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Vicuña L. Genetic associations with disease in populations with Indigenous American ancestries. Genet Mol Biol 2024; 47Suppl 1:e20230024. [PMID: 39254840 PMCID: PMC11384980 DOI: 10.1590/1678-4685-gmb-2023-0024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 07/13/2024] [Indexed: 09/11/2024] Open
Abstract
The genetic architecture of complex diseases affecting populations with Indigenous American ancestries is poorly understood due to their underrepresentation in genomics studies. While most of the genetic diversity associated with disease trait variation is shared among worldwide populations, a fraction of this component is expected to be unique to each continental group, including Indigenous Americans. Here, I describe the current state of knowledge from genome-wide association studies on Indigenous populations, as well as non-Indigenous populations with partial Indigenous ancestries from the American continent, focusing on disease susceptibility and anthropometric traits. While some studies identified risk alleles unique to Indigenous populations, their effects on trait variation are mostly small. I suggest that the associations rendered by many inter-population studies are probably inflated due to the absence of socio-cultural-economic covariates in the association models. I encourage the inclusion of admixed individuals in future GWAS studies to control for inter-ancestry differences in environmental factors. I suggest that some complex diseases might have arisen as trade-off costs of adaptations to past evolutionary selective pressures. Finally, I discuss how expanding panels with Indigenous ancestries in GWAS studies is key to accurately assess genetic risk in populations from the American continent, thus decreasing global health disparities.
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Affiliation(s)
- Lucas Vicuña
- University of Chicago, Department of Medicine, Section of Genetic Medicine, Chicago, USA
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Romero-Hidalgo S, Sagaceta-Mejía J, Villalobos-Comparán M, Tejero ME, Domínguez-Pérez M, Jacobo-Albavera L, Posadas-Sánchez R, Vargas-Alarcón G, Posadas-Romero C, Macías-Kauffer L, Vadillo-Ortega F, Contreras-Sieck MA, Acuña-Alonzo V, Barquera R, Macín G, Binia A, Guevara-Chávez JG, Sebastián-Medina L, Menjívar M, Canizales-Quinteros S, Carnevale A, Villarreal-Molina T. Selection scan in Native Americans of Mexico identifies FADS2 rs174616: Evidence of gene-diet interactions affecting lipid levels and Delta-6-desaturase activity. Heliyon 2024; 10:e35477. [PMID: 39166092 PMCID: PMC11334880 DOI: 10.1016/j.heliyon.2024.e35477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2024] [Accepted: 07/29/2024] [Indexed: 08/22/2024] Open
Abstract
Searching for positive selection signals across genomes has identified functional genetic variants responding to environmental change. In Native Americans of Mexico, we used the fixation index (Fst) and population branch statistic (PBS) to identify SNPs suggesting positive selection. The 103 most differentiated SNPs were tested for associations with metabolic traits, the most significant association was FADS2/rs174616 with body mass index (BMI). This variant lies within a linkage disequilibrium (LD) block independent of previously reported FADS selection signals and has not been clearly associated with metabolic phenotypes. We tested this variant in two independent cohorts with cardiometabolic data. In the Genetics of Atherosclerotic Disease (GEA) cohort, the derived allele (T) was associated with increased BMI, lower LDL-C levels and a decreased risk of subclinical atherosclerosis in women. Significant gene-diet interactions affected lipid, apolipoprotein and adiponectin levels with differences according to sex, involving mainly total and complex dietary carbohydrate%. In the Genotype-related Effects of PUFA trial, the derived allele was associated with lower Δ-6 desaturase activity and erythrocyte membrane dihomo-gamma-linolenic acid (DGLA) levels, and with increased Δ-5 desaturase activity and eicosapentaenoic acid levels. This variant interacted with dietary carbohydrate% affecting Δ-6 desaturase activity. Notably, the relationship of DGLA and other erythrocyte membrane LC-PUFA indices with HOMA-IR differed according to rs174616 genotype, which has implications regarding how these indices should be interpreted. In conclusion, this observational study identified rs174616 as a signal suggesting selection in an independent linkage disequilibrium block, was associated with cardiometabolic and erythrocyte measurements of LC-PUFA in two independent Mexican cohorts and showed significant gene-diet interactions.
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Affiliation(s)
- Sandra Romero-Hidalgo
- Departamento de Genómica Computacional, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Janine Sagaceta-Mejía
- Laboratorio de Nutrigenética y Nutrigenómica, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | | | - María Elizabeth Tejero
- Laboratorio de Nutrigenética y Nutrigenómica, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Mayra Domínguez-Pérez
- Laboratorio de Genómica de Enfermedades Cardiovasculares, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Leonor Jacobo-Albavera
- Laboratorio de Genómica de Enfermedades Cardiovasculares, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Rosalinda Posadas-Sánchez
- Departamento de Endocrinología, Instituto Nacional de Cardiología “Ignacio Chávez”, Mexico City, Mexico
| | - Gilberto Vargas-Alarcón
- Departmento de Biología Molecular y Dirección de Investigación, Instituto Nacional de Cardiología Ignacio Chávez, Mexico City, Mexico
| | - Carlos Posadas-Romero
- Departamento de Endocrinología, Instituto Nacional de Cardiología “Ignacio Chávez”, Mexico City, Mexico
| | - Luis Macías-Kauffer
- Unidad de Genómica de Poblaciones Aplicada a la Salud, Facultad de Química UNAM e Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Felipe Vadillo-Ortega
- Unidad de Vinculación de la Facultad de Medicina UNAM en el Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | | | - Víctor Acuña-Alonzo
- Laboratorio de Genética Molecular, Escuela Nacional de Antropología e Historia, Mexico City, Mexico
| | - Rodrigo Barquera
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology (MPI-EVA), Leipzig, Germany
- Anthropology (MPI-EVA), Leipzig, Germany
| | - Gastón Macín
- Escuela Nacional de Antropología e Historia, Mexico City, Mexico
| | - Aristea Binia
- Nestlé Institute of Health Sciences, Innovation Park, EPFL, Lausanne, Switzerland
| | - Jose Guadalupe Guevara-Chávez
- Laboratorio de Genómica de Enfermedades Cardiovasculares, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Leticia Sebastián-Medina
- Laboratorio de Nutrigenética y Nutrigenómica, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Martha Menjívar
- Departamento de Biología, Facultad de Química UNAM, Mexico City and Unidad Académica de Ciencias y Tecnología, UNAM-Yucatán, Mérida, Mexico
| | - Samuel Canizales-Quinteros
- Unidad de Genómica de Poblaciones Aplicada a la Salud, Facultad de Química UNAM e Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Alessandra Carnevale
- Laboratorio de Enfermedades Mendelianas, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Teresa Villarreal-Molina
- Laboratorio de Genómica de Enfermedades Cardiovasculares, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
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Du S, Chen J, Li J, Qian W, Wu S, Peng Q, Liu Y, Pan T, Li Y, Hadi SS, Tan J, Yuan Z, Wang J, Tang K, Wang Z, Wen Y, Dong X, Zhou W, Ruiz-Linares A, Shi Y, Jin L, Liu F, Zhang M, Wang S. A multi-ancestry GWAS meta-analysis of facial features and its application in predicting archaic human features. J Genet Genomics 2024:S1673-8527(24)00181-4. [PMID: 39002897 DOI: 10.1016/j.jgg.2024.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Revised: 07/06/2024] [Accepted: 07/06/2024] [Indexed: 07/15/2024]
Abstract
Facial morphology, a complex trait influenced by genetics, holds great significance in evolutionary research. However, due to limited fossil evidence, the facial characteristics of Neanderthals and Denisovans have remained largely unknown. In this study, we conducted a large-scale multi-ethnic meta-analysis of the genome-wide association study (GWAS), including 9674 East Asians and 10,115 Europeans, quantitatively assessing 78 facial traits using 3D facial images. We identified 71 genomic loci associated with facial features, including 21 novel loci. We developed a facial polygenic score (FPS) that enables the prediction of facial features based on genetic information. Interestingly, the distribution of FPSs among populations from diverse continental groups exhibited relevant correlations with observed facial features. Furthermore, we applied the FPS to predict the facial traits of seven Neanderthals and one Denisovan using ancient DNA and aligned predictions with the fossil records. Our results suggested that Neanderthals and Denisovans likely shared similar facial features, such as a wider but shorter nose and a wider endocanthion distance. The decreased mouth width was characterized specifically in Denisovans. The integration of genomic data and facial trait analysis provides valuable insights into the evolutionary history and adaptive changes in human facial morphology.
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Affiliation(s)
- Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Jieyi Chen
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China
| | - Jiarui Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Wei Qian
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Sijie Wu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Qianqian Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Yu Liu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Ting Pan
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yi Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Sibte Syed Hadi
- Department of Forensic Sciences, College of Criminal Justice, Naif Arab University for Security Sciences, Riyadh 11452, Kingdom of Saudi Arabia
| | - Jingze Tan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Ziyu Yuan
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, China
| | - Jiucun Wang
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, China; Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200120, China; Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai 200438, China
| | - Kun Tang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Zhuo Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yanqin Wen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Xinran Dong
- Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China
| | - Wenhao Zhou
- Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China; Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong 510623, China
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China; Aix-Marseille Université, CNRS, EFS, ADES, Marseille 13005, France; Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London WC1E 6BT, UK
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Li Jin
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, China; Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200120, China; Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai 200438, China
| | - Fan Liu
- Department of Forensic Sciences, College of Criminal Justice, Naif Arab University for Security Sciences, Riyadh 11452, Kingdom of Saudi Arabia; Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, 3015 CN Rotterdam, the Netherlands
| | - Manfei Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China; Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200120, China.
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650223, China.
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Yuan M, Goovaerts S, Vanneste M, Matthews H, Hoskens H, Richmond S, Klein OD, Spritz RA, Hallgrimsson B, Walsh S, Shriver MD, Shaffer JR, Weinberg SM, Peeters H, Claes P. Mapping genes for human face shape: exploration of univariate phenotyping strategies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597731. [PMID: 38895298 PMCID: PMC11185724 DOI: 10.1101/2024.06.06.597731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits. Author Summary Advancements linking variation in the human genome to phenotypes have rapidly evolved in recent decades and have revealed that most human traits are influenced by genetic variants to at least some degree. While many traits, such as stature, are straightforward to acquire and investigate, the multivariate and multipartite nature of facial shape makes quantification more challenging. In this study, we compared the impact of different facial phenotyping approaches on gene mapping outcomes. Our findings suggest that the choice of facial phenotyping method has an impact on apparent trait heritability and the ability to detect genetic association signals. These results offer valuable insights into the importance of phenotyping in genetic investigations, especially when dealing with highly complex morphological traits.
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Wisetchat S, Stevens KA, Frost SR. Facial modeling and measurement based upon homologous topographical features. PLoS One 2024; 19:e0304561. [PMID: 38820264 PMCID: PMC11142440 DOI: 10.1371/journal.pone.0304561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 05/13/2024] [Indexed: 06/02/2024] Open
Abstract
Measurement of human faces is fundamental to many applications from recognition to genetic phenotyping. While anthropometric landmarks provide a conventional set of homologous measurement points, digital scans are increasingly used for facial measurement, despite the difficulties in establishing their homology. We introduce an alternative basis for facial measurement, which 1) provides a richer information density than discrete point measurements, 2) derives its homology from shared facial topography (ridges, folds, etc.), and 3) quantifies local morphological variation following the conventions and practices of anatomical description. A parametric model that permits matching a broad range of facial variation by the adjustment of 71 parameters is demonstrated by modeling a sample of 80 adult human faces. The surface of the parametric model can be adjusted to match each photogrammetric surface mesh generally to within 1 mm, demonstrating a novel and efficient means for facial shape encoding. We examine how well this scheme quantifies facial shape and variation with respect to geographic ancestry and sex. We compare this analysis with a more conventional, landmark-based geometric morphometric (GMM) study with 43 landmarks placed on the same set of scans. Our multivariate statistical analysis using the 71 attribute values separates geographic ancestry groups and sexes with a high degree of reliability, and these results are broadly similar to those from GMM, but with some key differences that we discuss. This approach is compared with conventional, non-parametric methods for the quantification of facial shape, including generality, information density, and the separation of size and shape. Potential uses for phenotypic and dysmorphology studies are also discussed.
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Affiliation(s)
- Sawitree Wisetchat
- Department of Anthropology, University of Oregon, Eugene, Oregon, United States of America
| | - Kent A. Stevens
- Department of Computer and Information Science, University of Oregon, Eugene, Oregon, United States of America
| | - Stephen R. Frost
- Department of Anthropology, University of Oregon, Eugene, Oregon, United States of America
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Qiao H, Tan J, Yan J, Sun C, Yin X, Li Z, Wu J, Guan H, Wen S, Zhang M, Xu S, Jin L. A comprehensive evaluation of the phenotype-first and data-driven approaches in analyzing facial morphological traits. iScience 2024; 27:109325. [PMID: 38487017 PMCID: PMC10937830 DOI: 10.1016/j.isci.2024.109325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 01/17/2024] [Accepted: 02/20/2024] [Indexed: 03/17/2024] Open
Abstract
The phenotype-first approach (PFA) and data-driven approach (DDA) have both greatly facilitated anthropological studies and the mapping of trait-associated genes. However, the pros and cons of the two approaches are poorly understood. Here, we systematically evaluated the two approaches and analyzed 14,838 facial traits in 2,379 Han Chinese individuals. Interestingly, the PFA explained more facial variation than the DDA in the top 100 and 1,000 except in the top 10 phenotypes. Accordingly, the ratio of heterogeneous traits extracted from the PFA was much greater, while more homogenous traits were found using the DDA for different sex, age, and BMI groups. Notably, our results demonstrated that the sex factor accounted for 30% of phenotypic variation in all traits extracted. Furthermore, we linked DDA phenotypes to PFA phenotypes with explicit biological explanations. These findings provide new insights into the analysis of multidimensional phenotypes and expand the understanding of phenotyping approaches.
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Affiliation(s)
- Hui Qiao
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Sciences, Fudan University, Shanghai 200438, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Jingze Tan
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Sciences, Fudan University, Shanghai 200438, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Jun Yan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Chang Sun
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Xing Yin
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Zijun Li
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Jiazi Wu
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Haijuan Guan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
| | - Shaoqing Wen
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Menghan Zhang
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 201203, China
- Institute of Modern Languages and Linguistics, Fudan University, Shanghai 200433, China
- Research Institute of Intelligent Complex Systems, Fudan University, Shanghai 200433, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Sciences, Fudan University, Shanghai 200438, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Sciences, Fudan University, Shanghai 200438, China
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Bao DY, Yang Y, Tong X, Qin HY. Activation of wnt/β-catenin signaling pathway down regulated osteogenic differentiation of bone marrow-derived stem cells in an anhidrotic ectodermal dysplasia patient with EDA/EDAR/EDARADD mutation. Heliyon 2024; 10:e23057. [PMID: 38169761 PMCID: PMC10758735 DOI: 10.1016/j.heliyon.2023.e23057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 10/29/2023] [Accepted: 11/24/2023] [Indexed: 01/05/2024] Open
Abstract
Objective To explore the mechanism by which the Wnt/β-catenin pathway induces osteogenic differentiation of bone marrow-derived stem cells (BMSCs) in anhidrotic ectodermal dysplasia (AED) with an Ectodysplasin A (EDA)/EDA receptor (EDAR)/EDARADD mutation. Methods An AED patient served as the AED group, whereas the other patients without AED were included in the normal group. Peripheral venous blood collected from the AED patient was subjected to whole-genome resequencing. BMSCs from the mandible of patients with AED and normal individuals were isolated and cultured in vitro. Cell proliferation assay was performed to compare the growth speed of BMSCs between the AED and normal groups. CHIR-99021, an activator of the Wnt/β-catenin pathway and XAV-939, an inhibitor, was used to manage BMSCs in an osteogenic environment in both groups. The expression of β-catenin was detected by quantitative polymerase chain reaction, while that of RUNX2 was detected by western blotting. Alizarin red was used for staining. Results A novel mutation (c.152T > A in EDA) and two known mutations (c.1109T > C in EDAR and c.27G > A in EDARADD) were identified. The growth rate in the normal group was higher than that in the AED group. In the normal group, the number and size of calcified nodes and the expression of RUNX-2 increased with CHIR-99021 treatment, which could be inhibited by XAV-939. In contrast, CHIR-99021 inhibited osteogenesis in the AED group and this effect was promoted by XAV-939. Conclusion Activation of the Wnt/β-catenin pathway downregulates osteogenesis of BMSCs in AED patients with EDA/EDAR/EDARADD gene mutations. Further investigation in more AED patients is required, given the wide range of mutations involved in AED.
