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Gutiérrez-Hurtado IA, Sánchez-Méndez AD, Becerra-Loaiza DS, Rangel-Villalobos H, Torres-Carrillo N, Gallegos-Arreola MP, Aguilar-Velázquez JA. Loss of the Y Chromosome: A Review of Molecular Mechanisms, Age Inference, and Implications for Men's Health. Int J Mol Sci 2024; 25:4230. [PMID: 38673816 PMCID: PMC11050192 DOI: 10.3390/ijms25084230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 03/29/2024] [Accepted: 04/10/2024] [Indexed: 04/28/2024] Open
Abstract
Until a few years ago, it was believed that the gradual mosaic loss of the Y chromosome (mLOY) was a normal age-related process. However, it is now known that mLOY is associated with a wide variety of pathologies in men, such as cardiovascular diseases, neurodegenerative disorders, and many types of cancer. Nevertheless, the mechanisms that generate mLOY in men have not been studied so far. This task is of great importance because it will allow focusing on possible methods of prophylaxis or therapy for diseases associated with mLOY. On the other hand, it would allow better understanding of mLOY as a possible marker for inferring the age of male samples in cases of human identification. Due to the above, in this work, a comprehensive review of the literature was conducted, presenting the most relevant information on the possible molecular mechanisms by which mLOY is generated, as well as its implications for men's health and its possible use as a marker to infer age.
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Affiliation(s)
- Itzae Adonai Gutiérrez-Hurtado
- Departamento de Biología Molecular y Genómica, Centro Universitario de Ciencias de la Salud, Guadalajara 44340, Jalisco, Mexico
| | - Astrid Desireé Sánchez-Méndez
- Laboratorio de Ciencias Morfológico Forenses y Medicina Molecular, Departamento de Morfología, Centro Universitario de Ciencias de la Salud, Guadalajara 44340, Jalisco, Mexico
- Doctorado en Genética Humana, Departamento de Biología Molecular y Genómica, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Jalisco, Mexico
| | | | - Héctor Rangel-Villalobos
- Instituto de Investigación en Genética Molecular, Departamento de Ciencias Médicas y de la Vida, Centro Universitario de la Ciénega, Universidad de Guadalajara, Ocotlán 47820, Jalisco, Mexico
| | - Norma Torres-Carrillo
- Departamento de Microbiología y Patología, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Jalisco, Mexico
| | - Martha Patricia Gallegos-Arreola
- División de Genética, Centro de Investigación Biomédica de Occidente (CIBO), Instituto Mexicano del Seguro Social (IMSS), Guadalajara 44340, Jalisco, Mexico
| | - José Alonso Aguilar-Velázquez
- Laboratorio de Ciencias Morfológico Forenses y Medicina Molecular, Departamento de Morfología, Centro Universitario de Ciencias de la Salud, Guadalajara 44340, Jalisco, Mexico
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2
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Ong JS, Seviiri M, Dusingize JC, Wu Y, Han X, Shi J, Olsen CM, Neale RE, Thompson JF, Saw RPM, Shannon KF, Mann GJ, Martin NG, Medland SE, Gordon SD, Scolyer RA, Long GV, Iles MM, Landi MT, Whiteman DC, MacGregor S, Law MH. Uncovering the complex relationship between balding, testosterone and skin cancers in men. Nat Commun 2023; 14:5962. [PMID: 37789011 PMCID: PMC10547720 DOI: 10.1038/s41467-023-41231-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 08/24/2023] [Indexed: 10/05/2023] Open
Abstract
Male-pattern baldness (MPB) is related to dysregulation of androgens such as testosterone. A previously observed relationship between MPB and skin cancer may be due to greater exposure to ultraviolet radiation or indicate a role for androgenic pathways in the pathogenesis of skin cancers. We dissected this relationship via Mendelian randomization (MR) analyses, using genetic data from recent male-only meta-analyses of cutaneous melanoma (12,232 cases; 20,566 controls) and keratinocyte cancers (KCs) (up to 17,512 cases; >100,000 controls), followed by stratified MR analysis by body-sites. We found strong associations between MPB and the risk of KC, but not with androgens, and multivariable models revealed that this relationship was heavily confounded by MPB single nucleotide polymorphisms involved in pigmentation pathways. Site-stratified MR analyses revealed strong associations between MPB with head and neck squamous cell carcinoma and melanoma, suggesting that sun exposure on the scalp, rather than androgens, is the main driver. Men with less hair covering likely explains, at least in part, the higher incidence of melanoma in men residing in countries with high ambient UV.
