Mapping genetic susceptibility to preterm birth: Analysis of Utah pedigrees using shared genomic segment analysis

doi:10.21203/rs.3.rs-4941836/v1

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Mapping genetic susceptibility to preterm birth: Analysis of Utah pedigrees using shared genomic segment analysis

https://doi.org/10.21203/rs.3.rs-4941836/v1

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Background: Spontaneous preterm birth (SPTB) is the leading cause of neonatal morbidity and mortality. It is a final common pathway for multiple etiologies, some of which are well known while others likely remain to be identified. There is a genetic component to SPTB, but genetic mechanisms remain poorly defined. Well-characterized family-based studies may aid in identifying genetic contributors to SPTB.

Objective: To identify inherited risk variants for SPTB using large pedigrees.

Study Design: Using the Utah Population Database (UPDB), which links a 4.5 million-person genealogy to state birth certificate and fetal death records, we identified large pedigrees containing multiple women with early SPTB (<34 weeks’ gestation). We reviewed birth certificate data to exclude those with maternal and fetal diagnoses associated with iatrogenic preterm birth, resulting in 74 large multiplex pedigrees for early SPTB. Women with any SPTB (<37 weeks) within these early SPTB pedigrees were invited to participate. Enrolled women underwent comprehensive clinical phenotyping with review of primary medical records. Seven pedigrees, each containing at least 3 sampled women with SPTB, were the focus of this genetic study. High-density single-nucleotide polymorphism genotyping was conducted in maternal peripheral blood samples from women in the seven pedigrees. Shared genomic segment (SGS) analysis was performed to identify genome-wide significant chromosomal regions shared in excess by women with SPTB.

Results: We identified two genome-wide significant regions. In single-pedigree SGS analyses, a 1.75 Mb genome-wide significant region at 8q24.23 was shared by 5 out of 6 women with SPTB in a single large pedigree (false positive rate per genome, µ=0.028). In duo-pedigree analysis, this region showed overlapping evidence with a second pedigree. The shared 1.05 Mb 8q24.23 locus had a more extreme false-positive rate (µ=0.0019). and contains FAM135Band KHDRBS3 genes, which have previously been implicated in oncogenesis and ovarian cancer. Duo-pedigree SGS analysis also identified a second genome-wide significant 67 kb locus at 12q21.1-q21.2 that was shared by all SPTB cases in two independent pedigrees (µ=0.01). The intersecting region at 12q21.1-q21.2 contains genes (CAPS2; KCNC2) implicated in vascular-related complications of pregnancy and preterm labor.

Conclusion: We identified two risk loci for SPTB using shared genomic segments analysis in large multiplex pedigrees. Identification of genes associated with SPTB may provide novel therapeutic targets for prevention and treatment to prolong pregnancy and improve outcomes.

Population Genetics

Obstetrics & Gynecology

spontaneous preterm birth. shared genomic segments. inherited variants. pedigrees

Tweetable statement: Analysis of Utah spontaneous preterm birth pedigrees using shared genomic segment analysis.
Short Title: Inherited genetic variants and preterm birth.
AJOG at a Glance:

Why was this study conducted: Well-characterized family-based studies may aid in identifying inherited genetic contributors to spontaneous preterm birth.
Key findings: Shared genomic segments analysis identified regions at 8q24.23 and 12q21.1-q21.2 chromosomal regions that segregate in large, multiplex spontaneous preterm birth pedigrees.
What does this study add to what is known? This study provides the first genome-wide significant evidence for inherited variants in spontaneous preterm birth pedigrees. We propose further investigation of the pedigrees including functional work to determine avenues for novel therapeutic targets and guide efforts for spontaneous preterm birth prevention.

