KR20180129695A - Genetic Polymorphic marker for predicting skin-temperature and use thereof - Google Patents

Abstract

The present invention relates to a technology for predicting skin temperature by selecting a specific genetic polymorphic marker having a significant correlation with skin temperature, and more specifically, to a marker composition for predicting skin temperature comprising a specific genetic polymorphic marker having a significant correlation with skin temperature; to a composition for predicting skin temperature or a skin temperature prediction kit comprising an agent for detecting the sequence of the specific genetic polymorphic marker; and a method for predicting skin temperature by checking the nucleotide sequence of the marker.

Description

Gene polymorphic marker for predicting skin temperature and use thereof < RTI ID = 0.0 >

The present invention relates to a technique for predicting skin temperature by selecting a specific genetic polymorphic marker having a significant correlation with skin temperature, and more particularly, to a skin temperature prediction method including a specific gene polymorphic marker having a significant correlation with skin temperature A composition for predicting skin temperature or a kit for predicting skin temperature, and a method for predicting skin temperature by checking the nucleotide sequence of the marker.

Genetic analysis research has shifted from research to discovering genetic markers that are relevant to disease or phenotype, to studies that predict future diseases or phenotypes using derived genetic indices. In particular, genetic analysis of facial features and skin characteristics has also increased the number of research fields that predict facial deformity or skin aging (Kemp et al., Molecules, 2017 Feb 26; 22 (3), 2017).

In addition, in research fields that predict phenotypes with a single genetic indicator, more studies are being conducted to increase the prediction accuracy of phenotypes with multiple genetic indices (Siewierska-Gorska et al., Homo. 2017 Feb 4. pii: S0018-442X (17), 2017).

Genetic analysis studies are expanding to basic disease index or academic analysis research, commercial disease prediction services (23andMe, HelloGene), skin prediction services (Pathway Genomics Skinfit, GeneStyle) The combination of platform technology and genomics-based forecasting services in the BT sector is creating new businesses that involve global conglomerates in personalized health and beauty management services.

One example of the present invention provides a composition for predicting skin temperature comprising a gene polymorphism marker having a significant correlation with skin temperature, a drug capable of detecting the marker, and a skin temperature prediction kit including the same.

Another example is a method for predicting skin temperature or a method for classifying skin type according to skin temperature, which comprises identifying a sequence of a genetic polymorphic marker having a significant correlation with skin temperature in a gene sample separated from a human subject .

Another example provides a composition or kit for skin type classification comprising a detectable agent of a genetic polymorphic marker as described above, and / or a composition or kit for skin condition diagnosis.

Another example is a method for providing information to a skin type classification method or skin type classification, comprising identifying a nucleic acid sequence of a genetic polymorphic marker as described above in a biological sample separated from a human subject, and / Methods or methods for providing information to skin condition diagnosis.

The present inventors analyzed the skin temperature and genes of human subjects to identify nucleotide variations of the gene polymorphic markers located in genes expected to be related to the skin temperature, and selected gene polymorphic markers having a significant correlation with skin temperature , And a technique for predicting skin temperature based on information on the pattern of the selected marker among genes of the individual has been completed.

The present invention provides a genetic polymorphism marker composition for skin temperature prediction comprising a marker having a significant correlation with skin temperature.

The marker in one embodiment is rs172063, rs1353899, rs6960088, rs6987785, rs11881857, rs2994693, rs62286331, rs2437317, rs6793971, rs7975123, rs11679195, rs4844704, rs6990898, rs12932810, rs11942461, rs595744, rs7623554, rs1800414, rs12696304, rs7313554, rs35487349, rs35533493 , rs4765986, rs9859074, rs4505040, rs35487349, rs7313554, rs4548934, and rs142551041.

Among the markers, rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, rs172063, rs1800414, rs12696304, rs7313554, rs35487349, rs35533493, rs4765986, rs9859074, and rs4505040, For example, the skin temperature of the face). Thus, one embodiment includes one or more polymorphic markers selected from the group consisting of rs172063, rs1353899, rs6960088, rs6987785, rs11881857, rs2994693, rs62286331, rs2437317, rs6793971, rs1800414, rs12696304, rs7313554, rs35487349, rs35533493, rs4765986, rs9859074, (E.g., facial skin) temperature prediction (or measurement) after skin cleansing (e.g., facial cleansing).

For example, the marker composition for predicting (or measuring) skin temperature after skin cleansing may comprise one or more genetic polymorphism markers selected from the group consisting of rs6793971, rs2437317, rs699693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063 have. More specifically, the marker composition for predicting (or measuring) the skin temperature (e.g., facial skin temperature) after the skin cleansing (e.g., facial cleansing) may comprise one or more of the following:

(i) rs6793971,

(ii) a combination of (a) rs6793971 and (b) one or more gene polymorphic markers selected from the group consisting of rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063 (e.g. combination of rs6793971 and rs2437317) ,

(iii) a combination of one or more gene polymorphic markers selected from the group consisting of (a) rs6793971 and rs2437317, and (b) rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063 (e.g., rs6793971, rs2437317, and rs62286331 ),

(iv) a combination of one or more gene polymorphic markers selected from the group consisting of (a) rs6793971, rs2437317, and rs62286331, and (b) rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063 (e.g., rs6793971, rs2437317, rs62286331 And rs2994693),

(v) a combination of (a) rs6793971, rs2437317, rs62286331, and rs2994693, and (b) rs2994693, and rs11881857),

(vi) a combination of one or more gene polymorphism markers selected from the group consisting of (a) rs6793971, rs2437317, rs62286331, rs2994693, and rs11881857, and (b) rs6987785, rs6960088, rs1353899, and rs172063 (e.g., rs6793971, rs2437317, rs62286331 And combinations of rs2994693, rs11881857, and rs6987785)

(vii) a combination of one or more gene polymorphic markers selected from the group consisting of (a) rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, and rs6987785, and (b) rs6960088, rs1353899, and rs172063 (e.g., rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, and rs6960088)

(viii) a combination (rs6793971, rs2437317, rs62286331, rs2994693) of one or more gene polymorphic markers selected from the group consisting of (a) rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, and rs6960088, (b) rs1353899, and rs172063 , rs11881857, rs6987785, rs6960088, and rs1353899), and

(ix) Combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063.

Among the markers, rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, rs7975123, rs35487349, rs7313554, rs4548934 and rs142551041 have a significant effect on skin temperature (e.g., facial skin temperature) Can be correlated. Thus, one embodiment comprises a skin cleansing (e.g., a facial cleanser) comprising one or more genetic polymorphic markers selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, rs35487349, rs7313554, rs4548934 and rs142551041. Provides a marker composition for predicting (or measuring) a pre-skin temperature (e.g., facial skin temperature).

For example, the marker composition for predicting (or measuring) skin temperature before skin washing may comprise one or more gene polymorphic markers selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123. More specifically, the marker composition for predicting (or measuring) the pre-skin temperature (e.g. facial skin temperature) of the skin cleansing (e.g., facial) may comprise one or more of the following:

(i) rs7623554,

(ii) a combination of one or more gene polymorphic markers selected from the group consisting of (a) rs7623554 and (b) rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123 (e.g., combination of rs7623554 and rs595744)

(iii) a combination of one or more gene polymorphic markers selected from the group consisting of (a) rs7623554 and rs595744, and (b) rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123 (e.g., combinations of rs7623554, rs595744, and rs11942461 ),

(iv) a combination of one or more gene polymorphism markers selected from the group consisting of (a) rs7623554, rs595744, and rs11942461, and (b) rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123 (e.g., rs7623554, rs595744, rs11942461, combination of rs12932810),

(v) a combination of one or more gene polymorphism markers selected from the group consisting of (a) rs7623554, rs595744, rs11942461, and rs12932810, and (b) rs6990898, rs4844704, rs11679195, and rs7975123 (e.g., rs7623554, rs595744, rs11942461, rs12932810 , And rs6990898),

(vi) a combination of one or more gene polymorphism markers selected from the group consisting of (a) rs7623554, rs595744, rs11942461, rs12932810, and rs6990898, and (b) rs4844704, rs11679195, and rs7975123 (e.g., rs7623554, rs595744, rs11942461, rs12932810 , rs6990898, and rs4844704),

(vii) a combination of (a) rs7623554, rs595744, rs11942461, rs11942461, rs12932810, rs6990898, and rs4844704, rs6990898, rs4844704, and rs11679195), and

(viii) Combination of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123.

The gene polymorphic markers are summarized in Table 1 below:

Marker Chromosome number Chromosomal location Non-effect allele Effect Allele rs172063 7 24126684 C T rs1353899 3 177511191 T G rs6960088 7 153644969 C G rs6987785 8 6016978 A G rs11881857 19 12237582 A G rs2994693 9 72799574 A G rs62286331 3 194171686 A G rs2437317 4 40789990 A G rs6793971 3 3658190 T C rs7975123 12 12807342 G A rs11679195 2 121818509 G A rs4844704 One 208646201 C G rs6990898 8 102522711 C T rs12932810 16 83825042 T G rs11942461 4 60494379 T C rs595744 2 79986880 A G rs7623554 3 139259641 G A rs1800414 15 27951891 A G rs12696304 3 169763483 G C rs7313554 12 128306497 T C rs35487349 8 127560127 T C rs35533493 14 64800891-64800892 - T rs4765986 12 2728372 T G rs9859074 3 124504088 G A rs4505040 11 39574049 A T rs35487349 8 127560127 T C rs7313554 12 128306497 T C rs4548934 17 18811021 G A rs142551041 8 125614334-125614337 GAGG -

Major allele in the genetic makeup refers to an allele that can be detected in more than 50% of Koreans and a minor allele is an allele that can be detected in less than 50% . The presence of a major allele or minor allele in all two alleles is referred to as homozygote and the two alleles have a multivariate allele and a low frequency Major (minor) / minor (minor) cases are called heterozygotes. In Table 1, the effect allele and the non-effect allele are distinguished from the allele / low frequency allele, and the risk allele Among the alleles found in the genetic polymorphism, the alleles having a large influence on a specific phenotype (predicting skin temperature), and the normal alleles means alleles having a small influence.

In the present specification, the gene polymorphism marker has a significant correlation with skin temperature, and the number of risk alleles included in the position of the polymorphic marker of two alleles (for example, 0 for non-effect / non-effect, One for non-effect / effect, and two for effect / effect) and human normal or average skin temperature.

For example, the frequency of the risk alleles included in rs11881857, rs2437317, rs6793971, rs11679195, rs1800414, rs35487349, rs9859074, rs35487349, and / or rs142551041 among the gene polymorphic markers is directly proportional to skin temperature. As the number of risk alleles included in rs11881857, rs2437317, rs6793971, rs11679195, rs1800414, rs12696304, rs35487349, rs9859074, rs35487349, and rs142551041 increases (Non- effect / Non-effect → Non-effect / / effect order), skin temperature can be predicted to increase. In other words, the frequency of normal alleles included in rs11881857, rs2437317, rs6793971, rs11679195, rs1800414, rs12696304, rs35487349, rs98487349, rs35487349, and / or rs142551041 is inversely proportional to skin temperature.

Also, it included in the above polymorphism marker, rs172063, rs1353899, rs6960088, rs6987785, rs2994693, rs62286331, rs7975123, rs4844704, rs6990898, rs12932810, rs11942461, rs595744, rs7623554, rs7313554, rs35533493, rs4765986, rs4505040, rs7313554, and / or rs4548934 The frequency of risk alleles is inversely proportional to skin temperature. That is, the number of risk alleles contained in rs172063, rs1353899, rs6960088, rs6987785, rs2994693, rs62286331, rs7975123, rs4844704, rs6990898, rs12932810, rs11942461, rs595744, rs7623554, rs7313554, rs35533493, rs4765986, rs4505040, rs7313554, and / or rs4548934 (Non-effect / non-effect → non-effect / effect → effect / effect order), skin temperature can be predicted to decrease. On the other expression, the normal allele containing the rs172063, rs1353899, rs6960088, rs6987785, rs2994693, rs62286331, rs7975123, rs4844704, rs6990898, rs12932810, rs11942461, rs595744, rs7623554, rs7313554, rs35533493, rs4765986, rs4505040, rs7313554, and / or rs4548934 And the skin temperature are directly proportional to the frequency.

In this specification, a skin temperature prediction technique using the gene polymorphism marker is provided based on the correlation between the genetic polymorphism and skin temperature as described above.

