Independent relevance of adiposity measures to coronary heart disease risk among 0.5 million adults in UK Biobank.

BACKGROUND: Evidence on body fat distribution shows opposing effects of waist circumference (WC) and hip circumference (HC) for coronary heart disease (CHD). We aimed to investigate the causality and the shape of such associations. METHODS: UK Biobank is a prospective cohort study of 0.5 million adults aged 40-69 years recruited between 2006 and 2010. Adjusted hazard ratios (HRs) for the associations of measured and genetically predicted body mass index (BMI), WC, HC and waist-to-hip ratio with incident CHD were obtained from Cox models. Mendelian randomization (MR) was used to assess causality. The analysis included 456 495 participants (26 225 first-ever CHD events) without prior CHD. RESULTS: All measures of adiposity demonstrated strong, positive and approximately log-linear associations with CHD risk over a median follow-up of 12.7 years. For HC, however, the association became inverse given the BMI and WC (HR per usual SD 0.95, 95% CI 0.93-0.97). Associations for BMI and WC remained independently positive after adjustment for other adiposity measures and were similar (1.14, 1.13-1.16 and 1.18, 1.15-1.20, respectively), with WC displaying stronger associations among women. Blood pressure, plasma lipids and dysglycaemia accounted for much of the observed excess risk. MR results were generally consistent with the observational, implying causality. CONCLUSIONS: Body fat distribution measures displayed similar associations with CHD risk as BMI except for HC, which was inversely associated with CHD risk (given WC and BMI). These findings suggest that different measures of body fat distribution likely influence CHD risk through both overlapping and independent mechanisms.

Impact of New Cardiovascular Events on Quality of Life and Hospital Costs in People With Cardiovascular Disease in the United Kingdom and United States.

BACKGROUND: Despite optimized risk factor control, people with prior cardiovascular disease remain at high cardiovascular disease risk. We assess the immediate- and longer-term impacts of new vascular and nonvascular events on quality of life (QoL) and hospital costs among participants in the REVEAL (Randomized Evaluation of the Effects of Anacetrapib Through Lipid Modification) trial in secondary prevention. METHODS AND RESULTS: Data on demographic and clinical characteristics, health-related quality of life (QoL: EuroQoL 5-Dimension-5-Level), adverse events, and hospital admissions during the 4-year follow-up of the 21 820 participants recruited in Europe and North America informed assessments of the impacts of new adverse events on QoL and hospital costs from the UK and US health systems' perspectives using generalized linear regression models. Reductions in QoL were estimated in the years of event occurrence for nonhemorrhagic stroke (-0.067 [United Kingdom], -0.069 [US]), heart failure admission (-0.072 [United Kingdom], -0.103 [US]), incident cancer (-0.064 [United Kingdom], -0.068 [US]), and noncoronary revascularization (-0.071 [United Kingdom], -0.061 [US]), as well as in subsequent years following these events. Myocardial infarction and coronary revascularization (CRV) procedures were not found to affect QoL. All adverse events were associated with additional hospital costs in the years of events and in subsequent years, with the highest additional costs in the years of noncoronary revascularization (£5830 [United Kingdom], $14 133 [US Medicare]), of myocardial infarction with urgent CRV procedure (£5614, $24722), and of urgent/nonurgent CRV procedure without myocardial infarction (£4674/£4651 and $15 251/$17 539). CONCLUSIONS: Stroke, heart failure, and noncoronary revascularization procedures substantially reduce QoL, and all cardiovascular disease events increase hospital costs. These estimates are useful in informing cost-effectiveness of interventions to reduce cardiovascular disease risk in secondary prevention. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01252953; https://www.Isrctn.com. Unique identifier: ISRCTN48678192; https://www.clinicaltrialsregister.eu. Unique identifier: 2010-023467-18.

Apolipoprotein Proteomics for Residual Lipid-Related Risk in Coronary Heart Disease.

