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Additional file 6. Risk of ESKD progression in patients with CKD stage 3 or 4 (with or without HF) in (a) the US and (b) Japan, and risk of the HF composite in patients with HF (with or without CKD stage 3 or 4) in (c) the US and (d) Japan.

Additional file 4. Risk of the cardiorenal composite outcome by change in RAASi dose following an HK episode in (a) the US and (b) Japan in patients with CKD stage 3 or 4 (with or without HF).

Additional file 2. Patient characteristics at baseline in patients with CKD stage 3 or 4 (with or without HF).

Additional file 1: Table S1. Read codes and ICD-10 codes for clinical events of interest. Table S2. Patient mortality and risk by dialysis status and modality. Fig. S1. All-event rates per 100 PY (95% CI) for patients with CKD by dialysis status. Fig. S2. Incidence rates of adverse clinical events per 100 PY (95% CI) for patients with CKD over time. Fig. S3. All-event rates per 100 PY (95% CI) for patients with NDD-CKD by disease stage. Fig. S4. Incidence rates per 100 PY (95% CI) for patients with DD-CKD or IDD-CKD by dialysis modality. Fig. S5. Risk of mortality for patients with NDD-CKD by stage, IDD-CKD, and DD-CKD.

Additional file 3. Patient characteristics at baseline in patients with HF (with or without CKD stage 3 or 4).

Additional file 5. Risk of the cardiorenal composite outcome by change in RAASi dose following an HK episode in (a) the US and (b) Japan in patients with HF (with or without CKD stage 3 or 4).

Photons excited into ground state modes at finite temperature display partitioning among photon phases, lifetimes and distances travelled since creation. These distributions set the distance from an interface a created photon has some chance of emission. Excited photons at each frequency have a phase velocity set by each mode propagation index which determines mode density and internal energy contribution. All photons emitted after striking an interface obliquely are refracted. Their exit intensities are then irreversible except when weak internal attenuation occurs. At low temperature attenuation index is small so reversibility is approximate. As temperature rises refraction direction varies. Total emission remains reversible after transitioning through a non equilibrium state with no other heat inputs. In equilibrium the densities of excitations that create and annihilate photons are in balance with photon densities while emissivity depends on both indices and internal incident direction. Modelled exit intensities from pure water and crystalline silica contain strong resonant intensities and match data accurately. Intrinsic resonances formed within liquids and compounds are due to photon modes hybridising with localized excitations, including molecular oscillations and the anharmonic component of lattice distortions. They explain the many resonant spectral intensities seen in remote sensing. Each hybrid oscillator is a photonic virtual bound state whose energy fluctuates between levels separated by mode energy. Refraction induces solid angle changes and often anomalous refraction while thermal recycling of internally reflected photons modifies intensities and internal energy. Enhanced internal heat flux from phonon drag by photon density gradients under an external temperature gradient is also predicted., Comment: 27 pages, 5 figures

Background: Power tools are an integral part of orthopaedic surgery but have the capacity to cause iatrogenic injury. With this systematic review, we aimed to investigate the prevalence of iatrogenic injury due to the use of power tools in orthopaedic surgery and to discuss the current methods that can be used to reduce injury. Methods: We performed a systematic review of English-language studies related to power tools and iatrogenic injuries using a keyword search in MEDLINE, Embase, PubMed, and Scopus databases. Exclusion criteria included injuries related to cast-saw use, temperature-induced damage, and complications not clearly related to power-tool use. Results: A total of 3,694 abstracts were retrieved, and 88 studies were included in the final analysis. Few studies and individual case reports looked directly at the prevalence of injury due to power tools. These included 2 studies looking at the frequency of vascular injury during femoral fracture fixation (0.49% and 0.2%), 2 studies investigating the frequency of vertebral artery injury during spinal surgery (0.5% and 0.08%), and 4 studies investigating vascular injury during total joint arthroplasty (1 study involving 138 vascular injuries in 124 patients, 2 studies noting 0.13% and 0.1% incidence, and 1 questionnaire sent electronically to surgeons). There are multiple methods for preventing damage during power-tool use. These include the use of robotics and simulation, specific drill settings, and real-time feedback techniques such as spectroscopy and electromyography. Conclusions: Power tools have the potential to cause iatrogenic injury to surrounding structures during orthopaedic surgery. Fortunately, the published literature suggests that the frequency of iatrogenic injury using orthopaedic power tools is low. There are multiple technologies available to reduce damage using power tools. In high-risk operations, the use of advanced technologies to reduce the chance of iatrogenic injury should be considered. Level of Evidence: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

