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Keywords:

  • glycomics;
  • immunoglobulin G;
  • liver steatosis;
  • protein glycosylation.

Summary

  1. Top of page
  2. Summary
  3. What is already known about this subject
  4. What this study adds
  5. Introduction
  6. Patients and methods
  7. Results
  8. Discussion
  9. Acknowledgements
  10. Conflict of Interest Statement
  11. References

Objective

We have previously shown the potential of glycomics to distinguish patients with steatosis from patients with non-alcoholic steatohepatitis (NASH) in an adult population. The pattern of disease in paediatric patients is distinct from adults. The objective of this study was to characterize the N-glycomic profile of children with varying degrees of non-alcoholic fatty liver disease (NAFLD) and identify potential biomarker profiles of disease.

Methods

Serum protein N-glycosylation patterns of 51 paediatric NAFLD patients were assessed with deoxyribonucleic acid sequencer-assisted fluorophore-assisted capillary electrophoresis and compared with histology.

Results

Peak 1 (NGA2F) is the most significantly elevated N-glycan in paediatric NASH patients with peak 5 (NA2) demonstrating the largest decrease. The logarithmically transformed ratio of peak 1 to peak 5 was −0.85 (standard deviation [SD] 0.22) in patients with steatosis and borderline NASH and −0.73 (SD 0.12) in NASH (P = 0.02). The biomarker correlated well with the amount of lobular inflammation with a consistent increase of marker score in ascending stage of lobular inflammation. There was also a trend in differentiating patients with significant fibrosis ≥F2; −0.74 (SD 0.13) from patients with no/minimal fibrosis <F2; −0.86 (SD 0.24), P = 0.06. Analysis of the N-glycans on immunoglobulin G confirmed the undergalactosylation status typical for chronic inflammatory conditions.

Conclusions

This study is the first glycomic analysis performed in a paediatric NAFLD population. In agreement with the results obtained in adults, B cells play a dominant role in the N-glycan alterations of paediatric NASH patients.


What is already known about this subject

  1. Top of page
  2. Summary
  3. What is already known about this subject
  4. What this study adds
  5. Introduction
  6. Patients and methods
  7. Results
  8. Discussion
  9. Acknowledgements
  10. Conflict of Interest Statement
  11. References
  • IgG undergalactosylation is typical for chronic inflammatory diseases.
  • Serum N-glycosylation can distinguish NASH from steatosis in adult patients.
  • The pattern of disease in paediatric NASH patients is distinct from adults.

What this study adds

  1. Top of page
  2. Summary
  3. What is already known about this subject
  4. What this study adds
  5. Introduction
  6. Patients and methods
  7. Results
  8. Discussion
  9. Acknowledgements
  10. Conflict of Interest Statement
  11. References
  • Despite a different histology, paediatric NASH patients display similar glycomic alterations compared to adults.
  • This suggests that similar molecular mechanisms lay at the basis of the NASH pathogenesis.
  • The strong involvement of B cells in the glycomic alterations supports that NASH is a systemic disorder rather than a liver-specific disease.

Introduction

  1. Top of page
  2. Summary
  3. What is already known about this subject
  4. What this study adds
  5. Introduction
  6. Patients and methods
  7. Results
  8. Discussion
  9. Acknowledgements
  10. Conflict of Interest Statement
  11. References

In recent years, there has been an increased prevalence of paediatric obesity with a concomitant increase of paediatric non-alcoholic fatty liver disease (NAFLD). In fact, fatty liver is the most common liver abnormality in children aged 2–19 years [1, 2]. However, the true prevalence of paediatric NAFLD and non-alcoholic steatohepatitis (NASH) is unknown given that the modalities used for diagnosis are not standardized [3, 4]. Liver biopsy is the generally accepted standard for diagnosis and evaluation of severity but is clearly not a feasible tool for frequent monitoring of disease or for large-scale screening. In most cases, aminotransferase elevation in the absence of markers of any other liver disease was used as a surrogate marker of fatty liver disease [5, 6]. Other markers, such as insulin resistance index, could have a role in screening [7].

