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
CIC Digital (CICBA)
Institución
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
OAI Identificador
oai:digital.cic.gba.gob.ar:11746/2352
Acceder
id CICBA_138a694025c26df13a5c4472660ae7fc
oai_identifier_str oai:digital.cic.gba.gob.ar:11746/2352
network_acronym_str CICBA
repository_id_str 9441
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:CICBA2025-09-29T13:40:00Zoai: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:94412025-09-29 13:40:00.583CIC 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
_version_ 1844618592734150656
score 13.069144

Publicaciones similares