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Affiliation(s)
- Dong-yu Bao
- Department of Stomatology, the Affiliated Drum Tower Hospital of Nanjing University Medical School. 321 Zhongshan Road, Nanjing, 210008, China
- Department of Dental Implantology, Nanjing Stomatological Hospital, Medical School of Nanjing University, No.30 Zhongyang Road, Nanjing, 210008, China
| | - Yun Yang
- Department of Stomatology, the Affiliated Drum Tower Hospital of Nanjing University Medical School. 321 Zhongshan Road, Nanjing, 210008, China
| | - Xin Tong
- Department of Dental Implantology, Nanjing Stomatological Hospital, Medical School of Nanjing University, No.30 Zhongyang Road, Nanjing, 210008, China
| | - Hai-yan Qin
- Department of Stomatology, the Affiliated Drum Tower Hospital of Nanjing University Medical School. 321 Zhongshan Road, Nanjing, 210008, China
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Ali S, Abrar M, Hussain I, Batool F, Raza RZ, Khatoon H, Zoia M, Visel A, Shubin NH, Osterwalder M, Abbasi AA. Identification of ancestral gnathostome Gli3 enhancers with activity in mammals. Dev Growth Differ 2024; 66:75-88. [PMID: 37925606 PMCID: PMC10841732 DOI: 10.1111/dgd.12901] [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: 04/28/2023] [Revised: 09/01/2023] [Accepted: 10/23/2023] [Indexed: 11/06/2023]
Abstract
Abnormal expression of the transcriptional regulator and hedgehog (Hh) signaling pathway effector Gli3 is known to trigger congenital disease, most frequently affecting the central nervous system (CNS) and the limbs. Accurate delineation of the genomic cis-regulatory landscape controlling Gli3 transcription during embryonic development is critical for the interpretation of noncoding variants associated with congenital defects. Here, we employed a comparative genomic analysis on fish species with a slow rate of molecular evolution to identify seven previously unknown conserved noncoding elements (CNEs) in Gli3 intronic intervals (CNE15-21). Transgenic assays in zebrafish revealed that most of these elements drive activities in Gli3 expressing tissues, predominantly the fins, CNS, and the heart. Intersection of these CNEs with human disease associated SNPs identified CNE15 as a putative mammalian craniofacial enhancer, with conserved activity in vertebrates and potentially affected by mutation associated with human craniofacial morphology. Finally, comparative functional dissection of an appendage-specific CNE conserved in slowly evolving fish (elephant shark), but not in teleost (CNE14/hs1586) indicates co-option of limb specificity from other tissues prior to the divergence of amniotes and lobe-finned fish. These results uncover a novel subset of intronic Gli3 enhancers that arose in the common ancestor of gnathostomes and whose sequence components were likely gradually modified in other species during the process of evolutionary diversification.
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Affiliation(s)
- Shahid Ali
- National Center for Bioinformatics, Program of Comparative and Evolutionary Genomics, Faculty of Biological Sciences, Quaid-i-Azam University, 45320, Islamabad Pakistan
- Department of Organismal Biology and Anatomy, The University of Chicago, Chicago, IL 60637, USA
| | - Muhammad Abrar
- National Center for Bioinformatics, Program of Comparative and Evolutionary Genomics, Faculty of Biological Sciences, Quaid-i-Azam University, 45320, Islamabad Pakistan
| | - Irfan Hussain
- National Center for Bioinformatics, Program of Comparative and Evolutionary Genomics, Faculty of Biological Sciences, Quaid-i-Azam University, 45320, Islamabad Pakistan
| | - Fatima Batool
- National Center for Bioinformatics, Program of Comparative and Evolutionary Genomics, Faculty of Biological Sciences, Quaid-i-Azam University, 45320, Islamabad Pakistan
| | - Rabail Zehra Raza
- Department of Biological Sciences, Faculty of Multidisciplinary Studies, National University of Medical Sciences Rawalpindi, Pakistan
| | - Hizran Khatoon
- National Center for Bioinformatics, Program of Comparative and Evolutionary Genomics, Faculty of Biological Sciences, Quaid-i-Azam University, 45320, Islamabad Pakistan
| | - Matteo Zoia
- Department for Biomedical Research (DBMR), University of Bern, Bern, Switzerland
| | - Axel Visel
- Environmental Genomics and System Biology Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA
- U.S. Department of Energy Joint Genome Institute, 1 Cyclotron Road, Berkeley, CA 94720, USA
- School of Natural Sciences, University of California, Merced, Merced, CA 95343, USA
| | - Neil H. Shubin
- Department of Organismal Biology and Anatomy, The University of Chicago, Chicago, IL 60637, USA
| | - Marco Osterwalder
- Department for Biomedical Research (DBMR), University of Bern, Bern, Switzerland
- Department of Cardiology, Bern University Hospital, Bern, Switzerland
| | - Amir Ali Abbasi
- National Center for Bioinformatics, Program of Comparative and Evolutionary Genomics, Faculty of Biological Sciences, Quaid-i-Azam University, 45320, Islamabad Pakistan
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9
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Ruderman A. Population diversity and equity in the genomic era: going global to return to the local. J Community Genet 2023; 14:519-525. [PMID: 37670200 PMCID: PMC10725358 DOI: 10.1007/s12687-023-00669-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 08/29/2023] [Indexed: 09/07/2023] Open
Abstract
Advances in precision medicine depend on the quantity and quality of available genomic information. Various articles alert about the current disparities between the world's regions regarding the amount of genomic information available and the negative impact this will have on global health. The objective of this paper is to review these articles to describe what aspects they emphasize and highlight some issues that remain to be analyzed from the perspective of a "peripheral" country. Most of these articles come from central countries, where the need for more diversity in genomics is already detected. Several authors analyze lack of human diversity with focus on national, while others analyze the problem from a global perspective. Depending on the country of origin of the research, the claim for greater diversity has different meanings. Broadly, high-income countries advocate for better coverage looking within the boundaries of their own countries. In other regions of the world, where this field of research has not yet been massively developed, the same need for greater inclusiveness of origins in population genomics studies is not detected. An under-analyzed aspect is the unequal starting point between regions regarding the economic resources available for the development of this field of medicine, and for science and health in general. Although this macroeconomic and social aspect is usually absent in scientific analyses, without it solved, it will be impossible to guarantee that all world populations are equally represented in the panels or genomic databases that serve as input for precision medicine development.
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Affiliation(s)
- Anahí Ruderman
- Patagonian Institute of Social and Human Science. CONICET. Bv. Almirante Brown 2915, Puerto Madryn, Argentina.
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10
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Faux P, Ding L, Ramirez-Aristeguieta LM, Chacón-Duque JC, Comini M, Mendoza-Revilla J, Fuentes-Guajardo M, Jaramillo C, Arias W, Hurtado M, Villegas V, Granja V, Barquera R, Everardo-Martínez P, Quinto-Sánchez M, Gómez-Valdés J, Villamil-Ramírez H, Silva de Cerqueira CC, Hünemeier T, Ramallo V, Gonzalez-José R, Schüler-Faccini L, Bortolini MC, Acuña-Alonzo V, Canizales-Quinteros S, Poletti G, Gallo C, Rothhammer F, Rojas W, Schmid AB, Adhikari K, Bennett DL, Ruiz-Linares A. Neanderthal introgression in SCN9A impacts mechanical pain sensitivity. Commun Biol 2023; 6:958. [PMID: 37816865 PMCID: PMC10564861 DOI: 10.1038/s42003-023-05286-z] [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: 02/24/2023] [Accepted: 08/25/2023] [Indexed: 10/12/2023] Open
Abstract
The Nav1.7 voltage-gated sodium channel plays a key role in nociception. Three functional variants in the SCN9A gene (encoding M932L, V991L, and D1908G in Nav1.7), have recently been identified as stemming from Neanderthal introgression and to associate with pain symptomatology in UK BioBank data. In 1000 genomes data, these variants are absent in Europeans but common in Latin Americans. Analysing high-density genotype data from 7594 Latin Americans, we characterized Neanderthal introgression in SCN9A. We find that tracts of introgression occur on a Native American genomic background, have an average length of ~123 kb and overlap the M932L, V991L, and D1908G coding positions. Furthermore, we measured experimentally six pain thresholds in 1623 healthy Colombians. We found that Neanderthal ancestry in SCN9A is significantly associated with a lower mechanical pain threshold after sensitization with mustard oil and evidence of additivity of effects across Nav1.7 variants. Our findings support the reported association of Neanderthal Nav1.7 variants with clinical pain, define a specific sensory modality affected by archaic introgression in SCN9A and are consistent with independent effects of the Neanderthal variants on Nav1.7 function.
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Affiliation(s)
- Pierre Faux
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, 200438, Shanghai, China
- UMR ADES, Aix-Marseille Université, CNRS, EFS, 13005, Marseille, France
- UMR GenPhySE, INRAE, INP, ENVT, Université de Toulouse, 31326, Castanet-Tolosan, France
| | - Li Ding
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, 200438, Shanghai, China
| | | | - J Camilo Chacón-Duque
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, SE-10691, Stockholm, Sweden
- Department of Archaeology and Classical Studies, Stockholm University, SE-1069, Stockholm, Sweden
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK
| | - Maddalena Comini
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, OX3 9DU, UK
| | - Javier Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
- Unit of Human Evolutionary Genetics, Institut Pasteur, 75015, Paris, France
| | - Macarena Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, 1000000, Arica, Chile
| | - Claudia Jaramillo
- GENMOL (Genética Molecular), Universidad de Antioquia, 5001000, Medellín, Colombia
| | - William Arias
- GENMOL (Genética Molecular), Universidad de Antioquia, 5001000, Medellín, Colombia
| | - Malena Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
| | - Valeria Villegas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
| | - Vanessa Granja
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
| | - Rodrigo Barquera
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, 6600, Mexico, Mexico
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History (MPI-SHH), 07745, Jena, Germany
| | - Paola Everardo-Martínez
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, 6600, Mexico, Mexico
| | - Mirsha Quinto-Sánchez
- Forensic Science, Faculty of Medicine, UNAM (Universidad Nacional Autónoma de México), 06320, Mexico City, Mexico
| | - Jorge Gómez-Valdés
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, 6600, Mexico, Mexico
| | - Hugo Villamil-Ramírez
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, 4510, Mexico City, Mexico
| | | | - Tábita Hünemeier
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, 05508-090, São Paulo, SP, Brazil
| | - Virginia Ramallo
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, 90040-060, Porto Alegre, Brasil
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, U9129ACD, Puerto Madryn, Argentina
| | - Rolando Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, U9129ACD, Puerto Madryn, Argentina
| | - Lavinia Schüler-Faccini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, 90040-060, Porto Alegre, Brasil
| | - Maria-Cátira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, 90040-060, Porto Alegre, Brasil
| | - Victor Acuña-Alonzo
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, 6600, Mexico, Mexico
| | - Samuel Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, 4510, Mexico City, Mexico
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, 31, Lima, Perú
| | - Francisco Rothhammer
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica, 1000000, Arica, Chile
| | - Winston Rojas
- GENMOL (Genética Molecular), Universidad de Antioquia, 5001000, Medellín, Colombia
| | - Annina B Schmid
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, OX3 9DU, UK
| | - Kaustubh Adhikari
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK.
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, UK.
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK.
| | - David L Bennett
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, OX3 9DU, UK.
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, 200438, Shanghai, China.
- UMR ADES, Aix-Marseille Université, CNRS, EFS, 13005, Marseille, France.
- Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK.
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11
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Selleri L, Rijli FM. Shaping faces: genetic and epigenetic control of craniofacial morphogenesis. Nat Rev Genet 2023; 24:610-626. [PMID: 37095271 DOI: 10.1038/s41576-023-00594-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/14/2023] [Indexed: 04/26/2023]
Abstract
Major differences in facial morphology distinguish vertebrate species. Variation of facial traits underlies the uniqueness of human individuals, and abnormal craniofacial morphogenesis during development leads to birth defects that significantly affect quality of life. Studies during the past 40 years have advanced our understanding of the molecular mechanisms that establish facial form during development, highlighting the crucial roles in this process of a multipotent cell type known as the cranial neural crest cell. In this Review, we discuss recent advances in multi-omics and single-cell technologies that enable genes, transcriptional regulatory networks and epigenetic landscapes to be closely linked to the establishment of facial patterning and its variation, with an emphasis on normal and abnormal craniofacial morphogenesis. Advancing our knowledge of these processes will support important developments in tissue engineering, as well as the repair and reconstruction of the abnormal craniofacial complex.
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Affiliation(s)
- Licia Selleri
- Program in Craniofacial Biology, Department of Orofacial Sciences, School of Dentistry, University of California, San Francisco, CA, USA.
- Department of Anatomy, School of Medicine, University of California, San Francisco, CA, USA.
| | - Filippo M Rijli
- Laboratory of Developmental Neuroepigenetics, Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
- University of Basel, Basel, Switzerland.
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12
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Yuan M, Goovaerts S, Hoskens H, Richmond S, Walsh S, Shriver MD, Shaffer JR, Marazita ML, Weinberg SM, Peeters H, Claes P. Data-driven trait heritability-based extraction of human facial phenotypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.13.553129. [PMID: 37645810 PMCID: PMC10462092 DOI: 10.1101/2023.08.13.553129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
A genome-wide association study (GWAS) of a complex, multi-dimensional morphological trait, such as the human face, typically relies on predefined and simplified phenotypic measurements, such as inter-landmark distances and angles. These measures are predominantly designed by human experts based on perceived biological or clinical knowledge. To avoid use handcrafted phenotypes (i.e., a priori expert-identified phenotypes), alternative automatically extracted phenotypic descriptors, such as features derived from dimension reduction techniques (e.g., principal component analysis), are employed. While the features generated by such computational algorithms capture the geometric variations of the biological shape, they are not necessarily genetically relevant. Therefore, genetically informed data-driven phenotyping is desirable. Here, we propose an approach where phenotyping is done through a data-driven optimization of trait heritability, defined as the degree of variation in a phenotypic trait in a population that is due to genetic variation. The resulting phenotyping process consists of two steps: 1) constructing a feature space that models shape variations using dimension reduction techniques, and 2) searching for directions in the feature space exhibiting high trait heritability using a genetic search algorithm (i.e., heuristic inspired by natural selection). We show that the phenotypes resulting from the proposed trait heritability-optimized training differ from those of principal components in the following aspects: 1) higher trait heritability, 2) higher SNP heritability, and 3) identification of the same number of independent genetic loci with a smaller number of effective traits. Our results demonstrate that data-driven trait heritability-based optimization enables the automatic extraction of genetically relevant phenotypes, as shown by their increased power in genome-wide association scans.
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13
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Yankee TN, Oh S, Winchester EW, Wilderman A, Robinson K, Gordon T, Rosenfeld JA, VanOudenhove J, Scott DA, Leslie EJ, Cotney J. Integrative analysis of transcriptome dynamics during human craniofacial development identifies candidate disease genes. Nat Commun 2023; 14:4623. [PMID: 37532691 PMCID: PMC10397224 DOI: 10.1038/s41467-023-40363-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 07/25/2023] [Indexed: 08/04/2023] Open
Abstract
Craniofacial disorders arise in early pregnancy and are one of the most common congenital defects. To fully understand how craniofacial disorders arise, it is essential to characterize gene expression during the patterning of the craniofacial region. To address this, we performed bulk and single-cell RNA-seq on human craniofacial tissue from 4-8 weeks post conception. Comparisons to dozens of other human tissues revealed 239 genes most strongly expressed during craniofacial development. Craniofacial-biased developmental enhancers were enriched +/- 400 kb surrounding these craniofacial-biased genes. Gene co-expression analysis revealed that regulatory hubs are enriched for known disease causing genes and are resistant to mutation in the normal healthy population. Combining transcriptomic and epigenomic data we identified 539 genes likely to contribute to craniofacial disorders. While most have not been previously implicated in craniofacial disorders, we demonstrate this set of genes has increased levels of de novo mutations in orofacial clefting patients warranting further study.
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Affiliation(s)
- Tara N Yankee
- Graduate Program in Genetics and Developmental Biology, UConn Health, Farmington, CT, 06030, USA
| | - Sungryong Oh
- University of Connecticut School of Medicine, Department of Genetics and Genome Sciences, Farmington, CT, 06030, USA
| | | | - Andrea Wilderman
- Graduate Program in Genetics and Developmental Biology, UConn Health, Farmington, CT, 06030, USA
| | - Kelsey Robinson
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Tia Gordon
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Jill A Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Baylor Genetics Laboratory, Houston, TX, 77021, USA
| | - Jennifer VanOudenhove
- University of Connecticut School of Medicine, Department of Genetics and Genome Sciences, Farmington, CT, 06030, USA
| | - Daryl A Scott
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Elizabeth J Leslie
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Justin Cotney
- University of Connecticut School of Medicine, Department of Genetics and Genome Sciences, Farmington, CT, 06030, USA.
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, 06269, USA.
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14
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Li Y, Xiong Z, Zhang M, Hysi PG, Qian Y, Adhikari K, Weng J, Wu S, Du S, Gonzalez-Jose R, Schuler-Faccini L, Bortolini MC, Acuna-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Bedoya G, Rothhammer F, Wang J, Tan J, Yuan Z, Jin L, Uitterlinden AG, Ghanbari M, Ikram MA, Nijsten T, Zhu X, Lei Z, Jia P, Ruiz-Linares A, Spector TD, Wang S, Kayser M, Liu F. Combined genome-wide association study of 136 quantitative ear morphology traits in multiple populations reveal 8 novel loci. PLoS Genet 2023; 19:e1010786. [PMID: 37459304 PMCID: PMC10351707 DOI: 10.1371/journal.pgen.1010786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 05/16/2023] [Indexed: 07/20/2023] Open
Abstract
Human ear morphology, a complex anatomical structure represented by a multidimensional set of correlated and heritable phenotypes, has a poorly understood genetic architecture. In this study, we quantitatively assessed 136 ear morphology traits using deep learning analysis of digital face images in 14,921 individuals from five different cohorts in Europe, Asia, and Latin America. Through GWAS meta-analysis and C-GWASs, a recently introduced method to effectively combine GWASs of many traits, we identified 16 genetic loci involved in various ear phenotypes, eight of which have not been previously associated with human ear features. Our findings suggest that ear morphology shares genetic determinants with other surface ectoderm-derived traits such as facial variation, mono eyebrow, and male pattern baldness. Our results enhance the genetic understanding of human ear morphology and shed light on the shared genetic contributors of different surface ectoderm-derived phenotypes. Additionally, gene editing experiments in mice have demonstrated that knocking out the newly ear-associated gene (Intu) and a previously ear-associated gene (Tbx15) causes deviating mouse ear morphology.