Preterm birth, defined as the birth of a baby before 37 weeks’ gestation, is the leading cause of neonatal morbidity and mortality globally.¹ Spontaneous preterm birth (SPTB) occurs when the process of labor begins spontaneously prior to term and may be associated with mechanisms such as infection, inflammation, vascular pathology and/or environmental factors.^1–3 SPTB affects 10–15% of pregnancies and is more likely to recur in subsequent pregnancies.⁴ Although SPTB is heritable and genetic risk variants supported by genome-wide association studies (GWASs) have been identified,^5–9 findings from previous studies are inconsistent and currently provide insufficient evidence for targeted prediction, prevention or treatment of SPTB. Due to its heterogeneity throughout gestation and across families, no single genetic factor causes SPTB.¹⁰ Additional genetic variants assuredly contribute further to SPTB.

Studying single, large, multiplex pedigrees that contain extreme phenotypes, such as early SPTB (< 34 weeks’ gestation), is one strategy to decrease heterogeneity and improve power to identify genetic causes of common, complex disorders such as SPTB.¹¹ It has previously been shown that more statistical power can be leveraged by using a relatively small number of cases in large pedigrees than traditional methods that require larger sample sizes.^{12, 13} Such pedigrees are likely enriched for susceptibility variants, and the large number of generations allows methods, such as shared genomic segments (SGS) analysis, to estimate recombination events and delimit regions and specific haplotypes that contain rare risk variants. This allows for focused interrogation of regulatory variants, a mechanism likely to be involved in complex diseases.^{12, 13} We used the Utah Population Database (UPDB), a population-based genealogical resource linked to birth certificate records,¹⁴ to identify large, multiplex early SPTB pedigrees and perform SGS to map genes involved in SPTB. We hypothesized that inherited regulatory and coding risk variants will be localized by SGS in SPTB pedigrees and provide genomic regions for further targeted interrogation.

Data source, study population, and case determination

Heritability for SPTB was previously established in a study of gestational age in the UPDB.¹⁵ The UPDB links 4.5 million people in Utah with 3–17 generations of genealogy to statewide vital statistics records (births, deaths, marriages, fetal deaths) since 1890.¹⁴ Using the record linkage of genealogy and births/fetal deaths in the UPDB, we identified large, multigenerational pedigrees that contained multiple women with early SPTB (< 34 weeks’ gestation). Gestational age was calculated based on the date of the mother’s last menstrual period.¹⁵ We used this measure because it is consistent across the full timespan of records available, from 1945 through 2010. Rigorous review of birth certificate and fetal death records for SPTB cases in these pedigrees was conducted to determine and verify SPTB cases. Maternal and fetal diagnoses associated with iatrogenic preterm birth and women with multi-fetal gestations were excluded. We prioritized 74 pedigrees with ≥ 10 living women who had early SPTB (< 34 weeks’ gestation). All women with SPTB (< 37 weeks’ gestation) within these early SPTB pedigrees were eligible for participation. Informed consent was obtained and maternal peripheral blood samples were collected using Paxgene and processed for DNA extraction using the Infinium OmniExpress-24 DNA extraction kit (Illumina, Inc). Participants were asked to sign a release of medical information form and, whenever possible, maternal and neonatal medical records were reviewed to ensure accuracy of the SPTB gestation. Clinical estimates (based on ultrasound or other clinical judgment) were only used when the date of last menses was missing or incomplete or if it generated an out-of-range gestational age. This study was approved by the University of Utah’s Institutional Review Board (IRB number: 00053667).

Selection of pedigrees, sample genotyping and quality control

Utah pedigrees often include large sibships, increasing the chance for capturing SPTB occurrences in multiple pregnancies. We focused genetic analysis on those women whose first pregnancy was a SPTB (< 37 weeks’ gestation) or who had multiple SPTBs. Seven pedigrees contained at least 3 women with DNA and this narrower definition, with a large number of generations between these cases.¹² For SGS analysis, high-density single-nucleotide polymorphism (SNP) genotyping was conducted for 31 women using the OmniExpress Exome chip (Illumina, Inc). SNP quality control included: duplicate check, sex check, SNP call-rate (≥ 95%), sample call rate (≥ 95%), and failure of Hardy-Weinberg equilibrium (p ≤ 1×10^− 5). After quality control, 630,662 autosomal SNPs were available for SGS.

