The association between treatment and systemic inflammation in acromegaly

Validity of galactin-3 in acromegaly: comparison with traditional markers

BACKGROUND

Acromegaly occurs due to overproduction of growth hormone (GH) and insulin-like growth factor-1 (IGF-1). Galectin-3 (Gal-3) has recently emerged as a novel biomarker, related to IGF-1. This study aimed to assess Gal-3 in patients with acromegaly and compare its effectiveness with traditional biomarker tests.

MATERIALS AND METHODS

A randomized case control study conducted in a single center included 50 acromegaly patients and 40 apparently healthy subjects (HS) serve as control group matched both age and BMI. Laboratory test was measured by routine assay used in center. Gal-3, GH, and IGF-1 were measured by enzyme-linked immunosorbent assay (ELISA).

RESULT

There were 50 patients with an average age of 50.40 ± 12.229 (50% of males). Compared with HS, patients' serum GAL-3 levels have increased significantly. The serum GAL-3 exceeds 14.363 ng/ml, with a sensitivity of 100.0 and a specificity of 100.0. Furthermore, serum Gal-3 levels in combination with traditional tests (GH and IGF-1) by DeLoongs test had a significant difference in discriminating acromegaly more accurately than traditional tests.

CONCLUSION

In a summary, this study recommended clinicians measure serum Gal-3 as biomarkers for patients with acromegaly. In addition, the result above shed light on role of Gal-3 on acromegaly pathogenesis and might provide a therapeutic target of acromegaly patients.

Machine learning-based algorithms applied to drug prescriptions and other healthcare services in the Sicilian claims database to identify acromegaly as a model for the earlier diagnosis of rare diseases

Acromegaly is a rare disease characterized by a diagnostic delay ranging from 5 to 10 years from the symptoms' onset. The aim of this study was to develop and internally validate machine-learning algorithms to identify a combination of variables for the early diagnosis of acromegaly. This retrospective population-based study was conducted between 2011 and 2018 using data from the claims databases of Sicily Region, in Southern Italy. To identify combinations of potential predictors of acromegaly diagnosis, conditional and unconditional penalized multivariable logistic regression models and three machine learning algorithms (i.e., the Recursive Partitioning and Regression Tree, the Random Forest and the Support Vector Machine) were used, and their performance was evaluated. The random forest (RF) algorithm achieved the highest Area under the ROC Curve value of 0.83 (95% CI 0.79-0.87). The sensitivity in the test set, computed at the optimal threshold of predicted probabilities, ranged from 28% for the unconditional logistic regression model to 69% for the RF. Overall, the only diagnosis predictor selected by all five models and algorithms was the number of immunosuppressants-related pharmacy claims. The other predictors selected by at least two models were eventually combined in an unconditional logistic regression to develop a meta-score that achieved an acceptable discrimination accuracy (AUC = 0.71, 95% CI 0.66-0.75). Findings of this study showed that data-driven machine learning algorithms may play a role in supporting the early diagnosis of rare diseases such as acromegaly.

Role of IL33 in chronic inflammation and microvascular damage as a reflection of organ damage on a cohort of patients with acromegaly

AIM

Acromegaly is a rare chronic disease, caused by the over-secretion of growth hormone (GH), that creates a pro-inflammatory state, but the exact mechanisms by which GH or insulin-like growth factor 1 (IGF-1) act on inflammatory cells are not fully understood. Aim of the study was to evaluate Interleukin-33 (IL33) and the skin perfusion of hands in patients with acromegaly (AP) and healthy controls (HC).

METHODS

IL33 have been assessed in 40 AP and 40 HC. IL 33 was determined and skin perfusion of hands was assessed by laser speckle contrast analysis (LASCA) in both populations.

RESULTS

IL33 was significantly higher in AP compared to HC [45.72 pg/ml (IQR 28.74-60.86) vs 14 pg/ml (IQR 6.5535); p < 0.05]. At LASCA, peripheral blood perfusion (PBP) was significantly lower in AP compared to HC [53.39 pU (IQR 40.94-65.44) vs 87 pU (IQR 80-98) p < 0.001]. The median values of ROI1, ROI2 and ROI3 were significantly lower in AP compared to HC [97.32 pU (IQR 50.89-121.69) vs 131 pU (IQR 108-135); p < 0.001], [58.68 pU (IQR 37.72-84.92) vs 83 pU (IQR 70-89), p < 0.05] and HC [52.16 (34.47-73.78) vs 85 (78-98), p < 0.001], respectively. The proximal-distal gradient (PDG) was observed in 18 of 40 (45%) AP.

CONCLUSION

Serum IL33 is higher in AP compared to HC; conversely a reduction of PBP of hands was present in AP compared to HC, probably due to endothelial dysfunction, strictly dependent on acromegaly and are not influenced by the choice of treatment.

