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1.  Genomic study in Mexicans identifies a new locus for triglycerides and refines European lipid loci 
Journal of medical genetics  2013;50(5):298-308.
Background
The Mexican population and others with Amerindian heritage exhibit a substantial predisposition to dyslipidemias and coronary heart disease. Yet, these populations remain underinvestigated by genomic studies, and to date, no genome-wide association (GWA) studies have been reported for lipids in these rapidly expanding populations.
Methods and Findings
We performed a two-stage GWA study for hypertriglyceridemia and low high-density lipoprotein cholesterol (HDL-C) in Mexicans (n=4,361) and identified a novel Mexican-specific genome-wide significant locus for serum triglycerides (TGs) near the Niemann-Pick type C1 protein (NPC1) gene (P=2.43×10−08). Furthermore, three European loci for TGs (APOA5, GCKR, and LPL) and four loci for HDL-C (ABCA1, CETP, LIPC and LOC55908) reached genome-wide significance in Mexicans. We utilized cross-ethnic mapping to narrow three European TG GWA loci, APOA5, MLXIPL, and CILP2 that were wide and contained multiple candidate variants in the European scan. At the APOA5 locus, this reduced the most likely susceptibility variants to one, rs964184. Importantly, our functional analysis demonstrated a direct link between rs964184 and postprandial serum apoAV protein levels, supporting rs964184 as the causative variant underlying the European and Mexican GWA signal. Overall, 52 of the 100 reported associations from European lipid GWA meta-analysis generalized to Mexicans. However, in 82 of the 100 European GWA loci, a different variant other than the European lead/best-proxy variant had the strongest regional evidence of association in Mexicans.
Conclusions
This first Mexican GWA study of lipids identified a novel GWA locus for high TG levels; utilized the inter-population heterogeneity to significantly restrict three previously known European GWA signals; and surveyed whether the European lipid GWA SNPs extend to the Mexican population.
doi:10.1136/jmedgenet-2012-101461
PMCID: PMC3917605  PMID: 23505323
2.  Multiple recurrent de novo copy number variations (CNVs), including duplications of the 7q11.23 Williams-Beuren syndrome region, are strongly associated with autism 
Neuron  2011;70(5):863-885.
Summary
Given prior evidence for the contribution of rare copy number variations (CNVs) to autism spectrum disorders (ASD), we studied these events in 4,457 individuals from 1,174 simplex families, composed of parents, a proband and, in most kindreds, an unaffected sibling. We find significant association of ASD with de novo duplications of 7q11.23, where the reciprocal deletion causes Williams-Beuren syndrome, featuring a highly social personality. We identify rare recurrent de novo CNVs at five additional regions including two novel ASD loci, 16p13.2 (including the genes USP7 and C16orf72) and Cadherin13, and implement a rigorous new approach to evaluating the statistical significance of these observations. Overall, we find large de novo CNVs carry substantial risk (OR=3.55; CI =2.16-7.46, p=6.9 × 10−6); estimate the presence of 130-234 distinct ASD-related CNV intervals across the genome; and, based on data from multiple studies, present compelling evidence for the association of rare de novo events at 7q11.23, 15q11.2-13.1, 16p11.2, and Neurexin1.
doi:10.1016/j.neuron.2011.05.002
PMCID: PMC3939065  PMID: 21658581
3.  Replication of linkage at chromosome 20p13 and identification of suggestive sex-differential risk loci for autism spectrum disorder 
Molecular Autism  2014;5:13.
Background
Autism spectrum disorders (ASDs) are male-biased and genetically heterogeneous. While sequencing of sporadic cases has identified de novo risk variants, the heritable genetic contribution and mechanisms driving the male bias are less understood. Here, we aimed to identify familial and sex-differential risk loci in the largest available, uniformly ascertained, densely genotyped sample of multiplex ASD families from the Autism Genetics Resource Exchange (AGRE), and to compare results with earlier findings from AGRE.
Methods
From a total sample of 1,008 multiplex families, we performed genome-wide, non-parametric linkage analysis in a discovery sample of 847 families, and separately on subsets of families with only male, affected children (male-only, MO) or with at least one female, affected child (female-containing, FC). Loci showing evidence for suggestive linkage (logarithm of odds ≥2.2) in this discovery sample, or in previous AGRE samples, were re-evaluated in an extension study utilizing all 1,008 available families. For regions with genome-wide significant linkage signal in the discovery stage, those families not included in the corresponding discovery sample were then evaluated for independent replication of linkage. Association testing of common single nucleotide polymorphisms (SNPs) was also performed within suggestive linkage regions.
Results
We observed an independent replication of previously observed linkage at chromosome 20p13 (P < 0.01), while loci at 6q27 and 8q13.2 showed suggestive linkage in our extended sample. Suggestive sex-differential linkage was observed at 1p31.3 (MO), 8p21.2 (FC), and 8p12 (FC) in our discovery sample, and the MO signal at 1p31.3 was supported in our expanded sample. No sex-differential signals met replication criteria, and no common SNPs were significantly associated with ASD within any identified linkage regions.
Conclusions
With few exceptions, analyses of subsets of families from the AGRE cohort identify different risk loci, consistent with extreme locus heterogeneity in ASD. Large samples appear to yield more consistent results, and sex-stratified analyses facilitate the identification of sex-differential risk loci, suggesting that linkage analyses in large cohorts are useful for identifying heritable risk loci. Additional work, such as targeted re-sequencing, is needed to identify the specific variants within these loci that are responsible for increasing ASD risk.
