Search

Background: The number of known inherited metabolic diseases (IMDs) has been expanding, and the rate of diagnosis is improving with the development of innovative approaches including next generation sequencing (NGS). However, a substantial proportion of IMDs remain undetected by traditional diagnostic approaches. We aim to highlight the spectrum of IMDs diagnosed by the Undiagnosed Diseases Network (UDN) and to learn from the UDN diagnostic processes that were able to detect IMDs., Methods: We conducted a retrospective analysis of 757 UDN participants diagnosed from 2015 until 2023 using the cohort database, which were divided into a cohort with IMDs (n = 194; 27%) and a cohort whose phenotypes were not explained by an IMD (n = 563; 73%), based on the International Classification of Inherited Metabolic Disorders (ICIMD). Then, we divided the causes of the metabolic 194 diagnoses into seven groups that included all the ICIMD categories. We inspected which clinical and laboratory approaches contributed to a final UDN diagnosis. We also present a UDN case example from each group to highlight the diagnostic yields that resulted from combining newer diagnostic approaches in the UDN and illustrate potential pitfalls of current NGS methods., Results: These 194 cases of IMDs included examples from 21/25 (84%) of the ICIMD categories. Of the UDN subjects 164/194 (85%) were diagnosed with IMDs through NGS., Conclusion: The spectrum of IMDs detected in the UDN cohort is large and growing and appropriate use of newer multiple diagnostic approaches should further increase diagnosis of IMDs that are presently missed by the traditional laboratory screening methods., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests There are no conflicts of interest to declare., (© 2024. The Author(s).)

Objectives: Patients with rheumatoid arthritis (RA) commonly experience a high prevalence of multiple metabolic diseases (MD), leading to higher morbidity and premature mortality. Here, we aimed to investigate the pathogenesis of MD in RA patients (RA_MD) through an integrated multi-omics approach., Methods: Fecal and blood samples were collected from a total of 181 subjects in this study for multi-omics analyses, including 16S rRNA and internally transcribed spacer (ITS) gene sequencing, metabolomics, transcriptomics, proteomics and phosphoproteomics. Spearman's correlation and protein-protein interaction networks were used to assess the multi-omics data correlations. The Least Absolute Shrinkage and Selection Operator (LASSO) machine learning algorithm were used to identify disease-specific biomarkers for RA_MD diagnosis., Results: Our results found that RA_MD was associated with differential abundance of gut microbiota such as Turicibacter and Neocosmospora, metabolites including decreased unsaturated fatty acid, genes related to linoleic acid metabolism and arachidonic acid metabolism, as well as downregulation of proteins and phosphoproteins involved in cholesterol metabolism. Furthermore, a multi-omics classifier differentiated RA_MD from RA with high accuracy (AUC: 0.958). Compared to gouty arthritis and systemic lupus erythematosus, dysregulation of lipid metabolism showed disease-specificity in RA_MD., Conclusions: The integration of multi-omics data demonstrates that lipid metabolic pathways play a crucial role in RA_MD, providing the basis and direction for the prevention and early diagnosis of MD, as well as new insights to complement clinical treatment options., (© 2024. The Author(s).)

Aim: To analyze the relationship between metabolic disorders and obesity with hemodynamic parameters and the severity of the condition of patients with chronic thromboembolic pulmonary hypertension (CTEPH) based on the POLET register., Materials and Methods: The study included patients with CTEPH from the POLET register. Data from medical history, lipid profile, glycemia, uric acid level, weight, height, functional class (FC), distance in the 6-minute walk test (6MWT), echocardiography, and right heart catheterization were used for analysis., Results: The study included 84 patients 60±14 years old, including 45 men. The majority of patients had FC III - 51 (65%), which corresponded to 6MWT - 338±113 m. Nineteen (23%) people had experience in taking PAH specific therapy, 37 (46%) had cardiovascular comorbidity. In the general group, the body mass index (BMI) was 25.7±4.5 kg/m 2 , and normal glycemia, lipid profile, and uric acid levels were also determined. mPAP was 51±12 mmHg, RA area was 25.5 (20; 30) cm 2 . Correlations were identified between: RA area and the level of total cholesterol (r=0.60; p <0.01), triglycerides (r=-0.24; p <0.001), LDL cholesterol (r=0.75; p = 0.04), uric acid (r=0.75; p =0.03); total cholesterol and 6MWT (r=0.44; p =0.04). Analysis of metabolic disorders, FC and comorbidity revealed differences between FC III and IV groups in the level of HDL cholesterol ( p =0.02) and triglycerides ( p <0.01)., Conclusion: The POLET registry includes mainly older patients. Severe FC (87% - III and IV) may be a result of the older age and the presence of concomitant pathology in almost half of the patients. The discovered relationships between the area of RA and FC with lipid and purine metabolism were discovered for the first time, however, they correspond to the direction of the world scientific researches, are important due to the use of these indicators in the scale for calculating the risk of death in patients with PAH and require further development.

Background and Aim: LIVERSTAT is an artificial intelligence-based noninvasive test devised to screen for and provide risk stratification for metabolic dysfunction-associated fatty liver disease (MAFLD) by using simple blood biomarkers and anthropometric measurements. We aimed to study LIVERSTAT in patients with MAFLD and to explore its role for the diagnosis of advanced fibrosis., Methods: This is a retrospective study of data from MAFLD patients who underwent a liver biopsy. Patients with type 2 diabetes who underwent transient elastography and had liver stiffness measurement (LSM) < 5 kPa were included as patients with no fibrosis. Among these patients, controlled attenuation parameter <248 dB/m was considered as no steatosis. The LIVERSTAT results were generated based on a proprietary algorithm, blinded to the histological and LSM data., Results: The data for 350 patients were analyzed (mean age 53 years, 45% male, advanced fibrosis 22%). The sensitivity, specificity, positive predictive value, negative predictive value, and misclassification rate of LIVERSTAT to diagnose advanced fibrosis were 90%, 50%, 30%, 95%, and 42%, respectively. The corresponding rates for Fibrosis-4 score (FIB4) were 56%, 83%, 44%, 89%, and 22%, respectively. When LSM was used as a second test, the corresponding rates for LIVERSTAT were 60%, 97%, 76%, 94%, and 8%, respectively, while the corresponding rates for FIB4 were 38%, 99%, 83%, 89%, and 11%, respectively., Conclusion: LIVERSTAT had a higher negative predictive value compared with FIB4 and a lower misclassification rate compared with FIB4 when used in a two-step approach in combination with LSM for the diagnosis of advanced fibrosis., (© 2024 The Author(s). Journal of Gastroenterology and Hepatology published by Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.)

Competing Interests: Competing interests: None declared.

Macroglossia is an uncommon condition characterized by chronic, painless and abnormal enlargement of the tongue. A multitude of medical conditions can cause macroglossia. Major endocrine and metabolic disorders associated with macroglossia include genetic, congenital and acquired conditions, such as mucopolysaccharidoses; acquired and congenital hypothyroidism and myxedema; transient neonatal diabetes mellitus; acromegaly and amyloidosis. Macroglossia is often associated (~57-60%) with all types of mucopolysaccharidoses, particularly type I (Hurler syndrome) and type II (Hunter syndrome), being a prominent feature of the disorder. It may also occur in patients with acquired and congenital hypothyroidism and myxedema, being a common sign of congenital hypothyroidism with an approximate prevalence of 12-25% at the time of diagnosis. Macroglossia is a predominant oral finding in subjects with transient neonatal diabetes mellitus (~44%), acromegaly (54-69%) and amyloidosis (10-25%), particularly AL amyloidosis (20-40%) whereas is considered a hallmark of the disease. Secondary to macroglossia various disturbances may occur, such as difficulty in speech or eating, orthodontic anomalies or even more serious conditions including upper airway obstruction or obstructive sleep apnea. Until now, no comprehensive review has been conducted focusing on macroglossia in endocrine and metabolic disorders. The objective of this review is to summarize literature on the etiology and epidemiology of macroglossia in major endocrine and metabolic disorders. It highlights key aspects such as pathophysiology, clinical presentation, diagnostic evaluation, management and prognosis of macroglossia in the context of endocrine and metabolic disorders.

