1
|
Knol MJ, Poot RA, Evans TE, Satizabal CL, Mishra A, Sargurupremraj M, van der Auwera S, Duperron MG, Jian X, Hostettler IC, van Dam-Nolen DHK, Lamballais S, Pawlak MA, Lewis CE, Carrion-Castillo A, van Erp TGM, Reinbold CS, Shin J, Scholz M, Håberg AK, Kämpe A, Li GHY, Avinun R, Atkins JR, Hsu FC, Amod AR, Lam M, Tsuchida A, Teunissen MWA, Aygün N, Patel Y, Liang D, Beiser AS, Beyer F, Bis JC, Bos D, Bryan RN, Bülow R, Caspers S, Catheline G, Cecil CAM, Dalvie S, Dartigues JF, DeCarli C, Enlund-Cerullo M, Ford JM, Franke B, Freedman BI, Friedrich N, Green MJ, Haworth S, Helmer C, Hoffmann P, Homuth G, Ikram MK, Jack CR, Jahanshad N, Jockwitz C, Kamatani Y, Knodt AR, Li S, Lim K, Longstreth WT, Macciardi F, Mäkitie O, Mazoyer B, Medland SE, Miyamoto S, Moebus S, Mosley TH, Muetzel R, Mühleisen TW, Nagata M, Nakahara S, Palmer ND, Pausova Z, Preda A, Quidé Y, Reay WR, Roshchupkin GV, Schmidt R, Schreiner PJ, Setoh K, Shapland CY, Sidney S, St Pourcain B, Stein JL, Tabara Y, Teumer A, Uhlmann A, van der Lugt A, Vernooij MW, Werring DJ, Windham BG, Witte AV, Wittfeld K, Yang Q, Yoshida K, Brunner HG, Le Grand Q, Sim K, Stein DJ, Bowden DW, Cairns MJ, Hariri AR, Cheung CL, Andersson S, Villringer A, Paus T, Cichon S, Calhoun VD, Crivello F, Launer LJ, White T, Koudstaal PJ, Houlden H, Fornage M, Matsuda F, Grabe HJ, Ikram MA, Debette S, Thompson PM, Seshadri S, Adams HHH. Genetic variants for head size share genes and pathways with cancer. Cell Rep Med 2024; 5:101529. [PMID: 38703765 PMCID: PMC11148644 DOI: 10.1016/j.xcrm.2024.101529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 09/18/2023] [Accepted: 04/04/2024] [Indexed: 05/06/2024]
Abstract
The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.
Collapse
|
2
|
Boen R, Kaufmann T, van der Meer D, Frei O, Agartz I, Ames D, Andersson M, Armstrong NJ, Artiges E, Atkins JR, Bauer J, Benedetti F, Boomsma DI, Brodaty H, Brosch K, Buckner RL, Cairns MJ, Calhoun V, Caspers S, Cichon S, Corvin AP, Crespo-Facorro B, Dannlowski U, David FS, de Geus EJC, de Zubicaray GI, Desrivières S, Doherty JL, Donohoe G, Ehrlich S, Eising E, Espeseth T, Fisher SE, Forstner AJ, Fortaner-Uyà L, Frouin V, Fukunaga M, Ge T, Glahn DC, Goltermann J, Grabe HJ, Green MJ, Groenewold NA, Grotegerd D, Grøntvedt GR, Hahn T, Hashimoto R, Hehir-Kwa JY, Henskens FA, Holmes AJ, Håberg AK, Haavik J, Jacquemont S, Jansen A, Jockwitz C, Jönsson EG, Kikuchi M, Kircher T, Kumar K, Le Hellard S, Leu C, Linden DE, Liu J, Loughnan R, Mather KA, McMahon KL, McRae AF, Medland SE, Meinert S, Moreau CA, Morris DW, Mowry BJ, Mühleisen TW, Nenadić I, Nöthen MM, Nyberg L, Ophoff RA, Owen MJ, Pantelis C, Paolini M, Paus T, Pausova Z, Persson K, Quidé Y, Marques TR, Sachdev PS, Sando SB, Schall U, Scott RJ, Selbæk G, Shumskaya E, Silva AI, Sisodiya SM, Stein F, Stein DJ, Straube B, Streit F, Strike LT, Teumer A, Teutenberg L, Thalamuthu A, Tooney PA, Tordesillas-Gutierrez D, Trollor JN, van 't Ent D, van den Bree MBM, van Haren NEM, Vázquez-Bourgon J, Völzke H, Wen W, Wittfeld K, Ching CRK, Westlye LT, Thompson PM, Bearden CE, Selmer KK, Alnæs D, Andreassen OA, Sønderby IE. Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers. Biol Psychiatry 2024; 95:147-160. [PMID: 37661008 PMCID: PMC7615370 DOI: 10.1016/j.biopsych.2023.08.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 07/25/2023] [Accepted: 08/21/2023] [Indexed: 09/05/2023]
Abstract
BACKGROUND Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.
Collapse
|
3
|
Zhao L, Mühleisen TW, Pelzer DI, Burger B, Beins EC, Forstner AJ, Herms S, Hoffmann P, Amunts K, Palomero-Gallagher N, Cichon S. Relationships between neurotransmitter receptor densities and expression levels of their corresponding genes in the human hippocampus. Neuroimage 2023; 273:120095. [PMID: 37030412 PMCID: PMC10167541 DOI: 10.1016/j.neuroimage.2023.120095] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 03/02/2023] [Accepted: 04/05/2023] [Indexed: 04/08/2023] Open
Abstract
Neurotransmitter receptors are key molecules in signal transmission, their alterations are associated with brain dysfunction. Relationships between receptors and their corresponding genes are poorly understood, especially in humans. We combined in vitro receptor autoradiography and RNA sequencing to quantify, in the same tissue samples (7 subjects), the densities of 14 receptors and expression levels of their corresponding 43 genes in the Cornu Ammonis (CA) and dentate gyrus (DG) of human hippocampus. Significant differences in receptor densities between both structures were found only for metabotropic receptors, whereas significant differences in RNA expression levels mostly pertained ionotropic receptors. Receptor fingerprints of CA and DG differ in shapes but have similar sizes; the opposite holds true for their "RNA fingerprints", which represent the expression levels of multiple genes in a single area. In addition, the correlation coefficients between receptor densities and corresponding gene expression levels vary widely and the mean correlation strength was weak-to-moderate. Our results suggest that receptor densities are not only controlled by corresponding RNA expression levels, but also by multiple regionally specific post-translational factors.
Collapse
|
4
|
Refisch A, Komatsuzaki S, Ungelenk M, Chung HY, Schumann A, Schilling SS, Jantzen W, Schröder S, Mühleisen TW, Nöthen MM, Hübner CA, Bär KJ. Associations of common genetic risk variants of the muscarinic acetylcholine receptor M2 with cardiac autonomic dysfunction in patients with schizophrenia. World J Biol Psychiatry 2023; 24:1-11. [PMID: 35172679 DOI: 10.1080/15622975.2022.2043561] [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] [Indexed: 02/03/2023]
Abstract
OBJECTIVES Decreased vagal modulation, which has consistently been observed in schizophrenic patients, might contribute to increased cardiac mortality in schizophrenia. Previously, associations between CHRM2 (Cholinergic Receptor Muscarinic 2) and cardiac autonomic features have been reported. Here, we tested for possible associations between these polymorphisms and heart rate variability in patients with schizophrenia. METHODS A total of three single nucleotide polymorphisms (SNPs) in CHRM2 (rs73158705 A>G, rs8191992 T>A and rs2350782 T>C) that achieved significance (p < 5 * 10-8) in genome-wide association studies for cardiac autonomic features were genotyped in 88 drug-naïve patients, 61 patients receiving antipsychotic medication and 144 healthy controls. Genotypes were analysed for associations with parameters of heart rate variability and complexity, in each diagnostic group. RESULTS We observed a significantly altered heart rate variability in unmedicated patients with identified genetic risk status in rs73158705 A>G, rs8191992 T>A and rs2350782 T>C as compared to genotype non-risk status. In patients receiving antipsychotic medication and healthy controls, these associations were not observed. DISCUSSION We report novel candidate genetic associations with cardiac autonomic dysfunction in schizophrenia, but larger cohorts are required for replication.
