Abstract
Objectives
Monogenic diabetes (MD) is a group of diabetes subtypes caused by defects in single genes. We report phenotypes and genotypes of MD among Sudanese children.
Methods
Referred patients (from birth to 18 years of age) with diabetes and a clinical diagnosis of MD to Gaafar Ibnauf Pediatric Tertiary Hospital or the Sudan Childhood Diabetes Center between January 2006 and April 2023 were included. Patients were divided into two groups based on onset of diabetes before six months of age (Group 1, or neonatal diabetes mellitus) or after (Group 2, or non-neonatal diabetes mellitus). Genetic testing was performed for 87 patients at the Exeter Genomics laboratory and for one patient at the University of Cambridge, Metabolic Research Laboratories, UK.
Results
Out of 88 patients, 50 were from Group 1 and 38 from Group 2. We reported consanguinity in 63.6 % of the cohort and identified disease-causing variants for 18 genes in 43.2 % (Group 1) and 37.5 % (Group 2) of patients from the total cohort. The commonest causes in Group 1 and Group 2 were pathogenic variants in the EIF2AK3 and WFS1 genes, respectively. Pathogenic variants in recently reported novel genes ZNF808, NARS2, and FICD were detected in 8.5 %, 4.2%, and 1.4 % of patients, respectively. Patients with a disrupted WFS1 gene were found to have deafness (92.8 %) and optic atrophy (64 %). While skeletal deformities and liver disease were both seen in 28.6 % of patients with pathogenic variants in the ElF2AK3 gene. Hepatomegaly and hypophosphatemic rickets were uniformly seen in patients with pathogenic variants in the SLC2A2 gene. Generalized subcutaneous tissue loss and acanthosis nigricans were main features in AGPAT2 and INSR variants, respectively.
Conclusions
Characterization of MD in Sudan showed a predominance of syndromic forms. Genetic studies conducted on consanguineous populations may raise higher probabilities in identifying rare genes.
Keywords: monogenic diabetes, syndromic diabetes, Sudan, Wolcott-Rallison syndrome, wolfram’s syndrome, neonatal diabetes mellitus
Introduction
Monogenic diabetes (MD) is a heterogeneous group of rare forms of diabetes mellitus (DM) caused by single-gene defects [1]. To date, more than 50 distinct genetic forms have been identified [2], 3]. Neonatal diabetes mellitus (NDM) and maturity-onset diabetes of the young (MODY) represent the majority of MD cases [4]. The prevalence of MD is estimated to be 2–5% among all patients with diabetes [5]. Disease-causing variants can lead to impaired β cell differentiation, development and function [6]. Additionally, genetic defects may affect insulin synthesis, processing, secretion or cause insulin receptor dysfunction [6]. Other pathophysiological mechanisms may involve endoplasmic reticulum (ER) and mitochondrial dysfunction, defects in nucleoside or triacylglycerol synthesis, as well as several other pathways that remain poorly understood [7], 8].
Clinical features are highly variable and are influenced by gene function, the type and location of the pathogenic variant, as well as other factors affecting severity and penetrance [6]. Currently, many monogenic forms, such as MODY are misdiagnosed as type 1 DM (T1DM) or type 2 DM (T2DM) [9]. In contrast, syndromic forms of MD, characterized by distinct phenotypes, are more readily identifiable clinically and constitute a significant proportion of patients with MD from populations with high rates of consanguineous marriage [10].
Next-generation sequencing (NGS) facilitates the discovery of additional MD genes and expands our understanding of the pathophysiology underlying these rare forms of diabetes [9]. Precision in genetic diagnosis of MD positively impacts patient management and improves prognosis [2]. However, there is scarcity of studies addressing MD in populations outside Europe. In this study, we describe the genetic patterns and clinical features of MD in a large cohort from a population with a high degree of consanguinity (Sudan), providing new insights.
Materials and methods
This observational cross-sectional study was conducted at Gaafar Ibnauf Pediatric Tertiary Hospital and the Sudan Childhood Diabetes Center, both of which provide inpatient and outpatient services for children with DM. These two centers, located in Khartoum-the capital state-are the only tertiary diabetes centers in Sudan, receiving referrals from all states. During the study period, from January 2006 to April 2023, all referred Sudanese patients with DM presenting from birth to 18 years of age, with clinical suspicion for MD were enrolled after meeting the inclusion criteria described below. Patients were then divided into two groups based on the age of diabetes onset: Group 1 comprised the neonatal diabetes mellitus group (NDM) (onset before six months of age), and Group 2 comprised the non-neonatal diabetes mellitus group (non-NDM) (onset beyond six months of age). Medical records were reviewed to collect demographic data, including sex, age at onset, family history of consanguinity and other clinical information. Additional date included treatment details and disease-related complications.
Inclusion criteria
The selection criteria included anyone of the following:
-
–
The onset of diabetes occurs before six months of age.
-
–
Diabetes accompanied by syndromic features or extra-pancreatic manifestations.
-
–
Patients with diabetes onset after six months of age who have low insulin requirements (typically less than 0.5 units/kg/day), have discontinued insulin therapy without subsequently developing diabetic ketoacidosis (DKA), or have a family history of DM in two consecutive generations and have been tested for pancreatic autoantibodies.
-
–
Patients with DM who have siblings with a confirmed genetic diagnosis.
Genetic testing
Deoxyribonucleic acid (DNA) was extracted from peripheral blood using standard methods in 88 patients clinically diagnosed with MD. Interpretation and classification of sequence variants were performed according to the American College of Medical Genetics and Genomics guidelines [11]. Only variants classified as likely pathogenic (class 4) or pathogenic (class 5) were considered confirmed genetic causes.
Genetic testing performed at Exeter Genomics Laboratory in the UK
Genetic analysis was performed on 49 patients with NDM and 38 with non-NDM as previously described [12], 13].
Genetic Analysis for NDM (Group 1):
Briefly, all known genetic causes of NDM were tested using a combination of Sanger sequencing, targeted NGS, and MS-MLPA (Multiplex ligation dependent probe amplification). Whole-genome sequencing was performed for patients in whom no pathogenic variant in known genes were identified through prior analysis utilizing the BGI DNBSEQ technology. Reads were aligned to the GRCh37/hg19 human reference genome using BWA-MEM (v0.7.15), followed by local realignment using GATK Indel Realigner (v3.7.0). Variants were called using the GATK haplotype caller and annotated using Alamut Batch (Interactive Biosoftware v1.11, Rouen, France).
