Skin responses to ultraviolet radiation: effects of constitutive pigmentation,sex, and ancestry

Constitutive skin pigmentation and skin responses to ultraviolet radiation were measured on a sample of volunteers (n=250) living in State College, PA, USA. The sample was composed of individuals of European American (n=190), Hispanic (n=45), and East Asian ancestry (n=15). Constitutive pigmentation was measured using the Adjusted Melanin Index (AMI), Erythemal Dose Response (EDR) was measured using the slope of a* at 24 h (Deltaa*), and Melanogenic Dose-Response (MDR) was measured using DeltaAM, the slope of AMI at 7 d. The relationships between constitutive skin pigmentation, EDR, MDR, sex, age, and ancestry were investigated. European Americans showed a lower constitutive pigmentation, had a significantly higher burn response (EDR), and had a significantly lower tanning response (MDR) than Hispanics and East Asians. No significant difference is seen between Hispanics and East Asians for either constitutive pigmentation or EDR. Constitutive pigmentation in females was slightly lower than in males in all three samples, but the difference was not significant. While no differences were observed in MDR between sexes, males had a stronger EDR than females regardless of population or constitutive pigmentation level, and this difference was significant in European Americans and Hispanics. We observed no age-related differences in any of the populations or measures investigated. We evaluated the relationship between constitutive pigmentation, EDR and MDR. There was a strong inverse correlation between constitutive pigmentation and EDR in the three samples (European Americans, R2=0.176, P < 0.001; Hispanics, R2=0.204, P=0.009; East Asians, R2=0.223, P=0.098) and a strong direct correlation between constitutive pigmentation and MDR in European Americans and Hispanics (European Americans, R2=0.094, P < 0.001; Hispanics, R2=0.164, P=0.012). In other words, persons with lower constitutive pigmentation both burn more and tan less than persons with higher pigmentation. However, after controlling for constitutive pigmentation, EDR and MDR were significantly correlated in European Americans (R2=0.041 P=0.006). Thus, the general observation that persons who burn more tan less is probable because of the common link that these two phenotypes have with constitutive skin pigmentation and, in fact, once pigmentation has been adjusted for, there is a positive correlation between tanning response and burning response in European Americans.     

A genomewide single-nucleotide-polymorphism panel with high ancestry information for African American admixture mapping

Admixture mapping requires a genomewide panel of relatively evenly spaced markers that can distinguish the ancestral origins of chromosomal segments in admixed individuals. Through use of the results of the International HapMap Project and specific selection criteria, the current study has examined the ability of selected single-nucleotide polymorphisms (SNPs) to extract continental ancestry information in African American subjects and to explore parameters for admixture mapping. Genotyping of two linguistically diverse West African populations (Bini and Kanuri Nigerians, who are Niger-Congo [Bantu] and Nilo-Saharan speakers, respectively), European Americans, and African Americans validated a genomewide set of >4,000 SNP ancestry-informative markers with mean and median F(ST) values >0.59 and mean and median Fisher's information content >2.5. This set of SNPs extracted a larger amount of ancestry information in African Americans than previously reported SNP panels and provides nearly uniform coverage of the genome. Moreover, in the current study, simulations show that this more informative panel improves power for admixture mapping in African Americans when ethnicity risk ratios are modest. This is particularly important in the application of admixture mapping in complex genetic diseases for which only modest ethnicity risk ratios of relevant susceptibility genes are expected.     

Genetic ancestry,admixture and health determinants in Latin America

Background

Modern Latin American populations were formed via genetic admixture among ancestral source populations from Africa, the Americas and Europe. We are interested in studying how combinations of genetic ancestry in admixed Latin American populations may impact genomic determinants of health and disease. For this study, we characterized the impact of ancestry and admixture on genetic variants that underlie health- and disease-related phenotypes in population genomic samples from Colombia, Mexico, Peru, and Puerto Rico.