Collapse
|
5
|
Brouwer RM, Klein M, Grasby KL, Schnack HG, Jahanshad N, Teeuw J, Thomopoulos SI, Sprooten E, Franz CE, Gogtay N, Kremen WS, Panizzon MS, Olde Loohuis LM, Whelan CD, Aghajani M, Alloza C, Alnæs D, Artiges E, Ayesa-Arriola R, Barker GJ, Bastin ME, Blok E, Bøen E, Breukelaar IA, Bright JK, Buimer EEL, Bülow R, Cannon DM, Ciufolini S, Crossley NA, Damatac CG, Dazzan P, de Mol CL, de Zwarte SMC, Desrivières S, Díaz-Caneja CM, Doan NT, Dohm K, Fröhner JH, Goltermann J, Grigis A, Grotegerd D, Han LKM, Harris MA, Hartman CA, Heany SJ, Heindel W, Heslenfeld DJ, Hohmann S, Ittermann B, Jansen PR, Janssen J, Jia T, Jiang J, Jockwitz C, Karali T, Keeser D, Koevoets MGJC, Lenroot RK, Malchow B, Mandl RCW, Medel V, Meinert S, Morgan CA, Mühleisen TW, Nabulsi L, Opel N, de la Foz VOG, Overs BJ, Paillère Martinot ML, Redlich R, Marques TR, Repple J, Roberts G, Roshchupkin GV, Setiaman N, Shumskaya E, Stein F, Sudre G, Takahashi S, Thalamuthu A, Tordesillas-Gutiérrez D, van der Lugt A, van Haren NEM, Wardlaw JM, Wen W, Westeneng HJ, Wittfeld K, Zhu AH, Zugman A, Armstrong NJ, Bonfiglio G, Bralten J, Dalvie S, Davies G, Di Forti M, Ding L, Donohoe G, Forstner AJ, Gonzalez-Peñas J, Guimaraes JPOFT, Homuth G, Hottenga JJ, Knol MJ, Kwok JBJ, Le Hellard S, Mather KA, Milaneschi Y, Morris DW, Nöthen MM, Papiol S, Rietschel M, Santoro ML, Steen VM, Stein JL, Streit F, Tankard RM, Teumer A, van 't Ent D, van der Meer D, van Eijk KR, Vassos E, Vázquez-Bourgon J, Witt SH, Adams HHH, Agartz I, Ames D, Amunts K, Andreassen OA, Arango C, Banaschewski T, Baune BT, Belangero SI, Bokde ALW, Boomsma DI, Bressan RA, Brodaty H, Buitelaar JK, Cahn W, Caspers S, Cichon S, Crespo-Facorro B, Cox SR, Dannlowski U, Elvsåshagen T, Espeseth T, Falkai PG, Fisher SE, Flor H, Fullerton JM, Garavan H, Gowland PA, Grabe HJ, Hahn T, Heinz A, Hillegers M, Hoare J, Hoekstra PJ, Ikram MA, Jackowski AP, Jansen A, Jönsson EG, Kahn RS, Kircher T, Korgaonkar MS, Krug A, Lemaitre H, Malt UF, Martinot JL, McDonald C, Mitchell PB, Muetzel RL, Murray RM, Nees F, Nenadić I, Oosterlaan J, Ophoff RA, Pan PM, Penninx BWJH, Poustka L, Sachdev PS, Salum GA, Schofield PR, Schumann G, Shaw P, Sim K, Smolka MN, Stein DJ, Trollor JN, van den Berg LH, Veldink JH, Walter H, Westlye LT, Whelan R, White T, Wright MJ, Medland SE, Franke B, Thompson PM, Hulshoff Pol HE. Genetic variants associated with longitudinal changes in brain structure across the lifespan. Nat Neurosci 2022; 25:421-432. [PMID: 35383335 PMCID: PMC10040206 DOI: 10.1038/s41593-022-01042-4] [Citation(s) in RCA: 60] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 02/28/2022] [Indexed: 02/08/2023]
Abstract
Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.
Collapse
|
6
|
Sønderby IE, Ching CRK, Thomopoulos SI, van der Meer D, Sun D, Villalon‐Reina JE, Agartz I, Amunts K, Arango C, Armstrong NJ, Ayesa‐Arriola R, Bakker G, Bassett AS, Boomsma DI, Bülow R, Butcher NJ, Calhoun VD, Caspers S, Chow EWC, Cichon S, Ciufolini S, Craig MC, Crespo‐Facorro B, Cunningham AC, Dale AM, Dazzan P, de Zubicaray GI, Djurovic S, Doherty JL, Donohoe G, Draganski B, Durdle CA, Ehrlich S, Emanuel BS, Espeseth T, Fisher SE, Ge T, Glahn DC, Grabe HJ, Gur RE, Gutman BA, Haavik J, Håberg AK, Hansen LA, Hashimoto R, Hibar DP, Holmes AJ, Hottenga J, Hulshoff Pol HE, Jalbrzikowski M, Knowles EEM, Kushan L, Linden DEJ, Liu J, Lundervold AJ, Martin‐Brevet S, Martínez K, Mather KA, Mathias SR, McDonald‐McGinn DM, McRae AF, Medland SE, Moberget T, Modenato C, Monereo Sánchez J, Moreau CA, Mühleisen TW, Paus T, Pausova Z, Prieto C, Ragothaman A, Reinbold CS, Reis Marques T, Repetto GM, Reymond A, Roalf DR, Rodriguez‐Herreros B, Rucker JJ, Sachdev PS, Schmitt JE, Schofield PR, Silva AI, Stefansson H, Stein DJ, Tamnes CK, Tordesillas‐Gutiérrez D, Ulfarsson MO, Vajdi A, van 't Ent D, van den Bree MBM, Vassos E, Vázquez‐Bourgon J, Vila‐Rodriguez F, Walters GB, Wen W, Westlye LT, Wittfeld K, Zackai EH, Stefánsson K, Jacquemont S, Thompson PM, Bearden CE, Andreassen OA. Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs. Hum Brain Mapp 2022; 43:300-328. [PMID: 33615640 PMCID: PMC8675420 DOI: 10.1002/hbm.25354] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 01/07/2021] [Accepted: 01/13/2021] [Indexed: 01/21/2023] Open
Abstract
The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.
