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Identification and characterization of sebaceous gland atrophy-sparing DGAT1 inhibitors.

Muise ES, Zhu Y, Verras A, Karanam BV, Gorski J, Weingarth D, Lin HV, Hwa J, Thompson JR, Hu G, Liu J, He S, DeVita RJ, Shen DM, Pinto S - PLoS ONE (2014)

Bottom Line: DGAT1 inhibition has been shown to be a key regulator in an array of metabolic pathways; however, based on the DGAT1 KO mouse phenotype the anticipation is that pharmacological inhibition of DGAT1 could potentially lead to skin related adverse effects.One of the aims in developing small molecule DGAT1 inhibitors that target key metabolic tissues is to avoid activity on skin-localized DGAT1 enzyme.In addition, we demonstrate histological and RNA based biomarker approaches that can detect sebaceous gland atrophy pre-clinically that could be used as potential biomarkers in a clinical setting.

View Article: PubMed Central - PubMed

Affiliation: Discovery and Preclinical Sciences, Merck Research Laboratories, Whithouse Station, New Jersey, United States of America.

ABSTRACT
Inhibition of Diacylglycerol O-acyltransferase 1 (DGAT1) has been a mechanism of interest for metabolic disorders. DGAT1 inhibition has been shown to be a key regulator in an array of metabolic pathways; however, based on the DGAT1 KO mouse phenotype the anticipation is that pharmacological inhibition of DGAT1 could potentially lead to skin related adverse effects. One of the aims in developing small molecule DGAT1 inhibitors that target key metabolic tissues is to avoid activity on skin-localized DGAT1 enzyme. In this report we describe a modeling-based approach to identify molecules with physical properties leading to differential exposure distribution. In addition, we demonstrate histological and RNA based biomarker approaches that can detect sebaceous gland atrophy pre-clinically that could be used as potential biomarkers in a clinical setting.

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Related in: MedlinePlus

RNA biomarkers for sebaceous gland atrophy in skin.Shown are the 42 probesets, identified in the Training Set (Studies 1 and 2), that were regulated by skin-positive compound treatments (those that produced sebaceous gland atrophy) but not by the skin-negative compound treatments (the one that did not produce sebaceous gland atrophy). After excluding the absent probes (low intensity), these 42 probesets met the following cutoffs: 1.2 fold change and ANOVA p<0.01 between all 3 skin-positive compound treatments (red arrows) and their respective vehicle treatments, and ANOVA p>0.1 between the skin negative compound treatment (black arrow) and its respective vehicle treatment. The probesets for RIKEN genes were excluded. Plotted are the LogRatio values (+/− 4 fold fold scale) with magenta representing up-regulated probesets and cyan representing down-regulated probesets. Treatments from the independent Test Set (Study 4) are included for comparison but were not used to identify the 42 probesets.
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pone-0088908-g005: RNA biomarkers for sebaceous gland atrophy in skin.Shown are the 42 probesets, identified in the Training Set (Studies 1 and 2), that were regulated by skin-positive compound treatments (those that produced sebaceous gland atrophy) but not by the skin-negative compound treatments (the one that did not produce sebaceous gland atrophy). After excluding the absent probes (low intensity), these 42 probesets met the following cutoffs: 1.2 fold change and ANOVA p<0.01 between all 3 skin-positive compound treatments (red arrows) and their respective vehicle treatments, and ANOVA p>0.1 between the skin negative compound treatment (black arrow) and its respective vehicle treatment. The probesets for RIKEN genes were excluded. Plotted are the LogRatio values (+/− 4 fold fold scale) with magenta representing up-regulated probesets and cyan representing down-regulated probesets. Treatments from the independent Test Set (Study 4) are included for comparison but were not used to identify the 42 probesets.

Mentions: To identify biomarkers underlying the skin pathophysiology associated with DGAT1 inhibition we initiated global gene expression profiling. Diet induced obese (DIO) mice were treated with several structurally diverse DGAT1 inhibitors for 14 days and total RNA from skin biopsies were profiled on Affymetrix custom microarrays. Forty two probesets were identified using a Training Set consisting of two skin-positive compound treatments (compounds inducing sebaceous gland atrophy) and one skin-negative compound treatment (compound not inducing sebaceous gland atrophy; Figure 5 and Table 2). A composite score using these 42 probesets and an independent Test Set (treatments not used to identify the biomarkers) was able to differentiate between the skin-positive and the skin-negative compound treatments with p<0.0001 (Figure 6). Up-regulated genes in this set include proteins involved in the immune response such as Ccl1 (Chemokine (C-C motif) ligand 1), Defb1 (Defensin beta 1) and Cxcl16 (Chemokine (C-X-C motif) ligand 16) (Figure 7A and Table 2). Down-regulated genes include proteins involved in lipid, fatty acid, and steroid metabolism such as Scd3 (Stearoyl-coenzyme A desaturase 3), Acox2 (Acyl-Coenzyme A oxidase 2, branched chain), and Elovl5 (ELOVL family member 5) (Figure 7B and Table 2) consistent with the DGAT1 pathway. Twenty six of these 42 probesets were significantly regulated by the skin-positive compound in the Test Set and not by the skin-negative compound treatment (Table 2).


