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BACKGROUND: Few have studied the associations between rs9939609 genotypes in the obesity candidate locus FTO and energy and nutrient intakes and meal frequencies in adults with severe obesity. We are unaware of studies that have assessed adherence to key dietary recommendations in this population, at least in Norway. Increased knowledge of genotype associations with dietary factors could improve personalized obesity therapy. OBJECTIVES: The present study aimed to explore how the rs9939609 genotypes associate with dietary variables and adherence to key dietary recommendations in a sample of adults with severe obesity. METHODS: A cross-sectional observation study designed to have similar numbers of participants with genotypes TT, AT, and AA included 100 patients (70% women) with median (25(th), 75(th) percentile) age 42 (32, 50) y and BMI 42.8 (39.5, 46.4) kg/m(2). We assessed intakes of food groups, energy, and macro- and micronutrients from three 24-h dietary recalls and meal frequencies. Genotype associations were analyzed using regression analyses. Reported intakes were evaluated against national diet recommendations. RESULTS: Using a significance level of 0.01, we found no genotype associations with energy intake, energy density, adherence to recommendations, or meal frequency but tendencies of associations with energy adjusted protein intake (AA > AT, P = 0.037; AT > TT, P = 0.064), food groups milk and cream (AT > TT, P = 0.029), and Mixed dishes (AA > TT, P = 0.039). Few participants complied with recommendations for intakes of whole grains (21%), fruits and vegetables (11%), and fish (37%); however, 67% followed the recommendation to limit added sugar. Less than 20% had recommended intakes of vitamin D and folate. CONCLUSIONS: In our patients with severe obesity, we found tendencies of associations between the FTO rs9939609 genotypes and diet but no significant associations at the 0.01 level and below. Few met key food-based diet recommendations, suggesting that the food habits in this population pose an increased risk of nutrient deficiencies. Curr Dev Nutr 2023;xx:xx.

BACKGROUND Patients with substance use disorders (SUD) are at increased risk for symptom deterioration following treatment, with up to 60% resuming substance use the first year post treatment, and craving, together with neurocognitive and mental health variables play important roles in the understanding of the trajectories from abstinence to substance use. OBJECTIVE This study aims to improve our understanding of specific profiles of variables explaining SUD symptom deterioration. Specifically, how individual variability in mental health, neurocognitive functioning, and smartphone use is associated with craving and substance use in a young adult clinical population. METHODS In this pilot study, 26 patients with SUD were included 2 weeks prior to discharge from inpatient SUD treatment. Patients underwent baseline neuropsychological and mental health assessments and were equipped with smartwatches and downloaded an app for mobile sensor data collection on their smartphones. Every 2 days for up to 8 weeks the patients were administered mobile ecological momentary assessments (EMA) assessing substance use, craving, mental health, cognition, and a mobile go/no-go performance task. Repeated EMAs, as well as battery use sensor data was averaged across all days per subject and used as candidate input variables in models of craving intensity and relapse. RESULTS A total of 455 momentary assessments were completed. Using EMA and baseline data as candidate input variables, and craving and substance use as responses, automated model selection identified mean craving intensity as the most important predictor of substance use, with variability in self-reported impulsivity, mental health, and battery use as the significant predictors of craving intensity. CONCLUSIONS This study adds novelty by collecting high intensity data, for a considerable period of time, including both mental health, mobile sensor and mobile cognitive assessment data. The study also contributes to our knowledge about the most severe part of this clinical population in a vulnerable period during and after discharge from inpatient treatment. We confirmed the importance of temporal variability in executive dysfunction and mood in explaining variability in craving, and in addition that phone use may add to this understanding. Finally, we found that craving intensity is an important explanatory variable in relapse prediction. Our results inform further work towards precision medicine and just-in-time interventions with young adults with substance use disorders and may serve as decision support for clinicians evaluating discharge. CLINICALTRIAL

Not all data sets have explanatory variables and outcomes. The data may nevertheless contain associations that are worth revealing.

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.

Not all published research findings are reproducible — some because the findings are incorrect. What is the extent of the problem? A number of researchers have attempted to estimate how often published findings are false. They have used widely different approaches.

