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Gibson J, Russ TC, Clarke TK, Howard DM, Hillary RF, Evans KL, Walker RM, Bermingham ML, Morris SW, Campbell A, Hayward C, Murray AD, Porteous DJ, Horvath S, Lu AT, McIntosh AM, Whalley HC, Marioni RE. A meta-analysis of genome-wide association studies of epigenetic age acceleration. PLoS Genet 2019; 15:e1008104. [PMID: 31738745 PMCID: PMC6886870 DOI: 10.1371/journal.pgen.1008104 10.1371/journal.pgen.1008104] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 12/02/2019] [Accepted: 08/16/2019] [Indexed: 12/20/2023] Open
Abstract
'Epigenetic age acceleration' is a valuable biomarker of ageing, predictive of morbidity and mortality, but for which the underlying biological mechanisms are not well established. Two commonly used measures, derived from DNA methylation, are Horvath-based (Horvath-EAA) and Hannum-based (Hannum-EAA) epigenetic age acceleration. We conducted genome-wide association studies of Horvath-EAA and Hannum-EAA in 13,493 unrelated individuals of European ancestry, to elucidate genetic determinants of differential epigenetic ageing. We identified ten independent SNPs associated with Horvath-EAA, five of which are novel. We also report 21 Horvath-EAA-associated genes including several involved in metabolism (NHLRC, TPMT) and immune system pathways (TRIM59, EDARADD). GWAS of Hannum-EAA identified one associated variant (rs1005277), and implicated 12 genes including several involved in innate immune system pathways (UBE2D3, MANBA, TRIM46), with metabolic functions (UBE2D3, MANBA), or linked to lifespan regulation (CISD2). Both measures had nominal inverse genetic correlations with father's age at death, a rough proxy for lifespan. Nominally significant genetic correlations between Hannum-EAA and lifestyle factors including smoking behaviours and education support the hypothesis that Hannum-based epigenetic ageing is sensitive to variations in environment, whereas Horvath-EAA is a more stable cellular ageing process. We identified novel SNPs and genes associated with epigenetic age acceleration, and highlighted differences in the genetic architecture of Horvath-based and Hannum-based epigenetic ageing measures. Understanding the biological mechanisms underlying individual differences in the rate of epigenetic ageing could help explain different trajectories of age-related decline.
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Gibson J, Russ TC, Clarke TK, Howard DM, Hillary RF, Evans KL, Walker RM, Bermingham ML, Morris SW, Campbell A, Hayward C, Murray AD, Porteous DJ, Horvath S, Lu AT, McIntosh AM, Whalley HC, Marioni RE. A meta-analysis of genome-wide association studies of epigenetic age acceleration. PLoS Genet 2019; 15:e1008104. [PMID: 31738745 PMCID: PMC6886870 DOI: 10.1371/journal.pgen.1008104] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 12/02/2019] [Accepted: 08/16/2019] [Indexed: 12/22/2022] Open
Abstract
'Epigenetic age acceleration' is a valuable biomarker of ageing, predictive of morbidity and mortality, but for which the underlying biological mechanisms are not well established. Two commonly used measures, derived from DNA methylation, are Horvath-based (Horvath-EAA) and Hannum-based (Hannum-EAA) epigenetic age acceleration. We conducted genome-wide association studies of Horvath-EAA and Hannum-EAA in 13,493 unrelated individuals of European ancestry, to elucidate genetic determinants of differential epigenetic ageing. We identified ten independent SNPs associated with Horvath-EAA, five of which are novel. We also report 21 Horvath-EAA-associated genes including several involved in metabolism (NHLRC, TPMT) and immune system pathways (TRIM59, EDARADD). GWAS of Hannum-EAA identified one associated variant (rs1005277), and implicated 12 genes including several involved in innate immune system pathways (UBE2D3, MANBA, TRIM46), with metabolic functions (UBE2D3, MANBA), or linked to lifespan regulation (CISD2). Both measures had nominal inverse genetic correlations with father's age at death, a rough proxy for lifespan. Nominally significant genetic correlations between Hannum-EAA and lifestyle factors including smoking behaviours and education support the hypothesis that Hannum-based epigenetic ageing is sensitive to variations in environment, whereas Horvath-EAA is a more stable cellular ageing process. We identified novel SNPs and genes associated with epigenetic age acceleration, and highlighted differences in the genetic architecture of Horvath-based and Hannum-based epigenetic ageing measures. Understanding the biological mechanisms underlying individual differences in the rate of epigenetic ageing could help explain different trajectories of age-related decline.
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Ritchie SJ, Cox SR, Shen X, Lombardo MV, Reus LM, Alloza C, Harris MA, Alderson HL, Hunter S, Neilson E, Liewald DCM, Auyeung B, Whalley HC, Lawrie SM, Gale CR, Bastin ME, McIntosh AM, Deary IJ. Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants. Cereb Cortex 2019; 28:2959-2975. [PMID: 29771288 PMCID: PMC6041980 DOI: 10.1093/cercor/bhy109] [Citation(s) in RCA: 401] [Impact Index Per Article: 80.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 04/20/2018] [Indexed: 02/07/2023] Open
Abstract
Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric disorders and in some psychological traits that brain differences might help to explain. We report the largest single-sample study of structural and functional sex differences in the human brain (2750 female, 2466 male participants; mean age 61.7 years, range 44-77 years). Males had higher raw volumes, raw surface areas, and white matter fractional anisotropy; females had higher raw cortical thickness and higher white matter tract complexity. There was considerable distributional overlap between the sexes. Subregional differences were not fully attributable to differences in total volume, total surface area, mean cortical thickness, or height. There was generally greater male variance across the raw structural measures. Functional connectome organization showed stronger connectivity for males in unimodal sensorimotor cortices, and stronger connectivity for females in the default mode network. This large-scale study provides a foundation for attempts to understand the causes and consequences of sex differences in adult brain structure and function.
