Objective
To determine the impact of maternal and fetal single nucleotide polymorphisms in key betamethasone pathways on neonatal outcomes.
Study Design
DNA was obtained from women given betamethasone and their infants. Samples were genotyped for 73 exploratory drug metabolism and glucocorticoid pathway single nucleotide polymorphisms. Clinical variables and neonatal outcomes were obtained. Logistic regression analysis using relevant clinical variables and genotypes to model for associations with neonatal respiratory distress syndrome was performed.
Results
One hundred nine women delivering 117 infants were analyzed. Sixty-four infants (49%) developed respiratory distress syndrome. Multivariable analysis revealed that respiratory distress syndrome was associated with maternal single nucleotide polymorphisms in CYP3A5 (odds ratio [OR], 1.63; 95% confidence interval [CI], 1.16–2.30) and the glucocorticoid resistance (OR, 0.28; 95% CI, 0.08–0.95) and fetal single nucleotide polymorphisms in ADCY9 (OR, 0.17; 95% CI, 0.03–0.80) and CYP3A7*1E (rs28451617; OR, 23.68; 95% CI, 1.33–420.6).
Conclusion
Maternal and fetal genotypes are independently associated with neonatal respiratory distress syndrome after treatment with betamethasone for preterm labor.
One of the most important interventions developed for improving neonatal outcomes in preterm birth is the administration of antenatal corticosteroids. Decreasing preterm neonatal mortality and morbidity, antenatal corticosteroids are routinely administered to women with anticipated/threatened preterm delivery. However, not all neonates receive the same benefit. Differences in neonatal respiratory outcomes are seen in different ethnic groups, independent of gestational age, weight, and other sociodemographic factors. In addition, respiratory distress syndrome (RDS)-related mortality has a racial disparity that cannot be explained by demographic characteristics.
Pharmacogenetics attempts to clarify differences in response to drug therapy. Various ethnic groups have different rates of genetic polymorphisms in genes that play a major role in day-to-day functions within the body. Drug metabolizing enzymes, transporters, and receptors contain genetic variations that can explain differences in response and side effects to many drugs, notably cyclosporine, warfarin, and clopidogrel. In these cases and others, single nucleotide polymorphisms (SNPs) in key drug metabolizing enzymes and receptor pathways can have a profound impact on drug concentrations and response.
Glucocorticoids like betamethasone (BMZ) and dexamethasone are metabolized by the cytochrome P450 (CYP) 3A family of enzymes. SNPs in this enzyme family are identified that impact the drug concentrations of many compounds. In addition, SNP variants in the glucocorticoid resistance (GR) pathway have been associated with treatment differences in response to corticosteroids in asthmatics. We are unaware of any study on the pharmacogenetic impact of SNP variants in the outcomes from BMZ use in pregnancy.
The objective of this project was to determine the impact of genetic polymorphisms in the drug metabolism and glucocorticoid pathways of BMZ on neonatal outcomes. In addition, as pregnancy is a unique environment in which both the maternal and fetal/placental compartments play a role in drug metabolism, we sought to determine the impact on these outcomes analyzing both the maternal and fetal genotypes.
Materials and Methods
Study population
Women who were admitted to the hospital with threatened preterm labor and who received at least 1 dose of BMZ were recruited for this study. Informed consent was obtained from all subjects. Subjects were recruited at any of the hospitals associated with the Indiana University School of Medicine Department of Obstetrics/Gynecology. Women had to be at least 18 years old and at least 23 weeks’ gestation. Women were excluded if they had a known fetal anomaly or were unable to give consent. Standard neonatal resuscitation program protocols were followed by the neonatal provider teams at delivery. The neonatal outcome of RDS was diagnosed by the pediatricians according to standard NICHD Neonatal Research Network criteria. The project was approved by the governing institutional review board.
Sample collection and processing
Blood samples
Maternal whole blood was obtained on admission or during her hospital course. If she was unable to give a blood sample for some reason, we obtained a saliva sample as below for DNA isolation. Umbilical cord blood samples were obtained immediately after delivery in K 2 EDTA vacutainers by trained cord blood collectors. All whole blood samples were mixed by inversion 8-10 times after being drawn and then stored at −80°C until DNA isolation.
