The Prevalence of PMM2-CDG in Estonia Based on Population Carrier Frequencies and Diagnosed Patients

Abstract

PMM2-CDG (MIM#212065) is the most common type of congenital disorders of glycosylation (CDG) caused by mutations in PMM2 (MIM#601785). In Estonia, five patients from three families have been diagnosed with PMM2-CDG. Our aim was to evaluate the presence of different PMM2-CDG-causing mutations in a population-based cohort and to calculate the expected frequency of PMM2-CDG in Estonia. Also, we analyzed the prevalence of PMM2-CDG based on our patient group data. To calculate the expected frequency of PMM2-CDG, we used the whole genome sequencing data of 2,244 participants from biobank of the Estonian Genome Center, University of Tartu. Nineteen individuals carried mutated PMM2 alleles and altogether, five different mutations were identified. The observed carrier frequency for all PMM2 disease-causing mutations was thus 1/118, and for the most frequent mutation p.R141H, 1/224. The expected frequency of the disease in Estonian population is 1/77,000. It is comparable to the current prevalence of PMM2-CDG for the less than 18 years age group, which is 1/79,000. In conclusion, the frequency of PMM2-CDG in Estonia is lower than in other European populations reported thus far. We demonstrate that biobank data can be useful for gaining new information about the epidemiology of the PMM2-CDG.

Introduction

PMM2-CDG (MIM#212065) is the most common type of congenital disorders of glycosylation (CDG), and is inherited in an autosomal recessive pattern. There are at least 1,000 diagnosed PMM2-CDG patients worldwide, but the number is likely increasing as the awareness of CDG is growing.

PMM2 (MIM#601785) is located in chromosomal region 16p13 (Martinsson et al. 1994), with at least 117 disease-causing mutations listed in the Human Gene Mutation Database (HGMD^® Professional) from BIOBASE Corporation (Stenson et al. 2009), and 97 of them are missense mutations. In most cases, PMM-CDG patients are compound heterozygotes, and there are no reports describing the homozygosity of the most frequent mutation p.R141H because it is probably embryonically lethal (Matthijs et al. 1998). The homozygous state of other mutations like p.F119L, p.Y64C, p.D65Y, p.P113L, p.N216I, p.Y106F, p.F183S, and p.T237M has been described by different authors (Matthijs et al. 2000; Neumann et al. 2003; Najmabadi et al. 2011; Perez et al. 2011).

The population-based biobank of the Estonian Genome Center at the University of Tartu (EGCUT) contains almost 52,000 samples of the adult population (aged ≥18 years), which closely reflects the age, sex, and geographical distribution of the Estonian population, making it a valuable resource for population-based genetic studies (Leitsalu et al. 2015). Regarding clinical care, there is only one center in Estonia at the Tartu University Hospital (TUH) that consults the patients suffering from inborn errors of metabolism. Since 2012, CDG screening (serum transferrin isoelectric focusing, TIEF) is performed at TUH on requests made by clinicians from the whole country. Thus, it is highly likely that all patients diagnosed with CDG in Estonia have been clinically followed up in TUH.

Several reports describe different PMM2 mutations and their frequencies in larger cohorts of PMM2-CDG patients, but to our knowledge, only one report has estimated the disease frequency based on allele frequencies among healthy individuals (Schollen et al. 2000). Our aim was to evaluate the presence of different PMM2-CDG-causing mutations in a population-based cohort and to calculate the expected frequency of PMM2-CDG in Estonia. Also, we analyzed the prevalence of PMM2-CDG based on our patient group data.

Methods

Population Cohort

Whole genome sequencing (WGS) data of 2,244 geographically distributed individuals (selected randomly by county of birth) from EGCUT were available. WGS samples were sequenced at the Broad Institute (Cambridge, MA, USA) following a PCR-free sample preparation. Libraries were sequenced on the Illumina HiSeq X Ten (Illumina, San Diego, CA, USA) with the use of 150 bp paired-end reads to 30× mean coverage with a median insert size of 400 bp ± 25%.

All variants identified in the PMM2 were extracted and alleles listed as disease-causing according to HGMD were counted to estimate pathogenic allele frequencies. In addition, all other protein-altering variants were evaluated for possible additional novel disease-causing mutations.

