Caroline J. Gallant

Association of a functional variant downstream of TNFAIP3 with systemic lupus erythematosus

Systemic lupus erythematosus (SLE, MIM152700) is an autoimmune disease characterized by self-reactive antibodies resulting in systemic inflammation and organ failure. TNFAIP3, encoding the ubiquitin-modifying enzyme A20, is an established susceptibility locus for SLE. By fine mapping and genomic re-sequencing in ethnically diverse populations, we fully characterized the TNFAIP3 risk haplotype and identified a TT>A polymorphic dinucleotide (deletion T followed by a T to A transversion) associated with SLE in subjects of European (P = 1.58 × 10−8, odds ratio = 1.70) and Korean (P = 8.33 × 10−10, odds ratio = 2.54) ancestry. This variant, located in a region of high conservation and regulatory potential, bound a nuclear protein complex composed of NF-κB subunits with reduced avidity. Further, compared with the non-risk haplotype, the haplotype carrying this variant resulted in reduced TNFAIP3 mRNA and A20 protein expression. These results establish this TT>A variant as the most likely functional polymorphism responsible for the association between TNFAIP3 and SLE.

Evaluation of the TREX1 gene in a large multi-ancestral lupus cohort

Systemic lupus erythematosus (SLE) is a prototypic autoimmune disorder with a complex pathogenesis in which genetic, hormonal and environmental factors have a role. Rare mutations in the TREX1 gene, the major mammalian 3′–5′ exonuclease, have been reported in sporadic SLE cases. Some of these mutations have also been identified in a rare pediatric neurological condition featuring an inflammatory encephalopathy known as Aicardi–Goutières syndrome (AGS). We sought to investigate the frequency of these mutations in a large multi-ancestral cohort of SLE cases and controls. A total of 40 single-nucleotide polymorphisms (SNPs), including both common and rare variants, across the TREX1 gene, were evaluated in ∼8370 patients with SLE and ∼7490 control subjects. Stringent quality control procedures were applied, and principal components and admixture proportions were calculated to identify outliers for removal from analysis. Population-based case–control association analyses were performed. P-values, false-discovery rate q values, and odds ratios (OR) with 95% confidence intervals (CI) were calculated. The estimated frequency of TREX1 mutations in our lupus cohort was 0.5%. Five heterozygous mutations were detected at the Y305C polymorphism in European lupus cases but none were observed in European controls. Five African cases incurred heterozygous mutations at the E266G polymorphism and, again, none were observed in the African controls. A rare homozygous R114H mutation was identified in one Asian SLE patient, whereas all genotypes at this mutation in previous reports for SLE were heterozygous. Analysis of common TREX1 SNPs (minor allele frequency (MAF)>10%) revealed a relatively common risk haplotype in European SLE patients with neurological manifestations, especially seizures, with a frequency of 58% in lupus cases compared with 45% in normal controls (P=0.0008, OR=1.73, 95% CI=1.25–2.39). Finally, the presence or absence of specific autoantibodies in certain populations produced significant genetic associations. For example, a strong association with anti-nRNP was observed in the European cohort at a coding synonymous variant rs56203834 (P=2.99E−13, OR=5.2, 95% CI=3.18–8.56). Our data confirm and expand previous reports and provide additional support for the involvement of TREX1 in lupus pathogenesis.

Identification of a Systemic Lupus Erythematosus Susceptibility Locus at 11p13 between PDHX and CD44 in a Multiethnic Study