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Affiliation(s)
- Jue-Sheng Ong
- Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia.
| | - Mathias Seviiri
- Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Jean Claude Dusingize
- Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Yeda Wu
- Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Xikun Han
- Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Catherine M Olsen
- Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
- Faculty of Medicine, University of Queensland, Herston, QLD, Australia
| | - Rachel E Neale
- Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - John F Thompson
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
- Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Sydney, NSW, Australia
| | - Robyn P M Saw
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
- Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Sydney, NSW, Australia
| | - Kerwin F Shannon
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
- Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Sydney, NSW, Australia
| | - Graham J Mann
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Nicholas G Martin
- Department of Mental Health & Neuroscience, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Sarah E Medland
- Department of Mental Health & Neuroscience, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Scott D Gordon
- Department of Mental Health & Neuroscience, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Richard A Scolyer
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital & NSW Health Pathology, Sydney, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia
| | - Georgina V Long
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
- Department of Medical Oncology, Royal North Shore Hospital, St Leonards, NSW, Australia
| | - Mark M Iles
- Leeds Institute of Medical Research & Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
- NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - David C Whiteman
- Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Stuart MacGregor
- Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Matthew H Law
- Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia.
- School of Biomedical Sciences, Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD, Australia.
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3
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Orang A, Dredge BK, Liu CY, Bracken JM, Chen CH, Sourdin L, Whitfield HJ, Lumb R, Boyle ST, Davis MJ, Samuel MS, Gregory PA, Khew-Goodall Y, Goodall GJ, Pillman KA, Bracken CP. Basonuclin-2 regulates extracellular matrix production and degradation. Life Sci Alliance 2023; 6:e202301984. [PMID: 37536977 PMCID: PMC10400885 DOI: 10.26508/lsa.202301984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 07/16/2023] [Accepted: 07/20/2023] [Indexed: 08/05/2023] Open
Abstract
Epithelial-mesenchymal transition is essential for tissue patterning and organization. It involves both regulation of cell motility and alterations in the composition and organization of the ECM-a complex environment of proteoglycans and fibrous proteins essential for tissue homeostasis, signaling in response to chemical and biomechanical stimuli, and is often dysregulated under conditions such as cancer, fibrosis, and chronic wounds. Here, we demonstrate that basonuclin-2 (BNC2), a mesenchymal-expressed gene, that is, strongly associated with cancer and developmental defects across genome-wide association studies, is a novel regulator of ECM composition and degradation. We find that at endogenous levels, BNC2 controls the expression of specific collagens, matrix metalloproteases, and other matrisomal components in breast cancer cells, and in fibroblasts that are primarily responsible for the production and processing of the ECM within the tumour microenvironment. In so doing, BNC2 modulates the motile and invasive properties of cancers, which likely explains the association of high BNC2 expression with increasing cancer grade and poor patient prognosis.
