Different phenomena like the spread of a disease, social interactions or the biological relation between genes can be thought of as dynamic networks. These can be represented as a sequence of static ...graphs (so called graph snapshots). Based on this graph sequences, classical vertex centrality measures like closeness and betweenness centrality have been extended to quantify the importance of single vertices within a dynamic network. An implicit assumption for the calculation of temporal centrality measures is that the graph sequence contains all information about the network dynamics over time. This assumption is unlikely to be justified in many real world applications due to limited access to fully observed network data. Incompletely observed graph sequences lack important information about duration or existence of edges and may result in biased temporal centrality values.
To account for this incompleteness, we introduce the idea of extending original temporal centrality metrics by cloning graphs of an incomplete graph sequence. Focusing on temporal betweenness centrality as an example, we show for different simulated scenarios of incomplete graph sequences that our approach improves the accuracy of detecting important vertices in dynamic networks compared to the original methods. An age-related gene expression data set from the human brain illustrates the new measures. Additional results for the temporal closeness centrality based on cloned snapshots support our findings. We further introduce a new algorithm called REN to calculate temporal centrality measures. Its computational effort is linear in the number of snapshots and benefits from sparse or very dense dynamic networks.
We suggest to use clone temporal centrality measures in incomplete graph sequences settings. Compared to approaches that do not compensate for incompleteness our approach will improve the detection rate of important vertices. The proposed REN algorithm allows to calculate (clone) temporal centrality measures even for long snapshot sequences.
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Decreasing sedentary behaviour (SB) has emerged as a public health priority since prolonged sitting increases the risk of non-communicable diseases. Mostly, the independent association of factors ...with SB has been investigated, although lifestyle behaviours are conditioned by interdependent factors. Within the DEDIPAC Knowledge Hub, a system of sedentary behaviours (SOS)-framework was created to take interdependency among multiple factors into account. The SOS framework is based on a system approach and was developed by combining evidence synthesis and expert consensus. The present study conducted a Bayesian network analysis to investigate and map the interdependencies between factors associated with SB through the life-course from large scale empirical data.
Data from the Eurobarometer survey (80.2, 2013) that included the International physical activity questionnaire (IPAQ) short as well as socio-demographic information and questions on perceived environment, health, and psychosocial information were enriched with macro-level data from the Eurostat database. Overall, 33 factors were identified aligned to the SOS-framework to represent six clusters on the individual or regional level: 1) physical health and wellbeing, 2) social and cultural context, 3) built and natural environment, 4) psychology and behaviour, 5) institutional and home settings, 6) policy and economics. A Bayesian network analysis was conducted to investigate conditional associations among all factors and to determine their importance within these networks. Bayesian networks were estimated for the complete (23,865 EU-citizens with complete data) sample and for sex- and four age-specific subgroups. Distance and centrality were calculated to determine importance of factors within each network around SB.
In the young (15-25), adult (26-44), and middle-aged (45-64) groups occupational level was directly associated with SB for both, men and women. Consistently, social class and educational level were indirectly associated within male adult groups, while in women factors of the family context were indirectly associated with SB. Only in older adults, factors of the built environment were relevant with regard to SB, while factors of the home and institutional settings were less important compared to younger age groups.
Factors of the home and institutional settings as well as the social and cultural context were found to be important in the network of associations around SB supporting the priority for future research in these clusters. Particularly, occupational status was found to be the main driver of SB through the life-course. Investigating conditional associations by Bayesian networks gave a better understanding of the complex interplay of factors being associated with SB. This may provide detailed insights in the mechanisms behind the burden of SB to effectively inform policy makers for detailed intervention planning. However, considering the complexity of the issue, there is need for a more comprehensive system of data collection including objective measures of sedentary time.
