CRISPR-based genome and epigenome perturbation in stem cells to understand and reverse osteoarthritis risk

Osteoarthritis (OA) is a complex multi-factorial disorder, characterised by the painful breakdown of articular cartilage within the joints. The disease affects older individuals yet has a strong genetic component (30-50% heritability). To date, over 150 SNPs have been significantly associated with the disease via genome wide association studies (GWAS). Osteoporosis (OP) is a silent disease, characterised by a loss of bone density, leading to an increased incidence of fracture in patients. OP also has a strong genetic component (heritability estimates between 50-80%) and over 500 SNPs have been identified which significantly associate with increased disease risk.
Historically, GWAS have been difficult to interpret due to both the experimental methodology employed (the use of tag SNPs on genotyping microarrays) and the genetic complexity at the reported loci (i.e., areas of high linkage disequilibrium). However, genetic and epigenetic interactions can facilitate the identification of the target gene and mechanisms of pathogenesis through co-localization of quantitative trait loci (QTLs) with the reported variants, and functional follow up studies. A study recently published by the Rice group identified that, whilst OA is a disease affecting older people, the functional risk of OA development may be pre-programmed during skeletogenesis. This small-scale targeted study provided evidence that some loci may exert their functional impact early in life, with others contributing to disease later in the life course.
This project seeks to build on these findings by carrying out an epigenome-wide study of mQTLs in both cartilage and bone samples from the hips of OA patients, of those with neck of femur fracture (no OA, but presumably osteoporosis (OP) and in foetal hip bone and cartilage. We seek to identify clusters of loci which may share spatiotemporal impacts. The samples (n=312) have undergone genotyping via Illumina Global Screening Array (GSA), and their methylation status determined using an HumanMethylation EPIC array. We will analyse the data generated by this sequencing to identify mQTLs and undergo co-localisation analysis of the signals, aiming to prioritise genes and pathways that are involved in the development of OA. By interrogating the epigenome of the foetal cartilage and bone in comparison to the aged cartilage and bone from OA patients, we will gain a unique insight into the developmental origins of OA and OP.
We will then move on to functional studies to validate our findings and uncover the molecular mechanism behind how the identified genes contribute to disease. This will form the basis of in vivo analysis using primary human articular chondrocytes and osteoblasts (hACs and hOBs), immortalised adipose-derived stem cells (ad-MSCs), immortalised chondrocytes and osteoblasts (TC28a2, SaOS2) and a CRISPR-Cas9 toolbox to interrogate the genome and epigenome using precision editing.
During a planned 3-month placement with Prof. Farshid Guilak at the University of Washington in St. Louis we will translate our findings from ad-MSCs into human induced pluripotent stem cells, which can generate patient-matched OA models, to validate our findings.
The overarching aim of this work is to identify the functional genetic mechanisms underlying disease, the tissue-specificity of their impact, and the timepoint in the life course at which they exert their effects. This work will pave the way for the development of disease modifying OA drugs (DMOADs), where currently there is a lack of pharmacological cures. This may also allow for earlier treatment intervention, vital in progressive diseases such as OA and OP.