doi:10.1186/2040-2392-5-13
PMCID: PMC3942516  PMID: 24533643
Male brain; Sex differences; Intermediate phenotype; Linkage analysis; Association; AGRE
4.  The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data 
Thompson, Paul M. | Stein, Jason L. | Medland, Sarah E. | Hibar, Derrek P. | Vasquez, Alejandro Arias | Renteria, Miguel E. | Toro, Roberto | Jahanshad, Neda | Schumann, Gunter | Franke, Barbara | Wright, Margaret J. | Martin, Nicholas G. | Agartz, Ingrid | Alda, Martin | Alhusaini, Saud | Almasy, Laura | Almeida, Jorge | Alpert, Kathryn | Andreasen, Nancy C. | Andreassen, Ole A. | Apostolova, Liana G. | Appel, Katja | Armstrong, Nicola J. | Aribisala, Benjamin | Bastin, Mark E. | Bauer, Michael | Bearden, Carrie E. | Bergmann, Ørjan | Binder, Elisabeth B. | Blangero, John | Bockholt, Henry J. | Bøen, Erlend | Bois, Catherine | Boomsma, Dorret I. | Booth, Tom | Bowman, Ian J. | Bralten, Janita | Brouwer, Rachel M. | Brunner, Han G. | Brohawn, David G. | Buckner, Randy L. | Buitelaar, Jan | Bulayeva, Kazima | Bustillo, Juan R. | Calhoun, Vince D. | Cannon, Dara M. | Cantor, Rita M. | Carless, Melanie A. | Caseras, Xavier | Cavalleri, Gianpiero L. | Chakravarty, M. Mallar | Chang, Kiki D. | Ching, Christopher R. K. | Christoforou, Andrea | Cichon, Sven | Clark, Vincent P. | Conrod, Patricia | Coppola, Giovanni | Crespo-Facorro, Benedicto | Curran, Joanne E. | Czisch, Michael | Deary, Ian J. | de Geus, Eco J. C. | den Braber, Anouk | Delvecchio, Giuseppe | Depondt, Chantal | de Haan, Lieuwe | de Zubicaray, Greig I. | Dima, Danai | Dimitrova, Rali | Djurovic, Srdjan | Dong, Hongwei | Donohoe, Gary | Duggirala, Ravindranath | Dyer, Thomas D. | Ehrlich, Stefan | Ekman, Carl Johan | Elvsåshagen, Torbjørn | Emsell, Louise | Erk, Susanne | Espeseth, Thomas | Fagerness, Jesen | Fears, Scott | Fedko, Iryna | Fernández, Guillén | Fisher, Simon E. | Foroud, Tatiana | Fox, Peter T. | Francks, Clyde | Frangou, Sophia | Frey, Eva Maria | Frodl, Thomas | Frouin, Vincent | Garavan, Hugh | Giddaluru, Sudheer | Glahn, David C. | Godlewska, Beata | Goldstein, Rita Z. | Gollub, Randy L. | Grabe, Hans J. | Grimm, Oliver | Gruber, Oliver | Guadalupe, Tulio | Gur, Raquel E. | Gur, Ruben C. | Göring, Harald H. H. | Hagenaars, Saskia | Hajek, Tomas | Hall, Geoffrey B. | Hall, Jeremy | Hardy, John | Hartman, Catharina A. | Hass, Johanna | Hatton, Sean N. | Haukvik, Unn K. | Hegenscheid, Katrin | Heinz, Andreas | Hickie, Ian B. | Ho, Beng-Choon | Hoehn, David | Hoekstra, Pieter J. | Hollinshead, Marisa | Holmes, Avram J. | Homuth, Georg | Hoogman, Martine | Hong, L. Elliot | Hosten, Norbert | Hottenga, Jouke-Jan | Hulshoff Pol, Hilleke E. | Hwang, Kristy S. | Jack, Clifford R. | Jenkinson, Mark | Johnston, Caroline | Jönsson, Erik G. | Kahn, René S. | Kasperaviciute, Dalia | Kelly, Sinead | Kim, Sungeun | Kochunov, Peter | Koenders, Laura | Krämer, Bernd | Kwok, John B. J. | Lagopoulos, Jim | Laje, Gonzalo | Landen, Mikael | Landman, Bennett A. | Lauriello, John | Lawrie, Stephen M. | Lee, Phil H. | Le Hellard, Stephanie | Lemaître, Herve | Leonardo, Cassandra D. | Li, Chiang-shan | Liberg, Benny | Liewald, David C. | Liu, Xinmin | Lopez, Lorna M. | Loth, Eva | Lourdusamy, Anbarasu | Luciano, Michelle | Macciardi, Fabio | Machielsen, Marise W. J. | MacQueen, Glenda M. | Malt, Ulrik F. | Mandl, René | Manoach, Dara S. | Martinot, Jean-Luc | Matarin, Mar | Mather, Karen A. | Mattheisen, Manuel | Mattingsdal, Morten | Meyer-Lindenberg, Andreas | McDonald, Colm | McIntosh, Andrew M. | McMahon, Francis J. | McMahon, Katie L. | Meisenzahl, Eva | Melle, Ingrid | Milaneschi, Yuri | Mohnke, Sebastian | Montgomery, Grant W. | Morris, Derek W. | Moses, Eric K. | Mueller, Bryon A. | Muñoz Maniega, Susana | Mühleisen, Thomas W. | Müller-Myhsok, Bertram | Mwangi, Benson | Nauck, Matthias | Nho, Kwangsik | Nichols, Thomas E. | Nilsson, Lars-Göran | Nugent, Allison C. | Nyberg, Lars | Olvera, Rene L. | Oosterlaan, Jaap | Ophoff, Roel A. | Pandolfo, Massimo | Papalampropoulou-Tsiridou, Melina | Papmeyer, Martina | Paus, Tomas | Pausova, Zdenka | Pearlson, Godfrey D. | Penninx, Brenda W. | Peterson, Charles P. | Pfennig, Andrea | Phillips, Mary | Pike, G. Bruce | Poline, Jean-Baptiste | Potkin, Steven G. | Pütz, Benno | Ramasamy, Adaikalavan | Rasmussen, Jerod | Rietschel, Marcella | Rijpkema, Mark | Risacher, Shannon L. | Roffman, Joshua L. | Roiz-Santiañez, Roberto | Romanczuk-Seiferth, Nina | Rose, Emma J. | Royle, Natalie A. | Rujescu, Dan | Ryten, Mina | Sachdev, Perminder S. | Salami, Alireza | Satterthwaite, Theodore D. | Savitz, Jonathan | Saykin, Andrew J. | Scanlon, Cathy | Schmaal, Lianne | Schnack, Hugo G. | Schork, Andrew J. | Schulz, S. Charles | Schür, Remmelt | Seidman, Larry | Shen, Li | Shoemaker, Jody M. | Simmons, Andrew | Sisodiya, Sanjay M. | Smith, Colin | Smoller, Jordan W. | Soares, Jair C. | Sponheim, Scott R. | Sprooten, Emma | Starr, John M. | Steen, Vidar M. | Strakowski, Stephen | Strike, Lachlan | Sussmann, Jessika | Sämann, Philipp G. | Teumer, Alexander | Toga, Arthur W. | Tordesillas-Gutierrez, Diana | Trabzuni, Daniah | Trost, Sarah | Turner, Jessica | Van den Heuvel, Martijn | van der Wee, Nic J. | van Eijk, Kristel | van Erp, Theo G. M. | van Haren, Neeltje E. M. | van ‘t Ent, Dennis | van Tol, Marie-Jose | Valdés Hernández, Maria C. | Veltman, Dick J. | Versace, Amelia | Völzke, Henry | Walker, Robert | Walter, Henrik | Wang, Lei | Wardlaw, Joanna M. | Weale, Michael E. | Weiner, Michael W. | Wen, Wei | Westlye, Lars T. | Whalley, Heather C. | Whelan, Christopher D. | White, Tonya | Winkler, Anderson M. | Wittfeld, Katharina | Woldehawariat, Girma | Wolf, Christiane | Zilles, David | Zwiers, Marcel P. | Thalamuthu, Anbupalam | Schofield, Peter R. | Freimer, Nelson B. | Lawrence, Natalia S. | Drevets, Wayne
Brain Imaging and Behavior  2014;8:153-182.
The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA’s first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
doi:10.1007/s11682-013-9269-5
PMCID: PMC4008818  PMID: 24399358
Genetics; MRI; GWAS; Consortium; Meta-analysis; Multi-site
5.  Systems Biology of the Vervet Monkey 
ILAR Journal  2013;54(2):122-143.
Nonhuman primates (NHP) provide crucial biomedical model systems intermediate between rodents and humans. The vervet monkey (also called the African green monkey) is a widely used NHP model that has unique value for genetic and genomic investigations of traits relevant to human diseases. This article describes the phylogeny and population history of the vervet monkey and summarizes the use of both captive and wild vervet monkeys in biomedical research. It also discusses the effort of an international collaboration to develop the vervet monkey as the most comprehensively phenotypically and genomically characterized NHP, a process that will enable the scientific community to employ this model for systems biology investigations.
doi:10.1093/ilar/ilt049
PMCID: PMC3814400  PMID: 24174437
African green monkey; genetics; genomics; phenomics; simian immunodeficiency virus [SIV]; systems biology; transcriptomics; vervet
6.  Preferential Binding to Elk-1 by SLE-Associated IL10 Risk Allele Upregulates IL10 Expression 
PLoS Genetics  2013;9(10):e1003870.