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Affiliation(s)
- Yi Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
| | - Ziyi Xiong
- Department of Genetic Identification, Erasmus MC, University Medical Center, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
| | - Manfei Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
| | - Pirro G. Hysi
- Department of Twin Research and Genetic Epidemiology, King’s College London, United Kingdom
| | - Yu Qian
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
- Beijing No.8 High School, Beijing, China
| | - Kaustubh Adhikari
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, United Kingdom
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, United Kingdom
| | - Jun Weng
- Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
| | - Sijie Wu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
| | - Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
- University of Chinese Academy of Sciences, China
| | - Rolando Gonzalez-Jose
- Instituto Patagonico de Ciencias Sociales y Humanas, Centro Nacional Patagonico, CONICET, Argentina
| | | | | | - Victor Acuna-Alonzo
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico
| | - Samuel Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Quimica, UNAM-Instituto Nacional de Medicina Genomica, Mexico
| | - Carla Gallo
- Laboratorios de Investigacion y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Peru
| | - Giovanni Poletti
- Laboratorios de Investigacion y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Peru
| | - Gabriel Bedoya
- GENMOL (Genetica Molecular), Universidad de Antioquia, Medellin, Colombia
| | | | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
| | - Jingze Tan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
| | - Ziyu Yuan
- Fudan-Taizhou Institute of Health Sciences, China
| | - Li Jin
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
- Fudan-Taizhou Institute of Health Sciences, China
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center, the Netherlands
| | - Tamar Nijsten
- Department of Dermatology, Erasmus MC, University Medical Center, the Netherlands
| | - Xiangyu Zhu
- Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, China
| | - Zhen Lei
- Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
| | - Andres Ruiz-Linares
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, United Kingdom
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, China
- Aix-Marseille Universite, CNRS, EFS, ADES, France
| | - Timothy D. Spector
- Department of Twin Research and Genetic Epidemiology, King’s College London, United Kingdom
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, China
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC, University Medical Center, the Netherlands
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, China
- Department of Genetic Identification, Erasmus MC, University Medical Center, the Netherlands
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15
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Li Q, Chen J, Faux P, Delgado ME, Bonfante B, Fuentes-Guajardo M, Mendoza-Revilla J, Chacón-Duque JC, Hurtado M, Villegas V, Granja V, Jaramillo C, Arias W, Barquera R, Everardo-Martínez P, Sánchez-Quinto M, Gómez-Valdés J, Villamil-Ramírez H, Silva de Cerqueira CC, Hünemeier T, Ramallo V, Wu S, Du S, Giardina A, Paria SS, Khokan MR, Gonzalez-José R, Schüler-Faccini L, Bortolini MC, Acuña-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Rojas W, Rothhammer F, Navarro N, Wang S, Adhikari K, Ruiz-Linares A. Automatic landmarking identifies new loci associated with face morphology and implicates Neanderthal introgression in human nasal shape. Commun Biol 2023; 6:481. [PMID: 37156940 PMCID: PMC10167347 DOI: 10.1038/s42003-023-04838-7] [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: 03/22/2022] [Accepted: 04/12/2023] [Indexed: 05/10/2023] Open
Abstract
We report a genome-wide association study of facial features in >6000 Latin Americans based on automatic landmarking of 2D portraits and testing for association with inter-landmark distances. We detected significant associations (P-value <5 × 10-8) at 42 genome regions, nine of which have been previously reported. In follow-up analyses, 26 of the 33 novel regions replicate in East Asians, Europeans, or Africans, and one mouse homologous region influences craniofacial morphology in mice. The novel region in 1q32.3 shows introgression from Neanderthals and we find that the introgressed tract increases nasal height (consistent with the differentiation between Neanderthals and modern humans). Novel regions include candidate genes and genome regulatory elements previously implicated in craniofacial development, and show preferential transcription in cranial neural crest cells. The automated approach used here should simplify the collection of large study samples from across the world, facilitating a cosmopolitan characterization of the genetics of facial features.
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Affiliation(s)
- Qing Li
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
| | - Jieyi Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Pierre Faux
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France
| | - Miguel Eduardo Delgado
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- División Antropología, Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, La Plata, República Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, CONICET, Buenos Aires, República Argentina
| | - Betty Bonfante
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France
| | - Macarena Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, Arica, 1000000, Chile
| | - Javier Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
- Unit of Human Evolutionary Genetics, Institut Pasteur, Paris, 75015, France
| | - J Camilo Chacón-Duque
- Division of Vertebrates and Anthropology, Department of Earth Sciences, Natural History Museum, London, SW7 5BD, UK
| | - Malena Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Valeria Villegas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Vanessa Granja
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Claudia Jaramillo
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - William Arias
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - Rodrigo Barquera
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History (MPI-SHH), Jena, 07745, Germany
| | - Paola Everardo-Martínez
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Mirsha Sánchez-Quinto
- Forensic Science, Faculty of Medicine, UNAM (Universidad Nacional Autónoma de México), Mexico City, 06320, Mexico
| | - Jorge Gómez-Valdés
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Hugo Villamil-Ramírez
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, 4510, Mexico
| | | | - Tábita Hünemeier
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, 05508-090, Brazil
| | - Virginia Ramallo
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - Sijie Wu
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Andrea Giardina
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Soumya Subhra Paria
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Mahfuzur Rahman Khokan
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom
| | - Rolando Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - Lavinia Schüler-Faccini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
| | - Maria-Cátira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, 90040-060, Brazil
| | - Victor Acuña-Alonzo
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, 14050, Mexico, 6600, Mexico
| | - Samuel Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, 4510, Mexico
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, 31, Perú
| | - Winston Rojas
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - Francisco Rothhammer
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica, Arica, 1000000, Chile
| | - Nicolas Navarro
- Biogéosciences, UMR 6282 CNRS, Université de Bourgogne, Dijon, 21000, France
- EPHE, PSL University, Paris, 75014, France
| | - Sijia Wang
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom.
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK.
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, 200438, China.
- Aix-Marseille Université, CNRS, EFS, ADES, Marseille, 13005, France.
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK.
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16
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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: 12] [Impact Index Per Article: 12.0] [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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17
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Fabi SG, Hernandez C, Montes JR, Cotofana S, Dayan S. Aesthetic considerations when treating the Latin American patient: Thriving in diversity international roundtable series. J Cosmet Dermatol 2023; 22:593-602. [PMID: 36468194 DOI: 10.1111/jocd.15516] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/10/2022] [Accepted: 11/03/2022] [Indexed: 12/07/2022]
Abstract
BACKGROUND The Hispanic/Latin American population is the fastest growing non-Caucasian group in the United States. Within this group, demand for aesthetic procedures is on the rise. High ethnic variability among these patients influences treatment approaches and patient priorities. Understanding these ethnic differences is central to providing optimal care. AIMS To discuss similarities and differences in anatomy and treatment preferences of Hispanic/Latin American patients both within the United States and internationally and explore how these differences may influence or inform aesthetic practices. PATIENTS/METHODS In support of clinicians who wish to serve a diverse patient population, a 6-part, international roundtable series focused on diversity in aesthetics was conducted from August 24, 2021 to May 16, 2022. In this roundtable, held in Medellin, Columbia, expert clinicians from across Latin America and the United States were invited to contribute and share best practices. RESULTS The results of the second roundtable in the series, the Latin American Patient, are described here. A special emphasis is placed on procedures that address the most commonly encountered concerns in these patients. CONCLUSIONS Hispanic and Latino patients represent a broad demographic with unique anatomical features, aesthetic preferences, and treatment priorities. Clinicians should consider these differences when treating this patient population.
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Affiliation(s)
| | | | - José Raúl Montes
- Ophthalmology Department, University of Puerto Rico School of Medicine, San Juan, Puerto Rico.,Jose Raul Montes Eyes & Facial Rejuvenation, San Juan, Puerto Rico
| | | | - Steve Dayan
- Division of Facial Plastic and Reconstructive Surgery, Department of Otolaryngology, University of Illinois at Chicago, Chicago, Illinois, USA
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18
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Advancement in Human Face Prediction Using DNA. Genes (Basel) 2023; 14:genes14010136. [PMID: 36672878 PMCID: PMC9858985 DOI: 10.3390/genes14010136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/15/2022] [Accepted: 12/21/2022] [Indexed: 01/05/2023] Open
Abstract
The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed.
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19
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Yang G, Chen Y, Li Q, Benítez D, Ramírez LM, Fuentes-Guajardo M, Hanihara T, Scott GR, Acuña Alonzo V, Gonzalez Jose R, Bortolini MC, Poletti G, Gallo C, Rothhammer F, Rojas W, Zanolli C, Adhikari K, Ruiz-Linares A, Delgado M. Dental size variation in admixed Latin Americans: Effects of age, sex and genomic ancestry. PLoS One 2023; 18:e0285264. [PMID: 37141293 PMCID: PMC10159210 DOI: 10.1371/journal.pone.0285264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 04/19/2023] [Indexed: 05/05/2023] Open
Abstract
Dental size variation in modern humans has been assessed from regional to worldwide scales, especially under microevolutionary and forensic contexts. Despite this, populations of mixed continental ancestry such as contemporary Latin Americans remain unexplored. In the present study we investigated a large Latin American sample from Colombia (N = 804) and obtained buccolingual and mesiodistal diameters and three indices for maxillary and mandibular teeth (except third molars). We evaluated the correlation between 28 dental measurements (and three indices) with age, sex and genomic ancestry (estimated using genome-wide SNP data). In addition, we explored correlation patterns between dental measurements and the biological affinities, based on these measurements, between two Latin American samples (Colombians and Mexicans) and three putative parental populations: Central and South Native Americans, western Europeans and western Africans through PCA and DFA. Our results indicate that Latin Americans have high dental size diversity, overlapping the variation exhibited by the parental populations. Several dental dimensions and indices have significant correlations with sex and age. Western Europeans presented closer biological affinities with Colombians, and the European genomic ancestry exhibited the highest correlations with tooth size. Correlations between tooth measurements reveal distinct dental modules, as well as a higher integration of postcanine dentition. The effects on dental size of age, sex and genomic ancestry is of relevance for forensic, biohistorical and microevolutionary studies in Latin Americans.
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Affiliation(s)
- Guangrui Yang
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, China
| | - Yingjie Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, China
| | - Qing Li
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, China
| | - Daniel Benítez
- Department of Anthropology, University of Kentucky, Lexington, Kentucky, United States of America
| | | | - Macarena Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, Arica, Chile
| | - Tsunehiko Hanihara
- Department of Anatomy, Kitasato University School of Medicine, Sagamihara, Japan
| | - G Richard Scott
- Department of Anthropology, University of Nevada Reno, Reno, Nevada, United States of America
| | - Victor Acuña Alonzo
- Molecular Genetics Laboratory, National School of Anthropology and History, Mexico City, Mexico
| | - Rolando Gonzalez Jose
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, Argentina
| | - Maria Catira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Perú
| | | | - Winston Rojas
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, Colombia
| | | | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, United Kingdom
| | - Andres Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, China
- Laboratory of Biocultural Anthropology, Law, Ethics, and Health (Centre National de la Recherche Scientifique and Etablissement Français du Sang, UMR-7268), Aix-Marseille University, Marseille, France
| | - Miguel Delgado
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, China
- División Antropología, Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, La Plata, República Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, CONICET, Buenos Aires, República Argentina
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20
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Maréchal L, Dumoncel J, Santos F, Astudillo Encina W, Evteev A, Prevost A, Toro-Ibacache V, Venter RG, Heuzé Y. New insights into the variability of upper airway morphology in modern humans. J Anat 2022; 242:781-795. [PMID: 36585765 PMCID: PMC10093156 DOI: 10.1111/joa.13813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 11/29/2022] [Accepted: 12/12/2022] [Indexed: 01/01/2023] Open
Abstract
The biological adaptation of the human lineage to its environment is a recurring question in paleoanthropology. Particularly, how eco-geographic factors (e.g., environmental temperature and humidity) have shaped upper airway morphology in hominins have been subject to continuing debate. Nasal shape is the result of many intertwined factors that include, but are not limited to, genetic drift, sexual selection, or adaptation to climate. A quantification of nasal airway (NA) morphological variation in modern human populations is crucial to better understand these multiple factors. In the present research, we study 195 in vivo CT scans of adult individuals collected in five different geographic areas (Chile, France, Cambodia, Russia, and South Africa). After segmentation of the nasal airway, we reconstruct 3D meshes that are analyzed with a landmark-free geometric morphometrics method based on surface deformation. Our results highlight subtle but statistically significant morphological differences between our five samples. The two morphologically closest groups are France and Russia, whose NAs are longer and narrower, with an important protrusion of the supero-anterior part. The Cambodian sample is the most morphologically distinct and clustered sample, with a mean NA that is wider and shorter. On the contrary, the Chilean sample form the most scattered cluster with the greatest intra-population variation. The South African sample is morphologically close to the Cambodian sample, but also partially overlaps the French and Russian variation. Interestingly, we record no correlation between NA volume and geographic groups, which raises the question of climate-related metabolic demands for oxygen consumption. The other factors of variation (sex and age) have no influence on the NA shape in our samples. However, NA volume varies significantly according both to sex and age: it is higher in males than in females and tends to increase with age. In contrast, we observe no effect of temperature or humidity on NA volume. Finally, we highlight the important influence of asymmetries related to nasal septum deviations in NA shape variation.
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Affiliation(s)
- Laura Maréchal
- Université de Bordeaux, CNRS, Ministère de la Culture, PACEA, Pessac, France
| | - Jean Dumoncel
- Université de Bordeaux, CNRS, Ministère de la Culture, PACEA, Pessac, France
| | - Frédéric Santos
- Université de Bordeaux, CNRS, Ministère de la Culture, PACEA, Pessac, France
| | | | - Andrej Evteev
- Anuchin Research Institute and Museum of Anthropology, Lomonosov Moscow State University, Moscow, Russia
| | - Alice Prevost
- Plastic and Maxillo-facial Surgery Department, University Hospital Center of Toulouse, Toulouse, France
| | - Viviana Toro-Ibacache
- Centro de Análisis Cuantitativo en Antropología Dental, Universidad de Chile, Santiago, Chile
| | - Rudolph G Venter
- Division of Orthopaedic Surgery, Department of Surgical Sciences, Tygerberg Hospital, Stellenbosch University, Cape Town, South Africa
| | - Yann Heuzé
- Université de Bordeaux, CNRS, Ministère de la Culture, PACEA, Pessac, France
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21
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Xiong Z, Gao X, Chen Y, Feng Z, Pan S, Lu H, Uitterlinden AG, Nijsten T, Ikram A, Rivadeneira F, Ghanbari M, Wang Y, Kayser M, Liu F. Combining genome-wide association studies highlight novel loci involved in human facial variation. Nat Commun 2022; 13:7832. [PMID: 36539420 PMCID: PMC9767941 DOI: 10.1038/s41467-022-35328-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022] Open
Abstract
Standard genome-wide association studies (GWASs) rely on analyzing a single trait at a time. However, many human phenotypes are complex and composed by multiple correlated traits. Here we introduce C-GWAS, a method for combining GWAS summary statistics of multiple potentially correlated traits. Extensive computer simulations demonstrated increased statistical power of C-GWAS compared to the minimal p-values of multiple single-trait GWASs (MinGWAS) and the current state-of-the-art method for combining single-trait GWASs (MTAG). Applying C-GWAS to a meta-analysis dataset of 78 single trait facial GWASs from 10,115 Europeans identified 56 study-wide suggestively significant loci with multi-trait effects on facial morphology of which 17 are novel loci. Using data from additional 13,622 European and Asian samples, 46 (82%) loci, including 9 (53%) novel loci, were replicated at nominal significance with consistent allele effects. Functional analyses further strengthen the reliability of our C-GWAS findings. Our study introduces the C-GWAS method and makes it available as computationally efficient open-source R package for widespread future use. Our work also provides insights into the genetic architecture of human facial appearance.
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Affiliation(s)
- Ziyi Xiong
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Xingjian Gao
- grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China ,grid.440259.e0000 0001 0115 7868National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing, Jiangsu China
| | - Yan Chen
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Zhanying Feng
- grid.9227.e0000000119573309CEMS, NCMIS, HCMS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
| | - Siyu Pan
- grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Haojie Lu
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Andre G. Uitterlinden
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Tamar Nijsten
- grid.5645.2000000040459992XDepartment of Dermatology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Arfan Ikram
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Fernando Rivadeneira
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.5645.2000000040459992XDepartment of Oral and Maxillofacial Surgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Yong Wang
- grid.9227.e0000000119573309CEMS, NCMIS, HCMS, MDIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
| | - Manfred Kayser
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Fan Liu
- grid.5645.2000000040459992XDepartment of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands ,grid.9227.e0000000119573309CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
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22
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Wu W, Kong X, Jia Y, Jia Y, Ou W, Dai C, Li G, Gao R. An overview of PAX1: Expression, function and regulation in development and diseases. Front Cell Dev Biol 2022; 10:1051102. [PMID: 36393845 PMCID: PMC9649799 DOI: 10.3389/fcell.2022.1051102] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 10/18/2022] [Indexed: 11/06/2023] Open
Abstract
Transcription factors play multifaceted roles in embryonic development and diseases. PAX1, a paired-box transcription factor, has been elucidated to play key roles in multiple tissues during embryonic development by extensive studies. Recently, an emerging role of PAX1 in cancers was clarified. Herein, we summarize the expression and functions of PAX1 in skeletal system and thymus development, as well as cancer biology and outline its cellular and molecular modes of action and the association of PAX1 mutation or dysregulation with human diseases, thus providing insights for the molecular basis of congenital diseases and cancers.
