Dopamine signaling enriched striatal gene set predicts striatal dopamine synthesis and physiological activity in vivo.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
30 Apr 2024
Historique:
received: 04 09 2023
accepted: 22 03 2024
medline: 1 5 2024
pubmed: 1 5 2024
entrez: 30 4 2024
Statut: epublish

Résumé

The polygenic architecture of schizophrenia implicates several molecular pathways involved in synaptic function. However, it is unclear how polygenic risk funnels through these pathways to translate into syndromic illness. Using tensor decomposition, we analyze gene co-expression in the caudate nucleus, hippocampus, and dorsolateral prefrontal cortex of post-mortem brain samples from 358 individuals. We identify a set of genes predominantly expressed in the caudate nucleus and associated with both clinical state and genetic risk for schizophrenia that shows dopaminergic selectivity. A higher polygenic risk score for schizophrenia parsed by this set of genes predicts greater dopamine synthesis in the striatum and greater striatal activation during reward anticipation. These results translate dopamine-linked genetic risk variation into in vivo neurochemical and hemodynamic phenotypes in the striatum that have long been implicated in the pathophysiology of schizophrenia.

Identifiants

pubmed: 38688917
doi: 10.1038/s41467-024-47456-5
pii: 10.1038/s41467-024-47456-5
doi:

Substances chimiques

Dopamine VTD58H1Z2X

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3342

Informations de copyright

© 2024. The Author(s).

