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1.  GWAS of blood cell traits identifies novel associated loci and epistatic interactions in Caucasian and African-American children 
Human Molecular Genetics  2012;22(7):1457-1464.
Hematological traits are important clinical indicators, the genetic determinants of which have not been fully investigated. Common measures of hematological traits include red blood cell (RBC) count, hemoglobin concentration (HGB), hematocrit (HCT), mean corpuscular hemoglobin (MCH), MCH concentration (MCHC), mean corpuscular volume (MCV), platelet count (PLT) and white blood cell (WBC) count. We carried out a genome-wide association study of the eight common hematological traits among 7943 African-American children and 6234 Caucasian children. In African Americans, we report five novel associations of HBE1 variants with HCT and MCHC, the alpha-globin gene cluster variants with RBC and MCHC, and a variant at the ARHGEF3 locus with PLT, as well as replication of four previously reported loci at genome-wide significance. In Caucasians, we report a novel association of variants at the COPZ1 locus with PLT as well as replication of four previously reported loci at genome-wide significance. Extended analysis of an association observed between MCH and the alpha-globin gene cluster variants demonstrated independent effects and epistatic interaction at the locus, impacting the risk of iron deficiency anemia in African Americans with specific genotype states. In summary, we extend the understanding of genetic variants underlying hematological traits based on analyses in African-American children.
doi:10.1093/hmg/dds534
PMCID: PMC3657475  PMID: 23263863
2.  Integrative genomics identifies LMO1 as a neuroblastoma oncogene 
Nature  2010;469(7329):216-220.
Neuroblastoma is a childhood cancer of the sympathetic nervous system that accounts for approximately 10% of all paediatric oncology deaths1,2. To identify genetic risk factors for neuroblastoma, we performed a genome-wide association study (GWAS) on 2,251 patients and 6,097 control subjects of European ancestry from four case series. Here we report a significant association within LIM domain only 1 (LMO1) at 11p15.4 (rs110419, combined P = 5.2 × 10−16, odds ratio of risk allele = 1.34 (95% confidence interval 1.25–1.44)). The signal was enriched in the subset of patients with the most aggressive form of the disease. LMO1 encodes a cysteine-rich transcriptional regulator, and its paralogues (LMO2, LMO3 and LMO4) have each been previously implicated in cancer. In parallel, we analysed genome-wide DNA copy number alterations in 701 primary tumours. We found that the LMO1 locus was aberrant in 12.4% through a duplication event, and that this event was associated with more advanced disease (P < 0.0001) and survival (P = 0.041). The germline single nucleotide polymorphism (SNP) risk alleles and somatic copy number gains were associated with increased LMO1 expression in neuroblastoma cell lines and primary tumours, consistent with a gain-of-function role in tumorigenesis. Short hairpin RNA (shRNA)-mediated depletion of LMO1 inhibited growth of neuroblastoma cells with high LMO1 expression, whereas forced expression of LMO1 in neuroblastoma cells with low LMO1 expression enhanced proliferation. These data show that common polymorphisms at the LMO1 locus are strongly associated with susceptibility to developing neuroblastoma, but also may influence the likelihood of further somatic alterations at this locus, leading to malignant progression.
