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miRNAs are important regulators of biological processes in many tissues, including the differentiation and function of brown and white adipocytes. The endoribonuclease dicer is a major component of the miRNA-processing pathway, and in adipose tissue, levels of dicer have been shown to decrease with age, increase with caloric restriction, and influence stress resistance. Here, we demonstrated that mice with a fat-specific KO of dicer develop a form of lipodystrophy that is characterized by loss of intra-abdominal and subcutaneous white fat, severe insulin resistance, and enlargement and \"whitening\" of interscapular brown fat. Additionally, KO of dicer in cultured brown preadipocytes promoted a white adipocyte-like phenotype and reduced expression of several miRNAs. Brown preadipocyte whitening was partially reversed by expression of miR-365, a miRNA known to promote brown fat differentiation; however, introduction of other miRNAs, including miR-346 and miR-362, also contributed to reversal of the loss of the dicer phenotype. Interestingly, fat samples from patients with HIV-related lipodystrophy exhibited a substantial downregulation of dicer mRNA expression. Together, these findings indicate the importance of miRNA processing in white and brown adipose tissue determination and provide a potential link between this process and HIV-related lipodystrophy.

Lipodystrophy (LD) syndromes are characterized by loss of adipose tissue (AT), leading to insulin resistance and the development of metabolic syndrome. We identified a heterozygous nonsense variant in early B cell factor 2 ( EBF2 ) (Chr8:26033143C>A, NM_022659.4: c.493G>T, p.E165X) in a patient with atypical partial LD (PLD). The EBF family is crucial for the differentiation and function of various mesenchymal tissues. Through in vitro and in vivo disease models, we discovered that this variant limited adipocyte differentiation and hampered AT remodeling. Heterozygous-knockin ( Ebf2 E165X/+ ) mice showed restricted adipogenesis and defective extracellular matrix remodeling during the post-weaning period and high-fat diet–induced (HFD-induced) AT expansion. A HFD caused abnormal adipocyte hypertrophy, decreased the expression of adiponectin and leptin, and led to glucose intolerance in Ebf2 E165X/+ mice. Furthermore, key mitochondrial genes involved in fatty acid metabolism and oxidation were downregulated specifically in Ebf2 E165X/+ AT. Our results suggest that EBF2 dysfunction caused by this nonsense variant drives disease pathology, establishing a connection between EBF2 disruption and an atypical form of LD.

Recent research into laminopathic lipodystrophies—rare genetic disorders caused by mutations in the LMNA gene—has greatly expanded our knowledge of their complex pathology and metabolic implications. These disorders, including Hutchinson-Gilford progeria syndrome (HGPS), Mandibuloacral Dysplasia (MAD), and Familial Partial Lipodystrophy (FPLD), serve as crucial models for studying accelerated aging and metabolic dysfunction, enhancing our understanding of the cellular and molecular mechanisms involved. Research on laminopathies has highlighted how LMNA mutations disrupt adipose tissue function and metabolic regulation, leading to altered fat distribution and metabolic pathway dysfunctions. Such insights improve our understanding of the pathophysiological interactions between genetic anomalies and metabolic processes. This review merges current knowledge on the phenotypic classifications of these diseases and their associated metabolic complications, such as insulin resistance, hypertriglyceridemia, hepatic steatosis, and metabolic syndrome, all of which elevate the risk of cardiovascular disease, stroke, and diabetes. Additionally, a range of published therapeutic strategies, including gene editing, antisense oligonucleotides, and novel pharmacological interventions aimed at addressing defective adipocyte differentiation and lipid metabolism, will be explored. These therapies target the core dysfunctional lamin A protein, aiming to mitigate symptoms and provide a foundation for addressing similar metabolic and genetic disorders.

