Estimating Additive Interaction in Two-Stage Individual Participant Data Meta-Analysis.

Individual participant data (IPD) meta-analysis provides important opportunities to study interaction and effect modification for which individual studies often lack power. While previous meta-analyses have commonly focused on multiplicative interaction, additive interaction holds greater relevance for public health and may in certain contexts better reflect biological interaction. Methodological literature on interaction in IPD meta-analysis does not cover additive interaction for models including binary or time-to-event outcomes. We aimed to describe how the Relative Excess Risk due to Interaction (RERI) and other measures of additive interaction or effect modification can be validly estimated within two-stage IPD meta-analysis. First, we explain why direct pooling of study-level RERI estimates may lead to invalid results. Next, we propose a three-step procedure to estimate additive interaction: 1) estimate effects of both exposures and their product term on the outcome within each individual study; 2) pool study-specific estimates using multivariate meta-analysis; 3) estimate an overall RERI and 95% confidence interval based on the pooled effect estimates. We illustrate this procedure by investigating interaction between depression and smoking and risk of smoking-related cancers using data from the PSYchosocial factors and Cancer (PSY-CA) consortium. We discuss implications of this procedure, including the application in meta-analysis based on published data.

Long-term reliability of the phospholamban (PLN) p.(Arg14del) risk model in predicting major ventricular arrhythmia: a landmark study.

AIMS: Recently, a genetic variant-specific prediction model for phospholamban (PLN) p.(Arg14del)-positive individuals was developed to predict individual major ventricular arrhythmia (VA) risk to support decision-making for primary prevention implantable cardioverter defibrillator (ICD) implantation. This model predicts major VA risk from baseline data, but iterative evaluation of major VA risk may be warranted considering that the risk factors for major VA are progressive. Our aim is to evaluate the diagnostic performance of the PLN p.(Arg14del) risk model at 3-year follow-up. METHODS AND RESULTS: We performed a landmark analysis 3 years after presentation and selected only patients with no prior major VA. Data were collected of 268 PLN p.(Arg14del)-positive subjects, aged 43.5 ± 16.3 years, 38.9% male. After the 3 years landmark, subjects had a mean follow-up of 4.0 years (± 3.5 years) and 28 (10%) subjects experienced major VA with an annual event rate of 2.6% [95% confidence interval (CI) 1.6-3.6], defined as sustained VA, appropriate ICD intervention, or (aborted) sudden cardiac death. The PLN p.(Arg14del) risk score yielded good discrimination in the 3 years landmark cohort with a C-statistic of 0.83 (95% CI 0.79-0.87) and calibration slope of 0.97. CONCLUSION: The PLN p.(Arg14del) risk model has sustained good model performance up to 3 years follow-up in PLN p.(Arg14del)-positive subjects with no history of major VA. It may therefore be used to support decision-making for primary prevention ICD implantation not merely at presentation but also up to at least 3 years of follow-up.

Lipoprotein(a) levels in children with suspected familial hypercholesterolaemia: a cross-sectional study.

AIMS: Familial hypercholesterolaemia (FH) predisposes children to the early initiation of atherosclerosis and is preferably diagnosed by DNA analysis. Yet, in many children with a clinical presentation of FH, no mutation is found. Adult data show that high levels of lipoprotein(a) [Lp(a)] may underlie a clinical presentation of FH, as the cholesterol content of Lp(a) is included in conventional LDL cholesterol measurements. As this is limited to adult data, Lp(a) levels in children with and without (clinical) FH were evaluated. METHODS AND RESULTS: Children were eligible if they visited the paediatric lipid clinic (1989-2020) and if Lp(a) measurement and DNA analysis were performed. In total, 2721 children (mean age: 10.3 years) were included and divided into four groups: 1931 children with definite FH (mutation detected), 290 unaffected siblings/normolipidaemic controls (mutation excluded), 108 children with probable FH (clinical presentation, mutation not detected), and 392 children with probable non-FH (no clinical presentation, mutation not excluded). In children with probable FH, 32% were found to have high Lp(a) [geometric mean (95% confidence interval) of 15.9 (12.3-20.6) mg/dL] compared with 10 and 10% [geometric means (95% confidence interval) of 11.5 (10.9-12.1) mg/dL and 9.8 (8.4-11.3) mg/dL] in children with definite FH (P = 0.017) and unaffected siblings (P = 0.002), respectively. CONCLUSION: Lp(a) was significantly higher and more frequently elevated in children with probable FH compared with children with definite FH and unaffected siblings, suggesting that high Lp(a) may underlie the clinical presentation of FH when no FH-causing mutation is found. Performing both DNA analysis and measuring Lp(a) in all children suspected of FH is recommended to assess possible LDL cholesterol overestimation related to increased Lp(a).