Saliva samples
If maternal blood was not obtained, she was asked to provide a saliva sample using the Oragene saliva kit collection (DNA Genotek Inc., Ontario, Canada). If umbilical cord blood was not acquired at the time of delivery because of an off-hour delivery when the study personnel were not available, a trained member of the research team obtained buccal swabs from the neonate. For buccal cell collection we used Oragene saliva kit collection with cotton swabs. Oragene kits are shown to reduce microbial contamination and provide immediate stabilization of samples, allowing it to be stored at room temperature for years without processing or DNA degradation. Oragene “Saliva collection with cotton swabs or buccal brushes” protocol was followed and 5 swabs were obtained with each collection. Kits were then stored at room temperature. Before purification the Oragene saliva sample kits were briefly mixed by gentle inversion and incubated for a minimum of 2 hours in an air incubator set to 50°C. To remove saliva from buccal swabs manufacturer protocols for “DNA Recovery from Saliva Sponges” were followed.
DNA isolation
DNA was extracted from blood samples using the QIAamp DNA mini kits (Qiagen Inc, Valencia, CA). Manufacturer spin protocol instructions were followed for all kits. When manufacturer protocols listed steps for highly concentrated DNA those steps were followed. Isolated DNA was transferred into cryovials and all samples were stored at −80°C until quantification.
DNA was purified from saliva and buccal swab samples using the Oragene Kit (DNA Genotek) manufacturer recommendations. DNA isolation was achieved according to manufacturer instructions. Samples were frozen at −80°C until quantification.
DNA quantification
Concentration of double-stranded DNA in our samples was determined using a Quant-iT dsDNA Broad Range or High Sensitivity assay Kit and Qubit Flouromter (Invitrogen, Carlsbad, CA). This system uses a fluorescent nucleic acid stain to accurately and specifically measure dsDNA at highly sensitive levels. Maternal DNA yields were similar for blood and saliva. Neonatal DNA yields from buccal swabs were less than from umbilical cord blood but were still adequate for the analysis (data not shown).
Genotyping
Seventy-three SNPs were genotyped using a combination of methods specific to the desired SNP. Genotypic designations assigned from assayed SNPs in CYP 3A4, CYP3A5, CYP3A7 , sulfotransferase ( SULT ), multidrug resistance gene-1 ( ABCB1 ), GR, and associated pathway gene assays are listed in Table 1 . The SNPs were selected based on known metabolism pathways of glucocorticoids and prior work on relevant SNPs for glucocorticoid response in asthma. The individuals were genotyped for the majority of SNPs using the OpenArray Taqman genotyping platform (Applied Biosystems, Foster City, CA). A high throughput genotyping 32 SNP chip was used for some of the SNPs. For SNPs that did not have valid OpenArray assays, predesigned, and commercially available Taqman or fragment analysis real-time polymerase chain reaction (PCR) assays were used according to manufacturer published methods (Applied Biosystems). For other SNPs that did not have predesigned assays (namely CYP3A7 and GR), Sanger dideoxy-DNA bidirectional sequencing using high throughput capillary sequencing instrumentation was performed ( http://polymorphicdna.com/reeqvardisc.html ). SULT1A1 copy number variation was determined, using semiquantitative PCR, followed by fragment analysis. For each SNP, once a platform was chosen, all samples were genotyped using the same platform.