Références

Harrison, P. J. & Weinberger, D. R. Schizophrenia genes, gene expression, and neuropathology: on the matter of their convergence. Mol. Psychiatry 10, 40–68 (2005).
pubmed: 15263907 doi: 10.1038/sj.mp.4001558
Trubetskoy, V. et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature 604, 502–508 (2022).
pubmed: 35396580 pmcid: 9392466 doi: 10.1038/s41586-022-04434-5
Fromer, M. et al. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat. Neurosci. 19, 1442–1453 (2016).
pubmed: 27668389 pmcid: 5083142 doi: 10.1038/nn.4399
Parikshak, N. N., Gandal, M. J. & Geschwind, D. H. Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders. Nat. Rev. Genet. 16, 441–458 (2015).
pubmed: 26149713 pmcid: 4699316 doi: 10.1038/nrg3934
Gandal, M. J., Leppa, V., Won, H., Parikshak, N. N. & Geschwind, D. H. The road to precision psychiatry: translating genetics into disease mechanisms. Nat. Neurosci. 19, 1397–1407 (2016).
pubmed: 27786179 pmcid: 9012265 doi: 10.1038/nn.4409
Meyer-Lindenberg, A. S. et al. Regionally specific disturbance of dorsolateral prefrontal-hippocampal functional connectivity in schizophrenia. Arch. Gen. Psychiatry 62, 379–386 (2005).
pubmed: 15809405 doi: 10.1001/archpsyc.62.4.379
Howes, O. D., McCutcheon, R., Owen, M. J. & Murray, R. M. The role of genes, stress, and dopamine in the development of schizophrenia. Biol. Psychiatry 81, 9–20 (2017).
pubmed: 27720198 doi: 10.1016/j.biopsych.2016.07.014
Grace, A. A. Dysregulation of the dopamine system in the pathophysiology of schizophrenia and depression. Nat. Rev. Neurosci. 17, 524–532 (2016).
pubmed: 27256556 pmcid: 5166560 doi: 10.1038/nrn.2016.57
Weinberger, D. R. Implications of normal brain development for the pathogenesis of schizophrenia. Arch. Gen. Psychiatry 44, 660–669 (1987).
pubmed: 3606332 doi: 10.1001/archpsyc.1987.01800190080012
Creese, I., Burt, D. R. & Snyder, S. H. Dopamine receptor binding predicts clinical and pharmacological potencies of antischizophrenic drugs. Science 192, 481–483 (1976).
pubmed: 3854 doi: 10.1126/science.3854
Abi-Dargham, A. et al. Increased baseline occupancy of D2 receptors by dopamine in schizophrenia. Proc. Natl Acad. Sci. USA 97, 8104–8109 (2000).
pubmed: 10884434 pmcid: 16677 doi: 10.1073/pnas.97.14.8104
Howes, O. D. et al. The nature of dopamine dysfunction in schizophrenia and what this means for treatment. Arch. Gen. Psychiatry 69, 776–786 (2012).
pubmed: 22474070 pmcid: 3730746 doi: 10.1001/archgenpsychiatry.2012.169
Meyer-Lindenberg, A. et al. Reduced prefrontal activity predicts exaggerated striatal dopaminergic function in schizophrenia. Nat. Neurosci. 5, 267–271 (2002).
pubmed: 11865311 doi: 10.1038/nn804
Reith, J. et al. Elevated dopa decarboxylase activity in living brain of patients with psychosis. Proc. Natl Acad. Sci. USA 91, 11651–11654 (1994).
pubmed: 7972118 pmcid: 45289 doi: 10.1073/pnas.91.24.11651
Howes, O. D. et al. Elevated striatal dopamine function lnked to prodromal signs of schizophrenia. Arch. Gen. Psychiatry 66, 13–20 (2009).
pubmed: 19124684 doi: 10.1001/archgenpsychiatry.2008.514
Huttunen, J. et al. Striatal dopamine synthesis in first-degree relatives of patients with schizophrenia. Biol. Psychiatry 63, 114–117 (2008).
pubmed: 17655830 doi: 10.1016/j.biopsych.2007.04.017
Howes, O. et al. Progressive increase in striatal dopamine synthesis capacity as patients develop psychosis: a PET study. Mol. Psychiatry 16, 885–886 (2011).
pubmed: 21358709 doi: 10.1038/mp.2011.20
Eisenberg, D. P. et al. Clinical correlation but no elevation of striatal dopamine synthesis capacity in two independent cohorts of medication-free individuals with schizophrenia. Mol. Psychiatry 27, 1241–1247 (2022).
pubmed: 34789848 doi: 10.1038/s41380-021-01337-1
Kim, E. et al. Presynaptic dopamine capacity in patients with treatment-resistant schizophrenia taking clozapine: an [18F]DOPA PET Study. Neuropsychopharmacology 42, 941–950 (2017).
pubmed: 27857125 doi: 10.1038/npp.2016.258
D’Ambrosio, E. et al. The relationship between grey matter volume and striatal dopamine function in psychosis: a multimodal (18)F-DOPA PET and voxel-based morphometry study. Mol. Psychiatry 26, 1332–1345 (2021).
