Biology subjects

Hatzikotoulas, K.

Publications and source records attributed to Hatzikotoulas, K..

8 recordsLinked to original sources

bioRxiv2022

A community driven GWAS summary statistics standard

Summary statistics from genome-wide association studies (GWAS) represent a huge potential for research. A challenge for researchers in this field is the access and sharing of summary statistics data due to a lack of standards for the data content and file format. For this reason, the GWAS Catalog hosted a series of meetings in 2021 with summary statistics stakeholders to guide the development of a standard format. The key requirements from the stakeholders were for a standard that contained key data elements to be able to support a wide range of data analyses, required low bioinformatics skills for file access and generation, to have easily accessible metadata, and unambiguous and interoperable data. Here, we define the specifications for the first version of the GWAS-SSF format, which was developed to meet the requirements discussed with the community. GWAS-SSF consists of a tab-separated data file with well-defined fields and an accompanying metadata file.

bioinformatics↗

bioRxiv2020

Osteocyte Transcriptome Mapping Identifies a Molecular Landscape Controlling Skeletal Homeostasis and Susceptibility to Skeletal Disease

Osteocytes are master regulators of the skeleton. We mapped the transcriptome of osteocytes from different skeletal sites, across age and sexes in mice to reveal genes and molecular programs that control this complex cellular-network. We define an osteocyte transcriptome signature of 1239 genes that distinguishes osteocytes from other cells. 77% have no previously known role in the skeleton and are enriched for genes regulating neuronal network formation, suggesting this program is important in osteocyte communication. We evaluated 19 skeletal parameters in 733 knockout mouse lines and reveal 26 osteocyte transcriptome signature genes that control bone structure and function. We showed osteocyte transcriptome signature genes are enriched for human orthologs that cause monogenic skeletal disorders (P=2.4x10-22) and are associated with the polygenic diseases osteoporosis (P=1.8x10-13) and osteoarthritis (P=1.6x10-7). Thus, we reveal the molecular landscape that regulates osteocyte network formation and function and establish the importance of osteocytes in human skeletal disease.

systems biology↗

bioRxiv2019

Genome-wide association and functional analyses identify CASC20 and KIF26B as target loci in heterotopic ossification

Heterotopic ossification (HO) is bone formation that occurs after trauma within tissues that do not normally have the property of ossification, resulting in pain and disability. The genetic architecture of HO remains unclear. In the first genome-wide association studies of this disease, we identify the human-only long non-coding RNA-encoding gene CASC20 as a robust, replicating susceptibility locus for HO and KIF26B as a potential severity locus. We find that both CASC20 and KIF26B are expressed in human bone. Both CASC20 and KIF26B expression is upregulated upon BMP2 induced osteogenic differentiation in primary human mesenchymal stem cells, followed by RUNX2 and OSTERIX upregulation and mineralised nodule formation. A CRISPR-Cas9 mediated knockout of Kif26b inhibits BMP2-induced Runx2, Sp7/Osterix, Col1A1, Alp, and Bglap/Osteocalcin expression in a murine myocyte model of osteogenic trans-differentiation, and prevents mineralised nodule formation. These studies provide the first insights into the heritable biology of common, complex HO.

genetics↗

bioRxiv2018

Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank

Osteoarthritis is the most common musculoskeletal disease and the leading cause of disability globally. Here, we perform the largest genome-wide association study for osteoarthritis to date (77,052 cases and 378,169 controls), analysing 4 phenotypes: knee osteoarthritis, hip osteoarthritis, knee and/or hip osteoarthritis, and any osteoarthritis. We discover 64 signals, 52 of them novel, more than doubling the number of established disease loci. Six signals fine map to a single variant. We identify putative effector genes by integrating eQTL colocalization, fine-mapping, human rare disease, animal model, and osteoarthritis tissue expression data. We find enrichment for genes underlying monogenic forms of bone development diseases, and for the collagen formation and extracellular matrix organisation biological pathways. Ten of the likely effector genes, including TGFB1, FGF18, CTSK and IL11 have therapeutics approved or in clinical trials, with mechanisms of action supportive of evaluation for efficacy in osteoarthritis.

genetics↗

bioRxiv2018

Cohort-wide deep whole genome sequencing and the allelic architecture of complex traits

The role of rare variants in complex traits remains uncharted. Here, we conduct deep whole genome sequencing of 1,457 individuals from an isolated population, and test for rare variant burdens across six cardiometabolic traits. We identify a role for rare regulatory variation, which has hitherto been missed. We find evidence of rare variant burdens overlapping with, and mostly independent of established common variant signals (ADIPOQ and adiponectin, P=4.2x10-8; APOC3 and triglyceride levels, P=1.58x10-26; GGT1 and gamma-glutamyltransferase, P=2.3x10-6; UGT1A9 and bilirubin, P=1.9x10-8), and identify replicating evidence for a burden associated with triglyceride levels in FAM189A (P=2.26x10-8), indicating a role for this gene in lipid metabolism.

