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Identification of fetal and maternal single nucleotide polymorphisms in candidate genes that predispose to spontaneous preterm labor with intact membranes

      Objective

      The purpose of this study was to determine whether maternal/fetal single nucleotide polymorphisms (SNPs) in candidate genes are associated with spontaneous preterm labor/delivery.

      Study Design

      A genetic association study was conducted in 223 mothers and 179 fetuses (preterm labor with intact membranes who delivered <37 weeks of gestation [preterm birth (PTB)]), and 599 mothers and 628 fetuses (normal pregnancy); 190 candidate genes and 775 SNPs were studied. Single locus/haplotype association analyses were performed; the false discovery rate was used to correct for multiple testing.

      Results

      The strongest single locus associations with PTB were interleukin-6 receptor 1 (fetus; P = .000148) and tissue inhibitor of metalloproteinase 2 (mother; P = .000197), which remained significant after correction for multiple comparisons. Global haplotype analysis indicated an association between a fetal DNA variant in insulin-like growth factor F2 and maternal alpha 3 type IV collagen isoform 1 (global, P = .004 and .007, respectively).

      Conclusion

      An SNP involved in controlling fetal inflammation (interleukin-6 receptor 1) and DNA variants in maternal genes encoding for proteins involved in extracellular matrix metabolism approximately doubled the risk of PTB.

      Key words

      Preterm birth (PTB) is the leading cause of perinatal morbidity and death worldwide.
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      PTB may be the result of spontaneous preterm labor, with intact or ruptured membranes, or indicated PTB (for fetal or maternal indications).
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      The purpose of this genetic association study was to identify DNA variants in the maternal and fetal genomes that can alter the risk for spontaneous preterm labor and delivery. Seven hundred seventy-five single nucleotide polymorphisms (SNPs) from 190 candidate genes that have been implicated in the mechanisms of disease that are responsible for spontaneous preterm labor, preterm prelabor rupture of membranes (pPROM), small-for-gestational age (SGA), and preeclampsia were analyzed. The study was conducted in a Hispanic population at a single site from Chile that has an estimated PTB rate of 6%
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      and with extreme care to phenotypic characterization.

      Materials and Methods

      Study design

      This was a case-control study that included patients with spontaneous preterm labor and intact membranes who delivered a preterm neonate (mothers, 223; fetuses, 179) and control subjects (mothers, 599; fetuses, 628). Spontaneous preterm labor and delivery was defined by the presence of regular uterine contractions that occurred at a frequency of at least 2 every 10 minutes that resulted in a preterm delivery (<37 weeks of gestation). The control group included women who delivered at term (37-42 weeks of gestation) without complications of pregnancy, which included preterm labor with term delivery, preeclampsia, eclampsia, HELLP (hemolysis, elevated liver enzymes and low platelet count) syndrome, pPROM, SGA, large-for-gestational age neonates, fetal death, placental abruption, placenta previa, or chorioamnionitis.
      Patients of Hispanic origin were recruited at the Sotero del Rio Hospital, in Puente Alto, Chile. All eligible mothers were enrolled in a research protocol that requested permission to collect DNA from the mother and her neonate for research purposes. The exclusion criteria, beside those explained earlier for control subjects, included (1) known major fetal chromosomal and/or structural anomalies, (2) multiple pregnancy, (3) serious medical illness (eg, chronic renal failure, congestive heart failure, connective tissue disorders), (4) refusal to provide written informed consent, and (5) a clinical emergency that prevented counseling of the patient about participation in the study, such as fetal distress or maternal hemorrhage. A blood sample was obtained from the mother at the time of enrollment in the protocol and from the umbilical cord (blood of fetal origin) after delivery. Demographic and clinical characteristics of the mothers were obtained from a data collection form that was administered by trained medical and paramedical personnel. The collection of samples and their use for research purposes was approved by the Institutional Review Boards of the Sotero del Rio Hospital, Santiago, Chile (an affiliate of the Pontificia Catholic University of Santiago, Chile), and the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services.

