Circulating osteocalcin as a bone-derived hormone is inversely correlated with body fat in patients with type 1 diabetes

Osteocalcin is inversely associated with worse adipose tissue distribution and cardiovascular risk in autoimmune diabetes

BACKGROUND

Osteocalcin (OCN), whose release is impaired in diabetes, is suggested to regulate the adipose tissue (AT), being potentially associated with Cardiovascular risk (CVR). We aimed at evaluating whether OCN serum levels are associated with AT health and CVR in a primary CV prevention population with AD.

METHODS

Body mass composition was assessed in sixty-two people with AD.Serum levels of OCN, adipokines and markers of endothelial dysfunction were measured. Regression models were used to test the association of OCN with markers of AT, endothelial dysfunction and CVR categories as determined by the Steno Type 1 Risk Engine (ST1RE) score.

RESULTS

OCN was inversely associated with upper body fat deposition index (UBDFI) (Adj β coefficient -0.484, p value = 0.001). People in medium/high CV risk categories had higher UBFDI and lower OCN, while biomarkers of endothelial dysfunction were not different across CVR classes. A logistic binary regression for ST1RE score showed significant association of OCN with medium/high CVR category: OR [95 % CI for 1 SD increase: 0.541 [0.264--1.108], p = 0.093].

CONCLUSION

OCN is inversely associated with unhealthy AT, supporting the protective role of OCN in AT. Moreover, lower OCN levels are associated with increased CVR in AD population.

A teaching proposal for a short course on biomedical data science

As the availability of big biomedical data advances, there is a growing need of university students trained professionally on analyzing these data and correctly interpreting their results. We propose here a study plan for a master's degree course on biomedical data science, by describing our experience during the last academic year. In our university course, we explained how to find an open biomedical dataset, how to correctly clean it and how to prepare it for a computational statistics or machine learning phase. By doing so, we introduce common health data science terms and explained how to avoid common mistakes in the process. Moreover, we clarified how to perform an exploratory data analysis (EDA) and how to reasonably interpret its results. We also described how to properly execute a supervised or unsupervised machine learning analysis, and now to understand and interpret its outcomes. Eventually, we explained how to validate the findings obtained. We illustrated all these steps in the context of open science principles, by suggesting to the students to use only open source programming languages (R or Python in particular), open biomedical data (if available), and open access scientific articles (if possible). We believe our teaching proposal can be useful and of interest for anyone wanting to start to prepare a course on biomedical data science.

Osteocalcin: Beyond Bones

Apart from basic roles such as supporting the body, protecting internal organs, and storing calcium, the skeletal system also performs hormonal functions. In recent years, several reports have been published on proteins secreted by bones and their impact on the homeostasis of the entire body. These proteins include fibroblast growth factor 23, sclerostin, lipocalin 2, and osteocalcin. Osteocalcin, the most abundant non-collagenous protein in bone tissue, is routinely measured as a clinical marker for diagnosing bone metabolism disorders. Its molecule undergoes numerous transformations, with decarboxylation being the critical process. Decarboxylation occurs in the acidic environment typical of bone resorption, facilitating the release of the molecule into the bloodstream and enabling its hormonal action. Decarboxylated osteocalcin promotes insulin secretion and stimulates the proliferation of pancreatic islet β-cells. It also plays a role in reducing the accumulation of visceral fat and decreasing fat storage in the liver. Furthermore, decarboxylated osteocalcin levels are inversely correlated with fasting serum glucose levels, total body fat, visceral fat area, and body mass index. Apart from its role in energy metabolism, osteocalcin affects testosterone production and the synthesis of glucagon-like peptide-1. It is also actively involved in muscle-bone crosstalk and influences cognitive function.

Ensemble machine learning reveals key features for diabetes duration from electronic health records