Results

We analyzed a total of 347 admixed Latin American genomes along with 1102 putative ancestral source genomes from Africans, Europeans, and Native Americans. We characterized the genetic ancestry, relatedness, and admixture patterns for each of the admixed Latin American genomes, finding a spectrum of ancestry proportions within and between populations. We then identified single nucleotide polymorphisms (SNPs) with anomalous ancestry-enrichment patterns, i.e. SNPs that exist in any given Latin American population at a higher frequency than expected based on the population’s genetic ancestry profile. For this set of ancestry-enriched SNPs, we inspected their phenotypic impact on disease, metabolism, and the immune system. All four of the Latin American populations show ancestry-enrichment for a number of shared pathways, yielding evidence of similar selection pressures on these populations during their evolution. For example, all four populations show ancestry-enriched SNPs in multiple genes from immune system pathways, such as the cytokine receptor interaction, T cell receptor signaling, and antigen presentation pathways. We also found SNPs with excess African or European ancestry that are associated with ancestry-specific gene expression patterns and play crucial roles in the immune system and infectious disease responses. Genes from both the innate and adaptive immune system were found to be regulated by ancestry-enriched SNPs with population-specific regulatory effects.

Conclusions

Ancestry-enriched SNPs in Latin American populations have a substantial effect on health- and disease-related phenotypes. The concordant impact observed for same phenotypes across populations points to a process of adaptive introgression, whereby ancestry-enriched SNPs with specific functional utility appear to have been retained in modern populations by virtue of their effects on health and fitness.

     

Genetic admixture, self-reported ethnicity, self-estimated admixture, and skin pigmentation among Hispanics and Native Americans

The relationship between ethnicity and biology is of interest to anthropologists, biomedical scientists, and historians in understanding how human groups are constructed. Ethnic self-identification in recently admixed groups such as Hispanics, African Americans, and Native Americans (NA) is likely to be complex due to the heterogeneity in individual admixture proportions and social environments within these groups. This study examines the relationships between self-identified ethnicity, self-estimated admixture proportions, skin pigmentation, and genetic marker estimated admixture proportions. These measures were assessed using questionnaires, skin color measurements, and genotyping of a panel of 76 ancestry informative markers, among 170 Hispanics and NAs from New Mexico, a state known for its complex history of interactions between people of NA and European (EU) ancestry. Results reveal that NAs underestimate their degree of EU admixture, and that Hispanics underestimate their degree of NA admixture. Within Hispanics, genetic-marker estimated admixture is better predicted by forehead skin pigmentation than by self-estimated admixture. We also find that Hispanic individuals self-identified as "half-White, half Hispanic" and "Spanish" have lower levels of NA admixture than those self-identified as "Mexican" and "Mexican American." Such results highlight the interplay between culture and biology in how individuals identify and view themselves, and have implications for how ethnicity and disease risk are assessed in a medical setting.     

Eye colour: portals into pigmentation genes and ancestry

Several recent papers have tried to address the genetic determination of eye colour via microsatellite linkage, testing of pigmentation candidate gene polymorphisms and the genome wide analysis of SNP markers that are informative for ancestry. These studies show that the OCA2 gene on chromosome 15 is the major determinant of brown and/or blue eye colour but also indicate that other loci will be involved in the broad range of hues seen in this trait in Europeans.     

Recent admixture in an Indian population of African ancestry

Identification and study of genetic variation in recently admixed populations not only provides insight into historical population events but also is a powerful approach for mapping disease loci. We studied a population (OG-W-IP) that is of African-Indian origin and has resided in the western part of India for 500 years; members of this population are believed to be descendants of the Bantu-speaking population of Africa. We have carried out this study by using a set of 18,534 autosomal markers common between Indian, CEPH-HGDP, and HapMap populations. Principal-components analysis clearly revealed that the African-Indian population derives its ancestry from Bantu-speaking west-African as well as Indo-European-speaking north and northwest Indian population(s). STRUCTURE and ADMIXTURE analyses show that, overall, the OG-W-IPs derive 58.7% of their genomic ancestry from their African past and have very little inter-individual ancestry variation (8.4%). The extent of linkage disequilibrium also reveals that the admixture event has been recent. Functional annotation of genes encompassing the ancestry-informative markers that are closer in allele frequency to the Indian ancestral population revealed significant enrichment of biological processes, such as ion-channel activity, and cadherins. We briefly examine the implications of determining the genetic diversity of this population, which could provide opportunities for studies involving admixture mapping.     

