Biology subjects

Tworoger, S.

Publications and source records attributed to Tworoger, S..

6 recordsLinked to original sources

bioRxiv2024

Patterns of extreme outlier RNA expression in population data reveal sporadic over-activation of genes with co-regulated modules in subsets of individuals

BackgroundMost RNA-Seq datasets harbor genes with extreme expression levels in some samples. Such extreme outliers are usually treated as technical errors and are removed from the data before further statistical analysis. Here we focus on the patterns of such outlier expression. ResultsOur study is based on multiple datasets, including outbred and inbred mice, humans from the GTEx dataset, different Drosophila species and single-nuclei sequencing experiments from human brain tissues. All show comparable general patterns of outlier expression. Different individuals can harbor very different numbers of outliers, with some individuals showing extreme numbers in only one out of several organs of the respective individual. A three-generation family analysis in mice was generated and analyzed for the inheritance of outlier patterns. We find that most extreme over-expressions are not inherited, i.e., appear to be sporadically generated in individuals. Still, co-regulated outlier expressions are identifiable in various gene groups, and some correspond with known pathways. Among the co-regulated genes with extreme outlier expression are also the hormone genes prolactin and growth hormone, both in mice and humans, for which we include also protein level data from human cohorts. ConclusionsWe show that outlier patterns of gene expression are a biological reality occurring universally across tissues and species. Most of the outlier expressions are spontaneous and not inherited. We discuss the possibility that the outlier patterns reflect edge of chaos effects that are expected for systems of non-linear interactions and feedback loops, such as gene regulatory networks.

genomics↗

bioRxiv2024

Quantifiable Blood TCR Repertoire Components Associated with Immune Aging

T cell senescence results in decayed adaptive immune protection in older individuals, with decreased or increased abundance of certain T cell phenotypic subpopulations. However, no study has linked aging to the dynamic changes of T cell clones. Through a newly develop computational framework, Repertoire Functional Units (RFU), we investigated over 6,500 TCR repertoire sequencing samples from multiple human cohorts. Our analysis identified age-associated RFUs repeatedly and consistently across different cohorts. Quantification of RFU decreases with aging revealed accelerated loss under immunosuppressive conditions. Systematic analysis of age-associated RFUs in clinical samples manifested a potential link between these RFUs and improved clinical outcomes during acute viral infections, such as lower ICU admission and reduced risk of developing complications. Finally, our investigation of bone-marrow transplantation patients indicated a secondary expansion of the age-associated clones upon receiving stem cells from younger donors. Together, our results suggest the existence of certain clones or a TCR clock that could reflect the immune functions in aging populations.

immunology↗

bioRxiv2023

Quantifiable TCR repertoire changes in pre-diagnostic blood specimens among high-grade ovarian cancer patients

High grade serous ovarian cancer (HGOC) is a major cause of death in women. Early detection of HGOC usually leads to a cure, yet it remains a clinical challenge with over 90% HGOCs diagnosed at advanced stages. This is mainly because conventional biomarkers are not sensitive to detect the microscopic yet metastatic early HGOC lesions. In this study, we sequenced the blood T cell receptor (TCR) repertoires of 466 ovarian cancer patients and controls, and systematically investigated the immune repertoire signatures in HGOCs. We observed quantifiable changes of selected TCRs in HGOCs that are reproducible in multiple independent cohorts. Importantly, these changes are stronger during stage I. Using pre-diagnostic patient blood samples from the Nurses Health Study, we confirmed that HGOC signals can be detected in the blood TCR repertoire up to 4 years proceeding conventional diagnosis. Our findings may provide the basis of an immune-based HGOC early detection criterion. Statement of significanceWe made an unprecedented discovery that a strong and quantifiable change in the blood TCR repertoire occurs 4 to 2 years before high grade ovarian cancers could be diagnosed with conventional clinical tests. This finding might be useful to develop novel screening biomarkers to detect early-stage ovarian cancers.

immunology↗

bioRxiv2023

Breast Density Analysis of Digital Breast Tomosynthesis

We evaluated an automated percentage of breast density (BD) technique (PDa) with digital breast tomosynthesis (DBT) data. The approach is based on the wavelet expansion followed by analyzing signal dependent noise. Several measures were investigated as risk factors: normalized volumetric; total dense volume; average of the DBT slices (slice-mean); a two-dimensional (2D) metric applied to the synthetic images; and the mean and standard deviations of the pixel values. Volumetric measures were derived theoretically, and PDa was modeled as a function of compressed breast thickness. An alternative method for constructing synthetic 2D mammograms was investigated using the volume results. A matched case-control study (n = 426 pairs) was analyzed. Conditional logistic regression modeling, controlling body mass index and ethnicity, was used to estimate odds ratios (ORs) for each measure with 95% confidence intervals provided parenthetically. There were several significant findings: volumetric measure [OR = 1.43 (1.18, 1.72)], which produced an identical OR as the slice-mean measure as predicted; [OR =1.44 (1.18, 1.75)] when applied to the synthetic images; and mean of the pixel values (volume or 2D synthetic) [ORs [~] 1.31 (1.09, 1.57)]. PDa was modeled as 2nd degree polynomial (concave-down): its maximum value occurred at 0.41x(compressed breast thickness), which was similar across case-control groups, and was significant from this position [OR = 1.47 (1.21, 1.78)]. A standardized 2D synthetic image was produced, where each pixel value represents the percentage of BD above its location. The significant findings indicate the validity of the technique. Derivations supported by empirical analyses produced a new synthetic 2D standardized image technique. Ancillary to the objectives, the results provide evidence for understanding the percentage of BD measure applied to 2D mammograms. Notwithstanding the findings, the study design provides a template for investigating other measures such as texture.

biophysics↗

bioRxiv2022

Gut feelings: Associations of emotions and emotion regulation with the gut microbiome in women

Accumulating evidence suggests that positive and negative emotions, as well as emotion regulation processes, influence the onset and the progression of multiple human diseases. However, the underlying mechanisms connecting these emotion-related factors with physical health are not fully understood. Recent work linking the gut microbiome with both mental and physical health suggests it may be a potential pathway. Yet, its association with emotions and emotion regulation are understudied. In this study, we examined whether positive and negative emotions, as well as two emotion regulation strategies (i.e., cognitive reappraisal and suppression), were associated with the diversity, overall structure, and specific species/pathways of the gut microbiome in 206 healthy women. We found that the alpha diversity was negatively associated with suppression. Moreover, using multivariate analysis, we found that positive emotions were inversely associated with the relative abundance of Firmicutes bacterium CAG 94 and Ruminococcaceae bacterium D16, while negative emotions were directly related to relative abundance of these same species. Moreover, we found associations of emotions and emotion regulation with microbial metabolic pathways. For example, negative emotions were inversely related to biosynthesis of pantothenate, coenzyme A, and adenosine. Taken together, our findings offer human evidence supporting linkages of emotions and related regulatory processes with the gut microbiome. These findings highlight the critical importance of incorporating the human gut microbiome in our understanding of emotion-related factors and their associations with physical health.

microbiology↗

bioRxiv2016

A comprehensive survey of genetic variation in 20,691 subjects from four large cohorts

The Nurses Health Study (NHS), Nurses Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)).\n\nWe observed the strongest BMI association for the FTO SNP rs55872725 ({beta}=0.45, p=3.48x10-22), and using a significance level of p=0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR=2.17, 95% CI: 1.79-2.63, p=2.70x10-15), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes.

epidemiology↗