Glycomics and glycoproteomics focused on aging and age-related diseases — Glycans as a potential biomarker for physiological alterations

    Glycomics and glycoproteomics focused on aging and age-related diseases glycans as a potential biomarker for physiological alterations Yuri Miura, Tamao Endo PII: DOI: Reference:

S0304-4165(16)00022-2 doi: 10.1016/j.bbagen.2016.01.013 BBAGEN 28371

To appear in:

BBA - General Subjects

Received date: Revised date: Accepted date:

4 November 2015 13 January 2016 14 January 2016

Please cite this article as: Yuri Miura, Tamao Endo, Glycomics and glycoproteomics focused on aging and age-related diseases - glycans as a potential biomarker for physiological alterations -, BBA - General Subjects (2016), doi: 10.1016/j.bbagen.2016.01.013

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT 1

Glycomics and Glycoproteomics focused on Aging and Age-related

PT

Diseases - Glycans as a Potential Biomarker for Physiological

SC RI

Alterations -

NU

Yuri Miura & Tamao Endo*

MA

Research Team for Mechanism of Aging, Tokyo Metropolitan Institute of Gerontology, Tokyo

ED

173-0015, Japan

PT

*Corresponding author: Tamao Endo

CE

Research Team for Mechanism of Aging, Tokyo Metropolitan Institute of Gerontology 35-2 Sakaecho, Itabashi-ku, Tokyo 173-0015, Japan

AC

Tel: +81 3 3964 3241; Fax: +81 3 3579 4776; E-mail: [email protected]

ACCEPTED MANUSCRIPT 2

Abstract

PT

Background: Since glycosylation depends on glycosyltransferases, glycosidases, and sugar

SC RI

nucleotide donors, it is susceptible to the changes associated with physiological and pathological conditions. Therefore, alterations in glycan structures may be good targets and biomarkers for monitoring health conditions. Since human aging and longevity are affected by

NU

genetic and environmental factors such as diseases, lifestyle, and social factors, a scale that

MA

reflects various environmental factors is required in the study of human aging and longevity. Scope of Review: We herein focus on glycosylation changes elucidated by glycomic and

ED

glycoproteomic studies on aging, longevity, and age-related diseases including cognitive impairment, diabetes mellitus, and frailty. We also consider the potential of glycan structures as

PT

biomarkers and/or targets for monitoring physiological and pathophysiological changes.

CE

Major Conclusions: Glycan structures are altered in age-related diseases. These glycans and glycoproteins may be involved in the pathophysiology of these diseases and, thus, be useful

AC

diagnostic markers. Age-dependent changes in N-glycans have been reported previously in cohort studies, and characteristic N-glycans in extreme longevity have been proposed. These findings may lead to a deeper understanding of the mechanisms underlying aging as well as the factors influencing longevity. General Significance: Alterations in glycosylation may be good targets and biomarkers for monitoring health conditions, and be applicable to studies on age-related diseases and healthy aging.

Keywords; glycomics, glycoproteomics, glycosylation, aging, longevity, biomarker

ACCEPTED MANUSCRIPT 3

PT

Abbreviations;

SC RI

AD, Alzheimer’s disease; CGE-LIF, capillary gel electrophoresis with laser-induced fluorescence detection; CMP-SA, cytidine monophosphate-sialic acid; Con A, concanavalin A; CSF, cerebrospinal fluid; DS, Down syndrome; DSA-FACE, DNA sequencer-assisted,

FUT8,

-1,6-fucosyltransferase;

GAG,

glycosaminoglycan;

GDH,glutamate

MA

assay;

NU

fluorophore-assisted carbohydrate electrophoresis; ELISA, enzyme-linked immunosorbent

dehydrogenase; GFAP, glial fibrillary acidic protein; GnT-III, N-acetylglucosaminyltransferase

ED

III; GP96, glycoprotein 96; GWAS, genome-wide association study; HBP, hexosamine biosynthetic pathway; HILIC, hydrophilic interaction liquid chromatography; HNF1,

PT

hepatocyte nuclear factor 1 iNPH, idiopathic normal pressure hydrocephalus; LC-MS/MS,

CE

liquid chromatography-tandem mass spectrometry; MALDI-TOF, matrix-assisted laser desorption ionization time of flight; MCI, mild cognitive impairment; MS, mass spectrometry;

AC

PAP, placental anticoagulant protein; SSC, semisupercentenarian; T2DM, type 2 diabetes mellitus; UDP-GalNAc, uridine diphosphate-N-acetylgalactosamine; UDP-GlcNAc, uridine diphosphate-N-acetylglucosamine; WGA, wheat germ agglutinin; -1,4-GalT,-1,4-galactosyl transferase; 2D-PAGE, 2-dimensional polyacrylamide gel electrophoresis

ACCEPTED MANUSCRIPT 4

1. Introduction

PT

Aging is a complex biological process that has not yet been completely elucidated.

SC RI

Human aging and longevity are affected not only by genetic factors, but also by various environmental factors such as diseases, lifestyle, and social factors [1]. Social factors include various psychological factors, for example, personal relationships such as family, work, and

NU

various experiences, which may affect a number of biological functions, resulting in altered

MA

physiological and pathophysiological conditions (Fig. 1).

Cell-surface and secreted proteins are mostly decorated with sugar chains. Recent studies

ED

have suggested that glycans modify the functions of proteins and play important roles in intraand intercellular biological processes [2, 3]. In intercellular biological processes, glycans are

PT

involved in molecular recognition processes that occur in viral infections, cell adhesion in

CE

inflammation and tumor metastasis, and many other events. The sugar chains linked to proteins have been classified into 2 main groups: N-linked sugar chains, which are bound to the

AC

asparagine residue in a consensus sequence (Asn-X-Ser/Thr), and O-linked sugar chains, which are bound to the hydroxyl group of the serine or threonine residue. N-linked glycosylation (N-glycans) occurs in the endoplasmic reticulum, and involves the attachment of a lipid-linked precursor oligosaccharide to a protein, followed by the trimming of several monosaccharides by the actions of specific glycosidases and then further extension via a set of glycosyltransferases in the Golgi apparatus. O-linked glycosylation (O-glycans) also takes place in the Golgi apparatus

by the

stepwise

addition of

monosaccharides

via

a

different

set

of

glycosyltransferases. Glycosylation depends on the activities of glycosyltransferases and glycosidases in addition to the availability of sugar nucleotide donors [3]. Furthermore, glycan

ACCEPTED MANUSCRIPT 5

structures have a number of positional isomers and anomeric configurations including antennary

PT

branching. Therefore, glycan structures produced in the body are very diverse and

SC RI

heterogeneous.

A panel of glycosyltransferases, glycosidases, enzymes involved in sugar nucleotide biosynthesis, and nucleotide transporters participate in the biosynthesis of sugar chains. Since

NU

the activity and expression level of each enzyme are affected by pathological conditions,

MA

including cancer [4] and inflammatory diseases [5], the peripheral structures and branching of glycans are changed. Glycosylation is also affected by physiological conditions such as cell

ED

differentiation, cell morphogenesis, and tissue development; therefore, glycan structures may be good targets and biomarkers for monitoring health conditions and suitable as a scale to reflect

PT

human aging and longevity [6, 7].

