The association of polygenic risk for schizophrenia, bipolar disorder, and depression with neural connectivity in adolescents and young adults: examining developmental and sex differences.
- Authors
- Meyers, J L; Chorlian, D B; Bigdeli, T B; Johnson, E C; Aliev, F; Agrawal, A; Almasy, L; Anokhin, A; Edenberg, H J; Foroud, T; Goate, A; Kamarajan, C; Kinreich, S; Nurnberger, J; Pandey, A K; Pandey, G; Plawecki, M H; Salvatore, J E; Zhang, J; Fanous, A; Porjesz, B
- Year
- 2021
- Journal
- Translational psychiatry
- PMID
- 33446638
- DOI
- 10.1038/s41398-020-01185-7
- PMCID
- PMC7809462
Neurodevelopmental abnormalities in neural connectivity have been long implicated in the etiology of schizophrenia (SCZ); however, it remains unclear whether these neural connectivity patterns are associated with genetic risk for SCZ in unaffected individuals (i.e., an absence of clinical features of SCZ or a family history of SCZ). We examine whether polygenic risk scores (PRS) for SCZ are associated with functional neural connectivity in adolescents and young adults without SCZ, whether this association is moderated by sex and age, and if similar associations are observed for genetically related neuropsychiatric PRS. One-thousand four-hundred twenty-six offspring from 913 families, unaffected with SCZ, were drawn from the Collaborative Study of the Genetics of Alcoholism (COGA) prospective cohort (median age at first interview = 15.6 (12-26), 51.6% female, 98.1% European American, 41% with a family history of alcohol dependence). Participants were followed longitudinally with resting-state EEG connectivity (i.e., coherence) assessed every two years. Higher SCZ PRS were associated with elevated theta (3-7 Hz) and alpha (7-12 Hz) EEG coherence. Associations differed by sex and age; the most robust associations were observed between PRS and parietal-occipital, central-parietal, and frontal-parietal alpha coherence among males between ages 15-19 (B: 0.15-0.21, p < 10). Significant associations among EEG coherence and Bipolar and Depression PRS were observed, but differed from SCZ PRS in terms of sex, age, and topography. Findings reveal that polygenic risk for SCZ is robustly associated with increased functional neural connectivity among young adults without a SCZ diagnosis. Striking differences were observed between men and women throughout development, mapping onto key periods of risk for the onset of psychotic illness and underlining the critical importance of examining sex differences in associations with neuropsychiatric PRS across development.
Scalp topography of EEG electrodes used for the computation of coherence.The schematic represents a top view of the scalp, nose up. Coherence (solid lines) was computed between bipolar EEG signals, each of which was derived from a pair of adjacent electrodes (connected by dotted lines). Electrode labeling: letters F, C, T, P, and O represent frontal, central, temporal, parietal, and occipital areas of the scalp, respectively; odd and even numbers represent the left and right hemispheres, respectively, and “Z” denotes electrodes along the sagittal midline. 27 Coherences between bipolar electrode pairs are illustrated as follows: frontal-central sagittal coherences are represented in blue; (1) F8-T8--F7-T7, (2) F4-C4--F3-C3, (3) F3-C3--F8-T8, (4) F4-C4--F7-T7, (5) F3-C3--F7-T7, (6) F4-C4--F8-T8, (7) FZ-CZ--F7-T7, (8) FZ-CZ--F3-C3, (9) FZ-CZ--F8-T8, (10) FZ-CZ--F4-C4. Central-parietal sagittal coherences are represented in red; (11) T8-P8--T7-P7, (12) C4-P4--C3-P3, (13) C3-P3--T8-P8, (14) C4-P4--T7-P7, (15) C3-P3--T7-P7, (16) C4-P4--T8-P8, (17) T7-P7--CZ-PZ, (18) C3-P3--CZ-PZ, (19) T8-P8--CZ-PZ, (20) C4-P4--CZ-PZ, parietal-occipital sagittal coherences are represented in purple; (21) P4-O2--P3-O1. Intrahemispheric lateral coherences are represented in orange; (22) T7-C3--F7-F3, (23) P7-P3--F7-F3, (24) P7-P3--T7-C3, (25) T8-C4--F8-F4, (26) P8-P4--F8-F4, (27) P8-P4--T8-C4.
