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Estimating feature importance, which is the contribution of a prediction or several predictions due to a feature, is an essential aspect of explaining data-based models. Besides explaining the model itself, an equally relevant question is which features are important in the underlying data generating process. We present a Shapley-value-based framework for inferring the importance of individual features, including uncertainty in the estimator. We build upon the recently published model-agnostic feature importance score of SAGE (Shapley additive global importance) and introduce Sub-SAGE. For tree-based models, it has the advantage that it can be estimated without computationally expensive resampling. We argue that for all model types the uncertainties in our Sub-SAGE estimator can be estimated using bootstrapping and demonstrate the approach for tree ensemble methods. The framework is exemplified on synthetic data as well as large genotype data for predicting feature importance with respect to obesity.

Background The identification of gene–gene and gene–environment interactions in genome-wide association studies is challenging due to the unknown nature of the interactions and the overwhelmingly large number of possible combinations. Parametric regression models are suitable to look for prespecified interactions. Nonparametric models such as tree ensemble models, with the ability to detect any unspecified interaction, have previously been difficult to interpret. However, with the development of methods for model explainability, it is now possible to interpret tree ensemble models efficiently and with a strong theoretical basis. Results We propose a tree ensemble- and SHAP-based method for identifying as well as interpreting potential gene–gene and gene–environment interactions on large-scale biobank data. A set of independent cross-validation runs are used to implicitly investigate the whole genome. We apply and evaluate the method using data from the UK Biobank with obesity as the phenotype. The results are in line with previous research on obesity as we identify top SNPs previously associated with obesity. We further demonstrate how to interpret and visualize interaction candidates. Conclusions The new method identifies interaction candidates otherwise not detected with parametric regression models. However, further research is needed to evaluate the uncertainties of these candidates. The method can be applied to large-scale biobanks with high-dimensional data.

Associations between variants in the FTO locus and plasma concentrations of appetite related hormones are inconsistent, and might not work in a dose dependent fashion in people with obesity. Moreover, it is relevant to report meal related plasma concentrations of these hormones in persons with obesity given the growing interest in their pharmacological potential in obesity therapy. We find it clinically relevant to examine associations between the SNP rs9939609 genotypes and homeostatic appetite regulation in individuals with BMI ≥35 kg/m 2 . This study explored associations of the rs9939609 genotypes to plasma concentrations of acylated ghrelin, active glucagon-like peptide 1 (GLP-1), and total peptide YY (PYY), and moderating effects of fat mass (FM), in 96 adults (69% female) with BMI ≥35 kg/m 2 , using a cross sectional observation study designed to have 1/3 of participants each with genotypes TT, AT and AA, respectively. Participants were median (25 th , 75 th percentile) 42.5 (32, 50) years of age, weighed 120.9 (109.6, 142.4) kg, and had a BMI of 42.8 (39.5, 46.4) kg/m 2 . Acylated ghrelin, active GLP-1, and total PYY were measured in the fasted state and half-hourly for 2.5h after a standardized meal. We evaluated associations between genotype and appetite hormones in regression analysis controlling for FM and sex. Genotype did not associate with fasting or postprandial (area under curve, AUC) GLP-1 or PYY. Genotype did not associate with fasting acylated ghrelin, but in females with genotype AA, increased FM was associated with higher fasting and postprandial (AUC) acylated ghrelin concentrations relative to genotypes TT (fasting p = 0.025; AUC p = 0.004) and AT (fasting p = 0.002; AUC p < 0.001). This novel finding warrants further investigation.

Low cardiorespiratory fitness (CRF) is a well-established risk factor for cardiovascular disease (CVD) and all-cause mortality. Since CRF is largely genetically determined, understanding the genetic influences on CRF might reveal the protective mechanisms of high CRF. One gene found to be associated with CRF is COX7A2L . COX7A2L is a mitochondrial supercomplex assembly factor, but its role in cellular metabolism remains a topic of discussion. We hypothesized that COX7A2L could play a role in cellular respiration in cardiomyocytes, affecting cardiac function and CRF. To determine the effect of COX7A2L on cardiomyocyte function, we overexpressed and knocked down COX7A2L in human AC16 cardiomyocytes and performed MTT assays and Seahorse XF Cell Mito Stress Tests to assess cell viability and mitochondrial function. For the mitochondrial function measurements, we stimulated the cells with isoproterenol to investigate if the effect of altering COX7A2L levels would be larger under simulated increased energy demand. Overexpression and knockdown were validated using sandwich ELISA. Our findings showed that altering COX7A2L expression in human AC16 cardiomyocytes did not significantly affect cell viability or mitochondrial function. Further research is necessary to determine whether COX7A2L influences cardiomyocyte function and CRF.

