The Spexin gene is considered the most dysregulated in obese human fat. Limited data suggest that the novel peptide spexin may potentially impact food intake, weight regulation and body adiposity. The aim of this case-control study was to compare fasting serum spexin concentrations between normal weight (NW) and overweight/obese (OB/OW) adolescent females and explore the relationship between circulating spexin and anthropometric, bone and fat mass, metabolic and hormonal parameters. Eighty post-menarcheal females (mean age ± SD 16.23 ± 2.26 years); 55 NW (mean BMI ± SD 19.72 ± 2.52 kg/m²) and 25 OB/OW (mean BMI ± SD 29.35 ± 3.89 kg/m²) participated in the study. Circulating spexin levels did not differ significantly (p = 0.378) between NW (median (interquartile range), 0.26 (0.17) ng/mL) and OB/OW (median (interquartile range), 0.28 (0.06) ng/mL) adolescents and did not correlate with BMI (r_s = −0.090, p = 0.438), % body fat (r_s = −0.173, p = 0.409), glucose or insulin resistance indices derived from fasting and oral glucose tolerance states. In the total study sample, spexin concentrations correlated positively with lipoprotein(a) (r_s = 0.402, p = 0.046). In the OB/OW adolescents spexin levels correlated positively with testosterone (r_s = 0.727, p = 0.011) and free androgen index (r_s = 0.755, p = 0.007). In the NW adolescents, spexin concentrations correlated negatively with dehydroepiandrosterone sulphate (r_s = −0.445, p = 0.038). Results may suggest potential involvement of spexin in the regulation of lipoprotein(a) and of the reproductive/adrenal axis in post-menarcheal adolescent females.

In clinical practice, differences in glucocorticoid sensitivity among healthy subjects may influence the outcome and any adverse effects of glucocorticoid therapy. Thus, a fast and accurate methodology that could enable the classification of individuals based on their tissue glucocorticoid sensitivity would be of value. We investigated the usefulness of untargeted plasma metabolomics in identifying a panel of metabolites to distinguish glucocorticoid-resistant from glucocorticoid-sensitive healthy subjects who do not carry mutations in the human glucocorticoid receptor (NR3C1) gene. Applying a published methodology designed for the study of glucocorticoid sensitivity in healthy adults, 101 healthy subjects were ranked according to their tissue glucocorticoid sensitivity based on 8:00 a.m. serum cortisol concentrations following a very low-dose dexamethasone suppression test. Ten percent of the cohort, i.e., 11 participants, on each side of the ranking, with no NR3C1 mutations or polymorphisms, were selected, respectively, as the most glucocorticoid-sensitive and most glucocorticoid-resistant of the cohort to be analyzed and compared with untargeted blood plasma metabolomics using gas chromatography–mass spectrometry (GC–MS). The acquired metabolic profiles were evaluated using multivariate statistical analysis methods. Nineteen metabolites were identified with significantly lower abundance in the most sensitive compared to the most resistant group of the cohort, including fatty acids, sugar alcohols, and serine/threonine metabolism intermediates. These results, combined with a higher glucose, sorbitol, and lactate abundance, suggest a higher Cori cycle, polyol pathway, and inter-tissue one-carbon metabolism rate and a lower fat mobilization rate at the fasting state in the most sensitive compared to the most resistant group. In fact, this was the first study correlating tissue glucocorticoid sensitivity with serine/threonine metabolism. Overall, the observed metabolic signature in this cohort implies a worse cardiometabolic profile in the most glucocorticoid-sensitive compared to the most glucocorticoid-resistant healthy subjects. These findings offer a metabolic signature that distinguishes most glucocorticoid-sensitive from most glucocorticoid-resistant healthy subjects to be further validated in larger cohorts. Moreover, they support the correlation of tissue glucocorticoid sensitivity with insulin resistance and metabolic syndrome-associated pathways, further emphasizing the need for nutritionists and doctors to consider the tissue glucocorticoid sensitivity in dietary and exercise planning, particularly when these subjects are to be treated with glucocorticoids.

Background: Pathogenic variants within the gene encoding transforming growth factor β (TGF-β) are responsible for Loeys-Dietz syndrome (LDS), a heritable thoracic aortic disease sharing clinical features with Marfan syndrome, including craniofacial and skeletal abnormalities as well as aortic root aneurysms and dissections. In contrast to Marfan syndrome patients, who rarely develop aneurysms or dissections beyond the aortic root, LDS patients frequently exhibit vessel aneurysms in locations other than the aortic root. Here, we report the case of a 61-year-old patient who initially presented with marfanoid characteristics and an aortic root aneurysm and was presumed to have Marfan syndrome two decades ago. Later, the patient developed an abdominal aorta aneurysm, necessitating endovascular repair and stent placement. That fact raised doubts regarding the initial diagnosis of Marfan syndrome, and we decided to investigate the genetic cause of the disorder. Methods: Genetic testing was performed using WES analysis and Sanger sequencing. Results: The genetic analysis detected a de novo heterozygous pathogenic variant c.896G>A in exon 5 of the TGFB2 gene, resulting in the amino acid substitution p. Arg299Gln that has devastating destabilizing structural effects on 3D folding of the protein, as demonstrated by the molecular modeling study we performed. This variant is pathogenic for LDS type 4, partially consistent with the patient’s clinical presentation. Conclusions: Our case emphasizes the significance of precise clinical assessment and genetic verification in patients exhibiting marfanoid characteristics. Furthermore, our findings contribute to the understanding of the diverse clinical spectrum associated with this specific pathogenic variant of TGFB2, underscoring the importance of detailed clinical assessment in expanding knowledge of genotype-phenotype correlations. Accurate diagnosis is crucial for tailored and appropriate management of individuals with heritable thoracic aortic diseases.

