Pharmacogenomics: Driving Personalized Medicine.

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

Time-Varying Exposures and Miscarriage: A Comparison of Statistical Models Through Simulation.

Epidemiologists face a unique challenge in measuring risk relationships involving time-varying exposures in early pregnancy. Each week in early pregnancy is distinct in its contribution to fetal development, and this period is commonly characterized by shifts in maternal behavior and, consequently, exposures. In this simulation study, we used alcohol as an example of an exposure that often changes during early pregnancy and miscarriage as an outcome affected by early exposures. Data on alcohol consumption patterns from more than 5,000 women in the Right From the Start cohort study (United States, 2000-2012) informed measures of the prevalence of alcohol exposure, the distribution of gestational age at cessation of alcohol use, and the likelihood of miscarriage by week of gestation. We then compared the bias and precision of effect estimates and statistical power from 5 different modeling approaches in distinct simulated relationships. We demonstrate how the accuracy and precision of effect estimates depended on alignment between model assumptions and the underlying simulated relationship. Approaches that incorporated data about patterns of exposure were more powerful and less biased than simpler models when risk depended on timing or duration of exposure. To uncover risk relationships in early pregnancy, it is critical to carefully define the role of exposure timing in the underlying causal hypothesis.

Development and Validation of a Model to Predict Neonatal Abstinence Syndrome.

OBJECTIVES: To develop and validate clinical risk prediction tools for neonatal abstinence syndrome (NAS). STUDY DESIGN: We developed prediction models for NAS based on a set of 30 demographic and antenatal exposure covariates collected during pregnancy. Data (outpatient prescription, vital, and administrative records), were obtained from enrollees in the Tennessee Medicaid Program from 2009 to 2014. Models were created using logistic regression and backward selection based on improvement in the Akaike information criterion, and internally validated using bootstrap cross-validation. RESULTS: A total of 218 020 maternal and infant dyads met inclusion criteria, of whom 3208 infants were diagnosed with NAS. The general population model included age, hepatitis C virus infection, days of opioid used by type, number of cigarettes used daily, and the following medications used in the last 30 day of pregnancy: bupropion, antinausea medicines, benzodiazepines, antipsychotics, and gabapentin. Infant characteristics included birthweight, small for gestational age, and infant sex. A high-risk model used a smaller number of predictive variables. Both models discriminated well with an area under the curve of 0.89 and were well-calibrated for low-risk infants. CONCLUSIONS: We developed 2 predictive models for NAS based on demographics and antenatal exposure during the last 30 days of pregnancy that were able to risk stratify infants at risk of developing the syndrome.

Week-by-week alcohol consumption in early pregnancy and spontaneous abortion risk: a prospective cohort study.

BACKGROUND: Half of women use alcohol in the first weeks of gestation, but most stop once pregnancy is detected. The relationship between timing of alcohol use cessation in early pregnancy and spontaneous abortion risk has not been determined. OBJECTIVE: This study aimed to evaluate the association between week-by-week alcohol consumption in early pregnancy and spontaneous abortion. STUDY DESIGN: Participants in Right from the Start, a community-based prospective pregnancy cohort, were recruited from 8 metropolitan areas in the United States (2000-2012). In the first trimester, participants provided information about alcohol consumed in the prior 4 months, including whether they altered alcohol use; date of change in use; and frequency, amount, and type of alcohol consumed before and after change. We assessed the association between spontaneous abortion and week of alcohol use, cumulative weeks exposed, number of drinks per week, beverage type, and binge drinking. RESULTS: Among 5353 participants, 49.7% reported using alcohol during early pregnancy and 12.0% miscarried. Median gestational age at change in alcohol use was 29 days (interquartile range, 15-35 days). Alcohol use during weeks 5 through 10 from last menstrual period was associated with increased spontaneous abortion risk, with risk peaking for use in week 9. Each successive week of alcohol use was associated with an 8% increase in spontaneous abortion relative to those who did not drink (adjusted hazard ratio, 1.08; 95% confidence interval, 1.04-1.12). This risk is cumulative. In addition, risk was not related to number of drinks per week, beverage type, or binge drinking. CONCLUSION: Each additional week of alcohol exposure during the first trimester increases risk of spontaneous abortion, even at low levels of consumption and when excluding binge drinking.

