BACKGROUND: Coronary artery disease (CAD) is the leading cause of death globally, with early risk prediction being vital for timely intervention. In this study we utilized advanced machine learning techniques, incorporating clinical, lifestyle, and Genetic factors with the aim to enhance the 10-year risk prediction of CAD in early middle-aged adults (40–55 years). METHODS: For developing the machine learning models, we used data from the UK Biobank, a large cohort of over 500,000 participants. Among participants aged 40 to 55, we identified 3,012 CAD cases and 155,176 controls, without any prior CAD diagnosis. More than 700 clinical and lifestyle variables were evaluated, alongside a polygenic risk score (PRS) derived from more than 560,000 genetic variants. Forward feature selection was performed, followed by the application of a stacking ensemble model combining Random Forest and Deep Learning Neural Networks as base learners with a Logistic Regression model serving as a meta-learner. The model’s performance for the 10-years prediction of CAD risk was evaluated using Area Under the Receiver Operating Characteristic Curve (AUC) and calibrated against the ACC/AHA guidelines. RESULTS: Forward feature selection identified 22 CAD risk factors, including the PRS. The final model yielded an AUC of 0.81 in the training dataset and 0.80 in the testing dataset. At the 7.5% risk threshold, the model demonstrated higher sensitivity (0.511 vs. 0.346) and comparable specificity (0.863 vs. 0.866) compared to the ACC ASCVD model. The Net Reclassification Index (NRI) improved by 13.79%, emphasizing the model’s accuracy and alignment. CONCLUSIONS: Our findings highlight the potential of combining Genetic information with clinical and lifestyle factors through machine learning to improve CAD risk prediction in early middle-aged adults. The use of a stacking ensemble approach enabled modeling of complex relationships, yielding superior performance over standard risk models. This framework supports more precise and actionable 10-year risk stratification, reinforcing the value of PRSs when combined with traditional factors. Future research should validate these methods across diverse populations and clinical environments.

Epidemiological cohort studies associating long-term exposure to ambient air pollution with health outcomes most often do not account for individually assigned exposure measurement error. Here, we implemented Cox proportional hazards models to explore the relationships between NO2, PM2.5 and ozone exposures with the incidence of natural-cause mortality and several morbidity outcomes in 61,797 London-dwelling respondents of the UK Biobank cohort. Data from an existing personal monitoring campaign was used as an external validation dataset to estimate measurement error structures between "true" personal exposure and several surrogate (measured and modelled) estimates of assigned exposure, allowing for the application of two health effect estimate correction methodologies: regression calibration (RCAL) and simulation extrapolation (SIMEX). Uncorrected hazard ratios (HRs) suggested an increase in the risk of natural-cause mortality for modelled NO2 estimates (HR: 1.028 [0.983, 1.074] per IQR increment of 14.54 μg/m3) and no statistically significant association was observed for PM2.5 surrogate exposure measures. Measurement error corrected HRs were generally larger in magnitude, although exhibited wider confidence intervals than uncorrected effect estimates. Chronic obstructive pulmonary disease (COPD) was associated with increased exposure to modelled NO2 (1.087 [1.022, 1.155]). Both RCAL and SIMEX correction resulted in increased HRs (1.254 [1.061, 1.482] and 1.192 [1.093, 1.301], respectively). SIMEX correction of modelled PM2.5 (IQR: 1.72 μg/m3) associations with COPD increased the HR (1.079 [1.001, 1.164]) in comparison to uncorrected (1.042 [0.988, 1.099]). These findings suggest that health effect estimates not corrected for exposure measurement error may lead to underestimation in the magnitude of effects.

