Limits...
Multivariate genetic determinants of EEG oscillations in schizophrenia and psychotic bipolar disorder from the BSNIP study.

Narayanan B, Soh P, Calhoun VD, Ruaño G, Kocherla M, Windemuth A, Clementz BA, Tamminga CA, Sweeney JA, Keshavan MS, Pearlson GD - Transl Psychiatry (2015)

Bottom Line: We assessed eight data-driven EEG frequency activity derived from group-independent component analysis (ICA) in conjunction with a reduced subset of 10,422 SNPs through novel multivariate association using parallel ICA (para-ICA).Para-ICA extracted five frequency and nine SNP components, of which theta and delta activities were significantly correlated with two different gene components, comprising genes participating extensively in brain development, neurogenesis and synaptogenesis.The gene clusters were enriched for biological properties affecting neural circuitry and involved in brain function and/or development.

View Article: PubMed Central - PubMed

Affiliation: Olin Neuropsychiatry Research Center, Hartford Hospital, Institute of Living, Hartford, CT, USA.

ABSTRACT
Schizophrenia (SZ) and psychotic bipolar disorder (PBP) are disabling psychiatric illnesses with complex and unclear etiologies. Electroencephalogram (EEG) oscillatory abnormalities in SZ and PBP probands are heritable and expressed in their relatives, but the neurobiology and genetic factors mediating these abnormalities in the psychosis dimension of either disorder are less explored. We examined the polygenic architecture of eyes-open resting state EEG frequency activity (intrinsic frequency) from 64 channels in 105 SZ, 145 PBP probands and 56 healthy controls (HCs) from the multisite BSNIP (Bipolar-Schizophrenia Network on Intermediate Phenotypes) study. One million single-nucleotide polymorphisms (SNPs) were derived from DNA. We assessed eight data-driven EEG frequency activity derived from group-independent component analysis (ICA) in conjunction with a reduced subset of 10,422 SNPs through novel multivariate association using parallel ICA (para-ICA). Genes contributing to the association were examined collectively using pathway analysis tools. Para-ICA extracted five frequency and nine SNP components, of which theta and delta activities were significantly correlated with two different gene components, comprising genes participating extensively in brain development, neurogenesis and synaptogenesis. Delta and theta abnormality was present in both SZ and PBP, while theta differed between the two disorders. Theta abnormalities were also mediated by gene clusters involved in glutamic acid pathways, cadherin and synaptic contact-based cell adhesion processes. Our data suggest plausible multifactorial genetic networks, including novel and several previously identified (DISC1) candidate risk genes, mediating low frequency delta and theta abnormalities in psychoses. The gene clusters were enriched for biological properties affecting neural circuitry and involved in brain function and/or development.

No MeSH data available.


Related in: MedlinePlus

Mean loading coefficients (LC) for spatio-spectral EEG components and gene networks for schizophrenia (SZ) (n=105), psychotic bipolar probands (PBP; n=145) and healthy controls (HC; n=56). EEG LC represents each subject's contribution to the spatial weights associated with the delta and theta frequency components. Genetic LC represents each subject's contribution to the genetic network. E4 is posterior theta activity. E2 included two anterior delta components. Error bars represent standard deviation. Post hoc comparisons included pairwise t-tests between HCs and SZ and PBP probands. EEG, electroencephalogram; SNP, single-nucleotide polymorphism.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4490286&req=5

fig3: Mean loading coefficients (LC) for spatio-spectral EEG components and gene networks for schizophrenia (SZ) (n=105), psychotic bipolar probands (PBP; n=145) and healthy controls (HC; n=56). EEG LC represents each subject's contribution to the spatial weights associated with the delta and theta frequency components. Genetic LC represents each subject's contribution to the genetic network. E4 is posterior theta activity. E2 included two anterior delta components. Error bars represent standard deviation. Post hoc comparisons included pairwise t-tests between HCs and SZ and PBP probands. EEG, electroencephalogram; SNP, single-nucleotide polymorphism.

Mentions: Para-ICA identified five spatio-spectral EEG and nine SNP components from the pooled data (SZ+PBP+HC). EEG components E4 and E2 were significantly associated with genetic components G1 (r=−0.34, P<4.4E−09) and G3 (r=0.31, P<1.1E−7), respectively (see Figure 2). The prominent EEG frequency oscillations in components E4 and E2 were posterior theta and anterior delta activity, respectively. The genetic component G1 comprised 551 SNPs/340 unique genes, while G3 included 564 SNPs/342 distinct genes. The top 20 most significant genes from G1 and G3, their Z-scores and associated functions are listed in Table 2. LCs were normally distributed and between-group variance was statistically equivalent. Post hoc analyses revealed significant group differences in LC of E2 (delta activity), E4 (theta) and both genetic networks between HCs and both probands. Theta activity and the LC (representing minor allele frequency) of two genetic networks differed between the SZ and PBP probands (see Figure 3). Theta activity was positively associated with schizo–bipolar scale (r=0.17, P<0.009) scores. No significant correlation was observed with PANSS scores. Both E4 and E2 were not significantly correlated (r=0.13, P=0.15 and r=−0.06, P=0.47) with chlorpromazine equivalents. Reliability test by leave-one-out cross-validation revealed an average within modality correlation >0.9 for both EEG and SNP component, indicating stable structure across several runs of the para-ICA.