Growth charts for Marfan syndrome in the Netherlands and analysis of genotype-phenotype relationships.

To optimize care for children with Marfan syndrome (MFS) in the Netherlands, Dutch MFS growth charts were constructed. Additionally, we aimed to investigate the effect of FBN1 variant type (haploinsufficiency [HI]/dominant negative [DN]) on growth, and compare MFS-related height increase across populations. Height and weight data of individuals with MFS aged 0-21 years were retrospectively collected. Generalized Additive Models for Location, Scale and Shape (GAMLSS) was used for growth chart modeling. To investigate genotype-phenotype relationships, FBN1 variant type was included as an independent variable in height-for-age and BMI-for-age models. MFS-related height increase was compared with that of previous MFS growth studies from the United States, Korea, and France. Height and weight data of 389 individuals with MFS were included (210 males). Height-for-age, BMI-for-age, and weight-for-height charts reflected the tall and slender MFS habitus throughout childhood. Mean increase in height of individuals with MFS compared with the general Dutch population was significantly lower than in the other three MFS populations compared to their reference populations. FBN1-HI variants were associated with taller height in both sexes, and decreased BMI in females (p-values <0.05). This Dutch MFS growth study broadens the notion that genetic background and MFS variant type (HI/DN) influence tall and slender stature in MFS.

Alert system-supported lay defibrillation and basic life-support for cardiac arrest at home.

AIMS: Automated external defibrillators (AEDs) are placed in public, but the majority of out-of-hospital cardiac arrests (OHCA) occur at home. METHODS AND RESULTS: In residential areas, 785 AEDs were placed and 5735 volunteer responders were recruited. For suspected OHCA, dispatchers activated nearby volunteer responders with text messages, directing two-thirds to an AED first and one-third directly to the patient. We analysed survival (primary outcome) and neurologically favourable survival to discharge, time to first defibrillation shock, and cardiopulmonary resuscitation (CPR) before Emergency Medical Service (EMS) arrival of patients in residences found with ventricular fibrillation (VF), before and after introduction of this text-message alert system. Survival from OHCAs in residences increased from 26% to 39% {adjusted relative risk (RR) 1.5 [95% confidence interval (CI): 1.03-2.0]}. RR for neurologically favourable survival was 1.4 (95% CI: 0.99-2.0). No CPR before ambulance arrival decreased from 22% to 9% (RR: 0.5, 95% CI: 0.3-0.7). Text-message-responders with AED administered shocks to 16% of all patients in VF in residences, while defibrillation by EMS decreased from 73% to 39% in residences (P < 0.001). Defibrillation by first responders in residences increased from 22 to 40% (P < 0.001). Use of public AEDs in residences remained unchanged (6% and 5%) (P = 0.81). Time from emergency call to defibrillation decreased from median 11.7 to 9.3 min; mean difference -2.6 (95% CI: -3.5 to -1.6). CONCLUSION: Introducing volunteer responders directed to AEDs, dispatched by text-message was associated with significantly reduced time to first defibrillation, increased bystander CPR and increased overall survival for OHCA patients in residences found with VF.

A deep learning approach identifies new ECG features in congenital long QT syndrome.

