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. Author manuscript; available in PMC: 2014 Nov 1.
Published in final edited form as: J Pediatr. 2013 Jul 26;163(5):10.1016/j.jpeds.2013.06.025. doi: 10.1016/j.jpeds.2013.06.025

Candidate gene analysis: Severe intraventricular hemorrhage in inborn preterm neonates

Ulrika Ådén 1, Aiping Lin 2, Waldemar Carlo 4, Alan Leviton 6, Jeffrey C Murray 7, Mikko Hallman 8, Richard P Lifton 3, Heping Zhang 9, Laura R Ment 2,10, on behalf of the Gene Targets for Intraventricular Hemorrhage Study Group
PMCID: PMC3812267  NIHMSID: NIHMS498832  PMID: 23896193

Abstract

Intraventricular hemorrhage is a disorder of complex etiology. We analyzed genotypes for 7 genes from 224 inborn preterm neonates treated with antenatal steroids and Grade 3-4 intraventricular hemorrhage and 389 matched controls. Only methylenetetrahydrofolate reductase was more prevalent in cases of intraventricular hemorrhage, emphasizing the need for more comprehensive genetic strategies.


Converging data suggest that intraventricular hemorrhage (IVH) of the preterm neonate is a disorder of complex etiology. IVH has been attributed to changes in cerebral blood flow to the immature germinal matrix microvasculature,1 and the more severe grades are characterized by acute distension of the ventricular system (Grade 3) and parenchymal venous infarction (Grade 4). Nationally, ~15% of all very low birth weight infants have grade (Gr) 3–4 IVH,2 and one-half to three-quarters of survivors develop cognitive impairment and/or cerebral palsy.3-5 Despite advances in neonatal intensive care, the incidence of Gr 3-4 IVH has changed little over the past two decades.2 Recent studies have tested the hypothesis that IVH may be secondary to variability in risk genes, and candidate gene studies have implicated the coagulation, inflammatory and vascular pathways.6-8 However, few have been replicated in independent populations. Factors contributing to these findings include the wide range of ancestries of infants studied, small sample sizes and lack of appropriate controls.

If a major focus of perinatal care is to prevent brain injury and abnormal development,9 then physicians and scientists must better understand those factors that contribute to severe IVH. The objective of this report is to interrogate previously published genetic risk factors for Gr 3-4 IVH in a cohort of inborn appropriate for gestational age (AGA) preterm neonates.

METHODS

Inborn infants with birth weights (BW) 500-1250 g and Gr 3–4 IVH and neonates with normal cranial ultrasounds were enrolled prospectively at 24 universities; additional samples were provided from ELGAN,10 Iowa Prematurity6 and Oulu University11 cohorts. The protocol was approved by the institutional review board of each institution.

Candidate genes

PubMed searches were performed of original and review articles published prior to 1 January 2013 that reported significant associations between specific genotypes and Gr 3-4 IVH. PubMed terms included: candidate, gene, genetic, grades 3–4, infant, intraventricular hemorrhage, IVH, neonate, polymorphism, premature, preterm, and risk factor.

Eleven polymorphic genetic variants in 9 genes were identified. dbSNP ID numbers follow: COL4A1(rs1139941148); ESR1(rs223469312); F2(rs17999637,13); F5(rs60256,7,13); IL1B(rs11436276, rs169446,14); IL6(rs180079515); MTHFR(rs18011337; 18011317); TNF(rs180062916); and TNFB2(rs13843566917).

Description of cases and controls

Cases had Gr 3–4 IVH based upon blinded cUS review and met the following criteria: inborn; ANS exposure; BW 500–1250 g; AGA; no congenital malformations, infections or chromosomal disorder; no family history of coagulopathy; and not a sibling of an enrolled subject. Controls met these criteria and had normal ultrasounds. Analysis was performed on neonates of European ancestry to reduce confounding from racial admixture. Data were entered into a secure online database at Yale University.

Genotyping

Genomic DNA was isolated from buccal swabs, umbilical cords and blood, and genotyping was performed using Illumina 1 Million Quad and HumanOmniExpress-12 v1.0 arrays as previously described.18 For SNPs not on the arrays, proxy SNPs selected secondary to strong linkage disequilibrium with the candidate were employed. The D’ between the candidate and proxy19 was determined based on the 1000 genomes European data.20

dbSNP ID numbers for the variants follow: COL4A1(rs3825481); ESR1 (rs1643821); F2(rs5898); F5 (rs6015); IL1B(rs16944, rs1143627); IL6(rs1800797); MTHFR(rs1801133; rs1801131); TNF(rs1800629). D’ values for the best proxies for ESR1 and TNFB2 were 0.496 and 0.732, and thus these were not evaluated, permitting evaluation of 9 variants in 7 genes.