BACKGROUND: Recognition of the importance of conventional lipid measures and the advent of novel lipid-lowering medications have prompted the need for more comprehensive lipid panels to guide use of emerging treatments for the prevention of coronary heart disease (CHD). This report assessed the relevance of 13 apolipoproteins measured using a single mass-spectrometry assay for risk of CHD in the PROCARDIS case-control study of CHD (941 cases/975 controls). METHODS: The associations of apolipoproteins with CHD were assessed after adjustment for established risk factors and correction for statin use. Apolipoproteins were grouped into 4 lipid-related classes [lipoprotein(a), low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides] and their associations with CHD were adjusted for established CHD risk factors and conventional lipids. Analyses of these apolipoproteins in a subset of the ASCOT trial (Anglo-Scandinavian Cardiac Outcomes Trial) were used to assess their within-person variability and to estimate a correction for statin use. The findings in the PROCARDIS study were compared with those for incident cardiovascular disease in the Bruneck prospective study (n=688), including new measurements of Apo(a). RESULTS: Triglyceride-carrying apolipoproteins (ApoC1, ApoC3, and ApoE) were most strongly associated with the risk of CHD (2- to 3-fold higher odds ratios for top versus bottom quintile) independent of conventional lipid measures. Likewise, ApoB was independently associated with a 2-fold higher odds ratios of CHD. Lipoprotein(a) was measured using peptides from the Apo(a)-kringle repeat and Apo(a)-constant regions, but neither of these associations differed from the association with conventionally measured lipoprotein(a). Among HDL-related apolipoproteins, ApoA4 and ApoM were inversely related to CHD, independent of conventional lipid measures. The disease associations with all apolipoproteins were directionally consistent in the PROCARDIS and Bruneck studies, with the exception of ApoM. CONCLUSIONS: Apolipoproteins were associated with CHD independent of conventional risk factors and lipids, suggesting apolipoproteins could help to identify patients with residual lipid-related risk and guide personalized approaches to CHD risk reduction.

Proteomic profiling identifies novel independent relationships between inflammatory proteins and myocardial infarction.

BACKGROUND: Inflammation has been implicated in the pathogenesis of coronary heart disease, but the relevance and independence of individual inflammatory proteins is uncertain. OBJECTIVE: To examine the relationships between a spectrum of inflammatory proteins and myocardial infarction (MI). METHODS AND RESULTS: A panel of 92 inflammatory proteins was assessed using an OLINK multiplex immunoassay among 432 MI cases (diagnosed < 66 years) and 323 controls. Logistic regression was used to estimate associations between individual proteins and MI, after adjustment for established cardiovascular risk factors and medication use, and stepwise regression to identify proteins with independent effects. Machine learning techniques (Boruta analysis and LASSO regression) and bioinformatic resources were used to examine the concordance of results with those obtained by conventional methods and explore the underlying biological processes to inform the validity of the associations. Among the 92 proteins studied, 62 (67%) had plasma concentrations above the lower limit of detection in at least 50% of samples. Of these, 15 individual proteins were significantly associated with MI after covariate adjustment and correction for multiple testing. Five of these 15 proteins (CDCP1, CD6, IL1-8R1, IL-6, and CXCL1) were independently associated with MI, with up to three-fold higher risks of MI per doubling in plasma concentrations. Findings were further validated using machine learning techniques and biologically focused analyses. CONCLUSIONS: This study, demonstrating independent relationships between five inflammatory proteins and MI, provides important novel insights into the inflammatory hypothesis of MI and the potential utility of proteomic analyses in precision medicine.

The PROCARDIS study conducted a hypothesis-free proteomic study using a panel of 92 inflammatory proteins in cases with early onset myocardial infarction (MI) and healthy controls and identified 15 proteins that were significantly associated with MI, including five proteins that independently contributed to risk of MI. The study used state-of-the-art analytical methods including conventional statistical analysis and machine learning approaches to characterize the proteomic associations with MI. It also integrated bioinformatic and genomic data to consider the biological relevance of the proteins independently associated with MI. The findings provide novel insights into the 'inflammatory basis' of MI and provide support for prioritizing a wider array of inflammatory proteins for further study than have been previously considered in order to discover if therapeutic modification could be used for treatment and prevention of MI.

Determining the Relationship Between Blood Pressure, Kidney Function, and Chronic Kidney Disease: Insights From Genetic Epidemiology.

