Genome-wide association study of parity in Bangladeshi women

Evolutionary transcriptomics implicates new genes and pathways in human pregnancy and adverse pregnancy outcomes

Evolutionary changes in the anatomy and physiology of the female reproductive system underlie the origins and diversification of pregnancy in Eutherian ('placental') mammals. This developmental and evolutionary history constrains normal physiological functions and biases the ways in which dysfunction contributes to reproductive trait diseases and adverse pregnancy outcomes. Here, we show that gene expression changes in the human endometrium during pregnancy are associated with the evolution of human-specific traits and pathologies of pregnancy. We found that hundreds of genes gained or lost endometrial expression in the human lineage. Among these are genes that may contribute to human-specific maternal-fetal communication (HTR2B) and maternal-fetal immunotolerance (PDCD1LG2) systems, as well as vascular remodeling and deep placental invasion (CORIN). These data suggest that explicit evolutionary studies of anatomical systems complement traditional methods for characterizing the genetic architecture of disease. We also anticipate our results will advance the emerging synthesis of evolution and medicine ('evolutionary medicine') and be a starting point for more sophisticated studies of the maternal-fetal interface. Furthermore, the gene expression changes we identified may contribute to the development of diagnostics and interventions for adverse pregnancy outcomes.

Screening of Methylation Signature and Gene Functions Associated With the Subtypes of Isocitrate Dehydrogenase-Mutation Gliomas

Isocitrate dehydrogenase (IDH) is an oncogene, and the expression of a mutated IDH promotes cell proliferation and inhibits cell differentiation. IDH exists in three different isoforms, whose mutation can cause many solid tumors, especially gliomas in adults. No effective method for classifying gliomas on genetic signatures is currently available. DNA methylation may be applied to distinguish cancer cells from normal tissues. In this study, we focused on three subtypes of IDH-mutation gliomas by examining methylation data. Several advanced computational methods were used, such as Monte Carlo feature selection (MCFS), incremental feature selection (IFS), support machine vector (SVM), etc. The MCFS method was adopted to analyze methylation features, resulting in a feature list. Then, the IFS method incorporating SVM was applied to the list to extract important methylation features and construct an optimal SVM classifier. As a result, several methylation features (sites) were found to relate to glioma subclasses, which are annotated onto multiple genes, such as FLJ37543, LCE3D, FAM89A, ADCY5, ESR1, C2orf67, REST, EPHA7, etc. These genes are enriched in biological functions, including cellular developmental process, neuron differentiation, cellular component morphogenesis, and G-protein-coupled receptor signaling pathway. Our results, which are supported by literature reports and independent dataset validation, showed that our identified genes and functions contributed to the detailed glioma subtypes. This study provided a basic research on IDH-mutation gliomas.

A genome-wide association study of mitochondrial DNA copy number in two population-based cohorts

BACKGROUND

Mitochondrial DNA copy number (mtDNA CN) exhibits interindividual and intercellular variation, but few genome-wide association studies (GWAS) of directly assayed mtDNA CN exist. We undertook a GWAS of qPCR-assayed mtDNA CN in the Avon Longitudinal Study of Parents and Children (ALSPAC) and the UK Blood Service (UKBS) cohort. After validating and harmonising data, 5461 ALSPAC mothers (16-43 years at mtDNA CN assay) and 1338 UKBS females (17-69 years) were included in a meta-analysis. Sensitivity analyses restricted to females with white cell-extracted DNA and adjusted for estimated or assayed cell proportions. Associations were also explored in ALSPAC children and UKBS males.

RESULTS

A neutrophil-associated locus approached genome-wide significance (rs709591 [MED24], β (change in SD units of mtDNA CN per allele) [SE] - 0.084 [0.016], p = 1.54e-07) in the main meta-analysis of adult females. This association was concordant in magnitude and direction in UKBS males and ALSPAC neonates. SNPs in and around ABHD8 were associated with mtDNA CN in ALSPAC neonates (rs10424198, β [SE] 0.262 [0.034], p = 1.40e-14), but not other study groups. In a meta-analysis of unrelated individuals (N = 11,253), we replicated a published association in TFAM (β [SE] 0.046 [0.017], p = 0.006), with an effect size much smaller than that observed in the replication analysis of a previous in silico GWAS.