-
B.
Genetic Analysis for non-NDM (Group 2):
The first-line test was NGS of the MD genes. The gene panel used for non-NDM patients was different from the one used to analyze NDM patients (see Supplementary Table S1).
Genetic testing performed at the Metabolic Research Laboratories, University of Cambridge, UK
Genetic testing for one patient with NDM (Group 1) was conducted by Sanger sequencing analysis of the insulin receptor (INSR) gene coding regions and splice junctions. Briefly, polymerase chain reaction (PCR) amplification of exons and their flanking sequences was performed, followed by purification by Exo-SAP-IT (Affymetrix, Santa Clara, CA). The purified samples were then sequenced using the BigDye Terminator v3.1 cycle sequencing kit in an ABI3730 genetic analyzer (Applied Biosystems, Foster City, CA, USA) after clean up with Agencourt AMPure XP Beads (Beckman Coulter Inc, Atlanta, GA, USA). Sequence data were analyzed using Sequencher (Gene Codes Corp., Ann Arbour, MI, USA).
Results
Description of the cohort (n=88)
A total of 88 Sudanese patients from 77 unrelated families were included in the study. Fifty patients (56.8 %) were classified as NDM (Group 1) and 38 (43.2 %) as non-NDM (Group 2). Group 2 included patients with MODY and syndromic monogenic diabetes (SMD) (Figure 1).
Figure 1:
Classification of patients with monogenic diabetes mellitus (n=88). The total number of patients included in the study was divided into two broad categories: Group 1 (NDM) and Group 2 (non-NDM) based on the onset of diabetes mellitus being before or after six months of age. Group 2 was further divided into MODY and SMD groups. Subsequently, each group was further divided into two groups based on the presence or absence of identified disease-causing variants. %=percentage, MODY=maturity-onset diabetes of the young, n=number of patients, NDM=neonatal diabetes mellitus, non-NDM = non-neonatal diabetes mellitus, SMD=syndromic monogenic diabetes.
The male-to-female ratio was 1.2:1. The mean age of onset for NDM (Group 1) was 66.56±49.93 days, while for non-NDM (Group 2) it was 6.55±5.39 years. A family history of parental consanguinity (first-or second-degree cousins) was reported in 56 patients from the cohort (63.6 %). Among the 71 patients with identified genetic causes, homozygous variants were found in 55 patients (77.5 %).
Monogenic diabetes types and their genetic variants
Group 1: NDM (n=50)
This group constituted more than half of the total cohort. Disease-causing variants were identified in 14 different genes, affecting 38 patients (Figure 1).
Syndromic forms constituted the majority of NDM (Group 1) patients, with the most common cause being recessive variants in the eukaryotic translation initiation factor alpha 2-kinase 3 (EIF2AK3) gene, which cause Wolcott-Rallison syndrome (WRS) (Table 1).
Table 1:
Genetic description of the patients in Group 1 (NDM).
| Gene | Transcript reference sequence | Number of patients (number of families) | Male (females) | Genetic description {number of patients with the same variant} | |||
|---|---|---|---|---|---|---|---|
| cDNA description | Protein description | Zygosity | ACMG | ||||
| SLC2A2 | NM_000340.2 | 3 (3) | 2 (1) | c.157C>T {5} c.320G>A c.735C>A c.1171‐2A>G | p.Arg53* p.Gly107Asp p.Tyr245* p.? | Homo Homo Homo Homo | P LP LP P |
| EIF2AK3 | NM_004836.7 | 7 (7) | 4 (3) | c.805_806dup c.1912C>T c.1650+2T>A c.1742del c.2970T>A c.1912C>T c.3026C>T | p.Pro270Phefs*37 p.Arg638* p.? p.Asn582Thrfs*9 p.Tyr990* p.Arg638* p.Ser1009Phe | Homo Homo Homo Homo Homo Homo Homo | LP P LP LP LP P LP |
| ZNF808 | NM_001039886.4 | 3 (2) | 2 (1) | c.2309del {3} | p.Asn770Ilefs*98 | Homo | LP |
| INSR | NM_000208.4 | 1 | (1) | c.1049C>T | p.Ser323Leu | Homo | P |
| KCNJ11 | NM_000525.4 | 4 (3) | 4 | c.175G>A {2} c.158G>A c.1000G>C | p.Val59Met p.Gly53Asp p.Gly334Arg | Hete Hete Hete | P LP P |
| SLC19A2 | NM_006996.3 | 3 (2) | 1 (2) | c.327_334del {3} | p.Ile109Metfs*27 | Homo | LP |
| NARS2 | NM_024678.6 | 3 (3) | 2 (1) | c.648C>G {3} | p.Phe216Leu | Homo | LP |
| INS | NM_00207.3 | 3 (3) | 1 (2) | c.94G>A c.188-31G>A c.-331C>G | p.Gly32Ser p.? p.? | Hete Hete Homo | LP LP LP |
| Chr6q24 | NA | 3 (3) | 2 (1) | Duplication of the paternal allele Maternal hypomethylation {2} |
Imprinting defect | NA | |
| AGPAT2 | NM_006412.4 | 2 (2) | 2 | c.524G>C c.589-2A>G | p.Arg175Pro p.? | Homo Homo | LP LP |
| ABCC8 | NM_001287174.1 | 2 (2) | 1 (1) | c.3940C>A c.2476C>T | p.Arg1314Ser p.Arg826Trp | Homo Hete | LP P |
| GCK | NM_000162.5 | 2 (1) | 2 | c.216_217dup {2} | p.Asp73Glyfs*15 | Homo | P |
| PTF1A | NM_178161.3 | 1 | (1) | Distal enhancer Chr10:g.23508363A>G | p.? | Homo | P |
| FICD | NM_007076.3 | 1 | 1 | c.1113G>T | p.Arg371Ser | Homo | LP |
| INS | NM_00207.3 | 1 | (1) | c.107T>G | p.Val36Gly | Hete | VUS |
The Table illustrates names of genes and transcript reference numbers in relation to number of patients and families, gender, and genetic descriptions of variants, including ACMG classification for patients from Group 1. ACMG, american college of medical genetics and genomics classification; Hete, heterozygous; Homo, homozygous; LP, likely pathogenic; NA, not applicable; NDM, neonatal diabetes; P, pathogenic.
