Polymorphic Variants of BH4 Pathway Genes and Isolated Hypospadias Risk

Kamil Konrad Hozyasz; Adrianna Mostowska; Andrzej Kowal; Pawel P Jagodzinski

doi:10.5812/ijp.86944

Polymorphic Variants of BH4 Pathway Genes and Isolated Hypospadias Risk

authors:

Kamil Konrad Hozyasz ^{1
, *} , Adrianna Mostowska ² , Andrzej Kowal ³ , Pawel P Jagodzinski ²

1 Institute of Health Sciences, State School of Higher Education, Biała Podlaska, Poland

2 Department of Biochemistry and Molecular Biology, Poznań University of Medical Sciences, Poznań, Poland

3 Department of Paediatric Surgery, Institute of Mother and Child, Warsaw, Poland

Iranian Journal of Pediatrics: Vol.30, issue 3; e86944

published online: May 4, 2020

article type: Research Article

received: December 10, 2018

accepted: March 19, 2020

DOI: https://doi.org/10.5812/ijp.86944

how to cite: Hozyasz K K, Mostowska A, Kowal A, Jagodzinski P P. Polymorphic Variants of BH4 Pathway Genes and Isolated Hypospadias Risk. Iran J Pediatr. 2020;30(3):e86944. https://doi.org/10.5812/ijp.86944.

Abstract

Background:

Hypospadias (HS) is one of the most common congenital malformations. Complications of corrective surgery in HS correlate with patients’ opinions on their voiding ability and sexual life as adults. Etiology of HS involves both genetic and environmental factors. GCH1, which belongs to recently identified urothelial genes influencing voiding behavior, encodes rate-limiting enzyme catalyzing the production of tetrahydrobiopterin (BH4). A requirement for BH4, a metabolite structurally related to folic acid and riboflavin, in embryonic development was reported.

Objectives:

The aim of the present study was to investigate the association of selected polymorphic variants of BH4 pathway genes with hypospadias.

Methods:

We performed an analysis of 6 SNPs of GCH1, PAH and AGMO-DGKB loci in a group of 166 boys with isolated hypospadias and a properly matched control group.

Results:

There was no evidence for either allelic or genotypic association with the risk of HS for the tested nucleotide variants (rs12425434, rs7485331, rs17128050, rs8004018, rs17128077, rs2191349). The lack of association with single SNPs was confirmed at the haplotype level. The exhaustive multifactor dimensionality reduction (MDR) analysis revealed no significant interactive effect of polymorphic variants of BH4 pathway genes on HS susceptibility.

Conclusions:

The presented results did not support an association between SNPs of GCH1 and PAH and the risk of HS.

Keywords

Hypospadias BH4 Pathway Candidate Genes

1. Background

Hypospadias (HS) has been defined as a condition in which the urethral meatus may be proximal to its normal glanural occurrence on the ventral surface of the penis, on the scrotum or the perineum. In humans HS is the second most common congenital anomaly with an incidence of 1 in 250 - 300 live male births and its pathogenesis is complex, multifactorial, and determined by genetic, hormonal and environmental causes (1). There is an increasing interest in the concept that maternal use of preparations containing folic acid and other water-soluble vitamins may influence the occurrence of this abnormality in offspring (2, 3). The presence of HS has severe consequences on both physical and psychological development and living situation (1, 4). Complications of corrective surgery in HS correlate with patients’ opinions on their voiding ability and sexual life as adults (5, 6).

Recently, Douglas et al. (7) reported a requirement for 6(R)-L-erythro-5,6,7,8-tetrahydrobiopterin (BH4) in embryonic development. BH4, a metabolite structurally related to riboflavin and folic acid by sharing the common pterin backbone, is synthesized de novo from guanosine triphosphate (GTP) through the catalysis of three enzymatic reactions by GTP cyclohydrolase (GTPCH, EC 3.5.4.16; rate-limiting step), 6-pyruvoytetrahydrobiopterin synthase, and sepiapterin reductase (8). GTPCH deficiency, due to loss of function mutations in the GCH1 gene, results in neurological disorders (7-9). Urine profiles of pterin compounds have the potential to become predictive biomarkers of bladder cancer (10). Moreover, Acevedo-Alavarez and colleagues (11) reported that mouse urothelial transcripts of Gch1 might play an important role in modulating voiding behavior changes.

