Single-Cell Gene-Regulatory Networks of Advanced Symptomatic Atherosclerosis

BACKGROUND

While our understanding of the single-cell gene expression patterns underlying the transformation of vascular cell types during the progression of atherosclerosis is rapidly improving, the clinical and pathophysiological relevance of these changes remains poorly understood.

METHODS

Single-cell RNA sequencing data generated with SmartSeq2 (≈8000 genes/cell) in nearly 19 000 single cells isolated during atherosclerosis progression in Ldlr-/-Apob100/100 mice with human-like plasma lipoproteins and from humans with asymptomatic and symptomatic carotid plaques was clustered into multiple subtypes. For clinical and pathophysiological context, the advanced-stage and symptomatic subtype clusters were integrated with 135 tissue-specific (atherosclerotic aortic wall, mammary artery, liver, skeletal muscle, and visceral and subcutaneous, fat) gene-regulatory networks (GRNs) inferred from 600 coronary artery disease patients in the STARNET (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task) study.

RESULTS

Advanced stages of atherosclerosis progression and symptomatic carotid plaques were largely characterized by 3 smooth muscle cells (SMCs), and 3 macrophage subtype clusters with extracellular matrix organization/osteogenic (SMC), and M1-type proinflammatory/Trem2-high lipid-associated (macrophage) phenotypes. Integrative analysis of these 6 clusters with STARNET revealed significant enrichments of 3 arterial wall GRNs: GRN33 (macrophage), GRN39 (SMC), and GRN122 (macrophage) with major contributions to coronary artery disease heritability and strong associations with clinical scores of coronary atherosclerosis severity (SYNTAX/Duke scores). The presence and pathophysiological relevance of GRN39 were verified in 5 independent RNAseq data sets obtained from the human coronary and aortic artery, and primary SMCs and by targeting its top-key drivers, FRZB and ALCAM, in cultured human vascular SMCs.

CONCLUSIONS

By identifying and integrating the most gene-rich single-cell subclusters of atherosclerosis to date with a coronary artery disease framework of GRNs, GRN39 was identified and independently validated as being critical for the transformation of contractile SMCs into an osteogenic phenotype promoting advanced-stage, symptomatic atherosclerosis.

Association between bone mineral density and coronary artery calcification: an observational and Mendelian randomization study

Observational studies have reported inconsistent associations between bone mineral density (BMD) and coronary artery calcification (CAC). We examined the observational association of BMD with CAC in two large population-based studies and evaluated the evidence for a potential causal relation between BMD and CAC using polygenic risk scores (PRS), 1- and 2-sample Mendelian randomization (MR) approaches. Our study populations comprised 1414 individuals (mean age 69.9 years, 52.0% women) from the Rotterdam Study and 2233 individuals (mean age 56.5 years, 50.9% women) from the Framingham Heart Study with complete information on CAC and BMD measurements at the total body (TB-), lumbar spine (LS-), and femoral neck (FN-). We used linear regression models to evaluate the observational association between BMD and CAC. Subsequently, we compared the mean CAC across PRSBMD quintile groups at different skeletal sites. In addition, we used the 2-stage least squares regression (2SLS) and the inverse variance weighted (IVW) model as primary methods for 1- and 2-sample MR to test evidence for a potentially causal association. We did not observe robust associations between measured BMD levels and CAC. These results were consistent with a uniform random distribution of mean CAC across PRSBMD quintile groups (p-value >0.05). Moreover, neither 1- nor 2-sample MR supported the possible causal association between BMD and CAC. Our results do not support the contention that lower BMD is (causally) associated with an increased CAC risk. These findings suggest that previously reported epidemiological associations of BMD with CAC are likely explained by unmeasured confounders or shared etiology, rather than by causal pathways underlying both osteoporosis and vascular calcification processes.

Multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci

Genome-wide association studies (GWASs) have identified hundreds of risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWASs, and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotypes to identify quantitative trait loci for expression (eQTLs) and splicing (sQTLs) in coronary arteries from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary artery; 19% exhibited cell-type-specific expression. Colocalization revealed subgroups of eGenes unique to CAD and blood pressure GWAS. Fine-mapping highlighted additional eGenes, including TBX20 and IL5. We also identified sQTLs for 1,690 genes, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing to accurately identify disease-relevant isoform expression. Our work provides a patient-derived coronary artery eQTL resource and exemplifies the need for diverse study populations and multifaceted approaches to characterize gene regulation in disease processes.

Polygenic Risk Score Associates With Atherosclerotic Plaque Characteristics at Autopsy

BACKGROUND

Polygenic risk scores (PRSs) for coronary artery disease (CAD) potentially improve cardiovascular risk prediction. However, their relationship with histopathologic features of CAD has never been examined systematically.

METHODS

From 4327 subjects referred to CVPath by the State of Maryland Office Chief Medical Examiner for sudden death between 1994 and 2015, 2455 cases were randomly selected for genotyping. We generated PRS from 291 known CAD risk loci. Detailed histopathologic examination of the coronary arteries was performed in all subjects. The primary study outcome measurements were histopathologic plaque features determining severity of atherosclerosis, including %stenosis, calcification, thin-cap fibroatheromas, and thrombotic CAD.