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Insufficient physical activity (PA) in children is considered one of the major contributors to obesity and cardiometabolic complications later in life. Although regular exercise may contribute to ...disease prevention and health promotion, reliable early biomarkers are required to objectively discern people performing low PA from those who exercise enough. Here, we aimed to identify potential transcript-based biomarkers through the analysis of a whole-genome microarray in peripheral blood cells (PBC) from physically less active (n = 10) comparing with more active (n = 10) children. A set of genes differentially expressed (p < 0.01, Limma test) in less physically active children were identified, including the down-regulation of genes related to cardiometabolic benefits and improved skeletal function (KLB, NOX4, and SYPL2), and the up-regulation of genes whose elevated expression levels are associated with metabolic complications (IRX5, UBD, and MGP). The analysis of the enriched pathways significantly affected by PA levels were those associated with protein catabolism, skeletal morphogenesis, and wound healing, among others, which may suggest a differential impact of low PA on these processes. Microarray analysis comparing children according to their usual PA has revealed potential PBC transcript-based biomarkers that may be useful in early discerning children expending high sedentary time and its associated negative consequences.
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Childhood obesity is a complex disorder that appears to be influenced by an interacting system of many factors. Taking this complexity into account, we aim to investigate the causal structure ...underlying childhood obesity. Our focus is on identifying potential early, direct or indirect, causes of obesity which may be promising targets for prevention strategies. Using a causal discovery algorithm, we estimate a cohort causal graph (CCG) over the life course from childhood to adolescence. We adapt a popular method, the so-called PC-algorithm, to deal with missing values by multiple imputation, with mixed discrete and continuous variables, and that takes background knowledge such as the time-structure of cohort data into account. The algorithm is then applied to learn the causal structure among 51 variables including obesity, early life factors, diet, lifestyle, insulin resistance, puberty stage and cultural background of 5112 children from the European IDEFICS/I.Family cohort across three waves (2007-2014). The robustness of the learned causal structure is addressed in a series of alternative and sensitivity analyses; in particular, we use bootstrap resamples to assess the stability of aspects of the learned CCG. Our results suggest some but only indirect possible causal paths from early modifiable risk factors, such as audio-visual media consumption and physical activity, to obesity (measured by age- and sex-adjusted BMI z-scores) 6 years later.
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Differential expression analysis is usually adjusted for variation. However, most studies that examined the expression variability (EV) have used computations affected by low expression levels and ...did not examine healthy tissue. This study aims to calculate and characterize an unbiased EV in primary fibroblasts of childhood cancer survivors and cancer-free controls (N0) in response to ionizing radiation.
Human skin fibroblasts of 52 donors with a first primary neoplasm in childhood (N1), 52 donors with at least one second primary neoplasm (N2 +), as well as 52 N0 were obtained from the KiKme case-control study and exposed to a high (2 Gray) and a low dose (0.05 Gray) of X-rays and sham- irradiation (0 Gray). Genes were then classified as hypo-, non-, or hyper-variable per donor group and radiation treatment, and then examined for over-represented functional signatures.
We found 22 genes with considerable EV differences between donor groups, of which 11 genes were associated with response to ionizing radiation, stress, and DNA repair. The largest number of genes exclusive to one donor group and variability classification combination were all detected in N0: hypo-variable genes after 0 Gray (n = 49), 0.05 Gray (n = 41), and 2 Gray (n = 38), as well as hyper-variable genes after any dose (n = 43). While after 2 Gray positive regulation of cell cycle was hypo-variable in N0, (regulation of) fibroblast proliferation was over-represented in hyper-variable genes of N1 and N2+. In N2+, 30 genes were uniquely classified as hyper-variable after the low dose and were associated with the ERK1/ERK2 cascade. For N1, no exclusive gene sets with functions related to the radiation response were detected in our data.
N2+ showed high degrees of variability in pathways for the cell fate decision after genotoxic insults that may lead to the transfer and multiplication of DNA-damage via proliferation, where apoptosis and removal of the damaged genome would have been appropriate. Such a deficiency could potentially lead to a higher vulnerability towards side effects of exposure to high doses of ionizing radiation, but following low-dose applications employed in diagnostics, as well.