Delirium in critical ill patients is a complex and common neurological syndrome in the intensive care unit (ICU) that is caused by a range of structural or functional abnormalities. ICU Delirium is associated with reduced compliance, prolonged hospital stays, greater use or delayed withdrawal of sedatives, higher rates and durations of mechanical ventilation, and higher rates of mortality. The aetiology and pathogenesis of ICU delirium are unclear, and the lack of better prediction, prevention, and treatment measures leads to a non-standardized control of delirium. By searching the relevant literature, we aim in this narrative review to describe progress in the pathogenesis, predictive biomarkers, diagnosis, and treatment of ICU delirium.

Background: Neuregulin 4 (Nrg4) is a brown adipose tissue-derived adipokine that greatly affects systemic metabolism and improves metabolic derangements. Although abnormal circulating levels of Nrg4 are common in obesity, it remains elusive whether low or elevated levels of this batokine are associated with the onset of metabolic diseases., Aim: To assess Nrg4 levels and its role as a feasible biomarker to predict the severity of obesity, gestational diabetes mellitus (GDM), type 2 diabetes mellitus (T2DM), non-alcoholic fatty liver disease (NAFLD), and cardiovascular diseases (CVD)., Methods: A search for relevant studies was performed systematically using prominent search engines, including PubMed, Google Scholar, and Embase, by following PRISMA guidelines., Results: Ample clinical evidence reported low serum/plasma levels of Nrg4 in obesity and these were inversely proportional to the indices of metabolic syndrome, including body mass index, waist circumference, triglycerides, fasting plasma glucose, and homoeostatic model assessment for insulin resistance as well as high-sensitivity C-reactive protein. Low circulating Nrg4 levels may aid in the prediction of morbid obesity, and subsequent GDM, T2DM, NAFLD, and CVD., Conclusion: Current clinical evidence emphasizes that the circulating levels of Nrg4 are decreased in morbid obesity, and it also highlights that Nrg4 May serve as a potential prognostic biomarker for obesity-related metabolic diseases.

Detecting and quantifying amino acids is vital in biochemical analyses, especially for diagnosing metabolic disorders. L-proline, among these amino acids, holds significant relevance for various metabolic disorders in living organisms, particularly in humans. hyperprolinemia arises when ineffective breakdown of L-proline occurs due to enzyme deficiencies, leading to its accumulation in the body and underscoring the need for precise monitoring. To address this challenge, molecular imprinting offers a reliable single-step technique for detecting target molecules like proteins, peptides, amino acids, or ions with high selectivity. Moreover, nanoparticles, with significant surface area-to-volume ratios, enable high-level mass transfer and binding kinetics, making them ideal for nano-scale sensitive applications. In this study, 2-hydroxyethyl methacrylate-based molecularly imprinted nanoparticles were synthesized via mini-emulsion polymerization, combining the advantages of molecular imprinting technique and nanoparticles for the specific recognition of L-proline, and were well-characterized by Scanning Electron Microscopy, zeta-sizer particle size analysis, and Fourier Transform Infrared Spectroscopy. Based on zeta-sizer analysis, the estimated diameters of L-proline-imprinted and non-imprinted nanoparticles (Pro-MIPs and NIPs) were determined to be approximately 27.51 nm and 20.66 nm, respectively. The adsorption of L-proline onto nanoparticles from aqueous solutions was investigated in a batch system, and the maximum L-proline adsorption capacity was determined to be 26.58 mg/g for Pro-MIPs and 4.65 mg/g for and NIPs. The selectivity of Pro-MIPs was assessed using Liquid Chromatography-Tandem Mass Spectrometry, even in human serum and in the presence of competing molecules (L-histidine and L-phenylalanine). Additionally, Pro-MIPs maintained their adsorption capacity through up to 10 adsorption-desorption cycles without significant decrease., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The co-occurrence of multiple chronic metabolic diseases is highly prevalent, posing a huge health threat. Clarifying the metabolic associations between them, as well as identifying metabolites which allow discrimination between diseases, will provide new biological insights into their co-occurrence. Herein, we utilized targeted serum metabolomics and lipidomics covering over 700 metabolites to characterize metabolic alterations and associations related to seven chronic metabolic diseases (obesity, hypertension, hyperuricemia, hyperglycemia, hypercholesterolemia, hypertriglyceridemia, fatty liver) from 1626 participants. We identified 454 metabolites were shared among at least two chronic metabolic diseases, accounting for 73.3% of all 619 significant metabolite-disease associations. We found amino acids, lactic acid, 2-hydroxybutyric acid, triacylglycerols (TGs), and diacylglycerols (DGs) showed connectivity across multiple chronic metabolic diseases. Many carnitines were specifically associated with hyperuricemia. The hypercholesterolemia group showed obvious lipid metabolism disorder. Using logistic regression models, we further identified distinguished metabolites of seven chronic metabolic diseases, which exhibited satisfactory area under curve (AUC) values ranging from 0.848 to 1 in discovery and validation sets. Overall, quantitative metabolome and lipidome data sets revealed widespread and interconnected metabolic disorders among seven chronic metabolic diseases. The distinguished metabolites are useful for diagnosing chronic metabolic diseases and provide a reference value for further clinical intervention and management based on metabolomics strategy.

Competing Interests: Declaration of competing interest SAP has no competing interests. CSM reports grants through his institution from Merck, Massachusetts Life Sciences Center and Boehringer Ingelheim, he reports personal consulting fees and support through his institution from Ansh Inc., collaborative research support from LabCorp Inc., reports personal consulting fees from Nestle, Olympus, Genfit, Lumos, Novo Nordisk, Amgen, Corcept, Intercept, 89 Bio, Madrigal, Aligos, Esperion, Biodexa and Regeneron, reports educational activity meals through his institution or national conferences from Esperion, Merck, Boehringer Ingelheim and travel support and fees from UptoDate, TMIOA, Elsevier, and the Cardio Metabolic Health Conference. None is related to this manuscript.

Background and Aim: To identify individuals with metabolic dysfunction-associated steatohepatitis (MASH) or "at-risk" MASH among patients with metabolic dysfunction-associated steatotic liver disease (MASLD), three noninvasive models are available with satisfactory efficiency, which include magnetic resonance imaging [MRI]- AST (MAST), FibroScan-AST (FAST score), and magnetic resonance elastography [MRE] plus FIB-4 (MEFIB). We aimed to evaluate the most accurate approach for diagnosing MASH or "at-risk" MASH., Methods: We included 108 biopsy-proven MASLD patients who underwent simultaneous assessment of MRE, MRI proton density fat fraction (MRI-PDFF), and FibroScan scans. Compared with the histological diagnosis, we analyzed the AUC of each model and assessed the accuracy., Results: Our study cohort consisted of 64.8% of MASH and 25.9% of "at-risk" MASH. When analyzing the performance of each model for the diagnostic accuracy of MASH, we found that the AUC [95% CI] of MAST was comparable to FAST (0.803 [0.719-0.886] vs 0.799 [0.707-0.891], P = 0.930) and better than MEFIB (0.671 [0.571-0.772], P = 0.005). Similar findings were observed in the "at-risk" MASH patients. The AUCs [95% CI] for MAST, FAST, and MEFIB were 0.810 [0.719-0.900], 0.782 [0.689-0.874], and 0.729 [0.619-0.838], respectively. The models of MAST and FAST had comparable AUCs (P = 0.347), which were statistically significantly higher than that of MEFIB (P = 0.041). Additionally, the cutoffs for diagnosis of MASH were lower than "at-risk" MASH., Conclusion: MAST and FAST performed better than MEFIB in diagnosing "at-risk" MASH and MASH using lower cutoff values. Our findings provided evidence for selecting the most accurate noninvasive model to identify patients with MASH or at-risk MASH., (© 2024 The Authors. Journal of Gastroenterology and Hepatology published by Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.)

