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Biochemical Markers in Ophthalmology
Published in Ching-Yu Cheng, Tien Yin Wong, Ophthalmic Epidemiology, 2022
Abdus Samad Ansari, Pirro G. Hysi
The genetic architecture of common traits and disorders is more complex. These traits and disorders tend to have a more elaborate genetic architecture, where a large number of common variants located over the entire genome, each with individually small effects, tend to collectively explain the majority of the phenotypic heritability [15]. Although phenotypically powerful rare variants may contribute to common disorders [16], their contribution at the general population level is often modest.
Common disorders and genetic counselling
Published in Angus Clarke, Alex Murray, Julian Sampson, Harper's Practical Genetic Counselling, 2019
The terms ‘multifactorial’ or ‘polygenic’ are frequently used to describe the genetic basis underlying the great majority of common disorders where there is no clear Mendelian pattern. Of the two terms, multifactorial is the more appropriate since it recognises that these disorders are the result of both environmental and genetic factors and does not prejudge the relative role of either category. ‘Polygenic’ means that many different genetic loci are involved, and usually implies that there is a very large number of such factors involved, each being of very small effect, and that their influences combine in a straightforward fashion. In fact, for many diseases where the ‘genetic architecture’ of disease susceptibility has been examined, there is rather a spectrum of genetic factors ranging from rare genetic variants of large effect, through a moderate number of genetic variants of lesser but still substantial effect (sometimes known as ‘oligogenes’), to a multitude of genetic variants of small or very small effect. Very little is known about the way these factors interact. It is often simply assumed that they interact in regular, predictable patterns (with relative risks being combined multiplicatively, as if they were independent) because the research that would be needed to measure the complex interactions between the different factors would be so demanding.
Applications of imaging genomics beyond oncology
Published in Ruijiang Li, Lei Xing, Sandy Napel, Daniel L. Rubin, Radiomics and Radiogenomics, 2019
Xiaohui Yao, Jingwen Yan, Li Shen
Also, efforts have been made in AD genetic research to investigate the role of various types of genetic variants including rare variants and copy number variants (CNVs) to help improve the understanding of genetic architecture of AD [37,38]. However, besides the well-known APOE genotype explaining an estimated 20% genetic variance of LOAD [18], other genetic findings have suggested only small size of disease effect and have been rarely replicated [39].
Gene-environment Interaction in Spherical Equivalent and Myopia: An Evidence-based Review
Published in Ophthalmic Epidemiology, 2022
Xiyan Zhang, Qiao Fan, Fengyun Zhang, Gang Liang, Chen-Wei Pan
Gene-environment effects, which might play an essential role in the increasing trend of myopia, should be considered.23–26 Moreover, it could offer an attractive explanation for how environmental exposures and genetic factors can contribute to the change of myopia prevalence. Gene-environment interaction on myopia can be defined as “a different effect of an environmental exposure (near work/ outdoor activities) on myopia with different candidate genetic factors,” or equivalently “a different effect of a candidate gene on myopia with different environmental exposures”.27 Why should the interaction effect be studied? Traditional studies cannot explain the relationship between statistical interactions at the population level and biological interactions at the individual level. Potentially gene-environment interactions allow us better to understand the underlying genetic architecture of a particular trait, and as such we can begin to fill in the missing heritability for a particular phenotype.28 However, data on the relationship between gene-environment interaction and myopia in previous studies is limited. We conducted a systematic review to give a more comprehensive display of the current research on this issue.
The Overlap between Genetic Susceptibility to COVID-19 and Skin Diseases
Published in Immunological Investigations, 2022
Navid Jabalameli, Fateme Rajabi, Alireza Firooz, Nima Rezaei
Since the emergence of the new coronavirus disease 19 (COVID-19) pandemic, many attempts have been made to identify the risk factors of getting severely ill with the virus. Though several factors such as age, and sex were identified early on, they were not able to explain the devastating casualties in young and healthy individuals. Genetic studies could provide more insight into this matter. The results of these genetic studies can be more understandable when they are translated into clinical traits. Most genetic variants however are not linked to a specific phenotype and multiple alleles with modest effect size are combined to result in a clinical phenotype. In these instances, finding diseases that share the same genetic architecture provides valuable data for risk assessment based on the presence of the meta-traits (Li et al. 2012, 2014). Genetic studies might also help in understanding the disease pathogenesis, and its potential drug targets. In this report, we have discussed the potential overlaps between genetic susceptibility to major cutaneous diseases and that of severe COVID-19.
Cohort profile and heritability assessment of familial pancreatic cancer: a nation-wide study
Published in Scandinavian Journal of Gastroenterology, 2021
Ming Tan, Klaus Brusgaard, Anne-Marie Gerdes, Michael Bau Mortensen, Sönke Detlefsen, Ove B. Schaffalitzky de Muckadell, Maiken Thyregod Joergensen
This study estimated the heritability of FPC based on PDAC phenotype correlation among FDRs to assess the overall genetic contribution to FPC without using genomic information. This is similar to the traditional twin studies that estimate heritability based on phenotype correlation in twin pairs with no molecular data needed. In genetic epidemiology, a moderate to high heritability estimate calls for the practice to explore the genetic architecture of the disease using genetic association studies. The estimated heritability of 51% for FPC highlights the importance of investigating genetic variations underlying the etiology of the disease. While the phenotype-based heritability estimate provides an overall assessment of genetic contribution to FPC, genetic association studies including GWAS based on genomic information can help to identify the DNA sequence variations associated with FPC. A GWAS conducted on patients with family history of pancreatic cancer or diagnosed under age 50 reported multiple SNPs influencing risk of PDAC and other cancers [32]. However, it is now widely known that the common genetic variants detected by GWAS only explain a limited proportion of the estimated overall genetic contribution (heritability) to a specific complex disorder – a phenomenon referred to as the ‘missing heritability’ problem, and thus rare variants association analysis has been proposed as an alternative to GWAS to dissolve the issue [33].