IMPORTANCE: Acquisition of reliable randomized clinical trial evidence of the effects of cardiovascular interventions on cognitive decline is a priority. OBJECTIVES: To estimate the association of cognitive aging with the avoidance of vascular events in cardiovascular intervention trials and understand whether reports of nonsignificant results exclude worthwhile benefit. DESIGN, SETTING, AND PARTICIPANTS: This secondary analysis of 3 randomized clinical trials in participants with preexisting occlusive vascular disease or diabetes included survivors to final in-trial follow-up in the Heart Protection Study (HPS), Study of the Effectiveness of Additional Reductions in Cholesterol and Homocysteine (SEARCH), and Treatment of HDL (High-Density Lipoprotein) to Reduce the Incidence of Vascular Events (HPS2-THRIVE) trials of lipid modification for prevention of cardiovascular events. Data were collected from February 1994 through January 2013 and analyzed from January 2015 through December 2018. EXPOSURES: Incident vascular events and diabetes and statin therapy. MAIN OUTCOMES AND MEASURES: Cognitive function was assessed at the end of a mean (SD) of 4.9 (1.5) years of follow-up using a 14-item verbal test. Associations of the incidence of vascular events and new-onset diabetes during the trials, with cognitive function at final in-trial follow-up were estimated and expressed as years of cognitive aging (using the association of the score with age >60 years). The benefit on cognitive aging mediated through the effects of lowering low-density lipoprotein cholesterol levels on events was estimated by applying these findings to nonfatal event differences observed with statin therapy in the HPS trial. RESULTS: Among 45 029 participants undergoing cognitive assessment, mean (SD) age was 67.9 (8.0) years; 80.7% were men. Incident stroke (n = 1197) was associated with 7.1 (95% CI, 5.7-8.5) years of cognitive aging; incident transient ischemic attack, myocardial infarction, heart failure, and new-onset diabetes were associated with 1 to 2 years of cognitive aging. In HPS, randomization to statin therapy for 5 years resulted in 2.0% of survivors avoiding a nonfatal stroke or transient ischemic attack and 2.4% avoiding a nonfatal cardiac event, which yielded an expected reduction in cognitive aging of 0.15 (95% CI, 0.11-0.19) years. With 15 926 participants undergoing cognitive assessment, HPS had 80% power to detect a 1-year (ie, 20% during the 5 years) difference in cognitive aging. CONCLUSIONS AND RELEVANCE: The expected cognitive benefits of the effects of preventive therapies on cardiovascular events during even the largest randomized clinical trials may have been too small to be detectable. Hence, nonsignificant findings may not provide good evidence of a lack of worthwhile benefit on cognitive function with prolonged use of such therapies. TRIAL REGISTRATION: isrctn.com and ClinicalTrials.gov Identifiers: ISRCTN48489393, ISRCTN74348595, and NCT00461630.

