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At least 19 recordsLinked to original sources
PubMed1989

Are special treatment facilities for female alcoholics needed? A controlled 2-year follow-up study from a specialized female unit (EWA) versus a mixed male/female treatment facility.

Women with alcohol problems constitute an increasing number of patients in medical service. Do they need special care? How should the treatment program be designed? The specialized female Karolinska Project for Early Treatment of Women with Alcohol Addiction (EWA) unit at the Karolinska Hospital in Stockholm, Sweden, was opened in 1981. The aim of the project is to reach women in an early stage of alcohol dependence behavior and to develop treatment programs specific to the needs of females alone. In order to investigate the value of such a specialized female unit a controlled 2-year follow-up study was carried out including 200 women. The probands were treated in the female only EWA-unit, whereas the controls were placed in the care of traditional mixed-sex alcoholism treatment centers. The 2-year follow-up study showed a more successful rehabilitation regarding alcohol consumption and social adjustment for the women treated in the specialized female unit (EWA). Improvement was noted also for the controls but to a lesser extent. Probably one of the most important achievements of a specialized female unit, such as EWA, is to attract women to come for help earlier.

Adolescent↗
PubMed2026

EWAS in a polyphenol dense, DNA methylation-targeted, controlled diet and lifestyle study.

BACKGROUND: Dietary and lifestyle factors can influence DNA methylation patterns. We previously reported epigenetic age attenuation following a controlled study using an 8-week polyphenol-dense, DNA methylation-targeted diet and lifestyle intervention in healthy males (Methylation Diet and Lifestyle Study), with phytonutrient/polyphenol-rich foods (green tea, oolong tea, curcumin, garlic, and berries) being most predictive of this effect. METHODS: Here we conducted an epigenome-wide association study (EWAS) in 38 participants from the Methylation Diet and Lifestyle Study. The intervention included a dietary pattern intentionally rich in substrate and cofactor nutrients for methylation pathways, and components known to alter DNA-methyltransferase (DNMT) enzyme activity. In line with prior EWAS studies with small sample sizes where FDR-significant findings are unlikely, we used pre-specified nominal P-value thresholds (0.001, 0.0001) for the exploratory analyses. RESULTS: At P < 0.001 (unadjusted), 676 differentially methylated loci (DML) were identified in the intervention group versus 286 in controls. At P < 0.0001 (unadjusted), 50 DML were identified in the intervention group compared to 13 in controls. Fifteen DML were in transcription start site-proximal regions of genes including those involved in zinc homeostasis and nutrient sensing, development and pluripotency, proteostasis and genome stability, tumor suppression, and synaptic function. A group-by-time interaction analysis identified 70 intervention-specific DML at P < 0.0001, with nominal enrichment including autophagy, mTOR signaling, and chromatin remodeling pathways. A regional DMR analysis identified 128 within-group and 129 interaction-specific DMRs. DMR functional enrichment analyses revealed convergent nominal associations with lipid metabolism (alpha-linolenic acid, lipoic acid, biosynthesis of unsaturated fatty acids, PPAR signaling, cholesterol homeostasis), central energy metabolism (TCA cycle, glycolysis/gluconeogenesis, pentose phosphate, pyruvate), and nutrient sensing (PI3K-Akt, mTOR, AMPK, autophagy as well as other pathways). As expected for the limited cohort size and short intervention duration, none of the single CpG findings or enrichment analyses survived multiple test correction and are therefore considered exploratory and hypothesis-generating only. CONCLUSION: This EWAS identified a larger number of nominally changing CpGs in the intervention group compared to controls as well as biologically coherent methylation changes. These findings provide mechanistic hypotheses for previously observed epigenetic age attenuation. Replication in larger cohorts, longer intervention durations, and functional validation remain essential.

DNA methylation↗
PubMed2025

Detection of cell-type-specific differentially methylated regions in epigenome-wide association studies.