      Genotyping

      Candidate genes were selected for analysis on the basis of biologic plausibility for a role in preterm labor and other pregnancy complications that included SGA, pPROM, and preeclampsia. Genes that are involved in processes such as the control of the immune response (pattern recognition receptors, cytokines, chemokines, and their respective receptors), uteroplacental ischemia, and angiogenesis were considered appropriate candidates for this study. A complete list of the 190 genes and all SNPs that were genotyped are included in the supplemental materials (Supplemental Table 1).
      APPENDIXList of all single nucleotide polymorphisms and genes that were examined
      Gene codeSingle nucleotide polymorphisms rs no.
      ACErs4298
      ACErs4309
      ACErs4311
      ACErs4331
      ACErs4354
      ADRB2rs2053044
      ADRB2rs1800888
      AGTrs4762
      AGTrs2478522
      AGTR1rs275652
      AGTR1rs5182
      AGTR1rs5183
      ANGrs11701
      ANGPT2rs2515507
      ANGPT2rs3739391
      ANGPT2rs3020221
      ANGPT2rs963496
      ANGPT2rs1961222
      ANGPT2rs2442622
      ANGPT2rs2979671
      APOA1rs12718466
      APOBrs1367117
      APOBrs570877
      APOBrs1801700
      APOBrs12720828
      APOBrs2854725
      APOBrs533617
      APOBrs693
      APOBrs1801701
      APOC3rs35536400
      APOC3GNSC_633938806
      APOC3GNSC_633938845
      APOC3rs4520
      APOC3rs2070666
      APOC3rs34635405
      APOErs769446
      APOErs405509
      APOErs440446
      APOErs769449
      AQP2rs3759126
      AQP2GNSC_629722626
      AQP2rs3741559
      AQP2rs426496
      AQP2GNSC_629722653
      CARD15rs2066850
      CARD15rs2067085
      CARD15rs1861759
      CARD15rs5743291
      CCL2rs2857657
      CCL2rs4586
      CCR2rs3749461
      CCR2rs61751656
      CD14GNSC_13154561
      CD14GNSC_13154559
      CETPrs17245715
      CETPrs4783962
      CETPrs17231534
      CETPrs289714
      CETPrs891144
      CETPrs5880
      CETPrs1800774
      CETPrs5882
      CETPrs289741
      COL1A1rs11079898
      COL1A1rs17639446
      COL1A1rs2141279
      COL1A1rs1007086
      COL1A1rs2586490
      COL1A1rs2586488
      COL1A1rs2277632
      COL1A1rs2249492
      COL1A2GNSC_28207362
      COL1A2rs4729131
      COL1A2rs42518
      COL1A2rs28754326
      COL1A2rs2521206
      COL1A2rs2621208
      COL1A2rs2301643
      COL1A2rs13240759
      COL1A2rs13240759
      COL1A2rs1800248
      COL1A2rs10046552
      COL1A2rs11764718
      COL3A1rs7579903
      COL3A1rs13306272
      COL3A1rs13306257
      COL3A1rs3765161
      COL3A1rs28763878
      COL4A1GNSC_633869360
      COL4A1rs41275106
      COL4A1rs626444
      COL4A1rs645114
      COL4A1rs598893
      COL4A1rs12867220
      COL4A1rs685884
      COL4A1rs17591246
      COL4A1GNSC_633878169
      COL4A1rs16975492
      COL4A1rs16975491
      COL4A1rs503053
      COL4A1GNSC_633856439
      COL4A1rs1778817
      COL4A1rs1816884
      COL4A1rs16975424
      COL4A2rs3803229
      COL4A2rs3803228
      COL4A2rs2296852
      COL4A2rs41315048
      COL4A2rs2296849
      COL4A2rs421177
      COL4A2rs12873113
      COL4A2rs7338575
      COL4A2rs391859
      COL4A2rs2479426
      COL4A3rs13424243
      COL4A3rs1882435
      COL4A3rs10178458
      COL4A3rs55997063
      COL4A3rs12621551
      COL4A3rs13386404
      COL4A3rs7559693
      COL4A3rs35467545
      COL4A3GNSC_634673660
      COL4A3rs10933172
      COL4A3rs56326869
      COL4A4rs12465531
      COL4A4rs12475686
      COL4A4rs1800516
      COL4A4rs13027659
      COL4A4rs3752896
      COL4A4rs3752895
      COL4A5rs55941015
      COL4A5rs2273051
      COL4A5rs28465565
      COL4A6rs1266731
      COL4A6GNSC_634841755
      COL4A6GNSC_634410330
      COL5A1rs3811149
      COL5A1rs7036997
      COL5A1GNSC_634237373
      COL5A1rs7868111
      COL5A1rs13946
      COL5A2rs4128539
      COL5A2GNSC_635138172
      COL5A2GNSC_635136454
      COL5A2GNSC_635148121
      COL5A2GNSC_635148713
      COL5A2rs6750027
      COL5A2rs6434312
      COL5A2GNSC_635134938
      COL5A2rs10208525
      COL5A2rs7420715
      CRHR1rs12936511
      CRHR1rs17762882
      CRHR1rs17425752
      CRHR1rs16940668
      CRHR1rs17689966
      CRHR1rs28364026
      CRHR2rs41417745
      CRHR2rs8192496
      CRHR2rs4723000
      CRHR2rs8192498
      CRHR2rs7812133
      CSF1rs2297706
      CSF1rs2275123
      CSF1rs333970
      CSF1rs1058885
      CSF1rs2229165
      CSF2rs1469149
      CSF3rs25645
      CSPG2rs11742293
      CSPG2rs12332199
      CSPG2rs4470745
      CSPG2rs2287926
      CSPG2rs2548541
      CSPG2rs309559
      CSPG2rs188703
      CSPG2rs160279
      CSPG2rs160277
      DAFrs28371583
      DAFrs10746462
      DEFA5rs4610776
      DEFA5rs2272719
      DEFB1rs5743418
      DEFB1rs5743420
      DLATGNSC_659891580
      EDN1rs2070699
      EDN1rs1800543
      EDN1rs5369
      ELNrs2301995
      ELNrs28763981
      ELNrs2528796
      ELNrs2071307
      ELNrs2856728
      ELNrs28763986
      ELNrs17855988
      ESR1rs867239
      ESR1rs746432
      ESR2rs3829768
      ESR2rs944050
      ESR2rs4986938
      F12rs1801020
      F12rs17876029
      F12rs17876047
      F13A1rs5981
      F13A1rs2274393
      F13A1rs3024444
      F13A1rs5982
      F13A1rs3024458
      F13Brs1412632
      F13Brs5996
      F13Brs1759009
      F13Brs5990
      F2rs2070850
      F2rs3136434
      F2rs3136435
      F2rs2070852
      F2rs5896
      F2rs5900
      F2rs3136516
      F3rs13306321
      F3rs610277
      F5rs6019
      F5rs6012
      F5rs2239854
      F5rs6015
      F5rs6020
      F5rs9332607
      F5rs9332608
      F5rs9332620
      F5rs6030
      F5rs2301517
      F7rs2774030
      F7rs6046
      FABP2rs13306357
      FABP2rs1397614
      FGBGNSC_12297445
      FGF1rs9324894
      FGF1rs17217240
      FGF1rs34003
      FGF2rs41456044
      FGF2rs4554090
      FGF2rs45627736
      FGF4rs2073464
      FGF4GNSC_634043245
      FGF4rs3740640
      FIGFGNSC_634828146
      FLT1GNSC_634778804
      FLT1rs17086747
      FLT1rs17086681
      FLT1GNSC_634071775
      FLT1rs2296190
      FLT1rs2296189
      FLT1rs2296188
      FLT1rs9579177
      FLT4rs3736061
      FLT4GNSC_22175089
      FLT4rs728986
      FLT4rs307826
      FLT4rs2242213
      FLT4rs2242215
      FN1rs2289202
      FN1rs3796123
      FN1rs7570208
      FN1rs1053238
      FN1rs1250215
      FN1GNSC_633954160
      FN1rs1250204
      FN1rs2304573
      FN1rs7568287
      FN1rs10498037
      FN1rs11651
      GJA4rs56078817
      GJA4rs1764389
      GJA4rs41266431
      GJA4GNSC_10346829
      GJB2GNSC_20116657
      GJB2rs2274084
      GNB3rs5440
      GNB3GNSC_43188143
      GNB3rs28395781
      GNB3rs2301339
      GNB3rs5445
      GP1BArs6066
      HLA-EGNSC_632164643
      HLA-Ers1059510
      HLA-Ers1264457
      HLA-Grs1233334
      HLA-Grs1630185
      HLA-Grs12722477
      HLA-Grs1049033
      HPGDrs17524423
      HPGDrs17524423
      HSPG2rs28546127
      HSPG2rs2290498
      HSPG2GNSC_634045807
      HSPG2rs6658388
      HSPG2rs2290501
      HSPG2GNSC_634098268
      HSPG2rs2229489
      HSPG2rs2229491
      HSPG2rs35570238
      HSPG2rs17459097
      HSPG2rs2229487
      HSPG2rs4654771
      HSPG2rs2229488
      HTR2Ars6314
      IFNGR1rs1327474
      IFNGR1rs1887415
      IFNGR2rs9808753
      IFNGR2rs11910627
      IFNGR2rs1532
      IGF1rs5742612
      IGF1rs5742620
      IGF1Rrs7174918
      IGF1Rrs2272037
      IGF1Rrs951715
      IGF1Rrs34816681
      IGF1Rrs2684806
      IGF1Rrs3743262
      IGF1Rrs28401726
      IGF1Rrs2293117
      IGF2rs3213223
      IGF2rs3213225
      IGF2rs2230949
      IGF2Rrs2277070
      IGF2Rrs8191754
      IGF2Rrs894817
      IGF2Rrs998074
      IGF2Rrs2282139
      IGF2Rrs6909681
      IGF2Rrs8191819
      IGF2Rrs2274849
      IGF2Rrs8191888
      IGF2Rrs629849
      IGF2Rrs8191890
      IGF2Rrs1805075
      IGF2Rrs2297367
      IL10rs1800895
      IL10rs1800872
      IL10rs3024509
      IL10rs5743627
      IL10RArs4252303
      IL10RArs17121493
      IL10RArs4252274
      IL10RArs2229115
      IL10RArs2229114
      IL12Ars2243115
      IL12BGNSC_632292870
      IL12Brs11574790
      IL12Brs3213119
      IL12RB1rs436857
      IL12RB1rs2305743
      IL12RB1rs11086087
      IL12RB1rs11673460
      IL12RB1rs383483
      IL12RB1rs3746190
      IL12RB2rs1495963
      IL12RB2rs4297265
      IL12RB2rs2229546
      IL13RA2rs5988195
      IL18rs1946519
      IL18rs549908
      IL18BPrs5743658
      IL18BPrs5743661
      IL18BPrs1892919
      IL1Ars2071374
      IL1Ars17561
      IL1Ars3783550
      IL1Brs3136558
      IL1Brs1143634
      IL1Brs1143643
      IL1R1rs997049
      IL1R1rs3917318
      IL1R2rs3218852
      IL1R2rs2230400
      IL1R2rs2282747
      IL1R2rs2072479
      IL1R2rs3218974
      IL1R2rs3218977
      IL1RAPL1GNSC_634739537
      IL1RNrs439154
      IL1RNrs451578
      IL1RNrs454078
      IL2rs2069762
      IL2rs2069771
      IL2rs2069772
      IL2RArs4986791
      IL2RArs12358961
      IL2RArs11256360
      IL2RArs10752175
      IL2RArs28360490
      IL2RArs7899538
      IL2RArs7076103
      IL3rs31480
      IL3rs40401
      IL3rs2069790
      IL3RAGNSC_649033887
      IL4rs2243247
      IL4rs2243290
      IL4Rrs3024544
      IL4Rrs2234895
      IL4Rrs2301807
      IL4Rrs4787423
      IL4Rrs3024668
      IL4Rrs2234897
      IL4Rrs1805015
      IL4Rrs3024678
      IL4Rrs1805016
      IL4Rrs8674
      IL4Rrs1029489
      IL5rs2069812
      IL5RArs13090169
      IL5RArs2290608
      IL5RArs13097407
      IL5RArs17878995
      IL6GNSC_30713312
      IL6GNSC_632284204
      IL6rs2066992
      IL6rs2069840
      IL6rs2069849
      IL6RGNSC_24750639
      IL6Rrs8192282
      IL6Rrs2229237
      IL6Rrs7521458
      IL8rs4073
      IL8RArs16858811
      IL8RBrs4674259
      IL9rs1799962
      IL9rs2069882
      IL9rs2069885
      IL9RGNSC_14430798
      IL9RGNSC_14433537
      IRS1GNSC_632344426
      IRS1rs3731597
      IRS1rs1801278
      ITGB3rs3809862
      ITGB3rs5918
      ITGB3rs13306478
      ITGB3rs2292864
      ITGB3rs41315064
      ITGB3rs15908
      ITGB3rs11870252
      ITGB3rs3760372
      ITGB3rs3809863
      LEPrs6976701
      LEPrs28954080
      LIPCrs1077835
      LIPCGNSC_16324977
      LIPCGNSC_11247957
      LIPCrs6078
      LIPCrs2414592
      LIPCrs6080
      LIPCrs6083
      LIPCrs6074
      LPArs41269142
      LPArs9365178
      LPArs41272110
      LPArs41272112
      LPArs41272114
      LPArs4708871
      LPArs3798220
      LPArs3127596
      LPLGNSC_12584682
      LPLrs1801177
      LPLrs1121923
      LPLrs254
      LPLrs270
      LPLrs327
      LPLrs11570891
      LPLrs4922115
      LTArs2229094
      LTArs3093542
      LTArs1041981
      LTFrs4683227
      LTFGNSC_633839426
      LTFrs17141147
      LTFrs1475967
      LTFrs2239692
      LTFrs2269435
      LTFGNSC_633838636
      LTFGNSC_633838704
      LTFrs2073493
      LTFGNSC_617330042
      LYZrs511589
      LYZrs513342
      LYZrs1800973
      LYZrs686407
      MBL2GNSC_633877244
      MBL2rs5030737
      MBL2rs35805975
      MGPrs1800801
      MIFGNSC_641918458
      MMP1rs514921
      MMP1rs470132
      MMP1rs470558
      MMP1rs5031036
      MMP1rs1051121
      MMP1rs488178
      MMP1rs1938901
      MMP1rs470747
      MMP1rs2071230
      MMP10rs17435959
      MMP10rs486055
      MMP10rs17293607
      MMP10rs17860949
      MMP10rs17860950
      MMP10rs470277
      MMP10rs17860995
      MMP10rs470168
      MMP11rs28363645
      MMP11rs738792
      MMP11rs28363648
      MMP11rs9612427
      MMP11rs28363665
      MMP11rs2877173
      MMP12rs2276109
      MMP12rs632009
      MMP13rs2252070
      MMP14rs2236302
      MMP14rs2236303
      MMP14rs2236304
      MMP14rs2236307
      MMP14rs743257
      MMP15rs28733439
      MMP15rs2241774
      MMP16rs28907871
      MMP16rs16892543
      MMP16rs28907593
      MMP16rs3739381
      MMP16rs3739382
      MMP17rs12322870
      MMP17rs11835665
      MMP19rs2291267
      MMP19rs1056784
      MMP19GNSC_20236865
      MMP2rs243864
      MMP2rs2285053
      MMP2rs1132896
      MMP2rs243849
      MMP2rs243843
      MMP2rs11541998
      MMP2rs243832
      MMP3GNSC_962641
      MMP3rs646910
      MMP7GNSC_9685579
      MMP7rs14983
      MMP8rs1320632
      MMP8rs17099443
      MMP8rs3740938
      MMP8rs35866072
      MMP9rs3918253
      MMP9rs2274755
      MMP9rs2250889
      MTHFRrs2066470
      MTHFRrs1994798
      NFKB1rs1609993
      NFKB1rs4648110
      NFKB1rs3817685
      NFKB1rs1609798
      NOS2Ars2779248
      NOS2Ars10459953
      NOS2Ars3730013
      NOS2Ars3730017
      NOS2Ars3729508
      NOS2Ars1137933
      NOS2Ars28999412
      NOS2Ars3729727
      NOS2Ars41337547
      NOS3rs1549758
      NOS3rs1800782
      NOS3rs2853796
      NOS3rs3730305
      NOS3rs3730006
      NOS3rs743507
      NOS3rs891512
      NPPArs17376426
      NPPArs5063
      NPPArs5064
      NPPArs5065
      NPPArs5068
      NPR1rs3891075
      NPYrs16147
      NPYrs16145
      NPYrs16143
      NPYrs16478
      NPYGNSC_3047601
      OXTRGNSC_631469588
      OXTRGNSC_631469608
      OXTRrs237911
      PAFAH1B1GNSC_451949
      PDGFBrs9622979
      PDGFBGNSC_635156599
      PDGFCGNSC_634820282
      PDGFCrs3815861
      PECAM1GNSC_632346114
      PECAM1rs668
      PGFrs2159907
      PGFGNSC_632345684
      PIGFGNSC_15616680
      PIGFrs2242033
      PLATrs8178674
      PLATrs2020919
      PLATrs2020920
      PLATrs8178750
      PLATrs2020922
      PLATrs1136159
      PLAUrs2227562
      PLAUrs2227564
      PLAUrs2227571
      PLAURGNSC_7898646
      PLAURrs4251831
      PLAURrs4251877
      PLAURrs4251883
      PLAURrs3786953
      PLAURrs2302525
      PLAURrs2302524
      PLAURrs4251923
      PON1rs705381
      PON1rs2074351
      PON1rs854560
      PON1rs3917541
      PPARArs1800246
      PPARArs1800234
      PPARArs4253772
      PPARGrs1801282
      PPARGrs3856806
      PROCrs5937
      PROS1rs8178610
      PTGER1rs3810254
      PTGER1rs28364035
      PTGER1rs28364039
      PTGER1rs3745459
      PTGER1rs10421765
      PTGER1rs10419296
      PTGER2rs1254600
      PTGER2rs2229187
      PTGER3rs5673
      PTGER4rs2228058
      PTGER4GNSC_626750174
      PTGS1rs1236913
      PTGS1rs3842787
      PTGS1rs3842788
      PTGS1rs2282169
      PTGS1rs5788
      PTGS1rs5789
      PTGS1rs3842798
      PTGS1rs10306183
      PTGS2rs20424
      PTGS2rs2066826
      PTGS2rs4648276
      RENrs1464816
      RENrs3730102
      RENrs3730103
      RENrs2368564
      SELErs5361
      SELErs2076059
      SELErs1534904
      SELErs5363
      SELErs1076637
      SELErs5356
      SELPrs3917727
      SELPrs6136
      SELPrs6128
      SERPINC1rs5878
      SERPINC1rs2759328
      SERPINC1rs677
      SERPINE1rs6092
      SERPINE1rs6090
      SERPINE1rs2227684
      SERPINE1rs2227692
      SERPINE1GNSC_629203538
      SOD3rs8192288
      SOD3rs8192290
      SPARCrs4958281
      SPARCrs2304052
      SPARCrs2116780
      SPARCrs7719521
      SPARCrs1060151
      TAP1rs1351382
      TAP1rs4148878
      TAP1rs2071538
      TAP1rs2071482
      TAP1rs16871027
      TAP1rs1135216
      TAP1rs1057149
      TBXAS1rs10256282
      TBXAS1GNSC_53711588
      TBXAS1rs3735355
      TBXAS1rs2072179
      TBXAS1rs5763
      TGFB1rs1800468
      TGFB1rs1800469
      TGFB1rs1800471
      TGFB1rs2241716
      TGFB1rs1800472
      THBDrs1042579
      THBDrs1962
      THBS1rs2292305
      THBS1rs2228263
      THBS1rs17632916
      THBS4rs2241826
      THBS4rs1866389
      THBS4rs256439
      THBS4rs16877469
      THBS4rs17885983
      THBS4rs2288395
      THPOrs956732
      THPOrs2280740
      THPOrs6142
      TIMP1rs11551797
      TIMP2rs8080623
      TIMP2rs55743137
      TIMP2rs2277698
      TLR1rs5743553
      TLR1rs5743557
      TLR1rs5743611
      TLR1rs3923647
      TLR2rs3804100
      TLR2rs5743700
      TLR3rs5743309
      TLR3rs5743312
      TLR3rs3775290
      TLR4rs4986790
      TLR4rs4986791
      TLR5rs1773766
      TLR5rs5744168
      TLR5rs2072493
      TLR6rs5743818
      TLR9rs352140
      TNFrs361525
      TNFrs1800610
      TNFrs3093664
      TNFrs3093665
      TNFRSF1Ars4149570
      TNFRSF1Ars4149621
      TNFRSF1Ars1800692
      TNFRSF1Ars12426675
      TNFRSF1Brs5746016
      TNFRSF1Brs472093
      TNFRSF1Brs1061622
      TNFRSF1Brs5746026
      TNFRSF1Brs2275416
      TNFRSF1Brs5746051
      TNRGNSC_633863341
      TNRrs859398
      TNRrs2239818
      TNRrs2239819
      TNRrs859400
      TNRrs859427
      TNRrs1385540
      TNRrs2228359
      TNRrs2301432
      TNRrs2213635
      TNRrs34842046
      VEGFrs2146323
      VEGFrs3024997
      VEGFrs3025000
      VEGFrs3025039
      VEGFBrs11603042
      VEGFCGNSC_636236098
      VEGFCrs4604006
      VEGFCrs7664413
      VWFGNSC_635156524
      VWFrs1800377
      VWFGNSC_635285421
      VWFrs216325
      VWFrs216321
      VWFGNSC_634065200
      VWFrs1800380
      VWFrs17491334
      VWFrs216900
      VWFrs2270151
      VWFrs2362483
      VWFrs7976955
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      SNP discovery within the candidate genes was performed by DNA sequencing at Genaissance Pharmaceuticals, Inc (New Haven, CT) with the use of its Index Repository, which includes a total of 93 subjects with Native American, Hispanic/Latino, European, Asian, and African American ancestry.
      • Stephens J.C.
      • Schneider J.A.
      • Tanguay D.A.
      • et al.
      Haplotype variation and linkage disequilibrium in 313 human genes.
      To determine which individuals in the Genaissance Index Repository were most representative of the genetic variation that was observed in the Chilean population, 96 unrelated Chilean individuals who were representative of the patient cohort were sequenced for 16 DNA fragments. A subset of 42 subjects from the Index Repository that is heavily weighted with the Native American and Hispanic/Latino subjects (although European, Asian, and African American subjects contributed to the subset as well) was determined to be most representative of the variation for the Chilean population. This was based on the correlation in the minor allele frequencies for the SNPs in 16 DNA fragments that were sequenced in both the Index Repository and the sample of patients from Chile (mothers with the same ethnicity who were delivered at the same hospital). This subset of 42 individuals was used to select polymorphisms for the candidate genes. The selection was performed by the application of the Shannon-Wiener diversity metric to this subset, as previously described;
      • Judson R.
      • Salisbury B.
      • Schneider J.
      • Windemuth A.
      • Stephens J.C.
      How many SNPs does a genome-wide haplotype map require?.
      the SNPs that were selected for genotyping were intended to capture at least 90% of the haplotypic diversity of each gene, which would cover the variation in the coding regions, 100 bases at each end of the introns, 1000 bases upstream of the start codon, and 100 bases downstream of the stop codon.
      • Judson R.
      • Salisbury B.
      • Schneider J.
      • Windemuth A.
      • Stephens J.C.
      How many SNPs does a genome-wide haplotype map require?.
      Template DNA for genotyping was obtained by whole-genome amplification
      • Kuivaniemi H.
      • Yoon S.
      • Shibamura H.
      • Skunca M.
      • Vongpunsawad S.
      • Tromp G.
      Primer-extension preamplified DNA is a reliable template for genotyping.
      of genomic DNA that was isolated from blood with an automated DNA isolation protocol (BioRobot 9604; Qiagen, Valencia, CA). Genotyping was carried out with the MassARRAY TM System (Sequenom, Inc, San Diego, CA) at the high-throughput genotyping facility at Genaissance Pharmaceuticals Inc. Each genotyping assay involved polymerase chain reaction amplification from template DNA in a target region that was defined by specific primers for the respective polymorphic sites, purification of the amplification product, annealing of the indicated extension primer to 1 strand of the amplification product adjacent to the polymorphic site, extending the primer by 1 nucleotide with the use of the MassEXTEND TM reaction (Sequenom Inc), and detection of the allele-specific extension product by mass spectrometry.
      • Winkelmann B.R.
      • Hoffmann M.M.
      • Nauck M.
      • et al.
      Haplotypes of the cholesteryl ester transfer protein gene predict lipid-modifying response to statin therapy.

