Generalizability of polygenic prediction models: how is the R2 defined on test data?

BACKGROUND: Polygenic risk scores (PRS) quantify an individual's genetic predisposition for different traits and are expected to play an increasingly important role in personalized medicine. A crucial challenge in clinical practice is the generalizability and transferability of PRS models to populations with different ancestries. When assessing the generalizability of PRS models for continuous traits, the R 2 is a commonly used measure to evaluate prediction accuracy. While the R 2 is a well-defined goodness-of-fit measure for statistical linear models, there exist different definitions for its application on test data, which complicates interpretation and comparison of results. METHODS: Based on large-scale genotype data from the UK Biobank, we compare three definitions of the R 2 on test data for evaluating the generalizability of PRS models to different populations. Polygenic models for several phenotypes, including height, BMI and lipoprotein A, are derived based on training data with European ancestry using state-of-the-art regression methods and are evaluated on various test populations with different ancestries. RESULTS: Our analysis shows that the choice of the R 2  definition can lead to considerably different results on test data, making the comparison of R 2  values from the literature problematic. While the definition as the squared correlation between predicted and observed phenotypes solely addresses the discriminative performance and always yields values between 0 and 1, definitions of the R 2 based on the mean squared prediction error (MSPE) with reference to intercept-only models assess both discrimination and calibration. These MSPE-based definitions can yield negative values indicating miscalibrated predictions for out-of-target populations. We argue that the choice of the most appropriate definition depends on the aim of PRS analysis - whether it primarily serves for risk stratification or also for individual phenotype prediction. Moreover, both correlation-based and MSPE-based definitions of R 2 can provide valuable complementary information. CONCLUSIONS: Awareness of the different definitions of the R 2 on test data is necessary to facilitate the reporting and interpretation of results on PRS generalizability. It is recommended to explicitly state which definition was used when reporting R 2 values on test data. Further research is warranted to develop and evaluate well-calibrated polygenic models for diverse populations.

A community effort in SARS-CoV-2 drug discovery.

The COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the "Billion molecules against COVID-19 challenge", to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors. Participating teams used a wide variety of computational methods to screen a minimum of 1 billion virtual molecules against 6 protein targets. Overall, 31 teams participated, and they suggested a total of 639,024 molecules, which were subsequently ranked to find 'consensus compounds'. The organizing team coordinated with various contract research organizations (CROs) and collaborating institutions to synthesize and test 878 compounds for biological activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (only the Nsp12 domain), and (alpha) spike protein S. Overall, 27 compounds with weak inhibition/binding were experimentally identified by binding-, cleavage-, and/or viral suppression assays and are presented here. Open science approaches such as the one presented here contribute to the knowledge base of future drug discovery efforts in finding better SARS-CoV-2 treatments.

Recent Methodological Trends in Epidemiology: No Need for Data-Driven Variable Selection?

Variable selection in regression models is a particularly important issue in epidemiology, where one usually encounters observational studies. In contrast to randomized trials or experiments, confounding is often not controlled by the study design, but has to be accounted for by suitable statistical methods. For instance, when risk factors should be identified with unconfounded effect estimates, multivariable regression techniques can help to adjust for confounders. We investigated the current practice of variable selection in 4 major epidemiologic journals in 2019 and found that the majority of articles used subject-matter knowledge to determine a priori the set of included variables. In comparison with previous reviews from 2008 and 2015, fewer articles applied data-driven variable selection. Furthermore, for most articles the main aim of analysis was hypothesis-driven effect estimation in rather low-dimensional data situations (i.e., large sample size compared with the number of variables). Based on our results, we discuss the role of data-driven variable selection in epidemiology.

The benefit of knowledge: postural response modulation by foreknowledge of equilibrium perturbation in an upper limb task.

