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PubMed2006

Association of educational level with inflammatory markers in the Framingham Offspring Study.

Socioeconomic position consistently predicts coronary heart disease; however, the biologic mechanisms that may mediate this association are not well understood. The objective of this study was to determine whether socioeconomic position (measured as educational level) is associated with inflammatory risk factors for coronary heart disease, including C-reactive protein, interleukin-6, soluble intercellular adhesion molecule-1, monocyte chemoattractant protein-1, and P-selectin. The study sample included 2,729 participants (53.4% women; mean age, 62 +/- 10 years) from the US Framingham Offspring Study cohort who attended examination cycles 3 (1984-1987) and 7 (1998-2001) and provided educational attainment data. Inflammatory markers were measured in fasting serum samples. Multivariable linear regression analyses were performed, adjusting for potential confounders including age, sex, and clinical risk factors. In age- and sex-adjusted analyses, educational attainment was significantly inversely associated with C-reactive protein (p < 0.0001), interleukin-6 (p < 0.0001), soluble intercellular adhesion molecule-1 (p < 0.0001), and monocyte chemoattractant protein-1 (p = 0.0004). After further adjustment for clinical risk factors, educational level remained significantly associated with C-reactive protein (p = 0.0002), soluble intercellular adhesion molecule-1 (p = 0.01), and monocyte chemoattractant protein-1 (p = 0.01). In conclusion, educational attainment is associated with inflammatory risk factors for coronary heart disease. The association provides evidence suggestive of a biologic pathway by which socioeconomic position may predispose to coronary heart disease.

Biomarkers↗

PubMed2006

Plasma sphingomyelin and subclinical atherosclerosis: findings from the multi-ethnic study of atherosclerosis.

Plasma sphingomyelin has been shown to be an independent risk factor for coronary heart disease, but the relation of plasma sphingomyelin to earlier, subclinical atherosclerotic disease has not been reported. The authors examined the association between plasma sphingomyelin and three measures of subclinical cardiovascular disease (carotid intimal-medial wall thickness, ankle-arm blood pressure index, and Agatston coronary artery calcium score) among 6,814 middle-aged, asymptomatic adults in the Multi-Ethnic Study of Atherosclerosis, which was initiated in 2000. The sphingomyelin level was positively correlated with lipids and the Framingham risk score (p < 0.01 for both), and the mean level was higher in women than men (50 (standard deviation (SD), 16) vs. 45 (SD, 15) mg/dl) (p < 0.01) and higher in never versus current smokers (49 (SD, 16) vs. 45 (SD, 17) mg/dl) (p < 0.01). Women with sphingomyelin levels of 60 or more mg/dl had more severe subclinical disease by all three measures than did the referent group with sphingomyelin levels of 39 or less mg/dl, although associations were not significant after multivariate adjustment for standard cardiovascular disease risk factors. Men with sphingomyelin levels of 60 or more mg/dl versus those with sphingomyelin levels of 39 or less mg/dl had higher calcium scores (135 vs. 99 Agatston units) (p = 0.01). These observations are consistent with the hypothesis that plasma sphingomyelin is in the biologic pathway that mediates the risk for subclinical disease attributable to standard cardiovascular disease risk factors.

Aged↗

PubMed2002

Recognizing features that are dissimilar in male and female breast cancer: expression of p21Waf1 and p27Kip1 using an immunohistochemical assay.