BACKGROUND: It is well established that decreased kidney function can increase blood pressure (BP), but it is unproven whether moderately elevated BP causes chronic kidney disease (CKD) or glomerular hyperfiltration. METHODS: 311 119 White British UK Biobank participants were included in logistic regression analyses to estimate the odds of CKD (defined as long-term kidney replacement therapy, estimated glomerular filtration rate [eGFR]< 60mL/min/1.73m2, or urinary albumin:creatinine ratio ≥3 mg/mmol) associated with higher genetically predicted BP using genetic risk scores comprising 219 systolic and 223 diastolic BP loci. Analyses estimating associations with clinical categories of eGFR and urinary albumin:creatinine ratio were also conducted, with an eGFR ≥120 mL (min·1.73m2) considered evidence of glomerular hyperfiltration. RESULTS: 21 623 participants had CKD: 7781 with reduced eGFR and 15 500 with albuminuria. 1828 participants had an eGFR ≥120 mL/min/1.73m2. Each genetically predicted 10 mmHg higher systolic BP and 5 mmHg higher diastolic BP were associated with a 37% (95% CI, 1.29-1.45) and 19% (1.14-1.25) higher odds of CKD, respectively. Associations were evident for both the reduced eGFR and albuminuria components of the CKD outcome. The odds of hyperfiltration (versus an eGFR ≥60 and <90 mL/min/1.73m2 were 49% higher (95% CI, 1.21-1.84) for each genetically predicted 10 mmHg higher systolic BP. Associations with CKD and hyperfiltration were similar irrespective of preexisting diabetes, vascular disease, or different levels of adiposity. CONCLUSIONS: In this general population, genetic epidemiological evidence supports a causal role of life-long differences in BP for decreased kidney function, glomerular hyperfiltration, and albuminuria. Physiological autoregulation may not afford complete renal protection against the moderate BP elevations.

Oxidized phospholipids on apolipoprotein B-100 versus plasminogen and risk of coronary heart disease in the PROCARDIS study.

BACKGROUND AND AIMS: Oxidized phospholipids carried on the apolipoprotein B-100 (OxPL-apoB) component of Lp(a) are predictive of coronary heart disease (CHD), but the role of oxidized phospholipids carried on plasminogen (OxPL-PLG) is unknown. We examined the independent effects of OxPL-apoB and OxPL-PLG for risk of CHD before and after adjustment for Lp(a). METHODS: Plasma levels of OxPL-apoB, OxPL-PLG, plasminogen and Lp(a) were measured in the PROCARDIS study of early-onset CHD (906 cases/858 controls). Multivariable logistic regression was used to estimate the odds ratios (OR) for each biomarker with CHD after adjustment for established risk factors. RESULTS: Mean levels of OxPL-apoB were higher in cases than controls, but levels of OxPL-PLG and plasminogen were similar. For OxPL-apoB, individuals in the top vs bottom fifth had 2-fold higher age and sex-adjusted OR of CHD (OR = 2.61 [95%CI: 1.91, 3.55]), which were partially attenuated after adjustment for established risk factors. The findings for OxPL-apoB and CHD in PROCARDIS were comparable with those of a meta-analysis of all such studies. However, the associations of OxPL-apoB with CHD were fully attenuated by additional adjustment for Lp(a) (OR = 0.93 [0.54,1.60]). Neither OxPL-PLG nor plasminogen were associated with CHD. Overall, there were no differences in the predictive value for CHD of high vs normal levels (<20th or >80th percentile) of OxPL-apoB, OxPL-PLG, plasminogen or Lp(a) after stratifying for each other. CONCLUSIONS: These results highlight the context-dependency of OxPL in plasma and suggest that their associated risk of CHD is chiefly mediated by their carriage on Lp(a).

Genetic associations of adult height with risk of cardioembolic and other subtypes of ischemic stroke: A mendelian randomization study in multiple ancestries.

BACKGROUND: Taller adult height is associated with lower risks of ischemic heart disease in mendelian randomization (MR) studies, but little is known about the causal relevance of height for different subtypes of ischemic stroke. The present study examined the causal relevance of height for different subtypes of ischemic stroke. METHODS AND FINDINGS: Height-associated genetic variants (up to 2,337) from previous genome-wide association studies (GWASs) were used to construct genetic instruments in different ancestral populations. Two-sample MR approaches were used to examine the associations of genetically determined height with ischemic stroke and its subtypes (cardioembolic stroke, large-artery stroke, and small-vessel stroke) in multiple ancestries (the MEGASTROKE consortium, which included genome-wide studies of stroke and stroke subtypes: 60,341 ischemic stroke cases) supported by additional cases in individuals of white British ancestry (UK Biobank [UKB]: 4,055 cases) and Chinese ancestry (China Kadoorie Biobank [CKB]: 10,297 cases). The associations of genetically determined height with established cardiovascular and other risk factors were examined in 336,750 participants from UKB and 58,277 participants from CKB. In MEGASTROKE, genetically determined height was associated with a 4% lower risk (odds ratio [OR] 0.96; 95% confidence interval [CI] 0.94, 0.99; p = 0.007) of ischemic stroke per 1 standard deviation (SD) taller height, but this masked a much stronger positive association of height with cardioembolic stroke (13% higher risk, OR 1.13 [95% CI 1.07, 1.19], p < 0.001) and stronger inverse associations with large-artery stroke (11% lower risk, OR 0.89 [0.84, 0.95], p < 0.001) and small-vessel stroke (13% lower risk, OR 0.87 [0.83, 0.92], p < 0.001). The findings in both UKB and CKB were directionally concordant with those observed in MEGASTROKE, but did not reach statistical significance: For presumed cardioembolic stroke, the ORs were 1.08 (95% CI 0.86, 1.35; p = 0.53) in UKB and 1.20 (0.77, 1.85; p = 0.43) in CKB; for other subtypes of ischemic stroke in UKB, the OR was 0.97 (95% CI 0.90, 1.05; p = 0.49); and for other nonlacunar stroke and lacunar stroke in CKB, the ORs were 0.89 (0.80, 1.00; p = 0.06) and 0.99 (0.88, 1.12; p = 0.85), respectively. In addition, genetically determined height was also positively associated with atrial fibrillation (available only in UKB), and with lean body mass and lung function, and inversely associated with low-density lipoprotein (LDL) cholesterol in both British and Chinese ancestries. Limitations of this study include potential bias from assortative mating or pleiotropic effects of genetic variants and incomplete generalizability of genetic instruments to different populations. CONCLUSIONS: The findings provide support for a causal association of taller adult height with higher risk of cardioembolic stroke and lower risk of other ischemic stroke subtypes in diverse ancestries. Further research is needed to understand the shared biological and physical pathways underlying the associations between height and stroke risks, which could identify potential targets for treatments to prevent stroke.

