Browsing by Author "Breslin, Krystal"

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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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    Forensic DNA phenotyping and massive parallel sequencing
    (2017-12-04) Breslin, Krystal; Walsh, Susan
    In the forensic science community, there is an immense need for tools to help assist investigations where conventional DNA profiling methods have been non-informative. Forensic DNA Phenotyping (FDP) aims to bridge that gap and aid investigations by providing physical appearance information when other investigative methods have been exhausted. To create a “biological eye witness”, it becomes necessary to constantly improve these methods in order to develop a complete and accurate image of the individual who left the sample. To add to our previous prediction systems IrisPlex and HIrisPlex, we have developed the HIrisPlex-S system for the all-in-one combined prediction of eye, hair, and skin color from DNA. The skin color prediction model uses 36 variants that were recently proposed for the accurate prediction of categorical skin color on a global scale, and the system is completed by the developmental validation of a 17-plex capillary electrophoresis (CE) genotyping assay that is run in conjunction with the HIrisPlex assay to generate these genotypes. The predicted skin color output includes Very Pale, Pale, Intermediate, Dark and Dark-to-Black categories in addition to categorical eye (Blue, Intermediate, and Brown) and hair (Black, Brown, Blond, and Red) color predictions. We demonstrate that the HIrisPlex-S assay performs in full agreement with guidelines from the Scientific Working Group on DNA Analysis Methods (SWGDAM), achieving high sensitivity levels with a minimum 63pg DNA input. In addition to adding skin color to complete the pigmentation prediction system termed HIrisPlex-S, we successfully designed a Massively Parallel Sequencing (MPS) assay to complement the system and bring Next Generation Sequencing (NGS) to the forefront of forensic DNA analyses methods. Using Illumina’s MiSeq system enables the generation of HIrisPlex-S’s 41 variants using sequencing data that has the capacity to xiii better deconvolute mixtures and perform with even more sensitivity and accuracy. This transition opens the door for a plethora of new ways in which this physical appearance assay can grow as sequencing technology is not limited by variant number; therefore, in essence many more traits have the potential to be included in this one assay design. For now, the HIrisPlex-S design of 41 variants using MPS is being fully assessed according to SWGDAM validated guidelines; therefore, this design paves the way for Forensic DNA Phenotyping to be used in any forensic laboratory. This new and improved HIrisPlex-S system will have a profound impact on casework, missing persons cases, and anthropological cases, as it is relatively inexpensive to run, HIrisPlex-S is easy to use, developmentally validated and one of the largest systems freely available online for physical appearance prediction from DNA using the freely available online web tool found at https://hirisplex.erasmusmc.nl/. Lastly, moving forward in our aim to include additional traits for prediction from DNA, we contributed to a large-scale research collaboration to unearth variants associated with hair morphology. 1026 samples were successfully sequenced using an inhouse MPS design at 91 proposed hair morphological loci. From this reaction, we were able to contribute to the identification of significant correlations between the SNPs rs2219783, rs310642 and rs80293268 with categorical hair morphology: straight, wavy or curly.
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    Forensic DNA Phenotyping: Improving the Prediction of Eye, Hair, and Skin Color through Quantitative Measurement
    (Office of the Vice Chancellor for Research, 2015-04-17) Breslin, Krystal; Eller, Ryan; Muralidharan, Charanya; Walsh, Susan
    Without a match in the DNA database or a reference profile, current methods in forensic DNA profiling fail to give any leads to further criminal investigations. Forensic DNA Phenotyping bridges that gap in the investigation by providing ‘intelligence’ through the identification of externally visible characteristics of the unknown individual from their biological sample left at the crime scene. Recent work on eye and hair color prediction using a tool called ‘HIrisPlex’ has allowed accurate predictions of blue or brown eye color with a precision greater than 95%, and of hair color with a precision of approximately 75% for blond, brown, black and red categories. DNA phenotyping is a new and exciting area of DNA profiling, however there are areas that still require improvement. These include the prediction of intermediate eye colors such as green, or the mechanisms and/or genes involved in age-dependent hair color changes. At this time, categorical skin color prediction is still being developed and will soon be included in the HIrisPlex system, however it is not until the day that pigmentation measurements move toward a quantitative color scale that accuracy will be at a maximum. Our research hopes to target this area specifically. While the predication of categorical measurements is helpful, the term “light brown” is subjective and leads to the possibility of error in interpretation. In order to circumvent this interpretation issue, understanding quantitative color prediction is key. To achieve this, we are in the midst of a database collection of approximately 5000 individuals in which we will perform genome-wide association studies (GWAS) to locate additional eye, hair and skin color genes associated with a quantitative pigment scale phenotype. This database will help create a world-wide representative statistical panel from which quantitative predictive measures can be ascertained. Furthermore, in conjunction with computer programming techniques, it will allow the creation of a user-friendly software program that will enable the prediction of pigmentation-related externally visible characteristics such as eye, hair and skin color. This software has the capacity to be a revolutionary intelligence tool to aid law enforcement investigations by producing a color-print out biological mugshot.
