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Background. Lipedema, a complex and enigmatic adipose tissue disorder, remains poorly understood despite its significant impact on the patients' quality of life. Genetic investigations have uncovered potential contributors to its pathogenesis, including somatic mutations, which are nonheritable genetic alterations that can play a pivotal role in the development of this disease. AIM. This review aims to elucidate the role of somatic mutations in the etiology of lipedema by examining their implications in adipose tissue biology, inflammation, and metabolic dysfunction. Results. Studies focusing on leukocyte clones, genetic alterations like TET2 and DNMT3A, and the intricate interplay between adipose tissue and other organs have shed light on the underlying mechanisms driving lipedema. From the study of the scientific literature, mutations to genes correlated to three main pathways could be involved in the somatic development of lipedema: genes related to mitochondrial activity, genes related to localized disorders of subcutaneous adipose tissue, and genes of leukocyte clones. Conclusions. The insights gained from these diverse studies converge to highlight the complex genetic underpinnings of lipedema and offer potential avenues for therapeutic interventions targeting somatic mutations to alleviate the burden of this condition on affected individuals. [ABSTRACT FROM AUTHOR]

Adipocytes express various enzymes, such as aldo-keto reductases (AKR1C), 11β-hydroxysteroid dehydrogenase (11β-HSD), aromatase, 5α-reductases, 3β-HSD, and 17β-HSDs involved in steroid hormone metabolism in adipose tissues. Increased activity of AKR1C enzymes and their expression in mature adipocytes might indicate the association of these enzymes with subcutaneous adipose tissue deposition. The inactivation of androgens by AKR1C enzymes increases adipogenesis and fat mass, particularly subcutaneous fat. AKR1C also causes reduction of estrone, a weak estrogen, to produce 17β-estradiol, a potent estrogen and, in addition, it plays a role in progesterone metabolism. Functional impairments of adipose tissue and imbalance of steroid biosynthesis could lead to metabolic disturbances. In this review, we will focus on the enzymes involved in steroid metabolism and fat tissue deposition. [ABSTRACT FROM AUTHOR]

Adipose tissue distribution usually varies among men and women. In men, adipose tissue is known to accumulate in the abdominal region surrounding the visceral organs (android fat distribution) whereas, in women, the accumulation of adipose tissue generally occurs in the gluteal-femoral regions (gynoid fat distribution). In some cases, however, android distribution can be found in women and gynoid distribution can be found in men. The regulation of adipose tissue accumulation involves interaction of a variety of genetic and environmental factors. This review examines genetic factors that cause differential distribution of adipose tissue in different depots of the body, between men and women and between different ethnicities. Genome-wide association studies can be used to identify genetic associations with the distribution and accumulation of adipose tissue. Insight into adipose tissue accumulation and distribution mechanisms could lead to development of personalized interventions for people who develop increased fat mass. [ABSTRACT FROM AUTHOR]

Correction to: Eur Rev Med Pharmacol Sci 2023; 27 (6 Suppl): 127-136-DOI: 10.26355/eurrev_202312_34697 After publication and following some post-publication concerns, the authors have applied the following corrections to the galley proof. -       The conflict of interest section has been amended as follows: J. Kaftalli and G. Marceddu are employees at MAGI EUREGIO. K. Donato is employee at MAGI EUREGIO and MAGISNAT. M. Bertelli is president of MAGI EUREGIO, MAGISNAT, and MAGI's LAB. G. Bonetti, K. Dhuli, A. Macchia, and P.E. Maltese are employees at MAGI's LAB. M. Bertelli, P.E. Maltese, K. Louise Herbst, Sa. Michelini, Se. Michelini, and P. Chiurazzi are patent inventors (US20220362260A1). M. Bertelli, P.E. Maltese, G. Marceddu are patent inventors (US20230173003A1). M. Bertelli, K. Dhuli and P.E. Maltese are patent inventors (WO2022079498A1). M. Bertelli, P.E. Maltese, Sa. Michelini, Se. Michelini, P. Chiurazzi, K. Louise Herbst, J. Kaftalli, K. Donato, and A. Bernini are patent applicants (Application Number 18/516,241). M. Bertelli, K. Donato, P. Chiurazzi, G. Marceddu, K. Dhuli, G. Bonetti and J. Kaftalli are patent applicants (Application Number: 18/466.879). M. Bertelli, G. Bonetti, G. Marceddu, K. Donato, K. Dhuli, J. Kaftalli, Sa. Michelini, and K. Louise Herbst are patent applicants (Application Number 63/495,155). The remaining authors have no conflict of interest to disclose. -       Figure 5 has been modified as follows to better distinguish outliers: -       The legend of Figure 5 has to be modified as follows: Relative expression of AKR1C1 and AKR1C3 in different groups (CTR = non affected controls, L = lipedema patients without overexpression of AKR1C2, L-over = Lipedema patients with overexpression of AKR1C2), showing that lipedema patients expressed AKR1C1 and AKR1C3 levels similar to the control group. Outliers are reported as black triangles. There are amendments to this paper. The Publisher apologizes for any inconvenience this may cause. https://www.europeanreview.org/article/34697.

