Parental breeding age effects on descendants' longevity interact over 2 generations in matrilines and patrilines

Individuals within populations vary enormously in mortality risk and longevity, but the causes of this variation remain poorly understood. A potentially important and phylogenetically widespread source of such variation is maternal age at breeding, which typically has negative effects on offspring longevity. Here, we show that paternal age can affect offspring longevity as strongly as maternal age does and that breeding age effects can interact over 2 generations in both matrilines and patrilines. We manipulated maternal and paternal ages at breeding over 2 generations in the neriid fly Telostylinus angusticollis. To determine whether breeding age effects can be modulated by the environment, we also manipulated larval diet and male competitive environment in the first generation. We found separate and interactive effects of parental and grand-parental ages at breeding on descendants' mortality rate and life span in both matrilines and patrilines. These breeding age effects were not modulated by grand-parental larval diet quality or competitive environment. Our findings suggest that variation in maternal and paternal ages at breeding could contribute substantially to intrapopulation variation in mortality and longevity

Analyse intégrative des données phénomiques, protéomiques et métabolomiques des maladies lysosomales

Inherited metabolic diseases (IMDs) are genetic disorders arising from abnormalities within specific biochemical pathways. These disorders result from the deficiency of an enzyme, its cofactor, or a transporter. Systems medicine (SM) is advancing biomedical research and healthcare by integrating multimodal data to better understand biological networks and improve patient stratification. Through datadriven strategies, SM is promising to enhance disease diagnosis, treatment, and prevention of IMDs. In this thesis, we employed a deep multiomics and phenomics approach combined with machine learning and network-based strategies to characterize two lysosomal diseases, a sub-group of IMDs. The first project studied Fabry disease (FD) and enabled the identification of plasma omics-based profiles (metabolites and proteins) that unambiguously separated FD patients from controls. Furthermore, we observed a tissue-wide functional remodeling of several processes, such as cytokine-mediated pathways, extracellular matrix, and vacuolar/lysosomal proteome. Our findings highlight the pro-inflammatory cytokines' involvement in FD pathogenesis along with extracellular matrix remodeling. The second project studied type 1 Gaucher disease (GD). The results showed promising plasma biological imprints in type 1 GD. The study revealed a significant disruption in lipid metabolism, inflammation, and mitochondrial function, potentially attributed to endoplasmic reticulum stress, impaired lipid trafficking, and inhibition of autophagy. As part of this thesis, we evaluated the analytical performance of a new volumetric micro-sampling blood collection device compared with dried blood spot for the assessment of lysosomal enzyme activity. In addition, a highthroughput method was developed to assess lysosphingolipids (biomarkers for sphingolipidosis). In summary, an integrative multiomics and phenomics approach was used to investigate two sphingolipidoses, revealing distinct biological imprints.Les maladies héréditaires du métabolisme (MHM) sont des affections génétiques résultant d'anomalies au sein de voies biochimiques spécifiques. Elles sont dues à un déficit d’une enzyme, de son cofacteur ou d'un transporteur. La médecine des systèmes (MS) est un moteur moderne pour la recherche biomédicale intégrant des données multimodales pour mieux comprendre les réseaux biologiques et améliorer la stratification des patients. Grâce à des stratégies basées sur la valorisation des données biomédicales et l’expertise clinique, la MS promet d'améliorer la prévention, diagnostic et le traitement des MHM. Dans cette thèse, nous avons adopté des approches multiomique et phénomique combinées à des stratégies d'apprentissage automatique et d’analyse des réseaux pour caractériser deux maladies lysosomales, maladie de Fabry (MF) et maladie de Gaucher (MD). Le premier projet a porté sur la MF et a permis d'identifier des profils omiques plasmatiques (métabolites et protéines) discriminant des patients Fabry. De plus, nous avons observé un remodelage métabolique de plusieurs processus biologiques, tels que les voies médiées par les cytokines, la matrice extracellulaire et le protéome vacuolaire/lysosomal. Nos découvertes mettent en évidence l'implication des cytokines pro-inflammatoires dans la pathogenèse de la MF, ainsi que la réorganisation de la matrice extracellulaire. Le deuxième projet a porté sur la MG de type 1. Les résultats ont révélé des empreintes biologiques plasmatiques. L'étude a révélé une perturbation significative du métabolisme des lipides, de l'inflammation et de la fonction mitochondriale, potentiellement attribuable au stress du réticulum endoplasmique, à un trafic lipidique altéré et à l'inhibition de l'autophagie. Dans le cadre de la thèse, nous avons évalué les performances analytiques d’un nouveau dispositif volumétrique de collecte de sang par micro-échantillonnage comparativement au sang séché sur buvard pour le dosage de l’activité des enzymes lysosomales. Par ailleurs, une méthode à haut débit a été développée pour évaluer les lysosphingolipides (biomarqueurs pour les sphingolipidoses). En résumé, une approche intégrative multiomique et phénomique a été utilisée pour étudier deux sphingolipidoses, révélant des empreintes plasmatiques biologiques spécifiques