Are polygenic risk scores for systolic blood pressure and LDL-cholesterol associated with treatment effectiveness, and clinical outcomes among those on treatment?

AIMS: Many studies have investigated associations between polygenic risk scores (PRS) and the incidence of cardiovascular disease (CVD); few have examined whether risk factor-related PRS predict CVD outcomes among adults treated with risk-modifying therapies. We assessed whether PRS for systolic blood pressure (PRSSBP) and for low-density lipoprotein cholesterol (PRSLDL-C) were associated with achieving SBP and LDL-C-related targets, and with major adverse cardiovascular events (MACE: non-fatal stroke or myocardial infarction, CVD death, and revascularization procedures). METHODS AND RESULTS: Using observational data from the UK Biobank (UKB), we calculated PRSSBP and PRSLDL-C and constructed two sub-cohorts of unrelated adults of White British ancestry aged 40-69 years and with no history of CVD, who reported taking medications used in the treatment of hypertension or hypercholesterolaemia. Treatment effectiveness in achieving adequate risk factor control was ascertained using on-treatment blood pressure (BP) or LDL-C levels measured at enrolment (uncontrolled hypertension: BP ≥ 140/90 mmHg; uncontrolled hypercholesterolaemia: LDL-C ≥ 3 mmol/L). We conducted multivariable logistic and Cox regression modelling for incident events, adjusting for socioeconomic characteristics, and CVD risk factors. There were 55 439 participants using BP lowering therapies (51.0% male, mean age 61.0 years, median follow-up 11.5 years) and 33 787 using LDL-C lowering therapies (58.5% male, mean age 61.7 years, median follow-up 11.4 years). PRSSBP was associated with uncontrolled hypertension (odds ratio 1.70; 95% confidence interval: 1.60-1.80) top vs. bottom quintile, equivalent to a 5.4 mmHg difference in SBP, and with MACE [hazard ratio (HR) 1.13; 1.04-1.23]. PRSLDL-C was associated with uncontrolled hypercholesterolaemia (HR 2.78; 2.58-3.00) but was not associated with subsequent MACE. CONCLUSION: We extend previous findings in the UKB cohort to examine PRSSBP and PRSLDL-C with treatment effectiveness. Our results indicate that both PRSSBP and PRSLDL-C can help identify individuals who, despite being on treatment, have inadequately controlled SBP and LDL-C, and for SBP are at higher risk for CVD events. This extends the potential role of PRS in clinical practice from identifying patients who may need these interventions to identifying patients who may need more intensive intervention.

Robust estimates of heritable coronary disease risk in individuals with type 2 diabetes.

