L'analyse comparative croisée des troubles comorbides révèle de nouveaux gènes candidats à l'autisme

Aperçu: G.M.

De nombreuses études ont mis en évidence le degré élevé de comorbidité associée au trouble du spectre de l'autisme.

Ces affections comorbides peuvent ajouter d'autres déficiences aux personnes avec un diagnostic d'autisme et sont beaucoup plus répandues par rapport aux populations neurotypiques. Ces taux élevés de comorbidité ne sont pas surprenants compte tenu du chevauchement des symptômes que les TSA partagent avec d'autres pathologies. Du point de vue de la recherche, cela suggère des mécanismes moléculaires communs impliqués dans ces conditions. Par conséquent, l'identification de gènes cruciaux dans le chevauchement entre TSA et ces troubles comorbides peut aider à démêler les processus biologiques communs impliqués et, en fin de compte, éclairer la compréhension de l'étiologie de l'autisme.

Les chercheurs ont travaillé sur une approche de biologie des systèmes à double planche axée spécialement sur les processus biologiques et les réseaux de gènes pour effectuer une analyse comparative de l'autisme avec 31 troubles fréquemment comorbides afin de définir un sous-composant multidisciplinaire de TSA et de prédire de nouveaux gènes potentiels pertinents pour l'etiologie du TSA.

L'étude a identifié un ensemble de 19 gènes qui n'étaient pas précédemment liés au TSA qui étaient significativement régulés différemment chez les personnes avec un diagnostic d'autisme.

Cette étude propose un modèle par lequel la connaissance préalable des réseaux d'interaction peut éclairer et concentrer la recherche génomique des gènes candidats de l'autisme afin de mieux définir l'hétérogénéité génétique du TSA.

 

BMC Genomics. 2017 Apr 20;18(1):315. doi: 10.1186/s12864-017-3667-9.

Cross-disorder comparative analysis of comorbid conditions reveals novel autism candidate genes

Diaz-Beltran L^1,2,3, Esteban FJ³, Varma M^1,2, Ortuzk A^1,2, David M^1,2, Wall DP^4,5,6.

Author information

1

Division of Systems Medicine, Department of Pediatrics, School of Medicine, Stanford University, 1265 Welch Road, Stanford, CA, 94305-5488, USA.

2

Division of Systems Medicine, Department of Psychiatry, Stanford University, Stanford, CA, USA.

3

Systems Biology Unit, Department of Experimental Biology, University of Jaén, Jaén, Spain.

4

Division of Systems Medicine, Department of Pediatrics, School of Medicine, Stanford University, 1265 Welch Road, Stanford, CA, 94305-5488, USA. dpwall@stanford.edu.

5

Division of Systems Medicine, Department of Psychiatry, Stanford University, Stanford, CA, USA. dpwall@stanford.edu.

6

Department of Biomedical Data Science, Stanford University, Stanford, CA, USA. dpwall@stanford.edu.

Abstract

BACKGROUND:

Numerous studies have highlighted the elevated degree of comorbidity associated with autism spectrum disorder (ASD). These comorbid conditions may add further impairments to individuals with autism and are substantially more prevalent compared to neurotypical populations. These high rates of comorbidity are not surprising taking into account the overlap of symptoms that ASD shares with other pathologies. From a research perspective, this suggests common molecular mechanisms involved in these conditions. Therefore, identifying crucial genes in the overlap between ASD and these comorbid disorders may help unravel the common biological processes involved and, ultimately, shed some light in the understanding of autism etiology.

RESULTS:

In this work, we used a two-fold systems biology approach specially focused on biological processes and gene networks to conduct a comparative analysis of autism with 31 frequently comorbid disorders in order to define a multi-disorder subcomponent of ASD and predict new genes of potential relevance to ASD etiology. We validated our predictions by determining the significance of our candidate genes in high throughput transcriptome expression profiling studies. Using prior knowledge of disease-related biological processes and the interaction networks of the disorders related to autism, we identified a set of 19 genes not previously linked to ASD that were significantly differentially regulated in individuals with autism. In addition, these genes were of potential etiologic relevance to autism, given their enriched roles in neurological processes crucial for optimal brain development and function, learning and memory, cognition and social behavior.

CONCLUSIONS:

Taken together, our approach represents a novel perspective of autism from the point of view of related comorbid disorders and proposes a model by which prior knowledge of interaction networks may enlighten and focus the genome-wide search for autism candidate genes to better define the genetic heterogeneity of ASD.

