SASH1, a new potential link between smoking and atherosclerosis

Weidmann, Henri; Touat-Hamici, Zahia; Durand, H; Mueller, Christian; Chardonnet, Solenne; Pionneau, Cédric; Charlotte, Frédéric; Janssen, Klaus–Peter; Verdugo, Ricardo A.; Cambien, François; Blankenberg, Stefan; Tiret, Laurence; Zeller, Tanja; Ninio, Ewa

doi:10.1016/j.atherosclerosis.2015.08.013

Cited by 27 publications

(31 citation statements)

References 165 publications

(230 reference statements)

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“…Notably, P2Y6 receptor expression was found to be one of the most strongly induced genes in lung tissue of mice exposed to smoke [56]. Other genes present in the consensus signature such as SASH1 may link smoking and atherosclerosis [58]. Therefore, the consensus blood smoking signature may not only include genes that reflect a response to smoke exposure, but also genes that may play roles in smoke-related disease pathogenesis in the long term.…”

Section: Discussionmentioning

confidence: 99%

The sbv IMPROVER Systems Toxicology computational challenge: Identification of human and species-independent blood response markers as predictors of smoking exposure and cessation status

Belcastro

Poussin

Xiang

et al. 2018

Computational Toxicology

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Cigarette smoking entails chronic exposure to a mixture of harmful chemicals that trigger molecular changes over time, and is known to increase the risk of developing diseases. Risk assessment in the context of 21st century toxicology relies on the elucidation of mechanisms of toxicity and the identification of exposure response markers, usually from high-throughput data, using advanced computational methodologies. The sbv IMPROVER Systems Toxicology computational challenge (Fall 2015–Spring 2016) aimed to evaluate whether robust and sparse (≤40 genes) human (sub-challenge 1, SC1) and species-independent (sub-challenge 2, SC2) exposure response markers (so called gene signatures) could be extracted from human and mouse blood transcriptomics data of current (S), former (FS) and never (NS) smoke-exposed subjects as predictors of smoking and cessation status. Best-performing computational methods were identified by scoring anonymized participants’ predictions. Worldwide participation resulted in 12 (SC1) and six (SC2) final submissions qualified for scoring. The results showed that blood gene expression data were informative to predict smoking exposure (i.e. discriminating smoker versus never or former smokers) status in human and across species with a high level of accuracy. By contrast, the prediction of cessation status (i.e. distinguishing FS from NS) remained challenging, as reflected by lower classification performances. Participants successfully developed inductive predictive models and extracted human and species-independent gene signatures, including genes with high consensus across teams. Post-challenge analyses highlighted “feature selection” as a key step in the process of building a classifier and confirmed the importance of testing a gene signature in independent cohorts to ensure the generalized applicability of a predictive model at a population-based level. In conclusion, the Systems Toxicology challenge demonstrated the feasibility of extracting a consistent blood-based smoke exposure response gene signature and further stressed the importance of independent and unbiased data and method evaluations to provide confidence in systems toxicology-based scientific conclusions.

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Section: Discussionmentioning

confidence: 99%

The sbv IMPROVER Systems Toxicology computational challenge: Identification of human and species-independent blood response markers as predictors of smoking exposure and cessation status

Belcastro

Poussin

Xiang

et al. 2018

Computational Toxicology

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“…Similarly, the expression and methylation levels of LRRN3 (Leucine rich repeat protein 3) have been associated with smoking in various studies [ 5 , 32 , 33 ]. SASH 1 (SAM and SH3 domain containing 1) expression levels have also been associated with smoking and smoking-related atherosclerosis [ 28 , 34 ]. SASH1 is believed to be a tumor suppressor in breast and colon cancer and has been shown to inhibit cell migration and enhance cell adhesion of epithelial cells [ 35 ].…”

Section: Discussionmentioning

confidence: 99%

Gene expression profiles associated with cigarette smoking and moist snuff consumption

