Efficient inference for genetic association studies with multiple outcomes

Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single clinical outcome on many genetic variants one by one, but there is an increasing demand for joint analysis of many molecular outcomes and genetic variants in order to unravel functional interactions. Unfortunately, most existing approaches to joint modelling are either too simplistic to be powerful or are impracticable for computational reasons. Inspired by Richardson et al. (2010, Bayesian Statistics 9), we consider a sparse multivariate regression model that allows simultaneous selection of predictors and associated responses. As Markov chain Monte Carlo (MCMC) inference on such models can be prohibitively slow when the number of genetic variants exceeds a few thousand, we propose a variational inference approach which produces posterior information very close to that of MCMC inference, at a much reduced computational cost. Extensive numerical experiments show that our approach outperforms popular variable selection methods and tailored Bayesian procedures, dealing within hours with problems involving hundreds of thousands of genetic variants and tens to hundreds of clinical or molecular outcomes

Variation in severity-adjusted resource use and outcome in intensive care units

Purpose Intensive care patients have increased risk of death and their care is expensive. We investigated whether risk-adjusted mortality and resources used to achieve survivors change over time and if their variation is associated with variables related to intensive care unit (ICU) organization and structure. Methods Data of 207,131 patients treated in 2008-2017 in 21 ICUs in Finland, Estonia and Switzerland were extracted from a benchmarking database. Resource use was measured using ICU length of stay, daily Therapeutic Intervention Scoring System Scores (TISS) and purchasing power parity-adjusted direct costs (2015-2017; 17 ICUs). The ratio of observed to severity-adjusted expected resource use (standardized resource use ratio; SRUR) was calculated. The number of expected survivors and the ratio of observed to expected mortality (standardized mortality ratio; SMR) was based on a mortality prediction model covering 2015-2017. Fourteen a priori variables reflecting structure and organization were used as explanatory variables for SRURs in multivariable models. Results SMR decreased over time, whereas SRUR remained unchanged, except for decreased TISS-based SRUR. Direct costs of one ICU day, TISS score and ICU admission varied between ICUs 2.5-5-fold. Differences between individual ICUs in both SRUR and SMR were up to > 3-fold, and their evolution was highly variable, without clear association between SRUR and SMR. High patient turnover was consistently associated with low SRUR but not with SMR. Conclusion The wide and independent variation in both SMR and SRUR suggests that they should be used together to compare the performance of different ICUs or an individual ICU over time.Peer reviewe

Blood Omega-3 Fatty Acids Are Inversely Associated With Albumin-Creatinine Ratio in Young and Healthy Adults (The Omega-Kid Study).

Background: Omega-3 fatty acids are associated with a lower risk of cardiovascular disease (CVD) and with beneficial effects on CV risk factors. The albumin-creatinine ratio (ACR) is a risk factor for CVD, all-cause mortality and accelerated glomerular filtration rate (GFR) decline in the general population. We aimed to investigate the association between n-3 PUFAS and ACR in heathy individuals with preserved GFR. Design and Methods: The present cross-sectional analysis is part of the GAPP study, a population-based cohort of healthy adults aged 25-41 years. Individuals with known CVD, diabetes, or a BMI >35 kg/m2 were excluded. eGFR was calculated according to the combined Creatinine/Cystatin C CKD-EPI formula. ACR was obtained from a fasting morning urine sample. The Omega-3 Index (relative amount of EPA and DHA of total fatty acids in %) was obtained from whole blood aliquots. Results: Overall, 2001 participants (median age 37 years IQR 31; 40, 53% female) were included in this analysis. Median Omega-3 Index was 4.59 (IQR 4.06; 5.25) and median eGFR 111 ml/min/1.73 m2 (IQR 103; 118). Median ACR was 0.14 mg/mmol (IQR 0; 0.43). We found a significant inverse association of the Omega-3 Index with ACR (ratio 0.84, 95%CI 0.73-0.96; p = 0.011) which remained after comprehensive adjustment (ratio 0.86, 95%CI 0.74-1.00; p = 0.048). No association of the Omega-3 Index with eGFR was found. The adjusted difference in eGFR per 1-unit increase in Omega3-Index was -0.21 (95%CI -0.76; 0.35; p = 0.47). Conclusions: A higher Omega-3 Index was significantly associated with lower ACR in this young and healthy population with preserved eGFR. Omega-3 fatty acids may exhibit cardio- and nephroprotective effects in healthy individuals through modulation of ACR

Efficacy of standard and low dose hydrochlorothiazide in the recurrence prevention of calcium nephrolithiasis (NOSTONE trial): protocol for a randomized double-blind placebo-controlled trial