Type 2 diabetes (T2D) is an important heritable risk factor for coronary artery disease (CAD), the risk of both diseases being increased by metabolic syndrome (MS). With the availability of large-scale genome-wide association data, we aimed to elucidate the genetic burden of CAD risk in T2D predisposed individuals within the context of MS and their shared genetic architecture. Mendelian randomization (MR) analyses supported a causal relationship between T2D and CAD [odds ratio (OR) = 1.13 per log-odds unit 95% confidence interval (CI): 1.10-1.16; p = 1.59 × 10-17 ]. Simultaneously adjusting MR analyses for the effects of the T2D instrument including blood pressure, dyslipidaemia, and obesity attenuated the association between T2D and CAD (OR = 1.07, 95% CI: 1.04-1.11). Bayesian locus-overlap analysis identified 44 regions with the same causal variant underlying T2D and CAD genetic signals (FDR < 1%) at a posterior probability >0.7; five (MHC, LPL, ABO, RAI1 and MC4R) of these regions contain genome-wide significant (p < 5 × 10-8 ) associations for both traits. Given the small effect sizes observed in genome-wide association studies for complex diseases, even with 44 potential target regions, this has implications for the likely magnitude of CAD risk reduction that might be achievable by pure T2D therapies.

Smoking and COVID-19 outcomes: an observational and Mendelian randomisation study using the UK Biobank cohort.

BACKGROUND: Conflicting evidence has emerged regarding the relevance of smoking on risk of COVID-19 and its severity. METHODS: We undertook large-scale observational and Mendelian randomisation (MR) analyses using UK Biobank. Most recent smoking status was determined from primary care records (70.8%) and UK Biobank questionnaire data (29.2%). COVID-19 outcomes were derived from Public Health England SARS-CoV-2 testing data, hospital admissions data, and death certificates (until 18 August 2020). Logistic regression was used to estimate associations between smoking status and confirmed SARS-CoV-2 infection, COVID-19-related hospitalisation, and COVID-19-related death. Inverse variance-weighted MR analyses using established genetic instruments for smoking initiation and smoking heaviness were undertaken (reported per SD increase). RESULTS: There were 421 469 eligible participants, 1649 confirmed infections, 968 COVID-19-related hospitalisations and 444 COVID-19-related deaths. Compared with never-smokers, current smokers had higher risks of hospitalisation (OR 1.80, 95% CI 1.26 to 2.29) and mortality (smoking 1-9/day: OR 2.14, 95% CI 0.87 to 5.24; 10-19/day: OR 5.91, 95% CI 3.66 to 9.54; 20+/day: OR 6.11, 95% CI 3.59 to 10.42). In MR analyses of 281 105 White British participants, genetically predicted propensity to initiate smoking was associated with higher risks of infection (OR 1.45, 95% CI 1.10 to 1.91) and hospitalisation (OR 1.60, 95% CI 1.13 to 2.27). Genetically predicted higher number of cigarettes smoked per day was associated with higher risks of all outcomes (infection OR 2.51, 95% CI 1.20 to 5.24; hospitalisation OR 5.08, 95% CI 2.04 to 12.66; and death OR 10.02, 95% CI 2.53 to 39.72). INTERPRETATION: Congruent results from two analytical approaches support a causal effect of smoking on risk of severe COVID-19.

Independent effects of adiposity measures on risk of atrial fibrillation in men and women: a study of 0.5 million individuals.

BACKGROUND: Atrial fibrillation (AF) has a higher prevalence in men than in women and is associated with measures of adiposity and lean mass (LM). However, it remains uncertain whether the risks of AF associated with these measures vary by sex. METHODS: Among 477 904 UK Biobank participants aged 40-69 without prior AF, 23 134 incident AF cases were identified (14 400 men, 8734 women; median follow-up 11.1 years). Cox proportional hazards models were used to estimate the covariate adjusted hazard ratios (HRs) describing the association of AF with weight, measures of adiposity [fat mass (FM), waist circumference (WC)] and LM, and their independent relevance, by sex. RESULTS: Weight and WC were independently associated with risk of AF [HR: 1.25 (1.23-1.27) per 10 kg, HR: 1.11 (1.09-1.14) per 10 cm, respectively], with comparable effects in both sexes. The association with weight was principally driven by LM, which, per 5 kg, conferred double the risk of AF compared with FM when mutually adjusted [HR: 1.20 (1.19-1.21), HR: 1.10 (1.09-1.11), respectively]; however, the effect of LM was weaker in men than in women (p-interaction = 4.3 x 10-9). Comparing the relative effects of LM, FM and WC identified different patterns within each sex; LM was the strongest predictor for both, whereas WC was stronger than FM in men but not in women. CONCLUSIONS: LM and FM (as constituents of weight) and WC are risk factors for AF. However, the independent relevance of general adiposity for AF was more limited in men than in women. The relevance of both WC and LM suggests a potentially important role for visceral adiposity and muscle mass in AF development.

Genome-Wide Association Study of Peripheral Artery Disease.

