Browsing by Author "Kayser, Manfred"

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    Ancient genomes indicate population replacement in Early Neolithic Britain
    (Springer Nature, 2019-05) Brace, Selina; Diekmann, Yoan; Booth, Thomas J.; van Dorp, Lucy; Faltyskova, Zuzana; Rohland, Nadin; Mallick, Swapan; Olalde, Iñigo; Ferry, Matthew; Michel, Megan; Oppenheimer, Jonas; Broomandkhoshbacht, Nasreen; Stewardson, Kristin; Martiniano, Rui; Walsh, Susan; Kayser, Manfred; Charlton, Sophy; Hellenthal, Garrett; Armit, Ian; Schulting, Rick; Craig, Oliver E.; Sheridan, Alison; Parker Pearson, Mike; Stringer, Chris; Reich, David; Thomas, Mark G.; Barnes, Ian; Biology, School of Science
    The roles of migration, admixture and acculturation in the European transition to farming have been debated for over 100 years. Genome-wide ancient DNA studies indicate predominantly Aegean ancestry for continental Neolithic farmers, but also variable admixture with local Mesolithic hunter-gatherers. Neolithic cultures first appear in Britain circa 4000 BC, a millennium after they appeared in adjacent areas of continental Europe. The pattern and process of this delayed British Neolithic transition remain unclear. We assembled genome-wide data from 6 Mesolithic and 67 Neolithic individuals found in Britain, dating 8500-2500 BC. Our analyses reveal persistent genetic affinities between Mesolithic British and Western European hunter-gatherers. We find overwhelming support for agriculture being introduced to Britain by incoming continental farmers, with small, geographically structured levels of hunter-gatherer ancestry. Unlike other European Neolithic populations, we detect no resurgence of hunter-gatherer ancestry at any time during the Neolithic in Britain. Genetic affinities with Iberian Neolithic individuals indicate that British Neolithic people were mostly descended from Aegean farmers who followed the Mediterranean route of dispersal. We also infer considerable variation in pigmentation levels in Europe by circa 6000 BC.
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    Erratum to: Global skin colour prediction from DNA
    (Springer Nature, 2017-07) Walsh, Susan; Chaitanya, Lakshmi; Breslin, Krystal; Muralidharan, Charanya; Bronikowska, Agnieszka; Pospiech, Ewelina; Koller, Julia; Kovatsi, Leda; Wollstein, Andreas; Branicki, Wojciech; Liu, Fan; Kayser, Manfred; Biology, School of Science
    Erratum for Global skin colour prediction from DNA. [Hum Genet. 2017]
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    Evaluation of supervised machine-learning methods for predicting appearance traits from DNA
    (Elsevier, 2021) Katsara, Maria-Alexandra; Branicki, Wojciech; Walsh, Susan; Kayser, Manfred; Nothnagel, Michael; VISAGE Consortium; Biology, School of Science
    The prediction of human externally visible characteristics (EVCs) based solely on DNA information has become an established approach in forensic and anthropological genetics in recent years. While for a large set of EVCs, predictive models have already been established using multinomial logistic regression (MLR), the prediction performances of other possible classification methods have not been thoroughly investigated thus far. Motivated by the question to identify a potential classifier that outperforms these specific trait models, we conducted a systematic comparison between the widely used MLR and three popular machine learning (ML) classifiers, namely support vector machines (SVM), random forest (RF) and artificial neural networks (ANN), that have shown good performance outside EVC prediction. As examples, we used eye, hair and skin color categories as phenotypes and genotypes based on the previously established IrisPlex, HIrisPlex, and HIrisPlex-S DNA markers. We compared and assessed the performances of each of the four methods, complemented by detailed hyperparameter tuning that was applied to some of the methods in order to maximize their performance. Overall, we observed that all four classification methods showed rather similar performance, with no method being substantially superior to the others for any of the traits, although performances varied slightly across the different traits and more so across the trait categories. Hence, based on our findings, none of the ML methods applied here provide any advantage on appearance prediction, at least when it comes to the categorical pigmentation traits and the selected DNA markers used here.
