…

The convergence of psoriasis and depression within a single patient is far more than a coincidental pairing of two common conditions; it represents a measurable biological phenomenon in which chronic peripheral inflammation reshapes brain chemistry, mood regulation, and behavior. Epidemiological surveys across multiple countries have consistently found that individuals with moderate to severe psoriasis face roughly a one-and-a-half to two-fold increased risk of developing major depressive disorder compared with the general population, and the relationship appears to run in both directions. People with depression show altered immune profiles that can exacerbate inflammatory skin disease, while the visible and often stigmatizing nature of psoriatic lesions generates psychosocial stress that feeds back into the inflammatory loop. Understanding the molecular threads that tie these two disorders together has therefore become a priority for researchers seeking interventions that address the comorbidity as a unified disease process rather than as two separate clinical problems.

The study under discussion approached this question by combining several complementary analytical strategies, each of which addresses a different limitation of conventional observational research. Observational studies of psoriasis and depression are notoriously vulnerable to confounding: shared risk factors such as obesity, smoking, alcohol use, sleep disturbance, and socioeconomic adversity influence both conditions independently, making it difficult to determine whether the association reflects causation or shared predisposition. Mendelian randomization offers a way around this obstacle by exploiting the random allocation of genetic variants at conception. Because alleles are inherited independently of environmental exposures and lifestyle factors, genetic variants that influence gene expression can serve as proxies—so-called instrumental variables—for testing whether altered expression of a particular gene causally affects disease risk. When the researchers used expression quantitative trait loci, or eQTLs, from the eQTLGen consortium as instruments, they identified 340 gene-expression signals associated with psoriasis and 307 associated with depression, of which only nine genes showed evidence of causal involvement in both directions. This small intersection is itself informative: it suggests that the molecular overlap between the two disorders is concentrated in a limited set of genes rather than being distributed diffusely across the genome, narrowing the search space for therapeutic targets considerably.

The nine intersecting genes were then subjected to least absolute shrinkage and selection operator regression, a machine learning technique designed to identify the most predictive features from a larger candidate pool while guarding against overfitting. LASSO works by applying a penalty that shrinks the coefficients of less informative variables toward zero, effectively forcing the model to rely on only the most robust predictors. From this procedure, four genes emerged as central hubs: MAP3K20, WARS2, TBXAS1, and ABHD15. Each of these genes carries a distinct biological profile that helps explain how a skin-limited inflammatory disease and a neuropsychiatric condition could share common molecular ground.

MAP3K20, better known in the literature as ASK1, encodes a mitogen-activated protein kinase kinase kinase that sits at a critical junction in cellular stress signaling. It activates the p38 and JNK pathways in response to oxidative stress, endoplasmic reticulum stress, and inflammatory cytokines such as tumor necrosis factor-alpha. In the context of psoriasis, MAP3K20 signaling in keratinocytes contributes to the proliferative and pro-inflammatory responses that characterize plaque formation. In neural tissue, the same pathway has been implicated in stress-induced neuronal dysfunction and in the neuroinflammatory responses associated with depressive-like behavior in animal models. The dual role of MAP3K20 in both epithelial inflammation and stress-responsive neural signaling makes it a plausible molecular bridge between the two conditions.

WARS2 encodes tryptophanyl-tRNA synthetase, the mitochondrial enzyme responsible for charging transfer RNA molecules with tryptophan during protein synthesis. This gene occupies an intriguing position at the intersection of several pathways relevant to the comorbidity. Tryptophan is not only a building block for proteins but also the precursor for serotonin synthesis, and disruptions in tryptophan availability or metabolism have long been linked to mood disorders. Moreover, tryptophan is diverted along the kynurenine pathway during inflammation, generating neuroactive metabolites that can be either neuroprotective or neurotoxic depending on the enzymatic context. Chronic inflammatory conditions like psoriasis shift tryptophan metabolism toward kynurenine, potentially reducing serotonin availability in the brain while simultaneously producing metabolites that influence glutamate signaling and neuronal survival. A gene that governs tryptophan handling at the cellular level therefore connects inflammatory metabolism directly to monoamine neurotransmission.

