1
|
Kukla-Bartoszek M, Teisseyre P, Pośpiech E, Karłowska-Pik J, Zieliński P, Woźniak A, Boroń M, Dąbrowski M, Zubańska M, Jarosz A, Płoski R, Grzybowski T, Spólnicka M, Mielniczuk J, Branicki W. Searching for improvements in predicting human eye colour from DNA. Int J Legal Med 2021; 135:2175-2187. [PMID: 34259936 PMCID: PMC8523394 DOI: 10.1007/s00414-021-02645-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 06/17/2021] [Indexed: 01/29/2023]
Abstract
Increasing understanding of human genome variability allows for better use of the predictive potential of DNA. An obvious direct application is the prediction of the physical phenotypes. Significant success has been achieved, especially in predicting pigmentation characteristics, but the inference of some phenotypes is still challenging. In search of further improvements in predicting human eye colour, we conducted whole-exome (enriched in regulome) sequencing of 150 Polish samples to discover new markers. For this, we adopted quantitative characterization of eye colour phenotypes using high-resolution photographic images of the iris in combination with DIAT software analysis. An independent set of 849 samples was used for subsequent predictive modelling. Newly identified candidates and 114 additional literature-based selected SNPs, previously associated with pigmentation, and advanced machine learning algorithms were used. Whole-exome sequencing analysis found 27 previously unreported candidate SNP markers for eye colour. The highest overall prediction accuracies were achieved with LASSO-regularized and BIC-based selected regression models. A new candidate variant, rs2253104, located in the ARFIP2 gene and identified with the HyperLasso method, revealed predictive potential and was included in the best-performing regression models. Advanced machine learning approaches showed a significant increase in sensitivity of intermediate eye colour prediction (up to 39%) compared to 0% obtained for the original IrisPlex model. We identified a new potential predictor of eye colour and evaluated several widely used advanced machine learning algorithms in predictive analysis of this trait. Our results provide useful hints for developing future predictive models for eye colour in forensic and anthropological studies.
Collapse
Affiliation(s)
- Magdalena Kukla-Bartoszek
- Faculty of Biochemistry, Biophysics and Biotechnology, Jagiellonian University, Kraków, Poland. .,Malopolska Centre of Biotechnology of the Jagiellonian University, Kraków, Poland.
| | - Paweł Teisseyre
- Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland.,Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
| | - Ewelina Pośpiech
- Malopolska Centre of Biotechnology of the Jagiellonian University, Kraków, Poland
| | - Joanna Karłowska-Pik
- Faculty of Mathematics and Computer Science, Nicolaus Copernicus University in Toruń, Toruń, Poland
| | - Piotr Zieliński
- Institute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland
| | - Anna Woźniak
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | - Michał Boroń
- Central Forensic Laboratory of the Police, Warsaw, Poland
| | - Michał Dąbrowski
- Laboratory of Bioinformatics, Neurobiology Centre, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
| | - Magdalena Zubańska
- Faculty of Law and Administration, Department of Criminology and Forensic Sciences, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland.,Unit of Forensic Sciences, Faculty of Internal Security, Police Academy, Szczytno, Poland
| | - Agata Jarosz
- Malopolska Centre of Biotechnology of the Jagiellonian University, Kraków, Poland
| | - Rafał Płoski
- Department of Medical Genetics, Warsaw Medical University, Warsaw, Poland
| | - Tomasz Grzybowski
- Division of Molecular and Forensic Genetics, Department of Forensic Medicine, Nicolaus Copernicus University in Toruń, Collegium Medicum in Bydgoszcz, Bydgoszcz, Poland
| | | | - Jan Mielniczuk
- Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland.,Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
| | - Wojciech Branicki
- Malopolska Centre of Biotechnology of the Jagiellonian University, Kraków, Poland. .,Central Forensic Laboratory of the Police, Warsaw, Poland.