MOTIVATION: DNA methylation at cytosine-phosphate-guanine (CpG) sites is one of the most important epigenetic markers. Therefore, epidemiologists are interested in investigating DNA methylation in large cohorts through epigenome-wide association studies (EWAS). However, the observed EWAS data are bulk data with signals aggregated from distinct cell types. Deconvolution of cell-type-specific signals from EWAS data is challenging because phenotypes can affect both cell-type proportions and cell-type-specific methylation levels. Recently, there has been active research on detecting cell-type-specific risk CpG sites for EWAS data. However, existing methods all assume that the methylation levels of different CpG sites are independent and perform association detection for each CpG site separately. Although these methods significantly improve the detection at the aggregated-level-identifying a CpG site as a risk CpG site as long as it is associated with the phenotype in any cell type, they have low power in detecting cell-type-specific associations for EWAS with typical sample sizes. RESULTS: Here, we develop a new method, Fine-scale inference for Differentially Methylated Regions (FineDMR), to borrow strengths of nearby CpG sites to improve the cell-type-specific association detection. Via a Bayesian hierarchical model built upon Gaussian process functional regression, FineDMR takes advantage of the spatial dependencies between CpG sites. FineDMR can provide cell-type-specific association detection as well as output subject-specific and cell-type-specific methylation profiles for each subject. Simulation studies and real data analysis show that FineDMR substantially improves the power in detecting cell-type-specific associations for EWAS data. AVAILABILITY AND IMPLEMENTATION: FineDMR is freely available at https://github.com/JiaRuofan/Detection-of-Cell-type-specific-DMRs-in-EWAS.

DNA Methylation↗
PubMed1988

Gamma camera radionuclide images: improved contrast with energy-weighted acquisition.

An energy-weighted acquisition (EWA) technique has been developed that utilizes all scintillation events, weighting their contributions depending on their energy, to formulate a radionuclide image. Photopeak events from primary radiation contribute positively; scatter events contribute negatively, providing for scatter subtraction and improved image contrast. EWA is employed with an on-line weighted-acquisition module (WAM) as the data are acquired, rather than as a postprocessing technique. EWA was compared with normal window imaging in patients and in phantoms. For gallium-67 and thallium-201, contrast improved by as much as 40%. A much smaller improvement in contrast was observed with technetium-99m due to its ideal monoenergetic emissions. Single photon emission computed tomographic studies also showed improved contrast and were without artifact. EWA has great promise, and with further development quantitative scatter correction may be possible.

Gallium Radioisotopes↗
PubMed2026

eQTM (expression quantitative trait methylation) Atlas: a comprehensive resource of over 11 million DNA methylation-gene expression associations through across 11 tissues and 4 diseases.

MOTIVATION: Epigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. RESULTS: We developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG- searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. AVAILABILITY AND IMPLEMENTATION: The eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/. The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas.

DNA methylation↗
PubMed2025

Estimating population structure using epigenome-wide methylation data.

INTRODUCTION: In epigenome-wide association analysis (EWAS), unaddressed population stratification often leads to inflation. We aimed to compute methylation population scores (MPSs) that predict genetic principal components (GPCs) using a feature selection and regression approach. METHODS: We used multi-ethnic methylation data (Illumina 450K/EPIC array) from unrelated MESA (n=929), CARDIA (n=1123), JHS (n=1365), ARIC (n=2338), and HCHS/SOL (n=1475) individuals, randomly assigning 85% of participants from each cohort to a training dataset and the remaining 15% to a test dataset. First, we estimated the associations of GPCs with each available CpG methylation site using linear regression within each cohort, adjusting for age, sex, smoking status, race/ethnic background (as a proxy for background information associated with lifestyle and other environmental exposures that may impact methylation), alcohol use status, body mass index, and cell type proportions. We meta-analyzed the associations across cohorts and selected CpG sites with association FDR-adjusted q-value <0.05. We next aggregated individuallevel data across the cohort-specific training datasets, and applied two-stage weighted least squares Lasso regression, with the GPCs as the outcomes and the selected CpG sites as penalized predictors, adjusting for the aforementioned covariates. The developed MPSs are the weighted sum of selected CpG sites from the Lasso. To evaluate the developed MPSs, we constructed them in the test dataset, and compared them with GPCs, and with MPSs constructed based on a previously-published paper. Comparison was based on correlation analysis and data visualization. We demonstrate the use of the MPSs in EWAS. RESULTS: In the test dataset, the MPSs were highly correlated with GPCs, with correlation decreasing, though not monotonically, for later components. Specifically, MPS1 and GPC1 had R2= 0.99, while MPS7 and GPC7 had R2=0.27 (the lowest observed correlation). In data visualization, MPSs had similar patterns as GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups, while outperforming MPC constructed using alternative published methods. MPSs showed comparable performance to GPCs in reducing some of the inflation in EWAS. CONCLUSIONS: Methylation-based population scores provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent. Unlike previous methods based on unsupervised methylation PCA, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations. The weights for each GPCs derived in our study can be applied to generate MPSs in other studies.