Accurate quantification of model uncertainty has long been recognized as a fundamental requirement for trusted AI. In regression tasks, uncertainty is typically quantified using prediction intervals calibrated to a specific operating point, making evaluation and comparison across different studies difficult. Our work leverages: (1) the concept of operating characteristics curves and (2) the notion of a gain over a simple reference, to derive a novel operating point agnostic assessment methodology for prediction intervals. The paper describes the corresponding algorithm, provides a theoretical analysis, and demonstrates its utility in multiple scenarios. We argue that the proposed method addresses the current need for comprehensive assessment of prediction intervals and thus represents a valuable addition to the uncertainty quantification toolbox., 10 pages main paper, 9 pages appendix

IMPORTANCE: A better understanding of the role of atherosclerosis in the development of ischemic stroke subtypes could help to improve strategies for prevention of stroke worldwide. OBJECTIVE: To assess the role of carotid atherosclerosis in the association between major cardiovascular risk factors and ischemic stroke subtypes. DESIGN, SETTING, AND PARTICIPANTS: The prospective China Kadoorie Biobank cohort study was conducted in the general population of 5 urban and 5 rural areas in China, with a baseline survey obtained between June 2004 and July 2008. A random sample of 23 973 participants with no history of cardiovascular disease at enrollment who had carotid artery ultrasonographic measurements recorded at a resurvey from September 2013 to June 2014 were included. Data analysis was performed from July 1, 2016, to April 10, 2019. EXPOSURES: Major cardiovascular risk factors (ie, blood pressure [BP], blood lipid levels, smoking, and diabetes). MAIN OUTCOMES AND MEASURES: Carotid ultrasonographic measures of plaque burden (derived from number and maximum size of carotid artery plaques at resurvey) and first ischemic stroke during follow-up (n = 952), with subtyping (data release, August 2018) as lacunar (n = 263), probable large artery (n = 193), probable cardioembolic (n = 66), or unconfirmed (n = 430). Associations between cardiovascular risk factors, carotid plaque burden, and ischemic stroke subtypes were adjusted for age, sex, and geographic area. RESULTS: The 23 973 participants in the study had a mean (SD) age of 50.6 (10.0) years, and 14 833 (61.9%) were women. Systolic BP had a stronger association (odds ratio [OR] per SD, 1.51; 95% CI, 1.42-1.61) than plaque burden (OR per SD, 1.34; 95% CI, 1.26-1.44) with ischemic stroke, and the associations of systolic BP with each subtype of ischemic stroke were modestly attenuated by adjustment for plaque burden. After adjustment for BP, plaque burden had a stronger association with probable large artery stroke (OR, 1.43; 95% CI, 1.24-1.63) than with lacunar stroke (OR, 1.25; 95% CI, 1.10-1.43) but was not associated with probable cardioembolic stroke (OR, 1.06; 95% CI, 0.83-1.36). CONCLUSIONS AND RELEVANCE: Although BP was an important risk factor for all ischemic stroke subtypes, carotid atherosclerosis was an important risk factor only for large artery and lacunar strokes, suggesting that drug treatments targeting atherosclerosis may reduce the risk of stroke subtypes to different extents.

This document contains Extended Data (supplementary material containing details of the inclusion criteria for the analyses) to accompany the paper "Approaches to minimising the epidemiological impact of sources of systematic and random variation that may affect biochemistry assay data in UK Biobank". This upload also includes the underlying SAS code and macros used in the changepoint analysis and date of assay corrections., Supplementary material (Extended Data). This project was funded by the Wellcome Trust, Medical Research Council, British Heart Foundation and Diabetes UK.

Building and maintaining high-quality test sets remains a laborious and expensive task. As a result, test sets in the real world are often not properly kept up to date and drift from the production traffic they are supposed to represent. The frequency and severity of this drift raises serious concerns over the value of manually labeled test sets in the QA process. This paper proposes a simple but effective technique that drastically reduces the effort needed to construct and maintain a high-quality test set (reducing labeling effort by 80-100% across a range of practical scenarios). This result encourages a fundamental rethinking of the testing process by both practitioners, who can use these techniques immediately to improve their testing, and researchers who can help address many of the open questions raised by this new approach., International Workshop on Challenges in Deploying and Monitoring Machine Learning Systems in Conjunction with ICML 2020