TBXAS1 encodes thromboxane A synthase 1, the enzyme that converts prostaglandin H2 into thromboxane A2, a potent vasoconstrictor and platelet aggregator. Thromboxane signaling is well established in cardiovascular biology, and elevated thromboxane production is a recognized feature of the systemic inflammatory state that accompanies psoriasis and contributes to the elevated cardiovascular risk observed in these patients. Less widely appreciated is the role of thromboxane signaling in the central nervous system, where it influences microglial activation, neurovascular function, and inflammatory signaling within the brain. The presence of TBXAS1 among the shared genes suggests that prostanoid metabolism may represent a conduit through which peripheral inflammatory signals generated in psoriatic skin and vasculature are translated into neuroinflammatory changes relevant to depression.

ABHD15, the least characterized of the four, encodes a protein that functions as a regulator of lipolysis and has been implicated in metabolic signaling pathways. Its identification in this analysis points toward the metabolic dimension of the comorbidity. Psoriasis is strongly associated with metabolic syndrome, insulin resistance, and dyslipidemia, and depression likewise shows consistent associations with altered lipid metabolism and insulin signaling. The enrichment results reported in the study highlighted cholesterol metabolism as one of the pathways in which the four hub genes participate, reinforcing the idea that lipid biology constitutes a shared mechanistic layer between the two disorders.

Pathway enrichment analysis of these four genes revealed convergence on the interleukin-17 signaling cascade, nuclear factor kappa B activation, and FoxO transcription factor regulation. The IL-17 pathway is the signature immune axis of psoriasis, and biologic drugs targeting IL-17 or its receptor have transformed the treatment of moderate to severe disease. NF-kappa B serves as a master transcriptional regulator of inflammatory gene expression across virtually all cell types, integrating signals from cytokine receptors, pattern recognition receptors, and stress pathways into coordinated transcriptional responses. FoxO transcription factors, meanwhile, govern cellular responses to oxidative stress, regulate autophagy, and influence neuronal survival. The convergence of all four hub genes on these pathways suggests that the comorbidity operates through a self-reinforcing circuit in which IL-17-driven inflammation activates NF-kappa B in both peripheral immune cells and central nervous system cells, while FoxO-mediated stress responses determine whether cells succumb to or survive the inflammatory assault.

Perhaps the most novel finding to emerge from the single-cell sequencing component of the analysis was the connection to ferroptosis, a form of regulated cell death discovered relatively recently and defined by its dependence on iron-catalyzed lipid peroxidation. Unlike apoptosis or necroptosis, ferroptosis is driven by oxidative damage to lipid membranes and is suppressed by the glutathione peroxidase 4 enzyme and by system xc-mediated cystine import. Ferroptosis has been implicated in a growing list of inflammatory and neurodegenerative conditions, and its involvement in both psoriatic keratinocytes and depressive neurocircuitry represents an emerging area of investigation. In the skin, ferroptotic death of keratinocytes can release damage-associated molecular patterns that amplify inflammatory signaling, potentially perpetuating the psoriatic cycle. In the brain, ferroptosis of neurons and oligodendrocytes has been linked to the hippocampal atrophy and synaptic dysfunction observed in chronic stress models and in patients with major depression. The correlation between the four hub genes and ferroptosis markers identified in this study suggests that iron-dependent lipid peroxidation may serve as a downstream execution mechanism through which chronic inflammation translates into cellular damage in both organ systems.

The single-cell transcriptomic data added a layer of cellular resolution that bulk RNA sequencing cannot provide. By examining individual cells from psoriatic skin lesions and from brain-related tissue in depression cohorts, the researchers were able to determine which cell populations express the four hub genes and how that expression changes in disease states. This cell-type-specific localization matters because the same gene can perform entirely different functions depending on whether it is expressed in keratinocytes, endothelial cells, infiltrating neutrophils, microglia, or neurons. The finding that the hub genes show enrichment in specific immune cell populations and correlate with patterns of immune infiltration provides a spatial framework for understanding how molecular signals propagate across tissue boundaries.

