Mapping and annotating genomic loci to prioritize genes and implicate distinct polygenic adaptations for skin color.

Evidence for adaptation of human skin color to regional ultraviolet radiation suggests shared and distinct genetic variants across populations. However, skin color evolution and genetics in East Asians are understudied. We quantified skin color in 48,433 East Asians using image analysis and identified associated genetic variants and potential causal genes for skin color as well as their polygenic interplay with sun exposure. This genome-wide association study (GWAS) identified 12 known and 11 previously unreported loci and SNP-based heritability was 23-24%. Potential causal genes were determined through the identification of nonsynonymous variants, colocalization with gene expression in skin tissues, and expression levels in melanocytes. Genomic loci associated with pigmentation in East Asians substantially diverged from European populations, and we detected signatures of polygenic adaptation. This large GWAS for objectively quantified skin color in an East Asian population improves understanding of the genetic architecture and polygenic adaptation of skin color and prioritizes potential causal genes.

Skin aging-related microbial types separated by Cutibacterium and α-diversity.

BACKGROUND: Studies on the skin microbiome have been conducted to uncover the relationship between skin microbes and the host. However, most of these studies have primarily focused on analyzing individual microbial compositions, which has resulted in a limited understanding of the overall relationship. METHODS: We analyzed the facial skin characteristics and microbial profiles of 100 healthy Korean female volunteers using the V1-V2 region of the 16S ribosomal RNA gene. RESULTS: The two most prominent features of the facial skin microbiome, the proportion of Cutibacterium and α-diversity, were associated with most of the skin characteristics. Based on clustering results, we proposed four types of facial skin microbiome: type C for Cutibacterium, type B for balanced, type CB for those between types C and B, and type O for others. Type C, which has a high proportion of Cutibacterium, showed high levels of pigmentation, wrinkles, pores, and sagging pores, indicating a tendency for severe skin aging. Type B, which has no dominant species and high microbial diversity, had lower values for pigmentation and wrinkles indicating less severe skin aging. Type CB was an intermediate type between type C and type B in terms of microbial composition and the level of skin aging. Type O dominated by microorganisms other than Cutibacterium, had high levels of sebum and pores but low levels of wrinkles. CONCLUSION: We proposed a criterion for classifying facial skin microbial types, each of which showed distinct facial skin aging features. Our simplified microbial types will contribute to a better understanding of facial skin microbial studies.

Longitudinal study of the interplay between the skin barrier and facial microbiome over 1 year.

Skin is a diverse ecosystem that provides a habitat for microorganisms. The skin condition and the skin microbiome interact each other under diverse environmental conditions. This study was conducted on 10 study participants for a one-year, from September 2020 to August 2021, to investigate the variability of skin microbiome and skin biophysical parameters [TEWL, hydration, and elasticity (R5)] according to season, and to understand the interplay between skin microbiome and skin characteristics. We identified that Cutibacterium, Corynebacterium, Staphyloccocus, unclassified genus within Neisseriaceae, and Streptococcus were major skin microbial taxa at the genus level, and fluctuated with the seasons. Cutibacterium was more abundant in winter, while Corynebacterium, Staphylococcus, and Streptococcus were more abundant in summer. Notably, Cutibacterium and skin barrier parameter, TEWL, exhibited a co-decreasing pattern from winter to summer and showed a significant association between Cutibacterium and TEWL. Furthermore, functional profiling using KEGG provided clues on the impact of Cutibacterium on the host skin barrier. This study enhances our understanding of the skin microbiome and its interplay with skin characteristics and highlights the importance of seasonal dynamics in shaping skin microbial composition.

Two newly developed indices evaluating facial skin aging.

BACKGROUND: Skin assessment methodologies have focused mainly on intuitive aging characteristics, including facial wrinkles and pigmented spots, and usually adopt pattern recognition algorithms. Recently, distinct methods of interpreting skin aging, such as the detection of facial landmarks and age prediction using machine learning techniques, have been conducted. MATERIALS AND METHODS: We defined two indices that represent the severity of facial aging. The first index was the ratio of the bizygomatic distance and bigonial distance. The second index was the ratio of the degrees of the near mandible. The indices extracted from two-dimensional frontal face images were intended to show the deformation of the facial skin downward with aging progress. To validate whether these proposed indicators can represent facial aging, we conducted correlation tests with age and facial skin characteristics and performed association tests between the indices and facial skin characteristics, adjusted for age. RESULTS: The indices showed strong correlations with age (r = 0.557 and 0.464, respectively) and facial skin characteristics. Although there were correlations between the indices and facial skin features, the associations between the indices and facial skin characteristics adjusted for age were weak or not significant. This suggests that the newly developed indices are appropriate for evaluating facial skin aging and distinct from typical measurements. CONCLUSION: We suggest two novel indices for evaluating facial aging based on frontal face images. The indices exhibited strong correlations with age and representative facial skin characteristics. The newly developed values can be differentiated indicators of facial aging compared with general skin features.

Allele-Specific Quantification of HLA-DRB1 Transcripts Reveals Imbalanced Allelic Expression That Modifies the Amino Acid Effects in HLA-DRß1.

