Background Polycystic ovary syndrome (PCOS) is a common, complex genetic disorder affecting up to 15% of reproductive-age women worldwide, depending on the diagnostic criteria applied. These diagnostic criteria are based on expert opinion and have been the subject of considerable controversy. The phenotypic variation observed in PCOS is suggestive of an underlying genetic heterogeneity, but a recent meta-analysis of European ancestry PCOS cases found that the genetic architecture of PCOS defined by different diagnostic criteria was generally similar, suggesting that the criteria do not identify biologically distinct disease subtypes. We performed this study to test the hypothesis that there are biologically relevant subtypes of PCOS. Methods and findings Using biochemical and genotype data from a previously published PCOS genome-wide association study (GWAS), we investigated whether there were reproducible phenotypic subtypes of PCOS with subtype-specific genetic associations. Unsupervised hierarchical cluster analysis was performed on quantitative anthropometric, reproductive, and metabolic traits in a genotyped cohort of 893 PCOS cases (median and interquartile range [IQR]: age = 28 [25-32], body mass index [BMI] = 35.4 [28.2-41.5]). The clusters were replicated in an independent, ungenotyped cohort of 263 PCOS cases (median and IQR: age = 28 [24-33], BMI = 35.7 [28.4-42.3]). The clustering revealed 2 distinct PCOS subtypes: a "reproductive" group (21%-23%), characterized by higher luteinizing hormone (LH) and sex hormone binding globulin (SHBG) levels with relatively low BMI and insulin levels, and a "metabolic" group

The duration of pregnancy is influenced by fetal and maternal genetic and non-genetic factors. Here we report a fetal genome-wide association meta-analysis of gestational duration, and early preterm, preterm, and postterm birth in 84,689 infants. One locus on chromosome 2q13 is associated with gestational duration; the association is replicated in 9,291 additional infants (combined P = 3.96 × 10 −14 ). Analysis of 15,588 mother-child pairs shows that the association is driven by fetal rather than maternal genotype. Functional experiments show that the lead SNP, rs7594852, alters the binding of the HIC1 transcriptional repressor. Genes at the locus include several interleukin 1 family members with roles in pro-inflammatory pathways that are central to the process of parturition. Further understanding of the underlying mechanisms will be of great public health importance, since giving birth either before or after the window of term gestation is associated with increased morbidity and mortality.

OBJECTIVES: Symptoms are inconsistently associated with esophageal motor findings on high-resolution manometry (HRM). We aimed to evaluate predictors of dysphagia severity, including esophageal hypervigilance and visceral anxiety, among patients evaluated with HRM. METHODS: Adult patients undergoing HRM at 4 academic medical centers (United States and France) were prospectively evaluated. HRM was completed and analyzed per the Chicago Classification v3.0. Validated symptom scores, including the Brief Esophageal Dysphagia Questionnaire and Esophageal Hypervigilance and Anxiety Scale, were completed at the time of HRM. RESULTS: Two hundred thirty-six patients, aged 18–85 (mean 53) years, 65% female, were included. Approximately 59 (25%) patients had a major motor disorder on HRM: 19 achalasia, 24 esophagogastric junction outflow obstruction, 12 absent contractility, and 4 jackhammer. Approximately 177 (75%) patients did not have a major motor disorder: 71 ineffective esophageal motility and 106 normal motility. Having a major motor disorder was a significant predictor of dysphagia severity (R2adj = 0.049, P < 0.001), but the Esophageal Hypervigilance and Anxiety Scale score carried a predictive relationship of Brief Esophageal Dysphagia Questionnaire that was 2-fold higher than having a major motor disorder: R2adj = 0.118 (P < 0.001). This finding remained when evaluated by the major motor disorder group. HRM metrics were nonsignificant. DISCUSSION: In a prospective, international multicenter study, we found that esophageal hypervigilance and visceral anxiety were the strongest predictors of dysphagia severity among patients evaluated with HRM. Thus, an assessment of esophageal hypervigilance and visceral anxiety is important to incorporate when evaluating symptom severity in clinical practice and research studies.