CONCLUSIONS

In a hypothesis-generating GWAS, we confirm an association between TFAM and mtDNA CN and present putative loci requiring replication in much larger samples. We discuss the limitations of our work, in terms of measurement error and cellular heterogeneity, and highlight the need for larger studies to better understand nuclear genomic control of mtDNA copy number.

Genetic loci associated with coronary artery disease harbor evidence of selection and antagonistic pleiotropy

Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits. While selection on quantitative traits is much more common, very few signals have been detected because of their polygenic nature. We searched for positive selection signals underlying coronary artery disease (CAD) in worldwide populations, using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk. We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk. These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness. We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductive success is antagonistic. This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans. Lastly, we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines, which further highlights the unique biological significance of candidate adaptive loci underlying CAD. Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD.

An Ancient Fecundability-Associated Polymorphism Switches a Repressor into an Enhancer of Endometrial TAP2 Expression

Variation in female reproductive traits, such as fertility, fecundity, and fecundability, is heritable in humans, but identifying and functionally characterizing genetic variants associated with these traits has been challenging. Here, we explore the functional significance and evolutionary history of a T/C polymorphism of SNP rs2071473, which we have previously shown is an eQTL for TAP2 and significantly associated with fecundability (time to pregnancy). We replicated the association between the rs2071473 genotype and TAP2 expression by using GTEx data and demonstrated that TAP2 is expressed by decidual stromal cells at the maternal-fetal interface. Next, we showed that rs2071473 is located within a progesterone-responsive cis-regulatory element that functions as a repressor with the T allele and an enhancer with the C allele. Remarkably, we found that this polymorphism arose before the divergence of modern and archaic humans, segregates at intermediate to high frequencies across human populations, and has genetic signatures of long-term balancing selection. This variant has also previously been identified in genome-wide association studies of immune-related disease, suggesting that both alleles are maintained as a result of antagonistic pleiotropy.

Genome-Wide Association Mapping for Female Infertility in Inbred Mice

The genetic factors underlying female infertility in humans are only partially understood. Here, we performed a genome-wide association study of female infertility in 25 inbred mouse strains by using publicly available SNP data. As a result, a total of four SNPs were identified after chromosome-wise multiple test correction. The first SNP rs29972765 is located in a gene desert on chromosome 18, about 72 kb upstream of Skor2 (SKI family transcriptional corepressor 2). The second SNP rs30415957 resides in the intron of Plce1 (phospholipase C epsilon 1). The remaining two SNPs (rs30768258 and rs31216810) are close to each other on chromosome 19, in the vicinity of Sorbs1 (sorbin and SH3 domain containing 1). Using quantitative RT-PCR, we found that Sorbs1 is highly expressed in the mouse uterus during embryo implantation. Knockdown of Sorbs1 by siRNA attenuates the induction of differentiation marker gene Prl8a2 (decidual prolactin-related protein) in an in vitro model of decidualization using mouse endometrial stromal cells, suggesting that Sorbs1 may be a potential candidate gene for female infertility in mice. Our results may represent an opportunity to further understand female infertility in humans.

Ovarian Physiology and GWAS: Biobanks, Biology, and Beyond

Ovarian function is central to female fertility, and several genome-wide association studies (GWAS) have been carried out to elucidate the genetic background of traits and disorders that reflect and affect ovarian physiology. While GWAS have been successful in reporting numerous genetic associations and highlighting involved pathways relevant to reproductive aging, for ovarian disorders, such as premature ovarian insufficiency and polycystic ovary syndrome, research has lagged behind due to insufficient study sample size. Novel approaches to study design and analysis methods that help to fit GWAS findings into biological context will improve our knowledge about genetics governing ovarian function in fertility and disease, and provide input for clinical tools and better patient management.