Association of SCZ PRS with interhemispheric and intrahemispheric high-alpha (9–12 Hz) EEG coherence networks in males (A) and females (B) from ages 12–31.Age is represented on the x-axis and coherences are represented on the y-axis, with numbering 1–27 corresponding to coherences between bipolar electrode pairs illustrated in Fig. 1. Regional divisions are marked with horizonal white grid lines: 1–10 anterior (frontal-central); 11–21 posterior (central-parietal-occipital); 22–27 left and right/anterior and posterior intrahemispheric. Color values in the main panels indicate levels of significance (p-values on a negative log 10 scale) as indicated by the color bars on the right.
Associations of rs59979824 (top panel a) and rs11740474 (bottom panel b) with high-alpha EEG coherence in males from ages 12–31.Age is represented on the x-axis and coherences are represented on the y-axis, with numbering 1–27 corresponding to coherences between bipolar electrode pairs illustrated in Fig. 1. Regional divisions are marked with horizontal white grid lines: 1–10 anterior (frontal-central); 11–21 posterior (central-parietal-occipital); 22–27 left and right intrahemispheric. Color values in the main panels indicate levels of significance (p-values on a negative log 10 scale) as indicated by the color bars on the right.
Association of depression PRS with interhemispheric and intrahemispheric high-alpha EEG coherence networks in males (A) and females (B) from ages 12–31.Age is represented on the x-axis and coherences are represented on the y-axis, with numbering 1–27 corresponding to coherences between bipolar electrode pairs illustrated in Fig. 1. Regional divisions are marked with horizontal white grid lines: 1–10 anterior (frontal-central); 11–21 posterior (central-parietal-occipital); 22–27 left and right intrahemispheric. Color values in the main panels indicate levels of significance (p-values on a negative log 10 scale) as indicated by the color bars on the right.
Association of bipolar disorder PRS with interhemispheric and intrahemispheric high-alpha EEG coherence networks in males (A) and females (B) from ages 12–31.Age is represented on the x-axis and coherences are represented on the y-axis, with numbering 1–27 corresponding to coherences between bipolar electrode pairs illustrated in Fig. 1. Regional divisions are marked with horizontal white grid lines: 1–10 anterior (frontal-central); 11–21 posterior (central-parietal-occipital); 22–27 left and right intrahemispheric. Color values in the main panels indicate levels of significance (p-values on a negative log 10 scale) as indicated by the color bars on the right.
| Name | Type |
|---|---|
| 1000 Genomes Project | cohort |
| adolescents | cohort |
| adulthood | cohort |
| Age 15-19 local | cohort |
| Age 24-26 local | cohort |
| Ages 12-17 local | cohort |
| Ages 18-25 local | cohort |
| Ages 26-31 local | cohort |
| alcohol | phenotype |
| alcohol dependence | phenotype |
| Alcohol Use Disorder | phenotype |
| alpha band | phenotype |
| Alpha coherence | phenotype |
| ALX-540763 local | drug |
| autism spectrum disorder | phenotype |
| Bilateral temporal lobe cortices local | anatomy |
| BiP | phenotype |
| bipolar disorder | phenotype |
| Bipolar disorder polygenic risk score local | phenotype |
| BiP PRS local | drug |
| bitopertin | drug |
| Brain connectivity patterns local | anatomy |
| Braineac database local | cohort |
| Callosal white matter fibers local | anatomy |
| cannabis use | phenotype |
| central | anatomy |
| central-frontal high-alpha coherence local | anatomy |
| Central-parietal local | anatomy |
| central-parietal high-alpha coherence local | anatomy |
| Central-parietal region local | anatomy |
| central-posterior local | anatomy |
| central-temporal high-alpha coherence local | anatomy |
| COGA EA participants local | cohort |
| COGA EA sample local | cohort |
| COGA sample | cohort |
| cognition | phenotype |
| Collaborative Study on the Genetics of Alcoholism (COGA) | cohort |
| default mode network | anatomy |
| EEG coherence | phenotype |
| EEG coherence (alpha) local | phenotype |
| EEG coherence (beta) local | phenotype |
| EEG coherence (theta) local | phenotype |
| European ancestry | cohort |
| executive functioning | phenotype |
| F3-C3 local | anatomy |
| F3-C3--F7-T7 local | anatomy |