Immunoregulatory cytokine interleukin-10 (IL-10) is elevated in sera from patients with systemic lupus erythematosus (SLE) correlating with disease activity. The established association of IL10 with SLE and other autoimmune diseases led us to fine map causal variant(s) and to explore underlying mechanisms. We assessed 19 tag SNPs, covering the IL10 gene cluster including IL19, IL20 and IL24, for association with SLE in 15,533 case and control subjects from four ancestries. The previously reported IL10 variant, rs3024505 located at 1 kb downstream of IL10, exhibited the strongest association signal and was confirmed for association with SLE in European American (EA) (P = 2.7×10−8, OR = 1.30), but not in non-EA ancestries. SNP imputation conducted in EA dataset identified three additional SLE-associated SNPs tagged by rs3024505 (rs3122605, rs3024493 and rs3024495 located at 9.2 kb upstream, intron 3 and 4 of IL10, respectively), and SLE-risk alleles of these SNPs were dose-dependently associated with elevated levels of IL10 mRNA in PBMCs and circulating IL-10 protein in SLE patients and controls. Using nuclear extracts of peripheral blood cells from SLE patients for electrophoretic mobility shift assays, we identified specific binding of transcription factor Elk-1 to oligodeoxynucleotides containing the risk (G) allele of rs3122605, suggesting rs3122605 as the most likely causal variant regulating IL10 expression. Elk-1 is known to be activated by phosphorylation and nuclear localization to induce transcription. Of interest, phosphorylated Elk-1 (p-Elk-1) detected only in nuclear extracts of SLE PBMCs appeared to increase with disease activity. Co-expression levels of p-Elk-1 and IL-10 were elevated in SLE T, B cells and monocytes, associated with increased disease activity in SLE B cells, and were best downregulated by ERK inhibitor. Taken together, our data suggest that preferential binding of activated Elk-1 to the IL10 rs3122605-G allele upregulates IL10 expression and confers increased risk for SLE in European Americans.
Author Summary
Systemic lupus erythematosus (SLE), a debilitating autoimmune disease characterized by the production of pathogenic autoantibodies, has a strong genetic basis. Variants of the IL10 gene, which encodes cytokine interleukin-10 (IL-10) with known function of promoting B cell hyperactivity and autoantibody production, are associated with SLE and other autoimmune diseases, and serum IL-10 levels are elevated in SLE patients correlating with increased disease activity. In this study, to discover SLE-predisposing causal variant(s), we assessed variants within the genomic region containing IL10 and its gene family member IL19, IL20 and IL24 for association with SLE in case and control subjects from diverse ancestries. We identified SLE-associated SNP rs3122605 located at 9.2 kb upstream of IL10 as the most likely causal variant in subjects of European ancestry. The SLE-risk allele of rs3122605 was dose-dependently associated with elevated IL10 expression at both mRNA and protein levels in peripheral blood samples from SLE patients and controls, which could be explained, at least in part, by its preferential binding to Elk-1, a transcription factor activated in B cells during active disease of SLE patients. Elk-1-mediated IL-10 overexpression could be downregulated by inhibiting activation of mitogen-activated protein kinases, suggesting a potential therapeutic target for SLE.
doi:10.1371/journal.pgen.1003870
PMCID: PMC3794920  PMID: 24130510
7.  A non-human primate system for large-scale genetic studies of complex traits 
Human Molecular Genetics  2012;21(15):3307-3316.
Non-human primates provide genetic model systems biologically intermediate between humans and other mammalian model organisms. Populations of Caribbean vervet monkeys (Chlorocebus aethiops sabaeus) are genetically homogeneous and large enough to permit well-powered genetic mapping studies of quantitative traits relevant to human health, including expression quantitative trait loci (eQTL). Previous transcriptome-wide investigation in an extended vervet pedigree identified 29 heritable transcripts for which levels of expression in peripheral blood correlate strongly with expression levels in the brain. Quantitative trait linkage analysis using 261 microsatellite markers identified significant (n = 8) and suggestive (n = 4) linkages for 12 of these transcripts, including both cis- and trans-eQTL. Seven transcripts, located on different chromosomes, showed maximum linkage to markers in a single region of vervet chromosome 9; this observation suggests the possibility of a master trans-regulator locus in this region. For one cis-eQTL (at B3GALTL, beta-1,3-glucosyltransferase), we conducted follow-up single nucleotide polymorphism genotyping and fine-scale association analysis in a sample of unrelated Caribbean vervets, localizing this eQTL to a region of <200 kb. These results suggest the value of pedigree and population samples of the Caribbean vervet for linkage and association mapping studies of quantitative traits. The imminent whole genome sequencing of many of these vervet samples will enhance the power of such investigations by providing a comprehensive catalog of genetic variation.
doi:10.1093/hmg/dds160
PMCID: PMC3392106  PMID: 22556363
8.  Stratification Based on Language-Related Endophenotypes in Autism: Attempt to Replicate Reported Linkage 
The identification of autism susceptibility genes has been hampered by phenotypic heterogeneity of autism, among other factors. However, the use of endophenotypes has shown preliminary success in reducing heterogeneity and identifying potential autism-related susceptibility regions. To further explore the utility of using language related endophenotypes, we performed linkage analysis on multiplex autism families stratified according to delayed expressive speech and also assessed the extent to which parental phenotype information would aid in identifying regions of linkage. A whole genome scan using a multipoint nonparametric linkage approach was performed in 133 families, stratifying the sample by phrase speech delay and word delay. None of the regions reached suggested genome-wide or replication significance thresholds. However, several loci on chromosomes 1, 2, 4, 6, 7, 8, 9, 10, 12, 15, and 19 yielded nominally higher linkage signals in the delayed groups. The results did not support reported linkage findings for loci on chromosomes 7 or 13 that were a result of stratification based on the language delay endophenotype. In addition, inclusion of information on parental history of language delay did not appreciably affect the linkage results. The nominal increase in NPL scores across several regions using language delay endophenotypes for stratification suggests that this strategy may be useful in attenuating heterogeneity. However, the inconsistencies in regions identified across studies highlight the importance of increasing sample sizes to provide adequate power to test replications in independent samples.