      Quality control

      Univariate and multivariate distributions were evaluated for each variable to identify significant outliers. The values of the outliers were removed only if they were found to be incorrect on reexamination. Each SNP was verified to ensure genetic consistency between the genotypes of mother and offspring. Numerous programs are available for the detection of relationship errors;
      • Boehnke M.
      • Cox N.J.
      Accurate inference of relationships in sib-pair linkage studies.
      • Goring H.H.
      • Ott J.
      Relationship estimation in affected sib pair analysis of late-onset diseases.
      • Olson J.M.
      Relationship estimation by Markov-process models in a sib-pair linkage study.
      • Epstein M.P.
      • Duren W.L.
      • Boehnke M.
      Improved inference of relationship for pairs of individuals.
      • Abecasis G.R.
      • Cherny S.S.
      • Cookson W.O.
      • Cardon L.R.
      GRR: graphical representation of relationship errors.
      however, to produce accurate results, these programs require genotyping for a larger proportion of the genome than was available in this study. Therefore, we considered the number of Mendelian inconsistencies between mother and offspring to identify potential relationship errors (eg, sample mix-ups or mislabeling). When an inconsistency for an individual marker was observed, those genotypes were removed at that marker. In the case of multiple inconsistencies in a given pair, the pair was excluded from further analysis (10 pairs in control subjects and 5 pairs in cases). Finally, we assessed the presence of genotyping errors. In some instances, genotyping errors will lead to Mendelian inconsistencies, which can be identified easily and removed from the analysis. However, most genotyping errors for SNPs will be Mendelian consistent.
      • Douglas J.A.
      • Skol A.D.
      • Boehnke M.
      Probability of detection of genotyping errors and mutations as inheritance inconsistencies in nuclear-family data.
      For example, with mother-offspring pedigree structures, genotyping errors in which a homozygous individual has been mistyped as a heterozygous individual will never lead to a Mendelian inconsistency for SNPs. Deviations from Hardy-Weinberg equilibrium (HWE) may indicate the presence of a genotyping error or hidden population stratification
      • Lee W.C.
      Detecting population stratification using a panel of single nucleotide polymorphisms.
      or reflect a biologic effect such as natural selection (or other evolutionary force) and/or the association of disease and genotype.
      • Feder J.N.
      • Gnirke A.
      • Thomas W.
      • et al.
      A novel MHC class I-like gene is mutated in patients with hereditary haemochromatosis.
      • Nielsen D.M.
      • Ehm M.G.
      • Weir B.S.
      Detecting marker-disease association by testing for Hardy-Weinberg disequilibrium at a marker locus.
      • Wittke-Thompson J.K.
      • Pluzhnikov A.
      • Cox N.J.
      Rational inferences about departures from Hardy-Weinberg equilibrium.
      • Trikalinos T.A.
      • Salanti G.
      • Khoury M.J.
      • Ioannidis J.P.
      Impact of violations and deviations in Hardy-Weinberg equilibrium on postulated gene-disease associations.
      • Ryckman K.K.
      • Jiang L.
      • Li C.
      • Bartlett J.
      • Haines J.L.
      • Williams S.M.
      A prevalence-based association test for case-control studies.
      Tests for deviations from HWE were performed for mothers and offspring separately and again separately for diagnostic subgroups. Because it is currently unclear how to distinguish unequivocally between deviations from HWE because of genotyping error and biologic causes (such as location at or near a disease susceptibility locus), we noted SNPs that deviated from HWE, but we did not remove them from the analysis. If necessary, we could follow up these observations with additional testing. In this study, no SNPs that were found to be associated with spontaneous preterm labor/delivery with intact membranes deviated from HWE in both cases and control subjects. We tested for population stratification in cases and control subjects using STRUCTURE.
      • Pritchard J.K.
      • Stephens M.
      • Donnelly P.
      Inference of population structure using multilocus genotype data.
      We used the Caucasian European (CEU) and Asian (Chinese [CHB] and Japanese [JPT]) populations as reference populations because Hispanic populations in the Americas, including those in Chile, are the products of admixture between European and Native American populations, and Native American populations are derived most recently from Asia. The analyses show that the Chilean samples, both cases and control subjects, cluster within the HapMap CEU samples, which indicates that our cases and control subjects do not represent stratified populations (Figure 1).
      Figure thumbnail gr1
      FIGURE 1Structure analysis to detect population stratification
      A, Each mother is represented; cases are in red, and control subjects are in green. Also included are samples from HapMap (phase 3). These samples are the Caucasian European (blue) and Asian samples (Chinese and Japanese; yellow) to test the hypothesis of population stratification. Clustering at the vertices indicate genetic similarity and little stratification. The samples from the Chile cluster within the space are defined by the European samples, which supports the hypotheses of little or no genetic stratification. B, This is the same analysis that was conducted with fetal samples that were included in the current study; the criteria and color coding are the same as in A. As with the maternal samples, there is no evidence of substantial population stratification.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.

      Statistical analysis

      Continuous demographic and clinical characteristics of cases and control subjects (gestational age, birthweight, maternal age, and body mass index) were tested for normality by the Shapiro-Wilks test. All measurements deviated significantly from normality; therefore, Mann-Whitney 2-sample rank sum tests were used for case-control comparisons. χ2 tests were used to test for differences in parity, Apgar scores at 1 and 5 minutes, smoking, and differences in fetal gender between cases and control subjects. Stata 10.0 statistical software (StataCorp, College Station, TX) was used for all analyses.

      Single locus tests of association

      Statistical tests for single locus association and for deviations from HWE were calculated with PLINK software.
      • Purcell S.
      • Neale B.
      • Todd-Brown K.
      • et al.
      PLINK: a tool set for whole-genome association and population-based linkage analyses.
      Deviations from HWE in cases and control subjects were determined by χ2 test. Single locus tests of association were performed with logistic regression with the use of an additive genotypic model in which the minor allele was coded as the risk allele. Standard summary statistics, odds ratios (ORs), and confidence intervals (CIs) were reported for these tests of association. Before performing single locus and haplotype analyses, linkage disequilibrium (LD)–based SNP pruning was performed with PLINK software, with a cutoff of r2 = 0.8. Of the 775 SNPs that passed quality control, we analyzed 697 maternal and 645 fetal SNPs. We excluded a small number of X chromosome SNPs for fetal data, because the neonates who were included in the study were both male and female. This accounted for most of the difference in the number of SNPs that were tested in mothers and fetuses.

      Haplotype tests of association

      Haplotype analyses were performed on genes with at least 1 significantly associated SNP (P < .01) and at least 2 SNPs in the same gene. Haplotype frequencies and haplotype-based association analyses for the dichotomous spontaneous preterm labor/delivery outcome with 2 and 3 marker sliding windows were calculated with the PLINK software. Only haplotypes that had a frequency of ≥ .05 were analyzed, and only SNPs that had less than 5% missing data were used. The strongest associated haplotype windows are reported (P ≤ .05); only these were analyzed for haplotype-specific effects. We present the calculation of ORs for each haplotype (using the most common haplotype as referent) and the determination of case and control haplotype frequencies. Standard summary statistics for pairwise LD, D', and r2 were calculated with Haploview.
      • Devlin B.
      • Risch N.
      A comparison of linkage disequilibrium measures for fine-scale mapping.
      • Barrett J.C.
      • Fry B.
      • Maller J.
      • Daly M.J.
      Haploview: analysis and visualization of LD and haplotype maps.
      Haplotype blocks were assigned with the use of the D' confidence interval algorithm that was created by Gabriel et al.
      • Gabriel S.B.
      • Schaffner S.F.
      • Nguyen H.
      • et al.
      The structure of haplotype blocks in the human genome.
      D is the standard population genetic measure of LD that calculates the deviation of haplotype frequencies from that expected if there were random combinations of alleles at 2 loci. Because D is allele frequency dependent, D' is often used because it normalizes the LD (to a range of 0–1) based on actual allele frequencies. In contrast, r2 is the standard correlation statistic that is based on the population distribution of 2 SNPs. All 3 of these measures reflect similar patterns of LD.

      Histologic chorioamnionitis analysis

      All statistically significant single locus and haplotype associations were further analyzed for allele and haplotype differences between patients with spontaneous preterm labor and delivery (<34 weeks of gestation) with histologic chorioamnionitis alone or with funisitis and term control subjects (delivered >37 weeks of gestation without histologic chorioamnionitis or funisitis). The purpose of these analyses was to further evaluate whether histologic chorioamnionitis was driving the observed associations.

      Multiple testing corrections

      A false discovery rate correction was performed to adjust for multiple comparisons with the use of a q* of 0.15 in single locus tests of association.
      • Benjamini Y.
      • Drai D.
      • Elmer G.
      • Kafkafi N.
      • Golani I.
      Controlling the false discovery rate in behavior genetics research.
      The q* indicates the expected proportion of results that are identified as interesting that are actually false. This is in contrast to α (typically set to .05), which indicates the probability of obtaining a false-positive result among all tests that are performed. False discovery rate is used to measure global error, that is, the expected number of false rejections of the null hypothesis among the total number of rejections. The critical significance level was calculated by ranking the results by probability values and then multiplying this rank by q* divided by the total number of tests. Although the choice of q* is somewhat arbitrary, a q* of 0.15 was chosen to be permissive enough in our analyses not to run the risk of eliminating potentially interesting findings because of a type II error.

