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Abstract Background Oral cholic acid therapy is an effective therapy in children with primary bile acid synthesis deficiencies. Most reported patients with this treatment have 3β-hydroxy-Δ5-C27-steroid oxidoreductase deficiency. The aim of the study was the evaluation of cholic acid therapy in a cohort of patients with the rarer Δ4-3-oxosteroid 5β-reductase (Δ4-3-oxo-R) deficiency. Methods Sixteen patients with Δ4-3-oxo-R deficiency confirmed by AKR1D1 gene sequencing who received oral cholic acid were retrospectively analyzed. Results First symptoms were reported early in life (median 2 months of age), with 14 and 3 patients having cholestatic jaundice and severe bleeding respectively. Fifteen patients received ursodeoxycholic acid before diagnosis, with partial improvement in 8 patients. Four patients had liver failure at the time of cholic acid initiation. All 16 patients received cholic acid from a median age of 8.1 months (range 3.1–159) and serum liver tests normalized in all within 6–12 months of treatment. After a median cholic acid therapy of 4.5 years (range 1.1–24), all patients were alive with their native liver. Median daily cholic acid dose at last follow-up was 8.3 mg/kg of body weight. All patients, but one, had normal physical examination and all had normal serum liver tests. Fibrosis, evaluated using liver biopsy (n = 4) or liver elastography (n = 9), had stabilized or improved. Cholic acid therapy enabled a 12-fold decrease of 3-oxo-∆4 derivatives in urine. Patients had normal growth and quality of life. The treatment was well tolerated without serious adverse events and signs of hepatotoxicity. Conclusions Oral cholic acid therapy is a safe and effective treatment for patients with Δ4-3-oxo-R deficiency.

Abstract Metachromatic leukodystrophy (MLD) is a lysosomal storage disease caused by a deficiency of the arylsulfatase A (ARSA). ARSA deficiency leads to an accumulation of sulfatides primarily in the nervous system ultimately causing demyelination. With evolving therapeutic options, there is an increasing need for indicators to evaluate disease progression. Here, we report targeted metabolic urine profiling of 56 MLD patients including longitudinal sampling, using 1H (proton) nuclear magnetic resonance (NMR) spectroscopy. 1H‐NMR urine spectra of 119 MLD samples and 323 healthy controls were analyzed by an in vitro diagnostics research (IVDr) tool, covering up to 50 endogenous and 100 disease‐related metabolites on a 600‐MHz IVDr NMR spectrometer. Quantitative data reports were analyzed regarding age of onset, clinical course, and therapeutic intervention. The NMR data reveal metabolome changes consistent with a multiorgan affection in MLD patients in comparison to controls. In the MLD cohort, N‐acetylaspartate (NAA) excretion in urine is elevated. Early onset MLD forms show a different metabolic profile suggesting a metabolic shift toward ketogenesis in comparison to late onset MLD and controls. In samples of juvenile MLD patients who stabilize clinically after hematopoietic stem cell transplantation (HSCT), the macrophage activation marker neopterin is elevated. We were able to identify different metabolic patterns reflecting variable organ disturbances in MLD, including brain and energy metabolism and inflammatory processes. We suggest NAA in urine as a quantitative biomarker for neurodegeneration. Intriguingly, elevated neopterin after HSCT supports the hypothesis that competent donor macrophages are crucial for favorable outcome.

Background & Aims: Bile salt export pump (BSEP) deficiency frequently necessitates liver transplantation in childhood. In contrast to two predicted protein truncating mutations (PPTMs), homozygous p.D482G or p.E297G mutations are associated with relatively mild phenotypes, responsive to surgical interruption of the enterohepatic circulation (siEHC). The phenotype of patients with a compound heterozygous genotype of one p.D482G or p.E297G mutation and one PPTM has remained unclear. We aimed to assess their genotype-phenotype relationship. Methods: From the NAPPED database, we selected patients with homozygous p.D482G or p.E297G mutations (BSEP1/1; n = 31), with one p.D482G or p.E297G, and one PPTM (BSEP1/3; n = 30), and with two PPTMs (BSEP3/3; n = 77). We compared clinical presentation, native liver survival (NLS), and the effect of siEHC on NLS. Results: The groups had a similar median age at presentation (0.7-1.3 years). Overall NLS at age 10 years was 21% in BSEP1/3 vs. 75% in BSEP1/1 and 23% in BSEP3/3 (p

