Ewelina Pośpiech

Model-based prediction of human hair color using DNA variants

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.

Gene–gene interactions contribute to eye colour variation in humans

Prediction of phenotypes from genetic data is considered to be the first practical application of data gained from association studies, with potential importance for medicine and the forensic sciences. Multiple genes and polymorphisms have been found to be associated with variation in human pigmentation. Their analysis enables prediction of blue and brown eye colour with a reasonably high accuracy. More accurate prediction, especially in the case of intermediate eye colours, may require better understanding of gene–gene interactions affecting this polygenic trait. Using multifactor dimensionality reduction and logistic regression methods, a study of gene–gene interactions was conducted based on variation in 11 known pigmentation genes examined in a cohort of 718 individuals of European descent. The study revealed significant interactions of a redundant character between the HERC2 and OCA2 genes affecting determination of hazel eye colour and between HERC2 and SLC24A4 affecting determination of blue eye colour. Our research indicates interactive effects of a synergistic character between HERC2 and OCA2, and also provides evidence for a novel strong synergistic interaction between HERC2 and TYRP1, both affecting determination of green eye colour.

Development of a methylation marker set for forensic age estimation using analysis of public methylation data and the Agena Bioscience EpiTYPER system

Individual age estimation has the potential to provide key information that could enhance and extend DNA intelligence tools. Following predictive tests for externally visible characteristics developed in recent years, prediction of age could guide police investigations and improve the assessment of age-related phenotype expression patterns such as hair colour changes and early onset of male pattern baldness. DNA methylation at CpG positions has emerged as the most promising DNA tests to ascertain the individual age of the donor of a biological contact trace. Although different methodologies are available to detect DNA methylation, EpiTYPER technology (Agena Bioscience, formerly Sequenom) provides useful characteristics that can be applied as a discovery tool in localized regions of the genome. In our study, a total of twenty-two candidate genomic regions, selected from the assessment of publically available data from the Illumina HumanMethylation 450 BeadChip, had a total of 177 CpG sites with informative methylation patterns that were subsequently investigated in detail. From the methylation analyses made, a novel age prediction model based on a multivariate quantile regression analysis was built using the seven highest age-correlated loci of ELOVL2, ASPA, PDE4C, FHL2, CCDC102B, C1orf132 and chr16:85395429. The detected methylation levels in these loci provide a median absolute age prediction error of ±3.07years and a percentage of prediction error relative to the age of 6.3%. We report the predictive performance of the developed model using cross validation of a carefully age-graded training set of 725 European individuals and a test set of 52 monozygotic twin pairs. The multivariate quantile regression age predictor, using the CpG sites selected in this study, has been placed in the open-access Snipper forensic classification website.

Bona fide colour: DNA prediction of human eye and hair colour from ancient and contemporary skeletal remains

BackgroundDNA analysis of ancient skeletal remains is invaluable in evolutionary biology for exploring the history of species, including humans. Contemporary human bones and teeth, however, are relevant in forensic DNA analyses that deal with the identification of perpetrators, missing persons, disaster victims or family relationships. They may also provide useful information towards unravelling controversies that surround famous historical individuals. Retrieving information about a deceased person’s externally visible characteristics can be informative in both types of DNA analyses. Recently, we demonstrated that human eye and hair colour can be reliably predicted from DNA using the HIrisPlex system. Here we test the feasibility of the novel HIrisPlex system at establishing eye and hair colour of deceased individuals from skeletal remains of various post-mortem time ranges and storage conditions.MethodsTwenty-one teeth between 1 and approximately 800 years of age and 5 contemporary bones were subjected to DNA extraction using standard organic protocol followed by analysis using the HIrisPlex system.ResultsTwenty-three out of 26 bone DNA extracts yielded the full 24 SNP HIrisPlex profile, therefore successfully allowing model-based eye and hair colour prediction. HIrisPlex analysis of a tooth from the Polish general Władysław Sikorski (1881 to 1943) revealed blue eye colour and blond hair colour, which was positively verified from reliable documentation. The partial profiles collected in the remaining three cases (two contemporary samples and a 14th century sample) were sufficient for eye colour prediction.ConclusionsOverall, we demonstrate that the HIrisPlex system is suitable, sufficiently sensitive and robust to successfully predict eye and hair colour from ancient and contemporary skeletal remains. Our findings, therefore, highlight the HIrisPlex system as a promising tool in future routine forensic casework involving skeletal remains, including ancient DNA studies, for the prediction of eye and hair colour of deceased individuals.