BACKGROUND: Peripheral artery disease (PAD) affects >200 million people worldwide and is associated with high mortality and morbidity. We sought to identify genomic variants associated with PAD overall and in the contexts of diabetes and smoking status. METHODS: We identified genetic variants associated with PAD and then meta-analyzed with published summary statistics from the Million Veterans Program and UK Biobank to replicate their findings. Next, we ran stratified genome-wide association analysis in ever smokers, never smokers, individuals with diabetes, and individuals with no history of diabetes and corresponding interaction analyses, to identify variants that modify the risk of PAD by diabetic or smoking status. RESULTS: We identified 5 genome-wide significant (Passociation ≤5×10-8) associations with PAD in 449 548 (Ncases=12 086) individuals of European ancestry near LPA (lipoprotein [a]), CDKN2BAS1 (CDKN2B antisense RNA 1), SH2B3 (SH2B adaptor protein 3) - PTPN11 (protein tyrosine phosphatase non-receptor type 11), HDAC9 (histone deacetylase 9), and CHRNA3 (cholinergic receptor nicotinic alpha 3 subunit) loci (which overlapped previously reported associations). Meta-analysis with variants previously associated with PAD showed that 18 of 19 published variants remained genome-wide significant. In individuals with diabetes, rs116405693 at the CCSER1 (coiled-coil serine rich protein 1) locus was associated with PAD (odds ratio [95% CI], 1.51 [1.32-1.74], Pdiabetes=2.5×10-9, Pinteractionwithdiabetes=5.3×10-7). Furthermore, in smokers, rs12910984 at the CHRNA3 locus was associated with PAD (odds ratio [95% CI], 1.15 [1.11-1.19], Psmokers=9.3×10-10, Pinteractionwithsmoking=3.9×10-5). CONCLUSIONS: Our analyses confirm the published genetic associations with PAD and identify novel variants that may influence susceptibility to PAD in the context of diabetes or smoking status.

The impact of atrial fibrillation and stroke risk factors on left atrial blood flow characteristics.

AIMS: Altered left atrial (LA) blood flow characteristics account for an increase in cardioembolic stroke risk in atrial fibrillation (AF). Here, we aimed to assess whether exposure to stroke risk factors is sufficient to alter LA blood flow even in the presence of sinus rhythm (SR). METHODS AND RESULTS: We investigated 95 individuals: 37 patients with persistent AF, who were studied before and after cardioversion [Group 1; median CHA2DS2-VASc = 2.0 (1.5-3.5)]; 35 individuals with no history of AF but similar stroke risk to Group 1 [Group 2; median CHA2DS2-VASc = 3.0 (2.0-4.0)]; and 23 low-risk individuals in SR [Group 3; median CHA2DS2-VASc = 0.0 (0.0-0.0)]. Cardiac function and LA flow characteristics were evaluated using cardiac magnetic resonance. Before cardioversion, Group 1 displayed impaired left ventricular (LV) and LA function, reduced LA flow velocities and vorticity, and a higher normalized vortex volume (all P < 0.001 vs. Groups 2 and 3). After restoration of SR at ≥4-week post-cardioversion, LV systolic function and LA flow parameters improved significantly (all P < 0.001 vs. pre-cardioversion) and were no longer different from those in Group 2. However, in the presence of SR, LA flow peak and mean velocity, and vorticity were lower in Groups 1 and 2 vs. Group 3 (all P < 0.01), and were associated with impaired LA emptying fraction (LAEF) and LV diastolic dysfunction. CONCLUSION: Patients at moderate-to-high stroke risk display altered LA flow characteristics in SR in association with an LA myopathic phenotype and LV diastolic dysfunction, regardless of a history of AF.

Assessment of the causal relevance of ECG parameters for risk of atrial fibrillation: A mendelian randomisation study.

