The Farber Lab uses innovative systems genetics and genomics approaches to study complex bone phenotypes related to physiology and disease. We are interested in understanding how genetic variation influences cellular networks and how network changes alter physiology and disease. Ultimately, we hope to define and mechanistically understand the genetic determinants of bone strength and improve the clinical approach to osteoporosis and other bone diseases.
MAKING SENSE OF GWAS
Genome-wide association studies (GWASs) are powerful tools to dissect the genetic basis of a complex disease. In a GWAS, millions of genetic variants (single nucleotide polymorphisms (SNPs)) are typed in tens of thousands of individuals. These data are then used to identify regions of the human genome that contain genetic variants associated with disease. In the osteoporosis field, GWASs have identified dozens of loci for bone mineral density (BMD). The next step is to use these data to identify the genetic variants and genes responsible for the genetic effects. In the Farber lab, we are using both experimental and computational approaches to achieve this goal. We hope that the discovery of new genes could lead to the development of novel approaches to treat and prevent bone fragility.
SYSTEMS GENETICS OF BONE STRENGTH
Many bone-related disorders, like osteoporosis, are characterized by decreased bone strength. As the genetic determinants of bone strength are not well understood, we in the Farber Lab aim to identify some of them, in a systems genetics context. This project aims to do so by using the Diversity Outbred (DO) mouse population, a highly polymorphic, genetically complex mouse stock that is an excellent model for precision genetics and medicine. In collaboration with the Rosen Lab (Maine Medical Center Research Institute), the Bouxsein Lab (Beth Israel Deaconess Medical Center), the Horowitz Lab (Yale School of Medicine) and the Tommasini Lab (Yale School of Medicine), over 60 traits will be measured in 800 DO mice, in order to identify quantitative trait loci (QTL) and expression quantitative trait loci (eQTL) affecting bone strength. Network approaches, namely Weighted Gene Co-Expression Network Analysis (WGCNA) and Bayesian Networks (BNs) will be used to extract significant gene clusters, inform genetic pathways, and elucidate genetic information flow as they relate to bone strength. High-confidence putatively causal genes will then be experimentally validated in genetically-engineered mice.
SYSTEMS GENETICS OF OSTEOBLAST ACTIVITY
In order to learn more about the genetics underlying bone mineral density and osteoporosis, numerous genome-wide association studies have been conducted. We hypothesize that some of the loci identified in these studies harbor variants that influence BMD by altering the activity of osteoblasts. Thus, we're using RNA sequencing in osteoblasts from a genetically diverse population of mice to identify groups of genes that are co-expressed in osteoblasts. We identified one such group of genes that is enriched for BMD GWAS-implicated genes, correlated with in vitro measures of mineralization, and enriched for genes that, when knocked out in mice, produce a bone phenotype. We are currently knocking out these genes in an osteoblast cell line to understand their function in mineralization.