BackgroundThe focus of suicide research changes from traditional risk factors to acute warning signs. Patient self-reported suicidal ideation (SI) is not a reliable measure of acute suicide risk. Presuicidal syndromes such as suicide crisis syndrome (SCS) attempt to describe measurable syndromes based on warning signs other than SI.MethodsSeven hundred and ten acutely admitted patients were included in the study. Identification of symptoms describing the five components of SCS was done by performing a retrospective text analysis of the patient records (electronic medical records). Patients were grouped according to high or low level of SCS symptoms. We performed statistical tests for group differences in demographics, traditional risk factors, and clinical variables, including agitation assessed by the Positive and Negative Symptom Scale-Excited Component (PANSS-EC).ResultsSeventy-two patients had high levels of SCS symptoms. They reported less SI the last month before admission; suicidality was less relevant for referral, the intake suicide assessment more often concluded with high suicide risk, they were more often referred and admitted involuntarily, and they had higher total scores on PANSS-EC.ConclusionThe individual SCS symptoms may provide useful information in the evaluation of acute suicide risk at intake. A high level of SCS symptoms suggests more severe conditions. The lower reports among high-level than low-level SCS patients of self-reported SI last month before admission, shows the limitation of using SI as a warning sign. The association between the level of SCS symptoms and PANSS-EC total score suggests that agitation could give valuable additional information for suicide risk assessments.

The main aim of this study was to examine weight associations between parents and offspring at two time points: 1995-97 and 2006-08, taking into account body mass index (BMI) and waist circumference. The study included 8425 parent-offspring trios who participated in the population based Health Study of Nord Trøndelag (the HUNT Study), Norway, at either the HUNT2 (1995-97) or the HUNT3 (2006-08) survey. We used linear mixed effects models with siblings clustered within mothers to analyze the associations between 1) parental grouped BMI and offspring BMI z-scores and 2) parental grouped waist circumference and offspring waist circumference z-scores. Adolescent and adult overweight and obesity were higher in 2006-08 than in 1995-97, with the greatest increase observed in waist circumference. Both mother's and father's BMI and waist circumference were strongly associated with corresponding measures in offspring. Compared with both parents being normal weight (BMI <25 kg/m2), having two overweight or obese parents (BMI ≥25 kg/m2) was associated with a higher offspring BMI z-score of 0.76 (95% CI; 0.65, 0.87) and 0.64 (95% CI; 0.48, 0.80) in daughters, and 0.76 (95% CI; 0.65, 0.87) and 0.69 (95% CI; 0.53, 0.80) in sons, in 1995-97 and 2006-08 respectively. Offspring with one parent being overweight/obese had BMI z-scores of approximately half of offspring with two parents categorized as overweight/obese. The results of the waist circumference based analyses did not differ substantially from the BMI based analyses. Parental overweight was strongly positively associated with offspring weight both in 1995-97 and 2006-08 where both parents being overweight/obese gave the largest effect. This seemingly stable association, strongly address the importance of public health initiatives towards preventing obesity in parents of both sexes to decrease further obesity expansion in offspring.

Our aim was to assess the influence of age, gender and lifestyle factors on the effect of the obesity-promoting alleles of FTO and MCR4. The HUNT study comprises health information on the population of Nord-Trøndelag county, Norway. Extreme phenotype participants (gender-wise lower and upper quartiles of waist-hip-ratio and BMI ≥ 35 kg/m2) in the third survey, HUNT3 (2006-08), were genotyped for the single-nucleotide polymorphisms rs9939609 (FTO) and rs17782313 (MC4R); 25686 participants were successfully genotyped. Extreme sampling was chosen to increase power to detect genetic and gene-environment effects on waist-hip-ratio and BMI. Statistical inference was based on linear regression models and a missing-covariate likelihood approach for the extreme phenotype sampling design. Environmental factors were physical activity, diet (artificially sweetened beverages) and smoking. Longitudinal analysis was performed using material from HUNT2 (1995-97). Cross-sectional and longitudinal genetic effects indicated stronger genetic associations with obesity in young than in old, as well as differences between women and men. We observed larger genetic effects among physically inactive compared to active individuals. This interaction was age-dependent and seen mainly in 20-40 year olds. We observed a greater FTO effect among men with a regular intake of artificially sweetened beverages, compared to non-drinkers. Interaction analysis of smoking was mainly inconclusive. In a large all-adult and area-based population survey the effects of obesity-promoting minor-alleles of FTO and MCR4, and interactions with life style factors are age- and gender-related. These findings appear relevant when designing individualized treatment for and prophylaxis against obesity.