Systemic lupus erythematosus (SLE) is considered to be the prototypic autoimmune disease, with a complex genetic architecture influenced by environmental factors. We sought to replicate a putative association at 11p13 not yet exceeding genome-wide significance (p < 5 × 10(-8)) identified in a genome-wide association study (GWAS). Our GWA scan identified two intergenic SNPs located between PDHX and CD44 showing suggestive evidence of association with SLE in cases of European descent (rs2732552, p = 0.004, odds ratio [OR] = 0.78; rs387619, p = 0.003, OR = 0.78). The replication cohort consisted of >15,000 subjects, including 3562 SLE cases and 3491 controls of European ancestry, 1527 cases and 1811 controls of African American (AA) descent, and 1265 cases and 1260 controls of Asian origin. We observed robust association at both rs2732552 (p = 9.03 × 10(-8), OR = 0.83) and rs387619 (p = 7.7 × 10(-7), OR = 0.83) in the European samples with p(meta) = 1.82 × 10(-9) for rs2732552. The AA and Asian SLE cases also demonstrated association at rs2732552 (p = 5 × 10(-3), OR = 0.81 and p = 4.3 × 10(-4), OR = 0.80, respectively). A meta-analysis of rs2732552 for all racial and ethnic groups studied produced p(meta) = 2.36 × 10(-13). This locus contains multiple regulatory sites that could potentially affect expression and functions of CD44, a cell-surface glycoprotein influencing immunologic, inflammatory, and oncologic phenotypes, or PDHX, a subunit of the pyruvate dehydrogenase complex.

Simultaneous Multiplexed Measurement of RNA and Proteins in Single Cells

Summary Significant advances have been made in methods to analyze genomes and transcriptomes of single cells, but to fully define cell states, proteins must also be accessed as central actors defining a cell’s phenotype. Methods currently used to analyze endogenous protein expression in single cells are limited in specificity, throughput, or multiplex capability. Here, we present an approach to simultaneously and specifically interrogate large sets of protein and RNA targets in lysates from individual cells, enabling investigations of cell functions and responses. We applied our method to investigate the effects of BMP4, an experimental therapeutic agent, on early-passage glioblastoma cell cultures. We uncovered significant heterogeneity in responses to treatment at levels of RNA and protein, with a subset of cells reacting in a distinct manner to BMP4. Moreover, we found overall poor correlation between protein and RNA at the level of single cells, with proteins more accurately defining responses to treatment.

Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction

We present a scalable, integrated strategy for coupled protein and RNA detection from single cells. Our approach leverages the DNA polymerase activity of reverse transcriptase to simultaneously perform proximity extension assays and complementary DNA synthesis in the same reaction. Using the Fluidigm C1™ system, we profile the transcriptomic and proteomic response of a human breast adenocarcinoma cell line to a chemical perturbation, benchmarking against in situ hybridizations and immunofluorescence staining, as well as recombinant proteins, ERCC Spike-Ins, and population lysate dilutions. Through supervised and unsupervised analyses, we demonstrate synergies enabled by simultaneous measurement of single-cell protein and RNA abundances. Collectively, our generalizable approach highlights the potential for molecular metadata to inform highly-multiplexed single-cell analyses.

Evaluation of TRAF6 in a large multiancestral lupus cohort

OBJECTIVE Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease with significant immune system aberrations resulting from complex heritable genetics as well as environmental factors. We undertook to study the role of TRAF6 as a candidate gene for SLE, since it plays a major role in several signaling pathways that are important for immunity and organ development. METHODS Fifteen single-nucleotide polymorphisms (SNPs) across TRAF6 were evaluated in 7,490 SLE patients and 6,780 control subjects from different ancestries. Population-based case-control association analyses and meta-analyses were performed. P values, false discovery rate q values, and odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated. RESULTS Evidence of associations was detected in multiple SNPs. The best overall P values were obtained for SNPs rs5030437 and rs4755453 (P = 7.85 × 10(-5) and P = 4.73 × 10(-5) , respectively) without significant heterogeneity among populations (P = 0.67 and P = 0.50, respectively, in Q statistic). In addition, SNP rs540386, which was previously reported to be associated with rheumatoid arthritis (RA), was found to be in linkage disequilibrium with these 2 SNPs (r(2) = 0.95) and demonstrated evidence of association with SLE in the same direction (meta-analysis P = 9.15 × 10(-4) , OR 0.89 [95% CI 0.83-0.95]). The presence of thrombocytopenia improved the overall results in different populations (meta-analysis P = 1.99 × 10(-6) , OR 0.57 [95% CI 0.45-0.72], for rs5030470). Finally, evidence of family-based association in 34 African American pedigrees with the presence of thrombocytopenia was detected in 1 available SNP (rs5030437) with a Z score magnitude of 2.28 (P = 0.02) under a dominant model. CONCLUSION Our data indicate the presence of association of TRAF6 with SLE, consistent with the previous report of association with RA. These data provide further support for the involvement of TRAF6 in the pathogenesis of autoimmunity.