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Affiliation(s)
- Ayla Orang
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - B Kate Dredge
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Chi Yau Liu
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Julie M Bracken
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Chun-Hsien Chen
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Laura Sourdin
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Holly J Whitfield
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Australia
| | - Rachael Lumb
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Sarah T Boyle
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
| | - Melissa J Davis
- South Australian ImmunogGENomics Cancer Institute, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, Australia
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Australia
- Department of Clinical Pathology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Australia
- Fraser Institute, University of Queensland, Wooloongabba, Australia
| | - Michael S Samuel
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, Australia
| | - Philip A Gregory
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Department of Medicine and School of Biological Sciences, University of Adelaide, Adelaide, Australia
| | - Yeesim Khew-Goodall
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Department of Medicine and School of Biological Sciences, University of Adelaide, Adelaide, Australia
| | - Gregory J Goodall
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Department of Medicine and School of Biological Sciences, University of Adelaide, Adelaide, Australia
| | - Katherine A Pillman
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Department of Medicine and School of Biological Sciences, University of Adelaide, Adelaide, Australia
| | - Cameron P Bracken
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, Australia
- Department of Medicine and School of Biological Sciences, University of Adelaide, Adelaide, Australia
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4
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Kayser M, Branicki W, Parson W, Phillips C. Recent advances in Forensic DNA Phenotyping of appearance, ancestry and age. Forensic Sci Int Genet 2023; 65:102870. [PMID: 37084623 DOI: 10.1016/j.fsigen.2023.102870] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 04/04/2023] [Indexed: 04/09/2023]
Abstract
Forensic DNA Phenotyping (FDP) comprises the prediction of a person's externally visible characteristics regarding appearance, biogeographic ancestry and age from DNA of crime scene samples, to provide investigative leads to help find unknown perpetrators that cannot be identified with forensic STR-profiling. In recent years, FDP has advanced considerably in all of its three components, which we summarize in this review article. Appearance prediction from DNA has broadened beyond eye, hair and skin color to additionally comprise other traits such as eyebrow color, freckles, hair structure, hair loss in men, and tall stature. Biogeographic ancestry inference from DNA has progressed from continental ancestry to sub-continental ancestry detection and the resolving of co-ancestry patterns in genetically admixed individuals. Age estimation from DNA has widened beyond blood to more somatic tissues such as saliva and bones as well as new markers and tools for semen. Technological progress has allowed forensically suitable DNA technology with largely increased multiplex capacity for the simultaneous analysis of hundreds of DNA predictors with targeted massively parallel sequencing (MPS). Forensically validated MPS-based FDP tools for predicting from crime scene DNA i) several appearance traits, ii) multi-regional ancestry, iii) several appearance traits together with multi-regional ancestry, and iv) age from different tissue types, are already available. Despite recent advances that will likely increase the impact of FDP in criminal casework in the near future, moving reliable appearance, ancestry and age prediction from crime scene DNA to the level of detail and accuracy police investigators may desire, requires further intensified scientific research together with technical developments and forensic validations as well as the necessary funding.
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Affiliation(s)
- Manfred Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
| | - Wojciech Branicki
- Institute of Zoology and Biomedical Research, Jagiellonian University, Kraków, Poland,; Institute of Forensic Research, Kraków, Poland
| | - Walther Parson
- Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria; Forensic Science Program, The Pennsylvania State University, PA, USA
| | - Christopher Phillips
- Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain
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5
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Fridman C, Ferreira MA, Marano LA, Forlenza BS. Analysis of genetic polymorphisms associated with the presence of freckles for phenotypic prediction. FORENSIC SCIENCE INTERNATIONAL GENETICS SUPPLEMENT SERIES 2022. [DOI: 10.1016/j.fsigss.2022.09.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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6
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Pośpiech E, Teisseyre P, Mielniczuk J, Branicki W. Predicting Physical Appearance from DNA Data-Towards Genomic Solutions. Genes (Basel) 2022; 13:genes13010121. [PMID: 35052461 PMCID: PMC8774670 DOI: 10.3390/genes13010121] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/03/2022] [Accepted: 01/04/2022] [Indexed: 02/04/2023] Open
Abstract
The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical phenotype suggests that genetic data can be easily predicted, but this has only become possible with less polygenic traits. The forensic community has developed DNA-based predictive tools by employing a limited number of the most important markers analysed with targeted massive parallel sequencing. The complexity of the genetics of many other appearance phenotypes requires big data coupled with sophisticated machine learning methods to develop accurate genomic predictors. A significant challenge in developing universal genomic predictive methods will be the collection of sufficiently large data sets. These should be created using whole-genome sequencing technology to enable the identification of rare DNA variants implicated in phenotype determination. It is worth noting that the correctness of the forensic sketch generated from the DNA data depends on the inclusion of an age factor. This, however, can be predicted by analysing epigenetic data. An important limitation preventing whole-genome approaches from being commonly used in forensics is the slow progress in the development and implementation of high-throughput, low DNA input sequencing technologies. The example of palaeoanthropology suggests that such methods may possibly be developed in forensics.
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Affiliation(s)
- Ewelina Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, 30-387 Kraków, Poland;
| | - Paweł Teisseyre
- Institute of Computer Science, Polish Academy of Sciences, 01-248 Warsaw, Poland; (P.T.); (J.M.)
- Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, Poland
| | - Jan Mielniczuk
- Institute of Computer Science, Polish Academy of Sciences, 01-248 Warsaw, Poland; (P.T.); (J.M.)
- Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, Poland
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, 30-387 Kraków, Poland;
- Central Forensic Laboratory of the Police, 00-583 Warsaw, Poland
- Correspondence: ; Tel.: +48-126-645-024
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7
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Katsara MA, Branicki W, Pośpiech E, Hysi P, Walsh S, Kayser M, Nothnagel M. Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modeling of human appearance traits. Forensic Sci Int Genet 2020; 50:102412. [PMID: 33260052 DOI: 10.1016/j.fsigen.2020.102412] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 09/09/2020] [Accepted: 10/25/2020] [Indexed: 11/26/2022]
Abstract
The prediction of appearance traits by use of solely genetic information has become an established approach and a number of statistical prediction models have already been developed for this purpose. However, given limited knowledge on appearance genetics, currently available models are incomplete and do not include all causal genetic variants as predictors. Therefore such prediction models may benefit from the inclusion of additional information that acts as a proxy for this unknown genetic background. Use of priors, possibly informed by trait category prevalence values in biogeographic ancestry groups, in a Bayesian framework may thus improve the prediction accuracy of previously predicted externally visible characteristics, but has not been investigated as of yet. In this study, we assessed the impact of using trait prevalence-informed priors on the prediction performance in Bayesian models for eye, hair and skin color as well as hair structure and freckles in comparison to the respective prior-free models. Those prior-free models were either similarly defined either very close to the already established ones by using a reduced predictive marker set. However, these differences in the number of the predictive markers should not affect significantly our main outcomes. We observed that such priors often had a strong effect on the prediction performance, but to varying degrees between different traits and also different trait categories, with some categories barely showing an effect. While we found potential for improving the prediction accuracy of many of the appearance trait categories tested by using priors, our analyses also showed that misspecification of those prior values often severely diminished the accuracy compared to the respective prior-free approach. This emphasizes the importance of accurate specification of prevalence-informed priors in Bayesian prediction modeling of appearance traits. However, the existing literature knowledge on spatial prevalence is sparse for most appearance traits, including those investigated here. Due to the limitations in appearance trait prevalence knowledge, our results render the use of trait prevalence-informed priors in DNA-based appearance trait prediction currently infeasible.
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Affiliation(s)
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland; Central Forensic Laboratory of the Police, Warsaw, Poland
| | - Ewelina Pośpiech
- Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland
| | - Pirro Hysi
- Department of Twin Research & Genetic Epidemiology, St Thomas Hospital, Campus, Kings College London (KCL), London, UK
| | - Susan Walsh
- Department of Biology, Indiana University Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Michael Nothnagel
- Cologne Center for Genomics, University of Cologne, Cologne, Germany; University Hospital Cologne, Cologne, Germany.
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8
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Chen Y, Branicki W, Walsh S, Nothnagel M, Kayser M, Liu F. The impact of correlations between pigmentation phenotypes and underlying genotypes on genetic prediction of pigmentation traits. Forensic Sci Int Genet 2020; 50:102395. [PMID: 33070049 DOI: 10.1016/j.fsigen.2020.102395] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 08/25/2020] [Accepted: 09/15/2020] [Indexed: 12/31/2022]
Abstract
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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Affiliation(s)
- Yan Chen
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
| | - Susan Walsh
- Department of Biology, Indiana University Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA
| | - Michael Nothnagel
- Cologne Center for Genomics, University of Cologne, Cologne, Germany; University Hospital Cologne, Cologne, Germany
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Fan Liu
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China.
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9
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Evaluation of the VISAGE Basic Tool for Appearance and Ancestry Prediction Using PowerSeq Chemistry on the MiSeq FGx System. Genes (Basel) 2020; 11:genes11060708. [PMID: 32604780 PMCID: PMC7349024 DOI: 10.3390/genes11060708] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 06/09/2020] [Accepted: 06/11/2020] [Indexed: 01/23/2023] Open
Abstract
The study of DNA to predict externally visible characteristics (EVCs) and the biogeographical ancestry (BGA) from unknown samples is gaining relevance in forensic genetics. Technical developments in Massively Parallel Sequencing (MPS) enable the simultaneous analysis of hundreds of DNA markers, which improves successful Forensic DNA Phenotyping (FDP). The EU-funded VISAGE (VISible Attributes through GEnomics) Consortium has developed various targeted MPS-based lab tools to apply FDP in routine forensic analyses. Here, we present an evaluation of the VISAGE Basic tool for appearance and ancestry prediction based on PowerSeq chemistry (Promega) on a MiSeq FGx System (Illumina). The panel consists of 153 single nucleotide polymorphisms (SNPs) that provide information about EVCs (41 SNPs for eye, hair and skin color from HIrisPlex-S) and continental BGA (115 SNPs; three overlap with the EVCs SNP set). The assay was evaluated for sensitivity, repeatability and genotyping concordance, as well as its performance with casework-type samples. This targeted MPS assay provided complete genotypes at all 153 SNPs down to 125 pg of input DNA and 99.67% correct genotypes at 50 pg. It was robust in terms of repeatability and concordance and provided useful results with casework-type samples. The results suggest that this MPS assay is a useful tool for basic appearance and ancestry prediction in forensic genetics for users interested in applying PowerSeq chemistry and MiSeq for this purpose.
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10
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MC1R variants and associations with pigmentation characteristics and genetic ancestry in a Hispanic, predominately Puerto Rican, population. Sci Rep 2020; 10:7303. [PMID: 32350296 PMCID: PMC7190662 DOI: 10.1038/s41598-020-64019-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Accepted: 04/06/2020] [Indexed: 12/29/2022] Open
Abstract
Skin cancer risk information based on melanocortin-1 receptor (MC1R) variants could inform prevention and screening recommendations for Hispanics, but limited evidence exists on the impact of MC1R variants in Hispanic populations. We studied Hispanic subjects, predominately of Puerto Rican heritage, from Tampa, Florida, US, and Ponce, PR. Blood or saliva samples were collected by prospective recruitment or retrieved from biobanks for genotyping of MC1R variants and ancestry informative markers. Participant demographic and self-reported phenotypic information was collected via biobank records or questionnaires. We determined associations of MC1R genetic risk categories and phenotypic variables and genetic ancestry. Over half of participants carried MC1R variants known to increase risk of skin cancer, and there was diversity in the observed variants across sample populations. Associations between MC1R genetic risk groups and some pigmentation characteristics were identified. Among Puerto Ricans, the proportion of participants carrying MC1R variants imparting elevated skin cancer risk was consistent across quartiles of European, African, and Native American genetic ancestry. These findings demonstrate that MC1R variants are important for pigmentation characteristics in Hispanics and that carriage of high risk MC1R alleles occurs even among Hispanics with stronger African or Native American genetic ancestry.
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11
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Kukla-Bartoszek M, Pośpiech E, Woźniak A, Boroń M, Karłowska-Pik J, Teisseyre P, Zubańska M, Bronikowska A, Grzybowski T, Płoski R, Spólnicka M, Branicki W. DNA-based predictive models for the presence of freckles. Forensic Sci Int Genet 2019; 42:252-259. [DOI: 10.1016/j.fsigen.2019.07.012] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Revised: 06/12/2019] [Accepted: 07/21/2019] [Indexed: 01/05/2023]
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Salvoro C, Faccinetto C, Zucchelli L, Porto M, Marino A, Occhi G, de Los Campos G, Vazza G. Performance of four models for eye color prediction in an Italian population sample. Forensic Sci Int Genet 2019; 40:192-200. [PMID: 30884346 DOI: 10.1016/j.fsigen.2019.03.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 01/27/2019] [Accepted: 03/10/2019] [Indexed: 11/29/2022]
Abstract
Forensic DNA phenotyping (FDP) has recently provided important advancements in forensic investigations, by predicting the physical appearance of a subject from a biological sample, using SNP markers. The majority of operable prediction models have been developed for iris color; however, replication studies to understand their applicability on a worldwide scale are still limited for many of them. In this work, 4 models for eye color prediction (IrisPlex, Ruiz, Allwood and Hart models) were systematically evaluated in a sample of 296 subjects of Italian origin. Genotypes were determined by a custom NGS-based panel targeting all the predictive SNPs included in the 4 tested models. Overall, 60-69% of the Italian sample could be correctly predicted with the IrisPlex, Ruiz and Allwood models, applying the recommended threshold. The IrisPlex model showed the lowest frequency of errors (17%), but also the highest number of inconclusive results (18%). In the absence of the threshold, the highest proportion of correct predictions was again obtained with the IrisPlex model (76%), followed by the Allwood (73%) and the Ruiz (65%) models. Lastly, the Hart predictive algorithm had the lowest error rate (2%), but the majority of predictions (87%) were restricted to the less informative categories of "not-blue" and "not-brown", and correct color predictions were obtained only for 11% of the sample. As observed in previous studies, the majority of incorrect and undefined predictions were ascribable to the intermediate category, which represented 25% of the Italian sample. An adjustment of the IrisPlex (multinomial logistic regression) and Ruiz models (Snipper Bayesian classifier) with Italian allele frequencies gave only minor improvements in predicting intermediate eye color and no remarkable overall changes in performance. This suggests an incomplete knowledge underlying the intermediate colors. Considering the impact of this phenotype in the Italian sample as well as in other admixed populations, future improvements of eye color prediction methods should include a better genetic and phenotypic characterization of this category.