      Multilocus analysis

      Spontaneous preterm labor with intact membranes is a complex phenotype with no clear pattern of inheritance in pedigrees. Therefore, it is reasonable to assume that multiple variants, either alone or interacting, predispose to this phenotype. Because of this complexity, it is important to explore genetic models that do not assume independent single locus effects, because such analyses have the potential to reveal genetic models that are hidden by single locus analyses. Such analyses previously have revealed associations that were undetected by single locus analyses for hypertension
      • Williams S.M.
      • Ritchie M.D.
      • Phillips III, J.A.
      • et al.
      Multilocus analysis of hypertension: a hierarchical approach.
      and associations with PTB.
      • Menon R.
      • Velez D.R.
      • Simhan H.
      • et al.
      Multilocus interactions at maternal tumor necrosis factor-alpha, tumor necrosis factor receptors, interleukin-6 and interleukin-6 receptor genes predict spontaneous preterm labor in European-American women.
      One method that was designed to discover complex models is multifactor dimensionality reduction (MDR). We performed exploratory multilocus analyses using MDR to identify interactions among maternal, fetal, and maternal/fetal SNPs. MDR was described previously by Ritchie et al
      • Ritchie M.D.
      • Hahn L.W.
      • Roodi N.
      • et al.
      Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer.
      (available as open source software at www.epistasis.org). Briefly, MDR is a nonparametric (does not assume any statistical model) and model-free (no assumption mode of genetic inheritance) unique tool for the identification of gene-gene interactions. MDR collapses all of the genetic data into 2 categories (high- and low-risk) by comparing all single locus and all multilocus combinations and then categorizing each genotype into either high-risk or low-risk on the basis of the ratio of cases to control subjects that have that genotype. MDR ultimately selects 1 genetic model, either single or multilocus, that most successfully predicts phenotype or disease status. Analyses were performed separately for maternal and fetal data (tag SNPs only) and combined for available maternal and fetal paired DNA samples (eg, instead of an individual having 751 SNPs [the number of SNPs that completely overlapped maternal and fetal DNAs], this increased the number of SNPs that were analyzed to 1502). Data were analyzed for 2- and 3-way interactions with 10-fold cross-validation and average balanced accuracy as the metrics for evaluation of a model.
      • Velez D.R.
      • White B.C.
      • Motsinger A.A.
      • et al.
      A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction.
      Several filtering steps and parameters were explored and are described in Supplemental Table 2. The MDR algorithm was implemented with the full array of tag SNPs and after filtering with the Tuned ReliefF (TuRF) algorithm approach as described in detail by Moore and White.
      • Moore J.H.
      • White B.C.
      Tuning relief for genome-wide genetic analysis.
      TuRF is a modification of ReliefF. Briefly, ReliefF is a method that estimates the quality of attributes (eg, SNPs) through a nearest neighbor algorithm that selects neighbors from the same and different classes based on the values of the attributes (in this case genotypes).
      • Kira K.
      • Rendell L.A.
      A practical approach to feature selection.
      TuRF is a method that systematically removes attributes (eg, SNPs) that poorly differentiate cases and control subjects.
      • Moore J.H.
      • White B.C.
      Tuning relief for genome-wide genetic analysis.
      ReliefF and similar computational algorithms have been developed, primarily in computer science and data mining fields, to provide a means to screen attributes/variables on a rational basis that relate to quality in terms of the ability to classify an outcome. These algorithms allow the reduction in importance of those attributes that are irrelevant to an outcome and will generate noise to any subsequent analyses. Many of the developed algorithms assume independent effects and therefore are not appropriate when there are interactions among variables that affect outcome/disease. ReliefF does not make this assumption. It is an extension of ReliefF, and we will briefly describe ReliefF to provide a better understanding of the attribute election process. In ReliefF, an instance (in this case an individual, either case or control) is selected randomly and then the 2 nearest neighbors (the nearest case and the nearest control, based on the multilocus genotype data) are selected. Attributes that are shared with those of the same status are increased in value, and those attributes that are shared among individuals of opposite classes are devalued. Unshared values of an attribute in 2 cases are similarly decreased in value. This is repeated a preset number of times. ReliefF has the added feature of choosing just a single individual of the same and a single individual of the opposite status; an arbitrary number of individuals is selected to assess the attributes. In our case, we use a sample of 10 nearest cases and 10 nearest control subjects on the genotype space. TuRF goes a step further; instead of just changing the attributes (eg, SNP) values, it systematically removes attributes (eg, SNPs) that poorly differentiate cases and control subjects. The motivation behind this algorithm is that the ReliefF estimates of the true associating SNPs will improve as the nonassociating SNPs are removed from the dataset. In addition, SNPs were filtered based on the results of the single SNP analyses, and only SNPs that had a marginal probability value of ≤ .1 were included, or only those with a probability value of < .05 were analyzed separately. Permutation testing with 1000 permutations was used to determine statistical significance of all MDR models.
      SUPPLEMENTAL TABLE 2Parameters explored in multifactor dimensionality reduction analyses
      AlgorithmSingle nucleotide polymorphisms includedPopulation
      Balanced accuracyAll tagMaternal
      Tag with P < .05
      Tag with p < .10
      All tagFetal
      Tag with P < .05
      Tag with P < .10
      All tagMaternal-fetal combined
      Tag with P < .05
      Tag with P < .10
      Balanced accuracy with the Tuned ReliefF algorithm with 10 single nucleotide polymorphism filterAll tagMaternal
      Fetal
      Maternal-fetal combined
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      MDR as described is ideal for a balanced data set in which the number of cases and control subjects are the same or close to the same. However, computational methods have been developed because of the initial development of MDR to test for prediction accuracies in an imbalanced data set, such as ours.
      • Velez D.R.
      • White B.C.
      • Motsinger A.A.
      • et al.
      A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction.
      The method, termed balanced accuracy, corrects for imbalanced data by taking an average of the sensitivity and specificity and is defined as the arithmetic mean of sensitivity and specificity. We tested for balanced accuracy in this article.

      Bioinformatics tools

      The SNPper (http://snpper.chip.org) database that uses dbSNP build 125 was used to determine marker positions (base pairs), marker function, and identify amino acid changes.

      Pathway analysis

      As with the multilocus analyses, it is important to provide a more comprehensive assessment of our results in terms of pathway involvement in spontaneous preterm labor and delivery with intact membranes because it is likely that single genes are not adequate by themselves to affect disease risk; however, multiple genes within a single pathway may affect function enough to increase risk. Therefore, as part of a hypothesis-generating exercise, we performed pathway-based analyses using Ingenuity Pathway Analysis (IPA; Ingenuity Systems, Inc, Redwood City, CA).
      • Menon R.
      • Pearce B.
      • Velez D.R.
      • et al.
      Racial disparity in pathophysiologic pathways of preterm birth based on genetic variants.
      • Calvano S.E.
      • Xiao W.
      • Richards D.R.
      • et al.
      A network-based analysis of systemic inflammation in humans.
      • Loza M.J.
      • McCall C.E.
      • Li L.
      • Isaacs W.B.
      • Xu J.
      • Chang B.L.
      Assembly of inflammation-related genes for pathway-focused genetic analysis.
      • Kuijl C.
      • Savage N.D.
      • Marsman M.
      • et al.
      Intracellular bacterial growth is controlled by a kinase network around PKB/AKT1.
      • Winn V.D.
      • Haimov-Kochman R.
      • Paquet A.C.
      • et al.
      Gene expression profiling of the human maternal-fetal interface reveals dramatic changes between mid gestation and term.
      Specifically, IPA was used to examine whether the SNPs found to be associated putatively with spontaneous preterm labor and delivery with intact membranes mapped to different biologic networks and disease functions. The genes with variants that were associated significantly with PTB (P < .05) were entered into the IPA analysis tool. These genes were termed focus genes. The IPA software was used to measure associations of these molecules with other molecules, their network interactions, and biologic functions stored in its knowledge base. The knowledge base encompasses relationships between proteins, genes, cells, tissues, xenobiotics, and diseases. The information is scientist-curated, updated, and integrated from the published literature and other databases such as OMIM, GO, and KEGG. Our focus genes served as seeds for the IPA algorithm, which recognizes functional networks by identifying interconnected molecules, including molecules not among the focus genes from the IPA knowledge base. The software illustrates the networks graphically and calculates a score for each network, which represents the approximate ”fit” between the eligible focus molecules and each network. The network score is based on the hypergeometric distribution and is reported as the –log (Fisher's exact test result).
      We also used IPA to identify functionally related genes that correspond to canonical pathways. We determined enrichment of our focus genes among the >200 well-characterized metabolic and cell-signaling “canonical” pathways curated by IPA scientists from journal articles, text books, and KEGG ligand. The Fisher's exact test was used to calculate a probability value that represented the probability that the association between the genes in our dataset and the canonical pathway can be explained by chance alone.

      Results

      Significant differences between cases and control subjects were identified for gestational age at delivery (P < .0001), birthweight (P < .0001), and Apgar scores at 1 (P < .0001) and 5 minutes (P < .0001; Table 1). We did not observe significant differences between cases and control subjects for body mass index and smoking status, which are 2 variables that previously have been associated with risk for PTB.
      • Goldenberg R.L.
      • Tamura T.
      Prepregnancy weight and pregnancy outcome.
      • Andres R.L.
      • Day M.C.
      Perinatal complications associated with maternal tobacco use.
      • Cnattingius S.
      The epidemiology of smoking during pregnancy: smoking prevalence, maternal characteristics, and pregnancy outcomes.
      • Hendler I.
      • Goldenberg R.L.
      • Mercer B.M.
      • et al.
      The Preterm Prediction study: association between maternal body mass index and spontaneous and indicated preterm birth.
      • Torloni M.R.
      • Betran A.P.
      • Daher S.
      • et al.
      Maternal BMI and preterm birth: a systematic review of the literature with meta-analysis.
      TABLE 1Demographic and clinical characteristics of the study population
      VariableCases (n = 223)Control subjects (n = 599)P value
      Parity, n
      Results are expressed as median (25th-75th percentile).
      1 (0-2)1 (0-1).193
      Maternal age, y
      Results are expressed as median (25th-75th percentile).
      24 (19-32)24 (20-30).984
      Body mass index, kg/m2
      Results are expressed as median (25th-75th percentile).
      23 (21-26)24 (22-26).455
      Smoking, %1314.506
      Gestational age at delivery, wk
      Results are expressed as median (25th-75th percentile).
      34 (30-35)40 (39-41)< .0001
      Birthweight, g
      Results are expressed as median (25th-75th percentile).
      2200 (1680-2600)3440 (3230-3650)< .0001
      Apgar score
      Results are expressed as median (25th-75th percentile).
      1-minute
      Results are expressed as median (25th-75th percentile).
      8 (5-9)9 (9-9)< .0001
      5-minute
      Results are expressed as median (25th-75th percentile).
      9 (8-9)9 (8-9)< .0001
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      a Results are expressed as median (25th-75th percentile).

      Single locus association

      SNPs that are associated with spontaneous preterm labor/delivery with intact membranes in maternal and fetal DNA (P < .01) are presented in Table 2. There were no statistically significant deviations from HWE in control subjects for any of these DNA variants. The most significant association in maternal DNA was observed at a synonymous coding SNP (S101S) in the gene for the tissue inhibitor of metalloproteinase 2 (TIMP2) rs2277698 (OR, 1.98; 95% CI, 1.38–2.83; P = .000197; Table 3). The minor allele frequency for this SNP (A) was 0.13 in cases and 0.07 in control subjects. This SNP was significant after false discovery rate correction for multiple testing.
      TABLE 2Gene summary information strongest associations
      PopulationGene nameGene coders no.ChromosomePosition (bp)Function
      MaternalInterleukin 6 receptor isoform 1IL6Rrs81922821152668303Coding exon (A/A 31)
      Alpha 3 type IV collagen isoform 1COL4A3rs18824352227810996Intron
      LactotransferrinLTFrs2269435346462007Intron
      Fibroblast growth factor 1 (acidic) isoform 1FGF1rs340035141955251Intron
      Guanine nucleotide-binding protein, beta-3GNB3rs5440126819160Promoter
      Insulin-like growth factor 1 (somatomedin C)IGF1rs574261212101398994Promoter
      Tissue inhibitor of metalloproteinase 2TIMP2rs22776981774378612Coding exon (S/S 101)
      FetalCoagulation factor III precursorF3rs610277194771147Intron
      Natriuretic peptide receptor A/guanylate cyclaseNPR1rs38910751151924811Intron
      Interleukin 6 receptor isoform 1 precursorIL6Rrs81922821152668303Coding exon (A/A 31)
      Tenascin R (restrictin, janusin)TNRrs22283591173591274Coding exon (D/D 1079)
      Interleukin 1, beta proproteinIL1Brs11436432113304773Intron
      Fibronectin 1 isoform 3 preproproteinFN1rs23045732215951895Intron
      Interleukin 2 precursorIL2rs20697724123592583Intron
      Fibroblast growth factor 1 (acidic) isoform 1FGF1rs340035141955251Intron
      Interferon gamma receptor 1IFNGR1rs18874156137560931Coding exon (L/P 467)
      Insulin-like growth factor 2IGF2rs3213225112113112Intron
      Alpha 1 type IV collagen preproproteinCOL4A1rs1697549213109631703Coding exon (P/P 710)
      Tissue inhibitor of metalloproteinase 2TIMP2rs22776981774378612Coding exon (S/S 101)
      P < .01.
      bp, base pair.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      TABLE 3Single nucleotide polymorphisms associated significantly with spontaneous preterm labor/delivery in single locus tests of association
      PopulationGene coders#Minor alleleMinor allele frequencyOdds ratio
      For the additive genotypic model;
      95% CIP value
      CasesControl subjectsLowerUpper
      Maternal (cases, 223; control subjects, 599)IL6Rrs8192282A0.130.081.701.192.41.003
      COL4A3rs1882435A0.330.261.401.101.79.007
      LTFrs2269435C0.380.301.391.101.76.007
      FGF1rs34003G0.320.410.690.540.87.002
      GNB3rs5440G0.360.430.730.580.92.007
      IGF1rs5742612C0.060.100.560.360.87.009
      TIMP2rs2277698A0.130.071.981.382.83.000197
      Significant after false discovery rate correction.
      Fetal (cases, 179; control subjects, 628)F3rs610277C0.100.012.471.314.67.005
      NPR1rs3891075T0.090.072.041.273.30.003
      IL6Rrs8192282A0.130.102.071.423.02.000148
      Significant after false discovery rate correction.
      TNRrs2228359T0.410.301.471.141.91.004
      IL1Brs1143643A0.200.231.551.182.03.002
      FN1rs2304573C0.620.490.700.540.91.008
      IL2rs2069772G0.000.130.530.350.80.003
      FGF1rs34003G0.300.420.670.510.87.003
      IFNGR1rs1887415C0.040.070.500.320.79.003
      IGF2rs3213225C0.090.360.670.510.89.005
      COL4A1rs16975492A0.410.270.670.510.89.006
      TIMP2rs2277698A0.130.141.821.272.62.001
      None of these markers had statistically significant deviations from Hardy-Weinberg equilibrium in cases or control subjects.
      P < .01.
      CI, confidence interval.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      a For the additive genotypic model;
      b Significant after false discovery rate correction.
      The most significant association that was observed in fetal DNA was also a synonymous SNP (A31A) in the interleukin-6 receptor 1 (IL6R) rs8192282 (OR, 2.07; 95% CI 1.42–3.02; P = .000148; Table 3). The minor allele frequency for this SNP (A) was 0.13 for cases and 0.10 for control subjects. This SNP also remained statistically significant after false discovery rate correction.
      Additional SNPs that were associated with spontaneous preterm labor/delivery with intact membranes at a probability value of < .05 are presented in Table 4. Although we have not emphasized these findings in the present report, in some instances these SNPs represent associations in genes previously reported that may lend support to previous findings, or may be additional SNPs in genes that were reported with a probability value of < .01. Such findings strengthen the likelihood of an association because it will be based on multiple SNPs for the same gene (eg, collagen type IV, lactotransferrin [LTF], and TIMP2 in mothers and insulin-like growth factor 2 [IGF2], interleukin-2 [IL2], TIMP2, collagen type IV, and TNR in fetuses).
      TABLE 4Single SNP associations (.01 < P < .05)
      GeneSNPMinor alleleOR95% CIP value
      LowerUpper
      Maternal DNA
      AGTR1rs5183G2.751.226.22.015
      HSPG2rs2229489A1.951.143.34.016
      SELErs5356C1.351.061.72.016
      MMP16rs3739382T2.561.195.54.017
      AGTrs4762T1.431.061.93.019
      COL4A2rs2296852A0.570.350.91.020
      LTFrs1475967T0.760.610.96.020
      COL4A4rs3752896G1.311.041.64.021
      IL18rs549908C1.331.041.69.021
      MMP10rs486055A1.761.092.87.022
      SERPINE1GNSC_629203538T2.401.135.08.023
      THPOrs2280740A1.491.052.11.024
      LTFrs2239692G1.411.051.89.024
      VEGFCrs7664413A0.750.580.97.029
      F3rs610277C2.131.074.24.031
      TIMP2rs55743137C1.361.021.80.034
      CRHR2rs8192498A2.511.056.00.038
      IL12BGNSC_632292870G2.661.046.80.041
      SELErs1076637A1.281.011.62.043
      RENrs3730103G1.661.022.72.043
      IL10rs1800872A1.271.011.60.043
      COL5A2rs6750027A1.321.011.74.043
      MMP10rs17860949T1.451.012.09.043
      HTR2Ars6314T0.570.330.99.046
      TBXAS1rs3735355A0.480.230.99.047
      TLR2rs5743700T0.380.150.99.047
      IL1Brs1143634T0.720.521.00.047
      THBS4rs2241826G1.321.001.74.048
      LTFGNSC_617330042A1.391.001.93.048
      OXTRGNSC_631469608A1.581.002.47.049
      Fetal DNA
      IL10RArs17121493G1.821.162.85.010
      TIMP2rs55743137C1.491.102.03.011
      TLR1rs5743553A2.731.255.95.012
      COL4A3rs1882435A1.391.071.81.013
      COL4A4rs3752896A0.740.580.95.016
      CETPrs891144T1.601.082.37.018
      COL4A2rs7338575C1.371.061.78.018
      SERPINE1rs6092A1.631.082.46.020
      IL4Rrs1029489A0.750.590.96.020
      AGTR1rs5183G2.561.155.67.021
      NPPArs5068C0.260.080.83.023
      HSPG2GNSC_634098268T1.411.051.89.023
      ELNrs2301995A1.441.051.97.023
      COL4A2rs12873113T1.451.052.01.026
      IGF2Rrs894817A1.321.031.68.027
      IRS1rs1801278A1.761.062.95.031
      COL4A3rs56326869C0.110.020.83.032
      COL4A4rs3752895C0.770.610.98.034
      IL9RGNSC_14430798C0.440.210.95.036
      LPArs4708871G2.201.054.59.037
      RENrs3730103G1.751.032.98.038
      ELNrs17855988C1.631.032.59.038
      IL2rs2069771T2.661.056.71.039
      TIMP1rs11551797T0.450.210.96.039
      COL4A5rs28465565C0.460.220.97.040
      IL3RAGNSC_649033887A0.370.140.96.041
      SERPINC1rs677C1.601.022.52.042
      TNRrs1385540T1.371.011.86.043
      IL1R1rs3917318G1.291.011.65.043
      FIGFGNSC_634828146C0.470.230.98.045
      IGF2rs2230949T1.571.012.43.045
      F7rs6046A1.381.001.90.047
      COL4A2rs391859A0.720.521.00.048
      COL4A6GNSC_634841755A0.470.221.00.049
      COL4A4rs1800516C0.300.091.00.050
      CI, confidence interval; OR, odds ratio, SNP, single nucleotide polymorphism.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.

