Variational autoencoders for generative modeling of drug dosing determinants in renal, hepatic, metabolic, and cardiac disease states.

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.

Diminished antibody response to SARS-CoV-2 in rheumatoid arthritis compared to metabolic disorders following the primary series of vaccinations and its recovery with a booster: A single-center prospective observational study.

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.

[Analysis of non-alcoholic fatty liver disease differences from metabolic dysfunction-associated fatty liver disease based on clinical features].

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.

Investigating the Impact of Bariatric Surgery on Macular and Peripapillary Vessel Density in Obese Individuals without Metabolic Disease.

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 < 0.05). A significant increase was observed in macular vessel density in the deep capillary plexus postoperatively (p < 0.01). However, no significant postoperative increase occurred in macular vascular density in the superficial and intermediate capillary plexus (p > 0.05). Moreover, there was no change in peripapillary vascular density (p > 0.05). Postoperative thickening of the foveal, parafoveal, and perifoveal retinal layers was significant (p < 0.001). No significant correlation was detected between BMI change and macular and peripapillary vessel density changes (p > 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.

Comparative analysis of inherited metabolic diseases in normal newborns and high-risk children: Insights from a 10-year study in Shanghai.

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.

Result of a Pilot External Quality Assessment Scheme for Clinical Diagnosis of Inherited Metabolic Disorders in China.

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.

Next-generation sequencing based newborn screening and comparative analysis with MS/MS.

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.

An interpretable predictive deep learning platform for pediatric metabolic diseases.

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.

Availability of psychological resources for parents receiving communication of positivity at newborn screening for metabolic diseases in Italy.

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.

Molecular testing in newborn screening: VUS burden among true positives and secondary reproductive limitations via expanded carrier screening panels.

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.

From NAFLD to MASLD: When metabolic comorbidity matters.

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.

OBMeta: a comprehensive web server to analyze and validate gut microbial features and biomarkers for obesity-associated metabolic diseases.

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/.

IGAm: A novel index predicting long-term survival in patients with early-diagnosed inherited metabolic disorders.

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.

[Evaluation and optimization of newborn screening by structured long-term follow-up-using the example of inherited metabolic diseases]. / Evaluierung und Optimierung des Neugeborenenscreenings mittels strukturierter Langzeitbeobachtung ­ am Beispiel der angeborenen Stoffwechselerkrankungen.

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.

Harmonization of distributed multi-center analysis based on dried blood spot reference materials supporting the screening of neonatal inherited metabolic disorders.

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.

Clinical Presentation of Inherited Metabolic Diseases in Newborns Hospitalised in an Intensive Care Unit.

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.

Menstrual Cycle Irregularity in Adolescence Is Associated With Cardiometabolic Health in Early Adulthood.

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.