doi:10.1038/nature09609
PMCID: PMC3320515  PMID: 21124317
3.  Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis 
Sawcer, Stephen | Hellenthal, Garrett | Pirinen, Matti | Spencer, Chris C.A. | Patsopoulos, Nikolaos A. | Moutsianas, Loukas | Dilthey, Alexander | Su, Zhan | Freeman, Colin | Hunt, Sarah E. | Edkins, Sarah | Gray, Emma | Booth, David R. | Potter, Simon C. | Goris, An | Band, Gavin | Oturai, Annette Bang | Strange, Amy | Saarela, Janna | Bellenguez, Céline | Fontaine, Bertrand | Gillman, Matthew | Hemmer, Bernhard | Gwilliam, Rhian | Zipp, Frauke | Jayakumar, Alagurevathi | Martin, Roland | Leslie, Stephen | Hawkins, Stanley | Giannoulatou, Eleni | D’alfonso, Sandra | Blackburn, Hannah | Boneschi, Filippo Martinelli | Liddle, Jennifer | Harbo, Hanne F. | Perez, Marc L. | Spurkland, Anne | Waller, Matthew J | Mycko, Marcin P. | Ricketts, Michelle | Comabella, Manuel | Hammond, Naomi | Kockum, Ingrid | McCann, Owen T. | Ban, Maria | Whittaker, Pamela | Kemppinen, Anu | Weston, Paul | Hawkins, Clive | Widaa, Sara | Zajicek, John | Dronov, Serge | Robertson, Neil | Bumpstead, Suzannah J. | Barcellos, Lisa F. | Ravindrarajah, Rathi | Abraham, Roby | Alfredsson, Lars | Ardlie, Kristin | Aubin, Cristin | Baker, Amie | Baker, Katharine | Baranzini, Sergio E. | Bergamaschi, Laura | Bergamaschi, Roberto | Bernstein, Allan | Berthele, Achim | Boggild, Mike | Bradfield, Jonathan P. | Brassat, David | Broadley, Simon A. | Buck, Dorothea | Butzkueven, Helmut | Capra, Ruggero | Carroll, William M. | Cavalla, Paola | Celius, Elisabeth G. | Cepok, Sabine | Chiavacci, Rosetta | Clerget-Darpoux, Françoise | Clysters, Katleen | Comi, Giancarlo | Cossburn, Mark | Cournu-Rebeix, Isabelle | Cox, Mathew B. | Cozen, Wendy | Cree, Bruce A.C. | Cross, Anne H. | Cusi, Daniele | Daly, Mark J. | Davis, Emma | de Bakker, Paul I.W. | Debouverie, Marc | D’hooghe, Marie Beatrice | Dixon, Katherine | Dobosi, Rita | Dubois, Bénédicte | Ellinghaus, David | Elovaara, Irina | Esposito, Federica | Fontenille, Claire | Foote, Simon | Franke, Andre | Galimberti, Daniela | Ghezzi, Angelo | Glessner, Joseph | Gomez, Refujia | Gout, Olivier | Graham, Colin | Grant, Struan F.A. | Guerini, Franca Rosa | Hakonarson, Hakon | Hall, Per | Hamsten, Anders | Hartung, Hans-Peter | Heard, Rob N. | Heath, Simon | Hobart, Jeremy | Hoshi, Muna | Infante-Duarte, Carmen | Ingram, Gillian | Ingram, Wendy | Islam, Talat | Jagodic, Maja | Kabesch, Michael | Kermode, Allan G. | Kilpatrick, Trevor J. | Kim, Cecilia | Klopp, Norman | Koivisto, Keijo | Larsson, Malin | Lathrop, Mark | Lechner-Scott, Jeannette S. | Leone, Maurizio A. | Leppä, Virpi | Liljedahl, Ulrika | Bomfim, Izaura Lima | Lincoln, Robin R. | Link, Jenny | Liu, Jianjun | Lorentzen, Åslaug R. | Lupoli, Sara | Macciardi, Fabio | Mack, Thomas | Marriott, Mark | Martinelli, Vittorio | Mason, Deborah | McCauley, Jacob L. | Mentch, Frank | Mero, Inger-Lise | Mihalova, Tania | Montalban, Xavier | Mottershead, John | Myhr, Kjell-Morten | Naldi, Paola | Ollier, William | Page, Alison | Palotie, Aarno | Pelletier, Jean | Piccio, Laura | Pickersgill, Trevor | Piehl, Fredrik | Pobywajlo, Susan | Quach, Hong L. | Ramsay, Patricia P. | Reunanen, Mauri | Reynolds, Richard | Rioux, John D. | Rodegher, Mariaemma | Roesner, Sabine | Rubio, Justin P. | Rückert, Ina-Maria | Salvetti, Marco | Salvi, Erika | Santaniello, Adam | Schaefer, Catherine A. | Schreiber, Stefan | Schulze, Christian | Scott, Rodney J. | Sellebjerg, Finn | Selmaj, Krzysztof W. | Sexton, David | Shen, Ling | Simms-Acuna, Brigid | Skidmore, Sheila | Sleiman, Patrick M.A. | Smestad, Cathrine | Sørensen, Per Soelberg | Søndergaard, Helle Bach | Stankovich, Jim | Strange, Richard C. | Sulonen, Anna-Maija | Sundqvist, Emilie | Syvänen, Ann-Christine | Taddeo, Francesca | Taylor, Bruce | Blackwell, Jenefer