649 genomes from the rest of the world to reconstruct the emergence of Delta and quantify its introduction to and regional dissemination across England in the context of changing travel and social restrictions. Using analysis of human movement, contact tracing and virus genomic data, we find that the geographic focus of the expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced more than 1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers reduced onward transmission from importations; however, the transmission chains that later dominated the Delta wave in England were seeded before travel restrictions were introduced. Increasing inter-regional travel within England drove the nationwide dissemination of Delta, with some cities receiving more than 2,000 observable lineage introductions from elsewhere. Subsequently, increased levels of local population mixing—and not the number of importations—were associated with the faster relative spread of Delta. The invasion dynamics of Delta depended on spatial heterogeneity in contact patterns, and our findings will inform optimal spatial interventions to reduce the transmission of current and future variants of concern, such as Omicron (Pango lineage B.1.1.529).

Leptin is an adipocyte-secreted hormone important in energy homeostasis and diverse physiological processes. A circulating soluble form of the leptin receptor [soluble leptin receptor (sOB-R)] is the main leptin-binding protein and determinant of free leptin index (FLI), the presumed biologically active form of leptin. We performed observational and interventional studies to elucidate the regulation of sOB-R and FLI in humans. In a cross-sectional study (n = 118), leptin, gender, and adiposity were significant determinants of sOB-R. By multivariate analysis, estradiol (E2) and testosterone predict sOB-R, whereas insulin predicts leptin and FLI. In a frequent-sampling study (n = 6), sOB-R followed a significant circadian rhythm inverse to that of leptin, suggesting that leptin's biological activity may have an even more pronounced diurnal variation than originally thought. A 72-h fast in eight men decreased leptin levels by 80% and increased lymphocyte expression of leptin receptor mRNA and serum sOB-R levels by 100%. Physiological and pharmacological doses of recombinant-methionyl human leptin (rhLeptin) administered to fasted men prevented the fasting-induced increase of sOB-R levels, and pharmacological doses resulted in a decrease in sOB-R levels. These studies provide evidence that sOB-R is regulated by gender, adiposity, hormones, and rhLeptin administration. This may have important implications for the biological activity of leptin in disease states associated with abnormal leptin levels (e.g., obesity and anorexia nervosa)., Leptin, the protein product of the ob gene, is produced by adipose tissue and is secreted into circulation. It acts mainly in the hypothalamus but also in other tissues by [...]

Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) have been postulated to affect susceptibility to COVID-19. Observational studies so far have lacked rigorous ascertainment adjustment and international generalisability. We aimed to determine whether use of ACEIs or ARBs is associated with an increased susceptibility to COVID-19 in patients with hypertension.

After the first wave of SARS-CoV-2 infections in spring 2020, Europe experienced a resurgence of the virus starting in late summer 2020 that was deadlier and more difficult to contain1. Relaxed intervention measures and summer travel have been implicated as drivers of the second wave2. Here we build a phylogeographical model to evaluate how newly introduced lineages, as opposed to the rekindling of persistent lineages, contributed to the resurgence of COVID-19 in Europe. We inform this model using genomic, mobility and epidemiological data from 10 European countries and estimate that in many countries more than half of the lineages circulating in late summer resulted from new introductions since 15 June 2020. The success in onward transmission of newly introduced lineages was negatively associated with the local incidence of COVID-19 during this period. The pervasive spread of variants in summer 2020 highlights the threat of viral dissemination when restrictions are lifted, and this needs to be carefully considered in strategies to control the current spread of variants that are more transmissible and/or evade immunity. Our findings indicate that more effective and coordinated measures are required to contain the spread through cross-border travel even as vaccination is reducing disease burden.