pubmed: 31690805 doi: 10.1038/s41380-019-0570-6
Benjamin, K. J. M. et al. Analysis of the caudate nucleus transcriptome in individuals with schizophrenia highlights effects of antipsychotics and new risk genes. Nat. Neurosci. 25, 1559–1568 (2022).
pubmed: 36319771 pmcid: 10599288 doi: 10.1038/s41593-022-01182-7
Zhang, Y. et al. Polymorphisms in human dopamine D2 receptor gene affect gene expression, splicing, and neuronal activity during working memory. Proc. Natl Acad. Sci. USA 104, 20552–20557 (2007).
pubmed: 18077373 pmcid: 2154469 doi: 10.1073/pnas.0707106104
Bertolino, A. et al. Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance. PLoS ONE 5, e9348 (2010).
pubmed: 20179754 pmcid: 2825256 doi: 10.1371/journal.pone.0009348
Howes, O. D. & Murray, R. M. Schizophrenia: an integrated sociodevelopmental-cognitive model. Lancet 383, 1677–1687 (2014).
pubmed: 24315522 doi: 10.1016/S0140-6736(13)62036-X
Owen, M. J., Sawa, A. & Mortensen, P. B. Schizophrenia. Lancet 388, 86–97 (2016).
pubmed: 26777917 pmcid: 4940219 doi: 10.1016/S0140-6736(15)01121-6
Li, Z. et al. Inheritance of neural substrates for motivation and pleasure. Psychol. Sci. 30, 1205–1217 (2019).
pubmed: 31318629 pmcid: 6794661 doi: 10.1177/0956797619859340
Pergola, G. et al. DRD2 co-expression network and a related polygenic index predict imaging, behavioral and clinical phenotypes linked to schizophrenia. Transl. Psychiatry 7, e1006 (2017).
pubmed: 28094815 pmcid: 5545721 doi: 10.1038/tp.2016.253
Fazio, L. et al. Transcriptomic context of DRD1 is associated with prefrontal activity and behavior during working memory. Proc. Natl Acad. Sci. USA 115, 5582–5587 (2018).
pubmed: 29735686 pmcid: 6003490 doi: 10.1073/pnas.1717135115
Braun, U. et al. Brain network dynamics during working memory are modulated by dopamine and diminished in schizophrenia. Nat. Commun. 12, 3478 (2021).
pubmed: 34108456 pmcid: 8190281 doi: 10.1038/s41467-021-23694-9
Zhang, B. & Horvath, S. A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 4, 17 (2005). Article.
doi: 10.2202/1544-6115.1128
Gandal, M. J. et al. Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap. Science 359, 693–697 (2018).
pubmed: 29439242 pmcid: 5898828 doi: 10.1126/science.aad6469
Pergola, G. et al. Prefrontal coexpression of schizophrenia risk genes is associated with treatment response in patients. Biol. Psychiatry 86, 45–55 (2019).
pubmed: 31126695 doi: 10.1016/j.biopsych.2019.03.981
Radulescu, E. et al. Identification and prioritization of gene sets associated with schizophrenia risk by co-expression network analysis in human brain. Mol. Psychiatry 25, 791–804 (2020).
pubmed: 30478419 doi: 10.1038/s41380-018-0304-1
Pergola, G. et al. Consensus molecular environment of schizophrenia risk genes in coexpression networks shifting across age and brain regions. Sci. Adv. 9, eade2812 (2023).
pubmed: 37058565 pmcid: 10104472 doi: 10.1126/sciadv.ade2812
Hore, V. et al. Tensor decomposition for multiple-tissue gene expression experiments. Nat. Genet, 48, 1094–1100 (2016).
pubmed: 27479908 pmcid: 5010142 doi: 10.1038/ng.3624
Ramdhani, S. et al. Tensor decomposition of stimulated monocyte and macrophage gene expression profiles identifies neurodegenerative disease-specific trans-eQTLs. PLoS Genet. 16, e1008549 (2020).
pubmed: 32012164 pmcid: 7018232 doi: 10.1371/journal.pgen.1008549
Saelens, W., Cannoodt, R. & Saeys, Y. A comprehensive evaluation of module detection methods for gene expression data. Nat. Commun. 9, 1090 (2018).
pubmed: 29545622 pmcid: 5854612 doi: 10.1038/s41467-018-03424-4
de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: Generalized Gene-Set Analysis of GWAS Data. PLoS Comput. Biol. 11, e1004219 (2015).
pubmed: 25885710 pmcid: 4401657 doi: 10.1371/journal.pcbi.1004219
Sey, N. Y. A. et al. A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles. Nat. Neurosci. 23, 583–593 (2020).
pubmed: 32152537 pmcid: 7131892 doi: 10.1038/s41593-020-0603-0
Tran, M. N. et al. Single-nucleus transcriptome analysis reveals cell-type-specific molecular signatures across reward circuitry in the human brain. Neuron 109, 3088–3103.e3085 (2021).