Parsing Fabry Disease Metabolic Plasticity Using Metabolomics

Background: Fabry disease (FD) is an X-linked lysosomal disease due to a deficiency in the activity of the lysosomal α-galactosidase A (GalA), a key enzyme in the glycosphingolipid degradation pathway. FD is a complex disease with a poor genotype–phenotype correlation. FD could involve kidney, heart or central nervous system impairment that significantly decreases life expectancy. The advent of omics technologies offers the possibility of a global, integrated and systemic approach well-suited for the exploration of this complex disease. Materials and Methods: Sixty-six plasmas of FD patients from the French Fabry cohort (FFABRY) and 60 control plasmas were analyzed using liquid chromatography and mass spectrometry-based targeted metabolomics (188 metabolites) along with the determination of LysoGb3 concentration and GalA enzymatic activity. Conventional univariate analyses as well as systems biology and machine learning methods were used. Results: The analysis allowed for the identification of discriminating metabolic profiles that unambiguously separate FD patients from control subjects. The analysis identified 86 metabolites that are differentially expressed, including 62 Glycerophospholipids, 8 Acylcarnitines, 6 Sphingomyelins, 5 Aminoacids and 5 Biogenic Amines. Thirteen consensus metabolites were identified through network-based analysis, including 1 biogenic amine, 2 lysophosphatidylcholines and 10 glycerophospholipids. A predictive model using these metabolites showed an AUC-ROC of 0.992 (CI: 0.965–1.000). Conclusion: These results highlight deep metabolic remodeling in FD and confirm the potential of omics-based approaches in lysosomal diseases to reveal clinical and biological associations to generate pathophysiological hypotheses

Parsing Fabry Disease Metabolic Plasticity Using Metabolomics

International audienceBackground: Fabry disease (FD) is an X-linked lysosomal disease due to a deficiency in the activity of the lysosomal α-galactosidase A (GalA), a key enzyme in the glycosphingolipid degradation pathway. FD is a complex disease with a poor genotype–phenotype correlation. FD could involve kidney, heart or central nervous system impairment that significantly decreases life expectancy. The advent of omics technologies offers the possibility of a global, integrated and systemic approach well-suited for the exploration of this complex disease. Materials and Methods: Sixty-six plasmas of FD patients from the French Fabry cohort (FFABRY) and 60 control plasmas were analyzed using liquid chromatography and mass spectrometry-based targeted metabolomics (188 metabolites) along with the determination of LysoGb3 concentration and GalA enzymatic activity. Conventional univariate analyses as well as systems biology and machine learning methods were used. Results: The analysis allowed for the identification of discriminating metabolic profiles that unambiguously separate FD patients from control subjects. The analysis identified 86 metabolites that are differentially expressed, including 62 Glycerophospholipids, 8 Acylcarnitines, 6 Sphingomyelins, 5 Aminoacids and 5 Biogenic Amines. Thirteen consensus metabolites were identified through network-based analysis, including 1 biogenic amine, 2 lysophosphatidylcholines and 10 glycerophospholipids. A predictive model using these metabolites showed an AUC-ROC of 0.992 (CI: 0.965–1.000). Conclusion: These results highlight deep metabolic remodeling in FD and confirm the potential of omics-based approaches in lysosomal diseases to reveal clinical and biological associations to generate pathophysiological hypotheses

