The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform
Inés Joekes - One of the best experts on this subject based on the ideXlab platform.
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Hair Color changes and protein damage caused by ultraviolet radiation
Journal of Photochemistry and Photobiology B-biology, 2004Co-Authors: Ana Carolina Santos Nogueira, Inés JoekesAbstract:Abstract Ultraviolet and visible radiations are known to damage Hair. However, quantitative data relating damage to Hair type, proteins and Color to the radiation wavelength are missing. We studied the effect of UV plus visible, UVA plus visible, visible mercury-vapor lamp radiation and sunlight on (blended) virgin dark-brown, blond and red Hair and (one head) virgin black and curly dark-brown Hair. All Hair types showed a substantial increase in protein loss in water after lamp and sun irradiation. The damaging effect of UVB was about 2–5 times higher than that of UVA plus visible radiation, depending on the Hair type. Significant Color changes were also observed in every Hair type, after lamp and sun irradiation, being more pronounced for the light Colored Hairs. The luminosity difference parameter was the major contributor to the Hair Color changes, but significant changes in the red–green and yellow–blue parameters of every Hair were observed. In this case, the damaging effect is ascribable mainly to UVA radiation. No significant changes in the mechanical properties or topography were observed in any case. We discuss these results in terms of Hair type and composition and melanin types.
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Hair Color changes and protein damage caused by ultraviolet radiation
Journal of Photochemistry and Photobiology B: Biology, 2004Co-Authors: Ana Carolina Santos Nogueira, Inés JoekesAbstract:Ultraviolet and visible radiations are known to damage Hair. However, quantitative data relating damage to Hair type, proteins and Color to the radiation wavelength are missing. We studied the effect of UV plus visible, UVA plus visible, visible mercury-vapor lamp radiation and sunlight on (blended) virgin dark-brown, blond and red Hair and (one head) virgin black and curly dark-brown Hair. All Hair types showed a substantial increase in protein loss in water after lamp and sun irradiation. The damaging effect of UVB was about 2-5 times higher than that of UVA plus visible radiation, depending on the Hair type. Significant Color changes were also observed in every Hair type, after lamp and sun irradiation, being more pronounced for the light Colored Hairs. The luminosity difference parameter was the major contributor to the Hair Color changes, but significant changes in the red-green and yellow-blue parameters of every Hair were observed. In this case, the damaging effect is ascribable mainly to UVA radiation. No significant changes in the mechanical properties or topography were observed in any case. We discuss these results in terms of Hair type and composition and melanin types. © 2004 Elsevier B.V. All rights reserved.
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human Hair Color changes caused by daily care damages on ultra structure
Web Science, 2003Co-Authors: Carla Scanavez, Marina Silveira, Inés JoekesAbstract:Abstract The relation between Hair ultra-structure damages and Color changes was studied. Virgin dark-brown Hair was hand-washed, using lauryl sodium sulfate solution in 40 °C water, rinsed, wet-combed, heat-dried and dry-combed for up to 120 times. Ultra-structure changes were studied by electron microscopy. The treatments damage the cuticle and the cortex. The extraction of soluble material renders cavities, or holes, in the endocuticle. The cavities are 50–200 nm in diameter. There are two kinds of cavities: some filled with lower density material than the remaining endocuticle and some filled with air or water vapor. Displacement, cracking and cleavage of cuticle cells are also observed. Cuticle removal was found to proceed in two ways: via cleavage through the cell membrane complex, and via endocuticle rupture, taking place preferentially in the cavities’ surroundings. In the cortex, cavities develop in the intermacrofibrilar cement, in the cell membrane complex and around the melanin granules. These ultra-structural damages give rise to significant changes on Hair Color, as shown by diffuse reflectance spectrophotometry. The Hair lightness was found to increase after soft washing treatments (5–20 washes), or after keeping it in 40 °C water. Deeper Hair degradation turns the Hair lightness undistinguishable from the initial value, but changes the Color mainly by a yellowing of the Hair. A simple model based on light reflection was developed to explain Hair reflectance behavior before and after damage; results show a reasonable agreement with the experimental data.