PMID: 28427329

DOI: 10.1186/s12864-017-3667-9

Le séquençage ciblé identifie 91 gènes à risque de trouble neurodéveloppemental avec des biais sur l'autisme et le trouble développemental

Aperçu: G.M.

 Les mutations perturbatrices de gènes contribuent à la biologie des troubles neurodéveloppementaux (NDD), mais la plupart des gènes pathogènes apparentés ne sont pas connus. Nous avons séquencé 208 gènes candidats de> 11 730 cas et> 2 867 témoins. Nous avons identifié 91 gènes, dont 38 nouveaux gènes NDD, avec un excès de mutations de novo ou des mutations perturbatrices privées dans 5,7% des cas. 

Les tests fonctionnels de la drosophile ont révélé un sous-ensemble avec une participation accrue aux NDD. Nous avons identifié 25 gènes montrant un biais pour l'autisme par rapport au handicap intellectuel et a mis en évidence un réseau associé à un autisme à haut fonctionnement (QI >100).  

Le suivi clinique pour NAA15, KMT5B et ASH1L a mis en évidence de nouvelles formes de maladie syndromiques et non syndromiques.

Nat Genet. 2017 Apr;49(4):515-526. doi: 10.1038/ng.3792. Epub 2017 Feb 13.

Targeted sequencing identifies 91 neurodevelopmental-disorder risk genes with autism and developmental-disability biases

Stessman HA¹, Xiong B^1,2, Coe BP¹, Wang T³, Hoekzema K¹, Fenckova M^4,5, Kvarnung M^6,7, Gerdts J⁸, Trinh S⁸, Cosemans N⁹, Vives L¹, Lin J¹, Turner TN¹, Santen G¹⁰, Ruivenkamp C¹⁰, Kriek M¹⁰, van Haeringen A¹⁰, Aten E¹⁰, Friend K^11,12, Liebelt J¹³, Barnett C¹³, Haan E^11,13, Shaw M¹¹, Gecz J^11,12,14, Anderlid BM^6,7, Nordgren A^6,7, Lindstrand A^6,7, Schwartz C¹⁵, Kooy RF¹⁶, Vandeweyer G¹⁶, Helsmoortel C¹⁶, Romano C¹⁷, Alberti A¹⁷, Vinci M¹⁸, Avola E¹⁷, Giusto S¹⁹, Courchesne E²⁰, Pramparo T²⁰, Pierce K²⁰, Nalabolu S²⁰, Amaral DG²¹, Scheffer IE^22,23,24, Delatycki MB^22,25,26, Lockhart PJ^22,26, Hormozdiari F²⁷, Harich B^4,5, Castells-Nobau A^4,5, Xia K³, Peeters H⁹, Nordenskjöld M^6,7, Schenck A^4,5, Bernier RA⁸, Eichler EE^1,28.

Author information

1

Department of Genome Sciences, University of Washington, Seattle, Washington, USA.

2

Department of Forensic Medicine and Institute of Brain Research, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

3

State Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, China.

4

Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands.

5

Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.

6

Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.

7

Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.

8

Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington, USA.

9

Centre for Human Genetics, KU Leuven and Leuven Autism Research (LAuRes), Leuven, Belgium.

10

Department of Clinical Genetics, Leiden University Medical Center (LUMC), Leiden, the Netherlands.

11

School of Medicine and the Robinson Research Institute, the University of Adelaide at the Women's and Children's Hospital, Adelaide, South Australia, Australia.

12

Genetics and Molecular Pathology, SA Pathology, Adelaide, South Australia, Australia.

13

South Australian Clinical Genetics Service, SA Pathology (at the Women's and Children's Hospital), Adelaide, South Australia, Australia.

14

South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia.

15

Center for Molecular Studies, J.C. Self Research Institute of Human Genetics, Greenwood Genetic Center, Greenwood, South Carolina, USA.

16

Department of Medical Genetics, University of Antwerp, Antwerp, Belgium.

17

Unit of Pediatrics &Medical Genetics, IRCCS Associazione Oasi Maria Santissima, Troina, Italy.

18

Laboratory of Medical Genetics, IRCCS Associazione Oasi Maria Santissima, Troina, Italy.

19

Unit of Neurology, IRCCS Associazione Oasi Maria Santissima, Troina, Italy.

20

Department of Neurosciences, UC San Diego Autism Center, School of Medicine, University of California San Diego, La Jolla, California, USA.

21

MIND Institute and the University of California Davis School of Medicine, Sacramento, California, USA.

22

Department of Paediatrics, University of Melbourne, Royal Children's Hospital, Melbourne, Victoria, Australia.