Molecular docking simulation of small molecule drugs to macromolecules is valuable in structural biology and medicinal chemistry research. Its spread is supported by freely available software and databases. Like many resources in the free domain, docking software is command-line based, which comes to a limitation when defining the volume encompassing an active site, the so-called docking box. The box center and size, usually specified as cartesian coordinates, can be adjusted to correctly cover the active site only with a third-party molecular graphics program compatible with the docking input/output files, which reduces the choice to a few options. Moreover, the additional staff training may hamper the adoption of such software, e.g., in an enterprise environment. We exposed the functionality of Autodock and Autodock Vina into a graphical user interface extending upon that of PyMOL. Both the functionality of PyMOL and Autodock are merged, synergizing the capabilities of each program. To overcome such limitations, here we present MAGI-Dock. This graphical user interface combines the power of two of the most used free software for docking and graphics, Autodock Vina and PyMOL. MAGI-Dock is a free open-source software available under the GPL and can be downloaded from https://github.com/gjonwick/MAGI-Dock. The coupling of Autodock Vina with PyMOL through a graphical interface removes the molecular modeling limitations that come with Autodock. Therefore, MAGI-Dock could be conducive to lowering the learning curve for molecular docking simulation, with benefits for trainees in both academia and enterprise environments.

Objective: Lipedema is a debilitating chronic condition predominantly affecting women, characterized by the abnormal accumulation of fat in a symmetrical, bilateral pattern in the extremities, often coinciding with hormonal imbalances., Patients and Methods: Despite the conjectured role of sex hormones in its etiology, a definitive link has remained elusive. This study explores the case of a patient possessing a mutation deletion within the C-terminal region of Aldo-keto reductases Member C2 (AKR1C2), Ser320PheTer2, that could lead to heightened enzyme activity. A cohort of 19 additional lipedema patients and 2 additional affected family members14 were enrolled in this study. The two additional affected family members are relatives of the patient with the AKR1C1 L213Q variant, which is included in the 19 cohorts and described in literature., Results: Our investigation revealed that AKR1C2 was overexpressed, as quantified by qPCR, in 5 out of 21 (24%) lipedema patients who did not possess mutations in the AKR1C2 gene. Collectively, these findings implicate AKR1C2 in the pathogenesis of lipedema, substantiating its causative role., Conclusions: This study demonstrates that the activating mutation in the enzyme or its overexpression is a causative factor in the development of lipedema. Further exploration and replication in diverse populations will bolster our understanding of this significant connection.

Objective: Lipedema is an autosomal dominant genetic disease that mainly affects women. It is characterized by excess deposition of subcutaneous adipose tissue, pain, and anxiety. The genetic and environmental etiology of lipedema is still largely unknown. Although considered a rare disease, this pathology has been suggested to be underdiagnosed or misdiagnosed as obesity or lymphedema. Steroid hormones seem to be involved in the pathogenesis of lipedema. Indeed, aldo-keto reductase family 1 member C1 (AKR1C1), a gene coding for a protein involved in steroid hormones metabolism, was the first proposed to be correlated with lipedema., Patients and Methods: In this study, we employed a molecular dynamics approach to assess the pathogenicity of AKR1C1 genetic variants found in patients with lipedema. Moreover, we combined information theory and structural bioinformatics to identify AKR1C1 polymorphisms from the gnomAD database that could predispose to the development of lipedema., Results: Three genetic variants in AKR1C1 found in patients with lipedema were disruptive to the protein's function. Furthermore, eight AKR1C1  variants found in the general population could predispose to the development of lipedema., Conclusions: The results of this study provide evidence that AKR1C1 may be a key gene in lipedema pathogenesis, and that common polymorphisms could predispose to lipedema development.