IMPORTANCE: Chlorthalidone is currently recommended as the preferred thiazide diuretic to treat hypertension, but no trials have directly compared risks and benefits. OBJECTIVE: To compare the effectiveness and safety of chlorthalidone and hydrochlorothiazide as first-line therapies for hypertension in real-world practice. DESIGN, SETTING, AND PARTICIPANTS: This is a Large-Scale Evidence Generation and Evaluation in a Network of Databases (LEGEND) observational comparative cohort study with large-scale propensity score stratification and negative-control and synthetic positive-control calibration on databases spanning January 2001 through December 2018. Outpatient and inpatient care episodes of first-time users of antihypertensive monotherapy in the United States based on 2 administrative claims databases and 1 collection of electronic health records were analyzed. Analysis began June 2018. EXPOSURES: Chlorthalidone and hydrochlorothiazide. MAIN OUTCOMES AND MEASURES: The primary outcomes were acute myocardial infarction, hospitalization for heart failure, ischemic or hemorrhagic stroke, and a composite cardiovascular disease outcome including the first 3 outcomes and sudden cardiac death. Fifty-one safety outcomes were measured. RESULTS: Of 730 225 individuals (mean [SD] age, 51.5 [13.3] years; 450 100 women [61.6%]), 36 918 were dispensed or prescribed chlorthalidone and had 149 composite outcome events, and 693 337 were dispensed or prescribed hydrochlorothiazide and had 3089 composite outcome events. No significant difference was found in the associated risk of myocardial infarction, hospitalized heart failure, or stroke, with a calibrated hazard ratio for the composite cardiovascular outcome of 1.00 for chlorthalidone compared with hydrochlorothiazide (95% CI, 0.85-1.17). Chlorthalidone was associated with a significantly higher risk of hypokalemia (hazard ratio [HR], 2.72; 95% CI, 2.38-3.12), hyponatremia (HR, 1.31; 95% CI, 1.16-1.47), acute renal failure (HR, 1.37; 95% CI, 1.15-1.63), chronic kidney disease (HR, 1.24; 95% CI, 1.09-1.42), and type 2 diabetes mellitus (HR, 1.21; 95% CI, 1.12-1.30). Chlorthalidone was associated with a significantly lower risk of diagnosed abnormal weight gain (HR, 0.73; 95% CI, 0.61-0.86). CONCLUSIONS AND RELEVANCE: This study found that chlorthalidone use was not associated with significant cardiovascular benefits when compared with hydrochlorothiazide, while its use was associated with greater risk of renal and electrolyte abnormalities. These findings do not support current recommendations to prefer chlorthalidone vs hydrochlorothiazide for hypertension treatment in first-time users was found. We used advanced methods, sensitivity analyses, and diagnostics, but given the possibility of residual confounding and the limited length of observation periods, further study is warranted.

To characterize the incidence of kidney failure associated with intravitreal anti-VEGF exposure; and compare the risk of kidney failure in patients treated with ranibizumab, aflibercept, or bevacizumab.

Uncertainty remains about the optimal monotherapy for hypertension, with current guidelines recommending any primary agent among the first-line drug classes thiazide or thiazide-like diuretics, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, dihydropyridine calcium channel blockers, and non-dihydropyridine calcium channel blockers, in the absence of comorbid indications. Randomised trials have not further refined this choice.

The 2013–2016 West African epidemic caused by the Ebola virus was of unprecedented magnitude, duration and impact. Here we reconstruct the dispersal, proliferation and decline of Ebola virus throughout the region by analysing 1,610 Ebola virus genomes, which represent over 5% of the known cases. We test the association of geography, climate and demography with viral movement among administrative regions, inferring a classic ‘gravity’ model, with intense dispersal between larger and closer populations. Despite attenuation of international dispersal after border closures, cross-border transmission had already sown the seeds for an international epidemic, rendering these measures ineffective at curbing the epidemic. We address why the epidemic did not spread into neighbouring countries, showing that these countries were susceptible to substantial outbreaks but at lower risk of introductions. Finally, we reveal that this large epidemic was a heterogeneous and spatially dissociated collection of transmission clusters of varying size, duration and connectivity. These insights will help to inform interventions in future epidemics.

A study of the early genetic diversity and history of the HIV-1 epidemic in North America through sequencing of eight full-length viral genomes from the 1970s.

Background:The TOPCAT trial did not find an overall benefit of spironolactone in the management of HFpEF. However, subsequent investigations have found heterogeneous treatment effects across patients, questioning the extent TOPCAT is representative of the real world. Previous analyses addressing this question have been limited by focusing on single phenotypic axes that do not capture the entirety of the patient phenotypes.Methods:We constructed a multidimensional phenomap of TOPCAT on 76 pre-randomization characteristics spanning demographics, diagnoses, procedures, medications, labs, vitals, conditions, and imaging-derived measures. We then compared this map to patients with HFpEF in the EHR of the Yale-New Haven Hospital. The EHR cohort was based on echocardiography and selected if they had a HF hospitalization during 2015-2019. All corresponding 76 features were extracted for the Yale EHR population by a team of clinicians and data scientists. To accomplish this, we computed a pairwise Gower dissimilarity metric across the 76 pre-randomization characteristics. Results:Compared with TOPCAT participants (n=3445), Yale EHR (n=2394) patients were older (69 vs 78 years), more frequently women (52% vs 57%), and Black (9% vs 17%). In univariate analyses, there was similar use of anti-hypertensive therapy. Mutlivariately, however, there was minimal overlap of the clinical population in TOPCAT compared with the Yale EHR, with a median patient-level dissimilarity distance of 41% (IQR 35% - 43%) (Fig A), with qualitative separation in the clinical populations in the trial and EHR (Fig B).Conclusions:In assessments across 76 phenotypic features, there was minimal similarity in patients in TOPCAT and real-world patients drawn from EHR, suggesting challenges with generalizability of the findings. Phenomapping-based strategies can enhance quantitative and qualitative assessment of trial representativeness to real-world populations.