RESULTS

After exclusion of cases with insufficient DNA sample quality or with missing data, 954 cases (mean age, 48.8±14.7 years; 75.7% men) remained in the final study cohort. Subjects in the highest PRS quintile exhibited more severe atherosclerosis compared with subjects in the lowest quintile, with greater %stenosis (80.3%±27.0% versus 50.4%±38.7%; adjusted P<0.001) and a higher frequency of calcification (69.6% versus 35.8%; adjusted P=0.004) and thin-cap fibroatheroma (26.7% versus 9.5%; adjusted P=0.007). Even after adjustment for traditional CAD risk factors, subjects within the highest PRS quintile had higher odds of severe atherosclerosis (ie, ≥75% stenosis; adjusted odds ratio, 3.77 [95% CI, 2.10-6.78]; P<0.001) and plaque rupture (adjusted odds ratio, 4.05 [95% CI, 2.26-7.24]; P<0.001). Moreover, subjects within the highest quintile had higher odds of CAD-associated cause of death, especially among those aged ≤50 years (adjusted odds ratio, 4.08 [95% CI, 2.01-8.30]; P<0.001). No statistically significant associations were observed with plaque erosion after adjusting for covariates.

CONCLUSIONS

This is the first autopsy study investigating associations between PRS and atherosclerosis severity at the histopathologic level in subjects with sudden death. Our pathological analysis suggests PRS correlates with plaque burden and features of advanced atherosclerosis and may be useful as a method for CAD risk stratification, especially in younger subjects.

Integrative single-cell meta-analysis reveals disease-relevant vascular cell states and markers in human atherosclerosis

Coronary artery disease (CAD) is characterized by atherosclerotic plaque formation in the arterial wall. CAD progression involves complex interactions and phenotypic plasticity among vascular and immune cell lineages. Single-cell RNA-seq (scRNA-seq) studies have highlighted lineage-specific transcriptomic signatures, but human cell phenotypes remain controversial. Here, we perform an integrated meta-analysis of 22 scRNA-seq libraries to generate a comprehensive map of human atherosclerosis with 118,578 cells. Besides characterizing granular cell-type diversity and communication, we leverage this atlas to provide insights into smooth muscle cell (SMC) modulation. We integrate genome-wide association study data and uncover a critical role for modulated SMC phenotypes in CAD, myocardial infarction, and coronary calcification. Finally, we identify fibromyocyte/fibrochondrogenic SMC markers (LTBP1 and CRTAC1) as proxies of atherosclerosis progression and validate these through omics and spatial imaging analyses. Altogether, we create a unified atlas of human atherosclerosis informing cell state-specific mechanistic and translational studies of cardiovascular diseases.

Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification

Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.

Leukocytes carrying Clonal Hematopoiesis of Indeterminate Potential (CHIP) Mutations invade Human Atherosclerotic Plaques

Background

Leukocyte progenitors derived from clonal hematopoiesis of undetermined potential (CHIP) are associated with increased cardiovascular events. However, the prevalence and functional relevance of CHIP in coronary artery disease (CAD) are unclear, and cells affected by CHIP have not been detected in human atherosclerotic plaques.

Methods

CHIP mutations in blood and tissues were identified by targeted deep-DNA-sequencing (DNAseq: coverage >3,000) and whole-genome-sequencing (WGS: coverage >35). CHIP-mutated leukocytes were visualized in human atherosclerotic plaques by mutaFISH™. Functional relevance of CHIP mutations was studied by RNAseq.

Results

DNAseq of whole blood from 540 deceased CAD patients of the Munich cardIovaScular StudIes biObaNk (MISSION) identified 253 (46.9%) CHIP mutation carriers (mean age 78.3 years). DNAseq on myocardium, atherosclerotic coronary and carotid arteries detected identical CHIP mutations in 18 out of 25 mutation carriers in tissue DNA. MutaFISH™ visualized individual macrophages carrying DNMT3A CHIP mutations in human atherosclerotic plaques. Studying monocyte-derived macrophages from Stockholm-Tartu Atherosclerosis Reverse Networks Engineering Task (STARNET; n=941) by WGS revealed CHIP mutations in 14.2% (mean age 67.1 years). RNAseq of these macrophages revealed that expression patterns in CHIP mutation carriers differed substantially from those of non-carriers. Moreover, patterns were different depending on the underlying mutations, e.g. those carrying TET2 mutations predominantly displayed upregulated inflammatory signaling whereas ASXL1 mutations showed stronger effects on metabolic pathways.

Conclusions

Deep-DNA-sequencing reveals a high prevalence of CHIP mutations in whole blood of CAD patients. CHIP-affected leukocytes invade plaques in human coronary arteries. RNAseq data obtained from macrophages of CHIP-affected patients suggest that pro-atherosclerotic signaling differs depending on the underlying mutations. Further studies are necessary to understand whether specific pathways affected by CHIP mutations may be targeted for personalized treatment.

Polygenic Risk Score Associates with Atherosclerotic Plaque Characteristics at Autopsy

Background

Polygenic risk scores (PRS) for coronary artery disease (CAD) potentially improve cardiovascular risk prediction. However, their relationship with histopathologic features of CAD has never been examined systematically.

Methods

From 4,327 subjects referred to CVPath by the State of Maryland Office Chief Medical Examiner (OCME) for sudden death between 1994 and 2015, 2,455 cases were randomly selected for genotyping. We generated PRS from 291 known CAD risk loci. Detailed histopathologic examination of the coronary arteries was performed in all subjects. The primary study outcome measurements were histopathologic plaque features determining severity of atherosclerosis, including %stenosis, calcification, thin-cap fibroatheromas (TCFA), and thrombotic CAD.