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy (GenDIP) Consortium assembled genome-wide association studies (GWAS) of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (p &lt; 5x10−8) with GDM, mapping to/near MTNR1B (p = 4.3x10−54), TCF7L2 (p = 4.0x10−16), CDKAL1 (p = 1.6 × 10−14), CDKN2A-CDKN2B (p = 4.1x10−9) and HKDC1 (p = 2.9x10−8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D; and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomisation analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

The timing of parturition is crucial for neonatal survival and infant health. Yet, its genetic basis remains largely unresolved. We present a maternal genome-wide meta-analysis of gestational duration (n = 195,555), identifying 22 associated loci (24 independent variants) and an enrichment in genes differentially expressed during labor. A meta-analysis of preterm delivery (18,797 cases, 260,246 controls) revealed six associated loci and large genetic similarities with gestational duration. Analysis of the parental transmitted and nontransmitted alleles (n = 136,833) shows that 15 of the gestational duration genetic variants act through the maternal genome, whereas 7 act both through the maternal and fetal genomes and 2 act only via the fetal genome. Finally, the maternal effects on gestational duration show signs of antagonistic pleiotropy with the fetal effects on birth weight: maternal alleles that increase gestational duration have negative fetal effects on birth weight. The present study provides insights into the genetic effects on the timing of parturition and the complex maternal–fetal relationship between gestational duration and birth weight.

The timing of parturition is crucial for neonatal survival and infant health. Yet, its genetic basis remains largely unresolved. We present a maternal genome-wide meta-analysis of the timing of parturition, identifying 22 loci associated with gestational duration (n = 195,555) and 6 with preterm delivery (cases = 18,797, controls = 260,246). We observed modest differences in the genetic effects between gestational duration and preterm delivery, with most loci shared between the two. Analysis of the transmitted and non-transmitted parental alleles (n = 136,833) shows that 15 of the identified variants act through the maternal genome, while nine have fetal or both maternal and fetal effects. We observe a sex-specific genetic link between testosterone (negative) and sex hormone-binding globulin (positive) on the timing of parturition, likely due to pleiotropic effects. Finally, we provide evidence of maternal-fetal antagonistic effects on gestational duration and birth weight: maternal alleles that increase gestational duration have negative effects on birth weight when present in the fetus.

Gene expression is a critical process in biological system that is influenced and modulated by many factors including genetic variation. Expression Quantitative Trait Loci (eQTL) analysis provides a powerful way to understand how genetic variants affect gene expression. For genome wide eQTL analysis, the number of genetic variants and that of genes are large and thus the search space is tremendous. Therefore, eQTL analysis brings about computational and statistical challenges. In this paper, we provide a comprehensive review of recent advances in methods for eQTL analysis in population-based studies. We first present traditional pairwise association methods, which are widely used in human genetics. To account for expression heterogeneity, we investigate the methods for correcting confounding factors. Next, we discuss newly developed statistical learning methods including Lasso-based models. In the conclusion, we provide an overview of future method development in analyzing eQTL associations. Although we focus on human genetics in this review, the methods are applicable to many other organisms.

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy (GenDIP) Consortium assembled genome-wide association studies (GWAS) of diverse ancestry in a total of 5,485 women with GDM and 347,856 without GDM. Through trans-ancestry meta-analysis, we identified five loci with genome-wide significant association (p<5×10-8) with GDM, mapping to/near MTNR1B (p=4.3×10-54), TCF7L2 (p=4.0×10-16), CDKAL1 (p=1.6×10-14), CDKN2A-CDKN2B (p=4.1×10-9) and HKDC1 (p=2.9×10-8). Multiple lines of evidence pointed to genetic contributions to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D; and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomisation analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.