Generating high quality uncertainty estimates for sequential regression, particularly deep recurrent networks, remains a challenging and open problem. Existing approaches often make restrictive assumptions (such as stationarity) yet still perform poorly in practice, particularly in presence of real world non-stationary signals and drift. This paper describes a flexible method that can generate symmetric and asymmetric uncertainty estimates, makes no assumptions about stationarity, and outperforms competitive baselines on both drift and non drift scenarios. This work helps make sequential regression more effective and practical for use in real-world applications, and is a powerful new addition to the modeling toolbox for sequential uncertainty quantification in general.

Today's AI deployments often require significant human involvement and skill in the operational stages of the model lifecycle, including pre-release testing, monitoring, problem diagnosis and model improvements. We present a set of enabling technologies that can be used to increase the level of automation in AI operations, thus lowering the human effort required. Since a common source of human involvement is the need to assess the performance of deployed models, we focus on technologies for performance prediction and KPI analysis and show how they can be used to improve automation in the key stages of a typical AI operations pipeline.

Understanding model performance on unlabeled data is a fundamental challenge of developing, deploying, and maintaining AI systems. Model performance is typically evaluated using test sets or periodic manual quality assessments, both of which require laborious manual data labeling. Automated performance prediction techniques aim to mitigate this burden, but potential inaccuracy and a lack of trust in their predictions has prevented their widespread adoption. We address this core problem of performance prediction uncertainty with a method to compute prediction intervals for model performance. Our methodology uses transfer learning to train an uncertainty model to estimate the uncertainty of model performance predictions. We evaluate our approach across a wide range of drift conditions and show substantial improvement over competitive baselines. We believe this result makes prediction intervals, and performance prediction in general, significantly more practical for real-world use., Comment: 7+6 pages, 5 figures, AAAI 2021

Key Points Question Do null results on cognitive function in cardiovascular trials exclude worthwhile benefit? Findings In this secondary analysis of 3 randomized clinical trials including 45 029 participants undergoing cognitive assessment, the prevention of nonfatal cardiovascular events in 4.5% of survivors in the Heart Protection Study, by randomization to statin, yielded an estimated cognitive function difference equivalent to avoiding 0.15 years of aging. By contrast, the trial was powered to detect a difference in cognitive aging of at least 1 year. Meaning Nonsignificant findings, even from large trials, should not be taken as good evidence of a lack of worthwhile benefit on cognitive function of prolonged use of cardioprotective therapies., This secondary analysis of 3 randomized clinical trials estimates the effect on cognitive aging of the avoidance of vascular events and evaluates whether reports of nonsignificant results exclude worthwhile benefit among patients with vascular disease., Importance Acquisition of reliable randomized clinical trial evidence of the effects of cardiovascular interventions on cognitive decline is a priority. Objectives To estimate the association of cognitive aging with the avoidance of vascular events in cardiovascular intervention trials and understand whether reports of nonsignificant results exclude worthwhile benefit. Design, Setting, and Participants This secondary analysis of 3 randomized clinical trials in participants with preexisting occlusive vascular disease or diabetes included survivors to final in-trial follow-up in the Heart Protection Study (HPS), Study of the Effectiveness of Additional Reductions in Cholesterol and Homocysteine (SEARCH), and Treatment of HDL (High-Density Lipoprotein) to Reduce the Incidence of Vascular Events (HPS2-THRIVE) trials of lipid modification for prevention of cardiovascular events. Data were collected from February 1994 through January 2013 and analyzed from January 2015 through December 2018. Exposures Incident vascular events and diabetes and statin therapy. Main Outcomes and Measures Cognitive function was assessed at the end of a mean (SD) of 4.9 (1.5) years of follow-up using a 14-item verbal test. Associations of the incidence of vascular events and new-onset diabetes during the trials, with cognitive function at final in-trial follow-up were estimated and expressed as years of cognitive aging (using the association of the score with age >60 years). The benefit on cognitive aging mediated through the effects of lowering low-density lipoprotein cholesterol levels on events was estimated by applying these findings to nonfatal event differences observed with statin therapy in the HPS trial. Results Among 45 029 participants undergoing cognitive assessment, mean (SD) age was 67.9 (8.0) years; 80.7% were men. Incident stroke (n = 1197) was associated with 7.1 (95% CI, 5.7-8.5) years of cognitive aging; incident transient ischemic attack, myocardial infarction, heart failure, and new-onset diabetes were associated with 1 to 2 years of cognitive aging. In HPS, randomization to statin therapy for 5 years resulted in 2.0% of survivors avoiding a nonfatal stroke or transient ischemic attack and 2.4% avoiding a nonfatal cardiac event, which yielded an expected reduction in cognitive aging of 0.15 (95% CI, 0.11-0.19) years. With 15 926 participants undergoing cognitive assessment, HPS had 80% power to detect a 1-year (ie, 20% during the 5 years) difference in cognitive aging. Conclusions and Relevance The expected cognitive benefits of the effects of preventive therapies on cardiovascular events during even the largest randomized clinical trials may have been too small to be detectable. Hence, nonsignificant findings may not provide good evidence of a lack of worthwhile benefit on cognitive function with prolonged use of such therapies. Trial Registration isrctn.com and ClinicalTrials.gov Identifiers: ISRCTN48489393, ISRCTN74348595, and NCT00461630

