Integration of segmented regression analysis with weighted gene correlation network analysis identifies genes whose expression is remodeled throughout physiological aging in mouse tissues.
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ABSTRACT:
SUBMITTER: Ferreira M
PROVIDER: S-EPMC8351669 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:High-throughput expression profiling experiments with ordered conditions (e.g. time-course or spatial-course) are becoming more common for studying detailed differentiation processes or spatial patterns. Identifying dynamic changes at both the individual gene and whole transcriptome level can provide important insights about genes, pathways, and critical time points. RESULTS:We present an R package, Trendy, which utilizes segmented regression models to simultaneously characterize each gene's expression pattern and summarize overall dynamic activity in ordered condition experiments. For each gene, Trendy finds the optimal segmented regression model and provides the location and direction of dynamic changes in expression. We demonstrate the utility of Trendy to provide biologically relevant results on both microarray and RNA-sequencing (RNA-seq) datasets. CONCLUSIONS:Trendy is a flexible R package which characterizes gene-specific expression patterns and summarizes changes of global dynamics over ordered conditions. Trendy is freely available on Bioconductor with a full vignette at https://bioconductor.org/packages/release/bioc/html/Trendy.html .
| S-EPMC6192113 | biostudies-literature
Project description:Studies of the health effects of the microbiome often measure overall associations by using diversity metrics, and individual taxa associations in separate analyses, but do not consider the correlated relationships between taxa in the microbiome. In this study, we applied random subset weighted quantile sum regression with repeated holdouts (WQSRSRH), a mixture method successfully applied to ‘omic data to account for relationships between many predictors, to processed amplicon sequencing data from the Human Microbiome Project. We simulated a binary variable associated with 20 operational taxonomic units (OTUs). WQSRSRH was used to test for the association between the microbiome and the simulated variable, adjusted for sex, and sensitivity and specificity were calculated. The WQSRSRH method was also compared to other standard methods for microbiome analysis. The method was further illustrated using real data from the Growth and Obesity Cohort in Chile to assess the association between the gut microbiome and body mass index. In the analysis with simulated data, WQSRSRH predicted the correct directionality of association between the microbiome and the simulated variable, with an average sensitivity and specificity of 75% and 70%, respectively, in identifying the 20 associated OTUs. WQSRSRH performed better than all other comparison methods. In the illustration analysis of the gut microbiome and obesity, the WQSRSRH analysis identified an inverse association between body mass index and the gut microbe mixture, identifying Bacteroides, Clostridium, Prevotella, and Ruminococcus as important genera in the negative association. The application of WQSRSRH to the microbiome allows for analysis of the mixture effect of all the taxa in the microbiome, while simultaneously identifying the most important to the mixture, and allowing for covariate adjustment. It outperformed other methods when using simulated data, and in analysis with real data found results consistent with other study findings.
| S-EPMC9819204 | biostudies-literature
Project description:IntroductionAnemia among children aged 6-59 months remains a major public health problem in low-and high-income countries including Ethiopia. Anemia is associated with significant consequences on the health of children such as under-five morbidity and mortality, increased risk of infection, and poor academic performance. The prevalence of anemia in Ethiopia has varied across areas. Therefore, this study aimed to investigate the geographic weighted regression analysis of anemia and its associated factors among children aged 6-59 months in Ethiopia.MethodsThis study was based on the 2016 Ethiopian Demographic and Health Survey (EDHS) data. A total weighted sample of 8482 children aged 6-59 months was included. For the spatial analysis, Arc-GIS version 10.7 and SaTScan version 9.6 statistical software were used. Spatial regression was done to identify factors associated with the hotspots of anemia and model comparison was based on adjusted R2 and Corrected Akaike Information Criteria (AICc). For the associated factors, the multilevel robust Poisson regression was fitted since the prevalence of anemia was greater than 10%. Variables with a p-value < 0.2 in the bi-variable analysis were considered for the multivariable analysis. In the multivariable multilevel robust Poisson regression analysis, the adjusted prevalence ratio with the 95% confidence interval was reported to declare the statistical significance and strength of association.ResultsThe prevalence of anemia among children aged 6-59 months was 57.56% (95%CI: 56.50%, 58.61%) with significant spatial variation across regions in Ethiopia. The significant hot spot areas of anemia among children aged 6-59 months were detected in the central, west, and east Afar, Somali, Dire Dawa, Harari, and