Summary

The Probabilistic Identification of Causal SNPs (PICS) algorithm and web application was developed as a fine-mapping tool to determine the likelihood that each single nucleotide polymorphism (SNP) in LD with a reported index SNP is a true causal polymorphism. PICS is notable for its ability to identify candidate causal SNPs within a locus using only the index SNP, which are widely available from published GWAS, whereas other methods require full summary statistics or full genotype data. However, the original PICS web application operates on a single SNP at a time, with slow performance, severely limiting its usability. We have developed a next-generation PICS tool, PICS2, which enables performance of PICS analyses of large batches of index SNPs with much faster performance. Additional updates and extensions include use of LD reference data generated from 1000 Genomes phase 3; annotation of variant consequences; annotation of GTEx eQTL genes and downloadable PICS SNPs from GTEx eQTLs; the option of generating PICS probabilities from experimental summary statistics; and generation of PICS SNPs from all SNPs of the GWAS catalog, automatically updated weekly. These free and easy-to-use resources will enable efficient determination of candidate loci for biological studies to investigate the true causal variants underlying disease processes.

Availability and implementation

PICS2 is available at https://pics2.ucsf.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

OBJECTIVE: Systemic lupus erythematosus (SLE) is an autoimmune disease resulting in debilitating clinical manifestations that vary in severity by race and ethnicity with a disproportionate burden in African American, Mestizo, and Asian populations compared with populations of European descent. Differences in global and local genetic ancestry may shed light on the underlying mechanisms contributing to these disparities, including increased prevalence of lupus nephritis, younger age of symptom onset, and presence of autoantibodies. METHODS: A total of 1,139 European, African American, and Mestizos patients with SLE were genotyped using the Affymetrix LAT1 World array. Global ancestry proportions were estimated using ADMIXTURE, and local ancestry was estimated using RFMIXv2.0. We investigated associations between lupus nephritis, age at onset, and autoantibody status with both global and local ancestry proportions within the Major Histocompatibility Complex region. RESULTS: Our results showed small effect sizes that did not meet the threshold for statistical significance for global or local ancestry proportions in either African American or Mestizo patients with SLE who presented with the clinical manifestations of interest compared with those who did not. CONCLUSION: These findings suggest that local genetic ancestry within the Major Histocompatibility Complex region is not a major contributor to these SLE manifestations among patients with SLE from admixed populations.

GCLiPP is a global RNA interactome capture method that detects RNA-binding protein (RBP) occupancy transcriptome-wide. GCLiPP maps RBP-occupied sites at a higher resolution than phase separation-based techniques. GCLiPP sequence tags correspond with known RBP binding sites and are enriched for sites detected by RBP-specific crosslinking immunoprecipitation (CLIP) for abundant cytosolic RBPs. Comparison of human Jurkat T cells and mouse primary T cells uncovers shared peaks of GCLiPP signal across homologous regions of human and mouse 3' UTRs, including a conserved mRNA-destabilizing cis-regulatory element. GCLiPP signal overlapping with immune-related SNPs uncovers stabilizing cis-regulatory regions in CD5, STAT6, and IKZF1.

Systemic lupus erythematous (SLE) is a heterogeneous autoimmune disease in which outcomes vary among different racial groups. Here, we aim to identify SLE subgroups within a multiethnic cohort using an unsupervised clustering approach based on the American College of Rheumatology (ACR) classification criteria. We identify three patient clusters that vary according to disease severity. Methylation association analysis identifies a set of 256 differentially methylated CpGs across clusters, including 101 CpGs in genes in the Type I Interferon pathway, and we validate these associations in an external cohort. A cis-methylation quantitative trait loci analysis identifies 744 significant CpG-SNP pairs. The methylation signature is enriched for ethnic-associated CpGs suggesting that genetic and non-genetic factors may drive outcomes and ethnic-associated methylation differences. Our computational approach highlights molecular differences associated with clusters rather than single outcome measures. This work demonstrates the utility of applying integrative methods to address clinical heterogeneity in multifactorial multi-ethnic disease settings.

Systemic lupus erythematosus (SLE) is an autoimmune disease in which outcomes vary among different racial groups. We leverage cell-sorted RNA-seq data (CD14+ monocytes, B cells, CD4+ T cells, and NK cells) from 120 SLE patients (63 Asian and 57 White individuals) and apply a four-tier approach including unsupervised clustering, differential expression analyses, gene co-expression analyses, and machine learning to identify SLE subgroups within this multiethnic cohort. K-means clustering on each cell-type resulted in three clusters for CD4 and CD14, and two for B and NK cells. To understand the identified clusters, correlation analysis revealed significant positive associations between the clusters and clinical parameters including disease activity as well as ethnicity. We then explored differentially expressed genes between Asian and White groups for each cell-type. The shared differentially expressed genes across cells were involved in SLE or other autoimmune-related pathways. Co-expression analysis identified similarly regulated genes across samples and grouped these genes into modules. Finally, random forest classification of disease activity in the White and Asian cohorts showed the best classification in CD4+ T cells in White individuals. The results from these analyses will help stratify patients based on their gene expression signatures to enable SLE precision medicine.

Objective

African Americans, East Asians, and Hispanics with systemic lupus erythematosus (SLE) are more likely to develop renal disease than are SLE patients of European descent. This study was undertaken to investigate whether European genetic ancestry protects against the development of lupus nephritis, with the aim of exploring the genetic and socioeconomic factors that might explain this effect.