Turning from mechanism to therapeutics, the researchers queried the Comparative Toxicogenomics Database, a publicly available resource that catalogs interactions between chemicals, genes, and diseases, to identify compounds that might modulate the activity of the four hub genes. Among the candidates that emerged, folic acid stood out for its ability to target three of the four genes. Folic acid, the synthetic form of folate or vitamin B9, is an essential cofactor in one-carbon metabolism, supporting the synthesis of purines, thymidine, and the methyl groups required for epigenetic regulation and neurotransmitter synthesis. Folate deficiency has long been associated with depression, and low folate levels predict poorer response to selective serotonin reuptake inhibitors, which is why L-methylfolate is sometimes used as an adjunctive treatment in psychiatry. In the context of psoriasis, folate metabolism intersects with the rapid keratinocyte proliferation that characterizes the disease, and methotrexate—the most widely used conventional systemic agent for psoriasis—works in part by inhibiting folate-dependent enzymes, which is why folate supplementation is routinely co-prescribed to mitigate toxicity.

The identification of folic acid as a potential modulator of the shared molecular network therefore carries both mechanistic and clinical significance. It suggests that the same nutrient pathway that supports neurotransmitter synthesis in the brain also influences the proliferative and inflammatory programs active in psoriatic skin, providing a biological rationale for why nutritional status might modulate both conditions simultaneously. It also raises the possibility that folate-related interventions, whether through dietary optimization, supplementation, or pharmacological modulation of one-carbon metabolism, could be explored as adjunctive therapies aimed at the comorbidity rather than at either condition in isolation.

It is worth emphasizing what this study does and does not establish. The findings rest on computational integration of publicly available datasets rather than on new laboratory experiments or clinical trials, and the causal inferences drawn from Mendelian randomization depend on assumptions—that the genetic instruments are valid proxies, that they influence the outcomes only through the exposure of interest, and that confounding through population stratification has been adequately controlled. The eQTL data were derived from peripheral blood, which may not fully capture gene expression in skin or brain tissue, and the GWAS summary statistics came from populations of European ancestry, potentially limiting generalizability to other populations. The sample sizes for the psoriasis transcriptomic datasets were modest, and single-cell datasets, while informative, reflect specific tissue contexts that may not represent the full cellular diversity of either disease. These limitations do not invalidate the findings but rather frame them as hypothesis-generating results that require experimental validation in cellular models, animal studies, and ultimately prospective clinical cohorts.

Nevertheless, the study contributes a structured framework for thinking about psoriasis and depression as a biologically integrated comorbidity. By triangulating genetic causality, transcriptomic signatures, machine learning feature selection, and single-cell resolution, it narrows a vast molecular landscape down to four genes and a handful of interconnected pathways. The convergence on IL-17 signaling, NF-kappa B activation, FoxO regulation, cholesterol metabolism, synaptic vesicle cycling, and ferroptosis paints a coherent picture in which chronic inflammatory signaling, altered lipid handling, and oxidative stress-induced cell death form a mutually reinforcing network spanning skin, vasculature, and brain. For clinicians, the findings reinforce the importance of routine depression screening in psoriasis care and suggest that monitoring inflammatory markers, metabolic parameters, and nutritional status may provide actionable windows into comorbidity risk. For researchers, the four hub genes and the pathways they anchor offer concrete starting points for experimental validation and for the development of interventions that target the shared biology underlying both conditions, moving the field closer to the goal of precision therapy for patients living with the burden of this dual diagnosis.

Subject of Research: Molecular mechanisms underlying the comorbidity of psoriasis and depression

Article Title: Molecular mechanisms underlying psoriasis and depression: an integrated analysis using mendelian randomization, transcriptomics, and single-cell sequencing

Article References: De, B., Bao, W., Hea, N., & Fang, J. (2026). Molecular mechanisms underlying psoriasis and depression: an integrated analysis using mendelian randomization, transcriptomics, and single-cell sequencing. Frontiers in Molecular Medicine, 6, Article 1770665. https://doi.org/10.3389/fmmed.2026.1770665

Image Credits: AI Generated

DOI: 10.3389/fmmed.2026.1770665

Keywords: psoriasis, depression, Mendelian randomization, single-cell sequencing, transcriptomics, ferroptosis, folic acid, MAP3K20, WARS2, TBXAS1, ABHD15, immune infiltration