Results

After exclusion of cases with insufficient DNA sample quality or with missing data, 954 cases (mean age 48.8±14.7; 75.7% men) remained in the final study cohort. Subjects in the highest PRS quintile exhibited more severe atherosclerosis compared to subjects in the lowest quintile, with greater %stenosis (80.3%±27.0% vs. 50.4%±38.7%; adjusted p<0.001) and a higher frequency of calcification (69.6% vs. 35.8%; adjusted p=0.004) and TCFAs (26.7% vs. 9.5%; adjusted p=0.007). Even after adjustment for traditional CAD risk factors subjects within the highest PRS quintile had higher odds of severe atherosclerosis (i.e., ≥75% stenosis; adjusted OR 3.77; 95%CI 2.10-6.78; p<0.001) and plaque rupture (adjusted OR 4.05; 95%CI 2.26-7.24; p<0.001). Moreover, subjects within the highest quintile had higher odds of CAD-associated cause of death, especially among those aged 50 years and younger (adjusted OR 4.08; 95%CI 2.01-8.30; p<0.001). No associations were observed with plaque erosion.

Conclusions

This is the first autopsy study investigating associations between PRS and atherosclerosis severity at the histopathologic level in subjects with sudden death. Our pathological analysis suggests PRS correlates with plaque burden and features of advanced atherosclerosis and may be useful as a method for CAD risk stratification, especially in younger subjects.

Highlights

In this autopsy study including 954 subjects within the CVPath Sudden Death Registry, high PRS correlated with plaque burden and atherosclerosis severity.The PRS showed differential associations with plaque rupture and plaque erosion, suggesting different etiologies to these two causes of thrombotic CAD.PRS may be useful for risk stratification, particularly in the young. Further examination of individual risk loci and their association with plaque morphology may help understand molecular mechanisms of atherosclerosis, potentially revealing new therapy targets of CAD.

Graphic Abstract

A polygenic risk score, generated from 291 known CAD risk loci, was assessed in 954 subjects within the CVPath Sudden Death Registry. Histopathologic examination of the coronary arteries was performed in all subjects. Subjects in the highest PRS quintile exhibited more severe atherosclerosis as compared to subjects in the lowest quintile, with a greater plaque burden, more calcification, and a higher frequency of plaque rupture.

Integrative multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci

Genome-wide association studies (GWAS) have identified hundreds of genetic risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWAS and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotype information to identify quantitative trait loci (QTL) for gene expression and splicing in coronary arteries obtained from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary arteries and 19% exhibited cell-type-specific expression. Colocalization analysis with GWAS identified subgroups of eGenes unique to CAD and blood pressure. Fine-mapping highlighted additional eGenes of interest, including TBX20 and IL5 . Splicing (s)QTLs for 1,690 genes were also identified, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing events to accurately identify disease-relevant gene expression. Our work provides the first human coronary artery eQTL resource from a patient sample and exemplifies the necessity of diverse study populations and multi-omic approaches to characterize gene regulation in critical disease processes.

Study Design Overview

Transcriptomic-based clustering of human atherosclerotic plaques identifies subgroups with different underlying biology and clinical presentation

Histopathological studies have revealed key processes of atherosclerotic plaque thrombosis. However, the diversity and complexity of lesion types highlight the need for improved sub-phenotyping. Here we analyze the gene expression profiles of 654 advanced human carotid plaques. The unsupervised, transcriptome-driven clustering revealed five dominant plaque types. These plaque phenotypes were associated with clinical presentation and showed differences in cellular compositions. Validation in coronary segments showed that the molecular signature of these plaques was linked to coronary ischemia. One of the plaque types with the most severe clinical symptoms pointed to both inflammatory and fibrotic cell lineages. Further, we did a preliminary analysis of potential circulating biomarkers that mark the different plaques phenotypes. In conclusion, the definition of the plaque at risk for a thrombotic event can be fine-tuned by in-depth transcriptomic-based phenotyping. These differential plaque phenotypes prove clinically relevant for both carotid and coronary artery plaques and point to distinct underlying biology of symptomatic lesions.

Polygenic risk score associates with atherosclerosis severity at autopsy

Background

Polygenic risk scores (PRS) for coronary artery disease (CAD) are emerging as a potential method to improve cardiovascular risk prediction. Questions remain about their applicability to diverse populations as well as their correlation with coronary histopathology.

Purpose

To assess whether high genetic risk associates with histopathologic coronary plaque morphology.

Methods

We assessed 122 known CAD risk loci in 954 Black and White subjects within our sudden death registry to generate a PRS. The cohort was divided into quintiles according to z-score-standardized PRS, both in a race-stratified fashion and in the pooled sample. Detailed histopathologic examination of the coronary arteries was performed in all subjects.