One example provides a composition for predicting (or measuring) a skin temperature comprising a detectable agent of a genetic polymorphism marker. The skin temperature may be a facial skin temperature. The gene polymorphism markers are as described above for the marker composition. In one embodiment, one or more gene polymorphism markers selected from the group consisting of rs172063, rs1353899, rs6960088, rs6987785, rs11881857, rs2994693, rs62286331, rs2437317, rs6793971, rs1800414, rs12696304, rs7313554, rs35487349, rs35533493, rs4765986, rs9859074, and rs4505040 (E.g., cleansing), which comprises a detectable agent of one or more gene polymorphic markers selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6987785, rs6960088, rs1353899, and rs172063 (E.g., facial skin temperature) prediction (or measurement). In other embodiments, one or more of the polymorphic markers (e.g., rs7623554, rs595744, rs11942461, rs12932810, rs6990898) selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, rs7975953, rs35487349, rs7313554, rs4548934 and rs142551041 (e.g., facial skin temperature) predicting (or measuring) a skin cleansing (e.g., facial) temperature, comprising a detectable formulation of a polynucleotide (e.g., one or more gene polymorphic markers selected from the group consisting of rs4844704, rs11679195, and rs7975123) / RTI >

The detectable agent of the genetic polymorphic marker is a polynucleotide comprising a polynucleotide comprising a polymorphic marker as described above on a chromosome, such as 1 to 200, 1 to 150, 1 to 100, 1 5 to 50, 5 to 100, 5 to 50, 10 to 200, 10 to 10, 2 to 50, 2 to 200, 2 to 150, 2 to 100, 2 to 50, 5 to 200, Which hybridizes to a polynucleotide region comprising a nucleotide sequence that is at least 70 nucleotides in length, including at least about 150 nucleotides, from about 10 nucleotides to about 150 nucleotides, from about 10 to about 100 nucleotides, from about 10 nucleotides to about 50 nucleotides, from about 15 nucleotides to about 15 nucleotides, 1 to 100, 1 to 80, 1 to 70, 1 to 60, 1 to 50, 1 to 45, 1 to 40, 1 to 35, 1 to 30, 1 To 25, 1 to 20, 5 to 100, 5 to 80, 5 to 70, 5 to 60, 5 to 50, 5 5 to 40, 5 to 35, 5 to 30, 5 to 25, 5 to 20, 7 to 100, 7 to 80, 7 to 70, 7 to 60, 7 7 to 20, 10 to 100, 10 to 80, 10 to 70, 10 to 10, 10 to 100, 10 to 50, 7 to 45, 7 to 40, 7 to 35, 7 to 30, 7 to 25, Oligonucleotides (e. G., Probes, polynucleotides, polynucleotides, polynucleotides, polynucleotides, polynucleotides, polynucleotides, polynucleotides, polynucleotides, polynucleotides, polynucleotides, polynucleotides, polynucleotides, Primer pairs, nucleic acid molecules of hairpin structure, etc.). The polynucleotide comprising the gene polymorphic marker may comprise, but is not limited to, a nucleic acid sequence selected from SEQ ID NOS: 1-28.

The detectable preparation of the gene polymorphism marker may be labeled with a labeling substance selected from the group consisting of conventional fluorescent substances, dyes, radioisotopes, and the like. In one embodiment, the detectable agent of the genetic polymorphism marker may be an oligonucleotide (hybridizable or having a complementary sequence) that binds to a polynucleotide site comprising a low frequency allele at the polymorphic position. In another embodiment, the detectable agent of the genetic polymorphism marker may be an oligonucleotide (hybridizable or having a complementary sequence) that binds to a polynucleotide site comprising a multinomial allele at the polymorphic position of the gene.

Another example provides a method for predicting (measuring) a skin temperature or a method for predicting (estimating) a skin temperature comprising identifying a nucleic acid sequence of the gene polymorphism marker. More particularly, there is provided a method for providing information to a skin temperature prediction (measurement) method or skin temperature prediction (measurement), comprising identifying a nucleic acid sequence of a genetic polymorphism marker in a separate biological sample. The skin temperature may be, for example, the skin temperature of the face. The gene polymorphism marker is as described in the marker composition described above.

In one embodiment, in the biological sample, one or more genes selected from the group consisting of rs172063, rs1353899, rs6960088, rs6987785, rs11881857, rs2994693, rs62286331, rs2437317, rs1800414, rs12696304, rs7313554, rs35533493, rs35533493, rs4765986, rs9859074, and rs4505040 (E.g., one or more gene polymorphic markers selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063) There is provided a method of predicting (or measuring) a skin temperature (e.g., a facial skin temperature) after skin cleansing (or cleansing) or predicting (or measuring) a skin temperature .

In other embodiments, one or more genetic polymorphic markers (e.g., rs7623554, rs595744, rs11942461, rs595744, rs595744, rs11942461) selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs35487349, rs35487349, rs7313554, rs4548934 and rs142551041, (e.g., facial skin temperature) predicting a skin cleansing (e.g., facial skin temperature), comprising identifying a nucleic acid sequence of at least one gene polymorphism marker selected from the group consisting of rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123 There is provided a method for providing information to a method (or a method) for estimating (or measuring) a skin temperature (e.g., facial skin temperature) before a skin cleansing (e.g., facial cleansing) method.

The biological sample refers to a sample separated from a living body and containing a dielectric substance. The biological sample is a cell (for example, oral epithelial cell or the like) or tissue or a cell / tissue fragment or a cell It may include seafood. The subject may be a human.

In the above method, the step of confirming the nucleic acid sequence of the gene polymorphism marker may include the step of confirming whether the risk polymorphism marker or the normal allele exists in the gene polymorphism marker. More specifically, identifying the nucleic acid sequence of the genetic polymorphic marker comprises contacting the allelic of the isolated biological sample with a detectable agent of one or more of the polymorphic markers as described above, Confirming the presence of alleles or normal alleles. Detectable agents of the polymorphic marker may be as described above, for example, a detectable agent of a risk allele of the polymorphic marker, a detectable agent of a normal allele, or both.

In one embodiment, the method further comprises:

(1) confirming the nucleic acid sequence of one or more gene polymorphic markers selected from the group consisting of rs11881857, rs2437317, rs6793971, rs11679195, rs1800414, rs35487349, rs9859074, rs35487349, and rs142551041 in the biological sample, and

(2) predict (or measure) skin temperature (e.g., facial skin temperature) to be higher as the number of risk alleles present in the gene polymorphic marker increases and / or increase skin temperature , Facial skin temperature) may be predicted to be low (or measured).

The step (2) may include one or more selected from the following:

(2-1) If one or more risk alleles are present in the gene polymorphism marker, it is predicted that the skin (e.g., facial skin) temperature is higher than the case where no risk allele is present at the gene polymorphism marker position (For example, facial skin) temperature (for example, skin temperature) in the absence of a risk allele at the position of the polymorphic marker when a risk allele is present in the gene polymorphism marker (Or measurement) of the gene polymorphism marker is predicted (or measured), and / or (ii) the presence of two risk alleles in the gene polymorphism marker is compared with the case (Or measuring) the skin (for example, facial skin) temperature to be high)

(2-2) If there is no risk allele in the gene polymorphism marker, it is predicted that the skin (for example, facial skin) temperature is low as compared with the case where one or more risk alleles are present at the gene polymorphism marker position Or measurement)

(2-3) If there is at least one normal allele in the gene polymorphism marker, it is predicted that the skin (for example, facial skin) temperature is low as compared with the case where the normal allele is not present at the polymorphic marker position (For example, facial skin) temperature (for example, skin temperature) is compared with the case where a normal allele is present in the gene polymorphic marker position (Or measuring) the gene polymorphism marker in the presence of two normal alleles in the gene polymorphism marker, and / or (ii) comparing the presence or absence of a normal allele in the gene polymorphism marker (Or measuring) the skin (e. G., Facial skin) temperature to be low), and

(2-4) If there is no normal allele in the gene polymorphism marker, it is predicted that the skin (for example, facial skin) temperature is higher than that in the case where there is not more than one normal allele at the gene polymorphic marker position Or measurement).

(2-1) and / or (2-2) can be performed when a detectable agent of the risk allele of the polymorphic marker is used, and the detectable agent of the normal allele of the polymorphic marker (2-3) and / or (2-4) can be performed, and both the detectable agent of the risk allele of the genetic polymorphic marker and the detectable agent of the normal allele are used , It is possible to perform at least one selected from the steps (2-1) to (2-4).

In another embodiment, the method further comprises:

1 'is selected from the group consisting of rs172063, rs1353899, rs6960088, rs6987785, rs2994693, rs62286331, rs7975123, rs4844704, rs6990898, rs12932810, rs11942461, rs595744, rs7623554, rs7313554, rs35533493, rs4765986, rs4505040, rs7313554, and rs4548934 in biological samples Identifying a nucleic acid sequence of one or more genetic polymorphism markers, and

(Or measured) the skin temperature (e.g., facial skin temperature) to be lower (or measured) as the number of risk alleles present in the gene polymorphic marker increases and / or the skin temperature (Or measuring) the skin temperature (e.g., skin temperature of the face) to be high.

The step (2 ') may include one or more selected from the following:

(2'-1) If one or more risk alleles are present in the gene polymorphism marker, it is predicted that the skin (for example, facial skin) temperature is low as compared with the case where the risk allele is not present at the polymorphic marker position (For example, facial skin), as compared with the case where the risk allele is not present at the position of the polymorphic marker, if there is one risk allele in the gene polymorphism marker (for example, (i) (Or measuring) the temperature of the genetic polymorphism marker, and / or (ii) if there are two risk alleles in the gene polymorphism marker, (Or measuring) the skin (e. G., Facial skin) temperature to be low)

(2'-2) If the risk polymorphism marker is not present in the gene polymorphism marker, it is predicted that the skin (for example, facial skin) temperature is higher than the case where one or more risk alleles are present at the polymorphic marker position (Or measuring)

(2'-3) When one or more normal alleles are present in the gene polymorphism marker, it is predicted that the skin (for example, facial skin) temperature is higher than the case where no normal allele is present at the polymorphic marker position (For example, facial skin) compared with the case where no normal allele is present at the position of the polymorphic marker, if there is one normal allele in the gene polymorphism marker, (Or measuring) the temperature of the gene polymorphism marker, and / or (ii) if there are two normal alleles in the gene polymorphism marker, (Or measuring) the skin (e.g., facial skin) temperature to be high), and

(2'-4) If there is no normal allele in the gene polymorphism marker, it is predicted that the skin (for example, facial skin) temperature is low as compared with the case where no one or more normal alleles exist at the gene polymorphic marker position (Or measurement).

(2'-1) and / or (2'-2) if a detectable agent of the risk allele of said polymorphic marker is used and the detection of normal allele of said polymorphic marker (2'-3) and / or (2'-4) can be performed if a possible agent is used, and the detectable agent of the risk allele of the polymorphic marker and the detectable agent of the normal allele (2'-1) to (2'-4) in the case of using all of the above-mentioned steps (2'-1) to (2'-4).