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Neilson E, Shen X, Cox SR, Clarke TK, Wigmore EM, Gibson J, Howard DM, Adams MJ, Harris MA, Davies G, Deary IJ, Whalley HC, McIntosh AM, Lawrie SM. Impact of Polygenic Risk for Schizophrenia on Cortical Structure in UK Biobank. Biol Psychiatry 2019; 86:536-544. [PMID: 31171358 DOI: 10.1016/j.biopsych.2019.04.013] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 04/05/2019] [Accepted: 04/05/2019] [Indexed: 11/28/2022]
Abstract
BACKGROUND Schizophrenia is a neurodevelopmental disorder with many genetic variants of individually small effect contributing to phenotypic variation. Lower cortical thickness (CT), surface area, and cortical volume have been demonstrated in people with schizophrenia. Furthermore, a range of obstetric complications (e.g., lower birth weight) are consistently associated with an increased risk for schizophrenia. We investigated whether a high polygenic risk score for schizophrenia (PGRS-SCZ) is associated with CT, surface area, and cortical volume in UK Biobank, a population-based sample, and tested for interactions with birth weight. METHODS Data were available for 2864 participants (nmale/nfemale = 1382/1482; mean age = 62.35 years, SD = 7.40). Linear mixed models were used to test for associations among PGRS-SCZ and cortical volume, surface area, and CT and between PGRS-SCZ and birth weight. Interaction effects of these variables on cortical structure were also tested. RESULTS We found a significant negative association between PGRS-SCZ and global CT; a higher PGRS-SCZ was associated with lower CT across the whole brain. We also report a significant negative association between PGRS-SCZ and insular lobe CT. PGRS-SCZ was not associated with birth weight and no PGRS-SCZ × birth weight interactions were found. CONCLUSIONS These results suggest that individual differences in CT are partly influenced by genetic variants and are most likely not due to factors downstream of disease onset. This approach may help to elucidate the genetic pathophysiology of schizophrenia. Further investigation in case-control and high-risk samples could help identify any localized effects of PGRS-SCZ, and other potential schizophrenia risk factors, on CT as symptoms develop.
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de Zwarte SMC, Brouwer RM, Agartz I, Alda M, Aleman A, Alpert KI, Bearden CE, Bertolino A, Bois C, Bonvino A, Bramon E, Buimer EEL, Cahn W, Cannon DM, Cannon TD, Caseras X, Castro-Fornieles J, Chen Q, Chung Y, De la Serna E, Di Giorgio A, Doucet GE, Eker MC, Erk S, Fears SC, Foley SF, Frangou S, Frankland A, Fullerton JM, Glahn DC, Goghari VM, Goldman AL, Gonul AS, Gruber O, de Haan L, Hajek T, Hawkins EL, Heinz A, Hillegers MHJ, Hulshoff Pol HE, Hultman CM, Ingvar M, Johansson V, Jönsson EG, Kane F, Kempton MJ, Koenis MMG, Kopecek M, Krabbendam L, Krämer B, Lawrie SM, Lenroot RK, Marcelis M, Marsman JBC, Mattay VS, McDonald C, Meyer-Lindenberg A, Michielse S, Mitchell PB, Moreno D, Murray RM, Mwangi B, Najt P, Neilson E, Newport J, van Os J, Overs B, Ozerdem A, Picchioni MM, Richter A, Roberts G, Aydogan AS, Schofield PR, Simsek F, Soares JC, Sugranyes G, Toulopoulou T, Tronchin G, Walter H, Wang L, Weinberger DR, Whalley HC, Yalin N, Andreassen OA, Ching CRK, van Erp TGM, Turner JA, Jahanshad N, Thompson PM, Kahn RS, van Haren NEM. The Association Between Familial Risk and Brain Abnormalities Is Disease Specific: An ENIGMA-Relatives Study of Schizophrenia and Bipolar Disorder. Biol Psychiatry 2019; 86:545-556. [PMID: 31443932 PMCID: PMC7068800 DOI: 10.1016/j.biopsych.2019.03.985] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 03/19/2019] [Accepted: 03/24/2019] [Indexed: 11/30/2022]
Abstract
BACKGROUND Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects. METHODS We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects. RESULTS FDRs-BD had significantly larger ICV (d = +0.16, q < .05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = -0.12, q < .05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < -0.09, q < .05 corrected); and third ventricle was larger (d = +0.15, q < .05 corrected). The findings were not explained by psychopathology in the relatives or control subjects. CONCLUSIONS Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct.
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van den Heuvel MP, Scholtens LH, van der Burgh HK, Agosta F, Alloza C, Arango C, Auyeung B, Baron-Cohen S, Basaia S, Benders MJNL, Beyer F, Booij L, Braun KPJ, Filho GB, Cahn W, Cannon DM, Chaim-Avancini TM, Chan SSM, Chen EYH, Crespo-Facorro B, Crone EA, Dannlowski U, de Zwarte SMC, Dietsche B, Donohoe G, Plessis SD, Durston S, Díaz-Caneja CM, Díaz-Zuluaga AM, Emsley R, Filippi M, Frodl T, Gorges M, Graff B, Grotegerd D, Gąsecki D, Hall JM, Holleran L, Holt R, Hopman HJ, Jansen A, Janssen J, Jodzio K, Jäncke L, Kaleda VG, Kassubek J, Masouleh SK, Kircher T, Koevoets MGJC, Kostic VS, Krug A, Lawrie SM, Lebedeva IS, Lee EHM, Lett TA, Lewis SJG, Liem F, Lombardo MV, Lopez-Jaramillo C, Margulies DS, Markett S, Marques P, Martínez-Zalacaín I, McDonald C, McIntosh AM, McPhilemy G, Meinert SL, Menchón JM, Montag C, Moreira PS, Morgado P, Mothersill DO, Mérillat S, Müller HP, Nabulsi L, Najt P, Narkiewicz K, Naumczyk P, Oranje B, Ortiz-Garcia de la Foz V, Peper JS, Pineda JA, Rasser PE, Redlich R, Repple J, Reuter M, Rosa PGP, Ruigrok ANV, Sabisz A, Schall U, Seedat S, Serpa MH, Skouras S, Soriano-Mas C, Sousa N, Szurowska E, Tomyshev AS, Tordesillas-Gutierrez D, Valk SL, van den Berg LH, van Erp TGM, van Haren NEM, van Leeuwen JMC, Villringer A, Vinkers CH, Vollmar C, Waller L, Walter H, Whalley HC, Witkowska M, Witte AV, Zanetti MV, Zhang R, de Lange SC. 10Kin1day: A Bottom-Up Neuroimaging Initiative. Front Neurol 2019; 10:425. [PMID: 31133958 PMCID: PMC6524614 DOI: 10.3389/fneur.2019.00425] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 04/08/2019] [Indexed: 01/11/2023] Open
Abstract
We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.
