👤 Gregoire Mignot

Kleine-Levin syndrome (KLS) is characterized by relapsing-remitting episodes of hypersomnia, cognitive impairment, and behavioral disturbances. We quantified cerebrospinal fluid (CSF) and serum proteins in KLS cases and controls. SomaScan was used to profile 1133 CSF proteins in 30 KLS cases and 134 controls, while 1109 serum proteins were profiled in serum from 26 cases and 65 controls. CSF and serum proteins were both measured in seven cases. Univariate and multivariate analyses were used to find differentially expressed proteins (DEPs). Pathway and tissue enrichment analyses (TEAs) were performed on DEPs. Univariate analyses found 28 and 141 proteins differentially expressed in CSF and serum, respectively (false discovery rate <0.1%). Upregulated CSF proteins included IL-34, IL-27, TGF-b, IGF-1, and osteonectin, while DKK4 and vWF were downregulated. Pathway analyses revealed microglial alterations and disrupted blood-brain barrier permeability. Serum profiles show upregulation of Src-family kinases (SFKs), proteins implicated in cellular growth, motility, and activation. TEA analysis of up- and downregulated proteins revealed changes in brain proteins (p < 6 × 10-5), notably from the pons, medulla, and midbrain. A multivariate machine-learning classifier performed robustly, achieving a receiver operating curve area under the curve of 0.90 (95% confidence interval [CI] = 0.78-1.0, p = 0.0006) in CSF and 1.0 (95% CI = 1.0-1.0, p = 0.0002) in serum in validation cohorts, with some commonality across tissues, as the model trained on serum sample also discriminated CSF samples of controls versus KLS cases. Our study identifies proteomic KLS biomarkers with diagnostic potential and provides insight into biological mechanisms that will guide future research in KLS. Show less

Beta cell failure and apoptosis following islet inflammation have been associated with autoimmune type 1 diabetes pathogenesis. As conveyors of biological active material, extracellular vesicles (EV) act as mediators in communication with immune effectors fostering the idea that EV from inflamed beta cells may contribute to autoimmunity. Evidence accumulates that beta exosomes promote diabetogenic responses, but relative contributions of larger vesicles as well as variations in the composition of the beta cell's vesiculome due to environmental changes have not been explored yet. Here, we made side-by-side comparisons of the phenotype and function of apoptotic bodies (AB), microvesicles (MV) and small EV (sEV) isolated from an equal amount of MIN6 beta cells exposed to inflammatory, hypoxic or genotoxic stressors. Under normal conditions, large vesicles represent 93% of the volume, but only 2% of the number of the vesicles. Our data reveal a consistently higher release of AB and sEV and to a lesser extent of MV, exclusively under inflammatory conditions commensurate with a 4-fold increase in the total volume of the vesiculome and enhanced export of immune-stimulatory material including the autoantigen insulin, microRNA, and cytokines. Whilst inflammation does not change the concentration of insulin inside the EV, specific Toll-like receptor-binding microRNA sequences preferentially partition into sEV. Exposure to inflammatory stress engenders drastic increases in the expression of monocyte chemoattractant protein 1 in all EV and of interleukin-27 solely in AB suggesting selective sorting toward EV subspecies. Functional Show less

Balanced chromosomal rearrangements associated with abnormal phenotype are rare events, but may be challenging for genetic counselling, since molecular characterisation of breakpoints is not performed routinely. We used next-generation sequencing to characterise breakpoints of balanced chromosomal rearrangements at the molecular level in patients with intellectual disability and/or congenital anomalies. Breakpoints were characterised by a paired-end low depth whole genome sequencing (WGS) strategy and validated by Sanger sequencing. Expression study of disrupted and neighbouring genes was performed by RT-qPCR from blood or lymphoblastoid cell line RNA. Among the 55 patients included (41 reciprocal translocations, 4 inversions, 2 insertions and 8 complex chromosomal rearrangements), we were able to detect 89% of chromosomal rearrangements (49/55). Molecular signatures at the breakpoints suggested that DNA breaks arose randomly and that there was no major influence of repeated elements. Non-homologous end-joining appeared as the main mechanism of repair (55% of rearrangements). A diagnosis could be established in 22/49 patients (44.8%), 15 by gene disruption ( Paired-end WGS is a valid strategy and may be used for structural variation characterisation in a clinical setting. Show less