Results

Subjects in the highest PRS quintile exhibited more severe atherosclerosis compared to subjects in the lowest quintile, with greater mean cross-sectional luminal narrowing (71.5% (95% CI, 66.6%-76.5%) vs. 56.6% (95% CI, 51.1%-62.1%); adjusted p&lt;0.001; Figure 1) and a higher frequency of calcification (adjusted OR 2.19; 95% CI 1.31–3.68; p=0.003) after adjustment for the first 10 principal components, age, sex, and race. Higher z-score-standardized PRS was predictive for the finding of severe atherosclerosis (i.e., ≥75% cross-sectional luminal narrowing) even after additional controlling for traditional CAD risk factors including hypertension, smoking, diabetes mellitus, and hyperlipidemia (adjusted OR 1.39; 95% CI 1.19–1.63; p&lt;0.001; Figure 2). Among Black subjects, higher PRS was associated with higher odds of plaque rupture (adjusted OR 1.31; 95% CI 1.03–1.66; p=0.03) and predicted CAD-associated cause of death among subjects younger than 50 years old (adjusted OR 1.26; 95% CI 1.01–1.58; p=0.04).

Conclusions

This is the first autopsy study investigating associations between PRS and atherosclerotic plaque morphology at a histopathologic level. Our pathological analysis suggests PRS correlates with plaque burden and coronary artery calcification and may be useful as a method for CAD risk stratification, especially in younger subjects.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): R01 HL141425 Leducq Foundation Grant

PlaqView 2.0: A comprehensive web portal for cardiovascular single-cell genomics

Single-cell RNA-seq (scRNA-seq) is a powerful genomics technology to interrogate the cellular composition and behaviors of complex systems. While the number of scRNA-seq datasets and available computational analysis tools have grown exponentially, there are limited systematic data sharing strategies to allow rapid exploration and re-analysis of single-cell datasets, particularly in the cardiovascular field. We previously introduced PlaqView, an open-source web portal for the exploration and analysis of published atherosclerosis single-cell datasets. Now, we introduce PlaqView 2.0 (www.plaqview.com), which provides expanded features and functionalities as well as additional cardiovascular single-cell datasets. We showcase improved PlaqView functionality, backend data processing, user-interface, and capacity. PlaqView brings new or improved tools to explore scRNA-seq data, including gene query, metadata browser, cell identity prediction, ad hoc RNA-trajectory analysis, and drug-gene interaction prediction. PlaqView serves as one of the largest central repositories for cardiovascular single-cell datasets, which now includes data from human aortic aneurysm, gene-specific mouse knockouts, and healthy references. PlaqView 2.0 brings advanced tools and high-performance computing directly to users without the need for any programming knowledge. Lastly, we outline steps to generalize and repurpose PlaqView's framework for single-cell datasets from other fields.

Opportunities and Challenges in Understanding Atherosclerosis by Human Biospecimen Studies

Over the last few years, new high-throughput biotechnologies and bioinformatic methods are revolutionizing our way of deep profiling tissue specimens at the molecular levels. These recent innovations provide opportunities to advance our understanding of atherosclerosis using human lesions aborted during autopsies and cardiac surgeries. Studies on human lesions have been focusing on understanding the relationship between molecules in the lesions with tissue morphology, genetic risk of atherosclerosis, and future adverse cardiovascular events. This review will highlight ways to utilize human atherosclerotic lesions in translational research by work from large cardiovascular biobanks to tissue registries. We will also discuss the opportunities and challenges of working with human atherosclerotic lesions in the era of next-generation sequencing.

Single-nucleus chromatin accessibility profiling highlights regulatory mechanisms of coronary artery disease risk

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across cell types. Genome-wide association studies (GWAS) have identified over 200 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements (CREs). Here, we applied single-nucleus ATAC-seq to profile 28,316 nuclei across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants. . We identified elements in smooth muscle cell (SMC) transition states (e.g. fibromyocytes) and functional variants predicted to alter SMC and macrophage-specific regulation of MRAS (3q22) and LIPA (10q23), respectively. We further nominated key driver transcription factors such as PRDM16 and TBX2. Together, this single nucleus atlas provides a critical step towards interpreting regulatory mechanisms across the continuum of CAD risk.

Abstract 468: Expression Qtl Analysis And Fine-mapping In Human Coronary Artery Prioritize Candidate Genes For Functional Characterization

Background: Atherosclerotic plaque progression to coronary artery disease is the leading cause of death worldwide. The basic pathophysiology of atherosclerosis is well described, but underlying genetic mechanisms of contributing cell types remain incompletely characterized. We utilized human coronary artery RNA sequencing data to identify differentially expressed genes and genetic variants that affect expression.

Methods: We used bulk RNA sequencing data from coronary artery samples from 138 American adults (30% female) representing a broad phenotypic range of atherosclerosis. To account for ancestral diversity, we incorporated local ancestry into permutation-based eQTL analyses using a combination of published methods. We also used mixQTL to evaluate the contribution of allele-specific expression to identifying eQTLs. All analyses adjusted for age, sex, and ancestry. We utilized CAD GWAS summary statistics, coronary artery ENCODE annotations, and activity-by-contact (ABC) scores to fine-map eGenes.

Results: In local-ancestry eQTL analyses, we report 467 eGenes (FDR<0.05), 75 of which had no significant coronary artery eQTLs in GTEx. Additionally, we identify over 4,000 eGenes using mixQTL. 25 GWAS signals colocalized using a European LD reference panel, 9 of which colocalized uniquely to 1 of 4 datasets analyzed. Fine-mapping demonstrated multiple independent associations at over 20% of loci, potentially representing ancestry-specific associations. Population-specific analyses are ongoing.

Conclusion: Understanding changes in the gene expression program at all disease stages will help characterize coronary artery disease processes as well as identify potential therapeutic targets for functional examination. This work represents a step toward characterizing CAD-related gene expression programs and highlight the importance of inclusive, deliberate study design.

Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits

One mechanism by which genetic factors influence complex traits and diseases is altering gene expression. Direct measurement of gene expression in relevant tissues is rarely tenable; however, genetically regulated gene expression (GReX) can be estimated using prediction models derived from large multi-omic datasets. These approaches have led to the discovery of many gene-trait associations, but whether models derived from predominantly European ancestry (EA) reference panels can map novel associations in ancestrally diverse populations remains unclear. We applied PrediXcan to impute GReX in 51,520 ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) participants (35% African American, 45% Hispanic/Latino, 10% Asian, and 7% Hawaiian) across 25 key cardiometabolic traits and relevant tissues to identify 102 novel associations. We then compared associations in PAGE to those in a random subset of 50,000 White British participants from UK Biobank (UKBB50k) for height and body mass index (BMI). We identified 517 associations across 47 tissues in PAGE but not UKBB50k, demonstrating the importance of diverse samples in identifying trait-associated GReX. We observed that variants used in PrediXcan models were either more or less differentiated across continental-level populations than matched-control variants depending on the specific population reflecting sampling bias. Additionally, variants from identified genes specific to either PAGE or UKBB50k analyses were more ancestrally differentiated than those in genes detected in both analyses, underlining the value of population-specific discoveries. This suggests that while EA-derived transcriptome imputation models can identify new associations in non-EA populations, models derived from closely matched reference panels may yield further insights. Our findings call for more diversity in reference datasets of tissue-specific gene expression.

Enhanced single-cell RNA-seq workflow reveals coronary artery disease cellular cross-talk and candidate drug targets

BACKGROUND AND AIMS

The atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability are not yet available. We sought to develop a scRNA-seq analysis workflow to investigate this environment and uncover potential therapeutic approaches. We designed a user-friendly, reproducible workflow that will be applicable to other disease-specific scRNA-seq datasets.

METHODS

Here we incorporated automated cell labeling, pseudotemporal ordering, ligand-receptor evaluation, and drug-gene interaction analysis into a ready-to-deploy workflow. We applied this pipeline to further investigate a previously published human coronary single-cell dataset by Wirka et al. Notably, we developed an interactive web application to enable further exploration and analysis of this and other cardiovascular single-cell datasets.

RESULTS

We revealed distinct derivations of fibroblast-like cells from smooth muscle cells (SMCs), and showed the key changes in gene expression along their de-differentiation path. We highlighted several key ligand-receptor interactions within the atherosclerotic environment through functional expression profiling and revealed several avenues for future pharmacological development for precision medicine. Further, our interactive web application, PlaqView (www.plaqview.com), allows lay scientists to explore this and other datasets and compare scRNA-seq tools without prior coding knowledge.

CONCLUSIONS

This publicly available workflow and application will allow for more systematic and user-friendly analysis of scRNA datasets in other disease and developmental systems. Our analysis pipeline provides many hypothesis-generating tools to unravel the etiology of coronary artery disease. We also highlight potential mechanisms for several drugs in the atherosclerotic cellular environment. Future releases of PlaqView will feature more scRNA-seq and scATAC-seq atherosclerosis-related datasets to provide a critical resource for the field, and to promote data harmonization and biological interpretation.

Abstract 113: Cell-specific Chromatin Landscape Of Human Coronary Artery Resolves Mechanisms Of Disease Risk

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis -regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped over 320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. Using differential peak analyses we identified a number of candidate mechanisms for smooth muscle cell transition states (e.g. fibromyocytes). By integrating these profiles with GWAS meta-analysis summary data we resolved cell type-specific putative binding sites for the majority of CAD risk variants. In particular, we prioritized functional variants predicted to alter MEF2 binding in smooth muscle cells at the MRAS locus. We also identify variants predicted to alter macrophage-specific regulation of LIPA. We further employed DNA to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. Together, this single cell atlas provides a critical step towards interpreting cis -regulatory mechanisms in the vessel wall across the continuum of CAD risk.

Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations

BACKGROUND

Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed.

METHODS

To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants.

RESULTS

Our results revealed 24 suggestive signals (p < 1 × 10-4) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN.

CONCLUSIONS

These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.

Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study

Background

Circulating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented.

Results

We performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance (P < 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance (P < 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations.

Conclusions

Our results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07745-5.

Comparison of adaptive multiple phenotype association tests using summary statistics in genome-wide association studies

Genome-wide association studies have been successful mapping loci for individual phenotypes, but few studies have comprehensively interrogated evidence of shared genetic effects across multiple phenotypes simultaneously. Statistical methods have been proposed for analyzing multiple phenotypes using summary statistics, which enables studies of shared genetic effects while avoiding challenges associated with individual-level data sharing. Adaptive tests have been developed to maintain power against multiple alternative hypotheses because the most powerful single-alternative test depends on the underlying structure of the associations between the multiple phenotypes and a single nucleotide polymorphism (SNP). Here we compare the performance of six such adaptive tests: two adaptive sum of powered scores (aSPU) tests, the unified score association test (metaUSAT), the adaptive test in a mixed-models framework (mixAda) and two principal-component-based adaptive tests (PCAQ and PCO). Our simulations highlight practical challenges that arise when multivariate distributions of phenotypes do not satisfy assumptions of multivariate normality. Previous reports in this context focus on low minor allele count (MAC) and omit the aSPU test, which relies less than other methods on asymptotic and distributional assumptions. When these assumptions are not satisfied, particularly when MAC is low and/or phenotype covariance matrices are singular or nearly singular, aSPU better preserves type I error, sometimes at the cost of decreased power. We illustrate this trade-off with multiple phenotype analyses of six quantitative electrocardiogram traits in the Population Architecture using Genomics and Epidemiology (PAGE) study.