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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, Clark VP, Mueller BA, de Zwarte SMC, Ophoff RA, van Haren NEM, Andreassen OA, Gurholt TP, Gruber O, Kraemer B, Richter A, Calhoun VD, Crespo-Facorro B, Roiz-Santiañez R, Tordesillas-Gutiérrez D, Loughland C, Catts S, Fullerton JM, Green MJ, Henskens F, Jablensky A, Mowry BJ, Pantelis C, Quidé Y, Schall U, Scott RJ, Cairns MJ, Seal M, Tooney PA, Rasser PE, Cooper G, Weickert CS, Weickert TW, Hong E, Kochunov P, Gur RE, Gur RC, Ford JM, Macciardi F, Mathalon DH, Potkin SG, Preda A, Fan F, Ehrlich S, King MD, De Haan L, Veltman DJ, Assogna F, Banaj N, de Rossi P, Iorio M, Piras F, Spalletta G, Pomarol-Clotet E, Kelly S, Ciufolini S, Radua J, Murray R, Marques TR, Simmons A, Borgwardt S, Schönborn-Harrisberger F, Riecher-Rössler A, Smieskova R, Alpert KI, Bertolino A, Bonvino A, Di Giorgio A, Neilson E, Mayer AR, Yun JY, Cannon DM, Lebedeva I, Tomyshev AS, Akhadov T, Kaleda V, Fatouros-Bergman H, Flyckt L, Rosa PGP, Serpa MH, Zanetti MV, Hoschl C, Skoch A, Spaniel F, Tomecek D, McIntosh AM, Whalley HC, Knöchel C, Oertel-Knöchel V, Howells FM, Stein DJ, Temmingh HS, Uhlmann A, Lopez-Jaramillo C, Dima D, Faskowitz JI, Gutman BA, Jahanshad N, Thompson PM, Turner JA. Reply to: New Meta- and Mega-analyses of Magnetic Resonance Imaging Findings in Schizophrenia: Do They Really Increase Our Knowledge About the Nature of the Disease Process? Biol Psychiatry 2019; 85:e35-e39. [PMID: 30470561 PMCID: PMC7041557 DOI: 10.1016/j.biopsych.2018.10.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Accepted: 10/05/2018] [Indexed: 10/27/2022]
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Brown SSG, Whalley HC, Kind PC, Stanfield AC. Decreased functional brain response to emotional arousal and increased psychiatric symptomology in FMR1 premutation carriers. Psychiatry Res Neuroimaging 2019; 285:9-17. [PMID: 30711710 DOI: 10.1016/j.pscychresns.2019.01.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 12/23/2018] [Accepted: 01/28/2019] [Indexed: 12/30/2022]
Abstract
The FMR1 premutation is an expansion of the CGG repeat island in the FMR1 gene to between 55 and 200 repeats. Evidence suggests that as well as conferring risk for neurodegeneration, the premutation is also associated with increased risk for autistic traits and psychiatric symptoms. An emotional processing fMRI task was used to examine the response to a change in emotional arousal in 17 male carriers and 17 matched controls. A psychiatric symptom checklist (SCL-90-R), autism spectrum and empathy quotients (AQ and EQ), and the Ekman Faces Test were used to investigate clinical symptoms and emotional processing. Carriers exhibited significantly lower activation compared to controls at the bilateral superior parietal lobe, bilateral Brodmann Area (BA) 17 (V1), right intraparietal area and right BA18 (V2) when comparing high and low arousal conditions. Group by age analyses were not significant. Assessments revealed that carriers displayed significantly worse symptoms of psychiatric symptoms and higher levels of autistic traits, as well as impaired facial emotion recognition. No measurements revealed an association with age. Here, we show significantly altered emotional processing in carriers which display stability over age, suggesting that, unlike degenerative aspects, emotional symptoms may be consistent over the lifespan in carriers.