doi:10.1002/ajmg.b.30329
PMCID: PMC3653581  PMID: 16752361
Autism; linkage; endophenotypes; language; AGRE
9.  Identification of common variants associated with human hippocampal and intracranial volumes 
Stein, Jason L | Medland, Sarah E | Vasquez, Alejandro Arias | Hibar, Derrek P | Senstad, Rudy E | Winkler, Anderson M | Toro, Roberto | Appel, Katja | Bartecek, Richard | Bergmann, Ørjan | Bernard, Manon | Brown, Andrew A | Cannon, Dara M | Chakravarty, M Mallar | Christoforou, Andrea | Domin, Martin | Grimm, Oliver | Hollinshead, Marisa | Holmes, Avram J | Homuth, Georg | Hottenga, Jouke-Jan | Langan, Camilla | Lopez, Lorna M | Hansell, Narelle K | Hwang, Kristy S | Kim, Sungeun | Laje, Gonzalo | Lee, Phil H | Liu, Xinmin | Loth, Eva | Lourdusamy, Anbarasu | Mattingsdal, Morten | Mohnke, Sebastian | Maniega, Susana Muñoz | Nho, Kwangsik | Nugent, Allison C | O’Brien, Carol | Papmeyer, Martina | Pütz, Benno | Ramasamy, Adaikalavan | Rasmussen, Jerod | Rijpkema, Mark | Risacher, Shannon L | Roddey, J Cooper | Rose, Emma J | Ryten, Mina | Shen, Li | Sprooten, Emma | Strengman, Eric | Teumer, Alexander | Trabzuni, Daniah | Turner, Jessica | van Eijk, Kristel | van Erp, Theo G M | van Tol, Marie-Jose | Wittfeld, Katharina | Wolf, Christiane | Woudstra, Saskia | Aleman, Andre | Alhusaini, Saud | Almasy, Laura | Binder, Elisabeth B | Brohawn, David G | Cantor, Rita M | Carless, Melanie A | Corvin, Aiden | Czisch, Michael | Curran, Joanne E | Davies, Gail | de Almeida, Marcio A A | Delanty, Norman | Depondt, Chantal | Duggirala, Ravi | Dyer, Thomas D | Erk, Susanne | Fagerness, Jesen | Fox, Peter T | Freimer, Nelson B | Gill, Michael | Göring, Harald H H | Hagler, Donald J | Hoehn, David | Holsboer, Florian | Hoogman, Martine | Hosten, Norbert | Jahanshad, Neda | Johnson, Matthew P | Kasperaviciute, Dalia | Kent, Jack W | Kochunov, Peter | Lancaster, Jack L | Lawrie, Stephen M | Liewald, David C | Mandl, René | Matarin, Mar | Mattheisen, Manuel | Meisenzahl, Eva | Melle, Ingrid | Moses, Eric K | Mühleisen, Thomas W | Nauck, Matthias | Nöthen, Markus M | Olvera, Rene L | Pandolfo, Massimo | Pike, G Bruce | Puls, Ralf | Reinvang, Ivar | Rentería, Miguel E | Rietschel, Marcella | Roffman, Joshua L | Royle, Natalie A | Rujescu, Dan | Savitz, Jonathan | Schnack, Hugo G | Schnell, Knut | Seiferth, Nina | Smith, Colin | Steen, Vidar M | Valdés Hernández, Maria C | Van den Heuvel, Martijn | van der Wee, Nic J | Van Haren, Neeltje E M | Veltman, Joris A | Völzke, Henry | Walker, Robert | Westlye, Lars T | Whelan, Christopher D | Agartz, Ingrid | Boomsma, Dorret I | Cavalleri, Gianpiero L | Dale, Anders M | Djurovic, Srdjan | Drevets, Wayne C | Hagoort, Peter | Hall, Jeremy | Heinz, Andreas | Jack, Clifford R | Foroud, Tatiana M | Le Hellard, Stephanie | Macciardi, Fabio | Montgomery, Grant W | Poline, Jean Baptiste | Porteous, David J | Sisodiya, Sanjay M | Starr, John M | Sussmann, Jessika | Toga, Arthur W | Veltman, Dick J | Walter, Henrik | Weiner, Michael W | Bis, Joshua C | Ikram, M Arfan | Smith, Albert V | Gudnason, Vilmundur | Tzourio, Christophe | Vernooij, Meike W | Launer, Lenore J | DeCarli, Charles | Seshadri, Sudha | Andreassen, Ole A | Apostolova, Liana G | Bastin, Mark E | Blangero, John | Brunner, Han G | Buckner, Randy L | Cichon, Sven | Coppola, Giovanni | de Zubicaray, Greig I | Deary, Ian J | Donohoe, Gary | de Geus, Eco J C | Espeseth, Thomas | Fernández, Guillén | Glahn, David C | Grabe, Hans J | Hardy, John | Hulshoff Pol, Hilleke E | Jenkinson, Mark | Kahn, René S | McDonald, Colm | McIntosh, Andrew M | McMahon, Francis J | McMahon, Katie L | Meyer-Lindenberg, Andreas | Morris, Derek W | Müller-Myhsok, Bertram | Nichols, Thomas E | Ophoff, Roel A | Paus, Tomas | Pausova, Zdenka | Penninx, Brenda W | Potkin, Steven G | Sämann, Philipp G | Saykin, Andrew J | Schumann, Gunter | Smoller, Jordan W | Wardlaw, Joanna M | Weale, Michael E | Martin, Nicholas G | Franke, Barbara | Wright, Margaret J | Thompson, Paul M
Nature genetics  2012;44(5):552-561.
Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer’s disease1,2 and is reduced in schizophrenia3, major depression4 and mesial temporal lobe epilepsy5. Whereas many brain imaging phenotypes are highly heritable6,7, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10−16) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10−12). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10−7).
doi:10.1038/ng.2250
PMCID: PMC3635491  PMID: 22504417
10.  Transcriptomic Analysis of Autistic Brain Reveals Convergent Molecular Pathology 
Nature  2011;474(7351):380-384.
Autism spectrum disorder (ASD) is a common, highly heritable neuro-developmental condition characterized by marked genetic heterogeneity1–3. Thus, a fundamental question is whether autism represents an etiologically heterogeneous disorder in which the myriad genetic or environmental risk factors perturb common underlying molecular pathways in the brain4. Here, we demonstrate consistent differences in transcriptome organization between autistic and normal brain by gene co-expression network analysis. Remarkably, regional patterns of gene expression that typically distinguish frontal and temporal cortex are significantly attenuated in the ASD brain, suggesting abnormalities in cortical patterning. We further identify discrete modules of co-expressed genes associated with autism: a neuronal module enriched for known autism susceptibility genes, including the neuronal specific splicing factor A2BP1/FOX1, and a module enriched for immune genes and glial markers. Using high-throughput RNA-sequencing we demonstrate dysregulated splicing of A2BP1-dependent alternative exons in ASD brain. Moreover, using a published autism GWAS dataset, we show that the neuronal module is enriched for genetically associated variants, providing independent support for the causal involvement of these genes in autism. In contrast, the immune-glial module showed no enrichment for autism GWAS signals, indicating a non-genetic etiology for this process. Collectively, our results provide strong evidence for convergent molecular abnormalities in ASD, and implicate transcriptional and splicing dysregulation as underlying mechanisms of neuronal dysfunction in this disorder.
doi:10.1038/nature10110
PMCID: PMC3607626  PMID: 21614001
11.  Fine Mapping of Xq28: Both MECP2 and IRAK1 Contribute to Risk for Systemic Lupus Erythematosus in Multiple Ancestral Groups 
Annals of the rheumatic diseases  2012;72(3):437-444.
Objectives
The Xq28 region containing IRAK1 and MECP2 has been identified as a risk locus for systemic lupus erythematosus (SLE) in previous genetic association studies. However, due to the strong linkage disequilibrium between IRAK1 and MECP2, it remains unclear which gene is affected by the underlying causal variant(s) conferring risk of SLE.
Methods
We fine-mapped ≥136 SNPs in a ~227kb region on Xq28, containing IRAK1, MECP2 and 7 adjacent genes (L1CAM, AVPR2, ARHGAP4, NAA10, RENBP, HCFC1 and TMEM187), for association with SLE in 15,783 case-control subjects derived from 4 different ancestral groups.
Results
Multiple SNPs showed strong association with SLE in European Americans, Asians and Hispanics at P<5×10−8 with consistent association in subjects with African ancestry. Of these, 6 SNPs located in the TMEM187-IRAK1-MECP2 region captured the underlying causal variant(s) residing in a common risk haplotype shared by all 4 ancestral groups. Among them, rs1059702 best explained the Xq28 association signals in conditional testings and exhibited the strongest P value in trans-ancestral meta-analysis (Pmeta=1.3×10−27, OR=1.43), and thus was considered to be the most-likely causal variant. The risk allele of rs1059702 results in the amino acid substitution S196F in IRAK1 and had previously been shown to increase NF-κB activity in vitro. We also found that the homozygous risk genotype of rs1059702 was associated with lower mRNA levels of MECP2, but not IRAK1, in SLE patients (P=0.0012) and healthy controls (P=0.0064).