BACKGROUND: Male breast cancer (MBC) is an uncommon disease, and most of our current knowledge of its biology, natural history and treatment has been extrapolated from data on the disease in women. Information is still needed on the molecular biological properties of male breast tumors and their predictive relevance. Kinase inhibitor proteins (KIPs) p27Kip1 and p21Waf1 negatively regulate cell cycle progression by preventing the passage of cycling cells from G1 to S phase through G1 cyclin-dependent kinase activation. No studies exist on the role of these factors in male breast carcinoma. PATIENTS AND METHODS: We have retrospectively analyzed the immunohistochemical expression of p21Waf1 and p27Kip1 protein in 27 primary MBC and in 101 female breast cancers (FBC) treated at the European Institute of Oncology between 1997 and 2000. We also assessed sex hormone receptors status, p53, bcl-2 and c-erb-B2 protein expression, and Ki-67 labeling index. RESULTS: We observed a statistically significant difference in the immunostaining of KIPs p27Kip1 and p21Waf1 in male patients compared with females. Expression of p21Waf1 was observed in 19 of the 27 (70.3%) primary MBCs versus 29 of 101 FBC (29%). Fourteen of 22 negative c-erbB-2 MBCs cases expressed immunostaining for p21Waf1 (P = 0.05). p27Kip1 immunoreactivity was been detected in 26 of 27 (96.2%) male breast patients versus 39 of 101 FBC (39.3%) (P = 0.000). Highly positive staining for P27Kip1 was found in 21 of 25 androgen receptor-expressing samples. Higher levels of p27Kip1 were expressed in bcl-2-positive samples (17 of 20). Eighteen of 22 c-erbB-2-negative cases were strongly immunoreactive for p27Kip1. CONCLUSIONS: p27Kip1 and p21Waf1 immunoreactivity is higher in MBCs compared with FBCs. The findings of higher p27Kip1 and p21Waf1 immunostaining may be an additional predictive factor in MBC. These biological features could be possible indicators for different biological pathways in the tumorigenesis of MBCs.

Adult↗

PubMed2026

Large-scale pleiotropic analysis across cancers reveals shared genetic mechanisms and identifies novel functional genes.

Pleiotropic genetic loci have been increasingly reported in cancer, and identifying genetic variants with pleiotropic associations can reveal shared biological pathways influencing multiple cancers. Using summary statistics from genome-wide association studies for 37 cancer types (N = 433 836), we identified extensive genome-wide and local genetic correlations among cancers. Through pairwise pleiotropic analysis, we identified 75 243 significant pleiotropic single nucleotide polymorphisms (SNPs) across 372 cancer pairs, among which 3472 were lead SNPs with potential regulatory functions. Using FUMA and MAGMA, we identified 2527 pleiotropic risk loci and 4272 candidate pleiotropic genes. Notably, genes such as TERT (5p15.33), POU5F1B (8q24.21), and FANCA (16q24.3) exhibited widespread pleiotropy across multiple cancer types. Pathway enrichment analysis highlighted the critical roles of pigment synthesis, metabolism, and apoptosis in skin-related cancers, while cross-cancer enrichment analysis emphasized pathways related to apoptosis, chromatin structure, and intermediate filaments. We also identified 33 novel functional genes harboring previously unreported cancer risk variants. Drug-gene interaction analysis revealed several repositionable FDA-approved drugs. Importantly, drug sensitivity assays demonstrated that bosutinib and cobimetinib exhibited promising therapeutic potential in breast cancer cell lines. Finally, we developed the PleioCancer database (https://gonglab.hzau.edu.cn/PleioCancer/), providing a comprehensive resource for cancer pleiotropy research. These findings have important implications for carcinogenesis cancer, prevention and treatment.

Humans↗

PubMed2026

shinyDeepGxP: a user-friendly R shiny app for predicting surface protein abundance from scRNA-seq expression using deep learning in blood cells.

MOTIVATION: Understanding accurate immune cell heterogeneity and function in single-cell datasets requires access to protein-level information, which is often unavailable due to experimental limitations. RESULTS: We present shinyDeepGxP, an interactive web application featuring our deep learning model, DeepGxP, for predicting surface protein abundance from single-cell RNA-sequencing (scRNA-seq) data. This platform makes DeepGxP accessible to researchers without programming skills. Users can upload scRNA-seq count matrices and use "Predict Protein" to predict the abundance of 224 biologically relevant surface proteins. shinyDeepGxP provides visualizations to help identify distinct cell populations based on predicted protein profiles. Moreover, users can choose "Explore Model" to reveal key RNA predictors and their associated biological pathways for each protein. Overall, shinyDeepGxP is a user-friendly, freely available web tool that provides protein-level detail for RNA-only single-cell datasets, enabling multimodal discovery without additional experiments. AVAILABILITY AND IMPLEMENTATION: shinyDeepGxP can be launched on https://shiny.crc.pitt.edu/deepgxp/.

