RE: Physical activity and the risk of liver cancer: A systematic review and meta-analysis of prospective studies and a bias analysis.

Background Physical inactivity is an established risk factor for several cancers of the digestive system and female reproductive organs, but the evidence for liver cancers is less conclusive.Methods The aim of this study was to synthesize prospective observational studies on the association of physical activity and liver cancer risk by means of a systematic review and meta-analysis. We searched Medline, Embase, and Scopus from inception to January 2019 for prospective studies investigating the association of physical activity and liver cancer risk. We calculated mean hazard ratios (HRs) and 95% confidence intervals (CIs) using a random-effects model. We quantified the extent to which an unmeasured confounder or an unaccounted selection variable could shift the mean hazard ratio to the null.Results Fourteen prospective studies, including 6,440 liver cancers, were included in the systematic review and meta-analysis. The mean hazard ratio for high compared with low physical activity was 0.75 (95% CI=0.63 to 0.89; 95% prediction interval=0.52 to 1.07; I-2=64.2%). We estimated that 67.6% (95% CI=56.6% to 78.5%) of all true effect estimates would have a hazard ratio less than 0.8. Bias analysis suggested than an unobserved confounder would have to be associated with a 1.99-fold increase in the risk of physical activity or liver cancer to explain away the observed mean hazard ratio. An unaccounted for selection variable would have to be related to exposure and endpoint with a relative risk of 1.58 to explain away the mean hazard ratio.Conclusions Physical activity is inversely related to the risk of liver cancer. Further studies with objectively measured physical activity and quasi-experimental designs addressing confounding are needed

To stratify or not to stratify: Power considerations for population-based genome-wide association studies of quantitative traits.

Meta-analyses of genome-wide association studies require numerous study partners to conduct pre-defined analyses and thus simple but efficient analyses plans. Potential differences between strata (e.g. men and women) are usually ignored, but often the question arises whether stratified analyses help to unravel the genetics of a phenotype or if they unnecessarily increase the burden of analyses. To decide whether to stratify or not to stratify, we compare general analytical power computations for the overall analysis with those of stratified analyses considering quantitative trait analyses and two strata. We also relate the stratification problem to interaction modeling and exemplify theoretical considerations on obesity and renal function genetics. We demonstrate that the overall analyses have better power compared to stratified analyses as long as the signals are pronounced in both strata with consistent effect direction. Stratified analyses are advantageous in the case of signals with zero (or very small) effect in one stratum and for signals with opposite effect direction in the two strata. Applying the joint test for a main SNP effect and SNP-stratum interaction beats both overall and stratified analyses regarding power, but involves more complex models. In summary, we recommend to employ stratified analyses or the joint test to better understand the potential of strata-specific signals with opposite effect direction. Only after systematic genome-wide searches for opposite effect direction loci have been conducted, we will know if such signals exist and to what extent stratified analyses can depict loci that otherwise are missed

Relationship between atopic dermatitis, depression and anxiety: A two-sample mendelian randomization study.

BACKGROUND: Growing evidence suggests that atopic dermatitis (AD) is associated with an increased risk of depressive disorders and anxiety. However, existing studies were observational and may uncover correlations but cannot easily disentangle non-causal or reverse-causal associations because these associations could be confounded and may not reflect true causal relationships. OBJECTIVES: We carried out a 2-sample Mendelian randomization (MR) study to examine the potential effect of AD on the risk of depressive disorders and anxiety. METHODS: Genetic instruments from the largest available genome-wide association study (GWAS) for AD (10,788 cases, 30,047 controls) were used to investigate the relation to broad depression (170,756 cases, 329,443 controls), major depressive disorder (MDD) (30,603 cases, 143,916 controls) and anxiety (5,580 cases, 11,730 controls). A set of complementary approaches were carried out to assess horizontal pleiotropy and related potential caveats occurring in MR studies. RESULTS: We observed no causal impact of AD on the risk of depressive disorders and anxiety, with close-to-zero effect estimates. The inverse weighted method revealed no associations of AD on broad depression (OR=1.014, P=0.4307), probable MDD (OR=1.004, P=0.5681), ICD-9/10-based MDD (OR=1.001, P=0.4659) or anxiety (OR=1.097, P=0.1801). CONCLUSIONS: In summary, this MR study does not support a causal effect of AD on depression and anxiety

Cardiorespiratory fitness and gray matter volume in the temporal, frontal, and cerebellar regions in the general population.

