BACKGROUND
the skin provides a protective barrier against invading microbial pathogens, while also serving as a habitat for a plethora of commensal bacteria.
the composition of skin microbiota varies among individuals, but a core set of microbes can be found in all subjects for each anatomical location .
recent advances in high-throughput sequencing technologies have enabled rapid analysis of microbial communities indigenous to specific niches in the human body  <cit> .
there is significant inter-individual variation in the skin microbiota, which is attributable to genetic differences and environmental factors.
colonization of the host body by bacteria occurs immediately after birth, with more complex microbial communities developing in distinct anatomical niches afterwards  <cit> .
succession of the microbiota within individual hosts is also driven by host-intrinsic factors, such as age, gender, genotype and health status, as well as environmental and lifestyle factors, such as climate, light exposure, and detergent use  <cit> .
previous studies have quantitatively explored host genetic effects on the gut microbiome composition using animal models and humans .
these studies revealed a significant influence of host genetic factors on the microbiota.
however, the impact of host gene expression on skin microbial diversity in human subjects has not been fully investigated.
the majority of complex human traits are governed by multiple gene interactions  <cit> .
these sophisticated interactions differ among individuals based on environmental factors.
studies on twins are therefore a useful method for estimating the genetic and environmental effects that a given factor has on human health  <cit> .
twin heritability and linkage studies segregate the genetic and environmental effects based on the assumption that monozygotic twins are genetically identical, and so their phenotypic differences are of environmental origin.
additionally, the shared environmental effects can be determined from monozygotic  and dizygotic  twins, as well as parent-offspring pairs  <cit> .
our knowledge of individual differences in the skin microbiota and genetic markers associated with its composition remains limited.
in this study, we analyzed the skin microbiota of  <dig> mz and  <dig> dz twins between  <dig> and 55 years of age and their mothers  to identify the heritable components of the skin microbiome and their association with host genetic factors.
to this end, we focused our analysis on host genes related to key dermatological conditions, including sebum production, skin humidity, pigmentation, epidermal barrier function, and hair follicle development.
using the microbial composition as quantitative traits, we identified one human single nucleotide polymorphisms  strongly associated with the abundance of corynebacterium jeikeium on the skin.
RESULTS
study population and composition of the human skin microbiome
the study population included korean subjects  with eight mz and four dz twin pairs, five singletons, and  <dig> of their mothers .
skin traits including skin humidity and pigmentation were measured in  <dig> subjects.
subjects were categorized as having sufficiently moisturized versus dry skin, and mid- versus light-tone skin color based on threshold values in an arbitrary unit for skin humidity  and pigmentation , respectively.
a total of  <dig>  sequencing reads from the v2-v <dig> regions of the human 16s rrna genes were generated from  <dig> skin swab samples, for an average of  <dig>  reads per sample.
we chose the flexor surface of the right upper arm to minimize variations due to differences in the use of cosmetics, surface temperature, acidity, humidity, handedness, and other external factors.
the skin microbiota was first assessed at the phylum level; actinobacteria , firmicutes , proteobacteria , and bacteroidetes  were the dominant phyla among the samples collected.
the composition of the skin microbiome in our study was consistent with previous reports  <cit> .
further classification of the skin microbiota at the genus level revealed high inter-individual variation with propionibacterium , staphylococcus , and streptococcus  prevailing on the skin .
at the species level, p. acnes was the most abundant inhabitant, accounting for  <dig>  % of the skin microbiota.
occupancy by the remaining species accounted for less than 1 % each.table.
<dig> summary of the study population
humidity , aubc
pigmentation , aubd
athree mz and two dz twins were analyzed as singletons, since one of their associated twins was excluded due to antibiotic use
bdermatologic phenotypes were measured from  <dig> mothers,  <dig> mz twins, and  <dig> dz twins
cthe level of skin humidity is expressed using arbitrary units  as given by the device .
corneometry values greater than 45 au indicate sufficiently moisturized skin, while values less than 45 au indicate dry skin
da melanin index of 0–150 au indicates light skin tone, and values of 150–250 au indicate mid-tone skin pigmentation
fig.