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    Genome-wide association studies identify multiple genetic loci influencing eyebrow color variation in Europeans
    (Elsevier, 2019) Peng, Fuduan; Zhu, Gu; Hysi, Pirro G.; Eller, Ryan J.; Chen, Yan; Li, Yi; Hamer, Merel A.; Zeng, Changqing; Hopkins, Racquel L.; Jacobus, Case L.; Wallace, Paige L.; Uitterlinden, André G.; Ikram, M. Arfan; Duffy, David L.; Nijsten, Tamar; Medland, Sarah E.; Spector, Timothy D.; Walsh, Susan; Martin, Nicholas G.; Liu, Fan; Kayser, Manfred; Biology, School of Science
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    Genome-wide association study in 176,678 Europeans reveals genetic loci for tanning response to sun exposure
    (Nature Publishing Group, 2018-05-08) Visconti, Alessia; Duffy, David L.; Liu, Fan; Zhu, Gu; Wu, Wenting; Chen, Yan; Hysi, Pirro G.; Zeng, Changqing; Sanna, Marianna; Iles, Mark M.; Kanetsky, Peter A.; Demenais, Florence; Hamer, Merel A.; Uitterlinden, Andre G.; Ikram, M. Arfan; Nijsten, Tamar; Martin, Nicholas G.; Kayser, Manfred; Spector, Tim D.; Han, Jiali; Bataille, Veronique; Falchi, Mario; Epidemiology, School of Public Health
    The skin's tendency to sunburn rather than tan is a major risk factor for skin cancer. Here we report a large genome-wide association study of ease of skin tanning in 176,678 subjects of European ancestry. We identify significant association with tanning ability at 20 loci. We confirm previously identified associations at six of these loci, and report 14 novel loci, of which ten have never been associated with pigmentation-related phenotypes. Our results also suggest that variants at the AHR/AGR3 locus, previously associated with cutaneous malignant melanoma the underlying mechanism of which is poorly understood, might act on disease risk through modulation of tanning ability.
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    Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color
    (American Association for the Advancement of Science, 2021-03-10) Simcoe, Mark; Valdes, Ana; Liu, Fan; Furlotte, Nicholas A.; Evans, David M.; Hemani, Gibran; Ring, Susan M.; Smith, George Davey; Duffy, David L.; Zhu, Gu; Gordon, Scott D.; Medland, Sarah E.; Vuckovic, Dragana; Girotto, Giorgia; Sala, Cinzia; Catamo, Eulalia; Concas, Maria Pina; Brumat, Marco; Gasparini, Paolo; Toniolo, Daniela; Cocca, Massimiliano; Robino, Antonietta; Yazar, Seyhan; Hewitt, Alex; Wu, Wenting; Kraft, Peter; Hammond, Christopher J.; Shi, Yuan; Chen, Yan; Zeng, Changqing; Klaver, Caroline C. W.; Uitterlinden, Andre G.; Ikram, M. Arfan; Hamer, Merel A.; van Duijn, Cornelia M.; Nijsten, Tamar; Han, Jiali; Mackey, David A.; Martin, Nicholas G.; Cheng, Ching-Yu; 23andMe Research Team; International Visible Trait Genetics Consortium; Hinds, David A.; Spector, Timothy D.; Kayser, Manfred; Hysi, Pirro G.; Epidemiology, School of Public Health
    Human eye color is highly heritable, but its genetic architecture is not yet fully understood. We report the results of the largest genome-wide association study for eye color to date, involving up to 192,986 European participants from 10 populations. We identify 124 independent associations arising from 61 discrete genomic regions, including 50 previously unidentified. We find evidence for genes involved in melanin pigmentation, but we also find associations with genes involved in iris morphology and structure. Further analyses in 1636 Asian participants from two populations suggest that iris pigmentation variation in Asians is genetically similar to Europeans, albeit with smaller effect sizes. Our findings collectively explain 53.2% (95% confidence interval, 45.4 to 61.0%) of eye color variation using common single-nucleotide polymorphisms. Overall, our study outcomes demonstrate that the genetic complexity of human eye color considerably exceeds previous knowledge and expectations, highlighting eye color as a genetically highly complex human trait.