International audience

International audience

International audience

International audience

Accuracy is an important concern for suppliers of artificial intelligence (AI) services, but considerations beyond accuracy, such as safety (which includes fairness and explainability), security, and provenance, are also critical elements to engender consumers' trust in a service. Many industries use transparent, standardized, but often not legally required documents called supplier's declarations of conformity (SDoCs) to describe the lineage of a product along with the safety and performance testing it has undergone. SDoCs may be considered multi-dimensional fact sheets that capture and quantify various aspects of the product and its development to make it worthy of consumers' trust. Inspired by this practice, we propose FactSheets to help increase trust in AI services. We envision such documents to contain purpose, performance, safety, security, and provenance information to be completed by AI service providers for examination by consumers. We suggest a comprehensive set of declaration items tailored to AI and provide examples for two fictitious AI services in the appendix of the paper., 31 pages

We have observed that in complex nanostructures, such as pairs of nanorods, hotspots of optical emission induced by electron-beam excitation exist at their point of closest proximity, where strong local field enhancements are expected.

We use electronic structure calculations based upon density functional theory to search for ideal plasmonic materials among the alkali noble intermetallics. Importantly, we use density functional perturbation theory to calculate the electron-phonon interaction and from there use a first order solution to the Boltzmann equation to estimate the phenomenological damping frequency in the Drude dielectric function. We discuss the necessary electronic features of a plasmonic material and investigate the optical properties of the alkali-noble intermetallics in terms of some generic plasmonic system quality factors. We conclude that at low negative permittivities, KAu with a damping frequency of 0.0224 eV and a high optical gap to bare plasma frequency ratio, outperforms gold and to some extent silver as a plasmonic material. Unfortunately, a low plasma frequency (1.54 eV) reduces its utility in modern plasmonics applications. We also discuss, briefly, the effect of local fields on the optical properties of these materials., Comment: 8 pages, 6 figures, 4 tables

The pulling nature of crises on the 'frontiers' stimulates Western interventionism focused on state building. This interventionism is fundamentally dependent upon collaboration with indigenous politics and 'collaborative systems', the relationships linking interventionist actors with indigenous ones, determine its structure and dynamics. State building interventions rely on collaborative systems because they define the interface of the external forces of the intervening power with indigenous politics. Unless the energy and resources of the intervening power can be translated and internalised into terms of indigenous politics, the intervention will be unable to achieve its state building goals. Presently, Western states are both failing to build appropriate collaborative systems and to manage their collaborative partners. However, if Western states can improve their approach to and implementation of collaboration with indigenous politics, they can better manage insecurity on the frontiers through state-building interventionism.