<dig> diversity of the skin microbiota and functional traits of the microbial communities.
a taxonomic classification of the skin microbiome at the genus level.
relative bacterial abundance for each individual is shown.
a familial relationship is indicated among those individuals represented by the same number.
twin pairs are presented in the parenthesis.
b skin metagenomes predicted using picrust .
relative contribution of each functional pathway is determined for the collective microbiota of all subjects.
error bars, sem
to explore the skin microbe-host interaction further, we used picrust  <cit> , an algorithm that detects the functional capabilities of a community by comparing its metagenome with reference genomes using microbial communities identified from all subjects.
picrust classified  <dig> functional pathways from the 16s rrna sequences of human skin microbiota.
functional traits determined based on 16s rrna genes showed categorical similarity with a recent skin metagenomic study , with a large proportion of the functions associated with carbohydrate, amino acid, vitamin, and nucleotide metabolism  <cit> .
discrepancies in the relative contribution of each pathway between the studies could be due to use of different sampling sites and analytical methods.
the previous metagenomic study reflects the microbial functions from two male subjects at mid-twenties with samples from five different body parts.
additionally, 16s rrna based predictions of the functional traits by picrust could possibly cause the discrepancies.
detailed categories of the functional traits and nearest sequenced taxon index  values are provided in additional file 1: table s <dig> and additional file 1: table s <dig>  respectively.
diversity of the human skin microbiome
microbial diversity “within” and “between” subject groups is denoted by alpha and beta diversity, respectively.
in an assessment of species richness, the rarefaction curves, reflective of alpha diversity, showed significantly higher levels of bacterial diversity at ages greater than 35 years .
the median value was used as the cutoff age at  <dig> to evenly disperse individuals into two groups.
previous studies have shown that age is a primary contributor to increased microbial diversity in the skin.
a study comparing the skin microbiota between children and adolescents revealed microbial shifts with the onset and progression of sexual maturation  <cit> .
the amount of sebaceous wax ester is known to be closely associated with age, increasing between the ages of 15–35 years and decreasing afterwards  <cit> .
an increase in skin lipids is thought to create an acidic environment, reducing the numbers of acid-susceptible bacteria—such as staphylococcal and streptococcal species—on adolescent skin.
disparities in sweat, sebum, and hormone production, as well as lifestyle choices such as the use of cosmetics, may underlie gender differences in skin microbiota  <cit> .
however, gender effects were not present on the inner wrist  when mothers were excluded to avoid confounding by age.
the gender effects on bacterial diversity seem to depend on the skin site; greater diversity of bacteria in females was evident on hands  <cit>  but not at the base of the neck  <cit> .
additionally, we could not observe the significant effect of skin humidity  on the skin.
this is likely due to the relatively low variation in humidity in the skin of the upper arm where the microbiota was sampled.
interestingly, skin pigmentation significantly influenced skin bacteria, increasing the diversity in individuals with an intermediate skin tone .
while there have been reports on the effects of bacterial species on melanogenesis , the exact nature of the relationship between the skin microbiota and pigmentation remains to be determined.
our data revealed only a weak association with skin humidity .
to compare the beta diversity profiles across different status of age, gender, skin humidity, and pigmentation, we performed a principal coordinate analysis  using weighted and unweighted unifrac metrics , wherein the distance between microbial communities was calculated based on phylogenetic information.
the results were not indicative of complete separation of microbiotas based on the host phenotypes  indicating that the groups divided by age, gender, skin humidity, and pigmentation did not include significantly different microbial compositions.fig.
<dig> differences in skin microbial diversity analyzed using rarefaction curves a age.
b gender.
c skin humidity .
d pigmentation .
error bars indicate 95 % confidence intervals.
* significance is based on the wilcoxon rank-sum test
heritability of the skin microbiota
comparison of the skin microbiota between twins and their mothers was performed using weighted and unweighted unifrac distances .
with both metrics, mz twins showed the highest similarity, followed by dz twins and mother-twins.
the dissimilarity of unrelated subject was the highest under the unweighted unifrac metrics whereas it was the second highest next to mother-twins under the weighted unifrac distance.
the similarity of the skin microbiota of mz twins was comparable to that of dz twins, but significantly higher than those in unrelated subjects and their mothers .
our subsequent analysis of the skin microbiota focused on heritability and the additional effects stemming from common environments .
heritability ranged from  <dig> – <dig>  % with the abundance of roseomonas in the skin showed the highest degree of heritability.