OBJECTIVE: HLA association fine-mapping studies have shown the effects of missense variants in HLA-DRB1 on rheumatoid arthritis (RA) susceptibility, prognosis, and autoantibody production. However, the phenotypic effects of expression changes in HLA-DRB1 remain poorly understood. Therefore, we investigated the allele-specific expression of HLA-DRB1 and its effect on an HLA-DRß1 structure-associated trait in RA. METHODS: We quantified the allele-specific expression of each HLA-DRB1 3-field classic allele in 48 Korean RA patients with anti-citrullinated protein antibodies (ACPAs) and 319 healthy European subjects by using both RNA sequencing and HLA-DRB1 genotype data to calculate the relative expression strength of multiple HLA-DRB1 alleles (n = 14 in Koreans and n = 25 in Europeans) in each population. The known association between ACPA level and alanine at position 74 of HLA-DRß1 in ACPA-positive RA was revisited to understand the phenotypic effect of allele-specific expression of HLA-DRB1 by modeling multivariate logistic regression with the genomic dosage or relative expression dosage of Ala-74 in 2 independent sets of 1,723 Korean RA patients with ACPA. RESULTS: The relative expression strength was highly allele-specific, causing imbalanced allelic expression in HLA-DRB1 heterozygotes. The association between HLA-DRß1 Ala-74 and ACPA level in RA was better explained by relative expression dosage of Ala-74 than by the genomic dosage (change in Akaike's information criterion = -6.98). Moreover, the expression variance of Ala-74 in Ala-74 heterozygotes with no genomic variance of Ala-74 was significantly associated with ACPA level (P = 2.26 × 10-3 ). CONCLUSION: Our findings illustrate the advantage of integrating quantitative and qualitative changes in HLA-DRB1 into a single model for understanding HLA-DRB1 associations.

Host Genetic and Gut Microbial Signatures in Familial Inflammatory Bowel Disease.

INTRODUCTION: The family history of inflammatory bowel disease (IBD) has been strongly associated with risk of developing IBD. This study aimed to identify the host genetic and gut microbial signatures in familial IBD. METHODS: Genetic analyses using genome-wide single nucleotide polymorphism genotyping and whole exome sequencing were performed to calculate weighted genetic risk scores from known IBD-associated common variants and to identify rare deleterious protein-altering variants specific to patients with familial IBD in 8 Korean families that each included more than 2 affected first-degree relatives (FDRs) and their unaffected FDR(s). In parallel, gut microbial community was analyzed by 16S rRNA sequencing of stools from the sample individuals. RESULTS: The risk of familial IBD was not well explained by the genetic burden from common IBD-risk variants, suggesting the presence of family-shared genetic and environmental disease-risk factors. We identified 17 genes (AC113554.1, ACE, AKAP17A, AKAP9, ANK2, ASB16, ASIC3, DNPH1, DUS3L, FAM200A, FZD10, LAMA5, NUTM2F, PKN1, PRR26, WDR66, and ZC3H4) that each contained rare, potentially deleterious variants transmitted to the affected FDRs in multiple families. In addition, metagenomic analyses revealed significantly different diversity of gut microbiota and identified a number of differentially abundant taxa in affected FDRs, highlighting 22 novel familial disease-associated taxa with large abundance changes and the previously reported gut dysbiosis including low alpha diversity in IBD and 16 known IBD-specific taxa. DISCUSSION: This study identified familial IBD-associated rare deleterious variants and gut microbial dysbiosis in familial IBD.

Deletion at 2q14.3 is associated with worse response to TNF-α blockers in patients with rheumatoid arthritis.

BACKGROUND: Structural variations such as copy number variations (CNVs) have a functional impact on various human traits. This study profiled genome-wide CNVs in Korean patients with rheumatoid arthritis (RA) to investigate the efficacy of treatment with TNF-α blockers. METHODS: A total of 357 Korean patients with RA were examined for the efficacy of TNF-α blocker treatment. Disease activity indexes were measured at baseline and 6 months after the treatment. The patients were classified as responders and non-responders based on the change in disease activity indexes according to the EULAR response criteria. CNVs in the same patients were profiled using fluorescence signal intensity data generated by a genome-wide SNP array. The association of CNVs with response to TNF-α blockers was analyzed by multivariate logistic regression accounting for genetic background and clinical factors including body mass index, gender, baseline disease activity, TNF-α blocker used, and methotrexate treatment. RESULTS: The study subjects varied in their responses to TNF-α blockers and had 286 common CNVs in autosomes. We identified that the 3.8-kb deletion at 2q14.3 in 5% of the subjects was associated with response to TNF-α blockers (1.37 × 10- 5 ≤ P ≤ 4.07 × 10- 4) at a false discovery rate threshold of 5%. The deletion in the identified CNV was significantly more frequent in the non-responders than in the responders, indicating worse response to TNF-α blockers in the deletion carriers. The 3.8-kb deletion at 2q14.3 is located in an intergenic region with the binding sites of two transcription factors, MAFF and MAFK. CONCLUSIONS: This study obtained the CNV landscape of Korean patients with RA and identified the common regional deletion associated with poor response to treatment with TNF-α blockers.