In embodiments, the skin temperature (e.g., facial skin temperature) (占 폚) after skin cleansing (e.g., facial cleansing) may be predicted or measured by one or more formulas selected from:

(i) 31.174 + (0.422) * A1 (A1 is the number of risk alleles for the rs6793971 marker) (using rs6793971 as a single base multi-cast marker)

(A1) is the number of risk alleles for rs6793971), A2 is the risk allele count for rs2437317 (using a combination of rs6793971 and rs2437317 as a single nucleotide polymorphism marker) and (ii) 30.834 + (0.403) * A1 + (0.355) ,

A2 is the number of risk alleles of rs2437317, and A3 is the risk allele of rs62286331 (iii) 31.070 + (0.399) * A1 + (0.340) * A2 + (-0.415) (Using a combination of rs6793971, rs2437317, and rs62286331 as single base multi-cast markers),

(iv) 31.398 + (0.390) * A1 + (0.321) * A2 + (-0.409) * A3 + (-0.323) * A4 (A1 is the number of risk alleles of rs6793971), A2 is the number of risk alleles of rs2437317, A3 is the number of risk alleles of rs62286331, A4 is the number of risk alleles of rs2994693) (using a combination of rs6793971, rs2437317, rs62286331 and rs2994693 as single base multi-cast markers)

A2 is the number of risk alleles of rs6793971, A2 is the number of risk alleles of rs2437317 (v) 31.167 + (0.384) * A1 + (0.312) * A2 + (-0.397) * A3 + (-0.301) (A3 is the number of risk alleles of rs62286331, A4 is the number of risk alleles of rs2994693, A5 is the number of risk alleles of rs11881857) (rs6793971, rs2437317, rs62286331, rs2994693, and rs11881857 ),

(vi) 31.323 + (0.344) * A1 + (0.331) * A2 + (-0.392) * A3 + (-0.287) * A4 + (0.284) * A5 + (-0.341) * A6 (A1 is the risk confrontation of rs6793971 A3 is the number of risk alleles of rs62286331, A4 is the number of risk alleles of rs2994693, A5 is the number of risk alleles of rs11881857, and A6 is the number of risk alleles of rs6987785). Using a combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, and rs6987785 as single base multi-cast markers)

A3 + (-0.235) * A4 + (0.259) * A5 + (-0.295) * A6 + (-0.335) * A7 (+0.359) A2 is the number of risk alleles of rs2437317, A3 is the number of risk alleles of rs62286331, A4 is the number of risk alleles of rs2994693, A5 is the number of risk alleles of rs11881857, A6 is rs6987785 (A7 is the number of risk alleles of rs6960088) (using a combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, and rs6960088 as single nucleotide polymorphism markers)

(-0.265) * A3 + (-0.265) * A4 + (0.275) * A5 + (-0.310) * A6 + (-0.265) * A7 + (0.303) A2 is the number of risk alleles of rs2437317, A3 is the number of risk alleles of rs62286331, A4 is the number of risk alleles of rs2994693, A5 is the risk of rs11881857 (A6 is the number of risk alleles of rs6987785, A7 is the number of risk alleles of rs6960088, and A8 is the number of risk alleles of rs1353899) (single base multiple molding markers rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, and rs1353899), and

(0.25) * A5 + (-0.281) * A6 + (-0.252) * A3 + (-0.271) * A3 + A3 is the number of risk alleles of rs62286331, A4 is the risk allele of rs2994693, A5 is the number of risk alleles of rs11881857, A6 is the risk alleles of rs6987785, A7 is the risk alleles of rs6960088, A8 is the risk alleles of rs1353899, and A9 is the risk alleles of rs172063) Using a combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063 as multi-molding markers).

In other embodiments, the skin temperature (e.g., facial skin temperature) (占 폚) before skin cleansing (e.g., facial cleansing) may be predicted or measured by one or more of the following formulas:

(i) 34.050 + (-0.248) * B1 (B1 is the number of risk alleles for rs7623554) (using rs7623554 as a single base multi-cast marker),

(ii) 34.157 + (-0.223) * B1 + (-0.206) * B2 (B1 is the number of risk alleles of rs7623554 and B2 is the risk alleles of rs595744) (combination of rs7623554 and rs595744 ),

(B1) is the number of risk alleles of rs7623554, B2 is the number of risk alleles of rs595744, and B3 is the risk overlap of rs11942461 (iii) 34.347 + (-0.215) * B1 + (-0.198) * B2 + (-0.216) Number of factors) (using a combination of rs7623554, rs595744, and rs11942461 as single base multi-cast markers),

(iv) 34410 + (-0.193) * B1 + (-0.184) * B2 + (-0.204) * B3 + (-0.161) * B4 (B1 is the number of risk alleles of rs7623554, B2 is the risk alleles of rs595744 , B3 is the number of risk alleles of rs11942461 and B4 is the risk allele number of rs12932810) (using a combination of rs7623554, rs595744, rs11942461, and rs12932810 as single base multi-cast markers)

(v) 34.481 + (-0.210) * B1 + (-0.181) * B2 + (-0.183) * B3 + (-0.125) * B4 + (-0.224) * B5 (B1 is the number of risk alleles of rs7623554, B2 B4 is the risk alleles of rs12932810, B5 is the risk alleles of rs6990898) (single base multiple molding marker: rs7623554, rs595744, rs11942461, rs12932810, And rs6990898),

(-0.148) * B5 + (-0.191) * B6 (B1 represents rs7623554 (vi) 34.526 + (-0.214) * B1 + (-0.149) * B2 + (-0.152) * B3 + B2 is the number of risk alleles of rs595744, B3 is the risk alleles of rs11942461, B4 is the risk alleles of rs12932810, B5 is the risk alleles of rs6990898, B6 is the risk alleles of rs4844704 ) (Using a combination of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, and rs4844704 as single base multi-cast markers)

(-0.141) * B6 + (-0.141) * B3 + (-0.111) * B4 + (-0.241) * B5 + (-0.190) * B6 + (0.202) B6 is the number of risk alleles of rs7623554, B2 is the number of risk alleles of rs595744, B3 is the number of risk alleles of rs11942461, B4 is the number of risk alleles of rs12932810, B5 is the number of risk alleles of rs6990898, rs4844704, and rs11679195), and B7 is the number of risk alleles of rs11679195 (using a combination of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, and rs11679195 as single-

B4 + (-0.227) * B5 + (-0.189) * B6 + (0.190) * B2 + (-0.144) * B3 + (-0.097) B4 is the number of risk alleles of rs7623554, B2 is the number of risk alleles of rs595744, B3 is the number of risk alleles of rs11942461, B4 is the number of risk alleles of rs12932810, B5 is the number of risk alleles of rs6990898 (B6 is the number of risk alleles of rs4844704, B7 is the number of risk alleles of rs11679195, and B8 is the number of risk alleles of rs7975123) (rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704 , rs11679195, and rs7975123).

The predicted or measured skin temperature (占 폚) may be the temperature ± 2 ° C or ± 1 ° C or ± 0.5 ° C or ± 0.4 ° C or ± 0.3 ° C or ± 0.2 ° C or ± 0.1 ° C calculated by the above formula.

The number of risk alleles means the number of risk alleles at a polymorphic position in a pair of alleles, 0 for normal allele / normal allele, 1 for normal allele / risk allele, 2 for allele / risk allele.

As used herein, the term " skin cleansing or cleansing " means cleansing the skin or face with lukewarm water for 3 minutes to 5 minutes using a cleansing foam, and " before cleansing or cleansing skin " Or 5 to 10 minutes before initiation of skin cleansing or cleansing, and " after cleansing or after cleansing " may mean from 5 to 10 minutes after completion of cleansing or cleansing the skin have. Compared with before or after cleansing the skin, the natural film on the surface of the skin is removed after cleansing or cleansing the skin.

The natural skin layer on the surface of the skin has a sterilizing ability by keeping the skin slightly acidic and protects the skin from being dried by preventing evaporation of water and includes at least one selected from the group consisting of squalene, triglyceride, wax and fatty acid .

The skin washout may include 5 to 15% by weight of squalene, 40 to 50% by weight of triglyceride, 20 to 30% by weight of wax, and 20 to 30% by weight of fatty acid, , 10 wt% of squalene, 43 wt% of triglyceride, 22 wt% of wax and 25 wt% of fatty acid. Also, it is preferable that the natural skin layer component is removed by washing the skin with the skin, and the natural skin layer component is not contained or is contained at a very low level, for example, 0.0001 to 3% by weight of the squalene, triglyceride, wax, And preferably from 0.0001 to 1% by weight. When the skin component is removed for one hour, about 50% of the component content of the skin component is recovered before the skin cleansing, and the component content of the skin component is restored to the skin component after 4 hours.

The term " skin " used in the present invention may include, but is not limited to, at least one selected from the group consisting of facial skin, neck skin, hand skin, chest skin, leg skin, For example, the markers provided herein can be used to predict facial skin temperature.

The term " oligonucleotide " as used herein means a nucleic acid-based molecule capable of forming a dimer with a marker having a complementary sequence to the nucleic acid sequence of the target gene polymorphism marker.

As used herein, the term " primer " refers to a nucleic acid sequence having a short free 3 'hydroxyl group and capable of forming a base pair with a complementary template, 5 to 50, 5 to 45, 5 to 40, 5 to 35, 5 to 30, 5 to 25, 5 to 20, 7 to 50, 7 to 45 , 7 to 40, 7 to 35, 7 to 30, 7 to 25, 7 to 20, 10 to 50, 10 to 45, 10 to 40, 10 to 35, 10 to 30 , 10 to 25 nucleotides, or 10 to 20 nucleotides. Primers are usually synthesized but can also be used in naturally occurring nucleic acids. The sequence of the primer does not necessarily have to be exactly the same as the sequence of the template, but is sufficiently complementary that it can hybridize with the template. Primers can initiate DNA synthesis in the presence of a polymerization reaction (i. E., A reagent for DNA polymerase or reverse transcriptase and four different nucleoside triphosphates) at the appropriate buffer solution and temperature. The primer of the present invention may have a length known in the art as having a sequence complementary to a marker having a significant correlation with skin temperature.

In one example, the primers comprise consecutive 1 to 200, 1 to 150, 1 to 100, 1 to 50, 2 to 200, 2 to 150, 2 to 100 5 to 50, 5 to 100, 5 to 50, 10 to 200, 10 to 150, 10 to 100, 10 to 50, 15 to 200, Oligonucleotides capable of hybridizing (having a complementary sequence) to the 5 'terminal region of a polynucleotide region comprising 15 to 150, 15 to 100, or 15 to 50 base pairs (bp) And a primer pair consisting of an oligonucleotide capable of hybridizing (having a complementary sequence) and a 3 'terminal region which are not mutually overlapping.

As used herein, the term " probe " refers to a nucleic acid fragment such as RNA or DNA corresponding to a few nucleotides or hundreds of nucleotides that can specifically bind to mRNA and is labeled, The presence or absence of the presence of the user can be confirmed. The probe may be prepared in the form of an oligonucleotide probe, a single stranded DNA probe, a double stranded DNA probe, or an RNA probe. In the present specification, the skin temperature can be predicted through hybridization by hybridizing with a marker having a significant correlation with skin temperature and a complementary probe. The selection and hybridization conditions of the probes can be modified based on what is known in the art.

In one example, the probes can comprise from 1 to 200 consecutive, 1 to 150, 1 to 100, 1 to 50, 2 to 200, 2 to 150, 2 to 100 consecutive , 2 to 50, 5 to 200, 5 to 150, 5 to 100, 5 to 50, 10 to 200, 10 to 150, 10 to 100, 10 to 50, 15 to 200 , 5 to 80, 5 to 70 (having hybridizable or complementary sequences) that bind to a polynucleotide site that comprises a nucleotide sequence comprising at least 15 nucleotides, 15 to 150 nucleotides, 15 to 100 nucleotides, or 15 to 50 nucleotides , 5 to 60, 5 to 50, 5 to 45, 5 to 40, 5 to 35, 5 to 30, 5 to 25, 5 to 20, 7 to 100, 7 to 80 7 to 70, 7 to 60, 7 to 50, 7 to 45, 7 to 40, 7 to 35, 7 to 30, 7 to 25, 7 to 20, 10 to 100 , 10 to 80, 10 to 70 , 10 to 60, 10 to 50, 10 to 45, 10 to 40, 10 to 35, 10 to 30, 10 to 25, or 10 to 20 nucleotides .

The primers or probes of the present invention can be chemically synthesized using a phosphoramidite solid support method, or other well-known methods. Such nucleic acid sequences may incorporate additional features that do not alter the basic properties. Examples of additional features that may be incorporated include, but are not limited to, methylation, capping, substitution of one or more nucleic acids with homologues, and modification between nucleic acids.

In the present specification, the detection of the polymorphic marker or the identification of the nucleotide sequence of the polymorphic marker can be performed by any means ordinarily used for detection of the polymorphism or identification of the nucleic acid sequence. For example, the detection of the polymorphic markers may be performed using a microarray, PCR (Polymerase Chain Reaction; for example, allele-specific PCR (AS-PCR), real-time PCR or the like), Single-strand conformation polymorphism (SSCP) Length polymorphism, RFLP, RAPD, Tm-shift genotyping, DASH, 5'-nuclease assay, (Molecular Beacons), OLA (Oligonucleoide Ligase Assay), Invader assay (Invasive Cleavage of Oligonucleotide Probes), Pyrosequencing, Single Base Extension, Fluorescence Polarization, MALDI-TOF (MS), Matrix-assisted laser desorption ionization time of flight mass spectrometry, digital PCR (Digital PCR), etc. However, It is not. Another example provides a detectable agent or previously described for the skin type classification, including for skin temperature prediction composition composition or kit, and / or skin condition diagnostic composition or kit of the polymorphism markers as described above.

Another example is a method for providing information to a skin type classification method or skin type classification, comprising identifying a nucleic acid sequence of a genetic polymorphic marker as described above in a biological sample separated from a human subject, and / Methods or methods for providing information to skin condition diagnosis. The method may include predicting or measuring the skin temperature by performing the skin temperature prediction or measurement method described above.

In such compositions, kits and methods, skin condition diagnosis may include predicting or measuring skin oil content and / or moisture content, predicting or diagnosing skin inflammation (e.g., atopic skin inflammation, seborrhoeic skin inflammation, etc.), and / Or a prediction or measurement of hemoglobin level or the like.