The objective of the study was to assess associations of the rs9939609 FTO allele to glucose tolerance, hepatic and total insulin sensitivity (IS) in individuals with obesity. From a low-dose hyperinsulinemic euglycemic clamp with glucose-tracer, hepatic IS was assessed by rates of basal and suppressed glucose appearance (Ra), a measure of endogenous glucose production (EGP), and the hepatic insulin resistance index (HIR). Total IS was assessed by rates of glucose infusion (GIR), disappearance (Rd), and metabolic clearance (MCR). From a meal test we assessed IS by the Matsuda index and glucose tolerance by glucose and insulin measurements in the fasted state and postprandially for 2.5 h. The meal test was performed in 97 healthy individuals with BMI ≥35 in similar-sized risk-allele groups (n = 32 T/T, 31 A/T, and 34 A/A), and 79 of them performed the clamp. We analyzed outcomes separately for males and females, and adjusted glucose Ra, Rd, MCR, GIR, and HIR for fat mass. We did not find genotype effects on EGP. Among males, genotype A/A was associated with a significantly lower glucose Rd, MCR, and Matsuda index score relative to genotype T/T. Glucose tolerance was significantly lower in males with genotype A/T vs. T/T and A/A. For females, there were no genotype effects on hepatic or total IS, or on glucose tolerance. Independently of genotypes, females displayed a significantly better hepatic and total IS, and better glucose tolerance than males. We conclude that in subjects with similar obesity we did not register any FTO risk-allele effect on hepatic IS. A FTO risk-allele effect on total IS was registered in males only, findings which need to be reproduced in further studies. Results confirm marked differences in IS between the biological sexes and extend present knowledge by demonstrating a lower endogenous glucose production in females vs. males in uniformly obese individuals.

Patients with severe substance use disorders are often characterized by neurocognitive impairments and elevated mental health symptom load, typically associated with craving intensity and substance use relapse. There is a need to improve the predictive capabilities of when relapse occurs in order to improve substance use treatment. The current paper contains data from 19 patients (seven females) in a long-term inpatient substance use treatment setting over the course of several weeks, with up to three weekly data collections. We collected data from 252 sessions, ranging from 1 to 24 sessions per subject. The subjects reported craving, self-control, and mental health on each occasion. Before starting the repeated data collection, a baseline neuropsychological screening was performed. In this repeated-measures prospective study, the mixed-effects models with time-lagged predictors support a model of substance use craving and relapse being predicted by the baseline reaction time as well as the temporal changes and variability in mental health symptom load, self-control, and craving intensity with moderate to high effect sizes. This knowledge may contribute to more personalized risk assessments and treatments for this group of patients.

Patients with substance use disorders (SUDs) are at increased risk for symptom deterioration following treatment, with up to 60% resuming substance use within the first year posttreatment. Substance use craving together with cognitive and mental health variables play important roles in the understanding of the trajectories from abstinence to substance use. This prospective observational feasibility study aims to improve our understanding of specific profiles of variables explaining SUD symptom deterioration, in particular, how individual variability in mental health, cognitive functioning, and smartphone use is associated with craving and substance use in a young adult clinical population. In this pilot study, 26 patients with SUDs were included at about 2 weeks prior to discharge from inpatient SUD treatment from 3 different treatment facilities in Norway. Patients underwent baseline neuropsychological and mental health assessments; they were equipped with smartwatches and they downloaded an app for mobile sensor data collection in their smartphones. Every 2 days for up to 8 weeks, the patients were administered mobile ecological momentary assessments (EMAs) to evaluate substance use, craving, mental health, cognition, and a mobile Go/NoGo performance task. Repeated EMAs as well as the smartphone's battery use data were averaged across all days per individual and used as candidate input variables together with the baseline measures in models of craving intensity and the occurrence of any substance use episodes. A total of 455 momentary assessments were completed out of a potential maximum of 728 assessments. Using EMA and baseline data as candidate input variables and craving and substance use as responses, model selection identified mean craving intensity as the most important predictor of having one or more substance use episodes and with variabilities in self-reported impulsivity, mental health, and battery use as significant explanatory variables of craving intensity. This prospective observational feasibility study adds novelty by collecting high-intensity data for a considerable period of time, including mental health data, mobile cognitive assessments, and mobile sensor data. Our study also contributes to our knowledge about a clinical population with the most severe SUD presentations in a vulnerable period during and after discharge from inpatient treatment. We confirmed the importance of variability in cognitive function and mood in explaining variability in craving and that smartphone usage may possibly add to this understanding. Further, we found that craving intensity is an important explanatory variable in understanding substance use episodes.