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    Global skin colour prediction from DNA
    (Springer Berlin Heidelberg, 2017) Walsh, Susan; Chaitanya, Lakshmi; Breslin, Krystal; Muralidharan, Charanya; Bronikowska, Agnieszka; Pospiech, Ewelina; Koller, Julia; Kovatsi, Leda; Wollstein, Andreas; Branicki, Wojciech; Liu, Fan; Kayser, Manfred; Biology, School of Science
    Human skin colour is highly heritable and externally visible with relevance in medical, forensic, and anthropological genetics. Although eye and hair colour can already be predicted with high accuracies from small sets of carefully selected DNA markers, knowledge about the genetic predictability of skin colour is limited. Here, we investigate the skin colour predictive value of 77 single-nucleotide polymorphisms (SNPs) from 37 genetic loci previously associated with human pigmentation using 2025 individuals from 31 global populations. We identified a minimal set of 36 highly informative skin colour predictive SNPs and developed a statistical prediction model capable of skin colour prediction on a global scale. Average cross-validated prediction accuracies expressed as area under the receiver-operating characteristic curve (AUC) ± standard deviation were 0.97 ± 0.02 for Light, 0.83 ± 0.11 for Dark, and 0.96 ± 0.03 for Dark-Black. When using a 5-category, this resulted in 0.74 ± 0.05 for Very Pale, 0.72 ± 0.03 for Pale, 0.73 ± 0.03 for Intermediate, 0.87±0.1 for Dark, and 0.97 ± 0.03 for Dark-Black. A comparative analysis in 194 independent samples from 17 populations demonstrated that our model outperformed a previously proposed 10-SNP-classifier approach with AUCs rising from 0.79 to 0.82 for White, comparable at the intermediate level of 0.63 and 0.62, respectively, and a large increase from 0.64 to 0.92 for Black. Overall, this study demonstrates that the chosen DNA markers and prediction model, particularly the 5-category level; allow skin colour predictions within and between continental regions for the first time, which will serve as a valuable resource for future applications in forensic and anthropologic genetics.
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    The HIrisPlex-S system for eye, hair and skin colour prediction from DNA: Introduction and forensic developmental validation
    (Elsevier, 2018) Chaitanya, Lakshmi; Breslin, Krystal; Zuñiga, Sofia; Wirken, Laura; Pośpiech, Ewelina; Kukla-Bartoszek, Magdalena; Sijen, Titia; de Knijff, Peter; Liu, Fan; Branicki, Wojciech; Kayser, Manfred; Walsh, Susan; Biology, School of Science
    Forensic DNA Phenotyping (FDP), i.e. the prediction of human externally visible traits from DNA, has become a fast growing subfield within forensic genetics due to the intelligence information it can provide from DNA traces. FDP outcomes can help focus police investigations in search of unknown perpetrators, who are generally unidentifiable with standard DNA profiling. Therefore, we previously developed and forensically validated the IrisPlex DNA test system for eye colour prediction and the HIrisPlex system for combined eye and hair colour prediction from DNA traces. Here we introduce and forensically validate the HIrisPlex-S DNA test system (S for skin) for the simultaneous prediction of eye, hair, and skin colour from trace DNA. This FDP system consists of two SNaPshot-based multiplex assays targeting a total of 41 SNPs via a novel multiplex assay for 17 skin colour predictive SNPs and the previous HIrisPlex assay for 24 eye and hair colour predictive SNPs, 19 of which also contribute to skin colour prediction. The HIrisPlex-S system further comprises three statistical prediction models, the previously developed IrisPlex model for eye colour prediction based on 6 SNPs, the previous HIrisPlex model for hair colour prediction based on 22 SNPs, and the recently introduced HIrisPlex-S model for skin colour prediction based on 36 SNPs. In the forensic developmental validation testing, the novel 17-plex assay performed in full agreement with the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, as previously shown for the 24-plex assay. Sensitivity testing of the 17-plex assay revealed complete SNP profiles from as little as 63 pg of input DNA, equalling the previously demonstrated sensitivity threshold of the 24-plex HIrisPlex assay. Testing of simulated forensic casework samples such as blood, semen, saliva stains, of inhibited DNA samples, of low quantity touch (trace) DNA samples, and of artificially degraded DNA samples as well as concordance testing, demonstrated the robustness, efficiency, and forensic suitability of the new 17-plex assay, as previously shown for the 24-plex assay. Finally, we provide an update of the publically available HIrisPlex website https://hirisplex.erasmusmc.nl/, now allowing the estimation of individual probabilities for 3 eye, 4 hair, and 5 skin colour categories from HIrisPlex-S input genotypes. The HIrisPlex-S DNA test represents the first forensically validated tool for skin colour prediction, and reflects the first forensically validated tool for simultaneous eye, hair and skin colour prediction from DNA.