Arimilli

Madahian²,

Chen

et al. 2017

BMC Genomics

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BackgroundAmong the different tobacco products that are available on the US market, cigarette smoking is shown to be the most harmful and the effects of cigarette smoking have been well studied. US epidemiological studies indicate that non-combustible tobacco products are less harmful than smoking and yet very limited biological and mechanistic information is available on the effects of these alternative tobacco products. For the first time, we characterized gene expression profiling in PBMCs from moist snuff consumers (MSC), compared with that from consumers of cigarettes (SMK) and non-tobacco consumers (NTC).ResultsMicroarray analysis identified 100 differentially expressed genes (DEGs) between the SMK and NTC groups and 46 DEGs between SMK and MSC groups. However, we found no significant differences in gene expression between MSC and NTC. Both hierarchical clustering and principle component analysis revealed that MSC and NTC expression profiles were more similar than to SMK. Random forest classification identified a subset of DEGs which predicted SMK from either NTC or MSC with high accuracy (AUC 0.98).ConclusionsPMBC gene expression profiles of NTC and MSC are similar to each other, while SMK exhibit distinct profiles with alterations in immune related pathways. In addition to discovering several biomarkers, these studies support further understanding of the biological effects of different tobacco products.Trial registrationClinicalTrials.gov. Identifier: NCT01923402. Date of Registration: August 14, 2013. Study was retrospectively registered.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3565-1) contains supplementary material, which is available to authorized users.

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“…In the current study, exome sequencing with linkage mapping identified the SASH1 S587R variant as a plausible cause of DUH. The SASH1 gene is located at 6q24.3 and is 279,746 base pairs in length, which includes 22 exons and 21 introns, and encodes scaffold proteins of 1230 amino acids that contain two nuclear localization signals, a SLY domain, a SH3 domain, and two SAM domains [19][20]. To date, the most commonly seen hotspot mutation region is located in the highly conserved SLY domain (382-536) [16].…”

Section: Discussionmentioning

confidence: 99%

SASH1 promotes melanin synthesis and migration via suppression of TGF-β1 secretion in melanocytes resulting in pathologic hyperpigmentation

Cui¹,

Shu²,

He³

et al. 2020

Int. J. Biol. Sci.

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Dyschromatosis universalis hereditaria (DUH) is an autosomal dominant pigmentary genodermatosis characterized by the presence of patches of hyperpigmentation and hypopigmented macules distributed over the body, with most cases reported in Asia. DUH is a heterogeneous disease and a small portion of patients carry the ABCB6 variant. In the present study, exome sequencing of four generations of a Chinese family with DUH identified a c.1761C>G (p.Ser587Arg) mutation in exon 15 of SAM and SH3 domain containing 1 (SASH1) that was found to co-segregate in some family members. Immunohistological analysis of biopsy specimens showed that SASH1 was diffusely distributed in all layers of the epidermis, suggesting increased transepithelial migration of melanocytes (MCs). The point mutation c.1761C>G of SASH1 was successfully induced in immortalized human melanocyte (PIG1) cells, which resulted in the downregulation of SASH1 expression. Bioinformatics analysis showed that mutated SASH1 downregulated thrombospondin 1 (THBS1) expression and inactivated transforming growth factor beta 1 (TGF-β1) signaling. TGF-β1 expression by PIG1cells was found to negatively regulate SASH1 protein expression. Transwell migration and wound-healing assays showed an increase in the migration and invasion capabilities of the cells carrying the mutation. Further, SASH1 mutations induced downregulation of melanin content. The study results suggest cross-talking between SASH1-TGF-β1 signaling, demonstrating the proposed MC migration modulation models and affecting melanin trafficking in the epithelium.

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SASH1, a new potential link between smoking and atherosclerosis

Cited by 27 publications

References 165 publications

The sbv IMPROVER Systems Toxicology computational challenge: Identification of human and species-independent blood response markers as predictors of smoking exposure and cessation status

The sbv IMPROVER Systems Toxicology computational challenge: Identification of human and species-independent blood response markers as predictors of smoking exposure and cessation status

Gene expression profiles associated with cigarette smoking and moist snuff consumption

SASH1 promotes melanin synthesis and migration via suppression of TGF-β1 secretion in melanocytes resulting in pathologic hyperpigmentation

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