Multi-Ethnic Genome-Wide Association Study of Decomposed Cardioelectric Phenotypes Illustrates Strategies to Identify and Characterize Evidence of Shared Genetic Effects for Complex Traits

BACKGROUND

We examined how expanding electrocardiographic trait genome-wide association studies to include ancestrally diverse populations, prioritize more precise phenotypic measures, and evaluate evidence for shared genetic effects enabled the detection and characterization of loci.

METHODS

We decomposed 10 seconds, 12-lead electrocardiograms from 34 668 multi-ethnic participants (15% Black; 30% Hispanic/Latino) into 6 contiguous, physiologically distinct (P wave, PR segment, QRS interval, ST segment, T wave, and TP segment) and 2 composite, conventional (PR interval and QT interval) interval scale traits and conducted multivariable-adjusted, trait-specific univariate genome-wide association studies using 1000-G imputed single-nucleotide polymorphisms. Evidence of shared genetic effects was evaluated by aggregating meta-analyzed univariate results across the 6 continuous electrocardiographic traits using the combined phenotype adaptive sum of powered scores test.

RESULTS

We identified 6 novels (CD36, PITX2, EMB, ZNF592, YPEL2, and BC043580) and 87 known loci (adaptive sum of powered score test P<5×10-9). Lead single-nucleotide polymorphism rs3211938 at CD36 was common in Blacks (minor allele frequency=10%), near monomorphic in European Americans, and had effects on the QT interval and TP segment that ranked among the largest reported to date for common variants. The other 5 novel loci were observed when evaluating the contiguous but not the composite electrocardiographic traits. Combined phenotype testing did not identify novel electrocardiographic loci unapparent using traditional univariate approaches, although this approach did assist with the characterization of known loci.

CONCLUSIONS

Despite including one-third as many participants as published electrocardiographic trait genome-wide association studies, our study identified 6 novel loci, emphasizing the importance of ancestral diversity and phenotype resolution in this era of ever-growing genome-wide association studies.

Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics

BACKGROUND

Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population.

RESULTS

We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP.

CONCLUSION

This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations.

Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count <10 (including singletons) in the imputation target samples, average information content rescued was >86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.

Genetic analyses of diverse populations improves discovery for complex traits

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry^1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific^4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations^11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions¹³-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.

The Future of Genomic Studies Must Be Globally Representative: Perspectives from PAGE

The past decade has seen a technological revolution in human genetics that has empowered population-level investigations into genetic associations with phenotypes. Although these discoveries rely on genetic variation across individuals, association studies have overwhelmingly been performed in populations of European descent. In this review, we describe limitations faced by single-population studies and provide an overview of strategies to improve global representation in existing data sets and future human genomics research via diversity-focused, multiethnic studies. We highlight the successes of individual studies and meta-analysis consortia that have provided unique knowledge. Additionally, we outline the approach taken by the Population Architecture Using Genomics and Epidemiology (PAGE) study to develop best practices for performing genetic epidemiology in multiethnic contexts. Finally, we discuss how limiting investigations to single populations impairs findings in the clinical domain for both rare-variant identification and genetic risk prediction.

Genome-wide association of white blood cell counts in Hispanic/Latino Americans: the Hispanic Community Health Study/Study of Latinos

Circulating white blood cell (WBC) counts (neutrophils, monocytes, lymphocytes, eosinophils, basophils) differ by ethnicity. The genetic factors underlying basal WBC traits in Hispanics/Latinos are unknown. We performed a genome-wide association study of total WBC and differential counts in a large, ethnically diverse US population sample of Hispanics/Latinos ascertained by the Hispanic Community Health Study and Study of Latinos (HCHS/SOL). We demonstrate that several previously known WBC-associated genetic loci (e.g. the African Duffy antigen receptor for chemokines null variant for neutrophil count) are generalizable to WBC traits in Hispanics/Latinos. We identified and replicated common and rare germ-line variants at FLT3 (a gene often somatically mutated in leukemia) associated with monocyte count. The common FLT3 variant rs76428106 has a large allele frequency differential between African and non-African populations. We also identified several novel genetic loci involving or regulating hematopoietic transcription factors (CEBPE-SLC7A7, CEBPA and CRBN-TRNT1) associated with basophil count. The minor allele of the CEBPE variant associated with lower basophil count has been previously associated with Amerindian ancestry and higher risk of acute lymphoblastic leukemia in Hispanics. Together, these data suggest that germline genetic variation affecting transcriptional and signaling pathways that underlie WBC development and lineage specification can contribute to inter-individual as well as ethnic differences in peripheral blood cell counts (normal hematopoiesis) in addition to susceptibility to leukemia (malignant hematopoiesis).