CE

Technical difficulties are associated with obtaining precise structural information on glycans because their structures are very diverse and heterogeneous. However, several recently

AC

developed methods have allowed for the total spectrum of glycans in the serum and body fluids of a large number of individuals to be examined as described later. In order to address the potential of glycan structures as biomarkers of health conditions, Gornik et al. examined the stability of N-glycan structures (N-glycomics) in the plasma of healthy individuals [8]. Hydrophilic interaction liquid chromatography (HILIC)-HPLC revealed the stability of N-glycomics between different blood collection times within an individual. Accordingly, if changes are detected in glycomics, they may be as a consequence of physiological or pathological responses, suggesting the high diagnostic potential of glycomic studies for aging-related diseases and aging in humans.

ACCEPTED MANUSCRIPT 6

We herein review alterations in glycosylation with aging-related diseases, aging, and

PT

longevity as elucidated by glycomic and glycoproteomic analyses. We also discuss the potential

SC RI

of glycans as biomarkers of health conditions.

2. Glycomics and glycoproteomics

NU

“Glycomics” is defined as the comprehensive analysis of glycan structures released

MA

from glycoproteins (Fig. 2). N-glycomics is performed more frequently than O-glycomics because N-glycans are released from proteins by a treatment with PNGase F. The resulting free

2-aminobezoic

acid

ED

N-glycans are labeled with fluorescent reagents such as 2-aminopyridine (PA) [9], (2-AA)

[10],

2-aminobenzamide

(2-AB)

[11],

and

PT

8-aminopyrene-1,3,6-trisulfonic acid (APTS) [12], followed by high-throughput analyses

CE

including HILIC-HPLC [10, 11, 13-17] and DNA sequencer-assisted, fluorophore-assisted carbohydrate electrophoresis (DSA-FACE) [12, 18-23]. Other high-throughput analyses include

AC

mass spectrometry (MS)-equipped methods such as matrix-assisted laser desorption ionization time of flight-MS (MALDI-TOF/MS) [24] and liquid chromatography-tandem MS (LC-MS/MS) [25]. MS analyses of glycans with or without fluorescent labeling provide molecular mass and structural information. If several possible isomers are present, each one may be discriminated from the others using multistage analyses (MSn). Since the glycans released from proteins are analyzed in glycomic studies, it is impossible to determine which proteins these glycans are attached to. However, glycans frequently affect the function of carrier proteins; therefore, information on proteins is essential for understanding the role of their glycans. Taken together, these findings indicate that an

ACCEPTED MANUSCRIPT 7

analysis of glycans and proteins is important for establishing the functions of glycoproteins,

PT

defined as “Glycoproteomics” (Fig. 2). Lectins are invaluable for glycoproteomics and are very

SC RI

useful for grouping glycoproteins on the basis of glycan-binding specificities [26]; for example, concanavalin A (Con A) binds to -linked mannosyl and glucosyl glycans, wheat germ agglutinin (WGA) binds to GlcNAc and sialic acid, and Jacalin lectin binds to galactosyl

NU

moieties coupled to N-acetylgalactosamine (GalNAc) via a (1,3) linkage. A group of

MA

glycoproteins is enriched using lectin-affinity chromatography, followed by a proteomics analysis such as 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE) [27-30]. The

ED

glycoprotein-specific gel and blot stain, ProQ®-Emerald, recently became commercially available. Therefore, 2D-PAGE has become a powerful tool in glycoproteomics and proteomics

PT

[31, 32]. Furthermore, LC-MS/MS is useful in glycoproteomics because the structures of

CE

glycans and identification of proteins are determined simultaneously [25, 32] (Fig. 2). On the other hand, a lectin microarray, in which a panel of lectins with different glycan-binding

AC

specificities is immobilized on a plate, is a useful tool for the rapid and highly sensitive analysis of glycoproteins [33-35].

3. Age-related diseases The relationship between glycan structures and diseases has been reviewed previously, for example, cancer [36-40]. We herein focus on glycomics and glycoproteomics in age-related diseases including cognitive impairment, diabetes mellitus, and frailty. 3.1 Cognitive impairment

ACCEPTED MANUSCRIPT 8

3.1.1 Alzheimer’s disease

PT

Alzheimer’s disease (AD) is the most common type of cognitive impairment in the

SC RI

elderly and is characterized by the accumulation of protein debris, namely, senile plaques and neurofibrillary tangles. The number of AD patients has reached 24 million worldwide, and diagnostic methods and preventive care are urgently required in addition to effective therapeutic

NU

approaches. Since the glycosylation of proteins is involved in proper protein folding, protein

MA

quality control, and the transport of proteins to specific organelles, glycosylation may be associated with the pathophysiology of AD and mild cognitive impairment (MCI). The glycosylation of several proteins involved in the pathology of AD such as the amyloid precursor

ED

protein (APP) [41, 42], -site APP-cleaving enzyme 1 (BACE-1) [43], nicastrin [44, 45], and

PT

Tau [46], has been investigated [47]. Alterations in the glycosylation of transferrin have also

CE

been reported in the serum of AD patients [48, 49]. However, studies on comprehensive glycomics and glycoproteomics with a focus on

AC

AD have been limited. Kanninen et al. performed a glycoproteomic study on cytosolic proteins in AD brains using 2D-PAGE, and found that glycosylation of the glial fibrillary acidic protein (GFAP) was enhanced in AD, while that of collapsin response mediator protein 2 (CRMP-2) was suppressed [31]. The glycosyl pattern of 1-antitrypsin was shown to be altered in the cerebrospinal fluid (CSF) of AD patients using LC-MS/MS [32]. Another method is the enrichment of glycoproteins by lectin chromatography followed by 2D-PAGE and protein identification with MS [27-29]. Butterfield and co-workers examined alterations in the Con Aand WGA-fractionated proteins of the hippocampus and inferior parietal lobule of AD patients and MCI patients. They found changes in the levels of several glycoproteins. For example,

ACCEPTED MANUSCRIPT 9

metabolic proteins (GDH and -enolase), chaperone proteins (HSP90 and GP96), cytoskeletal

PT

proteins (GFAP and 14-3-3 proteins), and synaptic proteins (-synuclein) were altered in the AD

SC RI

hippocampus. Since 14-3-3 proteins are known to interact with neurofibrillary tangles, they speculated that changes in the glycosylation of 14-3-3 proteins are associated with the pathogenesis of AD. On the other hand, the up-regulated expression of GFAP is a characteristic

NU

feature of reactive astrocytes that is associated with tangles, neuritic plaques, and A pathology

MA

[50]. Furthermore, the expression of GFAP was shown to be increased in the cerebrum of AD [51]. Glycosylated GFAP is known to be enhanced in AD [27, 31]; however, the effects of

ED

glycosylation on GFAP function and AD pathology currently remain unclear. Further studies are needed in order to address the pathological meaning of protein glycosylation changes in the AD

CE

PT

brain.

