Human cytomegalovirus extensively re-organizes the human genome, diminishing TEAD1 transcription factor activity.

Human cytomegalovirus (HCMV) infects up to 80% of the world's population. Here, we show that HCMV infection leads to widespread changes in human chromatin accessibility and chromatin looping, with hundreds of thousands of genomic regions affected 48 hours after infection. Integrative analyses reveal HCMV-induced perturbation of Hippo signaling through drastic reduction of TEAD1 transcription factor activity. We confirm extensive concordant loss of TEAD1 binding, active H3K27ac histone marks, and chromatin looping interactions upon infection. Our data position TEAD1 at the top of a hierarchy involving multiple altered important developmental pathways. HCMV infection reduces TEAD1 activity through four distinct mechanisms: closing of TEAD1-bound chromatin, reduction of YAP1 and phosphorylated YAP1 levels, reduction of TEAD1 transcript and protein levels, and alteration of TEAD1 exon-6 usage. Altered TEAD1-based mechanisms are highly enriched at genetic risk loci associated with eye and ear development, providing mechanistic insight into HCMV's established roles in these processes.

Association between systemic lupus erythematosus and myasthenia gravis: A population-based National Study.

BACKGROUND: Systemic lupus erythematosus (SLE) and myasthenia gravis (MG) are autoimmune diseases. Previous case reports and case series suggest an association may exist between these diseases, as well as an increased risk of SLE after thymectomy for MG. We undertook this study to determine whether SLE and MG were associated in large cohorts. METHODS: We searched the IBM Watson Health Explorys platform and the Department of Veterans Affairs Million Veteran Program (MVP) database for diagnoses of SLE and MG. In addition, we examined subjects enrolled in the Lupus Family Registry and Repository (LFRR) as well as controls for a diagnosis of MG. RESULTS: Among 59,780,210 individuals captured in Explorys, there were 25,750 with MG and 65,370 with SLE. 370 subjects had both. Those with MG were >10 times more likely to have SLE than those without MG. Those with both diseases were more likely to be women, African American, and at a younger age than MG subjects without SLE. In addition, the MG patients who underwent thymectomy had an increased risk of SLE compared to MG patients who had not undergone thymectomy (OR 3.11, 95% CI: 2.12 to 4.55). Autoimmune diseases such as pernicious anemia and miscellaneous comorbidities such as chronic kidney disease were significantly more common in MG patients who developed SLE. In the MVP, SLE and MG were also significantly associated. Association of SLE and MG in a large SLE cohort with rigorous SLE classification confirmed the association of SLE with MG at a similar level. CONCLUSION: While the number of patients with both MG and SLE is small, SLE and MG are strongly associated together in very large databases and a large SLE cohort.

Modeling of horizontal pleiotropy identifies possible causal gene expression in systemic lupus erythematosus.

Background: Systemic lupus erythematosus (SLE) is a chronic autoimmune condition with complex causes involving genetic and environmental factors. While genome-wide association studies (GWASs) have identified genetic loci associated with SLE, the functional genomic elements responsible for disease development remain largely unknown. Mendelian Randomization (MR) is an instrumental variable approach to causal inference based on data from observational studies, where genetic variants are employed as instrumental variables (IVs). Methods: This study utilized a two-step strategy to identify causal genes for SLE. In the first step, the classical MR method was employed, assuming the absence of horizontal pleiotropy, to estimate the causal effect of gene expression on SLE. In the second step, advanced probabilistic MR methods (PMR-Egger, MRAID, and MR-MtRobin) were applied to the genes identified in the first step, considering horizontal pleiotropy, to filter out false positives. PMR-Egger and MRAID analyses utilized whole blood expression quantitative trait loci (eQTL) and SLE GWAS summary data, while MR-MtRobin analysis used an independent eQTL dataset from multiple immune cell types along with the same SLE GWAS data. Results: The initial MR analysis identified 142 genes, including 43 outside of chromosome 6. Subsequently, applying the advanced MR methods reduced the number of genes with significant causal effects on SLE to 66. PMR-Egger, MRAID, and MR-MtRobin, respectively, identified 13, 7, and 16 non-chromosome 6 genes with significant causal effects. All methods identified expression of PHRF1 gene as causal for SLE. A comprehensive literature review was conducted to enhance understanding of the functional roles and mechanisms of the identified genes in SLE development. Conclusions: The findings from the three MR methods exhibited overlapping genes with causal effects on SLE, demonstrating consistent results. However, each method also uncovered unique genes due to different modelling assumptions and technical factors, highlighting the complementary nature of the approaches. Importantly, MRAID demonstrated a reduced percentage of causal genes from the Major Histocompatibility complex (MHC) region on chromosome 6, indicating its potential in minimizing false positive findings. This study contributes to unraveling the mechanisms underlying SLE by employing advanced probabilistic MR methods to identify causal genes, thereby enhancing our understanding of SLE pathogenesis.