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Affiliation(s)
- Weiyin Wu
- Institute of Cardiovascular Diseases, Xiamen Cardiovascular Hospital, School of medicine, Xiamen University, Xiamen, China
| | - Xiangjun Kong
- Department of Pharmacy, Xiang'an Hospital of Xiamen University, School of medicine, Xiamen University, Xiamen, China
| | - Yanhan Jia
- Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yihui Jia
- Institute of Cardiovascular Diseases, Xiamen Cardiovascular Hospital, School of medicine, Xiamen University, Xiamen, China
| | - Weimei Ou
- Institute of Cardiovascular Diseases, Xiamen Cardiovascular Hospital, School of medicine, Xiamen University, Xiamen, China
| | - Cuilian Dai
- Institute of Cardiovascular Diseases, Xiamen Cardiovascular Hospital, School of medicine, Xiamen University, Xiamen, China
| | - Gang Li
- Institute of Cardiovascular Diseases, Xiamen Cardiovascular Hospital, School of medicine, Xiamen University, Xiamen, China
| | - Rui Gao
- Institute of Cardiovascular Diseases, Xiamen Cardiovascular Hospital, School of medicine, Xiamen University, Xiamen, China
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23
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Naqvi S, Hoskens H, Wilke F, Weinberg SM, Shaffer JR, Walsh S, Shriver MD, Wysocka J, Claes P. Decoding the Human Face: Progress and Challenges in Understanding the Genetics of Craniofacial Morphology. Annu Rev Genomics Hum Genet 2022; 23:383-412. [PMID: 35483406 PMCID: PMC9482780 DOI: 10.1146/annurev-genom-120121-102607] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Variations in the form of the human face, which plays a role in our individual identities and societal interactions, have fascinated scientists and artists alike. Here, we review our current understanding of the genetics underlying variation in craniofacial morphology and disease-associated dysmorphology, synthesizing decades of progress on Mendelian syndromes in addition to more recent results from genome-wide association studies of human facial shape and disease risk. We also discuss the various approaches used to phenotype and quantify facial shape, which are of particular importance due to the complex, multipartite nature of the craniofacial form. We close by discussing how experimental studies have contributed and will further contribute to our understanding of human genetic variation and then proposing future directions and applications for the field.
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Affiliation(s)
- Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California, USA; ,
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Hanne Hoskens
- Center for Processing Speech and Images, Department of Electrical Engineering, KU Leuven, Leuven, Belgium; ,
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
| | - Franziska Wilke
- Department of Biology, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, USA; ,
| | - Seth M Weinberg
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; ,
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Department of Anthropology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - John R Shaffer
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; ,
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Susan Walsh
- Department of Biology, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, USA; ,
| | - Mark D Shriver
- Department of Anthropology, The Pennsylvania State University, University Park, Pennsylvania, USA;
| | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California, USA; ,
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, California, USA
| | - Peter Claes
- Center for Processing Speech and Images, Department of Electrical Engineering, KU Leuven, Leuven, Belgium; ,
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Murdoch Children's Research Institute, Melbourne, Victoria, Australia
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24
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Joshi RS, Rigau M, García-Prieto CA, Castro de Moura M, Piñeyro D, Moran S, Davalos V, Carrión P, Ferrando-Bernal M, Olalde I, Lalueza-Fox C, Navarro A, Fernández-Tena C, Aspandi D, Sukno FM, Binefa X, Valencia A, Esteller M. Look-alike humans identified by facial recognition algorithms show genetic similarities. Cell Rep 2022; 40:111257. [PMID: 36001980 DOI: 10.1016/j.celrep.2022.111257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 06/05/2022] [Accepted: 08/01/2022] [Indexed: 11/03/2022] Open
Abstract
The human face is one of the most visible features of our unique identity as individuals. Interestingly, monozygotic twins share almost identical facial traits and the same DNA sequence but could exhibit differences in other biometrical parameters. The expansion of the world wide web and the possibility to exchange pictures of humans across the planet has increased the number of people identified online as virtual twins or doubles that are not family related. Herein, we have characterized in detail a set of "look-alike" humans, defined by facial recognition algorithms, for their multiomics landscape. We report that these individuals share similar genotypes and differ in their DNA methylation and microbiome landscape. These results not only provide insights about the genetics that determine our face but also might have implications for the establishment of other human anthropometric properties and even personality characteristics.
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Affiliation(s)
- Ricky S Joshi
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, 08916 Barcelona, Spain
| | - Maria Rigau
- Barcelona Supercomputing Center (BSC), 08034 Barcelona, Spain
| | - Carlos A García-Prieto
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, 08916 Barcelona, Spain; Barcelona Supercomputing Center (BSC), 08034 Barcelona, Spain
| | | | - David Piñeyro
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, 08916 Barcelona, Spain; Centro de Investigacion Biomedica en Red Cancer (CIBERONC), 28029 Madrid, Spain
| | - Sebastian Moran
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, 08916 Barcelona, Spain
| | - Veronica Davalos
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, 08916 Barcelona, Spain
| | - Pablo Carrión
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Spain
| | - Manuel Ferrando-Bernal
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Spain
| | - Iñigo Olalde
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Spain
| | - Carles Lalueza-Fox
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Spain
| | - Arcadi Navarro
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003 Barcelona, Spain; Centre for Genomic Regulation (CNAG-CRG), 08003 Barcelona, Catalonia, Spain; Institucio Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain
| | | | - Decky Aspandi
- Departament de Tecnologies de la Informació i les Comunicaciones (DTIC), Universitat Pompeu Fabra (UPF), 08018 Barcelona, Spain
| | - Federico M Sukno
- Departament de Tecnologies de la Informació i les Comunicaciones (DTIC), Universitat Pompeu Fabra (UPF), 08018 Barcelona, Spain
| | - Xavier Binefa
- Departament de Tecnologies de la Informació i les Comunicaciones (DTIC), Universitat Pompeu Fabra (UPF), 08018 Barcelona, Spain
| | - Alfonso Valencia
- Barcelona Supercomputing Center (BSC), 08034 Barcelona, Spain; Institucio Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain
| | - Manel Esteller
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, 08916 Barcelona, Spain; Centro de Investigacion Biomedica en Red Cancer (CIBERONC), 28029 Madrid, Spain; Institucio Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain; Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona (UB), L'Hospitalet, 08907 Barcelona, Spain.
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25
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Trendafilova T, Adhikari K, Schmid AB, Patel R, Polgár E, Chisholm KI, Middleton SJ, Boyle K, Dickie AC, Semizoglou E, Perez-Sanchez J, Bell AM, Ramirez-Aristeguieta LM, Khoury S, Ivanov A, Wildner H, Ferris E, Chacón-Duque JC, Sokolow S, Saad Boghdady MA, Herchuelz A, Faux P, Poletti G, Gallo C, Rothhammer F, Bedoya G, Zeilhofer HU, Diatchenko L, McMahon SB, Todd AJ, Dickenson AH, Ruiz-Linares A, Bennett DL. Sodium-calcium exchanger-3 regulates pain "wind-up": From human psychophysics to spinal mechanisms. Neuron 2022; 110:2571-2587.e13. [PMID: 35705078 PMCID: PMC7613464 DOI: 10.1016/j.neuron.2022.05.017] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 03/31/2022] [Accepted: 05/16/2022] [Indexed: 11/17/2022]
Abstract
Repeated application of noxious stimuli leads to a progressively increased pain perception; this temporal summation is enhanced in and predictive of clinical pain disorders. Its electrophysiological correlate is "wind-up," in which dorsal horn spinal neurons increase their response to repeated nociceptor stimulation. To understand the genetic basis of temporal summation, we undertook a GWAS of wind-up in healthy human volunteers and found significant association with SLC8A3 encoding sodium-calcium exchanger type 3 (NCX3). NCX3 was expressed in mouse dorsal horn neurons, and mice lacking NCX3 showed normal, acute pain but hypersensitivity to the second phase of the formalin test and chronic constriction injury. Dorsal horn neurons lacking NCX3 showed increased intracellular calcium following repetitive stimulation, slowed calcium clearance, and increased wind-up. Moreover, virally mediated enhanced spinal expression of NCX3 reduced central sensitization. Our study highlights Ca2+ efflux as a pathway underlying temporal summation and persistent pain, which may be amenable to therapeutic targeting.
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Affiliation(s)
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, UK; Department of Genetics, Evolution and Environment, University College London, London, UK; Department of Cell and Developmental Biology, University College London, London, UK
| | - Annina B Schmid
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Ryan Patel
- Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Erika Polgár
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Kim I Chisholm
- Wolfson Centre for Age-Related Diseases, King's College London, London, UK
| | - Steven J Middleton
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Kieran Boyle
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Allen C Dickie
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | | | | | - Andrew M Bell
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | | | - Samar Khoury
- McGill University and Genome Quebec Innovation Centre, Montreal, QC, Canada
| | - Aleksandar Ivanov
- Department of Physiology Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Hendrik Wildner
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Eleanor Ferris
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Juan-Camilo Chacón-Duque
- Department of Genetics, Evolution and Environment, University College London, London, UK; Centre for Palaeogenetics, Stockholm, Sweden; Department of Archaeology and Classical Studies, Stockholm University, Stockholm, Sweden
| | - Sophie Sokolow
- Laboratoire de Pharmacodynamie et de Thérapeutique Faculté de Médecine Université Libre de Bruxelles, Brussels, Belgium; School of Nursing, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - André Herchuelz
- Laboratoire de Pharmacodynamie et de Thérapeutique Faculté de Médecine Université Libre de Bruxelles, Brussels, Belgium
| | - Pierre Faux
- CNRS, EFS, ADES, Aix-Marseille Université, Marseille, France
| | - Giovanni Poletti
- Unidad de Neurobiologia Molecular y Genética, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Carla Gallo
- Unidad de Neurobiologia Molecular y Genética, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | - Gabriel Bedoya
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellin, Colombia
| | - Hanns Ulrich Zeilhofer
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland; Institute of Pharmaceutical Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland
| | - Luda Diatchenko
- McGill University and Genome Quebec Innovation Centre, Montreal, QC, Canada
| | - Stephen B McMahon
- Wolfson Centre for Age-Related Diseases, King's College London, London, UK
| | - Andrew J Todd
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Anthony H Dickenson
- Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Andres Ruiz-Linares
- Department of Genetics, Evolution and Environment, University College London, London, UK; CNRS, EFS, ADES, Aix-Marseille Université, Marseille, France; Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, China.
| | - David L Bennett
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK.
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26
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Zhang X, Ji X, Li C, Yang T, Huang J, Zhao Y, Wu Y, Ma S, Pang Y, Huang Y, He Y, Su B. A Late Pleistocene human genome from Southwest China. Curr Biol 2022; 32:3095-3109.e5. [PMID: 35839766 DOI: 10.1016/j.cub.2022.06.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 05/27/2022] [Accepted: 06/08/2022] [Indexed: 11/25/2022]
Abstract
Southern East Asia is the dispersal center regarding the prehistoric settlement and migrations of modern humans in Asia-Pacific regions. However, the settlement pattern and population structure of paleolithic humans in this region remain elusive, and ancient DNA can provide direct information. Here, we sequenced the genome of a Late Pleistocene hominin (MZR), dated ∼14.0 thousand years ago from Red Deer Cave located in Southwest China, which was previously reported possessing mosaic features of modern and archaic hominins. MZR is the first Late Pleistocene genome from southern East Asia. Our results indicate that MZR is a modern human who represents an early diversified lineage in East Asia. The mtDNA of MZR belongs to an extinct basal lineage of the M9 haplogroup, reflecting a rich matrilineal diversity in southern East Asia during the Late Pleistocene. Combined with the published data, we detected clear genetic stratification in ancient southern populations of East/Southeast Asia and some degree of south-versus-north divergency during the Late Pleistocene, and MZR was identified as a southern East Asian who exhibits genetic continuity to present day populations. Markedly, MZR is linked deeply to the East Asian ancestry that contributed to First Americans.
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Affiliation(s)
- Xiaoming Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650201, China
| | - Xueping Ji
- Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China; Department of Paleoanthropology, Yunnan Institute of Cultural Relics and Archaeology, Kunming 650118, China.
| | - Chunmei Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650201, China
| | - Tingyu Yang
- Biomedical Pioneering Innovation Center (BIOPIC) and Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing 100871, China
| | - Jiahui Huang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yinhui Zhao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yun Wu
- Department of Paleoanthropology, Yunnan Institute of Cultural Relics and Archaeology, Kunming 650118, China; School of History, Wuhan University, Wuhan 430072, China; Archaeological Institute for Yangtze Civilization, Wuhan University, Wuhan 430072, China
| | - Shiwu Ma
- Mengzi Institute of Cultural Relics, Mengzi, Yunnan Province 661100, China
| | - Yuhong Pang
- Biomedical Pioneering Innovation Center (BIOPIC) and Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing 100871, China
| | - Yanyi Huang
- Biomedical Pioneering Innovation Center (BIOPIC) and Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing 100871, China
| | - Yaoxi He
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650201, China.
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650201, China.
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27
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Liang Y, Liu H, Gao Z, Li Q, Li G, Zhao J, Wang X. Ocular phenotype related SNP analysis in Southern Han Chinese population from Guangdong province. Gene 2022; 826:146458. [PMID: 35358651 DOI: 10.1016/j.gene.2022.146458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/23/2022] [Accepted: 03/25/2022] [Indexed: 11/15/2022]
Abstract
Ocular phenotype is recognizable among Asians, including eyelid fold, fissure inclination, and canthal index. Here we screened 27 facial phenotype-associated SNPs and reported a preliminary study in 246 Chinese individuals of Han origin in Guangdong province. Results showed that rs17760296 could explain 6.2% of the eyelid fold variation and double eyelids were more likely to appear when one's genotype was TT. With respect to the canthal index, rs4791774 and rs642961 were significantly associated with it. However, no individual SNP was associated with fissure inclination. We further constructed two models to predict eyelid fold and canthal index and evaluated them with receiver operating characteristic (ROC) curves and support vector machine (SVM) regression, respectively. The models showed a moderate-to-high predictive capacity (AUC = 0.75, sensitivity = 76%, and specificity = 72%) for the eyelid fold while a mild performance (R2 = 0.1074, MSE = 0.0005, P-value = 0.024) for the canthal index. In conclusion, our study indicates that rs17760296 could be selected into the facial phenotype prediction system for the Southern Han Chinese population. More SNPs are encouraged to improve the prediction accuracy of the canthal index besides rs4791774 and rs642961.
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Affiliation(s)
- Yimeng Liang
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University & Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan 2nd Road 74, Yuexiu District, Guangzhou, PR China
| | - Heming Liu
- Department of Physiology, Zhongshan School of Medicine, Sun Yat-Sen University, Zhongshan 2nd Road 74, Yuexiu District, Guangzhou, PR China
| | - Zhenjie Gao
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University & Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan 2nd Road 74, Yuexiu District, Guangzhou, PR China
| | - Qi Li
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University & Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan 2nd Road 74, Yuexiu District, Guangzhou, PR China
| | - Guoran Li
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University & Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan 2nd Road 74, Yuexiu District, Guangzhou, PR China
| | - Jian Zhao
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University & Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan 2nd Road 74, Yuexiu District, Guangzhou, PR China; Guangzhou Forensic Science Institute & Key Laboratory of Forensic Pathology, Ministry of Public Security, Baiyun Avenue 1708, Baiyun District, Guangzhou, PR China.
| | - Xiaoguang Wang
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University & Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan 2nd Road 74, Yuexiu District, Guangzhou, PR China.
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28
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Fernández-Rhodes L, Graff M, Buchanan VL, Justice AE, Highland HM, Guo X, Zhu W, Chen HH, Young KL, Adhikari K, Palmer ND, Below JE, Bradfield J, Pereira AC, Glover L, Kim D, Lilly AG, Shrestha P, Thomas AG, Zhang X, Chen M, Chiang CW, Pulit S, Horimoto A, Krieger JE, Guindo-Martínez M, Preuss M, Schumann C, Smit RA, Torres-Mejía G, Acuña-Alonzo V, Bedoya G, Bortolini MC, Canizales-Quinteros S, Gallo C, González-José R, Poletti G, Rothhammer F, Hakonarson H, Igo R, Adler SG, Iyengar SK, Nicholas SB, Gogarten SM, Isasi CR, Papnicolaou G, Stilp AM, Qi Q, Kho M, Smith JA, Langefeld CD, Wagenknecht L, Mckean-Cowdin R, Gao XR, Nousome D, Conti DV, Feng Y, Allison MA, Arzumanyan Z, Buchanan TA, Ida Chen YD, Genter PM, Goodarzi MO, Hai Y, Hsueh W, Ipp E, Kandeel FR, Lam K, Li X, Nadler JL, Raffel LJ, Roll K, Sandow K, Tan J, Taylor KD, Xiang AH, Yao J, Audirac-Chalifour A, de Jesus Peralta Romero J, Hartwig F, Horta B, Blangero J, Curran JE, Duggirala R, Lehman DE, Puppala S, Fejerman L, John EM, Aguilar-Salinas C, Burtt NP, Florez JC, García-Ortíz H, González-Villalpando C, Mercader J, Orozco L, Tusié-Luna T, Blanco E, Gahagan S, Cox NJ, Hanis C, Butte NF, Cole SA, Comuzzie AG, Voruganti VS, Rohde R, Wang Y, Sofer T, Ziv E, Grant SF, Ruiz-Linares A, Rotter JI, Haiman CA, Parra EJ, Cruz M, Loos RJ, North KE. Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits-The Hispanic/Latino Anthropometry Consortium. HGG ADVANCES 2022; 3:100099. [PMID: 35399580 PMCID: PMC8990175 DOI: 10.1016/j.xhgg.2022.100099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 03/06/2022] [Indexed: 02/05/2023] Open
Abstract
Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite their notable anthropometric variability, ancestry proportions, and high burden of growth stunting and overweight/obesity. To address this knowledge gap, we analyzed densely imputed genetic data in a sample of Hispanic/Latino adults to identify and fine-map genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (stage 1, n = 59,771) and generalized our findings in 9 additional studies (stage 2, n = 10,538). We conducted a trans-ancestral GWAS with summary statistics from HISLA stage 1 and existing consortia of European and African ancestries. In our HISLA stage 1 + 2 analyses, we discovered one BMI locus, as well as two BMI signals and another height signal each within established anthropometric loci. In our trans-ancestral meta-analysis, we discovered three BMI loci, one height locus, and one WHRadjBMI locus. We also identified 3 secondary signals for BMI, 28 for height, and 2 for WHRadjBMI in established loci. We show that 336 known BMI, 1,177 known height, and 143 known WHRadjBMI (combined) SNPs demonstrated suggestive transferability (nominal significance and effect estimate directional consistency) in Hispanic/Latino adults. Of these, 36 BMI, 124 height, and 11 WHRadjBMI SNPs were significant after trait-specific Bonferroni correction. Trans-ancestral meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our findings demonstrate that future studies may also benefit from leveraging diverse ancestries and differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.