For whole-body sway patterns, a compound motor response following an external stimulus may comprise reflexes, postural adjustments (anticipatory or compensatory), and voluntary muscular activity. Responses to equilibrium destabilization may depend on both motor set and a subject`s expectation of the disturbing stimulus. To disentangle these influences on lower limb responses, we studied a model in which subjects (n = 14) were suspended in the air, without foot support, and performed a fast unilateral wrist extension (WE) in response to a passive knee flexion (KF) delivered by a robot. To characterize the responses, electromyographic activity of rectus femoris and reactive leg torque was obtained bilaterally in a series of trials, with or without the requirement of WE (motor set), and/or beforehand information about the upcoming velocity of KF (subject`s expectation). Some fast-velocity trials resulted in StartReact responses, which were used to subclassify leg responses. When subjects were uninformed about the upcoming KF, large rectus femoris responses concurred with a postural reaction in conditions without motor task, and with both postural reaction and postural adjustment when WE was required. WE in response to a low-volume acoustic signal elicited no postural adjustments. When subjects were informed about KF velocity and had to perform WE, large rectus femoris responses corresponded to anticipatory postural adjustment rather than postural reaction. In conclusion, when subjects are suspended in the air and have to respond with WE, the prepared motor set includes anticipatory postural adjustments if KF velocity is known, and additional postural reactions if KF velocity is unknown.

Online Compassion Focused Therapy for overeating: Feasibility and acceptability pilot study.

OBJECTIVE: This pilot study aims to investigate the feasibility, acceptability, and potential effectiveness of online Compassion Focused Therapy for overeating (CFT-OE). METHOD: Eighteen Portuguese women seeking treatment for overeating were enrolled in this study, and 15 participants completed the CFT-OE. This was a single-arm study. Participants were assessed at pre- and post-intervention and 3-month follow-up. All participants completed measures assessing binge eating, cognitive restraint, uncontrolled eating, emotional eating, general eating psychopathology, general and body shame, self-criticism, self-compassion, and fears of self-compassion. RESULTS: The treatment attrition rate was 16.7%, which is relatively low compared to other similar online interventions. Participants gave positive feedback on the program and indicated they would recommend it to people with similar difficulties. CFT-OE improved self-compassion and reduced eating psychopathology symptoms, general and body shame, self-criticism, and fears of self-compassion. Clinical significance analysis showed that the majority of participants were classified as in recovery in all measures at post-intervention and 3-month follow-up. DISCUSSION: Preliminary results suggest that the online CFT-OE program is an acceptable and feasible intervention. Results also suggest that CFT-OE is beneficial for the treatment of women with difficulties with overeating. A future randomized controlled trial is necessary to establish the effectiveness of the CFT-OE. PUBLIC SIGNIFICANCE: This study indicates that online CFT-OE is a feasible and adequate intervention for women who struggle with overeating. This therapy showed promising results in reducing eating disorder symptoms, shame, and self-criticism and improving self-compassion. As an online intervention, CFT-OE may be more accessible and offer an alternative to in-person therapy.

MTHFR C677T and A1298C polymorphism's effect on risk of colorectal cancer in Lynch syndrome.