Background Coexisting long-term conditions (LTCs) in psoriasis and their potential causal associations with the disease are not well -established.Objectives To determine distinct clusters of LTCs in people with psoriasis and the potential bidirectional causal association between these LTCs and psoriasis.Methods Using latent class analysis, cross-sectional data from people with psoriasis from the UK Biobank were analysed to identify distinct psoriasis-related comorbidity profiles. Linkage disequilibrium score regression (LDSR) was applied to compute the genetic correlation between psoriasis and LTCs. Two-sample bidirectional Mendelian randomization (MR) analysis assessed the potential causal direction using independent genetic variants that reached genome-wide significance (P < 5 x 10(-8)).Results Five comorbidity clusters were identified in a population of 10 873 people with psoriasis. LDSR revealed that psoriasis was positively genetically correlated with heart failure [genetic correlation (rg) = 0.23, P = 8.8 x 10(-8)], depression (rg = 0.12, P = 2.7 x 10(-5)), coronary artery disease (CAD; rg = 0.15, P = 2 x 10(-4)) and type 2 diabetes (rg = 0.19, P = 3 x 10(-3)). Genetic liability to CAD was associated with an increased risk of psoriasis [inverse variance weighted (IVW) odds ratio (ORIVW) 1.159, 95% confidence interval (CI) 1.055-1.274; P = 2 x 10(-3)]. The MR pleiotropy residual sum and outlier (MR-PRESSO; ORMR-PRESSO 1.13, 95% CI 1.042-1.228; P = 6 x 10(-3)) and the MR-robust adjusted profile score (RAPS) (ORMR-RAPS 1.149, 95% CI 1.062-1.242; P = 5 x 10(-4)) approaches corroborate the IVW findings. The weighted median (WM) generated similar and consistent effect estimates but was not statistically significant (ORWM 1.076, 95% CI 0.949-1.221; P = 0.25). Evidence for a suggestive increased risk was detected for CAD (ORIVW 1.031, 95% CI 1.003-1.059; P = 0.03) and heart failure (ORIVW 1.019, 95% CI 1.005-1.033; P = 9 x 10(-3)) in those with a genetic liability to psoriasis; however, MR sensitivity analyses did not reach statistical significance.Conclusions Five distinct clusters of psoriasis comorbidities were observed with these findings to offer opportunities for an integrated approach to comorbidity prevention and treatment. Coexisting LTCs share with psoriasis common genetic and nongenetic risk factors, and aggressive lifestyle modification in these people is anticipated to have an impact beyond psoriasis risk. Genetically predicted CAD is possibly associated with an increased risk of psoriasis, altering our prior knowledge.

Abstract Background Obesity and diabetes are associated inversely with low‐grade prostate cancer risk and affect steroid hormone synthesis but whether they modify each other's impact on prostate cancer risk remains unknown. Methods We examined the independent associations of diabetes, body mass index (BMI), ‘a body shape index’ (ABSI), hip index (HI), circulating testosterone, sex hormone binding globulin (SHBG) (per one standard deviation increase) and oestradiol ≥175 pmol/L with total prostate cancer risk using multivariable Cox proportional hazards models for UK Biobank men. We evaluated multiplicative interactions (pMI) and additive interactions (relative excess risk from interaction (pRERI), attributable proportion (pAR), synergy index (pSI)) with obese (BMI ≥30 kg/m2) and diabetes. Results During a mean follow‐up of 10.3 years, 9417 incident prostate cancers were diagnosed in 195,813 men. Diabetes and BMI were associated more strongly inversely with prostate cancer risk when occurring together (pMI = 0.0003, pRERI = 0.032, pAP = 0.020, pSI = 0.002). ABSI was associated positively in obese men (HR = 1.081; 95% CI = 1.030–1.135) and men with diabetes (HR = 1.114; 95% CI = 1.021–1.216). The inverse associations with obesity and diabetes were attenuated for high‐ABSI ≥79.8 (pMI = 0.022, pRERI = 0.008, pAP = 0.005, pSI <0.0001 obesity; pMI = 0.017, pRERI = 0.047, pAP = 0.025, pSI = 0.0005 diabetes). HI was associated inversely in men overall (HR = 0.967; 95% CI = 0.947–0.988). Free testosterone (FT) was associated most strongly positively in normal weight men (HR = 1.098; 95% CI = 1.045–1.153) and men with diabetes (HR = 1.189; 95% CI = 1.081–1.308). Oestradiol was associated inversely in obese men (HR = 0.805; 95% CI = 0.682–0.951). The inverse association with obesity was stronger for high‐FT ≥243 pmol/L (pRERI = 0.040, pAP = 0.031, pSI = 0.002) and high‐oestradiol (pRERI = 0.030, pAP = 0.012, pSI <0.0001). The inverse association with diabetes was attenuated for high‐FT (pMI = 0.008, pRERI = 0.015, pAP = 0.009, pSI = 0.0006). SHBG was associated inversely in men overall (HR = 0.918; 95% CI = 0.895–0.941), more strongly for high‐HI ≥49.1 (pMI = 0.024). Conclusions Obesity and diabetes showed synergistic inverse associations with prostate cancer risk, likely involving testosterone reduction for diabetes and oestrogen generation for obesity, which were attenuated for high‐ABSI. HI and SHBG showed synergistic inverse associations with prostate cancer risk.

