Integrating functional genomics data using maximum likelihood based simultaneous component analysis

<p>Abstract</p> <p>Background</p> <p>In contemporary biology, complex biological processes are increasingly studied by collecting and analyzing measurements of the same entities that are collected with different analytical platforms. Such data comprise a number of data blocks that are coupled via a common mode. The goal of collecting this type of data is to discover biological mechanisms that underlie the behavior of the variables in the different data blocks. The simultaneous component analysis (SCA) family of data analysis methods is suited for this task. However, a SCA may be hampered by the data blocks being subjected to different amounts of measurement error, or noise. To unveil the true mechanisms underlying the data, it could be fruitful to take noise heterogeneity into consideration in the data analysis. Maximum likelihood based SCA (MxLSCA-P) was developed for this purpose. In a previous simulation study it outperformed normal SCA-P. This previous study, however, did not mimic in many respects typical functional genomics data sets, such as, data blocks coupled via the experimental mode, more variables than experimental units, and medium to high correlations between variables. Here, we present a new simulation study in which the usefulness of MxLSCA-P compared to ordinary SCA-P is evaluated within a typical functional genomics setting. Subsequently, the performance of the two methods is evaluated by analysis of a real life <it>Escherichia coli </it>metabolomics data set.</p> <p>Results</p> <p>In the simulation study, MxLSCA-P outperforms SCA-P in terms of recovery of the true underlying scores of the common mode and of the true values underlying the data entries. MxLSCA-P further performed especially better when the simulated data blocks were subject to different noise levels. In the analysis of an <it>E. coli </it>metabolomics data set, MxLSCA-P provided a slightly better and more consistent interpretation.</p> <p>Conclusion</p> <p>MxLSCA-P is a promising addition to the SCA family. The analysis of coupled functional genomics data blocks could benefit from its ability to take different noise levels per data block into consideration and improve the recovery of the true patterns underlying the data. Moreover, the maximum likelihood based approach underlying MxLSCA-P could be extended to custom-made solutions to specific problems encountered.</p

Randomized, double-blind, placebo-controlled, multicentre pilot study on the effects of empagliflozin on clinical outcomes in patients with acute decompensated heart failure (EMPA-RESPONSE-AHF)

Aims: Inhibition of sodium–glucose co-transporter 2 (SGLT2) reduces the risk of death and heart failure (HF) admissions in patients with chronic HF. However, safety and clinical efficacy of SGLT2 inhibitors in patients with acute decompensated HF are unknown. Methods and results: In this randomized, placebo-controlled, double-blind, parallel group, multicentre pilot study, we randomized 80 acute HF patients with and without diabetes to either empagliflozin 10 mg/day or placebo for 30 days. The primary outcomes were change in visual analogue scale (VAS) dyspnoea score, diuretic response (weight change per 40 mg furosemide), change in N-terminal pro brain natriuretic peptide (NT-proBNP), and length of stay. Secondary outcomes included safety and clinical endpoints. Mean age was 76 years, 33% were female, 47% had de novo HF and median NT-proBNP was 5236 pg/mL. No difference was observed in VAS dyspnoea score, diuretic response, length of stay, or change in NT-proBNP between empagliflozin and placebo. Empagliflozin reduced a combined endpoint of in-hospital worsening HF, rehospitalization for HF or death at 60 days compared with placebo [4 (10%) vs. 13 (33%); P = 0.014]. Urinary output up until day 4 was significantly greater with empagliflozin vs. placebo [difference 3449 (95% confidence interval 578–6321) mL; P < 0.01]. Empagliflozin was safe, well tolerated, and had no adverse effects on blood pressure or renal function. Conclusions: In patients with acute HF, treatment with empagliflozin had no effect on change in VAS dyspnoea, diuretic response, NT-proBNP, and length of hospital stay, but was safe, increased urinary output and reduced a combined endpoint of worsening HF, rehospitalization for HF or death at 60 days

Serial cardiac biomarkers, pulmonary artery pressures and traditional parameters of fluid status in relation to prognosis in patients with chronic heart failure:Design and rationale of the BioMEMS study