Outcomes of Returning Medically Actionable Genomic Results in Pediatric Research.

PURPOSE: The electronic Medical Records and Genomics (eMERGE) Phase III study was undertaken to assess clinical utility of returning medically actionable genomic screening results. We assessed pediatric clinical outcomes following return of pathogenic/likely pathogenic (P/LP) variants in autosomal dominant conditions with available effective interventions. METHODS: The two eMERGE III pediatric sites collected outcome data and assessed changes in medical management at 6 and 12 months. RESULTS: We returned P/LP results to 29 participants with outcome data. For 23 of the 29 participants, the P/LP results were previously unknown. Five of the 23 participants were already followed for conditions related to the P/LP variant. Of those receiving novel results and not being followed for the condition related to the P/LP result (n = 18), 14 (77.8%) had a change in healthcare after return of results (RoR). Following RoR, cascade testing of family members occurred for 10 of 23 (43.5%). CONCLUSIONS: The most common outcomes post-RoR included imaging/laboratory testing and health behavior recommendations. A change in healthcare was documented in 77.8% of those receiving results by 6 months. Our findings demonstrate how return of genomic screening results impacts healthcare in pediatric populations.

Genetic regulation of serum IgA levels and susceptibility to common immune, infectious, kidney, and cardio-metabolic traits.

Immunoglobulin A (IgA) mediates mucosal responses to food antigens and the intestinal microbiome and is involved in susceptibility to mucosal pathogens, celiac disease, inflammatory bowel disease, and IgA nephropathy. We performed a genome-wide association study of serum IgA levels in 41,263 individuals of diverse ancestries and identified 20 genome-wide significant loci, including 9 known and 11 novel loci. Co-localization analyses with expression QTLs prioritized candidate genes for 14 of 20 significant loci. Most loci encoded genes that produced immune defects and IgA abnormalities when genetically manipulated in mice. We also observed positive genetic correlations of serum IgA levels with IgA nephropathy, type 2 diabetes, and body mass index, and negative correlations with celiac disease, inflammatory bowel disease, and several infections. Mendelian randomization supported elevated serum IgA as a causal factor in IgA nephropathy. African ancestry was consistently associated with higher serum IgA levels and greater frequency of IgA-increasing alleles compared to other ancestries. Our findings provide novel insights into the genetic regulation of IgA levels and its potential role in human disease.

Haplotype-specific chromatin looping reveals genetic interactions of regulatory regions modulating gene expression in 8p23.1.

A major goal of genetics research is to elucidate mechanisms explaining how genetic variation contributes to phenotypic variation. The genetic variants identified in genome-wide association studies (GWASs) generally explain only a small proportion of heritability of phenotypic traits, the so-called missing heritability problem. Recent evidence suggests that additional common variants beyond lead GWAS variants contribute to phenotypic variation; however, their mechanistic underpinnings generally remain unexplored. Herein, we undertake a study of haplotype-specific mechanisms of gene regulation at 8p23.1 in the human genome, a region associated with a number of complex diseases. The FAM167A-BLK locus in this region has been consistently found in the genome-wide association studies (GWASs) of systemic lupus erythematosus (SLE) in all major ancestries. Our haplotype-specific chromatin interaction (Hi-C) experiments, allele-specific enhancer activity measurements, genetic analyses, and epigenome editing experiments revealed that: 1) haplotype-specific long-range chromatin interactions are prevalent in 8p23.1; 2) BLK promoter and cis-regulatory elements cooperatively interact with haplotype-specificity; 3) genetic variants at distal regulatory elements are allele-specific modifiers of the promoter variants at FAM167A-BLK; 4) the BLK promoter interacts with and, as an enhancer-like promoter, regulates FAM167A expression and 5) local allele-specific enhancer activities are influenced by global haplotype structure due to chromatin looping. Although systemic lupus erythematosus causal variants at the FAM167A-BLK locus are thought to reside in the BLK promoter region, our results reveal that genetic variants at distal regulatory elements modulate promoter activity, changing BLK and FAM167A gene expression and disease risk. Our results suggest that global haplotype-specific 3-dimensional chromatin looping architecture has a strong influence on local allelic BLK and FAM167A gene expression, providing mechanistic details for how regional variants controlling the BLK promoter may influence disease risk.

