Tissue-specific multi-omics analysis of atrial fibrillation

Opportunities and challenges for the use of human samples in translational cardiovascular research: a scientific statement of the ESC Working Group on Cellular Biology of the Heart, the ESC Working Group on Cardiovascular Surgery, the ESC Council on Basic Cardiovascular Science, the ESC Scientists of Tomorrow, the European Association of Percutaneous Cardiovascular Interventions of the ESC, and the Heart Failure Association of the ESC

Animal models offer invaluable insights into disease mechanisms but cannot entirely mimic the variability and heterogeneity of human populations, nor the increasing prevalence of multi-morbidity. Consequently, employing human samples-such as whole blood or fractions, valvular and vascular tissues, myocardium, pericardium, or human-derived cells-is essential for enhancing the translational relevance of cardiovascular research. For instance, myocardial tissue slices, which preserve crucial structural and functional characteristics of the human heart, can be used in vitro to examine drug responses. Human blood serves as a rich source of biomarkers, including extracellular vesicles, various types of RNA (miRNA, lncRNA, and circRNAs), circulating inflammatory cells, and endothelial colony-forming cells, facilitating detailed studies of cardiovascular diseases. Primary cardiomyocytes and vascular cells isolated from human tissues are invaluable for mechanistic investigations in vitro. In cases where these are unavailable, human induced pluripotent stem cells serve as effective substitutes, albeit with specific limitations. However, the use of human samples presents challenges such as ethical approvals, tissue procurement and storage, variability in patient genetics and treatment regimens, and the selection of appropriate control samples. Biobanks are central to the efficient use of these scarce and valuable resources. This scientific statement discusses opportunities to implement the use of human samples for cardiovascular research within specific clinical contexts, offers a practical framework for acquiring and utilizing different human materials, and presents examples of human sample applications for specific cardiovascular diseases, providing a valuable resource for clinicians, translational and basic scientists engaged in cardiovascular research.

The Genetic Mechanisms and Pathology of Atrial Fibrillation: A Narrative Review

Atrial fibrillation (AF), the most prevalent tachyarrhythmia worldwide, is a complex condition influenced by genetic, structural, and environmental factors. While AF in the elderly is often associated with underlying cardiac disease, early-onset or "lone" AF (LAF) exhibits a stronger genetic predisposition. Studies have identified both monogenic and polygenic contributors to AF risk. Monogenic mutations, inherited in Mendelian patterns, often affect ion channels and regulatory proteins, while polygenic variants modulate susceptibility and interact with environmental factors. Genome-wide association studies (GWAS) and exosome-wide association studies (ExWAS) have expanded our understanding of AF genetics, identifying numerous susceptibility loci, though challenges remain in linking these variants to specific molecular mechanisms. Pathophysiologically, AF results from a balance of triggers, drivers, and substrates. Triggers, such as ectopic foci in the pulmonary veins, initiate AF episodes, while structural and electrical remodeling perpetuates the arrhythmia. Fibrosis, atrial dilation, and tachycardia-induced remodeling promote reentry circuits and irregular conduction, increasing AF vulnerability. The interplay between genetic predisposition and remodeling processes underscores the complexity of AF maintenance, particularly in persistent AF forms. Emerging insights into AF genetics and pathophysiology highlight the need for personalized approaches to its prevention and management. Understanding genetic risk, combined with targeted therapies addressing structural and electrical remodeling, holds promise for improved patient outcomes. Future research into AF's molecular and genetic mechanisms will be key to advancing precision medicine in this field.

Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues

Non-communicable diseases (NCDs) such as cardiovascular diseases, chronic respiratory diseases, cancers, diabetes, and mental health disorders pose a significant global health challenge, accounting for the majority of fatalities and disability-adjusted life years worldwide. These diseases arise from the complex interactions between genetic, behavioral, and environmental factors, necessitating a thorough understanding of these dynamics to identify effective diagnostic strategies and interventions. Although recent advances in multi-omics technologies have greatly enhanced our ability to explore these interactions, several challenges remain. These challenges include the inherent complexity and heterogeneity of multi-omic datasets, limitations in analytical approaches, and severe underrepresentation of non-European genetic ancestries in most omics datasets, which restricts the generalizability of findings and exacerbates health disparities. This scoping review evaluates the global landscape of multi-omics data related to NCDs from 2000 to 2024, focusing on recent advancements in multi-omics data integration, translational applications, and equity considerations. We highlight the need for standardized protocols, harmonized data-sharing policies, and advanced approaches such as artificial intelligence/machine learning to integrate multi-omics data and study gene-environment interactions. We also explore challenges and opportunities in translating insights from gene-environment (GxE) research into precision medicine strategies. We underscore the potential of global multi-omics research in advancing our understanding of NCDs and enhancing patient outcomes across diverse and underserved populations, emphasizing the need for equity and fairness-centered research and strategic investments to build local capacities in underrepresented populations and regions.

The combination of decitabine with multi-omics confirms the regulatory pattern of the correlation between DNA methylation of the CACNA1C gene and atrial fibrillation

Background

Studies have shown that DNA methylation of the CACNA1C gene is involved in the pathogenesis of various diseases and the mechanism of drug action. However, its relationship with atrial fibrillation (AF) remains largely unexplored.

Objective

To investigate the association between DNA methylation of the CACNA1C gene and AF by combining decitabine (5-Aza-2'-deoxycytidine, AZA) treatment with multi-omics analysis.

Methods

HepG2 cells were treated with AZA to observe the expression of the CACNA1C gene, which was further validated using gene expression microarrays. Pyrosequencing was employed to validate differentially methylated sites of the CACNA1C gene observed in DNA methylation microarrays. A custom DNA methylation dataset based on the MSigDB database was combined with ChIP-sequencing and RNA-sequencing data to explore the regulatory patterns of DNA methylation of the CACNA1C gene.

Results

Treatment of HepG2 cells with three different concentrations of AZA (2.5 µM, 5.0 µM, and 10.0 µM) resulted in 1.6, 2.5, and 2.9-fold increases in the mRNA expression of the CACNA1C gene, respectively, compared to the DMSO group, with statistical significance at the highest concentration group (p < 0.05). Similarly, AZA treatment of T47D cells showed upregulated mRNA expression of the CACNA1C gene in the gene expression microarray results (adj P < 0.05). DNA methylation microarray analysis revealed that methylation of a CpG site in intron 30 of the CACNA1C gene may be associated with AF (adj P < 0.05). Pyrosequencing of this site and its adjacent two CpG sites demonstrated significant differences in DNA methylation levels between AF and sinus rhythm groups (p < 0.05). Subsequent multivariate logistic regression models confirmed that the DNA methylation degree of these three sites and their average was associated with AF (p < 0.05). Additionally, the UCSC browser combined with ChIP-sequencing revealed that the aforementioned region was enriched in enhancer markers H3K27ac and H3K4me1. Differential expression and pathway analysis of RNA-sequencing data ultimately identified ATF7IP and KAT2B genes as potential regulators of the CACNA1C gene.

Conclusion

The DNA methylation levels at three CpG sites in intron 30 of the CACNA1C gene are associated with AF status, and potentially regulated by ATF7IP and KAT2B.

PITX2 deficiency leads to atrial mitochondrial dysfunction

AIMS

Reduced left atrial PITX2 is associated with atrial cardiomyopathy and atrial fibrillation (AF). PITX2 is restricted to left atrial cardiomyocytes (aCMs) in the adult heart. The links between PITX2 deficiency, atrial cardiomyopathy, and AF are not fully understood.

METHODS AND RESULTS

To identify mechanisms linking PITX2 deficiency to AF, we generated and characterized PITX2-deficient human aCMs derived from human induced pluripotent stem cells (hiPSC) and their controls. PITX2-deficient hiPSC-derived atrial cardiomyocytes showed shorter and disorganized sarcomeres and increased mononucleation. Electron microscopy found an increased number of smaller mitochondria compared with isogenic controls. Mitochondrial protein expression was altered in PITX2-deficient hiPSC-derived atrial cardiomyocytes. Single-nuclear RNA-sequencing found differences in cellular respiration pathways and differentially expressed mitochondrial and ion channel genes in PITX2-deficient hiPSC-derived atrial cardiomyocytes. PITX2 repression in hiPSC-derived atrial cardiomyocytes replicated dysregulation of cellular respiration. Mitochondrial respiration was shifted to increased glycolysis in PITX2-deficient hiPSC-derived atrial cardiomyocytes. PITX2-deficient human hiPSC-derived atrial cardiomyocytes showed higher spontaneous beating rates. Action potential duration was more variable with an overall prolongation of early repolarization, consistent with metabolic defects. Gene expression analyses confirmed changes in mitochondrial genes in left atria from 42 patients with AF compared with 43 patients with sinus rhythm. Dysregulation of left atrial mitochondrial (COX7C) and metabolic (FOXO1) genes was associated with PITX2 expression in human left atria.