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. Copyright: © 2021 de Soysa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

BackgroundThe 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. Classical logistic regression models are suitable to look for pre-defined interactions while more complex models, such as tree ensemble models, with the ability to detect any interactions have previously been difficult to interpret. However, with the development of methods for model explainability, it is now possible to interpret tree ensemble models with a strong theoretical ground and efficiently.ResultsWe propose a tree ensemble- and SHAP-based method for identifying as well as interpreting both 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 interactions. The analysis suggests that the new method finds interactions between features that logistic regression models have difficulties in detecting.ConclusionsThe new method robustly detects interesting interactions, and can be applied to large-scale biobanks with high-dimensional data.

We consider cross-sectional genetic association studies (common and rare variants) where non-genetic information is available, or feasible to obtain for $N$ individuals, but where it is infeasible to genotype all $N$ individuals. We consider continuously measurable Gaussian traits (phenotypes). Genotyping $n

Symptoms of ADHD are strongly associated with alcohol use disorders, and mental health symptoms attenuate this relationship. There is limited knowledge about how specific symptoms of inattentiveness and hyperactivity/impulsivity can explain this association. We aimed to identify self-reported executive cognitive functioning and mental health and variables that may help identify subjects with an elevated risk of alcohol dependence in the general population. Data included 3917 subjects between 19 and 30 years old in the 4th Trøndelag Health Study. The Adult ADHD Self report Scale—Screener, the Hospital Anxiety and Depression Scale, and demographic variables were used as input variables. The alcohol screening instrument CAGE was used as the response variable for binary alcohol dependence risk. We used logistic regression and automated model selection to arrive at our final model that identified sex, age, inattentiveness, hyperactivity/impulsivity symptoms, and anxiety as predictors of having a CAGE score ≥2, achieving an area under the receiver operating characteristic curve of 0.692. A balanced accuracy approach indicated an optimal cut-off of 0.153 with sensitivity 0.55 and specificity 0.74. Despite attrition in the data, our findings may be important in the assessment of individual risk for alcohol dependency and when developing algorithms for risk triage in public health.

In genetic association studies, detecting phenotype–genotype association is a primary goal. We assume that the relationship between the data—phenotype, genetic markers and environmental covariates—can be modeled by a generalized linear model. The number of markers is allowed to be far greater than the number of individuals of the study. A multivariate score statistic is used to test each marker for association with a phenotype. We assume that the test statistics asymptotically follow a multivariate normal distribution under the complete null hypothesis of no phenotype–genotype association. We present the familywise error rate order k approximation method to find a local significance level (alternatively, an adjusted p‐value) for each test such that the familywise error rate is controlled. The special case k=1 gives the Šidák method. As a by‐product, an effective number of independent tests can be defined. Furthermore, if environmental covariates and genetic markers are uncorrelated, or no environmental covariates are present, we show that covariances between score statistics depend on genetic markers alone. This not only leads to more efficient calculations but also to a local significance level that is determined only by the collection of markers used, independent of the phenotypes and environmental covariates of the experiment at hand. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Background:Addictive disorders and substance use are significant health challenges worldwide, and relapse is a core component of addictive disorders. The dynamics surrounding relapse and especially the immediate period before it occurs is only partly understood, much due to difficulties collecting reliable and sufficient data from this narrow period. Mobile sensing has been an important way to improve data quality and enhance predictive capabilities for symptom worsening within physical and mental health care, but is less developed within substance use research. Methodology:This scoping review aimed to reviewing the currently available research on mobile sensing of substance use and relapse in substance use disorders. The search was conducted in January 2019 using PubMed and Web of Science. Results:Six articles were identified, all concerning subjects using alcohol. In the studies a range of mobile sensors and derived aggregated features were employed. Data collected through mobile sensing were predominantly used to make dichotomous inference on ongoing substance use or not and in some cases on the quantity of substance intake. Only one of the identified studies predicted later substance use. A range of statistical machine learning techniques was employed. Conclusions:The research on mobile sensing in this field remains scarce. The issues requiring further attention include more research on clinical populations in naturalistic settings, use of a priori knowledge in statistical modeling, focus on prediction of substance use rather than purely identification, and finally research on other substances than alcohol.