Pre-Clinical Autoimmunity in Lupus Relatives: Self-Reported Questionnaires and Immune Dysregulation Distinguish Relatives Who Develop Incomplete or Classified Lupus From Clinically Unaffected Relatives and Unaffected, Unrelated Individuals.

Systemic lupus erythematosus (SLE) is propelled by pathogenic autoantibody (AutoAb) and immune pathway dysregulation. Identifying populations at risk of reaching classified SLE is essential to curtail inflammatory damage. Lupus blood relatives (Rel) have an increased risk of developing SLE. We tested factors to identify Rel at risk of developing incomplete lupus (ILE) or classified SLE vs. clinically unaffected Rel and healthy controls (HC), drawing from two unique, well characterized lupus cohorts, the lupus autoimmunity in relatives (LAUREL) follow-up cohort, consisting of Rel meeting <4 ACR criteria at baseline, and the Lupus Family Registry and Repository (LFRR), made up of SLE patients, lupus Rel, and HC. Medical record review determined ACR SLE classification criteria; study participants completed the SLE portion of the connective tissue disease questionnaire (SLE-CSQ), type 2 symptom questions, and provided samples for assessment of serum SLE-associated AutoAb specificities and 52 plasma immune mediators. Elevated SLE-CSQ scores were associated with type 2 symptoms, ACR scores, and serology in both cohorts. Fatigue at BL was associated with transition to classified SLE in the LAUREL cohort (p≤0.01). Increased levels of BLyS and decreased levels of IL-10 were associated with type 2 symptoms (p<0.05). SLE-CSQ scores, ACR scores, and accumulated AutoAb specificities correlated with levels of multiple inflammatory immune mediators (p<0.05), including BLyS, IL-2Rα, stem cell factor (SCF), soluble TNF receptors, and Th-1 type mediators and chemokines. Transition to SLE was associated with increased levels of SCF (p<0.05). ILE Rel also had increased levels of TNF-α and IFN-γ, offset by increased levels of regulatory IL-10 and TGF-ß (p<0.05). Clinically unaffected Rel (vs. HC) had higher SLE-CSQ scores (p<0.001), increased serology (p<0.05), and increased inflammatory mediator levels, offset by increased IL-10 and TGF-ß (p<0.01). These findings suggest that Rel at highest risk of transitioning to classified SLE have increased inflammation coupled with decreased regulatory mediators. In contrast, clinically unaffected Rel and Rel with ILE demonstrate increased inflammation offset with increased immune regulation, intimating a window of opportunity for early intervention and enrollment in prevention trials.

Regulatory Architecture of the RCA Gene Cluster Captures an Intragenic TAD Boundary, CTCF-Mediated Chromatin Looping and a Long-Range Intergenic Enhancer.

The Regulators of Complement Activation (RCA) gene cluster comprises several tandemly arranged genes with shared functions within the immune system. RCA members, such as complement receptor 2 (CR2), are well-established susceptibility genes in complex autoimmune diseases. Altered expression of RCA genes has been demonstrated at both the functional and genetic level, but the mechanisms underlying their regulation are not fully characterised. We aimed to investigate the structural organisation of the RCA gene cluster to identify key regulatory elements that influence the expression of CR2 and other genes in this immunomodulatory region. Using 4C, we captured extensive CTCF-mediated chromatin looping across the RCA gene cluster in B cells and showed these were organised into two topologically associated domains (TADs). Interestingly, an inter-TAD boundary was located within the CR1 gene at a well-characterised segmental duplication. Additionally, we mapped numerous gene-gene and gene-enhancer interactions across the region, revealing extensive co-regulation. Importantly, we identified an intergenic enhancer and functionally demonstrated this element upregulates two RCA members (CR2 and CD55) in B cells. We have uncovered novel, long-range mechanisms whereby autoimmune disease susceptibility may be influenced by genetic variants, thus highlighting the important contribution of chromatin topology to gene regulation and complex genetic disease.