In one embodiment, the above-described skin temperature prediction or measurement method is performed so that the higher the skin temperature (in particular, the skin temperature of the forehead part) predicted or measured in the biological sample (test sample) separated from the subject, And / or the increase in oil content can be predicted, and the lower the increase in water content and / or the decrease in oil content can be predicted. For example, the method may further comprise the steps of: (i) comparing the predicted or measured skin temperature (especially the skin temperature of the forehead portion) in the biological sample (test sample) separated from the subject to the reference sample , And / or (ii) estimating (diagnosing) that the subject's skin has a low water content and / or a high oil content as compared with the separated subject, and / or (ii) (Diagnosis) that the moisture content of the subject's skin is high and / or the oil content is low compared to the individual to be subjected to the comparison if the skin temperature of the subject's skin (especially the forehead skin temperature) is lower than that of the subject sample As shown in FIG. The sample to be compared may be a biological sample separated from a subject that knows the moisture content and / or oil level of the skin.

In other embodiments, the skin temperature prediction or measurement method described above may be performed to determine the skin temperature (e.g., facial skin temperature) predicted or measured before and / or after skin cleansing (e.g., facial cleansing) The larger the difference, the more predictable or diagnosed that the skin inflammation is severe. The lower the skin temperature and / or the smaller the temperature difference, the more predictable or diagnosed that the skin inflammation is mild. For example, the method may comprise the steps of: (i) determining whether the skin temperature predicted or measured in the biological sample (test sample) separated from the subject is higher than the comparative sample and / (Diagnosis) that the subject's skin inflammation is severe as compared with the separated subject, and / or (ii) when the predicted or measured skin temperature difference is larger than the subject sample to be compared, Or the skin temperature difference predicted or measured before and after the skin washing is less than that of the comparison sample, the comparison sample is compared with the separated sample, (Diagnosis) that the skin inflammation of the skin is mild. The sample to be compared may be a biological sample separated from a subject whose skin inflammation level is known.

In another embodiment, the above-described skin temperature prediction or measurement method is performed to determine the difference between the predicted or measured skin temperature and / or the predicted measured skin temperature (e.g., facial skin temperature) difference before and after skin cleansing The greater the degree of vascular development or the hemoglobin level of the skin, the higher the skin temperature and / or the lower the temperature difference, the less the degree of vascular development or hemoglobin level of the skin is predicted or diagnosed . For example, the method may comprise the steps of: (i) determining whether the skin temperature predicted or measured in the biological sample (test sample) separated from the subject is higher than the comparative sample and / (Diagnosis) that the subject's skin vascular development level or skin hemoglobin level is higher than that of the separated subject when the predicted or measured skin temperature difference is larger than the comparison subject sample, and / Or (ii) when the temperature of the skin predicted or measured in the test sample is lower than that of the sample to be compared and / or the skin temperature difference predicted or measured before and after the skin is less than the sample to be compared, (Diagnosis) that the subject's skin vascular development level or skin hemoglobin level is low, Can. The sample to be compared may be a biological sample isolated from an individual having known degree of skin vascular development or skin hemoglobin level.

The skin temperature prediction technique according to the present invention predicts genetically inherent skin temperature to preserve the understanding of the skin type classified as the skin temperature or the symptom, And can be utilized in the development of personalized cosmetics.

The present invention will be described in more detail with reference to the following examples. However, the scope of protection of the present invention is not intended to be limited to the following examples.

Example 1. Search for genetic polymorphic markers for skin temperature prediction 1

1.1 Skin temperature measurement and sample preparation

To measure the subject's skin temperature, the skin temperature was measured by FLIR T420 (infrared infrared camera, FLIR Systems, Inc.) before and after cleansing for 469 women between 20 and 35 years old. Were used to collect oral internal gene samples. The facial cleansing was performed with weak acid foam at 15 ~ 21 ℃ and skin temperature between 5 and 10 minutes before cleansing. In the examples provided herein, the face skin temperature before and after cleansing was measured for the measurement of the temperature change before and after the cleansing of the skin. The appearance of the skin temperature change before and after the cleansing test was the same Can be similarly applied.

1.2 Selection of Significant Gene Polymorphic Markers

The average skin temperature before cleansing and after cleansing as measured in Example 1.1 was used as a phenotypic variable. A large SNP chip (PMRA SNP chip; Thermo Fisher Scientific Inc.) was used for the gene sample collected in Example 1.1, Were examined. Linear regression was used to identify genetic variants with significant differences in mean skin temperature variables before and after cleansing.

The selected markers for the model calculation are the combination of the effect allele and the non-effect allele, ie non-effect / non-effect homozygote, non-effect / effect heterozygote, Homozygotes, and each genotype has non-effect / non-effect to non-effect / effect, and skin temperature decreases when non-effect / effect to effect / effect Or increased. When the p-value was significantly lower (<0.05) in the tendency of skin temperature decrease or increase, 32 markers were obtained as a significant genetic factor for this analysis.

The explanatory power (R square) of the marker was calculated by linear regression analysis using the SPSS program. When the prediction value is calculated using the prediction model, the difference between the actual measured value and the predicted value is called a residual. The smaller the residual is, the higher the explanatory power (R square) It can be interpreted as the degree to which. Generally, if the explanatory power is 5% (0.05) or more, it is a meaningful value.

The excavated markers and their explanatory power (R square) values are shown in Table 2 below.

Effect Face temperature average after cleansing (℃) Effect Size Standard Error R ²  (Explanatory power) P (reliability) Non effect / Non effect Non effect / Effect Effect / Effect Average
(° C) frequency Average
(° C) frequency Average
(° C) frequency rs1800414 G 31.4 107 31.7 190 31.8 96 0.196 0.091 0.011 0.031 rs12696304 C 31.5 202 31.8 161 31.7 30 0.235 0.102 0.013 0.012 rs7313554 C 31.9 151 31.4 177 31.6 64 -0.222 0.091 0.015 0.016 rs7052636 A 31.7 323 31.3 64 31.1 3 -0.411 0.162 0.017 0.012 rs10124533 A 31.7 379 30.6 12 . 0 -1.083 0.377 0.022 0.004 rs74688858 G 31.6 371 32.8 19 . 0 1.265 0.3616 0.032 0.001 rs78028581 T 31.5 332 32.2 57 32.2 3 0.5806 0.1667 0.034 0.001 rs182577340 T 31.7 380 30.4 11 . 0 -1,277 0.3595 0.035 0.000 rs1446986 T 31.7 346 31.0 43 29.7 One -0.7185 0.1939 0.037 0.000 rs76236914 G 31.7 307 31.2 79 30.3 6 -0.5401 0.1466 0.037 0.000 rs148731118 G 31.6 374 32.7 16 . 0 1.183 0.3091 0.039 0.000 rs117662467 A 31.7 366 30.7 25 . 0 -0.9759 0.2582 0.039 0.000 rs62265306 A 31.5 336 32.2 48 32.5 5 0.6141 0.1594 0.041 0.000 rs35487349 C 31.4 222 31.9 151 32.2 17 0.4328 0.1098 0.044 0.000 rs78250553 T 31.5 367 32.6 25 . 0 1.078 0.2518 0.050 0.000 rs185131643 T 31.7 373 30.4 18 . 0 -1.249 0.3067 0.050 0.000 rs35533493 T 31.8 278 31.3 103 30.7 10 -0.5284 0.1246 0.053 0.000 rs150085678 T 31.5 363 32.6 29 . 0 1.039 0.2413 0.054 0.000 rs4765986 G 31.8 224 31.4 140 30.9 25 -0.4827 0.1077 0.055 0.000 rs4350340 G 31.8 240 31.4 130 30.4 15 -0.5358 0.1139 0.062 0.000 rs9859074 A 31.4 228 31.9 136 32.4 25 0.5063 0.1058 0.065 0.000 rs4505040 T 31.8 245 31.4 127 30.3 14 -0.5835 0.1142 0.073 0.000 Effect Face temperature average before cleansing (℃) Effect Size Standard Error R2 (explanatory power) P (reliability) Average
(° C) frequency Average
(° C) frequency Average
(° C) frequency rs35487349 C 33.7 222 33.8 151 34.2 17 0.14 0.07 .0090 .0410 rs62265306 A 33.8 336 34.0 48 34.3 5 0.22 0.10 .0120 .0260 rs150085678 T 33.8 363 34.2 29 . 0 0.39 0.15 .0180 .0075 rs182577340 T 33.8 380 33.2 11 . 0 -0.60 0.22 .0180 .0072 rs80037149 C 33.8 376 33.3 16 . 0 -0.69 0.19 .0230 .0027 rs7313554 C 34.0 151 33.7 177 33.7 64 -0.18 0.06 .0250 .0020 rs117867835 A 33.8 376 33.4 14 31.2 One -0.68 0.20 .0310 .0006 rs117662467 A 33.8 366 33.3 25 . 0 -0.56 0.16 .0310 .0006 rs76840544 G 33.8 369 33.2 23 . 0 -0.61 0.17 .0340 .0004 rs10124533 A 33.8 379 33.0 12 . 0 -0.86 0.22 .0398 .0002 rs7052636 A 33.9 323 33.5 64 32.8 3 -0.44 0.10 .0550 .0000 rs4548934 A 34.0 106 33.8 195 33.5 87 -0.26 0.05 .0560 .0000 rs142551041 - 33.6 149 33.9 183 34.1 60 0.26 0.06 .0600 .0000

(Average: average value (° C) of the face temperature of the subject having the SNP type; frequency: the number of subjects having the SNP type (persons);

Effect Size: The degree to which the phenotype (skin temperature) value increases or decreases each time the effect (risk allele) increases;

Effect Size, Standard Error, R ² value, and p-value: calculated by linear regression analysis using the SPSS program)

The following 12 markers were obtained by screening the genetic variants with a non-effect / non-effect / effect / effect / effect frequency of 10 or more among the 34 markers selected. More specifically, eight markers of rs1800414, rs12696304, rs7313554, rs35487349, rs35533493, rs4765986, rs9859074 and rs4505040 as markers for skin temperature prediction after cleansing and rs35487349, rs7313554, rs4548934, A total of eleven markers (four overlapping rs7313554) including four markers of rs142551041 were selected as markers for face temperature prediction.

Among the markers for skin temperature prediction after cleansing, rs1800414, rs12696304, rs35487349, and rs9859074 (effect size is "+" value) indicate the frequency with which the effect allele is retained and the skin temperature is in direct proportion As the frequency increases, rs7313554, rs35533493, rs4765986, and rs4505040 (effect size is "-") increase with increasing frequency (order of non-effect / non-effect → non-effect / effect → effect / effect) (Ie, non-effect / non-effect → non-effect / effect → effect / effect order) as the frequency with which the effect alleles are retained and the skin temperature are inversely proportional Skin temperature decreases after cleansing). In addition, rs35487349 and rs142551041 (effect size is "+" value) among the markers for predicting facial skin temperature before cleansing, the frequency with which the effect allele is retained and the skin temperature are in direct proportion (that is, (Non-effect / non-effect → order of non-effect / effect → effect / effect) and rs7313554 and rs4548934 (effect size is "-" value) (Non-effect / Non-effect → Non-effect / Effect → Effect / Effect order) and decrease in skin temperature before cleansing) Can be predicted.

Table 3 shows the position and variation information of the marker.