Statistical Analyses

Distributions for the 9 variants in cases and controls were examined for significant deviation (p< 0.01) from Hardy-Weinberg equilibrium. Each was pre-specified based on published reports in the primary analysis, and the frequencies of risk-associated variants and non-risk-associated variants were compared in cases and controls (Table I). In the secondary analysis, the distribution of all three genotypes was compared at each locus (Table II). Fisher exact test was applied to both.

Table 1.

Validation of predefined risk genotype comparisons in cases vs controls

Gene Varianta Genotype comparison SNP Proxy (D’ value with original SNP)b Odds Ratio (95% CI) P value
COL4A1 p.Gly1580Arg8 CG vs GG rs113994114 rs3825481 (nac) 0.89 (0.52-1.49) 0.712
F2 c.97G>A7,13 AG vs GG rs1799963 rs5898 (1.000) 1.40 (0.88-2.22) 0.139
F5 c.1601G>A6,7,13 AG vs GG rs6025 rs6015 (1.000) 1.07 (0.66-1.72) 0.817
IL1B c.-87-511T>C6,14 T vs C rs16944 - 1.02 (0.79-1.30) 0.902
c.-87-31C>T14 C vs T rs1143627 - 1.03 (0.80-1.31) 0.853
IL6 c.-116-121C>G15 CC vs CG or GG rs1800795 rs1800797 (1.000) 1.08 (0.76-1.56) 0.662
MTHFR c.677C>T7 TT or CT vs CC rs1801133 - 0.95 (0.67-1.34) 0.799
c.1298A>C7 CC or CA vs AA rs1801131 - 1.56 (1.10-2.20) 0.009
TNF c.-169-319G>A,16 AA or AG vs GG rs1800629 - 0.90 (0.62-1.31) 0.587
a

c – cDNA; p - protein

b

D’ = D/Dmax where D = the deviation of the observed frequency from the expected; and Dmax = the theoretical maximum for the observed allele frequencies

c

Allele frequency 0 for the original SNP from1000 genomes database

COL4A1 – collagen 4A1; F2 – prothrombin; F5 – factor V Leiden; IL – interleukin; MTHFR - Methylenetetrahydrofolate reductate; TNF – tumor necrosis factor α.

Table 2.

Genotype frequencies and p values in cases with Grade 3 – 4 IVH and controls

Gene Variant Genotype Number (%)
P value
Controls Cases

COL4A1 p.Gly1580Arg8 rs3825481* AA 85.8 87.4 0.817
AG 13.9 12.6
GG 0.3 0.0

F2 c.97G>A7,13 rs5898* GG 84.5 79.9 0.306
GA 14.5 19.2
AA 1.0 0.9

F5 c.1601G>A6,7,13 rs6015* CC 84.3 83.5 0.919
CT 15.2 16.1
TT 0.5 0.5

IL1B c.-87-511T>C6,14 rs16944 GG 41.4 37.5 0.206
AG 44.7 51.8
AA 13.9 10.7

c.-87-31C>T14 rs1143627 TT 41.4 37.1 0.184
CT 44.7 52.2
CC 13.9 10.7

IL6 c.-116-121C>G15 rs1800797* GG 35.7 33.9 0.873
AG 46.8 47.3
AA 17.5 18.8

MTHFR c.677C>T7 rs1801133 CC 42.4 43.8 0.782
CT 44.5 45.1
TT 13.1 11.2

c.1298A>C7 rs1801131 AA 54.8 43.8 0.021
AC 37.0 48.2
CC 8.2 8.0

TNF c.-169-319G>A16 rs1800629 GG 68.4 70.5 0.843
AG 29.3 27.7
AA 2.3 1.8
*

Proxy SNP

Continuous variables were compared using Student t test and categorical variables using Fisher’s exact test. P-value <0.01 was considered statistically significant without adjustment for multiple comparisons. Analyses were performed with SAS (version 9.3).

RESULTS

Cases had lower BW and GA than controls (Table III). Case mothers had less preeclampsia and cesarean deliveries but more chorioamnionitis and multiple gestation pregnancies than control mothers. Similarly, there were more cases with five minute Apgar scores < 3 and more receiving intubation for resuscitation.

Table 3.