      Haplotype association

      Haplotype analyses of genes with at least 1 significant SNP (P < .05) and 2 SNPs in the gene identified 4 genes in maternal samples (alpha 3 type IV collagen isoform 1 [COL4A3], IL6R, LTF, and fibroblast growth factor 1 [acidic] isoform 1 [FGF1]) and 3 genes in fetal samples (IGF2, IL2, and alpha 1 type IV collagen preprotein [COL4A1]) that were associated with the risk of spontaneous preterm labor/delivery with intact membranes (Table 5;Figure 2).
      TABLE 5Most significantly associating haplotypes
      PopulationGeneMarkersHaplotypeHaplotype frequencyOdds ratio95% CIP value
      CasesControl subjectsLowerUpper
      MaternalCOL4A3rs1882435-rs10178458-rs55997063Global P value.007
      CTT0.080.110.800.531.21.279
      ACT0.310.231.481.141.90.002
      CCT (referent)0.600.66
      IL6Rrs8192282-rs7521458Global P value.043
      AT0.120.081.511.042.20.023
      GT0.220.250.880.671.15.339
      GC (referent)0.660.66
      LTFrs2269435-rs2239692Global P value.013
      CG0.180.131.531.122.09.005
      CA0.190.161.320.981.78.058
      TA (referent)0.630.70
      FGF1rs34003-rs17217240-rs9324894Global P value.022
      TGT0.070.070.870.541.36.526
      GGC0.290.370.690.530.88.002
      TGC (referent)0.640.56
      FetalIGF2rs3213225-rs3213223Global P value.004
      TT0.230.072.781.963.94< .0001
      CC0.100.360.240.160.35< .0001
      TC (referent)0.670.57
      IL2rs2069772-rs2069771-rs2069762Global P value.005
      ACG0.190.410.260.190.35< .0001
      GCT0.000.14
      ACT (referent)0.810.45
      COL4A1rs685884-GNSC_633869360Global P value.012
      TA0.090.051.120.691.80.608
      CG0.190.490.240.180.33< .0001
      TG (referent)0.730.46
      CI, confidence interval.
      Global, P < .05.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      Figure thumbnail gr2
      FIGURE 2Patterns of linkage disequilibrium for genes associated in haplotype analyses of maternal samples
      Case and control patterns of linkage disequilibrium are shown separately. Haploview
      • Barrett J.C.
      • Fry B.
      • Maller J.
      • Daly M.J.
      Haploview: analysis and visualization of LD and haplotype maps.
      plots are presented with the single nucleotide polymorphisms and relative locations within the gene across the top of each panel. The bottom of each panel shows the pair-wise linkage disequilibrium values of all single nucleotide polymorphisms as measured by D' (a standardized measure of linkage disequilibrium); D' values are given in each diamond. D' between each pairwise combination of single nucleotide polymorphisms is given in each diamond on a scale of 0-100. A value of 100 represents maximum possible linkage disequilibrium. Specifically, in panel A, the D' between rs1882435 (687) and rs35467545 (693) can be seen by tracing down from each single nucleotide polymorphism to the diamond where the lines intersect. In this case, D' is 52. Solid red diamonds represent a D' of 100; blue diamonds are values with low logarithm of the odds scores (<2) and hence unreliable values. White diamonds represent evidence of strong recombination and hence little linkage disequilibrium. A, COL4A3 cases; B, COL4A3 control subjects; C, IL6R cases; D, IL6R control subjects; E, FGF1 cases; F, FGF1 control subjects; G, LTF cases; H, LTF control subjects.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      The most significant haplotype association for maternal DNA (P < .01) was for COL4A3 at rs1882435-rs10178458-rs55997063 (global P = .007; Table 5). This haplotype included COL4A3 SNP rs1882435, an SNP that is associated independently with spontaneous preterm labor/delivery (P = .007; Table 5), where the A allele was the risk allele. On examination of the individual haplotypes, it was clear that all statistically significant haplotypes for rs1882435-rs10178458-rs55997063 contained the rs1882435 risk allele. Examination of the LD plot for COL4A3 demonstrated that rs10178458 is in moderate LD with rs1882432, but the pattern of LD appears different between cases and control subjects (Figure 2, A and B).
      The most significant associations for fetal DNA (P < .01) were for IGF2 and IL2 (Table 5; Figure 3) . The haplotypes for IGF2 were at rs3213225-rs3213223 (global P = .004) and for IL2 at rs2069772-rs2069771-rs2069762 (global P = .005; Table 5). Both of these haplotypes contained an SNP that had a marginal effect; however, the IGF2 rs3213225-rs3213223 had a global haplotype probability value that was slightly more significant than the individual main effect (IGF2 rs3213225; P = .005; Table 5), and the associations at individual haplotypes suggest that the risk allele for rs3213225 is not driving the association at this haplotype. Further examination of the LD plot suggests that there is strong LD (as measured by D') between rs3213225-and rs3213223 in control subjects but not cases (Figure 3, A and B).
      Figure thumbnail gr3
      FIGURE 3Patterns of linkage disequilibrium for genes associated in haplotype analyses of fetal samples
      Case and control patterns of linkage disequilibrium are shown separately. Haploview
      • Barrett J.C.
      • Fry B.
      • Maller J.
      • Daly M.J.
      Haploview: analysis and visualization of LD and haplotype maps.
      plots are presented with the single nucleotide polymorphisms and relative locations within the gene across the top of each panel. The bottom of each panel shows the pair-wise linkage disequilibrium values of all single nucleotide polymorphisms as measured by D' (a standardized measure of linkage disequilibrium on a scale of 0-100); D' values are given in each diamond. A value of 100 represents maximum possible linkage disequilibrium. Solid red diamonds represent a D' of 100; blue diamonds are values with low logarithm of the odds scores (<2) and hence unreliable values. White diamonds represent evidence of strong recombination and hence little LD. A, IGF2 cases; B, IGF2 control subjects; C, IL2 cases; D, IL2 control subjects; E, COL4A1 cases; F, COL4A1 control subjects.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.

      Histologic chorioamnionitis

      Subanalyses of all statistically significant single locus and haplotype associations for differences between cases with histologic chorioamnionitis and control subjects (TABLE 6, TABLE 7) demonstrated a decrease in the OR for the maternal sample TIMP2 rs2277698, with the OR dropping from 1.98 (Table 3) to 1.49 and a loss of statistical significance (Table 6). However, there was an increase in the OR for fetal sample IL6R rs8192282 association (OR changing from 2.07 to 2.94), and this SNP remained statistically significant (P = .045). No significant global haplotype probability values (Table 7) were observed for any of the maternal sample haplotypes that demonstrated significant association in Table 5. There were not enough fetal cases (n = 14) with histologic chorioamnionitis to perform haplotype analyses of these samples. Overall, we caution that the interpretation of these findings should be tempered by the small samples sizes.
      TABLE 6Analysis of histologic chorioamnionitis for significantly associated single nucleotide polymorphisms
      PopulationGene coders#Odds ratio
      For the additive genotypic model.
      95% CIP value
      LowerUpper
      Maternal (cases, 30; control subjects, 464)IL6Rrs81922821.820.873.80.110
      COL4A3rs18824351.030.571.89.912
      LTFrs22694350.950.541.67.845
      FGF1rs340030.590.331.05.074
      GNB3rs54400.430.240.79.006
      IGF1rs57426120.500.151.65.256
      TIMP2rs22776981.490.623.61.377
      Fetal (cases, 14; control subjects, 465)F3rs6102773.780.7918.01.096
      NPR1rs38910751.680.367.76.505
      IL6Rrs81922822.941.028.43.045
      TNRrs22283591.010.422.42.979
      IL1Brs11436431.700.743.92.212
      FN1rs23045731.230.542.82.626
      IL2rs20697720.220.031.59.133
      FGF1rs340030.430.161.18.101
      IFNGR1rs18874150.600.142.58.495
      IGF2rs32132250.730.301.79.496
      COL4A1rs169754920.620.241.56.307
      TIMP2rs22776982.140.726.34.169
      CI, confidence interval.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      a For the additive genotypic model.
      TABLE 7Analysis of histologic chorioamnionitis for significantly associated haplotypes: maternal population
      GeneMarkersHaplotypeHaplotype frequencyOdds ratio95% CIP value
      CasesControl subjectsLowerUpper
      COL4A3rs1882435-rs10178458- rs55997063Global P value.914
      CTT0.090.110.770.232.00.581
      ACT0.230.230.980.481.88.953
      CCT (referent)0.690.66
      IL6Rrs8192282-rs7521458Global P value.229
      AT0.150.091.970.804.37.079
      GT0.270.251.190.602.25.584
      GC (referent)0.580.66
      LTFrs2269435-rs2239692Global P value.403
      CG0.170.121.350.592.84.405
      CA0.120.170.680.251.57.357
      TA (referent)0.720.71
      FGF1rs34003-rs17217240-rs9324894Global P value.103
      GGT0.010.060.210.011.32.098
      TGT0.040.060.620.122.05.435
      GGC0.260.350.560.281.06.060
      TGC (referent)0.690.53
      There were only 14 cases available to do haplotype analyses for the subanalysis of histologic chorioamnionitis, which were not enough cases to do haplotype analyses with the same criteria that were used for haplotype analyses in Table 3.
      CI, confidence interval.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.