BH4 is an important antioxidant and an essential cofactor for three isoforms of nitric oxide (NO) synthase and three aromatic amino acid hydroxylases, including phenylalanine hydroxylase (PAH, EC 1.14.16.1), as well as highly hydrophobic alkylglycerol monooxygenase (AGMO, also called glyceryl-ether monooxygenase, EC 1.14.16.5). AGMO is the only enzyme known to cleave the ether bond in alkylglycerol ether lipids. Alkylglycerols are a subclass of lipids, which are membrane constituents and are involved in many signaling pathways and in spermatogenesis (12).

Marrocco et al. (1) hypothesized in their recent review article that most patients develop HS because of interactions between environmental stimuli and polymorphic variants of genes. HS is associated with a high rate of extra urogenital anomalies, e.g., congenital heart defects, orofacial clefts and spina bifida (13-15), leading to the anticipation that there may be a partly shared genetic background for these congenital anomalies. Polymorphic variants of GCH1 are associated with the pathogenesis of spina bifida (16) and orofacial clefts (9). The involvement of the PAHgen in the etiology of orofacial clefts was reported in the Polish population (17). AGMO belongs to candidate genes for congenital heart anomalies in humans (18). Smith-Lemli-Opitz is an inherited autosomal recessive syndrome resulting from a defect in cholesterol synthesis. This syndrome is characterized by mental retardation and associated multiple anomalies including hypospadias (19). It is noteworthy that ether lipids deficiency impairs intracellular cholesterol distribution and homeostasis (12, 20). An association between diabetes and HS was suggested, although this issue is still debated (21). Of particular interest is the finding that polymorphic variant rs2191349, which lies between the AGMO and the DGKB gene, is associated with reduced glucose-stimulated insulin response at a genome-wide significance level (22, 23).

2. Objectives

We examined whether polymorphic variants in GCH1, PAH and AGMO/DGKB genes were associated with hypospadias risk in the Polish population.

3. Methods

3.1. Study Population

Cases were boys treated for HS at the Department of Paediatric Surgery of the Warsaw’s Institute of Mother and Child. The medical records were reviewed to obtain clinical data on HS phenotype and coexisting congenital malformations. Cases with a known cause of HS were excluded. To ensure independent analyses, only one case or control per family was included in the study by excluding youngest brothers or one of the brothers at random for same-sex twins. The study was approved by the local Ethic Committee. Oral and written consent was obtained from the legal guardians of all of the participants.

Previous research showed the familial occurrence of hypospadias for anterior and middle forms of that malformation but not for posterior types, pointing toward genetic risk factors being important (3). Because of this observations, we included only isolated anterior and middle cases to the current study. A total of 166 boys (13 months to 10 years old) presenting with isolated hypospadias and 285 unrelated boys without congenital malformations, were recruited. The ancestry contribution was estimated at 100% of Caucasians of the Polish descent in the case and the control group. DNA was isolated from peripheral blood lymphocytes by a salt-induced extraction procedure.

3.2. Single Nucleotide Polymorphism (SNP) Selection and Genotyping

Five SNPs in GCH1 and PAH, previously detected to be in association with orofacial clefts risk in the Polish population (9, 17), as well as rs2191349 of the AGMO-DGKB loci were evaluated in this study (Table 1). The genotyping was carried out by high-resolution melting curve analysis (HRM) on the Light Cycler 480 system (Table 2). For quality control, approximately 10% of the randomly chosen samples were re-genotyped. Samples that failed genotyping were not repeated and were removed from statistical calculations.

Table 1.

