Congenital disorders of glycosylation - diagnosis experience in the Republic of Moldova

Introduction

Congenital disorders of glycosylation (CDG) are a group of rare metabolic disorders, with multisystem impairment that result from disturbed protein and lipid glycosylation. The first case was clinically reported in 1980 by Jaeken et al. [1]. With the advent of next-generation sequencing methods in the early 2010s, the identification of CDG types has increased exponentially Currently, there are approximately 200 types of CDG with 189 phenotypes (fig.1) [2, 3]. The prevalence of this group of pathologies is estimated to be less than 1 per 100.000 in Europe [4].

Based on the mode of action, the CDG is classified in 8 categories:

1. Disorders of monosaccharide synthesis and interconversion;

2. Disorders of nucleotide sugar synthesis and transport;

3. Disorders of N-linked protein glycosylation;

4. Disorders of O-linked protein glycosylation;

5. Disorders of lipid glycosylation;

6. Disorders of vesicular trafficking;

7. Disorders of multiple glycosylation pathways;

8. Disorders of glycoprotein/glycan degradation [2].

Considering that CDG is a group of pathologies with multisystem damage, 19 involved organ systems has been described by BG Ng et al. The most affected was the nervous system in 81%, followed by ocular in 46% and muscular in 53%. The dysmorphic features were revealed in 56% [2]. Since 1984, Isoelectric focusing of transferrin (IEFT) has been considered a biochemical method used to detect abnormalities in transferrin glycosylation, making it a key screening tool for diagnosing Congenital Disorders of Glycosylation (CDG), particularly those involving N-glycosylation [1, 5]. IEFT is a specialized electrophoretic technique that separates transferrin isoforms based on their isoelectric point, which depends on the number of sialic acid residues attached to its N-glycans. Following the analysis of IEFT results, two pathological transferrin profiles can be identified: type I and type II. The IEFT type I profile is associated with defects in the endoplasmic reticulum, while the type II profile is linked to abnormalities in the Golgi apparatus. However, normal results do not exclude CDG, as some types may present with mild or absent transferrin abnormalities. This is why IEFT remains an essential first-line biochemical screening tool for CDG but should always be followed by molecular diagnostics for a definitive diagnosis [6].

The objective of this study is to diagnose CDG using Isoelectric Focusing of Transferrin in the Republic of Moldova and to identify diseases that mimic CDG.

Material and methods

The selective cross-sectional observational descriptive study was conducted at the Institute of Mother and Child, in the Laboratory of Prevention of Hereditary Pathologies from October 2018 to April 2024. The inclusion criteria for the study encompassed children with multisystem involvement of unclear etiology, defined by the following characteristics: age between 3 months and 18 years, psychomotor and growth retardation, muscle hypotonia, seizures, dysmorphic features and with chromosomal abnormalities excluded. These manifestations were accompanied by the involvement of other organs and systems, including but not limited to the cardiovascular, hepatic, musculoskeletal, ophthalmologic, dermatologic, immune, and endocrine systems. The exclusion criteria included children with multisystem involvement of confirmed etiology, viral hepatitis, and transferrin polymorphism in IEFT. Following the medical-genetic consultations at the Institute of Mother and Child in the Republic of Moldova and a comprehensive evaluation, including medical history, psychomotor development assessment, physical examination, 320 patients were selected according to the inclusion criteria and enrolled in the study. All patients have signed the consent for participation (approved by Research Ethics Committee of Nicolae Testemițanu State University of Medicine and Pharmacy Minutes No. 45, from July 03, 2019. For each included patient there was completed a questionnaire noting the clinical, phenotypical and investigational features. The biological samples were collected, including serum, plasma, urine, DNA, and DBS. The screening of 150 patients was performed using the IEFT method. For differential diagnosis of other diseases mimicking CDG, metabolic work-up (amino acids in blood, organic acid in urine, acylcarnitine profile) and selective MLPA, CGH-array, and SNP/WES/WGS have been performed. The diagnostic algorithm for CDG and mimicking pathologies was developed in accordance with the innovation act “Algorithm for the evaluation of children with multisystem involvement for the diagnosis of Congenital Disorders of Glycosylation” No. 555 from 29.07.2024. The database has been created using Microsoft Office Excel (Microsoft Corporation, Excel, version 2010, WA, USA), and IBM SPSS Statistics 28.0 program was used for the descriptive statistics to investigate the characteristics of the entire cohort.

Results

A total of 320 individuals were enrolled in the study. Due to the multisystem involvement, the clinical presentation of the patients included in the research exhibited significant variability. One hundred forty-two individuals (44.4%) were female, and 178 (55.6%) were male. The range of age was around 3-216 months, the mean age was 44 months. The clinical heterogeneity revealed the involvement of 13 affected systems, the leading system being attributed to central nervous system. The second place is hematological system followed by cardiovascular, ophthalmological, gastrointestinal, muscular, skeletal, hepatic, endocrine, renal, urological, auditory, pulmonary and immunological (tab. 1, fig. 2).