SGS and statistical analysis

Primary analysis: single-pedigree SGS. Pedigrees with at least 15 meioses between studied cases are powerful for genome-wide single-pedigree SGS analysis.¹² Four of the 7 large SPTB pedigrees fulfilled this requirement (Fig. 1, Panel A). We performed single-pedigree SGS analysis on each of the 4 large pedigrees individually to identify regions shared by multiple SPTB cases. Full details of the single-pedigree SGS method has been described previously.¹³ Briefly, the SGS approach identifies long DNA segments which are inherited across a large number of meiosis beyond that expected by chance, with p-values and significance thresholds determined using simulation-based methods specific to a pedigree’s structure. Here, we used 300,000 simulations for model fitting to determine pedigree-specific genome-wide thresholds that account for the multiplicity of testing across the genome and the subsets considered. Further simulations were performed to gain good resolution for small P-values, where necessary. A false positive rate of 0.05 per genome, µ\(\:\le\:\)0.05, was used to declare genome-wide significance, which indicates that the observation is expected to occur at a rate of 0.05 per genome or less. Suggestive evidence was declared for regions with µ\(\:\le\:\)1.0.

Secondary analysis: duo-pedigree SGS: If two pedigrees harbor segregating risk variants influencing the same gene, that shared evidence may be identified by considering pairs of pedigrees. The duo-pedigree SGS approach was developed to identify regions that are not significant within single pedigrees, but gain significance due to evidence for a consistent region shared across the two pedigrees.¹⁹ For these two pedigree analyses we considered an additional three large SPTB pedigrees, each containing 11–14 meioses (Fig. 1, Panel B). P-values for overlapping two-pedigree regions are approximated using Fisher’s combined probability test. Genome-wide duo-thresholds are determined to consider the additional multiple testing of pairing of pedigrees,¹⁹ and rates per genome µ(duo)\(\:\le\:\)0.05 used to declare genome-wide significance.

Analyses were conducted using the SGS analysis software that is freely available and can be accessed online: https://uofuhealth.utah.edu/huntsman/labs/camp/analysis-tool/shared-genomic-segment.php.

Thirty-one women whose first birth was SPTB (< 37 weeks) or who experienced multiple SPTBs (< 37 weeks) in seven multiplex pedigrees selected from UPDB for early SPTB were included in this study. All pedigrees contained at least three SPTB cases. Four of the seven pedigrees had ≥ 15 meioses between SPTB cases and were included in single-pedigree SGS analyses (Fig. 1, Panel A). Three pedigrees had fewer meiosis and were used in secondary analyses to identify regions shared in two pedigrees, using duo-pedigree SGS analysis (Fig. 1, Panel B).

In single-pedigree SGS analysis, we identified one genome-wide significant SGS region (P-value = 9.99×10^− 8; µ = 0.028) at chromosome 8 (8q24.23) (Table 1, Fig. 2). The genome-wide significant 8q24.23 SGS region is a 1.75 Mb segment of 406 contiguous SNPs (chr8: 137,013,447–138,759,742 GRCh37 bp) shared by five out of six women with SPTB in Pedigree 1 (Fig. 1, Panel Ai). The 1.75 Mb region was inherited through 24 meioses to five women with SPTB. Sixteen single-pedigree SGS genome-wide suggestive regions were also identified across the four pedigrees analyzed (Table 1).

