Genome-wide association and epidemiological analyses reveal common genetic origins between uterine leiomyomata and endometriosis.

Uterine leiomyomata (UL) are the most common neoplasms of the female reproductive tract and primary cause for hysterectomy, leading to considerable morbidity and high economic burden. Here we conduct a GWAS meta-analysis in 35,474 cases and 267,505 female controls of European ancestry, identifying eight novel genome-wide significant (P < 5 × 10-8) loci, in addition to confirming 21 previously reported loci, including multiple independent signals at 10 loci. Phenotypic stratification of UL by heavy menstrual bleeding in 3409 cases and 199,171 female controls reveals genome-wide significant associations at three of the 29 UL loci: 5p15.33 (TERT), 5q35.2 (FGFR4) and 11q22.3 (ATM). Four loci identified in the meta-analysis are also associated with endometriosis risk; an epidemiological meta-analysis across 402,868 women suggests at least a doubling of risk for UL diagnosis among those with a history of endometriosis. These findings increase our understanding of genetic contribution and biology underlying UL development, and suggest overlapping genetic origins with endometriosis.

A genome-wide association study identifies variants in KCNIP4 associated with ACE inhibitor-induced cough.

The most common side effect of angiotensin-converting enzyme inhibitor (ACEi) drugs is cough. We conducted a genome-wide association study (GWAS) of ACEi-induced cough among 7080 subjects of diverse ancestries in the Electronic Medical Records and Genomics (eMERGE) network. Cases were subjects diagnosed with ACEi-induced cough. Controls were subjects with at least 6 months of ACEi use and no cough. A GWAS (1595 cases and 5485 controls) identified associations on chromosome 4 in an intron of KCNIP4. The strongest association was at rs145489027 (minor allele frequency=0.33, odds ratio (OR)=1.3 (95% confidence interval (CI): 1.2-1.4), P=1.0 × 10(-8)). Replication for six single-nucleotide polymorphisms (SNPs) in KCNIP4 was tested in a second eMERGE population (n=926) and in the Genetics of Diabetes Audit and Research in Tayside, Scotland (GoDARTS) cohort (n=4309). Replication was observed at rs7675300 (OR=1.32 (1.01-1.70), P=0.04) in eMERGE and at rs16870989 and rs1495509 (OR=1.15 (1.01-1.30), P=0.03 for both) in GoDARTS. The combined association at rs1495509 was significant (OR=1.23 (1.15-1.32), P=1.9 × 10(-9)). These results indicate that SNPs in KCNIP4 may modulate ACEi-induced cough risk.

Epiregulin (EREG) and human V-ATPase (TCIRG1): genetic variation, ethnicity and pulmonary tuberculosis susceptibility in Guinea-Bissau and The Gambia.

We analyzed two West African samples (Guinea-Bissau: n=289 cases and 322 controls; The Gambia: n=240 cases and 248 controls) to evaluate single-nucleotide polymorphisms (SNPs) in Epiregulin (EREG) and V-ATPase (T-cell immune regulator 1 (TCIRG1)) using single and multilocus analyses to determine whether previously described associations with pulmonary tuberculosis (PTB) in Vietnamese and Italians would replicate in African populations. We did not detect any significant single locus or haplotype associations in either sample. We also performed exploratory pairwise interaction analyses using Visualization of Statistical Epistasis Networks (ViSEN), a novel method to detect only interactions among multiple variables, to elucidate possible interaction effects between SNPs and demographic factors. Although we found no strong evidence of marginal effects, there were several significant pairwise interactions that were identified in either the Guinea-Bissau or the Gambian samples, two of which replicated across populations. Our results indicate that the effects of EREG and TCIRG1 variants on PTB susceptibility, to the extent that they exist, are dependent on gene-gene interactions in West African populations as detected with ViSEN. In addition, epistatic effects are likely to be influenced by inter- and intra-population differences in genetic or environmental context and/or the mycobacterial lineages causing disease.

Parkinson disease loci in the mid-western Amish.

Previous evidence has shown that Parkinson disease (PD) has a heritable component, but only a small proportion of the total genetic contribution to PD has been identified. Genetic heterogeneity complicates the verification of proposed PD genes and the identification of new PD susceptibility genes. Our approach to overcome the problem of heterogeneity is to study a population isolate, the mid-western Amish communities of Indiana and Ohio. We performed genome-wide association and linkage analyses on 798 individuals (31 with PD), who are part of a 4,998 member pedigree. Through these analyses, we identified a region on chromosome 5q31.3 that shows evidence of association (p value < 1 × 10(-4)) and linkage (multipoint HLOD = 3.77). We also found further evidence of linkage on chromosomes 6 and 10 (multipoint HLOD 4.02 and 4.35 respectively). These data suggest that locus heterogeneity, even within the Amish, may be more extensive than previously appreciated.

First-trimester bleeding characteristics associate with increased risk of preterm birth: data from a prospective pregnancy cohort.

BACKGROUND: Prior evidence linking first-trimester bleeding with preterm birth (PTB, <37 weeks gestation) risk has been inconsistent and may be biased by subject selection and/or incomplete documentation of bleeding episodes for all participants. Prior studies have not carefully examined the role of bleeding characteristics in PTB risk. In the present study, we estimate the association between first-trimester bleeding and PTB in a non-clinical prospective cohort and test whether bleeding characteristics better predict risk. METHODS: Women were enrolled in Right from the Start (2000-2009), a prospective pregnancy cohort. Data about bleeding and bleeding characteristics were examined with logistic regression to assess association with PTB. RESULTS: Among 3978 pregnancies 344 were PTB and 3634 term. Bleeding was reported by 986 (26%) participants. After screening candidate confounders, only multiple gestations remained in the model. Bleeding associated with PTB [odds ratio (OR)(adjusted) = 1.40, 95% confidence interval (CI) 1.09-1.80]. Risk did not vary by race/ethnicity. Compared with non-bleeders, PTB risk was higher for bleeding with red color (OR(adjusted) = 1.92, 95% CI, 1.32-2.82), for heavy episodes (OR(adjusted) = 2.40, 95% CI 1.18-4.88) and long duration (OR(adjusted) = 1.67, 95% CI 1.17-2.38). CONCLUSIONS: Bleeding associated with PTB was not confounded by common risk factors for bleeding or PTB. PTB risk was greatest for women with heavy bleeding episodes with long duration and red color and would suggest that combining women with different bleeding characteristics may affect the accuracy of risk assessment. These data suggest a candidate etiologic pathway for PTB and warrant further investigation of the biologic mechanisms.

Synopsis of preterm birth genetic association studies: the preterm birth genetics knowledge base (PTBGene).

AIM: Our goal wasto produce a field synopsis of genetic associations with preterm birth and to set up a publicly available online database summarizing the data. METHODS: We performed a systematic review and meta-analyses to identify genetic associations with preterm birth. We have set up a publicly available online database of genetic association data on preterm birth called PTBGene (http://ric.einstein.yu.edu/ptbgene/index.html) and report on a structured synopsis thereof as of December 1, 2008. RESULTS: Data on 189 polymorphisms in 84 genes have been included and 36 meta-analyses have been performed. Five gene variants (4 in maternal DNA, one in newborn DNA) have shown nominally significant associations, but all have weak epidemiological credibility. CONCLUSION: After publishing this field synopsis, the PTBGene database will be regularly updated to keep track of the evolving evidence base of genetic factors in preterm birth with the goal of promoting knowledge sharing and multicenter collaboration among preterm birth research groups.