Contribution of 3D genome topological domains to genetic risk of cancers

Genome-wide association studies have identified statistical associations between various diseases, including cancers, and a large number of single-nucleotide polymorphisms (SNPs). However, they provide no direct explanation of the mechanisms underlying the association. Based on the recent discovery that changes in 3-dimensional genome organization may have functional consequences on gene regulation favoring diseases, we investigated systematically the genome-wide distribution of disease-associated SNPs with respect to a specific feature of 3D genome organization: topologically-associating domains (TADs) and their borders. For each of 449 diseases, we tested whether the associated SNPs are present in TAD borders more often than observed by chance, where chance (i.e. the null model in statistical terms) corresponds to the same number of pointwise loci drawn at random either in the entire genome, or in the entire set of disease-associated SNPs listed in the GWAS catalog. Our analysis shows that a fraction of diseases display such a preferential location of their risk loci. Moreover, cancers are relatively more frequent among these diseases, and this predominance is generally enhanced when considering only intergenic SNPs. The structure of SNP-based diseasome networks confirms that TAD border enrichment in risk loci differ between cancers and non-cancer diseases. Different TAD border enrichments are observed in embryonic stem cells and differentiated cells, which agrees with an evolution along embryogenesis of the 3D genome organization into topological domains. Our results suggest that, for certain diseases, part of the genetic risk lies in a local genetic variation affecting the genome partitioning in topologically-insulated domains. Investigating this possible contribution to genetic risk is particularly relevant in cancers. This study thus opens a way of interpreting genome-wide association studies, by distinguishing two types of disease-associated SNPs: one with a direct effect on an individual gene, the other acting in interplay with 3D genome organization.

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Contribution of 3D genome topological domains to genetic risk of cancers: a genome-wide computational study

10.21203/rs.3.rs-800781/v1 ◽

2021 ◽

Author(s):

Kim Philipp Jablonski ◽

Leopold Carron ◽

Julien Mozziconacci ◽

Thierry Forné ◽

Marc-Thorsten Hütt ◽

...

Keyword(s):

Genetic Risk ◽

Genome Organization ◽

Computational Study ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Topological Domains ◽

3D Genome ◽

Genome Wide ◽

A Genome

Abstract Background Genome-wide association studies have identified statistical associations between various diseases, including cancers, and a large number of single-nucleotide polymorphisms (SNPs). However, they provide no direct explanation of the mechanisms underlying the association. Based on the recent discovery that changes in 3-dimensional genome organization may have functional consequences on gene regulation favoring diseases, we investigated systematically the genome-wide distribution of disease-associated SNPs with respect to a specific feature of 3D genome organization: topologically-associating domains (TADs) and their borders. Results For each of 449 diseases, we tested whether the associated SNPs are present in TAD borders more often than observed by chance, where chance (i.e. the null model in statistical terms) corresponds to the same number of pointwise loci drawn at random either in the entire genome, or in the entire set of disease-associated SNPs listed in the GWAS catalog. Our analysis shows that a fraction of diseases displays such a preferential localization of their risk loci. Moreover, cancers are relatively more frequent among these diseases, and this predominance is generally enhanced when considering only intergenic SNPs. The structure of SNP-based diseasome networks confirms that localization of risk loci in TAD borders differ between cancers and non-cancer diseases. Furthermore, different TAD border enrichments are observed in embryonic stem cells and differentiated cells, consistent with changes in topological domains along embryogenesis and delineating their contribution to disease risk. Conclusions Our results suggest that, for certain diseases, part of the genetic risk lies in a local genetic variation affecting the genome partitioning in topologically-insulated domains. Investigating this possible contribution to genetic risk is particularly relevant in cancers. This study thus opens a way of interpreting genome-wide association studies, by distinguishing two types of disease-associated SNPs: one with a direct effect on an individual gene, the other acting in interplay with 3D genome organization.

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Contribution of 3D genome topological domains to genetic risk of cancers: a genome-wide computational study

Human Genomics ◽

10.1186/s40246-022-00375-2 ◽

2022 ◽

Vol 16 (1) ◽

Author(s):

Kim Philipp Jablonski ◽

Leopold Carron ◽

Julien Mozziconacci ◽

Thierry Forné ◽

Marc-Thorsten Hütt ◽

...

Keyword(s):

Genetic Risk ◽

Genome Organization ◽

Computational Study ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Topological Domains ◽

3D Genome ◽

Genome Wide ◽

A Genome

Abstract Background Genome-wide association studies have identified statistical associations between various diseases, including cancers, and a large number of single-nucleotide polymorphisms (SNPs). However, they provide no direct explanation of the mechanisms underlying the association. Based on the recent discovery that changes in three-dimensional genome organization may have functional consequences on gene regulation favoring diseases, we investigated systematically the genome-wide distribution of disease-associated SNPs with respect to a specific feature of 3D genome organization: topologically associating domains (TADs) and their borders. Results For each of 449 diseases, we tested whether the associated SNPs are present in TAD borders more often than observed by chance, where chance (i.e., the null model in statistical terms) corresponds to the same number of pointwise loci drawn at random either in the entire genome, or in the entire set of disease-associated SNPs listed in the GWAS catalog. Our analysis shows that a fraction of diseases displays such a preferential localization of their risk loci. Moreover, cancers are relatively more frequent among these diseases, and this predominance is generally enhanced when considering only intergenic SNPs. The structure of SNP-based diseasome networks confirms that localization of risk loci in TAD borders differs between cancers and non-cancer diseases. Furthermore, different TAD border enrichments are observed in embryonic stem cells and differentiated cells, consistent with changes in topological domains along embryogenesis and delineating their contribution to disease risk. Conclusions Our results suggest that, for certain diseases, part of the genetic risk lies in a local genetic variation affecting the genome partitioning in topologically insulated domains. Investigating this possible contribution to genetic risk is particularly relevant in cancers. This study thus opens a way of interpreting genome-wide association studies, by distinguishing two types of disease-associated SNPs: one with an effect on an individual gene, the other acting in interplay with 3D genome organization.

