The integration of molecular genetics approaches into the study of complex health phenomena is an increasingly important and available strategy for researchers across the health science disciplines. Pain sensation and response to painful stimuli are examples of complex health phenomena that are particularly amenable to molecular genetics approaches. Both human and animal model research suggests that differences in these responses may be related, in part, to variation in the genes that modulate sensation and behavior. The authors are currently managing a large cross-disciplinary research effort to identify child characteristics, including genotypes, that predict the degree of distress displayed by children following a painful medical procedure (i.e., IV insertion). The purpose of this article is to describe the strategies used to integrate molecular genetics methods into this project. The authors discuss the steps needed to complete this process, including (a) establishing a collaboration with genetics researchers and laboratory facilities, (b) developing and implementing a plan to manage biologic samples, and (c) incorporating genetics into the informed consent process.
Journal article
Integrating molecular genetics analyses into clinical research
Biological research for nursing, Vol.8(1), pp.67-77
07/01/2006
DOI: 10.1177/1099800406289909
PMID: 16766630
Abstract
Details
- Title: Subtitle
- Integrating molecular genetics analyses into clinical research
- Creators
- Debra L SchutteAnn Marie McCarthy - University of IowaMilena Floria-SantosKirsten Hanrahan - University of IowaJeffrey C MurrayCharmaine Kleiber - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Biological research for nursing, Vol.8(1), pp.67-77
- DOI
- 10.1177/1099800406289909
- PMID
- 16766630
- NLM abbreviation
- Biol Res Nurs
- ISSN
- 1099-8004
- Language
- English
- Date published
- 07/01/2006
- Academic Unit
- Stead Family Department of Pediatrics; Craniofacial Anomalies Research Center; Nursing; Community and Behavioral Health
- Record Identifier
- 9983557661702771
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