Objective: Globally, rates of metabolic disorders continue to climb, leading to significant disease morbidity and mortality. Individuals with mental illness are particularly prone to obesity, and some medications, such as antipsychotics, may increase the risk for metabolic disorders. The American Psychiatric Association and the American Diabetes Association recommend that patients taking antipsychotic medications receive regular screening for metabolic disorders. This study examined hospital and community factors associated with screening these patients for such disorders., Methods: The authors combined Centers for Medicare and Medicaid Services (CMS) hospital-level data on screening for metabolic disorders among patients with an antipsychotic prescription with community data, including urbanization classification, social vulnerability, and metabolic disease presence and risk factors. Data were merged at the county level and evaluated with a nonparametric multivariate regression model., Results: The CMS data set included 1,497 U.S. hospitals with data on screening for metabolic disorders among patients with an antipsychotic prescription. Screening rates varied by type of facility; acute care and critical access hospitals outperformed freestanding psychiatric facilities (p<0.001). No other variables examined in the multivariate model were associated with screening for metabolic disorders., Conclusions: Despite common resource limitations, screening for metabolic disorders may be driven more by logistics and less by time, finances, or a community's primary care network. Identifying the specific logistical challenges of freestanding psychiatric facilities could aid in the development of targeted interventions to improve the rates of screening for and treatment of not only metabolic disorders but also other common comorbid conditions., Competing Interests: The authors report no financial relationships with commercial interests.

Emerging in the 1800s under the label "fat in the liver" and later gaining prominence in the 1980 as non-alcoholic fatty liver disease (NAFLD), the disease predominantly attributed to metabolic dysfunction presents a formidable health issue marked by substantial morbidity and mortality. It was 2020 when a change of one letter "NAFLD" to metabolic dysfunction-associated fatty liver disease "MAFLD" linked with the change in the definition and diagnostic criteria began a new controversy around the globe. Metabolic dysfunction-associated fatty liver disease (MAFLD) criteria represent a substantial departure from previous diagnostic measures of NAFLD, and provide the first set of positive criteria for diagnosis of the disease in adults and children that emphasise the key attribute of metabolic dysfunction in the pathogenesis, and acknowledges that the disease is a continuum across the life span. In 2023, an adapted version of the diagnostic criteria of MAFLD was proposed to define a slightly modified term; metabolic dysfunction-associated steatotic liver disease (MASLD). The MASLD criteria did not provide any conceptual advantage, and emerging evidence suggests that it actually performs worse than the MAFLD criteria. This raises the intriguing question of why MASLD was unable to take advantage of being second? In this review, we will explore the possible reasons for this unique case and highlight the current evidence supporting the use of MAFLD instead of MASLD in defining metabolic dysfunction-associated fatty liver diseases.

Physiological determinants of drug dosing (PDODD) are a promising approach for precision dosing. This study investigates the alterations of PDODD in diseases and evaluates a variational autoencoder (VAE) artificial intelligence model for PDODD. The PDODD panel contained 20 biomarkers, and 13 renal, hepatic, diabetes, and cardiac disease status variables. Demographic characteristics, anthropometric measurements (body weight, body surface area, waist circumference), blood (plasma volume, albumin), renal (creatinine, glomerular filtration rate, urine flow, and urine albumin to creatinine ratio), and hepatic (R-value, hepatic steatosis index, drug-induced liver injury index), blood cell (systemic inflammation index, red cell, lymphocyte, neutrophils, and platelet counts) biomarkers, and medical questionnaire responses from the National Health and Nutrition Examination Survey (NHANES) were included. The tabular VAE (TVAE) generative model was implemented with the Synthetic Data Vault Python library. The joint distributions of the generated data vs. test data were compared using graphical univariate, bivariate, and multidimensional projection methods and distribution proximity measures. The PDODD biomarkers related to disease progression were altered as expected in renal, hepatic, diabetes, and cardiac diseases. The continuous PDODD panel variables generated by the TVAE satisfactorily approximated the distribution in the test data. The TVAE-generated distributions of some discrete variables deviated from the test data distribution. The age distribution of TVAE-generated continuous variables was similar to the test data. The TVAE algorithm demonstrated potential as an AI model for continuous PDODD and could be useful for generating virtual populations for clinical trial simulations., (© 2024 The Author(s). Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

N-glycans play important roles in a variety of biological processes. In recent years, analytical technologies with high resolution and sensitivity have advanced exponentially, enabling analysts to investigate N-glycomic changes in different states. Specific glycan and glycosylation signatures have been identified in multiple diseases, including cancer, autoimmune diseases, nervous system disorders, and metabolic and cardiovascular diseases. These glycans demonstrate comparable or superior indicating capability in disease diagnosis and prognosis over routine biomarkers. Moreover, synchronous glycan alterations concurrent with disease initiation and progression provide novel insights into pathogenetic mechanisms and potential treatment targets. This review elucidates the biological significance of N-glycans, compares the existing glycomic technologies, and delineates the clinical performance of N-glycans across a range of diseases.

Aim: To compare antibody responses after vaccinations between patients with rheumatoid arthritis (RA) and patients with metabolic disorders (MD). The study places special emphasis on understanding how common diseases affect antibody responses in individuals with RA within real-world settings., Methods: The participants were 117 patients with RA (66 with RA only and 51 with RA and MD) and 37 patients with MD who received both the primary series of vaccinations and a booster. Antibody titers were compared after the primary series of vaccinations and a booster, and factors influencing the antibody response were assessed., Results: Following the primary series of vaccinations, a significant reduction in antibody titers was observed in patients with longer days between vaccination and antibody measurement, the use of IL-6 inhibitors, selective T cell co-stimulation modulators, and methotrexate. Comorbid MD did not exhibit significant influences on antibody response in RA. Notably, the presence of RA itself was not significant in multivariate linear regression analysis. After the administration of the booster, however, day between vaccination and antibody measurement, the use of IL-6 inhibitor, and methotrexate no longer remained significant. Only the use of selective T cell co-stimulation modulators retained its significance., Conclusions: MD did not exhibit a significant impact on antibody responses in RA patients. The reduced antibody response following the primary series in RA patients appeared to be attributed more to specific RA medications rather than to the disease itself. Booster vaccines are vital in restoring the antibody response in RA., (© 2024 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.)

