Our post-GWAS functional analysis revealed that cathepsin L (CTSL) is an upstream regulator of CUX1, and it induces p16INK4a-dependent and atherosclerosis-associated senescence by indirectly activating CUX1 transcription in a process that requires its proteolytic activity. This suggests an unidentified transcription regulator between CTSL and CUX1, and CTSL-mediated cleavage of this regulator could transcribe CUX1, inducing senescence. Here, in search of this transcriptional regulator, we discovered that Notch1 is a substrate of CTSL, and CTSL can proteolytically activate Notch1 in a ligand-independent fashion, liberating NICD. NICD, after complexing with RBPJ in the nuclei, induces CUX1/p16INK4a-dependent senescence. Consistently, an upregulation of both CTSL and NICD, along with elevated cellular senescence in the plaques isolated from patients with atherosclerosis, was observed. In addition, we showed that endothelial deletion of CUX1 in the atherosclerosis-prone ApoE-/- mice blocks high-fat diet-induced senescence throughout the entire plaques, and these ApoE-/- mice exhibit similar phenotypes as the atherosclerosis-prone models with CTSL and Notch1/RBPJ inactivation including attenuated atherosclerotic lesion, intact and well-organized elastin fibers, and reduced macrophage content of plaque. This further supports our findings that both CTSL and Notch1/RBPJ are upstream regulators of CUX1, regulating senescence. Thus, while our studies identify a non-canonical Notch1 pathway that can be activated by CTSL in a ligand-independent fashion to induce senescence, our findings also reveal a role of senescence in the development of atherosclerosis. This provides new insight into developing drugs aimed to target cellular senescence for atherosclerosis.

BACKGROUND:Substantial efforts have been dedicated to exploring the link between genetic regulation and the proteome, informing studies of complex trait mechanisms. Most of these efforts have been limited to populations of European ancestry. RESULTS:We conduct an Olink protein quantitative trait locus (pQTL) analysis on 1245 proteins involving 1033 self-identified African American (AA) and 1764 non-Hispanic White (NHW) participants from the Women's Health Initiative and Framingham Heart Study. For replication of candidate pQTLs, we use data from 534 self-identified AA adults from the Jackson Heart Study and protein genome-wide association analysis statistics from the UK Biobank Pharma Proteomics Project, including 54,219 participants, of whom 931 are of African ancestry. In total, we identify and validate 5103 pQTLs (4496 or 88% cis- and 602 or 12% trans-pQTLs) for 983 proteins. Among these, 195 are previously unreported, with most (166 or 85%) identified in our AA sample, many of which were essentially monomorphic in European reference populations. Several of these newly identified African ancestry-specific pQTLs have been reported in ClinVar; our results suggest impact on circulating protein levels, potentially bolstering evidence for clinical significance. We identify a "cis pQTL hotspot" within the leukocyte receptor gene cluster on human chromosome 19q13.4. We also provide examples where a particular cis-pQTL, identified through conditional analysis, offers biological insights into an overlapping GWAS signal for disease susceptibility. CONCLUSIONS:The identification of previously undescribed African ancestry-specific pQTLs contributes to understanding protein genetic regulation and highlights the significance of proteomic analysis in diverse populations.

Large-scale single-cell CRISPR screens with single-cell RNA-seq (scRNA-seq) readouts provide critical data to map causal gene regulatory networks (GRNs). However, translating the complex scRNA-seq outputs into reliable causal insights remains a major analytical challenge. Here we present CausalGRN, a scalable computational framework that infers causal GRNs and predicts cellular responses to unseen perturbations. CausalGRN first mitigates pervasive spurious partial correlations in sparse scRNA-seq data through a novel adaptive thresholding correction, enabling robust inference of an undirected graph. It then orients this graph using observed perturbation outcomes. The resulting directed GRN can be used to predict the downstream effects of novel perturbations via network propagation. Across both simulations and diverse experimental datasets, CausalGRN substantially outperforms existing approaches in network reconstruction accuracy and in predicting the effects of unseen perturbations, providing a principled bridge from perturbation data to causal gene regulation.