Background and aims Several risk prediction models for coronary heart disease (CHD) are available today, however, they only explain a modest proportion of the incidence. Circulating microRNAs (miRs) have recently been associated with processes in CHD development, and may therefore represent new potential risk markers. The aim of the study was to assess the incremental value of adding circulating miRs to the Framingham Risk Score (FRS). Methods This is a case-control study with a 10-year observation period, with fatal and non-fatal myocardial infarction (MI) as endpoint. At baseline, ten candidate miRs were quantified by real-time polymerase chain reaction in serum samples from 195 healthy participants (60–79 years old). During the follow-up, 96 participants experienced either a fatal (n = 36) or a non-fatal MI (n = 60), whereas the controls (n = 99) remained healthy. By using best subset logistic regression, we identified the miRs that together with the FRS for hard CHD best predicted future MI. The model evaluation was performed by 10-fold cross-validation reporting area under curve (AUC) from the receiver operating characteristic curve (ROC). Results The best miR-based logistic regression risk-prediction model for MI consisted of a combination of miR-21-5p, miR-26a-5p, mir-29c-3p, miR-144-3p and miR-151a-5p. By adding these 5 miRs to the FRS, AUC increased from 0.66 to 0.80. In comparison, adding other important CHD risk factors (waist-hip ratio, triglycerides, glucose, creatinine) to the FRS only increased AUC from 0.66 to 0.68. Conclusions Circulating levels of miRs can add value on top of traditional risk markers in predicting future MI in healthy individuals.

Background 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. Methods 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). Results 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. Conclusions 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. © 2017 Bjørnland et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

We consider cross-sectional genetic association studies (common and rare variants) where non-genetic information is available or feasible to obtain for N individuals, but where it is infeasible to genotype all N individuals. We consider continuously measurable Gaussian traits (phenotypes). Genotyping nN extreme phenotype individuals can yield better power to detect phenotype-genotype associations, as compared to randomly selecting n individuals. We define a person as having an extreme phenotype if the observed phenotype is above a specified threshold or below a specified threshold. We consider a model where these thresholds can be tailored to each individual. The classical extreme sampling design is to set equal thresholds for all individuals. We introduce a design (z-extreme sampling) where personalized thresholds are defined based on the residuals of a regression model including only non-genetic (fully available) information. We derive score tests for the situation where only n extremes are analyzed (complete case analysis) and for the situation where the non-genetic information on N - n non-extremes is included in the analysis (all case analysis). For the classical design, all case analysis is generally more powerful than complete case analysis. For the z-extreme sample, we show that all case and complete case tests are equally powerful. Simulations and data analysis also show that z-extreme sampling is at least as powerful as the classical extreme sampling design and the classical design is shown to be at times less powerful than random sampling. The method of dichotomizing extreme phenotypes is also discussed.

Cardiovascular disease, obesity, and type 2 diabetes are conditions characterized by low-grade systemic inflammation, strongly influenced by lifestyle, but the mechanisms that link these characteristics are poorly understood. Our first objective was to investigate if a normocaloric diet with a calorically balanced macronutrient composition influenced immunological gene expression. Findings regarding the suitability of blood as biological material in nutrigenomics and gene expression profiling have been inconclusive. Our second objective was to compare blood and adipose tissue sample quality in terms of adequacy for DNA-microarray analyses, and to determine tissue-specific gene expression patterns. Blood and adipose tissue samples were collected for gene expression profiling from three obese men before, during, and after a 28-day normocaloric diet intervention where each meal contained an approximately equal caloric load of macronutrients. Time series analyses of blood gene expression revealed a cluster of downregulated genes involved in immunological processes. Blood RNA quality and yield were satisfactory, and DNA-microarray analysis reproducibility was similar in blood and adipose tissue. Gene expression correlation between blood and adipose tissue varied according to gene function, and was especially low for genes involved in immunological and metabolic processes. This suggests that diet composition is of importance in inflammatory processes in blood cells. The findings also suggest that a systems biology approach, in which tissues are studied in parallel, should be employed to fully understand the impact of dietary challenges on the human body.

Purpose: 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. Methods: 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. Results: 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

Exact unconditional tests for comparing two binomial probabilities are generally more powerful than conditional tests like Fisher's exact test. Their power can be further increased by the Berger and Boos confidence interval method, where a p-value is found by restricting the common binomial probability under H 0 to a 1−γ confidence interval. We studied the average test power for the exact unconditional z-pooled test for a wide range of cases with balanced and unbalanced sample sizes, and significance levels 0.05 and 0.01. The detailed results are available online on the web. Among the values 10−3, 10−4, …, 10−10, the value γ=10−4 gave the highest power, or close to the highest power, in all the cases we looked at, and can be given as a general recommendation as an optimal γ.