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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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    Meta-analysis of genome-wide association studies identifies 8 novel loci involved in shape variation of human head hair
    (Oxford University Press, 2018-02-01) Liu, Fan; Chen, Yan; Zhu, Gu; Hysi, Pirro G.; Wu, Sijie; Adhikari, Kaustubh; Breslin, Krystal; Pośpiech, Ewelina; Hamer, Merel A.; Peng, Fuduan; Muralidharan, Charanya; Acuna-Alonzo, Victor; Canizales-Quinteros, Samuel; Bedoya, Gabriel; Gallo, Carla; Poletti, Giovanni; Rothhammer, Francisco; Bortolini, Maria Catira; Gonzalez-Jose, Rolando; Zeng, Changqing; Xu, Shuhua; Jin, Li; Uitterlinden, André G.; Ikram, M. Arfan; van Duijn, Cornelia M.; Nijsten, Tamar; Walsh, Susan; Branicki, Wojciech; Wang, Sijia; Ruiz-Linares, Andrés; Spector, Timothy D.; Martin, Nicholas G.; Medland, Sarah E.; Kayser, Manfred; Biology, School of Science
    Shape variation of human head hair shows striking variation within and between human populations, while its genetic basis is far from being understood. We performed a series of genome-wide association studies (GWASs) and replication studies in a total of 28 964 subjects from 9 cohorts from multiple geographic origins. A meta-analysis of three European GWASs identified 8 novel loci (1p36.23 ERRFI1/SLC45A1, 1p36.22 PEX14, 1p36.13 PADI3, 2p13.3 TGFA, 11p14.1 LGR4, 12q13.13 HOXC13, 17q21.2 KRTAP, and 20q13.33 PTK6), and confirmed 4 previously known ones (1q21.3 TCHH/TCHHL1/LCE3E, 2q35 WNT10A, 4q21.21 FRAS1, and 10p14 LINC00708/GATA3), all showing genome-wide significant association with hair shape (P < 5e-8). All except one (1p36.22 PEX14) were replicated with nominal significance in at least one of the 6 additional cohorts of European, Native American and East Asian origins. Three additional previously known genes (EDAR, OFCC1, and PRSS53) were confirmed at the nominal significance level. A multivariable regression model revealed that 14 SNPs from different genes significantly and independently contribute to hair shape variation, reaching a cross-validated AUC value of 0.66 (95% CI: 0.62-0.70) and an AUC value of 0.64 in an independent validation cohort, providing an improved accuracy compared with a previous model. Prediction outcomes of 2504 individuals from a multiethnic sample were largely consistent with general knowledge on the global distribution of hair shape variation. Our study thus delivers target genes and DNA variants for future functional studies to further evaluate the molecular basis of hair shape in humans.
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    Towards broadening Forensic DNA Phenotyping beyond pigmentation: Improving the prediction of head hair shape from DNA
    (Elsevier, 2018-11) Pośpiech, Ewelina; Chen, Yan; Kukla-Bartoszek, Magdalena; Breslin, Krystal; Aliferi, Anastasia; Andersen, Jeppe D.; Ballard, David; Chaitanya, Lakshmi; Freire-Aradas, Ana; van der Gaag, Kristiaan J.; Girón-Santamaría, Lorena; Gross, Theresa E.; Gysi, Mario; Huber, Gabriela; Mosquera-Miguel, Ana; Muralidharan, Charanya; Skowron, Malgorzata; Carracedo, Ángel; Haas, Cordula; Morling, Niels; Parson, Walther; Phillips, Christopher; Schneider, Peter M.; Sijen, Titia; Syndercombe-Court, Denise; Vennemann, Marielle; Wu, Sijie; Xu, Shuhua; Jin, Li; Wang, Sijia; Zhu, Ghu; Martin, Nick G.; Medland, Sarah E.; Branicki, Wojciech; Walsh, Susan; Liu, Fan; Kayser, Manfred; Biology, School of Science
    Human head hair shape, commonly classified as straight, wavy, curly or frizzy, is an attractive target for Forensic DNA Phenotyping and other applications of human appearance prediction from DNA such as in paleogenetics. The genetic knowledge underlying head hair shape variation was recently improved by the outcome of a series of genome-wide association and replication studies in a total of 26,964 subjects, highlighting 12 loci of which 8 were novel and introducing a prediction model for Europeans based on 14 SNPs. In the present study, we evaluated the capacity of DNA-based head hair shape prediction by investigating an extended set of candidate SNP predictors and by using an independent set of samples for model validation. Prediction model building was carried out in 9674 subjects (6068 from Europe, 2899 from Asia and 707 of admixed European and Asian ancestries), used previously, by considering a novel list of 90 candidate SNPs. For model validation, genotype and phenotype data were newly collected in 2415 independent subjects (2138 Europeans and 277 non-Europeans) by applying two targeted massively parallel sequencing platforms, Ion Torrent PGM and MiSeq, or the MassARRAY platform. A binomial model was developed to predict straight vs. non-straight hair based on 32 SNPs from 26 genetic loci we identified as significantly contributing to the model. This model achieved prediction accuracies, expressed as AUC, of 0.664 in Europeans and 0.789 in non-Europeans; the statistically significant difference was explained mostly by the effect of one EDAR SNP in non-Europeans. Considering sex and age, in addition to the SNPs, slightly and insignificantly increased the prediction accuracies (AUC of 0.680 and 0.800, respectively). Based on the sample size and candidate DNA markers investigated, this study provides the most robust, validated, and accurate statistical prediction models and SNP predictor marker sets currently available for predicting head hair shape from DNA, providing the next step towards broadening Forensic DNA Phenotyping beyond pigmentation traits.