The naive importance sampling (IS) estimator generally does not work well in examples involving simultaneous inference on several targets, as the importance weights can take arbitrarily large values, making the estimator highly unstable. In such situations, alternative multiple IS estimators involving samples from multiple proposal distributions are preferred. Just like the naive IS, the success of these multiple IS estimators crucially depends on the choice of the proposal distributions. The selection of these proposal distributions is the focus of this article. We propose three methods: (i) a geometric space filling approach, (ii) a minimax variance approach, and (iii) a maximum entropy approach. The first two methods are applicable to any IS estimator, whereas the third approach is described in the context of Doss's (2010) two-stage IS estimator. For the first method, we propose a suitable measure of 'closeness' based on the symmetric Kullback-Leibler divergence, while the second and third approaches use estimates of asymptotic variances of Doss's (2010) IS estimator and Geyer's (1994) reverse logistic regression estimator, respectively. Thus, when samples from the proposal distributions are obtained by running Markov chains, we provide consistent spectral variance estimators for these asymptotic variances. The proposed methods for selecting proposal densities are illustrated using various detailed examples.

IntroductionPolygenic Risk Scores (PRS) are an emerging tool for predicting an individual’s genetic risk to a complex trait. Several methods have been proposed to construct and calculate these scores. Here, we develop a biologically driven PRS using the UK BioBank cohort through validated protein interactions (PPI) and network construction for psoriasis, incorporating variants mapped to the interacting genes of 14 psoriasis susceptibility (PSORS) loci, as identified from previous genetic linkage studies.MethodsWe constructed the PPI network via the implementation of two major meta-databases of protein interactions, and identified variants mapped to the identified PSORS-interacting genes. We selected only European unrelated participants including individuals with psoriasis and randomly selected healthy controls using an at least 1:4 ratio to maximize statistical power. We next compared our PPI-PRS model to (i) clinical risk models and (ii) conventional PRS calculations through p-value thresholding.ResultsOur PPI-PRS model provides comparable results to both clinical risk models and conventional approaches, despite the incorporation of a limited number of variants which have not necessarily reached genome-wide significance (GWS). Exclusion of variants mapped to the HLA-C locus, an established risk locus for psoriasis resulted in highly similar associations compared to our primary model, indicating the contribution of the genetic variability mapped to non-GWS variants in PRS computations.DiscussionOur findings support the implementation of biologically driven approaches in PRS calculations in psoriasis, highlighting their potential clinical utility in risk assessment and treatment management.

Introduction Investigation expectations for children and adolescents with cancer is an important issue for their psycho-emotional development as well as their quality of life. Objectives To investigate the expectations of children suffering from cancer. Methods 102 questionnaires were collected from pediatric patients suffering from neoplasia disease (62 boys and 40 girls) with a median age of 13 years, covering the multidimensional expectation questionnaire (MEQ) suitable for children with cancer in a 4-point Likert scale. The MEQ was then evaluated using the SPSS.21 statistical package, which resulted in 13 questions. The questionnaire of expectations highlighted three factors that referred to the “family life expectations”, “daily life / daily routine and career prospects”, and “expectations of networking friendship”, respectively. The statistical results were obtained by multi-line regression analysis, with the Stata 12.1 statistical package, while ethical issues were complied with and licensed. Results MEQ reliability (Cronbach’s alpha) for the entire scale was 0.82 and for agents ranged from 0.65-0.84. Overall, pediatric cancer patients delivered a fairly high average score of 3,33 ± 0,42 questions in the expectation’s questionnaire, while the mean scores were 3,29 ± 0,63, 3,51 ± 0, 45 and 3.19 ± 0.54, respectively. From the results of the analysis of multiple regression, it appeared that, as the age increases, the patients with neoplastic disease have overall 76 lower expectations (p = 0.014), while the satisfaction of the doctors-nursing staff in the total expectations is positive (p = 0.018). In the family life expectancy factor, the age of children appears to play a negative role in increasing age (p = 0.019), while positive body image and satisfaction with doctors-nursing staff (p = 0.040, p = 0.006) respectively. It appeared that children aged> 13 years have worse outcomes in expectations of the daily routine and career prospects with (p = 0.037). Conclusions The MEQ has proven to be a valid and reliable tool that can provide pediatric staff and researchers with information about the expectations of children and adolescents with cancer that require long-term health care. Disclosure of Interest None Declared

