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Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk
Infectious diseases still threaten global human health, and host genetic factors have been indicated as determining risk factors for observed variations in disease susceptibility, severity, and outcome. We performed a genome-wide meta-analysis on 4624 subjects from the 10,001 Dalmatians cohort, with...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138356/ https://www.ncbi.nlm.nih.gov/pubmed/37108169 http://dx.doi.org/10.3390/ijms24087006 |
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author | Gelemanović, Andrea Ćatipović Ardalić, Tatjana Pribisalić, Ajka Hayward, Caroline Kolčić, Ivana Polašek, Ozren |
author_facet | Gelemanović, Andrea Ćatipović Ardalić, Tatjana Pribisalić, Ajka Hayward, Caroline Kolčić, Ivana Polašek, Ozren |
author_sort | Gelemanović, Andrea |
collection | PubMed |
description | Infectious diseases still threaten global human health, and host genetic factors have been indicated as determining risk factors for observed variations in disease susceptibility, severity, and outcome. We performed a genome-wide meta-analysis on 4624 subjects from the 10,001 Dalmatians cohort, with 14 infection-related traits. Despite a rather small number of cases in some instances, we detected 29 infection-related genetic associations, mostly belonging to rare variants. Notably, the list included the genes CD28, INPP5D, ITPKB, MACROD2, and RSF1, all of which have known roles in the immune response. Expanding our knowledge on rare variants could contribute to the development of genetic panels that could assist in predicting an individual’s life-long susceptibility to major infectious diseases. In addition, longitudinal biobanks are an interesting source of information for identifying the host genetic variants involved in infectious disease susceptibility and severity. Since infectious diseases continue to act as a selective pressure on our genomes, there is a constant need for a large consortium of biobanks with access to genetic and environmental data to further elucidate the complex mechanisms behind host–pathogen interactions and infectious disease susceptibility. |
format | Online Article Text |
id | pubmed-10138356 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101383562023-04-28 Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk Gelemanović, Andrea Ćatipović Ardalić, Tatjana Pribisalić, Ajka Hayward, Caroline Kolčić, Ivana Polašek, Ozren Int J Mol Sci Article Infectious diseases still threaten global human health, and host genetic factors have been indicated as determining risk factors for observed variations in disease susceptibility, severity, and outcome. We performed a genome-wide meta-analysis on 4624 subjects from the 10,001 Dalmatians cohort, with 14 infection-related traits. Despite a rather small number of cases in some instances, we detected 29 infection-related genetic associations, mostly belonging to rare variants. Notably, the list included the genes CD28, INPP5D, ITPKB, MACROD2, and RSF1, all of which have known roles in the immune response. Expanding our knowledge on rare variants could contribute to the development of genetic panels that could assist in predicting an individual’s life-long susceptibility to major infectious diseases. In addition, longitudinal biobanks are an interesting source of information for identifying the host genetic variants involved in infectious disease susceptibility and severity. Since infectious diseases continue to act as a selective pressure on our genomes, there is a constant need for a large consortium of biobanks with access to genetic and environmental data to further elucidate the complex mechanisms behind host–pathogen interactions and infectious disease susceptibility. MDPI 2023-04-10 /pmc/articles/PMC10138356/ /pubmed/37108169 http://dx.doi.org/10.3390/ijms24087006 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Gelemanović, Andrea Ćatipović Ardalić, Tatjana Pribisalić, Ajka Hayward, Caroline Kolčić, Ivana Polašek, Ozren Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk |
title | Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk |
title_full | Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk |
title_fullStr | Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk |
title_full_unstemmed | Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk |
title_short | Genome-Wide Meta-Analysis Identifies Multiple Novel Rare Variants to Predict Common Human Infectious Diseases Risk |
title_sort | genome-wide meta-analysis identifies multiple novel rare variants to predict common human infectious diseases risk |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138356/ https://www.ncbi.nlm.nih.gov/pubmed/37108169 http://dx.doi.org/10.3390/ijms24087006 |
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