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Auteur Daria SALYAKINA |
Documents disponibles écrits par cet auteur (2)
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A noise-reduction GWAS analysis implicates altered regulation of neurite outgrowth and guidance in autism / John P. HUSSMAN in Molecular Autism, (January 2011)
[article]
Titre : A noise-reduction GWAS analysis implicates altered regulation of neurite outgrowth and guidance in autism Type de document : Texte imprimé et/ou numérique Auteurs : John P. HUSSMAN, Auteur ; Ren-Hua CHUNG, Auteur ; Anthony J. GRISWOLD, Auteur ; James M. JAWORSKI, Auteur ; Daria SALYAKINA, Auteur ; Deqiong MA, Auteur ; Ioanna KONIDARI, Auteur ; Patrice L. WHITEHEAD, Auteur ; Jeffery M. VANCE, Auteur ; Eden R. MARTIN, Auteur ; Michael L. CUCCARO, Auteur ; John R. GILBERT, Auteur ; Jonathan L. HAINES, Auteur ; Margaret A. O. PERICAK-VANCE, Auteur Année de publication : 2011 Article en page(s) : 16 p. Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Background
Genome-wide Association Studies (GWAS) have proved invaluable for the identification of disease susceptibility genes. However, the prioritization of candidate genes and regions for follow-up studies often proves difficult due to false-positive associations caused by statistical noise and multiple-testing. In order to address this issue, we propose the novel GWAS noise reduction (GWAS-NR) method as a way to increase the power to detect true associations in GWAS, particularly in complex diseases such as autism.
Methods
GWAS-NR utilizes a linear filter to identify genomic regions demonstrating correlation among association signals in multiple datasets. We used computer simulations to assess the ability of GWAS-NR to detect association against the commonly used joint analysis and Fisher's methods. Furthermore, we applied GWAS-NR to a family-based autism GWAS of 597 families and a second existing autism GWAS of 696 families from the Autism Genetic Resource Exchange (AGRE) to arrive at a compendium of autism candidate genes. These genes were manually annotated and classified by a literature review and functional grouping in order to reveal biological pathways which might contribute to autism aetiology.
Results
Computer simulations indicate that GWAS-NR achieves a significantly higher classification rate for true positive association signals than either the joint analysis or Fisher's methods and that it can also achieve this when there is imperfect marker overlap across datasets or when the closest disease-related polymorphism is not directly typed. In two autism datasets, GWAS-NR analysis resulted in 1535 significant linkage disequilibrium (LD) blocks overlapping 431 unique reference sequencing (RefSeq) genes. Moreover, we identified the nearest RefSeq gene to the non-gene overlapping LD blocks, producing a final candidate set of 860 genes. Functional categorization of these implicated genes indicates that a significant proportion of them cooperate in a coherent pathway that regulates the directional protrusion of axons and dendrites to their appropriate synaptic targets.
Conclusions
As statistical noise is likely to particularly affect studies of complex disorders, where genetic heterogeneity or interaction between genes may confound the ability to detect association, GWAS-NR offers a powerful method for prioritizing regions for follow-up studies. Applying this method to autism datasets, GWAS-NR analysis indicates that a large subset of genes involved in the outgrowth and guidance of axons and dendrites is implicated in the aetiology of autism.En ligne : http://dx.doi.org/10.1186/2040-2392-2-4 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=121
in Molecular Autism > (January 2011) . - 16 p.[article] A noise-reduction GWAS analysis implicates altered regulation of neurite outgrowth and guidance in autism [Texte imprimé et/ou numérique] / John P. HUSSMAN, Auteur ; Ren-Hua CHUNG, Auteur ; Anthony J. GRISWOLD, Auteur ; James M. JAWORSKI, Auteur ; Daria SALYAKINA, Auteur ; Deqiong MA, Auteur ; Ioanna KONIDARI, Auteur ; Patrice L. WHITEHEAD, Auteur ; Jeffery M. VANCE, Auteur ; Eden R. MARTIN, Auteur ; Michael L. CUCCARO, Auteur ; John R. GILBERT, Auteur ; Jonathan L. HAINES, Auteur ; Margaret A. O. PERICAK-VANCE, Auteur . - 2011 . - 16 p.
Langues : Anglais (eng)
in Molecular Autism > (January 2011) . - 16 p.
Index. décimale : PER Périodiques Résumé : Background
Genome-wide Association Studies (GWAS) have proved invaluable for the identification of disease susceptibility genes. However, the prioritization of candidate genes and regions for follow-up studies often proves difficult due to false-positive associations caused by statistical noise and multiple-testing. In order to address this issue, we propose the novel GWAS noise reduction (GWAS-NR) method as a way to increase the power to detect true associations in GWAS, particularly in complex diseases such as autism.
Methods
GWAS-NR utilizes a linear filter to identify genomic regions demonstrating correlation among association signals in multiple datasets. We used computer simulations to assess the ability of GWAS-NR to detect association against the commonly used joint analysis and Fisher's methods. Furthermore, we applied GWAS-NR to a family-based autism GWAS of 597 families and a second existing autism GWAS of 696 families from the Autism Genetic Resource Exchange (AGRE) to arrive at a compendium of autism candidate genes. These genes were manually annotated and classified by a literature review and functional grouping in order to reveal biological pathways which might contribute to autism aetiology.