Characteristics of Polymorphisms Genotyped in the GCH1, PAH and DGKB Genes

Gene	rs No.	Location^a	Alleles^b	SNP Function^c	MAF^d
PAH	rs12425434	chr12:103240067	C/T^b (FWD)	intron	0.27
PAH	rs7485331	chr12:103312619	A^b/C (FWD)	N/A (upstream)	0.29
GCH1	rs17128050	chr14:55343879	C^b/T (FWD)	intron	0.10
	rs8004018	chr14:55350696	A/G^b (FWD)	intron	0.10
	rs17128077	chr14:55386034	C/T^b (FWD)	N/A (upstream)	0.11
DGKB	rs2191349	chr7:15064309	G^b/T (FWD)	N/A (upstream)	0.44

Abbreviation: FWD, forward.

^aNCBI build 37/hg19.

^bDenotes the minor allele (based on whole sample).

^cAccording to the Single Nucleotide Polymorphism database (dbSNP).

^dMAF, minor allele frequency calculated from the control samples.

Table 2.

HRM Conditions for the Identification of Polymorphisms Genotyped in the Data Set

Gene	rs No.	Alleles^a	Primers for PCR Amplification (5’ - 3’)	Annealing Temp. (°C)	PCR Product Length (bp)	Melt. Temp. Range (°C)
PAH	rs12425434	C/T^a	F: ATTTGCACTCATTGGCAGTCC	60.6	68	68 - 80
	rs12425434	C/T^a	R: ATTGCCTGTCCTGGAAGTTGA	60.6	68	68 - 80
	rs7485331	A^a/C	F: TTCCCATAGTAAGTTGGAAGC	60.6	146	76 - 86
	rs7485331	A^a/C	R: TGAGGCTGAGGAATACAACA	60.6	146	76 - 86
GCH1	rs17128050	C^a/T	F: GCTCCAACATATCTAAAAGCTACCA	55.0	103	72 - 87
	rs17128050	C^a/T	R: GGGTTACCTTCTTGCTGCTG	55.0	103	72 - 87
	rs8004018	A/G^a	F: TTAAAAATTTGTGAGGAC	53.0	109	75 - 90
	rs8004018	A/G^a	R: ATTGATTTCTAATGAGTTGG	53.0	109	75 - 90
	rs17128077	C/T^a	F: ATGGAATCTAAGGCCATGTTCAGC	58.0	115	75 - 90
	rs17128077	C/T^a	R: AGACCAGCCTGGGACACATGA	58.0	115	75 - 90
DGKB	rs2191349	G^a/T	F: AGGCCTTAACTTTGGCTGGA	55	81	75 - 90
DGKB	rs2191349	G^a/T	R: AGACCCCACCGCTAGATGTT	55	81	75 - 90

^aDenotes the minor allele (based on whole sample).

3.3. Statistical Methods

For each SNP, the Hardy-Weinberg (HW) equilibrium was evaluated in both patients and controls by the chi-square (χ²) test. Statistically significant deviation from HW expectations was interpreted as P value < 0.05. The differences in allele frequencies between cases and controls were determined using standard χ² test. The strength of association was estimated by odds ratio (OR) and corresponding 95% confidence intervals (95%CIs). The dominant and recessive models were tested. To account for multiple comparisons the strict Bonferroni correction was applied. The P values below 0.0083 (0.05/6 SNPs) were considered as statistically significant.

The haplotype-based association analysis using a sliding window approach was conducted using Haploview V. 4.0 software. Significant P values were corrected using the 10,000-fold permutation test.

Higher-order gene-gene interactions among all tested single nucleotide polymorphisms were evaluated using the non-parametric and genetic model-free multifactor dimensionality reduction (MDR) approach (MDR version 3.0.2).

