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Published in Douglas D. Gunzler, Adam T. Perzynski, Adam C. Carle, Structural Equation Modeling for Health and Medicine, 2021
Douglas D. Gunzler, Adam T. Perzynski, Adam C. Carle
Genome-wide association studies (GWAS) are observational studies to identify genes involved in human disease. Researchers use data from these types of studies to pinpoint genes that influence the risk of developing certain diseases.
Clinical Cancer Genetics
Published in Pat Price, Karol Sikora, Treatment of Cancer, 2020
Rosalind A. Eeles, Lisa J. Walker
The advent of Genome-Wide Association Studies (GWAS) means that this is one way to identify single nucleotide changes, sometimes genes, and even markers that are associated with increased risk of conditions including cancers. The level of risk is not markedly increased for each variant; however as the risks are multiplicative these can give risk to substantial risks in a proportion of individuals who carry many of the risk variants. There are over 1000 such variants reported to be associated with disease traits (www.genome.gov/gwastudies/). Much work is still required to establish the significance of these findings, in particular the functional effects of these variants and their clinical application in the stratification of populations for targeted screening and their role in clinical care.
The Meta-Analysis of Genetic Studies
Published in Christopher H. Schmid, Theo Stijnen, Ian R. White, Handbook of Meta-Analysis, 2020
Cosetta Minelli, John Thompson
A genome-wide association study is an epidemiological design in which hundreds of thousands of genetic variants are measured in order to discover which of them are associated with a particular disease or trait. The participants are usually recruited in a case-control or a cohort design and the measured genetic variants are usually SNPs.
The rs1333040 and rs10757278 9p21 locus polymorphisms in patients with intracranial aneurysm: a meta-analysis
Published in International Journal of Neuroscience, 2023
Antonis Adamou, Georgios Mavrovounis, Eleftherios T. Beltsios, Ioannis Liampas, Zisis Tsouris, Athina-Maria Aloizou, Vasileios Siokas, Efthimios Dardiotis
Finally, our meta-analysis has several limitations that need to be addressed. The major limitation of our study is the limited number of publications and subjects included in the final meta-analysis. Having mentioned that, our results should be interpreted with care and generalizations should be avoided. There is a certain need for studies with a larger number of subjects in order to reach certain conclusions. This should be facilitated by the execution of larger GWAS. Moreover, we included studies using first generation sequencing methods (SNPs), which is considered as a relatively old method. Despite being old, it is not rendered obsolete, thus we analyzed the available data of this method to draw certain conclusions. In addition, studies with both hospitalized and healthy controls were included in our analyses. It is comprehensible that financial and ethical parameters impede the appropriate neuroimaging of healthy controls, probably inducing misclassification bias. On the other hand, the inclusion of hospitalized controls having undergone neuroimaging may be accountable for the induction selection bias (inclusion of patients with allele frequency different from the general population). Therefore, it was not possible for any study to involve an appropriate control group (healthy controls having undergone proper neuroimaging).
Human height: a model common complex trait
Published in Annals of Human Biology, 2023
Mitchell Conery, Struan F. A. Grant
In summary, height is broadly similar to other complex phenotypes apart from its ease of measurement and high heritability. These factors have made it a widely employed model trait for studying the topic of complex phenotype inheritance. However, throughout the GWAS era, height has not always been at the leading edge of variant and gene discovery, that is until its most recent GWAS by Yengo et al. In having at last closed the gap of missing common SNP-based heritability for a common trait, Yengo et al. may have signalled the beginning of the end of the GWAS era. Their work demonstrates the limits to endlessly increasing GWAS sample sizes and highlights the need for greater diversity in study populations. Moreover, their results directly contradict the most extreme form of the omnigenic model and imply that highly polygenic inheritance is likely a more appropriate model for complex traits. The analysed polygenic score results also suggest that when sample sizes across complex phenotype GWAS efforts increase to the point of heritability saturation across all ancestries, polygenic risk scores will become powerful tools for the prediction of disease risk. However, the implications of this study for the identification of individual effector disease genes are less optimistic. Should the GWAS era be drawing to a close, the era of gene identification that follows will surely be one of both great challenges and opportunities.
Linkage analysis identifies novel genetic modifiers of microbiome traits in families with inflammatory bowel disease
Published in Gut Microbes, 2022
Arunabh Sharma, Silke Szymczak, Malte Rühlemann, Sandra Freitag-Wolf, Carolin Knecht, Janna Enderle, Stefan Schreiber, Andre Franke, Wolfgang Lieb, Michael Krawczak, Astrid Dempfle
Most previous studies of the connection between gut microbiome and genetic variation employed a GWAS approach. However, GWAS are usually unable to discern the impact of rare variants upon the microbiome and, particularly when carried out in population-representative samples, cannot take the specificities of a certain disease context into account. This prompted us to adopt a family-based design to study the link between host genetics and gut microbiome in IBD etiology. Family-based studies are capable of localizing genetic effects irrespective of the frequencies of the variants involved as long as the effects of interest segregate in families.17,18 We therefore used genetic and microbiome data from the IBD kindred cohort (IBD-KC), a nationwide prospective study in Germany of IBD patients and their families, to examine the heritability of the abundance of individual microbial genera and the diversity of whole microbiomes, followed by a genome-wide quantitative trait locus (QTL) linkage analysis of the abundances and α diversity at genus level. Finally, we performed association analyses within the identified linkage regions to identify individual SNPs associated with one or more of these microbiome traits.