LipoDDx: a mobile application for identification of rare lipodystrophy syndromes

Patients' perspective on the medical pathway from first symptoms to diagnosis in genetic lipodystrophy

OBJECTIVE

Underdiagnosis is an important issue in genetic lipodystrophies, which are rare diseases with metabolic, cardiovascular, gynecological, and psychological complications. We aimed to characterize the diagnostic pathway in these diseases from the patients' perspective.

DESIGN

Cross-sectional study conducted through a self-reported patient questionnaire.

METHODS

Patients with genetic lipodystrophy were recruited throughout the French national reference network for rare diseases of insulin secretion and insulin sensitivity. Patients completed a self-reported questionnaire on disease symptoms, steps leading to the diagnosis, and healthcare professionals involved. Descriptive analyses were conducted.

RESULTS

Out of 175 eligible patients, 109 patients (84% women) were included; 93 had partial familial lipodystrophy and 16 congenital generalized lipodystrophy. Metabolic comorbidities (diabetes 68%, hypertriglyceridemia 66%, hepatic steatosis 57%), cardiovascular (hypertension 54%), and gynecologic complications (irregular menstruation 60%) were frequently reported. Median age at diagnosis was 30 years (interquartile range [IQR] 23-47). The overall diagnostic process was perceived as "very difficult" for many patients. It extended over 12 years (IQR 5-25) with more than five different physicians consulted by 36% of respondents, before diagnosis, for lipodystrophy-related symptoms. The endocrinologist made the diagnosis for 77% of the patients. Changes in morphotype were reported as the first symptoms by the majority of respondents.

CONCLUSIONS

Diagnostic pathway in patients with genetic lipodystrophy is rendered difficult by the multisystemic features of the disease and the lack of knowledge of non-specialized physicians. Training physicians to systematically include adipose tissue examination in routine clinical evaluation should improve diagnosis and management of lipodystrophy and lipodystrophy-associated comorbidities.

Clinical Spectrum of LMNA-Associated Type 2 Familial Partial Lipodystrophy: A Systematic Review

Type 2 familial partial lipodystrophy (FPLD2) is a laminopathic lipodystrophy due to pathogenic variants in the LMNA gene. Its rarity implies that it is not well-known. The aim of this review was to explore the published data regarding the clinical characterisation of this syndrome in order to better describe FPLD2. For this purpose, a systematic review through a search on PubMed until December 2022 was conducted and the references of the retrieved articles were also screened. A total of 113 articles were included. FPLD2 is characterised by the loss of fat starting around puberty in women, affecting limbs and trunk, and its accumulation in the face, neck and abdominal viscera. This adipose tissue dysfunction conditions the development of metabolic complications associated with insulin resistance, such as diabetes, dyslipidaemia, fatty liver disease, cardiovascular disease, and reproductive disorders. However, a great degree of phenotypical variability has been described. Therapeutic approaches are directed towards the associated comorbidities, and recent treatment modalities have been explored. A comprehensive comparison between FPLD2 and other FPLD subtypes can also be found in the present review. This review aimed to contribute towards augmenting knowledge of the natural history of FPLD2 by bringing together the main clinical research in this field.

Identifying congenital generalized lipodystrophy using deep learning-DEEPLIPO

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.

Dunnigan lipodystrophy syndrome: French National Diagnosis and Care Protocol (PNDS; Protocole National de Diagnostic et de Soins)

Dunnigan syndrome, or Familial Partial Lipodystrophy type 2 (FPLD2; ORPHA 2348), is a rare autosomal dominant disorder due to pathogenic variants of the LMNA gene. The objective of the French National Diagnosis and Care Protocol (PNDS; Protocole National de Diagnostic et de Soins), is to provide health professionals with a guide to optimal management and care of patients with FPLD2, based on a critical literature review and multidisciplinary expert consensus. The PNDS, written by members of the French National Reference Center for Rare Diseases of Insulin Secretion and Insulin Sensitivity (PRISIS), is available on the French Health Authority website (in French). Dunnigan syndrome is characterized by a partial atrophy of the subcutaneous adipose tissue and by an insulin resistance syndrome, associated with a risk of metabolic, cardiovascular and muscular complications. Its prevalence, assessed at 1/100.000 in Europe, is probably considerably underestimated. Thorough clinical examination is key to diagnosis. Biochemical testing frequently shows hyperinsulinemia, abnormal glucose tolerance and hypertriglyceridemia. Elevated hepatic transaminases (hepatic steatosis) and creatine phosphokinase, and hyperandrogenism in women, are common. Molecular analysis of the LMNA gene confirms diagnosis and allows for family investigations. Regular screening and multidisciplinary monitoring of the associated complications are necessary. Diabetes frequently develops from puberty onwards. Hypertriglyceridemia may lead to acute pancreatitis. Early atherosclerosis and cardiomyopathy should be monitored. In women, polycystic ovary syndrome is common. Overall, the management of patients with Dunnigan syndrome requires the collaboration of several health care providers. The attending physician, in conjunction with the national care network, will ensure that the patient receives optimal care through regular follow-up and screening. The various elements of this PNDS are described to provide such a support.

Familial partial lipodystrophy syndromes

Lipodystrophies are a heterogeneous group of rare conditions characterised by the loss of adipose tissue. The most common forms are the familial partial lipodystrophy (FPLD) syndromes, which include a set of disorders, usually autosomal dominant, due to different pathogenetic mechanisms leading to improper fat distribution (loss of fat in the limbs and gluteal region and variable regional fat accumulation). Affected patients are prone to suffering serious morbidity via the development of metabolic complications associated to insulin resistance and an inability to properly store lipids. Although no well-defined diagnostic criteria have been established for lipodystrophy, there are certain clues related to medical history, physical examination and body composition evaluation that may suggest FPLD prior to confirmatory genetic analysis. Its treatment must be fundamentally oriented towards the control of the metabolic abnormalities. In this sense, metreleptin therapy, the newer classes of hypoglycaemic agents and other investigational drugs are showing promising results. This review aims to summarise the current knowledge of FPLD syndromes and to describe their clinical and molecular picture, diagnostic approaches and recent treatment modalities.