The potential link between acromegaly and risk of acute ischemic stroke in patients with pituitary adenoma: a new perspective

Acromegaly is an endocrine disorder due to the excess production of growth hormone (GH) from the anterior pituitary gland after closed epiphyseal growth plates. Acromegaly is mainly caused by benign GH-secreting pituitary adenoma. Acute ischemic stroke (AIS) is one of the most common cardiovascular complications. It ranks second after ischemic heart disease (IHD) as a cause of disability and death in high-income countries globally. Thus, this review aimed to elucidate the possible link between acromegaly and the development of AIS. The local effects of acromegaly in the development of AIS are related to the development of pituitary adenoma and associated surgical and radiotherapies. Pituitary adenoma triggers the development of AIS through different mechanisms, particularly aneurysmal formation, associated thrombosis, and alteration of cerebral microcirculation. Cardiovascular complications and mortality were higher in patients with pituitary adenoma. The systemic effect of acromegaly-induced cardio-metabolic disorders may increase the risk for the development of AIS. Additionally, acromegaly contributes to the development of endothelial dysfunction (ED), inflammatory and oxidative stress, and induction of thrombosis that increases the risk for the development of AIS. Moreover, activated signaling pathways, including activator of transcription 3 (STAT3), nuclear factor kappa B (NF-κB), nod-like receptor pyrin 3 (NLRP3) inflammasome, and mitogen-activated protein kinase (MAPK) in acromegaly may induce systemic inflammation with the development of cardiovascular complications mainly AIS. Taken together, acromegaly triggers the development of AIS through local and systemic effects by inducing the formation of a cerebral vessel aneurysm, the release of pro-inflammatory cytokines, the development of oxidative stress, ED, and thrombosis correspondingly.

Association between Biomarkers (VEGF-R2, VEGF-R3, VCAM-1) and Treatment Duration in Patients with Neuroendocrine Tumors Receiving Therapy with First-Generation Somatostatin Analogues

Angiogenic factors (AF) promote vascular formation and may thus support neuroendocrine tumour (NET) development. This study aimed to assess AF serum level changes in NET patients treated with prolonged-acting somatostatin analogues (SSAs). The study enrolled 49 healthy volunteers (Group A) and 56 NET patients: treatment naïve (Group B) and after-SSA treatment in various periods (months): under 12 (Group C), 13–24 (Group D), 25–36 (Group E), 37–60 (Group F), and over 60 months (Group G). The serum vascular endothelial growth factor receptors 2, 3 (VEGF-R2, VEGF-R3), and vascular cell adhesion molecule-1 (VCAM-1) concentrations were tested using the ELISA. We noted significant differences in the concentrations of VEGF-R2, VEGF-R3, and VCAM-1 depending on the SSA treatment duration (p < 0.001). In the studied AFs, the highest decreasing levels of VEGF-R2 were observed after two years of therapy. However, monitoring VEGF-R2, VEGF-R3, and VCAM-1 during SSA treatment did not allow for the identification of good responders for this kind of therapy. Therefore, these biomarker measurements were not helpful in assessing SSA treatment effectiveness in NET patients.

Neutrophil-to-Lymphocyte, Platelet-to-Lymphocyte Ratios, and Systemic Immune-Inflammation Index as Potential Biomarkers of Chronic Inflammation in Patients with Newly Diagnosed Acromegaly: A Single-Centre Study

Acromegaly is a rare disease caused by overproduction of growth hormone (GH) by a pituitary adenoma, and consequently increased insulin-like growth factor 1 (IGF-1) concentration. The GH/IGF-1 axis and immune cells interactions are hypothesized to be involved in subclinical inflammation. This retrospective study aimed to investigate the differences in neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR) ratios, and systemic immune-inflammation index (SII) in GH-secreting adenomas compared with non-functioning pituitary adenomas (NFPAs) concerning clinical and radiological findings. After evaluation of 665 patients with pituitary tumors, 62 individuals with newly diagnosed acromegaly and 134 with NFPAs were enrolled in the analysis. The control group consisted of 120 healthy individuals. Fifty-eight patients with acromegaly were re-evaluated after medical or surgical therapies. NLR, PLR, SII values, and neutrophil count were significantly higher (p ≤ 0.001), whereas lymphocyte count was lower in acromegaly than in NFPAs (p = 0.001). No significant differences between NFPAs and controls were observed in analyzed ratios. Higher preoperative NLR, PLR, SII values were found in patients who failed to achieve a cure with surgery (p < 0.05). Although NLR, PLR, and SII values were significantly higher in acromegaly, these indices cannot be used to discriminate GH-secreting pituitary tumors from NFPAs. Treatment of acromegaly decreased the value of NLR and SII, but it requires further studies to consolidate the real clinical role of these inflammation-related ratios.