Epigenetic DNA Methylation Signatures Associated With the Severity of Paget's Disease of Bone

Genome-wide association study of growth curve parameters reveals novel genomic regions and candidate genes associated with metatarsal bone traits in chickens

The growth and development of chicken bones have an enormous impact on the health and production performance of chickens. However, the development pattern and genetic regulation of the chicken skeleton are poorly understood. This study aimed to evaluate metatarsal bone growth and development patterns in chickens via non-linear models, and to identify the genetic determinants of metatarsal bone traits using a genome-wide association study (GWAS) based on growth curve parameters. Data on metatarsal length (MeL) and metatarsal circumference (MeC) were obtained from 471 F2 chickens (generated by crossing broiler sires, derived from a line selected for high abdominal fat, with Baier layer dams) at 4, 6, 8, 10, and 12 weeks of age. Four non-linear models (Gompertz, Logistic, von Bertalanffy, and Brody) were used to fit the MeL and MeC growth curves. Subsequently, the estimated growth curve parameters of the mature MeL or MeC (A), time-scale parameter (b), and maturity rate (K) from the non-linear models were utilized as substitutes for the original bone data in GWAS. The Logistic and Brody models displayed the best goodness-of-fit for MeL and MeC, respectively. Single-trait and multi-trait GWASs based on the growth curve parameters of the Logistic and Brody models revealed 4 618 significant single nucleotide polymorphisms (SNPs), annotated to 332 genes, associated with metatarsal bone traits. The majority of these significant SNPs were located on Gallus gallus chromosome (GGA) 1 (167.433-176.318 Mb), GGA2 (96.791-103.543 Mb), GGA4 (65.003-83.104 Mb) and GGA6 (64.685-95.285 Mb). Notably, we identified 12 novel GWAS loci associated with chicken metatarsal bone traits, encompassing 35 candidate genes. In summary, the combination of single-trait and multi-trait GWASs based on growth curve parameters uncovered numerous genomic regions and candidate genes associated with chicken bone traits. The findings benefit an in-depth understanding of the genetic architecture underlying metatarsal growth and development in chickens.

Deciphering the role of immune cell composition in epigenetic age acceleration: Insights from cell-type deconvolution applied to human blood epigenetic clocks

Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health-related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA. We investigated associations of 12 immune cell types measured by cell-type deconvolution with EAA predicted by six widely-used DNA methylation clocks in data from >10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis. Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research. Our detailed map of immune cell type contributions serves as a resource for studies utilizing epigenetic clocks across diverse research fields, including aging-related diseases, precision medicine, and therapeutic interventions.

Paget's disease: a review of the epidemiology, etiology, genetics, and treatment

Paget's disease of bone (PDB) is the second most prevalent metabolic bone disorder worldwide, with a prevalence rate of 1.5%-8.3%. It is characterized by localized areas of accelerated, disorganized, and excessive bone production and turnover. Typically, PDB develops in the later stages of life, particularly in the late 50s, and affects men more frequently than women. PDB is a complex disease influenced by both genetic and environmental factors. PDB has a complex genetic basis involving multiple genes, with SQSTM1 being the gene most frequently associated with its development. Mutations affecting the UBA domain of SQSTM1 have been detected in both familial and sporadic PDB cases, and these mutations are often associated with severe clinical expression. Germline mutations in other genes such as TNFRSF11A, ZNF687 and PFN1, have also been associated with the development of the disease. Genetic association studies have also uncovered several PDB predisposing risk genes contributing to the disease pathology and severity. Epigenetic modifications of genes involved in bone remodelling and regulation, including RANKL, OPG, HDAC2, DNMT1, and SQSTM1, have been implicated in the development and progression of Paget's disease of bone, providing insight into the molecular basis of the disease and potential targets for therapeutic intervention. Although PDB has a tendency to cluster within families, the variable severity of the disease across family members, coupled with decreasing incidence rates, indicates that environmental factors may also play a role in the pathophysiology of PDB. The precise nature of these environmental triggers and how they interact with genetic determinants remain poorly understood. Fortunately, majority of PDB patients can achieve long-term remission with an intravenous infusion of aminobisphosphonates, such as zoledronic acid. In this review, we discuss aspects like clinical characteristics, genetic foundation, and latest updates in PDB research.