BACKGROUND: Congenital long QT syndrome (LQTS) is a rare heart disease caused by various underlying mutations. Most general cardiologists do not routinely see patients with congenital LQTS and may not always recognize the accompanying ECG features. In addition, a proportion of disease carriers do not display obvious abnormalities on their ECG. Combined, this can cause underdiagnosing of this potentially life-threatening disease. METHODS: This study presents 1D convolutional neural network models trained to identify genotype positive LQTS patients from electrocardiogram as input. The deep learning (DL) models were trained with a large 10-s 12-lead ECGs dataset provided by Amsterdam UMC and externally validated with a dataset provided by University Hospital Leuven. The Amsterdam dataset included ECGs from 10000 controls, 172 LQTS1, 214 LQTS2, and 72 LQTS3 patients. The Leuven dataset included ECGs from 2200 controls, 32 LQTS1, and 80 LQTS2 patients. The performance of the DL models was compared with conventional QTc measurement and with that of an international expert in congenital LQTS (A.A.M.W). Lastly, an explainable artificial intelligence (AI) technique was used to better understand the prediction models. RESULTS: Overall, the best performing DL models, across 5-fold cross-validation, achieved on average a sensitivity of 84 ± 2%, 90 ± 2% and 87 ± 6%, specificity of 96 ± 2%, 95 ± 1%, and 92 ± 4%, and AUC of 0.90 ± 0.01, 0.92 ± 0.02, and 0.89 ± 0.03, for LQTS 1, 2, and 3 respectively. The DL models were also shown to perform better than conventional QTc measurements in detecting LQTS patients. Furthermore, the performances held up when the DL models were validated on a novel external cohort and outperformed the expert cardiologist in terms of specificity, while in terms of sensitivity, the DL models and the expert cardiologist in LQTS performed the same. Finally, the explainable AI technique identified the onset of the QRS complex as the most informative region to classify LQTS from non-LQTS patients, a feature previously not associated with this disease. CONCLUSIONS: This study suggests that DL models can potentially be used to aid cardiologists in diagnosing LQTS. Furthermore, explainable DL models can be used to possibly identify new features for LQTS on the ECG, thus increasing our understanding of this syndrome.

Six-lead device superior to single-lead smartwatch ECG in atrial fibrillation detection.

This was a head-to-head comparative study on different electrocardiogram (ECG)-based smartwatches and devices for atrial fibrillation detection. We prospectively included 220 patients scheduled for electrical cardioversion and recorded ECGs with 3 different devices (Withings Move ECG, Apple Watch 5, Kardia Mobile 6-leads) as well as the standard 12-lead ECG (gold standard), both before and after cardioversion. All atrial fibrillation detection algorithms had high accuracy (sensitivity and specificity: 91-99%) but were hampered by uninterpretable recordings (20-24%). In cardiologists' interpretation, the 6-lead device was superior (sensitivity 99%, specificity 97%) to both single-lead smartwatches (P < .05) for atrial fibrillation detection.

A cross-sectional study on fatigue, anxiety, and symptoms of depression and their relation with medical status in adult patients with Marfan syndrome. Psychological consequences in Marfan syndrome.

Marfan syndrome (MFS) is a connective tissue disorder affecting the cardiovascular, ocular, and skeletal system, which may be accompanied by psychological features. This study aimed to determine the prevalence of fatigue, anxiety, and symptoms of depression in MFS patients, and to assess the degree to which sociodemographic and clinical variables are associated with fatigue and psychological aspects. The prevalence of fatigue, anxiety, and symptoms of depression were assessed in two cohorts of MFS patients and compared with healthy controls. The checklist individual strength (CIS), and hospital anxiety and depression scale (HADS) questionnaires were utilized. Medical status was assessed (family history of MFS, aortic root dilatation >40 mm, previous aortic surgery, aortic dissection, chronic pain, skeletal involvement, and scoliosis). Severe fatigue was experienced by 37% of the total MFS cohort (n = 155). MFS patients scored significantly higher on the CIS questionnaire, concerning severe fatigue, as compared with the general Dutch population (p < 0.0001). There were no differences in HADS anxiety or depression scores. In older MFS patients, with a more severe cardiovascular phenotype, chronic pain, and a higher unemployment rate, significantly more symptoms of depression were observed, when compared with the general population (p = 0.027) or compared with younger MFS patients (p = 0.026). Multivariate analysis, showed that anxiety was associated with chronic pain (p = 0.022) and symptoms of depression with unemployment (p = 0.024). MFS patients report significantly more severe fatigue as compared with the general population. Since the cause of fatigue is unclear, more research may be needed. Psychological intervention, for example, cognitive behavioral therapy, may contribute to a reduction in psychological symptoms.