Diabetes is a metabolic disorder that affects more than 420 million of people worldwide, and it is caused by the presence of a high level of sugar in blood for a long period. Diabetes can have serious long-term health consequences, such as cardiovascular diseases, strokes, chronic kidney diseases, foot ulcers, retinopathy, and others. Even if common, this disease is uneasy to spot, because it often comes with no symptoms. Especially for diabetes type 2, that happens mainly in the adults, knowing how long the diabetes has been present for a patient can have a strong impact on the treatment they can receive. This information, although pivotal, might be absent: for some patients, in fact, the year when they received the diabetes diagnosis might be well-known, but the year of the disease unset might be unknown. In this context, machine learning applied to electronic health records can be an effective tool to predict the past duration of diabetes for a patient. In this study, we applied a regression analysis based on several computational intelligence methods to a dataset of electronic health records of 73 patients with diabetes type 1 with 20 variables and another dataset of records of 400 patients of diabetes type 2 with 49 variables. Among the algorithms applied, Random Forests was able to outperform the other ones and to efficiently predict diabetes duration for both the cohorts, with the regression performances measured through the coefficient of determination R2. Afterwards, we applied the same method for feature ranking, and we detected the most relevant factors of the clinical records correlated with past diabetes duration: age, insulin intake, and body-mass index. Our study discoveries can have profound impact on clinical practice: when the information about the duration of diabetes of patient is missing, medical doctors can use our tool and focus on age, insulin intake, and body-mass index to infer this important aspect. Regarding limitations, unfortunately we were unable to find additional dataset of EHRs of patients with diabetes having the same variables of the two analyzed here, so we could not verify our findings on a validation cohort.

The Role of Bone-Derived Hormones in Glucose Metabolism, Diabetic Kidney Disease, and Cardiovascular Disorders

Bone contributes to supporting the body, protecting the central nervous system and other organs, hematopoiesis, the regulation of mineral metabolism (mainly calcium and phosphate), and assists in respiration. Bone has many functions in the body. Recently, it was revealed that bone also works as an endocrine organ and secretes several systemic humoral factors, including fibroblast growth factor 23 (FGF23), osteocalcin (OC), sclerostin, and lipocalin 2. Bone can communicate with other organs via these hormones. In particular, it has been reported that these bone-derived hormones are involved in glucose metabolism and diabetic complications. Some functions of these bone-derived hormones can become useful biomarkers that predict the incidence of diabetes and the progression of diabetic complications. Furthermore, other functions are considered to be targets for the prevention or treatment of diabetes and its complications. As is well known, diabetes is now a worldwide health problem, and many efforts have been made to treat diabetes. Thus, further investigations of the endocrine system through bone-derived hormones may provide us with new perspectives on the prediction, prevention, and treatment of diabetes. In this review, we summarize the role of bone-derived hormones in glucose metabolism, diabetic kidney disease, and cardiovascular disorders.

Glucose Metabolism in Osteoblasts in Healthy and Pathophysiological Conditions

Bone tissue in vertebrates is essential to performing movements, to protecting internal organs and to regulating calcium homeostasis. Moreover, bone has also been suggested to contribute to whole-body physiology as an endocrine organ, affecting male fertility; brain development and cognition; and glucose metabolism. A main determinant of bone quality is the constant remodeling carried out by osteoblasts and osteoclasts, a process consuming vast amounts of energy. In turn, clinical conditions associated with impaired glucose metabolism, including type I and type II diabetes and anorexia nervosa, are associated with impaired bone turnover. As osteoblasts are required for collagen synthesis and matrix mineralization, they represent one of the most important targets for pharmacological augmentation of bone mass. To fulfill their function, osteoblasts primarily utilize glucose through aerobic glycolysis, a process which is regulated by various molecular switches and generates adenosine triphosphate rapidly. In this regard, researchers have been investigating the complex processes of energy utilization in osteoblasts in recent years, not only to improve bone turnover in metabolic disease, but also to identify novel treatment options for primary bone diseases. This review focuses on the metabolism of glucose in osteoblasts in physiological and pathophysiological conditions.

Change in Circulating Undercarboxylated Osteocalcin (ucOCN) Is Associated With Fat Accumulation in HIV-Seropositive Women

BACKGROUND

Bone mineral density loss and fat accumulation are common in people living with HIV. The bone-derived hormone, undercarboxylated osteocalcin (ucOCN) regulates fat metabolism. We investigated the relationship between ucOCN change and body fat change among perimenopausal/postmenopausal HIV-seronegative and HIV-seropositive women on long-term antiretrovirals.

METHODS

Perimenopausal and postmenopausal women enrolled in the Women's Interagency HIV Study MSK substudy underwent trunk and total fat assessment by dual energy x-ray absorptiometry (DXA) at study enrollment (index visit) and again 2 years later. Circulating ucOCN and cOCN were also measured at the index and 2-year visits. The correlation between the 2-year change in ucOCN and cOCN and change in trunk and total fat was assessed as a function of HIV serostatus using linear regression modeling. Multivariate linear regression assessed the association between ucOCN and cOCN change and total and trunk fat change after adjusting for sociodemographic variables. Linear regression models restricted to HIV-seropositive women were performed to examine the contributions of HIV-specific factors (index CD4 count, viral load, and combined antiretroviral therapy use) on the associations.

