Analyses of PDE-regulated phosphoproteomes reveal unique and specific cAMP signaling modules in T cells

Thesis (Ph.D.)--University of Washington, 2017-06Specific functions for different cyclic nucleotide phosphodiesterases (PDEs) have not yet been identified in most cell types. Conventional approaches to study PDE function typically rely on measurements of global cAMP, general increases in cAMP-dependent protein kinase (PKA), or exchange protein activated by cAMP (EPAC) activity. Although newer approaches utilizing subcellularly-targeted FRET reporter sensors have helped to define more compartmentalized regulation of cAMP, PKA, and EPAC, they have limited ability to link this regulation to downstream effector molecules and biological functions. To address this problem, we used an unbiased, mass spectrometry based approach coupled with treatment using PDE isozyme-selective inhibitors to characterize the phosphoproteomes of the “functional pools” of cAMP/PKA/EPAC that are regulated by specific cAMP-PDEs (the PDE-regulated phosphoproteomes). In Jurkat cells we found multiple, distinct phosphoproteomes that differ in response to different PDE inhibitors. We also found that little phosphorylation occurs unless at least 2 different PDEs are concurrently inhibited in these cells. Moreover, bioinformatics analyses of these phosphoproteomes provides insight into the functional roles, mechanisms of action, and synergistic relationships among the different PDEs that coordinate cAMP-signaling cascades in these cells. The data strongly suggest that phosphorylation of many different substrates contribute to cAMP-dependent regulation of these cells. The findings further indicate that the approach of using selective, inhibitor-dependent phosphoproteome analysis can provide a generalized methodology for understanding the roles of different PDEs in the regulation of cyclic nucleotide signaling

An atlas of genetic influences on osteoporosis in humans and mice

Osteoporosis is a common aging-related disease diagnosed primarily using bone mineral density (BMD). We assessed genetic determinants of BMD as estimated by heel quantitative ultrasound in 426,824 individuals, identifying 518 genome-wide significant loci (301 novel), explaining 20% of its variance. We identified 13 bone fracture loci, all associated with estimated BMD (eBMD), in ~1.2 million individuals. We then identified target genes enriched for genes known to influence bone density and strength (maximum odds ratio (OR) = 58, P = 1 × 10) from cell-specific features, including chromatin conformation and accessible chromatin sites. We next performed rapid-throughput skeletal phenotyping of 126 knockout mice with disruptions in predicted target genes and found an increased abnormal skeletal phenotype frequency compared to 526 unselected lines (P

An atlas of genetic influences on osteoporosis in humans and mice.

Osteoporosis is a common aging-related disease diagnosed primarily using bone mineral density (BMD). We assessed genetic determinants of BMD as estimated by heel quantitative ultrasound in 426,824 individuals, identifying 518 genome-wide significant loci (301 novel), explaining 20% of its variance. We identified 13 bone fracture loci, all associated with estimated BMD (eBMD), in ~1.2 million individuals. We then identified target genes enriched for genes known to influence bone density and strength (maximum odds ratio (OR) = 58, P = 1 × 10-75) from cell-specific features, including chromatin conformation and accessible chromatin sites. We next performed rapid-throughput skeletal phenotyping of 126 knockout mice with disruptions in predicted target genes and found an increased abnormal skeletal phenotype frequency compared to 526 unselected lines (P < 0.0001). In-depth analysis of one gene, DAAM2, showed a disproportionate decrease in bone strength relative to mineralization. This genetic atlas provides evidence linking associated SNPs to causal genes, offers new insight into osteoporosis pathophysiology, and highlights opportunities for drug development

An atlas of genetic influences on osteoporosis in humans and mice.

Osteoporosis is a common aging-related disease diagnosed primarily using bone mineral density (BMD). We assessed genetic determinants of BMD as estimated by heel quantitative ultrasound in 426,824 individuals, identifying 518 genome-wide significant loci (301 novel), explaining 20% of its variance. We identified 13 bone fracture loci, all associated with estimated BMD (eBMD), in ~1.2 million individuals. We then identified target genes enriched for genes known to influence bone density and strength (maximum odds ratio (OR) = 58, P = 1 × 10-75) from cell-specific features, including chromatin conformation and accessible chromatin sites. We next performed rapid-throughput skeletal phenotyping of 126 knockout mice with disruptions in predicted target genes and found an increased abnormal skeletal phenotype frequency compared to 526 unselected lines (P < 0.0001). In-depth analysis of one gene, DAAM2, showed a disproportionate decrease in bone strength relative to mineralization. This genetic atlas provides evidence linking associated SNPs to causal genes, offers new insight into osteoporosis pathophysiology, and highlights opportunities for drug development

An atlas of genetic influences on osteoporosis in humans and mice

Osteoporosis is a common aging-related disease diagnosed primarily using bone mineral density (BMD). We assessed genetic determinants of BMD as estimated by heel quantitative ultrasound in 426,824 individuals, identifying 518 genome-wide significant loci (301 novel), explaining 20% of its variance. We identified 13 bone fracture loci, all associated with estimated BMD (eBMD), in ~1.2 million individuals. We then identified target genes enriched for genes known to influence bone density and strength (maximum odds ratio (OR) = 58, P = 1 × 10−75) from cell-specific features, including chromatin conformation and accessible chromatin sites. We next performed rapid-throughput skeletal phenotyping of 126 knockout mice with disruptions in predicted target genes and found an increased abnormal skeletal phenotype frequency compared to 526 unselected lines (P < 0.0001). In-depth analysis of one gene, DAAM2, showed a disproportionate decrease in bone strength relative to mineralization. This genetic atlas provides evidence linking associated SNPs to causal genes, offers new insight into osteoporosis pathophysiology, and highlights opportunities for drug development