Sequencing of the low-complexity ORF15 exon of RPGR, a gene correlated with retinitis pigmentosa and cone dystrophy, is difficult to achieve with NGS and Sanger sequencing. False results could lead to the inaccurate annotation of genetic variants in dbSNP and ClinVar databases, tools on which HGMD and Ensembl rely, finally resulting in incorrect genetic variants interpretation. This paper aims to propose PacBio sequencing as a feasible method to correctly detect genetic variants in low-complexity regions, such as the ORF15 exon of RPGR, and interpret their pathogenicity by structural studies. Biological samples from 75 patients affected by retinitis pigmentosa or cone dystrophy were analyzed with NGS and repeated with PacBio. The results showed that NGS has a low coverage of the ORF15 region, while PacBio was able to sequence the region of interest and detect eight genetic variants, of which four are likely pathogenic. Furthermore, molecular modeling and dynamics of the RPGR Glu-Gly repeats binding to TTLL5 allowed for the structural evaluation of the variants, providing a way to predict their pathogenicity. Therefore, we propose PacBio sequencing as a standard procedure in diagnostic research for sequencing low-complexity regions such as RPGR ORF15 , aiding in the correct annotation of genetic variants in online databases.

Background: Lipedema, a complex and enigmatic adipose tissue disorder, remains poorly understood despite its significant impact on the patients' quality of life. Genetic investigations have uncovered potential contributors to its pathogenesis, including somatic mutations, which are nonheritable genetic alterations that can play a pivotal role in the development of this disease., Aim: This review aims to elucidate the role of somatic mutations in the etiology of lipedema by examining their implications in adipose tissue biology, inflammation, and metabolic dysfunction., Results: Studies focusing on leukocyte clones, genetic alterations like TET2 and DNMT3A, and the intricate interplay between adipose tissue and other organs have shed light on the underlying mechanisms driving lipedema. From the study of the scientific literature, mutations to genes correlated to three main pathways could be involved in the somatic development of lipedema: genes related to mitochondrial activity, genes related to localized disorders of subcutaneous adipose tissue, and genes of leukocyte clones., Conclusions: The insights gained from these diverse studies converge to highlight the complex genetic underpinnings of lipedema and offer potential avenues for therapeutic interventions targeting somatic mutations to alleviate the burden of this condition on affected individuals.

Obesity is a chronic disease in which abnormal deposition of fat threatens health, leading to diabetes, cardiovascular diseases, cancer, and other chronic illnesses. According to the WHO, 19.8% of the adult population in Italy is obese, and the prevalence is higher among men. It is important to know the predisposition of an individual to become obese and to respond to bariatric surgery, the most up-to-date treatment for severe obesity. To this purpose, we developed an NGS gene panel, comprising 72 diagnostic genes and 244 candidate genes, and we sequenced 247 adult obese Italian patients. Eleven deleterious variants in 9 diagnostic genes and 17 deleterious variants in 11 candidate genes were identified. Interestingly, mutations were found in several genes correlated to the Bardet-Biedl syndrome. Then, 25 patients were clinically followed to evaluate their response to bariatric surgery. After a 12-month follow-up, the patients that carried deleterious variants in diagnostic or candidate genes had a reduced weight loss, as compared to the other patients. The NGS-based panel, including diagnostic and candidate genes used in this study, could play a role in evaluating, diagnosing, and managing obese individuals, and may help in predicting the outcome of bariatric surgery.

Every human being possesses an exclusive nutritional blueprint inside their genes. Bioactive food components and nutrients affect the expression of such genes. Nutrigenomics is the science that analyzes gene-nutrient interactions (nutrigenetics), which can lead to the development of personalized nutritional recommendations to maintain optimal health and prevent disease. Genomic diversity among various ethnic groups might affect nutrients bioavailability as well as their metabolism. Nutrigenomics combines different branches of science including nutrition, bioinformatics, genomics, molecular biology, molecular medicine, and epidemiology. Genes regulate intake and metabolism of different nutrients, while nutrients positively or negatively influence the expression of a number of genes; testing of specific genetic polymorphisms may therefore become a useful tool to manage weight loss and to fully understand gene-nutrient interactions. Indeed, several approaches are used to study gene-nutrient interactions: epigenetics, the study of genome modification not related to changes in nucleotide sequence; transcriptomics, the study of tissue-specific and time-specific RNA transcripts; proteomics, the study of proteins involved in biological processes; and metabolomics, the study of changes of primary and secondary metabolites in body fluids and tissues. Hence, the use of nutrigenomics to improve and optimize a healthy, balanced diet in clinical settings could be an effective approach for long-term lifestyle changes that might lead to consistent weight loss and improve quality of life., (©2022 Pacini Editore SRL, Pisa, Italy.)