Lynch syndrome (LS) is characterised by an increased risk of developing colorectal cancer (CRC) and other extracolonic epithelial cancers. It is caused by pathogenic germline variants in DNA mismatch repair (MMR) genes or the EPCAM gene, leading to a less functional DNA MMR system. Individuals diagnosed with LS (LS individuals) have a 10-80% lifetime risk of developing cancer. However, there is considerable variability in the age of cancer onset, which cannot be attributed to the specific MMR gene or variant alone. It is speculated that multiple genetic and environmental factors contribute to this variability, including two single nucleotide polymorphisms (SNPs) in the methylenetetrahydrofolate reductase (MTHFR) gene: C677T (rs1801133) and A1298C (rs1801131). By decreasing MTHFR activity, these SNPs theoretically reduce the silencing of DNA repair genes and increase the availability of nucleotides for DNA synthesis and repair, thereby protecting against early-onset cancer in LS. We investigated the effect of these SNPs on LS disease expression in 2,723 LS individuals from Australia, Poland, Germany, Norway and Spain. The association between age at cancer onset and SNP genotype (risk of cancer) was estimated using Cox regression adjusted for gender, country and affected MMR gene. For A1298C (rs1801131), both the AC and CC genotypes were significantly associated with a reduced risk of developing CRC compared to the AA genotype, but no association was seen for C677T (rs1801133). However, an aggregated effect of protective alleles was seen when combining the alleles from the two SNPs, especially for LS individuals carrying 1 and 2 alleles. For individuals with germline pathogenic variants in MLH1, the CC genotype of A1298C was estimated to reduce the risk of CRC significantly by 39% (HR = 0.61, 95% CI 0.42, 0.89, p = 0.011), while for individuals with pathogenic germline MSH2 variants, the AC genotype (compared to AA) was estimated to reduce the risk of CRC by 26% (HR = 0.66, 95% CI 0.53, 0.83, p = 0.01). In comparison, no association was observed for C677T (rs1801133). In conclusion, our study suggests that combining the MMR gene information with the MTHFR genotype, including the aggregated effect of protective alleles, could be useful in developing an algorithm that estimates the risk of CRC in LS individuals.

Incidence, risk factors and outcome of acute kidney injury in critically ill COVID-19 patients in Tyrol, Austria: a prospective multicenter registry study.

INTRODUCTION: Acute kidney injury is a frequent complication in critically ill patients with and without COVID-19. The aim of this study was to evaluate the incidence of, and risk factors for, acute kidney injury and its effect on clinical outcomes of critically ill COVID-19 patients in Tyrol, Austria. METHODS: This multicenter prospective registry study included adult patients with a SARS-CoV-2 infection confirmed by polymerase chain reaction, who were treated in one of the 12 dedicated intensive care units during the COVID-19 pandemic from February 2020 until May 2022. RESULTS: In total, 1042 patients were included during the study period. The median age of the overall cohort was 66 years. Of the included patients, 267 (26%) developed acute kidney injury during their intensive care unit stay. In total, 12.3% (n = 126) required renal replacement therapy with a median duration of 9 (IQR 3-18) days. In patients with acute kidney injury the rate of invasive mechanical ventilation was significantly higher with 85% (n = 227) compared to 41% (n = 312) in the no acute kidney injury group (p < 0.001). The most important risk factors for acute kidney injury were invasive mechanical ventilation (OR = 4.19, p < 0.001), vasopressor use (OR = 3.17, p < 0.001) and chronic kidney disease (OR = 2.30, p < 0.001) in a multivariable logistic regression analysis. Hospital and intensive care unit mortality were significantly higher in patients with acute kidney injury compared to patients without acute kidney injury (Hospital mortality: 52.1% vs. 17.2%, p < 0.001, ICU-mortality: 47.2% vs. 14.7%, p < 0.001). CONCLUSION: As in non-COVID-19 patients, acute kidney injury is clearly associated with increased mortality in critically ill COVID-19 patients. Among known risk factors, invasive mechanical ventilation has been identified as an independent and strong predictor of acute kidney injury.

Gene-based burden scores identify rare variant associations for 28 blood biomarkers.