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Bermingham ML, Walker RM, Marioni RE, Morris SW, Rawlik K, Zeng Y, Campbell A, Redmond P, Whalley HC, Adams MJ, Hayward C, Deary IJ, Porteous DJ, McIntosh AM, Evans KL. Identification of novel differentially methylated sites with potential as clinical predictors of impaired respiratory function and COPD. EBioMedicine 2019; 43:576-586. [PMID: 30935889 PMCID: PMC6557748 DOI: 10.1016/j.ebiom.2019.03.072] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Revised: 03/25/2019] [Accepted: 03/25/2019] [Indexed: 12/22/2022] Open
Abstract
Background The causes of poor respiratory function and COPD are incompletely understood, but it is clear that genes and the environment play a role. As DNA methylation is under both genetic and environmental control, we hypothesised that investigation of differential methylation associated with these phenotypes would permit mechanistic insights, and improve prediction of COPD. We investigated genome-wide differential DNA methylation patterns using the recently released 850 K Illumina EPIC array. This is the largest single population, whole-genome epigenetic study to date. Methods Epigenome-wide association studies (EWASs) of respiratory function and COPD were performed in peripheral blood samples from the Generation Scotland: Scottish Family Health Study (GS:SFHS) cohort (n = 3781; 274 COPD cases and 2919 controls). In independent COPD incidence data (n = 149), significantly differentially methylated sites (DMSs; p < 3.6 × 10−8) were evaluated for their added predictive power when added to a model including clinical variables, age, sex, height and smoking history using receiver operating characteristic analysis. The Lothian Birth Cohort 1936 (LBC1936) was used to replicate association (n = 895) and prediction (n = 178) results. Findings We identified 28 respiratory function and/or COPD associated DMSs, which mapped to genes involved in alternative splicing, JAK-STAT signalling, and axon guidance. In prediction analyses, we observed significant improvement in discrimination between COPD cases and controls (p < .05) in independent GS:SFHS (p = .016) and LBC1936 (p = .010) datasets by adding DMSs to a clinical model. Interpretation Identification of novel DMSs has provided insight into the molecular mechanisms regulating respiratory function and aided prediction of COPD risk. Further studies are needed to assess the causality and clinical utility of identified associations. Fund Wellcome Trust Strategic Award 10436/Z/14/Z.
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Howard DM, Adams MJ, Clarke TK, Hafferty JD, Gibson J, Shirali M, Coleman JRI, Hagenaars SP, Ward J, Wigmore EM, Alloza C, Shen X, Barbu MC, Xu EY, Whalley HC, Marioni RE, Porteous DJ, Davies G, Deary IJ, Hemani G, Berger K, Teismann H, Rawal R, Arolt V, Baune BT, Dannlowski U, Domschke K, Tian C, Hinds DA, Trzaskowski M, Byrne EM, Ripke S, Smith DJ, Sullivan PF, Wray NR, Breen G, Lewis CM, McIntosh AM. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci 2019; 22:343-352. [PMID: 30718901 PMCID: PMC6522363 DOI: 10.1038/s41593-018-0326-7] [Citation(s) in RCA: 1214] [Impact Index Per Article: 242.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Accepted: 12/11/2018] [Indexed: 12/13/2022]
Abstract
Major depression is a debilitating psychiatric illness that is typically associated with low mood and anhedonia. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximize sample size, we meta-analyzed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 genesets associated with depression, including both genes and gene pathways associated with synaptic structure and neurotransmission. An enrichment analysis provided further evidence of the importance of prefrontal brain regions. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant after multiple testing correction. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding etiology and developing new treatment approaches.
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Lawrie SM, Fletcher-Watson S, Whalley HC, McIntosh AM. Predicting major mental illness: ethical and practical considerations. BJPsych Open 2019; 5:e30. [PMID: 31068241 PMCID: PMC6469234 DOI: 10.1192/bjo.2019.11] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Revised: 01/30/2019] [Accepted: 01/31/2019] [Indexed: 12/15/2022] Open
Abstract
SummaryAn increasing body of genetic and imaging research shows that it is becoming possible to forecast the onset of major psychiatric disorders such as depression and schizophrenia before people become ill with ever improving accuracy. Practical issues such as the optimal combination of clinical and biological variables are being addressed, but the application of predictive algorithms to individuals or in routine clinical settings have yet to be tested. The development of predictive methods in mental health comes with substantial ethical questions, including whether people wish to know their level of risk, as well as individual and societal attitudes to the potential adverse effects of data sharing, early diagnosis and treatment, which so far have been largely ignored. Preliminary data suggests that at least some people think predictive research is valuable and would take part in such studies, and some would welcome knowing the results. Future initiatives should systematically assess opinions and attitudes in conjunction with scientific and technical advances.Declaration of interestIn the past 3 years, S.M.L. has received personal fees from Otsuaka, Sunovion and Janssen, and research grant support from Janssen and Lundbeck. A.M.M. has received research support from the Sackler Trust, Eli Lilly and Janssen. S.M.L. is part of the PSYSCAN consortium.
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Johnstone M, Vasistha NA, Barbu MC, Dando O, Burr K, Christopher E, Glen S, Robert C, Fetit R, Macleod KG, Livesey MR, Clair DS, Blackwood DHR, Millar K, Carragher NO, Hardingham GE, Wyllie DJA, Johnstone EC, Whalley HC, McIntosh AM, Lawrie SM, Chandran S. Reversal of proliferation deficits caused by chromosome 16p13.11 microduplication through targeting NFκB signaling: an integrated study of patient-derived neuronal precursor cells, cerebral organoids and in vivo brain imaging. Mol Psychiatry 2019; 24:294-311. [PMID: 30401811 PMCID: PMC6344377 DOI: 10.1038/s41380-018-0292-1] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Revised: 09/13/2018] [Accepted: 10/08/2018] [Indexed: 01/22/2023]
Abstract
The molecular basis of how chromosome 16p13.11 microduplication leads to major psychiatric disorders is unknown. Here we have undertaken brain imaging of patients carrying microduplications in chromosome 16p13.11 and unaffected family controls, in parallel with iPS cell-derived cerebral organoid studies of the same patients. Patient MRI revealed reduced cortical volume, and corresponding iPSC studies showed neural precursor cell (NPC) proliferation abnormalities and reduced organoid size, with the NPCs therein displaying altered planes of cell division. Transcriptomic analyses of NPCs uncovered a deficit in the NFκB p65 pathway, confirmed by proteomics. Moreover, both pharmacological and genetic correction of this deficit rescued the proliferation abnormality. Thus, chromosome 16p13.11 microduplication disturbs the normal programme of NPC proliferation to reduce cortical thickness due to a correctable deficit in the NFκB signalling pathway. This is the first study demonstrating a biologically relevant, potentially ameliorable, signalling pathway underlying chromosome 16p13.11 microduplication syndrome in patient-derived neuronal precursor cells.
