Identification of common predisposing loci to hematopoietic cancers in four dog breeds

Histiocytic sarcoma (HS) is a rare but aggressive cancer in both humans and dogs. The spontaneous canine model, which has clinical, epidemiological, and histological similarities with human HS and specific breed predispositions, provides a unique opportunity to unravel the genetic basis of this cancer. In this study, we aimed to identify germline risk factors associated with the development of HS in canine-predisposed breeds. We used a methodology that combined several genome-wide association studies in a multi-breed and multi-cancer approach as well as targeted next-generation sequencing, and imputation We combined several dog breeds (Bernese mountain dogs, Rottweilers, flat-coated retrievers, and golden retrievers), and three hematopoietic cancers (HS, lymphoma, and mast cell tumor). Results showed that we not only refined the previously identified HS risk CDKN2A locus, but also identified new loci on canine chromosomes 2, 5, 14, and 20. Capture and targeted sequencing of specific loci suggested the existence of regulatory variants in non-coding regions and methylation mechanisms linked to risk haplotypes, which lead to strong cancer predisposition in specific dog breeds. We also showed that these canine cancer predisposing loci appeared to be due to the additive effect of several risk haplotypes involved in other hematopoietic cancers such as lymphoma or mast cell tumors as well. This illustrates the pleiotropic nature of these canine cancer loci as observed in human oncology, thereby reinforcing the interest of predisposed dog breeds to study cancer initiation and progression.

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The tree that hides the forest: identification of common predisposing loci in several hematopoietic cancers and several dog breeds

10.1101/2020.07.23.214007 ◽

2020 ◽

Author(s):

Benoit Hédan ◽

Edouard Cadieu ◽

Maud Rimbault ◽

Amaury Vaysse ◽

Patrick Devauchelle ◽

...

Keyword(s):

Mast Cell ◽

Association Studies ◽

Canine Model ◽

Cell Tumor ◽

Risk Haplotype ◽

Genome Wide Association Studies ◽

Targeted Next Generation Sequencing ◽

Regulatory Variants ◽

Mast Cell Tumor ◽

Canine Cancer

AbstractHistiocytic sarcoma (HS) is a rare but aggressive cancer in humans and dogs. The spontaneous canine model, with the clinical, epidemiological and histological similarities with human HS and specific breed predispositions, is a unique model/opportunity to unravel the genetic bases of this cancer. In this study, we aimed to identify germline risk factors associated with the development of HS in canine predisposed breeds. We used a methodology that combined several genome-wide association studies in a multi-breed and multi-cancer approach, as well as targeted next generation sequencing, and imputation combining several breeds (Bernese mountain dog, Rottweiler, flat coated retriever and golden retriever) and three haematopoietic cancers (HS, lymphoma and mast cell tumor). Results showed that we not only refined the previously identified HS risk CDKN2A locus but we identified new loci on canine chromosomes 2, 5, 12, 14, 20, 26 and X. Capture and targeted sequencing of specific loci pointed towards the existence of regulatory variants in non coding regions and/or methylation mechanisms linked to risk haplotypes, leading to strong cancer predispositions in specific dog breeds. Our results showed that these canine cancer predisposing loci appear to be due to the additive effect of several risk haplotype involved also in other haematopoietic cancers such lymphoma or mast cell tumor, illustrating the pleiotropic nature of these canine cancer loci as observed in human oncology, thus reinforcing the interest of predisposed dog breeds to study cancer initiation and progression.

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Cutaneous Tumors in Swiss Dogs: Retrospective Data From the Swiss Canine Cancer Registry, 2008–2013

Veterinary Pathology ◽

10.1177/0300985818789466 ◽

2018 ◽

Vol 55 (6) ◽

pp. 809-820 ◽

Cited By ~ 4

Author(s):

Ramona Graf ◽

Andreas Pospischil ◽

Franco Guscetti ◽

Daniela Meier ◽

Monika Welle ◽

...

Keyword(s):