Jan Nico Bouwes Bavinck - One of the best experts on this subject based on the ideXlab platform.
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melanocortin 1 receptor mc1r gene variants are associated with an increased risk for cutaneous melanoma which is largely independent of skin type and Hair Color
Journal of Investigative Dermatology, 2001Co-Authors: C. Kennedy, Jeanet A C Ter Huurne, Marjo J P Berkhout, Nelleke A Gruis, Maarten T Bastiaens, Wilma Bergman, Roel Willemze, Jan Nico Bouwes BavinckAbstract:Individuals carrying melanocortin 1 receptor gene variants have an increased risk for the development of cutaneous melanoma. Melanocortin 1 receptor gene variants are also associated with other risk factors for melanoma such as fair skin and red Hair. We evaluated the relationship of melanocortin 1 receptor gene variants, fair skin, red Hair and the development of melanoma in 123 patients with cutaneous melanoma and 385 control subjects. To analyze the association between melanocortin 1 receptor gene variants and skin type or Hair Color we also made use of 453 patients with nonmelanoma skin cancer. We analyzed the coding sequence of the melanocortin 1 receptor gene region by single-stranded conformation polymorphism analysis, followed by DNA sequence analysis. Risk of melanoma dependent on the various melanocortin 1 receptor variant alleles was estimated by exposure odds ratios. The analyses of all different melanocortin 1 receptor gene variants combined, showed that the presence of melanocortin 1 receptor gene variants amounted to a higher melanoma risk, which, in stratified analyses, was independent of skin type and Hair Color. The odds ratios after adjusting for skin type were 3.6 (95% CI 1.7–7.2) for two variants and 2.7 (95% CI 1.5–5.1) for one variant, respectively. Compound heterozygotes and homozygotes for the Val60Leu, Val92Met, Arg142His, Arg151Cys, Arg160Trp, Arg163Gln, and His260Pro variants had odds ratios of about 4 to develop melanoma, whereas heterozygotes for these variants had half the risk. The presence of the melanocortin 1 receptor gene variant Asp84Glu appeared to impose the highest risk for cutaneous melanoma with odds ratios of 16.1 (95% CI 2.3–139.0) and 8.1 (95% CI 1.2–55.9) in compound heterozygotes and heterozygotes, respectively. The broad confidence intervals, when the different variants were analyzed separately, however, do not allow drawing definite conclusions about the magnitude of these risks. Of the more frequently occurring melanocortin 1 receptor variant alleles the Asp84Glu, Arg142His, Arg151Cys, Arg160Trp, His260Pro, and Asp294His variants were strongly associated with both fair skin and red Hair. The Val60Leu, Val92Met, and Arg163Gln variant alleles, however, were only weakly or not associated with fair skin type and/or red Hair, which further illustrates the finding that skin type, Hair Color, and melanoma are independent outcomes of the presence of melanocortin 1 receptor gene variants. We conclude that numerous melanocortin 1 receptor variants predispose to cutaneous melanoma and that possibly the Asp84Glu variant confers the highest risk. This predisposition is largely independent of skin type and Hair Color.
Abrar A Qureshi - One of the best experts on this subject based on the ideXlab platform.