pubmed: 34582785 pmcid: 8564763 doi: 10.1016/j.neuron.2021.09.001
Calabresi, P., Picconi, B., Tozzi, A., Ghiglieri, V. & Di Filippo, M. Direct and indirect pathways of basal ganglia: a critical reappraisal. Nat. Neurosci. 17, 1022–1030 (2014).
pubmed: 25065439 doi: 10.1038/nn.3743
Aguet, F. et al. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).
doi: 10.1038/nature24277
Pergola, G., Penzel, N., Sportelli, L. & Bertolino, A. Lessons learned from parsing genetic risk for schizophrenia into biological pathways. Biol. Psychiatry 94, 121–130 (2022).
Usiello, A. et al. Distinct functions of the two isoforms of dopamine D2 receptors. Nature 408, 199–203 (2000).
pubmed: 11089973 doi: 10.1038/35041572
Tzavara, E. T. et al. M4 muscarinic receptors regulate the dynamics of cholinergic and dopaminergic neurotransmission: relevance to the pathophysiology and treatment of related CNS pathologies. FASEB J. 18, 1410–1412 (2004).
pubmed: 15231726 doi: 10.1096/fj.04-1575fje
Chan, W. Y. et al. Allosteric modulation of the muscarinic M4 receptor as an approach to treating schizophrenia. Proc. Natl Acad. Sci. USA 105, 10978–10983 (2008).
pubmed: 18678919 pmcid: 2495016 doi: 10.1073/pnas.0800567105
Bodick, N. C. et al. Effects of xanomeline, a selective muscarinic receptor agonist, on cognitive function and behavioral symptoms in Alzheimer disease. Arch. Neurol. 54, 465–473 (1997).
pubmed: 9109749 doi: 10.1001/archneur.1997.00550160091022
Shekhar, A. et al. Selective muscarinic receptor agonist xanomeline as a novel treatment approach for schizophrenia. Am. J. Psychiatry 165, 1033–1039 (2008).
pubmed: 18593778 doi: 10.1176/appi.ajp.2008.06091591
Foster, D. J., Bryant, Z. K. & Conn, P. J. Targeting muscarinic receptors to treat schizophrenia. Behav. Brain Res. 405, 113201 (2021).
pubmed: 33647377 pmcid: 8006961 doi: 10.1016/j.bbr.2021.113201
Sauder, C. et al. Effectiveness of KarXT (xanomeline-trospium) for cognitive impairment in schizophrenia: post hoc analyses from a randomised, double-blind, placebo-controlled phase 2 study. Transl. Psychiatry 12, 491 (2022).
pubmed: 36414626 pmcid: 9681874 doi: 10.1038/s41398-022-02254-9
Yohn, S. E., Weiden, P. J., Felder, C. C. & Stahl, S. M. Muscarinic acetylcholine receptors for psychotic disorders: bench-side to clinic. Trends Pharmacol. Sci. 43, 1098–1112 (2022).
pubmed: 36273943 doi: 10.1016/j.tips.2022.09.006
McCutcheon, R., Beck, K., Jauhar, S. & Howes, O. D. Defining the locus of dopaminergic dysfunction in schizophrenia: a meta-analysis and test of the mesolimbic hypothesis. Schizophr. Bull. 44, 1301–1311 (2017).
pmcid: 5933516 doi: 10.1093/schbul/sbx180
Schott, B. H. et al. Mesolimbic functional magnetic resonance imaging activations during reward anticipation correlate with reward-related ventral striatal dopamine release. J. Neurosci. 28, 14311–14319 (2008).
pubmed: 19109512 pmcid: 6671462 doi: 10.1523/JNEUROSCI.2058-08.2008
da Silva Alves, F. et al. Dopaminergic modulation of the human reward system: a placebo-controlled dopamine depletion fMRI study. J. Psychopharmacol. 25, 538–549 (2010).
pubmed: 20530591 doi: 10.1177/0269881110367731
Lancaster, T. M. et al. Polygenic risk of psychosis and ventral striatal activation during reward processing in healthy adolescents. JAMA Psychiatry 73, 852–861 (2016).
pubmed: 27384424 doi: 10.1001/jamapsychiatry.2016.1135
Juckel, G. Inhibition of the reward system by antipsychotic treatment. Dialogues Clin. Neurosci. 18, 109–114 (2016).
pubmed: 27069385 pmcid: 4826766 doi: 10.31887/DCNS.2016.18.1/gjuckel
Juckel, G. et al. Dysfunction of ventral striatal reward prediction in schizophrenic patients treated with typical, not atypical, neuroleptics. Psychopharmacol. (Berl.) 187, 222–228 (2006).
doi: 10.1007/s00213-006-0405-4
Juckel, G. et al. Dysfunction of ventral striatal reward prediction in schizophrenia. Neuroimage 29, 409–416 (2006).
pubmed: 16139525 doi: 10.1016/j.neuroimage.2005.07.051
Nielsen, M. et al. Alterations of the brain reward system in antipsychotic naïve schizophrenia patients. Biol. Psychiatry 71, 898–905 (2012).
pubmed: 22418013 doi: 10.1016/j.biopsych.2012.02.007