The predominant complaints reported by study group showed the following incidences: fatigue in 280 patients (87.5%) (95% CI 0.84-0.91), low attention 250 (78.1%) (95% CI 0.74-0.83), concentration disorders 246 (76.9%) (95% CI 0.73-0.82), verbal retardation 223 (69.7%) (95% CI 0.65 - 0.75), failure to thrive 151 (47.2%) (95% CI 0.43-0.54), dehydration 65 (20.3%) (95% CI 0.17-0.26) and others. Regarding the inclusion criteria in the study, seizures have been registered in 161 patients (50.3%) (95% CI 0.45-0.56), psychomotor retardation – in 275 (85.9%) (95% CI 0.83-0.91), failure to thrive – in 199 (62.2%) (95% CI 0.58-0.68), muscle tone disorders – in 310 (96.9%) (95% CI 0.95-0.99), dysmorphic features – in 197 (9.7%) (95% CI 0.57-0.67), and totally of them 317 (99.1%) (95% CI 0.98-1.00) had multisystem involvement.

After a comprehensive clinical examination, the suspected CDG cases were screened by IEFT. In three cases of 150 patients, positive IEFT has been found. Metabolic work-up and molecular genetic studies were undertaken to finalize the diagnosis. After metabolic work-up, in one case, significant galactose levels in plasma were found, as well as galactitol in urine, suggestive for Galactose troubles. Another two cases revealed no particular metabolites. Then, molecular genetic testing by Sanger sequencing using the Genetic Analyzer 3500, manufacturer Applied Biosystems was undertaken, which revealed mutations in the ALDO B gene in two positive IEFT cases and the GALT gene in the other positive case, validating the diagnosis of Hereditary Fructose Intolerance and Galactosemia, respectively. In other two patients with IEFT negative, a mutation in the GNE gene was discovered by WGS, confirming GNE myopathy (tab.2) [7].

For 50 cases with negative IEFT, complementary tests such as MLPA (5 cases) and WGS (49 cases) allowed for exclusion of CDG and the confirmatory diagnosis of other diseases. For the remaining cases, it was not possible to obtain additional diagnostic information due to limitations in access to confirmatory testing in our country.

Discussions

CDG constitute a group of multisystem hereditary pathological conditions characterized by dysfunctions in the glycosylation process in the Endoplasmic Reticulum (ER) and the cellular Golgi Apparatus (AG). These dysfunctions affect the biosynthesis of glycoproteins and other glycoconjugates, significantly influencing their functionality. The scientific progress in genetics have facilitated the widespread use of high throughput sequencing methods, allowing scientists to identify the molecular etiologies of CDG and increasing the frequency of diagnosis since the first identifications in the 1980s [8]. Despite advances in the field, the incidence and prevalence of all types of CDG have not yet been precisely established.

Research in this field has led to conflicting opinions among scientific groups. Until recently, Hereditary Fructose Intolerance and Galactosemia were considered secondary abnormalities of the glycosylation process, being excluded from the list of CDG [9, 10]. However, in May 2024, these conditions were reclassified as CDG spectrum disorders, being attributed to derangements in monosaccharide synthesis and interconversion [2].

In the reported types of CDG, the most prevalent symptoms were neurological (80,5%), followed by dysmorphisms (55.6%), endocrine symptoms (55%), skeletal abnormalities (52.7%), ocular problems (46.3%), digestive issue (34.1%), cardiovascular abnormalities (22.0%), muscular problems (11.7%), respiratory issues (10.2%), genitourinary problems (9.8%), psychiatric symptoms (9.8%), renal complications (8.3%), hair-related issues (6.8%) and dental problems (4.4%) [2, 11].

In Moldovan cohort of CDG suspected patients, the most commonly affected systems were neurological and hematological, followed by cardiovascular, ophthalmological, gastrointestinal, skeletal, hepatic, endocrine, renal, urological, auditory, pulmonary, and immunological. The dental, hair-related, psychiatric, and dermatological symptoms were not reported in our cohort.