Genome-wide association study of red blood cell traits in Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos

Prior GWAS have identified loci associated with red blood cell (RBC) traits in populations of European, African, and Asian ancestry. These studies have not included individuals with an Amerindian ancestral background, such as Hispanics/Latinos, nor evaluated the full spectrum of genomic variation beyond single nucleotide variants. Using a custom genotyping array enriched for Amerindian ancestral content and 1000 Genomes imputation, we performed GWAS in 12,502 participants of Hispanic Community Health Study and Study of Latinos (HCHS/SOL) for hematocrit, hemoglobin, RBC count, RBC distribution width (RDW), and RBC indices. Approximately 60% of previously reported RBC trait loci generalized to HCHS/SOL Hispanics/Latinos, including African ancestral alpha- and beta-globin gene variants. In addition to the known 3.8kb alpha-globin copy number variant, we identified an Amerindian ancestral association in an alpha-globin regulatory region on chromosome 16p13.3 for mean corpuscular volume and mean corpuscular hemoglobin. We also discovered and replicated three genome-wide significant variants in previously unreported loci for RDW (SLC12A2 rs17764730, PSMB5 rs941718), and hematocrit (PROX1 rs3754140). Among the proxy variants at the SLC12A2 locus we identified rs3812049, located in a bi-directional promoter between SLC12A2 (which encodes a red cell membrane ion-transport protein) and an upstream anti-sense long-noncoding RNA, LINC01184, as the likely causal variant. We further demonstrate that disruption of the regulatory element harboring rs3812049 affects transcription of SLC12A2 and LINC01184 in human erythroid progenitor cells. Together, these results reinforce the importance of genetic study of diverse ancestral populations, in particular Hispanics/Latinos.

Comparison of 2 models for gene-environment interactions: an example of simulated gene-medication interactions on systolic blood pressure in family-based data

BACKGROUND

Nearly half of adults in the United States who are diagnosed with hypertension use blood-pressure-lowering medications. Yet there is a large interindividual variability in the response to these medications. Two complementary gene-environment interaction methods have been published and incorporated into publicly available software packages to examine interaction effects, including whether genetic variants modify the association between medication use and blood pressure. The first approach uses a gene-environment interaction term to measure the change in outcome when both the genetic marker and medication are present (the "interaction model"). The second approach tests for effect-size differences between strata of an environmental exposure (the "med-diff" approach). However, no studies have quantitatively compared how these methods perform with respect to 1 or 2 degree of freedom (DF) tests or in family-based data sets. We evaluated these 2 approaches using simulated genotype-medication response interactions at 3 single nucleotide polymorphisms (SNPs) across a range of minor allele frequencies (MAFs 0.1-5.4 %) using the Genetic Analysis Workshop 19 family sample.

RESULTS

The estimated interaction effect sizes were on average larger in the interaction model approach compared to the med-diff approach. The true positive proportion was higher for the med-diff approach for SNPs less than 1 % MAF, but higher for the interaction model when common variants were evaluated (MAF >5 %). The interaction model produced lower false-positive proportions than expected (5 %) across a range of MAFs for both the 1DF and 2DF tests. In contrast, the med-diff approach produced higher but stable false-positive proportions around 5 % across MAFs for both tests.

CONCLUSIONS

Although the 1DF tests both performed similarly for common variants, the interaction model estimated true interaction effects with less bias and higher true positive proportions than the med-diff approach. However, if rare variation (MAF <5 %) is of interest, our findings suggest that when convergence is achieved, the med-diff approach may estimate true interaction effects more conservatively and with less variability.

Genome-wide Association Study of Platelet Count Identifies Ancestry-Specific Loci in Hispanic/Latino Americans

Platelets play an essential role in hemostasis and thrombosis. We performed a genome-wide association study of platelet count in 12,491 participants of the Hispanic Community Health Study/Study of Latinos by using a mixed-model method that accounts for admixture and family relationships. We discovered and replicated associations with five genes (ACTN1, ETV7, GABBR1-MOG, MEF2C, and ZBTB9-BAK1). Our strongest association was with Amerindian-specific variant rs117672662 (p value = 1.16 × 10(-28)) in ACTN1, a gene implicated in congenital macrothrombocytopenia. rs117672662 exhibited allelic differences in transcriptional activity and protein binding in hematopoietic cells. Our results underscore the value of diverse populations to extend insights into the allelic architecture of complex traits.

SOX10 regulates expression of the SH3-domain kinase binding protein 1 (Sh3kbp1) locus in Schwann cells via an alternative promoter

The transcription factor SOX10 has essential roles in neural crest-derived cell populations, including myelinating Schwann cells-specialized glial cells responsible for ensheathing axons in the peripheral nervous system. Importantly, SOX10 directly regulates the expression of genes essential for proper myelin function. To date, only a handful of SOX10 target loci have been characterized in Schwann cells. Addressing this lack of knowledge will provide a better understanding of Schwann cell biology and candidate loci for relevant diseases such as demyelinating peripheral neuropathies. We have identified a highly-conserved SOX10 binding site within an alternative promoter at the SH3-domain kinase binding protein 1 (Sh3kbp1) locus. The genomic segment identified at Sh3kbp1 binds to SOX10 and displays strong promoter activity in Schwann cells in vitro and in vivo. Mutation of the SOX10 binding site ablates promoter activity, and ectopic expression of SOX10 in SOX10-negative cells promotes the expression of endogenous Sh3kbp1. Combined, these data reveal Sh3kbp1 as a novel target of SOX10 and raise important questions regarding the function of SH3KBP1 isoforms in Schwann cells.