Abstract Background 5q spinal muscular atrophy (SMA) is a disabling and life-limiting neuromuscular disease. In recent years, novel therapies have shown to improve clinical outcomes. Yet, the absence of reliable biomarkers renders clinical assessment and prognosis of possibly already affected newborns with a positive newborn screening result for SMA imprecise and difficult. Therapeutic decisions and stratification of individualized therapies remain challenging, especially in symptomatic children. The aim of this proof-of-concept and feasibility study was to explore the value of 1H-nuclear magnetic resonance (NMR)-based metabolic profiling in identifying non-invasive diagnostic and prognostic urinary fingerprints in children and adolescents with SMA. Results Urine samples were collected from 29 treatment-naïve SMA patients (5 pre-symptomatic, 9 SMA 1, 8 SMA 2, 7 SMA 3), 18 patients with Duchenne muscular dystrophy (DMD) and 444 healthy controls. Using machine-learning algorithms, we propose a set of prediction models built on urinary fingerprints that showed potential diagnostic value in discriminating SMA patients from controls and DMD, as well as predictive properties in separating between SMA types, allowing predictions about phenotypic severity. Interestingly, preliminary results of the prediction models suggest additional value in determining biochemical onset of disease in pre-symptomatic infants with SMA identified by genetic newborn screening and furthermore as potential therapeutic monitoring tool. Conclusions This study provides preliminary evidence for the use of 1H-NMR-based urinary metabolic profiling as diagnostic and prognostic biomarker in spinal muscular atrophy.

Abstract Background Metabolic syndrome (MetS) is a multimorbid long-term condition without consensual medical definition and a diagnostic based on compatible symptomatology. Here we have investigated the molecular signature of MetS in urine. Methods We used NMR-based metabolomics to investigate a European cohort including urine samples from 11,754 individuals (18–75 years old, 41% females), designed to populate all the intermediate conditions in MetS, from subjects without any risk factor up to individuals with developed MetS (4–5%, depending on the definition). A set of quantified metabolites were integrated from the urine spectra to obtain metabolic models (one for each definition), to discriminate between individuals with MetS. Results MetS progression produces a continuous and monotonic variation of the urine metabolome, characterized by up- or down-regulation of the pertinent metabolites (17 in total, including glucose, lipids, aromatic amino acids, salicyluric acid, maltitol, trimethylamine N-oxide, and p-cresol sulfate) with some of the metabolites associated to MetS for the first time. This metabolic signature, based solely on information extracted from the urine spectrum, adds a molecular dimension to MetS definition and it was used to generate models that can identify subjects with MetS (AUROC values between 0.83 and 0.87). This signature is particularly suitable to add meaning to the conditions that are in the interface between healthy subjects and MetS patients. Aging and non-alcoholic fatty liver disease are also risk factors that may enhance MetS probability, but they do not directly interfere with the metabolic discrimination of the syndrome. Conclusions Urine metabolomics, studied by NMR spectroscopy, unravelled a set of metabolites that concomitantly evolve with MetS progression, that were used to derive and validate a molecular definition of MetS and to discriminate the conditions that are in the interface between healthy individuals and the metabolic syndrome.

Phenylketonuria (PKU) is a rare metabolic disorder caused by mutations in the phenylalanine hydroxylase gene. Depending on the severity of the genetic mutation, medical treatment, and patient dietary management, elevated phenylalanine (Phe) may occur in blood and brain tissues. Research has recently shown that high Phe not only impacts the central nervous system, but also other organ systems (e.g., heart and microbiome). This study used ex vivo proton nuclear magnetic resonance (1H-NMR) analysis of urine samples from PKU patients (mean 14.9 ± 9.2 years, n = 51) to identify the impact of elevated blood Phe and PKU treatment on metabolic profiles. Our results found that 24 out of 98 urinary metabolites showed a significant difference (p < 0.05) for PKU patients compared to age-matched healthy controls (n = 51) based on an analysis of urinary metabolome. These altered urinary metabolites were related to Phe metabolism, dysbiosis, creatine synthesis or intake, the tricarboxylic acid (TCA) cycle, end products of nicotinamide-adenine dinucleotide degradation, and metabolites associated with a low Phe diet. There was an excellent correlation between the metabolome and genotype of PKU patients and healthy controls of 96.7% in a confusion matrix model. Metabolomic investigations may contribute to a better understanding of PKU pathophysiology.

