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Mullins N, Forstner AJ, O'Connell KS, Coombes B, Coleman JRI, Qiao Z, Als TD, Bigdeli TB, Børte S, Bryois J, Charney AW, Drange OK, Gandal MJ, Hagenaars SP, Ikeda M, Kamitaki N, Kim M, Krebs K, Panagiotaropoulou G, Schilder BM, Sloofman LG, Steinberg S, Trubetskoy V, Winsvold BS, Won HH, Abramova L, Adorjan K, Agerbo E, Al Eissa M, Albani D, Alliey-Rodriguez N, Anjorin A, Antilla V, Antoniou A, Awasthi S, Baek JH, Bækvad-Hansen M, Bass N, Bauer M, Beins EC, Bergen SE, Birner A, Bøcker Pedersen C, Bøen E, Boks MP, Bosch R, Brum M, Brumpton BM, Brunkhorst-Kanaan N, Budde M, Bybjerg-Grauholm J, Byerley W, Cairns M, Casas M, Cervantes P, Clarke TK, Cruceanu C, Cuellar-Barboza A, Cunningham J, Curtis D, Czerski PM, Dale AM, Dalkner N, David FS, Degenhardt F, Djurovic S, Dobbyn AL, Douzenis A, Elvsåshagen T, Escott-Price V, Ferrier IN, Fiorentino A, Foroud TM, Forty L, Frank J, Frei O, Freimer NB, Frisén L, Gade K, Garnham J, Gelernter J, Giørtz Pedersen M, Gizer IR, Gordon SD, Gordon-Smith K, Greenwood TA, Grove J, Guzman-Parra J, Ha K, Haraldsson M, Hautzinger M, Heilbronner U, Hellgren D, Herms S, Hoffmann P, Holmans PA, Huckins L, Jamain S, Johnson JS, Kalman JL, Kamatani Y, Kennedy JL, Kittel-Schneider S, Knowles JA, Kogevinas M, Koromina M, Kranz TM, Kranzler HR, Kubo M, Kupka R, Kushner SA, Lavebratt C, Lawrence J, Leber M, Lee HJ, Lee PH, Levy SE, Lewis C, Liao C, Lucae S, Lundberg M, MacIntyre DJ, Magnusson SH, Maier W, Maihofer A, Malaspina D, Maratou E, Martinsson L, Mattheisen M, McCarroll SA, McGregor NW, McGuffin P, McKay JD, Medeiros H, Medland SE, Millischer V, Montgomery GW, Moran JL, Morris DW, Mühleisen TW, O'Brien N, O'Donovan C, Olde Loohuis LM, Oruc L, Papiol S, Pardiñas AF, Perry A, Pfennig A, Porichi E, Potash JB, Quested D, Raj T, Rapaport MH, DePaulo JR, Regeer EJ, Rice JP, Rivas F, Rivera M, Roth J, Roussos P, Ruderfer DM, Sánchez-Mora C, Schulte EC, Senner F, Sharp S, Shilling PD, Sigurdsson E, Sirignano L, Slaney C, Smeland OB, Smith DJ, Sobell JL, Søholm Hansen C, Soler Artigas M, Spijker AT, Stein DJ, Strauss JS, Świątkowska B, Terao C, Thorgeirsson TE, Toma C, Tooney P, Tsermpini EE, Vawter MP, Vedder H, Walters JTR, Witt SH, Xi S, Xu W, Yang JMK, Young AH, Young H, Zandi PP, Zhou H, Zillich L, Adolfsson R, Agartz I, Alda M, Alfredsson L, Babadjanova G, Backlund L, Baune BT, Bellivier F, Bengesser S, Berrettini WH, Blackwood DHR, Boehnke M, Børglum AD, Breen G, Carr VJ, Catts S, Corvin A, Craddock N, Dannlowski U, Dikeos D, Esko T, Etain B, Ferentinos P, Frye M, Fullerton JM, Gawlik M, Gershon ES, Goes FS, Green MJ, Grigoroiu-Serbanescu M, Hauser J, Henskens F, Hillert J, Hong KS, Hougaard DM, Hultman CM, Hveem K, Iwata N, Jablensky AV, Jones I, Jones LA, Kahn RS, Kelsoe JR, Kirov G, Landén M, Leboyer M, Lewis CM, Li QS, Lissowska J, Lochner C, Loughland C, Martin NG, Mathews CA, Mayoral F, McElroy SL, McIntosh AM, McMahon FJ, Melle I, Michie P, Milani L, Mitchell PB, Morken G, Mors O, Mortensen PB, Mowry B, Müller-Myhsok B, Myers RM, Neale BM, Nievergelt CM, Nordentoft M, Nöthen MM, O'Donovan MC, Oedegaard KJ, Olsson T, Owen MJ, Paciga SA, Pantelis C, Pato C, Pato MT, Patrinos GP, Perlis RH, Posthuma D, Ramos-Quiroga JA, Reif A, Reininghaus EZ, Ribasés M, Rietschel M, Ripke S, Rouleau GA, Saito T, Schall U, Schalling M, Schofield PR, Schulze TG, Scott LJ, Scott RJ, Serretti A, Shannon Weickert C, Smoller JW, Stefansson H, Stefansson K, Stordal E, Streit F, Sullivan PF, Turecki G, Vaaler AE, Vieta E, Vincent JB, Waldman ID, Weickert TW, Werge T, Wray NR, Zwart JA, Biernacka JM, Nurnberger JI, Cichon S, Edenberg HJ, Stahl EA, McQuillin A, Di Florio A, Ophoff RA, Andreassen OA. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nat Genet 2021; 53:817-829. [PMID: 34002096 PMCID: PMC8192451 DOI: 10.1038/s41588-021-00857-4] [Citation(s) in RCA: 564] [Impact Index Per Article: 188.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 03/25/2021] [Indexed: 12/14/2022]
Abstract
Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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Dauvermann MR, Mothersill D, Rokita KI, King S, Holleran L, Kane R, McKernan DP, Kelly JP, Morris DW, Corvin A, Hallahan B, McDonald C, Donohoe G. Changes in Default-Mode Network Associated With Childhood Trauma in Schizophrenia. Schizophr Bull 2021; 47:1482-1494. [PMID: 33823040 PMCID: PMC8379545 DOI: 10.1093/schbul/sbab025] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND There is considerable evidence of dysconnectivity within the default-mode network (DMN) in schizophrenia, as measured during resting-state functional MRI (rs-fMRI). History of childhood trauma (CT) is observed at a higher frequency in schizophrenia than in the general population, but its relationship to DMN functional connectivity has yet to be investigated. METHODS CT history and rs-fMRI data were collected in 65 individuals with schizophrenia and 132 healthy controls. Seed-based functional connectivity between each of 4 a priori defined seeds of the DMN (medial prefrontal cortex, right and left lateral parietal lobes, and the posterior cingulate cortex) and all other voxels of the brain were compared across groups. Effects of CT on functional connectivity were examined using multiple regression analyses. Where significant associations were observed, regression analyses were further used to determine whether variance in behavioral measures of Theory of Mind (ToM), previously associated with DMN recruitment, were explained by these associations. RESULTS Seed-based analyses revealed evidence of widespread reductions in functional connectivity in patients vs controls, including between the left/right parietal lobe (LP) and multiple other regions, including the parietal operculum bilaterally. Across all subjects, increased CT scores were associated with reduced prefrontal-parietal connectivity and, in patients, with increased prefrontal-cerebellar connectivity also. These CT-associated differences in DMN connectivity also predicted variation in behavioral measures of ToM. CONCLUSIONS These findings suggest that CT history is associated with variation in DMN connectivity during rs-fMRI in patients with schizophrenia and healthy participants, which may partly mediate associations observed between early life adversity and cognitive performance.