Conclusion
These data suggest contributions of both IRAK1 and MECP2 to SLE susceptibility.
doi:10.1136/annrheumdis-2012-201851
PMCID: PMC3567234  PMID: 22904263
Systemic Lupus Erythematosus; Gene Polymorphism; Xq28; IRAK1; MECP2
12.  MicroRNA-3148 Modulates Allelic Expression of Toll-Like Receptor 7 Variant Associated with Systemic Lupus Erythematosus 
PLoS Genetics  2013;9(2):e1003336.
We previously reported that the G allele of rs3853839 at 3′untranslated region (UTR) of Toll-like receptor 7 (TLR7) was associated with elevated transcript expression and increased risk for systemic lupus erythematosus (SLE) in 9,274 Eastern Asians [P = 6.5×10−10, odds ratio (OR) (95%CI) = 1.27 (1.17–1.36)]. Here, we conducted trans-ancestral fine-mapping in 13,339 subjects including European Americans, African Americans, and Amerindian/Hispanics and confirmed rs3853839 as the only variant within the TLR7-TLR8 region exhibiting consistent and independent association with SLE (Pmeta = 7.5×10−11, OR = 1.24 [1.18–1.34]). The risk G allele was associated with significantly increased levels of TLR7 mRNA and protein in peripheral blood mononuclear cells (PBMCs) and elevated luciferase activity of reporter gene in transfected cells. TLR7 3′UTR sequence bearing the non-risk C allele of rs3853839 matches a predicted binding site of microRNA-3148 (miR-3148), suggesting that this microRNA may regulate TLR7 expression. Indeed, miR-3148 levels were inversely correlated with TLR7 transcript levels in PBMCs from SLE patients and controls (R2 = 0.255, P = 0.001). Overexpression of miR-3148 in HEK-293 cells led to significant dose-dependent decrease in luciferase activity for construct driven by TLR7 3′UTR segment bearing the C allele (P = 0.0003). Compared with the G-allele construct, the C-allele construct showed greater than two-fold reduction of luciferase activity in the presence of miR-3148. Reduced modulation by miR-3148 conferred slower degradation of the risk G-allele containing TLR7 transcripts, resulting in elevated levels of gene products. These data establish rs3853839 of TLR7 as a shared risk variant of SLE in 22,613 subjects of Asian, EA, AA, and Amerindian/Hispanic ancestries (Pmeta = 2.0×10−19, OR = 1.25 [1.20–1.32]), which confers allelic effect on transcript turnover via differential binding to the epigenetic factor miR-3148.
Author Summary
Systemic lupus erythematosus (SLE) is a debilitating autoimmune disease contributed to by excessive innate immune activation involving toll-like receptors (TLRs, particularly TLR7/8/9) and type I interferon (IFN) signaling pathways. TLR7 responds against RNA–containing nuclear antigens and activates IFN-α pathway, playing a pivotal role in the development of SLE. While a genomic duplication of Tlr7 promotes lupus-like disease in the Y-linked autoimmune accelerator (Yaa) murine model, the lack of common copy number variations at TLR7 in humans led us to identify a functional single nucleotide polymorphism (SNP), rs3853839 at 3′ UTR of the TLR7 gene, associated with SLE susceptibility in Eastern Asians. In this study, we fine-mapped the TLR7-TLR8 region and confirmed rs3853839 exhibiting the strongest association with SLE in European Americans, African Americans, and Amerindian/Hispanics. Individuals carrying the risk G allele of rs3853839 exhibited increased TLR7 expression at the both mRNA and protein level and decreased transcript degradation. MicroRNA-3148 (miR-3148) downregulated the expression of non-risk allele (C) containing transcripts preferentially, suggesting a likely mechanism for increased TLR7 levels in risk-allele carriers. This trans-ancestral mapping provides evidence for the global association with SLE risk at rs3853839, which resides in a microRNA–gene regulatory site affecting TLR7 expression.
doi:10.1371/journal.pgen.1003336
PMCID: PMC3585142  PMID: 23468661
13.  Support for calcium channel gene defects in autism spectrum disorders 
Molecular Autism  2012;3:18.
Background
Alternation of synaptic homeostasis is a biological process whose disruption might predispose children to autism spectrum disorders (ASD). Calcium channel genes (CCG) contribute to modulating neuronal function and evidence implicating CCG in ASD has been accumulating. We conducted a targeted association analysis of CCG using existing genome-wide association study (GWAS) data and imputation methods in a combined sample of parent/affected child trios from two ASD family collections to explore this hypothesis.
Methods
A total of 2,176 single-nucleotide polymorphisms (SNP) (703 genotyped and 1,473 imputed) covering the genes that encode the α1 subunit proteins of 10 calcium channels were tested for association with ASD in a combined sample of 2,781 parent/affected child trios from 543 multiplex Caucasian ASD families from the Autism Genetics Resource Exchange (AGRE) and 1,651 multiplex and simplex Caucasian ASD families from the Autism Genome Project (AGP). SNP imputation using IMPUTE2 and a combined reference panel from the HapMap3 and the 1,000 Genomes Project increased coverage density of the CCG. Family-based association was tested using the FBAT software which controls for population stratification and accounts for the non-independence of siblings within multiplex families. The level of significance for association was set at 2.3E-05, providing a Bonferroni correction for this targeted 10-gene panel.
Results
Four SNPs in three CCGs were associated with ASD. One, rs10848653, is located in CACNA1C, a gene in which rare de novo mutations are responsible for Timothy syndrome, a Mendelian disorder that features ASD. Two others, rs198538 and rs198545, located in CACN1G, and a fourth, rs5750860, located in CACNA1I, are in CCGs that encode T-type calcium channels, genes with previous ASD associations.
Conclusions
These associations support a role for common CCG SNPs in ASD.
doi:10.1186/2040-2392-3-18
PMCID: PMC3558437  PMID: 23241247
Autism spectrum disorders; Calcium channel genes; Common variants; Imputed SNPs; Association studies
14.  Adipose Co-expression networks across Finns and Mexicans identify novel triglyceride-associated genes 
BMC Medical Genomics  2012;5:61.
Background
High serum triglyceride (TG) levels is an established risk factor for coronary heart disease (CHD). Fat is stored in the form of TGs in human adipose tissue. We hypothesized that gene co-expression networks in human adipose tissue may be correlated with serum TG levels and help reveal novel genes involved in TG regulation.
Methods
Gene co-expression networks were constructed from two Finnish and one Mexican study sample using the blockwiseModules R function in Weighted Gene Co-expression Network Analysis (WGCNA). Overlap between TG-associated networks from each of the three study samples were calculated using a Fisher’s Exact test. Gene ontology was used to determine known pathways enriched in each TG-associated network.
Results
We measured gene expression in adipose samples from two Finnish and one Mexican study sample. In each study sample, we observed a gene co-expression network that was significantly associated with serum TG levels. The TG modules observed in Finns and Mexicans significantly overlapped and shared 34 genes. Seven of the 34 genes (ARHGAP30, CCR1, CXCL16, FERMT3, HCST, RNASET2, SELPG) were identified as the key hub genes of all three TG modules. Furthermore, two of the 34 genes (ARHGAP9, LST1) reside in previous TG GWAS regions, suggesting them as the regional candidates underlying the GWAS signals.