However, the spectrum of fatty liver encompasses a wider range of subjects than identified by elevated serum liver chemistries. Franzese et al. demonstrated that in 53% of obese children identified by ultrasound, only 32% had abnormalities in serum aminotransferases [8]. Furthermore, using magnetic resonance imaging, Burgert et al. showed that only 48% of obese children with intrahepatic fat accumulation had abnormal alanine aminotransferase (ALT) levels [9]. Moreover, NASH was diagnosed in 59% of adult NAFLD patients with normal ALT levels, indicating that routine liver function tests are not reliable to identify NASH or more severe disease [10]. Clearly, aminotransferase levels have very limited sensitivity and specificity in the diagnosis of NAFLD, and more importantly, it can not distinguish the severity of disease. This is particularly important for long-term monitoring and evaluation of therapeutic intervention. Therefore, the search for well-performing non-invasive markers for paediatric NASH continues.

Interest in glycomics is growing steadily as a high throughput novel technology in the identification of disease biomarkers [11, 12]. Glycans are carbohydrate sequences that are conjugated to proteins and lipids and are possibly the most diverse class of molecule and glycomics is the study of this diversity. Glycosylation is the post-translational modification of secreted proteins. Changes in glycosylation serve as a particularly good marker of liver dysfunction because most glycoproteins in serum (aside from immunoglobulin G, IgG) are made in the liver. Thus, the N-glycome profile will reflect any changes in either the liver or B cell function. We previously performed a glycomic investigation in an adult NAFLD population. A pilot study including bariatric surgery patients led to the development of a glycomarker that could distinguish NASH from steatosis independently of fibrosis. This glycomarker was the ratio of two N-glycans, NGA2F, a fully agalactosylated N-glycan that is exclusively present on IgG and NA2, the most abundant N-glycan on liver-produced protein but present in low quantity on IgG. This biomarker was subsequently validated in a large, independent clinical NAFLD population, and multivariate analysis showed that our glycomarker was an independent predictor of NASH [13].

A paediatric NAFLD population displays several differences with its adult counterpart, especially at the histological level. Schwimmer et al. examined the histological appearance of 100 paediatric cases and identified two types of steatohepatitis [14]. Type 1 NASH was consistent with NASH as described in adults and was characterized by steatosis, ballooning degeneration and perisinusoidal fibrosis in the absence of portal changes. In contrast, type 2 NASH was characterized by steatosis, portal inflammation and/or portal fibrosis in the absence of ballooning degeneration and perisinusoidal fibrosis. Type 1 NASH was reported to be present in only 17% of paediatric NAFLD, whereas type 2 NASH was present in 51%. Type 1 and type 2 NASH may have a different pathogenesis, natural history and response to treatment [14].

The aim of this study is to characterize the glycomic profile of children with varying degrees of NAFLD and identify potential biomarker profiles of disease.

Patients and methods

  1. Top of page
  2. Summary
  3. What is already known about this subject
  4. What this study adds
  5. Introduction
  6. Patients and methods
  7. Results
  8. Discussion
  9. Acknowledgements
  10. Conflict of Interest Statement
  11. References

Paediatric NAFLD population

Children with biopsy proven NAFLD (n = 51) were recruited from a tertiary care paediatric hepatology unit. Children with suspected NAFLD underwent a Menghini liver biopsy because of abnormal transaminases and/or splenomegaly. Biopsies were routinely processed; paraffin embedded sections were stained with haematoxylin and eosin, reticulin, orcein and Perls staining. In addition, fresh tissue (>1 mg) was sent for copper quantification to rule out Wilson's disease. A diagnosis of NAFLD was made on the basis of typical histological findings [15] by a hepatohistopathologist in the appropriate setting and following exclusion of other liver disease. None of the children drank alcohol. The following anthropomorphic data were collected from each child: height, weight and body mass index (BMI) z-score. Biochemical data included homeostatic model assessment insulin resistance (HOMA-IR), renal, liver and bone profiles, lipid profiles and full blood count. Finally, the echogenicity of the liver, spleen size and any anatomical abnormalities were recorded using ultrasound. For this study, additional serum was taken either on or within 30 d of biopsy. Serum was collected, centrifuged and stored at −80°C until analysis. Informed consent was given by the carer and the study was approved by the Ethical Committee of the Ghent University Hospital and the National Research Ethics Committee (UK) as part of a larger study on biomarkers of paediatric NAFLD.