Lupus enhancer risk variant causes dysregulation of IRF8 through cooperative lncRNA and DNA methylation machinery.

Despite strong evidence that human genetic variants affect the expression of many key transcription factors involved in autoimmune diseases, establishing biological links between non-coding risk variants and the gene targets they regulate remains a considerable challenge. Here, we combine genetic, epigenomic, and CRISPR activation approaches to screen for functional variants that regulate IRF8 expression. We demonstrate that the locus containing rs2280381 is a cell-type-specific enhancer for IRF8 that spatially interacts with the IRF8 promoter. Further, rs2280381 mediates IRF8 expression through enhancer RNA AC092723.1, which recruits TET1 to the IRF8 promoter regulating IRF8 expression by affecting methylation levels. The alleles of rs2280381 modulate PU.1 binding and chromatin state to regulate AC092723.1 and IRF8 expression differentially. Our work illustrates an integrative strategy to define functional genetic variants that regulate the expression of critical genes in autoimmune diseases and decipher the mechanisms underlying the dysregulation of IRF8 expression mediated by lupus risk variants.

A High Prevalence of Anti-EBNA1 Heteroantibodies in Systemic Lupus Erythematosus (SLE) Supports Anti-EBNA1 as an Origin for SLE Autoantibodies.

BACKGROUND: That Epstein-Barr virus (EBV) infection is associated with systemic lupus erythematosus (SLE) is established. The challenge is to explain mechanistic roles EBV has in SLE pathogenesis. Previous studies identify four examples of autoantibody cross-reactions between SLE autoantigens and Epstein-Barr nuclear antigen 1 (EBNA1). For two of these examples, the earliest detected autoantibody specifically cross-reacts with EBNA1; thereby, defined EBNA1 epitopes induce a robust autoantibody response in animals. These results suggest that the autoantibodies initiating the process leading to SLE may emerge from the anti-EBNA1 heteroimmune response. If this hypothesis is true, then anti-EBNA1 responses would be more frequent in EBV-infected SLE patients than in EBV-infected controls. We tested this prediction. METHODS: We evaluated published East Asian data by selecting those with a positive anti-viral capsid antigen (VCA) antibody immunoglobulin G (IgG) test and determining whether anti-EBNA1 was more common among the EBV-infected SLE cases than among matched EBV-infected controls with conditional logistic regression analysis. RESULTS: All the qualifying SLE patients (100%) in this dataset were EBV-infected compared to age- and sex-matched controls (92.2%) [odds ratio (OR) = 28.6, 95% CI 6.4-∞, p = 8.83 × 10-8], confirming the known close association of EBV infection with SLE. Furthermore, virtually all the SLE cases have both anti-VCA IgG and anti-EBNA1 IgG antibodies [124 of 125 (99.2%)], which are more frequently present than in age- and sex-matched EBV-infected controls [232 of 250 (93.2%)] (OR = 9.7, 95% CI 1.5-414, p = 0.0078) for an 89.7% SLE attributable risk from anti-EBNA1, which is in addition to the 100% SLE risk attributable to EBV infection in these data. CONCLUSIONS: The association of EBV infection with SLE is reconfirmed. The prediction that anti-EBNA1 is more frequent in these SLE cases than in EBV-infected controls is true, consistent with the hypothesis that anti-EBNA1 contributes to SLE. This second EBV-dependent risk factor is consistent with a molecular mimicry model for the generation of SLE, starting with EBV infection, progressing to anti-EBNA1 response; then molecular mimicry leads to anti-EBNA1 antibodies cross-reacting with an SLE autoantigen, causing autoantibody epitope spreading, and culminating in clinical SLE. These results support the anti-EBNA1 heteroimmune response being a foundation from which pathogenic SLE autoimmunity emerges.

The US Department of Veterans Affairs Science and Health Initiative to Combat Infectious and Emerging Life-Threatening Diseases (VA SHIELD): A Biorepository Addressing National Health Threats.