The Impact of Mitochondrial and Nuclear DNA Variants on Late-Onset Alzheimer's Disease Risk

We investigated the potential contribution of mitochondrial DNA (mtDNA) variants, haplogroups, and polymorphisms in nuclear genes essential for mitochondrial biogenesis and function (PGC-1α TFAM) to late-onset Alzheimers disease (LOAD) risk. Epistatic interaction analysis was conducted between the studied variables. Our results demonstrate that mtDNA haplogroups and subhaplogroups with putative role in partial uncoupling of oxidative phosphorylation are significantly associated with a decreased LOAD risk (OR <1). Conversely, mtDNA haplogroup H (p = 0.049) and HV cluster (p = 0.018) are significant LOAD risk factors, which was additionally confirmed by meta-analysis (OR = 1.22, OR = 1.25, respectively). Haplogroup K was demonstrated to exert a neutralizing effect on the high risk associated with APOE4+ status (p = 0.014). Further, two synergistic interactions between subhaplogroup H5 and APOE4 status (p = 0.009) and between TFAM rs1937 and APOE4 status (p < 0.001) were detected, influencing LOAD risk. No interaction pointing to a dual mitochondrial-nuclear genome variation effect on LOAD occurrence was identified.

Prediction of eye color in the Slovenian population using the IrisPlex SNPs

Aim To evaluate the accuracy of eye color prediction based on six IrisPlex single nucleotide polymorphisms (SNP) in a Slovenian population sample. Methods Six IrisPlex predictor SNPs (HERC2 – rs12913832, OCA2 – rs1800407, SLC45A2 – rs16891982 and TYR – rs1393350, SLC24A4 – rs12896399, and IRF4 – rs12203592) of 105 individuals were analyzed using single base extension approach and SNaPshot chemistry. The IrisPlex multinomial regression prediction model was used to infer eye color probabilities. The accuracy of the IrisPlex was assessed through the calculation of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the area under the receiver characteristic operating curves (AUC). Results Blue eye color was observed in 44.7%, brown in 29.6%, and intermediate in 25.7% participants. Prediction accuracy expressed by the AUC was 0.966 for blue, 0.913 for brown, and 0.796 for intermediate eye color. Sensitivity was 93.6% for blue, 58.1% for brown, and 0% for intermediate eye color. Specificity was 93.1% for blue, 89.2% for brown, and 100% for intermediate eye color. PPV was 91.7% for blue and 69.2% for brown color. NPV was 94.7% for blue and 83.5% for brown eye color. These values indicate prediction accuracy comparable to that established in other studies. Conclusion Blue and brown eye color can be reliably predicted from DNA samples using only six polymorphisms, while intermediate eye color defies prediction, indicating that more research is needed to genetically predict the whole variation of eye color in humans.

Evaluation of DNA Variants Associated with Androgenetic Alopecia and Their Potential to Predict Male Pattern Baldness

Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.

Evaluation of the predictive capacity of DNA variants associated with straight hair in Europeans.