Liver biopsy scoring

Histological specimens were scored according to NAFLD activity score (NAS), also scoring for stage of fibrosis [16]. This is the non-weighted sum of steatosis (0–3), ballooning (0–2) and lobular inflammation (0–3). NASH was defined as a score ≥5, ‘not NASH’ as a score ≤2 and a score of 3 or 4 was classified as ‘borderline NASH’. This scoring system does not replace the histopathologist in making a diagnosis of NASH but rather is useful in reproducibly stratifying severity of disease activity. Fibrosis was scored using a five-point scale: 0, no fibrosis; 1, mild/moderate perisinusoidal or portal fibrosis; 2, both perisinusoidal and portal fibrosis; 3, bridging fibrosis; 4, cirrhosis. A single histopathologist scored the specimens in batches of 30 to minimize intra-observer variability and was blinded to other markers. Distinction between NASH type 1 and 2 was made as previously described [14].

IgG depletion

Serum samples were depleted using beads covered with protein A/G (Thermo Scientific, Waltham, MA, USA). A total of 100 μL of serum was diluted with 100 μL of binding buffer and subsequently incubated with 50 μL beads for 1 h. The mixture was transferred to a 96-well filter plate and centrifuged at 1000 g for 15 s. The IgG-depleted eluate was captured in a microtiter plate. Subsequently, after five wash steps with binding buffer, pure IgG was eluted from the beads after incubation (5 min) with 0.1 M glycine pH 2 in the 96-well filter plate. After centrifugation at 1000 g for 15 s, the eluate is neutralized with 1 M Tris pH 8.8.

Glycomic analysis

For an elaborate description of the protocol, we refer to Laroy et al. [17]. Briefly, the N-glycans present in 5 μL of serum or pure IgG elution fraction was released from the proteins with peptide N-glycanase F. Subsequently, the N-glycans are fluorescently labelled and desialylated. The labelled glycans were profiled and analysed by deoxyribonucleic acid sequencer-assisted fluorophore-assisted capillary electrophoresis technology. In analogy with adult patients, we could observe 13 peaks in the total serum electropherogram and eight peaks in the IgG electropherogram. The height of every peak was quantified to obtain a numerical description of the profiles, and these were normalized to the total intensity of the measured peaks (represented as a percentage of the total peak height). Structural characterization of the fluorescently labelled N-glycans was done as previously described [18].

Statistical analysis

Statistical package for the Social Sciences (SPSS) v17.0 (SPSS, Chicago, IL, USA) was used for analysis. Descriptive results are expressed as median and inter-quartile range or number (percentage) of patients with a condition. In case of the logarithmically transformed glycomarker, the mean and standard deviation are expressed as it followed a normal distribution. The Mann–Whitney U-test, Fisher's exact test or the Kruskal–Wallis test was used to compare non-parametric categorical/continuous data. Pearson's chi-square test, Fisher's exact test or one-way analysis of variance was used to compare parametric data. Liver biopsy was used as the criterion standard. A P value of <0.05 was considered significant.

Results

  1. Top of page
  2. Summary
  3. What is already known about this subject
  4. What this study adds
  5. Introduction
  6. Patients and methods
  7. Results
  8. Discussion
  9. Acknowledgements
  10. Conflict of Interest Statement
  11. References

Demographics and clinical characteristics

Fifty-one children were recruited for this study with a median age of 13.3 years (range 4.5–17.4). Thirty-one (61%) were boys. The median BMI z-score of the group was 1.81. Of the paediatric population, 75% had splenomegaly at time of biopsy. No child had abnormal liver synthetic function, evidence of varices or decompensated liver disease. Of the children, 83% had evidence of abnormal insulin sensitivity (HOMA-IR>3). The overall median HOMA-IR was 4.83. Forty-seven paediatric patients had fibrosis (92.2%). Thirty-five of these patients were diagnosed with type 2 NASH (74.5%), 11 had mixed features (23.4%) and only one patient had proper type 1 NASH (2.1%). All clinical and demographic data are summarized in Table 1.

