It's in Our Blood: A Glimpse of Personalized Medicine

Abstract

Recent advances in protein profiling technology has facilitated simultaneous measurement of thousands of proteins in large population studies, exposing the depth and complexity of the plasma and serum proteomes. This revealed that proteins in circulation were organized into regulatory modules under genetic control and closely associated with current and future common diseases. Unlike networks in solid tissues, serum protein networks comprise members synthesized across different tissues of the body. Genetic analysis reveals that this cross-tissue regulation of the serum proteome participates in systemic homeostasis and mirrors the global disease state of individuals. Here, we discuss how application of this information in routine clinical evaluations may transform the future practice of medicine.

Keywords: biological networks; blood proteome; holistic disease state; personalized medicine.

Figure 1.. The Development of a Broad-Based Molecular Biomarker Platform.

For a Figure360 author presentation of Figure 1, see the figure legend at https://doi.org/10.1016/j.molmed.2020.09.003. An overview of the development of a biomarker platform from a large-scale collection of deep phenotype and blood proteome data to the construction of protein networks in the serum. The protein networks connect to all tissues and most diseases as well as to different states of disease, yielding a comprehensive molecular map of individuals from which specific treatment associated biomarkers can be established. Once a reference set of protein networks and relationships to diseases is established, the grouping and disease status of new donors using their serum can be inferred.

Figure 2.. Many Tissues Can Contribute Proteins to a Single Serum Protein Module.

(A) An example of a module from the coregulatory serum protein network comprising proteins synthesized in different tissues of the body. The hub protein is connected to many other proteins and is strongly associated with disease and overall survival. (B) Cross-tissue cis and trans pairs of serum proteins reveal a web of regulatory loops that connects different tissues in the body and is apparent in the serum protein network. For instance, a genetic variant that controls a protein encoded by a nearby gene (cis) in pancreas is exported to the blood and that, in turn, may regulate another protein in a physically distant tissue, such as liver.

Figure 3.. Serum Protein Networks to Cluster Donors.

(A) Using robust features of the protein networks (eigenvectors of protein modules), it is found that, at an individual-level, donors can be either positively, negatively, or not correlated to other donors. (B) The loading coefficients for the eigenproteins for each of the 27 serum protein modules capturing the variance of thousands of serum proteins can be measured in individuals and these patterns can be compared across the population to disease states to derive numeric tests. (C) Hypothetically, this information can be used to cluster individuals into groups and, since serum proteins also associate with disease, these groups specify disease subclusters in the population (the axis represents derived dimensions 1 and 2 used to cluster individuals). Abbreviations: CVD, cardiovascular disease; T2DM, type 2 diabetes mellitus.

Figure 4.. Blood Proteins Offer a Holistic View of the Disease State of Individuals.

Numeric-based tests derived from the serum protein networks that inform on the wellness status of individuals tested offer a richness and depth of the disease state of individuals that is currently missing in clinical practice. Current medical records are generally based on clinical presentation of disease (A) and are sparse. By contrast, inference of current and future disease with serum proteins will be richer and more forward looking (B).