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Sønderby IE, van der Meer D, Moreau C, Kaufmann T, Walters GB, Ellegaard M, Abdellaoui A, Ames D, Amunts K, Andersson M, Armstrong NJ, Bernard M, Blackburn NB, Blangero J, Boomsma DI, Brodaty H, Brouwer RM, Bülow R, Bøen R, Cahn W, Calhoun VD, Caspers S, Ching CRK, Cichon S, Ciufolini S, Crespo-Facorro B, Curran JE, Dale AM, Dalvie S, Dazzan P, de Geus EJC, de Zubicaray GI, de Zwarte SMC, Desrivieres S, Doherty JL, Donohoe G, Draganski B, Ehrlich S, Eising E, Espeseth T, Fejgin K, Fisher SE, Fladby T, Frei O, Frouin V, Fukunaga M, Gareau T, Ge T, Glahn DC, Grabe HJ, Groenewold NA, Gústafsson Ó, Haavik J, Haberg AK, Hall J, Hashimoto R, Hehir-Kwa JY, Hibar DP, Hillegers MHJ, Hoffmann P, Holleran L, Holmes AJ, Homuth G, Hottenga JJ, Hulshoff Pol HE, Ikeda M, Jahanshad N, Jockwitz C, Johansson S, Jönsson EG, Jørgensen NR, Kikuchi M, Knowles EEM, Kumar K, Le Hellard S, Leu C, Linden DEJ, Liu J, Lundervold A, Lundervold AJ, Maillard AM, Martin NG, Martin-Brevet S, Mather KA, Mathias SR, McMahon KL, McRae AF, Medland SE, Meyer-Lindenberg A, Moberget T, Modenato C, Sánchez JM, Morris DW, Mühleisen TW, Murray RM, Nielsen J, Nordvik JE, Nyberg L, Loohuis LMO, Ophoff RA, Owen MJ, Paus T, Pausova Z, Peralta JM, Pike GB, Prieto C, Quinlan EB, Reinbold CS, Marques TR, Rucker JJH, Sachdev PS, Sando SB, Schofield PR, Schork AJ, Schumann G, Shin J, Shumskaya E, Silva AI, Sisodiya SM, Steen VM, Stein DJ, Strike LT, Suzuki IK, Tamnes CK, Teumer A, Thalamuthu A, Tordesillas-Gutiérrez D, Uhlmann A, Ulfarsson MO, van 't Ent D, van den Bree MBM, Vanderhaeghen P, Vassos E, Wen W, Wittfeld K, Wright MJ, Agartz I, Djurovic S, Westlye LT, Stefansson H, Stefansson K, Jacquemont S, Thompson PM, Andreassen OA. 1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans. Transl Psychiatry 2021; 11:182. [PMID: 33753722 PMCID: PMC7985307 DOI: 10.1038/s41398-021-01213-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 12/23/2020] [Accepted: 01/08/2021] [Indexed: 01/07/2023] Open
Abstract
Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.
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Hannon E, Dempster EL, Mansell G, Burrage J, Bass N, Bohlken MM, Corvin A, Curtis CJ, Dempster D, Di Forti M, Dinan TG, Donohoe G, Gaughran F, Gill M, Gillespie A, Gunasinghe C, Hulshoff HE, Hultman CM, Johansson V, Kahn RS, Kaprio J, Kenis G, Kowalec K, MacCabe J, McDonald C, McQuillin A, Morris DW, Murphy KC, Mustard CJ, Nenadic I, O'Donovan MC, Quattrone D, Richards AL, Rutten BPF, St Clair D, Therman S, Toulopoulou T, Van Os J, Waddington JL, Sullivan P, Vassos E, Breen G, Collier DA, Murray RM, Schalkwyk LS, Mill J. DNA methylation meta-analysis reveals cellular alterations in psychosis and markers of treatment-resistant schizophrenia. eLife 2021; 10:e58430. [PMID: 33646943 PMCID: PMC8009672 DOI: 10.7554/elife.58430] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 02/23/2021] [Indexed: 12/30/2022] Open
Abstract
We performed a systematic analysis of blood DNA methylation profiles from 4483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia, and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia.
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Feurle P, Abentung A, Cera I, Wahl N, Ablinger C, Bucher M, Stefan E, Sprenger S, Teis D, Fischer A, Laighneach A, Whitton L, Morris DW, Apostolova G, Dechant G. SATB2-LEMD2 interaction links nuclear shape plasticity to regulation of cognition-related genes. EMBO J 2021; 40:e103701. [PMID: 33319920 PMCID: PMC7849313 DOI: 10.15252/embj.2019103701] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 10/22/2020] [Accepted: 11/06/2020] [Indexed: 01/22/2023] Open
Abstract
SATB2 is a schizophrenia risk gene and is genetically associated with human intelligence. How it affects cognition at molecular level is currently unknown. Here, we show that interactions between SATB2, a chromosomal scaffolding protein, and the inner nuclear membrane protein LEMD2 orchestrate the response of pyramidal neurons to neuronal activation. Exposure to novel environment in vivo causes changes in nuclear shape of CA1 hippocampal neurons via a SATB2-dependent mechanism. The activity-driven plasticity of the nuclear envelope requires not only SATB2, but also its protein interactor LEMD2 and the ESCRT-III/VPS4 membrane-remodeling complex. Furthermore, LEMD2 depletion in cortical neurons, similar to SATB2 ablation, affects neuronal activity-dependent regulation of multiple rapid and delayed primary response genes. In human genetic data, LEMD2-regulated genes are enriched for de novo mutations reported in intellectual disability and schizophrenia and are, like SATB2-regulated genes, enriched for common variants associated with schizophrenia and cognitive function. Hence, interactions between SATB2 and the inner nuclear membrane protein LEMD2 influence gene expression programs in pyramidal neurons that are linked to cognitive ability and psychiatric disorder etiology.
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Holland JF, Cosgrove D, Whitton L, Harold D, Corvin A, Gill M, Mothersill DO, Morris DW, Donohoe G. Effects of complement gene-set polygenic risk score on brain volume and cortical measures in patients with psychotic disorders and healthy controls. Am J Med Genet B Neuropsychiatr Genet 2020; 183:445-453. [PMID: 32918526 DOI: 10.1002/ajmg.b.32820] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 11/26/2019] [Accepted: 08/12/2020] [Indexed: 12/14/2022]
Abstract
Multiple genome-wide association studies of schizophrenia have reported associations between genetic variants within the MHC region and disease risk, an association that has been partially accounted for by alleles of the complement component 4 (C4) gene. Following on previous findings of association between both C4 and other complement-related variants and memory function, we tested the hypothesis that polygenic scores calculated based on identified schizophrenia risk alleles within the "complement" system would be broadly associated with memory function and associated brain structure. We tested this using a polygenic risk score (PRS) calculated for complement genes, but excluding C4 variants. Higher complement-based PRS scores were observed to be associated with lower memory scores for the sample as a whole (N = 620, F change = 8.25; p = .004). A significant association between higher PRS and lower hippocampal volume was also observed (N = 216, R2 change = 0.016, p = .015). However, after correcting for further testing of association with the more general indices of cortical thickness, surface area or total brain volume, none of which were associated with complement, the association with hippocampal volume became non-significant. A post-hoc analysis of hippocampal subfields suggested an association between complement PRS and several hippocampal subfields, findings that appeared to be particularly driven by the patient sample. In conclusion, our study yielded suggestive evidence of association between complement-based schizophrenia PRS and variation in memory function and hippocampal volume.
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Cosgrove D, Whitton L, Fahey L, Ó Broin P, Donohoe G, Morris DW. Genes influenced by MEF2C contribute to neurodevelopmental disease via gene expression changes that affect multiple types of cortical excitatory neurons. Hum Mol Genet 2020; 30:961-970. [PMID: 32975584 DOI: 10.1093/hmg/ddaa213] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 07/31/2020] [Accepted: 07/31/2020] [Indexed: 12/19/2022] Open
Abstract
Myocyte enhancer factor 2 C (MEF2C) is an important transcription factor during neurodevelopment. Mutation or deletion of MEF2C causes intellectual disability (ID), and common variants within MEF2C are associated with cognitive function and schizophrenia risk. We investigated if genes influenced by MEF2C during neurodevelopment are enriched for genes associated with neurodevelopmental phenotypes and if this can be leveraged to identify biological mechanisms and individual brain cell types affected. We used a set of 1055 genes that were differentially expressed in the adult mouse brain following early embryonic deletion of Mef2c in excitatory cortical neurons. Using genome-wide association studies data, we found these differentially expressed genes (DEGs) to be enriched for genes associated with schizophrenia, intelligence and educational attainment but not autism spectrum disorder (ASD). For this gene set, genes that overlap with target genes of the Fragile X mental retardation protein (FMRP) are a major driver of these enrichments. Using trios data, we found these DEGs to be enriched for genes containing de novo mutations reported in ASD and ID, but not schizophrenia. Using single-cell RNA sequencing data, we identified that a number of different excitatory glutamatergic neurons in the cortex were enriched for these DEGs including deep layer pyramidal cells and cells in the retrosplenial cortex, entorhinal cortex and subiculum, and these cell types are also enriched for FMRP target genes. The involvement of MEF2C and FMRP in synapse elimination suggests that disruption of this process in these cell types during neurodevelopment contributes to cognitive function and risk of neurodevelopmental disorders.