Background: Nephrolithiasis is a global healthcare problem with a current lifetime risk of 18.8% in men and 9.4% in women. Given the high cost of medical treatments and surgical interventions as well as the morbidity related to symptomatic stone disease, medical prophylaxis for stone recurrence is an attractive approach. Thiazide diuretics have been the cornerstone of pharmacologic metaphylaxis for more than 40 years. However, evidence for benefits and harms of thiazides in the prevention of calcium containing kidney stones in general remains unclear. In addition, the efficacy of the currently employed low dose thiazide regimens to prevent stone recurrence is not known. Methods: The NOSTONE trial is an investigator-initiated 3-year prospective, multicenter, double-blind, placebo-controlled trial to assess the efficacy of standard and low dose hydrochlorothiazide treatment in the recurrence prevention of calcium containing kidney stones. We plan to include 416 adult (≥ 18 years) patients with recurrent (≥ 2 stone episodes in the last 10 years) calcium containing kidney stones (containing ≥50% of calcium oxalate, calcium phosphate or a mixture of both). Patients will be randomly allocated to 50 mg or 25 mg or 12.5 mg hydrochlorothiazide or placebo. The primary outcome will be incidence of stone recurrence (a composite of symptomatic or radiologic recurrence). Secondary outcomes will be individual components of the composite primary outcome, safety and tolerability of hydrochlorothiazide treatment, changes in urinary biochemistry elicited by hydrochlorothiazide treatment and impact of baseline disease severity, biochemical abnormalities and stone composition on treatment response. Discussion: The NOSTONE study will provide long-sought information on the efficacy of hydrochlorothiazide in the recurrence prevention of calcium containing kidney stones. Strengths of the study include the randomized, double-blind and placebo-controlled design, the large amount of patients studied, the employment of high sensitivity and high specificity imaging and the exclusive public funding support. Trial registration: ClinicalTrials.gov, NCT03057431. Registered on February 20 2017

Accuracy of pancreatic stone protein for the diagnosis of infection in hospitalized adults: a systematic review and individual patient level meta-analysis

Background Accurate biomarkers to diagnose infection are lacking. Studies reported good performance of pancreatic stone protein (PSP) to detect infection. The objective of the study was to determine the performance of PSP in diagnosing infection across hospitalized patients and calculate a threshold value for that purpose. Methods A systematic search across Cochrane Central Register of Controlled Trials and MEDLINE databases (1966–March 2019) for studies on PSP published in English using ‘pancreatic stone protein’, ‘PSP’, ‘regenerative protein’, ‘lithostatin’ combined with ‘infection’ and ‘sepsis’ found 44 records. The search was restricted to the five trials that evaluated PSP for the initial detection of infection in hospitalized adults. Individual patient data were obtained from the investigators of all eligible trials. Data quality and validity was assessed according to PRISMA guidelines. We choose a fixed-effect model to calculate the PSP cut-off value that best discriminates infected from non-infected patients. Results Infection was confirmed in 371 of 631 patients. The median (IQR) PSP value of infected versus uninfected patients was 81.5 (30.0–237.5) versus 19.2 (12.6–33.57) ng/ml, compared to 150 (82.70–229.55) versus 58.25 (15.85–120) mg/l for C-reactive protein (CRP) and 0.9 (0.29–4.4) versus 0.15 (0.08–0.5) ng/ml for procalcitonin (PCT). Using a PSP cut-off of 44.18 ng/ml, the ROC AUC to detect infection was 0.81 (0.78–0.85) with a sensitivity of 0.66 (0.61–0.71), specificity of 0.83 (0.78–0.88), PPV of 0.85 (0.81–0.89) and NPV of 0.63 (0.58–0.68). When a model combining PSP and CRP was used, the ROC AUC improved to 0.90 (0.87–0.92) with higher sensitivity 0.81 (0.77–0.85) and specificity 0.84 (0.79–0.90) for discriminating infection from non-infection. Adding PCT did not improve the performance further. Conclusions PSP is a promising biomarker to diagnose infections in hospitalized patients. Using a cut-off value of 44.18 ng/ml, PSP performs better than CRP or PCT across the considered studies. The combination of PSP with CRP further enhances its accuracy

Generalized linear latent variable models with flexible distributions

We consider first a semi-nonparametric specification for the density of latent variables in Generalized Linear Latent Variable Models (GLLVM). This specification is flexible enough to allow for an asymmetric, multi-modal, heavy or light tailed smooth density. The degree of flexibility required by many applications can be achieved through this semi-nonparametric specification with a finite number of parameters. Even with this additional flexibility, we obtain an explicit expression of the likelihood for conditionally normal manifest variables. We show that the estimated density of latent variables capture the true one with good accuracy. In the second part we consider a spatial generalized linear latent variable model with and without assumption of normality on latent variables. The Laplace approximation is applicable when latent variables are multivariate normal. Otherwise the assumption of marginal normality is relaxed in favor of a mixture of normals. The pairwise likelihood estimators are explored by simulations

A Non-Gaussian Spatial Generalized Linear Latent Variable Model

We consider a spatial generalized linear latent variable model with and without nor- mality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simu- lations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents