Molecularly Imprinted Polymers: Shaping the Future of Early-Stage Bone Loss Detection-A Review

Abstract

Osteoporosis is the deterioration of bone mineral density (BMD) because of an imbalance between bone resorption and formation, which might happen due to lots of factors like age, hormonal imbalance, and several others. While this occurrence is prevalent in both genders, it is more common in women, especially postmenopausal women. It is an asymptomatic disease that is underlying until the first incidence of a fracture. The bone is weakened, making it more susceptible to fracture. Even a low trauma can result in a fracture, making osteoporosis an even more alarming disease. These fractures can sometimes be fatal or can make the patient bedridden. Osteoporosis is an understudied disease, and there are certain limitations in diagnosing and early-stage detection of this condition. The standard method of dual X-ray absorptiometry can be used to some extent and can be detected in standard radiographs after the deterioration of a significant amount of bone mass. Clinically assessing osteoporosis using biomarkers can still be challenging, as clinical tests can be expensive and cannot be accessed by most of the general population. In addition, manufacturing antibodies specific to these biomarkers can be a challenging, time-consuming, and expensive method. As an alternative to these antibodies, molecularly imprinted polymers (MIPs) can be used in the detection of these biomarkers. This Review provides a comprehensive exploration of bone formation, resorption, and remodeling processes, linking them to the pathophysiology of osteoporosis. It details biomarker-based detection and diagnosis methods, with a focus on MIPs for sensing CTX-1, NTX-1, and other biomarkers. The discussion compares traditional clinical practices with MIP-based sensors, revealing comparable sensitivity with identified limitations. Additionally, the Review contrasts antibody-functionalized sensors with MIPs. Finally, our Review concludes by highlighting the potential of MIPs in future early-stage osteoporosis detection.

Figure 1

Structure of bone from its whole structure down to its microarchitecture (from left to right), breaking down its structure sequentially as an organ, tissue, tissue elements, microstructures, and its basic components. Reproduced from ref (13) and reprinted from the Creative Commons Attribution 4.0 license (CC BY-NC-ND 4.0 DEED).

Figure 2

Wnt activates β-catenin-dependent canonical and β-catenin-independent noncanonical pathways; the β-catenin-dependent signal promotes bone formation by inducing osteoblastogenesis and OPG expression, while the β-catenin-independent pathway enhances the expression of LRP5/6, promoting osteoblast differentiation. Reproduced from ref (16) and reprinted from the Creative Commons Attribution 4.0 license (CC BY).

Figure 3

Bone formation, depicting intramembranous ossification (a) and enchondromal ossification (b). Reproduced from ref (13) and reprinted from the Creative Commons Attribution 4.0 license (CC BY-NC-ND 4.0 DEED).

Figure 4

Coupling mechanism of the bone starting with osteoclast cells signaling cells of osteoblast lineage cells in the canopy, osteoblast progenitors, (1) reversal cells in the bone surface, and osteoblast cells (2); it also signals the osteocytes in the bone matrix (3) which signal the osteoblast cells (4); physical changes in the bone are also signaled to the osteoblast cells to secrete and form the appropriate amount of bone matrix. Adapted from ref (28).

Figure 5

Biomarkers of bone resorption. Adapted from ref (55).

Figure 6

Molecularly imprinted polymers synthesized using various methods like bulk synthesis (a), precipitation synthesis (b), emulsion (c), suspension (d), surface printing (e), epitope printing (f), sol–gel method (g), and electropolymerization (h). (i) Key for each technique. Reproduced from ref (66) and reprinted from the Creative Commons Attribution 3.0 license (CC BY 3.0).

Figure 7

Various methods by which MIPs can be incorporated into sensing for the identification of analytes in the sample. Reproduced from ref (65) and reprinted from the Creative Commons Attribution 4.0 license (CC-BY 4.0).