3.1.2 Idiopathic normal pressure hydrocephalus

AC

Idiopathic normal pressure hydrocephalus (iNPH) is a cognitive impairment in the elderly that is caused by abnormal metabolism in the CSF. Since iNPH patients have dementia and ventriculomegaly, similar to AD patients, a useful index is required for a differential diagnosis between AD and iNPH. Futakawa et al. analyzed the glycosylation of transferrin in the CSF using a lectin microarray, and found two glycosylation isoforms of transferrin. Isoform 1 has a unique biantennary GlcNAc-terminated glycan, while isoform 2 has 2,6-sialylglycan, similar to serum transferrin. Since the ratio of isoform 2 to isoform 1 is higher in iNPH than in non-iNPH patients, including AD, they proposed this ratio as a pathogenic index, which may have the ability to distinguish iNPH from AD [52]. Further studies are needed in order to

ACCEPTED MANUSCRIPT 10

determine the relationship between changes in the ratio of isoform 2 to isoform 1 as well as its

SC RI

PT

pathological implications.

3.2 Diabetes mellitus

Diabetes mellitus has been classified into 2 categories, type 1 and type 2. Type 2

NU

(T2DM) is a complex and heterogeneous disease that is characterized by chronic hyperglycemia,

MA

insulin resistance, and relative insulin-secreting defects. Although obesity and a sedentary lifestyle have been correlated with T2DM, many aspects of the biochemical pathways involved

ED

remain unknown. Ito et al. [53] reported that -1,6-fucosylated biantennary glycan levels were increased in the serum of db/db mice, which are a model of T2DM, and also found elevations in

PT

-1,6-fucosyltransferase (FUT8) mRNA levels in the livers of these mice. They subsequently

CE

analyzed serum N-glycan profiles in human subjects with T2DM and reported an increase in the levels of a biantennary N-glycan that contained an 1,6-fucose with a bisecting GlcNAc. Based

AC

on these findings, they speculated that changes in T2DM patients were caused, at least partially, by enhanced FUT8 levels in the liver. Elevations have also been reported in fucose in the glycoproteins of diabetic subjects; however, the fucosyl linkage was not determined [54]. Testa et al. [23] performed N-glycomics on serum proteins in T2DM and metabolic syndrome patients using DSA-FACE, and detected significant changes in the composition of N-glycans in serum between T2DM patients and non-diabetic controls. They found that the levels of the isomer, -1,6 or -1,3-monogalactosylated, core--1,6-fucosylated biantennary glycan (NG1(6)A2F or NG1(3)A2F), were significantly lower in T2DM patients, and that this decrease was enhanced in T2DM patients with complications such as neuropathy, nephropathy,

ACCEPTED MANUSCRIPT 11

or/and retinopathy. Regarding decreases in NG1(6)A2F in T2DM, they speculated the following.

PT

The activity of -1,4-galactosyltransferase (GalT) initially increases in diabetic patients with

SC RI

complications [55]. NG1(6)A2F is then galactosylated to form a digalactosylated glycan, which decreases NG1(6)A2F. Furthermore, this decrease in NG1(6)A2F has also been detected in patients with metabolic syndrome, suggesting that metabolic syndrome and T2DM are similar

MA

NU

pathological conditions [23].

3.3 Frailty

ED

Frailty is a geriatric syndrome characterized by progressive physical decline including unintentional weight loss, muscle weakness, low activity levels, exhaustion, and a slow gait. Its

PT

pathology is widely observed in elderly people, even with individual differences, and ultimately

CE

increases the risk of disability, hospitalization, and mortality. Therefore, frailty is considered an important clinical and public health issue that needs to be resolved. The etiology of frailty

AC

requires further studies in order to identify high risk individuals. An epidemiological study revealed a correlation between frailty and inflammation markers (such as CRP and fibrinogen), metabolic markers (LDL cholesterol), and clotting process markers (including the D-dimer and the placental anticoagulant protein (PAP) complex). Sarcopenia, osteopenia, anorexia, immune dysfunction, and neuroendocrine dysregulation have also been implicated in frailty [56, 57]. Shamsi et al. focused on changes in glycoproteins with frailty, and performed a glycoproteomic study on plasma from frail subjects and age-matched controls using a lectin column and 2D-PAGE [30]. They enriched glycoproteins from plasma, which bound to Con A, WGA, or Jacalin, and found that seven glycoproteins (haptoglobin, transferrin, an isoform of

ACCEPTED MANUSCRIPT 12

the kininogen-1 variant, the hemopexin precursor, fibrinogen, leucin-rich -2-glycoprotein 1,

PT

and apolipoprotein E) differed by at least two-fold between the pre-frail group and non-frail

SC RI

group. They then validated the expression levels of these glycoproteins using ELISA, and suggested that inflammatory glycoproteins increased with frailty [58]. Furthermore, a comparison of the pre-frail and non-frail groups showed a decrease in Jacalin-bound hemopexin,

NU

no change in WGA-bound hemopexin, and an acidic shift in the isoelectric point of the

MA

Jacalin-bound kininogen-1 variant [30]. These findings suggest that the O-glycosylation (Gal3GalNAc) of hemopexin and the kininogen-1 variant change with frailty. A

ED

glycosylation biomarker of frailty will provide a useful means for identifying high risk

PT

individuals.

CE

4. Aging

Recent advances in glycan research on human aging including progeroid syndromes is

AC

described here.

4.1 Progeroid syndromes Progeroid-type Ehlers-Danlos syndrome was reported to be caused by defects in galactosyltransferase [59], which is involved in the synthesis of the common linkage region of glycosaminoglycans (GAGs). GAGs are sugar structures of different lengths, different types, and varying numbers of proteoglycan molecules. The synthesis of GAGs is initiated by the transfer of xylose on Ser in the core protein. The sequential addition of two galactoses, and a glucuronic acid forms a common tetrasaccharide core structure. Further elongation by GlcNAc or GalNAc to the common linkage structure leads to the formation of heparin sulfate or

ACCEPTED MANUSCRIPT 13

chondroitin sulfate/dermatan sulfate, respectively. Therefore, defects in the formation of the

PT

common linkage region may cause serious abnormalities in many tissues because proteoglycans

SC RI

play important roles in organogenesis and tissue development. Okajima et al. reported that mutations in the galactosyltransferase gene produced functional defects in proteins [60], indicating that GAGs are involved in the aging process. The relationship between glycans and

NU

other progeroid syndromes such as Hutchinson-Gilford progeria syndrome and Werner

MA

syndrome has not yet been elucidated.

Down syndrome (DS) is the most frequent chromosomal aberration in humans and is

ED

caused by trisomy of all or part of chromosome 21. DS is also characterized by a premature neurocognitive deficit and accelerated aging. Borelli et al. studied N-glycomics associated with

PT

the aging of DS and reported an overall decrease in galactosylation levels in plasma proteins

CE

similar to normal aging as described later. However, they found that this common change occurred markedly earlier in DS than in controls. On the other hand, they showed that the levels

AC

of -2,6-sialylated tri- and tetragalactosylated N-glycan were lower in DS than in controls. Based on these findings, they suggested that the progeroid nature of DS is detectable by analyzing plasma N-glycomics [61].