Transient neonatal diabetes (TND) was identified in four patients. It was caused either by methylation abnormalities in the imprinted genomic region on chromosome 6q24 (Chr. 6) (n=3; one case due to paternal duplication and two due to maternal hypomethylation defects) or by pathogenic variants in the solute carrier family two member 2 (SLC2A2) gene (n=1).
Isolated permanent NDM was primarily caused by activating pathogenic variants in the potassium ATP channel (KATP) genes: the potassium inwardly rectifying channel subfamily J member 11 (KCNJ11, n=4) and the ATP-binding cassette subfamily C member 8 (ABCC8, n=2) (Table 1).
No genetic cause for NDM could be identified in 11 patients. One patient harbored a heterozygous variant of uncertain significance (VUS) in the INS gene (c.107T>G, p.Val36Gly) (Table 1).
Group 2: Non-NDM (n=38)
This group included 38 patients, and disease-causing variants in seven different genes were detected in 33 patients (Figure 1).
Similar to Group 1, syndromic forms accounted for the majority of patients from Group 2. Recessive disease-causing variants in the Wolframin ER transmembrane glycoprotein 1 (WFS1) gene, which cause Wolfram syndrome (WFS), were the most common genetic cause, followed by pathogenic variants in the SLC2A2 gene, responsible for Fanconi–Bickel syndrome (FBS) (Table 2).
Table 2:
Genetic description of the patients in Group 2 (Non-NDM).
| Gene | Transcript reference sequence | Number of patients (number of families) | Males (females) | Genetic description {number of patients with same variant} | |||
|---|---|---|---|---|---|---|---|
| cDNA description | Protein description | Zygosity | ACMG | ||||
| WFS1 | NM_006005.3 | 14 (10) | 4 (10) | c.639_642del c.1230_1233del {2} c.1997G>A {2} c.1180G>T c.1572_1573ins[AluYd8;1558_1572] {4} c.(712+1_713-126)_(*94_?) del c.1623T>A c.2005T>G {2} |
p.Ala214Serfs*72 p.Val412Serfs*29 p.Trp666* p.Glu394* p. ? p.? p.Cys541Ter p.Tyr669Asp |
Homo Homo Homo Homo Homo Homo Homo Homo Homo |
P P P P P P P P LP |
| SLC2A2 | NM_000340.2 | 7 (7) | 4 (3) | c.157C>T c.1171‐2A>G |
p.Arg53* p? |
Homo Homo |
LP P |
| ZNF808 | NM_001039886.4 | 3 (1) | 2 (1) | c.2309del {3} | p.Asn770Ilefs*98 | Homo | LP |
| INSR | NM_000208.4 | 4 (3) | 1 (3) | c.1466A>G/c.3370-2A>C c.3038C>T/c.3287del {2} c.3086T>C |
p.Asn489Ser/p.? p.Pro1013Leu/p.Gly1096Alafs*7 p.Leu1029Pro |
Chete CHete DHete |
LP LP LP |
| SLC29A3 | NM_018344.6 | 3 (3) | 2 (1) | c.1228C>T c.1087C>T c.1309G>A |
p.Gln410* p.Arg363Trp p.Gly437Arg |
Homo Homo Homo |
LP LP LP |
| PIK3R1 | NM_181523.3 | 1 | 1 | c.1478T>G | p.Ile493Arg | Hete | LP |
| HNF1A | NM_000545.8 | 1 | 1 | c.326+2T>C | p.? | Hete | P |
| INSR | NM_000208.4 | 1 | (1) | c.766C>T | p.Arg256Cys | Hete | VUS |
The Table illustrates names of genes and transcript reference numbers, each in relation to number of patients and families, gender, and genetic descriptions of variants, including ACMG classification for patients in Group 2. ACMG, american college of medical genetics and genomics classification; CHete, compound heterozygous; DHete, de novo heterozygous; Hete, heterozygous; Homo, homozygous; LP, likely pathogenic; MODY, maturity onset diabetes of youth; NA, not applicable; Non-NDM, non-neonatal diabetes mellitus, P, pathogenic.
A MODY-causing variant was detected in only one patient (Figure 1). In four patients, no disease-causing variant was identified, while in one patient with clinical features of Rabson–Mendenhall syndrome (RMS), a heterozygous VUS (c.766C>T, p.Arg256Cys) in the INSR gene was found (Table 2).
Phenotypic characteristics of patients
Overall, clinical features varied according to the genetic diagnosis. In the majority of patients, DM preceded the onset of other clinical features. DKA was the presenting feature in 23 patients, most of them whom belonged to Group 1 (87 % of the patients who presented with DKA).
Extra-pancreatic clinical features were observed in syndromic forms of each group. Among seven patients in Group 1 with pathogenic variants of the EIF2AK3 gene, the most common features were skeletal deformities and liver disease, each present in 28.6 % patients (Table 3). Among 14 patients from Group 2 with pathogenic variants in the WFS1 gene, deafness (92.8 %) and optic atrophy (64 %) were the most prevalent clinical features.
Table 3:
Clinical features of patients (n=71) with pathogenic variants. Distribution and frequency of clinical features according to the involved disease-causing variant among 71 patients.