Conclusions
This study presents a novel adipose gene co-expression network with 34 genes significantly correlated with serum TG across populations.
doi:10.1186/1755-8794-5-61
PMCID: PMC3543280  PMID: 23217153
Mexicans; Finns; RNA sequencing; Triglycerides; Adipose tissue; Weighted gene co-expression network analysis
15.  Individual common variants exert weak effects on the risk for autism spectrum disorderspi 
Anney, Richard | Klei, Lambertus | Pinto, Dalila | Almeida, Joana | Bacchelli, Elena | Baird, Gillian | Bolshakova, Nadia | Bölte, Sven | Bolton, Patrick F. | Bourgeron, Thomas | Brennan, Sean | Brian, Jessica | Casey, Jillian | Conroy, Judith | Correia, Catarina | Corsello, Christina | Crawford, Emily L. | de Jonge, Maretha | Delorme, Richard | Duketis, Eftichia | Duque, Frederico | Estes, Annette | Farrar, Penny | Fernandez, Bridget A. | Folstein, Susan E. | Fombonne, Eric | Gilbert, John | Gillberg, Christopher | Glessner, Joseph T. | Green, Andrew | Green, Jonathan | Guter, Stephen J. | Heron, Elizabeth A. | Holt, Richard | Howe, Jennifer L. | Hughes, Gillian | Hus, Vanessa | Igliozzi, Roberta | Jacob, Suma | Kenny, Graham P. | Kim, Cecilia | Kolevzon, Alexander | Kustanovich, Vlad | Lajonchere, Clara M. | Lamb, Janine A. | Law-Smith, Miriam | Leboyer, Marion | Le Couteur, Ann | Leventhal, Bennett L. | Liu, Xiao-Qing | Lombard, Frances | Lord, Catherine | Lotspeich, Linda | Lund, Sabata C. | Magalhaes, Tiago R. | Mantoulan, Carine | McDougle, Christopher J. | Melhem, Nadine M. | Merikangas, Alison | Minshew, Nancy J. | Mirza, Ghazala K. | Munson, Jeff | Noakes, Carolyn | Nygren, Gudrun | Papanikolaou, Katerina | Pagnamenta, Alistair T. | Parrini, Barbara | Paton, Tara | Pickles, Andrew | Posey, David J. | Poustka, Fritz | Ragoussis, Jiannis | Regan, Regina | Roberts, Wendy | Roeder, Kathryn | Roge, Bernadette | Rutter, Michael L. | Schlitt, Sabine | Shah, Naisha | Sheffield, Val C. | Soorya, Latha | Sousa, Inês | Stoppioni, Vera | Sykes, Nuala | Tancredi, Raffaella | Thompson, Ann P. | Thomson, Susanne | Tryfon, Ana | Tsiantis, John | Van Engeland, Herman | Vincent, John B. | Volkmar, Fred | Vorstman, JAS | Wallace, Simon | Wing, Kirsty | Wittemeyer, Kerstin | Wood, Shawn | Zurawiecki, Danielle | Zwaigenbaum, Lonnie | Bailey, Anthony J. | Battaglia, Agatino | Cantor, Rita M. | Coon, Hilary | Cuccaro, Michael L. | Dawson, Geraldine | Ennis, Sean | Freitag, Christine M. | Geschwind, Daniel H. | Haines, Jonathan L. | Klauck, Sabine M. | McMahon, William M. | Maestrini, Elena | Miller, Judith | Monaco, Anthony P. | Nelson, Stanley F. | Nurnberger, John I. | Oliveira, Guiomar | Parr, Jeremy R. | Pericak-Vance, Margaret A. | Piven, Joseph | Schellenberg, Gerard D. | Scherer, Stephen W. | Vicente, Astrid M. | Wassink, Thomas H. | Wijsman, Ellen M. | Betancur, Catalina | Buxbaum, Joseph D. | Cook, Edwin H. | Gallagher, Louise | Gill, Michael | Hallmayer, Joachim | Paterson, Andrew D. | Sutcliffe, James S. | Szatmari, Peter | Vieland, Veronica J. | Hakonarson, Hakon | Devlin, Bernie
Human Molecular Genetics  2012;21(21):4781-4792.
While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.
doi:10.1093/hmg/dds301
PMCID: PMC3471395  PMID: 22843504
16.  Mitochondrial Dysfunction, Oxidative Stress, and Apoptosis Revealed by Proteomic and Transcriptomic Analyses of the Striata in Two Mouse Models of Parkinson’s Disease 
Journal of Proteome Research  2008;7(2):666-677.
The molecular mechanisms underlying the changes in the nigrostriatal pathway in Parkinson’s disease (PD) are not completely understood. Here, we use mass spectrometry and microarrays to study the proteomic and transcriptomic changes in the striatum of two mouse models of PD, induced by the distinct neurotoxins 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and methamphetamine (METH). Proteomic analyses resulted in the identification and relative quantification of 912 proteins with two or more unique peptides and 86 proteins with significant abundance changes following neurotoxin treatment. Similarly, microarray analyses revealed 181 genes with significant changes in mRNA, following neurotoxin treatment. The combined protein and gene list provides a clearer picture of the potential mechanisms underlying neurodegeneration observed in PD. Functional analysis of this combined list revealed a number of significant categories, including mitochondrial dysfunction, oxidative stress response, and apoptosis. These results constitute one of the largest descriptive data sets integrating protein and transcript changes for these neurotoxin models with many similar end point phenotypes but distinct mechanisms.
doi:10.1021/pr070546l
PMCID: PMC3319057  PMID: 18173235
Parkinson’s disease; transcriptomics; proteomics; codon usage; miRNA; mouse model
17.  Familial Aggregation of Hyperemesis Gravidarum 
Objective
This study was undertaken to determine whether there is familial aggregation of Hyperemesis Gravidarum making it a disease amenable to genetic study.
Study Design
Cases with severe nausea and vomiting in a singleton pregnancy treated with intravenous hydration and unaffected friend controls completed a survey regarding family history.
Results
Sisters of women with Hyperemesis Gravidarum have a significantly increased risk of having Hyperemesis Gravidarum themselves (OR=17.3, p=0.005). Cases have a significantly increased risk of having a mother with severe nausea and vomiting; 33% of cases reported an affected mother compared to 7.7% of controls (p<.0001). Cases reported a similar frequency of affected second-degree maternal and paternal relatives (18% maternal lineage, 23% paternal lineage).
Conclusion
There is familial aggregation of Hyperemesis Gravidarum. This study provides strong evidence for a genetic component to hyperemesis gravidarum. Identification of the predisposing gene(s) may determine the cause of this poorly understood disease of pregnancy.
doi:10.1016/j.ajog.2010.09.018
PMCID: PMC3030697  PMID: 20974461
Familial Aggregation; Genetic; Hyperemesis Gravidarum; Nausea; Pregnancy
18.  Detecting Rare Variant Associations: Methods for Testing Haplotypes and Multiallelic Genotypes 
Genetic Epidemiology  2011;35(Suppl 1):S85-S91.
We summarize the work done by the contributors to Group 13 at Genetic Analysis Workshop 17 (GAW17) and provide a synthesis of their data analyses. The Group 13 contributors used a variety of approaches to test associations of both rare variants and common single-nucleotide polymorphisms (SNPs) with the GAW17 simulated traits, implementing analytic methods that incorporate multiallelic genotypes and haplotypes. In addition to using a wide variety of statistical methods and approaches, the contributors exhibited a remarkable amount of flexibility and creativity in coding the variants and their genes and in evaluating their proposed approaches and methods. We describe and contrast their methods along three dimensions: (1) selection and coding of genetic entities for analysis, (2) method of analysis, and (3) evaluation of the results. The contributors consistently presented a strong rationale for using multiallelic analytic approaches. They indicated that power was likely to be increased by capturing the signals of multiple markers within genetic entities defined by sliding windows, haplotypes, genes, functional pathways, and the entire set of SNPs and rare variants taken in aggregate. Despite this variability, the methods were fairly consistent in their ability to identify two associated genes for each simulated trait. The first gene was selected for the largest number of causal alleles and the second for a high-frequency causal SNP. The presumed model of inheritance and choice of genetic entities are likely to have a strong effect on the outcomes of the analyses.
doi:10.1002/gepi.20656
PMCID: PMC3274416  PMID: 22128065
rare variants; sequence data; multiallelic data; Bayesian regression; penalized regression; tree-based clustering; pathway analysis; haplotypes
19.  Anatomic Brain Asymmetry in Vervet Monkeys 
PLoS ONE  2011;6(12):e28243.