M. | Tienari, Pentti | Bramon, Elvira | Tourbah, Ayman | Brown, Matthew A. | Tronczynska, Ewa | Casas, Juan P. | Tubridy, Niall | Corvin, Aiden | Vickery, Jane | Jankowski, Janusz | Villoslada, Pablo | Markus, Hugh S. | Wang, Kai | Mathew, Christopher G. | Wason, James | Palmer, Colin N.A. | Wichmann, H-Erich | Plomin, Robert | Willoughby, Ernest | Rautanen, Anna | Winkelmann, Juliane | Wittig, Michael | Trembath, Richard C. | Yaouanq, Jacqueline | Viswanathan, Ananth C. | Zhang, Haitao | Wood, Nicholas W. | Zuvich, Rebecca | Deloukas, Panos | Langford, Cordelia | Duncanson, Audrey | Oksenberg, Jorge R. | Pericak-Vance, Margaret A. | Haines, Jonathan L. | Olsson, Tomas | Hillert, Jan | Ivinson, Adrian J. | De Jager, Philip L. | Peltonen, Leena | Stewart, Graeme J. | Hafler, David A. | Hauser, Stephen L. | McVean, Gil | Donnelly, Peter | Compston, Alastair
Nature  2011;476(7359):214-219.
Multiple sclerosis (OMIM 126200) is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability.1 Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals;2,3 and systematic attempts to identify linkage in multiplex families have confirmed that variation within the Major Histocompatibility Complex (MHC) exerts the greatest individual effect on risk.4 Modestly powered Genome-Wide Association Studies (GWAS)5-10 have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects play a key role in disease susceptibility.11 Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the Class I region. Immunologically relevant genes are significantly over-represented amongst those mapping close to the identified loci and particularly implicate T helper cell differentiation in the pathogenesis of multiple sclerosis.
doi:10.1038/nature10251
PMCID: PMC3182531  PMID: 21833088
multiple sclerosis; GWAS; genetics
4.  Association of RASGRP1 with type 1 diabetes is revealed by combined follow-up of two genome-wide studies 
Journal of Medical Genetics  2009;46(8):553-554.
Background
The two genome-wide association studies published by us and by the Wellcome Trust Case-Control Consortium (WTCCC) revealed a number of novel loci but neither had the statistical power to elucidate all of the genetic components of type 1 diabetes risk, a task for which larger effective sample sizes are needed.
Methods
We analyzed data from two sources: 1) The previously published second stage of our study, with a total sample size of the two stages consisting of 1,046 Canadian case-parent trios and 538 multiplex families with 929 affected offspring from the Type 1 Diabetes Genetics Consortium (T1DGC); 2) The RR2 project of the T1DGC, which genotyped 4,417 individuals from 1,062 non-overlapping families, including 2,059 affected individuals (mostly sibling pairs) for the 1,536 markers with the highest statistical significance for type 1 diabetes in the WTCCC results.
Results
One locus, mapping to an LD block at chr15q14, reached statistical significance by combining results from two markers (rs17574546 and rs7171171) in perfect linkage disequilibrium (LD) with each other (r2=1). We obtained a joint p value of 1.3 ×10−6, which exceeds by an order of magnitude the conservative threshold of 3.26×10−5 obtained by correcting for the 1,536 SNPs tested in our study. Meta-analysis with the original WTCCC genome-wide data produced a p value of 5.83×10−9.
Conclusions
A novel type 1 diabetes locus was discovered. It involves RASGRP1, a gene known to play a crucial role in thymocyte differentiation and TCR signaling by activating the Ras signaling pathway.
doi:10.1136/jmg.2009.067140
PMCID: PMC3272492  PMID: 19465406
Etiology; Genetic susceptibility; Type 1 diabetes; RASGRP1
5.  Comparative genetic analysis of inflammatory bowel disease and type 1 diabetes implicates multiple loci with opposite effects 
Human Molecular Genetics  2010;19(10):2059-2067.