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Fahey L, Donohoe G, Broin PÓ, Morris DW. Genes regulated by BCL11B during T-cell development are enriched for de novo mutations found in schizophrenia patients. Am J Med Genet B Neuropsychiatr Genet 2020; 183:370-379. [PMID: 32729240 DOI: 10.1002/ajmg.b.32811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 04/20/2020] [Accepted: 05/28/2020] [Indexed: 11/06/2022]
Abstract
While abnormal neurodevelopment contributes to schizophrenia (SCZ) risk, there is also evidence to support a role for immune dysfunction in SCZ. BCL11B, associated with SCZ in genome-wide association study (GWAS), is a transcription factor that regulates the differentiation and development of cells in the central nervous and immune systems. Here, we use functional genomics data from studies of BCL11B to investigate the contribution of neuronal and immune processes to SCZ pathophysiology. We identified the gene targets of BCL11B in brain striatal cells (n = 223 genes), double negative 4 (DN4) developing T cells (n = 114 genes) and double positive (DP) developing T cells (n = 518 genes) using an integrated analysis of RNA-seq and ChIP-seq data. No gene-set was enriched for genes containing common variants associated with SCZ but the DP gene-set was enriched for genes containing missense de novo mutations (DNMs; p = .001) using data from 3,447 SCZ trios. Post hoc analysis revealed the enrichment to be stronger for DP genes negatively regulated by BCL11B. Biological processes enriched for genes negatively regulated by BCL11B in DP gene-set included immune system development and cytokine signaling. These analyses, leveraging a GWAS-identified SCZ risk gene and data on gene expression and transcription factor binding, indicate that DNMs in immune pathways contribute to SCZ risk.
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Rokita KI, Dauvermann MR, Mothersill D, Holleran L, Holland J, Costello L, Cullen C, Kane R, McKernan D, Morris DW, Kelly J, Gill M, Corvin A, Hallahan B, McDonald C, Donohoe G. Childhood trauma, parental bonding, and social cognition in patients with schizophrenia and healthy adults. J Clin Psychol 2020; 77:241-253. [DOI: 10.1002/jclp.23023] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 05/18/2020] [Accepted: 06/04/2020] [Indexed: 12/19/2022]
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van der Meer D, Sønderby IE, Kaufmann T, Walters GB, Abdellaoui A, Ames D, Amunts K, Andersson M, Armstrong NJ, Bernard M, Blackburn NB, Blangero J, Boomsma DI, Brodaty H, Brouwer RM, Bülow R, Cahn W, Calhoun VD, Caspers S, Cavalleri GL, Ching CRK, Cichon S, Ciufolini S, Corvin A, Crespo-Facorro B, Curran JE, Dalvie S, Dazzan P, de Geus EJC, de Zubicaray GI, de Zwarte SMC, Delanty N, den Braber A, Desrivieres S, Di Forti M, Doherty JL, Donohoe G, Ehrlich S, Eising E, Espeseth T, Fisher SE, Fladby T, Frei O, Frouin V, Fukunaga M, Gareau T, Glahn DC, Grabe HJ, Groenewold NA, Gústafsson Ó, Haavik J, Haberg AK, Hashimoto R, Hehir-Kwa JY, Hibar DP, Hillegers MHJ, Hoffmann P, Holleran L, Hottenga JJ, Hulshoff Pol HE, Ikeda M, Jacquemont S, Jahanshad N, Jockwitz C, Johansson S, Jönsson EG, Kikuchi M, Knowles EEM, Kwok JB, Le Hellard S, Linden DEJ, Liu J, Lundervold A, Lundervold AJ, Martin NG, Mather KA, Mathias SR, McMahon KL, McRae AF, Medland SE, Moberget T, Moreau C, Morris DW, Mühleisen TW, Murray RM, Nordvik JE, Nyberg L, Olde Loohuis LM, Ophoff RA, Owen MJ, Paus T, Pausova Z, Peralta JM, Pike B, Prieto C, Quinlan EB, Reinbold CS, Reis Marques T, Rucker JJH, Sachdev PS, Sando SB, Schofield PR, Schork AJ, Schumann G, Shin J, Shumskaya E, Silva AI, Sisodiya SM, Steen VM, Stein DJ, Strike LT, Tamnes CK, Teumer A, Thalamuthu A, Tordesillas-Gutiérrez D, Uhlmann A, Úlfarsson MÖ, van 't Ent D, van den Bree MBM, Vassos E, Wen W, Wittfeld K, Wright MJ, Zayats T, Dale AM, Djurovic S, Agartz I, Westlye LT, Stefánsson H, Stefánsson K, Thompson PM, Andreassen OA. Association of Copy Number Variation of the 15q11.2 BP1-BP2 Region With Cortical and Subcortical Morphology and Cognition. JAMA Psychiatry 2020; 77:420-430. [PMID: 31665216 PMCID: PMC6822096 DOI: 10.1001/jamapsychiatry.2019.3779] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 09/26/2019] [Indexed: 01/04/2023]
Abstract
Importance Recurrent microdeletions and duplications in the genomic region 15q11.2 between breakpoints 1 (BP1) and 2 (BP2) are associated with neurodevelopmental disorders. These structural variants are present in 0.5% to 1.0% of the population, making 15q11.2 BP1-BP2 the site of the most prevalent known pathogenic copy number variation (CNV). It is unknown to what extent this CNV influences brain structure and affects cognitive abilities. Objective To determine the association of the 15q11.2 BP1-BP2 deletion and duplication CNVs with cortical and subcortical brain morphology and cognitive task performance. Design, Setting, and Participants In this genetic association study, T1-weighted brain magnetic resonance imaging were combined with genetic data from the ENIGMA-CNV consortium and the UK Biobank, with a replication cohort from Iceland. In total, 203 deletion carriers, 45 247 noncarriers, and 306 duplication carriers were included. Data were collected from August 2015 to April 2019, and data were analyzed from September 2018 to September 2019. Main Outcomes and Measures The associations of the CNV with global and regional measures of surface area and cortical thickness as well as subcortical volumes were investigated, correcting for age, age2, sex, scanner, and intracranial volume. Additionally, measures of cognitive ability were analyzed in the full UK Biobank cohort. Results Of 45 756 included individuals, the mean (SD) age was 55.8 (18.3) years, and 23 754 (51.9%) were female. Compared with noncarriers, deletion carriers had a lower surface area (Cohen d = -0.41; SE, 0.08; P = 4.9 × 10-8), thicker cortex (Cohen d = 0.36; SE, 0.07; P = 1.3 × 10-7), and a smaller nucleus accumbens (Cohen d = -0.27; SE, 0.07; P = 7.3 × 10-5). There was also a significant negative dose response on cortical thickness (β = -0.24; SE, 0.05; P = 6.8 × 10-7). Regional cortical analyses showed a localization of the effects to the frontal, cingulate, and parietal lobes. Further, cognitive ability was lower for deletion carriers compared with noncarriers on 5 of 7 tasks. Conclusions and Relevance These findings, from the largest CNV neuroimaging study to date, provide evidence that 15q11.2 BP1-BP2 structural variation is associated with brain morphology and cognition, with deletion carriers being particularly affected. The pattern of results fits with known molecular functions of genes in the 15q11.2 BP1-BP2 region and suggests involvement of these genes in neuronal plasticity. These neurobiological effects likely contribute to the association of this CNV with neurodevelopmental disorders.