4.2 Age-dependent alterations in N-glycans of immunoglobulin Age-related alterations in the N-glycans of immunoglobulin have been reported by several groups. Parekh et al. analyzed the N-glycans of IgG and found that the levels of agalactosylated N-glycans began decreasing from birth to approximately 25 years of age, and thereafter increased with age [62]. They proposed the potential of the galactosylation of IgG as

ACCEPTED MANUSCRIPT 14

an age-related molecular parameter. Tsuchiya et al. also reported age-related increases in

PT

agalactosylated IgG from 20 to 70 years of age using Psathyrella velutina lectin, which

SC RI

preferentially interacts with agalactosylated moieties [63]. Shikata et al. and Yamada et al. performed glycan structural analyses using fluorescence labels and HPLC, and found positive and negative correlations between age and glycans with a bisecting GlcNAc or mono-sialylation,

NU

respectively [64, 65]. Age-related alterations in the N-glycomics of IgG or IgA were recently

MA

identified using high-throughput methods such as HILIC [17], MALDI-TOF/MS [66], DSA-FACE [19], and capillary gel electrophoresis with laser-induced fluorescence detection

ED

(CGE-LIF) [67]. These findings are consistent with the increases observed in agalactosylated and bisecting GlcNAc levels in IgG and decreases in sialylation with age. Bisecting GlcNAc

PT

levels were found to be lower in the offspring (age < 60 years) of nonagenarians, indicating the

CE

potential of bisecting GlcNAc in IgG N-glycans as a longevity marker [24]. A follow-up of individual offspring is awaited in order to determine whether they will also have long lifespans.

AC

Regarding IgA, age-related alterations have been weakly detected in N-glycans, with only core fucosylated biantennary glycans with bisecting GlcNAc increasing with age [67]. These findings indicate that age-dependent alterations in the N-glycans of immunoglobulin are different in each immunoglobulin class. Since structural changes in the N-glycans of IgG are associated with their functions, they may affect the immunoregulatory system in the elderly.

4.3 Age-dependent N-glycomic changes in plasma or serum glycoproteins N-glycomics derived from the total glycoprotein pool in plasma or serum were analyzed using high-throughput methods such as HILIC and DSA-FACE. Three groups have studied

ACCEPTED MANUSCRIPT 15

age-dependent N-glycomic changes in large cohorts using different methods of analyses.

PT

The Leiden Longevity Study consisted of Caucasian nonagenarian (age 90 years)

SC RI

sibling pairs, their offspring, and the partners of the offspring, who served as controls. Using the HILIC-HPLC-FL method, 26 peaks were detected in plasma glycoproteins, while increases were observed in agalactosylated glycans and decreases in core-fucosylated non- or

NU

mono-sialylated bigalactosylated glycans with age (between 30 and 80 years). Furthermore,

MA

triantennary trisialylated glycans decreased with age, whereas their fucosylated counterparts and several tetraantennary glycans increased. Since nonfucosylated biantennary glycans were

ED

significantly higher in the offspring of nonagenarians than in the controls [10], these glycans were proposed to be familial longevity-associated glycans.

PT

The Belgian and Italian cohort consisted of healthy individuals aged 20 to 90 years and

CE

centenarians (range: 91-105 years) [20, 68, 69]. Changes in total N-glycan profiles were analyzed in serum using DSA-FACE. They detected 10 peaks and suggested that

AC

agalactosylated glycans with (A) or without (B) bisecting GlcNAc increased, whereas digalactosylated glycans without bisecting GlcNAc (C) decreased with age up to centenarians. Similar findings were also obtained from Chinese cohorts [21]. Thus, as a biomarker to monitor age, Vanhooren et al. proposed the name of the GlycoAgeTest, which is calculated by the log value of the ratio of B/C and may be applicable to a larger population scale in cohorts [20]. The third cohorts were the Croatian Adriatic island of Vis and Korcula cohort and Chinese Han cohort. Knezevic et al. analyzed 33 peaks in N-glycans using HILIC, and examined the effects of age, gender, and various environmental determinants on plasma glycomics. Their findings of age-dependent alterations were consistent with those of other

ACCEPTED MANUSCRIPT 16

cohorts, namely, increases in biantennary agalactosylated or mono-galactosylated glycans with

PT

and without bisecting GlcNAc and/or fucosylation [11, 14, 70].

SC RI

Structural changes may occur as the result of alterations in the levels of glycosyltransferases, glycosidases, and sugar nucleotide donors. Age-dependent increases in agalactosylated glycans may be attributed to decreases in the activity of -1,4-galactosyl

NU

transferase (-1,4-GalT) or increases in that of -galactosidase during age [19]. Bisecting GlcNAc is generated by N-acetylglucosaminyltransferase III (GnT-III), which catalyzes the

MA

addition of GlcNAc through a -1,4-linkage to the -linked mannose of the trimannosyl core of

ED

N-linked sugar chains. Therefore, age-dependent increases in the bisecting GlcNAc of IgG [64, 65] suggest that GnT-III is up-regulated with age. Lauc et al. performed a genome-wide

PT

association study (GWAS) of glycosylation. They did not find a gene association between

CE

-1,4-GalT, -galactosidase, or GnT-III and human N-glycomics, but demonstrated that hepatocyte nuclear factor 1 (HNF1) and the fucosyltransferase genes, FUT6 and FUT8,

AC

influenced N-glycan levels in human plasma [71]. They extended their analyses further and identified three characteristic gene associations, MGAT5, B3GAT1, and SLC9A9 [72]. We will discuss this point later.

4.4 N-Glycomics relating to extreme longevity Shimizu et al. previously reported that blood type B was observed more frequently in centenarians living in the Tokyo area than in regionally matched controls [73]. This finding suggests that ABO blood glycans are closely related to human longevity; however, further studies are needed.

ACCEPTED MANUSCRIPT 17

We recently performed a N-glycomic study on plasma relating to longevity [25]. Plasma

PT

N-glycans in Japanese female semisupercentenarians (SSCs) (mean 106.7 years), aged controls

SC RI

(mean 71.6 years), and young controls (mean 30.2 years) were analyzed using LC-MS/MS, and 50 N-glycans containing multiple isomers were detected in the positive and negative ion modes. Using a multivariate analysis, orthogonal projections to latent structures (O-PLS), characteristic

NU

N-glycans in SSCs, were identified. These findings showed that multi-branched and highly

MA

sialylated N-glycans as well as agalacto- and/or bisecting N-glycans were increased in SSCs, whereas biantennary N-glycans were decreased. The increases observed in multi-branched and

ED

highly sialylated N-glycans in SSCs were not reported in other aging studies. Therefore, these changes may be associated with extreme longevity. Since multi-branched and highly sialylated

PT

N-glycans have been implicated in inflammation responses, these changes may play a role in

CE

responses to enhanced chronic inflammation in SSCs. However, further studies with a bigger cohort including male subjects are necessary because a limited number of female subjects were

AC

analyzed in the study.

