Dr Andrew Pocklington

2022

• Sanders, B. et al. 2022. Transcriptional programs regulating neuronal differentiation are disrupted in DLG2 knockout human embryonic stem cells and enriched for schizophrenia and related disorders risk variants. Nature Communications 13(1), article number: 27. (10.1038/s41467-021-27601-0)

2021

• Sanders, B. et al. 2021. DLG2 knockout in human embryonic stem cells results in changes of transcriptional programs affecting neuronal differentiation and associated with genetic risk for schizophrenia and related disorders. Nature Communications
• Clifton, N. E. et al. 2021. Genetic association of FMRP targets with psychiatric disorders. Molecular Psychiatry 26, pp. 2977-2990. (10.1038/s41380-020-00912-2)
• Hubbard, L. et al. 2021. Rare copy number variations are associated with poorer cognition in schizophrenia. Biological Psychiatry 90(1), pp. 28-34. (10.1016/j.biopsych.2020.11.025)

2020

• Grama, S. et al. 2020. Polygenic risk for schizophrenia and subcortical brain anatomy in the UK Biobank cohort. Translational Psychiatry 10, article number: 309. (10.1038/s41398-020-00940-0)
• Rees, E. et al. 2020. De novo mutations identified by exome sequencing implicate rare missense variants in SLC6A1 in schizophrenia. Nature Neuroscience 23(2), pp. 179-184. (10.1038/s41593-019-0565-2)
• Hall, L. S. et al. 2020. A transcriptome-wide association study implicates specific pre- and post-synaptic abnormalities in schizophrenia. Human Molecular Genetics 29(1), pp. 159-167. (10.1093/hmg/ddz253)

2019

• Pain, O. et al. 2019. Novel insight into the etiology of autism spectrum disorder gained by integrating expression data with genome-wide association statistics. Biological Psychiatry 86(4), pp. 265-273. (10.1016/j.biopsych.2019.04.034)
• Pardinas, A. F. et al. 2019. Pharmacogenomic variants and drug interactions identified through the genetic analysis of clozapine metabolism. American Journal of Psychiatry 176(6), pp. 477-486. (10.1176/appi.ajp.2019.18050589)
• Morgan, S. E. et al. 2019. Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes. Proceedings of the National Academy of Sciences 116(19), pp. 9604-9609. (10.1073/pnas.1820754116)
• Rees, E. et al. 2019. Targeted sequencing of 10,198 samples confirms abnormalities in neuronal activity and implicates voltage-gated sodium channels in schizophrenia pathogenesis. Biological Psychiatry 85(7), pp. 554-562. (10.1016/j.biopsych.2018.08.022)
• Lancaster, T. M. et al. 2019. Structural and functional neuroimaging of polygenic risk for schizophrenia: a recall-by-genotype-based approach. Schizophrenia Bulletin 45(2), pp. 405-414. (10.1093/schbul/sby037)
• Clifton, N. E. et al. 2019. Dynamic expression of genes associated with schizophrenia and bipolar disorder across development. Translational Psychiatry 9, article number: 74. (10.1038/s41398-019-0405-x)
• Vivian-Griffiths, T. et al. 2019. Predictive modeling of schizophrenia from genomic data: Comparison of polygenic risk score with kernel support vector machines approach. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 180(1), pp. 80-85. (10.1002/ajmg.b.32705)

2018

• Ruderfer, D. M. et al. 2018. Genomic dissection of bipolar disorder and schizophrenia, including 28 subphenotypes. Cell 173(7), pp. 1705-1715.e16. (10.1016/j.cell.2018.05.046)
• Pardinas, A. F. et al. 2018. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nature Genetics 50, pp. 381-389. (10.1038/s41588-018-0059-2)

2017

• Leonenko, G. et al. 2017. Mutation intolerant genes and targets of FMRP are enriched for nonsynonymous alleles in schizophrenia. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 174(7), pp. 724-731. (10.1002/ajmg.b.32560)
• Fernández, E. et al. 2017. Arc requires PSD95 for assembly into postsynaptic complexes involved with neural dysfunction and intelligence. Cell Reports 21(3), pp. 679-691. (10.1016/j.celrep.2017.09.045)
• Phillips, T. J. et al. 2017. Treating the placenta to prevent adverse effects of gestational hypoxia on fetal brain development. Scientific Reports 7, pp. -., article number: 9079. (10.1038/s41598-017-06300-1)
• McLaughlin, R. L. et al. 2017. Genetic correlation between amyotrophic lateral sclerosis and schizophrenia. Nature Communications 8, article number: 14774. (10.1038/ncomms14774)
• Clifton, N. E. et al. 2017. Schizophrenia copy number variants and associative learning. Molecular Psychiatry 22(2), pp. 178-182. (10.1038/mp.2016.227)
• Marshall, C. R. et al. 2017. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nature Genetics 49, pp. 27-35. (10.1038/ng.3725)

2016

• Rees, E. et al. 2016. Analysis of intellectual disability copy number variants for association with schizophrenia. JAMA Psychiatry 73(9), pp. 963-969. (10.1001/jamapsychiatry.2016.1831)
• Pardinas, A. et al. 2016. Common schizophrenia alleles are enriched in mutation-intolerant genes and maintained by background selection. [Online]. bioRxiv. (10.1101/068593) Available at: http://dx.doi.org/10.1101/068593
• Han, J. et al. 2016. Gender differences in CNV burden do not confound schizophrenia CNV associations. Scientific Reports 6, article number: 25986. (10.1038/srep25986)
• Franke, B. et al. 2016. Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept. Nature Neuroscience 19(3), pp. 420-431. (10.1038/nn.4228)
• Richards, A. et al. 2016. Exome arrays capture polygenic rare variant contributions to schizophrenia. Human Molecular Genetics 25(5), pp. 1001-1007. (10.1093/hmg/ddv620)