Design and analysis of admixture mapping studies

Admixture between populations originating on different continents can be exploited to detect disease susceptibility loci at which risk alleles are distributed differentially between these populations. We first examine the statistical power and mapping resolution of this approach in the limiting situation in which gamete admixture and locus ancestry are measured without uncertainty. We show that, for a rare disease, the most efficient design is to study affected individuals only. In a typical African American population (two-way admixture proportions 0.8/0.2, ancestry crossover rate 2 per 100 cM), a study of 800 affected individuals has 90% power to detect at P values <10(-5) a locus that generates a risk ratio of 2 between populations, with an expected mapping resolution (size of 95% confidence region for the position of the locus) of 4 cM. In practice, to infer locus ancestry from marker data requires Bayesian computationally intensive methods, as implemented in the program ADMIXMAP. Affected-only study designs require strong prior information on the frequencies of each allele given locus ancestry. We show how data from unadmixed and admixed populations can be combined to estimate these ancestry-specific allele frequencies within the admixed population under study, allowing for variation between allele frequencies in unadmixed and admixed populations. Using simulated data based on the genetic structure of the African American population, we show that 60% of information can be extracted in a test for linkage using markers with an ancestry information content of 36% at 3-cM spacing. As in classic linkage studies, the most efficient strategy is to use markers at a moderate density for an initial genome search and then to saturate regions of putative linkage with additional markers, to extract nearly all information about locus ancestry.     

Straightforward inference of ancestry and admixture proportions through ancestry-informative insertion deletion multiplexing

Ancestry-informative markers (AIMs) show high allele frequency divergence between different ancestral or geographically distant populations. These genetic markers are especially useful in inferring the likely ancestral origin of an individual or estimating the apportionment of ancestry components in admixed individuals or populations. The study of AIMs is of great interest in clinical genetics research, particularly to detect and correct for population substructure effects in case-control association studies, but also in population and forensic genetics studies. This work presents a set of 46 ancestry-informative insertion deletion polymorphisms selected to efficiently measure population admixture proportions of four different origins (African, European, East Asian and Native American). All markers are analyzed in short fragments (under 230 basepairs) through a single PCR followed by capillary electrophoresis (CE) allowing a very simple one tube PCR-to-CE approach. HGDP-CEPH diversity panel samples from the four groups, together with Oceanians, were genotyped to evaluate the efficiency of the assay in clustering populations from different continental origins and to establish reference databases. In addition, other populations from diverse geographic origins were tested using the HGDP-CEPH samples as reference data. The results revealed that the AIM-INDEL set developed is highly efficient at inferring the ancestry of individuals and provides good estimates of ancestry proportions at the population level. In conclusion, we have optimized the multiplexed genotyping of 46 AIM-INDELs in a simple and informative assay, enabling a more straightforward alternative to the commonly available AIM-SNP typing methods dependent on complex, multi-step protocols or implementation of large-scale genotyping technologies.     

Versatile simulations of admixture and accurate local ancestry inference with mixnmatch and ancestryinfer

It has become clear that hybridization between species is much more common than previously recognized. As a result, we now know that the genomes of many modern species, including our own, are a patchwork of regions derived from past hybridization events. Increasingly researchers are interested in disentangling which regions of the genome originated from each parental species using local ancestry inference methods. Due to the diverse effects of admixture, this interest is shared across disparate fields, from human genetics to research in ecology and evolutionary biology. However, local ancestry inference methods are sensitive to a range of biological and technical parameters which can impact accuracy. Here we present paired simulation and ancestry inference pipelines, mixnmatch and ancestryinfer, to help researchers plan and execute local ancestry inference studies. mixnmatch can simulate arbitrarily complex demographic histories in the parental and hybrid populations, selection on hybrids, and technical variables such as coverage and contamination. ancestryinfer takes as input sequencing reads from simulated or real individuals, and implements an efficient local ancestry inference pipeline. We perform a series of simulations with mixnmatch to pinpoint factors that influence accuracy in local ancestry inference and highlight useful features of the two pipelines. mixnmatch is a powerful tool for simulations of hybridization while ancestryinfer facilitates local ancestry inference on real or simulated data.     