Mast Cell ◽

Nova Scotia ◽

Cancer Registry ◽

Soft Tissue Sarcomas ◽

Population Data ◽

Cancer Registries ◽

Mast Cell Tumors ◽

Melanocytic Tumors ◽

Canine Cancer ◽

Tumor Types

Data collected in animal cancer registries comprise extensive and valuable information, even more so when evaluated in context with precise population data. The authors evaluated 11 740 canine skin tumors collected in the Swiss Canine Cancer Registry from 2008–2013, considering data on breed, sex, age, and anatomic locations. Their incidence rate (IR) per 100 000 dogs/year in the Swiss dog population was calculated based on data from the official and mandatory Swiss dog registration database ANIS. The most common tumor types were mast cell tumors (16.35%; IR, 60.3), lipomas (12.47%; IR, 46.0), hair follicle tumors (12.34%; IR, 45.5), histiocytomas (12.10%; IR, 44.6), soft tissue sarcomas (10.86%; IR, 40.1), and melanocytic tumors (8.63%; IR, 31.8) with >1000 tumors per type. The average IR of all tumor types across the 227 registered breeds was 372.2. The highest tumor incidence was found in the Giant Schnauzer (IR, 1616.3), the Standard Schnauzer (IR, 1545.4), the Magyar Vizsla (IR, 1534.6), the Rhodesian Ridgeback (IR, 1445.0), the Nova Scotia Duck Tolling Retriever (IR, 1351.7), and the Boxer (IR, 1350.0). Mixed-breed dogs (IR, 979.4) had an increased IR compared to the average of all breeds. Previously reported breed predispositions for most tumor types were confirmed. Nevertheless, the data also showed an increased IR for mast cell tumors and melanocytic tumors in the Nova Scotia Duck Tolling Retriever and for histiocytomas in the Flat Coated Retriever. The results from this study can be taken into consideration when selecting purebred dogs for breeding to improve a breed’s health.

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A comprehensive integrated post-GWAS analysis of Type 1 diabetes reveals enhancer-based immune dysregulation

PLoS ONE ◽

10.1371/journal.pone.0257265 ◽

2021 ◽

Vol 16 (9) ◽

pp. e0257265

Author(s):

Seung-Soo Kim ◽

Adam D. Hudgins ◽

Jiping Yang ◽

Yizhou Zhu ◽

Zhidong Tu ◽

...

Keyword(s):

Type 1 Diabetes ◽

Target Genes ◽

Association Studies ◽

Regulatory Elements ◽

Immune Dysregulation ◽

Specific Gene ◽

Genome Wide Association Studies ◽

Gwas Analysis ◽

Regulatory Variants

Type 1 diabetes (T1D) is an organ-specific autoimmune disease, whereby immune cell-mediated killing leads to loss of the insulin-producing β cells in the pancreas. Genome-wide association studies (GWAS) have identified over 200 genetic variants associated with risk for T1D. The majority of the GWAS risk variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes substantially contribute to T1D. However, identification of causal regulatory variants associated with T1D risk and their affected genes is challenging due to incomplete knowledge of non-coding regulatory elements and the cellular states and processes in which they function. Here, we performed a comprehensive integrated post-GWAS analysis of T1D to identify functional regulatory variants in enhancers and their cognate target genes. Starting with 1,817 candidate T1D SNPs defined from the GWAS catalog and LDlink databases, we conducted functional annotation analysis using genomic data from various public databases. These include 1) Roadmap Epigenomics, ENCODE, and RegulomeDB for epigenome data; 2) GTEx for tissue-specific gene expression and expression quantitative trait loci data; and 3) lncRNASNP2 for long non-coding RNA data. Our results indicated a prevalent enhancer-based immune dysregulation in T1D pathogenesis. We identified 26 high-probability causal enhancer SNPs associated with T1D, and 64 predicted target genes. The majority of the target genes play major roles in antigen presentation and immune response and are regulated through complex transcriptional regulatory circuits, including those in HLA (6p21) and non-HLA (16p11.2) loci. These candidate causal enhancer SNPs are supported by strong evidence and warrant functional follow-up studies.

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Cytology of Canine Cutaneous Round Cell Tumors

Veterinary Pathology ◽

10.1177/030098587901600605 ◽

1979 ◽

Vol 16 (6) ◽

pp. 673-679 ◽

Cited By ~ 35

Author(s):

J. R. Duncan ◽

K. W. Prasse

Keyword(s):

Mast Cell ◽

Final Diagnosis ◽

Cell Tumor ◽

Histologic Examination ◽

Round Cell ◽

Mast Cell Tumors ◽

Mast Cell Tumor ◽

Round Cell Tumors

Sixty-four canine cutaneous round cell tumors were divided into 25 mast cell tumors, 15 histiocytomas, nine cutaneous lymphosarcomas and 15 transmissible venereal tumors. The final diagnosis was made from cytologic, clinical and histologic findings. Cytologic features were significantly distinctive in mast cell tumor, transmissible venereal tumor, and most cases of histiocytoma and lymphosarcoma to allow a diagnostic opinion. This opinion was supported by subsequent histologic examination. In some instances cytology was considered essential in rendering a diagnostic opinion even though histology was available.