CONCLUSION

PITX2 deficiency causes atrial mitochondrial dysfunction and a metabolic shift to glycolysis in human aCMs. PITX2-dependent metabolic changes can contribute to the structural and functional defects found in PITX2-deficient atria.

Atrial fibrillation variant-to-gene prioritization through cross-ancestry eQTL and single-nucleus multiomic analyses

Atrial fibrillation (AF) is the most common arrhythmia in the world. Human genetics can provide strong AF therapeutic candidates, but the identification of the causal genes and their functions remains challenging. Here, we applied an AF fine-mapping strategy that leverages results from a previously published cross-ancestry genome-wide association study (GWAS), expression quantitative trait loci (eQTLs) from left atrial appendages (LAAs) obtained from two cohorts with distinct ancestry, and a paired RNA sequencing (RNA-seq) and ATAC sequencing (ATAC-seq) LAA single-nucleus assay (sn-multiome). At nine AF loci, our co-localization and fine-mapping analyses implicated 14 genes. Data integration identified several candidate causal AF variants, including rs7612445 at GNB4 and rs242557 at MAPT. Finally, we showed that the repression of the strongest AF-associated eQTL gene, LINC01629, in human embryonic stem cell-derived cardiomyocytes using CRISPR inhibition results in the dysregulation of pathways linked to genes involved in the development of atrial tissue and the cardiac conduction system.

CDK5R1, GSE1, HSPG2 and WDFY3 as indirect epigenetic-sensitive genes in atrial fibrillation

BACKGROUND

Although mounting evidence supports that aberrant DNA methylation occurs in the hearts of patients with atrial fibrillation (AF), noninvasive epigenetic characterization of AF has not yet been defined.

METHODS

We investigated DNA methylome changes in peripheral blood CD4+ T cells isolated from 10 patients with AF relative to 11 healthy subjects (HS) who were enrolled in the DIANA clinical trial (NCT04371809) via reduced-representation bisulfite sequencing (RRBS).

RESULTS

An atrial-specific PPI network revealed 18 hub differentially methylated genes (DMGs), wherein ROC curve analysis revealed reasonable diagnostic performance of DNA methylation levels found within CDK5R1 (AUC = 0.76; p = 0.049), HSPG2 (AUC = 0.77; p = 0.038), WDFY3 (AUC = 0.78; p = 0.029), USP49 (AUC = 0.76; p = 0.049), GSE1 (AUC = 0.76; p = 0.049), AIFM1 (AUC = 0.76; p = 0.041), CDK5RAP2 (AUC = 0.81; p = 0.017), COL4A1 (AUC = 0.86; p < 0.001), SEPT8 (AUC = 0.90; p < 0.001), PFDN1 (AUC = 0.90; p < 0.01) and ACOT7 (AUC = 0.78; p = 0.032). Transcriptional profiling of the hub DMGs provided a significant overexpression of PSDM6 (p = 0.004), TFRC (p = 0.01), CDK5R1 (p < 0.001), HSPG2 (p = 0.01), WDFY3 (p < 0.001), USP49 (p = 0.004) and GSE1 (p = 0.021) in AF patients vs HS.

CONCLUSIONS

CDK5R1, GSE1, HSPG2 and WDFY3 resulted the best discriminatory genes both at methylation and gene expression level. Our results provide several candidate diagnostic biomarkers with the potential to advance precision medicine in AF.

WITHDRAWN: The effect of ischemia on expression quantitative trait loci (eQTL) in human myocardium and insights into myocardial injury etiology

26 February, 2024. Research Square has withdrawn this preprint as it was submitted and made public without the full consent of all the authors and without the full consent of the principle investigator of the registered clinical trial. Therefore, this work should not be cited as a reference.

