Beyond MEN1, When to Think About MEN4? Retrospective Study on 5600 Patients in the French Population and Literature Review.

CONTEXT: Germline CDKN1B variants predispose patients to multiple endocrine neoplasia type 4 (MEN4), a rare MEN1-like syndrome, with <100 reported cases since its discovery in 2006. Although CDKN1B mutations are frequently suggested to explain cases of genetically negative MEN1, the prevalence and phenotype of MEN4 patients is poorly known, and genetic counseling is unclear. OBJECTIVE: To evaluate the prevalence of MEN4 in MEN1-suspected patients and characterize the phenotype of MEN4 patients. DESIGN: Retrospective observational nationwide study. Narrative review of literature and variant class reassessment. PATIENTS: We included all adult patients with class 3/4/5 CDKN1B variants identified by the laboratories from the French Oncogenetic Network on Neuroendocrine Tumors network between 2015 and 2022 through germline genetic testing for MEN1 suspicion. After class reassessment, we compared the phenotype of symptomatic patients with class 4/5 CDKN1B variants (ie, with genetically confirmed MEN4 diagnosis) in our series and in literature with 66 matched MEN1 patients from the UMD-MEN1 database. RESULTS: From 5600 MEN1-suspected patients analyzed, 4 with class 4/5 CDKN1B variant were found (0.07%). They presented with multiple duodenal NET, primary hyperparathyroidism (PHPT) and adrenal nodule, isolated PHPT, PHPT, and pancreatic neuroendocrine tumor. We listed 29 patients with CDKN1B class 4/5 variants from the literature. Compared with matched MEN1 patients, MEN4 patients presented lower NET incidence and older age at PHPT diagnosis. CONCLUSION: The prevalence of MEN4 is low. PHPT and pituitary adenoma represent the main associated lesions, NETs are rare. Our results suggest a milder and later phenotype than in MEN1. Our observations will help to improve genetic counseling and management of MEN4 families.

Rapid haemoglobin A and S quantification using Tosoh HLC-723G8 in variant mode for patients with sickle cell disease.

The management of life-threatening complications in patients with sickle cell disease (SCD) requires an accurate and reproducible quantification of haemoglobin A (HbA) and S (HbS) with a short turnaround time and 24-7 availability. We propose a novel method for quantifying HbA and HbS using the glycated haemoglobin (HbA1c) assay on a Tosoh HLC-723G8 (G8) analyser in variant mode. HbA and HbS results obtained using our method highly correlated with results obtained using a reference method (r > 0.99 for 124 samples of patients with SCD or sickle cell trait). Our method met laboratory requirements for linearity (coefficient of variation [CV] and bias <5%), between-run and within-run reproducibility (CV <10%) and carryover (<0.5%) over the range of HbS and HbA values expected in a therapeutic context. Using the G8 analyser in variant mode is viable for monitoring HbA and HbS concentrations in dire situations. This method is easy to use, quick (1.6 min per sample), and automatable and produces highly reproducible results without significant bias. Finally, it does not require modifications to the analytical pipeline recommended by the supplier, enabling a 24-7 availability without disrupting routine monitoring of HbA1c in the laboratory.

Update of the UMD-VHL database: classification of 164 challenging variants based on genotype-phenotype correlation among 605 entries.

BACKGROUND: The von Hippel-Lindau (VHL) disease is a hereditary tumour syndrome caused by germline mutations in VHL tumour suppressor gene. The identification of VHL variants requires accurate classification which has an impact on patient management and genetic counselling. METHODS: The TENGEN (French oncogenetics network of neuroendocrine tumors) and PREDIR (French National Cancer Institute network for Inherited predispositions to kidney cancer) networks have collected VHL genetic variants and clinical characteristics of all VHL-suspected patients analysed from 2003 to 2021 by one of the nine laboratories performing VHL genetic testing in France. Identified variants were registered in a locus-specific database, the Universal Mutation Database-VHL database (http://www.umd.be/VHL/). RESULTS: Here we report the expert classification of 164 variants, including all missense variants (n=124), all difficult interpretation variants (n=40) and their associated phenotypes. After initial American College of Medical Genetics classification, first-round classification was performed by the VHL expert group followed by a second round for discordant and ambiguous cases. Overall, the VHL experts modified the classification of 87 variants including 30 variants of uncertain significance that were as (likely)pathogenic variants for 19, and as likely benign for 11. CONCLUSION: Consequently, this work has allowed the diagnosis and influenced the genetic counselling of 45 VHL-suspected families and can benefit to the worldwide VHL community, through this review.