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Affiliation(s)
- Lindsay Fernández-Rhodes
- Department of Biobehavioral Health, Pennsylvania State University, 219 Biobehavioral Health Building, University Park, PA 16802, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Victoria L. Buchanan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Anne E. Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biomedical and Translational Informatics, Geisinger Health System, Danville, PA 17822, USA
| | - Heather M. Highland
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Wanying Zhu
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Hung-Hsin Chen
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Kristin L. Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, MK7 6AA Milton Keynes, UK
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Jennifer E. Below
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jonathan Bradfield
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Alexandre C. Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - LáShauntá Glover
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Daeeun Kim
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Adam G. Lilly
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Poojan Shrestha
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Alvin G. Thomas
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Xinruo Zhang
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Minhui Chen
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Charleston W.K. Chiang
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90007, USA
| | - Sara Pulit
- Vertex Pharmaceuticals, W2 6BD Oxford, UK
| | - Andrea Horimoto
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - Jose E. Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of São Paulo, São Paulo 05508-220, Brazil
| | - Marta Guindo-Martínez
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- The Novo Nordisk Center for Basic Metabolic Research, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Michael Preuss
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Claudia Schumann
- Hasso Plattner Institute, University of Potsdam, Digital Health Center, 14482 Potsdam, Germany
| | - Roelof A.J. Smit
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gabriela Torres-Mejía
- Department of Research in Cardiovascular Diseases, Diabetes Mellitus, and Cancer, Population Health Research Center, National Institute of Public Health, Cuernavaca, Morelos 62100, Mexico
| | | | - Gabriel Bedoya
- Molecular Genetics Investigation Group, University of Antioquia, Medellín 1226, Colombia
| | - Maria-Cátira Bortolini
- Department of Genetics, Federal University of Rio Grande do Sul, Porto Alegre 90040-060, Brazil
| | - Samuel Canizales-Quinteros
- Population Genomics Applied to Health Unit, The National Institute of Genomic Medicine and the Faculty of Chemistry at the National Autonomous University of Mexico, Mexico City 04510, Mexico
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | - Rolando González-José
- Patagonian Institute of the Social and Human Sciences, Patagonian National Center, Puerto Madryn U9120, Argentina
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
| | | | - Hakon Hakonarson
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Robert Igo
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Sharon G. Adler
- Division of Nephrology and Hypertension, Harbor-University of California Los Angeles Medical Center, Torrance, CA 90502, USA
| | - Sudha K. Iyengar
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Susanne B. Nicholas
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, CA 90095, USA
| | | | - Carmen R. Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | | | - Adrienne M. Stilp
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Carl D. Langefeld
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Lynne Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27101, USA
| | - Roberta Mckean-Cowdin
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Xiaoyi Raymond Gao
- Department of Ophthalmology and Visual Sciences, Department of Biomedical Informatics, Division of Human Genetics, The Ohio State University, Columbus, OH 43210, USA
| | - Darryl Nousome
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - David V. Conti
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Ye Feng
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Matthew A. Allison
- Department of Family Medicine, University of California, San Diego, CA 92161, USA
| | - Zorayr Arzumanyan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Thomas A. Buchanan
- Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Pauline M. Genter
- Department of Medicine, Division of Endocrinology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Yang Hai
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Willa Hsueh
- Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA
| | - Eli Ipp
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, CA 90095, USA
- Department of Medicine, Division of Endocrinology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Fouad R. Kandeel
- Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Kelvin Lam
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Xiaohui Li
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Jerry L. Nadler
- Department of Pharmacology at New York Medical College School of Medicine, Valhalla, NY 10595, USA
| | - Leslie J. Raffel
- Division of Genetic and Genomic Medicine, Department of Pediatrics, University of California, Irvine, CA 92697, USA
| | - Kathryn Roll
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Kevin Sandow
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Anny H. Xiang
- Research and Evaluation Branch, Kaiser Permanente of Southern California, Pasadena, CA 91101, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Astride Audirac-Chalifour
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Jose de Jesus Peralta Romero
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Fernando Hartwig
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas 96010-610, Brazil
| | - Bernando Horta
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas 96010-610, Brazil
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville and Edinburg, TX 78520 and 78539, USA
| | - Donna E. Lehman
- Department of Medicine, School of Medicine, University of Texas Health San Antonio, San Antonio, TX 78229, USA
| | - Sobha Puppala
- Department of Internal Medicine, Section of Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27109, USA
| | - Laura Fejerman
- Department of Public Health Sciences, School of Medicine, and the Comprehensive Cancer Center, University of California Davis, Davis, CA 95616, USA
| | - Esther M. John
- Departments of Epidemiology & Population Health and Medicine-Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Carlos Aguilar-Salinas
- Division of Nutrition, Salvador Zubirán National Institute of Health Sciences and Nutrition, Mexico City 14080, Mexico
| | - Noël P. Burtt
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
| | - Jose C. Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Humberto García-Ortíz
- Laboratory of Immunogenomics and Metabolic Diseases, National Institute of Genomic Medicine, Mexico City 14610, Mexico
| | - Clicerio González-Villalpando
- Center for Diabetes Studies, Research Unit for Diabetes and Cardiovascular Risk, Center for Population Health Studies, National Institute of Public Health, Mexico City 14080, Mexico
| | - Josep Mercader
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Lorena Orozco
- Laboratory of Immunogenomics and Metabolic Diseases, National Institute of Genomic Medicine, Mexico City 14610, Mexico
| | - Teresa Tusié-Luna
- Molecular Biology and Medical Genomics Unity, Institute of Biomedical Research, The National Autonomous University of Mexico and the Salvador Zubirán National Institute of Health Sciences and Nutrition, Mexico City 14080, Mexico
| | - Estela Blanco
- Center for Community Health, Division of Academic General Pediatrics, University of California at San Diego, San Diego, CA 92093, USA
| | - Sheila Gahagan
- Center for Community Health, Division of Academic General Pediatrics, University of California at San Diego, San Diego, CA 92093, USA
| | - Nancy J. Cox
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Craig Hanis
- University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Nancy F. Butte
- United States Department of Agriculture, Agricultural Research Service, The Children’s Nutrition Research Center, and the Department Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Shelley A. Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | | | - V. Saroja Voruganti
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
| | - Rebecca Rohde
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yujie Wang
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tamar Sofer
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Elad Ziv
- Division of General Internal Medicine, Department of Medicine, Helen Diller Family Comprehensive Cancer Center, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94115, USA
| | - Struan F.A. Grant
- Center for Applied Genomics, Division of Human Genetics, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Andres Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai 200438, China
- Department of Genetics, Evolution and Environment, and Genetics Institute of the University College London, London WC1E 6BT, UK
- Laboratory of Biocultural Anthropology, Law, Ethics, and Health, Aix-Marseille University, Marseille 13385, France
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502 USA
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Esteban J. Parra
- Department of Anthropology, University of Toronto- Mississauga, Mississauga, ON L5L 1C6, Canada
| | - Miguel Cruz
- Medical Research Unit in Biochemistry, Specialty Hospital, National Medical Center of the Twenty-First Century, Mexican Institute of Social Security, Mexico City 06725, Mexico
| | - Ruth J.F. Loos
- The Charles Bronfman Institutes for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kari E. North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
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29
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Zhang M, Wu S, Du S, Qian W, Chen J, Qiao L, Yang Y, Tan J, Yuan Z, Peng Q, Liu Y, Navarro N, Tang K, Ruiz-Linares A, Wang J, Claes P, Jin L, Li J, Wang S. Genetic variants underlying differences in facial morphology in East Asian and European populations. Nat Genet 2022; 54:403-411. [PMID: 35393595 DOI: 10.1038/s41588-022-01038-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 01/19/2022] [Accepted: 02/25/2022] [Indexed: 11/09/2022]
Abstract
Facial morphology-a conspicuous feature of human appearance-is highly heritable. Previous studies on the genetic basis of facial morphology were performed mainly in European-ancestry cohorts (EUR). Applying a data-driven phenotyping and multivariate genome-wide scanning protocol to a large collection of three-dimensional facial images of individuals with East Asian ancestry (EAS), we identified 244 variants in 166 loci (62 new) associated with typical-range facial variation. A newly proposed polygenic shape analysis indicates that the effects of the variants on facial shape in EAS can be generalized to EUR. Based on this, we further identified 13 variants related to differences between facial shape in EUR and EAS populations. Evolutionary analyses suggest that the difference in nose shape between EUR and EAS populations is caused by a directional selection, due mainly to a local adaptation in Europeans. Our results illustrate the underlying genetic basis for facial differences across populations.
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Affiliation(s)
- Manfei Zhang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.,CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Computer Science, Fudan University, Shanghai, China
| | - Sijie Wu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.,CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Wei Qian
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.,CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Computer Science, Fudan University, Shanghai, China
| | - Jieyi Chen
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Lu Qiao
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yajun Yang
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Jingze Tan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Ziyu Yuan
- Fudan-Taizhou Institute of Health Sciences, Taizhou, China
| | - Qianqian Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yu Liu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Nicolas Navarro
- Biogéosciences, UMR 6282 CNRS-EPHE, Université Bourgogne Franche-Comté, Dijon, France.,Ecole Pratique des Hautes Etudes, PSL University, Paris, France
| | - Kun Tang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Andrés Ruiz-Linares
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.,Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.,Aix-Marseille Université, CNRS, EFS, ADES, Marseille, France.,Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, UK
| | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.,Fudan-Taizhou Institute of Health Sciences, Taizhou, China
| | - Peter Claes
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium.,Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.,Department of Human Genetics, KU Leuven, Leuven, Belgium.,Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China. .,CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. .,Fudan-Taizhou Institute of Health Sciences, Taizhou, China.
| | - Jiarui Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. .,Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium. .,Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.
| | - Sijia Wang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China. .,CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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30
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Pan Y, Zhang C, Lu Y, Ning Z, Lu D, Gao Y, Zhao X, Yang Y, Guan Y, Mamatyusupu D, Xu S. Genomic diversity and post-admixture adaptation in the Uyghurs. Natl Sci Rev 2022; 9:nwab124. [PMID: 35350227 PMCID: PMC8953455 DOI: 10.1093/nsr/nwab124] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 05/30/2021] [Accepted: 06/07/2021] [Indexed: 11/17/2022] Open
Abstract
Population admixture results in genome-wide combinations of genetic variants derived from different ancestral populations of distinct ancestry, thus providing a unique opportunity for understanding the genetic determinants of phenotypic variation in humans. Here, we used whole-genome sequencing of 92 individuals with high coverage (30–60×) to systematically investigate genomic diversity in the Uyghurs living in Xinjiang, China (XJU), an admixed population of both European-like and East-Asian-like ancestry. The XJU population shows greater genetic diversity, especially a higher proportion of rare variants, compared with their ancestral source populations, corresponding to greater phenotypic diversity of XJU. Admixture-induced functional variants in EDAR were associated with the diversity of facial morphology in XJU. Interestingly, the interaction of functional variants between SLC24A5 and OCA2 likely influences the diversity of skin pigmentation. Notably, selection has seemingly been relaxed or canceled in several genes with significantly biased ancestry, such as HERC2–OCA2. Moreover, signatures of post-admixture adaptation in XJU were identified, including genes related to metabolism (e.g. CYP2D6), digestion (e.g. COL11A1), olfactory perception (e.g. ANO2) and immunity (e.g. HLA). Our results demonstrated population admixture as a driving force, locally or globally, in shaping human genetic and phenotypic diversity as well as in adaptive evolution.
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Affiliation(s)
- Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Chao Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University , Shanghai 200438, China
| | - Zhilin Ning
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Dongsheng Lu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
| | - Yang Gao
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
- School of Life Science and Technology, ShanghaiTech University , Shanghai 201210, China
| | - Xiaohan Zhao
- Human Phenome Institute, Fudan University , Shanghai 201203, China
| | - Yajun Yang
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University , Shanghai 200438, China
| | - Yaqun Guan
- Department of Biochemistry and Molecular Biology, Preclinical Medicine College, Xinjiang Medical University , Urumqi 830011, China
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University , Urumqi 830046, China
| | - Shuhua Xu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China
- State Key Laboratory of Genetic Engineering and Ministry of Education (MOE) Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University , Shanghai 200438, China
- School of Life Science and Technology, ShanghaiTech University , Shanghai 201210, China
- Human Phenome Institute, Fudan University , Shanghai 201203, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences , Kunming 650223, China
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University , Zhengzhou 450052, China
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31
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Qian W, Zhang M, Wan K, Xie Y, Du S, Li J, Mu X, Qiu J, Xue X, Zhuang X, Wu Y, Liu F, Wang S. Genetic evidence for facial variation being a composite phenotype of cranial variation and facial soft tissue thickness. J Genet Genomics 2022; 49:934-942. [DOI: 10.1016/j.jgg.2022.02.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 02/17/2022] [Accepted: 02/20/2022] [Indexed: 10/18/2022]
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32
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Ajmal M, Alshannaq AF, Moon H, Choi D, Akram A, Nayyar BG, Gibbons JG, Yu JH. Characterization of 260 Isolates of Aspergillus Section Flavi Obtained from Sesame Seeds in Punjab, Pakistan. Toxins (Basel) 2022; 14:toxins14020117. [PMID: 35202144 PMCID: PMC8876583 DOI: 10.3390/toxins14020117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 01/31/2022] [Accepted: 02/02/2022] [Indexed: 11/16/2022] Open
Abstract
Sesame Sesamum indicum L. is a major oil-based seed crop that has been widely cultivated and consumed in Pakistan. Unfortunately, sesame is highly prone to Aspergillus fungal growth in the field, and under inappropriate storage conditions can become contaminated with aflatoxins, the most potent carcinogen found in nature. Here, we have isolated a high number of Aspergillus isolates from sesame seeds in fresh and stored conditions obtained from rainfed and irrigated zones of Punjab, Pakistan, and characterized them for aflatoxigenic potentials. Using morphological identification techniques, 260 isolates were grouped as potential Aspergillus section Flavi, with 126 and 134 originating from the rainfed and irrigated zones, respectively. Out of 260 in total, 188 isolates were confirmed to produce aflatoxins. There were no significant differences in potential aflatoxigenic isolates with respect to the rainfed and irrigated zones. However, the number of potential aflatoxigenic isolates was significantly higher (p < 0.05) in stored samples than that of those from fresh sesame seeds in the rainfed and irrigated zone. Whole genome sequencing and comparative analyses of 12 select isolates have revealed that one of the A. flavus isolates, which produced very low aflatoxins (AFP10), has an elevated missense variant rate, numerous high impact mutations, and a 600 base pair deletion in the norB gene. In summary, our study provides insights into aflatoxigenic potential and the associated genetic diversity of indigenous Aspergillus section Flavi isolates and potential management strategies for reducing aflatoxin contamination levels in a major crop consumed in Punjab, Pakistan.
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Affiliation(s)
- Maryam Ajmal
- Department of Botany, Faculty of Sciences, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi 46300, Pakistan; (M.A.); (A.A.)
| | - Ahmad F. Alshannaq
- Department of Bacteriology, Food Research Institute, University of Wisconsin-Madison, 1550 Linden Drive, Madison, WI 53706, USA; (A.F.A.); (H.M.); (D.C.)
| | - Heungyun Moon
- Department of Bacteriology, Food Research Institute, University of Wisconsin-Madison, 1550 Linden Drive, Madison, WI 53706, USA; (A.F.A.); (H.M.); (D.C.)
| | - Dasol Choi
- Department of Bacteriology, Food Research Institute, University of Wisconsin-Madison, 1550 Linden Drive, Madison, WI 53706, USA; (A.F.A.); (H.M.); (D.C.)
| | - Abida Akram
- Department of Botany, Faculty of Sciences, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi 46300, Pakistan; (M.A.); (A.A.)
| | - Brian Gagosh Nayyar
- Department of Botany, Faculty of Sciences, University of Sialkot, Sialkot 51310, Pakistan;
| | - John G. Gibbons
- Department of Food Science, College of Natural Sciences, University of Massachusetts, Amherst, MA 01003, USA;
| | - Jae-Hyuk Yu
- Department of Bacteriology, Food Research Institute, University of Wisconsin-Madison, 1550 Linden Drive, Madison, WI 53706, USA; (A.F.A.); (H.M.); (D.C.)
- Department of Systems Biotechnology, Konkuk Institute of Science and Technology, Konkuk University, Seoul 05029, Korea
- Correspondence:
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Deng L, Pan Y, Wang Y, Chen H, Yuan K, Chen S, Lu D, Lu Y, Mokhtar SS, Rahman TA, Hoh BP, Xu S. Genetic Connections and Convergent Evolution of Tropical Indigenous Peoples in Asia. Mol Biol Evol 2022; 39:msab361. [PMID: 34940850 PMCID: PMC8826522 DOI: 10.1093/molbev/msab361] [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] [Indexed: 11/14/2022] Open
Abstract
Tropical indigenous peoples in Asia (TIA) attract much attention for their unique appearance, whereas their genetic history and adaptive evolution remain mysteries. We conducted a comprehensive study to characterize the genetic distinction and connection of broad geographical TIAs. Despite the diverse genetic makeup and large interarea genetic differentiation between the TIA groups, we identified a basal Asian ancestry (bASN) specifically shared by these populations. The bASN ancestry was relatively enriched in ancient Asian human genomes dated as early as ∼50,000 years before the present and diminished in more recent history. Notably, the bASN ancestry is unlikely to be derived from archaic hominins. Instead, we suggest it may be better modeled as a survived lineage of the initial peopling of Asia. Shared adaptations inherited from the ancient Asian ancestry were detected among the TIA groups (e.g., LIMS1 for hair morphology, and COL24A1 for bone formation), and they are enriched in neurological functions either at an identical locus (e.g., NKAIN3), or different loci in an identical gene (e.g., TENM4). The bASN ancestry could also have formed the substrate of the genetic architecture of the dark pigmentation observed in the TIA peoples. We hypothesize that phenotypic convergence of the dark pigmentation in TIAs could have resulted from parallel (e.g., DDB1/DAK) or genetic convergence driven by admixture (e.g., MTHFD1 and RAD18), new mutations (e.g., STK11), or notably purifying selection (e.g., MC1R). Our results provide new insights into the initial peopling of Asia and an advanced understanding of the phenotypic convergence of the TIA peoples.