Journal Article↗
PubMed1989

Energy-weighted acquisition of scintigraphic images using finite spatial filters.

Energy weighted acquisition (EWA) is a technique for improving image contrast by correcting for some of the blurring effects of Compton scattering within the patient. We outline image formation theory as it applies to energy weighting and present a pre-processing implementation that acquires images with real-number energy-dependent weighting functions of finite spatial extent. The effect of scattered radiation on quantitative accuracy, with and without EWA, is demonstrated with sheet and point sources at various depths. A planar phantom and a clinical 201TI study demonstrate enhanced contrast and edge definition. The performance of EWA in SPECT is shown by 99mTc and 123I phantom studies and a clinical 125I study.

Filtration↗
PubMed2026

Estimating population structure using epigenome-wide methylation data.

Population stratification is one of the source of inflation in epigenome-wide association studies (EWAS) when not properly accounted for. To address this, we developed methylation population scores (MPSs) to predict genetic principal components (GPCs) using a feature selection approach. We used multi-ethnic DNA methylation data from Illumina EPIC arrays across five cohorts, including MESA (n&#xa0;=&#xa0;929), CARDIA (n&#xa0;=&#xa0;1123), JHS (n&#xa0;=&#xa0;1365), ARIC (n&#xa0;=&#xa0;2338), and HCHS/SOL (n&#xa0;=&#xa0;1475), randomly splitting participants into training (85%) and test (15%) sets. Within each cohort, associations between GPCs and CpG sites were estimated using linear regression adjusting for age, sex, smoking and alcohol use, race/ethnicity, body mass index, and cell type proportions, followed by meta-analysis and selection of CpGs with FDR <0.05. We then applied a two-stage weighted least squares Lasso regression to construct MPSs, adjusting for the aforementioned covariates. In the test dataset, MPSs showed strong correlation with GPCs, with R&#xb2; ranging from 0.27 (MPS7 vs. GPC7) to 0.98 (MPS1 vs. GPC1). Visualization demonstrated that MPSs recapitulated the pattern shown by GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups and outperformed methylation-based principal components constructed using alternative published methods. Additionally, MPSs showed comparable performance to GPCs in reducing inflation in EWAS. Overall, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations, and provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent.

Humans↗
PubMedDate not supplied

The changes in regional myocardial surface area during coronary occlusion and reperfusion.

For the analysis of regional myocardial function, the measurement of regional myocardial surface area (RMA) was performed on the epicardial surface of myocardial segment lengths in a direction parallel to the superficial myocardial fibers (SLa) and at right angles to the first (SLb). In eight anesthetized dogs with opened-chests, measurements were done during a 60 s left anterior descending coronary artery occlusion and reperfusion. In the ischemic region, coronary occlusion resulted in dyskinesis in RMA, and the reduction of it during the ejection phase (ERA) decreased significantly at 10 s (p less than 0.05) and thereafter (p less than 0.01). Regional myocardial work (EWA) from the pressure-area loops during the ejection phase also decreased significantly at 10 s (p less than 0.05) and thereafter (p less than 0.01). The end-diastolic RMA (EDRMA) increased significantly at 30 s (p less than 0.01) and thereafter (p less than 0.01). In the non-ischemic region, compensatory changes were shown, namely ERA, EWA and EDRMA, increased significantly during occlusion. After reperfusion, recovery to the control level was prompt, and only EDRMA remained the increased value after 30 s (p less than 0.01). Between SLa and SLb, characteristics differed from each other, which suggested that the directional differences of SLs should be considered when regional myocardial function is assessed from unidirectional SL. The changes in RMA reflect both changes of SLa and SLb during coronary occlusion and reperfusion, and were more marked than each SL. Thus, the usefulness of RMA to assess regional myocardial function was demonstrated during coronary occlusion and reperfusion.

Animals↗