northwest Gambella regions. Mothers who had anemia, a child aged 23-59 months, mothers aged 15-19 years, and coming from a household with a poorer or poorest household were significant predictors of the spatial variations of anemia among children aged 6-59 months. In the multilevel robust Poisson analysis, born to mothers aged 30-39 (APR = 0.84, 95% CI: 0.76, 0.92) and 40-49 years (APR = 0.73, 95% CI: 0.65, 0.83), mothers who didn't have formal education (APR = 1.10, 95% CI: 1.00, 1.20), Children in the poorest household wealth index (APR = 1.17, 95% CI: 1.06, 1.29), being 4-6 (APR = 1.08, 95% CI: 1.02, 1.13) and above 6 order of birth (APR = 1.15, 95% CI: 1.07, 1.23), children born to anemic mothers (APR = 1.24, 95% CI: 1.19, 1.29), children aged 24-59 months (APR = 0.70, 95% CI: 0.68, 0.73), stunted children (APR = 1.09, 95% CI: 1.04, 1.13) and underweight children (APR = 1.07, 95% CI: 1.03, 1.13) were significantly associated with anemia among children aged 6-59 months.Conclusion and recommendationAnemia is still a public health problem for children in Ethiopia. Residing in a geographic area where a high proportion of children born to mothers aged 15-19 years, a child aged 6-23 months, coming from a household with poorer or poorest wealth index, and mothers with anemia increased the risk of experiencing anemia among children aged 6-59 months. Maternal education, maternal age, child age, household wealth, stunting, underweight, birth order, and maternal anemia were significant predictors of anemia among children. The detailed map of anemia hot spots among children aged 6-59 months and its predictors could assist program planners and decision-makers to design targeted public health interventions.
| S-EPMC8568114 | biostudies-literature
Project description:Functional linear regression models are effectively used in gene-based association analysis of complex traits. These models combine information about individual genetic variants, taking into account their positions and reducing the influence of noise and/or observation errors. To increase the power of methods, where several differently informative components are combined, weights are introduced to give the advantage to more informative components. Allele-specific weights have been introduced to collapsing and kernel-based approaches to gene-based association analysis. Here we have for the first time introduced weights to functional linear regression models adapted for both independent and family samples. Using data simulated on the basis of GAW17 genotypes and weights defined by allele frequencies via the beta distribution, we demonstrated that type I errors correspond to declared values and that increasing the weights of causal variants allows the power of functional linear models to be increased. We applied the new method to real data on blood pressure from the ORCADES sample. Five of the six known genes with P < 0.1 in at least one analysis had lower P values with weighted models. Moreover, we found an association between diastolic blood pressure and the VMP1 gene (P = 8.18×10-6), when we used a weighted functional model. For this gene, the unweighted functional and weighted kernel-based models had P = 0.004 and 0.006, respectively. The new method has been implemented in the program package FREGAT, which is freely available at https://cran.r-project.org/web/packages/FREGAT/index.html.
| S-EPMC5757938 | biostudies-literature
Project description:To evaluate readout-segmented echoplanar (rsEPI) diffusion weighted imaging (DWI) for multiparametric (mp) magnetic resonance imaging (MRI) of the prostate compared to the established single-shot echoplanar imaging (ssEPI) sequence.One hundred ten consecutive patients with clinical suspicion of prostate cancer underwent mp prostate MRI using both, the ssEPI and the rsEPI DWI sequence. For an objective assessment, delineation of the prostate shape on both DWI sequences was compared to T2-weighted images by measuring organ diameters. Apparent diffusion coefficient (ADC) values, image contrast and contrast-to-noise ratio (CNR) were compared between the 2 sequences on a region-of-interest-based analysis. Diagnostic accuracy for quantitative ADC-values was calculated. Histopathology from MRI/ultrasound fusion-guided biopsy was used as reference standard. For a subjective assessment, 2 independent readers visually assessed image quality of both sequences using Likert-scales.Delineation of the prostate shape was more accurate with rsEPI compared to ssEPI. ADC values in target lesions were not significantly different but significantly higher in the surrounding normal prostatic tissue of the transition zone. CNR was comparable between ssEPI and rsEPI. Sensitivity and specificity were good for both sequences with 84/84% and 82/73% with a Youden selected cut-off of ADC = 0.971*10 mm/s for rsEPI and 1.017*10 mm/s for ssEPI. Anatomic artifacts were significantly less and SNR was lower on rsEPI compared to ssEPI in the subjective analysis.Delineation of the prostate shape was more accurate with rsEPI DWI than with ssEPI DWI with less anatomic artifacts and higher subjective SNR and image quality on rsEPI DW images. Diagnostic ability of quantitative ADC-values was not significantly different between the 2 sequences. Thus, rsEPI DWI might be more suitable for prostate MRI with regard to MRI-guided targeted biopsy and therapy planning.