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Abstract 367: Extreme High-Density Lipoprotein Cholesterol Genetics: An Assortment of Large and Small Polygenic Effects

Arteriosclerosis Thrombosis and Vascular Biology ◽

10.1161/atvb.37.suppl_1.367 ◽

2017 ◽

Vol 37 (suppl_1) ◽

Author(s):

Jacqueline S Dron ◽

Jian Wang ◽

Cécile Low-Kam ◽

Sumeet A Khetarpal ◽

John F Robinson ◽

...

Keyword(s):

Large Scale ◽

Genetic Basis ◽

Rare Variants ◽

Association Studies ◽

Density Lipoprotein ◽

Copy Number Variations ◽

Genome Wide Association Studies ◽

Common Variants ◽

Targeted Next Generation Sequencing ◽

Common Genetic Variants

Rationale: Although HDL-C levels are known to have a complex genetic basis, most studies have focused solely on identifying rare variants with large phenotypic effects to explain extreme HDL-C phenotypes. Objective: Here we concurrently evaluate the contribution of both rare and common genetic variants, as well as large-scale copy number variations (CNVs), towards extreme HDL-C concentrations. Methods: In clinically ascertained patients with low ( N =136) and high ( N =119) HDL-C profiles, we applied our targeted next-generation sequencing panel (LipidSeq TM ) to sequence genes involved in HDL metabolism, which were subsequently screened for rare variants and CNVs. We also developed a novel polygenic trait score (PTS) to assess patients’ genetic accumulations of common variants that have been shown by genome-wide association studies to associate primarily with HDL-C levels. Two additional cohorts of patients with extremely low and high HDL-C (total N =1,746 and N =1,139, respectively) were used for PTS validation. Results: In the discovery cohort, 32.4% of low HDL-C patients carried rare variants or CNVs in primary ( ABCA1 , APOA1 , LCAT ) and secondary ( LPL , LMF1 , GPD1 , APOE ) HDL-C–altering genes. Additionally, 13.4% of high HDL-C patients carried rare variants or CNVs in primary ( SCARB1 , CETP , LIPC , LIPG ) and secondary ( APOC3 , ANGPTL4 ) HDL-C–altering genes. For polygenic effects, patients with abnormal HDL-C profiles but without rare variants or CNVs were ~2-fold more likely to have an extreme PTS compared to normolipidemic individuals, indicating an increased frequency of common HDL-C–associated variants in these patients. Similar results in the two validation cohorts demonstrate that this novel PTS successfully quantifies common variant accumulation, further characterizing the polygenic basis for extreme HDL-C phenotypes. Conclusions: Patients with extreme HDL-C levels have various combinations of rare variants, common variants, or CNVs driving their phenotypes. Fully characterizing the genetic basis of HDL-C levels must extend to encompass multiple types of genetic determinants—not just rare variants—to further our understanding of this complex, controversial quantitative trait.

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Regulatory Variants and Disease: The E-Cadherin −160C/A SNP as an Example

Molecular Biology International ◽

10.1155/2014/967565 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 17

Author(s):

Gongcheng Li ◽

Tiejun Pan ◽

Dan Guo ◽

Long-Cheng Li

Keyword(s):

Association Studies ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Protein Coding ◽

Regulate Gene Expression ◽

Regulatory Variants ◽

Genome Wide ◽

Regulatory Snps ◽

E Cadherin

Single nucleotide polymorphisms (SNPs) occurring in noncoding sequences have largely been ignored in genome-wide association studies (GWAS). Yet, amounting evidence suggests that many noncoding SNPs especially those that are in the vicinity of protein coding genes play important roles in shaping chromatin structure and regulate gene expression and, as such, are implicated in a wide variety of diseases. One of such regulatory SNPs (rSNPs) is the E-cadherin (CDH1) promoter −160C/A SNP (rs16260) which is known to affect E-cadherin promoter transcription by displacing transcription factor binding and has been extensively scrutinized for its association with several diseases especially malignancies. Findings from studying this SNP highlight important clinical relevance of rSNPs and justify their inclusion in future GWAS to identify novel disease causing SNPs.

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Limb amputation for surgical management of grade two mast cell tumor on digit of labrador retriever

ARSHI Veterinary Letters ◽

10.29244/avl.3.4.67-68 ◽

2019 ◽

Vol 3 (4) ◽

pp. 67-68

Author(s):

Tri Ayu Kristianty ◽

Siti Zaenab ◽

Osye Syanita Alamsari ◽

Sitaria Siallagan ◽

Sukmasari Arifah ◽

...