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Grasby KL, Jahanshad N, Painter JN, Colodro-Conde L, Bralten J, Hibar DP, Lind PA, Pizzagalli F, Ching CRK, McMahon MAB, Shatokhina N, Zsembik LCP, Thomopoulos SI, Zhu AH, Strike LT, Agartz I, Alhusaini S, Almeida MAA, Alnæs D, Amlien IK, Andersson M, Ard T, Armstrong NJ, Ashley-Koch A, Atkins JR, Bernard M, Brouwer RM, Buimer EEL, Bülow R, Bürger C, Cannon DM, Chakravarty M, Chen Q, Cheung JW, Couvy-Duchesne B, Dale AM, Dalvie S, de Araujo TK, de Zubicaray GI, de Zwarte SMC, den Braber A, Doan NT, Dohm K, Ehrlich S, Engelbrecht HR, Erk S, Fan CC, Fedko IO, Foley SF, Ford JM, Fukunaga M, Garrett ME, Ge T, Giddaluru S, Goldman AL, Green MJ, Groenewold NA, Grotegerd D, Gurholt TP, Gutman BA, Hansell NK, Harris MA, Harrison MB, Haswell CC, Hauser M, Herms S, Heslenfeld DJ, Ho NF, Hoehn D, Hoffmann P, Holleran L, Hoogman M, Hottenga JJ, Ikeda M, Janowitz D, Jansen IE, Jia T, Jockwitz C, Kanai R, Karama S, Kasperaviciute D, Kaufmann T, Kelly S, Kikuchi M, Klein M, Knapp M, Knodt AR, Krämer B, Lam M, Lancaster TM, Lee PH, Lett TA, Lewis LB, Lopes-Cendes I, Luciano M, Macciardi F, Marquand AF, Mathias SR, Melzer TR, Milaneschi Y, Mirza-Schreiber N, Moreira JCV, Mühleisen TW, Müller-Myhsok B, Najt P, Nakahara S, Nho K, Loohuis LMO, Orfanos DP, Pearson JF, Pitcher TL, Pütz B, Quidé Y, Ragothaman A, Rashid FM, Reay WR, Redlich R, Reinbold CS, Repple J, Richard G, Riede BC, Risacher SL, Rocha CS, Mota NR, Salminen L, Saremi A, Saykin AJ, Schlag F, Schmaal L, Schofield PR, Secolin R, Shapland CY, Shen L, Shin J, Shumskaya E, Sønderby IE, Sprooten E, Tansey KE, Teumer A, Thalamuthu A, Tordesillas-Gutiérrez D, Turner JA, Uhlmann A, Vallerga CL, van derMeer D, van Donkelaar MMJ, van Eijk L, van Erp TGM, van Haren NEM, van Rooij D, van Tol MJ, Veldink JH, Verhoef E, Walton E, Wang M, Wang Y, Wardlaw JM, Wen W, Westlye LT, Whelan CD, Witt SH, Wittfeld K, Wolf C, Wolfers T, Wu JQ, Yasuda CL, Zaremba D, Zhang Z, Zwiers MP, Artiges E, Assareh AA, Ayesa-Arriola R, Belger A, Brandt CL, Brown GG, Cichon S, Curran JE, Davies GE, Degenhardt F, Dennis MF, Dietsche B, Djurovic S, Doherty CP, Espiritu R, Garijo D, Gil Y, Gowland PA, Green RC, Häusler AN, Heindel W, Ho BC, Hoffmann WU, Holsboer F, Homuth G, Hosten N, Jack CR, Jang M, Jansen A, Kimbrel NA, Kolskår K, Koops S, Krug A, Lim KO, Luykx JJ, Mathalon DH, Mather KA, Mattay VS, Matthews S, Van Son JM, McEwen SC, Melle I, Morris DW, Mueller BA, Nauck M, Nordvik JE, Nöthen MM, O’Leary DS, Opel N, Martinot MLP, Pike GB, Preda A, Quinlan EB, Rasser PE, Ratnakar V, Reppermund S, Steen VM, Tooney PA, Torres FR, Veltman DJ, Voyvodic JT, Whelan R, White T, Yamamori H, Adams HHH, Bis JC, Debette S, Decarli C, Fornage M, Gudnason V, Hofer E, Ikram MA, Launer L, Longstreth WT, Lopez OL, Mazoyer B, Mosley TH, Roshchupkin GV, Satizabal CL, Schmidt R, Seshadri S, Yang Q, Alvim MKM, Ames D, Anderson TJ, Andreassen OA, Arias-Vasquez A, Bastin ME, Baune BT, Beckham JC, Blangero J, Boomsma DI, Brodaty H, Brunner HG, Buckner RL, Buitelaar JK, Bustillo JR, Cahn W, Cairns MJ, Calhoun V, Carr VJ, Caseras X, Caspers S, Cavalleri GL, Cendes F, Corvin A, Crespo-Facorro B, Dalrymple-Alford JC, Dannlowski U, de Geus EJC, Deary IJ, Delanty N, Depondt C, Desrivières S, Donohoe G, Espeseth T, Fernández G, Fisher SE, Flor H, Forstner AJ, Francks C, Franke B, Glahn DC, Gollub RL, Grabe HJ, Gruber O, Håberg AK, Hariri AR, Hartman CA, Hashimoto R, Heinz A, Henskens FA, Hillegers MHJ, Hoekstra PJ, Holmes AJ, Hong LE, Hopkins WD, Pol HEH, Jernigan TL, Jönsson EG, Kahn RS, Kennedy MA, Kircher TTJ, Kochunov P, Kwok JBJ, Le Hellard S, Loughland CM, Martin NG, Martinot JL, McDonald C, McMahon KL, Meyer-Lindenberg A, Michie PT, Morey RA, Mowry B, Nyberg L, Oosterlaan J, Ophoff RA, Pantelis C, Paus T, Pausova Z, Penninx BWJH, Polderman TJC, Posthuma D, Rietschel M, Roffman JL, Rowland LM, Sachdev PS, Sämann PG, Schall U, Schumann G, Scott RJ, Sim K, Sisodiya SM, Smoller JW, Sommer IE, St Pourcain B, Stein DJ, Toga AW, Trollor JN, Van der Wee NJA, van ‘t Ent D, Völzke H, Walter H, Weber B, Weinberger DR, Wright MJ, Zhou J, Stein JL, Thompson PM, Medland SE. The genetic architecture of the human cerebral cortex. Science 2020; 367:eaay6690. [PMID: 32193296 PMCID: PMC7295264 DOI: 10.1126/science.aay6690] [Citation(s) in RCA: 388] [Impact Index Per Article: 97.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 02/10/2020] [Indexed: 12/15/2022]
Abstract
The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
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McVeigh ÚM, McVeigh TP, Curran C, Miller N, Morris DW, Kerin MJ. Correction to: Diagnostic yield of a custom-designed multi-gene cancer panel in Irish patients with breast cancer. Ir J Med Sci 2020; 189:1515. [PMID: 32072478 DOI: 10.1007/s11845-020-02202-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The originally published version of this article contained typesetting errors in Figs. 2 and 3 legends. The correct figure legends are presented here. The original article has been corrected.
