A Systems-Level Analysis of Total-Body PET Data Reveals Complex Skeletal Metabolism Networks in vivo

Abstract

Bone is now regarded to be a key regulator of a number of metabolic processes, in addition to the regulation of mineral metabolism. However, our understanding of complex bone metabolic interactions at a systems level remains rudimentary. in vitro molecular biology and bioinformatics approaches have frequently been used to understand the mechanistic changes underlying disease at the cell level, however, these approaches lack the capability to interrogate dynamic multi-bone metabolic interactions in vivo. Here we present a novel and integrative approach to understand complex bone metabolic interactions in vivo using total-body positron emission tomography (PET) network analysis of murine 18F-FDG scans, as a biomarker of glucose metabolism in bones. In this report we show that different bones within the skeleton have a unique glucose metabolism and form a complex metabolic network, which could not be identified using single tissue simplistic PET standard uptake values analysis. The application of our approach could reveal new physiological and pathological tissue interactions beyond skeletal metabolism, due to PET radiotracers diversity and the advent of clinical total-body PET systems.

FGFR regulator Memo1 is dispensable for FGF23 expression by osteoblasts during folic acid‐driven kidney injury

“…Similarly, others have previously reported a much higher degree of Fgf23 expression increase in calvaria than in long bones (Durlacher‐Betzer et al, 2018 ; Egli‐spichtig et al, 2018 ; Hassan et al, 2016 ). This implies that distinct site‐dependent differences in the regulation of Fgf23 expression by the bone may exist that should be addressed in targeted studies, similar as the anatomical differences in bone energy metabolism inferred from site‐specific differences in glucose uptake (Suchacki et al, 2021 ). Finally, the lack of a phenotype in the bone of Memo obKO may be attributable to the mode of action chosen for Cre expression.…”

Identifying the individual metabolic abnormities from a systemic perspective using whole-body PET imaging

“…Another potential approach to derive the metabolic network at the subject level would be utilizing dynamic PET. For example, the time–activity curves of sub-brain regions were successfully correlated at the subject level [ 19 , 26 , 27 ]. However, the limitation of this approach is that regional kinetics carry information of non-specific tracer binding and delivery, which could hide the tracer-specific interaction with its targets [ 28 , 29 ].…”

“…Sundar et al [ 20 ] compared the metabolic rates at multiple organs between healthy male group and female group, based on group-averaged normative correlation analysis of the measured time-activity curves. Suchacki et al [ 19 ] reported an approach to understanding murine bone metabolic interactions in vivo by analyzing the correlations of the 18 F-FDG time-activity curves in bones.…”

Whole-Body PET Imaging: A Catalyst for Whole-Person Research?

“…Despite the increasing installed base of TB PET systems, the number of studies that explore TB PET beyond dose reduction and higher throughput for the sake of assessing the human connectome studies is limited. Preliminary studies have demonstrated the potential of using the temporal domain, namely raw time-activity curves, to derive metabolic associations between different bone compartments (21) or to construct normative networks for healthy male and female controls (22). Although neither study explained causality, dynamic TB PET has the potential to create personalized causal networks from a single subject.…”