Objectives: Metabolic disease in children is increasing worldwide and predisposes a wide array of chronic comorbid conditions with severe impacts on quality of life. Tools for early detection are needed to promptly intervene to prevent or slow the development of these long-term complications., Materials and Methods: No clinically available tools are currently in widespread use that can predict the onset of metabolic diseases in pediatric patients. Here, we use interpretable deep learning, leveraging longitudinal clinical measurements, demographical data, and diagnosis codes from electronic health record data from a large integrated health system to predict the onset of prediabetes, type 2 diabetes (T2D), and metabolic syndrome in pediatric cohorts., Results: The cohort included 49 517 children with overweight or obesity aged 2-18 (54.9% male, 73% Caucasian), with a median follow-up time of 7.5 years and mean body mass index (BMI) percentile of 88.6%. Our model demonstrated area under receiver operating characteristic curve (AUC) accuracies up to 0.87, 0.79, and 0.79 for predicting T2D, metabolic syndrome, and prediabetes, respectively. Whereas most risk calculators use only recently available data, incorporating longitudinal data improved AUCs by 13.04%, 11.48%, and 11.67% for T2D, syndrome, and prediabetes, respectively, versus models using the most recent BMI (P < 2.2 × 10-16)., Discussion: Despite most risk calculators using only the most recent data, incorporating longitudinal data improved the model accuracies because utilizing trajectories provides a more comprehensive characterization of the patient's health history. Our interpretable model indicated that BMI trajectories were consistently identified as one of the most influential features for prediction, highlighting the advantages of incorporating longitudinal data when available., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: Compare the differences between normal newborns and high-risk children with inherited metabolic diseases. The disease profile includes amino acidemias, fatty acid oxidation disorders, and organic acidemias., Methods: Data was collected on newborns and children from high-risk populations in Shanghai from December 2010 to December 2020., Results: 232,561 newborns were screened for disorders of organic, amino acid, and fatty acid metabolism. The initial positive rate was 0.66 % (1,526/232,561) and the positive recall rate was 77.85 %. The positive predictive value is 4.71 %. Among them, 56 cases were diagnosed as metabolic abnormalities. The total incidence rate is 1:4153. Hyperphenylalaninemia and short-chain acyl-CoA dehydrogenase are the most common diseases in newborns. In addition, in 56 children, 39 (69.42 %) were diagnosed by genetic sequencing. Some hotspot mutations in 14 IEMs have been observed, including PAH gene c.728G > A, c.611A > G, and ACADS gene c. 1031A > G, c.164C > T. A total of 49,860 symptomatic patients were screened, of which 185 were diagnosed with IEM, with a detection rate of 0.37 %. The most commonly diagnosed diseases in high-risk infants aremethylmalonic acidemia and hyperphenylalaninemia., Conclusion: There are more clinical cases of congenital metabolic errors diagnosed by tandem mass spectrometry than newborn screening. The spectrum of diseases, prevalence, and genetic characteristics of normal newborns and high-risk children are quite different., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Associations between dyslipidemia and metabolic dysfunction-associated steatotic liver disease (MASLD) have been reported. Previous studies have shown that the triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio may be a surrogate marker of MASLD, assessed by liver ultrasound. However, no studies have evaluated the utility of this ratio according to biopsy-proven MASLD and its stages. Therefore, our aim was to evaluate if the TG/HDL-C ratio allows for the identification of biopsy-proven MASLD in patients with obesity. We conducted a case-control study in 153 patients with obesity who underwent metabolic surgery and had a concomitant liver biopsy. Fifty-three patients were classified as no MASLD, 45 patients as metabolic dysfunction-associated steatotic liver-MASL, and 55 patients as metabolic dysfunction-associated steatohepatitis-MASH. A receiver operating characteristic (ROC) analysis was performed to assess the accuracy of the TG/HDL-C ratio to detect MASLD. We also compared the area under the curve (AUC) of the TG/HDL-C ratio, serum TG, and HDL-C. A higher TG/HDL-C ratio was observed among patients with MASLD, compared with patients without MASLD. No differences in the TG/HDL-C ratio were found between participants with MASL and MASH. The greatest AUC was observed for the TG/HDL-C ratio (AUC 0.747, p < 0.001) with a cut-off point of 3.7 for detecting MASLD (sensitivity = 70%; specificity = 74.5%). However, no statistically significant differences between the AUC of the TG/HDL-C ratio and TG or HDL-C were observed to detect MASLD. In conclusion, although an elevated TG/HDL-C ratio can be found in patients with MASLD, this marker did not improve the detection of MASLD in our study population, compared with either serum TG or HDL-C.

Objective: To explore the clinical features of fatty liver disease (FLD) from non-alcoholic fatty liver disease (NAFLD) to metabolic dysfunction-associated fatty liver disease (MASLD), so as to elucidate its clinical application value under three renames. Methods: Patients who were hospitalized in the Department of Hepatology, Hospital of Traditional Chinese Medicine Affiliated to Xinjiang Medical University, from January 2020 to September 2023 and met the diagnosis of NAFLD, metabolic-associated fatty liver disease (MAFLD), or MASLD were selected as the research subjects. The clinical indicators differences among the three groups of patients were compared, mainly including general information (age, gender, body mass index, past history, etc.), serological indicators (liver and kidney function, blood lipids, blood sugar, coagulation function, etc.), non-invasive liver fibrosis indicators, fat attenuation parameters, etc. Measurement data were analyzed using ANOVA and the rank sum test, while count data were analyzed using the χ (2) test. Results: NAFLD, MAFLD, and MASLD prevalence rates among 536 cases were 64.0%, 93.7%, and 100%, respectively. 318 cases (59.3%) met the three fatty liver names at the same time among them. Male population proportions in NAFLD, MAFLD, and MASLD were 30.9%, 55.8%, and 53.9%, respectively. The alcohol consumption history proportion was 0, 36.7%, and 36.0%, respectively. The smoking history proportion was 7.0%, 31.9%, and 30.6%, respectively. The body mass index was (27.66 ± 3.97), (28.33 ± 3.63), and (27.90 ± 3.89) kg/m(2), respectively. The γ-glutamyltransferase levels were 26.6 (18.0, 47.0) U/L, 31.0 (20.0, 53.0) U/L, and 30.8 (19.8, 30.8) U/L, respectively. The high-density lipoprotein cholesterol levels were 1.07 (0.90, 1.23) mmol/L, 1.02 (0.86, 1.19) mmol/L, and 1.03 (0.87,1.21) mmol/L, respectively. Sequentially measured uric acid was (322.98 ± 84.51) μmol/L, (346.57 ± 89.49) μmol/L, and (344.89 ±89.67) μmol/L, respectively. Sequentially measured creatinine was 69.6 (62.9, 79.0) μmol/L, 73.0 (65.0, 83.5) μmol/L, and 73.0 (65.0, 83.0) μmol/L, respectively. The sequential analysis of obesity proportion was 74.3%, 81.7%, and 76.5%, respectively, with statistically significant differences ( P <0.05). Conclusion: Compared with the NAFLD population, the MAFLD and MASLD populations were predominantly male, obese, and had a history of smoking and drinking. The levels of γ-glutamyltransferase, uric acid, and creatinine were slightly higher, while the levels of high-density lipoprotein cholesterol were lower. MASLD appeared in NAFLD and MAFLD on the basis of inheritance and progression, emphasizing once again the important role of metabolic factors in a fatty liver.

Background: We aimed to evaluate the diagnostic capabilities of Chinese laboratories for inherited metabolic disorders (IMDs) using gas chromatography-mass spectrometry (GC-MS) on urine samples. Meanwhile, based on the result of the pilot external quality assessment (EQA) scheme, we hope to establish a standardized and reliable procedure for future EQA practice., Methods: We recruited laboratories that participated in the EQA of quantitative analysis of urinary organic acids with GC-MS before joining the surveys. In each survey, a set of five real urine samples was distributed to each participant. The participants should analyze the sample by GC-MS and report the "analytical result", "the most likely diagnosis", and "recommendation for further tests" to the NCCL before the deadline., Results: A total of 21 laboratories participated in the scheme. The pass rates were 94.4% in 2020 and 89.5% in 2021. For all eight IMDs tested, the analytical proficiency rates ranged from 84.7% - 100%, and the interpretational performance rate ranged from 88.2% - 97.0%. The performance on hyperphenylalaninemia (HPA), 3-methylcrotonyl-CoA carboxylase deficiency (MCCD), and ethylmalonic encephalopathy (EE) samples were not satisfactory., Conclusions: In general, the participants of this pilot EQA scheme are equipped with the basic capability for qualitative organic acid analysis and interpretation of the results. Limited by the small size of laboratories and samples involved, this activity could not fully reflect the state of clinical practice of Chinese laboratories. NCCL will improve the EQA scheme and implement more EQA activities in the future.

Background: Newborn screening (NBS), such as tandem mass spectrometry (MS/MS), may yield false positive/negative results. Next-generation sequencing (NGS) has the potential to provide increased data output, efficiencies, and applications. This study aimed to analyze the types and distribution of pathogenic gene mutations in newborns in Huzhou, Zhejiang province, China and explore the applicability of NGS and MS/MS in NBS., Methods: Blood spot samples from 1263 newborns were collected. NGS was employed to screen for pathogenic variants in 542 disease-causing genes, and detected variants were validated using Sanger sequencing. Simultaneously, 26 inherited metabolic diseases (IMD) were screened using MS/MS. Positive or suspicious samples identified through MS/MS were cross-referenced with the results of NGS., Results: Among all newborns, 328 had no gene mutations detected. NGS revealed at least one gene mutation in 935 newborns, with a mutation rate of 74.0%. The top 5 genes were FLG, GJB2, UGT1A1, USH2A, and DUOX2. According to American College of Medical Genetics guidelines, gene mutations in 260 cases were classified as pathogenic or likely pathogenic mutation, with a positive rate of 20.6%. The top 5 genes were UGT1A1, FLG, GJB2, MEFV, and G6PD. MS/MS identified 18 positive or suspicious samples for IMD and 1245 negative samples. Verification of these cases by NGS results showed no pathogenic mutations, resulting in a false positive rate of 1.4% (18/1263)., Conclusion: NBS using NGS technology broadened the range of diseases screened, and enhanced the accuracy of diagnoses in comparison to MS/MS for screening IMD. Combining NGS and biochemical screening would improve the efficiency of current NBS., (© 2024. The Author(s).)