although the role is not well-defined, a recent study comparing skin microbes on the face and other body parts found an increased abundance of roseomonas on the scapula and inner elbow  <cit> .
two of the taxonomic branches described in this study were found to possess a heritable component: corynebacteriaceae/ corynebacterium and brevibacteriaceae/ brevibacterium/ brevibacterium aureum.
corynebacterium is a major constituent of the normal skin flora along with staphylococcus, propionium, streptococcus, and pseudomonas  <cit> .
c. jeikeium, the only species belonging to genus corynebacterium described in this study, is commonly found on skin epithelium, and it has been shown to cause nosocomial infections in immunocompromised patients  <cit> .
brevibacterium sp.
is a gram-negative bacterium capable of degrading cyfluthrin, an organic compound with xenobiotic characteristics and toxicity to the reproductive, neural, and respiratory systems in humans  <cit> .
the range of shared-environmental effects on the skin microbiome was 56– <dig>  %, with leuconostocaceae/ weissella/ weissella cibaria  and propionibacteriaceae/ propionibacterium/ propionibacterium acnes  significantly influenced by the common environment from family to species.
w. cibaria is a lactic acid bacterium belonging to the family of leuconostocaceae  <cit> .
lactic acid bacteria require specific nutrients, such as carbohydrates, amino acids, vitamins, purines, and pyrimidines for growth  <cit> .
despite these requirements, the bacteria have been isolated from a variety of environments, including the oral cavity, intestinal tract, and fermented foods  <cit> .
this adaptability likely accounts for the presence of the bacteria in two seemingly incongruous locations.
p. acnes, the most dominant and well-known skin commensal bacterium  <cit> , is heavily reliant on the metabolism of fatty acids found in sebum secretions.
soap, detergents, astringents, and other factors that alter the amount of sebum may account for the environmental effects on p. acnes colonization  <cit> .
individual-specific effects ranged from  <dig> – <dig>  %.fig.
<dig> comparison of the skin microbiota of twins and their families in terms of heritability and environmental effects.
a weighted and b unweighted unifrac distance between twin pairs , twins and mothers , and unrelated individuals .
the error bars represent the standard error.
*,p<  <dig>  based on wilcoxon rank sum test
table.
<dig> heritability and household effects of the skin microbiota after adjustment for age and gender
s__brevibacterium aureum
s__propionibacterium acnes
s__weissella cibaria
each taxonomic level is indicated by f, g, and s for family, genus, and species, respectively
genetic association of skin microbiotas
we next explored associations between the skin microbiota composition and host genetic variation.
for this investigation, we focused on snps in a panel of select host genes known to affect sebum production , pigmentation , skin humidity , skin barrier function , and hair follicle development  .
the selection of genes was performed manually.
one of  <dig> snps was significantly associated with the abundance of a specific bacterial species , where significance was defined using a cut-off level of p <  <dig> /275 =  <dig> .
the identified snp was localized in a gene known to play a role in skin barrier function .
marker rs <dig>  in flg was negatively associated with c. jeikeium, although the abundance difference was small between the host genotypes .
flg defects are known to cause allergic skin diseases, such as atopic eczema and ichthyosis vulgaris  <cit> , both of which are characterized by dry skin.
correspondingly, possession of the minor allele t tended lower skin humidity but it was not statistically proved .
flg, which encodes filaggrin, is a structural protein in the cornified envelop of the stratum corneum critical for skin barrier function  <cit> .
mutations in the serine protease st <dig> in mice, which impairs filaggrin processing, also results in an ichthyotic phenotype  <cit> .
importantly, corynebacterium is overrepresented in the skin microbiota of st14-deficient mice, suggestive of a possible link between bacteria and filaggrin processing and pathogenesis.
the allelic association with bacterial abundance was further confirmed using lefse analysis, an algorithm based on calculation of significantly different phenotypes using the kruskal-willis test followed by the wilcoxon rank-sum test for post hoc analysis   <cit> .
linear discriminant analysis  scores allowed us to estimate the effect size of the differentially abundant features.
lefse analysis showed an additional association between peptoniphilus asaccharolyticus and the minor allele of flg.