Inflammatory bowel disease, including Crohn's disease (CD) and ulcerative colitis (UC), and type 1 diabetes (T1D) are autoimmune diseases that may share common susceptibility pathways. We examined known susceptibility loci for these diseases in a cohort of 1689 CD cases, 777 UC cases, 989 T1D cases and 6197 shared control subjects of European ancestry, who were genotyped by the Illumina HumanHap550 SNP arrays. We identified multiple previously unreported or unconfirmed disease associations, including known CD loci (ICOSLG and TNFSF15) and T1D loci (TNFAIP3) that confer UC risk, known UC loci (HERC2 and IL26) that confer T1D risk and known UC loci (IL10 and CCNY) that confer CD risk. Additionally, we show that T1D risk alleles residing at the PTPN22, IL27, IL18RAP and IL10 loci protect against CD. Furthermore, the strongest risk alleles for T1D within the major histocompatibility complex (MHC) confer strong protection against CD and UC; however, given the multi-allelic nature of the MHC haplotypes, sequencing of the MHC locus will be required to interpret this observation. These results extend our current knowledge on genetic variants that predispose to autoimmunity, and suggest that many loci involved in autoimmunity may be under a balancing selection due to antagonistic pleiotropic effect. Our analysis implies that variants with opposite effects on different diseases may facilitate the maintenance of common susceptibility alleles in human populations, making autoimmune diseases especially amenable to genetic dissection by genome-wide association studies.
doi:10.1093/hmg/ddq078
PMCID: PMC2860894  PMID: 20176734
6.  Common variations in BARD1 influence susceptibility to high-risk neuroblastoma 
Nature genetics  2009;41(6):718-723.
We conducted a SNP-based genome-wide association study (GWAS) focused on the high-risk subset of neuroblastoma1. As our previous unbiased GWAS showed strong association of common 6p22 SNP alleles with aggressive neuroblastoma2, we now restricted our analysis to 397 high-risk cases compared to 2,043 controls. We detected new significant association of six SNPs at 2q35 within the BARD1 gene locus (Pallelic = 2.35×10−9 − 2.25×10−8). Each SNP association was confirmed in a second series of 189 high-risk cases and 1,178 controls (Pallelic = 7.90×10−7 − 2.77×10−4). The two most significant SNPs (rs6435862, rs3768716) were also tested in two additional independent high-risk neuroblastoma case series, yielding combined allelic odds-ratios of 1.68 each (P = 8.65×10−18 and 2.74×10−16, respectively). Significant association was also found with known BARD1 nsSNPs. These data show that common variation in BARD1 contributes to the etiology of the aggressive and most clinically relevant subset of human neuroblastoma.
doi:10.1038/ng.374
PMCID: PMC2753610  PMID: 19412175
7.  From Disease Association to Risk Assessment: An Optimistic View from Genome-Wide Association Studies on Type 1 Diabetes 
PLoS Genetics  2009;5(10):e1000678.
Genome-wide association studies (GWAS) have been fruitful in identifying disease susceptibility loci for common and complex diseases. A remaining question is whether we can quantify individual disease risk based on genotype data, in order to facilitate personalized prevention and treatment for complex diseases. Previous studies have typically failed to achieve satisfactory performance, primarily due to the use of only a limited number of confirmed susceptibility loci. Here we propose that sophisticated machine-learning approaches with a large ensemble of markers may improve the performance of disease risk assessment. We applied a Support Vector Machine (SVM) algorithm on a GWAS dataset generated on the Affymetrix genotyping platform for type 1 diabetes (T1D) and optimized a risk assessment model with hundreds of markers. We subsequently tested this model on an independent Illumina-genotyped dataset with imputed genotypes (1,008 cases and 1,000 controls), as well as a separate Affymetrix-genotyped dataset (1,529 cases and 1,458 controls), resulting in area under ROC curve (AUC) of ∼0.84 in both datasets. In contrast, poor performance was achieved when limited to dozens of known susceptibility loci in the SVM model or logistic regression model. Our study suggests that improved disease risk assessment can be achieved by using algorithms that take into account interactions between a large ensemble of markers. We are optimistic that genotype-based disease risk assessment may be feasible for diseases where a notable proportion of the risk has already been captured by SNP arrays.