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natural Hair Color and questionnaire reported pain among women in the united states
Pigment Cell & Melanoma Research, 2016Co-Authors: Wenqing Li, Abrar A Qureshi, Shelley S TworogerAbstract:Dear editor, Small-scale clinical studies have reported that individuals with naturally red Hair have increased resistance to inhaled and subcutaneous local anesthetics and need more anesthetic to alleviate pain (Liem et al., 2005; Liem et al., 2004). Previous studies have also reported that red-Haired individuals are more sensitive to thermal pain and dental pain (Binkley et al., 2009; Liem et al., 2005) and that individuals carrying MC1R variants associated with a red-Hair phenotype have increased requirements for anesthetics (Liem et al., 2004) or increased fear of pain (Binkley et al., 2009). However, other studies based on an experimental setting using quantitative controlled measurements of graded pain stimuli reported entirely different findings. For example, Mogil et al showed greater tolerance of pain and an increased analgesic response among red-Haired individuals with MC1R variants (Mogil et al., 2005; Mogil et al., 2003). Here we sought to revisit the problem with a different approach, the collection of information on self-reported pain from the Medical Outcomes Study Short-Form 36 Health Status Survey (SF-36) in the Nurses' Health Study (NHS) and NHS II. We recognize that self-reported assessments of pain and pain tolerance are subjective and cannot match experimental assessments of pain thresholds. Nevertheless, we believe that because nurses have high levels of education and are familiar with medical issues, the collected information is of high-quality and valid. An added advantage of using data in NHS and NHS II is that the information was collected prospectively and that it is based on a large number of participants, namely a total of 149,664 participants from the NHS (n=67,349) and NHS II (n=82,315). It has to be noted, however, that these cohorts only involved women, in fact mostly Caucasian women, and so extrapolations to men and other races/ethnicities require caution. Nevertheless, the baseline scores on SF-36 scales in NHS are quite comparable to a similarly aged group of working U.S. women (Coakley et al., 1998). Detailed information on the Materials and Methods is shown in the supplementary information (Data S1). Briefly, self-reported natural Hair Color in early adulthood was categorized as red, blonde, light brown, dark brown, and black and assigned values of 5, 4, 3, 2, and 1, respectively. In 1992, 1996, and 2000 (NHS) and 1993, 1997, and 2001 (NHS II), participants completed the SF-36 to measure quality of life. We utilized the answers to two items concerning bodily pain, i.e., the extent of bodily pain and the extent of bodily pain interfering with normal work during the past four weeks. We assigned a score for each item (see Data S1) and evaluated the associations between natural Hair Color and pain in various ways (assessment of average age-adjusted as well as multivariate-adjusted combined pain scores; repeated-measures pain scores, referred to as “updated pain scores”; average pain scores of three surveys in each cohort; change in pain scores over four years; and pain scores assessed separately for the two questionnaire items). The regression coefficients (95% confidence intervals (CIs)) were calculated for each Hair Color using generalized linear regression models. The mean age was 58.9 (SD=7.1) years in 1992 (range 46–72 years) in NHS and 38.1 (SD=4.6) years in 1993 (range 28–48 years) in NHS II. Overall, the pain scores tended to increase with age. Combining the two cohorts, each five-year increase in age was associated with a 1.18-point (95% CI: 0.89, 1.46) increase in pain score. As shown in Table 1, the combined pain scores differed significantly according to Hair Color. In both cohorts, participants with lighter Hair Color reported higher pain scores. The updated pain score analysis showed that, compared with dark-Haired individuals, the pain scores were 1.05 higher for dark brown-Haired, 1.08 higher for light brown-Haired, 1.25 higher for blonde-Haired, and 1.54 higher for red-Haired participants, after adjusting for potential confounders (P<0.0001 for all, last row of Table 1). The mean difference in pain score between red- and dark-Haired participants was equivalent to the mean difference in pain score observed between participants (adjusted across all Hair Colors) who were 6~7 years apart in age. Each unit increment of lighter Hair Color was associated with a 0.19-point higher pain score (95% CI: 0.11–0.27) (Ptrend<0.0001). Average pain score analysis yielded similar findings (Table 1). Furthermore, individuals with lighter Hair Color also showed a greater increase in pain score over a four-year time period. As shown in Table 2, when the results from NHS and NHS II were combined, each one-unit increment of lighter Hair Color was associated with a 0.17-point higher increase in pain score over 4 years (95% CI: 0.10–0.25 in pain score; Ptrend<0.0001). Compared with black-Haired