Breast Cancer Chemoresistance: Insights into the Regulatory Role of lncRNA.

Long noncoding RNAs (lncRNAs) are a subclass of noncoding RNAs composed of more than 200 nucleotides without the ability to encode functional proteins. Given their involvement in critical cellular processes such as gene expression regulation, transcription, and translation, lncRNAs play a significant role in organism homeostasis. Breast cancer (BC) is the second most common cancer worldwide and evidence has shown a relationship between aberrant lncRNA expression and BC development. One of the main obstacles in BC control is multidrug chemoresistance, which is associated with the deregulation of multiple mechanisms such as efflux transporter activity, mitochondrial metabolism reprogramming, and epigenetic regulation as well as apoptosis and autophagy. Studies have shown the involvement of a large number of lncRNAs in the regulation of such pathways. However, the underlying mechanism is not clearly elucidated. In this review, we present the principal mechanisms associated with BC chemoresistance that can be directly or indirectly regulated by lncRNA, highlighting the importance of lncRNA in controlling BC chemoresistance. Understanding these mechanisms in deep detail may interest the clinical outcome of BC patients and could be used as therapeutic targets to overcome BC therapy resistance.

Case report: Diagnosis of ADCY5-related dyskinesia explaining the entire phenotype in a patient with atypical citrullinemia type I.

In this case study, we report the case of a 13-year-old girl with citrullinemia type 1 (MIM #215700), an autosomal recessive inherited disorder of the urea cycle, which was confirmed by the identification of a homozygous pathogenic variant in the argininosuccinate synthetase 1 (ASS1) gene. However, the patient presented abnormal hyperkinetic movements with global developmental delay and clinical signs that were not fully consistent with those of citrullinemia type 1 or with those of her siblings with isolated citrullinemia type 1. Exome sequencing showed the presence of a de novo heterozygous pathogenic variant in the adenylate cyclase type 5 (ADCY5) gene. The variant confirmed the overlap with the so-called ADCY5-related dyskinesia with orofacial involvement, which is autosomal dominant (MIM #606703), a disorder disrupting the enzymatic conversion of adenosine triphosphate (ATP) to cyclic adenosine monophosphate (cAMP). In addition to the citrullinemia-related low-protein diet and arginine supplementation, the identification of this second disease led to the introduction of a treatment with caffeine, which considerably improved the dyskinesia neurological picture. In conclusion, this case highlights the importance of clinical-biological confrontation for the interpretation of genetic variants, as one hereditary metabolic disease may hide another with therapeutic consequences. Summary: This article reports the misleading superposition of two inherited metabolic diseases, showing the importance of clinical-biological confrontation in the interpretation of genetic variants.

Kynurenic Acid: A Novel Player in Cardioprotection against Myocardial Ischemia/Reperfusion Injuries.

BACKGROUND: Myocardial infarction is one of the leading causes of mortality worldwide; hence, there is an urgent need to discover novel cardioprotective strategies. Kynurenic acid (KYNA), a metabolite of the kynurenine pathway, has been previously reported to have cardioprotective effects. However, the mechanisms by which KYNA may be protective are still unclear. The current study addressed this issue by investigating KYNA's cardioprotective effect in the context of myocardial ischemia/reperfusion. METHODS: H9C2 cells and rats were exposed to hypoxia/reoxygenation or myocardial infarction, respectively, in the presence or absence of KYNA. In vitro, cell death was quantified using flow cytometry analysis of propidium iodide staining. In vivo, TTC-Evans Blue staining was performed to evaluate infarct size. Mitochondrial respiratory chain complex activities were measured using spectrophotometry. Protein expression was evaluated by Western blot, and mRNA levels by RT-qPCR. RESULTS: KYNA treatment significantly reduced H9C2-relative cell death as well as infarct size. KYNA did not exhibit any effect on the mitochondrial respiratory chain complex activity. SOD2 mRNA levels were increased by KYNA. A decrease in p62 protein levels together with a trend of increase in PARK2 may mark a stimulation of mitophagy. Additionally, ERK1/2, Akt, and FOXO3α phosphorylation levels were significantly reduced after the KYNA treatment. Altogether, KYNA significantly reduced myocardial ischemia/reperfusion injuries in both in vitro and in vivo models. CONCLUSION: Here we show that KYNA-mediated cardioprotection was associated with enhanced mitophagy and antioxidant defense. A deeper understanding of KYNA's cardioprotective mechanisms is necessary to identify promising novel therapeutic targets and their translation into the clinical arena.