Introduction The admission and hospitalization of a child in a Pediatric Intensive Care Unit (PICU) creates stress and anxiety in the family. The family is called upon to make important decisions about the child’s treatment, while roles within the family environment are disrupted. Objectives The investigation of the psychosocial needs of the relatives of hospitalized children in the NICU. Methods We conducted a systematic review of studies published until the end of 2022 in the Greek and English languages in the databases “Pubmed”, “Scopus” and “Iatrotec” with the following keywords: “Pediatric Intensive Care Unit”, “Socio-psychological Needs’ and ‘Parents’. Results Of the 26 studies found, 5 studies met the inclusion-exclusion criteria and were included in the review. The most frequently mentioned psychosocial needs of the parents were: (1) the need for complete, immediate and honest information regarding the health status of their hospitalized child and the changes in their condition, (2) the need to provide comfort to the parents during duration of their child’s hospitalization, (3) the parents’ need for psychological support and guidance regarding the care of their hospitalized child, (4) the feeling of security regarding the care provided, and (5) the need for frequent contact with the hospitalized child. Also, it was observed that the medical and nursing staff underestimated some needs of the parents, such as the need for closeness, while there were others that we underestimated, such as the religious needs. Conclusions Parents present increased psychosocial needs during their child’s hospitalization in the PICU. Nursing staff play an important role in supporting relatives by providing family-centered care. Disclosure of Interest None Declared

In this study we used Mendelian randomization (MR) to investigate the potential causal association of lipoprotein (a) [Lp(a)] levels with pulse wave velocity (PWV). Genetic variants associated with Lp(a) were retrieved from the UK Biobank GWAS ( N  = 290,497). A non- overlapping GWAS based on a European cohort ( N  = 7,000) was used to obtain genetic associations with PWV (outcome) and utilized two different measures for the same trait, brachial–ankle (baPWV) and carotid–femoral (cfPWV) PWV. We applied a two-sample MR using the inverse variance weighting method (IVW) and a series of sensitivity analyses for 170 SNPs that were selected as instrumental variables (IVs). Our analyses do not support a causal association between Lp(a) and PWV for neither measurement [β iwv (baPWV) = −.0005, p  = .8 and β iwv (cfPWV) = −.006, p  = .16]. The above findings were consistent across sensitivity analyses including weighted median, mode-based estimation, MR-Egger regression and MR-PRESSO. We did not find evidence indicating that Lp(a) is causally associated with PWV, the gold standard marker of arterial stiffness.

Several cardiovascular (CV) traits and diseases co-occur with Alzheimer’s disease (AD). We mapped their shared genetic architecture using multi-trait genome-wide association studies. Subsequent fine-mapping and colocalisation highlighted 19 genetic loci associated with both AD and CV diseases. We prioritised rs11786896, which colocalised with AD, atrial fibrillation (AF) and expression of PLEC in the heart left ventricle, and rs7529220, which colocalised with AD, AF and expression of C1Q family genes. Single-cell RNA-sequencing data, co-expression network and protein-protein interaction analyses provided evidence for different mechanisms of PLEC , which is upregulated in left ventricular endothelium and cardiomyocytes with heart failure (HF) and in brain astrocytes with AD. Similar common mechanisms are implicated for C1Q in heart macrophages with HF and in brain microglia with AD. These findings highlight inflammatory and pleomorphic risk determinants for the co-occurrence of AD and CV diseases and suggest PLEC, C1Q and their interacting proteins as novel therapeutic targets.