women, red-Haired women showed the largest increase in pain scores over time; the beta coefficient (95% CI) representing the relative change in pain score was 1.16 (0.74–1.57) in the combined cohorts (Table 2). The difference in pain score increase over four years between red-Haired and dark-Haired individuals was as large as the mean difference in pain score calculated regardless of Hair Color for participants who were five years apart in age. Similar results were obtained when the pain scores calculated from the two items on the questionnaire were analyzed separately. Compared with black-Haired women, red-Haired women had a score that was 1.88-point (P<0.0001) higher for the extent of bodily pain and 1.17 (P<0.0001) higher for the extent of bodily pain interfering with normal work. Red-Haired women also had the largest increase in scores of each pain item over time; the beta coefficient (95% CI) was 1.27 (P<0.0001) for change in score for bodily pain and 1.11 (P<0.0001) for change in score for bodily pain interfering with normal work. In a secondary analysis, we examined each pain item as ordinal outcome and the results did not change significantly (data not shown). Table 1 Mean difference in pain score according to natural Hair Color Table 2 Mean difference in change of pain score over four years associated with natural Hair Color It was conceivable that the above differences in Hair Color-associated pain scores were due to differences in overall health. Neither the detailed health status information presented in Table S1 nor additional sensitivity analyses performed by excluding specific groups of participants supported this assumption, however. For instance, selective exclusion of participants with major chronic diseases, major autoimmune diseases, or in addition the lowest quartile of the physical function scores did not change the above findings significantly, nor did, for that matter, restriction to Caucasians. Lastly, adjusting for weekly dosage of major over-the-counter pain killers or excluding current users of these medications did also not change the results appreciably (data not shown). However, as information on the use of prescribed pain medications was not available, we cannot assess the association between Hair Color and the overall use of pain medication. The above results show that lighter Hair Color, in particular red Hair, is associated with an increase in self-reported pain. They hence suggest, though they do not prove, that increased pain perception in individuals with lighter Hair Color might be due to a decrease in pain thresholds and not, at least not exclusively, an increased resistance to pain medications. The underlying mechanisms, however, are not clear. An obvious candidate potentially responsible for the observed differences is the endogenous opioid β-endorphin (Barfield et al., 2013). β-endorphin is known to reduce nociception and is derived from the same precursor, pro-opiomelanocortin (POMC), that also gives rise to the MC1R ligand α-melanocyte-stimulating hormone (α-MSH) (Cui et al., 2007; Dores et al., 2014). In fact, experimental data have suggested a link between β-endorphin, susceptibility to pain, and pigmentation. In mice, for instance, UV exposure not only leads to a tanning response but also a systemic elevation of β-endorphin levels and an increase in pain thresholds (Cui et al., 2007; Fell et al., 2014). Increased levels of plasma β-endorphin and β-lipotropin (β-LPH, another POMC derivative) after UV exposure have also been associated with enhanced pigmentation (Belon, 1985; Kauser et al., 2004; Levins et al., 1983). It is conceivable, though not yet demonstrated, that individuals with lighter Hair Color may have generally lower levels of β-endorphin, but other mechanisms such as genetic variations in CACNG2 (a voltage-dependent calcium channel) that have been associated with pain responses (Nissenbaum et al., 2010; Sorge et al., 2012) may have to be considered as well. Our study also revealed an interesting association between aging and pain. This association has also been studied previously, particularly for individuals at advanced age. For example, in one study, older individuals reported more head and chest pain, but less genital pain (Shega et al., 2014), but another study did not find age-related patterns to pain reporting among older adults (Riley et al., 2014). We here found not only that aging in general is significantly associated with increased pain perception but also that the age-related increase in pain is greater among red-Haired compared to black-Haired women. In conclusion, our analysis of two large, prospective, well-established cohorts suggest an association between lighter Hair Color and increased questionnaire-reported pain, particularly for those with red Hair. Further studies are warranted to confirm our findings in other populations and to investigate the common genetic predisposition underlying the associations as well as the biological mechanisms.
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Natural Hair Color and questionnaire-reported pain among women in the United States.