Identification and characterization of sebaceous gland atrophy-sparing DGAT1 inhibitors.

Muise ES, Zhu Y, Verras A, Karanam BV, Gorski J, Weingarth D, Lin HV, Hwa J, Thompson JR, Hu G, Liu J, He S, DeVita RJ, Shen DM, Pinto S - PLoS ONE (2014)

RNA biomarkers for sebaceous gland atrophy in skin.Shown are the 42 probesets, identified in the Training Set (Studies 1 and 2), that were regulated by skin-positive compound treatments (those that produced sebaceous gland atrophy) but not by the skin-negative compound treatments (the one that did not produce sebaceous gland atrophy). After excluding the absent probes (low intensity), these 42 probesets met the following cutoffs: 1.2 fold change and ANOVA p<0.01 between all 3 skin-positive compound treatments (red arrows) and their respective vehicle treatments, and ANOVA p>0.1 between the skin negative compound treatment (black arrow) and its respective vehicle treatment. The probesets for RIKEN genes were excluded. Plotted are the LogRatio values (+/− 4 fold fold scale) with magenta representing up-regulated probesets and cyan representing down-regulated probesets. Treatments from the independent Test Set (Study 4) are included for comparison but were not used to identify the 42 probesets.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3928314&req=5

pone-0088908-g005: RNA biomarkers for sebaceous gland atrophy in skin.Shown are the 42 probesets, identified in the Training Set (Studies 1 and 2), that were regulated by skin-positive compound treatments (those that produced sebaceous gland atrophy) but not by the skin-negative compound treatments (the one that did not produce sebaceous gland atrophy). After excluding the absent probes (low intensity), these 42 probesets met the following cutoffs: 1.2 fold change and ANOVA p<0.01 between all 3 skin-positive compound treatments (red arrows) and their respective vehicle treatments, and ANOVA p>0.1 between the skin negative compound treatment (black arrow) and its respective vehicle treatment. The probesets for RIKEN genes were excluded. Plotted are the LogRatio values (+/− 4 fold fold scale) with magenta representing up-regulated probesets and cyan representing down-regulated probesets. Treatments from the independent Test Set (Study 4) are included for comparison but were not used to identify the 42 probesets.
Mentions: To identify biomarkers underlying the skin pathophysiology associated with DGAT1 inhibition we initiated global gene expression profiling. Diet induced obese (DIO) mice were treated with several structurally diverse DGAT1 inhibitors for 14 days and total RNA from skin biopsies were profiled on Affymetrix custom microarrays. Forty two probesets were identified using a Training Set consisting of two skin-positive compound treatments (compounds inducing sebaceous gland atrophy) and one skin-negative compound treatment (compound not inducing sebaceous gland atrophy; Figure 5 and Table 2). A composite score using these 42 probesets and an independent Test Set (treatments not used to identify the biomarkers) was able to differentiate between the skin-positive and the skin-negative compound treatments with p<0.0001 (Figure 6). Up-regulated genes in this set include proteins involved in the immune response such as Ccl1 (Chemokine (C-C motif) ligand 1), Defb1 (Defensin beta 1) and Cxcl16 (Chemokine (C-X-C motif) ligand 16) (Figure 7A and Table 2). Down-regulated genes include proteins involved in lipid, fatty acid, and steroid metabolism such as Scd3 (Stearoyl-coenzyme A desaturase 3), Acox2 (Acyl-Coenzyme A oxidase 2, branched chain), and Elovl5 (ELOVL family member 5) (Figure 7B and Table 2) consistent with the DGAT1 pathway. Twenty six of these 42 probesets were significantly regulated by the skin-positive compound in the Test Set and not by the skin-negative compound treatment (Table 2).

Bottom Line: DGAT1 inhibition has been shown to be a key regulator in an array of metabolic pathways; however, based on the DGAT1 KO mouse phenotype the anticipation is that pharmacological inhibition of DGAT1 could potentially lead to skin related adverse effects.One of the aims in developing small molecule DGAT1 inhibitors that target key metabolic tissues is to avoid activity on skin-localized DGAT1 enzyme.In addition, we demonstrate histological and RNA based biomarker approaches that can detect sebaceous gland atrophy pre-clinically that could be used as potential biomarkers in a clinical setting.

View Article: PubMed Central - PubMed

Affiliation: Discovery and Preclinical Sciences, Merck Research Laboratories, Whithouse Station, New Jersey, United States of America.

ABSTRACT
Inhibition of Diacylglycerol O-acyltransferase 1 (DGAT1) has been a mechanism of interest for metabolic disorders. DGAT1 inhibition has been shown to be a key regulator in an array of metabolic pathways; however, based on the DGAT1 KO mouse phenotype the anticipation is that pharmacological inhibition of DGAT1 could potentially lead to skin related adverse effects. One of the aims in developing small molecule DGAT1 inhibitors that target key metabolic tissues is to avoid activity on skin-localized DGAT1 enzyme. In this report we describe a modeling-based approach to identify molecules with physical properties leading to differential exposure distribution. In addition, we demonstrate histological and RNA based biomarker approaches that can detect sebaceous gland atrophy pre-clinically that could be used as potential biomarkers in a clinical setting.

Show MeSH
Related in: MedlinePlus