Recent advances in functional genomics and human cellular models have substantially enhanced our understanding of the structure and regulation of the human genome. However, our grasp of the molecular functions of human genes remains incomplete and biased towards specific gene classes. The Molecular Phenotypes of Null Alleles in Cells (MorPhiC) Consortium aims to address this gap by creating a comprehensive catalogue of the molecular and cellular phenotypes associated with null alleles of all human genes using in vitro multicellular systems. In this Perspective, we present the strategic vision of the MorPhiC Consortium and discuss various strategies for generating null alleles, as well as the challenges involved. We describe the cellular models and scalable phenotypic readouts that will be used in the consortium's initial phase, focusing on 1,000 protein-coding genes. The resulting molecular and cellular data will be compiled into a catalogue of null-allele phenotypes. The methodologies developed in this phase will establish best practices for extending these approaches to all human protein-coding genes. The resources generated-including engineered cell lines, plasmids, phenotypic data, genomic information and computational tools-will be made available to the broader research community to facilitate deeper insights into human gene functions.

Transcriptome-wide association studies (TWASs) are widely used to prioritize genes for diseases. Current methods test gene-disease associations at the bulk tissue or cell-type-specific pseudobulk level, which do not account for the heterogeneity within cell types. We present TWiST, a statistical method for TWAS at cell-state resolution using single-cell expression quantitative trait locus (eQTL) data. Our method uses pseudotime to represent cell states and models the effect of gene expression on the trait as a continuous pseudotemporal curve. Therefore, it allows flexible hypothesis testing of global, dynamic, and nonlinear associations. Through simulation studies and real data analysis, we demonstrated that TWiST leads to significantly improved power compared to pseudobulk methods. Application to the OneK1K study identified hundreds of genes with dynamic effects on autoimmune diseases along the trajectory of immune cell differentiation. TWiST presents great promise to understand disease genetics using single-cell studies.

Emerging evidence indicates that endothelial cell senescence plays a critical role in the pathogenesis of pulmonary arterial hypertension (PAH). However, the underlying mechanisms and signaling pathways driving pulmonary endothelial senescence in PAH remain incompletely understood. In this study, we used a novel functional genomics approach to show that the intermediate filament protein Nestin binds to a cis-regulatory element (cis-RE) on the cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) locus, repressing p16INK4a expression and mitigating cellular senescence in human pulmonary arterial endothelial cells (PAECs). Consistently, Nestin expression was markedly downregulated in both PAH patients and rodent models, leading to increased p16INK4a level and enhanced endothelial senescence in PAH-affected lungs. We further demonstrated that SRY-related HMG-box 17 (SOX17), a transcription factor known to be associated with PAH, activated Nestin expression by binding directly to the Nestin promoter, which inhibited cellular senescence by suppressing p16INK4a expression in PAECs. In vivo, SOX17 overexpression, which leads to upregulation of Nestin and downregulation of p16INK4a in lungs of PAH rat models, significantly reduced PAEC senescence, attenuated pulmonary vascular remodeling, and alleviated PAH severity. Conversely, silencing of Nestin in the SOX17 overexpressing PAECs exacerbated PAEC senescence and worsened PAH in rodents. Our findings reveal a novel SOX17-Nestin-p16INK4a regulatory pathway that governs pulmonary endothelial cell senescence, which offers new insights into PAH pathobiology and represents a promising therapeutic target for intervention.

Cathepsin L (CTSL) has been implicated in aging and age-related diseases, such as cardiovascular diseases, specifically atherosclerosis. However, the underlying mechanism(s) is not well documented. Recently, we demonstrated a role of CUT-like homeobox 1 (CUX1) in regulating the p16INK4a-dependent cellular senescence in human endothelial cells (ECs) and vascular smooth muscle cells (VSMCs) via its binding to an atherosclerosis-associated functional SNP (fSNP) rs1537371 on the CDKN2A/B locus. In this study, to determine if CTSL, which was reported to proteolytically activate CUX1, regulates cellular senescence via CUX1, we measured the expression of CTSL, together with CUX1 and p16INK4a, in human ECs and VSMCs undergoing senescence. We discovered that CUX1 is not a substrate that is cleaved by CTSL. Instead, CTSL is an upstream regulator that activates CUX1 transcription indirectly in a process that requires the proteolytic activity of CTSL. Our findings suggest that there is a transcription factor in between CTSL and CUX1, and cleavage of this factor by CTSL can activate CUX1 transcription, inducing endothelial senescence. Thus, our findings provide new insights into the signal transduction pathway that leads to atherosclerosis-associated cellular senescence.