Esslinger, C. et al. Ventral striatal activation during attribution of stimulus saliency and reward anticipation is correlated in unmedicated first episode schizophrenia patients. Schizophr. Res. 140, 114–121 (2012).
pubmed: 22784688 doi: 10.1016/j.schres.2012.06.025
Heinz, A. & Schlagenhauf, F. Dopaminergic dysfunction in schizophrenia: salience attribution revisited. Schizophr. Bull. 36, 472–485 (2010).
pubmed: 20453041 pmcid: 2879696 doi: 10.1093/schbul/sbq031
Li, Z. et al. Striatal dysfunction in patients with schizophrenia and their unaffected first-degree relatives. Schizophrenia Res. 195, 215–221 (2018).
doi: 10.1016/j.schres.2017.08.043
Lui, S. S. et al. The nature of anhedonia and avolition in patients with first-episode schizophrenia. Psychol. Med. 46, 437–447 (2016).
pubmed: 26464039 doi: 10.1017/S0033291715001968
Heerey, E. A. & Gold, J. M. Patients with schizophrenia demonstrate dissociation between affective experience and motivated behavior. J. Abnorm. Psychol. 116, 268–278 (2007).
pubmed: 17516760 doi: 10.1037/0021-843X.116.2.268
Zeng, J. et al. Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI findings in the monetary incentive delay task. Transl. Psychiatry 12, 448 (2022).
pubmed: 36244990 pmcid: 9573872 doi: 10.1038/s41398-022-02201-8
Knutson, B. et al. Amphetamine modulates human incentive processing. Neuron 43, 261–269 (2004).
pubmed: 15260961 doi: 10.1016/j.neuron.2004.06.030
Schmitz, Y., Lee, C. J., Schmauss, C., Gonon, F. & Sulzer, D. Amphetamine distorts stimulation-dependent dopamine overflow: effects on D2 autoreceptors, transporters, and synaptic vesicle stores. J. Neurosci. 21, 5916–5924 (2001).
pubmed: 11487614 pmcid: 6763160 doi: 10.1523/JNEUROSCI.21-16-05916.2001
Prosser, E. S. et al. Depression, Parkinsonian symptoms, and negative symptoms in schizophrenics treated with neuroleptics. J. Nerv. Ment. Dis. 175, 100–105 (1987).
pubmed: 2879880 doi: 10.1097/00005053-198702000-00006
Kirsch, P., Ronshausen, S., Mier, D. & Gallhofer, B. The influence of antipsychotic treatment on brain reward system reactivity in schizophrenia patients. Pharmacopsychiatry 40, 196–198 (2007).
pubmed: 17874350 doi: 10.1055/s-2007-984463
Bunney, B. S. & Grace, A. A. Acute and chronic haloperidol treatment: comparison of effects on nigral dopaminergic cell activity. Life Sci. 23, 1715–1727 (1978).
pubmed: 31529 doi: 10.1016/0024-3205(78)90471-X
Grace, A. A., Bunney, B. S., Moore, H. & Todd, C. L. Dopamine-cell depolarization block as a model for the therapeutic actions of antipsychotic drugs. Trends Neurosci. 20, 31–37 (1997).
pubmed: 9004417 doi: 10.1016/S0166-2236(96)10064-3
Chiodo, L. & Bunney, B. Typical and atypical neuroleptics: differential effects of chronic administration on the activity of A9 and A10 midbrain dopaminergic neurons. J. Neurosci. 3, 1607–1619 (1983).
pubmed: 6135762 pmcid: 6564520 doi: 10.1523/JNEUROSCI.03-08-01607.1983
da Silva Alves, F. et al. Dopaminergic modulation of the reward system in schizophrenia: a placebo-controlled dopamine depletion fMRI study. Eur. Neuropsychopharmacol. 23, 1577–1586 (2013).
pubmed: 23978392 doi: 10.1016/j.euroneuro.2013.06.008
Nielsen, M. O. et al. Improvement of brain reward abnormalities by antipsychotic monotherapy in schizophrenia. Arch. Gen. Psychiatry 69, 1195–1204 (2012).
pubmed: 22868877 doi: 10.1001/archgenpsychiatry.2012.847
Schlagenhauf, F. et al. Reward system activation in schizophrenic patients switched from typical neuroleptics to olanzapine. Psychopharmacol. (Berl.) 196, 673–684 (2008).
doi: 10.1007/s00213-007-1016-4
Eisenberg, D. et al. Dopaminergic tone and neuroleptic mediated hyperactivity in the striatum of patients with schizophrenia. Neuropsychopharmacology 39, S244–S244 (2014).
Collado-Torres, L. et al. Regional heterogeneity in gene expression, regulation, and coherence in the frontal cortex and hippocampus across development and schizophrenia. Neuron 103, 203–216.e208 (2019).
pubmed: 31174959 pmcid: 7000204 doi: 10.1016/j.neuron.2019.05.013
Jaffe, A. E. et al. Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex. Nat. Neurosci. 19, 40–47 (2016).
pubmed: 26619358 doi: 10.1038/nn.4181