Life is considered to always be associated with genes [74], and previous studies attempted to discover the genetic basis of extreme longevity [75, 76]. A GWAS of N-glycomes in human plasma revealed polymorphisms in several glycan-associated genes [72]; one was MGAT5, which codes for the enzyme involved in the generation of multi-branched N-glycans, while another was SLC9A9, which codes for a proton pump affecting Golgi pH linked to the sialylation of glycans. It is of interest that the glycosyltransferases implicated in the characteristic N-glycans in SSCs, multi-branched and highly sialylated N-glycans, were detected in the GWAS of N-glycomes in human plasma. Further studies are warranted in order to

ACCEPTED MANUSCRIPT 18

determine whether these genes show any polymorphisms in SSCs, the findings of which may

SC RI

PT

contribute to a better understanding of the roles of glycans in human extreme longevity.

5. Future perspectives

Alterations in N-glycans occur with aging and age-related diseases. Therefore, some

NU

age-related glycans may be good targets and the most potent markers of aging and age-related

MA

diseases. Further studies are needed in order to establish and refine glycan markers, including the development of a convenient and high-throughput tool, which is important for analyzing a

ED

large number of samples instantly.

Glycosylation depends on the availability of sugar nucleotide donors as described

PT

already. Between 2 and 5% of all the glucose that enters a cell is known to be utilized in the

CE

hexosamine biosynthetic pathway (HBP) and many studies demonstrated that the HBP functions as a glucose sensor. UDP-GlcNAc is the final product of the HBP and is required in the

AC

biosynthesis of N- and O-glycans, glycolipids, hyaluronic acid, and GAGs. UDP-GlcNAc is also a precursor to CMP-SA, the sugar nucleotide donor utilized by sialyltransferases, and UDP-GlcNAc is interconverted with UDP-GalNAc. These findings suggest that the amount of sugar nucleotide donors is affected by glucose levels. Therefore, glycosylation may act as a nutrient sensor. UDP-GlcNAc is known to be a donor for O-GlcNAcylation, which occurs on many cytosolic and nuclear proteins, and actually O-GlcNAcylation is nutrient-responsive and plays multiple roles in metabolic regulation [77]. Additionally, N-glycan branching also regulates glucose homeostasis [78, 79]. Further studies are required in order to determine how O-GlcNAcylation, N-glycan processing, and the HBP interact during aging.

ACCEPTED MANUSCRIPT 19

The world is forecast to become an aging society in the near future. Therefore, the

PT

successful development of biomarkers for aging and age-related diseases will be useful for

SC RI

personalized medicine and resolving social issues in the ever-approaching aging society. Glycans have potential as biomarkers because they reflect the physiological and pathological conditions of individuals. Although aging is inevitable, the development of biomarkers for aging

NU

and age-related diseases may lead to improved treatments and the better management of care

MA

through the monitoring of individual vulnerabilities to adverse health outcomes in advance.

ED

Acknowledgments

Our cited studies in this review were partly supported by Challenging Exploratory

PT

Research (No. 24659141 to TE) from the Japan Society for the Promotion of Science, and partly

CE

by Mitsui Sumitomo Insurance Welfare Foundation (No. 18 to YM).

AC

Conflict of interest None

References [1] D. Rizzuto, L. Fratiglioni, Lifestyle factors related to mortality and survival: a mini-review, Gerontology 60 (2014) 327-335. [2] G.W. Hart, R.J. Copeland, Glycomics hits the big time, Cell 143 (2010) 672-676. [3] K. Ohtsubo, J.D. Marth, Glycosylation in cellular mechanisms of health and disease, Cell 126 (2006) 855-867.

ACCEPTED MANUSCRIPT 20

[4] K.S. Lau, J.W. Dennis, N-Glycans in cancer progression, Glycobiology 18 (2008) 750-760.

PT

[5] S. Bohm, D. Kao, F. Nimmerjahn, Sweet and sour: the role of glycosylation for the

SC RI

anti-inflammatory activity of immunoglobulin G, Curr. Top. Microbiol. Immunol. 382 (2014) 393-417.

[6] F. Dall'Olio, V. Vanhooren, C.C. Chen, P.E. Slagboom, M. Wuhrer, C. Franceschi, N-glycomic

NU

biomarkers of biological aging and longevity: a link with inflammaging, Ageing Res. Rev. 12

MA

(2013) 685-698.

[7] Y. Sato, T. Endo, Alteration of brain glycoproteins during aging, Geriatr. Gerontol. Int. 10

ED

Suppl 1 (2010) S32-40.

[8] O. Gornik, J. Wagner, M. Pucic, A. Knezevic, I. Redzic, G. Lauc, Stability of N-glycan

PT

profiles in human plasma, Glycobiology 19 (2009) 1547-1553.

CE

[9] H. Korekane, K. Shida, K. Murata, M. Ohue, Y. Sasaki, S. Imaoka, Y. Miyamoto, Evaluation of laser microdissection as a tool in cancer glycomic studies, Biochem. Biophys. Res.

AC

Commun. 352 (2007) 579-586. [10] L.R. Ruhaak, H.W. Uh, M. Beekman, C.H. Hokke, R.G. Westendorp, J. Houwing-Duistermaat, M. Wuhrer, A.M. Deelder, P.E. Slagboom, Plasma protein N-glycan profiles are associated with calendar age, familial longevity and health, J. Proteome Res. 10 (2011) 1667-1674. [11] A. Knezevic, O. Gornik, O. Polasek, M. Pucic, I. Redzic, M. Novokmet, P.M. Rudd, A.F. Wright, H. Campbell, I. Rudan, G. Lauc, Effects of aging, body mass index, plasma lipid profiles, and smoking on human plasma N-glycans, Glycobiology 20 (2010) 959-969. [12] W. Laroy, R. Contreras, N. Callewaert, Glycome mapping on DNA sequencing equipment,

ACCEPTED MANUSCRIPT 21

Nat. Protoc. 1 (2006) 397-405.

PT

[13] L.R. Ruhaak, C. Huhn, W.J. Waterreus, A.R. de Boer, C. Neususs, C.H. Hokke, A.M.

SC RI

Deelder, M. Wuhrer, Hydrophilic interaction chromatography-based high-throughput sample preparation method for N-glycan analysis from total human plasma glycoproteins, Anal. Chem. 80 (2008) 6119-6126.

NU

[14] A. Knezevic, O. Polasek, O. Gornik, I. Rudan, H. Campbell, C. Hayward, A. Wright, I.

MA

Kolcic, N. O'Donoghue, J. Bones, P.M. Rudd, G. Lauc, Variability, heritability and environmental determinants of human plasma N-glycome, J. Proteome Res. 8 (2009)

ED

694-701.

[15] M. Wuhrer, A.R. de Boer, A.M. Deelder, Structural glycomics using hydrophilic interaction

PT

chromatography (HILIC) with mass spectrometry, Mass Spectrom. Rev. 28 (2009) 192-206.

CE

[16] M. Pucic, S. Pinto, M. Novokmet, A. Knezevic, O. Gornik, O. Polasek, K. Vlahovicek, W. Wang, P.M. Rudd, A.F. Wright, H. Campbell, I. Rudan, G. Lauc, Common aberrations from

AC

the normal human plasma N-glycan profile, Glycobiology 20 (2010) 970-975. [17] M. Pucic, A. Knezevic, J. Vidic, B. Adamczyk, M. Novokmet, O. Polasek, O. Gornik, S. Supraha-Goreta, M.R. Wormald, I. Redzic, H. Campbell, A. Wright, N.D. Hastie, J.F. Wilson, I. Rudan, M. Wuhrer, P.M. Rudd, D. Josic, G. Lauc, High throughput isolation and glycosylation analysis of IgG-variability and heritability of the IgG glycome in three isolated human populations, Mol. Cell. Proteomics 10 (2011) M111 010090. [18] N. Callewaert, S. Geysens, F. Molemans, R. Contreras, Ultrasensitive profiling and sequencing of N-linked oligosaccharides using standard DNA-sequencing equipment, Glycobiology 11 (2001) 275-281.