| S-EPMC6709253 | biostudies-literature
Project description:We used next-generation RNA sequencing (RNA-Seq) technology on the whole transcriptome to identify genes whose expression is consistently affected by obesity across multiple arteries. Specifically, we examined transcriptional profiles of the iliac artery as well as the feed artery, first, second, and third branch order arterioles in the soleus, gastrocnemius, and diaphragm muscles from obese Otsuka Long-Evans Tokushima Fatty (OLETF) and lean Long-Evans Tokushima Otsuka (LETO) rats. Within the gastrocnemius and soleus muscles, the number of genes differentially expressed with obesity tended to increase with increasing branch order arteriole number (i.e., decreasing size of the artery). This trend was opposite in the diaphragm. We found a total of 15 genes that were consistently upregulated with obesity (MIS18A, CTRB1, FAM151B, FOLR2, PXMP4, OAS1B, SREBF2, KLRA17, SLC25A44, SNX10, SLFN3, MEF2BNB, IRF7, RAD23A, LGALS3BP) and five genes that were consistently downregulated with obesity (C2, GOLGA7, RIN3, PCP4, CYP2E1). A small fraction (∼9%) of the genes affected by obesity was modulated across all arteries examined. In conclusion, the present study identifies a select number of genes (i.e., 20 genes) whose expression is consistently altered throughout the arterial network in response to obesity and provides further insight into the heterogeneous vascular effects of obesity. Although there is no known direct function of the majority of 20 genes related to vascular health, the obesity-associated upregulation of SREBF2, LGALS3BP, IRF7, and FOLR2 across all arteries is suggestive of an unfavorable vascular phenotypic alteration with obesity. These data may serve as an important resource for identifying novel therapeutic targets against obesity-related vascular complications.
| S-EPMC4233283 | biostudies-literature
Project description:BACKGROUND:Hand, foot and mouth disease (HFMD) is a common infectious disease whose mechanism of transmission continues to remain a puzzle for researchers. The measurement and prediction of the HFMD incidence can be combined to improve the estimation accuracy, and provide a novel perspective to explore the spatiotemporal patterns and determinant factors of an HFMD epidemic. METHODS:In this study, we collected weekly HFMD incidence reports for a total of 138 districts in Shandong province, China, from May 2008 to March 2009. A Kalman filter was integrated with geographically weighted regression (GWR) to estimate the HFMD incidence. Spatiotemporal variation characteristics were explored and potential risk regions were identified, along with quantitatively evaluating the influence of meteorological and socioeconomic factors on the HFMD incidence. RESULTS:The results showed that the average error covariance of the estimated HFMD incidence by district was reduced from 0.3841 to 0.1846 compared to the measured incidence, indicating an overall improvement of over 50% in error reduction. Furthermore, three specific categories of potential risk regions of HFMD epidemics in Shandong were identified by the filter processing, with manifest filtering oscillations in the initial, local and long-term periods, respectively. Amongst meteorological and socioeconomic factors, the temperature and number of hospital beds per capita, respectively, were recognized as the dominant determinants that influence HFMD incidence variation. CONCLUSIONS:The estimation accuracy of the HFMD incidence can be significantly improved by integrating a Kalman filter with GWR and the integration is effective for exploring spatiotemporal patterns and determinants of an HFMD epidemic. Our findings could help establish more accurate HFMD prevention and control strategies in Shandong. The present study demonstrates a novel approach to exploring spatiotemporal patterns and determinant factors of HFMD epidemics, and it can be easily extended to other regions and other infectious diseases similar to HFMD.
