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From genetic discovery to future personalized health research

During the past ten years the field of human disease genetics has made major leaps, including the completion of the Human Genome Project, the HapMap Project, the development of the genome-wide association (GWA) studies to identify common disease-predisposing variants and the introduction of large-sc...

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Autores principales: Palotie, Aarno, Widén, Elisabeth, Ripatti, Samuli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3627963/
https://www.ncbi.nlm.nih.gov/pubmed/23165095
http://dx.doi.org/10.1016/j.nbt.2012.11.013
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author Palotie, Aarno
Widén, Elisabeth
Ripatti, Samuli
author_facet Palotie, Aarno
Widén, Elisabeth
Ripatti, Samuli
author_sort Palotie, Aarno
collection PubMed
description During the past ten years the field of human disease genetics has made major leaps, including the completion of the Human Genome Project, the HapMap Project, the development of the genome-wide association (GWA) studies to identify common disease-predisposing variants and the introduction of large-scale whole-genome and whole-exome sequencing studies. The introduction of new technologies has enabled researchers to utilize novel study designs to tackle previously unexplored research questions in human genomics. These new types of studies typically need large sample sizes to overcome the multiple testing challenges caused by the huge number of interrogated genetic variants. As a consequence, large consortia-studies are at present the default in disease genetics research. The systematic planning of the GWA-studies was a key element in the success of the approach. Similar planning and rigor in statistical inferences will probably be beneficial also to future sequencing studies. Already today, the next-generation exome sequencing has led to the identification of several genes underlying Mendelian diseases. In spite of the clear benefits, the method has proven to be more challenging than anticipated. In the case of complex diseases, next-generation sequencing aims to identify disease-associated low-frequency alleles. However, their robust detection will require very large study samples, even larger than in the case of the GWA-studies. This has stimulated study designs that capitalize on enriching sets of low-frequency alleles, for example, studies focusing on population isolates such as Finland or Iceland. One example is the collaborative SISu Project (Sequencing Initiative Suomi) that aims to provide near complete genome variation information from Finnish study samples and pave the way for large, nationwide genome health initiative studies.
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spelling pubmed-36279632013-04-17 From genetic discovery to future personalized health research Palotie, Aarno Widén, Elisabeth Ripatti, Samuli N Biotechnol Research Paper During the past ten years the field of human disease genetics has made major leaps, including the completion of the Human Genome Project, the HapMap Project, the development of the genome-wide association (GWA) studies to identify common disease-predisposing variants and the introduction of large-scale whole-genome and whole-exome sequencing studies. The introduction of new technologies has enabled researchers to utilize novel study designs to tackle previously unexplored research questions in human genomics. These new types of studies typically need large sample sizes to overcome the multiple testing challenges caused by the huge number of interrogated genetic variants. As a consequence, large consortia-studies are at present the default in disease genetics research. The systematic planning of the GWA-studies was a key element in the success of the approach. Similar planning and rigor in statistical inferences will probably be beneficial also to future sequencing studies. Already today, the next-generation exome sequencing has led to the identification of several genes underlying Mendelian diseases. In spite of the clear benefits, the method has proven to be more challenging than anticipated. In the case of complex diseases, next-generation sequencing aims to identify disease-associated low-frequency alleles. However, their robust detection will require very large study samples, even larger than in the case of the GWA-studies. This has stimulated study designs that capitalize on enriching sets of low-frequency alleles, for example, studies focusing on population isolates such as Finland or Iceland. One example is the collaborative SISu Project (Sequencing Initiative Suomi) that aims to provide near complete genome variation information from Finnish study samples and pave the way for large, nationwide genome health initiative studies. Elsevier 2013-03-25 /pmc/articles/PMC3627963/ /pubmed/23165095 http://dx.doi.org/10.1016/j.nbt.2012.11.013 Text en © 2013 Elsevier B.V. https://creativecommons.org/licenses/by/3.0/ Open Access under CC BY 3.0 (https://creativecommons.org/licenses/by/3.0/) license
spellingShingle Research Paper
Palotie, Aarno
Widén, Elisabeth
Ripatti, Samuli
From genetic discovery to future personalized health research
title From genetic discovery to future personalized health research
title_full From genetic discovery to future personalized health research
title_fullStr From genetic discovery to future personalized health research
title_full_unstemmed From genetic discovery to future personalized health research
title_short From genetic discovery to future personalized health research
title_sort from genetic discovery to future personalized health research
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3627963/
https://www.ncbi.nlm.nih.gov/pubmed/23165095
http://dx.doi.org/10.1016/j.nbt.2012.11.013
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