| Gene and allele designation a | RS ID no. | SNP type | Location | BP change | SNP allele frequency b |
|---|---|---|---|---|---|
| OpenArray platform | |||||
| ABCB1 Exon 12 | rs1128503 | Synonymous | Chr. 7- 87179601 | C > T | 0.367/0.317 |
| ABCB1 Exon 21 | rs2032582 | Nonsynonymous | Chr. 7- 87179616 | G > T/A | 0.548/0.505 |
| ABCB1 Exon 26 | rs1045642 | Synonymous | Chr. 7- 87138645 | C > T | 0.450/.409 |
| ADCY9 | rs2230739 | Nonsynonymous | Chr. 16-4033436 | A > G | 0.278/0.297 |
| CRH | rs12721511 | Nonsynonymous | Chr. 8- 67089709 | C > G | c |
| CRHR1 | rs1876828 | Intron | Chr. 17-43911525 | A > G | 0.126/0.161 |
| CRHR1 | rs242941 | Intron | Chr. 17-43892520 | G > T | 0.402/0.383 |
| CYP3A4 | rs4987159 | Synonymous | Chr. 7-99366068 | C > T | 0.016/0.027 |
| CYP3A5*3 | rs776746 | Intron | Chr. 7-99270539 | A > G | 0.303/0.328 |
| CYP3A7 | rs2687133 | Intron | Chr. 7-99332083 | A > G | 0.258/0.255 |
| CYP3A7*2 | rs2257401 | Nonsynonymous | Chr. 7-99306685 | C > G | 0.269/0.218 |
| GLCCI1 | rs37973 | nearGene-5′ | Chr. 7-8007876 | A > G | 0.376/0.349 |
| IPO13 | rs7412307 | nearGene-5′ | Chr. 1-44433864 | C > G | 0.409/0.389 |
| IPO13 | rs2301992 | Intron | Chr. 1- 44426823 | A > G | c |
| IPO13 | rs2301993 | Intron | Chr. 1-44426025 | C > T | 0.400/0.400 |
| IPO13 | rs2428953 | Intron | Chr. 1-44443459 | C > T | 0.238/0.234 |
| IPO13 | rs4448553 | nearGene-5′ | Chr. 1-4441189 | A > G | 0.369/0.359 |
| IPO13 | rs2486014 | Intron | Chr. 1-44419546 | A > G | 0.116/0.107 |
| IPO13 | rs2240447 | Synonymous | Chr. 1-44415414 | A > G | 0.438/0.417 |
| IPO13 | rs1990150 | Intron | Chr. 1-44414127 | C > G | 0.244/0.212 |
| IPO13 | rs6671164 | nearGene-5′ | Chr. 1-44403489 | G/T | 0.433/0.406 |
| IPO13 | rs1636879 | Intron | Chr. 1- 44428680 | C > G | c |
| NR3C1 | rs41423247 | Intron | Chr. 5-142778575 | C > G | 0.325/0.310 |
| OLR1 | rs3736233 | Intron | Chr. 12-10313265 | A > G | 0.440/0.427 |
| STIP1/FERMT3 | rs2236647 | Intron | Chr. 11-63964605 | C > T | 0.482/0.500 |
| SULT1A2 | rs1136703 | Nonsynonymous | Chr. 16- 28607232 | T > C | c |
| TBX21 | rs2240017 | Nonsynonymous | Chr. 17- 45810919 | C > G | c |
| TRAPPC5, FCER2 | rs28364072 | Intron | Chr. 19-7755285 | A > G | 0.315/0.280 |
| DNA sequencing | |||||
| CRHR1 | rs4564621 | Intron | Chr. 17-43895501 | C > G | 0.124/0.168 |
| CRHR1 | rs2316763 | Intron | Chr. 17-43895530 | C > T | 0.124/0.168 |
| CRHR1 | N/A | Intron | Chr. 17- 43895531 | G > A | 0.000/0.000 |
| CRHR1 | rs242939 | Intron | Chr. 17-43895579 | A > G | 0.149/0.143 |
| CRHR1 | rs2316764 | Intron | Chr. 17-43895602 | G > T | 0.124/0.168 |
| CRHR1 | rs4277389 | Intron | Chr. 17-43895653 | A > G | 0.124/0.168 |
| CRHR1 | rs66586071 | Intron | Chr. 17-43893780 | G > − | 0.284/0.347 |
| CRHR1 | N/A | Intron | Chr. 17- 43895671 | T > − | 0.000/0.010 |
| CRHR1 | rs80249281 AKA rs57839112 | Intron | Chr. 17-43893790 | −/A | 0.000/0.000 |