Superficial invasion of extravillous trophoblasts (EVTs) and impaired spiral artery remodelling are characterizing phenomena in pregnancies complicated by pre-eclampsia (PE) and fetal growth restriction (FGR). However, the underlying causes remain unclear. In this study, gene expression in decidua basalis tissue from pregnancies complicated with PE and/or FGR (n = 18) and normal pregnancies (n = 17) was assessed by Affymetrix HG Focus microarray to obtain hints of mechanisms involved in the pathogenesis. A total of 200 differentially expressed transcripts were detected at a false discovery rate (FDR)

This study aims to investigate changes that occur during progression and establishment of physiological and pathological cardiac hypertrophy, by microarray technology and functional annotations.Myocardial infarction leading to heart failure was induced in rats, with animals killed 1, 3, 7, 14, 42, and 92 days after coronary artery ligation. A second group was subjected to daily treadmill exercise and killed 1, 4, 24, and 48 h after a single exercise bout, or after 28 or 56 days of exercise training.Physiological hypertrophy was associated with less transcriptional alternation than pathological hypertrophy, indicating that posttranscriptional and translational regulation may be more important. The main difference between the two types of hypertrophy was that myocardial infarction was associated with downregulation of genes related to fatty acid metabolism, whereas no such change occurred after exercise training. Thus, fatty acid metabolism may distinguish adverse maladaptive hypertrophy from beneficial adaptive hypertrophy.This study points to specific genes and gene classes related to biological processes that may be important in these well-characterized rat models of physiological and pathological cardiac hypertrophy.

The relationship between inborn maximal oxygen uptake (VO2max) and skeletal muscle gene expression is unknown. Since low VO2maxis a strong predictor of cardiovascular mortality, genes related to low VO2maxmight also be involved in cardiovascular disease. To establish the relationship between inborn VO2maxand gene expression, we performed microarray analysis of the soleus muscle of rats artificially selected for high- and low running capacity (HCR and LCR, respectively). In LCR, a low VO2maxwas accompanied by aggregation of cardiovascular risk factors similar to the metabolic syndrome. Although sedentary HCR were able to maintain a 120% higher running speed at VO2maxthan sedentary LCR, only three transcripts were differentially expressed (FDR ≤ 0.05) between the groups. Sedentary LCR expressed high levels of a transcript with strong homology to human leucyl-transfer RNA synthetase, of whose overexpression has been associated with a mutation linked to mitochondrial dysfunction. Moreover, we studied exercise-induced alterations in soleus gene expression, since accumulating evidence indicates that long-term endurance training has beneficial effects on the metabolic syndrome. In terms of gene expression, the response to exercise training was more pronounced in HCR than LCR. HCR upregulated several genes associated with lipid metabolism and fatty acid elongation, whereas LCR upregulated only one transcript after exercise training. The results indicate only minor differences in soleus muscle gene expression between sedentary HCR and LCR. However, the inborn level of fitness seems to influence the transcriptional adaption to exercise, as more genes were upregulated after exercise training in HCR than LCR.

Neuroendocrine tumours (NETs) comprise a heterogenous group of malignancies with an often unpredictable course, and with limited treatment options. Thus, new diagnostic, prognostic, and therapeutic markers are needed. To shed new lights into the biology of NETs, we have by cDNA transcript profiling, sought to identify genes that are either up- or downregulated in NE as compared with non-NE tumour cells. A panel of six NET and four non-NET cell lines were examined, and out of 12 743 genes examined, we studied in detail the 200 most significantly differentially expressed genes in the comparison. In addition to potential new diagnostic markers (NEFM, CLDN4, PEROX2), the results point to genes that may be involved in the tumorigenesis (BEX1, TMEPAI, FOSL1, RAB32), and in the processes of invasion, progression and metastasis (MME, STAT3, DCBLD2) of NETs. Verification by real time qRT-PCR showed a high degree of consistency to the microarray results. Furthermore, the protein expression of some of the genes were examined. The results of our study has opened a window to new areas of research, by uncovering new candidate genes and proteins to be further investigated in the search for new prognostic, predictive, and therapeutic markers in NETs.

