Novel guidelines for the analysis of single nucleotide polymorphisms in disease association studies

How genetic mutations such as Single Nucleotide Polymorphisms (SNPs) affect the risk of contracting a specific disease is still an open question for numerous different medical conditions. Two problems related to SNPs analysis are (i) the selection of computational techniques to discover possible single and multiple SNP associations; and (ii) the size of the latest datasets, which may contain millions of SNPs. In order to find associations between SNPs and diseases, two popular techniques are investigated and enhanced. Firstly, the ‘Transmission Disequilibrium Test’ for familybased analysis is considered. The fixed length of haplotypes provided by this approach represents a possible limit to the quality of the obtained results. For this reason, an adaptation is proposed to select the minimum number of SNPs that are responsible for disease predisposition. Secondly, decision tree algorithms for case-control analysis in situations of unrelated individuals are considered. The application of a single tool may lead to limited analysis of the genetic association to a specific condition. Thus, a novel consensus approach is proposed exploiting the strengths of three different algorithms, ADTree, C4.5 and Id3. Results obtained suggest the new approach achieves improved performance. The recent explosive growth in size of current SNPs databases has highlighted limitations in current techniques. An example is ‘Linkage Disequilibrium’ which identifies redundancy in multiple SNPs. Despite the high accuracies obtained by this method, it exhibits poor scalability for large datasets, which severely impacts on its performance. Therefore, a new fast scalable tool based on ‘Linkage Disequilibrium’ is developed to reduce the size through the measurement and elimination of redundancy between SNPs included in the initial dataset. Experimental evidence validates the potentially improved performance of the new method

Novel guidelines for the analysis of single nucleotide polymorphisms in disease association studies

How genetic mutations such as Single Nucleotide Polymorphisms (SNPs) affect the risk of contracting a specific disease is still an open question for numerous different medical conditions. Two problems related to SNPs analysis are (i) the selection of computational techniques to discover possible single and multiple SNP associations; and (ii) the size of the latest datasets, which may contain millions of SNPs. In order to find associations between SNPs and diseases, two popular techniques are investigated and enhanced. Firstly, the ‘Transmission Disequilibrium Test’ for familybased analysis is considered. The fixed length of haplotypes provided by this approach represents a possible limit to the quality of the obtained results. For this reason, an adaptation is proposed to select the minimum number of SNPs that are responsible for disease predisposition. Secondly, decision tree algorithms for case-control analysis in situations of unrelated individuals are considered. The application of a single tool may lead to limited analysis of the genetic association to a specific condition. Thus, a novel consensus approach is proposed exploiting the strengths of three different algorithms, ADTree, C4.5 and Id3. Results obtained suggest the new approach achieves improved performance. The recent explosive growth in size of current SNPs databases has highlighted limitations in current techniques. An example is ‘Linkage Disequilibrium’ which identifies redundancy in multiple SNPs. Despite the high accuracies obtained by this method, it exhibits poor scalability for large datasets, which severely impacts on its performance. Therefore, a new fast scalable tool based on ‘Linkage Disequilibrium’ is developed to reduce the size through the measurement and elimination of redundancy between SNPs included in the initial dataset. Experimental evidence validates the potentially improved performance of the new method

A comparison of United Kingdom primary care data with other national data sources for monitoring the prevalence of smoking during pregnancy

Background: We aimed to assess the potential usefulness of primary care data for estimating smoking prevalence in pregnancy by comparing the primary care data estimates with those obtained from other data sources. Methods: In The Health Improvement Network (THIN) primary care database we identified pregnant smokers using smoking information recorded during pregnancy. Where this information was missing, we used smoking information recorded prior to pregnancy. We compared annual smoking prevalence from 2000 to 2012 in THIN with measures from the Infant Feeding Survey (IFS), Smoking At Time of Delivery (SATOD), Child Health Systems Programme (CHSP) and Scottish Morbidity Record (SMR). Results: Smoking estimates from THIN data converged with estimates from other sources after 2004, though still do not agree completely. For example, in 2012 smoking prevalence at booking was 11.6% in THIN using data recorded only during pregnancy, compared to 19.6% in SMR data. However, the use of smoking data recorded up to 27 months before conception increased the THIN prevalence to 20.3%, improving the agreement. Conclusion: Under-recording of smoking status during pregnancy results in unreliable prevalence estimates from primary care data and needs improvement. However, the inclusion of pre-conception smoking records may increase the utility of primary care data