| S-EPMC7146977 | biostudies-literature
Project description:Detecting the temporally and spatially varying correlations is important to understand the biological and disease systems. Here we proposed a geographically weighted temporally correlated logistic regression (GWTCLR) model to identify such dynamic correlation of predictors on binomial outcome data, by incorporating spatial and temporal information for joint inference. The local likelihood method is adopted to estimate the spatial relationship, while the smoothing method is employed to estimate the temporal variation. We present the construction and implementation of GWTCLR and the study of the asymptotic properties of the proposed estimator. Simulation studies were conducted to evaluate the robustness of the proposed model. GWTCLR was applied on real epidemiologic data to study the climatic determinants of human seasonal influenza epidemics. Our method obtained results largely consistent with previous studies but also revealed certain spatial and temporal varying patterns that were unobservable by previous models and methods.
| S-EPMC5780421 | biostudies-literature
Project description:ObjectivesAchieving national health equity is currently a pressing issue. Large regional variations in the health determinants are observed. Depression, one of the most common mental disorders, has large variations in incidence among different populations, and thus must be regionally analyzed. The present study aimed at analyzing regional disparities in depressive symptoms and identifying the health determinants that require regional interventions.MethodsUsing health indicators of depression in the Korea Community Health Survey 2011 and 2013, the Moran's I was calculated for each variable to assess spatial autocorrelation, and a validated geographically weighted regression analysis using ArcGIS version 10.1 of different domains: health behavior, morbidity, and the social and physical environments were created, and the final model included a combination of significant variables in these models.ResultsIn the health behavior domain, the weekly breakfast intake frequency of 1-2 times was the most significantly correlated with depression in all regions, followed by exposure to secondhand smoke and the level of perceived stress in some regions. In the morbidity domain, the rate of lifetime diagnosis of myocardial infarction was the most significantly correlated with depression. In the social and physical environment domain, the trust environment within the local community was highly correlated with depression, showing that lower the level of trust, higher was the level of depression. A final model was constructed and analyzed using highly influential variables from each domain. The models were divided into two groups according to the significance of correlation of each variable with the experience of depression symptoms.ConclusionsThe indicators of the regional health status are significantly associated with the incidence of depressive symptoms within a region. The significance of this correlation varied across regions.
| S-EPMC5668667 | biostudies-literature
Project description:Primary aldosteronism is present in ?10% of hypertensives. We previously performed a microarray assay on aldosterone-producing adenomas and their paired zona glomerulosa and fasciculata. Confirmation of top genes validated the study design and functional experiments of zona glomerulosa selective genes established the role of the encoded proteins in aldosterone regulation. In this study, we further analyzed our microarray data using AmiGO 2 for gene ontology enrichment and Ingenuity Pathway Analysis to identify potential biological processes and canonical pathways involved in pathological and physiological aldosterone regulation. Genes differentially regulated in aldosterone-producing adenoma and zona glomerulosa were associated with steroid metabolic processes gene ontology terms. Terms related to the Wnt signaling pathway were enriched in zona glomerulosa only. Ingenuity Pathway Analysis showed "NRF2-mediated oxidative stress response pathway" and "LPS (lipopolysaccharide)/IL-1 (interleukin-1)-mediated inhibition of RXR (retinoid X receptor) function" were affected in both aldosterone-producing adenoma and zona glomerulosa with associated genes having up to 21- and 8-fold differences, respectively. Comparing KCNJ5-mutant aldosterone-producing adenoma, zona glomerulosa, and zona fasciculata samples with wild-type samples, 138, 56, and 59 genes were differentially expressed, respectively (fold-change >2; P<0.05). ACSS3, encoding the enzyme that synthesizes acetyl-CoA, was the top gene upregulated in KCNJ5-mutant aldosterone-producing adenoma compared with wild-type. NEFM, a gene highly upregulated in zona glomerulosa, was upregulated in KCNJ5 wild-type aldosterone-producing adenomas. NR4A2, the transcription factor for aldosterone synthase, was highly expressed in zona fasciculata adjacent to a KCNJ5-mutant aldosterone-producing adenoma. Further interrogation of these genes and pathways could potentially provide further insights into the pathology of primary aldosteronism.
| S-EPMC5100803 | biostudies-literature