Objective: To analyze the association between cardiorespiratory fitness (CRF) and global and local brain volumes.Participants and Methods: We studied 2103 adults (21-84 years old) from 2 independent population-based cohorts (Study of Health in Pomerania, examinations from June 25, 2008, through September 30, 2012). Cardiorespiratory fitness was measured using peak oxygen uptake (VO(2)peak), oxygen uptake at the anaerobic threshold (VO2@AT), and maximal power output from cardiopulmonary exercise testing on a bicycle ergometer. Magnetic resonance imaging brain data were analyzed by voxel-based morphometry using regression models with adjustment for age, sex, education, smoking, body weight, systolic blood pressure, glycated hemoglobin level, and intracranial volume.Results: Volumetric analyses revealed associations of CRF with gray matter (GM) volume and total brain volume. After multivariable adjustment, a 1-standard deviation increase in VO(2)peak was related to a 5.31 cm(3) (95% CI, 3.27 to 7.35 cm(3)) higher GM volume. Whole-brain voxel-based morphometry analyses revealed significant positive relations between CRF and local GM volumes. The VO(2)peak was strongly associated with GM volume of the left middle temporal gyrus (228 voxels), the right hippocampal gyrus (146 voxels), the left orbitofrontal cortex (348 voxels), and the bilateral cingulate cortex (68 and 43 voxels).Conclusion: Cardiorespiratory fitness was positively associated with GM volume, total brain volume, and specific GM and white matter clusters in brain areas not primarily involved in movement processing. These results, from a representative population sample, suggest that CRF might contribute to improved brain health and might, therefore, decelerate pathology-specific GM decrease

Feasibility and quality development of biomaterials in the pretest studies of the German National Cohort.

BACKGROUND: The German National Cohort (GNC) is designed to address research questions concerning a wide range of possible causes of major chronic diseases (e.g. cancer, diabetes, infectious, allergic, neurologic and cardiovascular diseases) as well as to identify risk factors and prognostic biomarkers for early diagnosis and prevention of these diseases. The collection of biomaterials in combination with extensive information from questionnaires and medical examinations represents one of the central study components. OBJECTIVES: In two pretest studies of the German National Cohort conducted between 2011 and 2013, a range of biomaterials from a defined number of participants was collected. Ten study centres were involved in pretest 1 and 18 study centres were involved in pretest 2. Standard operation procedures (SOP) were developed and evaluated to minimize pre-analytical artefacts during biosample collection. Within the pretest studies different aspects concerning feasibility of sample collection/preparation [pretest 1 (a)] and quality control of biomarkers and proteome analyses were investigated [pretest 1 (b), (c)]. Additionally, recruitment of study participants for specific projects and examination procedures of all study centres in a defined time period according to common standards as well as transportation and decentralized storage of biological samples were tested (pretest 2). These analyses will serve as the basis for the biomaterial collection in the main study of the GNC starting in 2014. MATERIALS AND METHODS: Participants, randomly chosen from the population (n = 1000 subjects recruited at ten study sites in pretest 1) were asked to donate blood, urine, saliva and stool samples. Additionally, nasal and oropharyngeal swabs were collected at the study sites and nasal swabs were collected by the participants at home. SOPs for sample collection, preparation, storage and transportation were developed and adopted for pretest 2. In pretest 2, 18 study sites (n = 599 subjects) collected biomaterials mostly identical to pretest 1. Biomarker analyses to test the quality of the biomaterials were performed. RESULTS: In pretest 1 and 2, it was feasible to collect all biomaterials from nearly all invited participants without major problems. The mean response rate of the subjects was 95 %. As one important result we found for example that after blood draw the cellular fraction should be separated from the plasma and serum fractions during the first hour with no significant variation for up to 6 h at 4 ℃ for all analysed biomarkers. Moreover, quality control of samples using a proteomics approach showed no significant clustering of proteins according to different storage conditions. All developed SOPs were validated for use in the main study after some adaptation and modification. Additionally, electronic and paper documentation sheets were developed and tested to record time stamps, volumes, freezing times, and aliquot numbers of the collected biomaterials. DISCUSSION: The collection of the biomaterials was feasible without major problems at all participating study sites. However, the processing times were in some cases too long. To avoid pre-analytical artefacts in sample collection, appropriate standardisation among the study sites is necessary. To achieve this, blood and urine collection will have to be adapted to specific conditions of usage of liquid handling robots, which will be available at all participating study centres in the main study of the GNC. Strict compliance with the SOPs, thorough training of the staff and accurate documentation are mandatory to obtain high sample quality for later analyses. The so obtained biomaterials represent a valuable resource for research on infectious and other common complex diseases in the GNC