| CRHR1 | rs11316767 | Intron | Chr. 17-43893791 | −/A | 0.000/0.000 |
| CRHR1 | rs116593005 | Intron | Chr. 17- 4393810 | C > T | 0.008/0.010 |
| CRHR1 | rs149144271 | Intron | Chr. 17- 9167967 | A > G | 0.008/0.015 |
| CRHR1 | rs8077279 | Intron | Chr. 17-43893884 | C > T | 0.012/0.000 |
| CRHR1 | rs16940655 | Intron | Chr. 17-43893886 | C > T | 0.012/0.005 |
| CYP3A7 | rs45496695 | nearGene-5′ | Chr. 7-99332867 | A > C | 0.000/0.000 |
| CYP3A7 | rs45446698 | nearGene-5′ | Chr. 7-99332948 | A > C | 0.029/0.031 |
| CYP3A7 | rs113874418 | nearGene-5′ | Chr. 7- 99332955 | A > G | 0.004/0.000 |
| CYP3A7 | rs11568826 | nearGene-5′ | Chr. 7-99332978 | A > T | 0.029/0.031 |
| CYP3A7 | rs45467892 | nearGene-5′ | Chr. 7-99332997 | A > T | 0.029/0.031 |
| CYP3A7 | rs45575938 | nearGene-5′ | Chr. 7-99332998 | C > T | 0.029/0.031 |
| CYP3A7 | rs45494802 | nearGene-5′ | Chr. 7-99333000 | A > T | 0.029/0.031 |
| CYP3A7 | rs11568824 | nearGene-5′ | Chr. 7-9933007 | G > T | 0.029/0.031 |
| CYP3A7⁎1B | rs45465393 | nearGene-5′ | Chr. 7-9933030 | C > T | 0.000/0.005 |
| CYP3A7⁎1C | rs11568825 | nearGene-5′ | Chr. 7-99332986 | G > T | 0.029/0.031 |
| CYP3A7⁎1D | rs55798860 | 5′UTR | Chr. 7-99332807 | C > T | 0.000/0.000 |
| CYP3A7⁎1E | rs28451617 | 5′UTR | Chr. 7-99332765 | C > T | 0.033/0.026 |
| NR3C1 | rs6189 | Synonymous | Chr. 5-142780338 | A > G | 0.012/0.010 |
| NR3C1 | rs6190 | Nonsynonymous | Chr. 5-142780337 | A > G | 0.012/0.010 |
| NR3C1 | rs72542738 | Synonymous | Chr. 5-142780332 | A > G | 0.000/0.000 |
| NR3C1 | rs72481829 | Nonsynonymous | Chr. 5-142780331 | A > G | 0.000/0.000 |
| NR3C1 | rs61759025 | Synonymous | Chr. 5-142780264 | A > G | 0.000/0.000 |
| NR3C1 | rs79138720 | Nonsynonymous | Chr. 5-14278056 | A > C | 0.000/0.000 |
| NR3C1 | rs6192 | Nonsynonymous | Chr. 5-142780212 | G > T | 0.012/0.010 |
| NR3C1 | rs72558023 | Synonymous | Chr. 5-142780206 | A > G | 0.000/0.000 |
| NR3C1 | rs72542745 | Nonsynonymous | Chr. 5-142779432 | A > G | 0.000/0.000 |
| NR3C1 | rs72558022 | Nonsynonymous | Chr. 5-142779369 | C > G | 0.000/0.000 |
| NR3C1 | rs13306589 | Synonymous | Chr. 5-142779340 | A > G | 0.000/0.000 |
| NR3C1 | rs56149945 | Nonsynonymous | Chr. 5-142779317 | A > G > T | 0.025/0.015 |
| NR3C1 | rs1800445 | Nonsynonymous | Chr. 5-142779311 | A > G | 0.000/0.000 |
| Custom PCR assay | |||||
| CYP3A4⁎1B | rs2740574 | nearGene-5′ | Chr. 7-99382096 | A > G | 0.211/0.259 |
| CYP3A5⁎6 | rs10264272 | Synonymous | Chr. 7-99262835 | C > T | 0.041/0.040 |
| CYP3A5⁎7 | rs41303343 | Frameshift | Chr. 7-99250393 | A > T | 0.074/0.045 |
| SULT1A1⁎2 | rs9282861 | Nonsynonymous | Chr. 16-286171514 | A > G | 0.847/0.942 |
| SULT1A1 | rs3760091 | 5′UTR | Chr. 16-28620800 | C > G > T | 0.609/0.709 |
| SULT1A1 | rs750155 | 5′UTR | Chr. 16-28620572 | C > T | 0.726/0.674 |
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