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Smith EM, Reynolds S, Orchard F, Whalley HC, Chan SW. Cognitive biases predict symptoms of depression, anxiety and wellbeing above and beyond neuroticism in adolescence. J Affect Disord 2018; 241:446-453. [PMID: 30145516 DOI: 10.1016/j.jad.2018.08.051] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Revised: 07/23/2018] [Accepted: 08/12/2018] [Indexed: 01/23/2023]
Abstract
BACKGROUND Adolescence represents a period of vulnerability to affective disorders. Neuroticism is considered a heritable risk factor for depression, but is not directly amenable to intervention. Therefore, it is important to identify the contributions of modifiable risk factors. Negative cognitive biases are implicated in the onset and maintenance of affective disorders in adults, and may represent modifiable risk factors in adolescence. AIM(S) This study sought to assess to what extent cognitive biases are able to predict depression, anxiety and wellbeing beyond that of neuroticism in adolescents. METHODS Adolescents (N = 99), recruited from Scottish secondary schools (54.5% female; mean age = 14.7), ensured a sample representing the breadth of the mental health spectrum. In line with prevalence estimates, 18% of this sample demonstrated clinical levels of depression symptoms. Cognitive biases of autobiographical memory, self-referential memory, ambiguous scenarios interpretation, facial expression recognition, rumination and dysfunctional attitudes were assessed. Depression, anxiety, and wellbeing were indexed using the Mood and Feelings Questionnaire, Spence Children's Anxiety Scale and the BBC Subjective Wellbeing Scale. RESULTS Regression analyses demonstrated neuroticism to significantly predict depression, anxiety and wellbeing. The addition of cognitive biases resulted in a significant increase of explained variance with final models explaining just over 50% of variances of depression, anxiety and wellbeing. CONCLUSION These findings demonstrate that cognitive biases explain mental health symptoms over and above that of neuroticism. Depressive symptomology was particularly related to self-referential memory bias, while anxiety was predicted by interpretive bias. The key clinical implication is that targeting specific biases based on diagnostic features may be of particular benefit in alleviating distress and promoting wellbeing.
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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: 493] [Impact Index Per Article: 82.2] [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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Romaniuk L, Sandu AL, Waiter GD, McNeil CJ, Xueyi S, Harris MA, Macfarlane JA, Lawrie SM, Deary IJ, Murray AD, Delgado MR, Steele JD, McIntosh AM, Whalley HC. The Neurobiology of Personal Control During Reward Learning and Its Relationship to Mood. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 4:190-199. [PMID: 30470583 PMCID: PMC6374985 DOI: 10.1016/j.bpsc.2018.09.015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Revised: 09/05/2018] [Accepted: 09/18/2018] [Indexed: 01/08/2023]
Abstract
BACKGROUND The majority of reward learning neuroimaging studies have not focused on the motivational aspects of behavior, such as the inherent value placed on choice itself. The experience and affective value of personal control may have particular relevance for psychiatric disorders, including depression. METHODS We adapted a functional magnetic resonance imaging reward task that probed the value placed on exerting control over one's decisions, termed choice value, in 122 healthy participants. We examined activation associated with choice value; personally chosen versus passively received rewards; and reinforcement learning metrics, such as prediction error. Relationships were tested between measures of motivational orientation (categorized as autonomy, control, and impersonal) and subclinical depressive symptoms. RESULTS Anticipating personal choice activated left insula, cingulate, right inferior frontal cortex, and ventral striatum (pfamilywise error-corrected < .05). Ventral striatal activations to choice were diminished in participants with subclinical depressive symptoms. Personally chosen rewards were associated with greater activation of the insula and inferior frontal gyrus, cingulate cortex, hippocampus, thalamus, and substantia nigra compared with rewards that were passively received. In participants who felt they had little control over their own behavior (impersonal orientation), prediction error signals in nucleus accumbens were stronger during passive trials. CONCLUSIONS Previous findings regarding personal choice have been verified and advanced through the use of both reinforcement learning models and correlations with psychopathology. Personal choice has an impact on the extended reward network, potentially allowing these clinically important areas to be addressed in ways more relevant to personality styles, self-esteem, and symptoms such as motivational anhedonia.
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McCartney DL, Hillary RF, Stevenson AJ, Ritchie SJ, Walker RM, Zhang Q, Morris SW, Bermingham ML, Campbell A, Murray AD, Whalley HC, Gale CR, Porteous DJ, Haley CS, McRae AF, Wray NR, Visscher PM, McIntosh AM, Evans KL, Deary IJ, Marioni RE. Epigenetic prediction of complex traits and death. Genome Biol 2018; 19:136. [PMID: 30257690 PMCID: PMC6158884 DOI: 10.1186/s13059-018-1514-1] [Citation(s) in RCA: 99] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Accepted: 08/22/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Genome-wide DNA methylation (DNAm) profiling has allowed for the development of molecular predictors for a multitude of traits and diseases. Such predictors may be more accurate than the self-reported phenotypes and could have clinical applications. RESULTS Here, penalized regression models are used to develop DNAm predictors for ten modifiable health and lifestyle factors in a cohort of 5087 individuals. Using an independent test cohort comprising 895 individuals, the proportion of phenotypic variance explained in each trait is examined for DNAm-based and genetic predictors. Receiver operator characteristic curves are generated to investigate the predictive performance of DNAm-based predictors, using dichotomized phenotypes. The relationship between DNAm scores and all-cause mortality (n = 212 events) is assessed via Cox proportional hazards models. DNAm predictors for smoking, alcohol, education, and waist-to-hip ratio are shown to predict mortality in multivariate models. The predictors show moderate discrimination of obesity, alcohol consumption, and HDL cholesterol. There is excellent discrimination of current smoking status, poorer discrimination of college-educated individuals and those with high total cholesterol, LDL with remnant cholesterol, and total:HDL cholesterol ratios. CONCLUSIONS DNAm predictors correlate with lifestyle factors that are associated with health and mortality. They may supplement DNAm-based predictors of age to identify the lifestyle profiles of individuals and predict disease risk.