Combined Metabolipidomic and Machine Learning Approach in a Rat Model of Stroke Reveals a Deleterious Impact of Brain Injury on Heart Metabolism.

Cardiac complications are frequently found following a stroke in humans whose pathophysiological mechanism remains poorly understood. We used machine learning to analyse a large set of data from a metabolipidomic study assaying 630 metabolites in a rat stroke model to investigate metabolic changes affecting the heart within 72 h after a stroke. Twelve rats undergoing a stroke and 28 rats undergoing the sham procedure were investigated. A plasmatic signature consistent with the literature with notable lipid metabolism remodelling was identified. The post-stroke heart showed a discriminant metabolic signature, in comparison to the sham controls, involving increased collagen turnover, increased arginase activity with decreased nitric oxide synthase activity as well as an altered amino acid metabolism (including serine, asparagine, lysine and glycine). In conclusion, these results demonstrate that brain injury induces a metabolic remodelling in the heart potentially involved in the pathophysiology of stroke heart syndrome.

The top 10 most frequently involved genes in hereditary optic neuropathies in 2186 probands.

Hereditary optic neuropathies are caused by the degeneration of retinal ganglion cells whose axons form the optic nerves, with a consistent genetic heterogeneity. As part of our diagnostic activity, we retrospectively evaluated the combination of Leber hereditary optic neuropathy mutations testing with the exon sequencing of 87 nuclear genes on 2186 patients referred for suspected hereditary optic neuropathies. The positive diagnosis rate in individuals referred for Leber hereditary optic neuropathy testing was 18% (199/1126 index cases), with 92% (184/199) carrying one of the three main pathogenic variants of mitochondrial DNA (m.11778G>A, 66.5%; m.3460G>A, 15% and m.14484T>C, 11%). The positive diagnosis rate in individuals referred for autosomal dominant or recessive optic neuropathies was 27% (451/1680 index cases), with 10 genes accounting together for 96% of this cohort. This represents an overall positive diagnostic rate of 30%. The identified top 10 nuclear genes included OPA1, WFS1, ACO2, SPG7, MFN2, AFG3L2, RTN4IP1, TMEM126A, NR2F1 and FDXR. Eleven additional genes, each accounting for less than 1% of cases, were identified in 17 individuals. Our results show that 10 major genes account for more than 96% of the cases diagnosed with our nuclear gene panel.

A Metabolomic Signature of Ischemic Stroke Showing Acute Oxidative and Energetic Stress.

Metabolomics is a powerful data-driven tool for in-depth biological phenotyping that could help identify the specific metabolic profile of cryptogenic strokes, for which no precise cause has been identified. We performed a targeted quantitative metabolomics study in West African patients who had recently suffered an ischemic stroke, which was either cryptogenic (n = 40) or had a clearly identified cause (n = 39), compared to a healthy control group (n = 40). Four hundred fifty-six metabolites were accurately measured. Multivariate analyses failed to reveal any metabolic profile discriminating between cryptogenic ischemic strokes and those with an identified cause but did show superimposable metabolic profiles in both groups, which were clearly distinct from those of healthy controls. The blood concentrations of 234 metabolites were significantly affected in stroke patients compared to controls after the Benjamini-Hochberg correction. Increased methionine sulfoxide and homocysteine concentrations, as well as an overall increase in saturation of fatty acids, were indicative of acute oxidative stress. This signature also showed alterations in energetic metabolism, cell membrane integrity, monocarbon metabolism, and neurotransmission, with reduced concentrations of several metabolites known to be neuroprotective. Overall, our results show that cryptogenic strokes are not pathophysiologically distinct from ischemic strokes of established origin, and that stroke leads to intense metabolic remodeling with marked oxidative and energetic stresses.