Purpose: Expanded carrier screening (ECS) gene panels have several limitations, including variable content, current knowledge of disease-causing variants, and differing reporting policies. This study evaluated if the disease-associated variants identified in affected neonates who screened positive by California newborn screening (NBS) for an inherited metabolic disorder (IMD) by tandem mass spectrometry (MS/MS) would likely be reported by ECS gene panels., Methods: Retrospective review of neonates referred by the California Department of Public Health for a positive NBS by multianalyte MS/MS from January 1, 2020 through June 30, 2021., Results: One hundred thirty-six neonates screened positive for ≥1 NBS MS/MS indication. Nineteen neonates (14%) were ultimately diagnosed with an IMD, all of whom had abnormal biochemical testing. Eighteen of the 19 underwent molecular testing; 10 (56%) neonates had ≥1 variants of uncertain significance, 9 of whom were of non-White ancestry. ECS panels would have been negative for 56% (20/36) of parents with an affected neonate, 85% (17/20) of whom were of non-White ancestry., Conclusion: The number of variants of uncertain significance identified in this cohort highlights the need for more diversified variant databases. Due in part to the lack of diversity in currently sequenced populations, genomic sequencing cannot replace biochemical testing for the diagnosis of an IMD., Competing Interests: Conflict of Interest The authors declare no conflicts of interest., (Copyright © 2023 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Introduction and Objectives: In a recent development, a cohort of hepatologists has proposed altering the nomenclature of non-alcoholic fatty liver disease (NAFLD) to metabolic-associated steatotic liver disease (MASLD), accompanied by modified diagnostic criteria. Our objective was to investigate the effect of the revised definition on identifying significant hepatic fibrosis., Patients and Methods: From Jan 2009 to Dec 2022, a total of 428 patients with biopsy-proven hepatic steatosis were diagnosed with NAFLD. Patients were classified into subgroups according to MASLD and Cryptogenic-SLD diagnostic criteria. The clinical pathological features were compared between these two groups. Risk factors for significant fibrosis were analysed in the MASLD group. In total, 329 (76.9 %) patients were diagnosed with MASLD, and 99 (23.1 %) were diagnosed with Cryptogenic-SLD., Results: Those with MASLD exhibited a higher degree of disease severity regarding histology features than Cryptogenic-SLD. The prevalence of significant fibrosis increased from 13 % to 26.6 % for one and two criteria present to 42.5 % for meeting three or more cardiometabolic risk factor (CMRF) criteria (p = 0.001). ALB (aOR:0.94,95 %CI:0.90-1.00; p = 0.030), lower levels of PLT (aOR:0.99, 95 %CI:0.99-1.00; p < 0.001), and more metabolic comorbidities (aOR:1.42,95 %CI:1.14-1.78; p = 0.012) were independent risk factors of significant fibrosis in MASLD., Conclusions: The new nomenclature of MASLD and SLD is more applicable to identifying significant fibrosis than NAFLD. Patients with three or more cardiometabolic risk factors are at higher risk of fibrosis., Competing Interests: Declaration of interests None., (Copyright © 2023 Fundación Clínica Médica Sur, A.C. Published by Elsevier España, S.L.U. All rights reserved.)

Receiving information in the case of a positive or false-positive expanded newborn screening (ENBS) result for metabolic diseases is a stressful event. The availability of psychological support to families is crucial across the different communication steps and is recommended by different guidelines and position papers. However, more information is needed about the availability of psychological resources in the ENBS process. This national survey aimed to provide an overview of the availability of psychological resources for parents who received communication of positivity at the ENBS in the 23 Italian centers and how the support is provided to parents. An online survey was sent to the Heads of the ENBS centers asking about the availability of a clinical psychologist, their involvement in the ENBS process, and an estimation of parents receiving psychological support. More than 60% of the centers report having a clinical psychologist in the ENBS team; however, in more than 50% of cases, the psychologist does not participate in the consultation with parents (nor for the first consultation post-positivity or at confirmation of diagnosis). Furthermore, nearly 60% of the centers reported the experience of parental rejection of psychological sessions.  Conclusion: There is a need for harmonization among the Italian ENBS centers concerning the availability of psychological resources and how these resources are provided to families. Parents' needs remained only partially fulfilled. What is Known: • Receiving communication of positivity at the ENBS can be highly stressful for parents and requires adequate psychological support. • The guidelines recommend psychological support for parents during the ENBS process. What is New: • Only 14/23 (60.9%) of Italian ENBS centers have a clinical psychologist within the team. • In half of the consultations with parents receiving communication of positivity, the clinical psychologist is never involved., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: It is well established that microvascular structures are affected in obese people with metabolic disease. We aimed to evaluate the effect on microvascular structures by examining macular and peripapillary vessel density with optical coherence tomography angiography after bariatric surgery in obese individuals without metabolic disease., Methods: This prospective study included 96 eyes of 48 obese patients. Body mass index (BMI), macular vessel density in the superficial, intermediate, and deep capillary plexus, and peripapillary vessel density were measured before and 6 months after bariatric surgery., Results: BMI decreased significantly to 43.75 ± 4.4 kg/m2 postoperatively compared to 55.31 ± 5.1 kg/m2 preoperatively (p &lt; 0.05). A significant increase was observed in macular vessel density in the deep capillary plexus postoperatively (p &lt; 0.01). However, no significant postoperative increase occurred in macular vascular density in the superficial and intermediate capillary plexus (p &gt; 0.05). Moreover, there was no change in peripapillary vascular density (p &gt; 0.05). Postoperative thickening of the foveal, parafoveal, and perifoveal retinal layers was significant (p &lt; 0.001). No significant correlation was detected between BMI change and macular and peripapillary vessel density changes (p &gt; 0.05)., Conclusion: An increase in macular vascular density, particularly in the deep capillary plexus, and retinal layer thickness has been observed following bariatric surgery performed on obese individuals without metabolic disease. This increase may indicate that microvascular structures are affected even in the absence of metabolic disease and that microperfusion improves with surgery., (© 2024 The Author(s). Published by S. Karger AG, Basel.)

Like many physical disorders, the clinical signs associated with metabolic diseases affecting thyroid, adrenal, and pancreatic function are reflective of nonspecific changes in behavior. Additionally, patients who have underlying disorders associated with fear, anxiety, stress, conflict, and/or panic may be under treatment with medications that alter basal thyroid, glucose, and cortisol levels. Through reinforcement and punishment of behaviors associated with clinical signs caused by organic or iatrogenic endocrine disease, behaviors can be perpetuated and become persistent patterns. Screening all patients presenting with a primary behavior complaint or those with behavioral clinical signs of endocrine diseases is essential. Alleviating stress immediately while working up or treating metabolic disease reduces suffering and may stave off the adoption of behavior patterns more permanently., Competing Interests: Disclosure Dr L. Radosta currently serves on advisory boards for Purina, Zoundz, and Ellevet., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Motivation: Gut dysbiosis is closely associated with obesity and related metabolic diseases including type 2 diabetes (T2D) and nonalcoholic fatty liver disease (NAFLD). The gut microbial features and biomarkers have been increasingly investigated in many studies, which require further validation due to the limited sample size and various confounding factors that may affect microbial compositions in a single study. So far, it lacks a comprehensive bioinformatics pipeline providing automated statistical analysis and integrating multiple independent studies for cross-validation simultaneously., Results: OBMeta aims to streamline the standard metagenomics data analysis from diversity analysis, comparative analysis, and functional analysis to co-abundance network analysis. In addition, a curated database has been established with a total of 90 public research projects, covering three different phenotypes (Obesity, T2D, and NAFLD) and more than five different intervention strategies (exercise, diet, probiotics, medication, and surgery). With OBMeta, users can not only analyze their research projects but also search and match public datasets for cross-validation. Moreover, OBMeta provides cross-phenotype and cross-intervention-based advanced validation that maximally supports preliminary findings from an individual study. To summarize, OBMeta is a comprehensive web server to analyze and validate gut microbial features and biomarkers for obesity-associated metabolic diseases., Availability and Implementation: OBMeta is freely available at: http://obmeta.met-bioinformatics.cn/., (© The Author(s) 2023. Published by Oxford University Press.)