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    The impact of correlations between pigmentation phenotypes and underlying genotypes on genetic prediction of pigmentation traits
    (Elsevier, 2021-01) Chen, Yan; Branicki, Wojciech; Walsh, Susan; Nothnagel, Michael; Kayser, Manfred; Liu, Fan; Biology, School of Science
    Predicting appearance phenotypes from genotypes is relevant for various areas of human genetic research and applications such as genetic epidemiology, human history, anthropology, and particularly in forensics. Many appearance phenotypes, and thus their underlying genotypes, are highly correlated, with pigmentation traits serving as primary examples. However, all available genetic prediction models, including those for pigmentation traits currently used in forensic DNA phenotyping, ignore phenotype correlations. Here, we investigated the impact of appearance phenotype correlations on genetic appearance prediction in the exemplary case of three pigmentation traits. We used data for categorical eye, hair and skin colour as well as 41 DNA markers utilized in the recently established HIrisPlex-S system from 762 individuals with complete phenotype and genotype information. Based on these data, we performed genetic prediction modelling of eye, hair and skin colour via three different strategies, namely the established approach of predicting phenotypes solely based on genotypes while not considering phenotype correlations, and two novel approaches that considered phenotype correlations, either incorporating truly observed correlated phenotypes or DNA-predicted correlated phenotypes in addition to the DNA predictors. We found that using truly observed correlated pigmentation phenotypes as additional predictors increased the DNA-based prediction accuracies for almost all eye, hair and skin colour categories, with the largest increase for intermediate eye colour, brown hair colour, dark to black skin colour, and particularly for dark skin colour. Outcomes of dedicated computer simulations suggest that this prediction accuracy increase is due to the additional genetic information that is implicitly provided by the truly observed correlated pigmentation phenotypes used, yet not covered by the DNA predictors applied. In contrast, considering DNA-predicted correlated pigmentation phenotypes as additional predictors did not improve the performance of the genetic prediction of eye, hair and skin colour, which was in line with the results from our computer simulations. Hence, in practical applications of DNA-based appearance prediction where no phenotype knowledge is available, such as in forensic DNA phenotyping, it is not advised to use DNA-predicted correlated phenotypes as predictors in addition to the DNA predictors. In the very least, this is not recommended for the pigmentation traits and the established pigmentation DNA predictors tested here.
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    Likelihood ratio and posterior odds in forensic genetics: Two sides of the same coin
    (Elsevier, 2017-05) Caliebe, Amke; Walsh, Susan; Liu, Fan; Kayser, Manfred; Krawczak, Michael; Department of Biology, School of Science
    It has become widely accepted in forensics that, owing to a lack of sensible priors, the evidential value of matching DNA profiles in trace donor identification or kinship analysis is most sensibly communicated in the form of a likelihood ratio (LR). This restraint does not abate the fact that the posterior odds (PO) would be the preferred basis for returning a verdict. A completely different situation holds for Forensic DNA Phenotyping (FDP), which is aimed at predicting externally visible characteristics (EVCs) of a trace donor from DNA left behind at the crime scene. FDP is intended to provide leads to the police investigation helping them to find unknown trace donors that are unidentifiable by DNA profiling. The statistical models underlying FDP typically yield posterior odds (PO) for an individual possessing a certain EVC. This apparent discrepancy has led to confusion as to when LR or PO is the appropriate outcome of forensic DNA analysis to be communicated to the investigating authorities. We thus set out to clarify the distinction between LR and PO in the context of forensic DNA profiling and FDP from a statistical point of view. In so doing, we also addressed the influence of population affiliation on LR and PO. In contrast to the well-known population dependency of the LR in DNA profiling, the PO as obtained in FDP may be widely population-independent. The actual degree of independence, however, is a matter of (i) how much of the causality of the respective EVC is captured by the genetic markers used for FDP and (ii) by the extent to which non-genetic such as environmental causal factors of the same EVC are distributed equally throughout populations. The fact that an LR should be communicated in cases of DNA profiling whereas the PO are suitable for FDP does not conflict with theory, but rather reflects the immanent differences between these two forensic applications of DNA information.