In Reply to Performance of Deep Learning in the Interpretation of Serum Protein Electrophoresis.

We thank He et al. for their comments on our article (1), which gives us the opportunity to clarify some methodological points. 1. Detection of abnormal patterns: mechanics.

Clinically Symptomatic Resistance to Thyroid Hormone ß Syndrome Because of THRB Gene Mosaicism.

CONTEXT: Resistance to thyroid hormone ß syndrome (RTHß) is caused by pathogenic variants in the THRB gene, but such variants are found in only 85% of cases. We report the case of a patient with RTHß phenotype but for whom we found a pathogenic variant of the THRB gene in a mosaic state. CASE DESCRIPTION: The patient is a 52-year-old woman with clinical and biological signs of RTHß. Symptoms included asthenia, cardiac palpitations, and diarrhea. Repeated thyroid function tests showed an elevated serum TSH, elevated serum free T4, and variably normal or slightly elevated serum fT3. Pituitary magnetic resonance imaging was normal, and the thyrotropin-releasing hormone test result was compatible with the diagnosis of RTHß syndrome. Initial Sanger sequencing on blood samples could not highlight the presence of a mosaic variant because of insufficient sensitivity. When next-generation sequencing became accessible, blood samples were retested and we found a known pathogenic variant: c.949G > A; p.(ala317Thr), with an allelic frequency of 12%. Other samples from tissues of different embryological origin were also tested and found an allelic frequency of 5.7%, 17.9%, 9.9%, 6.4%, and 0% on urine tests, oral swab, nasal mucosa swab, skin biopsy, and conjunctival swab, respectively. Cloning confirmed the allelic frequency observed. CONCLUSIONS: We highlight that a pathogenic variant in a mosaic state in the THRB gene may be the cause of an authentic RTHß syndrome. High-throughput sequencing of multiple tissues eases the detection of pathogenic variant in a mosaic state and allows the correct diagnosis of patients with true RTHß, thus avoiding patient mismanagement.

Post-infarct cardiac remodeling predictions with machine learning.

BACKGROUND: We sought to improve the risk prediction of 3-month left ventricular remodeling (LVR) occurrence after myocardial infarction (MI), using a machine learning approach. METHODS: Patients were included from a prospective cohort study analyzing the incidence of LVR in ST-elevation MI in 443 patients that were monitored at Angers University Hospital, France. Clinical, biological and cardiac magnetic resonance (CMR) imaging data from the first week post MI were collected, and LVR was assessed with CMR at 3 month. Data were processed with a machine learning pipeline using multiple feature selection algorithms to identify the most informative variables. RESULTS: We retrieved 133 clinical, biological and CMR imaging variables, from 379 patients with ST-elevation MI. A baseline logistic regression model using previously known variables achieved an AUC of 0.71 on the test set, with 67% sensitivity and 64% specificity. In comparison, our best predictive model was a neural network using seven variables (in order of importance): creatine kinase, mean corpuscular volume, baseline left atrial surface, history of diabetes, history of hypertension, red blood cell distribution width, and creatinine. This model achieved an AUC of 0.78 on the test set, reaching a sensitivity of 92% and a specificity of 55%, outperforming the baseline model. CONCLUSION: These preliminary results show the value of using an unbiased data-driven machine learning approach. We reached a higher level of sensitivity compared to traditional methods for the prediction of a 3-month post-MI LVR.

A Tear Metabolomic Profile Showing Increased Ornithine Decarboxylase Activity and Spermine Synthesis in Thyroid-Associated Orbitopathy.