Tracing Cellular Origin of Human Exosomes Using Multiplex Proximity Extension Assays

Extracellular vesicles (EVs) are membrane-coated objects such as exosomes and microvesicles, released by many cell-types. Their presence in body fluids and the variable surface composition and content render them attractive potential biomarkers. The ability to determine their cellular origin could greatly move the field forward. We used multiplex proximity extension assays (PEA) to identify with high specificity and sensitivity the protein profiles of exosomes of different origins, including seven cell lines and two different body fluids. By comparing cells and exosomes, we successfully identified the cells originating the exosomes. Furthermore, by principal component analysis of protein patterns human milk EVs and prostasomes released from prostate acinar cells clustered with cell lines from breast and prostate tissues, respectively. Milk exosomes uniquely expressed CXCL5, MIA, and KLK6, whereas prostasomes carried NKX31, GSTP1, and SRC, highlighting that EVs originating from different origins express distinct proteins. In conclusion, PEA provides a powerful protein screening tool in exosome research, for purposes of identifying the cell source of exosomes, or new biomarkers in diseases such as cancer and inflammation.

PCR-Based Multiparametric Assays in Single Cells

Pathologists have long known that the functional state of a tissue is best understood from an overview of the different cells making up that tissue—cells that may differ radically in their lineage, their phase in the cell cycle, their responses to stimuli, and their clonal history of somatic mutation, e.g., in a tumor. With the radically expanding opportunities for the molecular analysis of nucleic acids, proteins, and combinations thereof, there is currently great interest in collecting information at cellular resolution, rather than recording population means, as has been common practice in molecular biology (1). In this issue of Clinical Chemistry , Stahlberg and coauthors (2) describe an interesting approach for jointly measuring DNA copy numbers and concentrations of mRNAs, microRNAs, and proteins in individual cells. These authors prepared single-cell lysates that were subsequently divided into separate reactions for each of the measured molecular species, and they recorded all of the results of the molecular-detection reactions via real-time quantitative PCR. This report represents an important first step in a new approach to detect multiple biological modalities in single cells with high analytical sensitivity and specificity. Nothing is quite new under the sun, of course, and there are already a number of approaches for molecular analyses at the level of individual cells. Various in situ analyses that provide cellular-level resolution are routinely used for analyzing DNA, RNA, or protein in populations of cells and in tissue sections. …

Additional file 9: Figure S8. of Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction

PCA separation of the various time points (0 hr = purple, 24 hr = green, 48 hr = blue). a A PCA over all quantitative protein targets and the corresponding ROC curves (b) for all three time points generated from random forest decision categorization with AUC of 0.98, 0.94, and 0.86 for 0 hr, 24 hr, and 48 hr, respectively. c A PCA over all quantitative RNA targets and the corresponding ROC curves (d) for all three time points generated from random forest decision categorization with AUC of 0.81, 0.80, and 0.57 for 0 hr, 24 hr, and 48 hr, respectively. e A PCA over all quantitative protein and RNA targets and the corresponding ROC curves (f) for all three time points generated from random forest decision categorization with AUC of 0.99, 0.94, and 0.84 for 0 hr, 24 hr, and 48 hr, respectively. For a, c, e, axis labels indicate which PC was used and what percent variance it explains. (PDF 269 kb)