Atrial fibrillation: pathophysiology, genetic and epigenetic mechanisms

Atrial fibrillation (AF) is the most common supraventricular arrhythmia affecting up to 1% of the general population. Its prevalence dramatically increases with age and could reach up to ∼10% in the elderly. The management of AF is a complex issue that is object of extensive ongoing basic and clinical research, it depends on its genetic and epigenetic causes, and it varies considerably geographically and also according to the ethnicity. Mechanistically, over the last decade, Genome Wide Association Studies have uncovered over 100 genetic loci associated with AF, and have shown that European ancestry is associated with elevated risk of AF. These AF-associated loci revolve around different types of disturbances, including inflammation, electrical abnormalities, and structural remodeling. Moreover, the discovery of epigenetic regulatory mechanisms, involving non-coding RNAs, DNA methylation and histone modification, has allowed unravelling what modifications reshape the processes leading to arrhythmias. Our review provides a current state of the field regarding the identification and functional characterization of AF-related genetic and epigenetic regulatory networks, including ethnic differences. We discuss clear and emerging connections between genetic regulation and pathophysiological mechanisms of AF.

Impact of rs1805127 and rs55742440 Variants on Atrial Remodeling in Hypertrophic Cardiomyopathy Patients with Atrial Fibrillation: A Romanian Cohort Study

Atrial fibrillation (AFib) is characterized by a complex genetic component. We aimed to investigate the association between variations in genes related to cardiac ion handling and AFib in a cohort of Romanian patients with hypertrophic cardiomyopathy (HCM). Forty-five unrelated probands with HCM were genotyped by targeted next-generation sequencing (NGS) for 24 genes associated with cardiac ion homeostasis. Subsequently, the study cohort was divided into two groups based on the presence (AFib+) or absence (AFiB-) of AFib detected during ECG monitoring. We identified two polymorphisms (rs1805127 located in KCNE1 and rs55742440 located in SCN1B) linked to AFib susceptibility. In AFib+, rs1805127 was associated with increased indexed left atrial (LA) maximal volume (LAVmax) (58.42 ± 21 mL/m2 vs. 32.54 ± 6.47 mL/m2, p < 0.001) and impaired LA strain reservoir (LASr) (13.3 ± 7.5% vs. 24.4 ± 6.8%, p < 0.05) compared to those without respective variants. The rs55742440 allele was less frequent in patients with AFib+ (12 out of 25, 48%) compared to those without arrhythmia (15 out of 20, 75%, p = 0.05). Also, AFib+ rs55742440 carriers had significantly lower LAVmax compared to those who were genotype negative. Among patients with HCM and AFib+, the rs1805127 variant was accompanied by pronounced LA remodeling, whereas rs55742440's presence was related to a milder LA enlargement.

Identification of a Novel Target Implicated in Chronic Obstructive Sleep Apnea-Related Atrial Fibrillation by Integrative Analysis of Transcriptome and Proteome

Objective

This study aimed to identify a newly identified target involved in atrial fibrillation (AF) linked to chronic obstructive sleep apnea (COSA) through an integrative analysis of transcriptome and proteome.

Methods

Fifteen beagle canines were randomly assigned to three groups: control (CON), obstructive sleep apnea (OSA), and OSA with superior left ganglionated plexi ablation (OSA+GP). A COSA model was established by intermittently obstructing the endotracheal cannula during exhalation for 12 weeks. Left parasternal thoracotomy through the fourth intercostal space allowed for superior left ganglionated plexi (SLGP) ablation. In vivo open-chest electrophysiological programmed stimulation was performed to assess AF inducibility. Histological, transcriptomic, and proteomic analyses were conducted on atrial samples.

Results

After 12 weeks, the OSA group exhibited increased AF inducibility and longer AF durations compared to the CON group. Integrated transcriptomic and proteomic analyses identified 2422 differentially expressed genes (DEGs) and 1194 differentially expressed proteins (DEPs) between OSA and CON groups, as well as between OSA+GP and OSA groups (1850 DEGs and 1418 DEPs). The analysis revealed that differentially regulated DEGs were primarily enriched in mitochondrial biological processes in the CON-vs.-OSA and OSA-vs.-GP comparisons. Notably, the key regulatory molecule GSTZ1 was activated in OSA and inhibited by GP ablation.