BACKGROUND: Long-term therapy with potent acid inhibitors is a common treatment for gastro-esophageal reflux disease. Administration of proton pump inhibitors (PPIs) causes profound and continuous hypochlorhydria by inhibition of the proton pump in gastric parietal cells. Long-term hypergastrinaemia increases mucosal thickness and enterochromaffin-like cell density in oxyntic mucosa. OBJECTIVE: The aim of this study was to see whether this very common clinical intervention induces significant changes in the gastric mucosal gene expression pattern. METHODS: Seven patients suffering from gastro-esophageal reflux disease were included in this study. Endoscopic biopsies were taken from the corpus mucosa before and toward the end of a 3-month treatment with the PPI esomeprazole. RESULTS: Microarray analysis identified 186 differentially expressed genes. A high proportion of genes with changed gene expression levels during PPI treatment are involved in proliferation, apoptosis, and stress response. CONCLUSION: This study identified many genes that were not previously known to be affected by inhibition of gastric acid secretion. Further characterization of the functional roles of genes whose expression is modulated by potent acid inhibition may give new insight into the biological responses to potent acid inhibition, including the mucosal response to the moderately increased gastrin levels encountered in clinical practice.

Pre-eclampsia (PE) is associated with increased oxidative stress and excessive maternal inflammatory response. Heme oxygenase 1 (HMOX1) is an important stress response enzyme and a mediator of cytoprotection against a wide variety of tissue injuries.In the present study, microarray technology was used to compare the expression of HMOX1 and other genes involved in stress and inflammatory responses in decidua basalis from 16 pregnancies complicated by PE and 17 healthy controls. In addition, the presence of HMOX1 protein in decidua basalis was examined by means of immunohistochemistry, and ELISA was used to measure the maternal serum concentration of HMOX1.Fifteen transcripts involved in stress response including HMOX1 were up-regulated in cases, using a cut-off value at p=0.01. HMOX1 protein expression in decidua basalis was significantly increased in cases compared to controls reflected by more pronounced intensity of HMOX1 positive decidual cells (1.8+/-0.3 versus 1.5+/-0.4, p=0.02) and an increased proportion of HMOX1 positive decidual leukocytes (31+/-29 versus 9+/-6%, p=0.001). Finally, serum HMOX1 levels were significantly higher among cases compared to controls (3.1+/-1.3 versus 1.9+/-0.5 ng/ml, p=0.008).Increased decidual and serum HMOX1 levels, together with altered decidual expression of some stress-related genes in cases, support the role of oxidative stress and excessive maternal inflammatory response in the pathogenesis of PE.

DNA microarray experiments have become a widely used tool for studying gene expression. An important, but difficult, part of these experiments is deciding on the appropriate number of biological replicates to use. Often, researchers will want a number of replicates that give sufficient power to recognize regulated genes while controlling the false discovery rate (FDR) at an acceptable level. Recent advances in statistical methodology can now help to resolve this issue. Before using such methods it is helpful to understand the reasoning behind them. In this Research Focus article we explain, in an intuitive way, the effect sample size has on the FDR and power, and then briefly survey some recently proposed methods in this field of research and provide an example of use.

Introduction A mild systemic inflammation may be beneficial to normal pregnancy, however exaggerated inflammation may contribute to pregnancy complications. Infections and cell stress or damage may evoke placental inflammation by activation of Toll-like receptors (TLRs). TLR3, TLR7, TLR8 and TLR9 are located intracellulary on endosomes and are activated by nucleic acids from microbes and damaged cells. Trophoblasts play a crucial role during placentation, and the role of TLRs in first trimester trophoblasts needs to be determined. Objectives To characterize endosomal TLR gene expression and activation in first trimester trophoblasts, to extend knowledge of endosomal TLR involvement in placental inflammation. Methods Primary trophoblasts were isolated from six first trimester placentas by enzyme degradation and gradient centrifugation. Gene expression of TLR3, TLR7, TLR8 and TLR9 in primary first trimester trophoblasts and the trophoblast cell line BeWo was quantified by RT-qPCR. The trophoblasts were stimulated with ligands for endosomal TLRs, and release of pro-inflammatory cytokines was analyzed by multiplex. Results Primary first trimester trophoblasts showed gene expression of all endosomal TLRs, and endosomal TLR activation gave increased production of the pro-inflammatory cytokines IL-6, IL-8, and IP-10. Conclusion Primary first trimester trophoblasts express functional endosomal TLRs, indicating TLR-mediated trophoblast involvement in early placental inflammation.