In duo-pedigree analysis, we required the joint P-value to be genome-wide significant, µ(duo)\(\:\le\:\)0.05, and each pedigree to have single-pedigree evidence at µ\(\:\le\:\)5.0 to avoid finding results that are simply driven by one of the two pedigrees. With these criteria only two regions reached genome-wide significance in duo-pedigree SGS analysis (Table 2). The same 8q24.23 region from single-pedigree SGS results was also identified as genome-wide significant in duo-pedigree SGS when Pedigree 1 was paired with Pedigree 2, yielding an order of magnitude smaller expected by chance rate than in Pedigree 1 alone, µ(duo)=0.0019. The overlapping region is 1.05 Mb at 8q24.23 (137,485,507–138,537,206 bp) and shared by 5 of 6 early SPTB cases in Pedigree 1 and 3 of 4 early SPTB cases in Pedigree 2. Figure 3A shows characteristics of the shared region, which contains two genes, FAM135B and KHDRBS3. A second genome-wide significant duo-pedigree SGS region was identified at 12q21.1-q21.2 for Pedigree 3 paired with Pedigree 1. This region was previously identified as suggestive in single-pedigree SGS analysis for Pedigree 3 (µ = 0.68; Table 1), and gained significance in the joint analysis, µ(duo) = 0.01. The very small 67,291 bp genome-wide significant segment (75,525,950–75,593,241 bp) is shared by all 3 cases in Pedigree 3 and all 6 cases in Pedigree 1. Figure 3B shows the region containing the intersecting shared segment and genes CAPS2 and KCNC2.

Comment

Principal findings

We identified two genome-wide significant SGS regions at 8q24.23 and 12q21.1-q21.2 using SGS analyses in large, multiplex SPTB pedigrees, providing evidence for segregating risk variants from a common founder. The 8q24.23 is a 1.75 Mb segment on chromosome 8 (contains FAM135B and KHDRBS3 genes), shared by 8 women with SPTB in two pedigrees. The 12q21.1-q21.2 a 67 kb segment on chromosome 12 (contains CAPS2 and KCNC2 genes), shared by 9 women in two pedigrees.

Results in the context of what is known in existing literature

Maternally inherited genes acting in the fetus are largely thought to be responsible for birth timing,^{20, 21} but only a few GWAS loci in candidate maternal genes (e.g., ZBTB38, WNT4, EBF1, HAND2, TET3, and KCNAB1) for SPTB have been identified^{5, 6} and replicated in recent GWAS meta-analyses.²² Preliminary investigations suggest rare, deleterious genetic variants could be enriched in both mothers and the preterm birth infant,²³ but efforts to characterize rare inherited variants are lacking. Family-based studies can identify segregating regions and have the advantage of localizing regions allowing specific regulatory regions to be considered. To date, only one family-based linkage study of SPTB has been conducted.²⁴ The study suggested novel fetal SPTB susceptibility genes, which included common SNPs near the IGF1R gene in 15q26.3 and 8q24.3, the latter in proximity to the genomic segment reported here. Previously there have not been any studies in large, multiplex SPTB pedigrees as we present here. Well-characterized large pedigrees are more likely to be homogeneous and genetically enriched, and thus provide the opportunity to discover segregating shared regions that harbor genetic variants for disease.¹²

In the present study, we used the UPDB to identify large pedigrees containing multiple women with early SPTB. We ascertained and studied the genetics of women within these pedigrees who experienced SPTB in their first or multiple pregnancies to identify maternally heritable effects on gestational age and on SPTB.¹⁵

Research and clinical implications

The genome-wide significant 8q24.23 segment localized a 1.05 Mb region containing KHDRBS3 and FAM135B, suggesting shared variants may regulate one of these two target genes. KHDRBS3 is a member of signal transduction and the activation of RNA family and regulates gene expression by RNA splicing.^{25, 26} Variation in this gene is associated with shorter telomere length or dysregulated telomerase activity, which have previously been associated with pregnancy complications.²⁷ In particular, in a recent study, maternal blood samples from SPTB cases had shorter telomeres, compared with maternal blood samples from uncomplicated pregnancies.²⁸ These findings suggest KHDRBS3 may contribute to SPTB by regulating telomere length and cell senescence. The other candidate target gene, FAM135B, promotes inflammation by inducing granulin (a protein-coding gene located on chromosome 17q21.32) precursor secretion and activating the PI3K/AKT/mTOR signaling pathway.²⁹ Excessive activation of inflammatory molecules within the placenta has been associated with preterm labor.³⁰ However, there were no previous links noted between FAM135B and SPTB.