| |
Collapse
|
2
|
Jia M, Zhu M, Zhou F, Wang M, Sun M, Yang Y, Wang X, Wang J, Jin L, Xiang J, Zhang Y, Chang J, Wei Q. Genetic variants of JNK and p38α pathways and risk of non-small cell lung cancer in an Eastern Chinese population. Int J Cancer 2016; 140:807-817. [DOI: 10.1002/ijc.30508] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Accepted: 10/19/2016] [Indexed: 12/12/2022]
Affiliation(s)
- Ming Jia
- Cancer Institute, Collaborative Innovation Center for Cancer Medicine, Fudan University Shanghai Cancer Center; Shanghai China
- Department of Oncology; Shanghai Medical College, Fudan University; Shanghai China
| | - Meiling Zhu
- Department of Oncology; Xinhua Hospital affiliated to Shanghai Jiaotong University, School of Medicine; Shanghai China
| | - Fei Zhou
- Cancer Institute, Collaborative Innovation Center for Cancer Medicine, Fudan University Shanghai Cancer Center; Shanghai China
- Department of Oncology; Shanghai Medical College, Fudan University; Shanghai China
| | - Mengyun Wang
- Cancer Institute, Collaborative Innovation Center for Cancer Medicine, Fudan University Shanghai Cancer Center; Shanghai China
- Department of Oncology; Shanghai Medical College, Fudan University; Shanghai China
| | - Menghong Sun
- Department of Oncology; Shanghai Medical College, Fudan University; Shanghai China
- Department of Pathology; Fudan University Shanghai Cancer Center; Xuhui, Shanghai China
| | - Yajun Yang
- Ministry of Education Key Laboratory of Contemporary Anthropology and State Key Laboratory of Genetic Engineering, School of Life Sciences; Fudan University; Shanghai China
- Fudan-Taizhou Institute of Health Sciences; Taizhou Jiangsu China
| | - Xiaofeng Wang
- Ministry of Education Key Laboratory of Contemporary Anthropology and State Key Laboratory of Genetic Engineering, School of Life Sciences; Fudan University; Shanghai China
- Fudan-Taizhou Institute of Health Sciences; Taizhou Jiangsu China
| | - Jiucun Wang
- Ministry of Education Key Laboratory of Contemporary Anthropology and State Key Laboratory of Genetic Engineering, School of Life Sciences; Fudan University; Shanghai China
- Fudan-Taizhou Institute of Health Sciences; Taizhou Jiangsu China
| | - Li Jin
- Ministry of Education Key Laboratory of Contemporary Anthropology and State Key Laboratory of Genetic Engineering, School of Life Sciences; Fudan University; Shanghai China
- Fudan-Taizhou Institute of Health Sciences; Taizhou Jiangsu China
| | - Jiaqing Xiang
- Department of Oncology; Shanghai Medical College, Fudan University; Shanghai China
- Department of Thoracic Surgery; Fudan University Shanghai Cancer Center; Xuhui, Shanghai China
| | - Yawei Zhang
- Department of Oncology; Shanghai Medical College, Fudan University; Shanghai China
- Department of Thoracic Surgery; Fudan University Shanghai Cancer Center; Xuhui, Shanghai China
| | - Jianhua Chang
- Department of Oncology; Shanghai Medical College, Fudan University; Shanghai China
- Department of Medical Oncology; Fudan University Shanghai Cancer Center; Xuhui, Shanghai China
| | - Qingyi Wei
- Cancer Institute, Collaborative Innovation Center for Cancer Medicine, Fudan University Shanghai Cancer Center; Shanghai China
- Department of Oncology; Shanghai Medical College, Fudan University; Shanghai China
- Duke Cancer Institute, Duke University Medical Center, and Department of Medicine; Duke University School of Medicine; Durham NC
| |
Collapse
|
3
|