Introduction The first trimester of pregnancy is characterised by a mild pro-inflammatory environment, however excessive inflammation threatens placental development and function. Toll-like receptors (TLRs) are crucial in initiating inflammation. TLR1, TLR2, TLR4, TLR5, TLR6 and TLR10 are expressed on the cell surface, and respond to microbial infection and cell damage and stress signals. Recent findings of TLRs in trophoblasts indicate a role in inflammation during pregnancy, but further studies are warranted. Objectives To investigate gene expression and function of cell surface TLRs in first trimester trophoblasts, to extend knowledge on the role of trophoblast TLRs during placental development. Methods Primary trophoblasts were isolated from first trimester placentas (n = 6) by enzyme degradation and density gradient centrifugation. Gene expression of TLR1, TLR2, TLR4, TLR5, TLR6 and TLR10 was quantified by RT-qPCR in primary first trimester trophoblasts and the trophoblast cell line BeWo. Trophoblasts were stimulated with cell surface TLR ligands and pro-inflammatory cytokine release was analysed by multiplex immunoassay. Results Primary first trimester trophoblasts expressed all cell surface TLR mRNAs, and activation of TLR2/1, TLR4 and TLR5 induced IL-6 and/or IL-8. Conclusion The broad expression of functional cell surface TLRs in primary first trimester trophoblasts suggests a central role for trophoblasts in placental inflammation and immune activation.

Targeting growth-regulatory pathways is a promising approach in cancer treatment. A prerequisite to the development of such therapies is characterisation of tumour growth regulation in the particular tumour cell type of interest. In order to gain insight into molecular mechanisms underlying proliferative responses in neuroendocrine (NE) gastrointestinal (GI) tumours, we investigated gene expression in human carcinoid BON cells after exposure to gastrin, hepatocyte growth factor (HGF), pituitary adenylate cyclase-activating polypeptide or epidermal growth factor. We particularly focused on gastrin- and HGF-induced gene expression, and identified 95 gastrin- and 101 HGF-responsive genes. The majority of these genes are known mediators of processes central in tumour biology, and a number of them have been associated with poor prognosis and metastasis in cancer patients. Furthermore, we identified 12 genes that were regulated by all four factors, indicating that they may be universally regulated during NE GI tumour cell proliferation. Our findings provide useful hypotheses for further studies aimed to search for new therapeutic targets as well as tumour markers in NE GI tumours.

Highlight The larvae of Mamestra brassicae feed less and show reduced growth on plants with ablated myrosin cells, which raises questions about the role of defence cells in Brassicaceae plants., The Brassicaceae family is characterized by a unique defence mechanism known as the ‘glucosinolate–myrosinase’ system. When insect herbivores attack plant tissues, glucosinolates are hydrolysed by the enzyme myrosinase (EC 3.2.1.147) into a variety of degradation products, which can deter further herbivory. This process has been described as ‘the mustard oil bomb’. Additionally, insect damage induces the production of glucosinolates, myrosinase, and other defences. Brassica napus seeds have been genetically modified to remove myrosinase-containing myrosin cells. These plants are termed MINELESS because they lack myrosin cells, the so-called toxic mustard oil mines. Here, we examined the interaction between B. napus wild-type and MINELESS plants and the larvae of the cabbage moth Mamestra brassicae. No-choice feeding experiments showed that M. brassicae larvae gained less weight and showed stunted growth when feeding on MINELESS plants compared to feeding on wild-type plants. M. brassicae feeding didn’t affect myrosinase activity in MINELESS plants, but did reduce it in wild-type seedlings. M. brassicae feeding increased the levels of indol-3-yl-methyl, 1-methoxy-indol-3-yl-methyl, and total glucosinolates in both wild-type and MINELESS seedlings. M. brassicae feeding affected the levels of glucosinolate hydrolysis products in both wild-type and MINELESS plants. Transcriptional analysis showed that 494 and 159 genes were differentially regulated after M. brassicae feeding on wild-type and MINELESS seedlings, respectively. Taken together, the outcomes are very interesting in terms of analysing the role of myrosin cells and the glucosinolate–myrosinase defence system in response to a generalist cabbage moth, suggesting that similar studies with other generalist or specialist insect herbivores, including above- and below-ground herbivores, would be useful.