NALCN is a conserved cation channel, which conducts a permanent sodium leak current and regulates resting membrane potential and neuronal excitability. It is part of a large ion channel complex, the "NALCN channelosome", consisting of multiple proteins including UNC80 and UNC79. The predominant neuronal expression pattern and its function suggest an important role in neuronal function and disease. So far, biallelic NALCN and UNC80 variants have been described in a small number of individuals leading to infantile hypotonia, psychomotor retardation, and characteristic facies 1 (IHPRF1, OMIM 615419) and 2 (IHPRF2, OMIM 616801), respectively. Heterozygous de novo NALCN missense variants in the S5/S6 pore-forming segments lead to congenital contractures of the limbs and face, hypotonia, and developmental delay (CLIFAHDD, OMIM 616266) with some clinical overlap. In this study, we present detailed clinical information of 16 novel individuals with biallelic NALCN variants, 1 individual with a heterozygous de novo NALCN missense variant and an interesting clinical phenotype without contractures, and 12 individuals with biallelic UNC80 variants. We report for the first time a missense NALCN variant located in the predicted S6 pore-forming unit inherited in an autosomal-recessive manner leading to mild IHPRF1. We show evidence of clinical variability, especially among IHPRF1-affected individuals, and discuss differences between the IHPRF1- and IHPRF2 phenotypes. In summary, we provide a comprehensive overview of IHPRF1 and IHPRF2 phenotypes based on the largest cohort of individuals reported so far and provide additional insights into the clinical phenotypes of these neurodevelopmental diseases to help improve counseling of affected families. Show less

The origins of periodic leg movements (PLMs), a strong correlate of restless legs syndrome (RLS), are uncertain. This study was performed to assess the relationship between PLMs and peripheral iron deficiency, as measured with ferritin levels corrected for inflammation. We included a cross-sectional sample of a cohort study of 801 randomly selected people (n = 1008 assays, mean age 58.6 ± 0.3 years) from Wisconsin state employee agencies. A previously validated automatic detector was used to measure PLMs during sleep. The patients were categorized into RLS symptoms-positive and RLS symptoms-negative based on a mailed survey response and prior analysis. Analyses were performed using a linear model with PLM category above and below 15 PLM/h (periodic leg movement index, PLMI) as the dependent variable, and adjusting for known covariates, including previously associated single-nucleotide polymorphisms (SNPs) within BTBD9, TOX3/BC034767, MEIS1, MAP2K5/SKOR1, and PTPRD. Ferritin and C-reactive protein (CRP) levels were measured in serum, and ferritin levels corrected for inflammation using CRP levels. After controlling for cofactors, PLMI ≥ 15 was associated with low (≤50 ng/mL) ferritin levels (OR = 1.55, p = 0.020). The best model was found using quasi-least squares regression of ferritin as a function of PLMI, with an increase of 0.0034 PLM/h predicted by a decrease of 1 ng/mL ferritin (p = 0.00447). An association was found between low ferritin and greater PLMs in a general population of older adults, independent of genetic polymorphisms, suggesting a role of low iron stores in the expression of these phenotypes. Patients with high PLMI may require to be checked for iron deficiency. Show less

To examine association between periodic leg movements (PLM) and 13 single nucleotide polymorphisms (SNPs) in 6 loci known to increase risk of restless legs syndrome (RLS). Stanford Center for Sleep Sciences and Medicine and Clinical Research Unit of University of Wisconsin Institute for Clinical and Translational Research. Adult participants (n = 1,090, mean age = 59.7 years) from the Wisconsin Sleep Cohort (2,394 observations, 2000-2012). A previously validated automatic detector was used to measure PLMI. Thirteen SNPs within BTBD9, TOX3/BC034767, MEIS1 (2 unlinked loci), MAP2K5/SKOR1, and PTPRD were tested. Analyses were performed using a linear model and by PLM category using a 15 PLM/h cutoff. Statistical significance for loci was Bonferroni corrected for 6 loci (P < 8.3 × 10(-3)). RLS symptoms were categorized into four groups: likely, possible, no symptoms, and unknown based on a mailed survey response. Prevalence of PLMI ≥ 15 was 33%. Subjects with PLMs were older, more likely to be male, and had more frequent RLS symptoms, a shorter total sleep time, and higher wake after sleep onset. Strong associations were found at all loci except one. Highest associations for PLMI > 15/h were obtained using a multivariate model including age, sex, sleep disturbances, and the best SNPs for each loci, yielding the following odds ratios (OR) and P values: BTBD9 rs3923809(A) OR = 1.65, P = 1.5×10(-8); TOX3/BC034767 rs3104788(T) OR = 1.35, P = 9.0 × 10(-5); MEIS1 rs12469063(G) OR = 1.38, P = 2.0 × 10(-4); MAP2K5/SKOR1 rs6494696(G) OR = 1.24, P = 1.3×10(-2); and PTPRD(A) rs1975197 OR = 1.31, P = 6.3×10(-3). Linear regression models also revealed significant PLM effects for BTBD9, TOX3/BC034767, and MEIS1. Co-varying for RLS symptoms only modestly reduced the genetic associations. Single nucleotide polymorphisms demonstrated to increase risk of RLS are strongly linked to increased PLM as well, although some loci may have more effects on one versus the other phenotype. Show less