Uterine fibroids and risk of preterm birth by clinical subtypes: a prospective cohort study.

BACKGROUND: Fibroids are present in approximately one in ten pregnancies and are inconsistently linked with preterm birth. We sought to determine the association between fibroids and preterm birth in a prospective cohort with standardized research ultrasounds for characterizing fibroids in early pregnancy while accounting for the clinical paths that precede preterm birth. METHODS: Participants who were pregnant or planning a pregnancy were recruited from communities in three states between 2000 and 2012. Members of this prospective cohort had a research ultrasound in the first trimester to establish pregnancy dating and to record detailed information about the presence, size, number, and location of fibroids. Baseline information from time of enrollment and a detailed first trimester interview contributed key information about candidate confounders. Birth outcomes, including clinical classification of type of preterm birth (preterm labor, preterm premature rupture of membranes, and medically indicated preterm birth) were cross-validated from participant report, labor and delivery records, and birth certificate data. RESULTS: Among 4,622 women with singleton pregnancies, 475 had at least one fibroid (10.3%) and 352 pregnancies resulted in preterm birth (7.6%). Prevalence of fibroids was similar for women with preterm and term births (10.2% vs. 10.3%). Fibroids were not associated with increased risk of preterm birth after taking into account confounding (risk ratio adjusted for race/ethnicity and maternal age, 0.88; 95% confidence interval, 0.62-1.24) nor any clinical subtype of preterm birth. No fibroid characteristic or combination of characteristics was associated with risk. CONCLUSIONS: If fibroids increase risk of preterm birth, the effect is substantially smaller than previous estimates. Given lack of effect in a large population of women from the general population, rather than higher risk academic tertiary populations previously most studied, we encourage a reconsideration of the clinical impression that presence of fibroids is a major risk factor for preterm birth.

The Effect of a General Healthy Lifestyle Intervention Delivered Around Pregnancy on Gestational Weight Gain and Infant Growth.

OBJECTIVES: A life-course perspective emphasizes healthy behaviors before, during, and after pregnancy to support a multi-generational risk reduction in obesity for mothers and infants. Optimal timing, content, and dose of such interventions is not well defined. METHODS: We conducted a nested cohort within a randomized trial to evaluate whether a healthy lifestyle intervention around pregnancy led to a "spill-over effect," including a healthier rate (kg/week) of maternal gestational weight gain, and infant growth during the first year. Study enrollment began in 2012, follow-up data collection completed in 2018, and the data were analyzed in 2019. The intervention focused on healthy maternal diet and physical activity but not pregnancy weight or infant feeding. Outcome data were abstracted from electronic medical records. RESULTS: Of the 165 women who became pregnant, 114 enrolled in the nested cohort. The average pre-pregnancy BMI was 29.6 (SD 5.1) kg/m2. Mixed effects models suggested clinically insignificant differences in both the rate of gestational weight gain (-0.02 kg/week; 95% CI -0.09, 0.06) and the rate of infant growth (difference at 1 year: -0.002 kg/cm; 95% CI -0.009, 0.005). CONCLUSIONS FOR PRACTICE: A behavioral intervention that focused on overall maternal health delivered in the time around pregnancy did not result in a "spill-over effect" on healthy gestational weight gain or healthy infant growth during the first year of life. TRIAL REGISTRATION: This study is registered at www.clinicaltrials.gov NCT01316653.

African genetic ancestry interacts with body mass index to modify risk for uterine fibroids.