Collapse
|
7
|
Bopp SK, Heilbronner U, Schlattmann P, Buspavanich PJ, Lang UE, Heinz A, Schulze TG, Adli M, Mühleisen TW, Ricken R. A GWAS top hit for circulating leptin is associated with weight gain but not with leptin protein levels in lithium-augmented patients with major depression. Eur Neuropsychopharmacol 2021; 53:114-119. [PMID: 34653833 PMCID: PMC8650825 DOI: 10.1016/j.euroneuro.2021.09.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 09/11/2021] [Accepted: 09/15/2021] [Indexed: 11/25/2022]
Abstract
Lithium-treated patients often suffer from weight gain as a common adverse event. In an earlier investigation, we found an impact of two single-nucleotide polymorphisms (rs10487506 and rs2278815) at the leptin gene on weight gain but not on leptin protein levels in serum under lithium augmentation. A recent genome-wide association study identified a polymorphism at the leptin gene locus (rs10487505) associated with circulating leptin protein levels. To characterize potential effects of this variant in acute major depressive disorder, we investigated body mass indices from 180 lithium-augmented patients and serum concentrations of leptin protein from 89 patients using linear mixed model analyses and rs6979832, a proxy SNP of rs10487505. Body mass index was measured before and after 4 weeks of lithium augmentation, in a subsample also after 4 and 7 months. Leptin serum levels were measured before and during lithium augmentation. G-allele homozygotes of rs6979832 had a significantly lower body mass index increase during observation compared to A-allele hetero- and homozygotes. However, we found no influence on leptin serum levels. Joint analyses of rs6979832 with the previously investigated polymorphisms rs10487506 and rs2278815, and expressed quantitative trait data, suggest a complex interplay between SNP alleles at the leptin locus. These results strongly support our earlier findings that common genetic variation at the leptin gene locus may be involved in lithium augmentation-associated weight gain in major depressive disorder.
Collapse
|
8
|
Unger N, Heim S, Hilger DI, Bludau S, Pieperhoff P, Cichon S, Amunts K, Mühleisen TW. Identification of Phonology-Related Genes and Functional Characterization of Broca's and Wernicke's Regions in Language and Learning Disorders. Front Neurosci 2021; 15:680762. [PMID: 34539327 PMCID: PMC8446646 DOI: 10.3389/fnins.2021.680762] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 08/04/2021] [Indexed: 12/02/2022] Open
Abstract
Impaired phonological processing is a leading symptom of multifactorial language and learning disorders suggesting a common biological basis. Here we evaluated studies of dyslexia, dyscalculia, specific language impairment (SLI), and the logopenic variant of primary progressive aphasia (lvPPA) seeking for shared risk genes in Broca's and Wernicke's regions, being key for phonological processing within the complex language network. The identified "phonology-related genes" from literature were functionally characterized using Atlas-based expression mapping (JuGEx) and gene set enrichment. Out of 643 publications from the last decade until now, we extracted 21 candidate genes of which 13 overlapped with dyslexia and SLI, six with dyslexia and dyscalculia, and two with dyslexia, dyscalculia, and SLI. No overlap was observed between the childhood disorders and the late-onset lvPPA often showing symptoms of learning disorders earlier in life. Multiple genes were enriched in Gene Ontology terms of the topics learning (CNTNAP2, CYFIP1, DCDC2, DNAAF4, FOXP2) and neuronal development (CCDC136, CNTNAP2, CYFIP1, DCDC2, KIAA0319, RBFOX2, ROBO1). Twelve genes showed above-average expression across both regions indicating moderate-to-high gene activity in the investigated cortical part of the language network. Of these, three genes were differentially expressed suggesting potential regional specializations: ATP2C2 was upregulated in Broca's region, while DNAAF4 and FOXP2 were upregulated in Wernicke's region. ATP2C2 encodes a magnesium-dependent calcium transporter which fits with reports about disturbed calcium and magnesium levels for dyslexia and other communication disorders. DNAAF4 (formerly known as DYX1C1) is involved in neuronal migration supporting the hypothesis of disturbed migration in dyslexia. FOXP2 is a transcription factor that regulates a number of genes involved in development of speech and language. Overall, our interdisciplinary and multi-tiered approach provided evidence that genetic and transcriptional variation of ATP2C2, DNAAF4, and FOXP2 may play a role in physiological and pathological aspects of phonological processing.
Collapse
|
9
|
Caspers S, Röckner ME, Jockwitz C, Bittner N, Teumer A, Herms S, Hoffmann P, Nöthen MM, Moebus S, Amunts K, Cichon S, Mühleisen TW. Pathway-Specific Genetic Risk for Alzheimer's Disease Differentiates Regional Patterns of Cortical Atrophy in Older Adults. Cereb Cortex 2021; 30:801-811. [PMID: 31402375 DOI: 10.1093/cercor/bhz127] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 04/30/2019] [Accepted: 05/18/2019] [Indexed: 11/13/2022] Open
Abstract
Brain aging is highly variable and represents a challenge to delimit aging from disease processes. Moreover, genetic factors may influence both aging and disease. Here we focused on this issue and investigated effects of multiple genetic loci previously identified to be associated with late-onset Alzheimer's disease (AD) on brain structure of older adults from a population sample. We calculated a genetic risk score (GRS) using genome-wide significant single-nucleotide polymorphisms from genome-wide association studies of AD and tested its effect on cortical thickness (CT). We observed a common pattern of cortical thinning (right inferior frontal, left posterior temporal, medial occipital cortex). To identify CT changes by specific biological processes, we subdivided the GRS effect according to AD-associated pathways and performed follow-up analyses. The common pattern from the main analysis was further differentiated by pathway-specific effects yielding a more bilateral pattern. Further findings were located in the superior parietal and mid/anterior cingulate regions representing 2 unique pathway-specific patterns. All patterns, except the superior parietal pattern, were influenced by apolipoprotein E. Our step-wise approach revealed atrophy patterns that partially resembled imaging findings in early stages of AD. Our study provides evidence that genetic burden for AD contributes to structural brain variability in normal aging.
Collapse
|
10
|
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: 531] [Impact Index Per Article: 177.0] [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.
Collapse
|
11
|
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.
Collapse
|
12
|
Refisch A, Chung HY, Komatsuzaki S, Schumann A, Mühleisen TW, Nöthen MM, Hübner CA, Bär KJ. A common variation in HCN1 is associated with heart rate variability in schizophrenia. Schizophr Res 2021; 229:73-79. [PMID: 33221148 DOI: 10.1016/j.schres.2020.11.017] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 07/02/2020] [Accepted: 11/13/2020] [Indexed: 01/09/2023]
Abstract
BACKGROUND There is growing evidence for a shared genetic basis between schizophrenia risk and cardiovascular disease. Reduced efferent vagal activity, indexed by reduced heart rate variability (HRV), has been consistently described in patients with schizophrenia and may potentially contribute to the increased cardiovascular risk in these patients. In this study, we tested the hypothesis whether the established schizophrenia risk variant HCN1 rs16902086 (A > G) is associated with reduced HRV. METHODS We analyzed the risk status of HCN1 rs16902086 (AG/GG vs. AA genotype) in 83 unmedicated patients with schizophrenia and 96 healthy controls and investigated genotype-related impacts on various HRV parameters. RESULTS We observed significantly increased resting heart rates and a marked decrease of vagal modulation in our patient cohort. Strikingly, HCN1 rs16902086 (A > G) was associated with reduced HRV parameters in patients only. A trend towards more pronounced HRV deviations was observed in homozygous (GG) compared to heterozygous patients (AG). CONCLUSION We present first evidence for a genetic risk factor that is associated with decreased vagal modulation in unmedicated patients with schizophrenia. Moreover, our findings suggest that HCN1 might be involved in reduced vagal modulation and possibly in increased cardiac mortality in schizophrenia patients. Thus, our data indicate that reduced vagal modulation might be an endophenotype of schizophrenia.