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Affiliation(s)
- Lian Deng
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yinan Wang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hao Chen
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Kai Yuan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Sihan Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Dongsheng Lu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Siti Shuhada Mokhtar
- Institute of Medical Molecular Biotechnology, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, Sungai Buloh, Selangor, Malaysia
| | - Thuhairah Abdul Rahman
- Clinical Pathology Diagnostic Centre Research Laboratory, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, Sungai Buloh, Selangor, Malaysia
| | - Boon-Peng Hoh
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Faculty of Medicine and Health Sciences, UCSI University, Cheras, Kuala Lumpur, Malaysia
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
- Jiangsu Key Laboratory of Phylogenomics and Comparative Genomics, School of Life Sciences, Jiangsu Normal University, Xuzhou, China
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
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Shape Prediction of Nasal Bones by Digital 2D-Photogrammetry of the Nose Based on Convolution and Back-Propagation Neural Network. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:5938493. [PMID: 35069786 PMCID: PMC8767378 DOI: 10.1155/2022/5938493] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 11/27/2021] [Indexed: 11/25/2022]
Abstract
In rhinoplasty, it is necessary to consider the correlation between the anthropometric indicators of the nasal bone, so that it prevents surgical complications and enhances the patient's satisfaction. The penetrating form of high-energy electromagnetic radiation is highly impacted on human health, which has often raised concerns of alternative method for facial analysis. The critical stage to assess nasal morphology is the nasal analysis on its anthropology that is highly reliant on the understanding of the structural features of the nasal radix. For example, the shape and size of nasal bone features, skin thickness, and also body factors aggregated from different facial anthropology values. In medical diagnosis, however, the morphology of the nasal bone is determined manually and significantly relies on the clinician's expertise. Furthermore, the evaluation anthropological keypoint of the nasal bone is nonrepeatable and laborious, also finding widely differ and intralaboratory variability in the results because of facial soft tissue and equipment defects. In order to overcome these problems, we propose specialized convolutional neural network (CNN) architecture to accurately predict nasal measurement based on digital 2D photogrammetry. To boost performance and efficacy, it is deliberately constructed with many layers and different filter sizes, with less filters and optimizing parameters. Through its result, the back-propagation neural network (BPNN) indicated the correlation between differences in human body factors mentioned are height, weight known as body mass index (BMI), age, gender, and the nasal bone dimension of the participant. With full of parameters could the nasal morphology be diagnostic continuously. The model's performance is evaluated on various newest architecture models such as DenseNet, ConvNet, Inception, VGG, and MobileNet. Experiments were directly conducted on different facials. The results show the proposed architecture worked well in terms of nasal properties achieved which utilize four statistical criteria named mean average precision (mAP), mean absolute error (MAE), R-square (R2), and T-test analyzed. Data has also shown that the nasal shape of Southeast Asians, especially Vietnamese, could be divided into different types in two perspective views. From cadavers for bony datasets, nasal bones can be classified into 2 morphological types in the lateral view which “V” shape was presented by 78.8% and the remains were “S” shape evaluated based on Lazovic (2015). With 2 angular dimension averages are 136.41 ± 7.99 and 104.25 ± 5.95 represented by the nasofrontal angle (g-n-prn) and the nasomental angle (n-prn-sn), respectively. For frontal view, classified by Hwang, Tae-Sun, et al. (2005), nasal morphology of Vietnamese participants could be divided into three types: type A was present in 57.6% and type B was present in 30.3% of the noses. In particular, types C, D, and E were not a common form of Vietnamese which includes the remaining number of participants. In conclusion, the proposed model performed the potential hybrid of CNN and BPNN with its application to give expected accuracy in terms of keypoint localization and nasal morphology regression. Nasal analysis can replace MRI imaging diagnostics that are reflected by the risk to human body.
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Qian Y, Xiong Z, Li Y, Kayser M, Liu L, Liu F. The effects of Tbx15 and Pax1 on facial and other physical morphology in mice. FASEB Bioadv 2021; 3:1011-1019. [PMID: 34938962 PMCID: PMC8664010 DOI: 10.1096/fba.2021-00094] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 08/19/2021] [Accepted: 08/23/2021] [Indexed: 12/13/2022] Open
Abstract
DNA variants in or close to the human TBX15 and PAX1 genes have been repeatedly associated with facial morphology in independent genome-wide association studies, while their functional roles in determining facial morphology remain to be understood. We generated Tbx15 knockout (Tbx15 -/-) and Pax1 knockout (Pax1 -/-) mice by applying the one-step CRISPR/Cas9 method. A total of 75 adult mice were used for subsequent phenotype analysis, including 38 Tbx15 mice (10 homozygous Tbx15 -/-, 18 heterozygous Tbx15 +/-, 10 wild-type Tbx15 +/+ WT littermates) and 37 Pax1 mice (12 homozygous Pax1 -/-, 15 heterozygous Pax1 +/-, 10 Pax1 +/+ WT littermates). Facial and other physical morphological phenotypes were obtained from three-dimensional (3D) images acquired with the HandySCAN BLACK scanner. Compared to WT littermates, the Tbx15 -/- mutant mice had significantly shorter faces (p = 1.08E-8, R2 = 0.61) and their ears were in a significantly lower position (p = 3.54E-8, R2 = 0.62) manifesting a "droopy ear" characteristic. Besides these face alternations, Tbx15 -/- mutant mice displayed significantly lower weight as well as shorter body and limb length. Pax1 -/- mutant mice showed significantly longer noses (p = 1.14E-5, R2 = 0.46) relative to WT littermates, but otherwise displayed less obvious morphological alterations than Tbx15 -/- mutant mice did. We provide the first direct functional evidence that two well-known and replicated human face genes, Tbx15 and Pax1, impact facial and other body morphology in mice. The general agreement between our findings in knock-out mice with those from previous GWASs suggests that the functional evidence we established here in mice may also be relevant in humans.
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Affiliation(s)
- Yu Qian
- CAS Key Laboratory of Genomic and Precision MedicineBeijing Institute of GenomicsChinese Academy of SciencesBeijingChina
- China National Center for BioinformationBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Ziyi Xiong
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
- Department of EpidemiologyErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
| | - Yi Li
- CAS Key Laboratory of Genomic and Precision MedicineBeijing Institute of GenomicsChinese Academy of SciencesBeijingChina
- China National Center for BioinformationBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Manfred Kayser
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
| | - Lei Liu
- Department of Plastic and Burn SurgeryThe Second HospitalCheeloo College of MedicineShandong UniversityJinanChina
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision MedicineBeijing Institute of GenomicsChinese Academy of SciencesBeijingChina
- China National Center for BioinformationBeijingChina
- University of Chinese Academy of SciencesBeijingChina
- Department of Genetic IdentificationErasmus MC University Medical Center RotterdamRotterdamthe Netherlands
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36
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Knol MJ, Pawlak MA, Lamballais S, Terzikhan N, Hofer E, Xiong Z, Klaver CCW, Pirpamer L, Vernooij MW, Ikram MA, Schmidt R, Kayser M, Evans TE, Adams HHH. Genetic architecture of orbital telorism. Hum Mol Genet 2021; 31:1531-1543. [PMID: 34791242 PMCID: PMC9071440 DOI: 10.1093/hmg/ddab334] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 11/09/2021] [Accepted: 11/10/2021] [Indexed: 11/19/2022] Open
Abstract
The interocular distance, or orbital telorism, is a distinctive craniofacial trait that also serves as a clinically informative measure. While its extremes, hypo- and hypertelorism, have been linked to monogenic disorders and are often syndromic, little is known about the genetic determinants of interocular distance within the general population. We derived orbital telorism measures from cranial magnetic resonance imaging by calculating the distance between the eyeballs’ centre of gravity, which showed a good reproducibility with an intraclass correlation coefficient of 0.991 (95% confidence interval 0.985–0.994). Heritability estimates were 76% (standard error = 12%) with a family-based method (N = 364) and 39% (standard error = 2.4%) with a single nucleotide polymorphism-based method (N = 34 130) and were unaffected by adjustment for height (model II) and intracranial volume (model III) or head width (model IV). Genome-wide association studies in 34 130 European individuals identified 56 significantly associated genomic loci (P < 5 × 10−8) across four different models of which 46 were novel for facial morphology, and overall these findings replicated in an independent sample (N = 10 115) with telorism-related horizontal facial distance measures. Genes located nearby these 56 identified genetic loci were 4.9-fold enriched for Mendelian hypotelorism and hypertelorism genes, underlining their biological relevance. This study provides novel insights into the genetic architecture underlying interocular distance in particular, and the face in general, and explores its potential for applications in a clinical setting.
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Affiliation(s)
- Maria J Knol
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands
| | - Mikolaj A Pawlak
- Department of Neurology and Cerebrovascular Disorders, Poznan University of Medical Sciences, Poznan, Poland.,Department of Clinical Genetics, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands
| | - Sander Lamballais
- Department of Clinical Genetics, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands
| | - Natalie Terzikhan
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands
| | - Edith Hofer
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Auenbruggerplatz 22, 8036 Graz, Austria.,Institute of Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 22, 8036 Graz, Austria
| | - Ziyi Xiong
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands.,Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands
| | - Caroline C W Klaver
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands.,Department of Ophthalmology, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands
| | - Lukas Pirpamer
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Auenbruggerplatz 22, 8036 Graz, Austria
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands
| | - Reinhold Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Auenbruggerplatz 22, 8036 Graz, Austria
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands
| | - Tavia E Evans
- Department of Clinical Genetics, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands
| | - Hieab H H Adams
- Department of Clinical Genetics, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, 3015 CE, the Netherlands
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37
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Grine FE, Gonzalvo E, Rossouw L, Holt S, Black W, Braga J. Variation in Middle Stone Age mandibular molar enamel-dentine junction topography at Klasies River Main Site assessed by diffeomorphic surface matching. J Hum Evol 2021; 161:103079. [PMID: 34739985 DOI: 10.1016/j.jhevol.2021.103079] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 09/07/2021] [Accepted: 09/12/2021] [Indexed: 11/19/2022]
Abstract
The morphology and variability of the Middle Stone Age (MSA) hominin fossils from Klasies River Main Site have been the focus of investigation for more than four decades. The mandibular remains have figured prominently in discussions relating to robusticity, size dimorphism, and symphyseal morphology. Variation in corpus size between the robust SAM-AP 6223 and the diminutive SAM-AP 6225 mandibles is particularly impressive, and the difference between the buccolingual diameters of their M2s significantly exceeds recent human sample variation. SAM-AP 6223 and SAM-AP 6225 are the only Klasies specimens with homologous teeth (M2 and M3) that permit comparisons of crown morphology. While the differences in dental trait expression at the outer enamel surfaces of these molars are slight, diffeomorphic surface analyses of their underlying enamel-dentine junction (EDJ) topographies reveal differences that are well beyond the means of pairwise differences among comparative samples of Later Stone Age (LSA) Khoesan and recent African homologues. The EDJs of both SAM-AP 6225 molars and the SAM-AP 6223 M3 fall outside the envelopes that define the morphospace of these two samples. Although the radiocarbon dated LSA individuals examined here differ by a maximum of some 7000 years, and the two Klasies jaws may differ by perhaps as much as 18,000 years, it is difficult to ascribe their differences to time alone. With reference to the morphoscopic traits by which the SAM-AP 6223 and SAM-AP 6225 EDJs differ, the most striking is the expression of the protoconid cingulum. This is very weakly developed on the SAM-AP 6223 molars and distinct in SAM-AP 6225. As such, this diminutive fossil exhibits a more pronounced manifestation of what is likely a plesiomorphic feature, thus adding to the morphological mosaicism that is evident in the Klasies hominin assemblage. Several possible explanations for the variation and mosaicism in this MSA sample are discussed.
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Affiliation(s)
- Frederick E Grine
- Department of Anthropology, Stony Brook University, Stony Brook, NY 11794-4364, USA; Department of Anatomical Sciences, Stony Brook University, Stony Brook, NY 11794-4364, USA.
| | - Elsa Gonzalvo
- Centre d'Anthropobiologie et de Génomique de Toulouse, Université Paul Sabatier Toulouse III, Faculté de Médecine Purpan, 37 Allées Jules Guesde, Toulouse, France
| | - Lloyd Rossouw
- Florisbad Quaternary Research Department, The National Museum, 36 Aliwal Street, Bloemfontein 9300, South Africa
| | - Sharon Holt
- Florisbad Quaternary Research Department, The National Museum, 36 Aliwal Street, Bloemfontein 9300, South Africa
| | - Wendy Black
- Archaeology Unit, Research and Exhibitions Department, Iziko Museums of South Africa, Cape Town, South Africa
| | - José Braga
- Centre d'Anthropobiologie et de Génomique de Toulouse, Université Paul Sabatier Toulouse III, Faculté de Médecine Purpan, 37 Allées Jules Guesde, Toulouse, France; Evolutionary Studies Institute, University of the Witwatersrand, Johannesburg, 2050, South Africa
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38
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Liu C, Lee MK, Naqvi S, Hoskens H, Liu D, White JD, Indencleef K, Matthews H, Eller RJ, Li J, Mohammed J, Swigut T, Richmond S, Manyama M, Hallgrímsson B, Spritz RA, Feingold E, Marazita ML, Wysocka J, Walsh S, Shriver MD, Claes P, Weinberg SM, Shaffer JR. Genome scans of facial features in East Africans and cross-population comparisons reveal novel associations. PLoS Genet 2021; 17:e1009695. [PMID: 34411106 PMCID: PMC8375984 DOI: 10.1371/journal.pgen.1009695] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Accepted: 07/02/2021] [Indexed: 12/16/2022] Open
Abstract
Facial morphology is highly variable, both within and among human populations, and a sizable portion of this variation is attributable to genetics. Previous genome scans have revealed more than 100 genetic loci associated with different aspects of normal-range facial variation. Most of these loci have been detected in Europeans, with few studies focusing on other ancestral groups. Consequently, the degree to which facial traits share a common genetic basis across diverse sets of humans remains largely unknown. We therefore investigated the genetic basis of facial morphology in an East African cohort. We applied an open-ended data-driven phenotyping approach to a sample of 2,595 3D facial images collected on Tanzanian children. This approach segments the face into hierarchically arranged, multivariate features that capture the shape variation after adjusting for age, sex, height, weight, facial size and population stratification. Genome scans of these multivariate shape phenotypes revealed significant (p < 2.5 × 10−8) signals at 20 loci, which were enriched for active chromatin elements in human cranial neural crest cells and embryonic craniofacial tissue, consistent with an early developmental origin of the facial variation. Two of these associations were in highly conserved regions showing craniofacial-specific enhancer activity during embryological development (5q31.1 and 12q21.31). Six of the 20 loci surpassed a stricter threshold accounting for multiple phenotypes with study-wide significance (p < 6.25 × 10−10). Cross-population comparisons indicated 10 association signals were shared with Europeans (seven sharing the same associated SNP), and facilitated fine-mapping of causal variants at previously reported loci. Taken together, these results may point to both shared and population-specific components to the genetic architecture of facial variation. Genetic factors play an important role in shaping human facial features. Over the last decade, studies have identified numerous genes associated with various facial traits. The vast majority of these studies have focused on European or Asian populations, while African populations have been underrepresented. Increasing the diversity of these analyses can reveal novel associations and cross-population analyses can help deepen our understanding of known genetic associations. We therefore performed a genome scan of 3D facial features in African children from Tanzania and then compared our results to Europeans. We found 20 regions of the genome associated with facial shape in Tanzanian children, 10 of which were also present in Europeans, indicating evidence for a partly shared genetic basis for human facial shape across populations. In addition, about half of the genetic associations observed in Tanzanians were not present in Europeans, and some of the shared signals differed between populations in the specific genetic variants associated or specific facial traits affected. These results shed light on the shared and population-specific genetic contributors to normal-range facial variation.