About half of patients with Graves' disease develop an orbitopathy related to an inflammatory expansion of the periorbital adipose tissue and muscles. We used a targeted metabolomic approach measuring 188 metabolites by mass spectrometry to compare the metabolic composition of tears in patients with active (n = 21) versus inactive (n = 24) thyroid-associated orbitopathy. Among the 44 metabolites accurately measured, 8 showed a significant alteration of their concentrations between the two groups. Two short-chain acylcarnitines, propionylcarnitine and butyrylcarnitine, and spermine showed increased concentrations in the tears of patients with active orbitopathy, whereas ornithine, glycine, serine, citrulline and histidine showed decreased concentrations in this group. In addition, the ratio putrescine/ornithine, representing the activity of ornithine decarboxylase, was significantly increased in patients with active compared to inactive orbitopathy (p = 0.0011, fold change 3.75). The specificity of this candidate biomarker was maintained when compared to a control group with unclassified dry eye disease. Our results suggest that the stimulation of ornithine decarboxylase by TSH receptor autoantibodies in orbital fibroblasts could lead to increased synthesis of spermine, through the increased activity of ornithine decarboxylase, that may contribute to periorbital expansion in Graves' ophthalmopathy.

International initiative for a curated SDHB variant database improving the diagnosis of hereditary paraganglioma and pheochromocytoma.

BACKGROUND: SDHB is one of the major genes predisposing to paraganglioma/pheochromocytoma (PPGL). Identifying pathogenic SDHB variants in patients with PPGL is essential to the management of patients and relatives due to the increased risk of recurrences, metastases and the emergence of non-PPGL tumours. In this context, the 'NGS and PPGL (NGSnPPGL) Study Group' initiated an international effort to collect, annotate and classify SDHB variants and to provide an accurate, expert-curated and freely available SDHB variant database. METHODS: A total of 223 distinct SDHB variants from 737 patients were collected worldwide. Using multiple criteria, each variant was first classified according to a 5-tier grouping based on American College of Medical Genetics and NGSnPPGL standardised recommendations and was then manually reviewed by a panel of experts in the field. RESULTS: This multistep process resulted in 23 benign/likely benign, 149 pathogenic/likely pathogenic variants and 51 variants of unknown significance (VUS). Expert curation reduced by half the number of variants initially classified as VUS. Variant classifications are publicly accessible via the Leiden Open Variation Database system (https://databases.lovd.nl/shared/genes/SDHB). CONCLUSION: This international initiative by a panel of experts allowed us to establish a consensus classification for 223 SDHB variants that should be used as a routine tool by geneticists in charge of PPGL laboratory diagnosis. This accurate classification of SDHB genetic variants will help to clarify the diagnosis of hereditary PPGL and to improve the clinical care of patients and relatives with PPGL.

NR2F1 database: 112 variants and 84 patients support refining the clinical synopsis of Bosch-Boonstra-Schaaf optic atrophy syndrome.

Pathogenic variants of the nuclear receptor subfamily 2 group F member 1 gene (NR2F1) are responsible for Bosch-Boonstra-Schaaf optic atrophy syndrome (BBSOAS), an autosomal dominant disorder characterized by optic atrophy associated with developmental delay and intellectual disability, but with a clinical presentation which appears to be multifaceted. We created the first public locus-specific database dedicated to NR2F1. All variants and clinical cases reported in the literature, as well as new unpublished cases, were integrated into the database using standard nomenclature to describe both molecular and phenotypic anomalies. We subsequently pursued a comprehensive approach based on computed representation and analysis suggesting a refinement of the BBSOAS clinical description with respect to neurological features and the inclusion of additional signs of hypotonia and feeding difficulties. This database is fully accessible for both clinician and molecular biologists and should prove useful in further refining the clinical synopsis of NR2F1 as new data is recorded.

Late-onset argininosuccinic aciduria in a 72-year-old man presenting with fatal hyperammonemia.

Argininosuccinate lyase deficiency (ASLD, MIM #207900) is an inherited urea cycle disorder. There are mainly two clinical forms, an acute neonatal form which manifests as life-threatening hyperammonemia, and a late-onset form characterised by polymorphic neuro-cognitive or psychiatric presentation with transient hyperammonemia episodes. Here, we report a late-onset case of ASLD in a 72-year-old man carrying a homozygous pathogenic variant in the exon 16 of the ASL gene, presenting for the first time with fatal hyperammonemic coma. This case report shows the need to systematically carry out an ammonia assay when faced with an unexplained coma.