Microtubules are critically important cytoskeletal elements. Together with microtubule associated proteins (MAPs), they form the latticework on which eukaryotic life exists. Simply put, microtubules are polymers of tubulin heterodimers, which are composed of the globular proteins alpha and beta tubulin. In vivo, these monomers associate with one another to form heterodimers, which then polymerize to form microtubules. In mammals, microtubule polymerization is a temperature-dependent process with an optimum of 37°C (Detrich et al., 2000). If temperatures exceed this optimal temperature by even a few degrees, the microtubule will begin to dissemble due to denaturation of the tubulin subunit and permanent loss of both shape and function will occur. This thermal barrier seems to be consistent in most eukaryotic organisms. Two exceptions are the thermophilic red algae, Cyanidium caldarium and Cyanidioschyzon merolae. These thermophilic acidophiles have been discovered in volcanic vents around the globe from Yellow Stone Park to Italy and grow at optimal temperatures of around 55°C. These organisms have been primarily studied in the context of evolutionary biology because of their primitive characteristics. Very little is known about the molecular biology of these organisms, and certainly nothing is known about how the biochemistry of these organisms brings about the ability to survive the harsh conditions of their environment. Currently, my hypothesis concerning the thermostable tubulin expressed within these organisms is that there may be key amino acid differences in the tubulin's primary structure that confer enhanced thermostability. I am testing this hypothesis by sequencing the alpha and beta tubulin genes of Cyanidium caldarium and Cyanidioschyzon merolae, generating homology models of the tubulin dimers, and comparing these models to a known mesophilic tubulin heterodimer structure in order to identify potential structural differences. Master of Science

The overhead involved in collecting fine-grained profiling information makes feedback-directed optimizations diÆult to perform online at runtime. As a result, the vast majority of work in offline feedback-directed optimization is not yet being applied in online systems. This paper describes the design and implementation of a fully automatic online approach for performing instrumentation and feedback-directed optimization. Our approach uses instrumentation sampling to reduce the overhead of instrumentation, thus eliminating many of the limitations present in existing online systems. Several online feedback-directed optimizations are described, including a novel algorithm for performing feedback-directed splitting. Our experimental results show improvements in peak performance of up to 20% while overhead remains low, with no individual execution being degraded more than 2%.

Dynamic class loading is an integral part of the Java programming language, offering a number advantages such as lazy class loading and dynamic installation of software components. Unfortunately, these advantages often come at the cost of decreased performance because certain optimizations become more difficult to perform when an optimizing compiler cannot assume that it has seen the whole program. This paper introduces thin guards, a simple but effective technique that uses lightweight runtime tests to identify regions of code within which speculative optimizations can be performed. One application of thin guards is described in detail, demonstrating how they can be used to perform speculative inlining in the presence of dynamic class loading. Our experimental evaluation shows that when used in combination with other traditional compiler optimizations, thin guards can eliminate most of the penalty dynamic class loading. Performance improvements of up to 27% are observed, eliminating up to 92% of the penalty imposed by dynamic class loading.