We report a strategy for analysis of data quality in cDNA microarrays based on the repeatability of repeatedly spotted clones. We describe how repeatability can be used to control data quality by developing adaptive filtering criteria for microarray data containing clones spotted in multiple spots. We have applied the method on five publicly available cDNA microarray data sets and one previously unpublished data set from our own laboratory. The results demonstrate the feasibility of the approach as a foundation for data filtering, and indicate a high degree of variation in data quality, both across the data sets and between arrays within data sets.

All-population and area-based investigations of diet in central obesity are scarce. We used cross-sectional data from 50 339 individuals who responded to the HUNT3 survey of 2006–2008, which recruited from all county-residing adults 20 years and older, to investigate whether those with central obesity eat and drink differently than others. Answers to dietary questions were recoded and analyzed with multiple linear regression, using waist/hip ratio (WHR), age, and sex as explanatory variables. Frequencies of consumption or amounts of food, beverages, and meals were compared among WHR quartiles. Central obesity was present in the quartile with the highest WHR, WHR4 (WHR ≥ 0.917 for women and 0.981 for men) but not in the quartile with the lowest WHR, WHR1 (WHR < 0.817 for women and 0.895 for men). Dietary variables differed markedly by age and sex. After adjustment for these factors and for multiple testing, we found significant differences between WHR4 and WHR1 for 19 of 30 dietary variables. Central obesity was associated with a lower intake of any bread, and of whole-grain bread in particular. Intake of fruits and berries, vegetables, and pasta and rice was less, and intake of sausages and hamburgers and boiled potatoes was more frequent. Intake of alcohol, tea, and fruit juice was lower in those with central obesity, whereas intake of sugar-free soft drinks and coffee was higher. The frequency of breakfast and lunch was lower and of nightly meals was higher in those with central obesity. In conclusion, in this large area-based population, central obesity was associated with differences in dietary habits, some of which (such as decreased consumption of whole-grain bread and increased intake of sugar-free drinks) are of possible clinical significance.

The conventional line transect approach of estimating effective search width from the perpendicular distance distribution is inappropriate in certain types of surveys, e.g., when an unknown fraction of the animals on the track line is detected, the animals can be observed only at discrete points in time, there are errors in positional measurements, and covariate heterogeneity exists in detectability. For such situations a hazard probability framework for independent observer surveys is developed. The likelihood of the data, including observed positions of both initial and subsequent observations of animals, is established under the assumption of no measurement errors. To account for measurement errors and possibly other complexities, this likelihood is modified by a function estimated from extensive simulations. This general method of simulated likelihood is explained and the methodology applied to data from a double-platform survey of minke whales in the northeastern Atlantic in 1995.

The objective of the present study was to determine whether genetic variability in UDP-glucuronosyltransferase (UGT) genes, together with clinical factors, contribute to variability in morphine glucuronide (M6G and M3G) to morphine serum concentration ratios in patients with advanced cancer receiving chronic morphine therapy.A total of 41 polymorphisms and predicted haplotypes in the UGT2B7, UGT1A1, and UGT1A8 genes were analyzed in 759 patients who were recruited from the European Pharmacogenetic Opioid Study and received chronic morphine therapy by the oral route (n=635) or parenterally (n=124). The administration groups were analyzed separately by multiple linear regression analyses.Two haplotypes in UGT1A1/UGT1A8 were weak predictors of reduced M6G/morphine and M3G/morphine serum ratios after oral administration (false discovery rate-corrected P-values0.1). No effect of genotype was seen in the parenteral group. Of the clinical variables (age, sex, BMI, renal function, Karnofsky performance status, and presence of liver metastases), renal function was the major contributor to variation in serum concentration ratios. Concomitant administration of paracetamol predicted significantly higher morphine metabolic ratios after oral administration of morphine (false discovery rate-corrected P-values2.1E-12). The regression models explained about 35% of the total variability in the data.Genetic variation in the UGT genes together with clinical factors influence morphine metabolic ratios in patients with advanced cancer disease and who are scheduled with oral morphine. This information may be included in future research that develop and test new classification systems for opioid treatment in patients with advanced cancer.