4. Results

None of the tested nucleotide variants showed evidence for deviation from Hardy-Weinberg equilibrium in either cases or controls. The minor allele frequency (MAF) for all SNPs was ≥ 10% (MAF calculated from the controls, Table 1). Genotype counts, OR and 95% CI calculations for the all tested SNPs are reported in Table 3. Overall, there was no evidence for either allelic or genotypic association with the risk of being born with HS. Haplotype analysis of nucleotide variants in the GCH1 and PAH locus revealed no haplotypes associated with the risk of HS (Table 4). Results of exhaustive MDR analysis evaluating combinations of all tested SNPs are summarized in Table 5. The combinations did not reach statistical significance in predicting susceptibility to HS.

Table 3.

Association of PAH, GCH1 and AGMO Polymorphisms with the risk of Hypospadias

Gene	rs No.	Alleles^a	Genotype Distribution^b, MAF		P_trend	P_allelic	P_geno	Dominant Model^c		Recessive Model^d
Gene	rs No.	Alleles^a	Cases	Controls	P_trend	P_allelic	P_geno	OR (95% CI)	P Value	OR (95% CI)	P Value
PAH	rs12425434	C/T^a	16 / 59 / 91	21 / 111 / 147	0.9975	0.9975	0.5664	0.918 (0.624 - 1.350)	0.6629	1.310 (0.663 - 5.589)	0.4352
	rs12425434	C/T^a	0.27	0.27	0.9975	0.9975	0.5664	0.918 (0.624 - 1.350)	0.6629	1.310 (0.663 - 5.589)	0.4352
	rs7485331	A^a/C	13 / 63 / 88	22 / 120 / 138	0.4905	0.4930	0.6426	0.839 (0.570 - 1.235)	0.3737	1.010 (0.494 - 2.063)	0.9790
	rs7485331	A^a/C	0.27	0.29	0.4905	0.4930	0.6426	0.839 (0.570 - 1.235)	0.3737	1.010 (0.494 - 2.063)	0.9790
GCH1	rs17128050	C^a/T	3 / 29 / 134	2 / 54 / 224	0.9305	0.9303	0.5216	0.955 (0.589 - 1.550)	0.8529	2.558 (0.423 - 15.478)	0.3659^e
	rs17128050	C^a/T	0.11	0.10	0.9305	0.9303	0.5216	0.955 (0.589 - 1.550)	0.8529	2.558 (0.423 - 15.478)	0.3659^e
	rs8004018	A/G^a	3 / 29 / 131	2 / 54 / 225	0.8456	0.8453	0.5272	0.982 (0.604 - 1.594)	0.9397	2.616 (0.432 - 15.826)	0.3616^e
	rs8004018	A/G^a	0.11	0.10	0.8456	0.8453	0.5272	0.982 (0.604 - 1.594)	0.9397	2.616 (0.432 - 15.826)	0.3616^e
	rs17128077	C/T^a	4 / 36 / 126	5 / 52 / 223	0.3440	0.3304	0.6377	1.242 (0.784 - 1.967)	0.3548	1.358 (0.359 - 5.131)	0.7324^e
	rs17128077	C/T^a	0.13	0.11	0.3440	0.3304	0.6377	1.242 (0.784 - 1.967)	0.3548	1.358 (0.359 - 5.131)	0.7324^e
AGMO	rs2191349	G^a/T	30 / 85 / 50	66 / 118 / 97	0.8790	0.8744	0.1359	1.213 (0.802 - 1.833)	0.3604	0.724 (0.447 - 1.173)	0.1881
AGMO	rs2191349	G^a/T	0.44	0.44	0.8790	0.8744	0.1359	1.213 (0.802 - 1.833)	0.3604	0.724 (0.447 - 1.173)	0.1881

Abbreviation: MAF, minor allele frequency.

^aDenotes the minor allele (in all cases the minor allele is the risk allele).

^bThe order of genotypes: dd/Dd/DD (d is the minor allele).

^cDominant model: dd + Dd vs. DD (d is the minor allele).

^dRecessive model: dd vs. Dd + DD (d is the minor allele).

^eFisher exact test.

Table 4.