Prediction of ventricular arrhythmia in phospholamban p.Arg14del mutation carriers-reaching the frontiers of individual risk prediction.

AIMS: This study aims to improve risk stratification for primary prevention implantable cardioverter defibrillator (ICD) implantation by developing a new mutation-specific prediction model for malignant ventricular arrhythmia (VA) in phospholamban (PLN) p.Arg14del mutation carriers. The proposed model is compared to an existing PLN risk model. METHODS AND RESULTS: Data were collected from PLN p.Arg14del mutation carriers with no history of malignant VA at baseline, identified between 2009 and 2020. Malignant VA was defined as sustained VA, appropriate ICD intervention, or (aborted) sudden cardiac death. A prediction model was developed using Cox regression. The study cohort consisted of 679 PLN p.Arg14del mutation carriers, with a minority of index patients (17%) and male sex (43%), and a median age of 42 years [interquartile range (IQR) 27-55]. During a median follow-up of 4.3 years (IQR 1.7-7.4), 72 (10.6%) carriers experienced malignant VA. Significant predictors were left ventricular ejection fraction, premature ventricular contraction count/24 h, amount of negative T waves, and presence of low-voltage electrocardiogram. The multivariable model had an excellent discriminative ability {C-statistic 0.83 [95% confidence interval (CI) 0.78-0.88]}. Applying the existing PLN risk model to the complete cohort yielded a C-statistic of 0.68 (95% CI 0.61-0.75). CONCLUSION: This new mutation-specific prediction model for individual VA risk in PLN p.Arg14del mutation carriers is superior to the existing PLN risk model, suggesting that risk prediction using mutation-specific phenotypic features can improve accuracy compared to a more generic approach.

The circulatory small non-coding RNA landscape in community-acquired pneumonia on intensive care unit admission.

Community-acquired pneumonia (CAP) is a major cause of sepsis. Despite several clinical trials targeting components of the inflammatory response, no specific treatment other than antimicrobial therapy has been approved. This argued for a deeper understanding of sepsis immunopathology, in particular factors that can modulate the host response. Small non-coding RNA, for example, micro (mi)RNA, have been established as important modifiers of cellular phenotypes. Notably, miRNAs are not exclusive to the intracellular milieu but have also been detected extracellular in the circulation with functional consequences. Here, we sought to determine shifts in circulatory small RNA levels of critically ill patients with CAP-associated sepsis and to determine the influence of clinical severity and causal pathogens on small RNA levels. Blood plasma was collected from 13 critically ill patients with sepsis caused by CAP on intensive care unit admission and from 5 non-infectious control participants. Plasma small RNA-sequencing identified significantly altered levels of primarily mature miRNAs in CAP relative to controls. Pathways analysis of high or low abundance miRNA identified various over-represented cellular biological pathways. Analysis of small RNA levels against common clinical severity and inflammatory parameters indices showed direct and indirect correlations. Additionally, variance of plasma small RNA levels in CAP patients may be explained, at least in part, by differences in causal pathogens. Small nuclear RNA levels were specifically altered in CAP due to Influenza infection in contrast to Streptococcus pneumoniae infection. Pathway analysis of plasma miRNA signatures unique to Influenza or Streptococcus pneumoniae infections showed enrichment for specific proteoglycan, cell cycle, and immunometabolic pathways.

Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses.

BACKGROUND: Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease. METHODS: We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions. RESULTS: We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (- 0.08 standard deviation (SD)[95% confidence interval (CI) - 0.12, - 0.03] in AMV and - 0.03SD [- 0.07, - 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (- 0.04SD [- 0.08, 0.00] in AMV and - 0.05SD [- 0.09, - 0.02] in MR), and lower phospholipids in very large HDL particles (- 0.04SD [- 0.08, 0.002] in AMV and - 0.05SD [- 0.08, - 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures. CONCLUSIONS: Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.

Antihypertensives and their relation to mortality by SARS-CoV-2 infection.