DNA-based prediction of hair morphology, defined as straight, curly or wavy hair, could contribute to an improved description of an unknown offender and allow more accurate forensic reconstructions of physical appearance in the field of forensic DNA phenotyping. Differences in scalp hair morphology are significant at the worldwide scale and within Europe. The only genome-wide association study made to date revealed the Trichohyalin gene (TCHH) to be significantly associated with hair morphology in Europeans and reported weaker associations for WNT10A and FRAS1 genes. We conducted a study that centered on six SNPs located in these three genes with a sample of 528 individuals from Poland. The predictive capacity of the candidate DNA variants was evaluated using logistic regression; classification and regression trees; and neural networks, by applying a 10-fold cross validation procedure. Additionally, an independent test set of 142 males from six European populations was used to verify performance of the developed prediction models. Our study confirmed association of rs11803731 (TCHH), rs7349332 (WNT10A) and rs1268789 (FRAS1) SNPs with hair morphology. The combined genotype risk score for straight hair had an odds ratio of 2.7 and these predictors explained ∼ 8.2% of the total variance. The selected three SNPs were found to predict straight hair with a high sensitivity but low specificity when a 10-fold cross validation procedure was applied and the best results were obtained using the neural networks approach (AUC=0.688, sensitivity=91.2%, specificity=23.0%). Application of the neural networks model with 65% probability threshold on an additional test set gave high sensitivity (81.4%) and improved specificity (50.0%) with a total of 78.7% correct calls, but a high non-classification rate (66.9%). The combined TTGGGG SNP genotype for rs11803731, rs7349332, rs1268789 (European frequency=4.5%) of all six straight hair-associated alleles was identified as the best predictor, giving >80% probability of straight hair. Finally, association testing of 44 SNPs previously identified to be associated with male pattern baldness revealed a suggestive association with hair morphology for rs4679955 on 3q25.1. The study results reported provide the starting point for the development of a predictive test for hair morphology in Europeans. More studies are now needed to discover additional determinants of hair morphology to improve the predictive accuracy of this trait in forensic analysis.

Increased risk of developing cutaneous malignant melanoma is associated with variation in pigmentation genes and VDR, and may involve epistatic effects.

Cutaneous malignant melanoma (CMM) is a malicious human skin cancer that primarily affects individuals with light pigmentation and heavy sun exposure, but also has a known familial association. Multiple genes and polymorphisms have been reported as low-penetrance susceptibility loci for CMM. Here, we examined 33 candidate polymorphisms located in 11 pigmentation genes and the vitamin D receptor gene (VDR) in a population of 130 cutaneous melanoma patients and 707 healthy controls. The genotypes obtained were evaluated for main association effects and potential gene–gene interactions. MC1R, TYR, VDR and SLC45A2 genes were found to be associated with CMM in our population. The results obtained for major function MC1R mutations were the most significant [with odds ratio (OR)=1.787, confidence interval (CI)=1.320–2.419 and P=1.715−4], followed by TYR (rs1393350) (with OR=1.569, CI=1.162–2.118, P=0.003), VDR (GCCC haplotype in rs2238136–rs4516035–rs7139166–rs11568820 block) (with OR=5.653, CI=1.794–17.811, P=0.003) and SLC45A2 (rs16891982) (with OR=0.238, CI=0.057–0.987, P=0.048). The study also detected significant intermolecular epistatic effects between MC1R and TYR, SLC45A2 and VDR, HERC2 and VDR, OCA2 and TPCN2, as well as intramolecular interactions between variants within the genes MC1R and VDR. In the final multivariate logistic regression model for CMM development, only the gene–gene interactions discovered remained significant, showing that epistasis may be an important factor in the risk of melanoma.

Potential association of single nucleotide polymorphisms in pigmentation genes with the development of basal cell carcinoma.

The risk of developing skin cancers is dependent on a combination of environmental factors and personal genetic predispositions. Basal cell carcinoma (BCC) has been associated with single nucleotide polymorphisms in several pigmentation genes; however, there is still controversy concerning the mechanism by which these variants may increase the risk of BCC. The pathway may lead to pigmentation alone, but evidence for their independent influence is growing. Using a single base extension protocol, candidate polymorphisms within 11 known pigment‐related genes were studied for their association with BCC in a population sample consisting of 164 patients and 707 controls. The significance of variation within the MC1R gene was confirmed and, in addition, position rs12203592 within the IRF4 gene was shown to be associated with BCC. These associations remained significant after adjustment for skin color. Gene–gene interactions were found to influence susceptibility to BCC. Among interacting genes are the two above‐mentioned loci with main effect on BCC risk and additionally KITLG, TYRP1, ASIP and TYR. The obtained results indicate that polymorphism at MC1R and IRF4 constitute pigmentation‐independent risk factor in the development of BCC. Moreover, susceptibility to BCC may be influenced by epistatic effects between pigmentation genes.