BACKGROUND: Atrial electrical and structural remodelling in older individuals with cardiovascular risk factors has been associated with changes in surface electrocardiographic (ECG) parameters (e.g., prolongation of the PR interval) and higher risks of atrial fibrillation (AF). However, it has been difficult to establish whether altered ECG parameters are the cause or a consequence of the myocardial substrate leading to AF. This study aimed to examine the potential causal relevance of ECG parameters on risk of AF using mendelian randomisation (MR). METHODS AND FINDINGS: Weighted genetic scores explaining lifelong differences in P-wave duration, PR interval, and QT interval were constructed, and associations between these ECG scores and risk of AF were estimated among 278,792 UK Biobank participants (mean age: 57 years at recruitment; 19,132 AF cases). The independent genetic variants contributing to each of the separate ECG scores, and their corresponding weights, were based on published genome-wide association studies. In UK Biobank, genetic scores representing a 5 ms longer P-wave duration or PR interval were significantly associated with lower risks of AF (odds ratio [OR] 0.91; 95% confidence interval [CI]: 0.87-0.96, P = 2 × 10-4 and OR 0.94; 95% CI: 0.93-0.96, P = 2 × 10-19, respectively), while longer QT interval was not significantly associated with AF. These effects were independently replicated among a further 17,931 AF cases from the AFGen Consortium. Investigation of potential mechanistic pathways showed that differences in ECG parameters associated with specific ion channel genes had effects on risk of AF consistent with the overall scores, while the overall scores were not associated with changes in left atrial size. Limitations of the study included the inherent assumptions of MR, restriction to individuals of European ancestry, and possible restriction of results to the normal ECG ranges represented in UK Biobank. CONCLUSIONS: In UK Biobank, we observed evidence suggesting a causal relationship between lifelong differences in ECG parameters (particularly PR interval) that reflect longer atrial conduction times and a lower risk of AF. These findings, which appear to be independent of atrial size and concomitant cardiovascular comorbidity, support the relevance of varying mechanisms underpinning AF and indicate that more individualised treatment strategies warrant consideration.

The Use of Primary Care Big Data in Understanding the Pharmacoepidemiology of COVID-19: A Consensus Statement From the COVID-19 Primary Care Database Consortium.

The use of big data containing millions of primary care medical records provides an opportunity for rapid research to help inform patient care and policy decisions during the first and subsequent waves of the coronavirus disease 2019 (COVID-19) pandemic. Routinely collected primary care data have previously been used for national pandemic surveillance, quantifying associations between exposures and outcomes, identifying high risk populations, and examining the effects of interventions at scale, but there is no consensus on how to effectively conduct or report these data for COVID-19 research. A COVID-19 primary care database consortium was established in April 2020 and its researchers have ongoing COVID-19 projects in overlapping data sets with over 40 million primary care records in the United Kingdom that are variously linked to public health, secondary care, and vital status records. This consensus agreement is aimed at facilitating transparency and rigor in methodological approaches, and consistency in defining and reporting cases, exposures, confounders, stratification variables, and outcomes in relation to the pharmacoepidemiology of COVID-19. This will facilitate comparison, validation, and meta-analyses of research during and after the pandemic.

Independent risk factors for simvastatin-related myopathy and relevance to different types of muscle symptom.

AIMS: Statins are widely used to prevent cardiovascular events, but little is known about the impact of different risk factors for statin-related myopathy or their relevance to reports of other types of muscle symptom. METHODS AND RESULTS: An observational analysis was undertaken of 171 clinically adjudicated cases of myopathy (defined as unexplained muscle pain or weakness with creatine kinase >10× upper limit of normal) and, separately, of 15 208 cases of other muscle symptoms among 58 390 individuals with vascular disease treated with simvastatin for a mean of 3.4 years. Cox proportional hazards models were used to identify independent predictors of myopathy. The rate of myopathy was low: 9 per 10 000 person-years of simvastatin therapy. Independent risk factors for myopathy included: simvastatin dose, ethnicity, sex, age, body mass index, medically treated diabetes, concomitant use of niacin-laropiprant, verapamil, beta-blockers, diltiazem and diuretics. In combination, these risk factors predicted more than a 30-fold risk difference between the top and bottom thirds of a myopathy risk score (hazard ratio : 34.35, 95% CI: 12.73-92.69, P across thirds = 9·1 × 10-48). However, despite the strong association with myopathy, this score was not associated with the other reported muscle symptoms (P across thirds = 0.93). Likewise, although SLCO1B1 genotype was associated with myopathy, it was not associated with other muscle symptoms. CONCLUSIONS: The absolute risk of simvastatin-related myopathy is low, but individuals at higher risk can be identified to help guide patient management. The lack of association of the myopathy risk score with other muscle symptoms reinforces randomized placebo-controlled evidence that statins do not cause the vast majority of reported muscle symptoms.

Genetic determinants of blood lipids and cerebral small vessel disease: role of high-density lipoprotein cholesterol.