The Long Non-Coding RNA SAMMSON Is a Regulator of Chemosensitivity and Metabolic Orientation in MCF-7 Doxorubicin-Resistant Breast Cancer Cells.

Despite improvements in therapeutic strategies for treating breast cancers, tumor relapse and chemoresistance remain major issues in patient outcomes. Indeed, cancer cells display a metabolic plasticity allowing a quick adaptation to the tumoral microenvironment and to cellular stresses induced by chemotherapy. Recently, long non-coding RNA molecules (lncRNAs) have emerged as important regulators of cellular metabolic orientation. In the present study, we addressed the role of the long non-coding RNA molecule (lncRNA) SAMMSON on the metabolic reprogramming and chemoresistance of MCF-7 breast cancer cells resistant to doxorubicin (MCF-7dox). Our results showed an overexpression of SAMMSON in MCF-7dox compared to doxorubicin-sensitive cells (MCF-7). Silencing of SAMMSON expression by siRNA in MCF-7dox cells resulted in a metabolic rewiring with improvement of oxidative metabolism, decreased mitochondrial ROS production, increased mitochondrial replication, transcription and translation and an attenuation of chemoresistance. These results highlight the role of SAMMSON in the metabolic adaptations leading to the development of chemoresistance in breast cancer cells. Thus, targeting SAMMSON expression levels represents a promising therapeutic route to circumvent doxorubicin resistance in breast cancers.

Achieving Expert-Level Interpretation of Serum Protein Electrophoresis through Deep Learning Driven by Human Reasoning.

BACKGROUND: Serum protein electrophoresis (SPE) is a common clinical laboratory test, mainly indicated for the diagnosis and follow-up of monoclonal gammopathies. A time-consuming and potentially subjective human expertise is required for SPE analysis to detect possible pitfalls and to provide a clinically relevant interpretation. METHODS: An expert-annotated SPE dataset of 159 969 entries was used to develop SPECTR (serum protein electrophoresis computer-assisted recognition), a deep learning-based artificial intelligence, which analyzes and interprets raw SPE curves produced by an analytical system into text comments that can be used by practitioners. It was designed following academic recommendations for SPE interpretation, using a transparent architecture avoiding the "black box" effect. SPECTR was validated on an external, independent cohort of 70 362 SPEs and challenged by a panel of 9 independent experts from other hospital centers. RESULTS: SPECTR was able to identify accurately both quantitative abnormalities (r ≥ 0.98 for fractions quantification) and qualitative abnormalities [receiver operating characteristic-area under curve (ROC-AUC) ≥ 0.90 for M-spikes, restricted heterogeneity of immunoglobulins, and beta-gamma bridging]. Furthermore, it showed highly accurate at both detecting (ROC-AUC ≥ 0.99) and quantifying (r = 0.99) M-spikes. It proved highly reproducible and resilient to minor variations and its agreement with human experts was higher (κ = 0.632) than experts between each other (κ = 0.624). CONCLUSIONS: SPECTR is an algorithm based on artificial intelligence suitable to high-throughput SPEs analyses and interpretation. It aims at improving SPE reproducibility and reliability. It is freely available in open access through an online tool providing fully editable validation assistance for SPE.

Metabolomic Sexual Dimorphism of the Mouse Brain is Predominantly Abolished by Gonadectomy with a Higher Impact on Females.

The importance of sexual dimorphism of the mouse brain metabolome was recently highlighted, in addition to a high regional specificity found between the frontal cortex, the cerebellum, and the brain stem. To address the origin of this dimorphism, we performed gonadectomy on both sexes, followed by a metabolomic study targeting 188 metabolites in the three brain regions. While sham controls, which underwent the same surgical procedure without gonadectomy, reproduced the regional sexual dimorphism of the metabolome previously identified, no sex difference was identifiable after gonadectomy, through both univariate and multivariate analyses. These experiments also made it possible to identify which sex was responsible for the dimorphism for 35 metabolites. The female sex contributed to the difference for more than 80% of them. Our results show that gonads are the main contributors to the brain sexual dimorphism previously observed, especially in females.