Collapse
|
13
|
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.
Collapse
|
14
|
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: 350] [Impact Index Per Article: 87.5] [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.
Collapse
|
15
|
Sønderby IE, Gústafsson Ó, Doan NT, Hibar DP, Martin-Brevet S, Abdellaoui A, Ames D, Amunts K, Andersson M, Armstrong NJ, Bernard M, Blackburn N, Blangero J, Boomsma DI, Bralten J, Brattbak HR, Brodaty H, Brouwer RM, Bülow R, Calhoun V, Caspers S, Cavalleri G, Chen CH, Cichon S, Ciufolini S, Corvin A, Crespo-Facorro B, Curran JE, Dale AM, Dalvie S, Dazzan P, de Geus EJC, de Zubicaray GI, de Zwarte SMC, Delanty N, den Braber A, Desrivières S, Donohoe G, Draganski B, Ehrlich S, Espeseth T, Fisher SE, Franke B, Frouin V, Fukunaga M, Gareau T, Glahn DC, Grabe H, Groenewold NA, Haavik J, Håberg A, Hashimoto R, Hehir-Kwa JY, Heinz A, Hillegers MHJ, Hoffmann P, Holleran L, Hottenga JJ, Hulshoff HE, Ikeda M, Jahanshad N, Jernigan T, Jockwitz C, Johansson S, Jonsdottir GA, Jönsson EG, Kahn R, Kaufmann T, Kelly S, Kikuchi M, Knowles EEM, Kolskår KK, Kwok JB, Hellard SL, Leu C, Liu J, Lundervold AJ, Lundervold A, Martin NG, Mather K, Mathias SR, McCormack M, McMahon KL, McRae A, Milaneschi Y, Moreau C, Morris D, Mothersill D, Mühleisen TW, Murray R, Nordvik JE, Nyberg L, Olde Loohuis LM, Ophoff R, Paus T, Pausova Z, Penninx B, Peralta JM, Pike B, Prieto C, Pudas S, Quinlan E, Quintana DS, Reinbold CS, Marques TR, Reymond A, Richard G, Rodriguez-Herreros B, Roiz-Santiañez R, Rokicki J, Rucker J, Sachdev P, Sanders AM, Sando SB, Schmaal L, Schofield PR, Schork AJ, Schumann G, Shin J, Shumskaya E, Sisodiya S, Steen VM, Stein DJ, Steinberg S, Strike L, Teumer A, Thalamuthu A, Tordesillas-Gutierrez D, Turner J, Ueland T, Uhlmann A, Ulfarsson MO, van 't Ent D, van der Meer D, van Haren NEM, Vaskinn A, Vassos E, Walters GB, Wang Y, Wen W, Whelan CD, Wittfeld K, Wright M, Yamamori H, Zayats T, Agartz I, Westlye LT, Jacquemont S, Djurovic S, Stefánsson H, Stefánsson K, Thompson P, Andreassen OA. Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia. Mol Psychiatry 2020; 25:584-602. [PMID: 30283035 PMCID: PMC7042770 DOI: 10.1038/s41380-018-0118-1] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 05/02/2018] [Accepted: 05/25/2018] [Indexed: 12/24/2022]
Abstract
Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10-6, 1.7 × 10-9, 3.5 × 10-12 and 1.0 × 10-4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes.
Collapse
|
16
|
Bopp SK, Heilbronner U, Schlattmann P, Mühleisen TW, Bschor T, Richter C, Steinacher B, Stamm TJ, Merkl A, Herms S, Köhler S, Sterzer P, Hellweg R, Heinz A, Cichon S, Lang UE, Schulze TG, Adli M, Ricken R. Leptin gene polymorphisms are associated with weight gain during lithium augmentation in patients with major depression. Eur Neuropsychopharmacol 2019; 29:211-221. [PMID: 30554862 DOI: 10.1016/j.euroneuro.2018.12.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 11/29/2018] [Accepted: 12/01/2018] [Indexed: 12/28/2022]
Abstract
Weight gain is a common adverse effect of lithium augmentation. Previous studies indicate an impact of genetic variants at the leptin gene on weight gain as a consequence of psychopharmacological treatment. The primary aim of our study was to identify variants at the leptin locus that might predict lithium-induced weight gain. The secondary aim was to investigate if these variants modulate leptin levels. In 180 patients with acute major depressive disorder, body mass index was measured before and after 4 weeks of lithium augmentation, in a subsample also after 4 and/or 7 months. In a subsample of 89 patients, leptin serum concentrations were measured before and during lithium augmentation. We used linear mixed model analyzes to investigate the effects of 2 polymorphisms at the leptin locus (rs4731426 and rs7799039, employing the respective proxy SNPs rs2278815 and rs10487506) on changes in body mass index and leptin levels. For both polymorphisms, which are in high linkage disequilibrium, body mass index was significantly lower in homozygous A-allele carriers than in carriers of other genotypes at baseline. Over the follow-up period, body mass index increased less in homozygous A-allele carriers of rs4731426 than in carriers of other genotypes. This was not the case for rs7799039. Neither polymorphism modulated leptin protein expression. Our study strongly supports the hypothesis that genetic variability at the leptin locus is involved in lithium augmentation-associated weight gain in major depressive disorder. Furthermore, Genotype-Tissue Expression data provide strong evidence that rs4731426 influences the expression of leptin messenger ribonucleic acid in fibroblasts.
