Mono- and bi-allelic variants in ALDH18A1 cause a spectrum of human disorders associated with cutaneous and neurological findings that overlap with both cutis laxa and spastic paraplegia. ALDH18A1 encodes the bifunctional enzyme pyrroline-5-carboxylate synthetase (P5CS) that plays a role in the de novo biosynthesis of proline and ornithine. Here we characterize a previously unreported homozygous ALDH18A1 variant (p.Thr331Pro) in four affected probands from two unrelated families, and demonstrate broad-based alterations in amino acid and antioxidant metabolism. These four patients exhibit variable developmental delay, neurological deficits and loose skin. Functional characterization of the p.Thr331Pro variant demonstrated a lack of any impact on the steady-state level of the P5CS monomer or mitochondrial localization of the enzyme, but reduced incorporation of the monomer into P5CS oligomers. Using an unlabeled NMR-based metabolomics approach in patient fibroblasts and ALDH18A1-null human embryonic kidney cells expressing the variant P5CS, we identified reduced abundance of glutamate and several metabolites derived from glutamate, including proline and glutathione. Biosynthesis of the polyamine putrescine, derived from ornithine, was also decreased in patient fibroblasts, highlighting the functional consequence on another metabolic pathway involved in antioxidant responses in the cell. RNA sequencing of patient fibroblasts revealed transcript abundance changes in several metabolic and extracellular matrix-related genes, adding further insight into pathogenic processes associated with impaired P5CS function. Together these findings shed new light on amino acid and antioxidant pathways associated with ALDH18A1-related disorders, and underscore the value of metabolomic and transcriptomic profiling to discover new pathways that impact disease pathogenesis.

Mosaic variants in the PIK3CA gene, encoding the catalytic subunit of phosphatidylinositol 3-kinase (PI3K), produce constitutive PI3K activation which causes PIK3CA-related overgrowth spectrum (PROS) disorders. To date, fewer than 20 patients have been described with germline alterations in PIK3CA. In this study, we describe three unrelated individuals with overgrowth and germline PIK3CA variants. These variants were discovered through whole-exome sequencing and confirmed as germline by testing multiple tissue types, when available. Functional analysis using Patient 1’s fibroblast cell line and two previously reported patients’ cell lines showed increased phosphorylation of AKT during cellular starvation revealing constitutive activation of the PI3K/AKT/mTOR pathway. Alternatively, stimulation of the cells by fetal bovine serum produced a reduced response, indicating an activated status of the PI3K complex reducing the pathway response to further external stimulation. Additional studies utilizing Biolog Phenotype Microarray technology indicated reduced energy production when cells were exposed to growth factors stimulating the PI3K/AKT/mTOR pathway, confirming the trend observed in the AKT phosphorylation test after stimulation. Furthermore, treatment with inhibitors of the PI3K/AKT/mTOR pathway rescued the normal energy response in the patients’ cells. Collectively, these data demonstrate that disease-causing germline PIK3CA variants have a functional consequence, similar to mosaic variants in the PI3K/AKT/mTOR pathway.

Autism spectrum disorder (ASD) is a heterogeneous group of neurodevelopmental disorders (NDDs) with a high unmet medical need. The diagnosis of ASD is currently based on behavior criteria, which overlooks the diversity of genetic, neurophysiological, and clinical manifestations. Failure to acknowledge such heterogeneity has hindered the development of efficient drug treatments for ASD and other NDDs. DEPI^® (Databased Endophenotyping Patient Identification) is a systems biology, multi-omics, and machine learning-driven platform enabling the identification of subgroups of patients with NDDs and the development of patient-tailored treatments. In this study, we provide evidence for the validation of a first clinically and biologically defined subgroup of patients with ASD identified by DEPI, ASD Phenotype 1 (ASD-Phen1). Among 313 screened patients with idiopathic ASD, the prevalence of ASD-Phen1 was observed to be ~24% in 84 patients who qualified to be enrolled in the study. Metabolic and transcriptomic alterations differentiating patients with ASD-Phen1 were consistent with an over-activation of NF-κB and NRF2 transcription factors, as predicted by DEPI. Finally, the suitability of STP1 combination treatment to revert such observed molecular alterations in patients with ASD-Phen1 was determined. Overall, our results support the development of precision medicine-based treatments for patients diagnosed with ASD.