BACKGROUND: A relevant part of the genetic architecture of complex traits is still unknown; despite the discovery of many disease-associated common variants. Polygenic risk score (PRS) models are based on the evaluation of the additive effects attributable to common variants and have been successfully implemented to assess the genetic susceptibility for many phenotypes. In contrast, burden tests are often used to identify an enrichment of rare deleterious variants in specific genes. Both kinds of genetic contributions are typically analyzed independently. Many studies suggest that complex phenotypes are influenced by both low effect common variants and high effect rare deleterious variants. The aim of this paper is to integrate the effect of both common and rare functional variants for a more comprehensive genetic risk modeling. METHODS: We developed a framework combining gene-based scores based on the enrichment of rare functionally relevant variants with genome-wide PRS based on common variants for association analysis and prediction models. We applied our framework on UK Biobank dataset with genotyping and exome data and considered 28 blood biomarkers levels as target phenotypes. For each biomarker, an association analysis was performed on full cohort using gene-based scores (GBS). The cohort was then split into 3 subsets for PRS construction and feature selection, predictive model training, and independent evaluation, respectively. Prediction models were generated including either PRS, GBS or both (combined). RESULTS: Association analyses of the cohort were able to detect significant genes that were previously known to be associated with different biomarkers. Interestingly, the analyses also revealed heterogeneous effect sizes and directionality highlighting the complexity of the blood biomarkers regulation. However, the combined models for many biomarkers show little or no improvement in prediction accuracy compared to the PRS models. CONCLUSION: This study shows that rare variants play an important role in the genetic architecture of complex multifactorial traits such as blood biomarkers. However, while rare deleterious variants play a strong role at an individual level, our results indicate that classical common variant based PRS might be more informative to predict the genetic susceptibility at the population level.

Lung Ultrasound in Predicting Outcomes in Patients with COVID-19 Treated with Extracorporeal Membrane Oxygenation.

Pulmonary involvement due to SARS-CoV-2 infection can lead to acute respiratory distress syndrome in patients with COVID-19. Consequently, pulmonary imaging is crucial for management of COVID-19. This study aimed to evaluate the prognostic value of lung ultrasound (LUS) with a handheld ultrasound device (HHUD) in patients with COVID-19 treated with extracorporeal membrane oxygenation (ECMO). Therefore, patients underwent LUS with a HHUD every two days until they were either discharged from the intensive care unit or died. The study was conducted at the University Hospital of Bonn's anesthesiological intensive care ward from December 2020 to August 2021. A total of 33 patients (median [IQR]: 56.0 [53-60.5] years) were included. A high LUS score was associated with a decreased P/F ratio (repeated measures correlation [rmcorr]: -0.26; 95% CI: -0.34, -0.15; p < 0.001), increased extravascular lung water, defined as fluid accumulation in the pulmonary interstitium and alveoli (rmcorr: 0.11; 95% CI: 0.01, 0.20; p = 0.030), deteriorated electrolyte status (base excess: rmcorr: 0.14; 95% CI: 0.05, 0.24; p = 0.004; pH: rmcorr: 0.12; 95% CI: 0.03, 0.21; p = 0.001), and decreased pulmonary compliance (rmcorr: -0.10; 95% CI: -0.20, -0.01; p = 0.034). The maximum LUS score was lower in survivors (median difference [md]: -0.35; 95% CI: -0.55, -0.06; p = 0.006). A cutoff value for non-survival was calculated at a LUS score of 2.63. At the time of maximum LUS score, P/F ratio (md: 1.97; 95% CI: 1.12, 2.76; p < 0.001) and pulmonary compliance (md: 18.67; 95% CI: 3.33, 37.15; p = 0.018) were higher in surviving patients. In conclusion, LUS with a HHUD enables continuous evaluation of cardiopulmonary function in COVID-19 patients receiving ECMO support therapy and provides prognostic value in determining the patients' likelihood of survival.

Cerebroplacental versus Umbilicocerebral Ratio-Analyzing the Predictive Value Regarding Adverse Perinatal Outcomes in Low- and High-Risk Fetuses at Term.