Cancer development is associated with aberrant DNA methylation, including increased stochastic variability. Statistical tests for discovering cancer methylation biomarkers have focused on changes in mean methylation. To improve the power of detection, we propose to incorporate increased variability in testing for cancer differential methylation by two joint constrained tests: one for differential mean and increased variance, the other for increased mean and increased variance. To improve small sample properties, likelihood ratio statistics are developed, accounting for the variability in estimating the sample medians in the Levene test. Efficient algorithms were developed and implemented in DMVC function of R package DMtest. The proposed joint constrained tests were compared to standard tests and partial area under the curve (pAUC) for the receiver operating characteristic curve (ROC) in simulated datasets under diverse models. Application to the high-throughput methylome data in The Cancer Genome Atlas (TCGA) shows substantially increased yield of candidate CpG markers.

Background: Ischemic stroke (IS) disproportionately affects populations of African descent due to genetic predispositions. A multiancestry Genome-wide Association Study (GWAS) identified non-coding SNPs in HNF1A locus highly associated with IS, exclusively to African ancestry. Analysis of this ancestry-specific genomic architecture can reveal novel pathogenic mechanism for IS. Methods: The IS-associated SNPs in HNF1A locus were analysed. Electrophoretic Mobility Shift Assay (EMSA) identified functional SNPs (fSNP) that allele-specifically bind to nuclear proteins from human vascular endothelial cells (ECs). Proteomics identified transcription factors (TFs) binding to fSNPs. siRNA knockdown was conducted to determine the function of TFs on HNF1A expression. The effects of stroke-like condition hypoxia on TFs and HNF1A were studied in various vascular cells. Results: GWAS-revealed non-coding tag SNP rs55931441 in HNF1A locus was associated with IS risk exclusively in African population. The frequency of risk allele A of tag SNP was 3.8% in African but absent in other races, supporting the causative role of this locus in determining the genetic risk of IS. EMSA revealed no nuclear protein binding to rs55931441, suggesting it is unlikely an fSNP with TF-mediated regulation on target genes. We expanded the screening to 7 haplotype SNPs in linkage disequilibrium with R 2 >0.8. Among them, rs144534697 presented with allele-imbalanced nuclear protein binding. Proteomics revealed ILF3, a vascular function-related TF, binds preferentially to non-risk allele C. Functional studies showed that ILF3 regulates HNF1A as a repressor. Less binding of ILF3 to risk allele A results in a loss of repression to HNF1A and augments its function as vascular pathogenic factor. Furthermore, vascular stressor hypoxia downregulated ILF3 and upregulated HNF1A in vascular ECs, smooth muscle cells and fibroblasts. Conclusion: Our functional genomics analysis of disease-associated SNPs identified by multiancestry GWAS offers a novel mechanistic approach for diseases with ancestry prominence. The newly identified ILF3-HNF1A pathway may serve as a general mechanistic explanation for the pathogenesis of IS, given their response to vascular stressor hypoxia.

Background: Pulmonary arterial hypertension (PAH) is a deadly pulmonary vascular disease highly relevant to genetic susceptibility and acquired pathogenic triggers, especially inflammation. Chr18q22.3 near cerebellin 2 (CBLN2) gene is the first genetic locus identified by Genome-wide Association Study (GWAS) that is significantly associated with PAH risk in population of European ancestry. This locus includes a group of closely linked non-coding intergenic single nucleotide polymorphisms (SNPs) downstream of CBLN2. Although CBLN2 is upregulated in PAH and causes pulmonary vascular dysfunction, it remains unknown how these non-coding SNPs remotely affect CBLN2 and in turn alter the genetic susceptibility of PAH. Methods and Results: We applied Hi-C analysis, combined with electrophoretic mobility shift assay, to identify rs11151770 as a functional SNP (fSNP) characterized with allele-imbalanced nuclear protein binding and chromatin interaction with CBLN2 promoter, among 19 haplotype SNPs in a linkage disequilibrium (LD r 2 >0.8) in CBLN2 locus. As an intergenic non-coding SNP, rs11151770 is located 110 kbp downstream of CBLN2 promoter. Proteomic analysis revealed nuclear transcription factor CUX1 binds specifically to the risk allele A of rs11151770 but not to the non-risk allele C. Acting as the activator for the expression of target gene CBLN2, CUX1 knockdown prevented, but CUX1 overexpression induced, the pathophenotypes of human pulmonary arterial endothelial cells (PAECs) associated with PAH. CUX1-CBLN2 was upregulated by acquired inflammatory PAH trigger IL-1β and was increased in lung tissues extracted from PAH patients. SNP genotyping in PAH patients and non-PAH controls showed a 2.2-fold risk allele A enrichment only in patients with PAH associated with connective tissue disorders, supporting a pathogenic mechanism of an inflammation-sensitive pathway (CUX1-CBLN2) combined with a PAH susceptible genotype (risk allele A of rs11151770) for the manifestation of clinical PAH. Conclusion: Our post-GWAS functional genomics analysis revealed a CUX1-mediated inflammatory pathway and provided a mechanistic explanation for the GWAS-identified association between the genetic variants in CBLN2 locus and PAH pathogenesis.