The role of antihypertensives, especially Renin-Angiotensin-Aldosterone System inhibitors, is still debatable in COVID-19-related severity and outcome. Therefore, we search for a more global analysis of antihypertensive medication in relation to SAS-CoV-2 severity using prescription data worldwide. The association between the percentage use of different types of antihypertensive medications and mortality rates due to a SARS-CoV-2 infection during the first 3 weeks of the pandemic was analyzed using random effects linear regression models for 30 countries worldwide. Higher percentages of prescribed angiotensin receptor blockers (ARBs) (ß, 95% confidence interval [CI]; -0.02 [-0.04 to -0.0012]; p = .042) and calcium channel blockers (CCBs) (ß, 95% CI; -0.023 [-0.05 to -0.0028]; p = .0304) were associated with a lower first 3-week SARS-CoV-2-related death rate, whereas a higher percentage of prescribed angiotensin-converting enzyme inhibitors (ACEis) (ß, 95% CI; 0.03 [0.0061-0.05]; p = .0103) was associated with a higher first 3-week death rate, even when adjusted for age and metformin use. There was no association between the amount of prescribed beta-blockers (BBs) and diuretics (Diu) and the first 3-week death rate. When analyzing the combination of drugs that is used by at least 50% of antihypertensive users, within the different countries, countries with the lowest first 3-week death rates had at least an angiotensin receptor blocker as one of the most often prescribed antihypertensive medications (ARBs/CCBs: [ß, 95% CI; -0.02 [-0.03 to -0.004]; p = .009], ARBs/BBs: [ß, 95% CI; -0.03 [-0.05 to -0.006]; p = .01]). Finally, countries prescribing high-potency ARBs had lower first 3-week ARBs. In conclusion, ARBs and CCB seem to have a protective effect against death from SARS-CoV-2 infection.

Between-hospital variation in rates of complications and decline of patient performance after glioblastoma surgery in the dutch Quality Registry Neuro Surgery.

INTRODUCTION: For decisions on glioblastoma surgery, the risk of complications and decline in performance is decisive. In this study, we determine the rate of complications and performance decline after resections and biopsies in a national quality registry, their risk factors and the risk-standardized variation between institutions. METHODS: Data from all 3288 adults with first-time glioblastoma surgery at 13 hospitals were obtained from a prospective population-based Quality Registry Neuro Surgery in the Netherlands between 2013 and 2017. Patients were stratified by biopsies and resections. Complications were categorized as Clavien-Dindo grades II and higher. Performance decline was considered a deterioration of more than 10 Karnofsky points at 6 weeks. Risk factors were evaluated in multivariable logistic regression analysis. Patient-specific expected and observed complications and performance declines were summarized for institutions and analyzed in funnel plots. RESULTS: For 2271 resections, the overall complication rate was 20 % and 16 % declined in performance. For 1017 biopsies, the overall complication rate was 11 % and 30 % declined in performance. Patient-related characteristics were significant risk factors for complications and performance decline, i.e. higher age, lower baseline Karnofsky, higher ASA classification, and the surgical procedure. Hospital characteristics, i.e. case volume, university affiliation and biopsy percentage, were not. In three institutes the observed complication rate was significantly less than expected. In one institute significantly more performance declines were observed than expected, and in one institute significantly less. CONCLUSIONS: Patient characteristics, but not case volume, were risk factors for complications and performance decline after glioblastoma surgery. After risk-standardization, hospitals varied in complications and performance declines.

Development and external validation of prediction models to predict implantable cardioverter-defibrillator efficacy in primary prevention of sudden cardiac death.

