Combining meta- and mega-analytic approaches for multi-site diffusion imaging based genetic studies: From the enigma-DTI working group


Autoria(s): Jahanshad, N.; Kochunov, P.; Nichols, T. E.; Sprooten, E.; Mandl, R. C.; Almasy, L.; Brouwer, R. M.; Curran, J. E.; de Zubicaray, G. I.; Dimitrova, R.; Fox, P. T.; Hong, L. E.; Landman, B. A.; Lemaitre, H.; Lopez, L.; Martin, N. G.; McMahon, K. L.; Mitchell, B. D.; Olvera, R. L.; Peterson, C. P.; Sussmann, J. E.; Toga, A. W.; Wardlaw, J. M.; Wright, M. J.; Wright, S. N.; Bastin, M. E.; McIntosh, A. M.; Boomsma, D. I.; Kahn, R. S.; Den Braber, A.; Deary, I. J.; Pol, H. E. H.; Williamson, D.; Blangero, J.; Van't Ent, D.; Glahn, D. C.; Thompson, P. M.
Data(s)

2014

Resumo

Meta-analyses estimate a statistical effect size for a test or an analysis by combining results from multiple studies without necessarily having access to each individual study's raw data. Multi-site meta-analysis is crucial for imaging genetics, as single sites rarely have a sample size large enough to pick up effects of single genetic variants associated with brain measures. However, if raw data can be shared, combining data in a "mega-analysis" is thought to improve power and precision in estimating global effects. As part of an ENIGMA-DTI investigation, we use fractional anisotropy (FA) maps from 5 studies (total N=2, 203 subjects, aged 9-85) to estimate heritability. We combine the studies through meta-and mega-analyses as well as a mixture of the two - combining some cohorts with mega-analysis and meta-analyzing the results with those of the remaining sites. A combination of mega-and meta-approaches may boost power compared to meta-analysis alone.

Identificador

http://eprints.qut.edu.au/85778/

Publicador

IEEE

Relação

DOI:10.1109/ISBI.2014.6868099

Jahanshad, N., Kochunov, P., Nichols, T. E., Sprooten, E., Mandl, R. C., Almasy, L., Brouwer, R. M., Curran, J. E., de Zubicaray, G. I., Dimitrova, R., Fox, P. T., Hong, L. E., Landman, B. A., Lemaitre, H., Lopez, L., Martin, N. G., McMahon, K. L., Mitchell, B. D., Olvera, R. L., Peterson, C. P., Sussmann, J. E., Toga, A. W., Wardlaw, J. M., Wright, M. J., Wright, S. N., Bastin, M. E., McIntosh, A. M., Boomsma, D. I., Kahn, R. S., Den Braber, A., Deary, I. J., Pol, H. E. H., Williamson, D., Blangero, J., Van't Ent, D., Glahn, D. C., & Thompson, P. M. (2014) Combining meta- and mega-analytic approaches for multi-site diffusion imaging based genetic studies: From the enigma-DTI working group. In 2014 IEEE International Symposium on Biomedical... by IEEE Signal Processing Society, 2014 IEEE International Symposium on Biomedical Imaging : Tuesday, 29 April - Friday, 2 May 2014 : Renaissance Beijing Capital Hotel, Beijing, China, IEEE, Beijing, China, pp. 1234-1238.

Direitos

Copyright 2014 IEEE

Fonte

Faculty of Health; Institute of Health and Biomedical Innovation

Palavras-Chave #DTI #ENIGMA #Heritability #Imaging genetics #Mega-analysis #Meta-analysis #Multi-site
Tipo

Conference Paper