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McVeigh ÚM, McVeigh TP, Curran C, Miller N, Morris DW, Kerin MJ. Diagnostic yield of a custom-designed multi-gene cancer panel in Irish patients with breast cancer. Ir J Med Sci 2020; 189:849-864. [PMID: 32008151 DOI: 10.1007/s11845-020-02174-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 01/20/2020] [Indexed: 12/25/2022]
Abstract
BACKGROUND Breast cancer is genetically heterogeneous, and parellel multi-gene sequencing is the most cost- and time-efficient manner to investigate breast cancer predisposition. Numerous multi-gene panels (MGPs) are commercially available, but many include genes with weak/unproven associaton with breast cancer, or with predisposition to cancer of other types. This study investigates the utility of a custom-designed multi-gene panel in an Irish cohort with breast cancer. METHODS A custom panel comprising 83 genes offered by 19 clinical "breast cancer predisposition" MGPs was designed and applied to germline DNA from 91 patients with breast cancer and 77 unaffected ethnicially matched controls. Variants were identified and classified using a custom pipeline. RESULTS Nineteen loss-of-function (LOF) and 334 missense variants were identified. After removing common and/or benign variants, 15 LOF and 30 missense variants were analysed. Variants in known breast cancer susceptibility genes were identified, including in BRCA1 and ATM in cases, and in NF1 and CHEK2 in controls. Most variants identified were in genes associated with predisposition to cancers other than breast cancer (BRIP1, RAD50, MUTYH, and mismatch repair genes), or in genes with unknown or unproven association with cancer. CONCLUSION Using multi-gene panels enables rapid, cost-effective identification of individuals with high-risk cancer predisposition syndromes. However, this approach also leads to an increased amount of uncertain results. Clinical management of individuals with particular genetic variants in the absence of a matching phenotype/family history is challenging. Further population and functional evidence is required to fully elucidate the clinical relevance of variants in genes of uncertain significance.
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Richards AL, Pardiñas AF, Frizzati A, Tansey KE, Lynham AJ, Holmans P, Legge SE, Savage JE, Agartz I, Andreassen OA, Blokland GAM, Corvin A, Cosgrove D, Degenhardt F, Djurovic S, Espeseth T, Ferraro L, Gayer-Anderson C, Giegling I, van Haren NE, Hartmann AM, Hubert JJ, Jönsson EG, Konte B, Lennertz L, Olde Loohuis LM, Melle I, Morgan C, Morris DW, Murray RM, Nyman H, Ophoff RA, van Os J, Petryshen TL, Quattrone D, Rietschel M, Rujescu D, Rutten BPF, Streit F, Strohmaier J, Sullivan PF, Sundet K, Wagner M, Escott-Price V, Owen MJ, Donohoe G, O’Donovan MC, Walters JTR. The Relationship Between Polygenic Risk Scores and Cognition in Schizophrenia. Schizophr Bull 2020; 46:336-344. [PMID: 31206164 PMCID: PMC7442352 DOI: 10.1093/schbul/sbz061] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Cognitive impairment is a clinically important feature of schizophrenia. Polygenic risk score (PRS) methods have demonstrated genetic overlap between schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), educational attainment (EA), and IQ, but very few studies have examined associations between these PRS and cognitive phenotypes within schizophrenia cases. METHODS We combined genetic and cognitive data in 3034 schizophrenia cases from 11 samples using the general intelligence factor g as the primary measure of cognition. We used linear regression to examine the association between cognition and PRS for EA, IQ, schizophrenia, BD, and MDD. The results were then meta-analyzed across all samples. A genome-wide association studies (GWAS) of cognition was conducted in schizophrenia cases. RESULTS PRS for both population IQ (P = 4.39 × 10-28) and EA (P = 1.27 × 10-26) were positively correlated with cognition in those with schizophrenia. In contrast, there was no association between cognition in schizophrenia cases and PRS for schizophrenia (P = .39), BD (P = .51), or MDD (P = .49). No individual variant approached genome-wide significance in the GWAS. CONCLUSIONS Cognition in schizophrenia cases is more strongly associated with PRS that index cognitive traits in the general population than PRS for neuropsychiatric disorders. This suggests the mechanisms of cognitive variation within schizophrenia are at least partly independent from those that predispose to schizophrenia diagnosis itself. Our findings indicate that this cognitive variation arises at least in part due to genetic factors shared with cognitive performance in populations and is not solely due to illness or treatment-related factors, although our findings are consistent with important contributions from these factors.
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Holland JF, Cosgrove D, Whitton L, Harold D, Corvin A, Gill M, Mothersill DO, Morris DW, Donohoe G. Beyond C4: Analysis of the complement gene pathway shows enrichment for IQ in patients with psychotic disorders and healthy controls. GENES BRAIN AND BEHAVIOR 2019; 18:e12602. [DOI: 10.1111/gbb.12602] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 07/23/2019] [Accepted: 07/30/2019] [Indexed: 12/22/2022]
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Higgins MG, Kenny DA, Fitzsimons C, Blackshields G, Coyle S, McKenna C, McGee M, Morris DW, Waters SM. The effect of breed and diet type on the global transcriptome of hepatic tissue in beef cattle divergent for feed efficiency. BMC Genomics 2019; 20:525. [PMID: 31242854 PMCID: PMC6593537 DOI: 10.1186/s12864-019-5906-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 06/17/2019] [Indexed: 01/07/2023] Open
Abstract
Background Feed efficiency is an important economic and environmental trait in beef production, which can be measured in terms of residual feed intake (RFI). Cattle selected for low-RFI (feed efficient) have similar production levels but decreased feed intake, while also emitting less methane. RFI is difficult and expensive to measure and is not widely adopted in beef production systems. However, development of DNA-based biomarkers for RFI may facilitate its adoption in genomic-assisted breeding programmes. Cattle have been shown to re-rank in terms of RFI across diets and age, while also RFI varies by breed. Therefore, we used RNA-Seq technology to investigate the hepatic transcriptome of RFI-divergent Charolais (CH) and Holstein-Friesian (HF) steers across three dietary phases to identify genes and biological pathways associated with RFI regardless of diet or breed. Results Residual feed intake was measured during a high-concentrate phase, a zero-grazed grass phase and a final high-concentrate phase. In total, 322 and 33 differentially expressed genes (DEGs) were identified across all diets for CH and HF steers, respectively. Three genes, GADD45G, HP and MID1IP1, were differentially expressed in CH when both the high-concentrate zero-grazed grass diet were offered. Two canonical pathways were enriched across all diets for CH steers. These canonical pathways were related to immune function. Conclusions The absence of common differentially expressed genes across all dietary phases and breeds in this study supports previous reports of the re-ranking of animals in terms of RFI when offered differing diets over their lifetime. However, we have identified biological processes such as the immune response and lipid metabolism as potentially associated with RFI divergence emphasising the previously reported roles of these biological processes with respect to RFI. Electronic supplementary material The online version of this article (10.1186/s12864-019-5906-8) contains supplementary material, which is available to authorized users.