ACCEPTED MANUSCRIPT 22

[19] V. Vanhooren, L. Desmyter, X.E. Liu, M. Cardelli, C. Franceschi, A. Federico, C. Libert, W.

SC RI

human aging, Rejuvenation Res. 10 (2007) 521-531a.

PT

Laroy, S. Dewaele, R. Contreras, C. Chen, N-glycomic changes in serum proteins during

[20] V. Vanhooren, S. Dewaele, C. Libert, S. Engelborghs, P.P. De Deyn, O. Toussaint, F. Debacq-Chainiaux, M. Poulain, Y. Glupczynski, C. Franceschi, K. Jaspers, I. van der Pluijm,

NU

J. Hoeijmakers, C.C. Chen, Serum N-glycan profile shift during human ageing, Exp. Gerontol.

MA

45 (2010) 738-743.

[21] N. Ding, H. Nie, X. Sun, W. Sun, Y. Qu, X. Liu, Y. Yao, X. Liang, C.C. Chen, Y. Li, Human

ED

serum N-glycan profiles are age and sex dependent, Age Ageing 40 (2011) 568-575. [22] V. Vanhooren, S. Dewaele, O.M. Kuro, N. Taniguchi, L. Dolle, L.A. van Grunsven, E.

PT

Makrantonaki, C.C. Zouboulis, C.C. Chen, C. Libert, Alteration in N-glycomics during

CE

mouse aging: a role for FUT8, Aging Cell 10 (2011) 1056-1066. [23] R. Testa, V. Vanhooren, A.R. Bonfigli, M. Boemi, F. Olivieri, A. Ceriello, S. Genovese, L.

AC

Spazzafumo, V. Borelli, M.G. Bacalini, S. Salvioli, P. Garagnani, S. Dewaele, C. Libert, C. Franceschi, N-glycomic changes in serum proteins in type 2 diabetes mellitus correlate with complications and with metabolic syndrome parameters, PLoS One 10 (2015) e0119983. [24] L.R. Ruhaak, H.W. Uh, M. Beekman, C.A. Koeleman, C.H. Hokke, R.G. Westendorp, M. Wuhrer, J.J. Houwing-Duistermaat, P.E. Slagboom, A.M. Deelder, Decreased levels of bisecting GlcNAc glycoforms of IgG are associated with human longevity, PLoS One 5 (2010) e12566. [25] Y. Miura, N. Hashii, H. Tsumoto, D. Takakura, Y. Ohta, Y. Abe, Y. Arai, N. Kawasaki, N. Hirose, T. Endo, Sonic, Change in N-Glycosylation of Plasma Proteins in Japanese

ACCEPTED MANUSCRIPT 23

Semisupercentenarians, PLoS One 10 (2015) e0142645.

PT

[26] I.J. Goldstein, C.E. Hollerman, E.E. Smith, Protein-Carbohydrate Interaction. Ii. Inhibition

SC RI

Studies on the Interaction of Concanavalin a with Polysaccharides, Biochemistry 4 (1965) 876-883.

[27] J.B. Owen, F. Di Domenico, R. Sultana, M. Perluigi, C. Cini, W.M. Pierce, D.A. Butterfield,

NU

Proteomics-determined differences in the concanavalin-A-fractionated proteome of

MA

hippocampus and inferior parietal lobule in subjects with Alzheimer's disease and mild cognitive impairment: implications for progression of AD, J. Proteome Res. 8 (2009)

ED

471-482.

[28] F. Di Domenico, J.B. Owen, R. Sultana, R.A. Sowell, M. Perluigi, C. Cini, J. Cai, W.M.

PT

Pierce, D.A. Butterfield, The wheat germ agglutinin-fractionated proteome of subjects with

CE

Alzheimer's disease and mild cognitive impairment hippocampus and inferior parietal lobule: Implications for disease pathogenesis and progression, J. Neurosci. Res. 88 (2010)

AC

3566-3577.

[29] D.A. Butterfield, J.B. Owen, Lectin-affinity chromatography brain glycoproteomics and Alzheimer disease: insights into protein alterations consistent with the pathology and progression of this dementing disorder, Proteomics Clin. Appl. 5 (2011) 50-56. [30] K.S. Shamsi, A. Pierce, A.S. Ashton, D.G. Halade, A. Richardson, S.E. Espinoza, Proteomic screening of glycoproteins in human plasma for frailty biomarkers, J. Gerontol. A Biol. Sci. Med. Sci. 67 (2012) 853-864. [31] K. Kanninen, G. Goldsteins, S. Auriola, I. Alafuzoff, J. Koistinaho, Glycosylation changes in Alzheimer's disease as revealed by a proteomic approach, Neurosci. Lett. 367 (2004)

ACCEPTED MANUSCRIPT 24

235-240.

PT

[32] C. Sihlbom, P. Davidsson, M. Sjogren, L.O. Wahlund, C.L. Nilsson, Structural and

SC RI

quantitative comparison of cerebrospinal fluid glycoproteins in Alzheimer's disease patients and healthy individuals, Neurochem. Res. 33 (2008) 1332-1340.

[33] A. Kuno, N. Uchiyama, S. Koseki-Kuno, Y. Ebe, S. Takashima, M. Yamada, J. Hirabayashi,

NU

Evanescent-field fluorescence-assisted lectin microarray: a new strategy for glycan profiling,

MA

Nat. Methods. 2 (2005) 851-856.

[34] S. Angeloni, J.L. Ridet, N. Kusy, H. Gao, F. Crevoisier, S. Guinchard, S. Kochhar, H. Sigrist,

ED

N. Sprenger, Glycoprofiling with micro-arrays of glycoconjugates and lectins, Glycobiology 15 (2005) 31-41.

PT

[35] K.T. Pilobello, L. Krishnamoorthy, D. Slawek, L.K. Mahal, Development of a lectin

CE

microarray for the rapid analysis of protein glycopatterns, Chembiochem. 6 (2005) 985-989. [36] R. Saldova, M.R. Wormald, R.A. Dwek, P.M. Rudd, Glycosylation changes on serum

AC

glycoproteins in ovarian cancer may contribute to disease pathogenesis, Dis. Markers 25 (2008) 219-232.

[37] S. Chugh, V.S. Gnanapragassam, M. Jain, S. Rachagani, M.P. Ponnusamy, S.K. Batra, Pathobiological implications of mucin glycans in cancer: Sweet poison and novel targets, Biochim. Biophys. Acta 1856 (2015) 211-225. [38] R.R. Drake, E.E. Jones, T.W. Powers, J.O. Nyalwidhe, Altered glycosylation in prostate cancer, Adv. Cancer Res. 126 (2015) 345-382. [39] N. Taniguchi, Y. Kizuka, Glycans and cancer: role of N-glycans in cancer biomarker, progression and metastasis, and therapeutics, Adv. Cancer Res. 126 (2015) 11-51.

