The aryl hydrocarbon receptor (AHR) is a nuclear receptor that modulates the response to environmental stimuli. It was recognized historically for its role in toxicology but, in recent decades, it has been increasingly recognized as an important modulator of disease—especially for its role in modulating immune and inflammatory responses. AHR has been implicated in many diseases that are driven by immune/inflammatory processes, including major depressive disorder, multiple sclerosis, rheumatoid arthritis, asthma, and allergic responses, among others. The mechanisms by which AHR has been suggested to impact immune/inflammatory diseases include targeted gene expression and altered immune differentiation. It has been suggested that single nucleotide polymorphisms (SNPs) that are near AHR-regulated genes may contribute to AHR-dependent disease mechanisms/pathways. Further, we have found that SNPs that are outside of nuclear receptor binding sites (i.e., outside of AHR response elements (AHREs)) may contribute to AHR-dependent gene regulation in a SNP- and ligand-dependent manner. This review will discuss the evidence and mechanisms of AHR contributions to immune/inflammatory diseases and will consider the possibility that SNPs that are outside of AHR binding sites might contribute to AHR ligand-dependent inter-individual variation in disease pathophysiology and response to pharmacotherapeutics.

Triple-negative breast cancer (TNBC) is a heterogeneous disease with poor prognosis that lacks targeted therapies, especially in patients with chemotherapy-resistant disease. Since DNA methylation-induced silencing of tumor suppressors is common in cancer, reversal of promoter DNA hypermethylation by 5-aza-2′-deoxycytidine (decitabine), an FDA-approved DNA methyltransferase (DNMT) inhibitor, has proven effective in treating hematological neoplasms. However, its antitumor effect varies in solid tumors, stressing the importance of identifying biomarkers predictive of therapeutic response. Here, we focused on the identification of biomarkers to select decitabine-sensitive TNBC through increasing our understanding of the mechanism of decitabine action. We showed that protein levels of DNMTs correlated with response to decitabine in patient-derived xenograft (PDX) organoids originating from chemotherapy-sensitive and -resistant TNBCs, suggesting DNMT levels as potential biomarkers of response. Furthermore, all 3 methytransferases, DNMT1, DNMT3A, and DNMT3B, were degraded following low-concentration, long-term decitabine treatment both in vitro and in vivo. The DNMT proteins could be ubiquitinated by the E3 ligase, TNF receptor–associated factor 6 (TRAF6), leading to lysosome-dependent protein degradation. Depletion of TRAF6 blocked decitabine-induced DNMT degradation, conferring resistance to decitabine. Our study suggests a potential mechanism of regulating DNMT protein degradation and DNMT levels as response biomarkers for DNMT inhibitors in TNBCs.

Cardiac fibrosis, a hallmark of heart failure and various cardiomyopathies, represents a complex pathological process that has long challenged therapeutic intervention. High-throughput omics technologies have begun revolutionizing our understanding of the molecular mechanisms driving cardiac fibrosis and are providing unprecedented insights into its heterogeneity and progression. This review provides a comprehensive analysis of how techniques—encompassing genomics, epigenomics, transcriptomics, proteomics, and metabolomics—are providing insight into our understanding of cardiac fibrosis. Genomic studies have identified novel genetic variants and regulatory networks associated with fibrosis susceptibility and progression, and single-cell transcriptomics has unveiled distinct cardiac fibroblast subpopulations with unique molecular signatures. Epigenomic profiling has revealed dynamic chromatin modifications controlling fibroblast activation states, and proteomic analyses have identified novel biomarkers and potential therapeutic targets. Metabolomic studies have uncovered important alterations in cardiac energetics and substrate utilization during fibrotic remodeling. The integration of these multi-omic data sets has led to the identification of previously unrecognized pathogenic mechanisms and potential therapeutic targets, including cell-type-specific interventions and metabolic modulators. We discuss how these advances are driving the development of precision medicine approaches for cardiac fibrosis while highlighting current challenges and future directions in translating multi-omic insights into effective therapeutic strategies. This review provides a systems-level perspective on cardiac fibrosis that may inform the development of more effective, personalized therapeutic approaches for heart failure and related cardiovascular diseases.