Haplotype Analysis of SNPs Genotyped in the PAH and GCH1 Genes

Gene	Polymorphisms	Haplotypes	Frequency	Case, Control Ratios	Chi-Square	P Value	P_corr Value^a
PAH	rs12425434-rs7485331	CC	0.445	0.456, 0.438	0.256	0.613	0.858
		CA	0.281	0.270, 0.288	0.320	0.572	0.837
		TC	0.270	0.273, 0.269	0.015	0.901	0.996
GCH1	rs17128050-rs8004018	TA	0.896	0.895, 0.896	0.008	0.930	1.000
	rs17128050-rs8004018	CG	0.104	0.105, 0.104	0.008	0.930	1.000
	rs8004018-rs17128077	AC	0.861	0.845, 0.871	1.121	0.290	0.674
		GT	0.085	0.086, 0.085	0.002	0.966	1.000
		AT	0.033	0.047, 0.026	2.840	0.092	0.247
		GC	0.020	0.022, 0.019	0.134	0.715	0.976
	rs17128050-rs8004018-rs17128077	TAC	0.861	0.846, 0.871	1.092	0.296	0.722
		CGT	0.085	0.084, 0.085	0.005	0.945	1.000
		TAT	0.034	0.049, 0.026	3.375	0.066	0.197
		CGC	0.020	0.022, 0.019	0.110	0.740	0.982

^aP value calculated using permutation test and a total of 1,000 permutations.

Table 5.

Results of MDR Analysis

Genes and rs Numbers	Testing Balanced Accuracy	Cross Validation Consistency	P Value^a
PAH-rs7485331, DGKB-rs2191349	0.4797	7 / 10	0.943
PAH-rs12425434, PAH-rs7485331, DGKB-rs2191349	0.4988	8 / 10	0.846
PAH-rs12425434, PAH-rs7485331, GCH1-rs17128077, DGKB-rs2191349	0.5299	7 / 10	0.535

^aSignificance of accuracy, empirical p value based on 1,000 permutations.

5. Discussion

The network-oriented picture of HS risk factors is complex and likely largely incomplete (1). Non-functional mutations of the GCH1, resulting in complete loss of BH4 synthesis, have not been described, suggesting that complete loss of GTPCH activity, as well as BH4-dependent enzymes activity, is likely to be embryonically lethal in humans (7). Our study addressed two questions. First, are SNPs of GCH1 and PAH that were nominally significant upon testing for association with birth defects known for frequent occurrence with hypospadias also associated with isolated hypospadias? Second, is the intensively studied SNP associated with abnormal glucose homeostasis linked to hypospadias susceptibility? To our knowledge, the present report is the first association study evaluating nucleotide variants of the BH4 pathway genes as possible risk factors for HS.

A study conducted by Lupo and colleagues (16) suggested a link between haplotypes of GCH1 gene and abnormal neural tube closure in the USA. In our previous study, we found a significant association between the GCH1 rs17128077, rs8004018 and rs17128050 variants with an increased risk for cleft lip with or without cleft palate (9). The correlation with single polymorphic variants was confirmed at the haplotype level (9). The investigated variants of the GCH1 were not found to be involved in the pathogenesis of HS.

The PAH rs7485331 and rs12425434 were reported to influence susceptibility to isolated orofacial clefts (17). Mutations in the PAH gene cause phenylketonuria, the most common inborn error of amino acids metabolism in Middle East Asians and Europeans. In the recent description of 30 patients with phenylketonuria and co-existent disorders from 13 treatment centers from Europe and Turkey, one boy suffered from hypospadias (24). In untreated or non-optimally treated pregnancies of phenylketonurics, HS in offspring as a less frequent sign of maternal phenylketonuria syndrome was described (25). However, in our study statistical analysis revealed no significant association between common nucleotide variants of PAH and the risk of HS.

The sequence of AGMO shows no significant similarity with the other known BH4-dependent enzymes but contains the typical fatty acid hydroxylase protein motive signature (26). The SNP rs2191349 of the AGMO-DGKB loci was not associated with abnormal penile development in the present study. Recent studies revealed no association between this polymorphic variant and cognitive function in children (27) and chronic kidney disease in patients with type 2 diabetes (28).