| Gene (number of patients) | Clinical features | n (%) |
|---|---|---|
| WFS1 (14) | Optic atrophy | 9 (64 %) |
| Sensory neural deafness | 13 (92.8 %) | |
| Diabetes insipidus/renal disease | 6 (42.8 %) | |
| Neurological disease | 1 (7.1 %) | |
| SLC2A2 (10) | Skeletal disease | 10 (100 %) |
| Liver disease/hepatomegally | 10 (100 | |
| Renal disease/renal tubular acidosis | 10 (100 %) | |
| Neonatal diabetes | 3 (30 %) | |
| EIF2AK3 (7) | Liver disease | 2 (28.6 %) |
| Skeletal disease | 2 (28.6 %) | |
| Renal disease | 1 (14.3 %) | |
| Neurological disease | 2 (28.6 %) | |
| Neonatal diabetes | 7 (100 %) | |
| INSR (5) | Acanthosis nigricans | 5 (100 %) |
| Cutaneious features | 5 (100 %) | |
| Coarse facial features | 5 (100 %) | |
| Hyper androginsm | 4 (80 %) | |
| Polycyctic ovaries | 4 (80 %) | |
| Nenatal diabetes | 1 (20 %) | |
| PTF1A (1) | Liver disease/hepatomegaly | 1 (100 %) |
| Skeletal disease | 1 (100 %) | |
| Malabsorption | 1 (100 %) | |
| Neonatal diabetes | 1 (100 %) | |
| AGPAT2 (2) | Genralized lipodystrophy | 2 (100 %) |
| Dylipidemia/xanthoma | 1 (50 %) | |
| Neonatal diabetes | 2 (100 %) | |
| PIK3R1 (1) | Dysmorphic facial features | 1 (100 %) |
| Cardiac disease | 1 (100 %) | |
| Cutaneious features | 1 (100 %) | |
| Neurological disease | 1 (100 %) | |
| Partial lipodystrophy | 1 (100 %) | |
| SLC19A2 (3) | Anemia | 3 (100 %) |
| Cardiac disease | 2 (66.7 %) | |
| Sensory neural deafness | 2 (66.7 %) | |
| Neurological disease | 1(33.3 %) | |
| Neonatal diabetes | 3 (100 %) | |
| FICD (1) | Neurological disease | 1 (100 %) |
| Bilitral catract | 1 (100 %) | |
| Neonatal diabetes | 1 (100 %) | |
| SLC29A3 (3) | Cutaneious features | 1 (100 %) |
| Sensory neural deafness | 2 (66.7 %) | |
| Proptosis | 1 (33.3 %) | |
| ZNF808 (6) | Malabsorption/chronic diarrhea | 6 (100 %) |
| Neonatal diabetes | 3 (50 %) | |
| NARS2 (3) | Neurological disease | 3 (100 %) |
| Neonatal diabetes | 3 (100 %) | |
| INS (3) | Neonatal diabetes | 3 (100 %) |
| GCK (2) | Neurological disease | 1 (50 %) |
| Neonatal diabetes | 2 (100 %) | |
| KCNJ11 (4) | Neonatal diabetes | 1 (100 %) |
| ABCC8 (2) | Neonatal diabetes | 1 (100 %) |
| Chr6 (3) | Neonatal diabetes | 1 (100 %) |
| HNF1A (1) | No specefic clinical features | NA |
%, percentage; n, number of clinical features; NA, not applicable.
All 10 patients with pathogenic variants in the SLC2A2 gene presented with the typical clinical features of FBS, with 30 % of these patients belonging to Group1. Two patients from Group 1, carrying pathogenic variants in AGPAT2 gene, exhibited generalized loss of subcutaneous tissue and dyslipidemia. Among all five patients (including one from Group 1) with pathogenic variants the INSR gene, acanthosis nigricans was universally observed. Other genetic variants manifested with distinct clinical features, as detailed in Table 3.
Discussion
In the context of MD, we aimed to characterize the genotypes and phenotypes within our Sudanese population and found that syndromic forms predominated. Clinical features of MD ranged from isolated hyperglycemia to complex multisystemic features. DKA was the initial presenting sign in many patients from Group 1. The delay in recognition and management of diabetes in infants may have likely resulted in the increased incidence of DKA in Group1 [14]. The wide variation in clinical features among the diverse forms of MD is attributed to the distinct pathophysiological roles of each involved gene [6]. The phenotypic heterogeneity (i.e., “variable expressivity”) observed between related patients carrying the same genotype, as seen in this study, has been previously reported [15], 16]. Extra-pancreatic clinical features in syndromic forms of MD are hallmark characteristics of each specific pathogenic variant, and DM usually precedes these features early in the disease course, as observed in this study [17].
In this study, genetic variants and forms of MD varied according to the age of diabetes onset. In Group 1, patients with NDM (i.e., onset before six months of age) comprised half of the cohort. The early onset of diabetes in newborns and infants, combined with the presence of distinctive syndromic clinical features, likely alerted physicians to the possibility of MD. Considering these factors, along with the high rate of consanguinity in the Sudanese population, most MD cases in this study were syndromic. In recent years, increasing reports from populations with high consanguinity have highlighted clinical and genetic causes that differ from those commonly observed worldwide [10], 18], 19]. Disease-causing variants responsible for WRS were the most prominent cause of NDM, consistent with findings from some Arab countries [20], [21], [22], [23], [24]. Pathogenic biallelic variants in EIF2AK3 lead to the accumulation of misfolded proteins within the ER, resulting in progressive β-cell dysfunction [25]. It has been recommended that, even in the absence of distinctive extra-pancreatic features, diagnostic consideration for WRS should be prioritized in patients with NDM from populations with high consanguinity [26], 27].
Both NDM and MODY are known to constitute the majority of MD subtypes; however, the prevalence of MODY in our population is apparently underestimated [4]. This underestimation may be attributed to the fact that islet autoantibodies and C-peptide levels are not routinely measured in patients with DM in Sudan due to the high cost of these tests and the lack of funded screening programs. Additionally, MODY patients are often overlooked by physicians because of limited awareness and a low index of clinical suspicion for MD, with very few, if any, utilizing MODY scoring systems. This challenge is compounded by the overlapping clinical features of MODY with the more common forms of diabetes (T1DM or T2DM) [28], 29]. According to the latest published data, the incidence of T1DM in Sudan is among the highest in Africa, at 10.1 per 100,000 individuals per year [30]. In that study, patients were diagnosed with T1DM based on clinical assessment by physicians rather than the presence of pancreatic autoantibodies [30]. Accurately identifying patients with MODY among this large diabetic population is a significant challenge, especially in low-resource settings, leading to a high likelihood of misdiagnosing many MODY cases.
In this study, genetic variants for NDM and MD with later onset were clearly overlapping. For example, the SLC2A2 variant was identified in two affected siblings – one presenting with NDM (Group 1) and the other with non-NDM (Group 2). Pathogenic variants of the SLC2A2 gene, which encodes the glucose transporter 2 (GLUT2) and causes FBS, accounted for a significant proportion of patients in this study. In recent years, there have been increasing reports of SLC2A2 variants causing MD, further supporting the role of GLUT2 in insulin secretion and glucose homeostasis [31], 32].
In Group 2 (Non-NDM), patients presented with disease onset after six months of age. In this group, biallelic variants in the WFS1 gene, which is responsible for WFS, also known as DIDMOAD syndrome and characterized by diabetes insipidus, diabetes mellitus, optic atrophy, and deafness – were the most prevalent cause, particularly among juvenile and adolescent patients. ER dysfunction is the primary pathogenic mechanism in WFS, with pancreatic β cells and neuronal cells exhibiting an increased vulnerability [33]. There is no clear genotype-phenotype correlation, and the exact age at which each clinical feature manifests varies [34]. Similarly, in our study, this autosomal recessive neurodegenerative disease progressed from early childhood onset of diabetes mellitus to the development of extra-pancreatic features at varying ages, ranging from childhood to late adolescence. These features included optic atrophy, sensorineural deafness, diabetes insipidus, as well as renal and neurological complications.
