Literature DB >> 26334954

Plasma N-Glycome Signature of Down Syndrome.

Vincenzo Borelli1, Valerie Vanhooren2,3, Emanuela Lonardi4, Karli R Reiding4, Miriam Capri1, Claude Libert2,3, Paolo Garagnani1,5, Stefano Salvioli1, Claudio Franceschi1,5,6,7, Manfred Wuhrer4,8,9.   

Abstract

In recent years, plasma N-glycans have emerged as biomarkers for health and disease. Here, we studied N-glycomic changes in Down Syndrome (DS). Because of the progeroid phenotype of DS, we focused on the dissection of syndrome- and aging-associated glycomic changes, as well as the interaction thereof. We analyzed the plasma N-glycome of 76 DS persons, 37 siblings (DSS), and 42 mothers (DSM) of DS persons by DNA-sequencer-aided, fluorophore-assisted-carbohydrate-electrophoresis, as well as by matrix-assisted laser desorption ionization-time-of-flight-mass spectrometry (MALDI-TOF-MS). The results showed an overall decrease of galactosylation and α2,3 sialylation, a concomitant increase of the level of fucosylated N-glycans as well as of monogalactosylated diantennary N-glycans in DS, while the GlycoAgeTest and the ratio of the two core-fucosylated, monogalactosylated diantennary isomers (galactose positioned on α1,6 arm versus α1,3 arm) were the strongest DS discriminators. Hypogalactosylation is a characteristic of both DS and aging of control individuals. A decrease in α2,3-sialylated species is also common to DS and aging of controls. However, regarding to α2,6-sialylated tri- and tetragalactosylated N-glycan species, we found those to be lowered in DS but showed an increase with age in the same persons, while these glycans were not affected by aging in control individuals. In conclusion, we identified specific glycomic changes associated with DS, aging in DS, as well as aging in controls, identifying glycomic features in line with accelerated aging in DS. Notably, our data demonstrate an aging phenotype in DS which only in part overlaps with aging in controls but reveals DS-specificity.

Entities:  

Keywords:  DSA-FACE; Down Syndrome; GlycoAgeTest; MALDI-TOF-MS; N-glycome; aging; ethyl esterification

Mesh:

Substances:

Year:  2015        PMID: 26334954     DOI: 10.1021/acs.jproteome.5b00356

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  21 in total

1.  The smell of longevity: a combination of Volatile Organic Compounds (VOCs) can discriminate centenarians and their offspring from age-matched subjects and young controls.

Authors:  Maria Conte; Giuseppe Conte; Morena Martucci; Daniela Monti; Laura Casarosa; Andrea Serra; Marcello Mele; Claudio Franceschi; Stefano Salvioli
Journal:  Geroscience       Date:  2019-12-05       Impact factor: 7.713

2.  Human Plasma N-glycosylation as Analyzed by Matrix-Assisted Laser Desorption/Ionization-Fourier Transform Ion Cyclotron Resonance-MS Associates with Markers of Inflammation and Metabolic Health.

Authors:  Karli R Reiding; L Renee Ruhaak; Hae-Won Uh; Said El Bouhaddani; Erik B van den Akker; Rosina Plomp; Liam A McDonnell; Jeanine J Houwing-Duistermaat; P Eline Slagboom; Marian Beekman; Manfred Wuhrer
Journal:  Mol Cell Proteomics       Date:  2016-12-08       Impact factor: 5.911

3.  Immunoglobulin G Glycosylation Changes in Aging and Other Inflammatory Conditions.

Authors:  Fabio Dall'Olio; Nadia Malagolini
Journal:  Exp Suppl       Date:  2021

4.  Fractionation and characterization of sialyl linkage isomers of serum N-glycans by CE-MS.

Authors:  Xiaomei Zhou; Woran Song; Milos V Novotny; Stephen C Jacobson
Journal:  J Sep Sci       Date:  2022-09       Impact factor: 3.614

5.  Glycosylation and Aging.

Authors:  Ana Cindrić; Jasminka Krištić; Marina Martinić Kavur; Marija Pezer
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 3.650

6.  Deep immune phenotyping reveals similarities between aging, Down syndrome, and autoimmunity.

Authors:  Katharina Lambert; Keagan G Moo; Azlann Arnett; Gautam Goel; Alex Hu; Kaitlin J Flynn; Cate Speake; Alice E Wiedeman; Vivian H Gersuk; Peter S Linsley; Carla J Greenbaum; S Alice Long; Rebecca Partridge; Jane H Buckner; Bernard Khor
Journal:  Sci Transl Med       Date:  2022-01-12       Impact factor: 19.319

Review 7.  Mass Spectrometry Approaches to Glycomic and Glycoproteomic Analyses.

Authors:  L Renee Ruhaak; Gege Xu; Qiongyu Li; Elisha Goonatilleke; Carlito B Lebrilla
Journal:  Chem Rev       Date:  2018-03-19       Impact factor: 60.622

8.  A pilot study on machine learning approach to delineate metabolic signatures in intellectual disability.

Authors:  Vidya Nikam; Suvidya Ranade; Naushad Shaik Mohammad; Mohan Kulkarni
Journal:  Int J Dev Disabil       Date:  2019-04-15

9.  Decreased epigenetic age of PBMCs from Italian semi-supercentenarians and their offspring.

Authors:  Steve Horvath; Chiara Pirazzini; Maria Giulia Bacalini; Davide Gentilini; Anna Maria Di Blasio; Massimo Delledonne; Daniela Mari; Beatrice Arosio; Daniela Monti; Giuseppe Passarino; Francesco De Rango; Patrizia D'Aquila; Cristina Giuliani; Elena Marasco; Sebastiano Collino; Patrick Descombes; Paolo Garagnani; Claudio Franceschi
Journal:  Aging (Albany NY)       Date:  2015-12       Impact factor: 5.682

10.  Effluent and serum protein N-glycosylation is associated with inflammation and peritoneal membrane transport characteristics in peritoneal dialysis patients.

Authors:  Evelina Ferrantelli; Karima Farhat; Agnes L Hipgrave Ederveen; Karli R Reiding; Robert H J Beelen; Frans J van Ittersum; Manfred Wuhrer; Viktoria Dotz
Journal:  Sci Rep       Date:  2018-01-17       Impact factor: 4.379

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