Background: The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has demonstrated the need to share data and biospecimens broadly to optimize clinical outcomes for US military Veterans. Methods: In response, the Veterans Health Administration established VA SHIELD (Science and Health Initiative to Combat Infectious and Emerging Life-threatening Diseases), a comprehensive biorepository of specimens and clinical data from affected Veterans to advance research and public health surveillance and to improve diagnostic and therapeutic capabilities. Results: VA SHIELD now comprises 12 sites collecting de-identified biospecimens from US Veterans affected by SARS-CoV-2. In addition, 2 biorepository sites, a data processing center, and a coordinating center have been established under the direction of the Veterans Affairs Office of Research and Development. Phase 1 of VA SHIELD comprises 34 157 samples. Of these, 83.8% had positive tests for SARS-CoV-2, with the remainder serving as contemporaneous controls. The samples include nasopharyngeal swabs (57.9%), plasma (27.9%), and sera (12.5%). The associated clinical and demographic information available permits the evaluation of biological data in the context of patient demographics, clinical experience and management, vaccinations, and comorbidities. Conclusions: VA SHIELD is representative of US national diversity with a significant potential to impact national healthcare. VA SHIELD will support future projects designed to better understand SARS-CoV-2 and other emergent healthcare crises. To the extent possible, VA SHIELD will facilitate the discovery of diagnostics and therapeutics intended to diminish COVID-19 morbidity and mortality and to reduce the impact of new emerging threats to the health of US Veterans and populations worldwide.

Antibody Responses to Epstein-Barr Virus in the Preclinical Period of Rheumatoid Arthritis Suggest the Presence of Increased Viral Reactivation Cycles.

OBJECTIVE: Patients with established rheumatoid arthritis (RA) demonstrate altered immune responses to Epstein-Barr virus (EBV), but the presence and roles of EBV have not been fully explored during the pre-clinical disease period. This study was undertaken to determine if EBV infection, as evidenced by an altered anti-EBV antibody response, either plays an important role in driving the development of RA or is a result of expanded RA-related autoimmunity. METHODS: A total of 83 subjects with RA according to the 1987 American College of Rheumatology (ACR) criteria and 83 age-, sex-, and race-matched control subjects without RA were included in our study. We collected sera from RA subjects and matched controls during the pre-RA and post-RA diagnosis periods and tested the sera for the presence of 5 anti-EBV antibodies (anti-EBV nuclear antigen 1 IgG isotype, anti-viral capsid antigen [anti-VCA] isotypes IgG and IgA, and anti-early antigen [EA] isotypes IgG and IgA), 7 RA-related autoantibodies (rheumatoid factor measured by nephelometry [RF-Neph] as well as isotype-specific IgA-RF, IgM-RF, and IgG-RF, and anti-cyclic citrullinated peptide [anti-CCP] antibodies, including anti-CCP2, anti-CCP3, and anti-CCP3.1), 22 cytokines/chemokines, 36 individual anti-citrullinated protein antibodies, and IgG-cytomegalovirus (CMV) antibodies. Random forest classification, mixed modeling, and joint mixed modeling were used to determine differences in anti-EBV antibody levels between RA subjects and controls. RESULTS: Random forest analysis identified the presence of preclinical EBV antibodies in the serum that differentiated RA subjects from controls without RA. Specifically, IgG-EA antibody levels were higher in RA subjects (mean ± SD 0.82 ± 0.72 international standardized ratio [ISR]) compared to controls (mean ± SD 0.49 ± 0.28 ISR). In subjects with RA, elevated serum IgG-EA levels in the preclinical period before seroconversion were significantly correlated with increased serum IgM-RF levels (P = 0.007), whereas this correlation was not seen in control subjects without RA (P = 0.15). IgG-CMV antibody levels did not differ between groups. CONCLUSION: Subjects whose serum IgG-EA antibody levels are elevated in the preclinical period will eventually develop RA, which suggests that EBV reactivation cycles are increased during the preclinical period of RA. A combination of RF and EBV reactivation may play an important role in the development of RA.

Reanalysis of eMERGE phase III sequence variants in 10,500 participants and infrastructure to support the automated return of knowledge updates.