Choi, E. Y., Tanimura, Y., Vage, P. R., Yates, E. H. & Haber, S. N. Convergence of prefrontal and parietal anatomical projections in a connectional hub in the striatum. NeuroImage 146, 821–832 (2017).
pubmed: 27646127 doi: 10.1016/j.neuroimage.2016.09.037
Wilks, C. et al. recount3: summaries and queries for large-scale RNA-seq expression and splicing. Genome Biol. 22, 323 (2021).
pubmed: 34844637 pmcid: 8628444 doi: 10.1186/s13059-021-02533-6
Bloomfield, M. A. P. et al. Dopamine function in cigarette smokers: an [18F]-DOPA PET Study. Neuropsychopharmacology 39, 2397–2404 (2014).
pubmed: 24718373 pmcid: 4138749 doi: 10.1038/npp.2014.87
Dahoun, T. et al. The effect of the DISC1 Ser704Cys polymorphism on striatal dopamine synthesis capacity: an [18F]-DOPA PET study. Hum. Mol. Genet, 27, 3498–3506 (2018).
pubmed: 29945223 doi: 10.1093/hmg/ddy242
Froudist-Walsh, S. et al. The effect of perinatal brain injury on dopaminergic function and hippocampal volume in adult life. eLife 6, e29088 (2017).
pubmed: 29179814 pmcid: 5705207 doi: 10.7554/eLife.29088
Jauhar, S. et al. The relationship between cortical glutamate and striatal dopamine in first-episode psychosis: a cross-sectional multimodal PET and magnetic resonance spectroscopy imaging study. Lancet Psychiatry 5, 816–823 (2018).
pubmed: 30236864 pmcid: 6162342 doi: 10.1016/S2215-0366(18)30268-2
Howes, O. D. et al. Midbrain dopamine function in schizophrenia and depression: a post-mortem and positron emission tomographic imaging study. Brain 136, 3242–3251 (2013).
pubmed: 24097339 pmcid: 3808688 doi: 10.1093/brain/awt264
Howes, O. D. et al. Dopamine synthesis capacity before onset of psychosis: a prospective [18F]-DOPA PET imaging study. Am. J. Psychiatry 168, 1311–1317 (2011).
pubmed: 21768612 pmcid: 3682447 doi: 10.1176/appi.ajp.2011.11010160
Patlak, C. S. & Blasberg, R. G. Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. Generalizations. J. Cereb. Blood Flow. Metab.: Off. J. Int. Soc. Cereb. Blood Flow. Metab. 5, 584–590 (1985).
doi: 10.1038/jcbfm.1985.87
Martinez, D. et al. Imaging human mesolimbic dopamine transmission with positron emission tomography. Part II: amphetamine-anduced dopamine release in the Functional Subdivisions of the Striatum. J. Cereb. Blood Flow. Metab. 23, 285–300 (2003).
pubmed: 12621304 doi: 10.1097/01.WCB.0000048520.34839.1A
Eisenberg, D. P. et al. Common variation in the DOPA decarboxylase (DDC) gene and human striatal DDC activity in vivo. Neuropsychopharmacology 41, 2303–2308 (2016).
pubmed: 26924680 pmcid: 4946061 doi: 10.1038/npp.2016.31
Knutson, B., Fong, G. W., Adams, C. M., Varner, J. L. & Hommer, D. Dissociation of reward anticipation and outcome with event-related fMRI. NeuroReport 12, 3683–3687 (2001).
pubmed: 11726774 doi: 10.1097/00001756-200112040-00016
Kohli, A. et al. Using expectancy theory to quantitatively dissociate the neural representation of motivation from its influential factors in the human brain: an fMRI study. NeuroImage 178, 552–561 (2018).
pubmed: 29751057 doi: 10.1016/j.neuroimage.2018.05.021
Choi, S. W., Mak, T. S.-H. & O’Reilly, P. F. Tutorial: a guide to performing polygenic risk score analyses. Nat. Protoc. 15, 2759–2772 (2020).
pubmed: 32709988 pmcid: 7612115 doi: 10.1038/s41596-020-0353-1
Durbin, R. M. et al. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).
pubmed: 20981092 doi: 10.1038/nature09534
Choi, S. W. et al. PRSet: pathway-based polygenic risk score analyses and software. PLoS Genet 19, e1010624 (2023).
pubmed: 36749789 pmcid: 9937466 doi: 10.1371/journal.pgen.1010624
Antonucci, L. A. et al. Thalamic connectivity measured with fMRI is associated with a polygenic index predicting thalamo-prefrontal gene co-expression. Brain Struct. Funct. 224, 1331–1344 (2019).
pubmed: 30725232 doi: 10.1007/s00429-019-01843-7
Mitchell, T. J. & Beauchamp, J. J. Bayesian variable selection in linear regression. J. Am. Stat. Assoc. 83, 1023–1032 (1988).
doi: 10.1080/01621459.1988.10478694
Parsana, P. et al. Addressing confounding artifacts in reconstruction of gene co-expression networks. Genome Biol. 20, 94 (2019).
pubmed: 31097038 pmcid: 6521369 doi: 10.1186/s13059-019-1700-9