With the proliferation of screening tools for chemical testing, it is now possible to create vast databases of chemicals easily. However, rigorous statistical methodologies employed to analyse these databases are in their infancy, and further development to facilitate chemical discovery is imperative. In this paper, we address the challenge of predicting an organic solvent's water pollution class based on its chemical structure. We hypothesise that solvents with similar chemical structure are more likely to belong in the same hazard class. This chemical similarity is measured by the Tanimoto distance, a non-Euclidean metric on the chemical space. To incorporate the similarity between chemical structures in the model, we propose a Gaussian process model on the chemical space, with the kernel being a function of the Tanimoto distance. A novel feature of the proposed model is the inclusion of a scaling parameter in the kernel, which controls the strength of the correlation between compounds and offers additional flexibility. We find that accounting for correlation between chemical compounds substantially improves predictive performance over the uncorrelated model, where compound similarity is unaccounted for. Our model also compares favourably against other established models in the literature. Furthermore, we present a genetic algorithm designed to identify important features to a compound's efficacy, with the goal of facilitating chemical discovery. The algorithm operates based on two criteria derived from the proposed model. Simulation studies are conducted to demonstrate the suitability of the proposed methods.

Despite the abundance of epidemiological evidence for the high comorbid rate between psoriasis and obesity, systematic approaches to common inflammatory mechanisms have not been adequately explored. We performed a meta-analysis of publicly available RNA-sequencing datasets to unveil putative mechanisms that are postulated to exacerbate both diseases, utilizing both late-stage, disease-specific meta-analyses and consensus gene co-expression network (cWGCNA). Single-gene meta-analyses reported several common inflammatory mechanisms fostered by the perturbed expression profile of inflammatory cells. Assessment of gene overlaps between both diseases revealed significant overlaps between up- (n = 170, P value = 6.07 x 10-65) and down-regulated (n = 49, P value = 7.1 x 10-7) genes, associated with increased T cell response and activated transcription factors. Our cWGCNA approach disentangled 48 consensus modules, associated with either the differentiation of leukocytes or metabolic pathways with similar correlation signals in both diseases. Notably, all our analyses confirmed the association of the perturbed T helper (Th)17 differentiation pathway in both diseases. Our novel findings through whole transcriptomic analyses characterize the inflammatory commonalities between psoriasis and obesity implying the assessment of several expression profiles that could serve as putative comorbid disease progression biomarkers and therapeutic interventions.

Several cardiovascular traits and diseases co-occur with Alzheimer's disease. We mapped their shared genetic architecture using multi-trait genome-wide association studies. Subsequent fine-mapping and colocalisation highlighted 16 genetic loci associated with both Alzheimer's and cardiovascular diseases. We prioritised rs11786896, which colocalised with Alzheimer's disease, atrial fibrillation and expression of PLEC in the heart left ventricle, and rs7529220, which colocalised with Alzheimer's disease, atrial fibrillation and expression of C1Q family genes. Single-cell RNA-sequencing data, co-expression network and protein-protein interaction analyses provided evidence for different mechanisms of PLEC, which is upregulated in left ventricular endothelium and cardiomyocytes with heart failure and in brain astrocytes with Alzheimer's disease. Similar common mechanisms are implicated for C1Q in heart macrophages with heart failure and in brain microglia with Alzheimer's disease. These findings highlight inflammatory and pleomorphic risk determinants for the co-occurrence of Alzheimer's and cardiovascular diseases and suggest PLEC, C1Q and their interacting proteins as potential therapeutic targets. Cardiovascular traits often co-occur with Alzheimer's disease. Here, the authors mapped shared genetic architecture, identifying 16 loci linked to both conditions. They highlight PLEC and C1Q as key genes, providing potential new therapeutic targets for treating the co-occurrence of these diseases.