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Alloza C, Cox SR, Blesa Cábez M, Redmond P, Whalley HC, Ritchie SJ, Muñoz Maniega S, Valdés Hernández MDC, Tucker-Drob EM, Lawrie SM, Wardlaw JM, Deary IJ, Bastin ME. Polygenic risk score for schizophrenia and structural brain connectivity in older age: A longitudinal connectome and tractography study. Neuroimage 2018; 183:884-896. [PMID: 30179718 PMCID: PMC6215331 DOI: 10.1016/j.neuroimage.2018.08.075] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 08/28/2018] [Accepted: 08/31/2018] [Indexed: 12/14/2022] Open
Abstract
Higher polygenic risk score for schizophrenia (szPGRS) has been associated with lower cognitive function and might be a predictor of decline in brain structure in apparently healthy populations. Age-related declines in structural brain connectivity-measured using white matter diffusion MRI -are evident from cross-sectional data. Yet, it remains unclear how graph theoretical metrics of the structural connectome change over time, and whether szPGRS is associated with differences in ageing-related changes in human brain connectivity. Here, we studied a large, relatively healthy, same-year-of-birth, older age cohort over a period of 3 years (age ∼ 73 years, N = 731; age ∼76 years, N = 488). From their brain scans we derived tract-averaged fractional anisotropy (FA) and mean diffusivity (MD), and network topology properties. We investigated the cross-sectional and longitudinal associations between these structural brain variables and szPGRS. Higher szPGRS showed significant associations with longitudinal increases in MD in the splenium (β = 0.132, pFDR = 0.040), arcuate (β = 0.291, pFDR = 0.040), anterior thalamic radiations (β = 0.215, pFDR = 0.040) and cingulum (β = 0.165, pFDR = 0.040). Significant declines over time were observed in graph theory metrics for FA-weighted networks, such as mean edge weight (β = -0.039, pFDR = 0.048) and strength (β = -0.027, pFDR = 0.048). No significant associations were found between szPGRS and graph theory metrics. These results are consistent with the hypothesis that szPGRS confers risk for ageing-related degradation of some aspects of structural connectivity.
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Ganzola R, McIntosh AM, Nickson T, Sprooten E, Bastin ME, Giles S, Macdonald A, Sussmann J, Duchesne S, Whalley HC. Diffusion tensor imaging correlates of early markers of depression in youth at high-familial risk for bipolar disorder. J Child Psychol Psychiatry 2018; 59:917-927. [PMID: 29488219 DOI: 10.1111/jcpp.12879] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/15/2018] [Indexed: 01/07/2023]
Abstract
BACKGROUND Mood disorders are familial psychiatric diseases, in which patients show reduced white matter (WM) integrity. We sought to determine whether WM integrity was affected in young offspring at high-familial risk of mood disorder before they go on to develop major depressive disorder (MDD). METHODS The Bipolar Family study is a prospective longitudinal study examining young individuals (age 16-25 years) at familial risk of mood disorder on three occasions 2 years apart. This study used baseline imaging data, categorizing groups according to clinical outcome at follow-up. Diffusion tensor MRI data were acquired for 61 controls and 106 high-risk individuals, the latter divided into 78 high-risk subjects who remained well throughout the study ('high-risk well') and 28 individuals who subsequently developed MDD ('high-risk MDD'). Voxel-wise between-group comparison of fractional anisotropy (FA) based on diagnostic status was performed using tract-based spatial statistics (TBSS). RESULTS Compared to controls, both high-risk groups showed widespread decreases in FA (pcorr < .05) at baseline. Although FA in the high-risk MDD group negatively correlated with subthreshold depressive symptoms at the time of scanning (pcorr < .05), there were no statistically significant differences at p-corrected levels between the two high-risk groups. CONCLUSIONS These results suggest that decreased FA is related to the presence of familial risk for mood disorder along with subdiagnostic symptoms at the time of scanning rather than predictive of subsequent diagnosis. Due to the difficulties performing such longitudinal prospective studies, we note, however, that this latter analysis may be underpowered due to sample size within the high-risk MDD group. Further clinical follow-up may clarify these findings.
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Barbu MC, Zeng Y, Shen X, Cox SR, Clarke TK, Gibson J, Adams MJ, Johnstone M, Haley CS, Lawrie SM, Deary IJ, McIntosh AM, Whalley HC. Association of Whole-Genome and NETRIN1 Signaling Pathway-Derived Polygenic Risk Scores for Major Depressive Disorder and White Matter Microstructure in the UK Biobank. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 4:91-100. [PMID: 30197049 PMCID: PMC6374980 DOI: 10.1016/j.bpsc.2018.07.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 07/12/2018] [Accepted: 07/12/2018] [Indexed: 11/10/2022]
Abstract
Background Major depressive disorder is a clinically heterogeneous psychiatric disorder with a polygenic architecture. Genome-wide association studies have identified a number of risk-associated variants across the genome and have reported growing evidence of NETRIN1 pathway involvement. Stratifying disease risk by genetic variation within the NETRIN1 pathway may provide important routes for identification of disease mechanisms by focusing on a specific process, excluding heterogeneous risk-associated variation in other pathways. Here, we sought to investigate whether major depressive disorder polygenic risk scores derived from the NETRIN1 signaling pathway (NETRIN1-PRSs) and the whole genome, excluding NETRIN1 pathway genes (genomic-PRSs), were associated with white matter microstructure. Methods We used two diffusion tensor imaging measures, fractional anisotropy (FA) and mean diffusivity (MD), in the most up-to-date UK Biobank neuroimaging data release (FA: n = 6401; MD: n = 6390). Results We found significantly lower FA in the superior longitudinal fasciculus (β = −.035, pcorrected = .029) and significantly higher MD in a global measure of thalamic radiations (β = .029, pcorrected = .021), as well as higher MD in the superior (β = .034, pcorrected = .039) and inferior (β = .029, pcorrected = .043) longitudinal fasciculus and in the anterior (β = .025, pcorrected = .046) and superior (β = .027, pcorrected = .043) thalamic radiation associated with NETRIN1-PRS. Genomic-PRS was also associated with lower FA and higher MD in several tracts. Conclusions Our findings indicate that variation in the NETRIN1 signaling pathway may confer risk for major depressive disorder through effects on a number of white matter tracts.