IRS accounted for a substantial number of patients in this study. Disease severity and age of onset are influenced by both the number of affected alleles and the position of the pathogenic variant [35], 36]. Insulin resistance and hyperandrogenism underlie the phenotypic presentation, with acanthosis nigricans serving as a key clinical feature as observed in all patients with pathogenic disruptions in the INSR gene in this study [37]. The age of onset for DM in IRS varies widely; very few cases present early as NDM, such as one patient in Group 1. More commonly, onset occurs later in life, when it is often mistaken for T2DM [38].
At the other end of the insulin resistance spectrum, lipodystrophy syndromes observed in this study appeared in two forms: congenital generalized lipodystrophy (CGL) and partial lipodystrophy. Pathogenic variants in the 1-acylglycerol-3-phosphate O-acyltransferase 2 (AGPAT2) gene result in impaired triacylglycerol synthesis and storage in adipocytes [39], 40]. In recent years, there have been few reports of AGPAT2 variants causing CGL type 1 and NDM, and all patients with AGPAT2 variants identified in this study presented with NDM [41].
Partial lipodystrophy syndromes can occur in children, and monoallelic variants in the PIK3R1 gene are known to cause partial lipodystrophy accompanied by multisystem disease, referred to as SHORT syndrome (characterized by short stature, hyperextensibility and/or inguinal hernias, ocular depression, Rieger anomaly, and delayed teething). This is exemplified by an adolescent from Group 2 who presented with diabetes, dysmorphic facial features, poor growth, insulin resistance, selective lipodystrophy, hyperpigmentation, and cardiomyopathy [42], 43].
The Solute Carrier Family 29 Member 3 (SLC29A3) gene encodes the human equilibrative nucleoside transporter 3 (hENT3), which is essential for the sodium-independent transport of nucleosides and plays a critical role in nucleotide synthesis [44], 45]. In addition to a constellation of multisystemic features, all three patients with SLC29A3 variants from Group 2 exhibited a consistent phenotypic presentation, including the hallmark cutaneous features of H syndrome, such as cutaneous hyperpigmentation, overlying hypertrichosis, edema, and sclerodermatous thickening.
Advancements made by genetic analysis in MD have helped to uncover the involvement of many rare or novel loci in the genome, especially among consanguineous populations [46]. In this study this was evident in the detection of a homozygous stop-gain variant (p.Asn770Ilefs ∗98) in a recently reported gene, ZNF808. This pathogenic variant was detected in six patients in this study. Three of whom presented with NDM (Group 1) were published previously in the novel report [47]. Due to the recent discovery and rarity of this variant, there is no clear phenotypic presentation, and further studies on the exact pathophysiology are required [47]. Reported clinical features in this study were early onset of diabetes, recurrent hypoglycemia, pancreatic insufficiency, and poor growth.
In this study, a biallelic loss-of-function variant (p.Phe216Leu) in a recently reported gene, NARS2 was a cause of NDM in three unrelated patients from Group 1. The NARS2 gene is known to encode an aminoacyl-tRNA synthetase, designated as mitochondrial aminoacylation (mt-aaRSs), crucial for the initiation of mitochondrial protein synthesis. To date, 18 different NARS2 disease-causing variants have been reported to cause early infantile neurodegenerative disorders [48]. The interplay between mitochondrial genes and diabetes has long been established but was only recently reported for the first time; to cause NDM with neurological manifestations in two siblings [49]. All three patients with NARS2 variants in this study represented 38 % of the recently published largest cohort of individuals with diabetes caused by NARS2 variants [50]. Our patients had a severe turbulent course of NDM with DKA, refractory seizures, and multi-organ failure and unfortunately died early in infancy. Further studies are recommended to elicit the exact disease-causing mechanism in NARS2 recessive variants resulting in neonatal and early-onset diabetes.
Pathogenic variants in the FICD gene, which were recently added to the list of causes of MD, result in DM in early infancy with neurodevelopmental delay [51]. A novel missense variant p.(Arg371Ser) in the FICD gene caused NDM in one patient from Group 1, with a similar clinical picture to that reported from three different consanguineous families with MD [51]. The FICD gene encodes a bifunctional Fic domain-containing enzyme, BiP, which regulates the ER Hsp70 chaperone [52].
Genetic discoveries made by NGS have opened avenues for clinical trials and studies that have led to dramatic improvements in the management of MD. This is illustrated in the remarkable improvement in glycemic control and neurological features followed the use of sulfonylurea therapy in patients with pathogenic variants of KATP channel genes [53], 54]. Despite the minority of patients in this study with NDM and MODY who were successfully transitioned to sulfonylurea, our report still reflected the merit of genetic testing in improving glycemic control and the quality of life by sparing these families the burden of daily insulin injections.
The limitations of this study included the high probability of missing out on patients with MODY due to some inconsistencies in physicians’ selection of referred patients with DM from the population for MODY testing and the lack of funded screening programs to support routine autoantibody testing of patients with diabetes in our population.
Conclusions
In this study, genetic testing helped in the characterization of MD in Sudan and revealed the predominance of SMD. The consanguineous complexity of the Sudanese population raises the probability of discovering rare or novel genes causing MD. We emphasize the need for educational awareness among physicians on MD and recommend a focused scoring system for MD testing to be practiced by all physicians treating patients with DM. Next-generation sequencing has improved our cognizance of the pathophysiology of MD and helped to shed more light on new insights in management, yet much still remains undiscovered.
Supplementary Material
Supplementary Material
Acknowledgments
The authors would like to extend their appreciation to Exeter Genomic Laboratories and University of Cambridge Institute of Metabolic Science. Special thanks to Mr. Gasmelseed Y. Ahmed, MD, PhD Biostatistician, Cardiology Department, Columbia University Medical Center, New York for statistical analysis and review.
Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/jpem-2025-0316).
Footnotes
Research ethics: The Endocrine and Diabetes Institutional Review Board at Gaafar Ibnauf paediatric tertiary hospital, Khartoum, has approved this study under approval number GIAH/EDIRB/2023/03/0012.