Author Summary
An often touted utility of genome-wide association studies (GWAS) is that the resulting discoveries can facilitate implementation of personalized medicine, in which preventive and therapeutic interventions for complex diseases can be tailored to individual genetic profiles. However, recent studies using whole-genome SNP genotype data for disease risk assessment have generally failed to achieve satisfactory results, leading to a pessimistic view of the utility of genotype data for such purposes. Here we propose that sophisticated machine-learning approaches on a large ensemble of markers, which contain both confirmed and as yet unconfirmed disease susceptibility variants, may improve the performance of disease risk assessment. We tested an algorithm called Support Vector Machine (SVM) on three large-scale datasets for type 1 diabetes and demonstrated that risk assessment can be highly accurate for the disease. Our results suggest that individualized disease risk assessment using whole-genome data may be more successful for some diseases (such as T1D) than other diseases. However, the predictive accuracy will be dependent on the heritability of the disease under study, the proportion of the genetic risk that is known, and that the right set of markers and right algorithms are being used.
doi:10.1371/journal.pgen.1000678
PMCID: PMC2748686  PMID: 19816555
8.  Copy number variation at 1q21.1 associated with neuroblastoma 
Nature  2009;459(7249):987-991.
Common copy number variations (CNVs) represent a significant source of genetic diversity, yet their influence on phenotypic variability, including disease susceptibility, remains poorly understood. To address this problem in cancer, we performed a genome-wide association study (GWAS) of CNVs in the childhood cancer neuroblastoma, a disease where SNP variations are known to influence susceptibility1,2. We first genotyped 846 Caucasian neuroblastoma patients and 803 healthy Caucasian controls at 550,000 single nucleotide polymorphisms, and performed a CNV-based test for association. We then replicated significant observations in two independent sample sets comprised of a total of 595 cases and 3,357 controls. We identified a common CNV at 1q21.1 associated with neuroblastoma in the discovery set, which was confirmed in both replication sets (Pcombined = 2.97 × 10−17; OR = 2.49, 95% CI: 2.02 to 3.05). This CNV was validated by quantitative PCR, fluorescent in situ hybridization, and analysis of matched tumor specimens, and was shown to be heritable in an independent set of 713 cancer-free trios. We identified a novel transcript within the CNV which showed high sequence similarity to several “Neuroblastoma breakpoint family” (NBPF) genes3,4 and represents a new member of this gene family (NBPFX). This transcript was preferentially expressed in fetal brain and fetal sympathetic nervous tissues, and expression level was strictly correlated with CNV state in neuroblastoma cells. These data demonstrate that inherited copy number variation at 1q21.1 is associated with neuroblastoma and implicate a novel NBPF gene in early tumorigenesis of this childhood cancer.
doi:10.1038/nature08035
PMCID: PMC2755253  PMID: 19536264
9.  A genome-wide association study identifies a susceptibility locus to clinically aggressive neuroblastoma at 6p22 
The New England journal of medicine  2008;358(24):2585-2593.
Background
Neuroblastoma is a malignancy of the developing sympathetic nervous system that most commonly affects young children and is often lethal. The etiology of this embryonal cancer is not known.
Methods
We performed a genome-wide association study by first genotyping 1,032 neuroblastoma patients and 2,043 controls of European descent using the Illumina HumanHap550 BeadChip. Three independent groups of neuroblastoma cases (N=720) and controls (N=2128) were then genotyped to replicate significant associations.
Results
We observed highly significant association between neuroblastoma and the common minor alleles of three single nucleotide polymorphisms (SNPs) within a 94.2 kilobase (Kb) linkage disequilibrium block at chromosome band 6p22 containing the predicted genes FLJ22536 and FLJ44180 (P-value range = 1.71×10-9-7.01×10-10; allelic odds ratio range 1.39-1.40). Homozygosity for the at-risk G allele of the most significantly associated SNP, rs6939340, resulted in an increased likelihood of developing neuroblastoma of 1.97 (95% CI 1.58-2.44). Subsequent genotyping of these 6p22 SNPs in the three independent case series confirmed our observation of association (P=9.33×10-15 at rs6939340 for joint analysis). Furthermore, neuroblastoma patients homozygous for the risk alleles at 6p22 were more likely to develop metastatic (Stage 4) disease (P=0.02), show amplification of the MYCN oncogene in the tumor cells (P=0.006), and to have disease relapse (P=0.01).
Conclusion
Common genetic variation at chromosome band 6p22 is associated with susceptibility to neuroblastoma.
doi:10.1056/NEJMoa0708698
PMCID: PMC2742373  PMID: 18463370
10.  Association Analysis of Type 2 Diabetes Loci in Type 1 Diabetes 
Diabetes  2008;57(7):1983-1986.
