Relative studies between hair index, hair area, and medullary index with age and sex in Thai scalp hair

Srettabunjong, Supawon; Patompakdeesakul, Panida; Limawongpranee, Suvit

doi:10.1016/j.forsciint.2016.08.030

Cited by 9 publications

(4 citation statements)

References 33 publications

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“…All individuals gave informed consent prior to sample donation. They were asked to fill in the questionnaire that included the basic information, such as gender, age and ethnic origin, as well as particular phenotypic features (individuals aged > 30 years were asked about the phenotypic features at their mid-20s) (Srettabunjong et al 2016 ), such as the iris and hair color, skin color and tone, susceptibility to sunburns and the presence of freckles (described as solar lentigines and ephelides). These traits were graded into the following categories: for iris color: brown/blue (or gray)/intermediate (including green), for hair color: black/brown/red/blonde, for skin color: dark (olive)/medium/light (pale), for tanning/skin sensitivity to sun: high susceptibility to sunburns/initial sunburns (but turning brown)/moderate tanning (without sunburns)/quick tanning, for freckling: severe freckling/moderate freckling/non-freckled skin.…”

Section: Methodsmentioning

confidence: 99%

“…But, still, little is known about the other EVC traits. Skin color is considered as an adaptive trait and melanin synthesis is a complex process, since multiple genes as well as other factors, such as age, diseases, drugs and environmental factors can contribute to the final outcome (Spichenok et al 2011 ; Srettabunjong et al 2016 ). Several candidate gene loci have been identified to be presumably associated with skin pigmentation traits in people of European ancestry as well as to differ among geographical populations.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches

2019

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Predicting phenotypes from DNA has recently become extensively studied field in forensic research and is referred to as Forensic DNA Phenotyping. Systems based on single nucleotide polymorphisms for accurate prediction of iris, hair and skin color in global population, independent of bio-geographical ancestry, have recently been introduced. Here, we analyzed 14 SNPs for distinct skin pigmentation traits in a homogeneous cohort of 222 Polish subjects. We compared three different algorithms: General Linear Model based on logistic regression, Random Forest and Neural Network in 18 developed prediction models. We demonstrate Random Forest to be the most accurate algorithm for 3- and 4-category estimations (total of 58.3% correct calls for skin color prediction, 47.2% for tanning prediction, 50% for freckling prediction). Binomial Logistic Regression was the best approach in 2-category estimations (total of 69.4% correct calls, AUC = 0.673 for tanning prediction; total of 52.8% correct calls, AUC = 0.537 for freckling prediction). Our study confirms the association of rs12913832 ( HERC2 ) with all three skin pigmentation traits, but also variants associated solely with certain pigmentation traits, namely rs6058017 and rs4911414 ( ASIP ) with skin sensitivity to sun and tanning abilities, rs12203592 ( IRF4 ) with freckling and rs4778241 and rs4778138 ( OCA2 ) with skin color and tanning. Finally, we assessed significant differences in allele frequencies in comparison with CEU data and our study provides a starting point for the development of prediction models for homogeneous populations with less internal differentiation than in the global predictive testing. Electronic supplementary material The online version of this article (10.1007/s00439-019-02012-w) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches

2019

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“…Human hair growth is asynchronous, and hair forms vary by somatic area. Additionally, the ratio of cortex to medulla is different between human and nonhuman mammalian hairs (Kshirsagar et al, 2009;Srettabunjong, Patompakdeesakul, & Limawongpranee, 2016). The extent of diversity in human hair morphology and microstructure and the drivers of this diversity have much still to be explicated.…”

Section: Mouse Modelsmentioning

confidence: 99%

The biology of human hair: A multidisciplinary review

Koch

Tridico²,

Bernard

et al. 2019

American J Hum Biol

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In the last century, human scalp hair morphology has been studied from multiple, and sometimes mutually exclusive, perspectives by anthropologists, biologists, geneticists, forensic scientists, and cosmetic scientists. Here, we review and synthesize historical and current research on hair to better understand the scientific basis and biological implications of hair microstructure and morphology. We revisit the origins of existing nomenclature regarding hair morphology and classifications, discuss the currently recognized limitations to hair analysis within the varied scientific disciplines studying hair, point out aspects of hair biology that remain unknown, and the great potential for integrating these diverse perspectives and expertise in future scientific investigations, while highlighting the benefits of combining nondestructive microscopical analysis with chemical and genomic analyses for explicating hair biology. Further, we propose consensus terminology for root growth stages through descriptions and images that will aid in the morphological and microscopical analysis of human scalp hair, thereby reducing confusion and the promulgation of inaccurate information that is presently in the literature.

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“…Also, more research is going into the physical properties of hair and variation between individuals. Srettabunjong et al looked into hair variation in Thailand, specifically at hair cross-sectional shape, thickness of hair, and medullary index, while Ho et al studied variation in twins. , The twin study took place in Australia and investigated the heritability of traits like hair diameter and curvature. Tang et al investigated how the age of the donor affects hair hardness, elastic modulus, and diameter .…”

Section: Hairmentioning

confidence: 99%

Toward Locard’s Exchange Principle: Recent Developments in Forensic Trace Evidence Analysis

et al. 2018

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Relative studies between hair index, hair area, and medullary index with age and sex in Thai scalp hair

Cited by 9 publications

References 33 publications

Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches

Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches

The biology of human hair: A multidisciplinary review

Toward Locard’s Exchange Principle: Recent Developments in Forensic Trace Evidence Analysis

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