Introduction Children and adolescents with thalassemia suffer from chronicity of the disease and its treatment, including transfusion dependence and complications of iron overload. Objectives To investigate the quality of life of children and adolescents with Beta Thalassaemia. Methods This study is a cross-sectional study conducted at the Greek public Children’s Hospital. PedsQL ™ 4.0 Generic Core Scale (Greek version) was used to evaluate HRQOL in 41 thalassemia patients aged between 5 and 18 years and in 41 healthy controls of the same age range. For the analysis, the Statistic Package (SPSS ver.24) was used. Using Spearman’s correlation coefficient, t-test and MannWhitney tests were used, while for variables with three or more levels the Anova and Kruskall-Wallis. In order to investigate the relationship between two quantitative variables, Spearman’s correlation coefficient was used, while the relationship between two qualitative variables was used to control x2. As a statistical significance level, α = 5% was defined. Results Of the 41 children with beta Thalassemia who participated in the study, 48.8% (n = 20) were boys and 51.2% (n = 21) girls. The mean age of children was 10.02 ± 4.10 years. For healthy children who participated in the study 51.2% (n = 21) were boys while 48.8% (n = 20) were girls. The mean age of the children was 9.63 ± 3.77 years. Children with Beta Thalassaemia have a lower quality of life in Physical Health and Activity(<0,001), Emotional Health(0,031), School Activities(0,008), Psychosocial Health(0,014), and the overall PedsQL 4.0 (<0,001)questionnaire compared to healthy children. Children between the ages of 5 and 7 have higher levels of quality of life in physical health and activity than older children(<0,001). In addition, children aged 5 to 7 have higher quality of life and overall PedsQL 4.0 score than older children(0,033) Children receiving combination therapy show better quality of life than children receiving subcutaneous therapy (total PedsQL 4.0 <0,001). Conclusions Children and adolescents in all five categories had a better quality of life, after improved iron chelating methods and other psychosocial interventions. Disclosure of Interest None Declared

Introduction Children with cancer face many difficulties on a daily basis which place them at increased risk of developing anxiety and discomfort. Objectives To assess the intensity of state-trait anxiety in children with cancer. Methods The sample of the study consisted of 100 children from Greek Children’s Hospital, aged 8-16 years, of which 56 had cancer, representing the study group while the control-group was 44 in an outpatient clinic with endocrinological problems. Data were collected by the completion of the questionnaire “State-Trait Anxiety Inventory for children” by Ch. Spielberger. Statistical package S.P.S.S. was used for statistical analysis. 22 and the statistical test, t-test and anova. The significance level was set at p <0.05. Results Of the total sample, sarcoma 38%, brain Ca 14%, 48% endocrine problem, and the largest percentage (57%) were aged 8-10 years. Children with cancer in 44.6% were under treatment and 55.4% in remission or recovery. Body image change was experienced by the 44%. The mean value of the state anxiety was 30.3±5.4 and trait was 35.3±6.9. Children with cancer experienced lower levels of state anxiety compared to control group, p =0.049, and did not differed in terms of trait anxiety, p=0.060. In the total sample, girls experienced trait anxiety of the highest intensity, p=0.018 and children aged 14-16, p=0.020. No statistically significant differences were found in relation to the type of cancer in both state and trait anxiety, p=0.096 and p=0.424, in relation to the phase of the disease and the change of body image, p>0.05. Children whose fathers were of higher education experienced less anxiety and differed significantly from those of primary and secondary education, p=0.036 and p=0.021, respectively. Comparison between control group and study group in relation to gender, showed that girls with cancer experienced trait anxiety of higher intensity, p=0.029 but children between 14-16 years from the control group experienced trait anxiety of higher intensity, p=0.030. Conclusions Children of both groups experienced mild to moderate anxiety and its intensity was related to socio-demographic factors of the children and their parents. Disclosure of Interest None Declared