Table 1. Clinical and demographic characteristics of the paediatric NAFLD population
 All (n = 51)Simple steatosis/borderline NASH (n = 23)NASH (n = 28)P value
  1. P values in italics indicate statistical significance.

Age (y)13.3 (11.6, 14.6)13.7 (12.2, 14.6)13.0 (11.5, 14.4)0.416
Sex: male [%]31 [60.8]14 [60.9]17 [60.7]0.991
BMI z-score1.81 (1.44, 2.16)1.84 (1.22, 2.2)1.81 (1.53, 2.11)0.656
Albumin (mg mL−1)48 (45, 49)48 (44, 49.5)47.5 (45.5, 49)0.500
ALP (U L−1)274 (233, 319)272 (226, 292)299 (243, 349)0.136
HOMA-IR4.83 (3.59, 7.16)4.9 (3.67, 6.95)4.74 (3.53, 8.52)0.891
Haemoglobin (g dL−1)13.4 (12.9, 14.2)13.4 (12.9, 14.6)13.4 (12.9, 13.8)0.378
White blood count (×103 μL−1)7.07 (6, 8.6)6.83 (6, 8.8)7.1 (5.98, 8.25)0.691
Platelets (×103 μL−1)323 (262, 368)326 (263, 368)310 (246, 379)0.698
INR International Normalized Ratio (INR)1.0 (0.96, 1.03)0.98 (0.92, 1.03)1.0 (0.97, 1.03)0.208
Tot Bil (μmol L−1)8 (6, 11)9 (6, 11)8 (6, 10)0.71
AST (U L−1)58 (42, 84)49 (36, 73)61 (50, 105)0.048
ALT (U L−1)73 (47, 103)67 (38, 108)76 (62, 101)0.525
GGT (U L−1)36 (25, 64)27 (18, 50)41 (31, 76)0.018
Cholesterol (mmol L−1)4.5 (4.0, 5.1)4.9 (4.2, 5.2)4.2 (3.7, 4.8)0.021
Triglycerides (mmol L−1)1.7 (1.1, 2.7)1.8 (1.35, 2.8)1.65 (1.1, 2.7)0.258
Splenomegaly [%]38 [75]20 [87]18 [64]0.577
Glycomarker−0.79 (0.18)−0.85 (0.22)−0.73 (0.12)0.02

Histological analysis

Five children scored as ‘not NASH’ or simple steatosis according to the Kleiner scoring system, 18 as borderline NASH and 28 as true NASH. To compensate for low numbers in the simple steatosis group, this was merged with the borderline NASH group in order to reflect relative severity of disease. Ten children (19.6%) scored 0 for inflammation, 29 (56.9%) scored 1 (mild inflammation) and 12 (23.5%) scored 2 (moderate inflammation). No child had severe inflammation on biopsy. Four children did not have evidence of fibrosis, 14 scored fibrosis stage 1, 13 as fibrosis stage 2, nineteen as fibrosis stage 3 and one child as cirrhotic. The children were classified as having no/minimal fibrosis (<F2), n = 18, or as significant fibrosis (≤F2), n = 33. Again, this was to preserve clinical relevance in the study. Histological data are summarized in Table 2.

Table 2. Histological findings in the paediatric study cohort (n = 51)
 All (n = 51) (%)Simple steatosis/borderline NASH (n = 23) (%)NASH (n = 28) (%)
Steatosis   
02 (3.9)2 (8.7)0 (0)
115 (29.4)15 (65.2)0 (0)
27 (13.7)4 (17.4)3 (10.7)
327 (53.0)2 (8.7)25 (89.3)
Inflammation   
010 (19.6)10 (43.5)0 (0)
129 (56.9)12 (52.2)17 (60.7)
212 (23.5)1 (4.3)11 (39.3)
30 (0)0 (0)0 (0)
Ballooning   
05 (9.8)5 (21.8)0 (0)
120 (39.2)9 (39.1)11 (39.3)
226 (51.0)9 (39.1)17 (60.7)
Fibrosis   
04 (7.8)2 (8.7)2 (7.2)
114 (27.5)11 (47.8)3 (10.7)
213 (25.5)4 (17.4)9 (32.1)
319 (37.2)6 (26.1)13 (46.4)
41 (2.0)0 (0)1 (3.6)