The use of accelerometers to objectively measure physical activity (PA) has become the most preferred method of choice in recent years. Traditionally, cutpoints are used to assign impulse counts ...recorded by the devices to sedentary and activity ranges. Here, hidden Markov models (HMM) are used to improve the cutpoint method to achieve a more accurate identification of the sequence of modes of PA.
1,000 days of labeled accelerometer data have been simulated. For the simulated data the actual sedentary behavior and activity range of each count is known. The cutpoint method is compared with HMMs based on the Poisson distribution (HMMPois), the generalized Poisson distribution (HMMGenPois) and the Gaussian distribution (HMMGauss) with regard to misclassification rate (MCR), bout detection, detection of the number of activities performed during the day and runtime.
The cutpoint method had a misclassification rate (MCR) of 11% followed by HMMPois with 8%, HMMGenPois with 3% and HMMGauss having the best MCR with less than 2%. HMMGauss detected the correct number of bouts in 12.8% of the days, HMMGenPois in 16.1%, HMMPois and the cutpoint method in none. HMMGenPois identified the correct number of activities in 61.3% of the days, whereas HMMGauss only in 26.8%. HMMPois did not identify the correct number at all and seemed to overestimate the number of activities. Runtime varied between 0.01 seconds (cutpoint), 2.0 minutes (HMMGauss) and 14.2 minutes (HMMGenPois).
Using simulated data, HMM-based methods were superior in activity classification when compared to the traditional cutpoint method and seem to be appropriate to model accelerometer data. Of the HMM-based methods, HMMGauss seemed to be the most appropriate choice to assess real-life accelerometer data.
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Background
Improved treatments for childhood cancer result in a growing number of long-term childhood cancer survivors (CCS). The diagnosis and the prevalence of comorbidities may, however, influence ...their lifestyle later in life. Nonetheless, little is known about differences in late effects between CCS of a first primary neoplasm (FPN) in childhood and subsequent second primary neoplasms (SPN) and their impact on lifestyle. Therefore, we aim to investigate associations between the occurrence of FPN or SPN and various diseases and lifestyle in the later life of CCS.
Methods
CCS of SPN (n=101) or FPN (n=340) and cancer-free controls (n=150) were matched by age and sex, and CCS additionally by year and entity of FPN. All participants completed a self-administered questionnaire on anthropometric and socio-economic factors, medical history, health status, and lifestyle. Mean time between FPN diagnosis and interview was 27.3 years for SPN and 26.2 years for FPN CCS. To confirm results from others and to generate new hypotheses on late effects of childhood cancer as well as CCS´ lifestyles, generalized linear mixed models were applied.
Results
CCS were found to suffer more likely from diseases compared to cancer-free controls. In detail, associations with cancer status were observed for hypercholesterinemia and thyroid diseases. Moreover, CCS were more likely to take regular medication compared to controls. A similar association was observed for CCS of SPN compared to CCS of FPN. In contrast to controls, CCS rarely exercise more than 5 hours per week, consumed fewer soft and alcoholic drinks, and were less likely to be current, former, or passive smokers. Additionally, they were less likely overweight or obese. All other exploratory analyses performed on cardiovascular, chronic lung, inflammatory bone, allergic, and infectious diseases, as well as on a calculated health-score revealed no association with tumor status.
Conclusion
CCS were more affected by pathologic conditions and may consequently take more medication, particularly among CCS of SPN. The observed higher disease burden is likely related to the received cancer therapy. To reduce the burden of long-term adverse health effects in CCS, improving cancer therapies should therefore be in focus of research in this area.
Childhood cancer survivors (CCS) are at particularly high risk for therapy-related late sequelae, with secondary primary neoplasms (SPN) being the most detrimental. Since there is no standardized ...questionnaire for retrospective assessment of associations between prior cancer treatments and late health effects, we developed a self-administered questionnaire and validated it in a cohort of CCS.