Journal Article↗

PubMed2003

GARBAN: genomic analysis and rapid biological annotation of cDNA microarray and proteomic data.

SUMMARY: Genomic Analysis and Rapid Biological ANnotation (GARBAN) is a new tool that provides an integrated framework to analyze simultaneously and compare multiple data sets derived from microarray or proteomic experiments. It carries out automated classifications of genes or proteins according to the criteria of the Gene Ontology Consortium at a level of depth defined by the user. Additionally, it performs clustering analysis of all sets based on functional categories or on differential expression levels. GARBAN also provides graphical representations of the biological pathways in which all the genes/proteins participate. AVAILABILITY: http://garban.tecnun.es.

Algorithms↗

PubMed2004

A mixture model-based strategy for selecting sets of genes in multiclass response microarray experiments.

MOTIVATION: Multiclass response (MCR) experiments are those in which there are more than two classes to be compared. In these experiments, though the null hypothesis is simple, there are typically many patterns of gene expression changes across the different classes that led to complex alternatives. In this paper, we propose a new strategy for selecting genes in MCR that is based on a flexible mixture model for the marginal distribution of a modified F-statistic. Using this model, false positive and negative discovery rates can be estimated and combined to produce a rule for selecting a subset of genes. Moreover, the method proposed allows calculation of these rates for any predefined subset of genes. RESULTS: We illustrate the performance our approach using simulated datasets and a real breast cancer microarray dataset. In this latter study, we investigate predefined subset of genes and point out interesting differences between three distinct biological pathways. AVAILABILITY: http://www.bgx.org.uk/software.html

Algorithms↗

PubMed2005

BioContrasts: extracting and exploiting protein-protein contrastive relations from biomedical literature.

MOTIVATION: Contrasts are useful conceptual vehicles for learning processes and exploratory research of the unknown. For example, contrastive information between proteins can reveal what similarities, divergences and relations there are of the two proteins, leading to invaluable insights for better understanding about the proteins. Such contrastive information are found to be reported in the biomedical literature. However, there have been no reported attempts in current biomedical text mining work that systematically extract and present such useful contrastive information from the literature for exploitation. RESULTS: Our BioContrasts system extracts protein-protein contrastive information from MEDLINE abstracts and presents the information to biologists in a web-application for exploitation. Contrastive information are identified in the text abstracts with contrastive negation patterns such as 'A but not B'. A total of 799 169 pairs of contrastive expressions were successfully extracted from 2.5 million MEDLINE abstracts. Using grounding of contrastive protein names to Swiss-Prot entries, we were able to produce 41 471 pieces of contrasts between Swiss-Prot protein entries. These contrastive pieces of information are then presented via a user-friendly interactive web portal that can be exploited for applications such as the refinement of biological pathways. AVAILABILITY: BioContrasts can be accessed at http://biocontrasts.i2r.a-star.edu.sg. It is also mirrored at http://biocontrasts.biopathway.org. SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.

Artificial Intelligence↗

PubMed2025

Meta-analysis models with group structure for pleiotropy detection at gene and variant level using summary statistics from multiple datasets.

Genome-wide association studies (GWASs) have highlighted the importance of pleiotropy in human diseases, where one gene can impact 2 or more unrelated traits. Examining shared genetic risk factors across multiple diseases can enhance our understanding of these conditions by pinpointing new genes and biological pathways involved. Furthermore, with an increasing wealth of GWAS summary statistics available to the scientific community, leveraging these findings across multiple phenotypes could unveil novel pleiotropic associations. Existing selection methods examine pleiotropic associations one by one at a scale of either the genetic variant or the gene, and thus cannot consider all the genetic information at the same time. To address this limitation, we propose a new approach called MPSG (Meta-analysis model adapted for Pleiotropy Selection with Group structure). This method performs a penalized multivariate meta-analysis method adapted for pleiotropy and takes into account the group structure information nested in the data to select relevant variants and genes (or pathways) from all the genetic information. To do so, we implemented an alternating direction method of multipliers algorithm. We compared the performance of the method with other benchmark meta-analysis approaches such as GCPBayes, PLACO, and ASSET by considering as inputs different kinds of summary statistics. We provide an application of our method to the identification of potential pleiotropic genes between breast and thyroid cancers.