Multivariate genetic determinants of EEG oscillations in schizophrenia and psychotic bipolar disorder from the BSNIP study.

Narayanan B, Soh P, Calhoun VD, Ruaño G, Kocherla M, Windemuth A, Clementz BA, Tamminga CA, Sweeney JA, Keshavan MS, Pearlson GD - Transl Psychiatry (2015)

Mean loading coefficients (LC) for spatio-spectral EEG components and gene networks for schizophrenia (SZ) (n=105), psychotic bipolar probands (PBP; n=145) and healthy controls (HC; n=56). EEG LC represents each subject's contribution to the spatial weights associated with the delta and theta frequency components. Genetic LC represents each subject's contribution to the genetic network. E4 is posterior theta activity. E2 included two anterior delta components. Error bars represent standard deviation. Post hoc comparisons included pairwise t-tests between HCs and SZ and PBP probands. EEG, electroencephalogram; SNP, single-nucleotide polymorphism.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4490286&req=5

fig3: Mean loading coefficients (LC) for spatio-spectral EEG components and gene networks for schizophrenia (SZ) (n=105), psychotic bipolar probands (PBP; n=145) and healthy controls (HC; n=56). EEG LC represents each subject's contribution to the spatial weights associated with the delta and theta frequency components. Genetic LC represents each subject's contribution to the genetic network. E4 is posterior theta activity. E2 included two anterior delta components. Error bars represent standard deviation. Post hoc comparisons included pairwise t-tests between HCs and SZ and PBP probands. EEG, electroencephalogram; SNP, single-nucleotide polymorphism.
Mentions: Para-ICA identified five spatio-spectral EEG and nine SNP components from the pooled data (SZ+PBP+HC). EEG components E4 and E2 were significantly associated with genetic components G1 (r=−0.34, P<4.4E−09) and G3 (r=0.31, P<1.1E−7), respectively (see Figure 2). The prominent EEG frequency oscillations in components E4 and E2 were posterior theta and anterior delta activity, respectively. The genetic component G1 comprised 551 SNPs/340 unique genes, while G3 included 564 SNPs/342 distinct genes. The top 20 most significant genes from G1 and G3, their Z-scores and associated functions are listed in Table 2. LCs were normally distributed and between-group variance was statistically equivalent. Post hoc analyses revealed significant group differences in LC of E2 (delta activity), E4 (theta) and both genetic networks between HCs and both probands. Theta activity and the LC (representing minor allele frequency) of two genetic networks differed between the SZ and PBP probands (see Figure 3). Theta activity was positively associated with schizo–bipolar scale (r=0.17, P<0.009) scores. No significant correlation was observed with PANSS scores. Both E4 and E2 were not significantly correlated (r=0.13, P=0.15 and r=−0.06, P=0.47) with chlorpromazine equivalents. Reliability test by leave-one-out cross-validation revealed an average within modality correlation >0.9 for both EEG and SNP component, indicating stable structure across several runs of the para-ICA.

Bottom Line: We assessed eight data-driven EEG frequency activity derived from group-independent component analysis (ICA) in conjunction with a reduced subset of 10,422 SNPs through novel multivariate association using parallel ICA (para-ICA).Para-ICA extracted five frequency and nine SNP components, of which theta and delta activities were significantly correlated with two different gene components, comprising genes participating extensively in brain development, neurogenesis and synaptogenesis.The gene clusters were enriched for biological properties affecting neural circuitry and involved in brain function and/or development.

View Article: PubMed Central - PubMed

Affiliation: Olin Neuropsychiatry Research Center, Hartford Hospital, Institute of Living, Hartford, CT, USA.

ABSTRACT
Schizophrenia (SZ) and psychotic bipolar disorder (PBP) are disabling psychiatric illnesses with complex and unclear etiologies. Electroencephalogram (EEG) oscillatory abnormalities in SZ and PBP probands are heritable and expressed in their relatives, but the neurobiology and genetic factors mediating these abnormalities in the psychosis dimension of either disorder are less explored. We examined the polygenic architecture of eyes-open resting state EEG frequency activity (intrinsic frequency) from 64 channels in 105 SZ, 145 PBP probands and 56 healthy controls (HCs) from the multisite BSNIP (Bipolar-Schizophrenia Network on Intermediate Phenotypes) study. One million single-nucleotide polymorphisms (SNPs) were derived from DNA. We assessed eight data-driven EEG frequency activity derived from group-independent component analysis (ICA) in conjunction with a reduced subset of 10,422 SNPs through novel multivariate association using parallel ICA (para-ICA). Genes contributing to the association were examined collectively using pathway analysis tools. Para-ICA extracted five frequency and nine SNP components, of which theta and delta activities were significantly correlated with two different gene components, comprising genes participating extensively in brain development, neurogenesis and synaptogenesis. Delta and theta abnormality was present in both SZ and PBP, while theta differed between the two disorders. Theta abnormalities were also mediated by gene clusters involved in glutamic acid pathways, cadherin and synaptic contact-based cell adhesion processes. Our data suggest plausible multifactorial genetic networks, including novel and several previously identified (DISC1) candidate risk genes, mediating low frequency delta and theta abnormalities in psychoses. The gene clusters were enriched for biological properties affecting neural circuitry and involved in brain function and/or development.

No MeSH data available.


Related in: MedlinePlus