Pigment Cell & Melanoma Research, 2016Co-Authors: Wenqing Li, Shelley S Tworoger, Abrar A QureshiAbstract:Dear editor, Small-scale clinical studies have reported that individuals with naturally red Hair have increased resistance to inhaled and subcutaneous local anesthetics and need more anesthetic to alleviate pain (Liem et al., 2005; Liem et al., 2004). Previous studies have also reported that red-Haired individuals are more sensitive to thermal pain and dental pain (Binkley et al., 2009; Liem et al., 2005) and that individuals carrying MC1R variants associated with a red-Hair phenotype have increased requirements for anesthetics (Liem et al., 2004) or increased fear of pain (Binkley et al., 2009). However, other studies based on an experimental setting using quantitative controlled measurements of graded pain stimuli reported entirely different findings. For example, Mogil et al showed greater tolerance of pain and an increased analgesic response among red-Haired individuals with MC1R variants (Mogil et al., 2005; Mogil et al., 2003). Here we sought to revisit the problem with a different approach, the collection of information on self-reported pain from the Medical Outcomes Study Short-Form 36 Health Status Survey (SF-36) in the Nurses' Health Study (NHS) and NHS II. We recognize that self-reported assessments of pain and pain tolerance are subjective and cannot match experimental assessments of pain thresholds. Nevertheless, we believe that because nurses have high levels of education and are familiar with medical issues, the collected information is of high-quality and valid. An added advantage of using data in NHS and NHS II is that the information was collected prospectively and that it is based on a large number of participants, namely a total of 149,664 participants from the NHS (n=67,349) and NHS II (n=82,315). It has to be noted, however, that these cohorts only involved women, in fact mostly Caucasian women, and so extrapolations to men and other races/ethnicities require caution. Nevertheless, the baseline scores on SF-36 scales in NHS are quite comparable to a similarly aged group of working U.S. women (Coakley et al., 1998). Detailed information on the Materials and Methods is shown in the supplementary information (Data S1). Briefly, self-reported natural Hair Color in early adulthood was categorized as red, blonde, light brown, dark brown, and black and assigned values of 5, 4, 3, 2, and 1, respectively. In 1992, 1996, and 2000 (NHS) and 1993, 1997, and 2001 (NHS II), participants completed the SF-36 to measure quality of life. We utilized the answers to two items concerning bodily pain, i.e., the extent of bodily pain and the extent of bodily pain interfering with normal work during the past four weeks. We assigned a score for each item (see Data S1) and evaluated the associations between natural Hair Color and pain in various ways (assessment of average age-adjusted as well as multivariate-adjusted combined pain scores; repeated-measures pain scores, referred to as “updated pain scores”; average pain scores of three surveys in each cohort; change in pain scores over four years; and pain scores assessed separately for the two questionnaire items). The regression coefficients (95% confidence intervals (CIs)) were calculated for each Hair Color using generalized linear regression models. The mean age was 58.9 (SD=7.1) years in 1992 (range 46–72 years) in NHS and 38.1 (SD=4.6) years in 1993 (range 28–48 years) in NHS II. Overall, the pain scores tended to increase with age. Combining the two cohorts, each five-year increase in age was associated with a 1.18-point (95% CI: 0.89, 1.46) increase in pain score. As shown in Table 1, the combined pain scores differed significantly according to Hair Color. In both cohorts, participants with lighter Hair Color reported higher pain scores. The updated pain score analysis showed that, compared with dark-Haired individuals, the pain scores were 1.05 higher for dark brown-Haired, 1.08 higher for light brown-Haired, 1.25 higher for blonde-Haired, and 1.54 higher for red-Haired participants, after adjusting for potential confounders (P
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a genome wide association study identifies novel alleles associated with Hair Color and skin pigmentation
PLOS Genetics, 2008Co-Authors: Peter Kraft, Susan E Hankinson, Constance Chen, Abrar A Qureshi, Frank B Hu, David L Duffy, Zhen Zhen Zhao, Nicholas G Martin, Grant W MontgomeryAbstract:We conducted a multi-stage genome-wide association study of natural Hair Color in more than 10,000 men and women of European ancestry from the United States and Australia. An initial analysis of 528,173 single nucleotide polymorphisms (SNPs) genotyped on 2,287 women identified IRF4 and SLC24A4 as loci highly associated with Hair Color, along with three other regions encompassing known pigmentation genes. We confirmed these associations in 7,028 individuals from three additional studies. Across these four studies, SLC24A4 rs12896399 and IRF4 rs12203592 showed strong associations with Hair Color, with p = 6.0×10−62 and p = 7.46×10−127, respectively. The IRF4 SNP was also associated with skin Color (p = 6.2×10−14), eye Color (p = 6.1×10−13), and skin tanning response to sunlight (p = 3.9×10−89). A multivariable analysis pooling data from the initial GWAS and an additional 1,440 individuals suggested that the association between rs12203592 and Hair Color was independent of rs1540771, a SNP between the IRF4 and EXOC2 genes previously found to be associated with Hair Color. After adjustment for rs12203592, the association between rs1540771 and Hair Color was not significant (p = 0.52). One variant in the MATP gene was associated with Hair Color. A variant in the HERC2 gene upstream of the OCA2 gene showed the strongest and independent association with Hair Color compared with other SNPs in this region, including three previously reported SNPs. The signals detected in a region around the MC1R gene were explained by MC1R red Hair Color alleles. Our results suggest that the IRF4 and SLC24A4 loci are associated with human Hair Color and skin pigmentation.
