Expression Pattern and Immunoregulatory Roles of Galectin-1 and Galectin-3 in Atopic Dermatitis and Psoriasis

Corrêa, Maria José Pinheiro; Correia-Silva, Rebeca D.; Sasso, Gisela Rodrigues da Silva; D'Ávila, Solange Corrêa Garcia Pires; Greco, Karin Vicente; Oliani, Sônia Maria; Gil, Cristiane Damas

doi:10.1007/s10753-021-01608-7

Cited by 10 publications

(6 citation statements)

References 61 publications

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“…There was a decrease in the level of gal-1 in psoriatic skin compared to normal control although it did not reach statistical significance. The same was found by many authors as de [42][43][44][45] They found a decrease of gal-1 level in both lesioned and nonlesioned skin samples from psoriatic patients. Contrary to normal epidermis, the psoriatic epithelium expressed no gal-1 and no glycoligands for gal-1.…”

Section: Discussionsupporting

confidence: 86%

“…A study by Corrêa et al, 2022 suggested that gal-1 downregulation is the leading cause of exacerbation of the inflammatory responses in psoriatic skin. 45 As any decrease in gal-1 level can lead to increase in the level of INF-γ and decrease of IL-10. The inflammatory changes started with activation of antigen-presenting Langerhans cells leading to T-cell stimulation and finally cytokines release.…”

Section: Discussionmentioning

confidence: 99%

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Galectin-1 in Psoriatic arthritis, Psoriasis, Rheumatoid arthritis and its relation with disease activity and skin lesion

Bably

Aziz

Adly

et al. 2023

EJI

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Immune mediated inflammatory diseases (IMIDs) are a diverse range of diseases that affect joints with early overlapping symptoms. Rheumatoid arthritis (RA) and psoriatic arthritis (PsA) are the most common disorders sharing immune-pathogenic mechanisms that cause peripheral arthritis. Psoriasis (Ps) is a chronic inflammatory autoimmune skin disease characterized by epidermal hyperplasia with significant invasion by inflammatory cells. New biomarkers are required to enable an early diagnosis and differentiation between different types of IMIDs. In autoimmune disorders, galectin 1 (Gal-1) is a recognized as negative immune system regulator. This study aimed to determine the possibility of using gal–1 as a diagnostic marker to differentiate between RA and PsA with polyarthritis pattern, and between PsA and Ps, and to assess its relationship with disease activity and with skin lesion. In this case-control study included 40 PsA patients with polyarthritis pattern, 40 psoriatic patients, 40 RA patients and 20 normal controls. Gal-1 levels were measured in serum and skin biopsy and disease Activity Score (DAS-ESR) was assessed. Serum gal-1 level was significantly higher in RA group in comparison to PsA, psoriatic and control. In addition, compared to the normal group, psoriatic skin lesions from PsA and Ps patients had lower levels of gal-1. Serum gal-1 levels in the RA group did not correlate with other factors such as age, disease duration, deformity, extra-articular symptoms, or DAS-ESR. Furthermore, there was no correlation between the skin’s level of gal-1 and psoriatic area and severity index (PASI) score, body surface area (BSA). In conclusion, serum Gal-1 concentration may serve as a diagnostic biomarker to distinguish between RA and PsA. However, it cannot assess activity or severity of RA, and cannot differentiate psoriatic lesion either from only Ps or PsA.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Galectin-1 in Psoriatic arthritis, Psoriasis, Rheumatoid arthritis and its relation with disease activity and skin lesion

Bably

Aziz

Adly

et al. 2023

EJI

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“…It has reported that the level of Gal-3 was decreased in AD epidermis compared with control samples. In vivo, the release of IL-6 in IL-4-stimulated keratinocytes was downregulated by Gal-3 [ 49 ]. Solute Carrier Family 29 Member 1 (SLC29A1) was point as a top novel gene for early allergic sensitization [ 50 ].…”

Section: Discussionmentioning

confidence: 99%

Construction and verification of atopic dermatitis diagnostic model based on pyroptosis related biological markers using machine learning methods