Total serum glycomic analysis in NASH vs. borderline NASH and steatosis

Analysis of the total serum N-glycome revealed two agalactosylated glycans, peak 1 (NGA2F) and peak 4 (NGA1A2F), which were significantly increased in abundance in children with NASH vs. the remainder (P = 0.011 and P = 0.033, respectively). Peak 9′ (NA3Fc) was also significantly elevated in this group (P = 0.022) (Fig. 1, Table 3).

figure

Figure 1. Representative total serum (a) and IgG (b) electropherogram of a paediatric patient with simple steatosis and NASH. Peak 1 is an agalacto, core-α-1,6-fucosylated biantennary (NGA2F), peak 2 is an agalacto, core-α1,6-fucosylated bisecting biantennary (NGA2FB), peak 3 and peak 4 are single agalacto, core-α-1,6-fucosylated biantennaries (NG1A2F), peak 5 is a bigalacto, biantennary (NA2), peak 6 is a bigalacto, core-α-1,6-fucosylated biantennary (NA2F), peak 7 is a bigalacto, core-α-1,6-fucosylated bisecting biantennary (NA2FB), peak 8 is a triantennary (NA3), peak 9 is a branching α1,3-fucosylated triantennary (NA3Fb), peak 9′ is a core-α-1,6-fucosylated triantennary (NA3Fc), peak 10 is branching α1,3-fucosylated and core α-1,6-fucosylated triantennary (NA3Fbc), peak 11 is a tetra-antennary (NA4) and peak 12 is branching α1,3-fucosylated tetra-antennary (NA4Fb). The symbols used in the structural formulas are square indicates β-linked N-acetylglucosamine (GlcNAc); yellow circle indicates β-linked galactose, triangle indicates α/β-1,3/6-linked fucose; green circle indicates α/β-linked mannose.

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Table 3. Relative percentages of the different peaks in the total serum and IgG electropherogram
 Total serumImmunoglobulin G
Simple steatosis/borderline NASH (n = 23)NASH (n = 28)P valueSimple steatosis/borderline NASH (n = 23)NASH (n = 28)P value
  1. P values in italics indicate statistical significance.

Peak 1 (%) NGA2F6.44 (5.65, 7.92)8.25 (6.68, 9.06)0.01121.46 (17.02, 24.5)23.41 (21.16, 26.71)0.024
Peak 2 (%) NGA2FB1.15 (0.98, 1.41)1.13 (1.01, 1.4)0.882.75 (2.3, 3.46)3.22 (2.75, 3.89)0.14
Peak 3 (%) NG1A2F7.82 (6.76, 9.05)7.62 (6.5, 9.08)0.91722.47 (20.7, 23.73)22.93 (21.12, 24.18)0.325
Peak 4 (%) NGA1A2F2.75 (2.3, 3.46)3.4 (2.7, 3.84)0.03310.11 (8.6, 10.77)10.45 (9.56, 11.57)0.05
Peak 5 (%) NA245.8 (40.88, 47.25)43.77 (40.2, 45.5)0.145.53 (4.91, 6.56)5.46 (4.56, 6.21)0.59
Peak 6 (%) NA2F20.93 (18.97, 24.38)20.86 (19.26, 22.61)0.79832.79 (27.32, 35.14)26.33 (25.27, 29.49)0.01
Peak 7 (%) NA2FB4.17 (3.42, 4.85)4.29 (3.58, 4.72)0.5455.61 (4.43, 7.06)5.61 (4.68, 6.43)0.776
Peak 8 (%) NA36.85 (5.16, 7.53)6.45 (5.12, 7.34)0.8060.28 (0.17, 0.46)0.32 (0.18, 0.61)0.466
Peak 9 (%) NA3Fb2.13 (1.34, 2.39)1.64 (1.25, 2.39)0.32   
Peak 9′ (%) NA3Fc0.92 (0.72, 1.13)1.37 (1.07, 1.68)0.022   
Peak 10 (%) NA3Fbc0.42 (0.32, 0.52)0.51 (0.35, 0.67)0.248   
Peak 11 (%) NA40.79 (0.68, 0.9)0.86 (0.73, 0.99)0.32   
Peak 12 (%) NA4F0.4 (0.33, 0.48)0.41 (0.34, 0.49)0.992   

