| Literature DB >> 32034166 |
Yazeid Alhaidan1,2,3,4, Martin J Larsen5,6, Anders Jørgen Schou7, Maria H Stenlid8, Mohammed A Al Balwi9,10, Henrik Thybo Christesen6,7,11, Klaus Brusgaard5,6,12.
Abstract
Unexplained or idiopathic ketotic hypoglycemia (KH) is the most common type of hypoglycemia in children. The diagnosis is based on the exclusion of routine hormonal and metabolic causes of hypoglycemia. We aimed to identify novel genes that cause KH, as this may lead to a more targeted treatment. Deep phenotyping of ten preschool age at onset KH patients (boys, n = 5; girls, n = 5) was performed followed by trio exome sequencing and comprehensive bioinformatics analysis. Data analysis revealed four novel candidate genes: (1) NCOR1 in a patient with KH, iron deficiency and loose stools; (2) IGF2BP1 in a proband with KH, short stature and delayed bone age; (3) SLC5A2 in a proband with KH, intermittent glucosuria and extremely elevated p-GLP-1; and (4) NEK11 in a proband with ketotic hypoglycemia and liver affliction. These genes are associated with different metabolic processes, such as gluconeogenesis, translational regulation, and glucose transport. In conclusion, WES identified DNA variants in four different genes as potential novel causes of IKH, suggesting that IKH is a heterogeneous disorder that can be split into several novel diseases: NCOR1-KH, IGF2BP1-KH, SGLT2-KH or familial renal glucosuria KH, and NEK11-KH. Precision medicine treatment based on exome sequencing may lead to advances in the management of IKH.Entities:
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Year: 2020 PMID: 32034166 PMCID: PMC7005888 DOI: 10.1038/s41598-020-58845-3
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Patient clinical information in 10 children with IKH.
| Family ID | Sex | Onset hypoglycemia | Lowest recorded blood glucose (mmol/L) | Highest ketone bodies (mmol/L or urine stick) | Other abnormal lab results | Familial hypoglycemia | Age at last follow-up | Treatment at last follow-up |
|---|---|---|---|---|---|---|---|---|
| HH16 | F | 22 m | 1.8 | 4.9 | Chronic iron deficiency and loose stools | None | 5 y, 4 m | Dietary, cornstarch Continuous maltose by gastrostomy Sandostatin LAR Sirolimus |
| HH21 | M | 12 m | 1.5 | 4+ Urine dipstick | Short stature (−2.54 SD), bone age 3.7 years delayed | None | 11 y, 6 m | Dietary, cornstarch |
| HH24 | M | 2 y, 2 m | 2.1 | 3.1 | IGF-I and IGF-BP3 low in the normal range Short stature (−2.1 SD), normal bone age | Father hypoglycemia-like episodes in childhood | 5 y, 11 m | Dietary, cornstarch |
| HH26 | M | 18 m | 1.1 | 1.8 | ↑ GLP-1 4 + glycosuria upon 15 h of fasting | None | 7 y, 8 m | Clinical remission |
| HH28 | F | 4 y, 10 m (first documented, suspicion from 1½ y) | 1.5 | 2.6 | Blood glucose was up to 31.6 mmol/L while nonketotic Born preterm (33 weeks) and weighed 2000 g | Brother and mother blood glucose 1.4 (1.7) −28 (32.4) mmol/L, hypoketotic Normal HbA1c. Maternal grandfather had hypoglycemia-suspected attacks | 7 y, 3 m | Dietary (avoidance of sugar-rich food items) |
| HH30 | M | 19 m | 1.2 | 2.9 | None | Mother ketotic hypoglycemia. Her two siblings and their mother suspected to have hypoglycemia as children | 3 y, 7 m | Dietary, cornstarch, Sandostatin LAR |
| F | 18 m (first documented) | 0.7 | 2.9 | None | 2 y, 2 m | Cornstarch, continuous maltose in gastrostomy during sleep | ||
| HH31 | M | 5 y (first documented) | 2.3 | 2.3 | ↑APTT ↑INR ↑p-ammonia ↓IGF-1 ↓IGF-BP3 Height -1.5 SD A migraine, tremor and mild retardation | None | 8 y, 9 m | Dietary, cornstarch GH treatment despite no GHD |
| HH32 | F | 13 m | 2.2 | 4.7 | None | None | 3 y, 8 m | Dietary, corn starch |
| HH37 | F | 20 m | 1.4 | 4.9 | Short stature (−2.0 SD) bone age -2,3 y low-normal p-IGF-1 | None | 8 y, 4 m | Dietary, cornstarch GH treatment |
Abbreviations: GHD; Growth Hormone Deficiency. FFA; Free Fatty Acid. SD; Standard Deviation. APTT; Activated Partial Thromboplastin Time. INR; International Normalized Ratio.