AIMS: This study was performed to develop and externally validate prediction models for appropriate implantable cardioverter-defibrillator (ICD) shock and mortality to identify subgroups with insufficient benefit from ICD implantation. METHODS AND RESULTS: We recruited patients scheduled for primary prevention ICD implantation and reduced left ventricular function. Bootstrapping-based Cox proportional hazards and Fine and Gray competing risk models with likely candidate predictors were developed for all-cause mortality and appropriate ICD shock, respectively. Between 2014 and 2018, we included 1441 consecutive patients in the development and 1450 patients in the validation cohort. During a median follow-up of 2.4 (IQR 2.1-2.8) years, 109 (7.6%) patients received appropriate ICD shock and 193 (13.4%) died in the development cohort. During a median follow-up of 2.7 (IQR 2.0-3.4) years, 105 (7.2%) received appropriate ICD shock and 223 (15.4%) died in the validation cohort. Selected predictors of appropriate ICD shock were gender, NSVT, ACE/ARB use, atrial fibrillation history, Aldosterone-antagonist use, Digoxin use, eGFR, (N)OAC use, and peripheral vascular disease. Selected predictors of all-cause mortality were age, diuretic use, sodium, NT-pro-BNP, and ACE/ARB use. C-statistic was 0.61 and 0.60 at respectively internal and external validation for appropriate ICD shock and 0.74 at both internal and external validation for mortality. CONCLUSION: Although this cohort study was specifically designed to develop prediction models, risk stratification still remains challenging and no large group with insufficient benefit of ICD implantation was found. However, the prediction models have some clinical utility as we present several scenarios where ICD implantation might be postponed.

Long-term clinical outcomes of losartan in patients with Marfan syndrome: follow-up of the multicentre randomized controlled COMPARE trial.

AIMS: The COMPARE trial showed a small but significant beneficial effect of 3-year losartan treatment on aortic root dilatation rate in adults with Marfan syndrome (MFS). However, no significant effect was found on clinical endpoints, possibly due to a short follow-up period. The aim of the current study was therefore to investigate the long-term clinical outcomes after losartan treatment. METHODS AND RESULTS: In the original COMPARE study (inclusion 2008-2009), adult patients with MFS (n = 233) were randomly allocated to either the angiotensin-II receptor blocker losartan® on top of regular treatment (ß-blockers in 71% of the patients) or no additional medication. After the COMPARE trial period of 3 years, study subjects chose to continue their losartan medication or not. In a median follow-up period of 8 years, 75 patients continued losartan medication, whereas 78 patients, originally allocated to the control group, never used losartan after inclusion. No differences existed between baseline characteristics of the two groups except for age at inclusion [losartan 34 (interquartile range, IQR 26-43) years, control 41 (IQR 30-52) years; P = 0.031], and ß-blocker use (losartan 81%, control 64%; P = 0.022). A pathological FBN1 mutation was present in 76% of patients and 58% of the patients were male. Clinical endpoints, defined as all-cause mortality, aortic dissection/rupture, elective aortic root replacement, reoperation, and vascular graft implantation beyond the aortic root, were compared between the two groups. A per-patient composite endpoint was also analysed. Five deaths, 14 aortic dissections, 23 aortic root replacements, 3 reoperations, and 3 vascular graft implantations beyond the aortic root occurred during follow-up. Except for aortic root replacement, all endpoints occurred in patients with an operated aortic root. Patients who used losartan during the entire follow-up period showed a reduced number of events compared to the control group (death: 0 vs. 5, P = 0.014; aortic dissection: 3 vs. 11, P = 0.013; elective aortic root replacement: 10 vs. 13, P = 0.264; reoperation: 1 vs. 2, P = 0.463; vascular graft implantations beyond the aortic root 0 vs. 3, P = 0.071; and composite endpoint: 14 vs. 26, P = 0.019). These results remained similar when corrected for age and ß-blocker use in a multivariate analysis. CONCLUSION: These results suggest a clinical benefit of combined losartan and ß-blocker treatment in patients with MFS.

Associations between gut microbiota, faecal short-chain fatty acids, and blood pressure across ethnic groups: the HELIUS study.