Blood lipids are causally involved in the pathogenesis of atherosclerosis, but their role in cerebral small vessel disease remains largely elusive. Here, we explored associations of genetic determinants of blood lipid levels, lipoprotein particle components, and targets for lipid-modifying drugs with small vessel disease phenotypes. We selected genetic instruments for blood levels of high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides, for cholesterol and triglycerides components of size-defined lipoprotein particles, and for lipid-modifying drug targets based on published genome-wide association studies (up to 617 303 individuals). Applying two-sample Mendelian randomization approaches we investigated associations with ischaemic and haemorrhagic manifestations of small vessel disease [small vessel stroke: 11 710 cases, 287 067 controls; white matter hyperintensities (WMH): 10 597 individuals; intracerebral haemorrhage: 1545 cases, 1481 controls]. We applied the inverse-variance weighted method and multivariable Mendelian randomization as our main analytical approaches. Genetic predisposition to higher HDL-C levels was associated with lower risk of small vessel stroke [odds ratio (OR) per standard deviation = 0.85, 95% confidence interval (CI) = 0.78-0.92] and lower WMH volume (ß = -0.07, 95% CI = -0.12 to -0.02), which in multivariable Mendelian randomization remained stable after adjustments for LDL-C and triglycerides. In analyses of lipoprotein particle components by size, we found these effects to be specific for cholesterol concentration in medium-sized high-density lipoprotein, and not large or extra-large high-density lipoprotein particles. Association estimates for intracerebral haemorrhage were negatively correlated with those for small vessel stroke and WMH volume across all lipid traits and lipoprotein particle components. HDL-C raising genetic variants in the gene locus of the target of CETP inhibitors were associated with lower risk of small vessel stroke (OR: 0.82, 95% CI = 0.75-0.89) and lower WMH volume (ß = -0.08, 95% CI = -0.13 to -0.02), but a higher risk of intracerebral haemorrhage (OR: 1.64, 95% CI = 1.26-2.13). Genetic predisposition to higher HDL-C, specifically to cholesterol in medium-sized high-density lipoprotein particles, is associated with both a lower risk of small vessel stroke and lower WMH volume. These analyses indicate that HDL-C raising strategies could be considered for the prevention of ischaemic small vessel disease but the net benefit of such an approach would need to be tested in a randomized controlled trial.

Identification of patients with atrial fibrillation: a big data exploratory analysis of the UK Biobank.

OBJECTIVE: Atrial fibrillation (AF) is the most common cardiac arrhythmia, with an estimated prevalence of around 1.6% in the adult population. The analysis of the electrocardiogram (ECG) data acquired in the UK Biobank represents an opportunity to screen for AF in a large sub-population in the UK. The main objective of this paper is to assess ten machine-learning methods for automated detection of subjects with AF in the UK Biobank dataset. APPROACH: Six classical machine-learning methods based on support vector machines are proposed and compared with state-of-the-art techniques (including a deep-learning algorithm), and finally a combination of a classical machine-learning and deep learning approaches. Evaluation is carried out on a subset of the UK Biobank dataset, manually annotated by human experts. MAIN RESULTS: The combined classical machine-learning and deep learning method achieved an F1 score of 84.8% on the test subset, and a Cohen's kappa coefficient of 0.83, which is similar to the inter-observer agreement of two human experts. SIGNIFICANCE: The level of performance indicates that the automated detection of AF in patients whose data have been stored in a large database, such as the UK Biobank, is possible. Such automated identification of AF patients would enable further investigations aimed at identifying the different phenotypes associated with AF.

Identifying small-effect genetic associations overlooked by the conventional fixed-effect model in a large-scale meta-analysis of coronary artery disease.

MOTIVATION: Common small-effect genetic variants that contribute to human complex traits and disease are typically identified using traditional fixed-effect (FE) meta-analysis methods. However, the power to detect genetic associations under FE models deteriorates with increasing heterogeneity, so that some small-effect heterogeneous loci might go undetected. A modified random-effects meta-analysis approach (RE2) was previously developed that is more powerful than traditional fixed and random-effects methods at detecting small-effect heterogeneous genetic associations, the method was updated (RE2C) to identify small-effect heterogeneous variants overlooked by traditional fixed-effect meta-analysis. Here, we re-appraise a large-scale meta-analysis of coronary disease with RE2C to search for small-effect genetic signals potentially masked by heterogeneity in a FE meta-analysis. RESULTS: Our application of RE2C suggests a high sensitivity but low specificity of this approach for discovering small-effect heterogeneous genetic associations. We recommend that reports of small-effect heterogeneous loci discovered with RE2C are accompanied by forest plots and standardized predicted random-effects statistics to reveal the distribution of genetic effect estimates across component studies of meta-analyses, highlighting overly influential outlier studies with the potential to inflate genetic signals. AVAILABILITY AND IMPLEMENTATION: Scripts to calculate standardized predicted random-effects statistics and generate forest plots are available in the getspres R package entitled from https://magosil86.github.io/getspres/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.