AimsHeart failure (HF), a global pandemic affecting millions of individuals, calls for adequate predictive guidance for improved therapy. Congestion, a key factor in HF-related hospitalizations, further underscores the need for timely interventions. Proactive monitoring of intracardiac pressures, guided by pulmonary artery (PA) pressure, offers opportunities for efficient early-stage intervention, since haemodynamic congestion precedes clinical symptoms.MethodsThe BioMEMS study, a substudy of the MONITOR-HF trial, proposes a multifaceted approach integrating blood biobank data with traditional and novel HF parameters. Two additional blood samples from 340 active participants in the MONITOR-HF trial were collected at baseline, 3-, 6-, and 12-month visits and stored for the BioMEMS biobank. The main aims are to identify the relationship between temporal biomarker patterns and PA pressures derived from the CardioMEMS-HF system, and to identify the biomarker profile(s) associated with the risk of HF events and cardiovascular death.ConclusionSince the prognostic value of single baseline measurements of biomarkers like N-terminal pro-B-type natriuretic peptide is limited, with the BioMEMS study we advocate a dynamic, serial approach to better capture HF progression. We will substantiate this by relating repeated biomarker measurements to PA pressures. This design rationale presents a comprehensive review on cardiac biomarkers in HF, and aims to contribute valuable insights into personalized HF therapy and patient risk assessment, advancing our ability to address the evolving nature of HF effectively.Design and rationale of the BioMEMS study. QoL, quality of life. Graphical abstract is created with BioRender.com imag

A randomised comparison of the effect of haemodynamic monitoring with CardioMEMS in addition to standard care on quality of life and hospitalisations in patients with chronic heart failure: Design and rationale of the MONITOR HF multicentre randomised clinical trial

Background: Assessing haemodynamic congestion based on filling pressures instead of clinical congestion can be a way to further improve quality of life (QoL) and clinical outcome by intervening before symptoms or weight gain occur in heart failure (HF) patients. The clinical efficacy of remote monitoring of pulmonary artery (PA) pressures (CardioMEMS; Abbott Inc., Atlanta, GA, USA) has been demonstrated in the USA. Currently, the PA sensor is not reimbursed in the European Union as its benefit when applied in addition to standard HF care is unknown in Western European countries, including the Netherlands. Aims: To demonstrate the efficacy and cost-effectiveness of haemodynamic PA monitoring in addition to contemporary standard HF care in a high-quality Western European health care system. Methods: The current study is a prospective, multi-centre, randomised clinical trial in 340 patients with chronic HF (New York Heart Association functional class III) randomised to HF care including remote monitoring with the CardioMEMS PA sensor or standard HF care alone. Eligible patients have at least one hospitalisation for HF in 12 months before enrolment and will be randomised in a 1:1 ratio. Minimum follow-up will be 1 year. The primary endpoint is the change in QoL as measured by the Kansas City Cardiomyopathy Questionnaire (KCCQ). Secondary endpoints are the number of HF hospital admissions and changes in health status assessed by EQ-5D-5L questionnaire including healt

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure &lt; 100 mmHg (n = 1127), estimated glomerular filtration rate &lt; 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

Left ventricular and renal dysfunction: an exploration of the cardiorenal axis

Both left ventricular dysfunction, and renal dysfunction are world wide public health problems. In the western countries there is a rising incidence and prevalence of both conditions, with poor outcomes and high cost. These two conditions do often co-exist and the concomitant presence of both conditions accumulates risk for morbidity and mortality. In severe chronic heart failure (CHF), impaired renal function is often present, and is even a stronger risk marker than functional cardiac parameters, such as left ventricular ejection fraction or NYHA class.1 On the other hand, left ventricular dysfunction is likely to develop in patients with chronic renal dysfunction (CRD) and accumulates with worsening renal function.2 One of the first signs of left ventricular dysfunction in patients with CRD is left ventricular hypertrophy (LVH). Several studies have demonstrated an association between renal dysfunction and LVH and the prevalence of LVH increases with worsening of renal function.3 Finally, several prevalence and longitudinal studies have shown that the well known age associated decline in renal function is more pronounced in patients with coexisting cardiovascular risk factors and pre-existing atherosclerotic vascular disease, suggesting that this decline is not a consistent phenomenon and reflect cardiovascular co-morbidity rather than normal aging

Prognostic importance of renal function in patients with early heart failure and mild left ventricular dysfunction