Background and Objectives: The aim of this study was to investigate the prediction of adverse perinatal outcomes using the cerebroplacental (CPR) and umbilicocerebral (UCR) ratios in different cohorts of singleton pregnancies. Materials and Methods: In this retrospective cohort study, we established our own Multiple of Median (MoM) for CPR and UCR. The predictive value for both ratios was studied in the following outcome parameters: emergency cesarean delivery, operative intervention (OI), OI due to fetal distress, 5-min Apgar < 7, admission to neonatal intensive care unit, and composite adverse perinatal outcome. The performance of the ratios was assessed in the following cohorts: total cohort (delivery ≥ 37 + 0 weeks gestation, all birth weight centiles), low-risk cohort (delivery ≥ 37 + 0 weeks gestation, birth weight ≥ 10. centile), prolonged pregnancy cohort (delivery ≥ 41 + 0 weeks gestation, birth weight ≥ 10. centile) and small-for-gestational-age fetuses (delivery ≥ 37 + 0 weeks gestation, birth weight < 10. centile). The underlying reference values for MoM were estimated using quantile regression depending on gestational age. Prediction performance was evaluated using logistic regression models assessing the corresponding Brier score, combining discriminatory power and calibration. Results: Overall, 3326 cases were included. Across all cohorts, in the case of a significant association between a studied outcome parameter and CPR, there was an association with UCR, respectively. The Brier score showed only minimal differences for both ratios. Conclusions: Our study provides further evidence regarding predictive values of CPR and UCR. The results of our study suggest that reversal of CPR to UCR does not improve the prediction of adverse perinatal outcomes.

Effects of Omega-3 Fatty Acids on Postoperative Inflammatory Response: A Systematic Review and Meta-Analysis.

Initial evidence indicates that preoperatively initiated administration of omega-3 fatty acids (FAs) attenuates the postoperative inflammatory reaction. The effects of immunonutrition containing omega-3 FAs, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), on the inflammatory response to abdominal surgery continues to be unclear, although improved outcomes have been reported. Therefore, we determined the effectiveness of preoperatively initiated omega-3 FAs administration on postoperative inflammation defined as CRP (C-Reactive Protein), IL-6 (Interleukin 6), and WBC (White Blood Count) and potential effects on postoperative length of hospital stay (LOS) due to an improved inflammatory response. METHODS: a literature search of Cochrane Library was conducted to identify all randomized controlled trials (RCTs) investigating the effects of preoperatively initiated omega-3 to standard care, placebo, or other immunonutrients excluding omega-3 FAs in patients undergoing abdominal surgery until the end of December 2022. RESULTS: a total of 296 articles were found during the initial search. Thirteen RCTs involving 950 patients were identified that met the search criteria. These were successively analyzed and included in this meta-analysis. There was no significant difference between the groups with respect to inflammatory markers IL-6: -0.55 [-1.22; 0.12] p = 0.10, CRP: -0.14 [-0.67; 0.40] p = 0.55, WBC: -0.58 [-3.05; 1.89] p = 0.42, or hospital stay -0.5 [-1.43; 0.41] p = 0.2. CONCLUSION: although reduced inflammatory markers were observed, preoperative administration of omega-3 FAs immunonutrients had no significant effect on the postoperative inflammatory response in patients undergoing abdominal surgeries. Yet, results obtained from this study are inconclusive, likely attributed to the limited number of trials and patients included. Further studies are required to obtain a better educated verdict.

AI-based multi-PRS models outperform classical single-PRS models.

Polygenic risk scores (PRS) calculate the risk for a specific disease based on the weighted sum of associated alleles from different genetic loci in the germline estimated by regression models. Recent advances in genetics made it possible to create polygenic predictors of complex human traits, including risks for many important complex diseases, such as cancer, diabetes, or cardiovascular diseases, typically influenced by many genetic variants, each of which has a negligible effect on overall risk. In the current study, we analyzed whether adding additional PRS from other diseases to the prediction models and replacing the regressions with machine learning models can improve overall predictive performance. Results showed that multi-PRS models outperform single-PRS models significantly on different diseases. Moreover, replacing regression models with machine learning models, i.e., deep learning, can also improve overall accuracy.

The relative area score for sublingual varices reliability measurement: a diagnostic study.