Patient Cohort

Five patients from three families (Table 1) have been diagnosed with PMM2-CDG in Estonia. All of them have European ancestry and their parents are unrelated Estonians, except for one parent who is French. All patients showed positive TIEF type 1 profile on screening and PMM2-CDG was molecularly confirmed with different DNA sequencing approaches.

Table 1.

PMM2-CDG genotypes in Estonia

PMM2-CDG genotypes	Number of patients	Phenotype
p.R141H/p.V231M	1	Severe
p.R239W/p.V231M	3a	Mild
p.R123Q/p.V231M	1	Severe

^aSiblings, described by Vals et al. (2017)

Statistical Methods

According to census in 2011, there are 1.29 million enumerated residents in Estonia and 18.4% of them are children, defined as age less than 18 years. To calculate the expected disease frequency, we used the assumption of p.R141H homozygotes being embryonically lethal (Matthijs et al. 1998). Thus, if q is the allele frequency of p.R141H and r the combined allele frequency for other identified mutations in our cohort, then r ² + 2qr denotes the expected disease frequency in the given population. For 95% confidence intervals (CI), test of given proportions (prop.test) was conducted in R version 3.2.3 (R Core Team 2016).

Results

Population Cohort

Out of 2,244 samples, 19 carried one mutated PMM2 allele and altogether, five different mutations were identified: p.R141H (10 alleles), p.V231M (5 alleles), p.R239W (2 alleles), p.V67M and p.T237R (both 1 allele) (Table 2). In addition to disease-causing variants appearing in HGMD, no possibly pathogenic novel mutations were identified. Based on these results, the observed carrier frequency for all PMM2 disease-causing mutations was 1/118 (95% CI 1/74–1/190) and for the most frequent mutation p.R141H, 1/224 (95% CI 1/118–1/441). Allele frequency of p.R141H (q) was 1/449 and of other mutations (r), 1/499. Based on these data, the expected frequency of the disease (r ² + 2qr) in Estonian population is 1/77,000.

Table 2.

Number of PMM2 mutations identified in population cohort (2,244 individuals) and the diagnosed five patients (three families)

Mutation	Population cohort	Patients
p.V67M	1	–
p.R141H	10	1
p.V231M	5	3
p.T237R	1	–
p.R239W	2	1
p.R123Q	–	1

Patients

The five patients were born from 1998 to 2015. One patient died in the first week of life and one has reached adulthood. Thus, the current prevalence of PMM2-CDG can be calculated for the whole population (four cases) as 1/322,000 (95% CI 1/117,000–1/1,007,000) and for the less than 18 years age group (three cases), 1/79,000 (95% CI 1/25,000–1/306,000).

Discussion

Many reports from different European countries describe cohorts of patients diagnosed with PMM2-CDG. The results give an overview about the frequencies of different mutations and genotypes, as well as their geographical distribution. p.R141H is the most commonly found mutation among molecularly confirmed Caucasian PMM2-CDG patients with prevalence ranging from 20.6 to 44% (Kjaergaard et al. 1998; Matthijs et al. 2000; Perez et al. 2011). Still, the population data have been only reported by Schollen et al. who studied p.R141H and p.F119L frequencies among Dutch neonates and Danish blood donors (Schollen et al. 2000). They showed that the carrier frequency for p.R141H is 1/72 and the expected disease frequency is 1/20,000 in these populations.

The Estonian Biobank represents 5% of Estonian adults and offers a unique database for research and population-based studies (Leitsalu et al. 2015). The data of 2,244 individuals revealed five different mutations with a combined carrier frequency of 1/118 for all mutations. The carrier frequency for p.R141H was 1/224. Compared to our results, the Dutch and Danish pooled data show a three times higher p.R141H frequency. Carrier frequency for other mutations is estimated to be 1/300 to 1/400 (Schollen et al. 2000) which in our population ranges from 1/448 to 1/2,244 depending on the mutation.

To our knowledge, there are no reports about the patients homozygous for the mutations identified in our cohort. Only the homozygosity of p.R141H has been shown to be absent, as it is probably lethal (Matthijs et al. 1998). By excluding p.R141H homozygotes, the expected frequency of PMM2-CDG in the Estonian population according to the modified Hardy–Weinberg equilibrium is 1/77,000. The frequency might be somewhat lower, as we have not considered the possibility that some of the recombinants of detected mutations are incompatible with life. If we compare the frequency with our population size and its age-specific distribution, there should be up to 16 people, including 3 children, with PMM2-CDG in Estonia.