Methods

This was a cross-sectional study of SLE patients from a multiethnic case collection. Participants were genotyped for 126 single-nucleotide polymorphisms (SNPs) informative for ancestry. A subset of participants was also genotyped for 80 SNPs in 14 candidate genes for renal disease in SLE. Logistic regression was used to test the association between European ancestry and renal disease. Analyses were adjusted for continental ancestries, socioeconomic status (SES), and candidate genes.

Results

Participants (n = 1,906) had, on average, 62.4% European, 15.8% African, 11.5% East Asian, 6.5% Amerindian, and 3.8% South Asian ancestry. Among the participants, 656 (34%) had renal disease. A 10% increase in the proportion of European ancestry estimated in each participant was associated with a 15% reduction in the odds of having renal disease, after adjustment for disease duration and sex (odds ratio 0.85, 95% confidence interval 0.82-0.87; P = 1.9 × 10(-30) ). Adjustment for other genetic ancestries, measures of SES, or SNPs in the genes most associated with renal disease (IRF5 [rs4728142], BLK [rs2736340], STAT4 [rs3024912], and HLA-DRB1*0301 and DRB1*1501) did not substantively alter this relationship.

Conclusion

European ancestry is protective against the development of renal disease in SLE, an effect that is independent of other genetic ancestries, candidate risk alleles, and socioeconomic factors.

Objective

African Americans, East Asians, and Hispanics with systemic lupus erythematous (SLE) are more likely to develop lupus nephritis (LN) than are SLE patients of European descent. The etiology of this difference is not clear, and this study was undertaken to investigate how genetic variants might explain this effect.

Methods

In this cross-sectional study, 1244 SLE patients from multiethnic case collections were genotyped for 817,810 single-nucleotide polymorphisms (SNPs) across the genome. Continental genetic ancestry was estimated utilizing the program ADMIXTURE. Gene-based testing and pathway analysis was performed within each ethnic group and meta-analyzed across ethnicities. We also performed candidate SNP association tests with SNPs previously established as risk alleles for SLE, LN, and chronic kidney disease (CKD). Association testing and logistic regression models were performed with LN as the outcome, adjusted for continental ancestries, sex, disease duration, and age.

Results

We studied 255 North European, 263 South European, 238 Hispanic, 224 African American and 264 East Asian SLE patients, of whom 606 had LN (48.7%). In genome-wide gene-based and candidate SNP analyses, we found distinct genes, pathways and established risk SNPs associated with LN for each ethnic group. Gene-based analyses showed significant associations between variation in ZNF546 (p = 1.0E-06), TRIM15 (p = 1.0E-06), and TRIMI0 (p = 1.0E-06) and LN among South Europeans, and TTC34 (p = 8.0E-06) was significantly associated with LN among Hispanics. The SNP rs8091180 in NFATC1 was associated with LN (OR 1.43, p = 3.3E-04) in the candidate SNP meta-analysis with the highest OR among African-Americans (OR 2.17, p = 0.0035).

Conclusion

Distinct genetic factors are associated with the risk of LN in SLE patients of different ethnicities. CKD risk alleles may play a role in the development of LN in addition to SLE-associated risk variants. These findings may further explain the clinical heterogeneity of LN risk and response to therapy observed between different ethnic groups.

Dendritic cells (DCs), which are known to support immune activation during infection, may also regulate immune homeostasis in resting animals. Here we show that mice lacking the ubiquitin-editing molecule A20 specifically in DCs spontaneously showed DC activation and population expansion of activated T cells. Analysis of DC-specific epistasis in compound mice lacking both A20 and the signaling adaptor MyD88 specifically in DCs showed that A20 restricted both MyD88-independent signals, which drive activation of DCs and T cells, and MyD88-dependent signals, which drive population expansion of T cells. In addition, mice lacking A20 specifically in DCs spontaneously developed lymphocyte-dependent colitis, seronegative ankylosing arthritis and enthesitis, conditions stereotypical of human inflammatory bowel disease (IBD). Our findings indicate that DCs need A20 to preserve immune quiescence and suggest that A20-dependent DC functions may underlie IBD and IBD-associated arthritides.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Objective

Findings from cross-sectional studies have revealed associations between DNA methylation and systemic lupus erythematosus (SLE) outcomes. This study was undertaken to investigate the dynamics of DNA methylation by examining participants from an SLE longitudinal cohort using samples collected at 2 time points.

Methods

A total of 101 participants from the California Lupus Epidemiology Study were included in our analysis. DNA was extracted from blood samples collected at the time of enrolment in the cohort and samples collected after 2 years and was analyzed using Illumina EPIC BeadChip kit. Paired t-tests were used to identify genome-wide changes which included 256 CpG sites previously found to be associated with SLE subtypes. Linear mixed models were developed to understand the relationship between DNA methylation and disease activity, medication use, and sample cell-type proportions, adjusted for age, sex, and genetic principal components.

Results

The majority of CpGs that were previously determined to be associated with SLE subtypes remained stable over 2 years (185 CpGs [72.3%]; t-test false discovery rate >0.05). Compared to background genome-wide methylation, there was an enrichment of SLE subtype-associated CpGs that changed over time (27.7% versus 0.34%). Changes in cell-type proportions were associated with changes at 67 CpGs (P < 2.70 × 10^-5 ), and 15 CpGs had at least 1 significant association with immunosuppressant use.

Conclusion

In this longitudinal SLE cohort, we identified a subset of SLE subtype-associated CpGs that remained stable over time and may be useful as biomarkers of disease subtypes. Another subset of SLE subtype-associated CpGs changed at a higher proportion compared to the genome-wide methylome. Additional studies are needed to understand the etiology and impact of these changes on methylation of SLE-associated CpGs.