IgG glycomic analysis in NASH vs. borderline NASH and steatosis

N-glycomic analysis of the glycans present on IgG revealed that peak 1 (NGA2F) was similarly significantly increased in NASH patients (P = 0.024). Peak 6 (NA2F) was significantly decreased in abundance in children with NASH vs. the remainder (P = 0.01) (Fig. 1, Table 3).

Evaluation of serum glycomarker test in paediatric population

Peak 1 (NGA2F) was the most significantly increased N-glycan in paediatric NASH patients with peak 5 (NA2) demonstrating the largest decrease (Table 3). The logarithmic proportion of these two peaks was therefore the most efficient glycomarker that could be developed to distinguish minimal from severe steatohepatitis. This biomarker was subsequently evaluated in the different patient groups. Patients with simple steatosis were found to have a mean score of −0.9 (±0.1), patients with borderline NASH had a mean score of −0.83 (±0.25) and NASH patients had a mean score of −0.73 (±0.12). When the scores of the patients with simple steatosis and borderline NASH were merged, this group displayed a mean value of −0.85 (±0.22), which was significantly lower in comparison with the NASH group (−0.73) (P = 0.02). The area under the receiver operating curve to distinguish children with NASH vs. the remainder was 0.72 (95% confidence interval [CI] 0.57–0.86) and 0.79 (95% CI 0.64–0.94) to distinguish the group with simple steatosis (Fig. 2).

figure

Figure 2. Classification efficiency. Receiver operating characteristic (ROC) curve analysis to evaluate efficiency of glycomarker in differentiating between the group with steatosis and borderline NASH and the group with NASH (top) and in differentiating between the group with steatosis and the group with borderline NASH and NASH (bottom).

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The glycomarker also correlated well with the amount of inflammation in biopsies. Mean score in patients with no inflammation was −0.88 (±0.27), mild inflammation was −0.77 (±0.17) and moderate inflammation was −0.74 (±0.08). There was also an increase in marker score in the paediatric patients with ballooning vs. no ballooning. Mean score in the patients with no ballooning was −0.83 (±0.1), with few balloon cells was −0.78 (±0.18) and with prominent ballooning was −0.78 (±0.2).

There was a trend towards significance in differentiating the group with significant fibrosis (≥F2 − n = 18), −0.74 (±0.13) from the group with no/minimal fibrosis (<F2 – n = 33), −0.86 (±0.24) (P = 0.06).

Discussion

  1. Top of page
  2. Summary
  3. What is already known about this subject
  4. What this study adds
  5. Introduction
  6. Patients and methods
  7. Results
  8. Discussion
  9. Acknowledgements
  10. Conflict of Interest Statement
  11. References

Non-invasive methods to screen an obese, paediatric population for NAFLD are not readily available. Most research efforts have focused on adult NAFLD; however, the paediatric population is not far behind in terms of prevalence with up to 10% of the children affected [2, 19]. Moreover, the problems of adult NAFLD patients generally originate in childhood, mostly during adolescence, and a correction in lifestyle or even clinical treatment in this early phase would be beneficial for the management of the disease. This study sets out to distinguish the differing degree of disease severity in children with NAFLD. This is important as the prognosis for those with simple steatosis may not be much different from the general population but is significantly worse in terms of both all cause and liver related mortality for those with NASH [20]. The severity of the condition will change over time and non-invasive biomarkers must be effective in monitoring disease progression/regression.