BACKGROUND: Sublingual varices (SV) and their predictive potential for other clinical parameters is a much studied topic in oral medicine. SVs have been well studied as predictive markers for many common diseases such as arterial hypertension, cardiovascular disease, smoking, type 2 diabetes mellitus and age. Despite many prevalence studies, it is still unclear how the reliability of SV inspection affects its predictive power. The aim of this study was to quantify the inspection reliability of SV. METHODS: In a diagnostic study, the clinical inspection of 78 patients by 23 clinicians was examined for the diagnosis of SV. Digital images of the underside of the tongue were taken from each patient. The physicians were then asked to rate them for the presence of sublingual varices (0/1) in an online inspection experiment. Statistical analysis for inter-item and inter-rater reliability was performed in a τ-equivalent measurement model with Cronbach's [Formula: see text] and Fleiss κ. RESULTS: The interrater reliability for sublingual varices was relatively low with κ = 0.397. The internal consistency of image findings for SV was relatively high with α≈ 0.937. This shows that although SV inspection is possible in principle, it has a low reliability R. This means that the inspection finding (0/1) of individual images often cannot be reproduced stably. Therefore, SV inspection is a difficult task of clinical investigation. The reliability R of SV inspection also limits the maximum linear correlation [Formula: see text] of SV with an arbitrary other parameter Y. The reliability of SV inspection R = 0.847 limits the maximum correlation to [Formula: see text] (SV, Y) = 0,920-a 100% correlation was a priori not achievable in our sample. To overcome the problem of low reliability in SV inspection, we propose the RA (relative area) score as a continuous classification system for SV, which normalises the area of visible sublingual veins to the square of the length of the tongue, providing a dimensionless measure of SV. CONCLUSIONS: The reliability of the SV inspection is relatively low. This limits the maximum possible correlation of SV with other (clinical) parameters. SV inspection reliability is an important indicator for the quality of SV as a predictive marker. This should be taken into account when interpreting previous studies on SV and has implications for future studies. The RA score could help to objectify the SV examination and thus increase its reliability.

Ability of a polygenic risk score to refine colorectal cancer risk in Lynch syndrome.

BACKGROUND: Polygenic risk scores (PRSs) have been used to stratify colorectal cancer (CRC) risk in the general population, whereas its role in Lynch syndrome (LS), the most common type of hereditary CRC, is still conflicting. We aimed to assess the ability of PRS to refine CRC risk prediction in European-descendant individuals with LS. METHODS: 1465 individuals with LS (557 MLH1, 517 MSH2/EPCAM, 299 MSH6 and 92 PMS2) and 5656 CRC-free population-based controls from two independent cohorts were included. A 91-SNP PRS was applied. A Cox proportional hazard regression model with 'family' as a random effect and a logistic regression analysis, followed by a meta-analysis combining both cohorts were conducted. RESULTS: Overall, we did not observe a statistically significant association between PRS and CRC risk in the entire cohort. Nevertheless, PRS was significantly associated with a slightly increased risk of CRC or advanced adenoma (AA), in those with CRC diagnosed <50 years and in individuals with multiple CRCs or AAs diagnosed <60 years. CONCLUSION: The PRS may slightly influence CRC risk in individuals with LS in particular in more extreme phenotypes such as early-onset disease. However, the study design and recruitment strategy strongly influence the results of PRS studies. A separate analysis by genes and its combination with other genetic and non-genetic risk factors will help refine its role as a risk modifier in LS.

Dissecting the genetic heterogeneity of gastric cancer.