Skin and hair pigmentation variation in Island Melanesia

Skin and hair pigmentation are two of the most easily visible examples of human phenotypic variation. Selection-based explanations for pigmentation variation in humans have focused on the relationship between melanin and ultraviolet radiation, which is largely dependent on latitude. In this study, skin and hair pigmentation were measured as the melanin (M) index, using narrow-band reflectance spectroscopy for 1,135 individuals from Island Melanesia. Overall, the results show remarkable pigmentation variation, given the small geographic region surveyed. This variation is discussed in terms of differences between males and females, among islands, and among neighborhoods within those islands. The relationship of pigmentation to age, latitude, and longitude is also examined. We found that male skin pigmentation was significantly darker than females in 5 of 6 islands examined. Hair pigmentation showed a negative, but weak, correlation with age, while skin pigmentation showed a positive, but also weak, correlation with age. Skin and hair pigmentation varied significantly between islands as well as between neighborhoods within those islands. Bougainvilleans showed significantly darker skin than individuals from any other island considered, and are darker than a previously described African-American population. These findings are discussed in relation to prevailing hypotheses about the role of natural selection in shaping pigmentation variation in the human species, as well as the role of demographic processes such as admixture and drift in Island Melanesia.     

The population genetic effects of ancestry and admixture in a subdivided cattle breed

The genetic structure of the Dexter, a minority cattle breed with complex demographic history, was investigated using microsatellite markers and a range of statistical approaches designed to detect both admixture and genetic drift. Modern representatives of two putative ancestral populations, the Devon and Kerry, together with the different populations of the Dexter, which have experienced different demographic histories, were analysed. Breed units showed comparatively high levels of genetic variability ( H _E = 0.63–0.68); however, distinct genetic subgroups were detected within the Dexter, which could be attributed to known demographic events. Much lower diversity was identified in three small, isolated Dexter populations ( H _E = 0.52–0.55) and higher differentiation ( F _ST > 0.13) was found. For one of these populations, where strong selection has taken place, we also found evidence of a demographic bottleneck. Three methods for quantifying breed admixture were applied and substantial method-based variation in estimates for the genetic contribution of the two proposed ancestral populations for each subdivision of the Dexter was found. Results were consistent only in the case of a group consisting of selected Traditional Dexter animals, where the ancestor of the modern Kerry breed was also determined as the greater parental contributor to the Dexter. The inconsistency of estimation of admixture proportions between the methods highlights the potentially confounding role of genetic drift in shaping small population structure, and the consequences of accurately describing population histories from contemporary genetic data.     

Genomic ancestry, self-reported "color" and quantitative measures of skin pigmentation in Brazilian admixed siblings

A current concern in genetic epidemiology studies in admixed populations is that population stratification can lead to spurious results. The Brazilian census classifies individuals according to self-reported "color", but several studies have demonstrated that stratifying according to "color" is not a useful strategy to control for population structure, due to the dissociation between self-reported "color" and genomic ancestry. We report the results of a study in a group of Brazilian siblings in which we measured skin pigmentation using a reflectometer, and estimated genomic ancestry using 21 Ancestry Informative Markers (AIMs). Self-reported "color", according to the Brazilian census, was also available for each participant. This made it possible to evaluate the relationship between self-reported "color" and skin pigmentation, self-reported "color" and genomic ancestry, and skin pigmentation and genomic ancestry. We observed that, although there were significant differences between the three "color" groups in genomic ancestry and skin pigmentation, there was considerable dispersion within each group and substantial overlap between groups. We also saw that there was no good agreement between the "color" categories reported by each member of the sibling pair: 30 out of 86 sibling pairs reported different "color", and in some cases, the sibling reporting the darker "color" category had lighter skin pigmentation. Socioeconomic status was significantly associated with self-reported "color" and genomic ancestry in this sample. This and other studies show that subjective classifications based on self-reported "color", such as the one that is used in the Brazilian census, are inadequate to describe the population structure present in recently admixed populations. Finally, we observed that one of the AIMs included in the panel (rs1426654), which is located in the known pigmentation gene SLC24A5, was strongly associated with skin pigmentation in this sample.     