SOX10 directly modulates ERBB3 transcription via an intronic neural crest enhancer

Background

The ERBB3 gene is essential for the proper development of the neural crest (NC) and its derivative populations such as Schwann cells. As with all cell fate decisions, transcriptional regulatory control plays a significant role in the progressive restriction and specification of NC derived lineages during development. However, little is known about the sequences mediating transcriptional regulation of ERBB3 or the factors that bind them.

Results

In this study we identified three transcriptional enhancers at the ERBB3 locus and evaluated their regulatory potential in vitro in NC-derived cell types and in vivo in transgenic zebrafish. One enhancer, termed ERBB3_MCS6, which lies within the first intron of ERBB3, directs the highest reporter expression in vitro and also demonstrates epigenetic marks consistent with enhancer activity. We identify a consensus SOX10 binding site within ERBB3_MCS6 and demonstrate, in vitro, its necessity and sufficiency for the activity of this enhancer. Additionally, we demonstrate that transcription from the endogenous Erbb3 locus is dependent on Sox10. Further we demonstrate in vitro that Sox10 physically interacts with that ERBB3_MCS6. Consistent with its in vitro activity, we also show that ERBB3_MCS6 drives reporter expression in NC cells and a subset of its derivative lineages in vivo in zebrafish in a manner consistent with erbb3b expression. We also demonstrate, using morpholino analysis, that Sox10 is necessary for ERBB3_MCS6 expression in vivo in zebrafish.

Conclusions

Taken collectively, our data suggest that ERBB3 may be directly regulated by SOX10, and that this control may in part be facilitated by ERBB3_MCS6.

A rare myelin protein zero (MPZ) variant alters enhancer activity in vitro and in vivo

Background

Myelin protein zero (MPZ) is a critical structural component of myelin in the peripheral nervous system. The MPZ gene is regulated, in part, by the transcription factors SOX10 and EGR2. Mutations in MPZ, SOX10, and EGR2 have been implicated in demyelinating peripheral neuropathies, suggesting that components of this transcriptional network are candidates for harboring disease-causing mutations (or otherwise functional variants) that affect MPZ expression.

Methodology

We utilized a combination of multi-species sequence comparisons, transcription factor-binding site predictions, targeted human DNA re-sequencing, and in vitro and in vivo enhancer assays to study human non-coding MPZ variants.

Principal Findings

Our efforts revealed a variant within the first intron of MPZ that resides within a previously described SOX10 binding site is associated with decreased enhancer activity, and alters binding of nuclear proteins. Additionally, the genomic segment harboring this variant directs tissue-relevant reporter gene expression in zebrafish.

Conclusions

This is the first reported MPZ variant within a cis-acting transcriptional regulatory element. While we were unable to implicate this variant in disease onset, our data suggests that similar non-coding sequences should be screened for mutations in patients with neurological disease. Furthermore, our multi-faceted approach for examining the functional significance of non-coding variants can be readily generalized to study other loci important for myelin structure and function.

Variable optimization for the formation of three-dimensional self-organized heart muscle

Cardiac tissue-engineering research is focused on the development of functional three-dimensional (3D) heart muscle in vitro. These models allow the detailed study of critical events in organogenesis, such as the establishment of cell-cell communication and construction and modification of the extracellular matrix. We have previously described a model for 3D heart muscle, termed cardioids, formed by the spontaneous delamination of a cohesive monolayer of primary cells in the absence of any synthetic scaffolding material. In an earlier publication, we have shown that, upon electrical stimulation, cardioids generate a twitch force in the range of 200-300 microN, generate a specific force (twitch force normalized to total cross-sectional area) of 2-4 kN/m(2), and can be electrically paced at frequencies of up to 10 Hz without any notable fatigue. We have two objectives for the current study: model development and model optimization. Our model development efforts are focused on providing additional characterization of the cardioid model. In this study, we show for the first time that cardioids show a pattern of gene expression comparable to that of cells cultured in two dimensions on tissue culture plastic and normal mammalian heart muscle. Compared with primary cardiac cells cultured on tissue culture plastic, the expression of alpha-myosin heavy chain (MHC), beta-MHC, SERCA2, and phospholamban was significantly higher in cardioids. Our second objective, model optimization, is focused on evaluating the effect of several cell culture variables on cardioid formation and function. Specifically, we looked at the effect of plating density (1.0-4.0 x 10(6) cells per cardioid), concentration of two adhesion proteins (laminin at 0.2-2.0 microg/cm(2) and fibronectin at 1-10 microg/cm(2)), myocyte purity (using preplating times of 15 and 60 min), and ascorbic acid stimulation (1-100 microl/ml). For our optimization studies, we utilized twitch force in response to electrical stimulation as our endpoint metric. Based on these studies, we found that cardioids formed with a plating density in the range 3-4 x 10(6) cells per cardioid generated the maximum twitch force, whereas increasing the surface adhesion protein (using either laminin or fibronectin) and increasing the myocyte purity both resulted in a decrease in twitch force. In addition, increasing the ascorbic acid concentration resulted in an increase in the baseline force of cardioids, which was recorded in the absence of electrical stimulation. Based on the model development studies, we have shown that cardioids do indeed exhibit a gene expression pattern similar to normal mammalian heart muscle. This provides further validity for the cardioid model. Based on the model optimization studies, we have identified specific cell culture regimes which support cardioid formation and function. These results are specific to the cardioid model; however, they may be translated and applied to other tissue-engineering models. Collectively, the work described in this study provides insight into the formation of functional 3D heart muscle and the effect of several cell culture variables on tissue formation and function.