BACKGROUND: Gastric cancer (GC) is clinically heterogenous according to location (cardia/non-cardia) and histopathology (diffuse/intestinal). We aimed to characterize the genetic risk architecture of GC according to its subtypes. Another aim was to examine whether cardia GC and oesophageal adenocarcinoma (OAC) and its precursor lesion Barrett's oesophagus (BO), which are all located at the gastro-oesophageal junction (GOJ), share polygenic risk architecture. METHODS: We did a meta-analysis of ten European genome-wide association studies (GWAS) of GC and its subtypes. All patients had a histopathologically confirmed diagnosis of gastric adenocarcinoma. For the identification of risk genes among GWAS loci we did a transcriptome-wide association study (TWAS) and expression quantitative trait locus (eQTL) study from gastric corpus and antrum mucosa. To test whether cardia GC and OAC/BO share genetic aetiology we also used a European GWAS sample with OAC/BO. FINDINGS: Our GWAS consisting of 5816 patients and 10,999 controls highlights the genetic heterogeneity of GC according to its subtypes. We newly identified two and replicated five GC risk loci, all of them with subtype-specific association. The gastric transcriptome data consisting of 361 corpus and 342 antrum mucosa samples revealed that an upregulated expression of MUC1, ANKRD50, PTGER4, and PSCA are plausible GC-pathomechanisms at four GWAS loci. At another risk locus, we found that the blood-group 0 exerts protective effects for non-cardia and diffuse GC, while blood-group A increases risk for both GC subtypes. Furthermore, our GWAS on cardia GC and OAC/BO (10,279 patients, 16,527 controls) showed that both cancer entities share genetic aetiology at the polygenic level and identified two new risk loci on the single-marker level. INTERPRETATION: Our findings show that the pathophysiology of GC is genetically heterogenous according to location and histopathology. Moreover, our findings point to common molecular mechanisms underlying cardia GC and OAC/BO. FUNDING: German Research Foundation (DFG).

Clinically relevant combined effect of polygenic background, rare pathogenic germline variants, and family history on colorectal cancer incidence.

BACKGROUND AND AIMS: Summarised in polygenic risk scores (PRS), the effect of common, low penetrant genetic variants associated with colorectal cancer (CRC), can be used for risk stratification. METHODS: To assess the combined impact of the PRS and other main factors on CRC risk, 163,516 individuals from the UK Biobank were stratified as follows: 1. carriers status for germline pathogenic variants (PV) in CRC susceptibility genes (APC, MLH1, MSH2, MSH6, PMS2), 2. low (< 20%), intermediate (20-80%), or high PRS (> 80%), and 3. family history (FH) of CRC. Multivariable logistic regression and Cox proportional hazards models were applied to compare odds ratios and to compute the lifetime incidence, respectively. RESULTS: Depending on the PRS, the CRC lifetime incidence for non-carriers ranges between 6 and 22%, compared to 40% and 74% for carriers. A suspicious FH is associated with a further increase of the cumulative incidence reaching 26% for non-carriers and 98% for carriers. In non-carriers without FH, but high PRS, the CRC risk is doubled, whereas a low PRS even in the context of a FH results in a decreased risk. The full model including PRS, carrier status, and FH improved the area under the curve in risk prediction (0.704). CONCLUSION: The findings demonstrate that CRC risks are strongly influenced by the PRS for both a sporadic and monogenic background. FH, PV, and common variants complementary contribute to CRC risk. The implementation of PRS in routine care will likely improve personalized risk stratification, which will in turn guide tailored preventive surveillance strategies in high, intermediate, and low risk groups.

Boosting multivariate structured additive distributional regression models.

We develop a model-based boosting approach for multivariate distributional regression within the framework of generalized additive models for location, scale, and shape. Our approach enables the simultaneous modeling of all distribution parameters of an arbitrary parametric distribution of a multivariate response conditional on explanatory variables, while being applicable to potentially high-dimensional data. Moreover, the boosting algorithm incorporates data-driven variable selection, taking various different types of effects into account. As a special merit of our approach, it allows for modeling the association between multiple continuous or discrete outcomes through the relevant covariates. After a detailed simulation study investigating estimation and prediction performance, we demonstrate the full flexibility of our approach in three diverse biomedical applications. The first is based on high-dimensional genomic cohort data from the UK Biobank, considering a bivariate binary response (chronic ischemic heart disease and high cholesterol). Here, we are able to identify genetic variants that are informative for the association between cholesterol and heart disease. The second application considers the demand for health care in Australia with the number of consultations and the number of prescribed medications as a bivariate count response. The third application analyses two dimensions of childhood undernutrition in Nigeria as a bivariate response and we find that the correlation between the two undernutrition scores is considerably different depending on the child's age and the region the child lives in.