Race, specifically African ancestry, and obesity are important risk factors for uterine fibroids, and likely interact to provide the right conditions for fibroid growth. However, existing studies largely focus on the main-effects rather than their interaction. Here, we firstly provide evidence for interaction between categories of body mass index (BMI) and reported-race in relation to uterine fibroids. We then investigate whether the association between inferred local European ancestry and fibroid risk is modified by BMI in African American (AA) women in the Vanderbilt University Medical Center bio-repository (BioVU) (539 cases and 794 controls) and the Coronary Artery Risk Development in Young Adults study (CARDIA, 264 cases and 173 controls). We used multiple logistic regression to evaluate interactions between local European ancestry and BMI in relation to fibroid risk, then performed fixed effects meta-analysis. Statistical significance threshold for local-ancestry and BMI interactions was empirically estimated with 10,000 permutations (p-value = 1.18x10-4). Admixture mapping detected an association between European ancestry and fibroid risk which was modified by BMI (continuous-interaction p-value = 3.75x10-5) around ADTRP (chromosome 6p24); the strongest association was found in the obese category (ancestry odds ratio (AOR) = 0.51, p-value = 2.23x10-5). Evaluation of interaction between genotyped/imputed variants and BMI in this targeted region suggested race-specific interaction, present in AAs only; strongest evidence was found for insertion/deletion variant (6:11946435), again in the obese category (OR = 1.66, p-value = 1.72x10-6). We found nominal evidence for interaction between local ancestry and BMI at a previously reported region in chromosome 2q31-32, which includes COL5A2, and TFPI, an immediate downstream target of ADTRP. Interactions between BMI and SNPs (single nucleotide polymorphisms) found in this region in AA women were also detected in an independent European American population of 1,195 cases and 1,164 controls. Findings from our study provide an example of how modifiable and non-modifiable factors may interact to influence fibroid risk and suggest a biological role for BMI in fibroid etiology.

Gestational Age at Arrest of Development: An Alternative Approach for Assigning Time at Risk in Studies of Time-Varying Exposures and Miscarriage.

The time between arrest of pregnancy development and miscarriage represents a window in which the pregnancy is nonviable and not developing. In effect, the pregnancy loss has already occurred, and additional exposure cannot influence its outcome. However, epidemiologic studies of miscarriage traditionally use gestational age at miscarriage (GAM) to assign time in survival analyses, which overestimates duration of exposure and time at risk. In Right From the Start, a pregnancy cohort study (2000-2012), we characterized the gap between estimated gestational age at arrest of development (GAAD) and miscarriage using transvaginal ultrasound in 500 women recruited from 3 states (North Carolina, Tennessee, and Texas). We compared effect estimates from models using GAAD with GAM to assign time at risk through a simulation study of several exposure patterns with varying effect sizes. The median gap between GAAD and miscarriage was 23 days (interquartile range, 15-32). Use of GAAD decreased the bias and variance of the estimated association for time-varying exposures, whereas half the time using GAM led to estimates that differed from the true effect by more than 20%. Using GAAD to assign time at risk should result in more accurate and consistent characterization of miscarriage risk associated with time-varying exposures.

Alcohol Use in Pregnancy and Miscarriage: A Systematic Review and Meta-Analysis.

To systematically review and critically evaluate studies reporting alcohol exposure during pregnancy and miscarriage. We searched PubMed, EMBASE, PsycINFO, and ProQuest Theses for publications from January 1970 to January 2019. We identified studies about alcohol exposure during pregnancy and miscarriage. Information about study population, alcohol exposure assessment, outcome definition, covariates, and measures of association was collected. We assessed study quality using an adapted Newcastle-Ottawa Scale. Data were abstracted by 2 investigators independently. We conducted a random-effects meta-analysis to calculate the association between alcohol exposure and miscarriage risk and performed subgroup analyses to determine robustness of results to study differences. For studies reporting dose-specific effects, a pooled dose-response association was estimated using generalized least squares regression with and without restricted cubic spline terms for number of drinks consumed per week. Of 2,164 articles identified, 24 were eligible for inclusion. Meta-analysis of data from 231,808 pregnant women finds those exposed to alcohol during pregnancy have a greater risk of miscarriage compared to those who abstained (odds ratio [OR] 1.19, 95% confidence intervals [CI] 1.12, 1.28). Estimates did not vary by study design, study country, or method of alcohol ascertainment. For alcohol use of 5 or fewer drinks per week, each additional drink per week was associated with a 6% increase in miscarriage risk (OR 1.06, 95% CI 1.01, 1.10). Common study limitations reflect challenges inherent to this research, including difficulty recruiting participants early enough in pregnancy to observe miscarriage and collecting and quantifying information about alcohol consumption during pregnancy that accurately reflects use. This review provides evidence that alcohol consumption during pregnancy is associated with a dose-mediated increase in miscarriage risk. Future studies evaluating change in alcohol use in pregnancy are needed to provide insight into how alcohol consumption prior to pregnancy recognition impacts risk.