Competing risks survival data in the presence of partially masked causes are frequently encountered in medical research or clinical trials. When longitudinal biomarkers are also available, it is of great clinical importance to examine associations between the longitudinal biomarkers and the cause-specific survival outcomes. In this article, we propose a cause-specific C-index for joint models of longitudinal and competing risks survival data accounting for masked causes. We also develop a posterior predictive algorithm for computing the out-of-sample cause-specific C-index using Markov chain Monte Carlo samples from the joint posterior of the in-sample longitudinal and competing risks survival data. We further construct the Δ $$ \Delta $$ C-index to quantify the strength of association between the longitudinal and cause-specific survival data, or between the out-of-sample longitudinal and survival data. Empirical performance of the proposed assessment criteria is examined through an extensive simulation study. An in-depth analysis of the real data from large cancer prevention trials is carried out to demonstrate the usefulness of the proposed methodology.

Background: Bladder cancer (BCa) is one of the most common urinary tract malignancies. Our study aimed to provide promising biomarkers for BCa screening and prognosis.Methods: BCa samples were obtained from Gene Expression Omnibus (GEO) datasets. Differentially expressed genes (DEGs) were analysed by GO/KEGG analysis. Univariate Cox hazard analysis and Kaplan Meier Curve clarified the relevance of DEGs and survival. Receiver operating characteristic (ROC) curve showed the discrimination ability of DEGs in BCa patient outcome prediction. RT-PCR was used to validate gene expression.Results: Overall, 61 common up regulated and 170 common down-regulated genes in BCa were obtained. DEGs were mainly enriched in proliferation and metastasis processes. CDC20, COL14A1, SPARCL1, TMOD1, RHOJ, FXYD6 and MFAP4 had clinical relevance to survival with high accuracy. CDC20, SPARCL1 and TMOD1 are promising biomarkers of BCa. CDC20, SPARCL1 and TMOD1 are involved in cancer immune infiltration.Conclusion: CDC20, SPARCL1 and TMOD1 are promising biomarkers of bladder cancer. In addition, CDC20, SPARCL1 and TMOD1 are involved in cancer immune infiltration, which provides new targets in immune therapy in bladder cancer.

Genome-wide association studies (GWAS) have validated a strong association of atherosclerosis with the CDKN2A/B locus, a locus harboring three tumor suppressor genes: p14ARF , p15INK4b , and p16INK4a . Post-GWAS functional analysis reveals that CUX is a transcriptional activator of p16INK4a via its specific binding to a functional SNP (fSNP) rs1537371 on the atherosclerosis-associated CDKN2A/B locus, regulating endothelial senescence. In this work, we characterize SATB2, another transcription factor that specifically binds to rs1537371. We demonstrate that even though both CUX1 and SATB2 are the homeodomain transcription factors, unlike CUX1, SATB2 is a transcriptional suppressor of p16INK4a and overexpression of SATB2 competes with CUX1 for its binding to rs1537371, which inhibits p16INK4a and p16INK4a -dependent cellular senescence in human endothelial cells (ECs). Surprisingly, we discovered that SATB2 expression is transcriptionally repressed by CUX1. Therefore, upregulation of CUX1 inhibits SATB2 expression, which enhances the binding of CUX1 to rs1537371 and subsequently fine-tunes p16INK4a expression. Remarkably, we also demonstrate that IL-1β, a senescence-associated secretory phenotype (SASP) gene itself and a biomarker for atherosclerosis, induces cellular senescence also by upregulating CUX1 and/or downregulating SATB2 in human ECs. A model is proposed to reconcile our findings showing how both primary and secondary senescence are activated via the atherosclerosis-associated p16INK4a expression.