Background/Objectives: Aggregate prescribing behavior for inflammatory lesions of rosacea has been described, but individual physician behavior has not been characterized. This study aims to assess the modern state of topical rosacea drug selection by analyzing prescribing patterns among individual dermatologists. Methods: We assessed utilization patterns of four topical papulopustular rosacea agents in 2021 Medicare Part-D data. K-means cluster analysis identified prescriber phenotypes based on the proportion of claims for each drug by physician. Results: Cluster analysis identified four prescriber phenotypes for topical rosacea agents, with the majority favoring metronidazole. In each of the other clusters, metronidazole was co-prescribed alongside the primary agent. Significant predictors of phenotype included patient ages, patient risk scores, and a group practice setting. Conclusions: The study reveals nonuniform prescribing patterns for topical papulopustular rosacea treatments among U.S. dermatologists. While aggregate data indicate diverse drug utilization, cluster analysis suggests that individual prescribers tend to use a limited selection of agents. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to analyze the characteristics and performance of university-industry (U-I) collaboration for knowledge transfer in relation to environmental sustainability, considering for both parties of the collaborations. Design/methodology/approach: The study is explorative in nature, based on an original data set of more than 350 U-I research and consultancy contracts signed by more than 70 professors specializing in environmental sustainability-related academic disciplines at the University of Padova (Italy) for the period 2008-2012. A mixed-method approach is adopted. Social network analysis and regressions are used to explore the impact of U-I on performance considering for characteristics of the firms, the professors and the collaboration. Interviews with key informants at University of Padova is used to complement and validate the emerging evidence. Findings: Results suggest that U-I positively impacts the performance of firms, but not of professors. Indeed, the hypothesis that professors' performance (measures in terms of academic publications) is positively associated with academic engagement is not supported. On the contrary, firms' financial performance is positively associated with U-I collaboration focused on knowledge transfer for environmental innovation; the higher the contracts activated the better the economic performance. Originality/value: While most previous research has focused either on the university or the firm side of U-I, this study looks at both sides and focuses specifically on engagement in green contracts. The analysis of the geographical scope of U-I collaborations contributes to the growing body of literature by outlining geography's role in U-I collaborations related to sustainability.

After SARS-CoV-2 infection, the molecular phenoreversion of the immunological response and its associated metabolic dysregulation are required for a full recovery of the patient. This process is patient-dependent due to the manifold possibilities induced by virus severity, its phylogenic evolution and the vaccination status of the population. We have here investigated the natural history of COVID-19 disease at the molecular level, characterizing the metabolic and immunological phenoreversion over time in large cohorts of hospitalized severe patients (n = 886) and non-hospitalized recovered patients that self-reported having passed the disease (n = 513). Non-hospitalized recovered patients do not show any metabolic fingerprint associated with the disease or immune alterations. Acute patients are characterized by the metabolic and lipidomic dysregulation that accompanies the exacerbated immunological response, resulting in a slow recovery time with a maximum probability of around 62 days. As a manifestation of the heterogeneity in the metabolic phenoreversion, age and severity become factors that modulate their normalization time which, in turn, correlates with changes in the atherogenesis-associated chemokine MCP-1. Our results are consistent with a model where the slow metabolic normalization in acute patients results in enhanced atherosclerotic risk, in line with the recent observation of an elevated number of cardiovascular episodes found in post-COVID-19 cohorts.

The complex manifestations of COVID-19 are still not fully decoded on the molecular level. We combined quantitative the nuclear magnetic resonance (NMR) spectroscopy serum analysis of metabolites, lipoproteins and inflammation markers with clinical parameters and a targeted cytokine panel to characterize COVID-19 in a large (534 patient samples, 305 controls) outpatient cohort of recently tested PCR-positive patients. The COVID-19 cohort consisted of patients who were predominantly in the initial phase of the disease and mostly exhibited a milder disease course. Concerning the metabolic profiles of SARS-CoV-2-infected patients, we identified markers of oxidative stress and a severe dysregulation of energy metabolism. NMR markers, such as phenylalanine, inflammatory glycoproteins (Glyc) and their ratio with the previously reported supramolecular phospholipid composite (Glyc/SPC), showed a predictive power comparable to laboratory parameters such as C-reactive protein (CRP) or ferritin. We demonstrated interfaces between the metabolism and the immune system, e.g., we could trace an interleukin (IL-6)-induced transformation of a high-density lipoprotein (HDL) to a pro-inflammatory actor. Finally, we showed that metadata such as age, sex and constitution (e.g., body mass index, BMI) need to be considered when exploring new biomarkers and that adding NMR parameters to existing diagnoses expands the diagnostic toolbox for patient stratification and personalized medicine.