Expression Quantitative Trait Locus Mapping Studies in Mid-secretory Phase Endometrial Cells Identifies HLA-F and TAP2 as Fecundability-Associated Genes.

Fertility traits in humans are heritable, however, little is known about the genes that influence reproductive outcomes or the genetic variants that contribute to differences in these traits between individuals, particularly women. To address this gap in knowledge, we performed an unbiased genome-wide expression quantitative trait locus (eQTL) mapping study to identify common regulatory (expression) single nucleotide polymorphisms (eSNPs) in mid-secretory endometrium. We identified 423 cis-eQTLs for 132 genes that were significant at a false discovery rate (FDR) of 1%. After pruning for strong LD (r2 >0.95), we tested for associations between eSNPs and fecundability (the ability to get pregnant), measured as the length of the interval to pregnancy, in 117 women. Two eSNPs were associated with fecundability at a FDR of 5%; both were in the HLA region and were eQTLs for the TAP2 gene (P = 1.3x10-4) and the HLA-F gene (P = 4.0x10-4), respectively. The effects of these SNPs on fecundability were replicated in an independent sample. The two eSNPs reside within or near regulatory elements in decidualized human endometrial stromal cells. Our study integrating eQTL mapping in a primary tissue with association studies of a related phenotype revealed novel genes and associated alleles with independent effects on fecundability, and identified a central role for two HLA region genes in human implantation success.

The CHRNA5/CHRNA3/CHRNB4 Nicotinic Receptor Regulome: Genomic Architecture, Regulatory Variants, and Clinical Associations.

Functionally related genes often cluster into a genome region under coordinated regulation, forming a local regulome. To understand regulation of the CHRNA5/CHRNA3/CHRNB4 nicotinic receptor gene cluster, we integrate large-scale RNA expression data (brain and peripheral) from GTEx (Genotype Tissue Expression), clinical associations (GRASP), and linkage disequilibrium data (1000 Genomes) to find candidate SNPs representing independent regulatory variants. CHRNA3, CHRNA5, CHRNB4 mRNAs, and a well-expressed CHRNA5 antisense RNA (RP11-650L12.2) are co-expressed in many human tissues, suggesting common regulatory elements. The CHRNA5 enhancer haplotype tagged by rs880395 not only increases CHRNA5 mRNA expression in all tissues, but also enhances RP11-650L12.2 and CHRNA3 expression, suggesting DNA looping to multiple promoters. However, in nucleus accumbens and putamen, but not other brain regions, CHRNA3 expression associates uniquely with a haplotype tagged by rs1948 (located in the CHRNB4 3'UTR). Haplotype/diplotype analysis of rs880395 and rs1948 plus rs16969968 (a nonsynonymous CHRNA5 risk variant) in GWAS (COGEND, UW-TTURC, SAGE) yields a nicotine dependence risk profile only partially captured by rs16969968 alone. An example of local gene clusters, this nicotinic regulome is controlled by complex genetic variation, with broad implications for interpreting GWAS.

Prospective Cohort Study of Uterine Fibroids and Miscarriage Risk.