Background Congenital generalized lipodystrophy (CGL) is a rare inherited disease characterized by a near-total absence of adipose tissue and is associated with organ system abnormalities and severe metabolic complications. Here, we have analyzed the disease characteristics of the largest CGL cohort from the Middle East and North Africa (MENA) who have not received lipodystrophy-specific treatment. Methods CGL was diagnosed clinically by treating physicians through physical assessment and supported by genetic analysis, fat loss patterns, family history, and the presence of parental consanguinity. Data were obtained at the time of patient diagnosis and during leptin-replacement naïve follow-up visits as permitted by available medical records. Results Data from 43 patients with CGL (37 females, 86%) were collected from centers located in eight countries. The mean (median, range) age at diagnosis was 5.1 (1.0, at birth–37) years. Genetic analysis of the overall cohort showed that CGL1 (n = 14, 33%) and CGL2 (n = 18, 42%) were the predominant CGL subtypes followed by CGL4 (n = 10, 23%); a genetic diagnosis was unavailable for one patient (2%). There was a high prevalence of parental consanguinity (93%) and family history (67%) of lipodystrophy, with 64% (n = 25/39) and 51% (n = 20/39) of patients presenting with acromegaloid features and acanthosis nigricans, respectively. Eighty-one percent (n = 35/43) of patients had at least one organ abnormality; the most frequently affected organs were the liver (70%, n = 30/43), the cardiovascular system (37%, n = 16/43) and the spleen (33%, n = 14/43). Thirteen out of 28 (46%) patients had HbA1c > 5.7% and 20/33 (61%) had triglyceride levels > 2.26 mmol/L (200 mg/dl). Generally, patients diagnosed in adolescence or later had a greater severity of metabolic disease versus those diagnosed during childhood; however, metabolic and organ system abnormalities were observed in a subset of patients diagnosed before or at 1 year of age. Conclusions This analysis suggests that in addition to the early onset of fat loss, family history and high consanguinity enable the identification of young patients with CGL in the MENA region. In patients with CGL who have not received lipodystrophy-specific treatment, severe metabolic disease and organ abnormalities can develop by late childhood and worsen with age.

1-Acylglycerol-3-phosphate O-acyltransferase (1-AGPAT) is an enzyme family composed of 11 isoforms. Notably, 1-AGPAT 2, the most studied isoform since its discovery, is a critical enzyme in the triglyceride synthesis pathway, converting lysophosphatidic acid to phosphatidic acid. In addition, AGPAT2 gene expression is shown to be essential for adipocyte development and maturation. Defects in AGPAT2 are responsible for significant pathophysiological alterations related to adipose tissue (AT). Pathogenic variants in this gene are the molecular etiology of Congenital Generalized Lipodystrophy type 1 (CGL1), in which fatty tissue is absent from birth. Metabolically, these individuals have several metabolic complications, including hypoleptinemia, hypoadiponectinemia, hyperglycemia, and hypertriglyceridemia. Furthermore, numerous AGPAT2 pathogenic variants that enormously affect the amino acid sequence, the tertiary structure of 1-AGPAT 2, and their transmembrane and functional domains were found in CGL1 patients. However, studies investigating the genotype–phenotype relationship in this disease are scarce. Here, we used bioinformatics tools to verify the effect of the main pathogenic variants reported in the AGPAT2 gene: c.366-588del, c.589-2A>G, c.646A>T, c.570C>A, c.369-372delGCTC, c.202C>T, c.514G>A, and c.144C>A in the 1-AGPAT 2 membrane topology. We also correlated the phenotype of CGL1 subjects harboring these variants to understand the genotype–phenotype relationship. We provided an integrative view of clinical, genetic, and metabolic features from CGL1 individuals, helping to understand the role of 1-AGPAT 2 in the pathogenesis of this rare disease. Data reviewed here highlight the importance of new molecular studies to improve our knowledge concerning clinical and genetic heterogeneity in CGL1.

In this study, we analysed the mutation spectrum in subjects with suspected lipodystrophy using a targeted Next-generation sequencing (NGS) approach. Subjects with suspected lipodystrophy were for screened six genes ( AGPAT2 , BSCL2 , LMNA , PPARG , ZMPSTE24 , INSR ) and the variants identified were confirmed through Sanger sequencing. The clinical and biochemical parameters were compared among the mutation positive and negative subjects. We identified eight individuals with pathogenic or likely pathogenic mutations, including both homozygous and heterozygous variants. Homozygous variants included   AGPAT2 (NM_006412.4):c.493-2A>G, AGPAT2 (NM_006412.4):c.254_258dup, and BSCL2 (NM_001122955.4):c.570del, while heterozygous variants encompassed LMNA (NM_170707.4):c.1444C>T, LMNA (NM_170707.4):c.1456A>G, LMNA (NM_170707.4):c.1445G>A, and PPARG (NM_015869.5):c.949T>C mutations. In this cohort, three subjects were diagnosed with congenital generalized lipodystrophy, while the remaining five had familial partial lipodystrophy. Majority (7/8) of the patients with lipodystrophy had hepatic involvement. Notably, more than half of the subjects (5/8) achieved optimal glycemic control through insulin sensitizers (PPARγ agonist and Metformin). Interestingly, even with a limited gene panel test, mutation-positive individuals exhibited a higher prevalence of typical clinical features and biochemical characteristics associated with lipodystrophy compared to their mutation-negative counterparts. In subjects with lipodystrophy, targeted NGS based screening may establish a genetic diagnosis and aid in family screening and genetic counselling. Knowing the clinical and biochemical features typical to lipodystrophy may help in diagnosis especially in resource limited setting.