It is worth noting that negative results of single-marker analysis for GCH1 and PAH were confirmed by haplotype evaluation. Variation in populations is inherently structured into haplotypes (29). Analysis of epistasis is useful in determining the true contribution of genetic factors to birth defect susceptibility (30). All of the genes we examined have not been studied previously for their contribution to HS. In contrast to preliminary expectations, we did not identify the significant interactive effect of polymorphic variants of BH4 pathway genes on HS risk.

An important strength of presented study is the use of data from individuals recruited from the homogeneous population. The major limitation is the sample size, which did not allow us to detect modest interactions and associations. We must also note that the number of selected SNPs does not cover the GCH1 and PAH genes fully and extensively. Additional extensions and modifications of the MDR approach will be needed to fully address the complexity of genetic association data.

In conclusion, the presented results did not support any association between polymorphic variants of GCH1, PAH and AGMO-DGKB loci, and risk of being born with hypospadias in the Polish population.

Footnotes

Authors' Contribution: Study concept and design: Kamil Konrad Hozyasz and Adrianna Mostowska; acquisition of data: Andrzej Kowal and Adrianna Mostowska; analysis and interpretation of data: Kamil Konrad Hozyasz, Pawel Jagodzinski, Adrianna Mostowska and Andrzej Kowal; drafting of the manuscript: Kamil Konrad Hozyasz and Adrianna Mostowska; critical revision of the manuscript for important intellectual content: Pawel Jagodzinski and Andrzej Kowal; statistical analysis: Kamil Konrad Hozyasz and Adrianna Mostowska.
Conflict of Interests: The authors report no conflicts of interest in this work.
Ethical Approval: The study was approved by the local Ethic Committee.
Funding/Support: The study was supported by grants from Poznań University of Medical Sciences.