Introduction:Randomized controlled trials (RCT) represent the cornerstone of evidence-based medicine but often carry high financial costs and lengthy time frames.Hypothesis:We hypothesized that a machine learning (ML) strategy of predictive enrichment can reduce the size of RCTs through adaptive enrollment based on projected response profiles.Methods:We conducted a post-hocanalysis of individual patient data from the Insulin Resistance Intervention after Stroke (IRIS) trial using dynamic computational trial phenomapping. After a study period of 36 months, we performed serial annual interim analyses (A). For this, we designed an algorithm that used a phenotypic trial representation using 59 baseline variables to predict personalized effects of pioglitazone on fatal/nonfatal stroke or myocardial infarction (study outcome). Compared with a complete trial enrollment (100%), in an adaptive fashion, we a priorirestricted enrollment to two thirds (66.7%) of eligible participants between each interim analysis based on the projected treatment benefit. Since this was defined by their baseline phenotypic profile, treatment randomization was preserved. We employed these patient subsets as comparators and assessed the effect of pioglitazone on the study outcome through Cox regression models.Results:Compared to the unrestricted enrollment of participants (blue line), an ML-guided adaptive strategy of predictive enrichment (green line) was associated with defining the same treatment effect size with a lower trial size - 3876 vs 2946 participants (B-C). Both approaches appeared to meet statistical significance at 6 years after the trial onset (D-E). In contrast, a strategy of random patient selection (orange line) did not show significant benefit at the same population size.Conclusions:We developed an adaptive strategy for predictive enrichment to increase efficiency of RCTs using machine learning.

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To determine how HIV-1 risk groups impact transmitted diversity and the tempo of viral evolution at a population scale.

Threats to the validity of observational studies on the effects of interventions raise questions about the appropriate role of such studies in decision making. Nonetheless, scholarly journals in fields such as medicine, education, and the social sciences feature many such studies, often with limited exploration of these threats, and the lay press is rife with news stories based on these studies. Consumers of these studies rely on the expertise of the study authors to conduct appropriate analyses, and on the thoroughness of the scientific peer-review process to check the validity, but the introspective and ad hoc nature of the design of these analyses appears to elude any meaningful objective assessment of their performance. Here, we review some of the challenges encountered in observational studies and review an alternative, data-driven approach to observational study design, execution, and analysis. Although much work remains, we believe this research direction shows promise.

Host species switches by bacterial pathogens leading to new endemic infections are important evolutionary events that are difficult to reconstruct over the long term. We investigated the host switching of Staphylococcus aureusover a long evolutionary timeframe by developing Bayesian phylogenetic methods to account for uncertainty about past host associations and using estimates of evolutionary rates from serially sampled whole-genome data. Results suggest multiple jumps back and forth between human and bovids with the first switch from humans to bovids taking place around 5500 BP, coinciding with the expansion of cattle domestication throughout the Old World. The first switch to poultry is estimated at around 275 BP, long after domestication but still preceding large-scale commercial farming. These results are consistent with a central role for anthropogenic change in the emergence of new endemic diseases.

We propose a Bayesian multivariate model in which a single linear combination of the covariates predict multiple outcomes simultaneously. The single linear combination is a data-derived score along the lines of the Apache or Charlson index scores for critically ill patients, the Karnofsky or Eastern Cooperative Oncology Group score for cancer patients or Euro-score for cardiac patients that may be used to predict multiple outcomes. Outcomes may be discrete or continuous and we use a composition of generalized linear models for the marginal distribution for each outcome. We explain how to set the prior distribution and we use Markov chain Monte Carlo methods to calculate the posterior distribution. We propose two types of expanded models to diagnose whether each outcome indeed has predictor effects common with the other outcomes, and whether a particular predictor is commonly predictive for all outcomes. We determine a final model based on the diagnostic models. The method is applied to a study yielding multiple psychometric outcomes of mixed type measured in young people living with human immunodeficiency virus.