Kidney disease is a global health burden with high morbidity and mortality. Causes of kidney disease are numerous, extending from common disease groups like diabetes and arterial hypertension to rare conditions including inherited metabolic diseases (IMDs). Given its unique anatomy and function, the kidney is a target organ in about 10% of known IMDs, emphasizing the relevant contribution of IMDs to kidney disease. The pattern of injury affects all segments of the nephron including glomerular disease, proximal and distal tubular damage, kidney cyst formation, built-up of nephrocalcinosis and stones as well as severe malformations. We revised and updated the list of known metabolic etiologies associated with kidney involvement and found 190 relevant IMDs. This represents the 14th of a series of educational articles providing a comprehensive and revised list of metabolic differential diagnoses according to system involvement., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Newborn screening (NBS) is a highly successful secondary prevention program with the goal of preventing severe sequelae of congenital, mostly genetic, diseases by identifying them as early as possible, ideally in the pre-symptomatic period. Studies to date have shown the important achievements of NBS programs but also reveal a number of relevant weaknesses. These include the often incompletely understood natural history and phenotypic diversity of rare diseases as well as the inadequate ability to accurately predict individual disease severity at an early stage and thus the uncertainties in case definition, risk stratification, and treatment indication.In light of the rapid developments in high-throughput genetic technologies and the associated opportunities for substantial future expansion of NBS programs, it seems overdue to make structured long-term follow-up and the subsequent evaluation of the long-term health benefits mandatory for individuals with rare diseases identified through NBS. This article explains the importance of long-term follow-up for the evaluation and continuous optimization of the screening. Long-term clinical outcomes of people with inherited metabolic diseases identified by NBS are presented as examples., (© 2023. The Author(s).)

Background: The process of receiving a communication of positivity for metabolic diseases at expanded newborn screening (ENBS) is extremely articulated, involves a variety of actors (parents, maternal and child departments, clinical centres and laboratories) and is open to a variety of outcomes from false positive to true positive cases. Receiving communication of positivity can be highly stressful for parents and requires an adequate communication process to give clear and reliable information without causing excessive worry. This qualitative study describes the parents' experience of receiving a communication of positivity to metabolic diseases at ENBS, and their assessment of the quality of the communication process and steps, with the main aim to identify the process' strengths and weaknesses and to advance tailored recommendations to improve the communication process., Method: Fourteen in-depth, semi-structured phone interviews were conducted with parents whose children resulted positive to the ENBS. As part of the ENBS communication process, parents received a first phone call communication of positivity and a second in-person communication at metabolic clinical centres (MCC). The framework analysis method was used to organize the data and identify emerging themes., Results: Parents were largely dissatisfied with the quality and depth of the information received and with the way the healthcare staff delivered the first communication phone call, which failed to create a caring, empathic and safe setting. Many parents tried to reduce the uncertainty by searching online information or consulting with other providers. Nevertheless, the majority of parents described the in-person visit at MCC as clear, welcoming and reassuring., Conclusion: More efforts are needed to improve the quality of the communication process of the ENBS. Guidelines, recommendations and standard scripts to communicate positivity are needed along with programmes and educational resources to train tailored communication skills., (© 2023 The Authors. Child: Care, Health and Development published by John Wiley & Sons Ltd.)

Background: The first clinical manifestations of inherited metabolic diseases occur in the neonatal period in up to half of cases, often with nonspecific symptoms, making their recognition challenging. This study aimed to characterise inherited metabolic disease cases with neonatal presentation requiring admission to the paediatric intensive care unit in a Portuguese reference centre for inherited metabolic diseases., Material and Methods: An observational study with retrospective data collection was performed, including all newborns with an inherited metabolic disease admitted to the pediatric intensive care unit between June 2011 and June 2022. Three 'pathophysiological' groups were defined: cases due to small molecules, energy deficiency and complex molecules., Results: Twenty newborns, with a median age at admission of 7.5 days, were included. Thirteen (65%) were female, sixteen (80%) had a small molecule disorder, and four (20%) had diseases of energy defects. Neurological manifestations were the most common, with most newborns presenting symptomatically in the first week of life. There was no difference between the groups in neurological, cardiac, and hepatic involvement and shock at presentation. A symptom-free interval was more frequent in patients with small molecule disorders than the others (p=0.01). The main metabolic changes found were altered plasma amino acids (n=13) and organic aciduria (n=10), creatine kinase elevation (n=13), hyperlactatemia (n=12), metabolic acidosis with increased anion gap (n=8) and hyperammonaemia (n=7). Newborn screening of metabolites helped make a diagnosis in 60% of cases. Five newborns died due to multiorgan failure (n=3) or refractory cardiogenic shock (n=1), and in one, therapeutic efforts were limited due to an adverse neurological prognosis., Conclusion: Although the symptoms and signs are often nonspecific, we should suspect inherited metabolic disease when a newborn presents with neurological symptoms after a symptom-free period, however short it might be. Newborns with suspected inherited metabolic disease should be evaluated with simple biochemical tests, and newborn screening should be urgently expanded to start specific treatment earlier, reducing mortality and morbidity., (© 2023 Catarina Teixeira et al., published by Sciendo.)

Objectives: The childhood mortality rate for IMDs is approximately 25 % in populations with no expanded newborn screening program. Although the factors that increase mortality risk are known, an index predicting long-term survival has yet to be established., Methods: Two hundred sixty patients who were hospitalized during the first month of their life were screened, and 94 patients diagnosed with IMDs were included in the study. Clinical and laboratory data were assessed to identify any independent prognostic factors for overall survival., Results: Among the 38 patients with IMDs in the exitus group, the presence of dysmorphism, extremity abnormalities, respiratory distress, cyanosis, elevated transaminases, elevated INR, hypoglycemia, hypoalbuminemia, metabolic acidosis, electrolyte imbalance and anemia were associated with poorer survival. Elevated INR (Hazard Ratio [HR]: 0.17, 95 % CI: 0.03-0.87, p=0.034), hypoglycemia (HR: 0.48, 95 % CI: 0.25-0.91, p=0.026) and hypoalbuminemia (HR: 0.09, 95 % CI: 0.03-0.26, p<0.001) were the independent prognostic factors for survival after adjusting for confounding factors. For the prediction of survival, INR, glucose, and albumin were used to structure a novel index (IGAm = INR-Glucose-Albumin metabolic index). The median survival was shorter in the IGAm-high group (2 or 3 points) than in the IGAm-low group (p<0.001). Harrell's c-index was 0.73 for the IGAm index., Conclusions: The devised novel IGAm index can predict long-term survival in patients with IMDs, with a high IGAm index being associated with higher mortality in patients with IMDs., (© 2023 Walter de Gruyter GmbH, Berlin/Boston.)

Background: The standardization of quantification data is critical for ensuring the reliability and measurement traceability in the screening of neonatal inherited metabolic disorders. However, the availability of national certified reference materials is limited in China., Methods: In this study, we developed a series of dried blood spot (DBS) reference materials containing 9 amino acids (AA) and 10 acylcarnitines (AC) for neonatal screening. Four levels of the reference materials were measured with tandem mass spectrometry (MS/MS) by seven laboratories using different commercial In Vitro Diagnostic Device (IVD) kits. Then, 100 clinical samples were measured using both derivatization and non-derivatization methods by the same laboratory., Results: We found high homogeneity and stability at all levels of the reference materials, with the coefficient of variation (CV) of the analytes less than 15%. These reference materials can be used to assess the testing capabilities of different laboratories. Our test also revealed that the correction factors (CF) calculated by the reference materials, along with clinical samples, could increase the consistency for different kits., Conclusion: The DBS reference materials proposed in this study provide reliability for the harmonization in multi-center analysis for the screening of neonatal inherited metabolic disorders. And applying our correction method for the screening could improve the data consistency of the DBS samples prepared by different methods., (© 2023 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC.)

