TY - JOUR
T1 - A pilot multivariate parallel ICA study to investigate differential linkage between neural networks and genetic profiles in schizophrenia
AU - Meda, Shashwath A.
AU - Jagannathan, Kanchana
AU - Gelernter, Joel
AU - Calhoun, Vince D.
AU - Liu, Jingyu
AU - Stevens, Michael C.
AU - Pearlson, Godfrey D.
N1 - Funding Information:
We thank the research staff at the Olin Neuropsychiatry Research Center who helped to collect and process the data. This research was supported by the National Institutes of Health , under grants R01 EB005846 and 1 R01 EB006841 (to VDC), and 2 RO1 MH43775 , 5 RO1 MH52886 (to GP) and a grant from the MIND Institute (NPB).
PY - 2010/11
Y1 - 2010/11
N2 - Understanding genetic influences on both healthy and disordered brain function is a major focus in psychiatric neuroimaging. We utilized task-related imaging findings from an fMRI auditory oddball task known to be robustly associated with abnormal activation in schizophrenia, to investigate genomic factors derived from multiple single nucleotide polymorphisms (SNPs) from genes previously shown to be associated with schizophrenia. Our major aim was to investigate the relationship of these genomic factors to normal/abnormal brain functionality between controls and schizophrenia patients. We studied a Caucasian-only sample of 35 healthy controls and 31 schizophrenia patients. All subjects performed an auditory oddball task, which consists of detecting an infrequent sound within a series of frequent sounds. Each subject was characterized on 24 different SNP markers spanning multiple risk genes previously associated with schizophrenia. We used a recently developed technique named parallel independent component analysis (para-ICA) to analyze this multimodal data set (Liu et al., 2008). The method aims to identify simultaneously independent components of each modality (functional imaging, genetics) and the relationships between them. We detected three fMRI components significantly correlated with two distinct gene components. The fMRI components, along with their significant genetic profile (dominant SNP) correlations were as follows: (1) Inferior frontal-anterior/posterior cingulate-thalamus-caudate with SNPs from Brain derived neurotropic factor (BDNF) and dopamine transporter (DAT) [. r= -0.51; p< 0.0001], (2) superior/middle temporal gyrus-cingulate-premotor with SLC6A4_PR and SLC6A4_PR_AG (serotonin transporter promoter; 5HTTLPR) [. r= 0.27; p= 0.03], and (3) default mode-fronto-temporal gyrus with Brain derived neurotropic factor and dopamine transporter (BDNF, DAT) [. r= -0.25; p= 0.04]. Functional components comprised task-relevant regions (including PFC, ACC, STG and MTG) frequently identified as abnormal in schizophrenia. Further, gene-fMRI combinations 1 (Z= 1.75; p= 0.03), 2 (Z= 1.84; p= 0.03) and 3 (Z= 1.67; p= 0.04) listed above showed significant differences between controls and patients, based on their correlated loading coefficients. We demonstrate a framework to identify interactions between "clusters" of brain function and of genetic information. Our results reveal the effect/influence of specific interactions, (perhaps epistastatic in nature), between schizophrenia risk genes on imaging endophenotypes representing attention/working memory and goal directed related brain function, thus establishing a useful methodology to probe multivariate genotype-phenotype relationships.
AB - Understanding genetic influences on both healthy and disordered brain function is a major focus in psychiatric neuroimaging. We utilized task-related imaging findings from an fMRI auditory oddball task known to be robustly associated with abnormal activation in schizophrenia, to investigate genomic factors derived from multiple single nucleotide polymorphisms (SNPs) from genes previously shown to be associated with schizophrenia. Our major aim was to investigate the relationship of these genomic factors to normal/abnormal brain functionality between controls and schizophrenia patients. We studied a Caucasian-only sample of 35 healthy controls and 31 schizophrenia patients. All subjects performed an auditory oddball task, which consists of detecting an infrequent sound within a series of frequent sounds. Each subject was characterized on 24 different SNP markers spanning multiple risk genes previously associated with schizophrenia. We used a recently developed technique named parallel independent component analysis (para-ICA) to analyze this multimodal data set (Liu et al., 2008). The method aims to identify simultaneously independent components of each modality (functional imaging, genetics) and the relationships between them. We detected three fMRI components significantly correlated with two distinct gene components. The fMRI components, along with their significant genetic profile (dominant SNP) correlations were as follows: (1) Inferior frontal-anterior/posterior cingulate-thalamus-caudate with SNPs from Brain derived neurotropic factor (BDNF) and dopamine transporter (DAT) [. r= -0.51; p< 0.0001], (2) superior/middle temporal gyrus-cingulate-premotor with SLC6A4_PR and SLC6A4_PR_AG (serotonin transporter promoter; 5HTTLPR) [. r= 0.27; p= 0.03], and (3) default mode-fronto-temporal gyrus with Brain derived neurotropic factor and dopamine transporter (BDNF, DAT) [. r= -0.25; p= 0.04]. Functional components comprised task-relevant regions (including PFC, ACC, STG and MTG) frequently identified as abnormal in schizophrenia. Further, gene-fMRI combinations 1 (Z= 1.75; p= 0.03), 2 (Z= 1.84; p= 0.03) and 3 (Z= 1.67; p= 0.04) listed above showed significant differences between controls and patients, based on their correlated loading coefficients. We demonstrate a framework to identify interactions between "clusters" of brain function and of genetic information. Our results reveal the effect/influence of specific interactions, (perhaps epistastatic in nature), between schizophrenia risk genes on imaging endophenotypes representing attention/working memory and goal directed related brain function, thus establishing a useful methodology to probe multivariate genotype-phenotype relationships.
KW - 5HTTLPR
KW - Auditory oddball
KW - BDNF
KW - DAT
KW - FMRI
KW - Gene
KW - Multivariate
KW - Parallel ICA
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U2 - 10.1016/j.neuroimage.2009.11.052
DO - 10.1016/j.neuroimage.2009.11.052
M3 - Article
C2 - 19944766
AN - SCOPUS:77956228096
SN - 1053-8119
VL - 53
SP - 1007
EP - 1015
JO - NeuroImage
JF - NeuroImage
IS - 3
ER -