although not identified in the snp analysis, a substantial percentage of peptoniphilus abundance could be attributed to heritability, indicating a possible genetic relationship between the bacteria and host.
interactions between the host and the skin microbiota have been analyzed in association with multiple skin diseases .
for example, a recent quantitative trait locus  mapping of mouse skin microbiotas revealed a strong connection between disease susceptibility and the host genotype-dependent microbial composition  <cit> .
this study, performed on a genome-wide scale, detected qtl regions related to innate immune activation.
this and our investigation did not identify overlapping qtl regions, which is conceivable because our snp analysis was based on the specifically selected gene categories with known implications for human skin structure and function.
beyond the identification of cis-regulatory element associated snps, recent snp association studies are expanding to include flanking regions of the target genes and long-range enhancer/promoter .
in this way, it is able to discover the interplay between target snps and their transcriptional regulators and ultimately, practical roles of the snps.
further studies on such long-range snps should allow us deeper insights into the genetic associations on the skin microbiome.table.
<dig> associations between the skin microbiota and snps of targeted human genes after adjustment for age and gender
corynebacterium jeikeium
flg
the direction of the β value in table  <dig> indicates the positive or negative association between the minor allele and the bacteria
aminor allele frequency
bregression coefficient
clinear discriminant analysis effect size assessed using the lefse  software
fig.
<dig> effect of the host genotype on skin traits.
a manhattan plot summarizing the results of an association analysis of  <dig> candidate snps with corynebacterium jeikeium.
each dot represents the candidate snp plotted across the genome.
b relative abundance of c. jeikeium with respect to rs <dig>  the means and standard errors are indicated by solid and dashed bars, respectively.
c level of skin humidity by genotype at rs <dig>  boxes represent the 25th percentile, median, and 75th percentile.
whiskers represent the lowest values and the highest values of skin humidity.
filled circles represent outliers.
au: arbitrary unit.
d lda  plot of skin bacteria found by lefse showing their association with the host genotype at rs <dig>  cladogram on the right indicates the phylogenetic distribution of the skin bacteria.
each color represents host genotype: cc genotype in red and ct in green.
circles are arranged by phylogenetic levels from kingdom, phylum, class, family, genus, and species from inside out
CONCLUSIONS
in this study, we describe host genetic factors and other host-intrinsic characteristics that directly influence the composition of the skin microbiota.
we further demonstrated a strong association between the composition of skin microbiota and human genetic factors related to skin barrier function.
analysis of genetically identical mz twins and half-identical dz twins can be used to identify and discriminate genetic and environmental effects on the microbiome  <cit> .
investigation of the twin pairs proved that the skin microbiome is shaped both by host genetics and their environmental factors.
additionally, analysis of human genetic traits associated with the skin microbiota was performed using a candidate-gene approach.
for this investigation, we chose five representative traits that affect dermatologic conditions; namely, sebum production, pigmentation, skin humidity, skin barrier function, and hair follicle formation.
to confirm the results of the association analysis, the bacterial abundance associated with host alleles was further analyzed using lefse.
one snp, located in a gene related to skin barrier function, was significantly associated with c. jeikeium.
c. jeikeium abundance was lower in subjects containing the minor allele of flg, which encodes filaggrin, a structural protein in the cornified envelop of the stratum corneum critical for skin barrier function.
although we have explored intrinsic characteristics of the human skin microbiome in aspect of host genetics and environmental factors, our study has statistical limitations from a small sample size.
in genetic association studies, a sufficient number of samples are critical to detect causality between genes and phenotypes.
furthermore, the collective size of bacteria identified by microbiome analysis creates more stringent p-values to achieve asking for increased sample size to identify additional links between host genetic factors and the composition of the skin microbiota.
to overcome such limitations, we tried to assess the genetic impacts put on the skin microbiome using different analytical approaches and the results are supportive of our findings.
yet, more expansive genome-wide association studies with increased sample size are warranted to identify additional links between host genetic factors and the composition of the skin microbiota.
our results provide insight into skin traits associated with individual’s microbiome and potential genomic and microbial targets for skin healthcare.