ObjectiveTo quantify the comparative risk of thrombosis with thrombocytopenia syndrome or thromboembolic events associated with use of adenovirus based covid-19 vaccines versus mRNA based covid-19 vaccines.DesignInternational network cohort study.SettingRoutinely collected health data from contributing datasets in France, Germany, the Netherlands, Spain, the UK, and the US.ParticipantsAdults (age ≥18 years) registered at any contributing database and who received at least one dose of a covid-19 vaccine (ChAdOx1-S (Oxford-AstraZeneca), BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), or Ad26.COV2.S (Janssen/Johnson & Johnson)), from December 2020 to mid-2021.Main outcome measuresThrombosis with thrombocytopenia syndrome or venous or arterial thromboembolic events within the 28 days after covid-19 vaccination. Incidence rate ratios were estimated after propensity scores matching and were calibrated using negative control outcomes. Estimates specific to the database were pooled by use of random effects meta-analyses.ResultsOverall, 1 332 719 of 3 829 822 first dose ChAdOx1-S recipients were matched to 2 124 339 of 2 149 679 BNT162b2 recipients from Germany and the UK. Additionally, 762 517 of 772 678 people receiving Ad26.COV2.S were matched to 2 851 976 of 7 606 693 receiving BNT162b2 in Germany, Spain, and the US. All 628 164 Ad26.COV2.S recipients from the US were matched to 2 230 157 of 3 923 371 mRNA-1273 recipients. A total of 862 thrombocytopenia events were observed in the matched first dose ChAdOx1-S recipients from Germany and the UK, and 520 events after a first dose of BNT162b2. Comparing ChAdOx1-S with a first dose of BNT162b2 revealed an increased risk of thrombocytopenia (pooled calibrated incidence rate ratio 1.33 (95% confidence interval 1.18 to 1.50) and calibrated incidence rate difference of 1.18 (0.57 to 1.8) per 1000 person years). Additionally, a pooled calibrated incidence rate ratio of 2.26 (0.93 to 5.52) for venous thrombosis with thrombocytopenia syndrome was seen with Ad26.COV2.S compared with BNT162b2.ConclusionsIn this multinational study, a pooled 30% increased risk of thrombocytopenia after a first dose of the ChAdOx1-S vaccine was observed, as was a trend towards an increased risk of venous thrombosis with thrombocytopenia syndrome after Ad26.COV2.S compared with BNT162b2. Although rare, the observed risks after adenovirus based vaccines should be considered when planning further immunisation campaigns and future vaccine development.

Emerging infectious diseases, especially if caused by bat-borne viruses, significantly affect public health and the global economy. There is an urgent need to understand the mechanism of interspecies transmission, particularly to humans. Viral genetics; host factors, including polymorphisms in the receptors; and ecological, environmental, and population dynamics are major parameters to consider. Here, we describe the taxonomy, geographic distribution, and unique traits of bats associated with their importance as virus reservoirs. Then, we summarize the origin, intermediate hosts, and the current understanding of interspecies transmission of Middle East respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), SARS-CoV-2, Nipah, Hendra, Ebola, Marburg virus, and rotaviruses. Finally, the molecular interactions of viral surface proteins with host cell receptors are examined, and a comparison of these interactions in humans, intermediate hosts, and bats is conducted. This uncovers adaptive mutations in virus spike protein that facilitate cross-species transmission and risk factors associated with the emergence of novel viruses from bats.

Adapting arguments from queuing theory, we investigate a mathematical model for protein production efficiency from mRNA. Our model involves six parameters: the mRNA length, the clearance distance a ribosome must travel from the initiation site before another ribosome can attach, the ribosomal attachment rate, the ribosomal traveling speed along the mRNA, the mRNA degradation rate, and the probability that a ribosome prematurely disengages from the mRNA. The model allows for different mechanisms of mRNA degradation; the more complicated mechanisms postulate a functional role for the mRNA poly A tail. We determine the probability generating function of the number Nof fully formed proteins from a single mRNA. This function yields the moments of Nexactly and the entire distribution of Nnumerically via the finite Fourier transform. Using biologically plausible estimates, we examine the sensitivity of protein production to the model parameters and degradation mechanisms. Model predictions are most sensitive to the degradation and attachment rates, two parameters which are poorly measured in vivo.