Collapse
|
17
|
Satizabal CL, Adams HHH, Hibar DP, White CC, Knol MJ, Stein JL, Scholz M, Sargurupremraj M, Jahanshad N, Roshchupkin GV, Smith AV, Bis JC, Jian X, Luciano M, Hofer E, Teumer A, van der Lee SJ, Yang J, Yanek LR, Lee TV, Li S, Hu Y, Koh JY, Eicher JD, Desrivières S, Arias-Vasquez A, Chauhan G, Athanasiu L, Rentería ME, Kim S, Hoehn D, Armstrong NJ, Chen Q, Holmes AJ, den Braber A, Kloszewska I, Andersson M, Espeseth T, Grimm O, Abramovic L, Alhusaini S, Milaneschi Y, Papmeyer M, Axelsson T, Ehrlich S, Roiz-Santiañez R, Kraemer B, Håberg AK, Jones HJ, Pike GB, Stein DJ, Stevens A, Bralten J, Vernooij MW, Harris TB, Filippi I, Witte AV, Guadalupe T, Wittfeld K, Mosley TH, Becker JT, Doan NT, Hagenaars SP, Saba Y, Cuellar-Partida G, Amin N, Hilal S, Nho K, Mirza-Schreiber N, Arfanakis K, Becker DM, Ames D, Goldman AL, Lee PH, Boomsma DI, Lovestone S, Giddaluru S, Le Hellard S, Mattheisen M, Bohlken MM, Kasperaviciute D, Schmaal L, Lawrie SM, Agartz I, Walton E, Tordesillas-Gutierrez D, Davies GE, Shin J, Ipser JC, Vinke LN, Hoogman M, Jia T, Burkhardt R, Klein M, Crivello F, Janowitz D, Carmichael O, Haukvik UK, Aribisala BS, Schmidt H, Strike LT, Cheng CY, Risacher SL, Pütz B, Fleischman DA, Assareh AA, Mattay VS, Buckner RL, Mecocci P, Dale AM, Cichon S, Boks MP, Matarin M, Penninx BWJH, Calhoun VD, Chakravarty MM, Marquand AF, Macare C, Kharabian Masouleh S, Oosterlaan J, Amouyel P, Hegenscheid K, Rotter JI, Schork AJ, Liewald DCM, de Zubicaray GI, Wong TY, Shen L, Sämann PG, Brodaty H, Roffman JL, de Geus EJC, Tsolaki M, Erk S, van Eijk KR, Cavalleri GL, van der Wee NJA, McIntosh AM, Gollub RL, Bulayeva KB, Bernard M, Richards JS, Himali JJ, Loeffler M, Rommelse N, Hoffmann W, Westlye LT, Valdés Hernández MC, Hansell NK, van Erp TGM, Wolf C, Kwok JBJ, Vellas B, Heinz A, Olde Loohuis LM, Delanty N, Ho BC, Ching CRK, Shumskaya E, Singh B, Hofman A, van der Meer D, Homuth G, Psaty BM, Bastin ME, Montgomery GW, Foroud TM, Reppermund S, Hottenga JJ, Simmons A, Meyer-Lindenberg A, Cahn W, Whelan CD, van Donkelaar MMJ, Yang Q, Hosten N, Green RC, Thalamuthu A, Mohnke S, Hulshoff Pol HE, Lin H, Jack CR, Schofield PR, Mühleisen TW, Maillard P, Potkin SG, Wen W, Fletcher E, Toga AW, Gruber O, Huentelman M, Davey Smith G, Launer LJ, Nyberg L, Jönsson EG, Crespo-Facorro B, Koen N, Greve DN, Uitterlinden AG, Weinberger DR, Steen VM, Fedko IO, Groenewold NA, Niessen WJ, Toro R, Tzourio C, Longstreth WT, Ikram MK, Smoller JW, van Tol MJ, Sussmann JE, Paus T, Lemaître H, Schroeter ML, Mazoyer B, Andreassen OA, Holsboer F, Depondt C, Veltman DJ, Turner JA, Pausova Z, Schumann G, van Rooij D, Djurovic S, Deary IJ, McMahon KL, Müller-Myhsok B, Brouwer RM, Soininen H, Pandolfo M, Wassink TH, Cheung JW, Wolfers T, Martinot JL, Zwiers MP, Nauck M, Melle I, Martin NG, Kanai R, Westman E, Kahn RS, Sisodiya SM, White T, Saremi A, van Bokhoven H, Brunner HG, Völzke H, Wright MJ, van 't Ent D, Nöthen MM, Ophoff RA, Buitelaar JK, Fernández G, Sachdev PS, Rietschel M, van Haren NEM, Fisher SE, Beiser AS, Francks C, Saykin AJ, Mather KA, Romanczuk-Seiferth N, Hartman CA, DeStefano AL, Heslenfeld DJ, Weiner MW, Walter H, Hoekstra PJ, Nyquist PA, Franke B, Bennett DA, Grabe HJ, Johnson AD, Chen C, van Duijn CM, Lopez OL, Fornage M, Wardlaw JM, Schmidt R, DeCarli C, De Jager PL, Villringer A, Debette S, Gudnason V, Medland SE, Shulman JM, Thompson PM, Seshadri S, Ikram MA. Genetic architecture of subcortical brain structures in 38,851 individuals. Nat Genet 2019; 51:1624-1636. [PMID: 31636452 PMCID: PMC7055269 DOI: 10.1038/s41588-019-0511-y] [Citation(s) in RCA: 152] [Impact Index Per Article: 30.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Accepted: 09/05/2019] [Indexed: 12/15/2022]
Abstract
Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
Collapse
|
18
|
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: 899] [Impact Index Per Article: 179.8] [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.
Collapse
|
19
|
Budde M, Friedrichs S, Alliey-Rodriguez N, Ament S, Badner JA, Berrettini WH, Bloss CS, Byerley W, Cichon S, Comes AL, Coryell W, Craig DW, Degenhardt F, Edenberg HJ, Foroud T, Forstner AJ, Frank J, Gershon ES, Goes FS, Greenwood TA, Guo Y, Hipolito M, Hood L, Keating BJ, Koller DL, Lawson WB, Liu C, Mahon PB, McInnis MG, McMahon FJ, Meier SM, Mühleisen TW, Murray SS, Nievergelt CM, Nurnberger JI, Nwulia EA, Potash JB, Quarless D, Rice J, Roach JC, Scheftner WA, Schork NJ, Shekhtman T, Shilling PD, Smith EN, Streit F, Strohmaier J, Szelinger S, Treutlein J, Witt SH, Zandi PP, Zhang P, Zöllner S, Bickeböller H, Falkai PG, Kelsoe JR, Nöthen MM, Rietschel M, Schulze TG, Malzahn D. Efficient region-based test strategy uncovers genetic risk factors for functional outcome in bipolar disorder. Eur Neuropsychopharmacol 2019; 29:156-170. [PMID: 30503783 DOI: 10.1016/j.euroneuro.2018.10.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Revised: 10/16/2018] [Accepted: 10/23/2018] [Indexed: 11/21/2022]
Abstract
Genome-wide association studies of case-control status have advanced the understanding of the genetic basis of psychiatric disorders. Further progress may be gained by increasing sample size but also by new analysis strategies that advance the exploitation of existing data, especially for clinically important quantitative phenotypes. The functionally-informed efficient region-based test strategy (FIERS) introduced herein uses prior knowledge on biological function and dependence of genotypes within a powerful statistical framework with improved sensitivity and specificity for detecting consistent genetic effects across studies. As proof of concept, FIERS was used for the first genome-wide single nucleotide polymorphism (SNP)-based investigation on bipolar disorder (BD) that focuses on an important aspect of disease course, the functional outcome. FIERS identified a significantly associated locus on chromosome 15 (hg38: chr15:48965004 - 49464789 bp) with consistent effect strength between two independent studies (GAIN/TGen: European Americans, BOMA: Germans; n = 1592 BD patients in total). Protective and risk haplotypes were found on the most strongly associated SNPs. They contain a CTCF binding site (rs586758); CTCF sites are known to regulate sets of genes within a chromatin domain. The rs586758 - rs2086256 - rs1904317 haplotype is located in the promoter flanking region of the COPS2 gene, close to microRNA4716, and the EID1, SHC4, DTWD1 genes as plausible biological candidates. While implication with BD is novel, COPS2, EID1, and SHC4 are known to be relevant for neuronal differentiation and function and DTWD1 for psychopharmacological side effects. The test strategy FIERS that enabled this discovery is equally applicable for tag SNPs and sequence data.