Conclusion

These findings suggest that GSTZ1 may play a pivotal role in mitochondrial damage, triggering AF substrate formation, and increasing susceptibility to AF in the context of COSA.

PET/CT-identified atrial hypermetabolism is an index of atrial inflammation in patients with atrial fibrillation

BACKGROUND

Although atrial inflammation has been implicated in the pathophysiology of atrial fibrillation (AF), the identification of atrial inflammation remains challenging. We aimed to establish a positron emission tomography/computed tomography (PET/CT) protocol with 18Fluor-labeled fluorodeoxyglucose (18F-FDG) for the detection of atrial hypermetabolism as surrogate for inflammation in AF.

METHODS

We included n = 75 AF and n = 75 non-AF patients undergoing three common PET/CT protocols (n = 25 per group) optimized for the detection of (a) inflammation and (b) malignancy in predefined fasting protocols, and (c) cardiac viability allowing for maximized glucose uptake. 18F-FDG-uptake was analyzed in predefined loci.

RESULTS

Differences of visual atrial uptake in AF vs non-AF patients were observed in fasting (inflammation [13/25 vs 0/25] and malignancy [10/25 vs 0/25]) protocols while viability protocols showed non-specific uptake in both the groups. In the inflammation protocol, AF patients showed higher uptake in the right atrium [(SUVmax: 2.5 ± .7 vs 2.0 ± .7, P = .01), atrial appendage (SUVmax: 2.4 ± .7 vs 2.0 ± .6, P = .03), and epicardial adipose tissue (SUVmax: 1.4 ± .5 vs 1.1 ± .4, P = .04)]. Malignancy and viability protocols failed to differentiate between AF and non-AF.

CONCLUSION

Glucose uptake suppression protocols appear suitable in detecting differential atrial 18F-FDG uptake between AF and non-AF patients. Imaging-based assessment of inflammation might help to stratify AF patients offering individualized therapeutic approaches.

Beyond the Rhythm: In Silico Identification of Key Genes and Therapeutic Targets in Atrial Fibrillation

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia worldwide and is characterized by a high risk of thromboembolism, ischemic stroke, and fatality. The precise molecular mechanisms of AF pathogenesis remain unclear. The purpose of this study was to use bioinformatics tools to identify novel key genes in AF, provide deeper insights into the molecular pathogenesis of AF, and uncover potential therapeutic targets. Four publicly available raw RNA-Seq datasets obtained through the ENA Browser, as well as proteomic analysis results, both derived from atrial tissues, were used in this analysis. Differential gene expression analysis was performed and cross-validated with proteomics results to identify common genes/proteins between them. A functional enrichment pathway analysis was performed. Cross-validation analysis revealed five differentially expressed genes, namely FGL2, IGFBP5, NNMT, PLA2G2A, and TNC, in patients with AF compared with those with sinus rhythm (SR). These genes play crucial roles in various cardiovascular functions and may be part of the molecular signature of AF. Furthermore, functional enrichment analysis revealed several pathways related to the extracellular matrix, inflammation, and structural remodeling. This study highlighted five key genes that constitute promising candidates for further experimental exploration as biomarkers as well as therapeutic targets for AF.

AI-powered therapeutic target discovery

Disease modeling and target identification are the most crucial initial steps in drug discovery, and influence the probability of success at every step of drug development. Traditional target identification is a time-consuming process that takes years to decades and usually starts in an academic setting. Given its advantages of analyzing large datasets and intricate biological networks, artificial intelligence (AI) is playing a growing role in modern drug target identification. We review recent advances in target discovery, focusing on breakthroughs in AI-driven therapeutic target exploration. We also discuss the importance of striking a balance between novelty and confidence in target selection. An increasing number of AI-identified targets are being validated through experiments and several AI-derived drugs are entering clinical trials; we highlight current limitations and potential pathways for moving forward.