RESULTS

Increased ucOCN over the 2-year follow-up was associated with less trunk and total fat accumulation in models adjusting for HIV serostatus and participants sociodemographics, whereas there was no association with cOCN and the fat parameters. None of the HIV-specific factors evaluated influenced the association between ucOCN and fat parameters.

CONCLUSION

The current study suggests that increases in ucOCN are associated with decreased fat accumulation in HIV-seronegative and HIV-seropositive postmenopausal women on long-term antiretroviral therapy.

Serum C-peptide and osteocalcin levels in children with recently diagnosed diabetes

BACKGROUND

We explored the association of C-peptide (marker of secreted insulin), proinsulin and proinsulin ⁄C-peptide ratio (PI/C) (markers of beta-cell endoplasmic reticulum [ER] stress) with undercarboxylated (uOC) and carboxylated osteocalcin (cOC) and their ratio (uOC/cOC) in children with recently diagnosed type 1 (T1D) or type 2 diabetes (T2D), and the correlation of these variables with partial remission (PR) in children with T1D.

METHODS

Demographic and clinical data of children with new-onset diabetes (n = 68; median age = 12.2 years; 33.8% non-Hispanic White, 45.6% Hispanic/Latino, 16.2% African American and 4.4% other) were collected at diagnosis and during the first (V1), second (V2) and third clinical visits at 9.0, 32.0 and 175.7 weeks, respectively. Serum proinsulin, C-peptide, uOC and cOC values were measured 7.0 weeks after diagnosis. PR was defined as insulin dose-adjusted HbA1c (IDAA1c) ≤9.

RESULTS

In children with new-onset T1D with DKA (33.3%) or T2D (29.4%), Spearman's correlation coefficient revealed a positive association between the C-peptide levels and both uOC and uOC/cOC ratio. In T1D (n = 48), both higher serum C-peptide levels and low PI:C ratio were associated with higher BMI percentile (β = 0.02, P = .001; β = -0.01, P = .02, respectively) and older age at diagnosis (β = 0.13, P = .001; β = -0.12, P = .001, respectively). Furthermore, in children with T1D, C-peptide levels at V1 correlated with IDAA1c ≤ 9 at V1 (P = .04).

CONCLUSION

C-peptide levels are associated with a higher uOC and uOC/cOC ratio in paediatric diabetes. In new-onset T1D children, older age and higher BMI were associated with lower beta-cell stress and higher preserved function, which was predictive of PR on follow-up.

Association Study between BGLAP Gene HindIII Polymorphism and Type 2 Diabetes Mellitus Development in Ukrainian Population

Type 2 diabetes mellitus (T2DM) belongs to the diseases with hereditary predisposition, so both environmental and genetic factors contribute to its development. Recent studies have demonstrated that the skeleton realizes systemic regulation of energy metabolism through the secretion of osteocalcin (OCN). Thus, the association analysis between HindIII single nucleotide polymorphism of OCN gene (BGLAP) promoter region and T2DM development in Ukrainian population was carried out. 153 individuals diagnosed with T2DM and 311 control individuals were enrolled in the study. The genotyping was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. The lack of association between BGLAP HindIII single nucleotide polymorphism (SNP) and T2DM development among Ukrainians was found. Further studies with extended groups of comparison are needed to confirm the obtained results.

Impact of Diabetes Mellitus on Bone Health

Long-term exposure to a diabetic environment leads to changes in bone metabolism and impaired bone micro-architecture through a variety of mechanisms on molecular and structural levels. These changes predispose the bone to an increased fracture risk and impaired osseus healing. In a clinical practice, adequate control of diabetes mellitus is essential for preventing detrimental effects on bone health. Alternative fracture risk assessment tools may be needed to accurately determine fracture risk in patients living with diabetes mellitus. Currently, there is no conclusive model explaining the mechanism of action of diabetes mellitus on bone health, particularly in view of progenitor cells. In this review, the best available literature on the impact of diabetes mellitus on bone health in vitro and in vivo is summarised with an emphasis on future translational research opportunities in this field.