23

Department of Medicine, University of Melbourne, Austin Health, Melbourne, Victoria, Australia.

24

Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia.

25

Victorian Clinical Genetics Services, Parkville, Victoria, Australia.

26

Bruce Lefroy Centre for Genetic Health Research, Murdoch Children's Research Institute, Parkville, Victoria, Australia.

27

Department of Biochemistry and Molecular Medicine, University of California, Davis, Davis, California, USA.

28

Howard Hughes Medical Institute, Seattle, Washington, USA.

Abstract

Gene-disruptive mutations contribute to the biology of neurodevelopmental disorders (NDDs), but most of the related pathogenic genes are not known. We sequenced 208 candidate genes from >11,730 cases and >2,867 controls. We identified 91 genes, including 38 new NDD genes, with an excess of de novo mutations or private disruptive mutations in 5.7% of cases. Drosophila functional assays revealed a subset with increased involvement in NDDs. We identified 25 genes showing a bias for autism versus intellectual disability and highlighted a network associated with high-functioning autism (full-scale IQ >100). Clinical follow-up for NAA15, KMT5B, and ASH1L highlighted new syndromic and nonsyndromic forms of disease.

PMID: 28191889

PMCID: PMC5374041  [Available on 2017-08-13]

DOI: 10.1038/ng.3792

Gènes candidats pour la susceptibilité héréditaire à l'autiste dans la population libanaise

Aperçu: G.M.

Le trouble du spectre de l'autisme (TSA) se caractérise par des comportements rituels répétitifs et une communication verbale / non verbale altérée. Beaucoup de gènes de sensibilité aux TSA impliqués dans les voies neuronales / développement du cerveau ont été identifiés. La population libanaise est idéale pour découvrir des gènes récessifs en raison de l'ascendance partagée et d'un taux élevé de mariages consanguins.

 Bien qu'une légère augmentation du nombre ait été observée chez les personnes avec un diagnostic de TSA et les membres de la famille par rapport aux témoins, il n'y avait pas de différences significatives dans les fréquences alléliques entre les personnes avec un diagnostic de TSA et les témoins (C / TTCTG: valeur γ2 = 0,014; p = 0,904). 

 Le polymorphisme CNTNAP2 identifié dans cette population, par conséquent, n'est pas lié au phénotype TSA.

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Sci Rep. 2017 Mar 30;7:45336. doi: 10.1038/srep45336.

Candidate Genes for Inherited Autism Susceptibility in the Lebanese Population

Kourtian S^1,2, Soueid J¹, Makhoul NJ¹, Guisso DR¹, Chahrour M³, Boustany RN^1,4.

Author information

1

American University of Beirut Medical Center Special Kids Clinic, Neurogenetics Program and Division of Pediatric Neurology, Lebanon.

2

Department of Biological and Environmental Sciences, Faculty of Science, Beirut Arab University, Lebanon.

3

Eugene McDermott Center for Human Growth and Development, Departments of Neuroscience and Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA.

4

Biochemistry and Molecular Genetics, American university of Beirut, Lebanon.

Abstract

Autism spectrum disorder (ASD) is characterized by ritualistic-repetitive behaviors and impaired verbal/non-verbal communication. Many ASD susceptibility genes implicated in neuronal pathways/brain development have been identified. The Lebanese population is ideal for uncovering recessive genes because of shared ancestry and a high rate of consanguineous marriages. Aims here are to analyze for published ASD genes and uncover novel inherited ASD susceptibility genes specific to the Lebanese. We recruited 36 ASD families (ASD: 37, unaffected parents: 36, unaffected siblings: 33) and 100 unaffected Lebanese controls. Cytogenetics 2.7 M Microarrays/CytoScan™ HD arrays allowed mapping of homozygous regions of the genome. The CNTNAP2 gene was screened by Sanger sequencing. Homozygosity mapping uncovered DPP4, TRHR, and MLF1 as novel candidate susceptibility genes for ASD in the Lebanese. Sequencing of hot spot exons in CNTNAP2 led to discovery of a 5 bp insertion in 23/37 ASD patients. This mutation was present in unaffected family members and unaffected Lebanese controls. Although a slight increase in number was observed in ASD patients and family members compared to controls, there were no significant differences in allele frequencies between affecteds and controls (C/TTCTG: γ² value = 0.014; p = 0.904). The CNTNAP2 polymorphism identified in this population, hence, is not linked to the ASD phenotype.

PMID: 28358038

DOI: 10.1038/srep45336