Significant inter-individual variation in terms of susceptibility to several stress-related disorders, such as myocardial infarction and Alzheimer’s disease, and therapeutic response has been observed among healthy subjects. The molecular features responsible for this phenomenon have not been fully elucidated. Proteomics, in association with bioinformatics analysis, offer a comprehensive description of molecular phenotypes with clear links to human disease pathophysiology. The aim of this study was to conduct a comparative plasma proteomics analysis of glucocorticoid resistant and glucocorticoid sensitive healthy subjects and provide clues of the underlying physiological differences. For this purpose, 101 healthy volunteers were given a very low dose (0.25 mg) of dexamethasone at midnight, and were stratified into the 10% most glucocorticoid sensitive (S) (n = 11) and 10% most glucocorticoid resistant (R) (n = 11) according to the 08:00 h serum cortisol concentrations determined the following morning. One month following the very-low dose dexamethasone suppression test, DNA and plasma samples were collected from the 22 selected individuals. Sequencing analysis did not reveal any genetic defects in the human glucocorticoid receptor (NR3C1) gene. To investigate the proteomic profile of plasma samples, we used Liquid Chromatography–Mass Spectrometry (LC-MS/MS) and found 110 up-regulated and 66 down-regulated proteins in the S compared to the R group. The majority of the up-regulated proteins in the S group were implicated in platelet activation. To predict response to cortisol prior to administration, a random forest classifier was developed by using the proteomics data in order to distinguish S from R individuals. Apolipoprotein A4 (APOA4) and gelsolin (GSN) were the most important variables in the classification, and warrant further investigation. Our results indicate that a proteomics signature may differentiate the S from the R healthy subjects, and may be useful in clinical practice. In addition, it may provide clues of the underlying molecular mechanisms of the chronic stress-related diseases, including myocardial infarction and Alzheimer’s disease.

Background: Osteodysplastic syndromes comprise a very diverse group of clinically and genetically heterogeneous disorders characterized by defects in bone and connective tissue development, as well as in bone density. Here, we report the case of a 48-year-old female with a complex medical history characterized by bone dysplasia, hyperostosis, and partial tooth agenesis. Methods: Genetic testing was performed using WES analysis and Sanger sequencing. Molecular modeling analysis and dynamics simulation explored the impact of detected pathogenic variants. Results: The genetic analysis detected multiple pathogenic variants in genes CREB3L1, SLCO2A1, SFRP4, LRP5, and LRP6, each of which has been associated with rare osteodysplastic syndromes. The patient was homozygous for the same rare alleles associated with three of the identified autosomal recessive disorders osteogenesis imperfecta type XVI, primary hypertrophic osteoarthropathy, and metaphyseal dysplasia Pyle type. She also had a variant linked to autosomal dominant endosteal hyperostosis and a variant previously associated with increased risk of osteoporosis and bone fractures. Two of the detected variants are predicted to cause abnormal splicing, while molecular modeling and dynamics simulations analysis suggest that the other three variants probably confer altered local secondary structure and flexibility that may have functionally devastating consequences. Conclusions: Our case highlights the rare coexistence of multiple osteodysplastic syndromes in a single patient that may complicate differential diagnosis. Furthermore, this case emphasizes the necessity for early genetic investigation of such complex cases with overlying phenotypic traits, followed by genetic counseling, facilitating orchestration of clinical interventions and allowing prevention and/or prompt management of manifestations.

Background: Osteodysplastic syndromes compose a very diverse group of clinically and genetically heterogeneous disorders characterized by defects in bone and connective tissue development, as well as in bone density. Here, we report the case of a 48-year-old female with a complex medical history characterized by bone dysplasia, hyperostosis, and partial tooth agenesis. Methods: Genetic testing was performed using WES analysis and Sanger sequencing. Molecular modeling analysis and dynamics simulation explored the impact of detected pathogenic variants. Results: The genetic analysis detected multiple pathogenic variants in genes CREB3L1, SLCO2A1, SFRP4, LRP5 and LRP6, which are associated with rare osteodysplastic syndromes. The patient was homozygous for the same rare alleles associated with three of the identified autosomal recessive disorders, such as osteogenesis imperfecta type XVI, primary hypertrophic osteoarthropathy, and metaphyseal dysplasia Pyle type. She also had a variant linked to autosomal dominant endosteal hyperostosis and a variant previously associated with increased risk of osteoporosis and fractures. Two of the detected variants are predicted to cause abnormal splicing, while molecular modelling and dynamics simulations analysis suggest that the other three variants probably confer altered local secondary structure and flexibility that may be functionally devastating consequences. Conclusions: Our case highlights the rare coexistence of multiple osteodysplastic syndromes in a single patient that may complicate differential diagnosis. Furthermore, this case emphasizes the necessity for early genetic investigation of such complex cases with overlying phenotypic traits, followed by genetic counseling, in order to orchestrate clinical interventions and prevent or promptly manage manifestations.