Abstract Growing evidence suggests that functional cis-regulatory elements (cis-REs) not only exist in epigenetically marked but also in unmarked sites of the human genome. While it is already difficult to identify cis-REs in the epigenetically marked sites, interrogating cis-REs residing within the unmarked sites is even more challenging. Here, we report adapting Reel-seq, an in vitro high-throughput (HTP) technique, to fine-map cis-REs at high resolution over a large region of the human genome in a systematic and continuous manner. Using Reel-seq, as a proof-of-principle, we identified 408 candidate cis-REs by mapping a 58 kb core region on the aging-related CDKN2A/B locus that harbors p16INK4a. By coupling Reel-seq with FREP-MS, a proteomics analysis technique, we characterized two cis-REs, one in an epigenetically marked site and the other in an epigenetically unmarked site. These elements are shown to regulate the p16INK4a expression over an ∼100 kb distance by recruiting the poly(A) binding protein PABPC1 and the transcription factor FOXC2. Downregulation of either PABPC1 or FOXC2 in human endothelial cells (ECs) can induce the p16INK4a-dependent cellular senescence. Thus, we confirmed the utility of Reel-seq and FREP-MS analyses for the systematic identification of cis-REs at high resolution over a large region of the human genome.

Accumulation of senescent cells with age is an important driver of aging and age-related diseases. However, the mechanisms and signaling pathways that regulate senescence remain elusive. In this report, we performed post-genome-wide association studies (GWAS) functional studies on the CDKN2A/B locus, a locus known to be associated with multiple age-related diseases and overall human lifespan. We demonstrate that transcription factor CUX1 (Cut-Like Homeobox 1) specifically binds to an atherosclerosis-associated functional single-nucleotide polymorphism (fSNP) (rs1537371) within the locus and regulates the CDKN2A/B- encoded proteins p14 ARF , p15 INK4b and p16 INK4a and the antisense noncoding RNA in the CDK4 (INK4) locus (ANRIL) in endothelial cells (ECs). Endothelial CUX1 expression correlates with telomeric length and is induced by both DNA-damaging agents and oxidative stress. Moreover, induction of CUX1 expression triggers both replicative and stress-induced senescence via activation of p16 INK4a expression. Thus, our studies identify CUX1 as a regulator of p16 INK4a -dependent endothelial senescence and a potential therapeutic target for atherosclerosis and other age-related diseases.

Background A model was built that characterized effects of individual factors on five-year prostate cancer (PCa) risk in the Prostate, Lung, Colon, and Ovarian Cancer Screening Trial (PLCO) and the Selenium and Vitamin E Cancer Prevention Trial (SELECT). This model was validated in a third San Antonio Biomarkers of Risk (SABOR) screening cohort. Methods A prediction model for 1- to 5-year risk of developing PCa and Gleason > 7 PCa (HG PCa) was built on PLCO and SELECT using the Cox proportional hazards model adjusting for patient baseline characteristics. Random forests and neural networks were compared to Cox proportional hazard survival models, using the trial datasets for model building and the SABOR cohort for model evaluation. The most accurate prediction model is included in an online calculator. Results The respective rates of PCa were 8.9%, 7.2%, and 11.1% in PLCO (n = 31,495), SELECT (n = 35,507), and SABOR (n = 1790) over median follow-up of 11.7, 8.1 and 9.0 years. The Cox model showed higher prostate-specific antigen (PSA), BMI and age, and African American race to be associated with PCa and HGPCa. Five-year risk predictions from the combined SELECT and PLCO model effectively discriminated risk in the SABOR cohort with C-index 0.76 (95% CI [0.72, 0.79]) for PCa, and 0.74 (95% CI [0.65,0.83]) for HGPCa. Conclusions A 1- to 5-year PCa risk prediction model developed from PLCO and SELECT was validated with SABOR and implemented online. This model can individualize and inform shared screening decisions.