 the skin provides a protective barrier against invading microbial pathogens, while also serving as a habitat for a plethora of commensal bacteria. the composition of skin microbiota varies among individuals, but a core set of microbes can be found in all subjects for each anatomical location. recent advances in high-throughput sequencing technologies have enabled rapid analysis of microbial communities indigenous to specific niches in the human body. there is significant inter-individual variation in the skin microbiota, which is attributable to genetic differences and environmental factors. colonization of the host body by bacteria occurs immediately after birth, with more complex microbial communities developing in distinct anatomical niches afterwards. succession of the microbiota within individual hosts is also driven by host-intrinsic factors, such as age, gender, genotype and health status, as well as environmental and lifestyle factors, such as climate, light exposure, and detergent use. previous studies have quantitatively explored host genetic effects on the gut microbiome composition using animal models and humans. these studies revealed a significant influence of host genetic factors on the microbiota. however, the impact of host gene expression on skin microbial diversity in human subjects has not been fully investigated. the majority of complex human traits are governed by multiple gene interactions. these sophisticated interactions differ among individuals based on environmental factors. studies on twins are therefore a useful method for estimating the genetic and environmental effects that a given factor has on human health. twin heritability and linkage studies segregate the genetic and environmental effects based on the assumption that monozygotic twins are genetically identical, and so their phenotypic differences are of environmental origin. additionally, the shared environmental effects can be determined from monozygotic and dizygotic twins, as well as parent-offspring pairs. our knowledge of individual differences in the skin microbiota and genetic markers associated with its composition remains limited. in this study, we analyzed the skin microbiota of mz and dz twins between and 55 years of age and their mothers to identify the heritable components of the skin microbiome and their association with host genetic factors. to this end, we focused our analysis on host genes related to key dermatological conditions, including sebum production, skin humidity, pigmentation, epidermal barrier function, and hair follicle development. using the microbial composition as quantitative traits, we identified one human single nucleotide polymorphisms strongly associated with the abundance of corynebacterium jeikeium on the skin.  study population and composition of the human skin microbiome the study population included korean subjects with eight mz and four dz twin pairs, five singletons, and of their mothers. skin traits including skin humidity and pigmentation were measured in subjects. subjects were categorized as having sufficiently moisturized versus dry skin, and mid- versus light-tone skin color based on threshold values in an arbitrary unit for skin humidity and pigmentation, respectively. a total of sequencing reads from the v2-v regions of the human 16s rrna genes were generated from skin swab samples, for an average of reads per sample. we chose the flexor surface of the right upper arm to minimize variations due to differences in the use of cosmetics, surface temperature, acidity, humidity, handedness, and other external factors. the skin microbiota was first assessed at the phylum level; actinobacteria, firmicutes, proteobacteria, and bacteroidetes were the dominant phyla among the samples collected. the composition of the skin microbiome in our study was consistent with previous reports. further classification of the skin microbiota at the genus level revealed high inter-individual variation with propionibacterium, staphylococcus, and streptococcus prevailing on the skin. at the species level, p. acnes was the most abundant inhabitant, accounting for  % of the skin microbiota. occupancy by the remaining species accounted for less than 1 % each.table. summary of the study population humidity, aubc pigmentation, aubd athree mz and two dz twins were analyzed as singletons, since one of their associated twins was excluded due to antibiotic use bdermatologic phenotypes were measured from mothers, mz twins, and dz twins cthe level of skin humidity is expressed using arbitrary units as given by the device. corneometry values greater than 45 au indicate sufficiently moisturized skin, while values less than 45 au indicate dry skin da melanin index of 0–150 au indicates light skin tone, and values of 150–250 au indicate mid-tone skin pigmentation fig. diversity of the skin microbiota and functional traits of the microbial communities. a taxonomic classification of the skin microbiome at the genus level. relative bacterial abundance for each individual is shown. a familial relationship is indicated among those individuals represented by the same number. twin pairs are presented in the parenthesis. b skin metagenomes predicted using picrust. relative contribution of each functional pathway is determined for the collective microbiota of all subjects. error bars, sem to explore the skin microbe-host interaction further, we used picrust, an algorithm that detects the functional capabilities of a community by comparing its metagenome with reference genomes using microbial communities identified from all subjects. picrust