We sought to determine the relationship of fibroids to pregnancy loss in a prospective cohort in which fibroid status was uniformly documented in early pregnancy. Participants had an intake interview, transvaginal ultrasonography, computer-assisted telephone interview, and follow-up assessment of outcomes. We recruited diverse participants for the Right From the Start study from 8 metropolitan areas in 3 states in the United States during 2000-2012. Participants were at least 18 years of age, trying to become pregnant or at less than 12 weeks' gestation, not using fertility treatments, fluent in English or Spanish, and available for telephone interviews. Miscarriage was defined as loss before 20 weeks' gestation. Fibroid presence, number, type, and volume were assessed using standardized ultrasonography methods. We used proportional hazards models to estimate associations. Among 5,512 participants, 10.4% had at least 1 fibroid, and 10.8% experienced a miscarriage. Twenty-three percent had experienced a prior miscarriage and 52% prior births. Presence of fibroids was associated with miscarriage in models without adjustments. Adjusting for key confounders indicated no increase in risk (adjusted hazard ratio = 0.83, 95% confidence interval: 0.63, 1.08). No characteristic of fibroids was associated with risk. Prior evidence attributing miscarriage to fibroids is potentially biased. These findings imply that surgical removal of fibroids to reduce risk of miscarriage deserves careful scrutiny.

A multi-stage genome-wide association study of uterine fibroids in African Americans.

Uterine fibroids are benign tumors of the uterus affecting up to 77% of women by menopause. They are the leading indication for hysterectomy, and account for $34 billion annually in the United States. Race/ethnicity and age are the strongest known risk factors. African American (AA) women have higher prevalence, earlier onset, and larger and more numerous fibroids than European American women. We conducted a multi-stage genome-wide association study (GWAS) of fibroid risk among AA women followed by in silico genetically predicted gene expression profiling of top hits. In Stage 1, cases and controls were confirmed by pelvic imaging, genotyped and imputed to 1000 Genomes. Stage 2 used self-reported fibroid and GWAS data from 23andMe, Inc. and the Black Women's Health Study. Associations with fibroid risk were modeled using logistic regression adjusted for principal components, followed by meta-analysis of results. We observed a significant association among 3399 AA cases and 4764 AA controls at rs739187 (risk-allele frequency = 0.27) in CYTH4 (OR (95% confidence interval) = 1.23 (1.16-1.30), p value = 7.82 × 10-9). Evaluation of the genetic association results with MetaXcan identified lower predicted gene expression of CYTH4 in thyroid tissue as significantly associated with fibroid risk (p value = 5.86 × 10-8). In this first multi-stage GWAS for fibroids among AA women, we identified a novel risk locus for fibroids within CYTH4 that impacts gene expression in thyroid and has potential biological relevance for fibroids.

Erratum to: A multi-stage genome-wide association study of uterine fibroids in African Americans.

The article "A multi-stage genome-wide association study of uterine fibroids in African Americans", written by Jacklyn N. Hellwege, was originally published Online First without open access. After publication in volume 136, issue 10, page 1363-1373 the author decided to opt for Open Choice and to make the article an open access publication. Therefore, the copyright of the article has been changed to

Obesity and pelvic organ prolapse: a systematic review and meta-analysis of observational studies.

BACKGROUND: Studies evaluating the association between obesity and pelvic organ prolapse report estimates that range from negative to positive associations. Heterogeneous definitions for pelvic organ prolapse and variable choices for categorizing obesity measures have made it challenging to conduct meta-analysis. OBJECTIVE: We systematically evaluated evidence to provide quantitative summaries of association between degrees of obesity and pelvic organ prolapse, and identify sources of heterogeneity. STUDY DESIGN: We searched for all indexed publications relevant to pelvic organ prolapse up until June 18, 2015, in PubMed/MEDLINE to identify analytical observational studies published in English that reported risk ratios (relative risk, odds ratio, or hazard ratio) for body mass index categories in relation to pelvic organ prolapse. Random effects meta-analyses were conducted to report associations with pelvic organ prolapse for overweight and obese body mass index categories compared with women in the normal-weight category (referent: body mass index <25 kg/m2). RESULTS: Of the 70 studies that reported evidence on obesity and pelvic organ prolapse, 22 eligible studies provided effect estimates for meta-analysis of the overweight and obese body mass index categories. Compared with the referent category, women in the overweight and obese categories had meta-analysis risk ratios of at least 1.36 (95% confidence interval, 1.20-1.53) and at least 1.47 (95% confidence interval, 1.35-1.59), respectively. Subgroup analyses showed effect estimates for objectively measured clinically significant pelvic organ prolapse were higher than for self-reported pelvic organ prolapse. Other potential sources of heterogeneity included proportion of postmenopausal women in study and reported study design. CONCLUSION: Overweight and obese women are more likely to have pelvic organ prolapse compared with women with body mass index in the normal range. The finding that the associations for obesity measures were strongest for objectively measured, clinically significant pelvic organ prolapse further strengthens this evidence. However, prospective investigations evaluating obesity and pelvic organ prolapse are few.