Asymmetry is a prominent feature of human brains with important functional consequences. Many asymmetric traits show population bias, but little is known about the genetic and environmental sources contributing to inter-individual variance. Anatomic asymmetry has been observed in Old World monkeys, but the evidence for the direction and extent of asymmetry is equivocal and only one study has estimated the genetic contributions to inter-individual variance. In this study we characterize a range of qualitative and quantitative asymmetry measures in structural brain MRIs acquired from an extended pedigree of Old World vervet monkeys (n = 357), and implement variance component methods to estimate the proportion of trait variance attributable to genetic and environmental sources. Four of six asymmetry measures show pedigree-level bias and one of the traits has a significant heritability estimate of about 30%. We also found that environmental variables more significantly influence the width of the right compared to the left prefrontal lobe.
doi:10.1371/journal.pone.0028243
PMCID: PMC3244392  PMID: 22205941
20.  Identifying rare variants from exome scans: the GAW17 experience 
BMC Proceedings  2011;5(Suppl 9):S1.
Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop.
doi:10.1186/1753-6561-5-S9-S1
PMCID: PMC3287821  PMID: 22373325
21.  A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder 
Casey, Jillian P. | Magalhaes, Tiago | Conroy, Judith M. | Regan, Regina | Shah, Naisha | Anney, Richard | Shields, Denis C. | Abrahams, Brett S. | Almeida, Joana | Bacchelli, Elena | Bailey, Anthony J. | Baird, Gillian | Battaglia, Agatino | Berney, Tom | Bolshakova, Nadia | Bolton, Patrick F. | Bourgeron, Thomas | Brennan, Sean | Cali, Phil | Correia, Catarina | Corsello, Christina | Coutanche, Marc | Dawson, Geraldine | de Jonge, Maretha | Delorme, Richard | Duketis, Eftichia | Duque, Frederico | Estes, Annette | Farrar, Penny | Fernandez, Bridget A. | Folstein, Susan E. | Foley, Suzanne | Fombonne, Eric | Freitag, Christine M. | Gilbert, John | Gillberg, Christopher | Glessner, Joseph T. | Green, Jonathan | Guter, Stephen J. | Hakonarson, Hakon | Holt, Richard | Hughes, Gillian | Hus, Vanessa | Igliozzi, Roberta | Kim, Cecilia | Klauck, Sabine M. | Kolevzon, Alexander | Lamb, Janine A. | Leboyer, Marion | Le Couteur, Ann | Leventhal, Bennett L. | Lord, Catherine | Lund, Sabata C. | Maestrini, Elena | Mantoulan, Carine | Marshall, Christian R. | McConachie, Helen | McDougle, Christopher J. | McGrath, Jane | McMahon, William M. | Merikangas, Alison | Miller, Judith | Minopoli, Fiorella | Mirza, Ghazala K. | Munson, Jeff | Nelson, Stanley F. | Nygren, Gudrun | Oliveira, Guiomar | Pagnamenta, Alistair T. | Papanikolaou, Katerina | Parr, Jeremy R. | Parrini, Barbara | Pickles, Andrew | Pinto, Dalila | Piven, Joseph | Posey, David J. | Poustka, Annemarie | Poustka, Fritz | Ragoussis, Jiannis | Roge, Bernadette | Rutter, Michael L. | Sequeira, Ana F. | Soorya, Latha | Sousa, Inês | Sykes, Nuala | Stoppioni, Vera | Tancredi, Raffaella | Tauber, Maïté | Thompson, Ann P. | Thomson, Susanne | Tsiantis, John | Van Engeland, Herman | Vincent, John B. | Volkmar, Fred | Vorstman, Jacob A. S. | Wallace, Simon | Wang, Kai | Wassink, Thomas H. | White, Kathy | Wing, Kirsty | Wittemeyer, Kerstin | Yaspan, Brian L. | Zwaigenbaum, Lonnie | Betancur, Catalina | Buxbaum, Joseph D. | Cantor, Rita M. | Cook, Edwin H. | Coon, Hilary | Cuccaro, Michael L. | Geschwind, Daniel H. | Haines, Jonathan L. | Hallmayer, Joachim | Monaco, Anthony P. | Nurnberger, John I. | Pericak-Vance, Margaret A. | Schellenberg, Gerard D. | Scherer, Stephen W. | Sutcliffe, James S. | Szatmari, Peter | Vieland, Veronica J. | Wijsman, Ellen M. | Green, Andrew | Gill, Michael | Gallagher, Louise | Vicente, Astrid | Ennis, Sean
Human Genetics  2011;131(4):565-579.
Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.
Electronic supplementary material
The online version of this article (doi:10.1007/s00439-011-1094-6) contains supplementary material, which is available to authorized users.
doi:10.1007/s00439-011-1094-6
PMCID: PMC3303079  PMID: 21996756
22.  Association of IRF5 polymorphisms with activation of the interferon α pathway 
Annals of the rheumatic diseases  2009;69(3):611-617.
Objective
The genetic association of interferon regulatory factor 5 (IRF5) with systemic lupus erythematosus (SLE) susceptibility has been convincingly established. To gain understanding of the effect of IRF5 variation in individuals without SLE, a study was undertaken to examine whether such genetic variation predisposes to activation of the interferon α (IFNα) pathway.
Methods
Using a computer simulated approach, 14 single nucleotide polymorphisms (SNPs) and haplotypes of IRF5 were tested for association with mRNA expression levels of IRF5, IFNα and IFN-inducible genes and chemokines in lymphoblastoid cell lines (LCLs) from individuals of European (CEU), Han Chinese (CHB), Japanese (JPT) and Yoruba Nigerian (YRI) backgrounds. IFN-inducible gene expression was assessed in LCLs from children with SLE in the presence and absence of IFNα stimulation.
Results
The major alleles of IRF5 rs13242262 and rs2280714 were associated with increased IRF5 mRNA expression levels in the CEU, CHB+JPT and YRI samples. The minor allele of IRF5 rs10488631 was associated with increased IRF5, IFNα and IFN-inducible chemokine expression in CEU (pc=0.0005, 0.01 and 0.04, respectively). A haplotype containing these risk alleles of rs13242262, rs10488631 and rs2280714 was associated with increased IRF5, IFNα and IFN-inducible chemokine expression in CEU LCLs. In vitro studies showed specific activation of IFN-inducible genes in LCLs by IFNα.
Conclusions
SNPs of IRF5 in healthy individuals of a number of ethnic groups were associated with increased mRNA expression of IRF5. In European-derived individuals, an IRF5 haplotype was associated with increased IRF5, IFNα and IFN-inducible chemokine expression. Identifying individuals genetically predisposed to increased IFN-inducible gene and chemokine expression may allow early detection of risk for SLE.
doi:10.1136/ard.2009.118315
PMCID: PMC3135414  PMID: 19854706
23.  Association of Genetic Variants in Complement Factor H and Factor H-Related Genes with Systemic Lupus Erythematosus Susceptibility 
PLoS Genetics  2011;7(5):e1002079.