Marker Chromosome number Chromosomal location Darwin's allele
(Major) Low frequency allele
(Minor) Sequence (extending by 50 bp in the 5 'and 3' direction) rs1800414 15 27951891 A G GAGTCAGAAGGTTGTGCAGAGTAAATGAGCTGTGGTTTCTCTCTTACAGC [A / G] TAGGATATCTGACGGGATTCTGCTCGCCAAATGCCTGACAGTGTTGGGAT (SEQ ID NO: 1) rs12696304 3 169763483 G C CGTCTCAAAAAAAAGAGAAGAAAAAAGCGATCTTAGATCACCTTGAGTAAA [G / C] CTGAGGCTTACTGAAGCTGAGCTACTTCCTCAAGACTCTAGACAAGTTCTT (SEQ ID NO: 2) rs7313554 12 128306497 T C CCACCTCGGCCTCCCAAAGTGCTGGGATTACAGGCGTGAGCCACCGCACC [T / C] GGCCACCCTGTGAAGAAATTCTAACTTGTAATTTGGGGGTTTCTGCTTTC (SEQ ID NO: 3) rs35487349 8 127560127 T C GGGAAGTGGGGTAAAAACACCCATCACTTGACTCCATAAATGCCTTTCCA [T / C] CTCCATGATGAAGACAAACTCCAGAGATGGTGCATTTATGCAACTGAGTA (SEQ ID NO: 4) rs35533493 14 64800891-64800892 - T TCTCATCAGGGTTTTCCGTAAAGACATCTGTTAGGGAAAAGGGTGTACTC [- / T] TCAGGACCAAACTGGAAGTCGGGAAAGTCAGGCTCAGAGGGTTTATTCCC (SEQ ID NO: 5) rs4765986 12 2728372 T G TTTTGAGAAGCGTCTGTTCATGTCCTTTGCCCACTTTTTATTGGAGATAT [T / G] TTTGCTCATTGATTTGTTAAGTTACTTTTAGATTCTGGATATTAGACCTT (SEQ ID NO: 6) rs9859074 3 124504088 G A TTGCAGGAAACCTCGGAAGTGCTCTCGTGGTACTCAGAGCACTTGGACCC [G / A] CATAAAAATTTGTTTCAGGTTTATACAAGTACTTGTTACAGAAATAGGGA (SEQ ID NO: 7) rs4505040 11 39574049 A T ATCATCTCTATATTCACACAGATTAGGTCCAAATCCTTAATTCCATTTAT [A / T] CTAACTGGGTCATCATAAGTAAGCTTACAAATTGATTCATCCTTTCATTA (SEQ ID NO: 8) rs35487349 8 127560127 T C GGGAAGTGGGGTAAAAACACCCATCACTTGACTCCATAAATGCCTTTCCA [T / C] CTCCATGATGAAGACAAACTCCAGAGATGGTGCATTTATGCAACTGAGTA (SEQ ID NO: 9) rs4548934 17 18811021 G A CCACCTCGGCCTCCCAAAGTGCTGGGATTACAGGCGTGAGCCACCGCACC [T / C] GGCCACCCTGTGAAGAAATTCTAACTTGTAATTTGGGGGTTTCTGCTTTC (SEQ ID NO: 10) rs142551041 8 125614334-125614337 GAGG - GTGCGAGTGTGTATGTAAGCGTGAGTTAAGCCTGTGTGGTCTGTATGTGT [GAGG / -] GAGAGTCGTGTGTGTGTATGAGAGTTGTGTGCGGGTGGCATAGGTGTCTG (SEQ ID NO: 11)

1.3. Calculate explanatory power according to marker combination

In order to calculate the explanatory power when a single marker is used in combination, explanatory power in a combination in which markers are added one by one in the order of highest explanatory power is confirmed, and when the explanatory power increases to a maximum value, the formula is selected as the optimum combination. Table 4 (after cleansing) and Table 5 (before cleansing) show the results for skin temperature predictive markers before and after cleansing, respectively.

In Table 4 and Table 5, explanatory power R ² was calculated by linear regression analysis using the SPSS program.

As can be seen in Tables 4 and 5, the combination of F7 and F8 exhibits the best explanatory power after cleansing, and it is possible to genetically explain about 24% of the skin temperature after cleansing with these combinations (F7 or F8) Prior to cleansing, the explanatory power of the combination of F11 and F12 is excellent, and the combination (F11 or F12) can genetically explain about 15% of the skin temperature before cleansing. In particular, F7 and F11 showed the most efficient combination of F8 and F12, which do not show any significant difference in the explanatory power.

1.4. Prediction of skin temperature by combination of markers

Table 1 summarizes the explanatory power of each marker selected in Example 1. 2 (Table 2), and based on this, an equation for predicting the skin temperature according to the marker is completed as shown in Table 7.

division Marker R2 (explanatory power) Non-effect allele Effect allele Non-effect / Non-effect ¹⁾ Non-effect / Effect ²⁾ Effect / Effect ³⁾ A1 rs4505040 0.073 A T 0 One 2 A2 rs9859074 0.065 G A 0 One 2 A3 rs4765986 0.055 T G 0 One 2 A4 rs35533493 0.053 - T 0 One 2 A5 rs35487349 0.044 T C 0 One 2 A6 rs7313554 0.015 T C 0 One 2 A7 rs12696304 0.013 G C 0 One 2 A8 rs1800414 0.011 A G 0 One 2 B1 rs142551041 0.06 GAGG - 0 One 2 B2 rs4548934 0.056 G A 0 One 2 B3 rs7313554 0.025 T C 0 One 2 B4 rs35487349 0.009 T C 0 One 2

( ¹⁾ : a score to be assigned to the following equation when the marker is non-effect / non-effect;

²⁾ : a score to be substituted into the following equation when the marker is non-effect / effect;

³⁾ : If the marker is Effect / Effect, the score to be assigned to the following formula)

Combination (Fn) Forecast temperature (℃) F1 31.869 + (-0.582) * A1 F2 31.641 + (-0.581) * A1 + 0.500 * A2 F3 31.843 + (-0.566) * A1 + 0.444 * A2 + (-0.382) * A3 F4 31.956 + (-0.542) * A1 + 0.425 * A2 + (-0.354) * A3 + (-0.432) * A4 F5 31.798 + (-0.498) * A1 + 0.402 * A2 + (-0.354) * A3 + (-0.402) * A4 + 0.306 * A5 F6 A9 + 0.299 * A5 + (-0.215) * A6 + (-0.495) * A1 + 0.400 * A2 + F7 A0 + 0.393 * A2 + -0.336 * A3 + -0.390 * A4 + 0.282 * A5 + (-0.216) * A6 + 0.194 * A7 F8 A0 + 0.384 * A2 + (-0.323) * A3 + (-0.386) * A4 + 0.281 * A5 + (-0.208) * A6 + 0.197 * A7 + 0.100 * A8 F9 33.603 + 0.263 * B1 F10 33.835 + 0.268 * B1 + (-0.249) * B2 F11 33.970 + 0.260 * B1 + (-0.251) * B2 + (-0.161) * B3 F12 33.934 + 0.244 * B1 + (-0.268) * B2 + (-0.160) * B3 + 0.127 * B4

(Non-effect / Effect: 1, Effect / Effect: 2) according to the number possessing the effect allele, The average temperature of the facial skin before and after cleansing can be predicted.

Example 2: Search for genetic polymorphism markers for predicting skin temperature 2

2.1 Skin temperature measurement and sample preparation

To measure the subject's skin temperature, 411 women between 20 and 35 years of age were measured for skin temperature before and after cleansing with FLIR T420 (infrared infrared camera, FLIR Systems, Inc.) Were used to collect oral internal gene samples. The cleansing was carried out using a weakly acidic foam at a water temperature of 15 to 21 ° C., and skin temperature was measured for 5 to 10 minutes before and after cleansing.

2.2 Selection of Significant Gene Polymorphic Markers

The average skin temperature before cleansing and after cleansing as measured in Example 2.1 was used as a phenotypic variable. The gene samples collected in Example 2.1 were analyzed using a large-scale SNP chip (PMRA SNP chip; Thermo Fisher Scientific Inc.) Were examined. Linear regression was used to identify genetic variants with significant differences in mean skin temperature variables before and after cleansing.

The selected markers for the model calculation are the combination of the effect allele and the non-effect allele, ie non-effect / non-effect homozygote, non-effect / effect heterozygote, Homozygotes, and each genotype has non-effect / non-effect to non-effect / effect, and skin temperature decreases when non-effect / effect to effect / effect Or increased. When the p-value was significantly lower (<0.0001) in the tendency to decrease or increase the skin temperature, 32 markers were obtained as significant genetic factors for this analysis (15 for average face temperature after washing and 1 for cleansing 17 for average face temperature).

The explanatory power (R square) of the marker was calculated by linear regression analysis using the SPSS program. When the prediction value is calculated using the prediction model, the difference between the actual measured value and the predicted value is called a residual. The smaller the residual is, the higher the explanatory power (R square) It can be interpreted as the degree to which.

The excavated markers and their explanatory power (R square) values are shown in Table 8 below.

Effect Average temperature after cleansing Effect Size Standard Error R2 (explanatory power) P (reliability) Non-effect / Non-effect Non-effect / Effect Effect / Effect Average
(° C) frequency Average
(° C) frequency Average
(° C) frequency rs6793971 T 31.23 115 31.54 216 32.10 77 .4223 0.091 0.057 0.000 rs1353899 G 31.71 231 31.60 150 30.54 29 -.3761 0.094 0.042 0.000 rs62286331 A 31.78 229 31.41 159 30.66 20 -.4485 0.102 0.051 0.000 rs2437317 A 31.33 104 31.42 203 32.09 101 .3817 0.086 0.052 0.000 rs55725714 T 31.70 319 31.13 84 30.80 6 -.5339 0.129 0.045 0.000 rs172063 A 31.87 182 31.36 187 31.28 42 -.3660 0.092 0.041 0.000 rs10271355 A 31.66 362 30.94 46 29.60 One -.7502 0.185 0.043 0.000 rs846437 A 31.66 359 30.98 48 29.60 One -.7154 0.181 0.041 0.000 rs6960088 G 31.73 250 31.33 139 30.76 18 -.4332 0.108 0.042 0.000 rs6987785 G 31.72 274 31.36 118 30.71 19 -.4277 0.106 0.042 0.000 rs2994693 G 31.92 117 31.54 196 31.20 95 -.3633 0.086 0.048 0.000 rs4149056 C 31.44 306 31.93 98 32.44 7 .4926 0.128 0.039 0.000 rs74980862 G 31.67 361 30.90 49 . 0 -.7689 0.187 0.044 0.000 rs11881857 A 31.30 178 31.70 190 32.06 42 .3876 0.095 0.043 0.000 rs73245304 T 31.47 344 32.04 63 32.93 3 .5981 0.155 0.039 0.000 Effect Average temperature before cleansing Effect Size Standard Error R2 (explanatory power) P (reliability) Non-effect / Non-effect Non-effect / Effect Effect / Effect Average
(° C) frequency Average
(° C) frequency Average
(° C) frequency rs4844704 G 34.00 242 33.60 142 33.6 23 -.2580 0.063 0.044 0.000 rs595744 G 34.00 200 33.70 163 33.5000 47 -2420 0.055 0.051 0.000 rs11679195 A 33.7 209 33.9 167 34.2 33 .2440 0.060 0.043 0.000 rs4490345 A 33.7 293 34.1 109 34.2 6 .3060 0.078 0.041 0.000 rs7623554 G 34 104 33.9 204 33.5 100 -2480 0.054 0.056 0.000 rs11942461 C 34 108 33.8 208 33.6 90 -.2400 0.055 0.050 0.000 rs2200330 T 33.7 280 34 121 34.4 8 .3000 0.075 0.041 0.000 rs6990898 T 33.9 254 33.7 138 33.3 18 -.2690 0.065 0.045 0.000 rs5894728 G 33.9 345 33.6 59 32.4 3 -.3870 0.101 0.039 0.000 rs112070666 - 33.9 320 33.5 83 33.4 5 -.3440 0.084 0.044 0.000 rs7975123 A 33.9 234 33.7 148 33.4 28 -2410 0.061 0.041 0.000 rs2991396 G 33.9 347 33.4 59 33.2 4 -.4190 0.100 0.046 0.000 rs12932810 G 34 201 33.8 166 33.4 42 -.2330 0.056 0.045 0.000 rs11641810 C 33.7 298 34 102 34.3 8 .3020 0.075 0.042 0.000 rs16971241 G 33.7 318 34 85 34.8 6 .3400 0.081 0.046 0.000 rs79997269 A 33.9 338 33.5 69 33.2 3 -.3430 0.095 0.034 0.000 rs2269626 A 33.8 364 34.3 46 33.6 One .4750 0.118 0.042 0.000

(Average: average value (° C) of the face temperature of the subject having the SNP type; frequency: the number of subjects having the SNP type (persons);

Effect Size: The degree to which the phenotype (skin temperature) value increases or decreases each time the effect (risk allele) increases;

Effect Size, Standard Error, R ² value, and p-value: calculated by linear regression analysis using the SPSS program)

A total of 17 markers were selected by screening the genetic variants with non-effect / non-effect, non-effect / effect, and effect / effect frequency of 10 or more among the selected 32 markers. More specifically, nine markers such as rs172063, rs1353899, rs6960088, rs6987785, rs11881857, rs2994693, rs62286331, rs2437317, and rs6793971 as markers for skin temperature prediction after cleansing and rs7975123 and rs11679195 A total of 17 markers including eight markers of rs4844704, rs6990898, rs12932810, rs11942461, rs595744, and rs7623554 were selected as markers for face temperature prediction.