Evaluating the role of race and medication in protection of uterine fibroids by type 2 diabetes exposure.

BACKGROUND: Uterine fibroids (UF) affect 77% of women by menopause, and account for $9.4 billion in annual healthcare costs. Type-2-diabetes (T2D) has inconsistently associated with protection from UFs in prior studies. To further evaluate the relationship between T2D and UFs we tested for association between T2D and UF risk in a large clinical population as well as the potential differences due to T2D medications and interaction with race. METHODS: This nested case-control study is derived from a clinical cohort. Our outcome was UF case-control status and our exposure was T2D. UF outcomes and T2D exposure were classified using validated electronic medical record (EMR) algorithms. Logistic regression, adjusted for covariates, was used to model the association between T2D diagnosis and UF risk. Secondary analyses were performed evaluating the interaction between T2D exposure and race and stratifying T2D exposed subjects by T2D medication being taken. RESULTS: We identified 3,789 subjects with UF outcomes (608 UF cases and 3,181 controls), 714 were diabetic and 3,075 were non-diabetic. We observed a nominally significant interaction between T2D exposure and race in adjusted models (interaction p = 0.083). Race stratified analyses demonstrated more protection by T2D exposure on UF risk among European Americans (adjusted odds ratio [aOR] = 0.50, 95% CI 0.35 to 0.72) than African Americans (aOR = 0.76, 95% CI 0.50 to 1.17). We also observed a protective effect by T2D regardless of type of T2D medication being taken, with slightly more protection among subjects on insulin treatments (European Americans aOR = 0.42, 95% CI 0.26 to 0.68; African Americans aOR = 0.60, 95% CI 0.36 to 1.01). CONCLUSIONS: These data, conducted in a large population of UF cases and controls, support prior studies that have found a protective association between diabetes presence and UF risk and is further modified by race. Protection from UFs by T2D exposure was observed regardless of medication type with slightly more protection among insulin users. Further mechanistic research in larger cohorts is necessary to reconcile the potential role of T2D in UF risk.

Non-linear interactions between candidate genes of myocardial infarction revealed in mRNA expression profiles.

BACKGROUND: Alterations in gene expression are key events in disease etiology and risk. Poor reproducibility in detecting differentially expressed genes across studies suggests individual genes may not be sufficiently informative for complex diseases, such as myocardial infarction (MI). Rather, dysregulation of the 'molecular network' may be critical for pathogenic processes. Such a dynamic network can be built from pairwise non-linear interactions. RESULTS: We investigate non-linear interactions represented in mRNA expression profiles that integrate genetic background and environmental factors. Using logistic regression, we test the association of individual GWAS-based candidate genes and non-linear interaction terms (between these mRNA expression levels) with MI. Based on microarray data in CATHGEN (CATHeterization in GENetics) and FHS (Framingham Heart Study), we find individual genes and pairs of mRNAs, encoded by 41 MI candidate genes, with significant interaction terms in the logistic regression model. Two pairs replicate between CATHGEN and FHS (CNNM2|GUCY1A3 and CNNM2|ZEB2). Analysis of RNAseq data from GTEx (Genotype-Tissue Expression) shows that 20 % of these disease-associated RNA pairs are co-expressed, further prioritizing significant interactions. Because edges in sparse co-expression networks formed solely by the 41 candidate genes are unlikely to represent direct physical interactions, we identify additional RNAs as links between network pairs of candidate genes. This approach reveals additional mRNAs and interaction terms significant in the context of MI, for example, the path CNNM2|ACSL5|SCARF1|GUCY1A3, characterized by the common themes of magnesium and lipid processing. CONCLUSIONS: The results of this study support a role for non-linear interactions between genes in MI and provide a basis for further study of MI systems biology. mRNA expression profiles encoded by a limited number of candidate genes yield sparse networks of MI-relevant interactions that can be expanded to include additional candidates by co-expression analysis. The non-linear interactions observed here inform our understanding of the clinical relevance of gene-gene interactions in the pathophysiology of MI, while providing a new strategy in developing clinical biomarker panels.