This study evaluates the role of postterm age at assessment and the use of one or two video recordings for the detection of fidgety movements (FMs) and prediction of cerebral palsy (CP) using computer vision software. Recordings between 9 and 17 weeks postterm age from 52 preterm and term infants (24 boys, 28 girls; 26 born preterm) were used. Recordings were analyzed using computer vision software. Movement variables, derived from differences between subsequent video frames, were used for quantitative analysis. Sensitivities, specificities, and area under curve were estimated for the first and second recording, or a mean of both. FMs were classified based on the Prechtl approach of general movement assessment. CP status was reported at 2 years. Nine children developed CP of whom all recordings had absent FMs. The mean variability of the centroid of motion (CSD) from two recordings was more accurate than using only one recording, and identified all children who were diagnosed with CP at 2 years. Age at assessment did not influence the detection of FMs or prediction of CP. The accuracy of computer vision techniques in identifying FMs and predicting CP based on two recordings should be confirmed in future studies.

Genome-wide transcription data of utero-placental tissue has been used to identify altered gene expression associated with preeclampsia (PE). As many women with PE deliver preterm, there is often a difference in gestational age between PE women and healthy pregnant controls. This may pose a potential bias since gestational age has been shown to dramatically influence gene expression in utero-placental tissue. By pooling data from three genome-wide transcription studies of the maternal-fetal interface, we have evaluated the relative effect of gestational age and PE on gene expression. A total of 18,180 transcripts were evaluated in 49 PE cases and 105 controls, with gestational age ranging from week 14 to 42. A total of 22 transcripts were associated with PE, whereas 92 transcripts with gestational age (nominal P value

Acetylsalicylic acid (ASA) is a cornerstone in the treatment of coronary artery disease (CAD) due to its antiplatelet effect. Cessation of aspirin before coronary artery bypass grafting (CABG) is often recommended to avoid bleeding, but the practice is controversial because it is suggested to worsen the underlying CAD. The aims of the present prospective, randomized study were to assess if ASA administration until the day before CABG decreases the oxidative load through a reduction of inflammation and myocardial damage, compared with patients with preoperative discontinuation of ASA.Twenty patients scheduled for CABG were randomly assigned to either routine ASA-treatment (160 mg daily) until the time of surgery (ASA), or to ASA-withdrawal 7 days before surgery (No-ASA). Blood-samples were taken from a radial artery and coronary sinus, during and after surgery and analysed for 8-iso-prostaglandin (PG) F2α; a major F2-isoprostane, high-sensitivity C-reactive protein (hs-CRP), cytokines and troponin T. Left ventricle Tru-Cut biopsies were taken from viable myocardium close to the left anterior descending artery just after connection to cardiopulmonary bypass, and before cardioplegia were established for gene analysis (Illumina HT-12) and immunohistochemistry (CD45).8-Iso-PGF2α at baseline (t1) were 111 (277) pmol/l and 221 (490) pmol/l for ASA and No-ASA, respectively (P = 0.065). Area under the curve showed a significantly lower level in plasma concentration of 8-iso-PGF2α and hsCRP in the ASA group compared with the No-ASA group with (158 pM vs 297 pM, P = 0.035) and hsCRP (8.4 mg/l vs 10.1 mg/l, P = 0.013). All cytokines increased during surgery, but no significant differences between the two groups were observed. Nine genes (10 transcripts) were found with a false discovery rate (FDR)0.1 between the ASA and No-ASA groups.Continued ASA treatment until the time of CABG reduced oxidative and inflammatory responses. Also, a likely beneficial effect upon myocardial injury was noticed. Although none of the genes known to be involved in oxidative stress or inflammation took a different expression in myocardial tissue, the genetic analysis showed interesting differences in the mRNA level. Further research in this field is necessary to understand the role of the genes.

RNA-transfected cell microarray shows great promise in functional genomics. By printing siRNA complexed with transfection reagent on glass slides, arrays of transfected cells are formed in which the phenotypic consequences of gene suppression can be investigated. Using reporter plasmids with fluorescence intensity as output data, we have developed a strategy for statistical analysis of the intensity data from medium-scale functional studies using data from several experimental replicates.