Abstract
The availability of large human datasets for genome-wide association studies (GWAS) and the advancement of sequencing technologies have boosted the identification of genetic variants in complex and rare diseases in the skeletal field. Yet, interpreting results from human association studies remains a challenge. To bridge the gap between genetic association and causality, a systematic functional investigation is necessary. Multiple unknowns exist for putative causal genes, including cellular localization of the molecular function. Intermediate traits (“endophenotypes”), e.g. molecular quantitative trait loci (molQTLs), are needed to identify mechanisms of underlying associations. Furthermore, index variants often reside in non-coding regions of the genome, therefore challenging for interpretation. Knowledge of non-coding variance (e.g. ncRNAs), repetitive sequences, and regulatory interactions between enhancers and their target genes is central for understanding causal genes in skeletal conditions. Animal models with deep skeletal phenotyping and cell culture models have already facilitated fine mapping of some association signals, elucidated gene mechanisms, and revealed disease-relevant biology. However, to accelerate research towards bridging the current gap between association and causality in skeletal diseases, alternative in vivo platforms need to be used and developed in parallel with the current -omics and traditional in vivo resources. Therefore, we argue that as a field we need to establish resource-sharing standards to collectively address complex research questions. These standards will promote data integration from various -omics technologies and functional dissection of human complex traits. In this mission statement, we review the current available resources and as a group propose a consensus to facilitate resource sharing using existing and future resources. Such coordination efforts will maximize the acquisition of knowledge from different approaches and thus reduce redundancy and duplication of resources. These measures will help to understand the pathogenesis of osteoporosis and other skeletal diseases towards defining new and more efficient therapeutic targets.
Highlights
Perspective of the GEMSTONE Consortium on Current and Future Approaches to Functional Validation for Skeletal Genetic Disease Using Cellular, Molecular and AnimalModeling Techniques
A series of large and well-powered studies have dramatically increased our appreciation of a multitude of genetic factors that influence skeletal diseases, including osteoporosis
genome-wide association studies (GWAS) and whole genome sequencing (WGS) analyses have transformed the genetic analysis of complex diseases in general and osteoporosis in particular
Summary
Proteomics Immunological quantification of targeted proteins from postmenopausal iliac bone biopsies [185, 186]. [192] Transcriptomics RNA-seq of transiliac bone biopsies and subchondral femoral head samples (Prijatelj et al.) publication in progress eQTL analysis of transiliac bone biopsies (Prijatelj, Reppe et al.) publication in progress RNA-seq of purified osteoblasts from male iliac bone biopsies [127] Microchip RNA profiling of postmenopausal transiliac bone biopsies [193] PCR based and microchip profiling of postmenopausal iliac or femoral bone biopsy ncRNAs. [195] Microchip profiling of postmenopausal intertrochanteric bone biopsies (10 with OA + 10 osteoporotic + 10 autopsies from controls) [196, 197] PCR profiling of postmenopausal intertrochanteric bone biopsies (25 osteoporotic with fracture + 29 with OA) [187] LC-MS analysis of young adult alveolar bone from two healthy females and two males (aged 15−21 years) [188] Stable isotope labeling by amino acids in cell culture (SILAC) analysis of primary cultured human osteoblasts co-cultured with human umbilical vein endothelial cells (HUVECs) [189] Shotgun proteomics (LC-MS) of archeological human bone from 4 adults and 2 infants [190] LC-MS/MS analysis of cranial suture samples stripped of periosteum from 5 infants (ages 3–12 months) [191] LC-MS/MS analysis of alveolar bone and dental cementum from 5 females and 2 males ranging from 20 to 30 years old. [192] Transcriptomics RNA-seq of transiliac bone biopsies and subchondral femoral head samples (Prijatelj et al.) publication in progress eQTL analysis of transiliac bone biopsies (Prijatelj, Reppe et al.) publication in progress RNA-seq of purified osteoblasts from male iliac bone biopsies [127] Microchip RNA profiling of postmenopausal transiliac bone biopsies [193] PCR based and microchip profiling of postmenopausal iliac or femoral bone biopsy ncRNAs. [194] Microchip RNA profiling of 19 spine and 5 iliac crest bone biopsies from 13 male donors. [195] Microchip profiling of postmenopausal intertrochanteric bone biopsies (10 with OA + 10 osteoporotic + 10 autopsies from controls) [196, 197] PCR profiling of postmenopausal intertrochanteric bone biopsies (25 osteoporotic with fracture + 29 with OA) [187]
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