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Axial Spondyloarthritis
Published in Jason Liebowitz, Philip Seo, David Hellmann, Michael Zeide, Clinical Innovation in Rheumatology, 2023
A genetic contribution to AxSpA has long been recognized, primarily via the HLA-B27 gene. To date, there have not been consistent data suggesting any specific genetic risk for progressive disease. It is likely that risk for progression may be polygenic and mediated by environmental exposures and other factors. In the coming decade, we may further elucidate the role of specific genes in pathogenesis and, potentially, ability to obtain a polygenic risk score at onset of disease for prognostic purposes.47
Preimplantation Genetic Testing for Polygenic Disorders
Published in Carlos Simón, Carmen Rubio, Handbook of Genetic Diagnostic Technologies in Reproductive Medicine, 2022
Nathan R. Treff, Diego Marin, Laurent C. A. M. Tellier
When a DNA sequence-based predictor of polygenic disease is applied to individuals, it is often referred to as polygenic risk scoring (13). Stratification of individuals based on polygenic risk scores can be performed before diseases typically manifest in adulthood (5,14). Interest in polygenic risk scoring has therefore rapidly grown from a solid foundation in basic research to contemplation of systematic implementation by national healthcare policymakers (15). With the low cost of genome-wide DNA analysis, many countries are considering universal population testing, with the goal of early identification of high-risk individuals leading to overall reduction in healthcare costs and improvement in human health (16). Indeed, early detection and prevention of disease is a concept that has driven national research endeavors including the original human genome project (17).
Radiobiology of Normal Tissues
Published in W. P. M. Mayles, A. E. Nahum, J.-C. Rosenwald, Handbook of Radiotherapy Physics, 2021
Individuals have 23 pairs of chromosomes (one inherited from each parent) and therefore, two copies of every gene. If a person has a mutation in both copies, they are known as homozygotes. The syndromes listed in the previous paragraph are associated with homozygous mutations, and these are rare. More of us are heterozygotes, i.e. carrying one copy of a particular gene (and therefore, a mutation in just one chromosome). These tend to be carried in a recessive mode, i.e. without expressing the syndrome itself. Heterozygotes for a radiosensitivity gene do not show the same level of sensitivity as the homozygote (who carries two identical copies of a particular gene), but they may show a tendency towards increased radiation damage. When a heterozygote mutation is seen in a large proportion of a population (>1%), it is called a single nucleotide polymorphism (SNP). SNPs are the most common type of genetic variation between individuals. SNPs affect phenotypes (e.g. eye colour and height) and disease susceptibility. Many traits (e.g. eye colour and height) are termed polygenic; i.e. SNPs in multiple genes (hundreds) affect the trait, with each having a small effect but together, a large effect. Current studies are attempting to identify the genetic variants that influence radiation sensitivity and exploring tests that measure an individual patient's radiosensitivity (Barnett et al. 2012).
Non-Invasive Prenatal Testing for “Non-Medical” Traits: Ensuring Consistency in Ethical Decision-Making
Published in The American Journal of Bioethics, 2023
Hilary Bowman-Smart, Christopher Gyngell, Cara Mand, David J. Amor, Martin B. Delatycki, Julian Savulescu
Information about non-medical traits might be provided through testing for specific variants or chromosomal changes. For example, the 15q11.2 microdeletion involving NIPA1 decreases IQ by an average of 4.3 points, which would be considered a sub-clinical impact on cognitive ability, although it also slightly increases the chance of intellectual disability (Jønch et al. 2019). It may also be possible to use polygenic scores—a score calculated from the contribution of many genetic variants—to predict a variety of non-medical traits such as cognitive ability, creativity, height and appearance (Lewis and Green 2021; Munday and Savulescu 2021). Polygenic scores for medical conditions such as diabetes and heart disease are frequently discussed in the clinical context as part of a move toward “personalized medicine” (Yanes et al. 2020); here, we focus on their use for non-medical traits.
Vitamin D-Binding Protein and Acute Myeloid Leukemia: A Genetic Association Analysis in Combination with Vitamin D Levels
Published in Nutrition and Cancer, 2023
Saeedeh Ghazaey Zidanloo, Danial Jahantigh, Nafiseh Amini
The overall analysis suggests that patients who were carriers of the mutant allele of the VDBP gene at positions rs4588 and rs7041 were significantly susceptible to AML, especially in the adult subgroup. Moreover, our results confirm that the risk of AML development depends on an interaction between VDBP genotypes and vitamin D status. Lower 25(OH)D levels were found to be associated with an increased incidence of AML, hence individuals with 25(OH)D deficiency, who are carriers of mutant alleles of VDBP gene variations (rs7041 G allele and rs4588 A allele), may be at higher risk of AML. Thus, clinicians are recommended to consider the genotypes of AML patients and evaluate their vitamin status before performing risk assessment and treatment. More extensive analyses should be conducted to confirm the role of these genetic variants of vitamin D metabolism in AML development. Ultimately, polygenic risk scores could be developed to improve personalized preventive medicine.
Human height: a model common complex trait
Published in Annals of Human Biology, 2023
Mitchell Conery, Struan F. A. Grant
Aside from exploring how well their GWAS saturated the discovery of height genetics, Yengo et al. also investigated the ability of their results to accurately predict height across ancestries using polygenic scores. Polygenic scores and risk scores predict individuals’ values and risks of complex traits and diseases respectively. Generally, these terms refer to statistical models that make genetic-based predictions using GWAS-estimated variant effect sizes (Sugrue and Desikan 2019; Wang et al. 2022), though under some definitions they may denote any genetics-based statistical or machine-learning model designed to predict phenotypes (Wand et al. 2021). Prior to the latest height GWAS, polygenic scores and risk scores had shown relatively modest success at predicting traits and disease risk for individuals drawn from the population used to create the scoring metrics (Schrodi et al. 2014; Hu et al. 2017). Though generally used on unrelated individuals, at least in the case of height polygenic scores, they can differentiate between siblings (Lello et al. 2020). It has been similarly shown that in order for these scores to obtain their maximum accuracy, they should include both coding and non-coding associated variants (Yong et al. 2020).