classified functional pathways from the 16s rrna sequences of human skin microbiota. functional traits determined based on 16s rrna genes showed categorical similarity with a recent skin metagenomic study, with a large proportion of the functions associated with carbohydrate, amino acid, vitamin, and nucleotide metabolism. discrepancies in the relative contribution of each pathway between the studies could be due to use of different sampling sites and analytical methods. the previous metagenomic study reflects the microbial functions from two male subjects at mid-twenties with samples from five different body parts. additionally, 16s rrna based predictions of the functional traits by picrust could possibly cause the discrepancies. detailed categories of the functional traits and nearest sequenced taxon index values are provided in additional file 1: table s and additional file 1: table s respectively. diversity of the human skin microbiome microbial diversity “within” and “between” subject groups is denoted by alpha and beta diversity, respectively. in an assessment of species richness, the rarefaction curves, reflective of alpha diversity, showed significantly higher levels of bacterial diversity at ages greater than 35 years. the median value was used as the cutoff age at to evenly disperse individuals into two groups. previous studies have shown that age is a primary contributor to increased microbial diversity in the skin. a study comparing the skin microbiota between children and adolescents revealed microbial shifts with the onset and progression of sexual maturation. the amount of sebaceous wax ester is known to be closely associated with age, increasing between the ages of 15–35 years and decreasing afterwards. an increase in skin lipids is thought to create an acidic environment, reducing the numbers of acid-susceptible bacteria—such as staphylococcal and streptococcal species—on adolescent skin. disparities in sweat, sebum, and hormone production, as well as lifestyle choices such as the use of cosmetics, may underlie gender differences in skin microbiota. however, gender effects were not present on the inner wrist when mothers were excluded to avoid confounding by age. the gender effects on bacterial diversity seem to depend on the skin site; greater diversity of bacteria in females was evident on hands but not at the base of the neck. additionally, we could not observe the significant effect of skin humidity on the skin. this is likely due to the relatively low variation in humidity in the skin of the upper arm where the microbiota was sampled. interestingly, skin pigmentation significantly influenced skin bacteria, increasing the diversity in individuals with an intermediate skin tone. while there have been reports on the effects of bacterial species on melanogenesis, the exact nature of the relationship between the skin microbiota and pigmentation remains to be determined. our data revealed only a weak association with skin humidity. to compare the beta diversity profiles across different status of age, gender, skin humidity, and pigmentation, we performed a principal coordinate analysis using weighted and unweighted unifrac metrics, wherein the distance between microbial communities was calculated based on phylogenetic information. the results were not indicative of complete separation of microbiotas based on the host phenotypes indicating that the groups divided by age, gender, skin humidity, and pigmentation did not include significantly different microbial compositions.fig. differences in skin microbial diversity analyzed using rarefaction curves a age. b gender. c skin humidity. d pigmentation. error bars indicate 95 % confidence intervals. * significance is based on the wilcoxon rank-sum test heritability of the skin microbiota comparison of the skin microbiota between twins and their mothers was performed using weighted and unweighted unifrac distances. with both metrics, mz twins showed the highest similarity, followed by dz twins and mother-twins. the dissimilarity of unrelated subject was the highest under the unweighted unifrac metrics whereas it was the second highest next to mother-twins under the weighted unifrac distance. the similarity of the skin microbiota of mz twins was comparable to that of dz twins, but significantly higher than those in unrelated subjects and their mothers. our subsequent analysis of the skin microbiota focused on heritability and the additional effects stemming from common environments. heritability ranged from –  % with the abundance of roseomonas in the skin showed the highest degree of heritability. although the role is not well-defined, a recent study comparing skin microbes on the face and other body parts found an increased abundance of roseomonas on the scapula and inner elbow. two of the taxonomic branches described in this study were found to possess a heritable component: corynebacteriaceae/ corynebacterium and brevibacteriaceae/ brevibacterium/ brevibacterium aureum. corynebacterium is a major constituent of the normal skin flora along with staphylococcus, propionium, streptococcus, and pseudomonas. c. jeikeium, the only species belonging to genus corynebacterium described in this study, is commonly found on skin epithelium, and it has been shown to cause nosocomial infections in immunocompromised patients. brevibacterium sp. is a gram-negative bacterium capable of degrading cyfluthrin, an organic compound with xenobiotic characteristics and toxicity to the reproductive, neural, and respiratory systems in humans. the range of shared-environmental