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Shen X, Cox SR, Adams MJ, Howard DM, Lawrie SM, Ritchie SJ, Bastin ME, Deary IJ, McIntosh AM, Whalley HC. Resting-State Connectivity and Its Association With Cognitive Performance, Educational Attainment, and Household Income in the UK Biobank. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 3:878-886. [PMID: 30093342 PMCID: PMC6289224 DOI: 10.1016/j.bpsc.2018.06.007] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Revised: 06/18/2018] [Accepted: 06/18/2018] [Indexed: 01/01/2023]
Abstract
Background Cognitive ability is an important predictor of lifelong physical and mental well-being, and impairments are associated with many psychiatric disorders. Higher cognitive ability is also associated with greater educational attainment and increased household income. Understanding neural mechanisms underlying cognitive ability is of crucial importance for determining the nature of these associations. In the current study, we examined the spontaneous activity of the brain at rest to investigate its relationships with not only cognitive ability but also educational attainment and household income. Methods We used a large sample of resting-state neuroimaging data from the UK Biobank (n = 3950). Results First, analysis at the whole-brain level showed that connections involving the default mode network (DMN), frontoparietal network (FPN), and cingulo-opercular network (CON) were significantly positively associated with levels of cognitive performance assessed by a verbal-numerical reasoning test (standardized β cingulo-opercular values ranged from 0.054 to 0.097, pcorrected < .038). Connections associated with higher levels of cognitive performance were also significantly positively associated with educational attainment (r = .48, n = 4160) and household income (r = .38, n = 3793). Furthermore, analysis on the coupling of functional networks showed that better cognitive performance was associated with more positive DMN–CON connections, decreased cross-hemisphere connections between the homotopic network in the CON and FPN, and stronger CON–FPN connections (absolute βs ranged from 0.034 to 0.063, pcorrected < .045). Conclusions The current study found that variation in brain resting-state functional connectivity was associated with individual differences in cognitive ability, largely involving the DMN and lateral prefrontal network. In addition, we provide evidence of shared neural associations of cognitive ability, educational attainment, and household income.
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Neilson E, Bois C, Clarke TK, Hall L, Johnstone EC, Owens DGC, Whalley HC, McIntosh AM, Lawrie SM. Polygenic risk for schizophrenia, transition and cortical gyrification: a high-risk study. Psychol Med 2018; 48:1532-1539. [PMID: 29065934 DOI: 10.1017/s0033291717003087] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Schizophrenia is a highly heritable disorder, linked to several structural abnormalities of the brain. More specifically, previous findings have suggested that increased gyrification in frontal and temporal regions are implicated in the pathogenesis of schizophrenia. METHODS The current study included participants at high familial risk of schizophrenia who remained well (n = 31), who developed sub-diagnostic symptoms (n = 28) and who developed schizophrenia (n = 9) as well as healthy controls (HC) (n = 16). We first tested whether individuals at high familial risk of schizophrenia carried an increased burden of trait-associated alleles using polygenic risk score analysis. We then assessed the extent to which polygenic risk was associated with gyral folding in the frontal and temporal lobes. RESULTS We found that individuals at high familial risk of schizophrenia who developed schizophrenia carried a significantly greater burden of risk-conferring variants for the disorder compared to those at high risk (HR) who developed sub-diagnostic symptoms or remained well and HC. Furthermore, within the HR cohort, there was a significant and positive association between schizophrenia polygenic risk score and bilateral frontal gyrification. CONCLUSIONS These results suggest that polygenic risk for schizophrenia impacts upon early neurodevelopment to confer greater gyral folding in adulthood and an increased risk of developing the disorder.
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McCartney DL, Stevenson AJ, Walker RM, Gibson J, Morris SW, Campbell A, Murray AD, Whalley HC, Porteous DJ, McIntosh AM, Evans KL, Deary IJ, Marioni RE. Investigating the relationship between DNA methylation age acceleration and risk factors for Alzheimer's disease. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2018; 10:429-437. [PMID: 30167451 PMCID: PMC6111045 DOI: 10.1016/j.dadm.2018.05.006] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Introduction The “epigenetic clock” is a DNA methylation–based estimate of biological age and is correlated with chronological age—the greatest risk factor for Alzheimer's disease (AD). Genetic and environmental risk factors exist for AD, several of which are potentially modifiable. In this study, we assess the relationship between the epigenetic clock and AD risk factors. Methods Multilevel models were used to assess the relationship between age acceleration (the residual of biological age regressed onto chronological age) and AD risk factors relating to cognitive reserve, lifestyle, disease, and genetics in the Generation Scotland study (n = 5100). Results We report significant associations between age acceleration and body mass index, total cholesterol to high-density lipoprotein cholesterol ratios, socioeconomic status, high blood pressure, and smoking behavior (Bonferroni-adjusted P < .05). Discussion Associations are present between environmental risk factors for AD and age acceleration. Measures to modify such risk factors might improve the risk profile for AD and the rate of biological ageing. Future longitudinal analyses are therefore warranted.