References

1.
Marrocco G, Grammatico P, Vallasciani S, Gulia C, Zangari A, Marrocco F, et al. Environmental, parental and gestational factors that influence the occurrence of hypospadias in male patients. J Pediatr Urol. 2015;11(1):12-9. [PubMed ID: 25725611]. https://doi.org/10.1016/j.jpurol.2014.10.003.
2.
Carmichael SL, Ma C, Feldkamp ML, Munger RG, Olney RS, Botto LD, et al. Nutritional factors and hypospadias risks. Paediatr Perinat Epidemiol. 2012;26(4):353-60. [PubMed ID: 22686387]. [PubMed Central ID: PMC3376012]. https://doi.org/10.1111/j.1365-3016.2012.01272.x.
3.
Dokter EM, van Rooij IA, Wijers CH, Groothuismink JM, van der Biezen JJ, Feitz WF, et al. Interaction between MTHFR 677C>T and periconceptional folic acid supplementation in the risk of Hypospadias. Birth Defects Res A Clin Mol Teratol. 2016;106(4):275-84. [PubMed ID: 26879531]. https://doi.org/10.1002/bdra.23487.
4.
Mohammadzadeh A, Farhat A, Esmaieli H, Shiranzaei S. Prevalence and risk factors of hypospadias in a private hospital in Northeast Iran. Iran J Pediatr. 2011;21(4):497-501. [PubMed ID: 23056838]. [PubMed Central ID: PMC3446125].
5.
Aho MO, Tammela OK, Tammela TL. Aspects of adult satisfaction with the result of surgery for hypospadias performed in childhood. Eur Urol. 1997;32(2):218-22. [PubMed ID: 9286657].
6.
van der Werff JF, Boeve E, Brusse CA, van der Meulen JC. Urodynamic evaluation of hypospadias repair. J Urol. 1997;157(4):1344-6. [PubMed ID: 9120936]. https://doi.org/10.1097/00005392-199704000-00047.
7.
Douglas G, Hale AB, Crabtree MJ, Ryan BJ, Hansler A, Watschinger K, et al. A requirement for Gch1 and tetrahydrobiopterin in embryonic development. Dev Biol. 2015;399(1):129-38. [PubMed ID: 25557619]. [PubMed Central ID: PMC4347993]. https://doi.org/10.1016/j.ydbio.2014.12.025.
8.
Gesierich A, Niroomand F, Tiefenbacher CP. Role of human GTP cyclohydrolase I and its regulatory protein in tetrahydrobiopterin metabolism. Basic Res Cardiol. 2003;98(2):69-75. [PubMed ID: 12607127]. https://doi.org/10.1007/s00395-003-0394-y.
9.
Hozyasz KK, Mostowska A, Wojcicki P, Lasota A, Zadurska M, Dunin-Wilczynska I, et al. Nucleotide Variants of the BH4 Biosynthesis Pathway Gene GCH1 and the Risk of Orofacial Clefts. Mol Neurobiol. 2016;53(1):769-76. [PubMed ID: 26215833]. [PubMed Central ID: PMC4703629]. https://doi.org/10.1007/s12035-015-9342-8.
10.
Koslinski P, Daghir-Wojtkowiak E, Szatkowska-Wandas P, Markuszewski M, Markuszewski MJ. The metabolic profiles of pterin compounds as potential biomarkers of bladder cancer-Integration of analytical-based approach with biostatistical methodology. J Pharm Biomed Anal. 2016;127:256-62. [PubMed ID: 26992657]. https://doi.org/10.1016/j.jpba.2016.02.038.
11.
Acevedo-Alvarez M, Yeh J, Alvarez-Lugo L, Lu M, Sukumar N, Hill WG, et al. Mouse urothelial genes associated with voiding behavior changes after ovariectomy and bladder lipopolysaccharide exposure. Neurourol Urodyn. 2018;37(8):2398-405. [PubMed ID: 29682797]. https://doi.org/10.1002/nau.23592.
12.
Gorgas K, Teigler A, Komljenovic D, Just WW. The ether lipid-deficient mouse: tracking down plasmalogen functions. Biochim Biophys Acta. 2006;1763(12):1511-26. [PubMed ID: 17027098]. https://doi.org/10.1016/j.bbamcr.2006.08.038.
13.
Voisin M, Djernit A, Morin D, Grolleau R, Dumas R, Jean R. [Congenital heart diseases and urinary malformations]. Arch Mal Coeur Vaiss. 1988;81(5):703-7. French. [PubMed ID: 2900625].
14.
Martinez-Frias ML. Spina bifida and hypospadias: a non random association or an X-linked recessive condition? Am J Med Genet. 1994;52(1):5-8. [PubMed ID: 7977461]. https://doi.org/10.1002/ajmg.1320520103.
15.
Wu WH, Chuang JH, Ting YC, Lee SY, Hsieh CS. Developmental anomalies and disabilities associated with hypospadias. J Urol. 2002;168(1):229-32. [PubMed ID: 12050549].
16.