All patients had an exclusion of muscular and liver diseases (including intramuscular glucagon test), pituitary (gh) and adrenal insufficiency unless otherwise specified.
Positive exome sequencing results in four families.
| Family ID | Gene | RefSeq ID | Change | NFE - Freq. | HGMD | SIFT/PolyPhen-2/PROVEAN Predictiona | ||
|---|---|---|---|---|---|---|---|---|
| Coding DNA | Amino Acid | Zygosity | ||||||
| HH16 | NM_006311.3 | c.4564 A > G | p.(Thr1522Ala) | Paternal heterozygous | 1.6 × 10−5 | NR | D/D/D | |
| HH21 | NM_006546.3 | c.1501 C > T | p.(Arg501Trp) | 9 × 10−6 | NR | D/D/D | ||
| HH26 | NM_003041.3 | c.198 + 6 A > G | — | Maternal heterozygous | 1.6 × 10−5 | NR | — | |
| HH31 | NM_001321221.1 | c.1844A > G | p.(Glu615Gly) | Paternal heterozygous | NR | NR | D/D/D | |
Abbreviations: NFE-freq; Non-FinishEuropean Frequency by the Genome Aggregation Database (gnomAD). NR = Never Reported.
aD: Deleterious.
Figure 1NCOR/HDAC3 recruitment for transcriptional induction of gluconeogenesis pathway. Molecular models of NCOR/HDAC3 recruitment for gluconeogenesis transcriptional genes during fasting. (A) In present of NCOR/HDAC3 complex, gluconeogenesis activated via FOXO/Class IIa HDACs. (B) in absent of NCOR/HDAC3 complex, Class IIa HDACs lose it is ability to activate FOXO leading to suppress gluconeogenesis transregional genes.
Figure 2HH21 family’s Sanger sequencing results for IGF2BP1 gene. Sanger sequencing results; (A) proband shows a heterozygous de novo mutation in location c.1501 C > T; p.Arg501Trp. The corresponding; (B) paternal and (C) maternal sequence presented wild-type alleles of IGF2BP1.
Figure 33D protein structure. The arginine (blue) in α1 is mutated into a Tryptophan (red). Due to this mutation, the hydrogen bonds (yellow dotted lines) between arginine and glutamine in α3 (green) are lost.
Target coverage and mean read depth.
| Family ID | HH16 | HH21 | HH24 | HH26 | HH28 | HH30 | HH31 | HH32 | HH37 |
|---|---|---|---|---|---|---|---|---|---|
| Target coverage (20x)(%) | 92.1 | 56.3 | 89.1 | 92.1 | 92.7 | 89.7 | 87.2 | 85.9 | 92.5 |
| Target coverage (10x )(%) | 95.2 | 60.4 | 94 | 95.4 | 95.6 | 94.6 | 93.6 | 93.1 | 95.2 |
| Mean read depth (x) | 86 | 62 | 92 | 82 | 85 | 109 | 70 | 67 | 143 |
Figure 4Exome data analysis strategy. Data filtering strategy; (A) Row data filter in all non-synonymous variants that presented within the exone regions or splicing sites including a minimum of 10X coverage. In parallel variant processed through two parameters; first parameter set with freq. of ≤0.01 for compound heterozygous, autosomal recessive, multifactorial inheritance, or de novo pattern while the second parameter set with freq. of ≤0.0001 for the dominant pattern. (B) Both parameters filtered against our gene list as well as individual mutations generated from step A will be kept without filtering. This step generates four excel files. (C) Data interpretation carried out manually for each file using multi-database with incorporated a considerable amount of judgment and extrapolation. This leads to generating a number of candidate genes that already known or newly discovered gene.