The role of menin in bone pathology

Role of Nutrition in the Management of Patients with Multiple Endocrine Neoplasia Type 1

Multiple endocrine neoplasia type 1 (MEN1) is a rare syndrome caused by inactivating mutations in the MEN1 tumor suppressor gene. The three main clinical manifestations of MEN1 are primary hyperparathyroidism (PHPT), duodenal-pancreatic neuroendocrine tumors (DP-NETs) and anterior pituitary tumors. Endocrine tumors in patients with MEN1 differ from sporadic tumors because of their younger age at onset, common multiple presentations and the different clinical course. MEN1 is characterized by a complex clinical phenotype; thus, patients should be followed by a multidisciplinary team of experts that includes an endocrinologist, a surgeon, a oncologist, a radiotherapist, and not least, a nutritionist. It is important to remember the fundamental role that diet plays as a primary prevention tool, together with a healthy and active lifestyle in preventing osteoporosis/osteopenia and reducing the risk of developing kidney stones due to hypercalciuria, two frequent clinical complications in MEN1 patients. Is very important for MEN1 patients to have an adequate intake of calcium, vitamin D, magnesium and phosphate to maintain good bone health. The intake of foods containing oxalates must also be kept under control because in combination with calcium they concur to form calcium oxalate crystals, increasing the risk of nephrolithiasis. Another aspect to consider is the management of patients with pancreatic neuroendocrine tumors undergoing major surgical resections of the pancreas that can lead to alterations in digestion and absorption mechanisms due to partial or total reduction in pancreatic enzymes such as amylase, lipase, and protease, resulting in malabsorption and malnutrition. Therefore, the nutritionist's aim should be to devise a dietary plan that takes into consideration each single patient, educating them about a healthy and active lifestyle, and accompanying them through various life stages by implementing strategies that can enhance their quality of life.

[Predicting the presence of MEN1 gene mutation based on the clinical phenotype of patients with primary hyperparathyroidism]

BACKGROUND

Timely referral of patients for genetic testing to rule out MEN1-associated primary PHPT is important factor in determining treatment strategy and prognosis. In the context of the limited availability of genetic testing, the search for clinical markers indicative of MEN1 gene mutations remains an extremely relevant task.

AIM

To determine the diagnostic value of clinical features of primary PHPT in young patients for predicting the presence of MEN1 gene mutations.

MATERIALS AND METHODS

A single-center, prospective study was conducted at the Endocrinology Research Centre, involving 273 patients with PHPT in the period 2015-2022. Based on the results of genetic and laboratory tests, patients were divided into three groups: those with MEN1 gene mutations (MEN+ group, n=71), those without MEN1 gene mutations - isolated sporadic PHPT (MEN- group, n=158), and patients with PHPT and associated endocrine gland disorders - MEN-1 syndrome phenocopies (PHEN group, n=32). Subgroups of patients younger than 40 years of age were also identified. Comparative analysis was performed among the independent groups and subgroups, and logistic regression analysis was used to develop a mathematical model for predicting the probability of the presence of MEN1 gene mutation.

RESULTS

Patients in the MEN+ and MEN- groups were comparable by gender and age at manifestation, as well as calcium-phosphorus metabolism parameters and PHPT complications. In the PHEN group, PHPT manifested at older age compared to the other groups (p<0.001 for all), with lower total calcium levels and a trend toward lower iPTH concentrations. The MEN+ group had a significantly higher frequency of multiglandular parathyroid (PG) involvement, PHPT recurrence, and positive family history compared to the MEN- and PHEN groups. Histologically, adenomas predominated in the PHEN and MEN- groups (92% and 94%, respectively), whereas hyperplasia of PGs were more common in the MEN+ group (49%). None of the PHEN patients had all three «classic» components of the MEN-1 syndrome, and the clinical course of PHPT was similar to that of the MEN- group. These differences were also observed in the subgroups of patients younger than 40 years, which formed the basis for the development of a mathematical model. The logistic regression equation for predicting the probability of the presence of the MEN1 gene mutation included eight predictors, with a diagnostic sensitivity of 96% and specificity of 98%.

CONCLUSION

Based on the analysis performed, eight hereditary predictors of PHPT within the MEN-1 syndrome were identified. A mathematical model was developed to predict the presence of the MEN1 gene mutation in patients, which demonstrated high classification performance on the training dataset. Further refinement of the model will help improve the quality of medical care for patients with PHPT.

Identification of ferroptosis-associated biomarkers for the potential diagnosis and treatment of postmenopausal osteoporosis

OBJECTIVE

Postmenopausal osteoporosis (PMOP) is one of the most commonly occurring conditions worldwide and is characterized by estrogen deficiency as well as persistent calcium loss with age. The aim of our study was to identify significant ferroptosis-associated biomarkers for PMOP.

METHODS AND MATERIALS

We obtained our training dataset from the Gene Expression Omnibus (GEO) database using GSE56815 expression profiling data. Meanwhile, we extracted ferroptosis-associated genes for further analysis. Differentially expressed ferroptosis-associated genes (DEFAGs) between OP patients and normal controls were selected using the "limma" package. We established a ferroptosis-associated gene signature using training models, specifically, random forest (RF) and support vector machine (SVM) models. It was further validated in another dataset (GSE56814) which also showed a high AUC: 0.98, indicating high diagnostic value. Using consensus clustering, the OP patient subtypes were identified. A ferroptosis associated gene (FAG)-Scoring scheme was developed by PCA. The important candidate genes associated with OP were also compared between different ferrclusters and geneclusters.

RESULTS

There were significant DEFAGs acquired, of which five (HMOX1, HAMP, LPIN1, MAP3K5, FLT3) were selected for establishing a ferroptosis-associated gene signature. Analyzed from the ROC curve, our established RF model had a higher AUC value than the SVM model (RF model AUC:1.00). Considering these results, the established RF model was chosen to be the most appropriate training model. Later, based on the expression levels of the five DEFAGs, a clinical application nomogram was established. The OP patients were divided into two subtypes (ferrcluster A, B and genecluster A, B, respectively) according to the consensus clustering method based on DEFAGs and differentially expressed genes (DEGs). Ferrcluster B and genecluster B had higher ferroptosis score than ferrcluster A and genecluster A, respectively. The expression of COL1A1 gene was significantly higher in ferrcluster B and gencluster B compared with ferrcluster A and gencluster A, respectively, while there is no statistical difference in term of VDR gene, COL1A2 genes, and PTH gene expressions between ferrcluster A and B, together with gencluster A and B.

CONCLUSIONS

On the basis of five explanatory variables (HMOX1, HAMP, LPIN1, MAP3K5 and FLT3), we developed a diagnostic ferroptosis-associated gene signature and identified two differently categorized OP subtypes that may potentially be applied for the early diagnosis and individualized treatment of PMOP. The ER gene, VDR gene, IL-6 gene, COL1A1 and COL1A2 genes, and PTH gene are important candidate gene of OP, however, more studies are still anticipated to further elucidate the relationship between these genes and ferroptosis in OP.