Collapse
|
20
|
Breuer R, Mattheisen M, Frank J, Krumm B, Treutlein J, Kassem L, Strohmaier J, Herms S, Mühleisen TW, Degenhardt F, Cichon S, Nöthen MM, Karypis G, Kelsoe J, Greenwood T, Nievergelt C, Shilling P, Shekhtman T, Edenberg H, Craig D, Szelinger S, Nurnberger J, Gershon E, Alliey-Rodriguez N, Zandi P, Goes F, Schork N, Smith E, Koller D, Zhang P, Badner J, Berrettini W, Bloss C, Byerley W, Coryell W, Foroud T, Guo Y, Hipolito M, Keating B, Lawson W, Liu C, Mahon P, McInnis M, Murray S, Nwulia E, Potash J, Rice J, Scheftner W, Zöllner S, McMahon FJ, Rietschel M, Schulze TG. Detecting significant genotype-phenotype association rules in bipolar disorder: market research meets complex genetics. Int J Bipolar Disord 2018; 6:24. [PMID: 30415424 PMCID: PMC6230336 DOI: 10.1186/s40345-018-0132-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Accepted: 08/22/2018] [Indexed: 12/21/2022] Open
Abstract
Background Disentangling the etiology of common, complex diseases is a major challenge in genetic research. For bipolar disorder (BD), several genome-wide association studies (GWAS) have been performed. Similar to other complex disorders, major breakthroughs in explaining the high heritability of BD through GWAS have remained elusive. To overcome this dilemma, genetic research into BD, has embraced a variety of strategies such as the formation of large consortia to increase sample size and sequencing approaches. Here we advocate a complementary approach making use of already existing GWAS data: a novel data mining procedure to identify yet undetected genotype–phenotype relationships. We adapted association rule mining, a data mining technique traditionally used in retail market research, to identify frequent and characteristic genotype patterns showing strong associations to phenotype clusters. We applied this strategy to three independent GWAS datasets from 2835 phenotypically characterized patients with BD. In a discovery step, 20,882 candidate association rules were extracted. Results Two of these rules—one associated with eating disorder and the other with anxiety—remained significant in an independent dataset after robust correction for multiple testing. Both showed considerable effect sizes (odds ratio ~ 3.4 and 3.0, respectively) and support previously reported molecular biological findings. Conclusion Our approach detected novel specific genotype–phenotype relationships in BD that were missed by standard analyses like GWAS. While we developed and applied our method within the context of BD gene discovery, it may facilitate identifying highly specific genotype–phenotype relationships in subsets of genome-wide data sets of other complex phenotype with similar epidemiological properties and challenges to gene discovery efforts. Electronic supplementary material The online version of this article (10.1186/s40345-018-0132-x) contains supplementary material, which is available to authorized users.
Collapse
|
21
|
Anttila V, Bulik-Sullivan B, Finucane HK, Walters RK, Bras J, Duncan L, Escott-Price V, Falcone GJ, Gormley P, Malik R, Patsopoulos NA, Ripke S, Wei Z, Yu D, Lee PH, Turley P, Grenier-Boley B, Chouraki V, Kamatani Y, Berr C, Letenneur L, Hannequin D, Amouyel P, Boland A, Deleuze JF, Duron E, Vardarajan BN, Reitz C, Goate AM, Huentelman MJ, Kamboh MI, Larson EB, Rogaeva E, St George-Hyslop P, Hakonarson H, Kukull WA, Farrer LA, Barnes LL, Beach TG, Demirci FY, Head E, Hulette CM, Jicha GA, Kauwe JSK, Kaye JA, Leverenz JB, Levey AI, Lieberman AP, Pankratz VS, Poon WW, Quinn JF, Saykin AJ, Schneider LS, Smith AG, Sonnen JA, Stern RA, Van Deerlin VM, Van Eldik LJ, Harold D, Russo G, Rubinsztein DC, Bayer A, Tsolaki M, Proitsi P, Fox NC, Hampel H, Owen MJ, Mead S, Passmore P, Morgan K, Nöthen MM, Rossor M, Lupton MK, Hoffmann P, Kornhuber J, Lawlor B, McQuillin A, Al-Chalabi A, Bis JC, Ruiz A, Boada M, Seshadri S, Beiser A, Rice K, van der Lee SJ, De Jager PL, Geschwind DH, Riemenschneider M, Riedel-Heller S, Rotter JI, Ransmayr G, Hyman BT, Cruchaga C, Alegret M, Winsvold B, Palta P, Farh KH, Cuenca-Leon E, Furlotte N, Kurth T, Ligthart L, Terwindt GM, Freilinger T, Ran C, Gordon SD, Borck G, Adams HHH, Lehtimäki T, Wedenoja J, Buring JE, Schürks M, Hrafnsdottir M, Hottenga JJ, Penninx B, Artto V, Kaunisto M, Vepsäläinen S, Martin NG, Montgomery GW, Kurki MI, Hämäläinen E, Huang H, Huang J, Sandor C, Webber C, Muller-Myhsok B, Schreiber S, Salomaa V, Loehrer E, Göbel H, Macaya A, Pozo-Rosich P, Hansen T, Werge T, Kaprio J, Metspalu A, Kubisch C, Ferrari MD, Belin AC, van den Maagdenberg AMJM, Zwart JA, Boomsma D, Eriksson N, Olesen J, Chasman DI, Nyholt DR, Avbersek A, Baum L, Berkovic S, Bradfield J, Buono RJ, Catarino CB, Cossette P, De Jonghe P, Depondt C, Dlugos D, Ferraro TN, French J, Hjalgrim H, Jamnadas-Khoda J, Kälviäinen R, Kunz WS, Lerche H, Leu C, Lindhout D, Lo W, Lowenstein D, McCormack M, Møller RS, Molloy A, Ng PW, Oliver K, Privitera M, Radtke R, Ruppert AK, Sander T, Schachter S, Schankin C, Scheffer I, Schoch S, Sisodiya SM, Smith P, Sperling M, Striano P, Surges R, Thomas GN, Visscher F, Whelan CD, Zara F, Heinzen EL, Marson A, Becker F, Stroink H, Zimprich F, Gasser T, Gibbs R, Heutink P, Martinez M, Morris HR, Sharma M, Ryten M, Mok KY, Pulit S, Bevan S, Holliday E, Attia J, Battey T, Boncoraglio G, Thijs V, Chen WM, Mitchell B, Rothwell P, Sharma P, Sudlow C, Vicente A, Markus H, Kourkoulis C, Pera J, Raffeld M, Silliman S, Boraska Perica V, Thornton LM, Huckins LM, William Rayner N, Lewis CM, Gratacos M, Rybakowski F, Keski-Rahkonen A, Raevuori A, Hudson JI, Reichborn-Kjennerud T, Monteleone P, Karwautz A, Mannik K, Baker JH, O'Toole JK, Trace SE, Davis OSP, Helder SG, Ehrlich S, Herpertz-Dahlmann B, Danner UN, van Elburg AA, Clementi M, Forzan M, Docampo E, Lissowska J, Hauser J, Tortorella A, Maj M, Gonidakis F, Tziouvas K, Papezova H, Yilmaz Z, Wagner G, Cohen-Woods S, Herms S, Julià A, Rabionet R, Dick DM, Ripatti S, Andreassen OA, Espeseth T, Lundervold AJ, Steen