So far, we have molecularly confirmed the PMM2-CDG in five children from three families. They are compound heterozygotes with four different previously described missense mutations. Undeniably, because of the small number of patients, it is difficult to draw any conclusions about the characteristic genotypes among our patients as well as to compare them with other countries, but they all have p.V231M in one allele and only one patient has p.R141H in the other allele. Based on their genotypes, our hypothesis was that the most frequent PMM2 mutation among Estonians is p.V231M. However, similarly to the other reports, the most frequently found mutation among biobank participants was p.R141H (56%) and p.V231M was the second most common mutation (23%). p.R239W was also represented in the population cohort, but p.R123Q was not. It might be explained by the fact that the allele with p.R123Q is inherited from the parent with French origin and the mutation is not geographically characteristic of Estonia. In our population cohort, we also did not find p.F119L, which is the second most common mutation among the South-Scandinavian population (Kjaergaard et al. 1998; Bjursell et al. 2000).

The prevalence of PMM2-CDG in Estonia in the whole population calculated by patient data was much lower, 1/322,000. We believe that the prevalence must be higher as the disease has not been diagnosed in any adult patients. Therefore, based on the data about the expected frequency of the disease, there should be undiagnosed patients with PMM2-CDG in Estonia whether due to patients not surviving into adulthood or due to the possible presence of undiagnosed individuals with mild phenotype. Although the availability of diagnostic tests is good in Estonia, congenital metabolic diseases, including CDG, are less likely to be considered and investigated by clinicians among the adult patients and CDG screening with serum TIEF serves mainly children. This is supported by the fact that three out of the five patients in Estonia were diagnosed with PMM2-CDG during infancy and that two other patients with a mild clinical presentation got their diagnosis as adolescents after the diagnosis of their youngest sibling (Vals et al. 2017). A similar age distribution favoring the diagnosis in children was showed by Matthijs et al. (2000). Therefore we also calculated the prevalence among children. As one patient has reached adulthood, the prevalence in the less than 18 years age group is 1/79,000, which is similar to the expected frequency of PMM2-CDG in Estonia based on population allele frequencies.

In conclusion, we showed that the frequency of PMM2-CDG in Estonia is lower than in other European populations reported thus far. We have also demonstrated that population cohort data give useful new information about the epidemiology of the PMM2-CDG.

Author Disclosure Statement

The authors declare no potential conflicts of interest with respect to the authorship and/or publication of this article.

Concise One-Sentence Take-Home Message

The expected frequency of the PMM2-CDG in Estonian population is 1/77,000.

General Rules

Details of the Contributions of Individual Authors

Mari-Anne Vals – performed serum transferrin isoelectric focusing to four patients, analyzed the population cohort data, performed statistical analysis, and compiled the manuscript.

Sander Pajusalu – analyzed the population cohort data, performed statistical analysis, coordinated analysis between different centers, and compiled the manuscript.

Mart Kals – analyzed biobank data, including quality control and compiled the manuscript.

Reedik Mägi – analyzed biobank data and compiled the manuscript.

Katrin Õunap – planned the study, diagnosed PMM2-CDG patients, coordinated work between different centers, and compiled the manuscript.

Correspondent and Guarantor

Mari-Anne Vals.

A Competing Interest Statement

The authors Mari-Anne Vals, Sander Pajusalu, Mart Kals, Reedik Mägi, and Katrin Õunap declare no potential conflicts of interest with respect to the authorship and/or publication of this article.

Details of Funding

This work was supported and funded by the Estonian Research Council grant PUT355, EU H2020 grant 692145, Estonian Research Council Grant IUT20-60, IUT24-6 and European Union through the European Regional Development Fund Project No. 2014-2020.4.01.15-0012 GENTRANSMED.

Details of Ethics Approval

This study was approved by the Research Ethics Committee of the University of Tartu (181/T-16, 20.04.2009 and 235/M-13, 17.03.2014). All participants in Estonian Biobank have signed a broad consent for using their data for research, and we also have an approval from the local ethics committee to use the omics data of gene donors of Estonian Biobank for genetic research (approval 234/T-12 for “Omics for health: an integrated approach to understand and predict human disease”).

A Patient Consent Statement

Informed consent was obtained from the parents of the five patients.