Jaffe, A. E. et al. Practical impacts of genomic data “cleaning” on biological discovery using surrogate variable analysis. BMC Bioinforma. 16, 372 (2015).
doi: 10.1186/s12859-015-0808-5
Risso, D., Ngai, J., Speed, T. P. & Dudoit, S. Normalization of RNA-seq data using factor analysis of control genes or samples. Nat. Biotechnol. 32, 896–902 (2014).
pubmed: 25150836 pmcid: 4404308 doi: 10.1038/nbt.2931
Zhu, Z. et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat. Genet. 48, 481–487 (2016).
pubmed: 27019110 doi: 10.1038/ng.3538
Benner, C. et al. FINEMAP: efficient variable selection using summary data from genome-wide association studies. Bioinformatics 32, 1493–1501 (2016).
pubmed: 26773131 pmcid: 4866522 doi: 10.1093/bioinformatics/btw018
Demontis, D. et al. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat. Genet. 51, 63–75 (2019).
pubmed: 30478444 doi: 10.1038/s41588-018-0269-7
Wray, N. R. et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat. Genet. 50, 668–681 (2018).
pubmed: 29700475 pmcid: 5934326 doi: 10.1038/s41588-018-0090-3
International Obsessive Compulsive Disorder Foundation Genetics C, Studies OCDCGA. Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis. Mol. Psychiatry 23, 1181–1188 (2018).
Liu, J. Z. et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat. Genet. 47, 979–986 (2015).
pubmed: 26192919 pmcid: 4881818 doi: 10.1038/ng.3359
Hannon, E. et al. An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation. Genome Biol. 17, 176 (2016).
pubmed: 27572077 pmcid: 5004279 doi: 10.1186/s13059-016-1041-x
Kinoshita, M. et al. Aberrant DNA methylation of blood in schizophrenia by adjusting for estimated cellular proportions. Neuromolecular Med. 16, 697–703 (2014).
pubmed: 25052007 doi: 10.1007/s12017-014-8319-5
Montano, C. et al. Association of DNA methylation differences with schizophrenia in an Epigenome-wide Association Study. JAMA Psychiatry 73, 506–514 (2016).
pubmed: 27074206 pmcid: 6353566 doi: 10.1001/jamapsychiatry.2016.0144
Numata, S., Ye, T., Herman, M. & Lipska, B. K. DNA methylation changes in the postmortem dorsolateral prefrontal cortex of patients with schizophrenia. Front. Genet. 5, 280 (2014).
pubmed: 25206360 pmcid: 4144343 doi: 10.3389/fgene.2014.00280
Wockner, L. F. et al. Genome-wide DNA methylation analysis of human brain tissue from schizophrenia patients. Transl. Psychiatry 4, e339–e339 (2014).
pubmed: 24399042 pmcid: 3905221 doi: 10.1038/tp.2013.111
Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291 (2016).
pubmed: 27535533 pmcid: 5018207 doi: 10.1038/nature19057
Skene, N. G. et al. Genetic identification of brain cell types underlying schizophrenia. Nat. Genet. 50, 825–833 (2018).
pubmed: 29785013 pmcid: 6477180 doi: 10.1038/s41588-018-0129-5
Habib, N. et al. Massively parallel single-nucleus RNA-seq with DroNc-seq. Nat. Methods 14, 955–958 (2017).
pubmed: 28846088 pmcid: 5623139 doi: 10.1038/nmeth.4407
Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).
pubmed: 25605792 pmcid: 4402510 doi: 10.1093/nar/gkv007
Wu, D. & Smyth, G. K. Camera: a competitive gene set test accounting for inter-gene correlation. Nucleic Acids Res. 40, e133–e133 (2012).
pubmed: 22638577 pmcid: 3458527 doi: 10.1093/nar/gks461
Yu, G., Wang, L. G., Han, Y. & He, Q. Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).
pubmed: 22455463 pmcid: 3339379 doi: 10.1089/omi.2011.0118
Mi, H. et al. PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements. Nucleic Acids Res. 45, D183–D189 (2016).
pubmed: 27899595 pmcid: 5210595 doi: 10.1093/nar/gkw1138
The International HapMap Consortium. The International HapMap Project. Nature 426, 789–796 (2003).
Viechtbauer, W. Conducting meta-analyses in R with the metafor Package. J. Stat. Softw. 36, 1–48 (2010).
doi: 10.18637/jss.v036.i03
Smith, S. M. & Nichols, T. E. Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 44, 83–98 (2009).
pubmed: 18501637 doi: 10.1016/j.neuroimage.2008.03.061
Spisák, T. et al. Probabilistic TFCE: a generalized combination of cluster size and voxel intensity to increase statistical power. Neuroimage 185, 12–26 (2019).
pubmed: 30296561 doi: 10.1016/j.neuroimage.2018.09.078