PURPOSE: The clinical genomics knowledgebase is dynamic with variant classifications changing as newly identified cases, additional population data, and other evidence become available. This is a challenge for the clinical laboratory because of limited resource availability for variant reassessment. METHODS: Throughout the Electronic Medical Records and Genomics phase III program, clinical sites associated with the Mass General Brigham/Broad sequencing center received automated, real-time notifications when reported variants were reclassified. In this study, we summarized the nature of these reclassifications and described the proactive reassessment framework we used for the Electronic Medical Records and Genomics program data set to identify variants most likely to undergo reclassification. RESULTS: Reanalysis of 1855 variants led to the reclassification of 2% (n = 45) of variants, affecting 0.6% (n = 67) of participants. Of these reclassifications, 78% (n = 35) were high-impact changes affecting reportability, with 8 variants downgraded from likely pathogenic/pathogenic to variants of uncertain significance (VUS) and 27 variants upgraded from VUS to likely pathogenic/pathogenic. Most upgraded variants (67%) were initially classified as VUS-Favor Pathogenic, highlighting the benefit of VUS subcategorization. The most common reason for reclassification was new published case data and/or functional evidence. CONCLUSION: Our results highlight the importance of periodic sequence variant reevaluation and the need for automated approaches to advance routine implementation of variant reevaluations in clinical practice.

Epstein-Barr virus nuclear antigen 2 extensively rewires the human chromatin landscape at autoimmune risk loci.

The interplay between environmental and genetic factors plays a key role in the development of many autoimmune diseases. In particular, the Epstein-Barr virus (EBV) is an established contributor to multiple sclerosis, lupus, and other disorders. Previously, we showed that the EBV nuclear antigen 2 (EBNA2) transactivating protein occupies up to half of the risk loci for a set of seven autoimmune disorders. To further examine the mechanistic roles played by EBNA2 at these loci on a genome-wide scale, we globally examined gene expression, chromatin accessibility, chromatin looping, and EBNA2 binding in a B cell line that was (1) uninfected, (2) infected with a strain of EBV lacking EBNA2, or (3) infected with a strain that expresses EBNA2. We identified more than 400 EBNA2-dependent differentially expressed human genes and more than 5000 EBNA2 binding events in the human genome. ATAC-seq analysis revealed more than 2000 regions in the human genome with EBNA2-dependent chromatin accessibility, and HiChIP data revealed more than 1700 regions where EBNA2 altered chromatin looping interactions. Autoimmune genetic risk loci were highly enriched at the sites of these EBNA2-dependent chromatin-altering events. We present examples of autoimmune risk genotype-dependent EBNA2 events, nominating genetic risk mechanisms for autoimmune risk loci such as ZMIZ1 Taken together, our results reveal important interactions between host genetic variation and EBNA2-driven disease mechanisms. Further, our study highlights a critical role for EBNA2 in rewiring human gene regulatory programs through rearrangement of the chromatin landscape and nominates these interactions as components of genetic mechanisms that influence the risk of multiple autoimmune diseases.

Validation of low-coverage whole-genome sequencing for mitochondrial DNA variants suggests mitochondrial DNA as a genetic cause of preterm birth.

Preterm birth (PTB), or birth that occurs earlier than 37 weeks of gestational age, is a major contributor to infant mortality and neonatal hospitalization. Mutations in the mitochondrial genome (mtDNA) have been linked to various rare mitochondrial disorders and may be a contributing factor in PTB given that maternal genetic factors have been strongly linked to PTB. However, to date, no study has found a conclusive connection between a particular mtDNA variant and PTB. Given the high mtDNA copy number per cell, an automated pipeline was developed for detecting mtDNA variants using low-coverage whole-genome sequencing (lcWGS) data. The pipeline was first validated against samples of known heteroplasmy, and then applied to 929 samples from a PTB cohort from diverse ethnic backgrounds with an average gestational age of 27.18 weeks (range: 21-30). Our new pipeline successfully identified haplogroups and a large number of mtDNA variants in this large PTB cohort, including 8 samples carrying known pathogenic variants and 47 samples carrying rare mtDNA variants. These results confirm that lcWGS can be utilized to reliably identify mtDNA variants. These mtDNA variants may make a contribution toward preterm birth in a small proportion of live births.

Novel EDGE encoding method enhances ability to identify genetic interactions.