Keyword(s):

Mast Cell ◽

Tumor Grade ◽

Punch Biopsy ◽

Axillary Node ◽

Cell Tumor ◽

Skin Tumors ◽

Labrador Retriever ◽

Limb Amputation ◽

Mast Cell Tumors ◽

Mast Cell Tumor

The Labrador retriever came to My vets animal clinic Bumi Serpong Damai with mass on digit for a month. Punch biopsy procedure was performed to differentiate the type of the cells involved. The histological report diagnosed mast cell tumor grade 2. Mast cell tumors are one of the most common skin tumors in dogs, its account for approximately 20-25% of skin tumors in dogs. Mast cell tumors can be classified as grade 1, 2 and 3 by histological assesment. Hematology, blood chemistry, chest radiography and abdomen ultrasound were taken to evaluate metastasis condition of the tumor and the results were normal. Mast cell tumors are corrected by surgical, and post-operative survival time is related to the degree of differentiation. Limb amputation was taken as an option to prevent the spread of tumor to the nearest lymph node, namely the axillary node.

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Integrating comprehensive functional annotations to boost power and accuracy in gene-based association analysis

PLoS Genetics ◽

10.1371/journal.pgen.1009060 ◽

2020 ◽

Vol 16 (12) ◽

pp. e1009060

Author(s):

Corbin Quick ◽

Xiaoquan Wen ◽

Gonçalo Abecasis ◽

Michael Boehnke ◽

Hyun Min Kang

Keyword(s):

Association Analysis ◽

Association Studies ◽

Early Gene ◽

Genome Wide Association Studies ◽

Functional Annotations ◽

Regulatory Variants ◽

Causal Genes ◽

And Performance ◽

The Uk ◽

Coding Variants

Gene-based association tests aggregate genotypes across multiple variants for each gene, providing an interpretable gene-level analysis framework for genome-wide association studies (GWAS). Early gene-based test applications often focused on rare coding variants; a more recent wave of gene-based methods, e.g. TWAS, use eQTLs to interrogate regulatory associations. Regulatory variants are expected to be particularly valuable for gene-based analysis, since most GWAS associations to date are non-coding. However, identifying causal genes from regulatory associations remains challenging and contentious. Here, we present a statistical framework and computational tool to integrate heterogeneous annotations with GWAS summary statistics for gene-based analysis, applied with comprehensive coding and tissue-specific regulatory annotations. We compare power and accuracy identifying causal genes across single-annotation, omnibus, and annotation-agnostic gene-based tests in simulation studies and an analysis of 128 traits from the UK Biobank, and find that incorporating heterogeneous annotations in gene-based association analysis increases power and performance identifying causal genes.

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Predicting target genes of non-coding regulatory variants with IRT

Bioinformatics ◽

10.1093/bioinformatics/btaa254 ◽

2020 ◽

Vol 36 (16) ◽

pp. 4440-4448 ◽

Cited By ~ 1

Author(s):

Zhenqin Wu ◽

Nilah M Ioannidis ◽

James Zou

Keyword(s):

Target Genes ◽

Cross Validation ◽

Learning Algorithm ◽

Association Studies ◽

Characteristic Curve ◽

Gc Content ◽

Supplementary Information ◽

Genome Wide Association Studies ◽

Regulatory Variants ◽

Coding Variants

Abstract Summary Interpreting genetic variants of unknown significance (VUS) is essential in clinical applications of genome sequencing for diagnosis and personalized care. Non-coding variants remain particularly difficult to interpret, despite making up a large majority of trait associations identified in genome-wide association studies (GWAS) analyses. Predicting the regulatory effects of non-coding variants on candidate genes is a key step in evaluating their clinical significance. Here, we develop a machine-learning algorithm, Inference of Connected expression quantitative trait loci (eQTLs) (IRT), to predict the regulatory targets of non-coding variants identified in studies of eQTLs. We assemble datasets using eQTL results from the Genotype-Tissue Expression (GTEx) project and learn to separate positive and negative pairs based on annotations characterizing the variant, gene and the intermediate sequence. IRT achieves an area under the receiver operating characteristic curve (ROC-AUC) of 0.799 using random cross-validation, and 0.700 for a more stringent position-based cross-validation. Further evaluation on rare variants and experimentally validated regulatory variants shows a significant enrichment in IRT identifying the true target genes versus negative controls. In gene-ranking experiments, IRT achieves a top-1 accuracy of 50% and top-3 accuracy of 90%. Salient features, including GC-content, histone modifications and Hi-C interactions are further analyzed and visualized to illustrate their influences on predictions. IRT can be applied to any VUS of interest and each candidate nearby gene to output a score reflecting the likelihood of regulatory effect on the expression level. These scores can be used to prioritize variants and genes to assist in patient diagnosis and GWAS follow-up studies. Availability and implementation Codes and data used in this work are available at https://github.com/miaecle/eQTL_Trees. Supplementary information Supplementary data are available at Bioinformatics online.

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