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Association analysis of juvenile idiopathic arthritis genetic susceptibility factors in Estonian patients

Clinical Rheumatology ◽

10.1007/s10067-021-05756-x ◽

2021 ◽

Author(s):

Tiit Nikopensius ◽

Priit Niibo ◽

Toomas Haller ◽

Triin Jagomägi ◽

Ülle Voog-Oras ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Juvenile Idiopathic Arthritis ◽

Autoimmune Diseases ◽

Genetic Risk ◽

Association Studies ◽

Control Sample ◽

Case Control ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide

Abstract Background Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic condition of childhood. Genetic association studies have revealed several JIA susceptibility loci with the strongest effect size observed in the human leukocyte antigen (HLA) region. Genome-wide association studies have augmented the number of JIA-associated loci, particularly for non-HLA genes. The aim of this study was to identify new associations at non-HLA loci predisposing to the risk of JIA development in Estonian patients. Methods We performed genome-wide association analyses in an entire JIA case–control sample (All-JIA) and in a case–control sample for oligoarticular JIA, the most prevalent JIA subtype. The entire cohort was genotyped using the Illumina HumanOmniExpress BeadChip arrays. After imputation, 16,583,468 variants were analyzed in 263 cases and 6956 controls. Results We demonstrated nominal evidence of association for 12 novel non-HLA loci not previously implicated in JIA predisposition. We replicated known JIA associations in CLEC16A and VCTN1 regions in the oligoarticular JIA sample. The strongest associations in the All-JIA analysis were identified at PRKG1 (P = 2,54 × 10−6), LTBP1 (P = 9,45 × 10−6), and ELMO1 (P = 1,05 × 10−5). In the oligoarticular JIA analysis, the strongest associations were identified at NFIA (P = 5,05 × 10−6), LTBP1 (P = 9,95 × 10−6), MX1 (P = 1,65 × 10−5), and CD200R1 (P = 2,59 × 10−5). Conclusion This study increases the number of known JIA risk loci and provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis. The reported loci are involved in molecular pathways of immunological relevance and likely represent genomic regions that confer susceptibility to JIA in Estonian patients. Key Points• Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease with heterogeneous presentation and genetic predisposition.• Present genome-wide association study for Estonian JIA patients is first of its kind in Northern and Northeastern Europe.• The results of the present study increase the knowledge about JIA risk loci replicating some previously described associations, so adding weight to their relevance and describing novel loci.• The study provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis.

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Faculty Opinions recommendation of Prediction of individual genetic risk to disease from genome-wide association studies.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.722875891.793562986 ◽

2019 ◽

Author(s):

John Nurnberger

Keyword(s):

Genetic Risk ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide

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Genome-wide association studies: a powerful tool for neurogenomics

Neurosurgical FOCUS ◽

10.3171/2010.10.focus09186 ◽

2010 ◽

Vol 28 (1) ◽

pp. E2 ◽

Cited By ~ 5

Author(s):

Matthew C. Cowperthwaite ◽

Deepankar Mohanty ◽

Mark G. Burnett

Keyword(s):

Neurological Diseases ◽

Association Studies ◽

Genome Wide Association ◽

Great Promise ◽

Genome Wide Association Studies ◽

Entire Genome ◽

Genome Wide ◽

New Generation ◽

Theoretical Issues ◽

Gwa Studies

As their power and utility increase, genome-wide association (GWA) studies are poised to become an important element of the neurosurgeon's toolkit for diagnosing and treating disease. In this paper, the authors review recent findings and discuss issues associated with gathering and analyzing GWA data for the study of neurological diseases and disorders, including those of neurosurgical importance. Their goal is to provide neurosurgeons and other clinicians with a better understanding of the practical and theoretical issues associated with this line of research. A modern GWA study involves testing hundreds of thousands of genetic markers across an entire genome, often in thousands of individuals, for any significant association with a particular disease. The number of markers assayed in a study presents several practical and theoretical issues that must be considered when planning the study. Genome-wide association studies show great promise in our understanding of the genes underlying common neurological diseases and disorders, as well as in leading to a new generation of genetic tests for clinicians.

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Prediction of individual genetic risk to disease from genome-wide association studies

Genome Research ◽

10.1101/gr.6665407 ◽

2007 ◽

Vol 17 (10) ◽

pp. 1520-1528 ◽

Cited By ~ 357

Author(s):

N. R. Wray ◽

M. E. Goddard ◽

P. M. Visscher

Keyword(s):

Genetic Risk ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide

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What is Next for the Genetics of Multiple Sclerosis?

Autoimmune Diseases ◽

10.4061/2011/519450 ◽

2011 ◽

Vol 2011 ◽

pp. 1-3 ◽

Cited By ~ 4

Author(s):

Sreeram V. Ramagopalan ◽

David A. Dyment

Keyword(s):

Multiple Sclerosis ◽

Genetic Risk ◽

Neurological Disease ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

New Genes ◽

Histocompatibility Complex ◽

Genome Wide ◽

The Common

We review here our current understanding of the genetic aetiology of the common complex neurological disease multiple sclerosis (MS). The strongest genetic risk factor for MS is the major histocompatibility complex which was identified in the 1970s. In 2011, after a number of genome-wide association studies have been completed and have identified approximately 20 new genes for MS, we ask the question—what is next for the genetics of MS?

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