Millions of patients suffer from major depressive disorder (MDD), but many do not respond to selective serotonin reuptake inhibitor (SSRI) therapy. We used a pharmacometabolomics-informed pharmacogenomics research strategy to identify genes associated with metabolites that were related to SSRI response. Specifically, 306 MDD patients were treated with citalopram or escitalopram and blood was drawn at baseline, 4 and 8 weeks for blood drug levels, genome-wide single nucleotide polymorphism (SNP) genotyping and metabolomic analyses. SSRI treatment decreased plasma serotonin concentrations (P<0.0001). Baseline and plasma serotonin concentration changes were associated with clinical outcomes (P<0.05). Therefore, baseline and serotonin concentration changes were used as phenotypes for genome-wide association studies (GWAS). GWAS for baseline plasma serotonin concentrations revealed a genome-wide significant (P=7.84E-09) SNP cluster on chromosome four 5’ of TSPAN5 and a cluster across ERICH3 on chromosome one (P=9.28E-08) that were also observed during GWAS for change in serotonin at 4 (P=5.6E-08 and P=7.54E-07, respectively) and 8 weeks (P=1.25E-06 and P=3.99E-07, respectively). The SNPs on chromosome four were expression quantitative trait loci for TSPAN5. Knockdown (KD) and overexpression (OE) of TSPAN5 in a neuroblastoma cell line significantly altered the expression of serotonin pathway genes (TPH1, TPH2, DDC and MAOA). Chromosome one SNPs included two ERICH3 nonsynonymous SNPs that resulted in accelerated proteasome-mediated degradation. In addition, ERICH3 and TSPAN5 KD and OE altered media serotonin concentrations. Application of a pharmacometabolomics-informed pharmacogenomic research strategy, followed by functional validation, indicated that TSPAN5 and ERICH3 are associated with plasma serotonin concentrations and may have a role in SSRI treatment outcomes.

Metabolomics provides valuable tools for the study of drug effects, unraveling the mechanism of action and variation in response due to treatment. In this study we used electrochemistry-based targeted metabolomics to gain insights into the mechanisms of action of escitalopram/citalopram focusing on a set of 31 metabolites from neurotransmitter-related pathways. Overall, 290 unipolar patients with major depressive disorder were profiled at baseline, after 4 and 8 weeks of drug treatment. The 17-item Hamilton Depression Rating Scale (HRSD₁₇) scores gauged depressive symptom severity. More significant metabolic changes were found after 8 weeks than 4 weeks post baseline.Within the tryptophan pathway, we noted significant reductions in serotonin (5HT) and increases in indoles that are known to be influenced by human gut microbial cometabolism. 5HT, 5-hydroxyindoleacetate (5HIAA), and the ratio of 5HIAA/5HT showed significant correlations to temporal changes in HRSD₁₇scores.In the tyrosine pathway, changes were observed in the end products of the catecholamines, 3-methoxy-4-hydroxyphenylethyleneglycol and vinylmandelic acid. Furthermore, two phenolic acids, 4-hydroxyphenylacetic acid and 4-hydroxybenzoic acid, produced through noncanconical pathways, were increased with drug exposure.In the purine pathway, significant reductions in hypoxanthine and xanthine levels were observed. Examination of metabolite interactions through differential partial correlation networks revealed changes in guanosine–homogentisic acid and methionine–tyrosine interactions associated with HRSD₁₇. Genetic association studies using the ratios of these interacting pairs of metabolites highlighted two genetic loci harboring genes previously linked to depression, neurotransmission, or neurodegeneration. Overall, exposure to escitalopram/citalopram results in shifts in metabolism through noncanonical pathways, which suggest possible roles for the gut microbiome, oxidative stress, and inflammation-related mechanisms.

Major depressive disorder (MDD) is a heterogeneous disease. Efforts to identify biomarkers for sub-classifying MDD and antidepressant therapy by genome-wide association studies (GWAS) alone have generally yielded disappointing results. We applied a metabolomics-informed genomic research strategy to study the contribution of genetic variation to MDD pathophysiology by assaying 31 metabolites, including compounds from the tryptophan, tyrosine, and purine pathways, in plasma samples from 290 MDD patients. Associations of metabolite concentrations with depressive symptoms were determined, followed by GWAS for selected metabolites and functional validation studies of the genes identified. Kynurenine (KYN), the baseline plasma metabolite that was most highly associated with depressive symptoms, was negatively correlated with severity of those symptoms. GWAS for baseline plasma KYN concentrations identified SNPs across the beta-defensin 1 (DEFB1) and aryl hydrocarbon receptor (AHR) genes that were cis-expression quantitative trait loci (eQTLs) forDEFB1andAHRmRNA expression, respectively. Furthermore, theDEFB1locus was associated with severity of MDD symptoms in a larger cohort of 803 MDD patients. Functional studies demonstrated that DEFB1 could neutralize lipopolysaccharide-stimulated expression of KYN-biosynthesizing enzymes in monocytic cells, resulting in altered KYN concentrations in the culture media. In addition, we demonstrated that AHR was involved in regulating the expression of enzymes in the KYN pathway and altered KYN biosynthesis in cell lines of hepatocyte and astrocyte origin. In conclusion, these studies identified SNPs that were cis-eQTLs forDEFB1andAHRand, which were associated with variation in plasma KYN concentrations that were related to severity of MDD symptoms.