This Core will help to create and maintain sampling frames, samples, and core databases needed to carry out the Center?s program of research. The Core consists of both computer hardware and a group of individuals to perform data management tasks and to maintain electronic linkages between the Center?s disparate sites. These resources will permit collaborative analyses of extant data, and improve our efficiency in designing and implementing new data collection activities. They will also provide an extraordinary resource for training and for research projects by new investigators, in the form of (1) some of the richest databases currently available anywhere for physiologically- and genetically-informed, developmental research; (2) a cadre of experts to provide training and technical support in database management. Overall supervision of the core will be provided by the Steering committee, of which the Core?s director is a member.
The specific aims are: 1) to establish combined datasets from four ongoing epidemiological studies - the Great Smoky Mountains Study (GSMS), the American Indian Study (AIS), the CCCS, and the Virginia Twin Study (VTS), 2) to use these datasets to address questions that cannot be addressed in any one dataset alone, and to provide increased power for other analyses, or to allow replication of key findings, 3) to use these samples to establish """"""""model examples"""""""" for testing new or extended statistical methods, 4) to develop a representative, ethnically diverse twin sample from the North Carolina database for future developmental behavioral genetic studies, 5) to create an integrated dataset that can be used for selecting subsamples for specific studies, 6) to generate genetically informative samples using the Duke study samples as a basis, 7) to improve methods of tracking and retaining subjects for longitudinal research, 8) To produce public access data sets comparable to those available from the ECA, NCS, etc., and 9) to train new researchers in the use of separate and aggregate data sets.
| Eaves, Lindon; Verhulst, Brad (2014) Problems and pit-falls in testing for G × E and epistasis in candidate gene studies of human behavior. Behav Genet 44:578-90 |
| Eaves, Lindon J; Pourcain, Beate St; Smith, George Davey et al. (2014) Resolving the effects of maternal and offspring genotype on dyadic outcomes in genome wide complex trait analysis (""M-GCTA""). Behav Genet 44:445-55 |
| Worthman, Carol M (2009) Habits of the heart: life history and the developmental neuroendocrinology of emotion. Am J Hum Biol 21:772-81 |
| Worthman, Carol M; Costello, E Jane (2009) Tracking biocultural pathways in population health: the value of biomarkers. Ann Hum Biol 36:281-97 |
| Costello, E J; Keeler, G P; Angold, A (2001) Poverty, race/ethnicity, and psychiatric disorder: a study of rural children. Am J Public Health 91:1494-8 |
| Costello, E J; Angold, A (2000) Developmental psychopathology and public health: past, present, and future. Dev Psychopathol 12:599-618 |