We evaluated the prognostic value of renal function in an initially “untreated” population with mild heart failure and compared the prognosis of this population with a matched controlled population. During a follow-up of 13 years (mean 11.7), 90 patients (56%) died. Mortality was higher compared with a matched controlled population. Multivariate Cox regression analysis demonstrated that beside the well-established risk markers of left ventricular ejection fraction and heart rate, renal function (estimated glomerular filtration rate, hazard ratio 1.16/10 ml/min/1.73 m2, p = 0.003) was the only additional independent predictor of cardiovascular mortality in patients with early heart failure. The aims of the present study were to evaluate whether renal function is an independent risk marker for cardiovascular mortality in patients with mild heart failure, and to establish the long-term prognosis of this population. Patients included in this analysis participated in the Dutch Ibopamine Multicenter Trial (DIMT), a multicenter heart failure study, as previously described.1 In summary, the study was a double-blind 6-month comparison of ibopamine, digoxin, and placebo in patients with mild heart failure (HF). Patients ranged in age from 18 to 75 years and were clinically stable for ≥2 weeks. Chronic heart failure was characterized by clinical signs and symptoms, and a radionuclide left ventricular (LV) ejection fraction <0.45 was obtained within the previous 2 months. Other inclusion and exclusion criteria were described in detail in the original publication.1 The population generally consisted of patients in New York Heart Association functional class II HF, and their mean LV ejection fraction was 0.29. Baseline data, including plasma neurohormones, were collected while these patients received only diuretics for their HF, because the clinical trials showing benefit of angiotensin-converting enzyme inhibitors and β-blockers in mild HF had not yet been published at that time (1988 to 1989). Estimated glomerular filtration rate (GFRc), using the Cockcroft-Gault equation ([140 − age in years] × [body weight in kg]/[72 × serum creatinine in milligrams per deciliter], in women multiplied by 0.85) was used as an indicator for renal function. Patient enrollment began in July 1989 and the last patient attended the last visit in October 1991. A total of 161 patients fulfilled all entry criteria. Follow-up was extended to a maximum of 13 years, which took place in 2002. Patients' physicians were contacted by telephone and were asked whether the patient was still alive. If the patient had died, cause of death was asked. Deaths were classified by their physicians, not centrally adjudicated, as cardiovascular death, sudden cardiac death, as defined previously,2 or noncardiac death. During follow-up, physicians were allowed to prescribe standard medication for HF, including angiotensin-converting enzyme inhibitors and β blockers. Data regarding use of medication were fully recovered until 1997. Statistics Netherlands provided data of the total mortality rate and cause of death of the Dutch population from 1990 to 2002. The data used from this control group were matched to age and gender with the DIMT population. We calculated person–years for each subject, commencing on the first day of inclusion and ending on the date of the last known vital status, emigration, or death. Expected numbers of deaths of the DIMT population were calculated on the basis of age- and gender-specific Dutch population mortality rates recorded by Statistics Netherlands. Data from 1990 to 2002 were applied. Data regarding the variables are presented as mean ± SD, unless indicated otherwise. For comparison of baseline data, Student's t test, Wilcoxon rank-sum-test (for non-normally distributed measures), and Fisher's exact test (for categorical measures) were used. To identify prognostic covariates that might have “explained” a difference in survival time, we estimated survival curves by the method described by Kaplan and Meier3 from the following variables: age, gender, LV ejection fraction, New York Heart Association functional class, heart rate, systolic blood pressure, GFRc, urea, hemoglobin, plasma norepinephrine, renin and aldosterone, use of diuretics, total exercise time, rhythm, HF etiology, and diabetes mellitus. Differences in survival times between groups were calculated using the log-rank test. All variables with a significance level of p <0.10 were introduced into a multivariate model as proposed by Cox.4 We checked the assumption of proportional hazards for each predictor variable by estimating the plots of the logarithm of the cumulative hazard. The end-multivariate model was constructed using a backward Wald analysis. The effect of ibopamine and digoxin on survival and other baseline characteristics that were prognostically relevant were also used in this analysis. Interaction terms were used to examine effect modification. For the statistical analysis, SPSS version 11.0 ( SPSS Inc., Chicago, Illinois) was used. Mean follow-up of our study population was 11.7 years (range 2.5 to 13.0). Follow-up was complete in 100% of the patients. At the end of follow-up, 90 patients (56%) had died. The major cause of death was cardiovascular (80%). Sudden cardiac death occurred in 51% of the deaths, progression of HF in 17%, stroke or rupture of abdominal aorta aneurysm occurred in 5%, and other cardiac causes in 7%. Of all noncardiovascular deaths (20%), (lung) cancer and pneumonia were the most common. Sudden cardiac death was equally high in both causes of HF (52% coronary artery disease vs 48% idiopathic dilated cardiomyopathy, p = NS). The baseline characteristics of the total population are listed in Table 1. The survivors were younger (p = 0.009), had a lower heart rate (p = 0.021), lower plasma norepinephrine levels (p = 0.043), and a higher LV ejection fraction (p = 0.005), GFRc (p = 0.021), and total exercise time (p = 0.015)