Informed consent: Written informed consent was provided from patients for genetic testing free of charge for research purpose and participation in this study with anonymized data.
Author contributions: SH: Is the primary caring physician of some patients, conceptualized and visualized the study, collected data from records, collected blood samples from patients for genetic testing and wrote the initial drafts, and finalized the main manuscript. SM, OB, AI and GM: primary caring physicians of some patients, reviewed the manuscript and assisted in data collection. AA, JS and OA reviewed the manuscript. KP, ED, RM, RV were responsible for molecular genetic diagnostics and interpretation, reviewed the genetic sections in the manuscript, reviewed and finalized the manuscript. MA: Primary caring physician of some patients, conceptualized the study, critically reviewed and finalized the manuscript. SH, ED, MA and KP were the main generators of this work and, as such, had full access to all the data in the study and they take responsibility for the integrity of the data and the accuracy of the data analysis. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Use of Large Language Models, AI and Machine Learning Tools: None declared.
Conflict of interest: The authors state no conflict of interest. Disclosure: A study on neonatal diabetes from the same centers was published in Wiley online Library, https://doi.org/10.1155/2024/2032425.
Research funding: Genetic testing at the University of Exeter was provided free of charge (cost covered by a Wellcome Trust Senior Investigator grant to Professors Andrew Hattersley and Sian Ellard). Genetic testing at Cambridge Metabolic Institute Science for INSR mutation in one patient was provided free of charge (cost covered by Dr Robert Semple MRCP PhD, Wellcome Trust Clinician Scientist, Honorary Consultant Endocrinologist). Genetic testing was funded by Diabetes UK (19/0005994 and 21/0006335). The work is supported by the National Institute for Health Research (NIHR) Exeter Biomedical Research Centre, Exeter, UK. The funding body had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. The views expressed are those of the author(s) and not necessarily those of NIHR.
Data availability: The data of this study are not publicly available due to privacy reasons but are available from corresponding author upon request (contact Dr. Samar Hassan hassansamar2006@gmail.com).
Contributor Information
Samar S. Hassan, Email: hassansamar2006@gmail.com.
Salwa A. Musa, Email: salwa_21@hotmail.com.
Elisa De Franco, Email: E.De-Franco@exeter.ac.uk.
Rebbeca Myers, Email: r.myers@exeter.ac.uk.
Racheal Van Heugten, Email: rachel.vanheughten@nhs.net.
Omer O. Babiker, Email: omerobabiker@gmail.com.
Areej A. Ibrahim, Email: aabashier@gmail.com.
Ghassan F. MohamadSalih, Email: ghasso81@gmail.com.
Amna Ahmed, Email: amnaib@gmail.com.
Jouyriah A. Shatta, Email: jouyriahmohmmed@gmail.com.
Olivia A. Al-Hassan, Email: olivoniy@gmail.com.
Kashyap A. Patel, Email: K.A.Patel@exeter.ac.uk.
Mohamed A. Abdullah, Email: mohamedabdullah@hotmail.com.
References
- 1.Zhang H, Colclough K, Gloyn AL, Pollin TI. Monogenic diabetes: a gateway to precision medicine in diabetes. J Clin Invest. 2021;131 doi: 10.1172/jci142244. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Murphy R, Colclough K, Pollin TI, Ikle JM, Svalastoga P, Maloney KA, et al. The use of precision diagnostics for monogenic diabetes: a systematic review and expert opinion. Commun Med. 2023;3:136. doi: 10.1038/s43856-023-00369-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Riddle MC, Philipson LH, Rich SS, Carlsson A, Franks PW, Greeley SAW, et al. Monogenic diabetes: from genetic insights to population-based precision in care. Reflections from a diabetes care editors’ expert forum. Diabetes Care. 2020;43:3117–28. doi: 10.2337/dci20-0065. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Jang KM. Maturity-onset diabetes of the young: update and perspectives on diagnosis and treatment. Yeungnam Univ J Med. 2020;37:13–21. doi: 10.12701/yujm.2019.00409. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Caballero LS, Gorgogietas V, Arroyo MN, Igoillo-Esteve M. Molecular mechanisms of β-cell dysfunction and death in monogenic forms of diabetes international review of cell and molecular. Biology. 2021;359:139–256. doi: 10.1016/bs.ircmb.2021.02.005. [DOI] [PubMed] [Google Scholar]
- 6.Greeley SA, Polak M, Njølstad PR, Barbetti F, Williams R, Castano L, et al. ISPAD clinical practice consensus guidelines 2022: the diagnosis and management of monogenic diabetes in children and adolescents. Paediatr Diabetes. 2022;23:1188. doi: 10.1111/pedi.13426. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Stone SI, Abreu D, McGill JB, Urano F. Monogenic and syndromic diabetes due to endoplasmic reticulum stress. J Diabetes Complicat. 2021;35:107618. doi: 10.1016/j.jdiacomp.2020.107618. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Yeung RO, Al Jundi M, Gubbi S, Bompu ME, Sirrs S, Tarnopolsky M, et al. Management of mitochondrial diabetes in the era of novel therapies. J Diabetes Complicat. 2021;35:107584. doi: 10.1016/j.jdiacomp.2020.107584. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Donath X, Saint-Martin C, Dubois-Laforgue D, Rajasingham R, Mifsud F, Ciangura C, et al. Monogenic diabetes study group of the Société Francophone du Diabète. Next-generation sequencing identifies monogenic diabetes in 16% of patients with late adolescence/adult-onset diabetes selected on a clinical basis: a cross-sectional analysis. BMC Med. 2019;17:1–0. doi: 10.1186/s12916-019-1363-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Russ-Silsby J, Teles M, Hassan SS, Elbarbary NS, Ngọc CT, De Franco E. Global perspectives on monogenic forms of diabetes. Diabetologia. 2025;16:1–2. doi: 10.1007/s00125-025-06495-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405–23. doi: 10.1038/gim.2015.30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Ellard S, Lango Allen H, De Franco E, Flanagan SE, Hysenaj G, Colclough K, et al. Improved genetic testing for monogenic diabetes using targeted next-generation sequencing. Diabetologia. 2013;56:1958–63. doi: 10.1007/s00125-013-2962-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Targeted next generation sequencing [internet] . https://www.diabetesgenes.org/tests-for-diabetes-subtypes/targeted-next-generation-sequencing-analysis-of-45-monogenic-diabetes-genes [cited 2025 Jul 20]. Available from.