Auteurs

Leonardo Sportelli (L)

Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.

Daniel P Eisenberg (DP)

Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA.

Roberta Passiatore (R)

Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.

Enrico D'Ambrosio (E)

Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.
Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.

Linda A Antonucci (LA)

Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.

Jasmine S Bettina (JS)

Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA.

Qiang Chen (Q)

Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.

Aaron L Goldman (AL)

Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.

Michael D Gregory (MD)

Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA.

Kira Griffiths (K)

Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.
Holmusk Technologies, New York, NY, USA.

Thomas M Hyde (TM)

Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Joel E Kleinman (JE)

Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Antonio F Pardiñas (AF)

MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.

Madhur Parihar (M)

Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.

Teresa Popolizio (T)

Radiology Department, IRCCS Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy.

Antonio Rampino (A)

Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.
Azienda Ospedaliero Universitaria Consorziale Policlinico, Bari, Italy.

Joo Heon Shin (JH)

Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.

Mattia Veronese (M)

Department of Information Engineering, University of Padua, Padua, Italy.
Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.

William S Ulrich (WS)

Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.

Caroline F Zink (CF)

Baltimore Research and Education Foundation, Baltimore, MD, USA.

Alessandro Bertolino (A)

Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.
Azienda Ospedaliero Universitaria Consorziale Policlinico, Bari, Italy.

Oliver D Howes (OD)

Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.

Karen F Berman (KF)

Clinical and Translational Neuroscience Branch, National Institute of Mental Health, Intramural Research Program, NIH, DHHS, Bethesda, MD, USA.

Daniel R Weinberger (DR)

Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA. Daniel.Weinberger@libd.org.
Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Daniel.Weinberger@libd.org.
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Daniel.Weinberger@libd.org.
Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Daniel.Weinberger@libd.org.
Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Daniel.Weinberger@libd.org.

Giulio Pergola (G)

Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA. Giulio.Pergola@libd.org.
Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy. Giulio.Pergola@libd.org.
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Giulio.Pergola@libd.org.

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