Electrochemical sensors have the capacity for rapid and accurate detection of a wide variety of target molecules in biological fluids. We have developed an electrochemical sensor assay involving hybridization of bacterial 16S rRNA to fluorescein-modified detector probes and to biotin-modified capture probes anchored to the sensor surface. Signal is generated by an oxidation-reduction current produced by the action of horseradish peroxidase conjugated to an anti-fluorescein monoclonal Fab. A previous study found that this electrochemical sensor strategy could identify uropathogens in clinical urine specimens. To improve assay sensitivity, we examined the key steps that affect the current amplitude of the electrochemical signal. Efficient lysis and release of 16S rRNA from both gram-negative and -positive bacteria was achieved with an initial treatment with Triton X-100 and lysozyme followed by alkaline lysis, resulting in a 12-fold increase in electrochemical signal compared with alkaline lysis alone. The distance in nucleotides between the target hybridization sites of the detector and capture probes and the location of fluorescein modification on the detector probe contributed to a 23-fold change in signal intensity. These results demonstrate the importance of target-probe and probe-probe interactions in the detection of bacterial 16S rRNA using an electrochemical DNA sensor approach.

Careful examination of viral dynamics during antiretroviral treatment can provide important insights into HIV pathogenesis. We examined viral evolution during and after enfuvirtide (T-20) treatment with an objective of defining the characteristics of viral evolution during advanced HIV immunodeficiency. Specifically, we examined the viral quasispecies from nine patients who experienced incomplete viral suppression on an enfuvirtide-based regimen, and who subsequently interrupted enfuvirtide while remaining on a stable optimized background regimen (enfuvirtide "partial treatment interruption"). On average, eight clones were sequenced from three time points: pre-enfuvirtide, post-enfuvirtide failure, and post-enfuvirtide interruption. We utilized a Bayesian hierarchical phylogenetic model to assess the evolutionary relatedness of the virus that emerged over time. In most subjects, interruption of enfuvirtide was associated with continued viral evolution as enfuvirtide mutations waned; in no subject did we find clear evidence supporting the reemergence of archived wild-type variants (Bayes factor = 30.2, p = 0.01). Evidence supporting ongoing viral evolution was particularly strong in subjects whose virus remained diverse or became more diverse during enfuvirtide therapy. In contrast to observations when all drugs are interrupted, loss of resistance during enfuvirtide interruption is most likely due to ongoing viral evolution (and back-mutation), rather than emergence of an archived virus.

ABSTRACTWe describe the first species-specific detection of bacterial pathogens in human clinical fluid samples using a microfabricated electrochemical sensor array. Each of the 16 sensors in the array consisted of three single-layer gold electrodes—working, reference, and auxiliary. Each of the working electrodes contained one representative from a library of capture probes, each specific for a clinically relevant bacterial urinary pathogen. The library included probes for Escherichia coli, Proteus mirabilis, Pseudomonas aeruginosa, Enterocococcusspp., and the Klebsiella-Enterobactergroup. A bacterial 16S rRNA target derived from single-step bacterial lysis was hybridized both to the biotin-modified capture probe on the sensor surface and to a second, fluorescein-modified detector probe. Detection of the target-probe hybrids was achieved through binding of a horseradish peroxidase (HRP)-conjugated anti-fluorescein antibody to the detector probe. Amperometric measurement of the catalyzed HRP reaction was obtained at a fixed potential of -200 mV between the working and reference electrodes. Species-specific detection of as few as 2,600 uropathogenic bacteria in culture, inoculated urine, and clinical urine samples was achieved within 45 min from the beginning of sample processing. In a feasibility study of this amperometric detection system using blinded clinical urine specimens, the sensor array had 100% sensitivity for direct detection of gram-negative bacteria without nucleic acid purification or amplification. Identification was demonstrated for 98% of gram-negative bacteria for which species-specific probes were available. When combined with a microfluidics-based sample preparation module, the integrated system could serve as a point-of-care device for rapid diagnosis of urinary tract infections.

To determine how knowledgeable physicians are regarding the toxic effects and drug interactions of herbal remedies.