- 14.Letourneau LR, Carmody D, Wroblewski K, Denson AM, Sanyoura M, Naylor RN, et al. Diabetes presentation in infancy: high risk of diabetic ketoacidosis. Diabetes Care. 2017;40:e147–8. doi: 10.2337/dc17-1145. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Alkorta-Aranburu G, Carmody D, Cheng YW, Nelakuditi V, Ma L, Dickens JT, et al. Phenotypic heterogeneity in monogenic diabetes: the clinical and diagnostic utility of a gene panel-based next-generation sequencing approach molecular genetics and metabolism. . 2014;113:315–20. doi: 10.1016/j.ymgme.2014.09.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Goodrich JK, Singer-Berk M, Son R, Sveden A, Wood J, England E, et al. Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes. Nat Commun. 2021;12:3505. doi: 10.1038/s41467-021-23556-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Li M, Popovic N, Wang Y, Chen C, Polychronakos C. Incomplete penetrance and variable expressivity in monogenic diabetes: a challenge but also an opportunity. Rev Endocr Metab Disord. 2023;24:673–84. doi: 10.1007/s11154-023-09809-1. [DOI] [PubMed] [Google Scholar]
- 18.Amaratunga SA, Hussein TT, Muhamad Sediq RN, Hama Salih FK, Dusatkova P, Wakeling MN, et al. Paediatric diabetes subtypes in a consanguineous population: a single-centre cohort study from Kurdistan. Iraq. Diabetol. 2024;67:113–23. doi: 10.1007/s00125-023-06030-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Ibrahim MN, Laghari TM, Riaz M, Khoso Z, Khan YN, Yasir M, et al. Monogenic diabetes in Pakistani infants and children: challenges in a resource-poor country. J Pediatr Endocrinol Metabol. 2021;34:1095–103. doi: 10.1515/jpem-2020-0669. [DOI] [PubMed] [Google Scholar]
- 20.Habeb AM, Flanagan SE, Deeb A, Al-Alwan I, Alawneh H, Balafrej AA, et al. Permanent neonatal diabetes: different aetiologies in Arabs compared to Europeans. Archives Dis Child. 2012;97:721–3. doi: 10.1136/archdischild-2012-301744. [DOI] [PubMed] [Google Scholar]
- 21.Hassan SS, Musa SA, De Franco E, Donis Frew R, Babiker OO, Mohamadsalih GF, et al. Incidence, phenotypes, and genotypes of neonatal diabetes: a 16‐year experience. The rare Genet aetiologies neonatal diabetes are common Sudan. Paediatr Diabetes. 2024;2024:2032425. doi: 10.1155/2024/2032425. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Habeb AM. Frequency and spectrum of Wolcott-Rallison syndrome in Saudi Arabia: a systematic review. Libyan J Med. 2013;8 doi: 10.3402/ljm.v8i0.21137. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Deeb A, Habeb A, Kaplan W, Attia S, Hadi S, Osman A, et al. Genetic characteristics, clinical spectrum, and incidence of neonatal diabetes in the Emirate of AbuDhabi, United Arab Emirates. Am J Med Genet. 2016;170:602–9. doi: 10.1002/ajmg.a.37419. [DOI] [PubMed] [Google Scholar]
- 24.Madani H, Elkaffas R, Alkholy B, Musa N, Shaalan Y, Elkaffas R, et al. Identification of novel variants in neonatal diabetes mellitus genes in Egyptian patients with permanent NDM. Int J Diabetes Dev Ctries. 2019;39:53–9. [Google Scholar]
- 25.Delépine M, Nicolino M, Barrett T, Golamaully M, Mark Lathrop G, Julier C. EIF2AK3, encoding translation initiation factor 2-α kinase 3, is mutated in patients with Wolcott-Rallison syndrome. Nat Genet. 2000;25:406–9. doi: 10.1038/78085. [DOI] [PubMed] [Google Scholar]
- 26.De Franco E, Flanagan SE, Houghton JA, Allen HL, Mackay DJ, Temple IK, et al. The effect of early, comprehensive genomic testing on clinical care in neonatal diabetes: an international cohort study. Lancet. 2015;386:957–63. doi: 10.1016/s0140-6736-15-60098-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Rubio-Cabezas O, Patch AM, Minton JA, Flanagan SE, Edghill EL, Hussain K, et al. Wolcott-Rallison syndrome is the most common genetic cause of permanent neonatal diabetes in consanguineous families. J Clin Endocrinol Metabolism. 2009;94:4162–70. doi: 10.1210/jc.2009-1137. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Shields BM, Hicks S, Shepherd MH, Colclough K, Hattersley AT, Ellard S. Maturity-onset diabetes of the young (MODY): how many cases are we missing? Diabetologia. 2010;53:2504–8. doi: 10.1007/s00125-010-1799-4. [DOI] [PubMed] [Google Scholar]
- 29.Awa WL, Schober E, Wiegand S, Herwig J, Meissner T, Schmidt F, et al. Reclassification of diabetes type in pediatric patients initially classified as type 2 diabetes mellitus: 15 years follow-up using routine data from the German/Austrian DPV database. Diabetes Res Clin Pract. 2011;94:463–7. doi: 10.1016/j.diabres.2011.09.011. [DOI] [PubMed] [Google Scholar]
- 30.Saad FM, Mahmoud LA, Mohammedali AM, Abdullah MA, Omer IM. Incidence and prevalence of type 1 diabetes mellitus in children and adolescents aged 6 months–19 years in Khartoum State, Sudan. Sudan J Paediatr. 2020;20:163–9. doi: 10.24911/sjp.106-1587542600. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Musa SA, Ibrahim AA, Hassan SS, Johnson MB, Basheer AT, Arabi AM, et al. Fanconi Bickel syndrome: clinical phenotypes and genetics in a cohort of Sudanese children. Int J Paediatr Endocrinol. 2020:1–6. doi: 10.1186/s13633-020-00091-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Al-Haggar M, Sakamoto O, Shaltopatients n = 88 A, Wahba Y, Abdel-Hadi D. Fanconi Bickel syndrome: novel mutations in GLUT 2 gene causing a distinguished form of renal tubular acidosis in two unrelated Egyptian families. Case Rep Nephrol. 2011;2011:754369. doi: 10.1155/2011/754369. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Morikawa S, Blacher L, Onwumere C, Urano F. Loss of function of WFS1 causes ER stress-mediated inflammation in pancreatic beta cells. Front Endocrinol. 2022;13:849204. doi: 10.3389/fendo.2022.849204. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Delvecchio M, Iacoviello M, Pantaleo A, Resta N. Clinical spectrum associated with Wolfram syndrome type 1 and type 2: a review on genotype-phenotype correlations. Int J Environ Res Publ Health. 2021;18:4796. doi: 10.3390/ijerph18094796. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Taylor SI, Cama A, Accili D, Barbetti F, Quon MJ, Sierra MD, et al. Mutations in the insulin receptor gene. Endocr Rev. 1992;13:566–95. doi: 10.1210/edrv-13-3-566. [DOI] [PubMed] [Google Scholar]