Dissecting Fabry disease biological plasticity using network-based metabolic phenotyping

International audienc

NGLY1 Deficiency: A Rare Newly Described Condition with a Typical Presentation

NGLY1 deficiency is the first recognized autosomal recessive disorder of N-linked deglycosylation (NGLY1-CDDG). This severe multisystemic disease is still poorly known and, to date, most cases have been diagnosed through whole exome or genome sequencing. The aim of this study is to provide the clinical, biochemical and molecular description of the first NGLY1-CDDG patient from France along with a literature review. The index case presented with developmental delay, acquired microcephaly, hypotonia, alacrimia, feeding difficulty, and dysmorphic features. Given the complex clinical picture and the multisystemic involvement, a trio-based exome sequencing was conducted and urine oligosaccharides were assessed using mass spectrometry. The exome sequencing revealed a novel variant in the NGLY1 gene in a homozygous state. NGLY1 deficiency was confirmed by the identification of the Neu5Ac1Hex1GlcNAc1-Asn oligosaccharide in the urine of the patient. Literature review revealed the association of some key clinical and biological features such as global developmental delay—hypertransaminasemia, movement disorders, feeding difficulties and alacrima/hypolacrima

NGLY1 Deficiency: A Rare Newly Described Condition with a Typical Presentation

NGLY1 deficiency is the first recognized autosomal recessive disorder of N-linked deglycosylation (NGLY1-CDDG). This severe multisystemic disease is still poorly known and, to date, most cases have been diagnosed through whole exome or genome sequencing. The aim of this study is to provide the clinical, biochemical and molecular description of the first NGLY1-CDDG patient from France along with a literature review. The index case presented with developmental delay, acquired microcephaly, hypotonia, alacrimia, feeding difficulty, and dysmorphic features. Given the complex clinical picture and the multisystemic involvement, a trio-based exome sequencing was conducted and urine oligosaccharides were assessed using mass spectrometry. The exome sequencing revealed a novel variant in the NGLY1 gene in a homozygous state. NGLY1 deficiency was confirmed by the identification of the Neu5Ac1Hex1GlcNAc1-Asn oligosaccharide in the urine of the patient. Literature review revealed the association of some key clinical and biological features such as global developmental delay—hypertransaminasemia, movement disorders, feeding difficulties and alacrima/hypolacrima

Integrative Metabolomics Reveals Deep Tissue and Systemic Metabolic Remodeling in Glioblastoma

(1) Background: Glioblastoma is the most common malignant brain tumor in adults. Its etiology remains unknown in most cases. Glioblastoma pathogenesis consists of a progressive infiltration of the white matter by tumoral cells leading to progressive neurological deficit, epilepsy, and/or intracranial hypertension. The mean survival is between 15 to 17 months. Given this aggressive prognosis, there is an urgent need for a better understanding of the underlying mechanisms of glioblastoma to unveil new diagnostic strategies and therapeutic targets through a deeper understanding of its biology. (2) Methods: To systematically address this issue, we performed targeted and untargeted metabolomics-based investigations on both tissue and plasma samples from patients with glioblastoma. (3) Results: This study revealed 176 differentially expressed lipids and metabolites, 148 in plasma and 28 in tissue samples. Main biochemical classes include phospholipids, acylcarnitines, sphingomyelins, and triacylglycerols. Functional analyses revealed deep metabolic remodeling in glioblastoma lipids and energy substrates, which unveils the major role of lipids in tumor progression by modulating its own environment. (4) Conclusions: Overall, our study demonstrates in situ and systemic metabolic rewiring in glioblastoma that could shed light on its underlying biological plasticity and progression to inform diagnosis and/or therapeutic strategies