Introduction:Intensive systolic blood pressure (SBP) control reduces major adverse cardiovascular events (MACE) in patients without type 2 diabetes mellitus (T2DM). However, these benefits are less clear in T2DM. We evaluated an application of machine learning to clinical trials of patients without and with T2DM in assessing a personalized cardiovascular benefit of intensive SBP control.Methods:In SPRINT, a trial of intensive (n=4678, SBP<120 mmHg) versus standard (n=4683, SBP<140 mmHg) SBP control in 9361 patients without T2DM, we created a topological representation of the trial patients using 59 baseline variables (trial phenomaps). Within each patient’s 5% topological neighborhood, we calculated hazard ratios (HR) for recurrent MACE (cardiovascular death, acute coronary syndrome, stroke, acute decompensated heart failure). We trained an extreme gradient boosting algorithm to predict the personalized effects of intensive SBP control using features linked to topological benefit. We then tested this machine learning tool in the ACCORD BP trial of patients with T2DM (n=2362 & 2371 in the intensive and standard arms respectively).Results:In SPRINT (age 68±9 years, 36% women) there were a total of 1046 recurrent MACE endpoints. The median individual patient HR was 0.58 [IQR, 0.38-0.82] (A). We developed a 10-variable tool in SPRINT (B) and subsequently tested in ACCORD BP (age 63±7 years, 48% women) where it identified individual patients with a higher benefit with intensive vs standard SBP control (adj. HR for time-to-MACE 0.77 [95% CI 0.61-0.98] in individuals with above median predicted benefit [high responders] (C) vs 0.97 [95% CI 0.77-1.23] (D) for below median predicted benefit [low responders]).Conclusions:We present a clinical trial-based, machine learning tool that identifies an individual’s personalized benefit from intensive versus standard SBP goals in patients with and without T2DM and may be used to guide clinical decision-making.

Introduction:Over one billion adults have hypertension globally, of whom 70% cannot achieve hypertension control with monotherapy. Data are lacking on patterns of dual combination therapies prescribed to patients who escalate from monotherapy.Methods:We described dual combination therapy utilization using eleven electronic health record databases covering 118 million patients across eight countries. We identified patients who newly initiated dual combination of four most commonly used antihypertensive drug classes (angiotensin-converting enzyme inhibitor [ACEi] or angiotensin receptor blocker [ARB]; calcium channel blocker [CCB]; beta-blocker; and thiazide or thiazide-like diuretic) after being on monotherapy.Results:We identified 980,648 patients with hypertension initiating dual combination therapy with antihypertensive agents after being on monotherapy: 12,541 from Australia, 6,980 from South Korea, 2,096 from Singapore, 7,008 from China, 16,663 from Taiwan, 103,994 from France, 76,082 from Italy, and 754,137 from the United States (US). Significant variations in treatment utilization existed across countries and patient subgroups. In Australia and Singapore, starting an ACEi/ARB monotherapy followed by a CCB was most common while in South Korea, China and Taiwan, starting a CCB monotherapy followed by an ACEi/ARB was most common. In Italy, France, and the US, sequential use of an ACEi/ARB monotherapy followed by a diuretic was most common. Younger patients were more likely to be prescribed ACEi/ARB followed by either a CCB or a diuretic compared with older patients. Women were more likely to be prescribed diuretics then an ACEi/ARB or a CCB compared with men.Conclusion:A large variation in the transition between monotherapy and dual combination therapy for hypertension was observed across countries. These results highlight the need for future research to identify which dual combination therapy is most effective for which patients.

Introduction:Sodium-glucose cotransporter-2 (SGLT2) inhibitors have well-documented cardioprotective effects in broad groups of patients with type 2 diabetes mellitus (T2DM) but are underused, in part due to high cost. Individualized prediction of the magnitude of cardiovascular risk reduction may allow more targeted use.Hypothesis:A machine learning decision support tool can predict ASCVD effect of canagliflozin therapy in T2DM based on each patient’s unique phenotypic profile.Methods:We constructed a topological representation of the Canagliflozin Cardiovascular Assessment Study (CANVAS) using 75 baseline variables collected from 4327 patients with T2DM randomly assigned to canagliflozin (n=2886) or placebo (n=1441). Within each patient’s 5% topological neighborhood, we calculated age- and sex-adjusted risk estimates for major adverse cardiovascular events (MACE: cardiovascular death, myocardial infarction, stroke). An extreme gradient boosting algorithm was trained to predict the personalized MACE effect of canagliflozin using features consistently associated with benefit in topological analyses and was validated in the independent CANVAS-R trial (n=5808, randomized 1:1 to canagliflozin or placebo).Results:In CANVAS (mean age 60.9±8.1 years, 33.9% women) 1605 (37.1%) patients had a neighborhood hazard ratio lower (more protective) than the overall effect estimate of 0.86 for the primary composite outcome of time to MACE (A). A 15-variable tool, INSIGHT, was developed in CANVAS (B), and subsequently tested in CANVAS-R (mean age 62.4±8.4 years, 2164 (37.3%) women) where it identified patient phenotypes with higher MACE benefit of canagliflozin (adj. HR 0.60 [95% CI: 0.41-0.89] (C) versus 0.99 [95% CI: 0.76-1.29] (D); P-value for interaction=0.04).Conclusions:We present an evidence-based, machine learning-guided algorithm to personalize the prescription of SGLT2 inhibitors for cardiovascular benefit in patients with T2DM.