Results
Computer simulations indicate that GWAS-NR achieves a significantly higher classification rate for true positive association signals than either the joint analysis or Fisher's methods and that it can also achieve this when there is imperfect marker overlap across datasets or when the closest disease-related polymorphism is not directly typed. In two autism datasets, GWAS-NR analysis resulted in 1535 significant linkage disequilibrium (LD) blocks overlapping 431 unique reference sequencing (RefSeq) genes. Moreover, we identified the nearest RefSeq gene to the non-gene overlapping LD blocks, producing a final candidate set of 860 genes. Functional categorization of these implicated genes indicates that a significant proportion of them cooperate in a coherent pathway that regulates the directional protrusion of axons and dendrites to their appropriate synaptic targets.
Conclusions
As statistical noise is likely to particularly affect studies of complex disorders, where genetic heterogeneity or interaction between genes may confound the ability to detect association, GWAS-NR offers a powerful method for prioritizing regions for follow-up studies. Applying this method to autism datasets, GWAS-NR analysis indicates that a large subset of genes involved in the outgrowth and guidance of axons and dendrites is implicated in the aetiology of autism.En ligne : http://dx.doi.org/10.1186/2040-2392-2-4 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=121 Variants in several genomic regions associated with asperger disorder / Daria SALYAKINA in Autism Research, 3-6 (December 2010)
[article]
Titre : Variants in several genomic regions associated with asperger disorder Type de document : Texte imprimé et/ou numérique Auteurs : Daria SALYAKINA, Auteur ; D.Q. MA, Auteur ; James M. JAWORSKI, Auteur ; Ioanna KONIDARI, Auteur ; Patrice L. WHITEHEAD, Auteur ; Robin K. HENSON, Auteur ; D. MARTINEZ, Auteur ; J.L. ROBINSON, Auteur ; S. SACHAROW, Auteur ; Harry H. WRIGHT, Auteur ; Ruth K. ABRAMSON, Auteur ; John R. GILBERT, Auteur ; Michael L. CUCCARO, Auteur ; Margaret A. O. PERICAK-VANCE, Auteur Année de publication : 2010 Article en page(s) : p.303-310 Langues : Anglais (eng) Mots-clés : asperger susceptibility genetics Index. décimale : PER Périodiques Résumé : Asperger disorder (ASP) is one of the autism spectrum disorders (ASD) and is differentiated from autism largely on the absence of clinically significant cognitive and language delays. Analysis of a homogenous subset of families with ASP may help to address the corresponding effect of genetic heterogeneity on identifying ASD genetic risk factors. To examine the hypothesis that common variation is important in ASD, we performed a genome-wide association study (GWAS) in 124 ASP families in a discovery data set and 110 ASP families in a validation data set. We prioritized the top 100 association results from both cohorts by employing a ranking strategy. Novel regions on 5q21.1 (P = 9.7 × 10−7) and 15q22.1–q22.2 (P = 7.3 × 10−6) were our most significant findings in the combined data set. Three chromosomal regions showing association, 3p14.2 (P = 3.6 × 10−6), 3q25–26 (P = 6.0 × 10–5) and 3p23 (P = 3.3 × 10−4) overlapped linkage regions reported in Finnish ASP families, and eight association regions overlapped ASD linkage areas. Our findings suggest that ASP shares both ASD-related genetic risk factors, as well as has genetic risk factors unique to the ASP phenotype. En ligne : http://dx.doi.org/10.1002/aur.158 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=115
in Autism Research > 3-6 (December 2010) . - p.303-310[article] Variants in several genomic regions associated with asperger disorder [Texte imprimé et/ou numérique] / Daria SALYAKINA, Auteur ; D.Q. MA, Auteur ; James M. JAWORSKI, Auteur ; Ioanna KONIDARI, Auteur ; Patrice L. WHITEHEAD, Auteur ; Robin K. HENSON, Auteur ; D. MARTINEZ, Auteur ; J.L. ROBINSON, Auteur ; S. SACHAROW, Auteur ; Harry H. WRIGHT, Auteur ; Ruth K. ABRAMSON, Auteur ; John R. GILBERT, Auteur ; Michael L. CUCCARO, Auteur ; Margaret A. O. PERICAK-VANCE, Auteur . - 2010 . - p.303-310.
Langues : Anglais (eng)
in Autism Research > 3-6 (December 2010) . - p.303-310
Mots-clés : asperger susceptibility genetics Index. décimale : PER Périodiques Résumé : Asperger disorder (ASP) is one of the autism spectrum disorders (ASD) and is differentiated from autism largely on the absence of clinically significant cognitive and language delays. Analysis of a homogenous subset of families with ASP may help to address the corresponding effect of genetic heterogeneity on identifying ASD genetic risk factors. To examine the hypothesis that common variation is important in ASD, we performed a genome-wide association study (GWAS) in 124 ASP families in a discovery data set and 110 ASP families in a validation data set. We prioritized the top 100 association results from both cohorts by employing a ranking strategy. Novel regions on 5q21.1 (P = 9.7 × 10−7) and 15q22.1–q22.2 (P = 7.3 × 10−6) were our most significant findings in the combined data set. Three chromosomal regions showing association, 3p14.2 (P = 3.6 × 10−6), 3q25–26 (P = 6.0 × 10–5) and 3p23 (P = 3.3 × 10−4) overlapped linkage regions reported in Finnish ASP families, and eight association regions overlapped ASD linkage areas. Our findings suggest that ASP shares both ASD-related genetic risk factors, as well as has genetic risk factors unique to the ASP phenotype. En ligne : http://dx.doi.org/10.1002/aur.158 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=115