Changes of ubiquitylated proteins in atrial fibrillation associated with heart valve disease: proteomics in human left atrial appendage tissue

Background

Correlations between posttranslational modifications and atrial fibrillation (AF) have been demonstrated in recent studies. However, it is still unclear whether and how ubiquitylated proteins relate to AF in the left atrial appendage of patients with AF and valvular heart disease.

Methods

Through LC-MS/MS analyses, we performed a study on tissues from eighteen subjects (9 with sinus rhythm and 9 with AF) who underwent cardiac valvular surgery. Specifically, we explored the ubiquitination profiles of left atrial appendage samples.

Results

In summary, after the quantification ratios for the upregulated and downregulated ubiquitination cutoff values were set at >1.5 and <1:1.5, respectively, a total of 271 sites in 162 proteins exhibiting upregulated ubiquitination and 467 sites in 156 proteins exhibiting downregulated ubiquitination were identified. The ubiquitylated proteins in the AF samples were enriched in proteins associated with ribosomes, hypertrophic cardiomyopathy (HCM), glycolysis, and endocytosis.

Conclusions

Our findings can be used to clarify differences in the ubiquitination levels of ribosome-related and HCM-related proteins, especially titin (TTN) and myosin heavy chain 6 (MYH6), in patients with AF, and therefore, regulating ubiquitination may be a feasible strategy for AF.

Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review

Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.

Prognostic Value of EMT Gene Signature in Malignant Mesothelioma

Malignant mesothelioma (MESO) consists of epithelioid, biphasic, and sarcomatoid subtypes with different epithelial-mesenchymal transition (EMT) phenotypes. We previously identified a panel of four MESO EMT genes correlating with an immunosuppressive tumor microenvironment and poor survival. In this study, we investigated the correlation between these MESO EMT genes, the immune profile, and the genomic and epigenomic alterations to identify potential therapeutic targets to prevent or reverse the EMT process. Using multiomic analysis, we observed that the MESO EMT genes were positively correlated with hypermethylation of epigenetic genes and loss of CDKN2A/B expression. MESO EMT genes such as COL5A2, ITGAV, SERPINH1, CALD1, SPARC, and ACTA2 were associated with upregulation of TGF-β signaling, hedgehog signaling, and IL-2-STAT5 signaling and downregulation of the IFN-α and IFN-γ response. Immune checkpoints such as CTLA4, CD274 (PD-L1), PDCD1LG2 (PD-L2), PDCD1 (PD-1), and TIGIT were upregulated, while LAG3, LGALS9, and VTCN1 were downregulated with the expression of MESO EMT genes. CD160, KIR2DL1, and KIR2DL3 were also broadly downregulated with the expression of MESO EMT genes. In conclusion, we observed that the expression of a panel of MESO EMT genes was associated with hypermethylation of epigenetic genes and loss of expression of CDKN2A and CDKN2B. Expression of MESO EMT genes was associated with downregulation of the type I and type II IFN response, loss of cytotoxicity and NK cell activity, and upregulation of specific immune checkpoints, as well as upregulation of the TGF-β1/TGFBR1 pathway.

Integration of Candida albicans-induced single-cell gene expression data and secretory protein concentrations reveal genetic regulators of inflammation

Both gene expression and protein concentrations are regulated by genetic variants. Exploring the regulation of both eQTLs and pQTLs simultaneously in a context- and cell-type dependent manner may help to unravel mechanistic basis for genetic regulation of pQTLs. Here, we performed meta-analysis of Candida albicans-induced pQTLs from two population-based cohorts and intersected the results with Candida-induced cell-type specific expression association data (eQTL). This revealed systematic differences between the pQTLs and eQTL, where only 35% of the pQTLs significantly correlated with mRNA expressions at single cell level, indicating the limitation of eQTLs use as a proxy for pQTLs. By taking advantage of the tightly co-regulated pattern of the proteins, we also identified SNPs affecting protein network upon Candida stimulations. Colocalization of pQTLs and eQTLs signals implicated several genomic loci including MMP-1 and AMZ1. Analysis of Candida-induced single cell gene expression data implicated specific cell types that exhibit significant expression QTLs upon stimulation. By highlighting the role of trans-regulatory networks in determining the abundance of secretory proteins, our study serve as a framework to gain insights into the mechanisms of genetic regulation of protein levels in a context-dependent manner.