et al. 2023

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Objective The aim of this study was to construct a model used for the accurate diagnosis of Atopic dermatitis (AD) using pyroptosis related biological markers (PRBMs) through the methods of machine learning. Method The pyroptosis related genes (PRGs) were acquired from molecular signatures database (MSigDB). The chip data of GSE120721, GSE6012, GSE32924, and GSE153007 were downloaded from gene expression omnibus (GEO) database. The data of GSE120721 and GSE6012 were combined as the training group, while the others were served as the testing groups. Subsequently, the expression of PRGs was extracted from the training group and differentially expressed analysis was conducted. CIBERSORT algorithm calculated the immune cells infiltration and differentially expressed analysis was conducted. Consistent cluster analysis divided AD patients into different modules according to the expression levels of PRGs. Then, weighted correlation network analysis (WGCNA) screened the key module. For the key module, we used Random forest (RF), support vector machines (SVM), Extreme Gradient Boosting (XGB), and generalized linear model (GLM) to construct diagnostic models. For the five PRBMs with the highest model importance, we built a nomogram. Finally, the results of the model were validated using GSE32924, and GSE153007 datasets. Results Nine PRGs were significant differences in normal humans and AD patients. Immune cells infiltration showed that the activated CD4+ memory T cells and Dendritic cells (DCs) were significantly higher in AD patients than normal humans, while the activated natural killer (NK) cells and the resting mast cells were significantly lower in AD patients than normal humans. Consistent cluster analysis divided the expressing matrix into 2 modules. Subsequently, WGCNA analysis showed that the turquoise module had a significant difference and high correlation coefficient. Then, the machine model was constructed and the results showed that the XGB model was the optimal model. The nomogram was constructed by using HDAC1, GPALPP1, LGALS3, SLC29A1, and RWDD3 five PRBMs. Finally, the datasets GSE32924 and GSE153007 verified the reliability of this result. Conclusions The XGB model based on five PRBMs can be used for the accurate diagnosis of AD patients.

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“…Gal3 has been found to act as an endogenous ligand for paracrine/autocrine toll-like receptor 4 (TLR4) as well as the triggering receptor expressed on myeloid cells 2 (TREM2), binding through its CRD [ 27 , 33 ]. Moreover, gal3 has been found significantly upregulated in AD patients [ 27 ], surrounding the atherosclerotic plaques in relation to atherogenesis [ 46 ], and associated with other human diseases such as major kidney adverse events [ 47 ], stroke [ 48 ] and atopic dermatitis and psoriasis [ 49 ]. Notably, it has been observed that gal3 inhibition decreases the inflammatory response of microglial cells to treatment with fibrillar Aβ.…”

Section: Introductionmentioning

confidence: 99%

Targeting galectin-3 to counteract spike-phase uncoupling of fast-spiking interneurons to gamma oscillations in Alzheimer’s disease

Arroyo-García

Bachiller

Ruiz

et al. 2023

Transl Neurodegener

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Background Alzheimer’s disease (AD) is a progressive multifaceted neurodegenerative disorder for which no disease-modifying treatment exists. Neuroinflammation is central to the pathology progression, with evidence suggesting that microglia-released galectin-3 (gal3) plays a pivotal role by amplifying neuroinflammation in AD. However, the possible involvement of gal3 in the disruption of neuronal network oscillations typical of AD remains unknown. Methods Here, we investigated the functional implications of gal3 signaling on experimentally induced gamma oscillations ex vivo (20–80 Hz) by performing electrophysiological recordings in the hippocampal CA3 area of wild-type (WT) mice and of the 5×FAD mouse model of AD. In addition, the recorded slices from WT mice under acute gal3 application were analyzed with RT-qPCR to detect expression of some neuroinflammation-related genes, and amyloid-β (Aβ) plaque load was quantified by immunostaining in the CA3 area of 6-month-old 5×FAD mice with or without Gal3 knockout (KO). Results Gal3 application decreased gamma oscillation power and rhythmicity in an activity-dependent manner, which was accompanied by impairment of cellular dynamics in fast-spiking interneurons (FSNs) and pyramidal cells. We found that the gal3-induced disruption was mediated by the gal3 carbohydrate-recognition domain and prevented by the gal3 inhibitor TD139, which also prevented Aβ42-induced degradation of gamma oscillations. Furthermore, the 5×FAD mice lacking gal3 (5×FAD-Gal3KO) exhibited WT-like gamma network dynamics and decreased Aβ plaque load. Conclusions We report for the first time that gal3 impairs neuronal network dynamics by spike-phase uncoupling of FSNs, inducing a network performance collapse. Moreover, our findings suggest gal3 inhibition as a potential therapeutic strategy to counteract the neuronal network instability typical of AD and other neurological disorders encompassing neuroinflammation and cognitive decline.

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Expression Pattern and Immunoregulatory Roles of Galectin-1 and Galectin-3 in Atopic Dermatitis and Psoriasis

Cited by 10 publications

References 61 publications

Galectin-1 in Psoriatic arthritis, Psoriasis, Rheumatoid arthritis and its relation with disease activity and skin lesion

Galectin-1 in Psoriatic arthritis, Psoriasis, Rheumatoid arthritis and its relation with disease activity and skin lesion

Construction and verification of atopic dermatitis diagnostic model based on pyroptosis related biological markers using machine learning methods

Targeting galectin-3 to counteract spike-phase uncoupling of fast-spiking interneurons to gamma oscillations in Alzheimer’s disease

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