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Stahl EA, Breen G, Forstner AJ, McQuillin A, Ripke S, Trubetskoy V, Mattheisen M, Wang Y, Coleman JRI, Gaspar HA, de Leeuw CA, Steinberg S, Pavlides JMW, Trzaskowski M, Byrne EM, Pers TH, Holmans PA, Richards AL, Abbott L, Agerbo E, Akil H, Albani D, Alliey-Rodriguez N, Als TD, Anjorin A, Antilla V, Awasthi S, Badner JA, Bækvad-Hansen M, Barchas JD, Bass N, Bauer M, Belliveau R, Bergen SE, Pedersen CB, Bøen E, Boks MP, Boocock J, Budde M, Bunney W, Burmeister M, Bybjerg-Grauholm J, Byerley W, Casas M, Cerrato F, Cervantes P, Chambert K, Charney AW, Chen D, Churchhouse C, Clarke TK, Coryell W, Craig DW, Cruceanu C, Curtis D, Czerski PM, Dale AM, de Jong S, Degenhardt F, Del-Favero J, DePaulo JR, Djurovic S, Dobbyn AL, Dumont A, Elvsåshagen T, Escott-Price V, Fan CC, Fischer SB, Flickinger M, Foroud TM, Forty L, Frank J, Fraser C, Freimer NB, Frisén L, Gade K, Gage D, Garnham J, Giambartolomei C, Pedersen MG, Goldstein J, Gordon SD, Gordon-Smith K, Green EK, Green MJ, Greenwood TA, Grove J, Guan W, Guzman-Parra J, Hamshere ML, Hautzinger M, Heilbronner U, Herms S, Hipolito M, Hoffmann P, Holland D, Huckins L, Jamain S, Johnson JS, Juréus A, Kandaswamy R, Karlsson R, Kennedy JL, Kittel-Schneider S, Knowles JA, Kogevinas M, Koller AC, Kupka R, Lavebratt C, Lawrence J, Lawson WB, Leber M, Lee PH, Levy SE, Li JZ, Liu C, Lucae S, Maaser A, MacIntyre DJ, Mahon PB, Maier W, Martinsson L, McCarroll S, McGuffin P, McInnis MG, McKay JD, Medeiros H, Medland SE, Meng F, Milani L, Montgomery GW, Morris DW, Mühleisen TW, Mullins N, Nguyen H, Nievergelt CM, Adolfsson AN, Nwulia EA, O'Donovan C, Loohuis LMO, Ori APS, Oruc L, Ösby U, Perlis RH, Perry A, Pfennig A, Potash JB, Purcell SM, Regeer EJ, Reif A, Reinbold CS, Rice JP, Rivas F, Rivera M, Roussos P, Ruderfer DM, Ryu E, Sánchez-Mora C, Schatzberg AF, Scheftner WA, Schork NJ, Shannon Weickert C, Shehktman T, Shilling PD, Sigurdsson E, Slaney C, Smeland OB, Sobell JL, Søholm Hansen C, Spijker AT, St Clair D, Steffens M, Strauss JS, Streit F, Strohmaier J, Szelinger S, Thompson RC, Thorgeirsson TE, Treutlein J, Vedder H, Wang W, Watson SJ, Weickert TW, Witt SH, Xi S, Xu W, Young AH, Zandi P, Zhang P, Zöllner S, Adolfsson R, Agartz I, Alda M, Backlund L, Baune BT, Bellivier F, Berrettini WH, Biernacka JM, Blackwood DHR, Boehnke M, Børglum AD, Corvin A, Craddock N, Daly MJ, Dannlowski U, Esko T, Etain B, Frye M, Fullerton JM, Gershon ES, Gill M, Goes F, Grigoroiu-Serbanescu M, Hauser J, Hougaard DM, Hultman CM, Jones I, Jones LA, Kahn RS, Kirov G, Landén M, Leboyer M, Lewis CM, Li QS, Lissowska J, Martin NG, Mayoral F, McElroy SL, McIntosh AM, McMahon FJ, Melle I, Metspalu A, Mitchell PB, Morken G, Mors O, Mortensen PB, Müller-Myhsok B, Myers RM, Neale BM, Nimgaonkar V, Nordentoft M, Nöthen MM, O'Donovan MC, Oedegaard KJ, Owen MJ, Paciga SA, Pato C, Pato MT, Posthuma D, Ramos-Quiroga JA, Ribasés M, Rietschel M, Rouleau GA, Schalling M, Schofield PR, Schulze TG, Serretti A, Smoller JW, Stefansson H, Stefansson K, Stordal E, Sullivan PF, Turecki G, Vaaler AE, Vieta E, Vincent JB, Werge T, Nurnberger JI, Wray NR, Di Florio A, Edenberg HJ, Cichon S, Ophoff RA, Scott LJ, Andreassen OA, Kelsoe J, Sklar P. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat Genet 2019; 51:793-803. [PMID: 31043756 PMCID: PMC6956732 DOI: 10.1038/s41588-019-0397-8] [Citation(s) in RCA: 910] [Impact Index Per Article: 182.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2018] [Accepted: 03/18/2019] [Indexed: 12/18/2022]
Abstract
Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.
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Rees E, Carrera N, Morgan J, Hambridge K, Escott-Price V, Pocklington AJ, Richards AL, Pardiñas AF, McDonald C, Donohoe G, Morris DW, Kenny E, Kelleher E, Gill M, Corvin A, Kirov G, Walters JTR, Holmans P, Owen MJ, O'Donovan MC. Targeted Sequencing of 10,198 Samples Confirms Abnormalities in Neuronal Activity and Implicates Voltage-Gated Sodium Channels in Schizophrenia Pathogenesis. Biol Psychiatry 2019; 85:554-562. [PMID: 30420267 PMCID: PMC6428681 DOI: 10.1016/j.biopsych.2018.08.022] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Revised: 08/31/2018] [Accepted: 08/31/2018] [Indexed: 12/30/2022]
Abstract
BACKGROUND Sequencing studies have pointed to the involvement in schizophrenia of rare coding variants in neuronally expressed genes, including activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-D-aspartate receptor (NMDAR) complexes; however, larger samples are required to reveal novel genes and specific biological mechanisms. METHODS We sequenced 187 genes, selected for prior evidence of association with schizophrenia, in a new dataset of 5207 cases and 4991 controls. Included among these genes were members of ARC and NMDAR postsynaptic protein complexes, as well as voltage-gated sodium and calcium channels. We performed a rare variant meta-analysis with published sequencing data for a total of 11,319 cases, 15,854 controls, and 1136 trios. RESULTS While no individual gene was significantly associated with schizophrenia after genome-wide correction for multiple testing, we strengthen the evidence that rare exonic variants in the ARC (p = 4.0 × 10-4) and NMDAR (p = 1.7 × 10-5) synaptic complexes are risk factors for schizophrenia. In addition, we found that loss-of-function variants and missense variants at paralog-conserved sites were enriched in voltage-gated sodium channels, particularly the alpha subunits (p = 8.6 × 10-4). CONCLUSIONS In one of the largest sequencing studies of schizophrenia to date, we provide novel evidence that multiple voltage-gated sodium channels are involved in schizophrenia pathogenesis and confirm the involvement of ARC and NMDAR postsynaptic complexes.
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Harold D, Connolly S, Riley BP, Kendler KS, McCarthy SE, McCombie WR, Richards A, Owen MJ, O'Donovan MC, Walters J, Donohoe G, Gill M, Corvin A, Morris DW. Population-based identity-by-descent mapping combined with exome sequencing to detect rare risk variants for schizophrenia. Am J Med Genet B Neuropsychiatr Genet 2019; 180:223-231. [PMID: 30801977 PMCID: PMC8863274 DOI: 10.1002/ajmg.b.32716] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Revised: 10/22/2018] [Accepted: 12/03/2018] [Indexed: 12/30/2022]
Abstract
Genome-wide association studies (GWASs) are highly effective at identifying common risk variants for schizophrenia. Rare risk variants are also important contributors to schizophrenia etiology but, with the exception of large copy number variants, are difficult to detect with GWAS. Exome and genome sequencing, which have accelerated the study of rare variants, are expensive so alternative methods are needed to aid detection of rare variants. Here we re-analyze an Irish schizophrenia GWAS dataset (n = 3,473) by performing identity-by-descent (IBD) mapping followed by exome sequencing of individuals identified as sharing risk haplotypes to search for rare risk variants in coding regions. We identified 45 rare haplotypes (>1 cM) that were significantly more common in cases than controls. By exome sequencing 105 haplotype carriers, we investigated these haplotypes for functional coding variants that could be tested for association in independent GWAS samples. We identified one rare missense variant in PCNT but did not find statistical support for an association with schizophrenia in a replication analysis. However, IBD mapping can prioritize both individual samples and genomic regions for follow-up analysis but genome rather than exome sequencing may be more effective at detecting risk variants on rare haplotypes.
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Cera I, Whitton L, Donohoe G, Morris DW, Dechant G, Apostolova G. Genes encoding SATB2-interacting proteins in adult cerebral cortex contribute to human cognitive ability. PLoS Genet 2019; 15:e1007890. [PMID: 30726206 PMCID: PMC6364870 DOI: 10.1371/journal.pgen.1007890] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 12/12/2018] [Indexed: 12/16/2022] Open
Abstract
During CNS development, the nuclear protein SATB2 is expressed in superficial cortical layers and determines projection neuron identity. In the adult CNS, SATB2 is expressed in pyramidal neurons of all cortical layers and is a regulator of synaptic plasticity and long-term memory. Common variation in SATB2 locus confers risk of schizophrenia, whereas rare, de novo structural and single nucleotide variants cause severe intellectual disability and absent or limited speech. To characterize differences in SATB2 molecular function in developing vs adult neocortex, we isolated SATB2 protein interactomes at the two ontogenetic stages and identified multiple novel SATB2 interactors. SATB2 interactomes are highly enriched for proteins that stabilize de novo chromatin loops. The comparison between the neonatal and adult SATB2 protein complexes indicates a developmental shift in SATB2 molecular function, from transcriptional repression towards organization of chromosomal superstructure. Accordingly, gene sets regulated by SATB2 in the neocortex of neonatal and adult mice show limited overlap. Genes encoding SATB2 protein interactors were grouped for gene set analysis of human GWAS data. Common variants associated with human cognitive ability are enriched within the genes encoding adult but not neonatal SATB2 interactors. Our data support a shift in the function of SATB2 in cortex over lifetime and indicate that regulation of spatial chromatin architecture by the SATB2 interactome contributes to cognitive function in the general population.