ACCEPTED MANUSCRIPT 25

[40] G. Lauc, M. Pezer, I. Rudan, H. Campbell, Mechanisms of disease: The human N-glycome,

PT

Bochim. Biophys. Acta in press (2016).

SC RI

[41] K. Akasaka-Manya, H. Manya, Y. Sakurai, B.S. Wojczyk, S.L. Spitalnik, T. Endo, Increased bisecting and core-fucosylated N-glycans on mutant human amyloid precursor proteins, Glycoconj. J. 25 (2008) 775-786.

NU

[42] I. Perdivara, R. Petrovich, B. Allinquant, L.J. Deterding, K.B. Tomer, M. Przybylski,

MA

Elucidation of O-glycosylation structures of the beta-amyloid precursor protein by liquid chromatography-mass spectrometry using electron transfer dissociation and collision induced

ED

dissociation, J. Proteome Res. 8 (2009) 631-642. [43] Y. Kizuka, S. Kitazume, R. Fujinawa, T. Saito, N. Iwata, T.C. Saido, M. Nakano, Y.

PT

Yamaguchi, Y. Hashimoto, M. Staufenbiel, H. Hatsuta, S. Murayama, H. Manya, T. Endo, N.

CE

Taniguchi, An aberrant sugar modification of BACE1 blocks its lysosomal targeting in Alzheimer's disease, EMBO Mol. Med. 7 (2015) 175-189.

AC

[44] W.T. Kimberly, M.J. LaVoie, B.L. Ostaszewski, W. Ye, M.S. Wolfe, D.J. Selkoe, Complex N-linked glycosylated nicastrin associates with active gamma-secretase and undergoes tight cellular regulation, J. Biol. Chem. 277 (2002) 35113-35117. [45] T. Tomita, R. Katayama, R. Takikawa, T. Iwatsubo, Complex N-glycosylated form of nicastrin is stabilized and selectively bound to presenilin fragments, FEBS Lett. 520 (2002) 117-121. [46] Y. Sato, Y. Naito, I. Grundke-Iqbal, K. Iqbal, T. Endo, Analysis of N-glycans of pathological tau: possible occurrence of aberrant processing of tau in Alzheimer's disease, FEBS Lett. 496 (2001) 152-160.

ACCEPTED MANUSCRIPT 26

[47] S. Schedin-Weiss, B. Winblad, L.O. Tjernberg, The role of protein glycosylation in

PT

Alzheimer disease, FEBS J. 281 (2014) 46-62.

SC RI

[48] S.J. van Rensburg, P. Berman, F. Potocnik, P. MacGregor, D. Hon, N. de Villiers, 5- and 6-glycosylation of transferrin in patients with Alzheimer's disease, Metab. Brain Dis. 19 (2004) 89-96.

NU

[49] E. Marklova, Z. Albahri, M. Valis, Microheterogeneity of some serum glycoproteins in

MA

neurodegenerative diseases, J. Neurol. Sci. 314 (2012) 20-25. [50] M.A. Korolainen, S. Auriola, T.A. Nyman, I. Alafuzoff, T. Pirttila, Proteomic analysis of

ED

glial fibrillary acidic protein in Alzheimer's disease and aging brain, Neurobiol. Dis. 20 (2005) 858-870.

PT

[51] T.G. Beach, R. Walker, E.G. McGeer, Patterns of gliosis in Alzheimer's disease and aging

CE

cerebrum, Glia 2 (1989) 420-436. [52] S. Futakawa, K. Nara, M. Miyajima, A. Kuno, H. Ito, H. Kaji, K. Shirotani, T. Honda, Y.

AC

Tohyama, K. Hoshi, Y. Hanzawa, S. Kitazume, R. Imamaki, K. Furukawa, K. Tasaki, H. Arai, T. Yuasa, M. Abe, H. Arai, H. Narimatsu, Y. Hashimoto, A unique N-glycan on human transferrin in CSF: a possible biomarker for iNPH, Neurobiol. Aging 33 (2012) 1807-1815. [53] N. Itoh, S. Sakaue, H. Nakagawa, M. Kurogochi, H. Ohira, K. Deguchi, S. Nishimura, M. Nishimura, Analysis of N-glycan in serum glycoproteins from db/db mice and humans with type 2 diabetes, Am. J. Physiol. Endocrinol. Metab. 293 (2007) E1069-1077. [54] D.E. McMillan, Elevation of glycoprotein fucose in diabetes mellitus, Diabetes 21 (1972) 863-871. [55] L.P. Lee, A. Prasad, K.J. Bolton, J.B. McKendry, I. Hynie, Serum UDP-galactose:

ACCEPTED MANUSCRIPT 27

glycoprotein galactosyltransferase in diabetics with microangiopathy, Clin. Biochem. 10

PT

(1977) 111-117.

SC RI

[56] J. Walston, M.A. McBurnie, A. Newman, R.P. Tracy, W.J. Kop, C.H. Hirsch, J. Gottdiener, L.P. Fried, S. Cardiovascular Health, Frailty and activation of the inflammation and coagulation systems with and without clinical comorbidities: results from the Cardiovascular

NU

Health Study, Arch. Intern. Med. 162 (2002) 2333-2341.

MA

[57] J. Walston, E.C. Hadley, L. Ferrucci, J.M. Guralnik, A.B. Newman, S.A. Studenski, W.B. Ershler, T. Harris, L.P. Fried, Research agenda for frailty in older adults: toward a better

ED

understanding of physiology and etiology: summary from the American Geriatrics Society/National Institute on Aging Research Conference on Frailty in Older Adults, J. Am.

PT

Geriatr. Soc. 54 (2006) 991-1001.

CE

[58] K. Darvin, A. Randolph, S. Ovalles, D. Halade, L. Breeding, A. Richardson, S.E. Espinoza, Plasma protein biomarkers of the geriatric syndrome of frailty, J. Gerontol. A Biol. Sci. Med.

AC

Sci. 69 (2014) 182-186.

[59] E. Quentin, A. Gladen, L. Roden, H. Kresse, A genetic defect in the biosynthesis of dermatan sulfate proteoglycan: galactosyltransferase I deficiency in fibroblasts from a patient with a progeroid syndrome, Proc. Natl. Acad. Sci. U. S. A. 87 (1990) 1342-1346. [60] T. Okajima, S. Fukumoto, K. Furukawa, T. Urano, Molecular basis for the progeroid variant of Ehlers-Danlos syndrome. Identification and characterization of two mutations in galactosyltransferase I gene, J. Biol. Chem. 274 (1999) 28841-28844. [61] V. Borelli, V. Vanhooren, E. Lonardi, K.R. Reiding, M. Capri, C. Libert, P. Garagnani, S. Salvioli, C. Franceschi, M. Wuhrer, Plasma N-Glycome Signature of Down Syndrome, J.

ACCEPTED MANUSCRIPT 28

Proteome Res. 14 (2015) 4232-4245.