Background Menstrual cycle irregularities are associated with cardiovascular and cardiometabolic disease. We tested associations between age at menarche and cycle irregularity in adolescence and cardiometabolic health in early adulthood in a subsample from the Pittsburgh Girls Study. Methods and Results Data from annual interviews were used to assess age at menarche and cycle irregularity (ie, greater or less than every 27-29 days) at age 15 years. At ages 22 to 25 years, cardiometabolic health was measured in a subsample of the Pittsburgh Girls Study (n=352; 68.2% Black), including blood pressure, waist circumference, and fasting serum insulin, glucose, and lipids. T tests were used for continuous data and odds ratios for dichotomous data to compare differences in cardiometabolic health as a function of onset and regularity of menses. Early menarche (ie, before age 11 years; n=52) was associated with waist circumference ( P =0.043). Participants reporting irregular cycles (n=50) in adolescence had significantly higher levels of insulin, glucose, and triglycerides, and higher systolic and diastolic blood pressure ( P values range from 0.035 to 0.005) and were more likely to have clinical indicators of cardiometabolic predisease in early adulthood compared with women who reported regular cycles (odds ratios ranged from 1.89 to 2.56). Conclusions Increasing rates and earlier onset of cardiovascular and metabolic disease among women, especially among Black women, highlights the need for identifying early and reliable risk indices. Menstrual cycle irregularity may serve this purpose and help elucidate the role of women's reproductive health in protecting and conferring risk for later cardiovascular and cardiometabolic diseases.

Objective: To retrospectively analyze the screening results for genetic metabolic diseases among newborns from Changsha in order to determine the prevalence of single diseases and their mutational spectrum., Methods: 352 449 neonates born from January 2016 to December 2021 in Changsha were subjected to tandem mass spectrometry. Suspected cases were further analyzed by biochemical and genetic testing., Results: Among the 352 449 newborns, 6 170 were positive for the screening, which yielded a positive rate of 1.75%. 5 437 cases were recalled, and 92 were confirmed, with the overall prevalence being 1∶3 831 and positive predictive value of 1.69%. Eighteen genetic metabolic diseases were detected among the 92 children, including 33 amino acid metabolic disorders, among which 20 were phenylalanine hydroxylase deficiency (60.60%). 17 cases had organic acid metabolic disorders, among which 4 were 2-methyl-dehydrogenase deficiency (23.50%). 42 had fatty acid metabolic disorders, among which 27 (64.30%) were primary carnitine deficiency and 12 were short-chain acyl-CoA dehydrogenase deficiency (28.60%). In total 90 genetic variants were identified, with the most common ones including c.51C>G, c.1400C>G, c.760C>T, c.1031A>G and c.1165A>G., Conclusion: The common neonatal genetic metabolic diseases in Changsha include primary carnitine deficiency, phenylalanine hydroxylase deficiency and short-chain acyl-CoA dehydrogenase deficiency. The preliminary delineation of mutational spectrum for genetic metabolic diseases in Changsha can facilitate early diagnosis and intervention, so as to improve the quality of newborn population.

Background: Healthcare professionals play a key role in the diagnosis, treatment, and follow-up of inborn metabolic diseases. However, the level of inborn metabolic disease knowledge of prospective healthcare professional students in our country has not yet been determined. Therefore, this study aimed to evaluate the level of knowledge of healthcare professional candidate students about inborn metabolic diseases., Methods: The knowledge levels of 761 students enrolled in the Department of Nutrition and Dietetics, Child Development, Midwifery, Occupational Therapy, Audiology, Health Management and Social Work at Gülhane Faculty of Health Sciences, Health Sciences University, were evaluated through a questionnaire using a face-to-face interview technique. Correct answers to the questions measuring the level of knowledge were scored as "1", and incorrect answers were scored as "0"., Results: The mean knowledge-level score of the individuals was 14.23 ± 4.56. A total of 56.0% of individuals had heard about inborn metabolic diseases before, 37.8% had heard of rare disease organizations/platforms before, and 16.8% had encountered an awareness campaign about inborn metabolic diseases. The level of exposure to awareness-raising campaigns, department of education, and grade level were shown to be factors affecting knowledge levels., Conclusion: It is necessary to improve the awareness and knowledge levels of health professional candidates involved in the treatment of inborn metabolic diseases. Education curricula in health sciences faculties should be evaluated with this aspect., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Inherited metabolic disorders (IMDs) usually occurs at young age and hence it severely threatening the health and life of young people. While so far there lacks a comprehensive study which can reveals China's nationwide landscape of IMDs. This study aimed to evaluate IMDs incidence and regional distributions in China at a national and province level to guide clinicians and policy makers., Methods: The retrospective study conducted from January 2012 to March 2021, we analyzed and characterized 372255 cases' clinical test information and diagnostic data from KingMed Diagnostics Laboratory. The samples were from 32 provincial regions of China, the urine organic acids were detected by gas chromatography-mass spectrometry (GC-MS), amino acids and acylcarnitines in dried blood spots were detected by liquid chromatography-tandem mass spectrometry (LC-MS/MS). We did a statistical analysis of the distribution of the 16 most common IMDs in amino acid disorders and organic acidemias, and then paid special attention to analyze the age and regional distributions of different IMDs. The statistical analyses and visualization analysis were performed with the programming language R (version 4.2.1)., Results: There were 4911 positive cases diagnosed, which was 1.32% of the total sample during the ten-year study period. Most diseases tended to occur at ages younger than 18 year-old. The Ornithine Transcarbamylase Deficiency tended to progress on male infants who were less than 28 days old. While the peak of the positive case number of Citrin Deficiency disease (CD) was at 1-6 months. Different IMDs' had different distribution patterns in China's provinces. Methylmalonic Acidemias and Hyperphenylalaninemia had an imbalanced distribution pattern in China and its positive rate was significantly higher in North China than South China. Conversely, the positive rate of CD was significantly higher in South China than North China., Conclusions: Results of this work, such as the differences in distribution pattern of different diseases in terms of age, region, etc. provide important insights and references for clinicians, researchers and healthcare policy makers. The policy makers could optimize the better health screening programs for covering children and infants in specific ages and regions based on our findings., (© 2023. Institut National de la Santé et de la Recherche Médicale (INSERM).)

Type 2 diabetes (T2D), cardiovascular disease (CVD) and chronic kidney disease (CKD), are recognized among the most disruptive public health issues of the current century. A large body of evidence from epidemiological and clinical research supports the existence of a strong interconnection between these conditions, such that the unifying term cardio-metabolic-renal (CMR) disease has been defined. This coexistence has remarkable epidemiological, pathophysiologic, and prognostic implications. The mechanisms of hyperglycemia-induced damage to the cardio-renal system are well validated, as are those that tie cardiac and renal disease together. Yet, it remains controversial how and to what extent CVD and CKD can promote metabolic dysregulation. The aim of this review is to recapitulate the epidemiology of the CMR connections; to discuss the well-established, as well as the putative and emerging mechanisms implicated in the interplay among these three entities; and to provide a pathophysiological background for an integrated therapeutic intervention aiming at interrupting this vicious crosstalks., (© 2023. The Author(s).)