Fc effector functions and antibody specificity, rather than IgG or neutralizing titers, may serve as protective correlates for Ebola vaccines.

Primary care in the United Kingdom has been advocated as an optimal location for the provision of genetic services for common diseases. Little, however, is known about general practitioners' own views toward this suggestion or the possible demand for such services from patients. To assess general practitioners' attitudes to providing genetic services for common diseases, and to estimate the demand from patients for these services, we used a single-page postal questionnaire survey of all 359 general practitioners registered with the Oxfordshire Health Authority; 339 (94%) responded. These physicians reported that a mean 4.1 patients (95% CI, 3.3–4.9) out of every 1,000 consulting them were concerned about their own risk of a common disease associated with a diagnosis in a family member. Half of the general practitioners (95% CI, 45–56%) counseled about genetics in the last year. A majority of general practitioners accept the need to provide genetic services, but far fewer are competent to do so. Although 60% (95% CI, 55–65%) believed they should be involved with genetic screening for common diseases, only 29% (95% CI, 24–34%) felt sufficiently prepared to take family histories and draw pedigrees, and only 15% (95% CI, 11–19%) felt sufficiently prepared to counsel patients about their genetic test results. Given the necessary training and information, 63% (95% CI, 58–68%) and 64% (95% CI, 59–69%) were willing to provide these services. Even with training and information, not all would be willing to provide these services, and lack of time may be a major deterrent. “Practice-enabling” strategies, such as computerized aids in genetics, may be useful.

ObjectiveTo investigate the use of repurposed and adjuvant drugs in patients admitted to hospital with covid-19 across three continents.DesignMultinational network cohort study.SettingHospital electronic health records from the United States, Spain, and China, and nationwide claims data from South Korea.Participants303 264 patients admitted to hospital with covid-19 from January 2020 to December 2020.Main outcome measuresPrescriptions or dispensations of any drug on or 30 days after the date of hospital admission for covid-19.ResultsOf the 303 264 patients included, 290 131 were from the US, 7599 from South Korea, 5230 from Spain, and 304 from China. 3455 drugs were identified. Common repurposed drugs were hydroxychloroquine (used in from <5 (<2%) patients in China to 2165 (85.1%) in Spain), azithromycin (from 15 (4.9%) in China to 1473 (57.9%) in Spain), combined lopinavir and ritonavir (from 156 (<2%) in the VA-OMOP US to 2,652 (34.9%) in South Korea and 1285 (50.5%) in Spain), and umifenovir (0% in the US, South Korea, and Spain and 238 (78.3%) in China). Use of adjunctive drugs varied greatly, with the five most used treatments being enoxaparin, fluoroquinolones, ceftriaxone, vitamin D, and corticosteroids. Hydroxychloroquine use increased rapidly from March to April 2020 but declined steeply in May to June and remained low for the rest of the year. The use of dexamethasone and corticosteroids increased steadily during 2020.ConclusionsMultiple drugs were used in the first few months of the covid-19 pandemic, with substantial geographical and temporal variation. Hydroxychloroquine, azithromycin, lopinavir-ritonavir, and umifenovir (in China only) were the most prescribed repurposed drugs. Antithrombotics, antibiotics, H2 receptor antagonists, and corticosteroids were often used as adjunctive treatments. Research is needed on the comparative risk and benefit of these treatments in the management of covid-19.