CCS of a first primary neoplasm (FPN, N=340) only or with a subsequent SPN (N=101) were asked whether they had received cancer therapies. Self-reports were compared to participants' medical records on cancer therapies from hospitals and clinical studies (N=242). Cohen's Kappa (κ) was used to measure their agreement and logistic regression was used to identify factors influencing the concordance. Associations between exposure to cancer therapies and late health effects (overweight/obesity, diseases of the lipid metabolism and the thyroid gland, cardiovascular diseases, occurrence of SPN) were analyzed in all participants by applying generalized linear mixed models to calculate odds ratios (OR) and 95% confidence intervals (95%CI).
For CCS of SPN, a perfect agreement was found between self-reports and medical records for chemotherapy (CT, κ=1.0) while the accordance for radiotherapy (RT) was lower but still substantial (κ=0.8). For the CCS of FPN the accordance was less precise (CT: κ=0.7, RT: κ=0.3). Cancer status, tumors of the central nervous system, sex, age at recruitment, vocational training, follow-up time, and comorbidities had no impact on agreement. CCS with exposure to CT were found to be less often overweight or obese compared to those without CT (OR=0.6 (95%CI 0.39; 0.91)). However, they were found to suffer more likely from thyroid diseases excluding thyroid cancers (OR=9.91 (95%CI 4.0; 24.57)) and hypercholesterolemia (OR=4.45 (95%CI 1.5; 13.23)). All other analyses did not show an association.
Our new questionnaire proved reliable for retrospective assessment of exposure to CT and RT in CCS of SPN. For the CCS of FPN, self-reported RT was very imprecise and should not be used for further analyses. We revealed an association between late health outcomes occurring as hypercholesterolemia and thyroid diseases, excluding thyroid cancer, and the use of CT for the treatment of childhood cancer.
Nearly 10 years ago, the World Health Organization reported the increasing prevalence of overweight and obesity worldwide as a challenge for public health due to the associated adverse consequences. ...Epidemiological studies established a firm relationship between an elevated body mass index and chronic conditions such as diabetes, dyslipidemia, hypertension, heart disease, non-alcoholic fatty liver disease, and some types of cancer. Omic studies demonstrated that microRNA (miRNA) profile changes in tissues correlate with a number of diseases, including obesity. Recent studies showed a remarkable stability of miRNAs also in blood, emphasizing their potential as theranostic agents for a variety of disorders and conditions. A number of miRNAs enriched in homeostasis of obesity and metabolic disorders have been characterized in previous researches.
This work was finalized to investigate the differential circulating miRNAs signature in early childhood obesity. Our cross-sectional study analyzed the signature of circulating miRNAs in plasma samples of normal weight (
= 159) and overweight/obese (
= 149) children and adolescents participating to the I.Family study, an EC-funded study finalized to investigate the etiology of overweight, obesity and related disorders and the determinants of food choice, lifestyle, and related health outcomes in children and adolescents of eight European countries (www.ifamilystudy.eu).
Differences in miRNA signature with respect to anthropometric and biochemical variables were analyzed. A high degree of variability in levels of circulating miRNAs was identified among children from different countries, in line with recent reports supporting the hypothesis that these molecules are likewise affected by environmental and lifestyle factors. A panel of miRNAs differentially expressed in overweight/low-grade obesity children was characterized (miR-551a and miR-501-5p resulted upregulated; miR-10b-5p, miR-191-3p, miR-215-5p, and miR-874-3p resulted downregulated). ROC curves were also constructed for experimentally confirmed miRNAs. Single miRNAs generally exhibited low AUC values with the highest values for miR-874-3p and miR-501-5p which in combination provided an interesting value (AUC = 0.782). Pearson's analysis confirmed that miR-10b-5p, miR-215-5p, miR-501-5p, miR-551a, and miR-874-3p significantly correlated with BMI
-score. Molecular interactions of obesity-associated miRNAs were also predicted by bioinformatics tools.
Our work showed that several circulating miRNAs are differentially represented in overweight/low-grade obesity children and adolescents. Although causal pathways cannot be firmly inferred, it is conceivable that circulating miRNAs may be new biomarkers of early childhood obesity.
ISRCTN, ISRCTN62310987. Registered 23/02/2018 - Retrospectively registered.
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