SURGE: uncovering context-specific genetic-regulation of gene expression from single-cell RNA sequencing using latent-factor models

Genetic regulation of gene expression is a complex process, with genetic effects known to vary across cellular contexts such as cell types and environmental conditions. We developed SURGE, a method for unsupervised discovery of context-specific expression quantitative trait loci (eQTLs) from single-cell transcriptomic data. This allows discovery of the contexts or cell types modulating genetic regulation without prior knowledge. Applied to peripheral blood single-cell eQTL data, SURGE contexts capture continuous representations of distinct cell types and groupings of biologically related cell types. We demonstrate the disease-relevance of SURGE context-specific eQTLs using colocalization analysis and stratified LD-score regression.

GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership

Parts-based representations, such as non-negative matrix factorization and topic modeling, have been used to identify structure from single-cell sequencing data sets, in particular structure that is not as well captured by clustering or other dimensionality reduction methods. However, interpreting the individual parts remains a challenge. To address this challenge, we extend methods for differential expression analysis by allowing cells to have partial membership to multiple groups. We call this grade of membership differential expression (GoM DE). We illustrate the benefits of GoM DE for annotating topics identified in several single-cell RNA-seq and ATAC-seq data sets.

GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership

Parts-based representations, such as non-negative matrix factorization and topic modeling, have been used to identify structure from single-cell sequencing data sets, in particular structure that is not as well captured by clustering or other dimensionality reduction methods. However, interpreting the individual parts remains a challenge. To address this challenge, we extend methods for differential expression analysis by allowing cells to have partial membership to multiple groups. We call this grade of membership differential expression (GoM DE). We illustrate the benefits of GoM DE for annotating topics identified in several single-cell RNA-seq and ATAC-seq data sets.

Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity

Uncovering the functional impact of genetic variation on gene expression is important in understanding tissue biology and the pathogenesis of complex traits. Despite large efforts to map expression quantitative trait loci (eQTLs) across many human tissues, our ability to translate those findings to understanding human disease has been incomplete, and the majority of disease loci are not explained by association with expression of a target gene. Cell-type specificity and the presence of multiple independent causal variants for many eQTLs are potential confounders contributing to the apparent discrepancy with disease loci. In this study, we investigate the tissue specificity of genetic effects on gene expression and the overlap with disease loci while considering the presence of multiple causal variants within and across tissues. We find evidence of pervasive tissue specificity of eQTLs, often masked by linkage disequilibrium that misleads traditional meta-analytic approaches. We propose CAFEH (colocalization and fine-mapping in the presence of allelic heterogeneity), a Bayesian method that integrates genetic association data across multiple traits, incorporating linkage disequilibrium to identify causal variants. CAFEH outperforms previous approaches in colocalization and fine-mapping. Using CAFEH, we show that genes with highly tissue-specific genetic effects are under greater selection, enriched in differentiation and developmental processes, and more likely to be involved in human disease. Last, we demonstrate that CAFEH can efficiently leverage the widespread allelic heterogeneity in genetic regulation of gene expression to prioritize the target tissue in genome-wide association complex trait loci, thereby improving our ability to interpret complex trait genetics.

Cardiovascular disease management in people with diabetes outside North America and Western Europe in 2006 and 2015

AIM

Optimal treatment of cardiovascular disease is essential to decrease mortality among people with diabetes, but information is limited on how actual treatment relates to guidelines. We analysed changes in therapeutic approaches to anti-hypertensive and lipid-lowering medications in people with Type 2 diabetes from 2006 and 2015.

METHODS

Summary data from clinical services in seven countries outside North America and Western Europe were collected for 39 684 people. Each site summarized individual-level data from outpatient medical records for 2006 and 2015. Data included: demographic information, blood pressure (BP), total cholesterol levels and percentage of people taking statins, anti-hypertensive medication (angiotensin-converting enzyme inhibitors, calcium channel blockers, angiotensin II receptor blockers, thiazide diuretics) and antiplatelet drugs.

RESULTS

From 2006 to 2015, mean cholesterol levels decreased in six of eight sites (range: -0.5 to -0.2), whereas the proportion with BP levels > 140/90 mmHg increased in seven of eight sites. Decreases in cholesterol paralleled increases in statin use (range: 3.1 to 47.0 percentage points). Overall, utilization of anti-hypertensive medication did not change. However, there was an increase in the use of angiotensin II receptor blockers and a decrease in angiotensin-converting enzyme inhibitors. The percentage of individuals receiving calcium channel blockers and aspirin remained unchanged.

CONCLUSIONS

Our findings indicate that control of cholesterol levels improved and coincided with increased use of statins. The percentage of people with BP > 140/90 mmHg was higher in 2015 than in 2006. Hypertension treatment shifted from using angiotensin-converting enzyme inhibitors to angiotensin II receptor blockers. Despite the potentially greater tolerability of angiotensin II receptor blockers, there was no associated improvement in BP levels.

Dynamic genetic regulation of gene expression during cellular differentiation

Genetic regulation of gene expression is dynamic, as transcription can change during cell differentiation and across cell types. We mapped expression quantitative trait loci (eQTLs) throughout differentiation to elucidate the dynamics of genetic effects on cell type-specific gene expression. We generated time-series RNA sequencing data, capturing 16 time points during the differentiation of induced pluripotent stem cells to cardiomyocytes, in 19 human cell lines. We identified hundreds of dynamic eQTLs that change over time, with enrichment in enhancers of relevant cell types. We also found nonlinear dynamic eQTLs, which affect only intermediate stages of differentiation and cannot be found by using data from mature tissues. These fleeting genetic associations with gene regulation may explain some of the components of complex traits and disease. We highlight one example of a nonlinear eQTL that is associated with body mass index.

[Primary squamous cell carcinoma of the breast. Report of three cases]

Primary squamous cell carcinoma of the breast is a rare neoplasma included in metaplastic breast cancer. The histogenesis remains unknown. Clinical and radiological appearances are not specific. Nodal involvement is rare and hormones receptors are negative. The treatment is based on surgery associated to radiation therapy and chemotherapy. Prognosis seems to be similar to others breast carcinoma. We report three cases of primary squamous cell carcinoma of the breast recruited at National Institute of Oncology with review of the literature.