AIMS: Preliminary evidence from animal and human studies shows that gut microbiota composition and levels of microbiota-derived metabolites, including short-chain fatty acids (SCFAs), are associated with blood pressure (BP). We hypothesized that faecal microbiota composition and derived metabolites may be differently associated with BP across ethnic groups. METHODS AND RESULTS: We included 4672 subjects (mean age 49.8 ± 11.7 years, 52% women) from six different ethnic groups participating in the HEalthy Life In an Urban Setting (HELIUS) study. The gut microbiota was profiled using 16S rRNA gene amplicon sequencing. Associations between microbiota composition and office BP were assessed using machine learning prediction models. In the subgroups with the largest associations, faecal SCFA levels were compared in 200 subjects with lower or higher systolic BP. Faecal microbiota composition explained 4.4% of the total systolic BP variance. Best predictors for systolic BP included Roseburia spp., Clostridium spp., Romboutsia spp., and Ruminococcaceae spp. Explained variance of the microbiota composition was highest in Dutch subjects (4.8%), but very low in South-Asian Surinamese, African Surinamese, Ghanaian, Moroccan and Turkish descent groups (explained variance <0.8%). Faecal SCFA levels, including acetate (P < 0.05) and propionate (P < 0.01), were lower in young Dutch participants with low systolic BP. CONCLUSIONS: Faecal microbiota composition is associated with BP, but with strongly divergent associations between ethnic groups. Intriguingly, while Dutch participants with lower BP had higher abundances of several SCFA-producing microbes, they had lower faecal SCFA levels. Intervention studies with SCFAs could provide more insight in the effects of these metabolites on BP.

Multiset sparse partial least squares path modeling for high dimensional omics data analysis.

BACKGROUND: Recent technological developments have enabled the measurement of a plethora of biomolecular data from various omics domains, and research is ongoing on statistical methods to leverage these omics data to better model and understand biological pathways and genetic architectures of complex phenotypes. Current reviews report that the simultaneous analysis of multiple (i.e. three or more) high dimensional omics data sources is still challenging and suitable statistical methods are unavailable. Often mentioned challenges are the lack of accounting for the hierarchical structure between omics domains and the difficulty of interpretation of genomewide results. This study is motivated to address these challenges. We propose multiset sparse Partial Least Squares path modeling (msPLS), a generalized penalized form of Partial Least Squares path modeling, for the simultaneous modeling of biological pathways across multiple omics domains. msPLS simultaneously models the effect of multiple molecular markers, from multiple omics domains, on the variation of multiple phenotypic variables, while accounting for the relationships between data sources, and provides sparse results. The sparsity in the model helps to provide interpretable results from analyses of hundreds of thousands of biomolecular variables. RESULTS: With simulation studies, we quantified the ability of msPLS to discover associated variables among high dimensional data sources. Furthermore, we analysed high dimensional omics datasets to explore biological pathways associated with Marfan syndrome and with Chronic Lymphocytic Leukaemia. Additionally, we compared the results of msPLS to the results of Multi-Omics Factor Analysis (MOFA), which is an alternative method to analyse this type of data. CONCLUSIONS: msPLS is an multiset multivariate method for the integrative analysis of multiple high dimensional omics data sources. It accounts for the relationship between multiple high dimensional data sources while it provides interpretable results through its sparse solutions. The biomarkers found by msPLS in the omics datasets can be interpreted in terms of biological pathways associated with the pathophysiology of Marfan syndrome and of Chronic Lymphocytic Leukaemia. Additionally, msPLS outperforms MOFA in terms of variation explained in the chronic lymphocytic leukaemia dataset while it identifies the two most important clinical markers for Chronic Lymphocytic Leukaemia AVAILABILITY: http://uva.csala.me/mspls.https://github.com/acsala/2018_msPLS.

Prophylactic Use of Implantable Cardioverter-Defibrillators in the Prevention of Sudden Cardiac Death in Dialysis Patients.