| F7-T7 local | anatomy |
| F8-T8 local | anatomy |
| frontal cortex | anatomy |
| fronto-central electrode pairs local | anatomy |
| fronto-central region | anatomy |
| fronto-parietal network | anatomy |
| functional connectivity | phenotype |
| FZ-CZ local | anatomy |
| FZ-CZ—F3-C3 high-alpha coherence local | anatomy |
| FZ-CZ--F8-T8 local | anatomy |
| GALNT10 local | gene |
| Genomic Psychiatry cohort | cohort |
| healthy controls | cohort |
| High-alpha local | phenotype |
| high-alpha EEG coherence local | phenotype |
| interhemispheric local | anatomy |
| intrahemispheric local | anatomy |
| major depressive disorder | phenotype |
| Major depressive disorder polygenic risk score local | phenotype |
| Males (12–32) local | cohort |
| MDD polygenic risk score local | phenotype |
| MDD PRS local | drug |
| mood disorders | phenotype |
| Negative symptom local | phenotype |
| nicotine | drug |
| occipital cortex | anatomy |
| P3 amplitude | phenotype |
| P8-P4--T8-C4 high-alpha coherence local | anatomy |
| Parietal-occipital region local | anatomy |
| PGC | cohort |
| PGC GWAS | cohort |
| PGC SCZ GWAS local | cohort |
| polygenic risk score | cohort |
| posterior | anatomy |
| posterior region | anatomy |
| processing speed | phenotype |
| PRS for BiP local | phenotype |
| PRS for MDD local | phenotype |
| PRS for SCZ local | phenotype |
| resting-state EEG coherence local | drug |
| Right intrahemispheric region local | anatomy |
| rs11740474 local | variant |
| rs59979824 local | variant |
| sarcosine | drug |
| schizophrenia | phenotype |
| schizophrenia polygenic risk score | cohort |
| SCZ | phenotype |
| SCZ polygenic risk score local | drug |
| SCZ polygenic risk score local | phenotype |
| SCZ PRS local | drug |
| SCZ PRS local | phenotype |
| SCZ PRS local | variant |
| sex | phenotype |
| theta oscillations | phenotype |
| TMEFF2 local | gene |
| Unaffected adolescents and young adults local | cohort |
| working memory | phenotype |
| young adults | cohort |
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External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Recent Advances in Schizophrenia Genomics and Emerging Clinical Implications. | Bigdeli TB et al. | — | 2025 | → |
| Sex-specific association between schizophrenia polygenic risk and subclinical schizophrenia-related traits. | Mas-Bermejo P et al. | — | 2025 | → |
| Disruption of alpha oscillation propagation in patients with schizophrenia. | Sihn D et al. | — | 2024 | → |
| Non-linear development of EEG coherence in adolescents and young adults shown by the analysis of neurophysiological trajectories and their covariance | Chorlian DB et al. | — | 2024 | — |
| Putative Risk Biomarkers of Bipolar Disorder in At-risk Youth. | Meng X et al. | — | 2024 | → |
| Real-time EEG-based emotion recognition for neurohumanities: perspectives from principal component analysis and tree-based algorithms. | Blanco-Ríos MA et al. | — | 2024 | → |
| Sex differences in aberrant functional connectivity of three core networks and subcortical networks in medication-free adolescent-onset major depressive disorder. | Yang C et al. | — | 2024 | → |
| Sex differences in serum trace elements and minerals levels in unmedicated patients with major depressive episode: The role of suicidal ideation. | Huang D et al. | — | 2024 | → |
| Age- and sex-specific associations between risk scores for schizophrenia and self-reported health in the general population. | Paquin V et al. | — | 2023 | → |
| Associated Genetics and Connectomic Circuitry in Schizophrenia and Bipolar Disorder. | Wei Y et al. | — | 2023 | → |
| Gender differences in the association of polygenic risk and divergent depression trajectories from mid to late life: a national longitudinal study. | Chen P et al. | — | 2023 | → |
| Low-frequency repetitive transcranial magnetic stimulation over the right orbitofrontal cortex for patients with first-episode schizophrenia: A randomized, double-blind, sham-controlled trial. | Hu Q et al. | — | 2023 | → |
| The collaborative study on the genetics of alcoholism: Brain function. | Meyers JL et al. | — | 2023 | → |
| The Collaborative Study on the Genetics of Alcoholism: Overview. | Agrawal A et al. | — | 2023 | → |
| VISPNN: VGG-inspired Stochastic Pooling Neural Network. | Wang SH et al. | — | 2022 | → |