effects on the skin microbiome was 56–  %, with leuconostocaceae/ weissella/ weissella cibaria and propionibacteriaceae/ propionibacterium/ propionibacterium acnes significantly influenced by the common environment from family to species. w. cibaria is a lactic acid bacterium belonging to the family of leuconostocaceae. lactic acid bacteria require specific nutrients, such as carbohydrates, amino acids, vitamins, purines, and pyrimidines for growth. despite these requirements, the bacteria have been isolated from a variety of environments, including the oral cavity, intestinal tract, and fermented foods. this adaptability likely accounts for the presence of the bacteria in two seemingly incongruous locations. p. acnes, the most dominant and well-known skin commensal bacterium, is heavily reliant on the metabolism of fatty acids found in sebum secretions. soap, detergents, astringents, and other factors that alter the amount of sebum may account for the environmental effects on p. acnes colonization. individual-specific effects ranged from –  %.fig. comparison of the skin microbiota of twins and their families in terms of heritability and environmental effects. a weighted and b unweighted unifrac distance between twin pairs, twins and mothers, and unrelated individuals. the error bars represent the standard error. *,p<  based on wilcoxon rank sum test table. heritability and household effects of the skin microbiota after adjustment for age and gender s__brevibacterium aureum s__propionibacterium acnes s__weissella cibaria each taxonomic level is indicated by f, g, and s for family, genus, and species, respectively genetic association of skin microbiotas we next explored associations between the skin microbiota composition and host genetic variation. for this investigation, we focused on snps in a panel of select host genes known to affect sebum production, pigmentation, skin humidity, skin barrier function, and hair follicle development. the selection of genes was performed manually. one of snps was significantly associated with the abundance of a specific bacterial species, where significance was defined using a cut-off level of p <  /275 = . the identified snp was localized in a gene known to play a role in skin barrier function. marker rs in flg was negatively associated with c. jeikeium, although the abundance difference was small between the host genotypes. flg defects are known to cause allergic skin diseases, such as atopic eczema and ichthyosis vulgaris, both of which are characterized by dry skin. correspondingly, possession of the minor allele t tended lower skin humidity but it was not statistically proved. flg, which encodes filaggrin, is a structural protein in the cornified envelop of the stratum corneum critical for skin barrier function. mutations in the serine protease st in mice, which impairs filaggrin processing, also results in an ichthyotic phenotype. importantly, corynebacterium is overrepresented in the skin microbiota of st14-deficient mice, suggestive of a possible link between bacteria and filaggrin processing and pathogenesis. the allelic association with bacterial abundance was further confirmed using lefse analysis, an algorithm based on calculation of significantly different phenotypes using the kruskal-willis test followed by the wilcoxon rank-sum test for post hoc analysis. linear discriminant analysis scores allowed us to estimate the effect size of the differentially abundant features. lefse analysis showed an additional association between peptoniphilus asaccharolyticus and the minor allele of flg. although not identified in the snp analysis, a substantial percentage of peptoniphilus abundance could be attributed to heritability, indicating a possible genetic relationship between the bacteria and host. interactions between the host and the skin microbiota have been analyzed in association with multiple skin diseases. for example, a recent quantitative trait locus mapping of mouse skin microbiotas revealed a strong connection between disease susceptibility and the host genotype-dependent microbial composition. this study, performed on a genome-wide scale, detected qtl regions related to innate immune activation. this and our investigation did not identify overlapping qtl regions, which is conceivable because our snp analysis was based on the specifically selected gene categories with known implications for human skin structure and function. beyond the identification of cis-regulatory element associated snps, recent snp association studies are expanding to include flanking regions of the target genes and long-range enhancer/promoter. in this way, it is able to discover the interplay between target snps and their transcriptional regulators and ultimately, practical roles of the snps. further studies on such long-range snps should allow us deeper insights into the genetic associations on the skin microbiome.table. associations between the skin microbiota and snps of targeted human genes after adjustment for age and gender corynebacterium jeikeium flg the direction of the β value in table  indicates the positive or negative association between the minor allele and the bacteria aminor allele frequency bregression coefficient clinear discriminant analysis effect size assessed using the lefse software fig. effect of the host genotype on skin traits. a manhattan plot summarizing the results of an association analysis of candidate snps with corynebacterium jeikeium. each dot represents the candidate snp plotted across the genome. b relative abundance of c. jeikeium with respect to rs the means and