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Affiliation(s)
- Chenxing Liu
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Myoung Keun Lee
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California, United States of America
- Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America
| | - Hanne Hoskens
- Medical Imaging Research Center, Katholieke Universiteit Leuven, Leuven, Belgium
- Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Dongjing Liu
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Julie D. White
- Department of Anthropology, Pennsylvania State University, State College, Pennsylvania, United States of America
| | - Karlijne Indencleef
- Medical Imaging Research Center, Katholieke Universiteit Leuven, Leuven, Belgium
- Processing Speech & Images, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Harold Matthews
- Medical Imaging Research Center, Katholieke Universiteit Leuven, Leuven, Belgium
- Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium
- Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
| | - Ryan J. Eller
- Department of Biology, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, United States of America
| | - Jiarui Li
- Medical Imaging Research Center, Katholieke Universiteit Leuven, Leuven, Belgium
- Processing Speech & Images, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Jaaved Mohammed
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California, United States of America
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, United States of America
| | - Tomek Swigut
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California, United States of America
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, United States of America
| | - Stephen Richmond
- Applied Clinical Research and Public Health, School of Dentistry, Cardiff University, Cardiff, United Kingdom
| | - Mange Manyama
- Anatomy in Radiology, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Benedikt Hallgrímsson
- Department of Anatomy and Cell Biology, Alberta Children´s Hospital Research Institute, University of Calgary, Calgary, Canada
| | - Richard A. Spritz
- Human Medical Genetics and Genomics Program, University of Colorado School of Medicine, Aurora, Colorado, United States of America
| | - Eleanor Feingold
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Mary L. Marazita
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California, United States of America
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, United States of America
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, California, United States of America
| | - Susan Walsh
- Department of Biology, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, United States of America
| | - Mark D. Shriver
- Department of Anthropology, Pennsylvania State University, State College, Pennsylvania, United States of America
| | - Peter Claes
- Medical Imaging Research Center, Katholieke Universiteit Leuven, Leuven, Belgium
- Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium
- Processing Speech & Images, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium
- Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
| | - Seth M. Weinberg
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Anthropology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- * E-mail: (SMW); (JRS)
| | - John R. Shaffer
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- * E-mail: (SMW); (JRS)
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39
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Liu D, Ban HJ, El Sergani AM, Lee MK, Hecht JT, Wehby GL, Moreno LM, Feingold E, Marazita ML, Cha S, Szabo-Rogers HL, Weinberg SM, Shaffer JR. PRICKLE1 × FOCAD Interaction Revealed by Genome-Wide vQTL Analysis of Human Facial Traits. Front Genet 2021; 12:674642. [PMID: 34434215 PMCID: PMC8381734 DOI: 10.3389/fgene.2021.674642] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 06/03/2021] [Indexed: 12/14/2022] Open
Abstract
The human face is a highly complex and variable structure resulting from the intricate coordination of numerous genetic and non-genetic factors. Hundreds of genomic loci impacting quantitative facial features have been identified. While these associations have been shown to influence morphology by altering the mean size and shape of facial measures, their effect on trait variance remains unclear. We conducted a genome-wide association analysis for the variance of 20 quantitative facial measurements in 2,447 European individuals and identified several suggestive variance quantitative trait loci (vQTLs). These vQTLs guided us to conduct an efficient search for gene-by-gene (G × G) interactions, which uncovered an interaction between PRICKLE1 and FOCAD affecting cranial base width. We replicated this G × G interaction signal at the locus level in an additional 5,128 Korean individuals. We used the hypomorphic Prickle1 Beetlejuice (Prickle1 Bj ) mouse line to directly test the function of Prickle1 on the cranial base and observed wider cranial bases in Prickle1 Bj/Bj . Importantly, we observed that the Prickle1 and Focadhesin proteins co-localize in murine cranial base chondrocytes, and this co-localization is abnormal in the Prickle1 Bj/Bj mutants. Taken together, our findings uncovered a novel G × G interaction effect in humans with strong support from both epidemiological and molecular studies. These results highlight the potential of studying measures of phenotypic variability in gene mapping studies of facial morphology.
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Affiliation(s)
- Dongjing Liu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Hyo-Jeong Ban
- Future Medicine Division, Korea Institute of Oriental Medicine, Daejeon, South Korea
| | - Ahmed M. El Sergani
- Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Myoung Keun Lee
- Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Jacqueline T. Hecht
- Department of Pediatrics, McGovern Medical Center, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - George L. Wehby
- Department of Health Management and Policy, The University of Iowa, Iowa City, IA, United States
| | - Lina M. Moreno
- Department of Orthodontics, The University of Iowa, Iowa City, IA, United States
| | - Eleanor Feingold
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
| | - Mary L. Marazita
- Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Psychiatry, Clinical and Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Seongwon Cha
- Future Medicine Division, Korea Institute of Oriental Medicine, Daejeon, South Korea
| | - Heather L. Szabo-Rogers
- Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Developmental Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Regenerative Medicine at the McGowan Institute, University of Pittsburgh, Pittsburgh, PA, United States
- Center for Craniofacial Regeneration, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Seth M. Weinberg
- Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
| | - John R. Shaffer
- Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
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Shi L, Bai H, Li Y, Yuan J, Wang P, Wang Y, Ni A, Jiang L, Ge P, Bian S, Zong Y, Isa AM, Tesfay HH, Yang F, Ma H, Sun Y, Chen J. Analysis of DNA Methylation Profiles in Mandibular Condyle of Chicks With Crossed Beaks Using Whole-Genome Bisulfite Sequencing. Front Genet 2021; 12:680115. [PMID: 34306022 PMCID: PMC8298039 DOI: 10.3389/fgene.2021.680115] [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: 03/13/2021] [Accepted: 06/03/2021] [Indexed: 01/17/2023] Open
Abstract
Crossed beaks have been observed in at least 12 chicken strains around the world, which severely impairs their growth and welfare. To explore the intrinsic factor causing crossed beaks, this study measured the length of bilateral mandibular ramus of affected birds, and investigated the genome-wide DNA methylation profiles of normal and affected sides of mandibular condyle. Results showed that the trait was caused by impaired development of unilateral mandibular ramus, which is extended through calcification of mandibular condyle. The methylation levels in the CG contexts were higher than that of CHG and CHH, with the highest methylation level of gene body region, followed by transcription termination sites and downstream. Subsequently, we identified 1,568 differentially methylated regions and 1,317 differentially methylated genes in CG contexts. Functional annotation analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes showed that these genes were involved in bone mineralization and bone morphogenesis. Furthermore, by combining the WGBS and previous RNA-Seq data, 11 overlapped genes were regulated by both long non-coding RNA and DNA methylation. Among them, FIGNL1 is an important gene in calcification of mandibular condyle. Generally, because the affected genes play key roles in maintaining mandibular calcification, these changes may be pivotal factors of crossed beaks.
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Affiliation(s)
- Lei Shi
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hao Bai
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, The Ministry of Education of China, Institutes of Agricultural Science and Technology Development, Yangzhou University, Yangzhou, China
| | - Yunlei Li
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jingwei Yuan
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Panlin Wang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yuanmei Wang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Aixin Ni
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Linlin Jiang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Pingzhuang Ge
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shixiong Bian
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yunhe Zong
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Adamu Mani Isa
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hailai Hagos Tesfay
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Fujian Yang
- Guangxi Shenhuang Group Co., Ltd., Yulin, China
| | - Hui Ma
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yanyan Sun
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jilan Chen
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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41
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Raza RZ, Ma L, Zhang Z, Bao Y, Abbasi AA. Selection trends on nasal-associated SNP variants across human populations. Meta Gene 2021. [DOI: 10.1016/j.mgene.2021.100872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
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42
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Chen Y, André M, Adhikari K, Blin M, Bonfante B, Mendoza-Revilla J, Fuentes-Guajardo M, Palmal S, Chacón-Duque JC, Hurtado M, Villegas V, Granja V, Jaramillo C, Arias W, Lozano RB, Everardo-Martínez P, Gómez-Valdés J, Villamil-Ramírez H, de Cerqueira CCS, Hünemeier T, Ramallo V, Gonzalez-José R, Schüler-Faccini L, Bortolini MC, Acuña-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Bedoya G, Rothhammer F, Balding D, Tobin DJ, Wang S, Faux P, Ruiz-Linares A. A genome-wide association study identifies novel gene associations with facial skin wrinkling and mole count in Latin Americans. Br J Dermatol 2021; 185:988-998. [PMID: 33959940 DOI: 10.1111/bjd.20436] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/04/2021] [Indexed: 12/01/2022]
Abstract
BACKGROUND Genome-wide association studies (GWASs) have identified genes influencing skin ageing and mole count in Europeans, but little is known about the relevance of these (or other genes) in non-Europeans. OBJECTIVES To conduct a GWAS for facial skin ageing and mole count in adults < 40 years old, of mixed European, Native American and African ancestry, recruited in Latin America. METHODS Skin ageing and mole count scores were obtained from facial photographs of over 6000 individuals. After quality control checks, three wrinkling traits and mole count were retained for genetic analyses. DNA samples were genotyped with Illumina's HumanOmniExpress chip. Association testing was performed on around 8 703 729 single-nucleotide polymorphisms (SNPs) across the autosomal genome. RESULTS Genome-wide significant association was observed at four genome regions: two were associated with wrinkling (in 1p13·3 and 21q21·2), one with mole count (in 1q32·3) and one with both wrinkling and mole count (in 5p13·2). Associated SNPs in 5p13·2 and in 1p13·3 are intronic within SLC45A2 and VAV3, respectively, while SNPs in 1q32·3 are near the SLC30A1 gene, and those in 21q21·2 occur in a gene desert. Analyses of SNPs in IRF4 and MC1R are consistent with a role of these genes in skin ageing. CONCLUSIONS We replicate the association of wrinkling with variants in SLC45A2, IRF4 and MC1R reported in Europeans. We identify VAV3 and SLC30A1 as two novel candidate genes impacting on wrinkling and mole count, respectively. We provide the first evidence that SLC45A2 influences mole count, in addition to variants in this gene affecting melanoma risk in Europeans.
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Affiliation(s)
- Y Chen
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, China
| | - M André
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France.,Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, 51010, Estonia
| | - K Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, UK.,Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK
| | - M Blin
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - B Bonfante
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - J Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú.,Unit of Human Evolutionary Genetics, Institut Pasteur, Paris, 75015, France
| | - M Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, Arica, 1000000, Chile
| | - S Palmal
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - J C Chacón-Duque
- Division of Vertebrates and Anthropology, Department of Earth Sciences, Natural History Museum, London, SW7 5BD, UK
| | - M Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - V Villegas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - V Granja
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - C Jaramillo
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - W Arias
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - R B Lozano
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico.,Department of Archaeogenetics, Max Planck Institute for the Science of Human History (MPI-SHH), Jena, 07745, Germany
| | - P Everardo-Martínez
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico
| | - J Gómez-Valdés
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico
| | - H Villamil-Ramírez
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, MC, 4510, Mexico
| | | | - T Hünemeier
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, 05508-090, Brazil
| | - V Ramallo
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90040-060, Brazil.,Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - R Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn, U9129ACD, Argentina
| | - L Schüler-Faccini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90040-060, Brazil
| | - M-C Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90040-060, Brazil
| | - V Acuña-Alonzo
- National Institute of Anthropology and History, Mexico City, MC, 6600, Mexico
| | - S Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City, MC, 4510, Mexico
| | - C Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - G Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - G Bedoya
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín, 5001000, Colombia
| | - F Rothhammer
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica, 1000000, Chile
| | - D Balding
- Melbourne Integrative Genomics, Schools of BioSciences and Mathematics & Statistics, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - D J Tobin
- The Charles Institute of Dermatology, University College Dublin, Dublin, Ireland
| | - S Wang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, Shanghai Institutes for Biological Sciences, University of the Chinese Academy of Sciences, Shanghai, 200031, China
| | - P Faux
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France
| | - A Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, China.,UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille, 13005, France.,Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London, WC1E 6BT, UK
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Hoskens H, Liu D, Naqvi S, Lee MK, Eller RJ, Indencleef K, White JD, Li J, Larmuseau MHD, Hens G, Wysocka J, Walsh S, Richmond S, Shriver MD, Shaffer JR, Peeters H, Weinberg SM, Claes P. 3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies. PLoS Genet 2021; 17:e1009528. [PMID: 33983923 PMCID: PMC8118281 DOI: 10.1371/journal.pgen.1009528] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 04/01/2021] [Indexed: 12/12/2022] Open
Abstract
The analysis of contemporary genomic data typically operates on one-dimensional phenotypic measurements (e.g. standing height). Here we report on a data-driven, family-informed strategy to facial phenotyping that searches for biologically relevant traits and reduces multivariate 3D facial shape variability into amendable univariate measurements, while preserving its structurally complex nature. We performed a biometric identification of siblings in a sample of 424 children, defining 1,048 sib-shared facial traits. Subsequent quantification and analyses in an independent European cohort (n = 8,246) demonstrated significant heritability for a subset of traits (0.17-0.53) and highlighted 218 genome-wide significant loci (38 also study-wide) associated with facial variation shared by siblings. These loci showed preferential enrichment for active chromatin marks in cranial neural crest cells and embryonic craniofacial tissues and several regions harbor putative craniofacial genes, thereby enhancing our knowledge on the genetic architecture of normal-range facial variation.
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Affiliation(s)
- Hanne Hoskens
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, UZ Leuven, Leuven, Belgium
| | - Dongjing Liu
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Sahin Naqvi
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California, United States of America
- Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America
| | - Myoung Keun Lee
- Department of Oral Biology, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Ryan J. Eller
- Department of Biology, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, United States of America
| | - Karlijne Indencleef
- Medical Imaging Research Center, UZ Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
- Department of Otorhinolaryngology, KU Leuven, Leuven, Belgium
| | - Julie D. White
- Department of Anthropology, The Pennsylvania State University, State College, Pennsylvania, United States of America
| | - Jiarui Li
- Medical Imaging Research Center, UZ Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Maarten H. D. Larmuseau
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Department of Biology, Laboratory of Socioecology and Social Evolution, KU Leuven, Leuven, Belgium
- Histories vzw, Mechelen, Belgium
| | - Greet Hens
- Department of Otorhinolaryngology, KU Leuven, Leuven, Belgium
| | - Joanna Wysocka
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California, United States of America
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, United States of America
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, California, United States of America
| | - Susan Walsh
- Department of Biology, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, United States of America
| | - Stephen Richmond
- Applied Clinical Research and Public Health, School of Dentistry, Cardiff University, Cardiff, United Kingdom
| | - Mark D. Shriver
- Department of Anthropology, The Pennsylvania State University, State College, Pennsylvania, United States of America
| | - John R. Shaffer
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Oral Biology, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Hilde Peeters
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Seth M. Weinberg
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Oral Biology, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Anthropology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Peter Claes
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, UZ Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
- Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
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Balestrini S, Lopez SM, Chinthapalli K, Sargsyan N, Demurtas R, Vos S, Altmann A, Suttie M, Hammond P, Sisodiya SM. Increased facial asymmetry in focal epilepsies associated with unilateral lesions. Brain Commun 2021; 3:fcab068. [PMID: 34222868 PMCID: PMC8244637 DOI: 10.1093/braincomms/fcab068] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 02/20/2021] [Accepted: 03/11/2021] [Indexed: 12/22/2022] Open
Abstract
The epilepsies are now conceptualized as network disruptions: focal epilepsies are considered to have network alterations in the hemisphere of seizure onset, whilst generalized epilepsies are considered to have bi-hemispheric network changes. Increasingly, many epilepsies are also considered to be neurodevelopmental disorders, with early changes in the brain underpinning seizure biology. The development of the structure of the face is influenced by complex molecular interactions between surface ectoderm and underlying developing forebrain and neural crest cells. This influence is likely to continue postnatally, given the evidence of facial growth changes over time in humans until at least 18 years of age. In this case-control study, we hypothesized that people with lateralized focal epilepsies (i.e. unilateral network changes) have an increased degree of facial asymmetry, compared with people with generalized epilepsies or controls without epilepsy. We applied three-dimensional stereophotogrammetry and dense surface models to evaluate facial asymmetry in people with epilepsy, aiming to generate new tools to explore pathophysiological mechanisms in epilepsy. We analysed neuroimaging data to explore the correlation between face and brain asymmetry. We consecutively recruited 859 people with epilepsy attending the epilepsy clinics at a tertiary referral centre. We used dense surface modelling of the full face and signature analyses of three-dimensional facial photographs to analyse facial differences between 378 cases and 205 healthy controls. Neuroimaging around the time of the facial photograph was available for 234 cases. We computed the brain asymmetry index between contralateral regions. Cases with focal symptomatic epilepsy associated with unilateral lesions showed greater facial asymmetry compared to controls (P = 0.0001, two-sample t-test). This finding was confirmed by linear regression analysis after controlling for age and gender. We also found a significant correlation between duration of illness and the brain asymmetry index of total average cortical thickness (r = -0.19, P = 0.0075) but not for total average surface area (r = 0.06, P = 0.3968). There was no significant correlation between facial asymmetry and asymmetry of regional cortical thickness or surface area. We propose that the greater facial asymmetry in cases with focal epilepsy caused by unilateral abnormality might be explained by early unilateral network disruption, and that this is independent of underlying brain asymmetry. Three-dimensional stereophotogrammetry and dense surface modelling are a novel powerful phenotyping tool in epilepsy that may permit greater understanding of pathophysiology in epilepsy, and generate further insights into the development of cerebral networks underlying epilepsy, and the genetics of facial and neural development.
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Affiliation(s)
- Simona Balestrini
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London.,Chalfont Centre for Epilepsy, Gerrards Cross, UK
| | - Seymour M Lopez
- Department of Medical Physics, Centre for Medical Image Computing, UCL, London, UK
| | - Krishna Chinthapalli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London.,Chalfont Centre for Epilepsy, Gerrards Cross, UK
| | - Narek Sargsyan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London.,Chalfont Centre for Epilepsy, Gerrards Cross, UK
| | - Rita Demurtas
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London.,Chalfont Centre for Epilepsy, Gerrards Cross, UK
| | - Sjoerd Vos
- Department of Medical Physics, Centre for Medical Image Computing, UCL, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Andre Altmann
- Department of Medical Physics, Centre for Medical Image Computing, UCL, London, UK
| | - Michael Suttie
- Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.,Big Data Institute, Old Road Campus, University of Oxford, Oxford, UK
| | - Peter Hammond
- Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.,Big Data Institute, Old Road Campus, University of Oxford, Oxford, UK
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London.,Chalfont Centre for Epilepsy, Gerrards Cross, UK
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45
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Yamaguchi T, Kim YI, Mohamed A, Hikita Y, Takahashi M, Haga S, Park SB, Maki K. Methods in Genetic Analysis for Evaluation Mandibular Shape and Size Variations in Human Mandible. J Craniofac Surg 2021; 33:e97-e101. [PMID: 33867516 DOI: 10.1097/scs.0000000000007686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
ABSTRACT The human mandible has been investigated from both clinical and evolutionary perspectives. Recent advances in genome science have identified the genetic regulation of human mandibular shape and size. Identification of genes that regulate mandibular shape and size would not only enhance our understanding of the mechanisms of mandibular growth and development but also help define a strategy to prevent mandibular dysplasia. This review provides a comprehensive summary of why and how the mandible was evaluated in the human mandible genome study. The variation in human mandibular shape and size has been progressively clarified, not only by focusing on the mandible alone but also by using extremely diverse approaches. The methods of data acquisition for evaluating human mandibular shape and size variation are well established. Furthermore, this review explains how to proceed with future research.
