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Table of Contents
1. Product Selection Using Genetic Analysis
Priority: Dec 20, 2011
(from WO 2013/093407 A1)
1.1 Technical Field
• In case you are curious, from Wikipedia: A biological pathway is a series of actions among molecules in a cell that leads to a certain product or a change in a cell. Such a pathway can trigger the assembly of new molecules, such as a fat or protein. Pathways can also turn genes on and off, or spur a cell to move.
1.2 Background
• Many factors influence the health and appearance of skin tissue
• Experts have long recognised a list of “active” ingredients that play a key role in skin health.
• The efficacy of an active ingredient relies on its ability to play a specific role in the biological pathway.
• This role is due to its capacity to interact with other molecules in the pathway to induce the desired response.
• Indeed an indirect or direct-Response relationship between an active ingredient and its target allows the ingredient to provide the best effect of a product.
1.3 Summary
1.4 Detailed Description
• The genetic era now opens up the possibility to utilise a deeper understanding of genetics in a customised, i.e. person-specific, way.
• A single-nucleotide polymorphism (SNP) found in the target (i.e. molecule to be affected) of an active ingredient (i.e. the key molecule in the drug) provides information on the quality of the expected response
• Use cross-validation of biological target
• This method uses detection of SNP to estimate protein-protein interaction between an ingredient and its direct or indirect target.
• As previously discussed, detecting SNPs to evaluate particular molecule efficacy in a biological pathway is known and is used in pharmacogenetics.
• However, the practice of identifying SNPs associated with an increased or decreased response to an active cosmetic ingredient (ACI) and then testing the individual to determine if they have at least one of said SNPs to determine whether that particularly cosmetic is likely to be effective for that individual, is new.
• The method described herein is different from that used in pharmacogenetics in the sense that, instead of looking at whether a specific SNP is associated with a disorder or defect, the aim is to qualify the effect of an ingredient by querying the target of that ingredient, i.e. by identifying/assessing the presence or absence of SNPs in the targets associated with the active ingredient. By doing so, it is possible to determine if the ingredient will be efficient.
1.4.1 1: Identification of ingredients and their biological targets
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1.4.2 2: Identification and selection of a SNP in the ingredient's target
1.4.3 3: Design of specific primers to amplify the specific SNP associated to ingredients
1.4.4 4: Matching ingredients to their target and the associated SNP
1.4.5 5: Correlation between ingredients and efficacy associated to SNP
1.4.6 6: Application: Selection of a group of SNPs associated with the composition of a cosmetic product and its outcome
1.5 Example 1
• Niacin (Nicotinic acid, vitamin B3) can act as a ligand that binds and activates certain protein receptors (HM74) sitting in the cell membrane (e.g. G protein-coupled receptors).
• This activation (after some intermediary steps) (see G-protein signaling) causes the release of ATP messengers as part of the cAMP signal pathway (i.e. cAMP is the second messenger).
• In this example the cAMP activate the PKA enzyme which releases its catalytic subunits to phosphorylate (i.e. turn on/off) specific target proteins. (How does PKA know what target to phosphorylate?)
• In this case they activate HSL which promotes free fatty acid (FFA) secretion by adipocyte cells.
• The presence of FFA in the skin may be very helpful as discussed here back in 1957.
• This is a complicated process, but as far as the patent is concerned the key step is to look at potential mutations in the DNA coding for the receptor protein.
• In particular genes HM74 (protein GPR109B) and HM74A (GPR109A) code for these proteins with the HM74A apparently coding for a better receptor.
• If you identify which of these genes is present (or perhaps even some variation on these genes) you can better predict which customer will better benefit from the metabolic effects of niacin.