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The transformative potential of an integrative approach to pregnancy.
Eidem, Haley R; McGary, Kriston L; Capra, John A; Abbot, Patrick; Rokas, Antonis.
Afiliação
  • Eidem HR; Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA.
  • McGary KL; Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA.
  • Capra JA; Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37235, USA.
  • Abbot P; Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA.
  • Rokas A; Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37235, USA. Electronic address: antonis.rokas@vanderbilt.edu.
Placenta ; 57: 204-215, 2017 Sep.
Article em En | MEDLINE | ID: mdl-28864013
BACKGROUND: Complex traits typically involve diverse biological pathways and are shaped by numerous genetic and environmental factors. Pregnancy-associated traits and pathologies are further complicated by extensive communication across multiple tissues in two individuals, interactions between two genomes-maternal and fetal-that obscure causal variants and lead to genetic conflict, and rapid evolution of pregnancy-associated traits across mammals and in the human lineage. Given the multi-faceted complexity of human pregnancy, integrative approaches that synthesize diverse data types and analyses harbor tremendous promise to identify the genetic architecture and environmental influences underlying pregnancy-associated traits and pathologies. METHODS: We review current research that addresses the extreme complexities of traits and pathologies associated with human pregnancy. RESULTS: We find that successful efforts to address the many complexities of pregnancy-associated traits and pathologies often harness the power of many and diverse types of data, including genome-wide association studies, evolutionary analyses, multi-tissue transcriptomic profiles, and environmental conditions. CONCLUSION: We propose that understanding of pregnancy and its pathologies will be accelerated by computational platforms that provide easy access to integrated data and analyses. By simplifying the integration of diverse data, such platforms will provide a comprehensive synthesis that transcends many of the inherent challenges present in studies of pregnancy.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Gravidez Tipo de estudo: Prognostic_studies Limite: Female / Humans Idioma: En Revista: Placenta Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Gravidez Tipo de estudo: Prognostic_studies Limite: Female / Humans Idioma: En Revista: Placenta Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos