9 research outputs found
Genotypeâphenotype correlation in PRKN- associated Parkinsonâs disease
Bi-allelic pathogenic variants in PRKN are the most common cause of autosomal recessive Parkinsonâs disease (PD). 647 patients with PRKN-PD were included in this international study. The pathogenic variants present were characterised and investigated for their effect on phenotype. Clinical features and progression of PRKN-PD was also assessed. Among 133 variants in index cases (n = 582), there were 58 (43.6%) structural variants, 34 (25.6%) missense, 20 (15%) frameshift, 10 splice site (7.5%%), 9 (6.8%) nonsense and 2 (1.5%) indels. The most frequent variant overall was an exon 3 deletion (n = 145, 12.3%), followed by the p.R275W substitution (n = 117, 10%). Exon3, RING0 protein domain and the ubiquitin-like protein domain were mutational hotspots with 31%, 35.4% and 31.7% of index cases presenting mutations in these regions respectively. The presence of a frameshift or structural variant was associated with a 3.4 ± 1.6 years or a 4.7 ± 1.6 years earlier age at onset of PRKN-PD respectively (p < 0.05). Furthermore, variants located in the N-terminus of the protein, a region enriched with frameshift variants, were associated with an earlier age at onset. The phenotype of PRKN-PD was characterised by slow motor progression, preserved cognition, an excellent motor response to levodopa therapy and later development of motor complications compared to early-onset PD. Non-motor symptoms were however common in PRKN-PD. Our findings on the relationship between the type of variant in PRKN and the phenotype of the disease may have implications for both genetic counselling and the design of precision clinical trials
Genotype-phenotype correlation in PRKN-associated Parkinson's disease
Bi-allelic pathogenic variants in PRKN are the most common cause of autosomal recessive Parkinson's disease (PD). 647 patients with PRKN-PD were included in this international study. The pathogenic variants present were characterised and investigated for their effect on phenotype. Clinical features and progression of PRKN-PD was also assessed. Among 133 variants in index cases (nâ=â582), there were 58 (43.6%) structural variants, 34 (25.6%) missense, 20 (15%) frameshift, 10 splice site (7.5%%), 9 (6.8%) nonsense and 2 (1.5%) indels. The most frequent variant overall was an exon 3 deletion (nâ=â145, 12.3%), followed by the p.R275W substitution (nâ=â117, 10%). Exon3, RING0 protein domain and the ubiquitin-like protein domain were mutational hotspots with 31%, 35.4% and 31.7% of index cases presenting mutations in these regions respectively. The presence of a frameshift or structural variant was associated with a 3.4â±â1.6 years or a 4.7â±â1.6 years earlier age at onset of PRKN-PD respectively (pâ<â0.05). Furthermore, variants located in the N-terminus of the protein, a region enriched with frameshift variants, were associated with an earlier age at onset. The phenotype of PRKN-PD was characterised by slow motor progression, preserved cognition, an excellent motor response to levodopa therapy and later development of motor complications compared to early-onset PD. Non-motor symptoms were however common in PRKN-PD. Our findings on the relationship between the type of variant in PRKN and the phenotype of the disease may have implications for both genetic counselling and the design of precision clinical trials
Le problÚme des gÚnes de résistance à des antibiotiques dans les plantes transgéniques
National audienc
Régulation par les miARNs des gÚnes régulant la fécondité et le développement embryonnaire précoce chez le poisson médaka
International audienceOogenesis is based on highly regulated and coordinated biological processes involving gene interactions and gene regulation. During oogenesis, ovarian somatic cells undergo many transcriptional changes to prepare undifferentiated germ cells to form gametes. In this context, the regulatory role of microRNAs (miRNAs) is not well knownin fish. Previous studies have found miRNAs particularly expressed in the ovary, such as miR-202, whose KO causes a decrease in gamete quantity and quality. In order to better understand the molecular networks involved, we studied the transcriptomic profile of medaka ovaries (Oryzias latipes)during the reproductive cycle. After reads mapping, annotations were added to those of the reference genome to predict 1131 new long non-coding RNAs and 539 new messenger RNAs. An analysis of the differential expression(DE)reveals 2412 differentially expressed genes. Clustering identified relevant differential expression profiles suggesting a clear difference between the early stages of oogenesiscycle and later ones. In parallel, the analysis identified 37 miRNAs particularly expressed in germinal tissues and 197 in non-germinal tissues. Their targets were predicted and analyzed, suggesting that genes differentially expressed during oogenesis are preferentially targeted by germinal m iRNAs, in accordance with their regulatory role. Our results suggest that some miRNAs would regulate the expression of their targets differently during the oogenesis cycle.LâovogenĂšse repose sur des processus biologiques hautement rĂ©gulĂ©s et coordonnĂ©s impliquant des interactions gĂ©niques et la rĂ©gulation de gĂšnes. Au cours de lâovogenĂšse, les cellules somatiques ovariennes subissent de nombreux changements transcriptionnels afin de prĂ©parer les cellules germinales non diffĂ©renciĂ©es Ă former des gamĂštes. Dans ce contexte, le rĂŽle rĂ©gulateur des micro-ARNs (miARNs) est peu connu. Des Ă©tudes prĂ©cĂ©dentes ont permis de dĂ©couvrir des miARNs particuliĂšrement exprimĂ©s dans lâovaire, comme miR-202 dont le KO entraine une diminution de la quantitĂ© et de la qualitĂ© des gamĂštes. Dans le but de mieux comprendre les rĂ©seaux molĂ©culaires impliquĂ©s, nous avons Ă©tudiĂ© le profil transcriptomique dâovaires de medaka (Oryzias latipes) au cours du cycle de reproduction. AprĂšs alignement des lectures, des annotations ont Ă©tĂ© ajoutĂ©es Ă celles du gĂ©nome de rĂ©fĂ©rence permettant de prĂ©dire 1131 nouveaux longs ARNs non codants et 539 nouveaux ARN messagers. Une analyse du diffĂ©rentiel dâexpression (DE) au cours du cycle dâovogĂ©nĂšse met en Ă©vidence 2412 gĂšnes diffĂ©rentiellement exprimĂ©s. Un clustering a permis dâidentifier des profils dâexpression diffĂ©rentielle pertinents suggĂ©rant une nette diffĂ©rence entre les premiers temps de lâovogenĂšse et les temps plus tardifs. En parallĂšle, lâanalyse a permis dâidentifier 37 miARNs particuliĂšrement exprimĂ©s dans les tissus germinaux et 197 dans les tissus non germinaux. Leurs cibles ont Ă©tĂ© prĂ©dites et analysĂ©es, suggĂ©rant que les gĂšnes diffĂ©rentiellement exprimĂ©s au cours de lâovogĂ©nĂšse sont prĂ©fĂ©rentiellement ciblĂ©s par les miARNs germinaux, en accord avec leur rĂŽle de rĂ©gulateur. Nos rĂ©sultats permettent de proposer que certains miARNs rĂ©guleraient diffĂ©remment lâexpression de leurs cibles au cours du cycle dâovogenĂšse
RFLP profiles in low oleic sunflower using SDI-, a stearoyl-ACP, and an oleoyl-PC desaturases cDNAs
International audienc
Structuration of the genetic diversity in sunflower cultivars using RFLPs
National audienc
Differences in Survival across Monogenic Forms of Parkinson's Disease
International audienceObjective: Survival of patients with monogenic Parkinson's disease may depend on the causative genes associated with the disease. In this study, we compare survival of patients with Parkinson's disease according to the presence of SNCA, PRKN, LRRK2, or GBA mutations.Methods: Data from the French Parkinson Disease Genetics national multicenter cohort study were used. Patients with sporadic and familial Parkinson's disease were recruited between 1990 and 2021. Patients were genotyped for the presence of mutations in the SNCA, PRKN, LRRK2, or GBA genes. Vital status was collected from the National death register for participants born in France. Hazard ratios (HRs) and 95% confidence intervals (CIs) were computed using multivariable Cox proportional hazards regression.Results: Of the 2,037 patients with Parkinson's disease, 889 had died after a follow-up of up to 30 years. Patients with PRKN (n = 100, HR = 0.41; p = 0.001) and LRRK2 mutations (n = 51, HR = 0.49; p = 0.023) had longer survival than those without any mutation, whereas patients with SNCA (n = 20, HR = 9.88; p < 0.001) or GBA mutations (n = 173, HR = 1.33; p = 0.048) had shorter survival.Interpretation: Survival differs across genetic forms of Parkinson's disease, with higher mortality for patients with SNCA or GBA mutations, and lower mortality for those with PRKN or LRRK2 mutations. Differences in severity and disease progression among monogenic forms of Parkinson's disease likely explain these findings, which has important consequences for genetic counselling and choice of end points for future clinical trials for targeted therapies. ANN NEUROL 2023
TEAD Inhibitors Sensitize KRAS<sup>G12C</sup> Inhibitors via Dual Cell Cycle Arrest in KRAS<sup>G12C</sup>-Mutant NSCLC
KRASG12C is one of the most common mutations detected in non-small cell lung cancer (NSCLC) patients, and it is a marker of poor prognosis. The first FDA-approved KRASG12C inhibitors, sotorasib and adagrasib, have been an enormous breakthrough for patients with KRASG12C mutant NSCLC; however, resistance to therapy is emerging. The transcriptional coactivators YAP1/TAZ and the family of transcription factors TEAD1-4 are the downstream effectors of the Hippo pathway and regulate essential cellular processes such as cell proliferation and cell survival. YAP1/TAZ-TEAD activity has further been implicated as a mechanism of resistance to targeted therapies. Here, we investigate the effect of combining TEAD inhibitors with KRASG12C inhibitors in KRASG12C mutant NSCLC tumor models. We show that TEAD inhibitors, while being inactive as single agents in KRASG12C-driven NSCLC cells, enhance KRASG12C inhibitor-mediated anti-tumor efficacy in vitro and in vivo. Mechanistically, the dual inhibition of KRASG12C and TEAD results in the downregulation of MYC and E2F signatures and in the alteration of the G2/M checkpoint, converging in an increase in G1 and a decrease in G2/M cell cycle phases. Our data suggest that the co-inhibition of KRASG12C and TEAD leads to a specific dual cell cycle arrest in KRASG12C NSCLC cells