Considering that CDG is a group of ultra-rare pathologies with multisystem disorder, often mimicking other genetic diseases, they are frequently underdiagnosed. In the diagnostic process, it is necessary to follow a staged diagnostic algorithm that requires a differential diagnosis to be carried out as meticulously as possible. The most important groups of pathologies that must be excluded are Mitochondrial Diseases and Disorders of Phospholipid Synthesis, both of which also involve multisystem damage [12]. At the same time, dysmorphic features related to a frequency of 55.6% in CDG, can often be found in other pathologies. The presence of fat pads can most commonly be seen in PMM2-CDG, and it has also been reported in Wiedemann-Rautenstrauch syndrome (neonatal progeria). Also, the presence of inverted nipples can occasionally be determined in other genetic diseases than CDG, such as Turner, Smith-Lemli-Opitz, Weaver and Robinow syndrome. Almond-shaped eyes can often be found in Prader-Willi syndrome, which is accompanied by hypotonia and feeding problems in childhood, which can also be seen in CDG [12]. Among the forms of CDG that involve liver damage, the differential diagnosis algorithm includes other various genetic diseases and inborn errors of metabolism as Alpers progressive infantile poliodystrophy, alpha-1 antitrypsin deficiency, cystic fibrosis, Gaucher disease, type IV glycogen storage disorder, glycerol dehydrogenase-1-deficiency-3-phosphate, hemochromatosis, 3-hydroxyacyl-CoA dehydrogenase deficiency, lysosomal acid lipase deficiency, Niemann-Pick disease type A, B, C, peroxisomal diseases, S-adenosine homocysteine ​​hydroxylase deficiency, tyrosinemia type I, and Wilson's disease [13]. Protein-lipid enteropathy, described especially in MPI-CDG, can also be found in severe celiac disease, congenital intestinal diseases and in various genetic diseases (Noon disease, Turner disease, skeletal dysplasia FGFR3). When an endocrine disorder is observed with predominance of hypoglycemia, it is necessary to carry out the differential diagnosis between fatty acid beta-oxidation defects, glycogen storage disorders, the average form of Beckwith-Wiedemann syndrome, congenital hypopituitarism and congenital adrenal hyperplasia [13]. In the presence of renal damage, it is recommended to exclude tubulopathies of metabolic cause, diseases with energy deficit and metabolic disorders of the storage type of complex molecules, as well as other genetic syndromes accompanied by polycystic kidney disease and nephrotic syndrome [12].

One of the objectives of our study was to identify pathologies that mimic the clinical manifestations of CDG. In the analyzed cohort, mitochondrial diseases were diagnosed in 6 cases, representing a significant percentage of the pathologies confused with CDG because of their multisystem affection. Prader-Willi syndrome was identified in 2 cases, and Angelman syndrome, Zellweger syndrome, and Wilson disease were each diagnosed in one case. Other neurological diseases that mimic CDG were determined by next generation sequencing (tab. 3). These genetic pathologies although have clinical manifestations similar to CDG, show distinct pathogenetic mechanisms, emphasizing the importance of a rigorous and differential diagnostic evaluation in the management of these complex conditions.

According to reported data, IEFT identifies alterations in the transferrin profile in only 60% of cases, primarily in the presence of N-glycosylation defects, however, a normal IEFT result does not rule out CDG [14]. Therefore, in cases with strong clinical and biochemical suspicion, advanced diagnostic approaches such as next-generation sequencing (NGS), including targeted gene panels or whole-exome/genome sequencing (WES/WGS), are recommended as a definitive diagnostic strategy [14, 15]. The remaining 265 cases did not reach a definitive diagnosis due to limited access to diagnostic methods in the Republic of Moldova, as these are very expensive and not performed in our country. In this context, we cannot exclude the possibility that other types of CDG, which test negative on IEFT, may be present in these 265 cases.

Conclusions

Our study revealed significant clinical diversity among patients with suspected CDG, with multisystem involvement and a predominance of central nervous system involvement. Despite the high frequency of symptoms associated with CDG, only three cases were confirmed by IEFT and genetic testing, with final diagnoses of Galactosemia and Hereditary Fructose Intolerance, representing the first group of glycosylation impairment in the novel classification. In addition, two cases were diagnosed with GNE myopathy. Among 50 cases with negative IEFT result, complementary molecular tests allowed the exclusion of CDG and the establishment of other diagnoses. This emphasizes the complexity of diagnosing CDG and the need for a rigorous diagnostic protocol, including advanced metabolic and genetic testing.

Competing interests

None declared.

Authors’ contribution

DB conceived conceptualization, methodology, data collection, analysis and interpretation, writing – original draft preparation. CB analyzed the result of screening by IEFT. AN – supervision on differential diagnosis data. VS – coordinator of genetic analysis. NU – research coordinator, conceived writing review and editing, validation. The authors read and approved the final version of the manuscript.

Patient consent

Obtained

Ethics approval

This study was approved by the Research Ethics Committee of Nicolae Testemițanu State University of Medicine and Pharmacy (Act No. 45, from July 03, 2019).

Acknowledgments and funding

The research was initiated by the scientific project 18.80012.04.04F, 2018-2019 (CDGSCREEN) and followed by the project 20.80009.8007.22, 07-PS, 2020-2023 (SCREENGEN) financed by the National Agency of Research and Development and Ministry of Education and Research of Republic of Moldova. The research was supported by the grant from the Ministry of Research, Innovation and Digitalization, CNCS-UEFISCDI, project PN-IV-P8-8.3-ROMD-2023-0249 (DiMoMeD), within PNCDI IV (Romania).

Provenance and peer review

Not commissioned, externally peer review.

Authors’ ORCID IDs

Daniela Blăniță – https://orcid.org/0000-0001-7736-3406

Chiril Boiciuc – https://orcid.org/0000-0002-7273-2492

Victoria Sacara – https://orcid.org/0000-0001-9200-0494

Alina Nicolescu – https://orcid.org/ 0000-0001-7022-8893

Natalia Ușurelu – https://orcid.org/0000-0001-8685-3933

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