      MDR analysis

      Exploratory MDR analyses were performed by different filtering approaches. The only statistically significant associations were in the analyses in which maternal and fetal genotypes were combined after filtering for SNPs with statistically significant main effects (both P < .05 and < .10; Table 8). The only model with a probability value of < .05 was found in analyses of SNPs that were filtered for main effects with a probability of < .10 (Table 8; Figure 4). This model included rs3752896 maternal, rs34003_2 fetal, and rs598893_2 fetal and had a testing balanced accuracy of 0.62 (P = .043), but a cross validation consistency of only 6 of 10, which suggests that this model is unlikely to generalize. The maternal SNP, rs3752896, is an intronic SNP in collagen type IV alpha 4 (COL4A4), and the 2 fetal SNPs are both intronic and include an SNP (rs34003) in FGF1 and an SNP (rs598893) in COL4A1. Only fetal SNP, rs34003, was among the most associated SNPs in the single locus analysis (Table 3). Two other models are worth mentioning: (1) a maternal model that used TuRF that included rs2069762-rs5369-GNSC_30713312, SNPs in IL2, endothelin1 (EDN1), and IL6, respectively (testing balanced accuracy, 0.61; P = .057; cross validation consistency [CVC] = 9/10; Table 8) and (2) a fetal model after TuRF filtering that included rs2304573-rs2621208-rs2252070, SNPs in fibronectin 1 (FN1), COL1A2, and MMP13, respectively (testing balanced accuracy, 0.62; P = .063; CVC = 8/10; Table 8).
      TABLE 8Summary of multifactor dimensionality reduction analyses
      AlgorithmModelTesting balanced accuracyCross validation consistencyP value
      Preterm birth: maternal
       Balanced accuracy with all tag single nucleotide polymorphismsrs20697620.556/10.377
      rs20697620.596/10.132
      rs17689966
      rs39173180.552/10.397
      rs2069762
      rs7338575
       Balanced accuracy with the Tuned ReliefF algorithm: 10 single nucleotide polymorphismsrs20697620.5510/10.321
      GNSC_6351487130.555/10.330
      rs2069762
      rs2069762 rs53690.619/10.057
      rs1800797
       Balanced accuracy with tag single nucleotide polymorphisms with P < .05rs18824350.569/10.331
      rs2269435 rs54400.563/10.306
      rs18824350.594/10.139
      rs34003
      rs10459953
       Balanced accuracy with tag single nucleotide polymorphism with P < .10rs18824350.568/10.356
      rs2269435 rs54400.532/10.579
      rs18824350.552/10.406
      rs34003
      Rs10459953
      Preterm birth: fetal
       Balanced accuracy with all tag single nucleotide polymorphismsrs20697620.544/10.581
      rs37528960.595/10.204
      rs2069762
      rs12502150.562/10.371
      rs3752896
      rs2069762
       Balanced accuracy with the Tuned ReliefF algorithm: 10 single nucleotide polymorphismsrs20697620.558/10.432
      rs23045730.6110/10.085
      rs2621208
      rs23045730.628/10.063
      rs2621208
      rs2252070
       Balanced accuracy with tag single nucleotide polymorphisms with P < .05rs20697720.568/10.292
      rs20697720.595/10.174
      rs16975492
      rs34003 rs3212250.533/10.634
      rs16975492
       Balanced accuracy with tag single nucleotide polymorphisms with P < .10rs20697720.568/10.292
      rs20697720.544/10.554
      rs1800692
      rs20697720.554/10.414
      rs2146323
      rs3213225
      Preterm birth: maternal-fetal combined
       Balanced accuracy with all tag single nucleotide polymorphismsrs20697620.556/10.461
      rs2069762_20.585/10.254
      rs2274849
       Balanced accuracy with the Tuned ReliefF algorithm: 10 single nucleotide polymorphismsrs2069762_20.538/10.614
      rs2069762_20.629/10.084
      rs16145
      rs2069762_20.514/10.943
      rs16145
      rs2243290
       Balanced accuracy with tag single nucleotide polymorphisms with P < .05rs8192282_20.617/10.050
      Statistically significant interaction (permutation, P < .05).
      rs53560.582/10.160
      rs1882435_2
      rs1882435_20.541/10.456
      rs16975492_2
      rs2277698
       Balanced accuracy with tag single nucleotide polymorphisms with P < .10rs8192282_20.617/10.050
      Statistically significant interaction (permutation, P < .05).
      rs1143643_20.542/10.522
      rs7338575_2
      rs37528960.626/10.043
      Statistically significant interaction (permutation, P < .05).
      rs34003_2
      rs598893_2
      Combined analysis consisted of matching fetal to maternal individuals and adding the single nucleotide polymorphisms to the analysis (eg, instead of an individual having 751 single nucleotide polymorphisms, this would increase the amount to 1449). Any results with a “_2” indicates that the genotypes were fetal. Any maternal or fetal genotypes without matches were removed from the combined analysis.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      a Statistically significant interaction (permutation, P < .05).
      Figure thumbnail gr4
      FIGURE 4Multifactor dimensionality reduction model for a 3-way interaction
      MDR model that involved maternal single nucleotide polymorphism rs3752896 (COL4A4) and fetal single nucleotide polymorphisms rs34003_2 (FGF1) and rs598893_2 (COL4A1). Each panel represents a 3 locus genotype; the genotype for each SNP is labeled on the figure. Each large square (3 × 3 box) represents a different genotype for rs598893_2 (GG on left, AG in the middle, and AA on the right). Within each square, each row of cells delineates rs34003_2 genotypes (top TT, middle GT and bottom GG) and each column the rs3752896 genotypes. Therefore, each small cell describes a single and unique 3 locus genotype. Within each cell are 2 bars that represent the number of cases with this genotype (left hand bar) and number of controls (right hand bar). Each multilocus cell is denoted as “high risk” (dark gray) or “low risk” (light gray) for spontaneous preterm labor/delivery with intact membranes. Risk status is determined by the ratio of cases to controls adjusted by the number of cases and controls studied. The testing average balanced accuracy is 62% (P = .043) with a cross-validation consistency of 6 out of 10.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.

      Pathway analysis

      In mothers, the IPA network algorithm discovered that the focus molecules were significantly interconnected in 4 networks, scoring 12 to 20 (P = 10−12 to P = 10−20; Table 9). Using the “overlapping network” feature of IPA, we found that these networks were joined together by a few molecules, namely TIMP2, and several network partners that were supplied by the IPA knowledge base (eg, MMPs and ACAN, which is involved in cell adhesion and physiologic functions that are associated with extracellular matrix). An example of the top scoring network is shown in Figure 5. Using the fetal genes as input, the IPA network algorithm discovered that fetal focus genes are also highly interconnected. It modeled these into 3 networks, scoring 7 to 35 (Table 10). In contrast to the maternal model, these networks did not have overlapping molecules joining them, although TIMP2 did play a role in the top-ranked network along with several inflammatory genes (including TLR) and coagulation factors (Figure 6).
      TABLE 9Ingenuity Pathway Analysis networks of maternal genes
      NetworkMolecules
      Focus molecules are underlined.
      Calculated scoreFocus moleculesTop functions of network
      1AGT,AGTR1, Akt, COL4A2, Collagen(s), Creb, Cyclin A, Cyclin E, ERK, ERK1/2, FAK, FLF1, G-protein beta, GNB3,IGF1,IL6R, Insulin, Laminin, Mapk, Mek, Mlc, OXTR, p70 S6k, PDGF BB, PI3K, Pkc(s), PLC, Ras, Ras homolog, Rsk, Shc, STAT, THPO,TIMP2, Vegf2010Cardiovascular system development and function, tissue morphology, cellular growth and proliferation
      2Angiotensin II receptor type 1, C8, Calcineurin protein(s), Cyclooxygenase, F3, Fibrinogen, Ifn gamma, Ige, IgG, Ikb, IKK (complex), IL1, IL10,IL18, IL12 (complex), Il12 receptor,IL12B, Interferon alpha, LDL, MHC Class II, Mmp, MMP16, Nfat (family), NFkB (complex), NfkB-RelA, Nos, P38 MAPK, SELE,SERPINE1, Sod, STAT5a/b, Tgf beta, Tlr, TLR2, VEGFC189Cell-mediated immune response, cellular movement, hematological system development and function
      3ACAN, acetaldehyde, ADAMTS1, Ap1, Calmodulin, Caspase, COL4A3,COL4A4 (includes EG:1286), FGFR1, FSH, Histone h3, Hsp70, HTR2A, IL17A (includes EG:3605), IL1B, ITGA3, Jnk, LRPAP1, LTF, MIF, MMP3, MMP7, MMP13, platelet activating factor, PTH, RAPGEF1, REN, SNCG, THBS4, Timp, TIMP2, Tnf receptor, Trypsin, xanthine, XDH168Connective tissue disorders, genetic disorder, cellular movement
      4ACAN, ADAM17, AFP, alcohol, CCL7, COL5A2, CRHR2, CRK, CXCL12, EGFR, FCER2, Fgfr, FGFR1, HMGA2, HSPG2 (includes EG:3339), IL6, IL17A (includes EG:3605), ITGA5, Mmp, MMP3, MMP7, MMP10, MMP13, MMP17, NQO1, platelet activating factor, PLC gamma, PTPN6, SAA2, TBXAS1, testosterone, Timp, TIMP2, TIMP4, TNF126Cellular movement, connective tissue disorders, genetic disorder
      Ingenuity Systems, Inc, Redwood City, CA.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      a Focus molecules are underlined.
      Figure thumbnail gr5
      FIGURE 5Connection map for the first ranked network
      Reproduced, with permission, from Ingenuity Pathway Analysis (Ingenuity Systems, Inc, Redwood City, CA) from maternal focus gene input.
      The biomarkers that passed the < .05 significance threshold (focus molecules, depicted in pink) were entered in to the Ingenuity Pathway Analysis software for an unsupervised functional analysis to discern regulatory networks that involved these molecules. The asterisk indicates that there was >1 single nucleotide polymorphism probe for the gene that was tested and that the most significant value was placed into the analysis. Solid lines show direct interaction (binding/physical contact); dashed lines show indirect interaction that is supported by the literature but possibly involving ≥1 intermediate molecules that have not been investigated definitively. Molecular interactions that involved only binding are connected with a line without an arrowhead because directionality cannot be inferred.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      TABLE 10Ingenuity Pathway Analysis networks of fetal genes
      NetworkMolecules
      Focus molecules are underlined.
      Calculated scoreFocus moleculesTop functions of network
      1Angiotensin II receptor type 1, CETP, Collagen(s), F3, F7, Fibrin, Fibrinogen, FN1, HDL, HSPG2 (includes EG:3339), Ifn gamma, IFNGR1, Ige, IGF2, IgG, IL1, IL10RA, IL12 (complex), IL1R1, IL4R, Interferon alpha, Laminin, LDL, LPA, Mmp, NFkB (complex), P38 MAPK, p70 S6k, [email protected], SERPINC1,SERPINE1, Tgf beta, TIMP2, Tlr, TLR13515Cardiovascular disease, hematological disease, infectious disease
      2AGTR1, Akt, Ap1, COL4A1,COL4A2,COL4A3, Creb, Cyclin A, Cyclin E, ERK, ERK1/2, FAK, FGF1,IGF2R, IL2,IL6R, Insulin, IRS1, MAP2K1/2, Mapk, Mek, MHC Class II, NPPA,NPR1, PDGF BB, PI3K, Pkc(s), PLC, Ras, REN, Shc, Sos, STAT, TCR, Vegf2712Cardiovascular disease, cardiovascular system development and function, embryonic development
      3ADAM8, BDNF, C11ORF82, CARD18, CHAT, Ck2, COL4A4 (includes EG:1286), CXCL6, ELN, FSH, GBP6, GNL1, H2-Q4, Histone h3, IL1/IL6/TNF, IL17B, IL17C, IL1B, Jnk, MHC CLASS I D2D ANTIGEN, MIF, PENK, PLD3, Rac, SAA2, SCUBE1, SCUBE2, SLC14A1, SLC5A2, SLC5A4B, SLFN12L, TMEM176B, TNF, TNR, TREM374Cancer, cell cycle, cell-to-cell signaling and interaction
      Ingenuity Systems, Inc, Redwood City, CA.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      a Focus molecules are underlined.
      Figure thumbnail gr6
      FIGURE 6Connection map for the first ranked network
      Reproduced, with permission, from Ingenuity Pathway Analysis (Ingenuity Systems, Inc, Redwood City, CA) from maternal focus gene input.
      The biomarkers passing the < .05 significance threshold (focus molecules, depicted in pink) were entered in to the IPA software for an unsupervised functional analysis to discern regulatory networks that involved these molecules. The asterisk indicates that there was >1 single nucleotide polymorphism probe for the gene that was tested and that the most significant value was placed into the analysis. Solid lines show direct interaction (binding/physical contact); dashed lines show indirect interaction that is supported by the literature but possibly involving ≥1 intermediate molecules that have not been investigated definitively. Molecular interactions that involved only binding are connected with a line without an arrowhead because directionality cannot be inferred. The symbol, [email protected] indicates serum amyloid, which includes SAA1, SAA2, SAA3P, and SAA4.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      Our focus genes were identified by IPA as part of several well-established canonical signaling pathways. In mothers, the IPA algorithm identified the “hepatic fibrosis/hepatic stellate cell activation” as the best scoring of the canonical pathways that involved the “focus genes” (P = 4.9 × 10−12). This pathway was also the best scoring of the canonical pathways in the fetal genes (P = 9.1 × 10−14). The coagulation system was the second ranked canonical pathway for the fetal genes (P = 1.0 × 10−6).

