Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms
- Autores
- López Soto, Eduardo Javier; Catanesi, Cecilia Inés
- Año de publicación
- 2015
- Idioma
- español castellano
- Tipo de recurso
- artículo
- Estado
- versión enviada
- Descripción
- Several single nucleotide polymorphisms (SNPs) in the Mu Opioid Receptor gene (OPRM1) have been identified and associated with a wide variety of clinical phenotypes related both to pain sensitivity and analgesic requirements. The A118G and other potentially functional OPRM1 SNPs show significant differences in their allele distributions among populations. However, they have not been properly addressed in a population genetic analysis. Population stratification could lead to erroneous conclusions when they are not taken into account in association studies. The aim of our study was to analyze OPRM1 SNP variability by comparing population samples of the International Hap Map database and to analyze a new population sample from the city of Corrientes, Argentina. The results confirm that OPRM1 SNP variability differs among human populations and displays a clear ancestry genetic structure, with three population clusters: Africa, Asia, and Europe-America.
- Materia
-
Biología Celular, Microbiología
OPRM1
SNPs
A118G
AMOVA
population genetics - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/2352
Ver los metadatos del registro completo
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oai:digital.cic.gba.gob.ar:11746/2352 |
network_acronym_str |
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network_name_str |
CIC Digital (CICBA) |
spelling |
Human population genetic structure detected by pain-related mu opioid receptor gene polymorphismsLópez Soto, Eduardo JavierCatanesi, Cecilia InésBiología Celular, MicrobiologíaOPRM1SNPsA118GAMOVApopulation geneticsSeveral single nucleotide polymorphisms (SNPs) in the Mu Opioid Receptor gene (OPRM1) have been identified and associated with a wide variety of clinical phenotypes related both to pain sensitivity and analgesic requirements. The A118G and other potentially functional OPRM1 SNPs show significant differences in their allele distributions among populations. However, they have not been properly addressed in a population genetic analysis. Population stratification could lead to erroneous conclusions when they are not taken into account in association studies. The aim of our study was to analyze OPRM1 SNP variability by comparing population samples of the International Hap Map database and to analyze a new population sample from the city of Corrientes, Argentina. The results confirm that OPRM1 SNP variability differs among human populations and displays a clear ancestry genetic structure, with three population clusters: Africa, Asia, and Europe-America.2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/2352spainfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-04T09:43:15Zoai:digital.cic.gba.gob.ar:11746/2352Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-04 09:43:15.509CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
dc.title.none.fl_str_mv |
Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms |
title |
Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms |
spellingShingle |
Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms López Soto, Eduardo Javier Biología Celular, Microbiología OPRM1 SNPs A118G AMOVA population genetics |
title_short |
Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms |
title_full |
Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms |
title_fullStr |
Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms |
title_full_unstemmed |
Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms |
title_sort |
Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms |
dc.creator.none.fl_str_mv |
López Soto, Eduardo Javier Catanesi, Cecilia Inés |
author |
López Soto, Eduardo Javier |
author_facet |
López Soto, Eduardo Javier Catanesi, Cecilia Inés |
author_role |
author |
author2 |
Catanesi, Cecilia Inés |
author2_role |
author |
dc.subject.none.fl_str_mv |
Biología Celular, Microbiología OPRM1 SNPs A118G AMOVA population genetics |
topic |
Biología Celular, Microbiología OPRM1 SNPs A118G AMOVA population genetics |
dc.description.none.fl_txt_mv |
Several single nucleotide polymorphisms (SNPs) in the Mu Opioid Receptor gene (OPRM1) have been identified and associated with a wide variety of clinical phenotypes related both to pain sensitivity and analgesic requirements. The A118G and other potentially functional OPRM1 SNPs show significant differences in their allele distributions among populations. However, they have not been properly addressed in a population genetic analysis. Population stratification could lead to erroneous conclusions when they are not taken into account in association studies. The aim of our study was to analyze OPRM1 SNP variability by comparing population samples of the International Hap Map database and to analyze a new population sample from the city of Corrientes, Argentina. The results confirm that OPRM1 SNP variability differs among human populations and displays a clear ancestry genetic structure, with three population clusters: Africa, Asia, and Europe-America. |
description |
Several single nucleotide polymorphisms (SNPs) in the Mu Opioid Receptor gene (OPRM1) have been identified and associated with a wide variety of clinical phenotypes related both to pain sensitivity and analgesic requirements. The A118G and other potentially functional OPRM1 SNPs show significant differences in their allele distributions among populations. However, they have not been properly addressed in a population genetic analysis. Population stratification could lead to erroneous conclusions when they are not taken into account in association studies. The aim of our study was to analyze OPRM1 SNP variability by comparing population samples of the International Hap Map database and to analyze a new population sample from the city of Corrientes, Argentina. The results confirm that OPRM1 SNP variability differs among human populations and displays a clear ancestry genetic structure, with three population clusters: Africa, Asia, and Europe-America. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/submittedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
submittedVersion |
dc.identifier.none.fl_str_mv |
https://digital.cic.gba.gob.ar/handle/11746/2352 |
url |
https://digital.cic.gba.gob.ar/handle/11746/2352 |
dc.language.none.fl_str_mv |
spa |
language |
spa |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:CIC Digital (CICBA) instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires instacron:CICBA |
reponame_str |
CIC Digital (CICBA) |
collection |
CIC Digital (CICBA) |
instname_str |
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
instacron_str |
CICBA |
institution |
CICBA |
repository.name.fl_str_mv |
CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
repository.mail.fl_str_mv |
marisa.degiusti@sedici.unlp.edu.ar |
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1842340409925173248 |
score |
12.623145 |