2015

• Pocklington, A. et al. 2015. Novel findings from CNVs implicate inhibitory and excitatory signaling complexes in schizophrenia. Neuron 86(5), pp. 1203-1214. (10.1016/j.neuron.2015.04.022)
• Vivian-Griffiths, T. et al. 2015. Utilising machine-learning algorithms to uncover complex genetic interactions in schizophrenia [Conference Abstract]. Human Heredity 79(1), pp. 48-48., article number: A46. (10.1159/000381109)
• Rees, E. et al. 2015. Analysis of exome sequence in 604 trios for recessive genotypes in schizophrenia. Translational Psychiatry 5(7), article number: e607. (10.1038/tp.2015.99)

2014

• Gusev, A. et al. 2014. Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. American Journal of Human Genetics 95(5), pp. 535-552. (10.1016/j.ajhg.2014.10.004)
• Martin, J. et al. 2014. Biological overlap of attention-deficit/hyperactivity disorder and autism spectrum disorder: evidence from copy number variants. Journal of the American Academy of Child and Adolescent Psychiatry 53(7), pp. 761-770.e26. (10.1016/j.jaac.2014.03.004)
• Ripke, S. et al. 2014. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511(7510), pp. 421-427. (10.1038/nature13595)
• Erk, S. et al. 2014. Replication of brain function effects of a genome-wide supported psychiatric risk variant in the CACNA1C gene and new multi-locus effects. NeuroImage 94, pp. 147-154. (10.1016/j.neuroimage.2014.03.007)
• Pocklington, A., O'Donovan, M. C. and Owen, M. J. 2014. The synapse in schizophrenia. European Journal of Neuroscience 39(7), pp. 1059-1067. (10.1111/ejn.12489)
• Fromer, M. et al. 2014. De novo mutations in schizophrenia implicate synaptic networks. Nature 506, pp. 179-184. (10.1038/nature12929)

2012

• Kirov, G. et al. 2012. De novo CNV analysis implicates specific abnormalities of postsynaptic signalling complexes in the pathogenesis of schizophrenia. Molecular Psychiatry 17(2), pp. 142-153. (10.1038/mp.2011.154)

2011

• Frank, R. A. et al. 2011. Clustered coding variants in the glutamate receptor complexes of individuals with schizophrenia and bipolar disorder. PLoS ONE 6(4), article number: e19011. (10.1371/journal.pone.0019011)

2010

• Jones, L. et al. 2010. Genetic evidence implicates the immune system and cholesterol metabolism in the aetiology of Alzheimer's disease. PLoS ONE 5(11), article number: e13950. (10.1371/journal.pone.0013950)

2009

• Armstrong, J. D., Malik, B., Pocklington, A., Emes, R. and Grant, S. 2009. Evolution of the synapse proteome [Conference abstract]. Journal of Neurogenetics 23, pp. S34-S35.
• Coba, M. P. et al. 2009. Neurotransmitters drive combinatorial multistate postsynaptic density networks. Science Signaling 2(68), article number: ra19. (10.1126/scisignal.2000102)

2008

• Emes, R. D. et al. 2008. Evolutionary expansion and anatomical specialization of synapse proteome complexity. Nature Neuroscience 11(7), pp. 799-806. (10.1038/nn.2135)

2006

• Armstrong, J. D., Pocklington, A., Cumiskey, M. A. and Grant, S. G. N. 2006. Reconstructing protein complexes: From proteomics to systems biology. Proteomics 6(17), pp. 4724-4731. (10.1002/pmic.200500895)
• Pocklington, A., Armstrong, J. D. and Grant, S. G. N. 2006. Organization of brain complexity--synapse proteome form and function. Briefings in Functional Genomics and Proteomics 5(1), pp. 66. (10.1093/bfgp/ell013)
• Pocklington, A., Cumiskey, M., Armstrong, J. D. and Grant, S. G. 2006. The proteomes of neurotransmitter receptor complexes form modular networks with distributed functionality underlying plasticity and behaviour. Molecular systems biology [electronic resource] 2(2006), pp. 23-23. (10.1038/msb4100041)

2003

• Dorey, P., Pocklington, A. and Tateo, R. 2003. Integrable aspects of the scaling q-state Potts models I: bound states and bootstrap closure. Nuclear Physics B 661(3), pp. 425-463. (10.1016/S0550-3213(03)00181-0)
• Dorey, P., Pocklington, A. and Tateo, R. 2003. Integrable aspects of the scaling q-state Potts models II: finite-size effects. Nuclear Physics B 661(3), pp. 464-513. (10.1016/S0550-3213(03)00182-2)

2000

• Khastgir, S. P., Pocklington, A. and Sasaki, R. 2000. Quantum Calogero-Moser models: integrability for all root systems. Journal of Physics A: Mathematical and General 33(49), pp. 9033-9064. (10.1088/0305-4470/33/49/303)

1998

• Dorey, P., Pocklington, A., Tateo, R. and Watts, G. 1998. TBA and TCSA with boundaries and excited states. Nuclear Physics B 525(3), pp. 641-663. (10.1016/S0550-3213(98)00339-3)