VM, Pinto D, Scherer SW, Aschauer H, Schosser A, Alfredsson L, Padyukov L, Halmi KA, Mitchell J, Strober M, Bergen AW, Kaye W, Szatkiewicz JP, Cormand B, Ramos-Quiroga JA, Sánchez-Mora C, Ribasés M, Casas M, Hervas A, Arranz MJ, Haavik J, Zayats T, Johansson S, Williams N, Dempfle A, Rothenberger A, Kuntsi J, Oades RD, Banaschewski T, Franke B, Buitelaar JK, Arias Vasquez A, Doyle AE, Reif A, Lesch KP, Freitag C, Rivero O, Palmason H, Romanos M, Langley K, Rietschel M, Witt SH, Dalsgaard S, Børglum AD, Waldman I, Wilmot B, Molly N, Bau CHD, Crosbie J, Schachar R, Loo SK, McGough JJ, Grevet EH, Medland SE, Robinson E, Weiss LA, Bacchelli E, Bailey A, Bal V, Battaglia A, Betancur C, Bolton P, Cantor R, Celestino-Soper P, Dawson G, De Rubeis S, Duque F, Green A, Klauck SM, Leboyer M, Levitt P, Maestrini E, Mane S, De-Luca DM, Parr J, Regan R, Reichenberg A, Sandin S, Vorstman J, Wassink T, Wijsman E, Cook E, Santangelo S, Delorme R, Rogé B, Magalhaes T, Arking D, Schulze TG, Thompson RC, Strohmaier J, Matthews K, Melle I, Morris D, Blackwood D, McIntosh A, Bergen SE, Schalling M, Jamain S, Maaser A, Fischer SB, Reinbold CS, Fullerton JM, Guzman-Parra J, Mayoral F, Schofield PR, Cichon S, Mühleisen TW, Degenhardt F, Schumacher J, Bauer M, Mitchell PB, Gershon ES, Rice J, Potash JB, Zandi PP, Craddock N, Ferrier IN, Alda M, Rouleau GA, Turecki G, Ophoff R, Pato C, Anjorin A, Stahl E, Leber M, Czerski PM, Cruceanu C, Jones IR, Posthuma D, Andlauer TFM, Forstner AJ, Streit F, Baune BT, Air T, Sinnamon G, Wray NR, MacIntyre DJ, Porteous D, Homuth G, Rivera M, Grove J, Middeldorp CM, Hickie I, Pergadia M, Mehta D, Smit JH, Jansen R, de Geus E, Dunn E, Li QS, Nauck M, Schoevers RA, Beekman AT, Knowles JA, Viktorin A, Arnold P, Barr CL, Bedoya-Berrio G, Bienvenu OJ, Brentani H, Burton C, Camarena B, Cappi C, Cath D, Cavallini M, Cusi D, Darrow S, Denys D, Derks EM, Dietrich A, Fernandez T, Figee M, Freimer N, Gerber G, Grados M, Greenberg E, Hanna GL, Hartmann A, Hirschtritt ME, Hoekstra PJ, Huang A, Huyser C, Illmann C, Jenike M, Kuperman S, Leventhal B, Lochner C, Lyon GJ, Macciardi F, Madruga-Garrido M, Malaty IA, Maras A, McGrath L, Miguel EC, Mir P, Nestadt G, Nicolini H, Okun MS, Pakstis A, Paschou P, Piacentini J, Pittenger C, Plessen K, Ramensky V, Ramos EM, Reus V, Richter MA, Riddle MA, Robertson MM, Roessner V, Rosário M, Samuels JF, Sandor P, Stein DJ, Tsetsos F, Van Nieuwerburgh F, Weatherall S, Wendland JR, Wolanczyk T, Worbe Y, Zai G, Goes FS, McLaughlin N, Nestadt PS, Grabe HJ, Depienne C, Konkashbaev A, Lanzagorta N, Valencia-Duarte A, Bramon E, Buccola N, Cahn W, Cairns M, Chong SA, Cohen D, Crespo-Facorro B, Crowley J, Davidson M, DeLisi L, Dinan T, Donohoe G, Drapeau E, Duan J, Haan L, Hougaard D, Karachanak-Yankova S, Khrunin A, Klovins J, Kučinskas V, Lee Chee Keong J, Limborska S, Loughland C, Lönnqvist J, Maher B, Mattheisen M, McDonald C, Murphy KC, Nenadic I, van Os J, Pantelis C, Pato M, Petryshen T, Quested D, Roussos P, Sanders AR, Schall U, Schwab SG, Sim K, So HC, Stögmann E, Subramaniam M, Toncheva D, Waddington J, Walters J, Weiser M, Cheng W, Cloninger R, Curtis D, Gejman PV, Henskens F, Mattingsdal M, Oh SY, Scott R, Webb B, Breen G, Churchhouse C, Bulik CM, Daly M, Dichgans M, Faraone SV, Guerreiro R, Holmans P, Kendler KS, Koeleman B, Mathews CA, Price A, Scharf J, Sklar P, Williams J, Wood NW, Cotsapas C, Palotie A, Smoller JW, Sullivan P, Rosand J, Corvin A, Neale BM, Schott JM, Anney R, Elia J, Grigoroiu-Serbanescu M, Edenberg HJ, Murray R. Analysis of shared heritability in common disorders of the brain. Science 2018; 360:eaap8757. [PMID: 29930110 PMCID: PMC6097237 DOI: 10.1126/science.aap8757] [Citation(s) in RCA: 847] [Impact Index Per Article: 141.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2016] [Revised: 02/07/2017] [Accepted: 04/24/2018] [Indexed: 01/01/2023]
Abstract
Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.
Collapse
|
22
|
Janouschek H, Eickhoff CR, Mühleisen TW, Eickhoff SB, Nickl-Jockschat T. Using coordinate-based meta-analyses to explore structural imaging genetics. Brain Struct Funct 2018; 223:3045-3061. [PMID: 29730826 DOI: 10.1007/s00429-018-1670-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Accepted: 04/19/2018] [Indexed: 12/29/2022]
Abstract
Imaging genetics has become a highly popular approach in the field of schizophrenia research. A frequently reported finding is that effects from common genetic variation are associated with a schizophrenia-related structural endophenotype. Genetic contributions to a structural endophenotype may be easier to delineate, when referring to biological rather than diagnostic criteria. We used coordinate-based meta-analyses, namely the anatomical likelihood estimation (ALE) algorithm on 30 schizophrenia-related imaging genetics studies, representing 44 single-nucleotide polymorphisms at 26 gene loci investigated in 4682 subjects. To test whether analyses based on biological information would improve the convergence of results, gene ontology (GO) terms were used to group the findings from the published studies. We did not find any significant results for the main contrast. However, our analysis enrolling studies on genotype × diagnosis interaction yielded two clusters in the left temporal lobe and the medial orbitofrontal cortex. All other subanalyses did not yield any significant results. To gain insight into possible biological relationships between the genes implicated by these clusters, we mapped five of them to GO terms of the category "biological process" (AKT1, CNNM2, DISC1, DTNBP1, VAV3), then five to "cellular component" terms (AKT1, CNNM2, DISC1, DTNBP1, VAV3), and three to "molecular function" terms (AKT1, VAV3, ZNF804A). A subsequent cluster analysis identified representative, non-redundant subsets of semantically similar terms that aided a further interpretation. We regard this approach as a new option to systematically explore the richness of the literature in imaging genetics.