ObjectiveTo quantify the background incidence rates of 15 prespecified adverse events of special interest (AESIs) associated with covid-19 vaccines.DesignMultinational network cohort study.SettingElectronic health records and health claims data from eight countries: Australia, France, Germany, Japan, the Netherlands, Spain, the United Kingdom, and the United States, mapped to a common data model.Participants126 661 070 people observed for at least 365 days before 1 January 2017, 2018, or 2019 from 13 databases.Main outcome measuresEvents of interests were 15 prespecified AESIs (non-haemorrhagic and haemorrhagic stroke, acute myocardial infarction, deep vein thrombosis, pulmonary embolism, anaphylaxis, Bell’s palsy, myocarditis or pericarditis, narcolepsy, appendicitis, immune thrombocytopenia, disseminated intravascular coagulation, encephalomyelitis (including acute disseminated encephalomyelitis), Guillain-Barré syndrome, and transverse myelitis). Incidence rates of AESIs were stratified by age, sex, and database. Rates were pooled across databases using random effects meta-analyses and classified according to the frequency categories of the Council for International Organizations of Medical Sciences.ResultsBackground rates varied greatly between databases. Deep vein thrombosis ranged from 387 (95% confidence interval 370 to 404) per 100 000 person years in UK CPRD GOLD data to 1443 (1416 to 1470) per 100 000 person years in US IBM MarketScan Multi-State Medicaid data among women aged 65 to 74 years. Some AESIs increased with age. For example, myocardial infarction rates in men increased from 28 (27 to 29) per 100 000 person years among those aged 18-34 years to 1400 (1374 to 1427) per 100 000 person years in those older than 85 years in US Optum electronic health record data. Other AESIs were more common in young people. For example, rates of anaphylaxis among boys and men were 78 (75 to 80) per 100 000 person years in those aged 6-17 years and 8 (6 to 10) per 100 000 person years in those older than 85 years in Optum electronic health record data. Meta-analytic estimates of AESI rates were classified according to age and sex.ConclusionThis study found large variations in the observed rates of AESIs by age group and sex, showing the need for stratification or standardisation before using background rates for safety surveillance. Considerable population level heterogeneity in AESI rates was found between databases.

Summary: BAli-Phy is a Bayesian posterior sampler that employs Markov chain Monte Carlo to explore the joint space of alignment and phylogeny given molecular sequence data. Simultaneous estimation eliminates bias toward inaccurate alignment guide-trees, employs more sophisticated substitution models during alignment and automatically utilizes information in shared insertion/deletions to help infer phylogenies. Availability: Software is available for download at http://www.biomath.ucla.edu/msuchard/bali-phy. Contact: msuchard@ucla.edu

Motivation: We introduce a dual multiple change-point (MCP) model for recombination detection among aligned nucleotide sequences. The dual MCP model is an extension of the model introduced previously by Suchard and co-workers. In the original single MCP model, one change-point process is used to model spatial phylogenetic variation. Here, we show that using two change-point processes, one for spatial variation of tree topologies and the other for spatial variation of substitution process parameters, increases recombination detection accuracy. Statistical analysis is done in a Bayesian framework using reversible jump Markov chain Monte Carlo sampling to approximate the joint posterior distribution of all model parameters. Results: We use primate mitochondrial DNA data with simulated recombination break-points at specific locations to compare the two models. We also analyze two real HIV sequences to identify recombination break-points using the dual MCP model. Availability: A software program ‘DualBrothers’ implementing the dual MCP model is available in the form of a Java package at http://www.biomath.ucla.edu/msuchard/DualBrothers Contact: msuchard@ucla.edu Supplementary information: http://www.biomath.ucla.edu/msuchard/DualBrothers

Abstract: Enfuvirtide (ENF) is a fusion inhibitor that prevents the entry of HIV virions into target cells. Studying the characteristics of viral evolution during treatment and after a treatment interruption can lend insight into the mechanisms of viral evolution and fitness. Although interruption of anti-HIV therapy often results in rapid emergence of an archived “wild-type” virus population, previous work from our group indicates that when only ENF is interrupted, viral gp41 continues to evolve forward and resistance mutations are lost due to back-mutation and remodeling of the envelope protein. To examine the co-evolution of gp120 and gp41 during ENF interruption we extend the Bayesian Hierarchical Phylogenetic model (HPM). Current HPMs enforce conditional independence across all outcomes while biologically all gene regions within a patient should return the same tree unless recombination confers an evolutionary selective advantage. A two-way-interaction HPM is proposed that provides middle ground between these two extremes and allows us to test for differences in evolutionary pressures across gene regions in multiple patients simultaneously. When the model is applied to a well-characterized cohort of HIV-infected patients interrupting ENF we find that across patients, the virus continued to evolve forward in both gene regions. Overall, the hypothesis of independence over dependence between the gene regions is supported. Models that allow for the examination of co-evolution over time will be increasingly important as more therapeutic classes are developed, each of which may impact other through novel and complex mechanisms. [Copyright &y& Elsevier]