Redundancy-aware unsupervised ranking based on game theory: Ranking pathways in collections of gene sets.

In Genetics, gene sets are grouped in collections concerning their biological function. This often leads to high-dimensional, overlapping, and redundant families of sets, thus precluding a straightforward interpretation of their biological meaning. In Data Mining, it is often argued that techniques to reduce the dimensionality of data could increase the maneuverability and consequently the interpretability of large data. In the past years, moreover, we witnessed an increasing consciousness of the importance of understanding data and interpretable models in the machine learning and bioinformatics communities. On the one hand, there exist techniques aiming to aggregate overlapping gene sets to create larger pathways. While these methods could partly solve the large size of the collections' problem, modifying biological pathways is hardly justifiable in this biological context. On the other hand, the representation methods to increase interpretability of collections of gene sets that have been proposed so far have proved to be insufficient. Inspired by this Bioinformatics context, we propose a method to rank sets within a family of sets based on the distribution of the singletons and their size. We obtain sets' importance scores by computing Shapley values; Making use of microarray games, we do not incur the typical exponential computational complexity. Moreover, we address the challenge of constructing redundancy-aware rankings where, in our case, redundancy is a quantity proportional to the size of intersections among the sets in the collections. We use the obtained rankings to reduce the dimension of the families, therefore showing lower redundancy among sets while still preserving a high coverage of their elements. We finally evaluate our approach for collections of gene sets and apply Gene Sets Enrichment Analysis techniques to the now smaller collections: As expected, the unsupervised nature of the proposed rankings allows for unremarkable differences in the number of significant gene sets for specific phenotypic traits. In contrast, the number of performed statistical tests can be drastically reduced. The proposed rankings show a practical utility in bioinformatics to increase interpretability of the collections of gene sets and a step forward to include redundancy-awareness into Shapley values computations.

Maintenance tocolysis, tocolysis in preterm premature rupture of membranes and in cervical cerclage - a Germany-wide survey on the current practice after dissemination of the German guideline.

OBJECTIVES: To investigate the adherence of German perinatal specialist units and those of basic obstetric care to the national guideline we compared data from a nation-wide survey on the practice of maintenance tocolysis, tocolysis in preterm premature rupture of membranes and in the perioperative setting of cervical cerclage, and bedrest during and after tocolysis with recommendations from the current German Guideline 015/025 "Prevention and Treatment of Preterm Birth". METHODS: A total of 632 obstetric clinics in Germany were approached and received a link to an online questionnaire. Data were descriptively analyzed by performing measures of frequency. To compare two or more groups Fisher's exact test was used. RESULTS: The response rate was 19%; 23 (19.2%) of respondents did not perform maintenance tocolysis, while 97 (80.8%) conducted maintenance tocolysis; 30 (25.0%) of obstetric units performed cervical cerclage without tocolysis and 90 (75.0%) combined cervical cerclage with tocolysis; 11 (9.2%) of respondents did not use tocolytics in patients with preterm premature rupture of membranes, while 109 (90.8%) conducted tocolysis in these patients; 69 (57.5%) of obstetric units did not recommend bed rest during tocolysis, whereas 51 (42.5%) favored bedrest. Perinatal care centers of basic obstetric care recommend bed arrest during tocolysis statistically significant more often to their patients than those of higher perinatal care levels (53.6 vs. 32.8%, p=0.0269). CONCLUSIONS: The results of our survey are in accordance to others from different countries and reveal considerable discrepancies between evidence-based guideline recommendations and daily clinical practice.