Generalized lipodystrophy is a feature of various hereditary disorders, often leading to a progeroid appearance. In the present study we identified a missense and a frameshift variant in a compound heterozygous state in SUPT7L in a boy with intrauterine growth retardation, generalized lipodystrophy, and additional progeroid features. SUPT7L encodes a component of the transcriptional coactivator complex STAGA. By transcriptome sequencing, we showed the predicted missense variant to cause aberrant splicing, leading to exon truncation and thereby to a complete absence of SUPT7L in dermal fibroblasts. In addition, we found altered expression of genes encoding DNA repair pathway components. This pathway was further investigated and an increased rate of DNA damage was detected in proband-derived fibroblasts and genome-edited HeLa cells. Finally, we performed transient overexpression of wildtype SUPT7L in both cellular systems, which normalizes the number of DNA damage events. Our findings suggest SUPT7L as a novel disease gene and underline the link between genome instability and progeroid phenotypes.

Congenital Generalized Lipodystrophy (CGL) is a rare autosomal recessive disease characterized by near complete absence of functional adipose tissue from birth. CGL diagnosis can be based on clinical data including acromegaloid features, acanthosis nigricans, reduction of total body fat, muscular hypertrophy, and protrusion of the umbilical scar. The identification and knowledge of CGL by the health care professionals is crucial once it is associated with severe and precocious cardiometabolic complications and poor outcome. Image processing by deep learning algorithms have been implemented in medicine and the application into routine clinical practice is feasible. Therefore, the aim of this study was to identify congenital generalized lipodystrophy phenotype using deep learning. A deep learning approach model using convolutional neural network was presented as a detailed experiment with evaluation steps undertaken to test the effectiveness. These experiments were based on CGL patient’s photography database. The dataset consists of two main categories (training and testing) and three subcategories containing photos of patients with CGL, individuals with malnutrition and eutrophic individuals with athletic build. A total of 337 images of individuals of different ages, children and adults were carefully chosen from internet open access database and photographic records of stored images of medical records of a reference center for inherited lipodystrophies. For validation, the dataset was partitioned into four parts, keeping the same proportion of the three subcategories in each part. The fourfold cross-validation technique was applied, using 75% (3 parts) of the data as training and 25% (1 part) as a test. Following the technique, four tests were performed, changing the parts that were used as training and testing until each part was used exactly once as validation data. As a result, a mean accuracy, sensitivity, and specificity were obtained with values of [90.85 ± 2.20%], [90.63 ± 3.53%] and [91.41 ± 1.10%], respectively. In conclusion, this study presented for the first time a deep learning model able to identify congenital generalized lipodystrophy phenotype with excellent accuracy, sensitivity and specificity, possibly being a strategic tool for detecting this disease.

Background The authors recently performed plastic surgeries for a small number of patients with hemophilia, HIV infection, and morphologic evidence of lipodystrophy. Because the pathophysiological mechanism of HIV-associated lipodystrophy remains to be elucidated, we analyzed subcutaneous adipose tissues from the patients. Methods All six patients had previously been treated with older nucleoside analogue reverse-transcriptase inhibitors (NRTIs; stavudine, didanosine or zidovudine). Abdominal and inguinal subcutaneous fat samples were obtained from the HIV+ patients with hemophilia and HIV− healthy volunteers (n = 6 per group), and analyzed via DNA microarray, real-time PCR, flow cytometry and immunohistochemistry. Results The time from initial NRTI treatment to collecting samples were 21.7 years in average. Cytometric analysis revealed infiltration of inflammatory M1 macrophages into HIV-infected adipose tissue and depletion of adipose-derived stem cells, possibly due to exhaustion following sustained adipocyte death. Genetic analysis revealed that adipose tissue from HIV+ group had increased immune activation, mitochondrial toxicity, chronic inflammation, progressive fibrosis and adipocyte dysfunction (e.g. insulin resistance, inhibited adipocyte differentiation and accelerated apoptosis). Of note, both triglyceride synthesis and lipolysis were inhibited in adipose tissue from patients with HIV. Conclusions Our findings provide important insights into the pathogenesis of HIV-associated lipodystrophy, suggesting that fat redistribution may critically depend on adipocytes’ sensitivity to drug-induced mitochondrial toxicity, which may lead either to atrophy or metabolic complications.

Congenital generalized lipodystrophy (CGL) is a rare autosomal recessive disease with a prevalence of less than one in ten million. To our knowledge, ~500 cases, including 95% of BSCL2, have been reported in the literatures, but no types of CGL with NOTCH2 gene mutation has been described.