Humans↗

PubMed2005

Gene-environment interactions between alcohol drinking and the MTHFR C677T polymorphism impact on esophageal cancer risk: results of a case-control study in Japan.

Folate takes part in two biological pathways involved in DNA methylation and synthesis, and a potential protective influence of this nutrient chemical against carcinogenicity has been recognized in several sites, including the esophagus. Therefore, the functional polymorphisms in genes encoding folate metabolizing enzymes, MTHFR C677T and MTR A2756G, might be suspected of impacting on esophageal cancer risk. We therefore conducted a matched case-control study of 165 esophageal cancer cases and 495 non-cancer controls to clarify associations among folate intake, MTHFR C677T and MTR A2756G polymorphisms, and esophageal cancer risk. Gene-environment interactions between the two polymorphisms, and drinking and smoking were also evaluated. Folate consumption and MTHFR 677TT were associated with a non-significant tendency for decreased risk while the MTR genotypes did not show any links in themselves; further, when analysis was limited to heavy drinkers, the MTHFR TT genotype significantly decreased esophageal cancer risk [odds ratio (OR) = 0.27, 95% confidence interval (CI), 0.09-0.76]. The OR for the gene-environment interaction between heavy drinking and the 677TT genotype in the case-only design was 0.31 (95% CI, 0.10-0.94), indicating risk with heavy drinking to be 69% decreased in individuals harboring the 677TT genotype. We failed to find any significant interaction between either of the polymorphisms and smoking.

Adenocarcinoma↗

PubMed2005

Modulation of gene expression and DNA adduct formation in HepG2 cells by polycyclic aromatic hydrocarbons with different carcinogenic potencies.

Polycyclic aromatic hydrocarbons (PAHs) can occur in relatively high concentrations in the air, and many PAHs are known or suspected carcinogens. In order to better understand differences in carcinogenic potency between PAHs, we investigated modulation of gene expression in human HepG2 cells after 6 h incubation with varying doses of benzo[a]pyrene (B[a]P), benzo[b]fluoranthene (B[b]F), fluoranthene (FA), dibenzo[a,h]anthracene (DB[a,h]A), 1-methylphenanthrene (1-MPA) or dibenzo[a,l]pyrene (DB[a,l]P), by using cDNA microarrays containing 600 toxicologically relevant genes. Furthermore, DNA adduct levels induced by the compounds were assessed with (32)P-post-labeling, and carcinogenic potency was determined by literature study. All tested PAHs, except 1-MPA, induced gene expression changes in HepG2 cells, although generally no dose-response relationship could be detected. Clustering and principal component analysis showed that gene expression changes were compound specific, since for each compound all concentrations grouped together. Furthermore, it showed that the six PAHs can be divided into three groups, first FA and 1-MPA, second B[a]P, B[b]F and DB[a,h]A, and third DB[a,l]P. This grouping corresponds with the carcinogenic potencies of the individual compounds. Many of the modulated genes are involved in biological pathways like apoptosis, cholesterol biosynthesis and fatty acid synthesis. The order of DNA adduct levels induced by the PAHs was: B[a]P >> DB[a,l]P > B[b]F > DB[a,h]A > 1-MPA >/= FA. When comparing the expression change of individual genes with DNA adduct levels, carcinogenic potency or Ah-receptor antagonicity (the last two were taken from literature), several highly correlated genes were found, of which CYP1A1, PRKCA, SLC22A3, NFKB1A, CYP1A2 and CYP2D6 correlated with all parameters. Our data indicate that discrimination of high and low carcinogenic PAHs by gene expression profiling is feasible. Also, the carcinogenic PAHs induce several pathways that were not affected by the least carcinogenic PAHs.

Carcinoma, Hepatocellular↗

PubMed1997

Oncogenic potential of TAR RNA binding protein TRBP and its regulatory interaction with RNA-dependent protein kinase PKR.

