TY - JOUR
T1 - Seeking optimal region-of-interest (ROI) single-value summary measures for fMRI studies in imaging genetics
AU - Tong, Yunxia
AU - Chen, Qiang
AU - Nichols, Thomas E.
AU - Rasetti, Roberta
AU - Callicott, Joseph H.
AU - Berman, Karen F.
AU - Weinberger, Daniel R.
AU - Mattay, Venkata S.
N1 - Funding Information:
This research was supported by the Intramural Research Program (NCT: 00001486; Protocol ID: 95-M-0150) of the National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, United States of America. This research was supported by the Intramural Research Program (NCT: 00001486; Protocol ID: 95-M-0150) of the National Institute of Mental Health, NIH, Bethesda, MD 20892, USA.
Funding Information:
This research was supported by the Intramural Research Program (NCT: 00001486; Protocol ID: 95-M-0150) of the National Institute of Mental Health, NIH, Bethesda, MD 20892, USA.
PY - 2016/3
Y1 - 2016/3
N2 - A data-driven hypothesis-free genome-wide association (GWA) approach in imaging genetics studies allows screening the entire genome to discover novel genes that modulate brain structure, chemistry, and function. However, a whole brain voxel-wise analysis approach in such genome-wide based imaging genetic studies can be computationally intense and also likely has low statistical power since a stringent multiple comparisons correction is needed for searching over the entire genome and brain. In imaging genetics with functional magnetic resonance imaging (fMRI) phenotypes, since many experimental paradigms activate focal regions that can be pre-specified based on a priori knowledge, reducing the voxel-wise search to single-value summary measures within a priori ROIs could prove efficient and promising. The goal of this investigation is to evaluate the sensitivity and reliability of different single-value ROI summary measures and provide guidance in future work. Four different fMRI databases were tested and comparisons across different groups (patients with schizophrenia, their siblings, vs. normal control subjects; across genotype groups) were conducted. Our results show that four of these measures, particularly those that represent values from the top most-activated voxels within an ROI are more powerful at reliably detecting group differences and generating greater effect sizes than the others.
AB - A data-driven hypothesis-free genome-wide association (GWA) approach in imaging genetics studies allows screening the entire genome to discover novel genes that modulate brain structure, chemistry, and function. However, a whole brain voxel-wise analysis approach in such genome-wide based imaging genetic studies can be computationally intense and also likely has low statistical power since a stringent multiple comparisons correction is needed for searching over the entire genome and brain. In imaging genetics with functional magnetic resonance imaging (fMRI) phenotypes, since many experimental paradigms activate focal regions that can be pre-specified based on a priori knowledge, reducing the voxel-wise search to single-value summary measures within a priori ROIs could prove efficient and promising. The goal of this investigation is to evaluate the sensitivity and reliability of different single-value ROI summary measures and provide guidance in future work. Four different fMRI databases were tested and comparisons across different groups (patients with schizophrenia, their siblings, vs. normal control subjects; across genotype groups) were conducted. Our results show that four of these measures, particularly those that represent values from the top most-activated voxels within an ROI are more powerful at reliably detecting group differences and generating greater effect sizes than the others.
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U2 - 10.1371/journal.pone.0151391
DO - 10.1371/journal.pone.0151391
M3 - Article
C2 - 26974435
AN - SCOPUS:84961629620
VL - 11
JO - PLoS One
JF - PLoS One
SN - 1932-6203
IS - 3
M1 - e0151391
ER -