Wang L, Wang K, Liu X, He Y. Association of education & lifestyle factors with the perception of genetic knowledge on the development of lung cancer. Indian J Med Res 2016; 143:S32-S37. [PMID: 27748275 PMCID: PMC5080926 DOI: 10.4103/0971-5916.191751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND & OBJECTIVES The perception of genetic knowledge is useful for improving the heath behaviour change against developing cancers. However, no studies have investigated the perception of genetic knowledge on the development of lung cancer. The aim of this study was to examine demographic and lifestyle factors of the perception of genetic knowledge on the development of lung cancer. METHODS Data on 2,295 US adults (739 had the perception of genetic knowledge) were taken from the 2003 Health Information National Trends Survey. Multiple logistic regression models were used to evaluate potential factors of the perception of genetic knowledge of lung cancer. RESULTS Participants aged ≥65 yr were more likely to have the perception of genetic knowledge than those aged 18-44 yr (OR=1.77, 95% CI=1.27-2.46). Higher education was associated with a greater perception of genetic knowledge (OR=1.47, 95% CI=1.16-1.87). Subjects with correct smoking attitude were more than three times more likely to have the perception of genetic knowledge (OR=3.15, 95% CI=2.10-4.72). Subjects with exercise were at an increased likelihood of having the perception of genetic knowledge than those without exercise (OR=1.63, 95% CI=1.24-2.13). INTERPRETATION & CONCLUSIONS Positive associations were observed between education and lifestyle factors and the perception of genetic knowledge on the development of lung cancer among US adults. Strategies developed to improve the perception of genetic knowledge of lung cancer may target on individuals who are young, less educated, and lack correct smoking attitude or exercise.
Collapse
Affiliation(s)
- Liang Wang
- Department of Biostatistics & Epidemiology, College of Public Health, East Tennessee State University, Johnson City, TN 37614, USA
| | - Kesheng Wang
- Department of Biostatistics & Epidemiology, College of Public Health, East Tennessee State University, Johnson City, TN 37614, USA
| | - Xuefeng Liu
- Department of Biostatistics & Epidemiology, College of Public Health, East Tennessee State University, Johnson City, TN 37614, USA
| | - Yi He
- Department of Biostatistics & Epidemiology, College of Public Health, East Tennessee State University, Johnson City, TN 37614, USA
| |
Collapse
|
4
|
Quan B, Qi X, Yu Z, Jiang Y, Liao M, Wang G, Feng R, Zhang L, Chen Z, Jiang Q, Liu G. Pathway analysis of genome-wide association study and transcriptome data highlights new biological pathways in colorectal cancer. Mol Genet Genomics 2014; 290:603-10. [PMID: 25362561 DOI: 10.1007/s00438-014-0945-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2014] [Accepted: 10/17/2014] [Indexed: 12/11/2022]
Abstract
Colorectal cancer (CRC) is a common malignancy that meets the definition of a complex disease. Genome-wide association study (GWAS) has identified several loci of weak predictive value in CRC, however, these do not fully explain the occurrence risk. Recently, gene set analysis has allowed enhanced interpretation of GWAS data in CRC, identifying a number of metabolic pathways as important for disease pathogenesis. Whether there are other important pathways involved in CRC, however, remains unclear. We present a systems analysis of KEGG pathways in CRC using (1) a human CRC GWAS dataset and (2) a human whole transcriptome CRC case-control expression dataset. Analysis of the GWAS dataset revealed significantly enriched KEGG pathways related to metabolism, immune system and diseases, cellular processes, environmental information processing, genetic information processing, and neurodegenerative diseases. Altered gene expression was confirmed in these pathways using the transcriptome dataset. Taken together, these findings not only confirm previous work in this area, but also highlight new biological pathways whose deregulation is critical for CRC. These results contribute to our understanding of disease-causing mechanisms and will prove useful for future genetic and functional studies in CRC.