Background/Objectives: In late 2019, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused a pandemic called the ‘coronavirus disease 2019’ (COVID-19). After the acute SARS-CoV-2 infection, many individuals (up to 33%) complained of unexplained symptoms involving multiple organ systems and were diagnosed as having Long COVID-19 (LC-19). Currently, LC-19 is inadequately defined, requiring the formation of consistent diagnostic parameters to provide a foundation for ongoing and future studies of epidemiology, risk factors, clinical characteristics, and therapy. LC-19 represents a significant burden on multiple levels. The reduced ability of workers to return to work or compromised work efficiency has led to consequences at national, economic, and societal levels by increasing dependence on community services. On a personal scale, the isolation and helplessness caused by the disease and its subsequent impact on the patient’s mental health and quality of life are incalculable. Methods: In this paper, we used Walker and Avants’ eight-step approach to perform a concept analysis of the term “Long COVID-19” and define its impact across these parameters. Results: Using this methodology, we provide an improved definition of LC-19 by connecting the clinical symptomology with previously under-addressed factors, such as mental, psychological, economic, and social effects. This definition of LC-19 features can help improve diagnostic procedures and help plan relevant healthcare services. Conclusions: LC-19 represents a complex and pressing public health challenge with diverse symptomology, an unpredictable timeline, and complex pathophysiology. This concept analysis serves as a tool for improving LC-19 definition, but it remains a dynamic disease with evolving diagnostic and therapeutic approaches, requiring deeper investigation and understanding of its long-term effects.

Background/Objectives: Phelan–McDermid syndrome (PMS), caused by either chromosome 22q13.3 deletions or pathogenic/likely pathogenic variants in the SHANK3 gene, is a rare neurodevelopmental disorder. Behavioral issues greatly impair the quality of life for affected individuals and their families. This genotype–phenotype study intended to further characterize key behavioral features and their genetic and metabolic correlates in PMS. Methods: We conducted a cross-sectional analysis of data on 56 individuals with PMS. Autistic and related behaviors were assessed with the Autism Diagnosis Interview—Revised (ADI-R) and adaptive behavior skills were assessed with the Vineland Adaptive Behavior Scales-Third Edition (Vineland-3), both covering multiple aspects of communication, socialization and abnormal behaviors. Genetic diagnostic information on deletions or pathogenic variants was supplemented with the sequencing data of nine candidate genes on 22q13.3. Metabolic data were obtained using the Biolog Phenotype Mammalian MicroArray plates (PM-M). Results. Every subject in the cohort presented either prominent autistic behavior or adaptive behavior impairment, 55.4% of them meeting the ASD cutoff in every ADI-R domain and 92.9% scoring in the lowest level of adaptive behavior (range of 20–70). Individuals with SHANK3 variants had lower adaptive behavioral skills than those with 22q13 deletions regardless of deletion size, while genomic parameters were largely unrelated to ADI-R scores. Metabolic profiling identified unique profiles of individuals with PMS compared with controls, while distinct profiles distinguished those who met or did not meet the ADI-R ASD cutoff. Cluster analyses revealed groups of individuals with ASD and other clinical features. Conclusion. This study highlighted the importance of SHANK3 in adaptive behavioral skills and uncovered potential metabolic biomarkers of therapeutic relevance.

Background/Objectives: Long COVID-19 (LC-19), also known as Post-Acute COVID-19 Syndrome (PACS), is a chronic condition some people experience after an initial SARS-CoV-2 infection. The etiology of this complex, multifactorial disease remains largely unknown, although various theories have been propounded. This study aims to profile and compare the metabolic activity of cells of normal and LC-19 patients. Methods: A cohort of 20 individuals, 10 with LC-19 and 10 without LC-19, was selected based on their post-COVID-19 symptomatology. Saliva was tested for opportunistic viruses like Epstein–Barr virus (EBV) and Human Herpesvirus 6 (HHV-6). Lymphoblastoid cell lines derived from blood were analyzed using the Biolog Phenotype Mammalian Microarrays (PM-M1, PM-M6, and PM-M7) to assess metabolic activity across a wide array of growth substrates and effector molecules. Results: Unique metabolic profiles emerged across the controls and LC-19 groups. The SARS-CoV-2 infection causes an over two-fold enhanced utilization of glycolytic and anaerobic substrates and a reduced response to growth factors and effectors. The increased energy source utilization assessed in PM-M1 is unsustainable, and the LC-19 groups demonstrate this with a clear correlation with the number of LC-19 symptoms, demonstrating a trend consistent with metabolic reprogramming. The infection also results in a reduced response to growth factors and effectors, assessed in PM-M6 and PM-M7, with the level of reduction commensurate with the symptom burden. Conclusions: The data from the patient groups were analyzed and compared to construct a metabolic profile unique to individuals who developed LC-19, which could, in the future, be used for diagnosis and to identify targets for therapeutic intervention. Our study identified an LC-19-specific metabolic profile indicative of adaptive responses to stress, cellular dysfunction, and prolonged inflammation, leading to the reprogramming of bioenergetic pathways.