Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms

Autores
López Soto, Eduardo Javier; Catanesi, Cecilia Ines
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
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.
Fil: López Soto, Eduardo Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; Argentina
Fil: Catanesi, Cecilia Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
Materia
A118G
AMOVA
OPRM1
POPULATION GENETICS
SNPS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/53492
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Human population genetic structure detected by pain-related mu opioid receptor gene polymorphismsLópez Soto, Eduardo JavierCatanesi, Cecilia InesA118GAMOVAOPRM1POPULATION GENETICSSNPShttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Several 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.Fil: López Soto, Eduardo Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; ArgentinaFil: Catanesi, Cecilia Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; ArgentinaSociedade Brasileira de Genética2015-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/53492López Soto, Eduardo Javier; Catanesi, Cecilia Ines; Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms; Sociedade Brasileira de Genética; Genetics and Molecular Biology; 38; 2; 6-2015; 152-1551415-47571678-4685CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4530646/pdf/1415-4757-gmb-38-2-152.pdfinfo:eu-repo/semantics/altIdentifier/doi/10.1590/S1415-4757382220140299info:eu-repo/semantics/altIdentifier/url/http://ref.scielo.org/95cwcyinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:08:12Zoai:ri.conicet.gov.ar:11336/53492instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:08:12.282CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
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
A118G
AMOVA
OPRM1
POPULATION GENETICS
SNPS
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 Ines
author López Soto, Eduardo Javier
author_facet López Soto, Eduardo Javier
Catanesi, Cecilia Ines
author_role author
author2 Catanesi, Cecilia Ines
author2_role author
dc.subject.none.fl_str_mv A118G
AMOVA
OPRM1
POPULATION GENETICS
SNPS
topic A118G
AMOVA
OPRM1
POPULATION GENETICS
SNPS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
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.
Fil: López Soto, Eduardo Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; Argentina
Fil: Catanesi, Cecilia Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
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 2015-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/53492
López Soto, Eduardo Javier; Catanesi, Cecilia Ines; Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms; Sociedade Brasileira de Genética; Genetics and Molecular Biology; 38; 2; 6-2015; 152-155
1415-4757
1678-4685
CONICET Digital
CONICET
url http://hdl.handle.net/11336/53492
identifier_str_mv López Soto, Eduardo Javier; Catanesi, Cecilia Ines; Human population genetic structure detected by pain-related mu opioid receptor gene polymorphisms; Sociedade Brasileira de Genética; Genetics and Molecular Biology; 38; 2; 6-2015; 152-155
1415-4757
1678-4685
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4530646/pdf/1415-4757-gmb-38-2-152.pdf
info:eu-repo/semantics/altIdentifier/doi/10.1590/S1415-4757382220140299
info:eu-repo/semantics/altIdentifier/url/http://ref.scielo.org/95cwcy
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Sociedade Brasileira de Genética
publisher.none.fl_str_mv Sociedade Brasileira de Genética
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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