Skin colorimetry and admixture measurement: Some further considerations

Several techniques for using skin colorimetric data to measure admixture contributions to a hybrid population have been reviewed by Lees and Relethford ('78), who find this general approach to be useful. This paper extends their evaluation, providing a method for obtaining an error term and considering at greater length certain potential sources of estimate bias. Questions are raised about their discussion of the appropriate employment of distance statistics in this context, and an alternative procedure for obtaining a single estimate of admixture proportions jointly over all reflectance measurements is offered. While it is shown that the hybrid reflectance curves do not support entirely an assumption of unlinked loci contributing equally and additively to skin color, preliminary findings indicate that admixture estimates made from these data are apparently unbiased and reasonably efficient.     

Prospects for admixture mapping of complex traits

Admixture mapping extends to human populations the principles that underlie linkage analysis of an experimental cross. For detecting genes that contribute to ethnic variation in disease risk, admixture mapping has greater statistical power than family-linkage studies. In comparison with association studies, admixture mapping requires far fewer markers to search the genome and is less affected by allelic heterogeneity. Statistical-analysis programs for admixture mapping are now available, and a genomewide panel of markers for admixture mapping in populations formed by West African-European admixture has been assembled. Some of the remaining technical challenges include the ability to ensure that the statistical methods are robust and to develop marker panels for other admixed populations. Where admixed populations and panels of markers informative for ancestry are available, admixture mapping can be applied to localize genes that contribute to ethnic variation in any measurable trait.     

Methods for high-density admixture mapping of disease genes

Admixture mapping (also known as "mapping by admixture linkage disequilibrium," or MALD) has been proposed as an efficient approach to localizing disease-causing variants that differ in frequency (because of either drift or selection) between two historically separated populations. Near a disease gene, patient populations descended from the recent mixing of two or more ethnic groups should have an increased probability of inheriting the alleles derived from the ethnic group that carries more disease-susceptibility alleles. The central attraction of admixture mapping is that, since gene flow has occurred recently in modern populations (e.g., in African and Hispanic Americans in the past 20 generations), it is expected that admixture-generated linkage disequilibrium should extend for many centimorgans. High-resolution marker sets are now becoming available to test this approach, but progress will require (a). computational methods to infer ancestral origin at each point in the genome and (b). empirical characterization of the general properties of linkage disequilibrium due to admixture. Here we describe statistical methods to estimate the ancestral origin of a locus on the basis of the composite genotypes of linked markers, and we show that this approach accurately estimates states of ancestral origin along the genome. We apply this approach to show that strong admixture linkage disequilibrium extends, on average, for 17 cM in African Americans. Finally, we present power calculations under varying models of disease risk, sample size, and proportions of ancestry. Studying approximately 2500 markers in approximately 2500 patients should provide power to detect many regions contributing to common disease. A particularly important result is that the power of an admixture mapping study to detect a locus will be nearly the same for a wide range of mixture scenarios: the mixture proportion should be 10%-90% from both ancestral populations.     

Analytical correction for multiple testing in admixture mapping

Admixture mapping, using unrelated individuals from the admixture populations that result from recent mating between members of each parental population, is an efficient approach to localize disease-causing variants that differ in frequency between two or more historically separated populations. Recently, several methods have been proposed to test linkage between a susceptibility gene and a disease locus by using admixture-generated linkage disequilibrium (LD) for each of the genotyped markers. In a genome scan, admixture mapping usually tests 2,000 to 3,000 markers across the genome. Currently, either a very conservative Sidak (or Bonferroni) correction or a very time consuming simulation-based method is used to correct for the multiple tests and evaluate the overall p value. In this report, we propose a computationally efficient analytical approach for correction of the multiple tests and for calculating the overall p value for an admixture genome scan. Except for the Sidak (or Bonferroni) correction, our proposed method is the first analytical approach for correction of the multiple tests and for calculating the overall p value for a genome scan. Our simulation studies show that the proposed method gives correct overall type I error rates for genome scans in all cases, and is much more computationally efficient than simulation-based methods.