      Comment

      We report the results of a large, carefully phenotyped genetic association study of women with preterm labor and delivery with intact membranes and their offspring in a single Hispanic population. This study identified maternal and fetal DNA variants that predispose to preterm labor with intact membranes leading to preterm delivery. The main observations were (1) an SNP in TIMP2 in mothers was significantly associated with the phenotype, (2) an SNP in IL6R in fetuses increased the risk for preterm labor/delivery, (3) haplotypes for COL4A3 in the mother and IGF2 and IL2 in the fetus were associated with preterm labor/delivery with intact membranes, (4) pathway analysis suggested that maternal and fetal genes that are involved in the control of inflammation and extracellular matrix metabolism are involved in the biologic processes that predispose to this pregnancy outcome, and (5) importantly, TIMP2 consistently was found in the different networks (maternal and fetal) that are associated with preterm labor/delivery with intact membranes. Collectively, these findings support the concept that there is a genetic component in the risk of spontaneous preterm labor/delivery with intact membranes in this population.
      The observed association between TIMP2 and spontaneous preterm labor with intact membranes is novel and implicates extracellular matrix metabolism as an important factor that predisposes to preterm parturition. TIMP-2 is expressed in the amnion
      • Rowe T.F.
      • King L.A.
      • MacDonald P.C.
      • Casey M.L.
      Tissue inhibitor of metalloproteinase-1 and tissue inhibitor of metalloproteinase-2 expression in human amnion mesenchymal and epithelial cells.
      and plays an important role in the regulation of the activity of matrix-degrading enzymes. At low concentrations, TIMP-2 can enhance activation of MMP-2; at high concentrations, it inhibits the activity of MMP-2.
      • Caterina J.J.
      • Yamada S.
      • Caterina N.C.
      • et al.
      Inactivating mutation of the mouse tissue inhibitor of metalloproteinases-2(Timp-2) gene alters proMMP-2 activation.
      • Worley J.R.
      • Thompkins P.B.
      • Lee M.H.
      • et al.
      Sequence motifs of tissue inhibitor of metalloproteinases 2 (TIMP-2) determining progelatinase A (proMMP-2) binding and activation by membrane-type metalloproteinase 1 (MT1-MMP).
      Similarly, higher concentrations of TIMP-2 inhibit MMP-9 (gelatinase B) activity. MMP-2 is a constitutive enzyme; MMP-9 is inducible in response to infection.
      • Fortunato S.J.
      • Menon R.
      • Bryant C.
      • Lombardi S.J.
      Programmed cell death (apoptosis) as a possible pathway to metalloproteinase activation and fetal membrane degradation in premature rupture of membranes.
      Both enzymes have been found in amniotic fluid,
      • Athayde N.
      • Romero R.
      • Gomez R.
      • et al.
      Matrix metalloproteinases-9 in preterm and term human parturition.
      • Riley S.C.
      • Leask R.
      • Chard T.
      • Wathen N.C.
      • Calder A.A.
      • Howe D.C.
      Secretion of matrix metalloproteinase-2, matrix metalloproteinase-9 and tissue inhibitor of metalloproteinases into the intrauterine compartments during early pregnancy.
      • Maymon E.
      • Romero R.
      • Pacora P.
      • et al.
      Evidence of in vivo differential bioavailability of the active forms of matrix metalloproteinases 9 and 2 in parturition, spontaneous rupture of membranes, and intra-amniotic infection.
      • Maymon E.
      • Romero R.
      • Pacora P.
      • et al.
      A role for the 72 kDa gelatinase (MMP-2) and its inhibitor (TIMP-2) in human parturition, premature rupture of membranes and intraamniotic infection.
      • Lavee M.
      • Goldman S.
      • Niel-Spiegel E.
      • Shalev E.
      Matrix metalloproteinase-2 is elevated in midtrimester amniotic fluid prior to the development of preeclampsia.
      and the activity and concentration of MMP-9 is increased in the amniotic fluid of women with preterm labor and intact membranes and in women with pPROM.
      • Athayde N.
      • Romero R.
      • Gomez R.
      • et al.
      Matrix metalloproteinases-9 in preterm and term human parturition.
      • Maymon E.
      • Romero R.
      • Pacora P.
      • et al.
      Evidence of in vivo differential bioavailability of the active forms of matrix metalloproteinases 9 and 2 in parturition, spontaneous rupture of membranes, and intra-amniotic infection.
      We have previously reported that amniotic fluid TIMP-2 concentrations are low in women with spontaneous labor (term and preterm) with intact or ruptured membranes, regardless of the microbial status of the amniotic cavity.
      • Maymon E.
      • Romero R.
      • Pacora P.
      • et al.
      A role for the 72 kDa gelatinase (MMP-2) and its inhibitor (TIMP-2) in human parturition, premature rupture of membranes and intraamniotic infection.
      A decrease in TIMP-2 is thought to favor the activity of MMPs, promoting extracellular matrix degradation associated with labor. In addition, TIMP-2 has been implicated in the metabolism of collagen IV, which is a component of the basement membrane region of the amnion/chorion and uterine cervix.
      • Frappart L.
      • Berger G.
      • Grimaud J.A.
      • et al.
      Basement membrane of the uterine cervix: immunofluorescence characteristics of the collagen component in normal or atypical epithelium and invasive carcinoma.
      • Stewart C.J.
      • McNicol A.M.
      Distribution of type IV collagen immunoreactivity to assess questionable early stromal invasion.
      • Miosge N.
      The ultrastructural composition of basement membranes in vivo.
      Moreover, TIMP-2 has been found to inhibit angiogenesis through mechanisms that are independent of MMPs.
      • Seo D.W.
      • Li H.
      • Guedez L.
      • et al.
      TIMP-2 mediated inhibition of angiogenesis: an MMP-independent mechanism.
      We recently reported that a subset of women who experience preterm labor with intact membranes have an increased plasma concentration of antiangiogenic factors before the development of this complication.
      • Chaiworapongsa T.
      • Romero R.
      • Tarca A.
      • et al.
      A subset of patients destined to develop spontaneous preterm labor has an abnormal angiogenic/anti-angiogenic profile in maternal plasma: evidence in support of pathophysiologic heterogeneity of preterm labor derived from a longitudinal study.
      In a parallel study, we found a significant association between the same TIMP2 SNP and pPROM. Collectively, this evidence provides biologic support for the association of a TIMP2 SNP with preterm labor/delivery with intact membranes.
      This is the first demonstration of an association between IL6R and spontaneous preterm labor with intact membranes in Hispanic women. This observation is consistent with previous reports of IL6R associations with spontaneous PTB in individuals of European and African descent.
      • Velez D.R.
      • Fortunato S.J.
      • Williams S.M.
      • Menon R.
      Interleukin-6 (IL-6) and receptor (IL6-R) gene haplotypes associate with amniotic fluid protein concentrations in preterm birth.
      The SNP that was found to be associated in our study was rs8192282. In contrast, the positive results of Velez et al
      • Velez D.R.
      • Fortunato S.J.
      • Williams S.M.
      • Menon R.
      Interleukin-6 (IL-6) and receptor (IL6-R) gene haplotypes associate with amniotic fluid protein concentrations in preterm birth.
      were based on multiple haplotypes in the IL6R gene in both European American and African American populations. However, the SNPs that were found to be significant in the previous study
      • Velez D.R.
      • Fortunato S.J.
      • Williams S.M.
      • Menon R.
      Interleukin-6 (IL-6) and receptor (IL6-R) gene haplotypes associate with amniotic fluid protein concentrations in preterm birth.
      are in strong LD in white HapMap samples with the SNP we found in the current study (Figure 7; D' = 0.78-1.00). The consistency of the association between IL6R and spontaneous preterm labor/delivery among different ethnic populations lends support to the importance of this finding.
      Figure thumbnail gr7
      FIGURE 7Linkage disequilibrium pattern of interleukin-6R region
      HapMap CEU samples of IL6R SNPs from the current study and that of Velez et al.
      • Velez D.R.
      • Fortunato S.J.
      • Williams S.M.
      • Menon R.
      Interleukin-6 (IL-6) and receptor (IL6-R) gene haplotypes associate with amniotic fluid protein concentrations in preterm birth.
      The SNP that associated with spontaneous preterm labor/delivery with intact membranes in the current study (rs8192282) is denoted by a rectangle surrounding it in the top of the panel. All other SNPs are from associating haplotypes in Velez et al.
      • Velez D.R.
      • Fortunato S.J.
      • Williams S.M.
      • Menon R.
      Interleukin-6 (IL-6) and receptor (IL6-R) gene haplotypes associate with amniotic fluid protein concentrations in preterm birth.
      Romero. Fetal and maternal DNA variants and spontaneous preterm labor. Am J Obstet Gynecol 2010.
      Although IL-6 has been considered neither sufficient nor necessary for preterm delivery in murine models,
      • Yoshimura K.
      • Hirsch E.
      Interleukin-6 is neither necessary nor sufficient for preterm labor in a murine infection model.
      the IL-6/IL-6R system previously has been implicated in preterm labor in humans.
      • Romero R.
      • Avila C.
      • Santhanam U.
      • Sehgal P.B.
      Amniotic fluid interleukin 6 in preterm labor: association with infection.
      • Romero R.
      • Yoon B.H.
      • Mazor M.
      • et al.
      The diagnostic and prognostic value of amniotic fluid white blood cell count, glucose, interleukin-6, and gram stain in patients with preterm labor and intact membranes.
      • Ghezzi F.
      • Cohen J.
      • Tolosa J.E.
      • et al.
      Microbial invasion of the amniotic cavity is associated with increased concentrations of amniotic fluid interleukin-6 soluble receptor.
      The median amniotic fluid concentration of IL-6 in the midtrimester of pregnancy is higher in women who are destined to have a pregnancy loss or a preterm delivery than that of women who deliver at term.
      • Wenstrom K.D.
      • Andrews W.W.
      • Tamura T.
      • DuBard M.B.
      • Johnston K.E.
      • Hemstreet G.P.
      Elevated amniotic fluid interleukin-6 levels at genetic amniocentesis predict subsequent pregnancy loss.
      • Wenstrom K.D.
      • Andrews W.W.
      • Hauth J.C.
      • Goldenberg R.L.
      • DuBard M.B.
      • Cliver S.P.
      Elevated second-trimester amniotic fluid interleukin-6 levels predict preterm delivery.
      • Yoon B.H.
      • Oh S.Y.
      • Romero R.
      • et al.
      An elevated amniotic fluid matrix metalloproteinase-8 level at the time of mid-trimester genetic amniocentesis is a risk factor for spontaneous preterm delivery.
      Moreover, among patients with preterm labor and intact membranes, amniotic fluid IL-6 concentrations are associated with preterm delivery, the amniocentesis-to-delivery interval, the likelihood of delivery within 48 hours and 7 days, and neonatal morbidity and death.
      • Yoon B.H.
      • Romero R.
      • Moon J.B.
      • et al.
      Clinical significance of intra-amniotic inflammation in patients with preterm labor and intact membranes.
      • Pacora P.
      • Chaiworapongsa T.
      • Maymon E.
      • et al.
      Funisitis and chorionic vasculitis: the histological counterpart of the fetal inflammatory response syndrome.
      IL-6 is a major mediator of the acute-phase response to infection and tissue injury and is expressed differentially by intrauterine tissues in the context of labor (term and preterm).
      • Menon R.
      • Merialdi M.
      • Lombardi S.J.
      • Fortunato S.J.
      Differences in the placental membrane cytokine response: a possible explanation for the racial disparity in preterm birth.
      • Steinborn A.
      • Geisse M.
      • Kaufmann M.
      Expression of cytokine receptors in the placenta in term and preterm labour.
      • Haddad R.
      • Tromp G.
      • Kuivaniemi H.
      • et al.
      Human spontaneous labor without histologic chorioamnionitis is characterized by an acute inflammation gene expression signature.
      Indeed, the fetal concentration of this cytokine has been used to define the fetal inflammatory response syndrome, which is associated with the onset of preterm labor, fetal multisystemic organ involvement, and neonatal morbidity.
      • Pacora P.
      • Chaiworapongsa T.
      • Maymon E.
      • et al.
      Funisitis and chorionic vasculitis: the histological counterpart of the fetal inflammatory response syndrome.
      • Gomez R.
      • Romero R.
      • Ghezzi F.
      • Yoon B.H.
      • Mazor M.
      • Berry S.M.
      The fetal inflammatory response syndrome.
      • Romero R.
      • Gomez R.
      • Ghezzi F.
      • et al.
      A fetal systemic inflammatory response is followed by the spontaneous onset of preterm parturition.
      • Romero R.
      • Maymon E.
      • Pacora P.
      • et al.
      Further observations on the fetal inflammatory response syndrome: a potential homeostatic role for the soluble receptors of tumor necrosis factor alpha.
      • Romero R.
      • Espinoza J.
      • Goncalves L.F.
      • et al.
      Fetal cardiac dysfunction in preterm premature rupture of membranes.
      • Kim Y.M.
      • Romero R.
      • Chaiworapongsa T.
      • Espinoza J.
      • Mor G.
      • Kim C.J.
      Dermatitis as a component of the fetal inflammatory response syndrome is associated with activation of Toll-like receptors in epidermal keratinocytes.
      • Gotsch F.
      • Romero R.
      • Kusanovic J.P.
      • et al.
      The fetal inflammatory response syndrome.
      In addition, DNA variants in the IL-6 gene have been associated with sepsis, brain injury, and cerebral palsy, especially in preterm neonates.
      • Kilpinen S.
      • Hulkkonen J.
      • Wang X.Y.
      • Hurme M.
      The promoter polymorphism of the interleukin-6 gene regulates interleukin-6 production in neonates but not in adults.
      • Harding D.
      • Dhamrait S.
      • Millar A.
      • et al.
      Is interleukin-6 -174 genotype associated with the development of septicemia in preterm infants?.
      • Harding D.R.
      • Dhamrait S.
      • Whitelaw A.
      • Humphries S.E.
      • Marlow N.
      • Montgomery H.E.
      Does interleukin-6 genotype influence cerebral injury or developmental progress after preterm birth?.
      • Wu Y.W.
      • Croen L.A.
      • Torres A.R.
      • Van De W.J.
      • Grether J.K.
      • Hsu N.N.
      Interleukin-6 genotype and risk for cerebral palsy in term and near-term infants.
      IL-6 mediates its biologic functions through IL-6R. A cleaved form of the IL-6R can be found in biologic fluids and tissues. The amniotic fluid concentrations of the soluble IL-6R are elevated in preterm labor with intraamniotic infection.