The NAS scoring system, while designed primarily to reflect changes over time in the context of clinical trials, is the best available tool against which to compare a biomarker. However, we emphasize that neither the diagnosis of NAFLD nor the presence of steatohepatitis can be inferred from the NAS and requires an overall assessment of the presence and distribution of the individual histological findings [21]. Despite this, not one scoring system has been properly validated and the NAS is the most widely used in studies that evaluate biomarkers in paediatric and adult NAFLD patients [22-26]. This makes comparison of diagnostic efficacy between biomarkers feasible.

Our data indicate that paediatric NAFLD patients show very similar results in a glycomic analysis compared with adult NAFLD patients with an increase of agalactosylated glycans in NASH patients. In this paediatric cohort, two of these N-glycans (NGA2F and NGA1A2F) reached significance. This undergalactosylation is exclusively present on IgG and its glycomic profile confirmed the increase of NGA2F in favour of the decrease of NA2F (Fig. 1). This is similar to the pattern found in other chronic inflammatory diseases such as rheumatoid arthritis, ankylosing spondylitis and Crohn's disease [27-30]. This reflects the inflammatory component to the disease and explains the association with steatohepatitis rather than with fibrosis. We also found a clear trend in differentiating patients with no/minimal fibrosis from patients with significant fibrosis. However, evaluation of the distribution of the different categories of lobular inflammation showed that nearly all patients with significant fibrosis had lobular inflammation, while more than a quarter of the patients with no/minimal fibrosis had no lobular inflammation.

An important issue in this study was the different pattern of fibrosis in children, which was type 2 in 75% and mixed in 21%. The similarity of the glycomic analysis in adult and paediatric patients despite the clearly different liver histology was an extra confirmation that IgG N-glycosylation predominantly determines the N-glycan alterations of NASH patients, whereas the N-glycosylation of liver-produced protein was only marginally affected. A larger multi-centre glycomic study of children with NAFLD may allow the development of biomarkers specific to the type 2 pattern of injury.

In agreement with the results in adult NAFLD patients, the log(NGA2F/NA2) biomarker displayed the best result in distinguishing minimal from severe steatohepatitis. The AUC to differentiate steatosis from borderline NASH and NASH was high at 0.79. However, the analysis to distinguish steatosis and borderline NASH patients from NASH patients will provide a better representation of real-life practice because of the small number of steatosis patients. This analysis still had a reasonable AUC of 0.72.

Our glycomarker showed a good correlation with the amount of inflammation with a consistent, gradual increase of mean marker score in ascending amount of lobular inflammation. This observation is important because the appearance of an inflammatory reaction defines the onset of NASH [31]. Importantly in this context, the most elaborate difference was observed between patients with no inflammation and patients with a mild inflammation; mean marker score does not augment further when patients progressed to a moderate amount of lobular inflammation. This suggests that the glycomarker would be a good tool to early identify patients with simple steatosis that progress to a more severe phenotype. The same was observed for the analysis in the different stages of ballooning, although the difference between patients with or without ballooning was not as extensive as in patients with or without inflammation.

The sample size is relatively small; however, it reflects the practice of a large tertiary paediatric liver centre. The strengths of the study include the fact that these children all had biopsy-proven disease in contrast to other studies in the field where the diagnosis of NAFLD was made on the basis of a bright liver on ultrasound. The findings of this study will ideally be validated in a larger cohort.

In conclusion, the results in this study are novel in that they represent the first glycomic analysis of paediatric NAFLD. They validate findings in adults with the condition in that a glycomarker can serve as a biomarker of severity of disease in NAFLD. The strong involvement of B cells in the glycomic alterations of NASH patients supports previous research that indicates that NASH is a systemic disease associated with visceral obesity and insulin resistance rather than a liver-specific disorder. Finally, this technology has recently been brought to a clinical platform in order that clinical chemistry laboratories will be able to use glycomics as a tool in the diagnosis and follow-up of NAFLD patients [32].

References

  1. Top of page
  2. Summary
  3. What is already known about this subject
  4. What this study adds
  5. Introduction
  6. Patients and methods
  7. Results
  8. Discussion
  9. Acknowledgements
  10. Conflict of Interest Statement
  11. References