Systemic lupus erythematosus (SLE), a complex polygenic autoimmune disease, is associated with increased complement activation. Variants of genes encoding complement regulator factor H (CFH) and five CFH-related proteins (CFHR1-CFHR5) within the chromosome 1q32 locus linked to SLE, have been associated with multiple human diseases and may contribute to dysregulated complement activation predisposing to SLE. We assessed 60 SNPs covering the CFH-CFHRs region for association with SLE in 15,864 case-control subjects derived from four ethnic groups. Significant allelic associations with SLE were detected in European Americans (EA) and African Americans (AA), which could be attributed to an intronic CFH SNP (rs6677604, in intron 11, Pmeta = 6.6×10−8, OR = 1.18) and an intergenic SNP between CFHR1 and CFHR4 (rs16840639, Pmeta = 2.9×10−7, OR = 1.17) rather than to previously identified disease-associated CFH exonic SNPs, including I62V, Y402H, A474A, and D936E. In addition, allelic association of rs6677604 with SLE was subsequently confirmed in Asians (AS). Haplotype analysis revealed that the underlying causal variant, tagged by rs6677604 and rs16840639, was localized to a ∼146 kb block extending from intron 9 of CFH to downstream of CFHR1. Within this block, the deletion of CFHR3 and CFHR1 (CFHR3-1Δ), a likely causal variant measured using multiplex ligation-dependent probe amplification, was tagged by rs6677604 in EA and AS and rs16840639 in AA, respectively. Deduced from genotypic associations of tag SNPs in EA, AA, and AS, homozygous deletion of CFHR3-1Δ (Pmeta = 3.2×10−7, OR = 1.47) conferred a higher risk of SLE than heterozygous deletion (Pmeta = 3.5×10−4, OR = 1.14). These results suggested that the CFHR3-1Δ deletion within the SLE-associated block, but not the previously described exonic SNPs of CFH, might contribute to the development of SLE in EA, AA, and AS, providing new insights into the role of complement regulators in the pathogenesis of SLE.
Author Summary
Systemic lupus erythematosus (SLE) is a complex autoimmune disease, associated with increased complement activation. Previous studies have provided evidence for the presence of SLE susceptibility gene(s) in the chromosome 1q31-32 locus. Within 1q32, genes encoding complement regulator factor H (CFH) and five CFH-related proteins (CFHR1-CFHR5) may contribute to the development of SLE, because genetic variants of these genes impair complement regulation and predispose to various human diseases. In this study, we tested association of genetic variants in the region containing CFH and CFHRs with SLE. We identified genetic variants predisposing to SLE in European American, African American, and Asian populations, which might be attributed to the deletion of CFHR3 and CFHR1 genes but not previously identified disease-associated exonic variants of CFH. This study provides the first evidence for consistent association between CFH/CFHRs and SLE across multi-ancestral SLE datasets, providing new insights into the role of complement regulators in the pathogenesis of SLE.
doi:10.1371/journal.pgen.1002079
PMCID: PMC3102741  PMID: 21637784
24.  Common variants conferring risk of schizophrenia 
Stefansson, Hreinn | Ophoff, Roel A. | Steinberg, Stacy | Andreassen, Ole A. | Cichon, Sven | Rujescu, Dan | Werge, Thomas | Pietiläinen, Olli P. H. | Mors, Ole | Mortensen, Preben B. | Sigurdsson, Engilbert | Gustafsson, Omar | Nyegaard, Mette | Tuulio-Henriksson, Annamari | Ingason, Andres | Hansen, Thomas | Suvisaari, Jaana | Lonnqvist, Jouko | Paunio, Tiina | Børglum, Anders D. | Hartmann, Annette | Fink-Jensen, Anders | Nordentoft, Merete | Hougaard, David | Norgaard-Pedersen, Bent | Böttcher, Yvonne | Olesen, Jes | Breuer, René | Möller, Hans-Jürgen | Giegling, Ina | Rasmussen, Henrik B. | Timm, Sally | Mattheisen, Manuel | Bitter, István | Réthelyi, János M. | Magnusdottir, Brynja B. | Sigmundsson, Thordur | Olason, Pall | Masson, Gisli | Gulcher, Jeffrey R. | Haraldsson, Magnus | Fossdal, Ragnheidur | Thorgeirsson, Thorgeir E. | Thorsteinsdottir, Unnur | Ruggeri, Mirella | Tosato, Sarah | Franke, Barbara | Strengman, Eric | Kiemeney, Lambertus A. | Melle, Ingrid | Djurovic, Srdjan | Abramova, Lilia | Kaleda, Vasily | Sanjuan, Julio | de Frutos, Rosa | Bramon, Elvira | Vassos, Evangelos | Fraser, Gillian | Ettinger, Ulrich | Picchioni, Marco | Walker, Nicholas | Toulopoulou, Timi | Need, Anna C. | Ge, Dongliang | Yoon, Joeng Lim | Shianna, Kevin V. | Freimer, Nelson B. | Cantor, Rita M. | Murray, Robin | Kong, Augustine | Golimbet, Vera | Carracedo, Angel | Arango, Celso | Costas, Javier | Jönsson, Erik G. | Terenius, Lars | Agartz, Ingrid | Petursson, Hannes | Nöthen, Markus M. | Rietschel, Marcella | Matthews, Paul M. | Muglia, Pierandrea | Peltonen, Leena | St Clair, David | Goldstein, David B. | Stefansson, Kari | Collier, David A.
Nature  2009;460(7256):744-747.
Schizophrenia is a complex disorder, caused by both genetic and environmental factors and their interactions. Research on pathogenesis has traditionally focused on neurotransmitter systems in the brain, particularly those involving dopamine. Schizophrenia has been considered a separate disease for over a century, but in the absence of clear biological markers, diagnosis has historically been based on signs and symptoms. A fundamental message emerging from genome-wide association studies of copy number variations (CNVs) associated with the disease is that its genetic basis does not necessarily conform to classical nosological disease boundaries. Certain CNVs confer not only high relative risk of schizophrenia but also of other psychiatric disorders1–3. The structural variations associated with schizophrenia can involve several genes and the phenotypic syndromes, or the ‘genomic disorders’, have not yet been characterized4. Single nucleotide polymorphism (SNP)-based genome-wide association studies with the potential to implicate individual genes in complex diseases may reveal underlying biological pathways. Here we combined SNP data from several large genome-wide scans and followed up the most significant association signals. We found significant association with several markers spanning the major histocompatibility complex (MHC) region on chromosome 6p21.3-22.1, a marker located upstream of the neurogranin gene (NRGN) on 11q24.2 and a marker in intron four of transcription factor 4 (TCF4) on 18q21.2. Our findings implicating the MHC region are consistent with an immune component to schizophrenia risk, whereas the association with NRGN and TCF4 points to perturbation of pathways involved in brain development, memory and cognition.
doi:10.1038/nature08186
PMCID: PMC3077530  PMID: 19571808
25.  Offering to Share: How to Put Heads Together in Autism Neuroimaging 
Data sharing in autism neuroimaging presents scientific, technical, and social obstacles. We outline the desiderata for a data-sharing scheme that combines imaging with other measures of phenotype and with genetics, defines requirements for comparability of derived data and recommendations for raw data, outlines a core protocol including multispectral structural and diffusion-tensor imaging and optional extensions, provides for the collection of prospective, confound-free normative data, and extends sharing and collaborative development not only to data but to the analytical tools and methods applied to these data. A theme in these requirements is the need to preserve creative approaches and risk-taking within individual laboratories at the same time as common standards are provided for these laboratories to build on.
doi:10.1007/s10803-006-0352-2
PMCID: PMC3076291  PMID: 17347882
Imaging; MRI; PET; Morphometry; Segmentation; Data sharing

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