Among the markers for predicting facial skin temperature after washing, rs11881857, rs2437317, and rs6793971 (effect size is "+" value) indicates that the frequency of effect (risk) alleles and skin temperature are in direct proportion (Non-effect / non-effect → non-effect / effect → effect / effect order) and increased skin temperature after cleansing) and rs172063, rs1353899, rs6960088, rs6987785, rs2994693, and rs62286331 Effectiveness / Effect / Effect / Effect) The frequency with which the effect allele is retained and the skin temperature are inversely proportional (ie, the frequency with which the effect allele is retained increases (Non-effect / Non- Effect sequence), skin temperature decreases after cleansing). In addition, rs11679195 (effect size "+" value) among the markers for predicting facial skin temperature before cleansing has a significant effect on the frequency with which the effect allele is retained and the skin temperature are directly proportional (ie, (The order of non-effect / non-effect → non-effect / effect → effect / effect) and skin temperature before cleansing) and rs7975123, rs4844704, rs6990898, rs12932810, rs11942461, rs595744, and rs7623554 (Non-effect / non-effect → non-effect / effect → effect / effect order) as the frequency with which the effect alleles are retained and the skin temperature are inversely proportional , Skin temperature before cleansing).

Table 9 shows the position and variation information of the marker.

Marker Chromosome number Chromosomal location Darwin's allele
(Major) Low frequency allele
(minor) Sequence (5 'and 3' extended in both directions by 50 bp) rs172063 7 24126684 C T TGACCCATTCACTTAAGCCAACTGAATTAAGTATTTGTAGCACCAGGTTC [C / T] TAAGAAAGAGGCCTATTTCTCAGAGTTTCTTGGAAAGTATTGGTGCCACT (SEQ ID NO: 12) rs1353899 3 177511191 T G GCATTTTCAGTTCTCTGCCTTTTCTTCTCATGTGACATGATGCATAGATG [A / G / T] TTGTTCAAATGGATATTTACAAATGATGACAATGAATGATAATAATTGAA (SEQ ID NO: 13) rs6960088 7 153644969 C G TCATATATATTTTGGATGTTGCATGTACCAATAACAAAGGGTAGCAATAC [A / C / G] ACTGCATTGTGATCTCATCGCAGACATATTAGGTTGTTTGAGATATTCTC (SEQ ID NO: 14) rs6987785 8 6016978 A G TACAAGGTAAGTTATTGCACACCATCCGAGACTGAGATGGAATTAAATGA [A / G] TGCCCCAAAATGACTAGAACAACCAGAAAAATCAAAGGTACCACTTTGGG (SEQ ID NO: 15) rs11881857 19 12237582 A G TGGAGCCACCTCGGCCTCTGGAAGGCTGAATTCAGTGGGTTAGGGGAACA [A / G] GAGCCCCTTAGACTTGCGGAGCTTGGCCCCACCCTCCTGGCGGAGCGCC (SEQ ID NO: 16) rs2994693 9 72799574 A G AAATTATGGTATAATTGAAAATTCTATTTTATTTTATTTGTTAAGCTTTC [A / G / T] GGAACCAGATAAATCCCCCCTTTGATGATATATGCTATTAATTTGATTTT (SEQ ID NO: 17) rs62286331 3 194171686 A G GTGTAAGTACACTCTGTGACGTTCACACAACAATGGAATTGCCTAAGCAC [A / G] CATTTCACAGAACGTGTCCTCGTTGTGAAGCATTGAATGAGTGTTTTTGA (SEQ ID NO: 18) rs2437317 4 40789990 A G AGGCAGACTCTCTTAAGCTAAGTCACAAGATCCTTAAAGGTATGATTGAT [A / C / G / T] TTTTACACCAGTTTGTATGGATTCTGTACCTTGGACTGGAAACTTATAAG (SEQ ID NO: 19) rs6793971 3 3658190 T C GCTGGTCGTTAGGGTTCAGAGTTTATGTCACAATTGTAATGGGTTATTGA [C / T] TGCCTCTTAAAGAACTTCATAGCTCCCCAGGCTTTGAATCCATTAATGAA (SEQ ID NO: 20) rs7975123 12 12807342 G A ACACCCTTCCTTTATCTGTGGGGTGCCGTAGACAGAATGCCTAGAGCCACA [A / G] TGCTTTTACATATCTCCAAAAACAGGTTTTCATTTCTTTCAAAATCAAAA (SEQ ID NO: 21) rs11679195 2 121818509 G A CAACCTCTAAGAGTCAGGGATGCTCCTTAACAACCTGCTGTGGATGGACC [A / G / T] GAAATTTATTTAAGCCCTCCCTGAACCTGTTTATGTTTCATTAAACTCTT (SEQ ID NO: 22) rs4844704 One 208646201 C G AAAACAAAACACAACCGAAATCAGTGCACCAAGAAGATGGTAACAAACTA [C / G] ATAGGGCATCAGGGTCTCTCCCTTTTGTGCTGAGGTGGATTTTGACTGTG (SEQ ID NO: 23) rs6990898 8 102522711 C T ATGTAAGTTCATGGATGGATCGCTTGCTGCCCTCAAGTGTGGTCGCTGCT [C / T] AGCACTCTGTGAACCCGGAAAGAAATCTTAGCCCCTTAGAGTGACCATTA (SEQ ID NO: 24) rs12932810 16 83825042 T G CTTCTTCACGACTCAGTTTAATTCTCAGCATAAGCCCTCCAGTCAATTCG [G / T] TGCTCTAAAAAGTTGGAAAACATTTATTAAACACCCACTGAATGCCAGGA (SEQ ID NO: 25) rs11942461 4 60494379 T C ACACCACAGCAGCCAAGATTGGAGAGAGAATATGCAAGTCACAAGAAGCA [A / C / T] TGTGATATTATTGAAAACATATCGTATCGAGGACTCTAGAAACCTGGTAC (SEQ ID NO: 26) rs595744 2 79986880 A G TGCTTCTCAAAGAAGCTACTTCCAGGGCCTCTGTTTACATGTTGTCTTTA [A / G] GAAGTAATTTAATCCAGAATGTAACAGACATCTTGATCTGCCCTGAGTTT (SEQ ID NO: 27) rs7623554 3 139259641 G A AGAGGTTACTTAGCTTTCCTTAGGTCACACAGTAGGGAAGTGTTAAATTT [A / G] AGGTTGTTACAGAAATATATTCAGTCCAAAAGAATTTAATAAAGACACAT (SEQ ID NO: 28)

2.3. Calculate explanatory power according to marker combination

In order to calculate the explanatory power when a single marker is used in combination, the explanatory power of the combination of the rs6793971 (average after cleansing) and rs7623554 (average before cleansing) , And when the explanatory power increases to the maximum, the formula is selected as the optimal combination. Table 10 and Table 11 show the results obtained for the pre-cleansing and post-cleansing skin temperature prediction markers, respectively.

In Table 10 and Table 11, the analysis p-value and the explanatory power R ² were calculated by linear regression analysis using the SPSS program.

In Table 10 and Table 11, the optimum combination was selected as a combination in which the explanatory force was not increased even further by adding the marker. As shown in Table 10 and Table 11, considering that the explanatory power increases in proportion to the number of markers and the degree of increase in the explanatory power due to the increase in the number of markers becomes gentle, the F4 combination (i.e., F4 combination (Approximately 18% of skin temperature after cleansing can be explained genetically), and F7 combination (ie, genetically explainable about 22% of skin temperature before cleansing through F7 combination) before cleansing.

2.4. Prediction of skin temperature by combination of markers

The descriptive power of each marker measured in Example 2.2 (Table 9) is summarized in Table 12 below, and based on this, a formula for predicting the skin temperature according to the marker as shown in Table 13 (after cleansing) and Table 14 Completed.

division Marker R2 (explanatory power) Non-effect allele Effect allele Non-effect /
Non-effect ¹⁾ Non-effect /
Effect ²⁾ Effect / Effect ³⁾ A1 (A_Ave1) rs6793971 0.057 T C 0 One 2 A2 (A_Ave2) rs2437317 0.052 A G 0 One 2 A3 (A_Ave3) rs62286331 0.051 A G 0 One 2 A4 (A_Ave4) rs2994693 0.048 A G 0 One 2 A5 (A_Ave5) rs11881857 0.043 A G 0 One 2 A6 (A_Ave6) rs6987785 0.042 A G 0 One 2 A7 (A_Ave7) rs6960088 0.042 C G 0 One 2 A8 (A_Ave8) rs1353899 0.042 T G 0 One 2 A9 (A_Ave9) rs172063 0.041 C T 0 One 2 B1 (B_Ave1) rs7623554 0.056 G A 0 One 2 B2 (B_Ave2) rs595744 0.051 A G 0 One 2 B3 (B_Ave3) rs11942461 0.050 T C 0 One 2 B4 (B_Ave4) rs12932810 0.045 T G 0 One 2 B5 (B_Ave5) rs6990898 0.045 C T 0 One 2 B6 (B_Ave6) rs4844704 0.044 C G 0 One 2 B7 (B_Ave7) rs11679195 0.043 G A 0 One 2 B8 (B_Ave8) rs7975123 0.041 G A 0 One 2

( ¹⁾ : a score to be assigned to the following equation when the marker is non-effect / non-effect; ^{2 )} : a score to be substituted into the following equation when the marker is non-effect / effect;

³⁾ : If the marker is Effect / Effect, the score to be assigned to the following formula)

Combination (Fn) Estimated skin average temperature after cleansing (℃) F1 31.174 + (0.422) * A1 F2 30.834 + (0.403) * A1 + (0.355) * A2 F3 31.070 + (0.399) * A1 + (0.340) * A2 + (-0.415) * A3 F4
(Optimal combination) 31.398 + (0.390) * A1 + (0.321) * A2 + (-0.409) * A3 + (-0.323) * A4 F5 (0.316) * A2 + (-0.397) * A3 + (-0.301) * A4 + (0.316) * A5 F6 A0 + (-0.392) * A3 + (-0.287) * A4 + (0.284) * A5 + (-0.341) * A6 F7 A5 + (-0.295) * A6 + (-0.335) * A7 + (0.329) * A2 + (-0.413) * A3 + (-0.285) F8 A6 + (-0.265) * A7 + (-0.265) * A4 + (0.275) * A5 + (0.303) * A1 + 0.280) * A8 F9 A7 + (-0.281) * A6 + (-0.252) * A7 + (-0.271) * A3 + (-0.271) 0.283) * A8 + (-0.300) * A9

Combination (Fn) Estimated skin average temperature before cleansing (℃) F1 34.050 + (-0.248) * B1 F2 34.157 + (-0.223) * B1 + (-0.206) * B2 F3 34.347 + (-0.215) * B1 + (-0.198) * B2 + (-0.216) * B3 F4 34.410 + (-0.193) * B1 + (-0.184) * B2 + (-0.204) * B3 + (-0.161) * B4 F5 B4 + (-0.210) * B1 + (-0.181) * B2 + (-0.183) * B3 + (-0.125) * B4 + (-0.224) * B5 F6 B4 + (-0.248) * B5 + (-0.191) * B6 + (-0.114) * B2 + (-0.149) F7 (Optimal combination) B3 + (-0.141) * B4 + (-0.141) * B5 + (-0.190) * B6 + (0.202) * B7 F8 B4 + (-0.127) * B6 + (-0.134) * B2 + (-0.144) * B3 + (-0.097) (-0.157) * B8

(Non-effect / effect: 1, effect / effect: 2) according to the number of minor alleles, The average temperature of the facial skin before and after cleansing can be predicted.

Example 3: Correlation test between temperature and skin index for each face region

Before and after skin cleansing, skin temperature was measured with FLIR T420 (FLIR Systems, Inc.) (see Examples 1.1 or 2.1) and the correlation with each skin index was tested.

For ease of testing, the facial regions are marked as follows:

SP1: forehead; SP2: Right view; SP3: Nose; SP4: left ball; SP5: mouth; SP6: Right eye; SP7: Left eye.

Hemoglobin is a red protein that contains iron in red blood cells, and is a pigment protein that imparts color to the skin, such as melanin or carotene pigment, and is particularly characterized by imparting red color to the skin. For example, the higher the intravascular hemoglobin concentration in the dermal layer of the skin, the darker the skin is imparted. The hemoglobin concentration in the skin can be measured using, for example, a device for measuring hemoglobin concentration per unit area, which is calculated as a result of analysis of a polarized image of a selected region. In this embodiment, Antera3D Pro? (Manufactured by Miravex). The mean hemoglobin concentration in the skin was found to be 1.0 to 1.5 AU, specifically 1.1 to 1.3 AU, as measured by 411 subjects with alleles of both alleles.