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Affiliation(s)
| | - Christian Faccinetto
- Reparto Carabinieri Investigazioni Scientifiche di Parma, Sezione Biologia, Parma, Italy.
| | - Luca Zucchelli
- Department of Biology, University of Padova, Padova, Italy
| | - Marika Porto
- Department of Biology, University of Padova, Padova, Italy
| | - Alberto Marino
- Reparto Carabinieri Investigazioni Scientifiche di Parma, Sezione Biologia, Parma, Italy
| | - Gianluca Occhi
- Department of Biology, University of Padova, Padova, Italy
| | - Gustavo de Los Campos
- Departments of Epidemiology & Biostatistics and Statistics & Probability, Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, Michigan United States
| | - Giovanni Vazza
- Department of Biology, University of Padova, Padova, Italy.
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Hernando B, Sanz-Page E, Pitarch G, Mahiques L, Valcuende-Cavero F, Martinez-Cadenas C. Genetic variants associated with skin photosensitivity in a southern European population from Spain. PHOTODERMATOLOGY PHOTOIMMUNOLOGY & PHOTOMEDICINE 2018; 34:415-422. [PMID: 29974532 DOI: 10.1111/phpp.12412] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Revised: 06/04/2018] [Accepted: 06/29/2018] [Indexed: 12/18/2022]
Abstract
BACKGROUND/PURPOSE Recent GWAS studies, mostly performed in populations of North European origin, have identified the genetic loci associated with pigmentation, sun sensitivity, freckling and skin cancer susceptibility. Here, we aimed at addressing the genetic determinants of sunlight sensitivity in Spain, a southern European population. METHODS Nine SNPs located in 8 pigmentation-related genes (IRF4, TYR, ASP, HERC2, OCA2, BNC2, SLC24A4 and SLC45A2) were genotyped in 456 Spaniards. Additionally, the complete sequence of the MC1R gene was obtained, testing each nonsynonymous mutation supported by the classification as R or r alleles. A standardised questionnaire was used to collect demographic characteristics, pigmentation and sun sensitivity traits, as well as sun exposure habits. RESULTS MC1R R alleles and IRF4 rs12203592 were significantly associated with sunlight sensitivity at the Bonferroni-corrected level (P-value < 4.54 × 10-3 ). Genetic variants in SLC45A2 (rs16891982) and HERC2 (rs12913832) were also found to be significantly associated with skin photosensitivity in our Spanish sample. Interaction analysis using the MDR method revealed epistatic effects when these four variants were considered together. CONCLUSION MC1R, IRF4, HERC2 and SLC45A2 play a significant role in skin sensitivity to sunlight in the Spanish population. Moreover, interaction among these four loci seems to modulate the ability of the skin to respond to UV radiation.
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Affiliation(s)
- Barbara Hernando
- Department of Medicine, Jaume I University of Castellon, Castellon, Spain
| | - Elena Sanz-Page
- Department of Medicine, Jaume I University of Castellon, Castellon, Spain
| | - Gerard Pitarch
- Department of Dermatology, Castellon University General Hospital, Castellon, Spain
| | - Laura Mahiques
- Department of Dermatology, Castellon University General Hospital, Castellon, Spain
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