Dataset Information

Adaptation of human skin color in various populations.

ABSTRACT: Skin color is a well-recognized adaptive trait and has been studied extensively in humans. Understanding the genetic basis of adaptation of skin color in various populations has many implications in human evolution and medicine.Impressive progress has been made recently to identify genes associated with skin color variation in a wide range of geographical and temporal populations. In this review, we discuss what is currently known about the genetics of skin color variation. We enumerated several cases of skin color adaptation in global modern humans and archaic hominins, and illustrated why, when, and how skin color adaptation occurred in different populations. Finally, we provided a summary of the candidate loci associated with pigmentation, which could be a valuable reference for further evolutionary and medical studies.Previous studies generally indicated a complex genetic mechanism underlying the skin color variation, expanding our understanding of the role of population demographic history and natural selection in shaping genetic and phenotypic diversity in humans. Future work is needed to dissect the genetic architecture of skin color adaptation in numerous ethnic minority groups around the world, which remains relatively obscure compared with that of major continental groups, and to unravel the exact genetic basis of skin color adaptation.

SUBMITTER: Deng L

PROVIDER: S-EPMC5502412 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Adaptation of human skin color in various populations.

Deng Lian L Xu Shuhua S

Hereditas 20170615

<h4>Background</h4>Skin color is a well-recognized adaptive trait and has been studied extensively in humans. Understanding the genetic basis of adaptation of skin color in various populations has many implications in human evolution and medicine.<h4>Discussion</h4>Impressive progress has been made recently to identify genes associated with skin color variation in a wide range of geographical and temporal populations. In this review, we discuss what is currently known about the genetics of skin ...[more]

PMID: 28701907

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Project description:BackgroundWhile skin cancers are less prevalent in people with skin of color, they are more often diagnosed at later stages and have a poorer prognosis. The use of artificial intelligence (AI) models can potentially improve early detection of skin cancers; however, the lack of skin color diversity in training datasets may only widen the pre-existing racial discrepancies in dermatology.ObjectiveThe aim of this study was to systematically review the technique, quality, accuracy, and implications of studies using AI models trained or tested in populations with skin of color for classification of pigmented skin lesions.MethodsPubMed was used to identify any studies describing AI models for classification of pigmented skin lesions. Only studies that used training datasets with at least 10% of images from people with skin of color were eligible. Outcomes on study population, design of AI model, accuracy, and quality of the studies were reviewed.ResultsTwenty-two eligible articles were identified. The majority of studies were trained on datasets obtained from Chinese (7/22), Korean (5/22), and Japanese populations (3/22). Seven studies used diverse datasets containing Fitzpatrick skin type I-III in combination with at least 10% from black Americans, Native Americans, Pacific Islanders, or Fitzpatrick IV-VI. AI models producing binary outcomes (e.g., benign vs. malignant) reported an accuracy ranging from 70% to 99.7%. Accuracy of AI models reporting multiclass outcomes (e.g., specific lesion diagnosis) was lower, ranging from 43% to 93%. Reader studies, where dermatologists' classification is compared with AI model outcomes, reported similar accuracy in one study, higher AI accuracy in three studies, and higher clinician accuracy in two studies. A quality review revealed that dataset description and variety, benchmarking, public evaluation, and healthcare application were frequently not addressed.ConclusionsWhile this review provides promising evidence of accurate AI models in populations with skin of color, the majority of the studies reviewed were obtained from East Asian populations and therefore provide insufficient evidence to comment on the overall accuracy of AI models for darker skin types. Large discrepancies remain in the number of AI models developed in populations with skin of color (particularly Fitzpatrick type IV-VI) compared with those of largely European ancestry. A lack of publicly available datasets from diverse populations is likely a contributing factor, as is the inadequate reporting of patient-level metadata relating to skin color in training datasets.

Project description:Nutritional and medicinal benefits have been attributed to the consumption of tissues from the black-boned chickens in oriental countries. Lueyang black-boned chicken is one of the native chicken breeds. However, some birds may instead have white or lighter skin, which directly causes economic losses every year. Previous studies of pigmentation have focused on a number of genes that may play important roles in coat color regulation. Illumina2000 sequencing technology was used to catalog the global gene expression profiles in the skin of the Lueyang chicken with white versus black skin. A total of 18,608 unigenes were assembled from the reads obtained from the skin of the white and black chickens. A total of 649 known genes were differentially expressed in the black versus white chickens, with 314 genes that were up regulated and 335 genes that were down-regulated, and a total of 162 novel genes were differentially expressed in the black versus white chickens, consisting of 73 genes that were up-regulated (including 4 highly expressed genes that were expressed exclusively in the skin of the black chickens) and 89 genes that were down-regulated. There were also a total of 8 known coat-color genes expressed in previous studies (ASIP, TYR, KIT, TYRP1, OCA2, KITLG, MITF and MC1R). In this study, 4 of which showed greater expression in the black chickens, and several were up-regulated, such as KIT, ASIP, TYR and OCA2. To our surprise, KITLG, MITF and MC1R showed no significant difference in expression between the black- and white-skinned chickens, and the expression of TYRP1 was not detected in either skin color. The expression of ASIP, TYR, KIT, TYRP1, OCA2, KITLG, MITF and MC1R was validated by real-time quantitative polymerase chain reaction (qPCR), and the results of the qPCR were consistent with the RNA-seq. This study provides several candidate genes that may be associated with the development of black versus white skin. More importantly, the fact that the MC1R gene showed no significant difference in expression between the black and white chickens is of particular interest for future studies that aim to elucidate its functional role in the regulation of skin color.

Dataset Information

Adaptation of human skin color in various populations.

Publications

Adaptation of human skin color in various populations.

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