C. Kennedy - One of the best experts on this subject based on the ideXlab platform.
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melanocortin 1 receptor mc1r gene variants are associated with an increased risk for cutaneous melanoma which is largely independent of skin type and Hair Color
Journal of Investigative Dermatology, 2001Co-Authors: C. Kennedy, Jeanet A C Ter Huurne, Marjo J P Berkhout, Nelleke A Gruis, Maarten T Bastiaens, Wilma Bergman, Roel Willemze, Jan Nico Bouwes BavinckAbstract:Individuals carrying melanocortin 1 receptor gene variants have an increased risk for the development of cutaneous melanoma. Melanocortin 1 receptor gene variants are also associated with other risk factors for melanoma such as fair skin and red Hair. We evaluated the relationship of melanocortin 1 receptor gene variants, fair skin, red Hair and the development of melanoma in 123 patients with cutaneous melanoma and 385 control subjects. To analyze the association between melanocortin 1 receptor gene variants and skin type or Hair Color we also made use of 453 patients with nonmelanoma skin cancer. We analyzed the coding sequence of the melanocortin 1 receptor gene region by single-stranded conformation polymorphism analysis, followed by DNA sequence analysis. Risk of melanoma dependent on the various melanocortin 1 receptor variant alleles was estimated by exposure odds ratios. The analyses of all different melanocortin 1 receptor gene variants combined, showed that the presence of melanocortin 1 receptor gene variants amounted to a higher melanoma risk, which, in stratified analyses, was independent of skin type and Hair Color. The odds ratios after adjusting for skin type were 3.6 (95% CI 1.7–7.2) for two variants and 2.7 (95% CI 1.5–5.1) for one variant, respectively. Compound heterozygotes and homozygotes for the Val60Leu, Val92Met, Arg142His, Arg151Cys, Arg160Trp, Arg163Gln, and His260Pro variants had odds ratios of about 4 to develop melanoma, whereas heterozygotes for these variants had half the risk. The presence of the melanocortin 1 receptor gene variant Asp84Glu appeared to impose the highest risk for cutaneous melanoma with odds ratios of 16.1 (95% CI 2.3–139.0) and 8.1 (95% CI 1.2–55.9) in compound heterozygotes and heterozygotes, respectively. The broad confidence intervals, when the different variants were analyzed separately, however, do not allow drawing definite conclusions about the magnitude of these risks. Of the more frequently occurring melanocortin 1 receptor variant alleles the Asp84Glu, Arg142His, Arg151Cys, Arg160Trp, His260Pro, and Asp294His variants were strongly associated with both fair skin and red Hair. The Val60Leu, Val92Met, and Arg163Gln variant alleles, however, were only weakly or not associated with fair skin type and/or red Hair, which further illustrates the finding that skin type, Hair Color, and melanoma are independent outcomes of the presence of melanocortin 1 receptor gene variants. We conclude that numerous melanocortin 1 receptor variants predispose to cutaneous melanoma and that possibly the Asp84Glu variant confers the highest risk. This predisposition is largely independent of skin type and Hair Color.