Rationale: Pulmonary arterial hypertension (PAH) is an enigmatic and morbid disease where insights are emerging regarding genetic susceptibility. Genome-wide Association Studies (GWAS) have identified SOX17 as the most significant PAH-associated genomic locus. The allele of tag SNP in this locus is associated with 1.8-fold higher PAH risk. It has been challenging to define the mechanisms underlying the contribution of the PAH-associated functional SNPs (fSNPs) to pathogenesis of the disease. Methods: We developed a post-GWAS functional genomics strategy to define the causative fSNPs and identify the associated biological mechanisms. This analysis includes Reel-seq (Regulatory element-sequencing), an EMSA-based high-throughput technique to identify fSNPs in a synthetic DNA library containing PAH-associated SNPs; SDCP-MS (SNP-specific DNA competition pulldown-mass spectrometry) to identify proteins that specifically bind to fSNPs; and AIDP-Wb (allele-imbalanced DNA pulldown-Western blot) to show allele-imbalanced binding of these proteins to fSNPs. The regulation of risk gene expression by these fSNP-binding proteins and their pathogenicity were determined in human pulmonary arterial endothelial cells (PAECs) and confirmed in PAH animal models and patients. Results: By using high-throughput Reel-seq and subsequent validation with EMSA, intergenic SNP rs4738801 in SOX17 locus was identified as a fSNP from a library containing 254 PAH-associated haplotype SNPs. This fSNP resides in a remote upstream enhancer region of SOX17, an endothelial effector increasingly associated with PAH pathogenesis. Using SDCP-MS and AIDP-Wb, we found that the transcription factor FUBP1 binds to rs4738801 risk allele C with lower affinity than non-risk allele G, resulting in a decrease in SOX17 expression. FUBP1 and target gene SOX17 controlled PAH-associated pathophenotypes in PAECs, including proliferation, apoptosis, and angiogenesis. Downregulated by the major acquired PAH trigger hypoxia, FUBP1 and SOX17 were decreased in lungs and pulmonary ECs isolated from PAH patients and mouse models. A 3.77-fold enrichment of fSNP rs4738801 risk allele C was found in patients with PAH induced by hypoxia, but not in PAH associated with connective tissue disease or congenital heart disease. Conclusions: FUBP1 controls SOX17 expression via allele-specific binding to PAH-associated fSNP rs4738801. The reduced binding of FUBP1 to risk allele C defines the genomic architecture contributing to the SOX17-dependent genetic susceptibility of PAH. The downregulation of FUBP1-SOX17 by hypoxia results in endothelial dysfunction, contributing to the acquired pathogenesis of PAH. These findings identify a novel role of FUBP1 in the functional regulation of SOX17 locus and elucidating a pathogenic mechanism that combines the acquired PAH-triggering factors and altered genetic susceptibility.

This research is motivated from the data from a large Selenium and Vitamin E Cancer Prevention Trial (SELECT). The prostate specific antigens (PSAs) were collected longitudinally, and the survival endpoint was the time to low-grade cancer or the time to high-grade cancer (competing risks). In this article, the goal is to model the longitudinal PSA data and the time-to-prostate cancer (PC) due to low- or high-grade. We consider the low-grade and high-grade as two competing causes of developing PC. A joint model for simultaneously analysing longitudinal and time-to-event data in the presence of multiple causes of failure (or competing risk) is proposed within the Bayesian framework. The proposed model allows for handling the missing causes of failure in the SELECT data and implementing an efficient Markov chain Monte Carlo sampling algorithm to sample from the posterior distribution via a novel reparameterization technique. Bayesian criteria, ΔDICSurv, and ΔWAICSurv, are introduced to quantify the gain in fit in the survival sub-model due to the inclusion of longitudinal data. A simulation study is conducted to examine the empirical performance of the posterior estimates as well as ΔDICSurv and ΔWAICSurv and a detailed analysis of the SELECT data is also carried out to further demonstrate the proposed methodology.

Currently, it remains difficult to identify which single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) are functional and how various functional SNPs (fSNPs) interact and contribute to disease susceptibility. GWAS have identified a CD40 locus that is associated with rheumatoid arthritis (RA). We previously used two techniques developed in our laboratory, single nucleotide polymorphism-next-generation sequencing (SNP-seq) and flanking restriction enhanced DNA pulldown-mass spectrometry (FREP-MS), to determine that the RA risk gene RBPJ regulates CD40 expression via a fSNP at the RA-associated CD40 locus. In the present work, by applying the same approach, we report the identification of six proteins that regulate RBPJ expression via binding to two fSNPs on the RA-associated RBPJ locus. Using these findings, together with the published data, we constructed an RA-associated signal transduction and transcriptional regulation network (STTRN) that functionally connects multiple RA-associated risk genes via transcriptional regulation networks (TRNs) linked by CD40-induced nuclear factor kappa B (NF-kB) signaling. Remarkably, this STTRN provides insight into the potential mechanism of action for the histone deacetylase inhibitor givinostat, an approved therapy for systemic juvenile idiopathic arthritis. Thus, the generation of disease-associated STTRNs based on post-GWAS functional studies is demonstrated as a novel and effective approach to apply GWAS for mechanistic studies and target identification.