Lupo PJ, Chapa C, Nousome D, Duhon C, Canfield MA, Shaw GM, et al. A GCH1 haplotype and risk of neural tube defects in the National Birth Defects Prevention Study. Mol Genet Metab. 2012;107(3):592-5. [PubMed ID: 23059057]. [PubMed Central ID: PMC3704723]. https://doi.org/10.1016/j.ymgme.2012.09.020.
17.
Hozyasz KK, Mostowska A, Wojcicki P, Lasota A, Wolkowicz A, Dunin-Wilczynska I, et al. Association of common variants in PAH and LAT1 with non-syndromic cleft lip with or without cleft palate (NSCL/P) in the Polish population. Arch Oral Biol. 2014;59(4):363-9. [PubMed ID: 24606907]. https://doi.org/10.1016/j.archoralbio.2014.01.003.
18.
Zaidi S, Choi M, Wakimoto H, Ma L, Jiang J, Overton JD, et al. De novo mutations in histone-modifying genes in congenital heart disease. Nature. 2013;498(7453):220-3. [PubMed ID: 23665959]. [PubMed Central ID: PMC3706629]. https://doi.org/10.1038/nature12141.
19.
Ryan AK, Bartlett K, Clayton P, Eaton S, Mills L, Donnai D, et al. Smith-Lemli-Opitz syndrome: a variable clinical and biochemical phenotype. J Med Genet. 1998;35(7):558-65. [PubMed ID: 9678700]. [PubMed Central ID: PMC1051366]. https://doi.org/10.1136/jmg.35.7.558.
20.
Krysiak-Zielonka I. Long-term complications of diabetes and the risk of diabetic foot. Health Problems of Civilization. 2018;12(1):14-21. https://doi.org/10.5114/hpc.2018.74185.
21.
Trabert B, Chodick G, Shalev V, Sella T, Longnecker MP, McGlynn KA. Gestational diabetes and the risk of cryptorchidism and hypospadias. Epidemiology. 2014;25(1):152-3. [PubMed ID: 24296929]. [PubMed Central ID: PMC3928021]. https://doi.org/10.1097/EDE.0000000000000014.
22.
Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, Jackson AU, et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet. 2010;42(2):105-16. [PubMed ID: 20081858]. [PubMed Central ID: PMC3018764]. https://doi.org/10.1038/ng.520.
23.
Boesgaard TW, Grarup N, Jorgensen T, Borch-Johnsen K, Meta-Analysis of G, Insulin-Related Trait C, et al. Variants at DGKB/TMEM195, ADRA2A, GLIS3 and C2CD4B loci are associated with reduced glucose-stimulated beta cell function in middle-aged Danish people. Diabetologia. 2010;53(8):1647-55. [PubMed ID: 20419449]. https://doi.org/10.1007/s00125-010-1753-5.
24.
MacDonald A, Ahring K, Almeida MF, Belanger-Quintana A, Blau N, Burlina A, et al. The challenges of managing coexistent disorders with phenylketonuria: 30 cases. Mol Genet Metab. 2015;116(4):242-51. [PubMed ID: 26498184]. https://doi.org/10.1016/j.ymgme.2015.10.001.
25.
van Wegberg AMJ, MacDonald A, Ahring K, Belanger-Quintana A, Blau N, Bosch AM, et al. The complete European guidelines on phenylketonuria: diagnosis and treatment. Orphanet J Rare Dis. 2017;12(1):162. [PubMed ID: 29025426]. [PubMed Central ID: PMC5639803]. https://doi.org/10.1186/s13023-017-0685-2.
26.
Watschinger K, Werner ER. Alkylglycerol monooxygenase. IUBMB Life. 2013;65(4):366-72. [PubMed ID: 23441072]. [PubMed Central ID: PMC3617469]. https://doi.org/10.1002/iub.1143.
27.
Bonilla C, Lawlor DA, Ben-Shlomo Y, Ness AR, Gunnell D, Ring SM, et al. Maternal and offspring fasting glucose and type 2 diabetes-associated genetic variants and cognitive function at age 8: a Mendelian randomization study in the Avon Longitudinal Study of Parents and Children. BMC Med Genet. 2012;13:90. [PubMed ID: 23013243]. [PubMed Central ID: PMC3570299]. https://doi.org/10.1186/1471-2350-13-90.
28.
Jiang G, Hu C, Tam CH, Lau ES, Wang Y, Luk AO, et al. Genetic and clinical variables identify predictors for chronic kidney disease in type 2 diabetes. Kidney Int. 2016;89(2):411-20. [PubMed ID: 26806836]. https://doi.org/10.1016/j.kint.2015.09.001.
29.
Clark AG. The role of haplotypes in candidate gene studies. Genet Epidemiol. 2004;27(4):321-33. [PubMed ID: 15368617]. https://doi.org/10.1002/gepi.20025.
30.
Niel C, Sinoquet C, Dina C, Rocheleau G. A survey about methods dedicated to epistasis detection. Front Genet. 2015;6:285. [PubMed ID: 26442103]. [PubMed Central ID: PMC4564769]. https://doi.org/10.3389/fgene.2015.00285.

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