Manfred Kayser - One of the best experts on this subject based on the ideXlab platform.
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A Practical Guide to the HIrisPlex System: Simultaneous Prediction of Eye and Hair Color from DNA.
Methods of Molecular Biology, 2016Co-Authors: Susan Walsh, Manfred KayserAbstract:: The HIrisPlex system, which consists of two parts, allows the simultaneous prediction of eye and Hair Color from DNA, e.g., samples extracted from crime scene evidence. The first part is a highly sensitive multiplex genotyping assay consisting of 24 DNA markers using SNaPshot™ chemistry, for analysis on all Capillary Electrophoresis machines. The second part consists of statistical models that respectively establish eye and Hair Color prediction probabilities from complete and incomplete genotype profiles using parameters generated from large genotype and phenotype databases. This combined prediction tool constitutes the online system freely available to users. Here we provide a practical guide on how to use the HIrisPlex system for forensic and other DNA applications.
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detecting low frequent loss of function alleles in genome wide association studies with red Hair Color as example
PLOS ONE, 2011Co-Authors: Maksim Struchalin, Kate Van Duijn, Albert Hofman, Andre G Uitterlinden, Cornelia M Van Duijn, Yurii S Aulchenko, Manfred KayserAbstract:Multiple loss-of-function (LOF) alleles at the same gene may influence a phenotype not only in the homozygote state when alleles are considered individually, but also in the compound heterozygote (CH) state. Such LOF alleles typically have low frequencies and moderate to large effects. Detecting such variants is of interest to the genetics community, and relevant statistical methods for detecting and quantifying their effects are sorely needed. We present a collapsed double heterozygosity (CDH) test to detect the presence of multiple LOF alleles at a gene. When causal SNPs are available, which may be the case in next generation genome sequencing studies, this CDH test has overwhelmingly higher power than single SNP analysis. When causal SNPs are not directly available such as in current GWA settings, we show the CDH test has higher power than standard single SNP analysis if tagging SNPs are in linkage disequilibrium with the underlying causal SNPs to at least a moderate degree (r2>0.1). The test is implemented for genome-wide analysis in the publically available software package GenABEL which is based on a sliding window approach. We provide the proof of principle by conducting a genome-wide CDH analysis of red Hair Color, a trait known to be influenced by multiple loss-of-function alleles, in a total of 7,732 Dutch individuals with Hair Color ascertained. The association signals at the MC1R gene locus from CDH were uniformly more significant than traditional GWA analyses (the most significant P for CDH = 3.11×10−142 vs. P for rs258322 = 1.33×10−66). The CDH test will contribute towards finding rare LOF variants in GWAS and sequencing studies.
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model based prediction of human Hair Color using dna variants
Human Genetics, 2011Co-Authors: Wojciech Branicki, Kate Van Duijn, Jolanta Drausbarini, Ewelina Pośpiech, Susan Walsh, Tomasz Kupiec, Anna Wojaspelc, Manfred KayserAbstract:Predicting complex human phenotypes from genotypes is the central concept of widely advocated personalized medicine, but so far has rarely led to high accuracies limiting practical applications. One notable exception, although less relevant for medical but important for forensic purposes, is human eye Color, for which it has been recently demonstrated that highly accurate prediction is feasible from a small number of DNA variants. Here, we demonstrate that human Hair Color is predictable from DNA variants with similarly high accuracies. We analyzed in Polish Europeans with single-observer Hair Color grading 45 single nucleotide polymorphisms (SNPs) from 12 genes previously associated with human Hair Color variation. We found that a model based on a subset of 13 single or compound genetic markers from 11 genes predicted red Hair Color with over 0.9, black Hair Color with almost 0.9, as well as blond, and brown Hair Color with over 0.8 prevalence-adjusted accuracy expressed by the area under the receiver characteristic operating curves (AUC). The identified genetic predictors also differentiate reasonably well between similar Hair Colors, such as between red and blond-red, as well as between blond and dark-blond, highlighting the value of the identified DNA variants for accurate Hair Color prediction.