standard errors are indicated by solid and dashed bars, respectively. c level of skin humidity by genotype at rs boxes represent the 25th percentile, median, and 75th percentile. whiskers represent the lowest values and the highest values of skin humidity. filled circles represent outliers. au: arbitrary unit. d lda plot of skin bacteria found by lefse showing their association with the host genotype at rs cladogram on the right indicates the phylogenetic distribution of the skin bacteria. each color represents host genotype: cc genotype in red and ct in green. circles are arranged by phylogenetic levels from kingdom, phylum, class, family, genus, and species from inside out  in this study, we describe host genetic factors and other host-intrinsic characteristics that directly influence the composition of the skin microbiota. we further demonstrated a strong association between the composition of skin microbiota and human genetic factors related to skin barrier function. analysis of genetically identical mz twins and half-identical dz twins can be used to identify and discriminate genetic and environmental effects on the microbiome. investigation of the twin pairs proved that the skin microbiome is shaped both by host genetics and their environmental factors. additionally, analysis of human genetic traits associated with the skin microbiota was performed using a candidate-gene approach. for this investigation, we chose five representative traits that affect dermatologic conditions; namely, sebum production, pigmentation, skin humidity, skin barrier function, and hair follicle formation. to confirm the results of the association analysis, the bacterial abundance associated with host alleles was further analyzed using lefse. one snp, located in a gene related to skin barrier function, was significantly associated with c. jeikeium. c. jeikeium abundance was lower in subjects containing the minor allele of flg, which encodes filaggrin, a structural protein in the cornified envelop of the stratum corneum critical for skin barrier function. although we have explored intrinsic characteristics of the human skin microbiome in aspect of host genetics and environmental factors, our study has statistical limitations from a small sample size. in genetic association studies, a sufficient number of samples are critical to detect causality between genes and phenotypes. furthermore, the collective size of bacteria identified by microbiome analysis creates more stringent p-values to achieve asking for increased sample size to identify additional links between host genetic factors and the composition of the skin microbiota. to overcome such limitations, we tried to assess the genetic impacts put on the skin microbiome using different analytical approaches and the results are supportive of our findings. yet, more expansive genome-wide association studies with increased sample size are warranted to identify additional links between host genetic factors and the composition of the skin microbiota. our results provide insight into skin traits associated with individual’s microbiome and potential genomic and microbial targets for skin healthcare. 
based on our analysis of the microbiota from individuals including monozygotic and dizygotic twins aged 26– years and their mothers, we found that skin microbial diversity was significantly influenced by age and skin pigmentation. furthermore, we observed a strong association between the abundance of corynebacterium jeikeium and single nucleotide polymorphisms in the host flg gene related to epidermal barrier function. here, we investigate the heritable components of the skin microbiome and their association with host genetic factors. this study reveals an intimate association of the human skin microbiome and host genes, and increases our understanding of the role of human genetic factors in establishing a microbial ecosystem on the body surface. both environmental and host genetic factors influence microbial communities in distinct anatomical niches, but little is known about their interplay in shaping the skin microbiome. heritability analysis revealed genetic and shared environmental impacts on the skin microbiome.
 the skin is the outermost layer of the human body and one of the key sites for host-microbe interactions. both environmental and host genetic factors influence microbial communities in distinct anatomical niches, but little is known about their interplay in shaping the skin microbiome. here, we investigate the heritable components of the skin microbiome and their association with host genetic factors.  based on our analysis of the microbiota from individuals including monozygotic and dizygotic twins aged 26– years and their mothers, we found that skin microbial diversity was significantly influenced by age and skin pigmentation. heritability analysis revealed genetic and shared environmental impacts on the skin microbiome. furthermore, we observed a strong association between the abundance of corynebacterium jeikeium and single nucleotide polymorphisms in the host flg gene related to epidermal barrier function.  this study reveals an intimate association of the human skin microbiome and host genes, and increases our understanding of the role of human genetic factors in establishing a microbial ecosystem on the body surface. electronic supplementary material the online version of this article contains supplementary material, which is available to authorized users. keywords skin microbiotaheritabilitytwin studyhost geneticscommon environment effectissue-copyright-statement© the author 2015 