Study Subjects

Gr 3 - 4 IVH Controls p value

Number of subjects 224 389

Birth weight grams (N, SD) 810.5 (224, 181.5) 864.3 (389, 174.0) <0.0001

GA wks (N, SD) 25.6 (224, 1.5) 26.5 (389, 1.5) <0.0001

Male subjects (%) 128/224 (57.1%) 231/389 (59.4%) 0.61

IVH status
 Grade 3 95
 Grade 4 129

Maternal variables

 Maternal prenatal visit (%) 216/222 (97.3%) 384/389 (98.7%) 0.2193

 Preeclampsia (%) 23/222 (10.4%) 91/388 (23.5%) <0.0001

 Clinical chorioamnionitis (%) 69/223 (30.9%) 69/389 (17.7%) 0.0003

 Any ANS w/in 7 d prior to delivery (%) 195/223 (87.4%) 336/388 (86.6%) 0.8043

 Complete ANS within 7 d (%) 118/224 (52.7%) 260/389 (66.8%) 0.0006

 Multiple gestation (%) 81/224 (36.2%) 90/386 (23.3%) 0.0008

 Cesarean delivery 133/224 (59.4%) 281/388 (72.4%) 0.0012

Delivery room variables

 Apgar 1 minute < 3 (%) 70/222 (31.5%) 89/388 (22.9%) 0.0216

 Apgar 5 minutes < 3 (%) 19/223 (8.5%) 14/388 (3.6%) 0.0145

Intubation for resuscitation 166/203 (81.8%) 243/351 (69.2%) 0.0013

Epinephrine for resuscitation 8/162 (4.9%) 5/215 (2.3%) 0.2535

The overall genotype call rate for the variants was 99.8% (range, 98.2-100%). To validate the quality of the genotypes from the markers, deviation from Hardy-Weinberg equilibrium was calculated. All showed insignificant deviation from expected by Hardy-Weinberg equilibrium (p>0.01).

None of the putative risk variants showed significant differences in frequency between cases and controls except the MTHFR 1298A>C polymorphism. To confirm these results, we analyzed the genotypes by 2×3 Fisher’s exact (Table I). The MTHFR 1298A>C polymorphism did not attain significance, but nearly so (Table II).

DISCUSSION

Although recent data have implicated genes contributing to the pathogenesis of IVH, we were unable to confirm as common risk factors for severe IVH 8 of the 9 published variants, and the 1298A>C variant for MTHFR gave equivocal results. Hartman reported that 4/16 preterm neonates with atypical Gr 4 IVH had this variant,7 and our cases were significantly more likely than controls to have the C allele. MTHFR catalyzes the reduction of 5,10-methylenetrahydrofolate to 5-methyltetrahydrofolate, which is necessary for the conversion of homocyteine to methionine. Hyperhomocysteinemia is associated with polymorphisms at -677 and -1298, especially the 677 TT variant, and results in endothelial cell injury and alterations in coagulation.21-23

We report a large reported cohort of inborn AGA preterm neonates of European ancestry with exposure to ANS, Gr 3–4 IVH and genotyping. Limitations include the small sample size, failure to date onset of hemorrhage and lack of homocysteine levels for study participants. This study was not able to evaluate rare variants, and, although we have previously reported a COL4A1 duplication in twins with severe IVH,24 the technology we employed was not designed to identify short insertions. The strengths include prospective collection of preterm neonates with tertiary neonatal care, centrally read ultrasounds and plans for state-of-the-art genetic analyses.

Table IV.

Site Cases Controls Total
Gene Targets for IVH 162 215 377
ELGAN 24 90 114
Iowa 17 46 63
Oulu 21 38 59
Total 224 389 613
*

Central blinded ultrasound readings were performed for all subjects from the Gene Targets for IVH, ELGAN and Iowa cohorts (554/613, 90%). Ultrasounds for Oulu subjects were performed by blinded readers but were not centrally read.

Acknowledgments

We are indebted to our medical, nursing and research colleagues and the infants and their parents who agreed to take part in this study. We also are indebted to Deborah Hirtz, MD, for scientific expertise, Jill Maller-Kesselman, MS, for study management, and Karen C. Schneider, MPH, for editorial expertise and assistance.

Supported by the National Institutes of Health (NS053865 and R01 DA016750-09 [to H.P.]). W.C. is a board member of Mednax.

ABBREVIATIONS

AGA

Appropriate for gestational age

ANS

Antenatal steroid

BW

Birth weight

COL4A1

Collagen 4A1

cUS

Cranial ultrasonography

GA

Gestational age

Gr

Grade

IL

Interleukin

IVH

Intraventricular hemorrhage

MTHFR

Methylenetetrahydrofolate reductase

TNF

Tumor necrosis factor α

Footnotes

Finally, we appreciate the contribution of our collaborators: Elizabeth Newton Alfred, MS (Department of Biostatistics, Harvard School of Public Health and Department of Neurology, Children’s Hospital Boston [ELGAN Study], Susan K. Berends, MA, Allison Momany, RN, John Daigle, MD, Nancy Weathers, RN (Iowa Prematurity, Department of Pediatrics, University of Iowa), and Johanna Huusko, MD (Oulu University, Department of Pediatrics).

The other authors declare no conflicts of interest.

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