      • Ghezzi F.
      • Cohen J.
      • Tolosa J.E.
      • et al.
      Microbial invasion of the amniotic cavity is associated with increased concentrations of amniotic fluid interleukin-6 soluble receptor.
      It is relevant to the findings of this study that Velez et al
      • Velez D.R.
      • Menon R.
      • Thorsen P.
      • et al.
      Ethnic differences in interleukin 6 (IL-6) and IL6 receptor genes in spontaneous preterm birth and effects on amniotic fluid protein levels.
      • Velez D.R.
      • Fortunato S.J.
      • Williams S.M.
      • Menon R.
      Interleukin-6 (IL-6) and receptor (IL6-R) gene haplotypes associate with amniotic fluid protein concentrations in preterm birth.
      reported that amniotic fluid IL-6 concentrations were associated strongly with IL6R haplotypes in mothers and fetuses in a white population in the United States. The effects of IL6R genetic variants on IL6 concentrations has also been reported in nonpregnant subjects; in 1 case, it was found to be more important than IL6 DNA variants themselves in the determination of IL-6 concentrations. This finding is consistent with our observation of both IL-6 and IL-6R associations in previous studies.
      • Rafiq S.
      • Frayling T.M.
      • Murray A.
      • et al.
      A common variant of the interleukin 6 receptor (IL-6r) gene increases IL-6r and IL-6 levels, without other inflammatory effects.
      • Reich D.
      • Patterson N.
      • Ramesh V.
      • et al.
      Admixture mapping of an allele affecting interleukin 6 soluble receptor and interleukin 6 levels.
      Pathway analyses indicated that IL6R operates in a network entailing other fetal genes that are associated with spontaneous preterm labor/delivery with intact membranes, including collagens and IL2. Therefore, the statistical findings in this study, the consistency of the findings among ethnic groups, and the biologic role of IL-6 in preterm labor indicate the importance of the IL-6/IL-6R system in the predisposition to spontaneous preterm labor/delivery.
      Maternal haplotype analysis found that haplotypes in 4 genes were associated with preterm labor/delivery: COL4A3, IL6R, LTF, and FGF1 (Table 5). The most significant global association was in COL4A3. One haplotype (ACT) was associated with a 48% increased risk of preterm labor/delivery. Collagen IV is a major component of the basement membrane of several organs, including the uterine cervix.
      • Frappart L.
      • Berger G.
      • Grimaud J.A.
      • et al.
      Basement membrane of the uterine cervix: immunofluorescence characteristics of the collagen component in normal or atypical epithelium and invasive carcinoma.
      • Stewart C.J.
      • McNicol A.M.
      Distribution of type IV collagen immunoreactivity to assess questionable early stromal invasion.
      • Miosge N.
      The ultrastructural composition of basement membranes in vivo.
      • Winkler M.
      • Rath W.
      Changes in the cervical extracellular matrix during pregnancy and parturition.
      Treatment of cervical smooth muscle cells with TNF-alpha results in increased MMP-9 messenger RNA expression, induction of MMP-9 production, and decreased TIMP-2 secretion.
      • Watari M.
      • Watari H.
      • DiSanto M.E.
      • Chacko S.
      • Shi G.P.
      • Strauss III, J.F.
      Pro-inflammatory cytokines induce expression of matrix-metabolizing enzymes in human cervical smooth muscle cells.
      Therefore, our findings with haplotype analysis for collagen IV and the single locus association in the mother supports the relationship between structural proteins of the extracellular matrix (collagen IV) and a regulator of its degradation (TIMP2).
      The significant association between a haplotype in IL6R in the mothers and spontaneous preterm labor/delivery further supports the role of the IL-6/IL-6R system in the predisposition for this phenotype. In addition, the IL6R SNP rs8192282 in mothers was of marginal significance, even though it did not remain after multiple testing corrections (Table 4). A maternal haplotype in lactoferrin was associated significantly with predisposition to preterm labor/delivery. This protein is a major component of the innate immune system and has antimicrobial properties, including the ability to protect against biofilm infections. Lactoferrin has been reported to prevent the formation of biofilms by Pseudomonas.
      • Singh P.K.
      • Parsek M.R.
      • Greenberg E.P.
      • Welsh M.J.
      A component of innate immunity prevents bacterial biofilm development.
      Biofilms recently have been reported in the amniotic cavity,
      • Romero R.
      • Schaudinn C.
      • Kusanovic J.P.
      • et al.
      Detection of a microbial biofilm in intraamniotic infection.
      and it is possible that a deficiency in the concentration of this protein may predispose to biofilm formation in this unique niche and its consequences, such as the difficulty in obtaining a positive culture and refractoriness to treatment.
      • Costerton J.W.
      • Stewart P.S.
      • Greenberg E.P.
      Bacterial biofilms: a common cause of persistent infections.
      • Stewart P.S.
      • Costerton J.W.
      Antibiotic resistance of bacteria in biofilms.
      • Donlan R.M.
      • Costerton J.W.
      Biofilms: survival mechanisms of clinically relevant microorganisms.
      A proposed mechanism of action for lactoferrin to inhibit biofilm formation is via iron chelation and stimulation of a specialized form of bacterial-surface motility (twitching), thereby preventing the formation of cell clusters and biofilms.
      • Singh P.K.
      • Parsek M.R.
      • Greenberg E.P.
      • Welsh M.J.
      A component of innate immunity prevents bacterial biofilm development.
      This protein is present normally in the amniotic fluid, and its concentration increases with gestational age and decreases at the time of the onset of spontaneous labor.
      • Pacora P.
      • Maymon E.
      • Gervasi M.T.
      • et al.
      Lactoferrin in intrauterine infection, human parturition, and rupture of fetal membranes.
      Another important aspect of lactoferrin is that it down-regulates proinflammatory cytokines and the production of reactive oxygen radicals. We previously reported that the amniotic fluid concentrations of lactoferrin are increased in women with preterm labor and intraamniotic infection.
      • Pacora P.
      • Maymon E.
      • Gervasi M.T.
      • et al.
      Lactoferrin in intrauterine infection, human parturition, and rupture of fetal membranes.
      A maternal haplotype for FGF1 was also associated with the risk of spontaneous preterm labor/delivery. This protein is very pleiotropic and has been implicated in vascularization.
      • Hoshino M.
      • Takahashi M.
      • Aoike N.
      Expression of vascular endothelial growth factor, basic fibroblast growth factor, and angiogenin immunoreactivity in asthmatic airways and its relationship to angiogenesis.
      A subgroup of patients with spontaneous preterm labor/delivery are thought to have vascular lesions as a primary mechanism of disease.
      • Arias F.
      • Rodriquez L.
      • Rayne S.C.
      • Kraus F.T.
      Maternal placental vasculopathy and infection: two distinct subgroups among patients with preterm labor and preterm ruptured membranes.
      It is possible that defective angiogenesis plays a role in some cases of preterm labor.
      • Chaiworapongsa T.
      • Romero R.
      • Tarca A.
      • et al.
      A subset of patients destined to develop spontaneous preterm labor has an abnormal angiogenic/anti-angiogenic profile in maternal plasma: evidence in support of pathophysiologic heterogeneity of preterm labor derived from a longitudinal study.
      Further studies are required to explore the role of FGF1 in this condition.
      Three genes in fetal DNA had significant haplotype associations: IGF2, IL2, and COL4A1. The association with COL4A1 in the fetus is consistent with the finding of a haplotype in COL4A3 in the mother in this study and TIMP2, as discussed earlier. The role of IL-2 in preterm parturition is less clear. This cytokine is a T-cell growth factor that has been reported to stimulate prostaglandin production by chorion.
      • Coulam C.H.
      • Edwin S.S.
      • LaMarche S.
      • Mitchell M.D.
      Actions of interleukin-2 on chorio-decidual prostaglandin biosynthesis.
      • Zicari A.
      • Ticconi C.
      • Pasetto N.
      • et al.
      Interleukin-2 in human amniotic fluid during pregnancy and parturition: implications for prostaglandin E2 release by fetal membranes.
      However, a role for IL-2 in parturition is not well-established. It is possible that this cytokine may play a role in tolerance regulation of the fetal allograft. Finally, fetal haplotypes in IGF2 were found to be a large modifier of the risk of preterm delivery; 1 haplotype increased the risk, and another 1 decreased the risk. This gene was studied because we were interested in examining the relationship between DNA variants and SGA. Spontaneous preterm labor has been associated with SGA
      • Espinoza J.
      • Kusanovic J.P.
      • Kim C.J.
      • et al.
      An episode of preterm labor is a risk factor for the birth of a small-for-gestational-age neonate.
      and with accelerated fetal growth.
      • Lampl M.
      • Kusanovic J.P.
      • Erez O.
      • et al.
      Early rapid growth, early birth: accelerated fetal growth and spontaneous late preterm birth.
      • Lampl M.
      • Kusanovic J.P.
      • Erez O.
      • et al.
      Growth perturbations in a phenotype with rapid fetal growth preceding preterm labor and term birth.
      The finding reported herein calls for further examination of the role of IGF2 and its pathway in spontaneous preterm parturition.
      Spontaneous preterm parturition is syndromic in nature, and multiple mechanisms of disease are likely to be involved.
      • Romero R.
      • Espinoza J.
      • Kusanovic J.P.
      • et al.
      The preterm parturition syndrome.
      • Romero R.
      Prenatal medicine: the child is the father of the man.
      • Di Renzo G.C.
      The great obstetrical syndromes.
      Discovery tools with unbiased methods have been used to study complex problems in obstetrics.
      • Romero R.
      • Kuivaniemi H.
      • Tromp G.
      Functional genomics and proteomics in term and preterm parturition.
      • Romero R.
      • Kuivaniemi H.
      • Tromp G.
      • Olson J.
      The design, execution, and interpretation of genetic association studies to decipher complex diseases.
      • Romero R.
      • Tromp G.
      High-dimensional biology in obstetrics and gynecology: functional genomics in microarray studies.
      • Romero R.
      • Espinoza J.
      • Gotsch F.
      • et al.
      The use of high-dimensional biology (genomics, transcriptomics, proteomics, and metabolomics) to understand the preterm parturition syndrome.
      To address the complexity of the genetic predisposition to spontaneous preterm labor and delivery, we performed 2 exploratory analyses. MDR explicitly addressed the potential role of interactions among genes (maternal, fetal, and maternal-fetal). The results of these analyses were not compelling in the identification of complex genetic models (eg, epistasis). Although such gene-gene interactions have been reported previously for spontaneous PTB that involves the IL6, IL6R, and TNF-alpha genes, these were in the mother in white individuals.
      • Menon R.
      • Velez D.R.
      • Simhan H.
      • et al.
      Multilocus interactions at maternal tumor necrosis factor-alpha, tumor necrosis factor receptors, interleukin-6 and interleukin-6 receptor genes predict spontaneous preterm labor in European-American women.
      Therefore, our negative results may reflect the different ethnic groups under study, different DNA variants between studies, and the sensitivity of interaction tests to changes in allele frequencies.
      • Greene C.S.
      • Penrod N.M.
      • Williams S.M.
      • Moore J.H.
      Failure to replicate a genetic association may provide important clues about genetic architecture.
      However, it is of note that the models that we detected, although not significant, did include SNPs in genes that are in extracellular matrix metabolism and inflammatory pathways, especially IL6, MMP13, and several collagen genes.
      Additionally, there is an increasing realization of the importance of pathways in predisposition to complex diseases. We used IPA to examine the contribution of genetic variants in determining networks and disease functions. The prominence of hepatic fibrosis among established signaling pathways in both maternal and fetal analysis presumably reflects involvement of inflammatory cascades and extracellular matrix remodeling. The findings suggest that maternal and fetal gene variants that involve inflammation and extracellular matrix metabolism pathways predispose to spontaneous preterm labor/delivery. These findings are consistent with a large body of literature that supports this view.
      The strengths of our study include a well-defined phenotype (spontaneous preterm labor/delivery with intact membranes) and a relatively homogeneous population. This is the largest study to examine the genetic predisposition to spontaneous PTB in Hispanic women. Moreover, the study includes both maternal and fetal DNA and a relatively large number of genes and DNA variants. The number of DNA variants that were selected was estimated to cover 90% of the coding DNA variation in the candidate genes. Importantly, we identified that both maternal and fetal DNA variants contributed to modify the risk. Limitations of these types of studies are that confirmation of the findings is required and that we have not examined the effect of environmental factors,
      • Macones G.A.
      • Parry S.
      • Elkousy M.
      • Clothier B.
      • Ural S.H.
      • Strauss III, J.F.
      A polymorphism in the promoter region of TNF and bacterial vaginosis: preliminary evidence of gene-environment interaction in the etiology of spontaneous preterm birth.
      • Romero R.
      • Chaiworapongsa T.
      • Kuivaniemi H.
      • Tromp G.
      Bacterial vaginosis, the inflammatory response and the risk of preterm birth: a role for genetic epidemiology in the prevention of preterm birth.
      • Merialdi M.
      • Murray J.C.
      The changing face of preterm birth.
      which are known to play a role in the risk of preterm delivery. In addition, functional studies are needed to assess the precise physiologic implications of the DNA variants and their iterations identified in this study.
      This large genetic association study of candidate genes that are involved in adverse pregnancy outcome revealed that both maternal and fetal DNA variants are associated with spontaneous preterm delivery.

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