TAR RNA binding protein (TRBP) belongs to an RNA binding protein family that includes the double-stranded RNA-activated protein kinase (PKR), Drosophila Staufen and Xenopus xlrbpa. One member of this family, PKR, is a serine/threonine kinase which has anti-viral and anti-proliferative effects. In this study we show that TRBP is a cellular down-regulator of PKR function. Assaying expression from an infectious HIV-1 molecular clone, we found that PKR inhibited viral protein synthesis and that over-expression of TRBP effectively countered this inhibition. In intracellular and in cell-free assays we show that TRBP directly inhibits PKR autophosphorylation through an RNA binding-independent pathway. Biologically, TRBP serves a growth-promoting role; cells that overexpress TRBP exhibit transformed phenotypes. Our results demonstrate the oncogenic potential of TRBP and are consistent with the notion that intracellular PKR function contributes physiologically towards regulating cellular proliferation.

3T3 Cells↗

PubMed2026

Using deep learning models as a genetic architecture for the simulation of breeding schemes.

In several simulation studies, long-term selection led to the rapid depletion of genetic variance. These outcomes differ from real-life observations that we aim to replicate, thereby highlighting a fundamental limitation of current classical quantitative genetic simulation models. Deep learning (DL) models have demonstrated promising results in capturing complex interactions essential for maintaining genetic variance; thus, we hypothesize that DL-based genetic simulation models may preserve more genetic variance than classical models, because the biological pathways underlying complex traits exhibit interactions that classical models ignore. The primary objective of this study was to introduce alternative DL-based genetic simulation models and compare them with classical genetic simulation models in terms of their retention of additive genetic variance under truncation selection in a simulated full-sib pig breeding scheme using real haplotypes as founders. After 20 generations of directional truncation selection, the classical models (A, ADAA, and ADAAADDD) retained between 55% and 64% of their initial additive genetic variance. In contrast, while the DL_simple model lost all its additive variance, the DL medium retained 92% to 98% of its additive variance, and the DL_complex model's initial additive variance increased by 296% to 314%. This paper introduces DL-based genetic simulation models and concludes that their ability to retain additive genetic variance depends on the models' architectural complexity. When sufficiently complex, DL-based models exhibit greater retention of additive genetic variance because they intrinsically capture epistatic interactions that are converted into additive variance, as selection progresses, thus, affirming the role of non-additive genetic effects in maintaining long-term genetic variation.

Deep Learning↗

PubMed2025

A genome-wide association study identified 10 novel genomic loci associated with intrinsic capacity.

BACKGROUND: Intrinsic capacity (IC) is a multidimensional concept within the World Health Organization framework for healthy aging. It refers to the composite of an individual's physical and mental capacities that enable them to maintain well-being, functional ability, and engagement in valued activities throughout life. While substantial evidence supports the biological basis of IC and its subdomains, the extent to which genetic factors influence IC remains largely unexplored, with no studies currently available. METHODS: Using datasets from the UK Biobank (UKB; N = 44 631) and the Canadian Longitudinal Study on Aging (CLSA; N = 13 085), we implemented the restricted maximum likelihood method to estimate SNP-based heritability (h2snp), followed by a Genome-Wide Association Study (GWAS) to identify genetic variants associated with IC, and post-GWAS analyses to pinpoint biological implications. RESULTS: The h2snp for IC was estimated at 25.2% in UKB and 19.5% in CLSA. Our GWAS identified 38 independent SNPs for IC across 10 genomic loci and 4289 candidate SNPs, mapped to 197 genes. Post-GWAS analysis revealed the role of these genes in cellular processes such as cell proliferation, immune function, metabolism, and neurodegeneration, with high expression in muscle, heart, brain, adipose, and nerve tissues. Of the 52 traits tested, 23 showed significant genetic correlations with IC, and a higher genetic loading for IC was associated with higher IC scores. CONCLUSIONS: Overall, this study provides comprehensive evidence on the genetic architecture of IC, identifying novel genetic variants and biological pathways, advancing our current knowledge and laying the foundation for ongoing and future research on healthy aging.