The Relationship between Total Fibroid Burden and First Trimester Bleeding and Pain.

BACKGROUND: Few studies comment on the association between fibroids and symptoms among pregnant women. These studies generally are retrospective and do not to assess the influence of number of tumours or their volume on risk of symptoms. METHODS: Right from the Start is a prospective cohort that enrolled pregnant women from the southeastern USA between 2000 and 2012. In the first trimester, all participants had standardised ultrasounds to determine the presence or absence of fibroids. Symptoms were queried in a telephone survey. We used polytomous logistic regression to model odds of bleeding, pain, or both symptoms in relation to increasing total fibroid number and volume among white and black women. RESULTS: Among 4509 participants, the prevalence of fibroids was 11%. Among those reporting symptoms (70%), 11% reported only bleeding, 59% reported only pain, and 30% reported both symptoms. After adjusting for age, race, parity, hypertension, smoking, alcohol use, and study site, increasing number of fibroids was associated with pain [odds ratio (OR) 1.16, 95% confidence interval (CI) 1.00, 1.33] and both symptoms [OR 1.25, 95% CI 1.08, 1.45] but not with bleeding among all women. Fibroid volume was not associated with symptoms among black women, but white women with the smallest fibroid volumes were more likely to report both symptoms than those without fibroids [OR 1.79, 95% CI 1.17, 2.72]. CONCLUSIONS: Very large tumours are not requisite for experiencing symptoms, as small fibroids and increasing number of tumours are associated with pain and both symptoms.

Analyzing allele specific RNA expression using mixture models.

BACKGROUND: Measuring allele-specific RNA expression provides valuable insights into cis-acting genetic and epigenetic regulation of gene expression. Widespread adoption of high-throughput sequencing technologies for studying RNA expression (RNA-Seq) permits measurement of allelic RNA expression imbalance (AEI) at heterozygous single nucleotide polymorphisms (SNPs) across the entire transcriptome, and this approach has become especially popular with the emergence of large databases, such as GTEx. However, the existing binomial-type methods used to model allelic expression from RNA-seq assume a strong negative correlation between reference and variant allele reads, which may not be reasonable biologically. RESULTS: Here we propose a new strategy for AEI analysis using RNA-seq data. Under the null hypothesis of no AEI, a group of SNPs (possibly across multiple genes) is considered comparable if their respective total sums of the allelic reads are of similar magnitude. Within each group of "comparable" SNPs, we identify SNPs with AEI signal by fitting a mixture of folded Skellam distributions to the absolute values of read differences. By applying this methodology to RNA-Seq data from human autopsy brain tissues, we identified numerous instances of moderate to strong imbalanced allelic RNA expression at heterozygous SNPs. Findings with SLC1A3 mRNA exhibiting known expression differences are discussed as examples. CONCLUSION: The folded Skellam mixture model searches for SNPs with significant difference between reference and variant allele reads (adjusted for different library sizes), using information from a group of "comparable" SNPs across multiple genes. This model is particularly suitable for performing AEI analysis on genes with few heterozygous SNPs available from RNA-seq, and it can fit over-dispersed read counts without specifying the direction of the correlation between reference and variant alleles.