The article by Maddaloni et al. (1), published recently in Diabetes Care, delves into the intricate relationship between biomarkers of the bone-vascular axis and cardiovascular (CV) events in patients with type 2 diabetes (T2D). Their findings elucidate a direct and independent association between osteoprotegerin and osteopontin, with an increased risk of CV outcomes. Additionally, a nonlinear relationship between osteocalcin levels and mortality was seen. We appreciate the study’s valuable contributions and highlight areas that merit further elucidation and investigation.

First, is the role of these bone-vascular axis biomarkers consistent across different subtypes of T2D? The function of these biomarkers in various T2D subtypes may vary due to differences in patient metabolic characteristics, insulin secretion capacity, degrees of insulin resistance, and immune responses. For instance, are the roles of biomarkers in individuals with severe insulin-deficient diabetes (SIDD) associated with insulin deficiency and autoimmune reactions? In contrast, in individuals with severe insulin-resistant diabetes (SIRD), is their biomarker function more intimately linked with the interplay between insulin resistance and inflammatory factors (2)? Exploring these questions is crucial for a comprehensive understanding of the role of the bone-vascular axis in diabetes-related CV diseases. Consequently, personalized treatment strategies for different T2D subtypes may need to consider the specific mechanisms of action of these biomarkers.

Second, the study appears to have overlooked the potential confounding effects of socioeconomic factors, psychological health considerations, and lifestyle elements such as diet, physical activity, and sleep disorders, which play a significant role in the pathogenesis of CV diseases (3,4). Furthermore, the insights from the Exenatide Study of Cardiovascular Event Lowering (EXSCEL) align with the emphasis on the importance of diabetes and CV disease management highlighted in the expert consensus of China, underscoring the significance of considering bone metabolism markers in the CV risk management of T2D.

Third, divergent glycemic management strategies may exert distinct influences on bone metabolism. For example, new hypoglycemic drugs, such as glucagon-like peptide 1 (GLP-1) receptor agonists and dipeptidyl peptidase 4 (DPP-4) inhibitors, have been demonstrated to modulate bone metabolism (5). Consequently, the question arises whether these pharmacotherapies alter the correlation between bone metabolic markers and CV events. Furthermore, considering the heterogeneity of diabetes complications, including nephropathy, retinopathy, and neuropathy, it is pertinent to inquire whether these comorbidities also impact the prognostic value of bone metabolic markers. This inquiry may precipitate the development of novel therapeutic agents and prompt a reevaluation of the impact of existing medications on bone metabolism.

In conclusion, the research of Maddaloni et al. (1) provides a compelling foundation for further exploration into the bone-vascular axis in T2D. Future studies should consider the nuances of T2D subtypes, potential confounders, and the impact of glycemic management on bone metabolism to refine our understanding and optimize cardiovascular risk management.

Funding. This work was supported by the Feng Xian District Science and Technology Commission Project (no. 20211838).

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Handling Editors. The journal editors responsible for overseeing the review of the manuscript were Steven E. Kahn and Vanita R. Aroda.

1.
Maddaloni
E
,
Nguyen
M
,
Shah
SH
, et al
.
Osteoprotegerin, osteopontin, and osteocalcin are associated with cardiovascular events in type 2 diabetes: insights from EXSCEL
.
Diabetes Care
2025
;
48
:
235
242
2.
Zaharia
OP
,
Strassburger
K
,
Strom
A
, et al;
German Diabetes Study Group
.
Risk of diabetes-associated diseases in subgroups of patients with recent-onset diabetes: a 5-year follow-up study
.
Lancet Diabetes Endocrinol
2019
;
7
:
684
694
3.
Cromer
SJ
,
Lakhani
CM
,
Mercader
JM
, et al
.
Association and interaction of genetics and area-level socioeconomic factors on the prevalence of type 2 diabetes and obesity
.
Diabetes Care
2023
;
46
:
944
952
4.
Han
H
,
Wang
Y
,
Li
T
, et al
.
Sleep duration and risks of incident cardiovascular disease and mortality among people with type 2 diabetes
.
Diabetes Care
2023
;
46
:
101
110
5.
Gilbert
MP
,
Pratley
RE.
The impact of diabetes and diabetes medications on bone health
.
Endocr Rev
2015
;
36
:
194
213
Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at https://www.diabetesjournals.org/journals/pages/license.