There were atopic dermatitis symptoms on both balls. The left and right hemispheric lesions (1.362 AU) were higher than the right hemisphere (1.239 AU: good) The temperature measurement results for each region are shown in Table 15:

As shown in Table 15, in the case of subject 1, the left ball (SP4) having a severe atopic dermatitis symptom and a high hemoglobin level (i.e., having more blood vessels developed) Is as high as about 0.9 占 폚. These results show that the skin temperature difference before and after cleansing is proportional to the degree of dermatitis and / or vascular development, and a large difference in skin temperature before and after cleansing is a site where the dermatitis symptoms are severe and the degree of vascular development is high. The greater the degree of dermatitis and / or the degree of vascular development can be said to mean.

Table 16 shows the results of skin temperature measurements for each face area before and after cleansing of an adult male subject 2 whose hemoglobin level in the left ball (1.435 AU; slightly higher) is higher than the right ball (1.335 AU: good)

As shown in Table 16, in the case of subject 2, the left ball (SP4) having a high hemoglobin level (i.e., the blood vessels were developed more) had a skin temperature before and after cleansing the right ball (SP2) As shown in Fig. These results indicate that the skin temperature is proportional to the degree of vascular development, which means that the higher the skin temperature, the greater the degree of vascular development (increased hemoglobin level).

Table 17 shows the results of measuring the skin temperature of each part of the face before and after cleansing of the adult female subject 3 who had more severe skin troubles (such as acne) in the right eye:

As shown in Table 17, in the case of subject 3, it was confirmed that the right ball (SP2), which had more severe skin troubles, had a skin temperature of about 1.4 degrees Celsius before cleansing and a skin temperature of about 2.4 degrees Celsius after cleansing . These results show that the skin temperature is related to the skin troubles, which means that the higher the skin temperature, the worse the skin trouble.

Table 18 shows the results of skin temperature measurement for each part of the face before and after cleansing of the adult female subject 4 who suffered from severe seborrheic dermatitis on the right ball:

As shown in Table 18, in the case of subject 4, the difference in skin temperature before and after cleansing of the right ball (SP2), which is more severe in seborrheic dermatitis, was about 1.2 DEG C, and the left ball SP4 ). &Lt; / RTI &gt; These results indicate that the difference in skin temperature before and after cleansing is related to seborrheic dermatitis. It is said that a large difference in skin temperature before and after cleansing is a severe site of seborrheic dermatitis, and the larger the difference, the more severe the symptoms of seborrheic dermatitis .

The results of skin temperature measurement for each part of the face before and after cleansing of subject 5 of an adult female subject with oil overexpression on the forehead are shown in Table 19:

As shown in Table 19, in the case of subject 5, it was confirmed that the skin temperature before and after cleansing of the forehead area (SP1), which is severely over-oiled, is higher than other parts (maximum of about 4.2 ° C and minimum of about 0.7 ° C) . These results indicate that the skin temperature is related to the degree of oiliness. It means that the region with high skin temperature is excessive region of oil, and the higher the temperature, the more the oil excess.

<110> AMOREPACIFIC CORPORATION          THERAGEN ETEX CO., LTD <120> Genetic Polymorphic marker for predicting skin-temperature and          use thereof <130> DPP20181350KR <150> 10-2017-0065444 <151> 2017-05-26 <160> 28 <170> Kopatentin 3.0 <210> 1 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs1800414, wherein n is A or G <400> 1 gagtcagaag gttgtgcaga gtaaatgagc tgtggtttct ctcttacagc ntaggatatc 60 tgacgggatt ctgctcgcca aatgcctgac agtgttggga t 101 <210> 2 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs12696304, wherein n is C or G <400> 2 cgtctcaaaa gaaagagaag aaaaagcgat cttagatcac cttgagtaaa nctgaggctt 60 actgaagctg agctacttcc tcaagactct agacaagttc t 101 <210> 3 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs7313554, wherein n is T or C <400> 3 ccacctcggc ctcccaaagt gctgggatta caggcgtgag ccaccgcacc nggccaccct 60 gtgaagaaat tctaacttgt aatttggggg tttctgcttt c 101 <210> 4 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs35487349, wherein n is T or C <400> 4 gggaagtggg gtaaaaacac ccatcacttg actccataaa tgcctttcca nctccatgat 60 gaagacaaac tccagagatg gtgcatttat gcaactgagt a 101 <210> 5 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs35533493, wherein n is absent or T <400> 5 tctcatcagg gttttccgta aagacatctg ttagggaaaa gggtgtactc ntcaggacca 60 aactggaagt cgggaaagtc aggctcagag ggtttattcc c 101 <210> 6 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs4765986, wherein n is T or G <400> 6 ttttgagaag cgtctgttca tgtcctttgc ccacttttta ttggagatat ntttgctcat 60 tgatttgtta agttactttt agattctgga tattagacct t 101 <210> 7 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs9859074, wherein n is G or <400> 7 ttgcaggaaa cctcggaagt gctctcgtgg tactcagagc acttggaccc ncataaaaat 60 ttgtttcagg tttatacaag tacttgttac agaaataggg a 101 <210> 8 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising RS4505040, wherein n is A or T <400> 8 atcatctcta tattcacaca gattaggtcc aaatccttaa ttccatttat nctaactggg 60 tcatcataag taagcttaca aattgattca tcctttcatt a 101 <210> 9 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs35487349, wherein n is T or C <400> 9 gggaagtggg gtaaaaacac ccatcacttg actccataaa tgcctttcca nctccatgat 60 gaagacaaac tccagagatg gtgcatttat gcaactgagt a 101 <210> 10 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs4548934, wherein n is T or C <400> 10 ccacctcggc ctcccaaagt gctgggatta caggcgtgag ccaccgcacc nggccaccct 60 gtgaagaaat tctaacttgt aatttggggg tttctgcttt c 101 <210> 11 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs142551041, wherein n is GAGG or          absent <400> 11 gtgcgagtgt gtatgtaagc gtgagttaag cctgtgtggt ctgtatgtgt ngagagtcgt 60 gtgtgtgtat gagagttgtg tgcgggtggc ataggtgtct g 101 <210> 12 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs172063, wherein n is C or T <400> 12 tgacccattc acttaagcca actgaattaa gtatttgtag caccaggttc ntaagaaaga 60 ggcctatttc tcagagtttc ttggaaagta ttggtgccac t 101 <210> 13 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide as rs1353899, wherein n is A, G, or T <400> 13 gcattttcag ttctctgcct tttcttctca tgtgacatga tgcatagatg nttgttcaaa 60 tggatattta caaatgatga caatgaatga taataattga a 101 <210> 14 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs6960088, wherein n is a, C, or G <400> 14 tcatatatat tttggatgtt gcatgtacca ataacaaagg gtagcaatac nactgcattg 60 tgatctcatc gcagacatat taggttgttt gagatattct c 101 <210> 15 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs6987785, wherein n is A or G <400> 15 tacaaggtaa gttattgcac accatccgag actgagatgg aattaaatga ntgccccaaa 60 atgactagaa caaccagaaa aatcaaaggt accactttgg g 101 <210> 16 <211> 100 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs11881857, wherein n is A or G <400> 16 tggagccacc tcggcctctg gaaggctgaa ttcagtgggt taggggaaca ngagcccctt 60 agacttgcgg agcttggccc caccctcctg gcggagcgcc 100 <210> 17 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs2994693, wherein n is A, G, or T <400> 17 aaattatggt ataattgaaa attctatttt attttatttg ttaagctttc nggaaccaga 60 taaatccccc ctttgatgat atatgctatt aatttgattt t 101 <210> 18 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs62286331, wherein n is A or G <400> 18 gtgtaagtac actctgtgac gttcacacaa caatggaatt gcctaagcac ncatttcaca 60 gaacgtgtcc tcgttgtgaa gcattgaatg agtgtttttg a 101 <210> 19 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotides comprising rs2437317, wherein n is A, C, G, or T <400> 19 aggcagactc tcttaagcta agtcacaaga tccttaaagg tatgattgat nttttacacc 60 agtttgtatg gattctgtac cttggactgg aaacttataa g 101 <210> 20 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs6793971, wherein n is C or T <400> 20 gctggtcgtt agggttcaga gtttatgtca caattgtaat gggttattga ntgcctctta 60 aagaacttca tagctcccca ggctttgaat ccattaatga a 101 <210> 21 <211> 102 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs7975123, wherein n is A or G <400> 21 acacccttcc cttatctgtg gggtgccgta gacagaatgc ctagagccac antgctttta 60 catatctcca aaaacaggtt ttcatttctt tcaaaatcaa aa 102 <210> 22 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs11679195, wherein n is A, G, or T <400> 22 caacctctaa gagtcaggga tgctccttaa caacctgctg tggatggacc ngaaatttat 60 ttaagccctc cctgaacctg tttatgtttc attaaactct t 101 <210> 23 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs4844704, wherein n is C or G <400> 23 aaaacaaaac acaaccgaaa tcagtgcacc aagaagatgg taacaaacta natagggcat 60 cagggtctct cccttttgtg ctgaggtgga ttttgactgt g 101 <210> 24 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs6990898, wherein n is C or T <400> 24 atgtaagttc atggatggat cgcttgctgc cctcaagtgt ggtcgctgct nagcactctg 60 tgaacccgga aagaaatctt agccccttag agtgaccatt a 101 <210> 25 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs12932810, wherein n is G or T <400> 25 cttcttcacg actcagttta attctcagca taagccctcc agtcaattcg ntgctctaaa 60 aagttggaaa acatttatta aacacccact gaatgccagg a 101 <210> 26 <211> 101 <212> DNA <213> Artificial Sequence <220> &Lt; 223 > Polynucleotide < / RTI > <400> 26 acaccagac agccaagatt ggagagagaa tatgcaagtc acaagaagca ntgtgatatt 60 attgaaaaca tatcgtatcg aggactctag aaacctggta c 101 <210> 27 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs595744, wherein n is A or G <400> 27 tgcttctcaa agaagctact tccagggcct ctgtttacat gttgtcttta ngaagtaatt 60 taatccagaa tgtaacagac atcttgatct gccctgagtt t 101 <210> 28 <211> 101 <212> DNA <213> Artificial Sequence <220> <223> Polynucleotide comprising rs7623554, wherein n is A or G <400> 28 agaggttact tagctttcct taggtcacac agtagggaag tgttaaattt naggttgtta 60 cagaaatata ttcagtccaa aagaatttaa taaagacaca t 101

Claims (27)