OBJECTIVE—To search for a possible association of type 1 diabetes with 10 validated type 2 diabetes loci, i.e., PPARG, KCNJ11, WFS1, HNF1B, IDE/HHEX, SLC30A8, CDKAL1, CDKN2A/B, IGF2BP2, and FTO/RPGRIP1L.
RESEARCH DESIGN AND METHODS—Two European population samples were studied: 1) one case-control cohort of 514 type 1 diabetic subjects and 2,027 control subjects and 2) one family cohort of 483 complete type 1 diabetic case-parent trios (total 997 affected). A total of 13 tag single nucleotide polymorphisms (SNPs) from the 10 type 2 diabetes loci were analyzed for type 1 diabetes association.
RESULTS—No association of type 1 diabetes was found with any of the 10 type 2 diabetes loci, and no age-at-onset effect was detected. By combined analysis using the Wellcome Trust Case-Control Consortium type 1 diabetes data, SNP rs1412829 in the CDKN2A/B locus bordered on significance (P = 0.039) (odds ratio 0.929 [95% CI 0.867–0.995]), which did not reach the statistical significance threshold adjusted for 13 tests (α = 0.00385).
CONCLUSIONS—This study suggests that the type 2 diabetes loci do not play any obvious role in type 1 diabetes genetic susceptibility. The distinct molecular mechanisms of the two diseases highlighted the importance of differentiation diagnosis and different treatment principles.
doi:10.2337/db08-0270
PMCID: PMC2453613  PMID: 18426861
11.  Genome-Wide Analyses of Exonic Copy Number Variants in a Family-Based Study Point to Novel Autism Susceptibility Genes 
PLoS Genetics  2009;5(6):e1000536.
The genetics underlying the autism spectrum disorders (ASDs) is complex and remains poorly understood. Previous work has demonstrated an important role for structural variation in a subset of cases, but has lacked the resolution necessary to move beyond detection of large regions of potential interest to identification of individual genes. To pinpoint genes likely to contribute to ASD etiology, we performed high density genotyping in 912 multiplex families from the Autism Genetics Resource Exchange (AGRE) collection and contrasted results to those obtained for 1,488 healthy controls. Through prioritization of exonic deletions (eDels), exonic duplications (eDups), and whole gene duplication events (gDups), we identified more than 150 loci harboring rare variants in multiple unrelated probands, but no controls. Importantly, 27 of these were confirmed on examination of an independent replication cohort comprised of 859 cases and an additional 1,051 controls. Rare variants at known loci, including exonic deletions at NRXN1 and whole gene duplications encompassing UBE3A and several other genes in the 15q11–q13 region, were observed in the course of these analyses. Strong support was likewise observed for previously unreported genes such as BZRAP1, an adaptor molecule known to regulate synaptic transmission, with eDels or eDups observed in twelve unrelated cases but no controls (p = 2.3×10−5). Less is known about MDGA2, likewise observed to be case-specific (p = 1.3×10−4). But, it is notable that the encoded protein shows an unexpectedly high similarity to Contactin 4 (BLAST E-value = 3×10−39), which has also been linked to disease. That hundreds of distinct rare variants were each seen only once further highlights complexity in the ASDs and points to the continued need for larger cohorts.
Author Summary
Autism spectrum disorders (ASDs) are common neurodevelopmental syndromes with a strong genetic component. ASDs are characterized by disturbances in social behavior, impaired verbal and nonverbal communication, as well as repetitive behaviors and/or a restricted range of interests. To identify genes likely to contribute to ASD etiology, we performed high density genotyping in 912 multiplex families from the Autism Genetics Resource Exchange (AGRE) collection and contrasted results to those obtained for 1,488 healthy controls. To enrich for variants most likely to interfere with gene function, we restricted our analyses to deletions and gains encompassing exons. Of the many genomic regions highlighted, 27 were seen to harbor rare variants in cases and not controls, both in the first phase of our analysis, and also in an independent replication cohort comprised of 859 cases and 1,051 controls. More work in a larger number of individuals will be required to determine which of the rare alleles highlighted here are indeed related to the ASDs and how they act to shape risk.
doi:10.1371/journal.pgen.1000536
PMCID: PMC2695001  PMID: 19557195

Results 1-11 (11)