The breadth and validity of the associations of nongenetic risk factors with celiac disease (CeD) are elusive in the literature. We aimed to evaluate which of these associations have strong epidemiological credibility and assessed presence and extent of potential literature biases. We systematically searched PubMed until April 2024 for systematic reviews and meta-analyses of studies examining associations between putative risk factors and CeD. Each association was categorized in five evidence grades (convincing, highly suggestive, suggestive, weak, and not statistically significant) based on broadly used criteria for evaluating quality of evidence in observational studies. Five eligible publications were included, describing 15 meta-analytic associations on seven nongenetic risk factors, three of which were nominally significant ( P  < 0.05). None of the associations received a strοng or highly suggestive evidence. One meta-analytic association received suggestive evidence, namely any infections during childhood and adulthood for a higher risk of CeD (OR, 1.37; 95% CI, 1.2-1.56; P =3.77 × 10 -6 ). Two meta-analyses reported weak evidence, pertaining to current smoking for a lower risk of CeD (OR, 0.52; 95% CI, 0.32-0.84; P =7.84 × 10 -3 ) and use of antibiotics for a higher risk (OR, 1.2; 95% CI, 1.04-1.38; P 14.8 × 10 -3 ). The rest of the meta-analyses did not report statistically significant results, and pertained to breastfeeding, time of gluten introduction, rotavirus vaccination, and cesarean section. No association of nongenetic risk factors for CeD received high levels of evidence. The evidence was suggestive for the association of any infections during childhood and adulthood with higher risk of CeD. More and prospective future research is warranted.

Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10-8) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5-18.2 mmHg, P = 2.22 × 10-126) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54-9.70; P = 4.13 × 10-44) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781-0.801) to 0.826 (95% CI, 0.817-0.836, ∆AUROC, 0.035, P = 1.98 × 10-34). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research.

Introduction The admission of children to PICU is a painful experience for parents. Regularly, they are asked to make important decisions about treatment options in collaboration with the care team, which causes them stress, uncertainty and trauma. Objectives To investigate the needs of parents during the child’s hospitalization in a pediatric intensive care unit (PICU). Methods A systematic review of the literature and a search of articles in the international databases PubMed, Cinahl, Google Scholar, Cochrane Library and Greek scientific journals was performed with a peer review process during the period between April and July 2022. A time limit was set regarding the date of publication of the articles (articles published in the last 15 years). Results Nine studies were found that met the criteria for inclusion in the review. The thematic analysis of the results deduced the following sections A: Need for information from health professionals regarding the child’s health status and the possible treatment options available, B: Need for psychological support from health professionals (psychologists, nurses, doctors) in order to be able to manage the difficult situation they are experiencing due to the hospitalization of their child, but also to be able to manage their grief and sorrow in case of loss of the child. C: Need for safe hospitalisation of the child. Conclusions Parents have needs during their child’s hospitalization in the PICU, which if put in boundaries-frames and guided by health professionals (who possess knowledge and composure in difficult moments) can bring about a smooth course of the child’s health during hospitalization. Disclosure of Interest None Declared

Obesity is accompanied by low-grade inflammation and leucocytosis and increases the risk of venous thromboembolism. Associations with platelet count, however, are unclear, because several studies have reported positive associations only in women. Associations with body shape are also unclear, because waist and hip circumferences reflect overall body size, as well as body shape, and are correlated strongly positively with body mass index (BMI).We evaluated body shape with the allometric body shape index (ABSI) and hip index (HI), which reflect waist and hip size among individuals with the same weight and height and are uncorrelated with BMI. We examined the associations of BMI, ABSI, and HI with platelet count, mean platelet volume (MPV), and platelet distribution width (PDW) in multivariable linear regression models for 125,435 UK Biobank women and 114,760 men. We compared men with women, post-menopausal with pre-menopausal women, and older (≥ 52 years) with younger (< 52 years) men.BMI was associated positively with platelet count in women, more strongly in pre-menopausal than in post-menopausal, and weakly positively in younger men but strongly inversely in older men. Associations of BMI with platelet count were shifted towards the inverse direction for daily alcohol consumption and current smoking, resulting in weaker positive associations in women and stronger inverse associations in men, compared to alcohol ≤ 3 times/month and never smoking. BMI was associated inversely with MPV and PDW in pre-menopausal women but positively in post-menopausal women and in men. ABSI was associated positively with platelet count, similarly in women and men, while HI was associated weakly inversely only in women. ABSI was associated inversely and HI positively with MPV but not with PDW and only in women. Platelet count was correlated inversely with platelet size and positively with leucocyte counts, most strongly with neutrophils.Competing factors determine the associations of BMI with platelet count. Factors with sexually dimorphic action (likely thrombopoietin, inflammatory cytokines, or cortisol), contribute to a positive association, more prominently in women than in men, while age-dependent factors (likely related to liver damage and fibrosis), contribute to an inverse association, more prominently in men than in women.