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Affiliation(s)
- Tetsutaro Yamaguchi
- Department of Orthodontics, Kanagawa Dental University, Japan Department of Orthodontics, Dental Research Institute, Pusan National University Dental Hospital, Yangsan, South Korea Department of Orthodontics, School of Dentistry, Showa University, Tokyo, Japan Department of Orthodontics, Suez Canal University, Ismailia, Egypt
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46
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Curtis SW, Chang D, Lee MK, Shaffer JR, Indencleef K, Epstein MP, Cutler DJ, Murray JC, Feingold E, Beaty TH, Claes P, Weinberg SM, Marazita ML, Carlson JC, Leslie EJ. The PAX1 locus at 20p11 is a potential genetic modifier for bilateral cleft lip. HGG ADVANCES 2021; 2:100025. [PMID: 33817668 PMCID: PMC8018676 DOI: 10.1016/j.xhgg.2021.100025] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 01/22/2021] [Indexed: 12/12/2022] Open
Abstract
Nonsyndromic orofacial clefts (OFCs) are a common birth defect and are phenotypically heterogenous in the structure affected by the cleft - cleft lip (CL) and cleft lip and palate (CLP) - as well as other features, such as the severity of the cleft. Here, we focus on bilateral and unilateral clefts as one dimension of OFC severity, because the genetic architecture of these subtypes is not well understood. We tested for subtype-specific genetic associations in 44 bilateral CL (BCL) cases, 434 unilateral CL (UCL) cases, 530 bilateral CLP cases (BCLP), 1123 unilateral CLP (UCLP) cases, and unrelated controls (N = 1626), using a mixed-model approach. While no novel loci were found, the genetic architecture of UCL was distinct compared to BCL, with 44.03% of suggestive loci having different effects between the two subtypes. To further understand the subtype-specific genetic risk factors, we performed a genome-wide scan for modifiers and found a significant modifier locus on 20p11 (p=7.53×10-9), 300kb downstream of PAX1, that associated with higher odds of BCL vs. UCL, and replicated in an independent cohort (p=0.0018) with no effect in BCLP (p>0.05). We further found that this locus was associated with normal human nasal shape. Taken together, these results suggest bilateral and unilateral clefts may have different genetic architectures. Moreover, our results suggest BCL, the rarest form of OFC, may be genetically distinct from the other OFC subtypes. This expands our understanding of modifiers for OFC subtypes and further elucidates the genetic mechanisms behind the phenotypic heterogeneity in OFCs.
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Affiliation(s)
- Sarah W. Curtis
- Department of Human Genetics, Emory University, Atlanta, GA 30322, USA
| | - Daniel Chang
- Department of Human Genetics, Emory University, Atlanta, GA 30322, USA
| | - Myoung Keun Lee
- Center for Craniofacial and Dental Genetics, Department of Oral Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - John R. Shaffer
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15621, USA
| | - Karlijne Indencleef
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | | | - David J. Cutler
- Department of Human Genetics, Emory University, Atlanta, GA 30322, USA
| | - Jeffrey C. Murray
- Department of Pediatrics, University of Iowa, Iowa City, IA 52242, USA
| | - Eleanor Feingold
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15621, USA
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Terri H. Beaty
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Peter Claes
- Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Seth M. Weinberg
- Center for Craniofacial and Dental Genetics, Department of Oral Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Mary L. Marazita
- Center for Craniofacial and Dental Genetics, Department of Oral Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15621, USA
| | - Jenna C. Carlson
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15621, USA
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA
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Palmal S, Adhikari K, Mendoza-Revilla J, Fuentes-Guajardo M, Silva de Cerqueira CC, Bonfante B, Chacón-Duque JC, Sohail A, Hurtado M, Villegas V, Granja V, Jaramillo C, Arias W, Lozano RB, Everardo-Martínez P, Gómez-Valdés J, Villamil-Ramírez H, Hünemeier T, Ramallo V, Parolin ML, Gonzalez-José R, Schüler-Faccini L, Bortolini MC, Acuña-Alonzo V, Canizales-Quinteros S, Gallo C, Poletti G, Bedoya G, Rothhammer F, Balding D, Faux P, Ruiz-Linares A. Prediction of eye, hair and skin colour in Latin Americans. Forensic Sci Int Genet 2021; 53:102517. [PMID: 33865096 DOI: 10.1016/j.fsigen.2021.102517] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 03/19/2021] [Accepted: 03/30/2021] [Indexed: 10/21/2022]
Abstract
Here we evaluate the accuracy of prediction for eye, hair and skin pigmentation in a dataset of > 6500 individuals from Mexico, Colombia, Peru, Chile and Brazil (including genome-wide SNP data and quantitative/categorical pigmentation phenotypes - the CANDELA dataset CAN). We evaluated accuracy in relation to different analytical methods and various phenotypic predictors. As expected from statistical principles, we observe that quantitative traits are more sensitive to changes in the prediction models than categorical traits. We find that Random Forest or Linear Regression are generally the best performing methods. We also compare the prediction accuracy of SNP sets defined in the CAN dataset (including 56, 101 and 120 SNPs for eye, hair and skin colour prediction, respectively) to the well-established HIrisPlex-S SNP set (including 6, 22 and 36 SNPs for eye, hair and skin colour prediction respectively). When training prediction models on the CAN data, we observe remarkably similar performances for HIrisPlex-S and the larger CAN SNP sets for the prediction of hair (categorical) and eye (both categorical and quantitative), while the CAN sets outperform HIrisPlex-S for quantitative, but not for categorical skin pigmentation prediction. The performance of HIrisPlex-S, when models are trained in a world-wide sample (although consisting of 80% Europeans, https://hirisplex.erasmusmc.nl), is lower relative to training in the CAN data (particularly for hair and skin colour). Altogether, our observations are consistent with common variation of eye and hair colour having a relatively simple genetic architecture, which is well captured by HIrisPlex-S, even in admixed Latin Americans (with partial European ancestry). By contrast, since skin pigmentation is a more polygenic trait, accuracy is more sensitive to prediction SNP set size, although here this effect was only apparent for a quantitative measure of skin pigmentation. Our results support the use of HIrisPlex-S in the prediction of categorical pigmentation traits for forensic purposes in Latin America, while illustrating the impact of training datasets on its accuracy.
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Affiliation(s)
- Sagnik Palmal
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille 13005, France
| | - Kaustubh Adhikari
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes MK7 6AA, UK; Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London WC1E 6BT, UK
| | - Javier Mendoza-Revilla
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú; Unit of Human Evolutionary Genetics, Institut Pasteur, Paris 75015, France
| | - Macarena Fuentes-Guajardo
- Departamento de Tecnología Médica, Facultad de Ciencias de la Salud, Universidad de Tarapacá, Arica 1000000, Chile
| | | | - Betty Bonfante
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille 13005, France
| | - Juan Camilo Chacón-Duque
- Division of Vertebrates and Anthropology, Department of Earth Sciences, Natural History Museum, London SW7 5BD, UK
| | - Anood Sohail
- Department of Biotechnology, Kinnaird College for Women, 93 - Jail Road, Lahore 54000, Pakistan
| | - Malena Hurtado
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - Valeria Villegas
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - Vanessa Granja
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - Claudia Jaramillo
- Department of Biotechnology, Kinnaird College for Women, 93 - Jail Road, Lahore 54000, Pakistan; GENMOL (Genética Molecular), Universidad de Antioquia, Medellín 5001000, Colombia
| | - William Arias
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín 5001000, Colombia
| | - Rodrigo Barquera Lozano
- National Institute of Anthropology and History, Mexico City 6600, Mexico; Department of Archaeogenetics, Max Planck Institute for the Science of Human History (MPI-SHH), Jena 07745, Germany
| | | | - Jorge Gómez-Valdés
- National Institute of Anthropology and History, Mexico City 6600, Mexico
| | - Hugo Villamil-Ramírez
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City 4510, Mexico
| | - Tábita Hünemeier
- Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP 05508-090, Brazil
| | - Virginia Ramallo
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre 90040-060, Brazil; Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn U9129ACD, Argentina
| | - Maria-Laura Parolin
- Instituto de Diversidad y Evolución Austral (IDEAus), Centro Nacional Patagónico, CONICET, Puerto Madryn, Argentina
| | - Rolando Gonzalez-José
- Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Puerto Madryn U9129ACD, Argentina
| | - Lavinia Schüler-Faccini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre 90040-060, Brazil
| | - Maria-Cátira Bortolini
- Departamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre 90040-060, Brazil
| | | | - Samuel Canizales-Quinteros
- Unidad de Genomica de Poblaciones Aplicada a la Salud, Facultad de Química, UNAM-Instituto Nacional de Medicina Genómica, Mexico City 4510, Mexico
| | - Carla Gallo
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - Giovanni Poletti
- Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 31, Perú
| | - Gabriel Bedoya
- GENMOL (Genética Molecular), Universidad de Antioquia, Medellín 5001000, Colombia
| | - Francisco Rothhammer
- Instituto de Alta Investigación, Universidad de Tarapacá, Arica 1000000, Chile; Programa de Genetica Humana, ICBM, Facultad de Medicina, Universidad de Chile, Santiago, Arica 1000000, Chile
| | - David Balding
- Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London WC1E 6BT, UK; Melbourne Integrative Genomics, Schools of BioSciences and Mathematics & Statistics, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Pierre Faux
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille 13005, France.
| | - Andrés Ruiz-Linares
- UMR 7268 ADES, CNRS, Aix-Marseille Université, EFS, Faculté de Médecine Timone, Marseille 13005, France; Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London WC1E 6BT, UK; Ministry of Education Key Laboratory of Contemporary Anthropology and Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Yangpu District, Shanghai, China.
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48
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Huang Y, Li D, Qiao L, Liu Y, Peng Q, Wu S, Zhang M, Yang Y, Tan J, Xu S, Jin L, Wang S, Tang K, Grünewald S. A genome-wide association study of facial morphology identifies novel genetic loci in Han Chinese. J Genet Genomics 2021; 48:198-207. [PMID: 33593615 DOI: 10.1016/j.jgg.2020.10.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 10/15/2020] [Indexed: 10/23/2022]
Abstract
The human face is a heritable surface with many complex sensory organs. In recent years, many genetic loci associated with facial features have been reported in different populations, yet there is a lack of studies on the Han Chinese population. Here, we report a genome-wide association study of 3D normal human faces of 2,659 Han Chinese with autosegment phenotypes of facial morphology. We identify single-nucleotide polymorphisms (SNPs) encompassing four genomic regions showing significant associations with different facial regions, including SNPs in DENND1B associated with the chin, SNPs among PISRT1 associated with eyes, SNPs between DCHS2 and SFRP2 associated with the nose, and SNPs in VPS13B associated with the nose. We replicate 24 SNPs from previously reported genetic loci in different populations, whose candidate genes are DCHS2, SUPT3H, HOXD1, SOX9, PAX3, and EDAR. These results provide a more comprehensive understanding of the genetic basis of variation in human facial morphology.
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Affiliation(s)
- Yin Huang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China
| | - Dan Li
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China; DeepBlue Technology (Shanghai) Co., Ltd, Shanghai 200336, China
| | - Lu Qiao
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China
| | - Yu Liu
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China
| | - Qianqian Peng
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China
| | - Sijie Wu
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China; State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Manfei Zhang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China; State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Yajun Yang
- State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200433, China; Fudan-Taizhou Institute of Health Sciences, Taizhou 225300, China
| | - Jingze Tan
- State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200433, China; Fudan-Taizhou Institute of Health Sciences, Taizhou 225300, China
| | - Shuhua Xu
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China; Collaborative Innovation Center of Genetics and Development, Shanghai 200438, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650223, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Li Jin
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China; State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200433, China; Fudan-Taizhou Institute of Health Sciences, Taizhou 225300, China; Collaborative Innovation Center of Genetics and Development, Shanghai 200438, China
| | - Sijia Wang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China; Collaborative Innovation Center of Genetics and Development, Shanghai 200438, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650223, China.
| | - Kun Tang
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China; DeepBlue Technology (Shanghai) Co., Ltd, Shanghai 200336, China.
| | - Stefan Grünewald
- Chinese Academy of Sciences Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai 200031, China.
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49
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Kataoka K, Fujita H, Isa M, Gotoh S, Arasaki A, Ishida H, Kimura R. The human EDAR 370V/A polymorphism affects tooth root morphology potentially through the modification of a reaction-diffusion system. Sci Rep 2021; 11:5143. [PMID: 33664401 PMCID: PMC7933414 DOI: 10.1038/s41598-021-84653-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 02/15/2021] [Indexed: 01/31/2023] Open
Abstract
Morphological variations in human teeth have long been recognized and, in particular, the spatial and temporal distribution of two patterns of dental features in Asia, i.e., Sinodonty and Sundadonty, have contributed to our understanding of the human migration history. However, the molecular mechanisms underlying such dental variations have not yet been completely elucidated. Recent studies have clarified that a nonsynonymous variant in the ectodysplasin A receptor gene (EDAR 370V/A; rs3827760) contributes to crown traits related to Sinodonty. In this study, we examined the association between the EDAR polymorphism and tooth root traits by using computed tomography images and identified that the effects of the EDAR variant on the number and shape of roots differed depending on the tooth type. In addition, to better understand tooth root morphogenesis, a computational analysis for patterns of tooth roots was performed, assuming a reaction-diffusion system. The computational study suggested that the complicated effects of the EDAR polymorphism could be explained when it is considered that EDAR modifies the syntheses of multiple related molecules working in the reaction-diffusion dynamics. In this study, we shed light on the molecular mechanisms of tooth root morphogenesis, which are less understood in comparison to those of tooth crown morphogenesis.
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Affiliation(s)
- Keiichi Kataoka
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa, 903-0215, Japan
- Department of Oral and Maxillofacial Functional Rehabilitation, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Hironori Fujita
- Astrobiology Center, National Institutes of Natural Sciences, Tokyo, Japan
- National Institute for Basic Biology, National Institutes of Natural Sciences, Aichi, Japan
- Department of Basic Biology, School of Life Science, SOKENDAI (The Graduate School for Advanced Studies), Aichi, Japan
| | - Mutsumi Isa
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa, 903-0215, Japan
| | - Shimpei Gotoh
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa, 903-0215, Japan
- Department of Oral and Maxillofacial Functional Rehabilitation, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Akira Arasaki
- Department of Oral and Maxillofacial Functional Rehabilitation, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Hajime Ishida
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa, 903-0215, Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa, 903-0215, Japan.
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50
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Fischer C, Koblmüller S, Börger C, Michelitsch G, Trajanoski S, Schlötterer C, Guelly C, Thallinger GG, Sturmbauer C. Genome sequences of Tropheus moorii and Petrochromis trewavasae, two eco-morphologically divergent cichlid fishes endemic to Lake Tanganyika. Sci Rep 2021; 11:4309. [PMID: 33619328 PMCID: PMC7900123 DOI: 10.1038/s41598-021-81030-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Accepted: 12/28/2020] [Indexed: 01/01/2023] Open
Abstract
With more than 1000 species, East African cichlid fishes represent the fastest and most species-rich vertebrate radiation known, providing an ideal model to tackle molecular mechanisms underlying recurrent adaptive diversification. We add high-quality genome reconstructions for two phylogenetic key species of a lineage that diverged about ~ 3-9 million years ago (mya), representing the earliest split of the so-called modern haplochromines that seeded additional radiations such as those in Lake Malawi and Victoria. Along with the annotated genomes we analysed discriminating genomic features of the study species, each representing an extreme trophic morphology, one being an algae browser and the other an algae grazer. The genomes of Tropheus moorii (TM) and Petrochromis trewavasae (PT) comprise 911 and 918 Mbp with 40,300 and 39,600 predicted genes, respectively. Our DNA sequence data are based on 5 and 6 individuals of TM and PT, and the transcriptomic sequences of one individual per species and sex, respectively. Concerning variation, on average we observed 1 variant per 220 bp (interspecific), and 1 variant per 2540 bp (PT vs PT)/1561 bp (TM vs TM) (intraspecific). GO enrichment analysis of gene regions affected by variants revealed several candidates which may influence phenotype modifications related to facial and jaw morphology, such as genes belonging to the Hedgehog pathway (SHH, SMO, WNT9A) and the BMP and GLI families.
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Affiliation(s)
- C Fischer
- Institute of Biology, University of Graz, Graz, Austria
- Institute of Biomedical Informatics, Graz University of Technology, Graz, Austria
| | - S Koblmüller
- Institute of Biology, University of Graz, Graz, Austria
| | - C Börger
- Institute of Biology, University of Graz, Graz, Austria
| | - G Michelitsch
- Center for Medical Research, Medical University of Graz, Graz, Austria
| | - S Trajanoski
- Center for Medical Research, Medical University of Graz, Graz, Austria
| | - C Schlötterer
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | - C Guelly
- Center for Medical Research, Medical University of Graz, Graz, Austria
| | - G G Thallinger
- Institute of Biomedical Informatics, Graz University of Technology, Graz, Austria.
- BioTechMed-Graz, Graz, Austria.
| | - C Sturmbauer
- Institute of Biology, University of Graz, Graz, Austria.
- BioTechMed-Graz, Graz, Austria.
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