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      Facial Genetics: A Brief Overview

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          Abstract

          Historically, craniofacial genetic research has understandably focused on identifying the causes of craniofacial anomalies and it has only been within the last 10 years, that there has been a drive to detail the biological basis of normal-range facial variation. This initiative has been facilitated by the availability of low-cost hi-resolution three-dimensional systems which have the ability to capture the facial details of thousands of individuals quickly and accurately. Simultaneous advances in genotyping technology have enabled the exploration of genetic influences on facial phenotypes, both in the present day and across human history.

          There are several important reasons for exploring the genetics of normal-range variation in facial morphology.

              - Disentangling the environmental factors and relative parental biological contributions to heritable traits can help to answer the age-old question “why we look the way that we do?”

              - Understanding the etiology of craniofacial anomalies; e.g., unaffected family members of individuals with non-syndromic cleft lip/palate (nsCL/P) have been shown to differ in terms of normal-range facial variation to the general population suggesting an etiological link between facial morphology and nsCL/P.

              - Many factors such as ancestry, sex, eye/hair color as well as distinctive facial features (such as, shape of the chin, cheeks, eyes, forehead, lips, and nose) can be identified or estimated using an individual’s genetic data, with potential applications in healthcare and forensics.

              - Improved understanding of historical selection and adaptation relating to facial phenotypes, for example, skin pigmentation and geographical latitude.

              - Highlighting what is known about shared facial traits, medical conditions and genes.

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          Most cited references156

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          'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?

          Associations between modifiable exposures and disease seen in observational epidemiology are sometimes confounded and thus misleading, despite our best efforts to improve the design and analysis of studies. Mendelian randomization-the random assortment of genes from parents to offspring that occurs during gamete formation and conception-provides one method for assessing the causal nature of some environmental exposures. The association between a disease and a polymorphism that mimics the biological link between a proposed exposure and disease is not generally susceptible to the reverse causation or confounding that may distort interpretations of conventional observational studies. Several examples where the phenotypic effects of polymorphisms are well documented provide encouraging evidence of the explanatory power of Mendelian randomization and are described. The limitations of the approach include confounding by polymorphisms in linkage disequilibrium with the polymorphism under study, that polymorphisms may have several phenotypic effects associated with disease, the lack of suitable polymorphisms for studying modifiable exposures of interest, and canalization-the buffering of the effects of genetic variation during development. Nevertheless, Mendelian randomization provides new opportunities to test causality and demonstrates how investment in the human genome project may contribute to understanding and preventing the adverse effects on human health of modifiable exposures.
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            Orienting the causal relationship between imprecisely measured traits using GWAS summary data

            Inference about the causal structure that induces correlations between two traits can be achieved by combining genetic associations with a mediation-based approach, as is done in the causal inference test (CIT). However, we show that measurement error in the phenotypes can lead to the CIT inferring the wrong causal direction, and that increasing sample sizes has the adverse effect of increasing confidence in the wrong answer. This problem is likely to be general to other mediation-based approaches. Here we introduce an extension to Mendelian randomisation, a method that uses genetic associations in an instrumentation framework, that enables inference of the causal direction between traits, with some advantages. First, it can be performed using only summary level data from genome-wide association studies; second, it is less susceptible to bias in the presence of measurement error or unmeasured confounding. We apply the method to infer the causal direction between DNA methylation and gene expression levels. Our results demonstrate that, in general, DNA methylation is more likely to be the causal factor, but this result is highly susceptible to bias induced by systematic differences in measurement error between the platforms, and by horizontal pleiotropy. We emphasise that, where possible, implementing MR and appropriate sensitivity analyses alongside other approaches such as CIT is important to triangulate reliable conclusions about causality.
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              Stability and flexibility of epigenetic gene regulation in mammalian development.

              Wolf Reik (2007)
              During development, cells start in a pluripotent state, from which they can differentiate into many cell types, and progressively develop a narrower potential. Their gene-expression programmes become more defined, restricted and, potentially, 'locked in'. Pluripotent stem cells express genes that encode a set of core transcription factors, while genes that are required later in development are repressed by histone marks, which confer short-term, and therefore flexible, epigenetic silencing. By contrast, the methylation of DNA confers long-term epigenetic silencing of particular sequences--transposons, imprinted genes and pluripotency-associated genes--in somatic cells. Long-term silencing can be reprogrammed by demethylation of DNA, and this process might involve DNA repair. It is not known whether any of the epigenetic marks has a primary role in determining cell and lineage commitment during development.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                16 October 2018
                2018
                : 9
                : 462
                Affiliations
                [1] 1Applied Clinical Research and Public Health, School of Dentistry, College of Biomedical and Life Sciences, Cardiff University , Cardiff, United Kingdom
                [2] 2MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol , Bristol, United Kingdom
                [3] 3Institute of Cardiovascular Science, University College London , London, United Kingdom
                [4] 4School of Oral and Dental Sciences, University of Bristol , Bristol, United Kingdom
                Author notes

                Edited by: Peter Claes, KU Leuven, Belgium

                Reviewed by: Hui-Qi Qu, Children’s Hospital of Philadelphia, United States; Eppo Wolvius, Erasmus Medical Center, Erasmus University Rotterdam, Netherlands

                *Correspondence: Stephen Richmond, richmonds@ 123456cardiff.ac.uk

                This article was submitted to Applied Genetic Epidemiology, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2018.00462
                6198798
                30386375
                103779a6-a604-4145-8d77-f70fc98344ca
                Copyright © 2018 Richmond, Howe, Lewis, Stergiakouli and Zhurov.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 06 July 2018
                : 20 September 2018
                Page count
                Figures: 1, Tables: 3, Equations: 0, References: 181, Pages: 21, Words: 0
                Categories
                Genetics
                Review

                Genetics
                3d imaging,admixture,ancestry,facial variation,geometric morphometrics,facial genetics,facial phenotyping,genetic-environmental influences

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