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Hibar DP, Westlye LT, Doan NT, Jahanshad N, Cheung JW, Ching CRK, Versace A, Bilderbeck AC, Uhlmann A, Mwangi B, Krämer B, Overs B, Hartberg CB, Abé C, Dima D, Grotegerd D, Sprooten E, Bøen E, Jimenez E, Howells FM, Delvecchio G, Temmingh H, Starke J, Almeida JRC, Goikolea JM, Houenou J, Beard LM, Rauer L, Abramovic L, Bonnin M, Ponteduro MF, Keil M, Rive MM, Yao N, Yalin N, Najt P, Rosa PG, Redlich R, Trost S, Hagenaars S, Fears SC, Alonso-Lana S, van Erp TGM, Nickson T, Chaim-Avancini TM, Meier TB, Elvsåshagen T, Haukvik UK, Lee WH, Schene AH, Lloyd AJ, Young AH, Nugent A, Dale AM, Pfennig A, McIntosh AM, Lafer B, Baune BT, Ekman CJ, Zarate CA, Bearden CE, Henry C, Simhandl C, McDonald C, Bourne C, Stein DJ, Wolf DH, Cannon DM, Glahn DC, Veltman DJ, Pomarol-Clotet E, Vieta E, Canales-Rodriguez EJ, Nery FG, Duran FLS, Busatto GF, Roberts G, Pearlson GD, Goodwin GM, Kugel H, Whalley HC, Ruhe HG, Soares JC, Fullerton JM, Rybakowski JK, Savitz J, Chaim KT, Fatjó-Vilas M, Soeiro-de-Souza MG, Boks MP, Zanetti MV, Otaduy MCG, Schaufelberger MS, Alda M, Ingvar M, Phillips ML, Kempton MJ, Bauer M, Landén M, Lawrence NS, van Haren NEM, Horn NR, Freimer NB, Gruber O, Schofield PR, Mitchell PB, Kahn RS, Lenroot R, Machado-Vieira R, Ophoff RA, Sarró S, Frangou S, Satterthwaite TD, Hajek T, Dannlowski U, Malt UF, Arolt V, Gattaz WF, Drevets WC, Caseras X, Agartz I, Thompson PM, Andreassen OA. Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group. Mol Psychiatry 2018; 23:932-942. [PMID: 28461699 PMCID: PMC5668195 DOI: 10.1038/mp.2017.73] [Citation(s) in RCA: 422] [Impact Index Per Article: 70.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Revised: 02/04/2017] [Accepted: 02/10/2017] [Indexed: 12/13/2022]
Abstract
Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 × 10-21), left fusiform gyrus (d=-0.288; P=8.25 × 10-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.
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Walton E, Hibar DP, van Erp TGM, Potkin SG, Roiz-Santiañez R, Crespo-Facorro B, Suarez-Pinilla P, Van Haren NEM, de Zwarte SMC, Kahn RS, Cahn W, Doan NT, Jørgensen KN, Gurholt TP, Agartz I, Andreassen OA, Westlye LT, Melle I, Berg AO, Morch-Johnsen L, Færden A, Flyckt L, Fatouros-Bergman H, Jönsson EG, Hashimoto R, Yamamori H, Fukunaga M, Jahanshad N, De Rossi P, Piras F, Banaj N, Spalletta G, Gur RE, Gur RC, Wolf DH, Satterthwaite TD, Beard LM, Sommer IE, Koops S, Gruber O, Richter A, Krämer B, Kelly S, Donohoe G, McDonald C, Cannon DM, Corvin A, Gill M, Di Giorgio A, Bertolino A, Lawrie S, Nickson T, Whalley HC, Neilson E, Calhoun VD, Thompson PM, Turner JA, Ehrlich S. Prefrontal cortical thinning links to negative symptoms in schizophrenia via the ENIGMA consortium. Psychol Med 2018; 48:82-94. [PMID: 28545597 PMCID: PMC5826665 DOI: 10.1017/s0033291717001283] [Citation(s) in RCA: 92] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity. METHODS This study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores). RESULTS Meta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (β std = -0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged. CONCLUSIONS Using an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.
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Alloza C, Bastin ME, Cox SR, Gibson J, Duff B, Semple SI, Whalley HC, Lawrie SM. Central and non-central networks, cognition, clinical symptoms, and polygenic risk scores in schizophrenia. Hum Brain Mapp 2017; 38:5919-5930. [PMID: 28881417 DOI: 10.1002/hbm.23798] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Revised: 08/02/2017] [Accepted: 08/24/2017] [Indexed: 12/25/2022] Open
Abstract
Schizophrenia is a complex disorder that may be the result of aberrant connections between specific brain regions rather than focal brain abnormalities. Here, we investigate the relationships between brain structural connectivity as described by network analysis, intelligence, symptoms, and polygenic risk scores (PGRS) for schizophrenia in a group of patients with schizophrenia and a group of healthy controls. Recently, researchers have shown an interest in the role of high centrality networks in the disorder. However, the importance of non-central networks still remains unclear. Thus, we specifically examined network-averaged fractional anisotropy (mean edge weight) in central and non-central subnetworks. Connections with the highest betweenness centrality within the average network (>75% of centrality values) were selected to represent the central subnetwork. The remaining connections were assigned to the non-central subnetwork. Additionally, we calculated graph theory measures from the average network (connections that occur in at least 2/3 of participants). Density, strength, global efficiency, and clustering coefficient were significantly lower in patients compared with healthy controls for the average network (pFDR < 0.05). All metrics across networks were significantly associated with intelligence (pFDR < 0.05). There was a tendency towards significance for a correlation between intelligence and PGRS for schizophrenia (r = -0.508, p = 0.052) that was significantly mediated by central and non-central mean edge weight and every graph metric from the average network. These results are consistent with the hypothesis that intelligence deficits are associated with a genetic risk for schizophrenia, which is mediated via the disruption of distributed brain networks. Hum Brain Mapp 38:5919-5930, 2017. © 2017 Wiley Periodicals, Inc.
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