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van Erp TGM, Walton E, Hibar DP, Schmaal L, Jiang W, Glahn DC, Pearlson GD, Yao N, Fukunaga M, Hashimoto R, Okada N, Yamamori H, Bustillo JR, Clark VP, Agartz I, Mueller BA, Cahn W, de Zwarte SMC, Hulshoff Pol HE, Kahn RS, Ophoff RA, van Haren NEM, Andreassen OA, Dale AM, Doan NT, Gurholt TP, Hartberg CB, Haukvik UK, Jørgensen KN, Lagerberg TV, Melle I, Westlye LT, Gruber O, Kraemer B, Richter A, Zilles D, Calhoun VD, Crespo-Facorro B, Roiz-Santiañez R, Tordesillas-Gutiérrez D, Loughland C, Carr VJ, Catts S, Cropley VL, Fullerton JM, Green MJ, Henskens F, Jablensky A, Lenroot RK, Mowry BJ, Michie PT, Pantelis C, Quidé Y, Schall U, Scott RJ, Cairns MJ, Seal M, Tooney PA, Rasser PE, Cooper G, Weickert CS, Weickert TW, Morris DW, Hong E, Kochunov P, Beard LM, Gur RE, Gur RC, Satterthwaite TD, Wolf DH, Belger A, Brown GG, Ford JM, Macciardi F, Mathalon DH, O’Leary DS, Potkin SG, Preda A, Voyvodic J, Lim KO, McEwen S, Yang F, Tan Y, Tan S, Wang Z, Fan F, Chen J, Xiang H, Tang S, Guo H, Wan P, Wei D, Bockholt HJ, Ehrlich S, Wolthusen RPF, King MD, Shoemaker JM, Sponheim SR, De Haan L, Koenders L, Machielsen MW, van Amelsvoort T, Veltman DJ, Assogna F, Banaj N, de Rossi P, Iorio M, Piras F, Spalletta G, McKenna PJ, Pomarol-Clotet E, Salvador R, Corvin A, Donohoe G, Kelly S, Whelan CD, Dickie EW, Rotenberg D, Voineskos A, Ciufolini S, Radua J, Dazzan P, Murray R, Marques TR, Simmons A, Borgwardt S, Egloff L, Harrisberger F, Riecher-Rössler A, Smieskova R, Alpert KI, Wang L, Jönsson EG, Koops S, Sommer IEC, Bertolino A, Bonvino A, Di Giorgio A, Neilson E, Mayer AR, Stephen JM, Kwon JS, Yun JY, Cannon DM, McDonald C, Lebedeva I, Tomyshev AS, Akhadov T, Kaleda V, Fatouros-Bergman H, Flyckt L, Busatto GF, Rosa PGP, Serpa MH, Zanetti MV, Hoschl C, Skoch A, Spaniel F, Tomecek D, Hagenaars SP, McIntosh AM, Whalley HC, Lawrie SM, Knöchel C, Oertel-Knöchel V, Stäblein M, Howells FM, Stein DJ, Temmingh H, Uhlmann A, Lopez-Jaramillo C, Dima D, McMahon A, Faskowitz JI, Gutman BA, Jahanshad N, Thompson PM, Turner JA. Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium. Biol Psychiatry 2018; 84:644-654. [PMID: 29960671 PMCID: PMC6177304 DOI: 10.1016/j.biopsych.2018.04.023] [Citation(s) in RCA: 532] [Impact Index Per Article: 88.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Revised: 04/19/2018] [Accepted: 04/20/2018] [Indexed: 12/31/2022]
Abstract
BACKGROUND The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. METHODS The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide. RESULTS Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. CONCLUSIONS The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.
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Higgins MG, Fitzsimons C, McClure MC, McKenna C, Conroy S, Kenny DA, McGee M, Waters SM, Morris DW. GWAS and eQTL analysis identifies a SNP associated with both residual feed intake and GFRA2 expression in beef cattle. Sci Rep 2018; 8:14301. [PMID: 30250203 PMCID: PMC6155370 DOI: 10.1038/s41598-018-32374-6] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 09/03/2018] [Indexed: 11/09/2022] Open
Abstract
Residual feed intake (RFI), a measure of feed efficiency, is an important economic and environmental trait in beef production. Selection of low RFI (feed efficient) cattle could maintain levels of production, while decreasing feed costs and methane emissions. However, RFI is a difficult and expensive trait to measure. Identification of single nucleotide polymorphisms (SNPs) associated with RFI may enable rapid, cost effective genomic selection of feed efficient cattle. Genome-wide association studies (GWAS) were conducted in multiple breeds followed by meta-analysis to identify genetic variants associated with RFI and component traits (average daily gain (ADG) and feed intake (FI)) in Irish beef cattle (n = 1492). Expression quantitative trait loci (eQTL) analysis was conducted to identify functional effects of GWAS-identified variants. Twenty-four SNPs were associated (P < 5 × 10-5) with RFI, ADG or FI. The variant rs43555985 exhibited strongest association for RFI (P = 8.28E-06). An eQTL was identified between this variant and GFRA2 (P = 0.0038) where the allele negatively correlated with RFI was associated with increased GFRA2 expression in liver. GFRA2 influences basal metabolic rates, suggesting a mechanism by which genetic variation may contribute to RFI. This study identified SNPs that may be useful both for genomic selection of RFI and for understanding the biology of feed efficiency.
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Whitton L, Apostolova G, Rieder D, Dechant G, Rea S, Donohoe G, Morris DW. Genes regulated by SATB2 during neurodevelopment contribute to schizophrenia and educational attainment. PLoS Genet 2018; 14:e1007515. [PMID: 30040823 PMCID: PMC6097700 DOI: 10.1371/journal.pgen.1007515] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Revised: 08/17/2018] [Accepted: 06/26/2018] [Indexed: 12/20/2022] Open
Abstract
SATB2 is associated with schizophrenia and is an important transcription factor regulating neocortical organization and circuitry. Rare mutations in SATB2 cause a syndrome that includes developmental delay, and mouse studies identify an important role for SATB2 in learning and memory. Interacting partners BCL11B and GATAD2A are also schizophrenia risk genes indicating that other genes interacting with or are regulated by SATB2 are making a contribution to schizophrenia and cognition. We used data from Satb2 mouse models to generate three gene-sets that contain genes either functionally related to SATB2 or targeted by SATB2 at different stages of development. Each was tested for enrichment using the largest available genome-wide association studies (GWAS) datasets for schizophrenia and educational attainment (EA) and enrichment analysis was also performed for schizophrenia and other neurodevelopmental disorders using data from rare variant sequencing studies. These SATB2 gene-sets were enriched for genes containing common variants associated with schizophrenia and EA, and were enriched for genes containing rare variants reported in studies of schizophrenia, autism and intellectual disability. In the developing cortex, genes targeted by SATB2 based on ChIP-seq data, and functionally affected when SATB2 is not expressed based on differential expression analysis using RNA-seq data, show strong enrichment for genes associated with EA. For genes expressed in the hippocampus or at the synapse, those targeted by SATB2 are more strongly enriched for genes associated EA than gene-sets not targeted by SATB2. This study demonstrates that single gene findings from GWAS can provide important insights to pathobiological processes. In this case we find evidence that genes influenced by SATB2 and involved in synaptic transmission, axon guidance and formation of the corpus callosum are contributing to schizophrenia and cognition. Schizophrenia is a complex disorder caused by many genes. Using new gene discoveries to understand pathobiology is a foundation for development of new treatments. Current drugs for schizophrenia are only partially effective and do not treat cognitive deficits, which are key factors for explaining disability, leading to unemployment, homelessness and social isolation. Genome-wide association studies (GWAS) of schizophrenia have been effective at identifying individual SNPs and genes that contribute to risk but have struggled to immediately uncover the bigger picture of the underlying biology of the disorder. Here we take an individual gene identified in a schizophrenia GWAS called SATB2, which on its own is a very important regulator of brain development. We use functional genomics data from mouse studies to identify sets of others genes that are influenced by SATB2 during development. We show that these gene sets are enriched for common variants associated with schizophrenia and educational attainment (used as a proxy for cognition), and for rare variants that increase risk of various neurodevelopmental disorders. This study provides evidence that the molecular mechanisms that underpin schizophrenia and cognitive function include disruption of biological processes influenced by SATB2 as the brain is being organized and wired during development.