- 36.Hosoe J, Kadowaki H, Miya F, Aizu K, Kawamura T, Miyata I, et al. Structural basis and genotype–phenotype correlations of INSR mutations causing severe insulin resistance. Diabetes. 2017;66:2713–23. doi: 10.2337/db17-0301. [DOI] [PubMed] [Google Scholar]
- 37.Angelidi AM, Filippaios A, Mantzoros CS. Severe insulin resistance syndromes. J Clin Invest. 2021;131 doi: 10.1172/jci142245. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Glaser B. Insulin mutations in diabetes: the clinical spectrum. Diabetes. 2008;57:799–800. doi: 10.2337/db08-0116. [DOI] [PubMed] [Google Scholar]
- 39.Agarwal AK, Arioglu E, De Almeida S, Akkoc N, Taylor SI, Bowcock AM, et al. AGPAT2 is mutated in congenital generalized lipodystrophy linked to chromosome 9q34. Nat Genet. 2002;31:21–3. doi: 10.1038/ng880. [DOI] [PubMed] [Google Scholar]
- 40.Garg A. Lipodystrophies: genetic and acquired body fat disorders. J Clin Endocrinol Metabol. 2011;96:3313–25. doi: 10.1210/jc.2011-1159. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Poovazhagi V, Shanthi S, Jahnavi S, Radha V, Mohan V. Berardinelli Seip congenital lipodystrophy presenting with neonatal diabetes mellitus due to a mutation in the AGPAT2 gene. Int J Diabetes Dev Ctries. 2013;33:66–8. doi: 10.1007/s13410-012-0099-6. [DOI] [Google Scholar]
- 42.Schroeder C, Riess A, Bonin M, Bauer P, Riess O, Döbler‐Neumann M, et al. PIK3R1 mutations in SHORT syndrome. Clin Genet. 2014;86:292–4. doi: 10.1111/cge.12263. [DOI] [PubMed] [Google Scholar]
- 43.Chudasama KK, Winnay J, Johansson S, Claudi T, König R, Haldorsen I, et al. SHORT syndrome with partial lipodystrophy due to impaired phosphatidylinositol 3 kinase signaling. Am J Hum Genet. 2013;93:150–7. doi: 10.1016/j.ajhg.2013.05.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Kang N, Jun AH, Bhutia YD, Kannan N, Unadkat JD, Govindarajan R. Human equilibrative nucleoside transporter-3 (hENT3) spectrum disorder mutations impair nucleoside transport, protein localisation, and stability. J Biol Chem. 2010;285:28343–52. doi: 10.1074/jbc.m110.109199. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Molho-Pessach V, Lerer I, Abeliovich D, Agha Z, Libdeh AA, Broshtilova V, et al. The H syndrome is caused by mutations in the nucleoside transporter hENT3. Am J Hum Genet. 2008 doi: 10.1016/j.ajhg.2008.09.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Barbetti F, Deeb A, Suzuki S. Neonatal diabetes mellitus around the world: update 2024. J Diabetes Investig. 2024;15:1711–24. doi: 10.1111/jdi.14312. 83(4):529-34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.De Franco E, Owens ND, Montaser H, Wakeling MN, Saarimäki-VJ et alriantou A, Triantou A, et al. Primate-specific ZNF808 is essential for pancreatic development in humans. Nat Genet. 2023;55:2075–81. doi: 10.1038/s41588-023-01565-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Štěrbová K, Vlčková M, Hansíková H, Sebroňová V, Sedláčková L, Pavlíček P, et al. Novel variants in the NARS2 gene as a cause of infantile-onset severe epilepsy leading to fatal refractory status epilepticus: case study and literature review. Neurogenetics. 2021;22:359–64. doi: 10.1007/s10048-021-00659-0. [DOI] [PubMed] [Google Scholar]
- 49.Yagasaki H, Sano F, Narusawa H, Watanabe D, Kaga Y, Kobayashi K, et al. Compound heterozygous variants of the NARS2 gene in siblings with developmental delay, epilepsy, and neonatal diabetes syndrome American. J Med Genet Part A. 2022;188:2466–71. doi: 10.1002/ajmg.a.62873. [DOI] [PubMed] [Google Scholar]
- 50.Donis R, Wakeling MN, Jeffery N, Govier M, Johnson MB, Hassan SS, et al. Neonatal diabetes mellitus is a significant feature of COXPD‐24 caused by recessive NARS2 variants. Diabet Med. 2025:e70129. doi: 10.1111/dme.70129. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Perera LA, Hattersley AT, Harding HP, Wakeling MN, Flanagan SE, Mohsina I, et al. Infancy‐onset diabetes caused by de‐regulated AMPylation of the human endoplasmic reticulum chaperone BiP. EMBO Mol Med. 2023;15:e16491. doi: 10.15252/emmm.202216491. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Rebelo AP, Ruiz A, Dohrn MF, Wayand M, Farooq A, Danzi MC, et al. BiP inactivation due to loss of the deAMPylation function of FICD causes a motor neuron disease. Genet Med. 2022;24:2487–500. doi: 10.1016/j.gim.2022.08.019. [DOI] [PubMed] [Google Scholar]
- 53.Pearson ER, Flechtner I, Njølstad PR, Malecki MT, Flanagan SE, Larkin B, et al. Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6. 2 mutations. N Engl J Med. 2006;355:467–77. doi: 10.1056/nejmoa061759. [DOI] [PubMed] [Google Scholar]
- 54.Bowman P, Sulen Å, Barbetti F, Beltrand J, Svalastoga P, Codner E, et al. Effectiveness and safety of long-term treatment with sulfonylureas in patients with neonatal diabetes due to KCNJ11 mutations: an international cohort study. Lancet Diabetes Endocrinol. 2018;6:637–46. doi: 10.1016/s2213-8587-18-30106-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Material