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)-rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action.

Medical Records-Based Genetic Studies of the Complement System.

BACKGROUND: Genetic variants in complement genes have been associated with a wide range of human disease states, but well-powered genetic association studies of complement activation have not been performed in large multiethnic cohorts. METHODS: We performed medical records-based genome-wide and phenome-wide association studies for plasma C3 and C4 levels among participants of the Electronic Medical Records and Genomics (eMERGE) network. RESULTS: In a GWAS for C3 levels in 3949 individuals, we detected two genome-wide significant loci: chr.1q31.3 (CFH locus; rs3753396-A; ß=0.20; 95% CI, 0.14 to 0.25; P=1.52x10-11) and chr.19p13.3 (C3 locus; rs11569470-G; ß=0.19; 95% CI, 0.13 to 0.24; P=1.29x10-8). These two loci explained approximately 2% of variance in C3 levels. GWAS for C4 levels involved 3998 individuals and revealed a genome-wide significant locus at chr.6p21.32 (C4 locus; rs3135353-C; ß=0.40; 95% CI, 0.34 to 0.45; P=4.58x10-35). This locus explained approximately 13% of variance in C4 levels. The multiallelic copy number variant analysis defined two structural genomic C4 variants with large effect on blood C4 levels: C4-BS (ß=-0.36; 95% CI, -0.42 to -0.30; P=2.98x10-22) and C4-AL-BS (ß=0.25; 95% CI, 0.21 to 0.29; P=8.11x10-23). Overall, C4 levels were strongly correlated with copy numbers of C4A and C4B genes. In comprehensive phenome-wide association studies involving 102,138 eMERGE participants, we cataloged a full spectrum of autoimmune, cardiometabolic, and kidney diseases genetically related to systemic complement activation. CONCLUSIONS: We discovered genetic determinants of plasma C3 and C4 levels using eMERGE genomic data linked to electronic medical records. Genetic variants regulating C3 and C4 levels have large effects and multiple clinical correlations across the spectrum of complement-related diseases in humans.

Lupus Susceptibility Region Containing CDKN1B rs34330 Mechanistically Influences Expression and Function of Multiple Target Genes, Also Linked to Proliferation and Apoptosis.

OBJECTIVE: In a recent genome-wide association study, a significant genetic association between rs34330 of CDKN1B and risk of systemic lupus erythematosus (SLE) in Han Chinese was identified. This study was undertaken to validate the reported association and elucidate the biochemical mechanisms underlying the effect of the variant. METHODS: We performed an allelic association analysis in patients with SLE, followed by a meta-analysis assessing genome-wide association data across 11 independent cohorts (n = 28,872). In silico bioinformatics analysis and experimental validation in SLE-relevant cell lines were applied to determine the functional consequences of rs34330. RESULTS: We replicated a genetic association between SLE and rs34330 (meta-analysis P = 5.29 × 10-22 , odds ratio 0.84 [95% confidence interval 0.81-0.87]). Follow-up bioinformatics and expression quantitative trait locus analysis suggested that rs34330 is located in active chromatin and potentially regulates several target genes. Using luciferase and chromatin immunoprecipitation-real-time quantitative polymerase chain reaction, we demonstrated substantial allele-specific promoter and enhancer activity, and allele-specific binding of 3 histone marks (H3K27ac, H3K4me3, and H3K4me1), RNA polymerase II (Pol II), CCCTC-binding factor, and a critical immune transcription factor (interferon regulatory factor 1 [IRF-1]). Chromosome conformation capture revealed long-range chromatin interactions between rs34330 and the promoters of neighboring genes APOLD1 and DDX47, and effects on CDKN1B and the other target genes were directly validated by clustered regularly interspaced short palindromic repeat (CRISPR)-based genome editing. Finally, CRISPR/dead CRISPR-associated protein 9-based epigenetic activation/silencing confirmed these results. Gene-edited cell lines also showed higher levels of proliferation and apoptosis. CONCLUSION: Collectively, these findings suggest a mechanism whereby the rs34330 risk allele (C) influences the presence of histone marks, RNA Pol II, and IRF-1 transcription factor to regulate expression of several target genes linked to proliferation and apoptosis. This process could potentially underlie the association of rs34330 with SLE.