Collapse
|
23
|
Mühleisen TW, Reinbold CS, Forstner AJ, Abramova LI, Alda M, Babadjanova G, Bauer M, Brennan P, Chuchalin A, Cruceanu C, Czerski PM, Degenhardt F, Fischer SB, Fullerton JM, Gordon SD, Grigoroiu-Serbanescu M, Grof P, Hauser J, Hautzinger M, Herms S, Hoffmann P, Kammerer-Ciernioch J, Khusnutdinova E, Kogevinas M, Krasnov V, Lacour A, Laprise C, Leber M, Lissowska J, Lucae S, Maaser A, Maier W, Martin NG, Mattheisen M, Mayoral F, McKay JD, Medland SE, Mitchell PB, Moebus S, Montgomery GW, Müller-Myhsok B, Oruc L, Pantelejeva G, Pfennig A, Pojskic L, Polonikov A, Reif A, Rivas F, Rouleau GA, Schenk LM, Schofield PR, Schwarz M, Streit F, Strohmaier J, Szeszenia-Dabrowska N, Tiganov AS, Treutlein J, Turecki G, Vedder H, Witt SH, Schulze TG, Rietschel M, Nöthen MM, Cichon S. Gene set enrichment analysis and expression pattern exploration implicate an involvement of neurodevelopmental processes in bipolar disorder. J Affect Disord 2018; 228:20-25. [PMID: 29197740 DOI: 10.1016/j.jad.2017.11.068] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Revised: 10/20/2017] [Accepted: 11/12/2017] [Indexed: 11/22/2022]
Abstract
BACKGROUND Bipolar disorder (BD) is a common and highly heritable disorder of mood. Genome-wide association studies (GWAS) have identified several independent susceptibility loci. In order to extract more biological information from GWAS data, multi-locus approaches represent powerful tools since they utilize knowledge about biological processes to integrate functional sets of genes at strongly to moderately associated loci. METHODS We conducted gene set enrichment analyses (GSEA) using 2.3 million single-nucleotide polymorphisms, 397 Reactome pathways and 24,025 patients with BD and controls. RNA expression of implicated individual genes and gene sets were examined in post-mortem brains across lifespan. RESULTS Two pathways showed a significant enrichment after correction for multiple comparisons in the GSEA: GRB2 events in ERBB2 signaling, for which 6 of 21 genes were BD associated (PFDR = 0.0377), and NCAM signaling for neurite out-growth, for which 11 out of 62 genes were BD associated (PFDR = 0.0451). Most pathway genes showed peaks of RNA co-expression during fetal development and infancy and mapped to neocortical areas and parts of the limbic system. LIMITATIONS Pathway associations were technically reproduced by two methods, although they were not formally replicated in independent samples. Gene expression was explored in controls but not in patients. CONCLUSIONS Pathway analysis in large GWAS data of BD and follow-up of gene expression patterns in healthy brains provide support for an involvement of neurodevelopmental processes in the etiology of this neuropsychiatric disease. Future studies are required to further evaluate the relevance of the implicated genes on pathway functioning and clinical aspects of BD.
Collapse
|
24
|
Bludau S, Mühleisen TW, Eickhoff SB, Hawrylycz MJ, Cichon S, Amunts K. Integration of transcriptomic and cytoarchitectonic data implicates a role for MAOA and TAC1 in the limbic-cortical network. Brain Struct Funct 2018; 223:2335-2342. [PMID: 29478144 PMCID: PMC5968065 DOI: 10.1007/s00429-018-1620-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2017] [Accepted: 01/25/2018] [Indexed: 12/11/2022]
Abstract
Decoding the chain from genes to cognition requires detailed insights how areas with specific gene activities and microanatomical architectures contribute to brain function and dysfunction. The Allen Human Brain Atlas contains regional gene expression data, while the JuBrain Atlas offers three-dimensional cytoarchitectonic maps reflecting interindividual variability. To date, an integrated framework that combines the analytical benefits of both scientific platforms towards a multi-level brain atlas of adult humans was not available. We have, therefore, developed JuGEx, a new method for integrating tissue transcriptome and cytoarchitectonic segregation. We investigated differential gene expression in two JuBrain areas of the frontal pole that we have structurally and functionally characterized in previous studies. Our results show a significant upregulation of MAOA and TAC1 in the medial area frontopolaris which is a node in the limbic-cortical network and known to be susceptible for gray matter loss and behavioral dysfunction in patients with depression. The MAOA gene encodes an enzyme which is involved in the catabolism of dopamine, norepinephrine, serotonin, and other monoaminergic neurotransmitters. The TAC1 locus generates hormones that play a role in neuron excitations and behavioral responses. Overall, JuGEx provides a new tool for the scientific community that empowers research from basic, cognitive and clinical neuroscience in brain regions and disease models with regard to gene expression.
Collapse
|
25
|
Scott RA, Scott LJ, Mägi R, Marullo L, Gaulton KJ, Kaakinen M, Pervjakova N, Pers TH, Johnson AD, Eicher JD, Jackson AU, Ferreira T, Lee Y, Ma C, Steinthorsdottir V, Thorleifsson G, Qi L, Van Zuydam NR, Mahajan A, Chen H, Almgren P, Voight BF, Grallert H, Müller-Nurasyid M, Ried JS, Rayner NW, Robertson N, Karssen LC, van Leeuwen EM, Willems SM, Fuchsberger C, Kwan P, Teslovich TM, Chanda P, Li M, Lu Y, Dina C, Thuillier D, Yengo L, Jiang L, Sparso T, Kestler HA, Chheda H, Eisele L, Gustafsson S, Frånberg M, Strawbridge RJ, Benediktsson R, Hreidarsson AB, Kong A, Sigurðsson G, Kerrison ND, Luan J, Liang L, Meitinger T, Roden M, Thorand B, Esko T, Mihailov E, Fox C, Liu CT, Rybin D, Isomaa B, Lyssenko V, Tuomi T, Couper DJ, Pankow JS, Grarup N, Have CT, Jørgensen ME, Jørgensen T, Linneberg A, Cornelis MC, van Dam RM, Hunter DJ, Kraft P, Sun Q, Edkins S, Owen KR, Perry JRB, Wood AR, Zeggini E, Tajes-Fernandes J, Abecasis GR, Bonnycastle LL, Chines PS, Stringham HM, Koistinen HA, Kinnunen L, Sennblad B, Mühleisen TW, Nöthen MM, Pechlivanis S, Baldassarre D, Gertow K, Humphries SE, Tremoli E, Klopp N, Meyer J, Steinbach G, Wennauer R, Eriksson JG, Mӓnnistö S, Peltonen L, Tikkanen E, Charpentier G, Eury E, Lobbens S, Gigante B, Leander K, McLeod O, Bottinger EP, Gottesman O, Ruderfer D, Blüher M, Kovacs P, Tonjes A, Maruthur NM, Scapoli C, Erbel R, Jöckel KH, Moebus S, de Faire U, Hamsten A, Stumvoll M, Deloukas P, Donnelly PJ, Frayling TM, Hattersley AT, Ripatti S, Salomaa V, Pedersen NL, Boehm BO, Bergman RN, Collins FS, Mohlke KL, Tuomilehto J, Hansen T, Pedersen O, Barroso I, Lannfelt L, Ingelsson E, Lind L, Lindgren CM, Cauchi S, Froguel P, Loos RJF, Balkau B, Boeing H, Franks PW, Barricarte Gurrea A, Palli D, van der Schouw YT, Altshuler D, Groop LC, Langenberg C, Wareham NJ, Sijbrands E, van Duijn CM, Florez JC, Meigs JB, Boerwinkle E, Gieger C, Strauch K, Metspalu A, Morris AD, Palmer CNA, Hu FB, Thorsteinsdottir U, Stefansson K, Dupuis J, Morris AP, Boehnke M, McCarthy MI, Prokopenko I. An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans. Diabetes 2017; 66:2888-2902. [PMID: 28566273 PMCID: PMC5652602 DOI: 10.2337/db16-1253] [Citation(s) in RCA: 456] [Impact Index Per Article: 65.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Accepted: 05/21/2017] [Indexed: 12/12/2022]
Abstract
To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.
Collapse
|