Adult↗

PubMed2002

Genetic modifiers of vision and hearing.

The identification of 'disease genes' and the mutations within them has greatly enhanced our understanding of normal function in the eye and ear. At the same time, it has become clear that these single-gene mutations must reside in a permissive genetic background for a disease phenotype to manifest. Segregating background genes can also modify the age of onset, rate of progression or severity of these diseases. These background genes that interact with the disease mutation and that are responsible for the specific phenotypes observed are commonly called genetic modifiers. Identification of these modifier genes may define the biological pathways that lead from the primary genetic defect to the aberrant phenotype. Once the identities of modifier genes that suppress vision or hearing loss become known, the door opens to new potential therapeutic targets, since these modifier genes may be more amenable to treatment than the primary mutant gene.

Animals↗

PubMed2003

Extracellular proteases and their inhibitors in genetic diseases of the central nervous system.

Cumulative evidence has shown that a delicate balance between serine proteases and their inhibitors is crucial for normal functioning of several biological pathways. The importance of proteases and their inhibitors is well documented in several human diseases. Among them, the best documented are hemophilia B, a genetic deficiency of the serine protease coagulation factor IX and serpinophathies. Alpha-1-antitrypsin deficiency (MIM 107400), is associated with early-onset emphysema and liver disease, while hereditary angioedema (HANE; MIM 106100) is caused by mutations in the C1 inhibitor, a serpin involved in the regulation of the complement cascade. Recently, two human genetic diseases of the central nervous system have been related to mutations in components of extracellular proteolytic systems. Here, we review the recent advances in this field.

Central Nervous System Diseases↗

PubMed2003

Role of psychosocial and nutritional stress on poor pregnancy outcome.

Epidemiological evidence suggests that maternal psychosocial stress, strenuous physical activity and fasting are independent risk factors for preterm birth and low birth weight. Data from clinical studies consistently demonstrate that women in preterm labor have significantly elevated levels of corticotropin-releasing hormone compared with age-matched control subjects. Because production of corticotropin-releasing hormone appears to be stress sensitive, this neuropeptide may play a critical role in the physiological mediation among stressful experiences, work stress and fasting and risk of preterm birth. In addition to the direct effect of elevated corticotropin-releasing hormone on the initiation of labor, it may have an immunomodulatory effect such that women with high levels of corticotropin-releasing hormone may be more susceptible to infection or the pathological consequences of infection. We review the epidemiological data linking maternal stress, physical stain and fasting to preterm birth and low birth weight and review the plausible biological pathways through which these exposures may increase risk of preterm birth. The timing of these exposures is considered important. Future research and clinical programs addressing these exposures must consider assessments and interventions before pregnancy.

Corticotropin-Releasing Hormone↗

PubMed2006

Treatment effects of maternal micronutrient supplementation vary by percentiles of the birth weight distribution in rural Nepal.

Certain antenatal micronutrient supplements increased birth weight by 40-70 g in rural Nepal. The effect was estimated by calculating the mean difference in birth weight between control and treatment groups, which assumes a constant treatment effect across the birth weight distribution. By estimating differences (and CI) in birth weight between treatment and control groups as a nonlinear, smooth function of the percentiles of the birth weight distribution, we can examine whether the shape of the birth weight distribution for a treatment group is different from that of the control group. Supplementation groups were folic acid, folic acid and iron, folic acid and iron and zinc, and a multiple micronutrient supplement all with vitamin A, compared with the control group of vitamin A alone. The shape of the birth weight distribution in the multiple micronutrient group was the same as that of the control group; however, the location of the distribution had shifted. The folic acid and iron group had fewer infants in the lower tail of its distribution but a similar proportion in the upper tail compared with the control group. The biologic pathways affecting intrauterine growth may vary by micronutrients such that some may confer a benefit among the most vulnerable infants, whereas others may have a more constant effect across the birth weight distribution. Future analytic approaches to estimating benefits of maternal supplementation on birth weight should examine whether there is a constant or variable treatment effect across the distribution of birth weight.

Adolescent↗