To measure selected parameters of energy metabolism and adenosine triphosphate (ATP) production in passaged monolayer cultures of human retinal glial (Müller) cells to assess the effects of varying substrate and oxygen availability on the biochemistry and histologic integrity of these cells.Confluent Müller cell cultures were incubated for up to 4 hours at 37 degrees C in a modified minimal essential medium (no serum) under aerobic or mitochondrial-inhibited conditions in the presence and absence of 5 mM glucose or in the presence of lactate, pyruvate, glutamate, or glutamine. Cellular ATP levels, lactic acid production, and (14)CO(2) production from labeled glucose or glutamate were measured along with an examination of cellular morphology. Immunohistochemistry with antibodies to glial cell-specific proteins was also performed. Cells were positive for vimentin, but negative for glial fibrillary acidic protein and glutamine synthetase.Human Müller cells maintained ATP content aerobically at the same level for 4 hours in the presence and absence of glucose. ATP content was also maintained anaerobically at a value equal to that found aerobically, but only in the presence of glucose. ATP content in human Müller cells declined to a very low level when glycolysis was blocked by iodoacetate, and inclusion of lactate, pyruvate, glutamate, or glutamine did not restore the level of ATP. Aerobically, lactic acid production accounted for 99% of the total glucose used, whereas the oxidation of glucose by the mitochondria accounted for only 1%. When mitochondria were inhibited with antimycin A, there was only a modest (1.3-fold) increase in the rate of lactic acid production. No significant differences were found in the histologic appearance of the cells after mitochondrial blockade, but there was massive death of cells after inhibition of glycolysis with iodoacetate.These results suggest that, in the presence of glucose and oxygen, cultured Müller cells obtain their ATP principally from glycolysis and have a low rate of oxygen consumption. This metabolic pattern may spare oxygen for retinal neurons, particularly in the inner nuclear and ganglion cell layers under normal physiological conditions. Furthermore, retinal Müller cells in culture are resistant to anoxia or absence of glucose, which provides a basis for understanding why Müller cells are less susceptible than neurons to ischemia or hypoglycemia.

One of the challenges present to a native code Java compiler is Java’s frequent use of runtime exceptions. These exceptions affect performance directly by requiring explicit checks, as well as indirectly by restricting code movement in order to satisfy Java’s precise exception model. Instruction scheduling is one transformation which is restricted by runtime exceptions since it relies heavily on reordering instructions to exploit maximum hardware performance. The goal of this study was to investigate the degree to which Java’s runtime exceptions hinder instruction scheduling, and to find new techniques for allowing more efficient execution of Java programs containing runtime exceptions.

Mid-Atlantic Student Workshop on Programming Languages and Systems

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XV, 506 p.

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Background: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. Methods: Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition–Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. Results: There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values 105 mL·min –1 ·1.73 m –2 , compared with those with eGFR between 60 and 105 mL·min –1 ·1.73 m –2 . Mendelian randomization analyses for CHD showed an association among participants with eGFR –1 ·1.73 m –2 , with a 14% (95% CI, 3%–27%) higher CHD risk per 5 mL·min –1 ·1.73 m –2 lower genetically predicted eGFR, but not for those with eGFR >105 mL·min –1 ·1.73 m –2 . Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. Conclusions: In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive approaches that preserve and modulate kidney function.

Cardiometabolic diseases are frequently polygenic in architecture, comprising a large number of risk alleles with small effects spread across the genome1–3. Polygenic scores (PGS) aggregate these into a metric representing an individual’s genetic predisposition to disease. PGS have shown promise for early risk prediction4–7 and there is an open question as to whether PGS can also be used to understand disease biology8. Here, we demonstrate that cardiometabolic disease PGS can be used to elucidate the proteins underlying disease pathogenesis. In 3,087 healthy individuals, we found that PGS for coronary artery disease, type 2 diabetes, chronic kidney disease and ischaemic stroke are associated with the levels of 49 plasma proteins. Associations were polygenic in architecture, largely independent of cis and trans protein quantitative trait loci and present for proteins without quantitative trait loci. Over a follow-up of 7.7 years, 28 of these proteins associated with future myocardial infarction or type 2 diabetes events, 16 of which were mediators between polygenic risk and incident disease. Twelve of these were druggable targets with therapeutic potential. Our results demonstrate the potential for PGS to uncover causal disease biology and targets with therapeutic potential, including those that may be missed by approaches utilizing information at a single locus., Ritchie et al. use polygenic scores to identify plasma proteins with causal roles in cardiometabolic disease.