BACKGROUND: Patients with end-stage renal disease who are undergoing dialysis are reported to be at high risk of sudden cardiac death (SCD), and to date, no therapy has been shown to be effective in reducing this risk. The feasibility and value of prophylactic implantable cardioverter-defibrillator (ICD) implantation to prevent SCD is uncertain. METHODS: We conducted the ICD2 trial (Implantable Cardioverter-Defibrillator in Dialysis Patients), a prospective, randomized, controlled study investigating the value and safety of ICD implantation to prevent SCD in 200 patients on dialysis with a left ventricular ejection fraction ≥35%, after adequate screening and optimization of other treatments. The primary end point was SCD. Secondary end points were all-cause mortality and ICD-related complications. RESULTS: The trial was stopped as per the recommendation of the data and safety monitoring board for futility reasons after inclusion of 188 patients, 97 in the ICD group and 91 in the control group. The median duration of follow-up was 6.8 years (interquartile range, 3.8-8.8 years). SCD occurred in 19 of 188 cases (10.1%), 11 of 97 in the ICD group and 8 of 91 in the control group. The cumulative SCD incidence at 5 years was 9.7% (95% CI, 3.3%-16.2%) in the ICD group and 7.9% (95% CI, 1.7-14.0%) in the control group, resulting in a hazard ratio of 1.32 (95% CI, 0.53-3.29; P=0.55). Overall, 99 of 188 patients died (52.7%), 52 in the ICD group and 47 in the control group. Five-year survival probability was 50.6% (95% CI, 39.8%-61.5%) in the ICD group and 54.5% (95% CI, 43.0-66.0%) in the control group, resulting in a hazard ratio of 1.02 (95% CI, 0.69-1.52; P=0.92). Among 80 patients who received an ICD, 25 adverse events related to ICD implantation occurred. CONCLUSIONS: In a well-screened and well-treated population undergoing dialysis, prophylactic ICD therapy did not reduce the rate of SCD or all-cause mortality, which remained high. CLINICAL TRIAL REGISTRATION: URL: http://www.controlled-trials.com . Unique identifier: ISRCTN20479861.

Handling missing predictor values when validating and applying a prediction model to new patients.

Missing data present challenges for development and real-world application of clinical prediction models. While these challenges have received considerable attention in the development setting, there is only sparse research on the handling of missing data in applied settings. The main unique feature of handling missing data in these settings is that missing data methods have to be performed for a single new individual, precluding direct application of mainstay methods used during model development. Correspondingly, we propose that it is desirable to perform model validation using missing data methods that transfer to practice in single new patients. This article compares existing and new methods to account for missing data for a new individual in the context of prediction. These methods are based on (i) submodels based on observed data only, (ii) marginalization over the missing variables, or (iii) imputation based on fully conditional specification (also known as chained equations). They were compared in an internal validation setting to highlight the use of missing data methods that transfer to practice while validating a model. As a reference, they were compared to the use of multiple imputation by chained equations in a set of test patients, because this has been used in validation studies in the past. The methods were evaluated in a simulation study where performance was measured by means of optimism corrected C-statistic and mean squared prediction error. Furthermore, they were applied in data from a large Dutch cohort of prophylactic implantable cardioverter defibrillator patients.

Glycoproteomic Analysis of the Aortic Extracellular Matrix in Marfan Patients.

OBJECTIVE: Marfan syndrome (MFS) is caused by mutations in FBN1 (fibrillin-1), an extracellular matrix (ECM) component, which is modified post-translationally by glycosylation. This study aimed to characterize the glycoproteome of the aortic ECM from patients with MFS and relate it to aortopathy. Approach and Results: ECM extracts of aneurysmal ascending aortic tissue from patients with and without MFS were enriched for glycopeptides. Direct N-glycopeptide analysis by mass spectrometry identified 141 glycoforms from 47 glycosites within 35 glycoproteins in the human aortic ECM. Notably, MFAP4 (microfibril-associated glycoprotein 4) showed increased and more diverse N-glycosylation in patients with MFS compared with control patients. MFAP4 mRNA levels were markedly higher in MFS aortic tissue. MFAP4 protein levels were also increased at the predilection (convexity) site for ascending aorta aneurysm in bicuspid aortic valve patients, preceding aortic dilatation. In human aortic smooth muscle cells, MFAP4 mRNA expression was induced by TGF (transforming growth factor)-ß1 whereas siRNA knockdown of MFAP4 decreased FBN1 but increased elastin expression. These ECM changes were accompanied by differential gene expression and protein abundance of proteases from ADAMTS (a disintegrin and metalloproteinase with thrombospondin motifs) family and their proteoglycan substrates, respectively. Finally, high plasma MFAP4 concentrations in patients with MFS were associated with a lower thoracic descending aorta distensibility and greater incidence of type B aortic dissection during 68 months follow-up. CONCLUSIONS: Our glycoproteomics analysis revealed that MFAP4 glycosylation is enhanced, as well as its expression during the advanced, aneurysmal stages of MFS compared with control aneurysms from patients without MFS.