Collapse
Affiliation(s)
- Baoku Quan
- Department of General Surgery, The First Hospital of Harbin, Harbin, China
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
5
|
Gao P, Zhao H, You J, Jing F, Hu Y. Association between interleukin-8 -251A/T polymorphism and risk of lung cancer: a meta-analysis. Cancer Invest 2014; 32:518-25. [PMID: 25311250 DOI: 10.3109/07357907.2014.964410] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
This study is to evaluate the association between IL-8 -251A/T polymorphism and lung cancer risk in diverse populations. We performed a meta-analysis of six case-control studies that included 3,265 lung-cancer cases and 3,607 case-free controls. Overall, results showed that the IL-8 -251A/T polymorphism was not associated with a significantly increased risk of lung cancer in all genetic models. However, stratified by ethnicity, a significantly increased risk was found among Asians. In conclusion, IL-8 -251A/T polymorphism is associated with lung cancer susceptibility in Asians and the -251 A allele may increase risk of lung cancer in Asians.
Collapse
Affiliation(s)
- Ping Gao
- Oncology Department, Chinese PLA General Hospital, Beijing, China,1
| | | | | | | | | |
Collapse
|
6
|
Yang IA, Holloway JW, Fong KM. Genetic susceptibility to lung cancer and co-morbidities. J Thorac Dis 2014; 5 Suppl 5:S454-62. [PMID: 24163739 DOI: 10.3978/j.issn.2072-1439.2013.08.06] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2013] [Accepted: 08/02/2013] [Indexed: 12/18/2022]
Abstract
Lung cancer is a leading cause of cancer death and disease burden in many countries. Understanding of the biological pathways involved in lung cancer aetiology is required to identify key biomolecules that could be of significant clinical value, either as predictive, prognostic or diagnostic markers, or as targets for the development of novel therapies to treat this disease, in addition to smoking avoidance strategies. Genome-wide association studies (GWAS) have enabled significant progress in the past 5 years in investigating genetic susceptibility to lung cancer. Large scale, multi-cohort GWAS of mainly Caucasian, smoking, populations have identified strong associations for lung cancer mapped to chromosomal regions 15q [nicotinic acetylcholine receptor (nAChR) subunits: CHRNA3, CHRNA5], 5p (TERT-CLPTM1L locus) and 6p (BAT3-MSH5). Some studies in Asian populations of smokers have found similar risk loci, whereas GWAS in never smoking Asian females have identified associations in other chromosomal regions, e.g., 3q (TP63), that are distinct from smoking-related lung cancer risk loci. GWAS of smoking behaviour have identified risk loci for smoking quantity at 15q (similar genes to lung cancer susceptibility: CHRNA3, CHRNA5) and 19q (CYP2A6). Other genes have been mapped for smoking initiation and smoking cessation. In chronic obstructive pulmonary disease (COPD), which is a known risk factor for lung cancer, GWAS in large cohorts have also found CHRNA3 and CHRNA5 single nucleotide polymorphisms (SNPs) mapping at 15q as risk loci, as well as other regions at 4q31 (HHIP), 4q24 (FAM13A) and 5q (HTR4). The overlap in risk loci between lung cancer, smoking behaviour and COPD may be due to the effects of nicotine addiction; however, more work needs to be undertaken to explore the potential direct effects of nicotine and its metabolites in gene-environment interaction in these phenotypes. Goals of future genetic susceptibility studies of lung cancer should focus on refining the strongest risk loci in a wide range of populations with lung cancer, and integrating other clinical and biomarker information, in order to achieve the aim of personalised therapy for lung cancer.
Collapse
Affiliation(s)
- Ian A Yang
- Department of Thoracic Medicine, The Prince Charles Hospital, Brisbane, Australia; ; UQ Thoracic Research Centre, The University of Queensland, Brisbane, Australia
| | | | | |
Collapse
|
7
|
Roukos DH. Genome network medicine: innovation to overcome huge challenges in cancer therapy. WIRES SYSTEMS BIOLOGY AND MEDICINE 2014; 6:201-208. [DOI: 10.1002/wsbm.1254] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/30/2023]
Affiliation(s)
- Dimitrios H. Roukos
- Centre for Biosystems & Genomic Network Medicine Ioannina University Ioannina Greece
| |
Collapse
|