Bone age assessment (BAA) is a typical clinical technique for diagnosing endocrine and metabolic diseases in children's development. Existing deep learning-based automatic BAA models are trained on the Radiological Society of North America dataset (RSNA) from Western populations. However, due to the difference in developmental process and BAA standards between Eastern and Western children, these models cannot be applied to bone age prediction in Eastern populations. To address this issue, this paper collects a bone age dataset based on the East Asian populations for model training. Nevertheless, it is laborious and difficult to obtain enough X-ray images with accurate labels. In this paper, we employ ambiguous labels from radiology reports and transform them into Gaussian distribution labels of different amplitudes. Furthermore, we propose multi-branch attention learning with ambiguous labels network (MAAL-Net). MAAL-Net consists of a hand object location module and an attention part extraction module to discover the informative regions of interest (ROIs) based only on image-level labels. Extensive experiments on both the RSNA dataset and the China Bone Age (CNBA) dataset demonstrate that our method achieves competitive results with the state-of-the-arts, and performs on par with experienced physicians in children's BAA tasks.

The application of natural and synthetic boron-containing compounds (BCC) in biomedical field is expanding. BCC have effects in the metabolism of living organisms. Some boron-enriched supplements are marketed as they exert effects in the bone and skeletal muscle; but also, BCC are being reported as acting on the enzymes and transporters of membrane suggesting they could modify the carbohydrate metabolism linked to some pathologies of high global burden, as an example is diabetes mellitus. Also, some recent findings are showing effects of BCC on lipid metabolism. In this review, information regarding the effects and interaction of these compounds was compiled, as well as the potential application for treating human metabolic disorders is suggested., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objective: This study evaluated the effectiveness of an automated prompt in the electronic medical record (EMR) to increase screening rates for metabolic conditions and referrals to health education and to improve BMI percentile among children with obesity., Methods: The intervention used an EMR reminder that provided a panel of lab orders (hemoglobin A1c, lipid panel, and alanine aminotransferase) during clinical encounters among pediatric patients ages 10 to 18 with BMI ≥ 95th percentile. Data on demographics, comorbid conditions, BMI, lab results, and health education referrals were analyzed. Cohorts during the year before (n = 3479) and after (n = 3439) workflow implementation were compared., Results: The distribution of race/ethnicity among children with obesity was 56% Hispanic, 19% White, 11% Filipino, 4% Pacific Islander, 3% Black, and 1% East/South Asian. Orders for metabolic lab tests increased from 2% in the pre-workflow period to 52% in the post-workflow period (p < 0.0001). Completed screening rates improved from 1% to 27% (p < 0.0001). Health education referrals increased from 0.4% to 7% (p < 0.0001). We observed a mean change in BMI percentile of -0.13% (p = 0.06)., Conclusions: This study validates the use of an EMR-based prompt to improve metabolic lab screening and health education referrals among children with obesity. During the limited period of follow-up, we found no significant change in BMI percentile., (© 2023 The Obesity Society.)

Background: Inherited Metabolic Disorders (IMDs) are rare diseases where one impaired protein leads to a cascade of changes in the adjacent chemical conversions. IMDs often present with non-specific symptoms, a lack of a clear genotype-phenotype correlation, and de novo mutations, complicating diagnosis. Furthermore, products of one metabolic conversion can be the substrate of another pathway obscuring biomarker identification and causing overlapping biomarkers for different disorders. Visualization of the connections between metabolic biomarkers and the enzymes involved might aid in the diagnostic process. The goal of this study was to provide a proof-of-concept framework for integrating knowledge of metabolic interactions with real-life patient data before scaling up this approach. This framework was tested on two groups of well-studied and related metabolic pathways (the urea cycle and pyrimidine de-novo synthesis). The lessons learned from our approach will help to scale up the framework and support the diagnosis of other less-understood IMDs., Methods: Our framework integrates literature and expert knowledge into machine-readable pathway models, including relevant urine biomarkers and their interactions. The clinical data of 16 previously diagnosed patients with various pyrimidine and urea cycle disorders were visualized on the top 3 relevant pathways. Two expert laboratory scientists evaluated the resulting visualizations to derive a diagnosis., Results: The proof-of-concept platform resulted in varying numbers of relevant biomarkers (five to 48), pathways, and pathway interactions for each patient. The two experts reached the same conclusions for all samples with our proposed framework as with the current metabolic diagnostic pipeline. For nine patient samples, the diagnosis was made without knowledge about clinical symptoms or sex. For the remaining seven cases, four interpretations pointed in the direction of a subset of disorders, while three cases were found to be undiagnosable with the available data. Diagnosing these patients would require additional testing besides biochemical analysis., Conclusion: The presented framework shows how metabolic interaction knowledge can be integrated with clinical data in one visualization, which can be relevant for future analysis of difficult patient cases and untargeted metabolomics data. Several challenges were identified during the development of this framework, which should be resolved before this approach can be scaled up and implemented to support the diagnosis of other (less understood) IMDs. The framework could be extended with other OMICS data (e.g. genomics, transcriptomics), and phenotypic data, as well as linked to other knowledge captured as Linked Open Data., (© 2023. The Author(s).)

Cardiometabolic diseases are a major public-health concern owing to their increasing prevalence worldwide. These diseases are characterized by a high degree of interindividual variability with regards to symptoms, severity, complications and treatment responsiveness. Recent technological advances, and the growing availability of wearable and digital devices, are now making it feasible to profile individuals in ever-increasing depth. Such technologies are able to profile multiple health-related outcomes, including molecular, clinical and lifestyle changes. Nowadays, wearable devices allowing for continuous and longitudinal health screening outside the clinic can be used to monitor health and metabolic status from healthy individuals to patients at different stages of disease. Here we present an overview of the wearable and digital devices that are most relevant for cardiometabolic-disease-related readouts, and how the information collected from such devices could help deepen our understanding of metabolic diseases, improve their diagnosis, identify early disease markers and contribute to individualization of treatment and prevention plans., (© 2023. Springer Nature Limited.)

Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders characterized by impaired social interaction, limited communication skills, and restrictive and repetitive behaviours. The pathophysiology of ASD is multifactorial and includes genetic, epigenetic, and environmental factors, whereas a causal relationship has been described between ASD and inherited metabolic disorders (IMDs). This review describes biochemical, genetic, and clinical approaches to investigating IMDs associated with ASD. The biochemical work-up includes body fluid analysis to confirm general metabolic and/or lysosomal storage diseases, while the advances and applications of genomic testing technology would assist with identifying molecular defects. An IMD is considered likely underlying pathophysiology in ASD patients with suggestive clinical symptoms and multiorgan involvement, of which early recognition and treatment increase their likelihood of achieving optimal care and a better quality of life.

"Metabolic dysfunction-associated fatty liver disease (MAFLD)" is the term suggested in 2020 to refer to fatty liver disease related to systemic metabolic dysregulation. The name change from nonalcoholic fatty liver disease (NAFLD) to MAFLD comes with a simple set of criteria to enable easy diagnosis at the bedside for the general medical community, including primary care physicians. Since the introduction of the term, there have been key areas in which the superiority of MAFLD over the traditional NAFLD terminology has been demonstrated, including for the risk of liver and extrahepatic mortality, disease associations, and for identifying high-risk individuals. Additionally, MAFLD has been adopted by a number of leading pan-national and national societies due to its concise diagnostic criterion, removal of the requirement to exclude concomitant liver diseases, and reduction in the stigma associated with this condition. The current article explores the differences between MAFLD and NAFLD diagnosis, areas of benefit, some potential limitations, and how the MAFLD terminology has opened up new fields of research.

Background: Phase angle (PhA) has been used as mortality prognostic, but there are no studies about its possible use as a screening tool. Therefore, an assessment of the possible utility of PhA in clinical practice is required. The aim of this systematic review was to explore all recent available evidence of PhA, and its possible utility as a screening tool in clinical practice in subjects with chronic metabolic diseases., Materials and Methods: This systematic review was performed and written as stated in the PRISMA 2020 guidelines. The search was conducted in PubMed, ScienceDirect and SciElo. In order to be considered eligible, within the entire search, only articles involving PhA and their utility in metabolic diseases were included., Results: PhA was associated with hyperuricemia and vitamin D deficiency in obese subjects, and decreased cardiovascular risk and malnutrition in hospitalized patients., Conclusion: PhA may be a potential screening tool in clinical practice to evaluate different biomarkers, cardiovascular risk, and nutritional diagnosis in metabolic diseases in adults.