genetics↗

bioRxiv2017

The genetic architecture of osteoarthritis: insights from UK Biobank

Osteoarthritis is a common complex disease with huge public health burden. Here we perform a genome-wide association study for osteoarthritis using data across 16.5 million variants from the UK Biobank resource. Following replication and meta-analysis in up to 30,727 cases and 297,191 controls, we report 9 new osteoarthritis loci, in all of which the most likely causal variant is non-coding. For three loci, we detect association with biologically-relevant radiographic endophenotypes, and in five signals we identify genes that are differentially expressed in degraded compared to intact articular cartilage from osteoarthritis patients. We establish causal effects for higher body mass index, but not for triglyceride levels or type 2 diabetes liability, on osteoarthritis.

genetics↗

bioRxiv2017

Very low depth whole genome sequencing in complex trait association studies

MotivationVery low depth sequencing has been proposed as a cost-effective approach to capture low-frequency and rare variation in complex trait association studies. However, a full characterisation of the genotype quality and association power for very low depth sequencing designs is still lacking.\n\nResultsWe perform cohort-wide whole genome sequencing (WGS) at low depth in 1,239 individuals (990 at 1x depth and 249 at 4x depth) from an isolated population, and establish a robust pipeline for calling and imputing very low depth WGS genotypes from standard bioinformatics tools. Using genotyping chip, whole-exome sequencing (WES, 75x depth) and high-depth (22x) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1x WGS recapitulates 95.2% of variants found by imputed GWAS with an average minor allele concordance of 97% for common and low-frequency variants. In our study, 1x further allowed the discovery of 140,844 true low-frequency variants with 73% genotype concordance when compared to high-depth WGS data. Finally, using association results for 57 quantitative traits, we show that very low depth WGS is an efficient alternative to imputed GWAS chip designs, allowing the discovery of up to twice as many true association signals than the classical imputed GWAS design.\n\nSupplementary DataSupplementary Data are appended to this manuscript.

genetics↗

bioRxiv2017

The Genetic Epidemiology of Developmental Dysplasia of the Hip: A Genome-Wide Association Study Harnessing National Clinical Audit Data

BackgroundDevelopmental dysplasia of the hip (DDH) is a common, heritable condition characterised by abnormal formation of the hip joint, but has a poorly understood genetic architecture due to small sample sizes. We apply a novel case-ascertainment approach using national clinical audit (NCA) data to conduct the largest DDH genome-wide association study (GWAS) to date, and replicate our findings in independent cohorts.\n\nMethodsWe used the English National Joint Registry (NJR) dataset to collect DNA and conducted a GWAS in 770 DDH cases and 3364 controls. We tested the variant most strongly associated with DDH in independent replication cohorts comprising 1129 patients and 4652 controls.\n\nResultsThe heritable component of DDH attributable to common variants was 55% and distributed similarly across autosomal and the X-chromosomes. Variation within the GDF5 gene promoter was strongly and reproducibly associated with DDH (rs143384, OR 1.44 [95% CI 1.34-1.56], p=3.55x10-22). Two further replicating loci showed suggestive association with DDH near NFIB (rs4740554, OR 1.30 [95% CI 1.16-1.45], p=4.44x10-6) and LOXL4 (rs4919218, 1.19 [1.10-1.28] p=4.38x10-6). Through gene-based enrichment we identify GDF5, UQCC1, MMP24, RETSAT and PDRG1 association with DDH (p<1.2x10-7). Using the UK Biobank and arcOGEN cohorts to generate polygenic risk scores we find that risk alleles for hip osteoarthritis explain <0.5% of the variance in DDH susceptibility.\n\nConclusionUsing the NJR as a proof-of-principle, we describe the genetic architecture of DDH and identify several candidate intervention loci and demonstrate a scalable recruitment strategy for genetic studies that is transferrable to other complex diseases.\n\nKey MessagesO_LIWe report the first genome-wide scan for DDH in a European population, and the first to use national clinical audit data for case-ascertainment in complex disease.\nC_LIO_LIThe heritable component of DDH attributable to common variants is 55% and is distributed similarly across autosomal and the X-chromosomes.\nC_LIO_LIVariation within the GDF5 gene promoter is strongly and reproducibly associated with DDH, with fine-mapping indicating rs143384 as the likely casual variant.\nC_LIO_LIEnrichment analyses implicate GDF5, UQCC1, MMP24, RETSAT and PDRG1 as candidate targets for intervention in DDH.\nC_LIO_LIDDH shares little common genetic aetiology with idiopathic osteoarthritis of the hip, despite sharing variation within the GDF5 promoter as a common risk factor.\nC_LI

genetics↗