The 8q24 region contains regulatory elements, including enhancers, that are thought to regulate nearby MYC oncogenes.³¹ Variants in 8q24 are associated with many cancers, including ovarian cancer.^{32, 33} Among women diagnosed with gynecologic cancer, the prevalence of preterm birth was higher compared with women without cancer diagnoses.³⁴ Although there were no reported links between MYC proto-oncogenes and SPTB, novel pathways of inflammation, which are regulated by MYC proto-oncogenes,³⁵ are associated with preterm birth and preterm pre-labor rupture of membranes.³⁶ Furthermore, given the possible damage to oocytes and prolonged immunosuppression, further investigation into the 8q24 genomic region may lead to novel biomarker and therapeutic development for preterm birth.

The genome-wide significant 12q21.1-q21.2 segment localized a 67 kb region containing CAPS2 (Calcyphosine 2) and KCNC2 (potassium voltage-gated channel subfamily C member 2), genes which have both been well described in several disease mechanisms.³⁷ CAPS2 is a calcium ion binding gene involved in the secretion of brain-derived neurotrophic factor and neurotrophin-3³⁸ and is implicated in autism in mice knock-out experiments.^{39, 40} Using probabilistic search model for identification of disease-causing variants, we previously identified CAPS2 among over-represented genes in key processes that may lead to SPTB.⁴¹ Epigenetic changes in calcium ion genes have also been detected using GO enrichment analyses among African American women with preterm birth history.⁴² Furthermore, epigenetic changes in CAPS2 in placenta and cord blood, respectively, have been associated with increased maternal blood pressure during pregnancy,⁴³ a risk factor for preterm birth, and physical development in children.³⁹ The potassium channel gene KCNC1 is linked with a group of rare, inherited disorders such as progressive myoclonus epilepsies.⁴⁴ Potassium channel dysfunction has been associated with vascular-related complications of pregnancy, and interestingly, the ATP-sensitive potassium channel agonist nicorandil is currently being assessed for the prevention of preterm labor.⁴⁵ During gestation, potassium channels are known to contribute to a normal gestational period and initiating labor contractions at term.⁴⁶ In concert, these prior findings and our current SGS results suggest that further investigation into CAPS2 and KCNC2 genes for preterm birth therapeutic development is warranted.

Strengths and limitations

Our study has some limitations. We do not have data on non-genetic factors associated with SPTB (e.g., tobacco smoking, nutrition, and socioeconomic status). Therefore, we cannot estimate the interactive effects of genes with environmental risk factors. In addition, our data is based on European-ancestry study participants. Population-based family studies of SPTB with individuals from diverse racial/ethnic backgrounds and studies that account for environmental risk factors may be impactful, informing prevention and intervention strategies. Also, the large pedigree design is powerful for identification of dominantly inherited variants. Other genetic risk mechanisms acting through inherited recessive or de novo variants, as suggested by a previous study,⁴⁷ cannot be identified or replicated with the SGS approach.²³ However, the SGS approach is complementary and provides an additional advantage because genetic heterogeneity is reduced within families.⁴⁸

In summary, our study provides the first genome-wide significant evidence for inherited SPTB loci in large multiplex pedigrees selected for early SPTB. Further investigation into the 8q24 and 12q21.1-q21.2 regions, including sequencing and functional work to identify genetic variants to elucidate these SPTB risk loci is a natural next step. Knowledge of SPTB risk genes and their mechanisms will provide avenues for novel therapeutic targets and may guide efforts for SPTB prevention to prolong pregnancy and improve outcomes.

Disclosure statement: The authors report no conflicts of interest.