Background Polygenic risk scores (PRSs) can stratify populations into cardiovascular disease (CVD) risk groups. We aimed to quantify the potential advantage of adding information on PRSs to conventional risk factors in the primary prevention of CVD. Methods and findings Using data from UK Biobank on 306,654 individuals without a history of CVD and not on lipid-lowering treatments (mean age [SD]: 56.0 [8.0] years; females: 57%; median follow-up: 8.1 years), we calculated measures of risk discrimination and reclassification upon addition of PRSs to risk factors in a conventional risk prediction model (i.e., age, sex, systolic blood pressure, smoking status, history of diabetes, and total and high-density lipoprotein cholesterol). We then modelled the implications of initiating guideline-recommended statin therapy in a primary care setting using incidence rates from 2.1 million individuals from the Clinical Practice Research Datalink. The C-index, a measure of risk discrimination, was 0.710 (95% CI 0.703–0.717) for a CVD prediction model containing conventional risk predictors alone. Addition of information on PRSs increased the C-index by 0.012 (95% CI 0.009–0.015), and resulted in continuous net reclassification improvements of about 10% and 12% in cases and non-cases, respectively. If a PRS were assessed in the entire UK primary care population aged 40–75 years, assuming that statin therapy would be initiated in accordance with the UK National Institute for Health and Care Excellence guidelines (i.e., for persons with a predicted risk of ≥10% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), then it could help prevent 1 additional CVD event for approximately every 5,750 individuals screened. By contrast, targeted assessment only among people at intermediate (i.e., 5% to, Luanluan Sun and colleagues investigate whether adding polygenic risk scores to conventional risk factors of cardiovascular disease helps predict disease risk., Author summary Why was this study done? Application of polygenic risk scores (PRSs) has opened opportunities to enhance risk stratification and prevention for common diseases. The clinical utility of PRSs in cardiovascular disease (CVD) risk prediction is, however, uncertain. Previous analyses have generally focused only on coronary heart disease (CHD) rather than the composite outcome of CHD and stroke, and have often lacked modelling of clinical implications of initiating guideline-recommended interventions (e.g., statin therapy). What did the researchers do and find? We quantified the incremental predictive gain with PRSs on top of conventional risk factors using data on 306,654 individuals from UK Biobank. We modelled the population health implications of initiating statin therapy as recommended by current guidelines using data from 2.1 million individuals from the Clinical Practice Research Datalink. Addition of information on PRSs to a conventional risk prediction model increased the C-index (a measure of risk discrimination) and improved risk classification of cases and non-cases. We estimated that targeted assessment of PRSs among people at intermediate (i.e., 5% to

Background Lean body mass has been identified as a key determinant of left ventricular mass and wall thickness. However, the importance of lean body mass or other body‐size measures as normative determinants of carotid intima‐media thickness ( cIMT ), a widely used early indicator of atherosclerosis, has not been well established. Methods and Results Carotid artery ultrasound measurements of cIMT and carotid artery plaque burden (derived from plaque number and maximum size) and measurements of body size, including height, body mass index, weight, body fat proportion, and lean body mass ([1−body fat proportion]×weight), were recorded in 25 020 participants from 10 regions of China. Analyses were restricted to a healthy younger subset (n=6617) defined as never or long‐term ex‐regular smokers aged cIMT , but was not associated with plaque burden: overall, each 10 kg higher lean body mass was associated with a 0.03 (95% CI , 0.03–0.04) mm higher cIMT ( P =5×10 −33 ). Fat mass, height, and other body‐size measures were more weakly associated with cIMT . Conclusions The strong association of lean body mass with cIMT, but not with plaque burden, in healthy adults suggests a normative relationship rather than reflecting atherosclerotic pathology. Common mechanisms may underlie the associations of lean body mass with cIMT and with nonatherosclerotic vascular traits.