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Donohoe G, Holland J, Mothersill D, McCarthy-Jones S, Cosgrove D, Harold D, Richards A, Mantripragada K, Owen MJ, O'Donovan MC, Gill M, Corvin A, Morris DW. Genetically predicted complement component 4A expression: effects on memory function and middle temporal lobe activation. Psychol Med 2018; 48:1608-1615. [PMID: 29310738 DOI: 10.1017/s0033291717002987] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND The longstanding association between the major histocompatibility complex (MHC) locus and schizophrenia (SZ) risk has recently been accounted for, partially, by structural variation at the complement component 4 (C4) gene. This structural variation generates varying levels of C4 RNA expression, and genetic information from the MHC region can now be used to predict C4 RNA expression in the brain. Increased predicted C4A RNA expression is associated with the risk of SZ, and C4 is reported to influence synaptic pruning in animal models. METHODS Based on our previous studies associating MHC SZ risk variants with poorer memory performance, we tested whether increased predicted C4A RNA expression was associated with reduced memory function in a large (n = 1238) dataset of psychosis cases and healthy participants, and with altered task-dependent cortical activation in a subset of these samples. RESULTS We observed that increased predicted C4A RNA expression predicted poorer performance on measures of memory recall (p = 0.016, corrected). Furthermore, in healthy participants, we found that increased predicted C4A RNA expression was associated with a pattern of reduced cortical activity in middle temporal cortex during a measure of visual processing (p < 0.05, corrected). CONCLUSIONS These data suggest that the effects of C4 on cognition were observable at both a cortical and behavioural level, and may represent one mechanism by which illness risk is mediated. As such, deficits in learning and memory may represent a therapeutic target for new molecular developments aimed at altering C4's developmental role.
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Ni G, Moser G, Wray NR, Lee SH, Ripke S, Neale BM, Corvin A, Walters JT, Farh KH, Holmans PA, Lee P, Bulik-Sullivan B, Collier DA, Huang H, Pers TH, Agartz I, Agerbo E, Albus M, Alexander M, Amin F, Bacanu SA, Begemann M, Belliveau RA, Bene J, Bergen SE, Bevilacqua E, Bigdeli TB, Black DW, Bruggeman R, Buccola NG, Buckner RL, Byerley W, Cahn W, Cai G, Campion D, Cantor RM, Carr VJ, Carrera N, Catts SV, Chambert KD, Chan RC, Chen RY, Chen EY, Cheng W, Cheung EF, Chong SA, Cloninger CR, Cohen D, Cohen N, Cormican P, Craddock N, Crowley JJ, Curtis D, Davidson M, Davis KL, Degenhardt F, Del Favero J, Demontis D, Dikeos D, Dinan T, Djurovic S, Donohoe G, Drapeau E, Duan J, Dudbridge F, Durmishi N, Eichhammer P, Eriksson J, Escott-Price V, Essioux L, Fanous AH, Farrell MS, Frank J, Franke L, Freedman R, Freimer NB, Friedl M, Friedman JI, Fromer M, Genovese G, Georgieva L, Giegling I, Giusti-Rodríguez P, Godard S, Goldstein JI, Golimbet V, Gopal S, Gratten J, de Haan L, Hammer C, Hamshere ML, Hansen M, Hansen T, Haroutunian V, Hartmann AM, Henskens FA, Herms S, Hirschhorn JN, Hoffmann P, Hofman A, Hollegaard MV, Hougaard DM, Ikeda M, Joa I, Juliá A, Kahn RS, Kalaydjieva L, Karachanak-Yankova S, Karjalainen J, Kavanagh D, Keller MC, Kennedy JL, Khrunin A, Kim Y, Klovins J, Knowles JA, Konte B, Kucinskas V, Kucinskiene ZA, Kuzelova-Ptackova H, Kähler AK, Laurent C, Keong JLC, Legge SE, Lerer B, Li M, Li T, Liang KY, Lieberman J, Limborska S, Loughland CM, Lubinski J, Lönnqvist J, Macek M, Magnusson PK, Maher BS, Maier W, Mallet J, Marsal S, Mattheisen M, Mattingsda M, McCarley RW, McDonald C, McIntosh AM, Meier S, Meijer CJ, Melegh B, Melle I, Mesholam-Gately RI, Metspalu A, Michie PT, Milani L, Milanova V, Mokrab Y, Morris DW, Mors O, Murphy KC, Murray RM, Myin-Germeys I, Müller-Myhsok B, Nelis M, Nenadic I, Nertney DA, Nestadt G, Nicodemus KK, Nikitina-Zake L, Nisenbaum L, Nordin A, O’Callaghan E, O’Dushlaine C, O’Neill FA, Oh SY, Olinc A, Olsen L, Van Os J, Pantelis C, Papadimitriou GN, Papio S, Parkhomenko E, Pato MT, Paunio T, Pejovic-Milovancevic M, Perkins DO, Pietiläinenl O, Pimm J, Pocklington AJ, Powell J, Price A, Pulver AE, Purcell SM, Quested D, Rasmussen HB, Reichenberg A, Reimers MA, Richards AL, Roffman JL, Roussos P, Ruderfer DM, Salomaa V, Sanders AR, Schall U, Schubert CR, Schulze TG, Schwab SG, Scolnick EM, Scott RJ, Seidman LJ, Shi J, Sigurdsson E, Silagadze T, Silverman JM, Sim K, Slominsky P, Smoller JW, So HC, Spencer CC, Stah EA, Stefansson H, Steinberg S, Stogmann E, Straub RE, Strengman E, Strohmaier J, Stroup TS, Subramaniam M, Suvisaari J, Svrakic DM, Szatkiewicz JP, Söderman E, Thirumalai S, Toncheva D, Tosato S, Veijola J, Waddington J, Walsh D, Wang D, Wang Q, Webb BT, Weiser M, Wildenauer DB, Williams NM, Williams S, Witt SH, Wolen AR, Wong EH, Wormley BK, Xi HS, Zai CC, Zheng X, Zimprich F, Stefansson K, Visscher PM, Adolfsson R, Andreassen OA, Blackwood DH, Bramon E, Buxbaum JD, Børglum AD, Cichon S, Darvasi A, Domenici E, Ehrenreich H, Esko T, Gejman PV, Gill M, Gurling H, Hultman CM, Iwata N, Jablensky AV, Jönsson EG, Kendler KS, Kirov G, Knight J, Lencz T, Levinson DF, Li QS, Liu J, Malhotra AK, McCarrol SA, McQuillin A, Moran JL, Mortensen PB, Mowry BJ, Nöthen MM, Ophoff RA, Owen MJ, Palotie A, Pato CN, Petryshen TL, Posthuma D, Rietsche M, Riley BP, Rujescu D, Sham PC, Sklar P, St Clair D, Weinberger DR, Wendland JR, Werge T, Daly MJ, Sullivan PF, O’Donovan MC. Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood. Am J Hum Genet 2018; 102:1185-1194. [PMID: 29754766 PMCID: PMC5993419 DOI: 10.1016/j.ajhg.2018.03.021] [Citation(s) in RCA: 96] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Accepted: 03/20/2018] [Indexed: 10/16/2022] Open
Abstract
Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on ∼150,000 individuals give a higher accuracy than LDSC estimates based on ∼400,000 individuals (from combined meta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.
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