PT

[62] R. Parekh, I. Roitt, D. Isenberg, R. Dwek, T. Rademacher, Age-related galactosylation of the

SC RI

N-linked oligosaccharides of human serum IgG, J. Exp. Med. 167 (1988) 1731-1736. [63] N. Tsuchiya, T. Endo, K. Matsuta, S. Yoshinoya, F. Takeuchi, Y. Nagano, M. Shiota, K. Furukawa, N. Kochibe, K. Ito, et al., Detection of glycosylation abnormality in rheumatoid

NU

IgG using N-acetylglucosamine-specific Psathyrella velutina lectin, J. Immunol. 151 (1993)

MA

1137-1146.

[64] K. Shikata, T. Yasuda, F. Takeuchi, T. Konishi, M. Nakata, T. Mizuochi, Structural changes

ED

in the oligosaccharide moiety of human IgG with aging, Glycoconj. J. 15 (1998) 683-689. [65] E. Yamada, Y. Tsukamoto, R. Sasaki, K. Yagyu, N. Takahashi, Structural changes of

CE

(1997) 401-405.

PT

immunoglobulin G oligosaccharides with age in healthy human serum, Glycoconj. J. 14

[66] M.P. Bakovic, M.H. Selman, M. Hoffmann, I. Rudan, H. Campbell, A.M. Deelder, G. Lauc,

AC

M. Wuhrer, High-throughput IgG Fc N-glycosylation profiling by mass spectrometry of glycopeptides, J. Proteome Res. 12 (2013) 821-831. [67] L.R. Ruhaak, C.A. Koeleman, H.W. Uh, J.C. Stam, D. van Heemst, A.B. Maier, J.J. Houwing-Duistermaat, P.J. Hensbergen, P.E. Slagboom, A.M. Deelder, M. Wuhrer, Targeted biomarker discovery by high throughput glycosylation profiling of human plasma alpha1-antitrypsin and immunoglobulin A, PLoS One 8 (2013) e73082. [68] V. Vanhooren, W. Laroy, C. Libert, C. Chen, N-glycan profiling in the study of human aging, Biogerontology 9 (2008) 351-356. [69] V. Vanhooren, X.E. Liu, C. Franceschi, C.F. Gao, C. Libert, R. Contreras, C. Chen, N-glycan

ACCEPTED MANUSCRIPT 29

profiles as tools in diagnosis of hepatocellular carcinoma and prediction of healthy human

PT

ageing, Mech. Ageing Dev. 130 (2009) 92-97.

SC RI

[70] J.P. Lu, A. Knezevic, Y.X. Wang, I. Rudan, H. Campbell, Z.K. Zou, J. Lan, Q.X. Lai, J.J. Wu, Y. He, M.S. Song, L. Zhang, G. Lauc, W. Wang, Screening novel biomarkers for metabolic syndrome by profiling human plasma N-glycans in Chinese Han and Croatian populations, J.

NU

Proteome Res. 10 (2011) 4959-4969.

MA

[71] G. Lauc, A. Essafi, J.E. Huffman, C. Hayward, A. Knezevic, J.J. Kattla, O. Polasek, O. Gornik, V. Vitart, J.L. Abrahams, M. Pucic, M. Novokmet, I. Redzic, S. Campbell, S.H. Wild,

ED

F. Borovecki, W. Wang, I. Kolcic, L. Zgaga, U. Gyllensten, J.F. Wilson, A.F. Wright, N.D. Hastie, H. Campbell, P.M. Rudd, I. Rudan, Genomics meets glycomics-the first GWAS study

PT

of human N-Glycome identifies HNF1alpha as a master regulator of plasma protein

CE

fucosylation, PLoS Genet 6 (2010) e1001256. [72] J.E. Huffman, A. Knezevic, V. Vitart, J. Kattla, B. Adamczyk, M. Novokmet, W. Igl, M.

AC

Pucic, L. Zgaga, A. Johannson, I. Redzic, O. Gornik, T. Zemunik, O. Polasek, I. Kolcic, M. Pehlic, C.A. Koeleman, S. Campbell, S.H. Wild, N.D. Hastie, H. Campbell, U. Gyllensten, M. Wuhrer, J.F. Wilson, C. Hayward, I. Rudan, P.M. Rudd, A.F. Wright, G. Lauc, Polymorphisms in B3GAT1, SLC9A9 and MGAT5 are associated with variation within the human plasma N-glycome of 3533 European adults, Hum. Mol. Genet. 20 (2011) 5000-5011. [73] K. Shimizu, N. Hirose, Y. Ebihara, Y. Arai, M. Hamamatsu, S. Nakazawa, Y. Masui, H. Inagaki, Y. Gondo, J. Fujimori, Y. Kanno, K. Konishi, K. Kitagawa, Blood type B might imply longevity, Exp. Gerontol. 39 (2004) 1563-1565. [74] C. Lopez-Otin, M.A. Blasco, L. Partridge, M. Serrano, G. Kroemer, The hallmarks of aging,

ACCEPTED MANUSCRIPT 30

Cell 153 (2013) 1194-1217.

PT

[75] P. Sebastiani, N. Solovieff, A.T. Dewan, K.M. Walsh, A. Puca, S.W. Hartley, E. Melista, S.

SC RI

Andersen, D.A. Dworkis, J.B. Wilk, R.H. Myers, M.H. Steinberg, M. Montano, C.T. Baldwin, J. Hoh, T.T. Perls, Genetic signatures of exceptional longevity in humans, PLoS One 7 (2012) e29848.

NU

[76] H.J. Gierman, K. Fortney, J.C. Roach, N.S. Coles, H. Li, G. Glusman, G.J. Markov, J.D.

MA

Smith, L. Hood, L.S. Coles, S.K. Kim, Whole-genome sequencing of the world's oldest people, PloS one 9 (2014) e112430.

ED

[77] G.W. Hart, M.P. Housley, C. Slawson, Cycling of O-linked beta-N-acetylglucosamine on nucleocytoplasmic proteins, Nature 446 (2007) 1017-1022.

PT

[78] P. Cheung, J. Pawling, E.A. Partridge, B. Sukhu, M. Grynpas, J.W. Dennis, Metabolic

CE

homeostasis and tissue renewal are dependent on beta1,6GlcNAc-branched N-glycans, Glycobiology 17 (2007) 828-837.

AC

[79] K. Ohtsubo, S. Takamatsu, M.T. Minowa, A. Yoshida, M. Takeuchi, J.D. Marth, Dietary and genetic control of glucose transporter 2 glycosylation promotes insulin secretion in suppressing diabetes, Cell 123 (2005) 1307-1321.

Figure legends Fig. 1. Contributing factors to human aging and longevity.

Fig. 2. A concerted workflow of glycomics and glycoproteomics.

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

MA

NU

SC RI

PT

31

ACCEPTED MANUSCRIPT

AC

CE

PT

ED

MA

NU

SC RI

PT

32

ACCEPTED MANUSCRIPT 33

Highlights max 85 characters including space Glycan changes in aging, longevity, and age-related diseases have been reviewed.



Glycomics and glycoproteomics are powerful tools for monitoring health conditions.



Changes in glycosylation are applicable to studies on human aging and longevity.

AC

CE

PT

ED

MA

NU

SC RI

PT