We thank the participants and their families who make this research possible. The study uses data from the Utah Population Database (UPDB) linked to data from the University of Utah Health and Intermountain Health healthcare systems. Partial support for all datasets within UPDB is provided by the University of Utah Huntsman Cancer Institute and P30 CA2014. Record linking from the UPDB to enterprise data warehouses at the two healthcare systems was supported by the University of Utah’s Center for Clinical and Translational Science Institute (CTSI), Information Technology Services and Biomedical Informatics core. C-H W. W. is supported by NIH/NIDDK grants DK135933. The authors acknowledge the Utah Genome Project for providing support for genotyping and sequencing.

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Table 1

Findings from genome-wide-significant and -suggestive SGS regions from single-pedigree SGS-analysis
Pedigree ID	Total number of early SPTB cases in SGS analysis	Number of meiosis between sampled SPTB cases	Locus Cytoband	Size in Mb	# of SNPs	# cases sharing	P-value	µ¹
1	6	29	8q24.23	1.75	406	5	1.0×10^− 7	0.028
			9p24.2	0.22	126	5	1.0×10^− 6	0.36
			20q11.23	0.88	186	4	1.4×10^− 6	0.51
			4q26	1.72	199	5	2.7×10^− 6	0.98
2	4	17	11q21	1.01	221	4	2.5×10^− 5	0.48
			11p15.4	1.64	319	4	2.8×10^− 5	0.53
			7p12.1-p11.2	1.08	255	4	3.4×10^− 5	0.63
			16q23.1-q23.2	0.35	203	4	3.6×10^− 5	0.67
			1q41-q42.12	1.56	313	4	3.8×10^− 5	0.71
			10q25.3	2.02	375	3	5.2×10^− 5	0.95
3	3	15	14q31.3	1.19	320	3	9.3×10^− 5	0.49
			6p21.31-p21.2	0.74	229	3	1.2×10^− 4	0.62
			12q21.1-q21.2	0.88	248	3	1.3×10^− 4	0.68
			3q13.33-q21.1	1.08	293	3	1.4×10^− 4	0.74
4	5	19	4q35.2	0.21	67	5	2.1×10^− 5	0.80
			17q21.32	0.73	178	5	2.2×10^− 5	0.88
			8q24.22	0.58	123	5	2.4×10^− 5	0.97
¹ Genome-wide false positive rate, indicating the expected degree of sharing per genome; genome-wide significant SGS region highlighted in Bold

Table 2. Genome-wide significant SGS regions with known genes/disease/phenotypes from duo-pedigree and single-pedigree SGS analyses

¹ Genome-wide false positive rate, indicating the expected degree of sharing per genome

² Genomic region according to the GRCh37/hg19 genome build position in the chromosome; for duo-SGS regions are the overlap

Locus Cytoband	Known Genes	Disease/ Phenotypes	SGS analysis type	Pedigree# (cases sharing /total cases)	P	µ¹	Size in Mb	Region²
8q24.23	FAM135B; KHDRBS3	Oncogenic; Ovarian Cancer	Single	1 (5/6)	1.0×10^− 7	0.028	1.75	137013447–138759742
			Single	2 (3/4)	9.7×10^− 5	1.72	1.05	137485507–138537206
			Duo	1 (5/6) & 2 (3/4)	2.5×10^− 10	0.0019	1.05	137485507–138537206
12q21.1-q21.2	CAPS2; KCNC2	Epilepsy; Autism; Preterm Labor	Single	3 (3/3)	1.3×10^− 4	0.68	0.88	75525950–76409990
			Single	1 (6/6)	3.6×10^− 6	1.30	0.80	74790141–75593241
			Duo	3 (3/3) & 1 (6/6)	1.0×10^− 8	0.010	0.07	75525950–75593241

The authors declare no competing interests.

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Mapping genetic susceptibility to preterm birth: Analysis of Utah pedigrees using shared genomic segment analysis

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Abstract

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Introduction

Materials and Methods

Data source, study population, and case determination

Selection of pedigrees, sample genotyping and quality control

SGS and statistical analysis

Results

Comment

Principal findings

Results in the context of what is known in existing literature

Research and clinical implications

Strengths and limitations

Conclusions

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References

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