rs172063, rs1353899, rs6960088, rs6987785, rs11881857, rs2994693, rs62286331, rs2437317, rs6793971, rs7975123, rs11679195, rs4844704, rs6990898, rs12932810, rs11942461, rs595744, rs7623554, rs1800414, rs12696304, rs7313554, rs35487349, rs35533493, rs4765986, rs9859074, rs4505040, A composition for predicting skin temperature, comprising a detectable agent of one or more gene polymorphic markers selected from the group consisting of rs35487349, rs7313554, rs4548934, and rs142551041. The method according to claim 1, wherein at least one gene polymorphism marker selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, rs172063, rs1800414, rs12696304, rs7313554, rs35487349, rs35533493, rs4765986, rs9859074, and rs4505040 Wherein the skin temperature after skin rinsing is predicted. 3. The method of claim 2, comprising a detectable agent of one or more gene polymorphic markers selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs696778, rs1353899, and rs172063, Wherein the skin temperature of the composition is in the range of from about 1 to about 10 hours. 4. The composition for predicting skin temperature according to claim 3, which comprises a detectable preparation of a polymorphism marker selected from the group consisting of:
(i) rs6793971,
(ii) a combination of (a) rs6793971 and (b) one or more gene polymorphism markers selected from the group consisting of rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063,
(iii) a combination of (a) rs6793971 and rs2437317, and (b) one or more gene polymorphic markers selected from the group consisting of rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063,
(iv) a combination of (a) one or more gene polymorphism markers selected from the group consisting of rs6793971, rs2437317, and rs62286331 and (b) rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063,
(v) a combination of (a) one or more gene polymorphism markers selected from the group consisting of rs6793971, rs2437317, rs62286331 and rs2994693, and (b) rs11881857, rs6987785, rs6960088, rs1353899, and rs172063,
(vi) a combination of (a) one or more gene polymorphic markers selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, and rs11881857, and (b) rs6987785, rs6960088, rs1353899, and rs172063,
(vii) a combination of (a) one or more gene polymorphism markers selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, and rs6987785, (b) rs6960088, rs1353899, and rs172063,
(viii) a combination of (a) one or more gene polymorphic markers selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, and rs6960088, (b) rs1353899, and rs172063, and
(ix) Combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063. 5. The composition for predicting skin temperature according to claim 4, which comprises a detectable preparation of a gene polymorphism marker selected from the group consisting of:
(i) rs6793971,
(ii) a combination of rs6793971 and rs2437317,
(iii) a combination of rs6793971, rs2437317, and rs62286331,
(iv) a combination of rs6793971, rs2437317, rs62286331 and rs2994693,
(v) a combination of rs6793971, rs2437317, rs62286331, rs2994693, and rs11881857,
(vi) a combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, and rs6987785,
(vii) a combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, and rs6960088,
(viii) combinations of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, and rs1353899, and
(ix) Combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063. The method according to claim 1, comprising a detectable preparation of one or more gene polymorphic markers selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, rs7975123, rs35487349, rs7313554, rs4548934, and rs142551041, A composition for predicting skin temperature, characterized by predicting skin temperature. The method according to claim 6, characterized by comprising a detectable preparation of at least one gene polymorphic marker selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4899704, rs11679195 and rs7975123, Wherein the composition is used for skin temperature prediction. 8. The composition for predicting skin temperature according to claim 7, which comprises a detectable preparation of a gene polymorphism marker selected from the group consisting of:
(i) rs7623554,
(ii) a combination of (a) rs7623554 and (b) one or more gene polymorphism markers selected from the group consisting of rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123,
(iii) a combination of (a) rs7623554 and rs595744, and (b) one or more gene polymorphism markers selected from the group consisting of rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123,
(iv) a combination of (a) rs7623554, rs595744, and rs11942461, and (b) one or more gene polymorphism markers selected from the group consisting of rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123,
(v) a combination of (a) one or more gene polymorphism markers selected from the group consisting of rs7623554, rs595744, rs11942461, and rs12932810, and (b) rs6990898, rs4844704, rs11679195, and rs7975123,
(vi) a combination of (a) one or more gene polymorphic markers selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, and rs6990898, and (b) rs4844704, rs11679195, and rs7975123,
(vii) a combination of (a) one or more gene polymorphism markers selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, and rs4844704, and (b) rs11679195 and rs7975123,
(viii) Combination of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123. 9. The composition for predicting skin temperature according to claim 8, which comprises a detectable preparation of a gene polymorphism marker selected from the group consisting of:
(i) rs7623554,
(ii) a combination of rs7623554 and rs595744,
(iii) a combination of rs7623554, rs595744, and rs11942461,
(iv) a combination of rs7623554, rs595744, rs11942461, and rs12932810,
(v) a combination of rs7623554, rs595744, rs11942461, rs12932810, and rs6990898,
(vi) a combination of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, and rs4844704,
(vii) combinations of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, and rs11679195, and
(viii) Combination of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123. 10. The method according to any one of claims 1 to 9, wherein the detectable agent of the genetic polymorphism marker comprises 1 to 100 nucleotides capable of binding to a site comprising a consecutive 1 to 200 nucleotides on the chromosome, A composition for predicting skin temperature, which is an oligonucleotide molecule comprising a nucleotide.  In a biological sample isolated from a human rs172063, rs1353899, rs6960088, rs6987785, rs11881857, rs2994693, rs62286331, rs2437317, rs6793971, rs7975123, rs11679195, rs4844704, rs6990898, rs12932810, rs11942461, rs595744, rs7623554, rs1800414, rs12696304, rs7313554, rs35487349, rs35533493 comprising identifying a nucleic acid sequence of one or more gene polymorphic markers selected from the group consisting of rs4765986, rs9859074, rs4505040, rs35487349, rs7313554, rs4548934, and rs142551041. 13. The method according to claim 12, wherein the polymorphic marker is selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, rs170063, rs1800414, rs12696304, rs7313554, rs35533493, rs35533493, rs4765986, rs9859074 and rs4505040 At least one skin temperature after skin rinsing, and predicting skin temperature after skin rinsing. 13. The method according to claim 12, wherein the gene polymorphism marker is at least one selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899 and rs172063, , And providing information on skin temperature prediction. 14. The method according to claim 13, wherein the gene polymorphism marker is selected from the following and predicts skin temperature after skin rinsing:
(i) rs6793971,
(ii) a combination of (a) rs6793971 and (b) one or more gene polymorphism markers selected from the group consisting of rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063,
(iii) a combination of (a) rs6793971 and rs2437317, and (b) one or more gene polymorphic markers selected from the group consisting of rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063,
(iv) a combination of (a) one or more gene polymorphism markers selected from the group consisting of rs6793971, rs2437317, and rs62286331 and (b) rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063,
(v) a combination of (a) one or more gene polymorphism markers selected from the group consisting of rs6793971, rs2437317, rs62286331 and rs2994693, and (b) rs11881857, rs6987785, rs6960088, rs1353899, and rs172063,
(vi) a combination of (a) one or more gene polymorphic markers selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, and rs11881857, and (b) rs6987785, rs6960088, rs1353899, and rs172063,
(vii) a combination of (a) one or more gene polymorphism markers selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, and rs6987785, (b) rs6960088, rs1353899, and rs172063,
(viii) a combination of (a) one or more gene polymorphic markers selected from the group consisting of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, and rs6960088, (b) rs1353899, and rs172063, and
(ix) Combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063. 15. The method according to claim 14, wherein the gene polymorphism marker is selected from the following and predicts the skin temperature after skin rinsing:
(i) rs6793971,
(ii) a combination of rs6793971 and rs2437317,
(iii) a combination of rs6793971, rs2437317, and rs62286331,
(iv) a combination of rs6793971, rs2437317, rs62286331 and rs2994693,
(v) a combination of rs6793971, rs2437317, rs62286331, rs2994693, and rs11881857,
(vi) a combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, and rs6987785,
(vii) a combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, and rs6960088,
(viii) combinations of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, and rs1353899, and
(ix) Combination of rs6793971, rs2437317, rs62286331, rs2994693, rs11881857, rs6987785, rs6960088, rs1353899, and rs172063. The method according to claim 15, wherein skin temperature after skin cleansing is predicted using at least one calculation formula selected from the following:
(i) 31.174 + (0.422) * A1,
(ii) 30.834 + (0.403) * A1 + (0.355) * A2,
(iii) 31.070 + (0.399) * A1 + (0.340) * A2 + (-0.415) * A3,
(iv) 31.398 + (0.390) * A1 + (0.321) * A2 + (-0.409) * A3 + (-0.323)
(V) 31.167 + (0.384) * A1 + (0.312) * A2 + (-0.397) * A3 + (-0.301)
(vi) 31.323 + 0.344 * A1 + 0.331 * A2 + -0.392 A3 + -0.287 A4 + 0.284 A5 +
A3 + (-0.235) * A4 + (0.259) * A5 + (-0.295) * A6 + (-0.335) * A7 (+0.359) ,
(-0.265) * A3 + (-0.265) * A4 + (0.275) * A5 + (-0.310) * A6 + (-0.265) * A7 + (0.303) + (-0.280) * A8, and
(0.25) * A5 + (-0.281) * A6 + (-0.252) * A3 + (-0.271) * A3 + + (-0.283) * A8 + (-0.300) * A9
(Where A1 is the number of risk alleles of rs6793971, A2 is the number of risk alleles of rs2437317, A3 is the number of risk alleles of rs62286331, A4 is the number of risk alleles of rs2994693, A5 is the number of risk alleles of rs11881857, A6 is the number of risk alleles of rs6987785, A7 is the number of risk alleles of rs6960088, A8 is the number of risk alleles of rs1353899, and A9 is the risk alleles of rs172063:

). The method according to claim 11, wherein the gene polymorphism marker is at least one selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, rs7975123, rs35487349, rs7313554, rs4548934 and rs142551041, Gt; wherein the skin temperature prediction is performed on the skin temperature. The method according to claim 17, wherein the gene polymorphism marker is at least one selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123, A method of providing information to temperature prediction. The method according to claim 18, wherein the gene polymorphism marker is selected from the following: predicting skin temperature before skin cleansing:
(i) rs7623554,
(ii) a combination of (a) rs7623554 and (b) one or more gene polymorphism markers selected from the group consisting of rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123,
(iii) a combination of (a) rs7623554 and rs595744, and (b) one or more gene polymorphism markers selected from the group consisting of rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123,
(iv) a combination of (a) rs7623554, rs595744, and rs11942461, and (b) one or more gene polymorphism markers selected from the group consisting of rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123,
(v) a combination of (a) one or more gene polymorphism markers selected from the group consisting of rs7623554, rs595744, rs11942461, and rs12932810, and (b) rs6990898, rs4844704, rs11679195, and rs7975123,
(vi) a combination of (a) one or more gene polymorphic markers selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, and rs6990898, and (b) rs4844704, rs11679195, and rs7975123,
(vii) a combination of (a) one or more gene polymorphism markers selected from the group consisting of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, and rs4844704, and (b) rs11679195 and rs7975123,
(viii) Combination of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123. 20. The method according to claim 19, wherein the gene polymorphism marker is selected from the following: predicting skin temperature before skin cleansing:
(i) rs7623554,
(ii) a combination of rs7623554 and rs595744,
(iii) a combination of rs7623554, rs595744, and rs11942461,
(iv) a combination of rs7623554, rs595744, rs11942461, and rs12932810,
(v) a combination of rs7623554, rs595744, rs11942461, rs12932810, and rs6990898,
(vi) a combination of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, and rs4844704,
(vii) combinations of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, and rs11679195, and
(viii) Combination of rs7623554, rs595744, rs11942461, rs12932810, rs6990898, rs4844704, rs11679195, and rs7975123. 21. The method according to claim 20, wherein skin temperature before skin cleans is predicted using at least one calculation formula selected from the following:
(i) 34.050 + (-0.248) * B1,
(ii) 34.157 + (-0.223) * B1 + (-0.206) * B2,
(iii) 34.347 + (-0.215) * B1 + (-0.198) * B2 + (-0.216) * B3,
(iv) 34.410 + (-0.193) * B1 + (-0.184) * B2 + (-0.204) * B3 + (-0.161) * B4,
(v) 34.481 + (-0.210) * B1 + (-0.181) * B2 + (-0.183) * B3 + (-0.125) * B4 + (-0.224) * B5,
(vi) 34.526 + (-0.214) * B1 + (-0.149) * B2 + (-0.152) * B3 + (-0.112) * B4 + (-0.248) * B5 + (-0.191)
(-0.141) * B6 + (-0.141) * B3 + (-0.111) * B4 + (-0.241) * B5 + (-0.190) * B6 + (0.202) * B7, and
B4 + (-0.227) * B5 + (-0.189) * B6 + (0.190) * B2 + (-0.144) * B3 + (-0.097) * B7 + (-0.157) * B8
B2 is the number of risk alleles of rs595744, B3 is the number of risk alleles of rs11942461, B4 is the number of risk alleles of rs12932810, B5 is the number of risk alleles of rs6990898, B6 is the number of risk alleles of rs4844704, B7 is the number of risk alleles of rs11679195, and B8 is the risk allele of rs7975123:

). Identifying a nucleic acid sequence of one or more gene polymorphic markers selected from the group consisting of rs11881857, rs2437317, rs6793971, rs11679195, rs1800414, rs35487349, rs9859074, rs35487349, and rs142551041 in the biological sample, and
It is predicted that the skin temperature is higher as the number of low frequency alleles present in the gene polymorphism marker increases or that the skin temperature is lower as the number of alleles of alleles increases
Wherein the skin temperature estimator is configured to determine a skin temperature estimate. One or more polymorphisms selected from the group consisting of rs172063, rs1353899, rs6960088, rs6987785, rs2994693, rs62286331, rs7975123, rs4844704, rs6990898, rs12932810, rs11942461, rs595744, rs7623554, rs7313554, rs35533493, rs4765986, rs4505040, rs7313554, and rs4548934 in biological samples Identifying the nucleic acid sequence of the marker, and
It is predicted that the skin temperature is lower as the number of low frequency alleles in the gene polymorphism marker increases or that the skin temperature is higher as the number of alleles of alleles increases
Wherein the skin temperature estimator is configured to determine a skin temperature estimate. 10. A composition for diagnosing skin condition comprising the composition for predicting skin temperature according to any one of claims 1 to 9. 25. The composition of claim 24, wherein the skin condition is skin oil content, skin moisture content, skin irritation, degree of skin vascular development, or skin hemoglobin level. 23. A method of providing information to a skin condition diagnosis, the method comprising performing a method of providing information to the skin temperature prediction of any one of claims 11 to 23. 27. The method of claim 26, wherein the skin condition is skin oil content, skin moisture content, skin irritation, degree of skin vascular development, or skin hemoglobin level.