Association between polycystic ovarian syndrome and adverse pregnancy and neonatal outcomes among women in Oman

Objectives: To examine the association between PCOS and selected metabolic, pregnancy and neonatal outcomes among pregnant women and their newborns. Methods: Cohort study using electronic hospital records from two tertiary hospitals in Oman. Data were collected from 922 women, contributing 1,939 pregnancies and 1,721 live born infants, in the period from 1 January 2006 to 31 May 2017. Metabolic, pregnancy and neonatal outcomes in the 305 women with a diagnosis of PCOS were compared to outcomes in 617 women without PCOS using multivariable multilevel regression models. Results: Women with PCOS were more likely to develop adverse metabolic outcomes during pregnancy compared to women without PCOS, including developing gestational diabetes mellitus (odds ratio (OR) 3.79, 95% CI 2.22, 6.48) and pregnancy induced hypertension (OR 2.81, 95% CI 1.26, 6.24). The odds of adverse birth outcomes of miscarriage (OR 4.43, 95% CI 2.92, 6.71) and preterm delivery (OR 3.46, 95% CI 1.94, 6.16) were also higher, as was the risk of undergoing emergency caesarean section (OR 3.51, 95% CI 1.80, 6.86). Infants born to mothers with PCOS were not at increased risk of macrosomia, low weight for gestational age or low APGAR score, but they were more likely to require admission to a neonatal unit (OR 2.41, 95% CI 1.10, 5.27). Conclusions: Pregnant women in Oman with PCOS are at a significantly increased risk of metabolic disorders during pregnancy and several adverse birth and neonatal outcomes. Close antenatal monitoring will help early detection and control of metabolic disorders and timely intervention

First trimester exposure to anxiolytic and hypnotic drugs and the risks of major congenital anomalies: a United Kingdom population-based cohort study.

BACKGROUND: Despite their widespread use the effects of taking benzodiazepines and non-benzodiazepine hypnotics during pregnancy on the risk of major congenital anomaly (MCA) are uncertain. The objectives were to estimate absolute and relative risks of MCAs in children exposed to specific anxiolytic and hypnotic drugs taken in the first trimester of pregnancy, compared with children of mothers with depression and/or anxiety but not treated with medication and children of mothers without diagnosed mental illness during pregnancy. METHODS: We identified singleton children born to women aged 15-45 years between 1990 and 2010 from a large United Kingdom primary care database. We calculated absolute risks of MCAs for children with first trimester exposures of different anxiolytic and hypnotic drugs and used logistic regression with a generalised estimating equation to compare risks adjusted for year of childbirth, maternal age, smoking, body mass index, and socioeconomic status. RESULTS: Overall MCA prevalence was 2.7% in 1,159 children of mothers prescribed diazepam, 2.9% in 379 children with temazepam, 2.5% in 406 children with zopiclone, and 2.7% in 19,193 children whose mothers had diagnosed depression and/or anxiety but no first trimester drug exposures. When compared with 2.7% in 351,785 children with no diagnosed depression/anxiety nor medication use, the adjusted odds ratios were 1.02 (99% confidence interval 0.63-1.64) for diazepam, 1.07 (0.49-2.37) for temazepam, 0.96 (0.42-2.20) for zopiclone and 1.27 (0.43-3.75) for other anxiolytic/hypnotic drugs and 1.01 (0.90-1.14) for un-medicated depression/anxiety. Risks of system-specific MCAs were generally similar in children exposed and not exposed to such medications. CONCLUSIONS: We found no evidence for an increase in MCAs in children exposed to benzodiazepines and non-benzodiazepine hypnotics in the first trimester of pregnancy. These findings suggest that prescription of these drugs during early pregnancy may be safe in terms of MCA risk, but findings from other studies are required before safety can be confirmed

Maternal depression, antidepressant prescriptions, and congenital anomaly risk in offspring: a population-based cohort study

OBJECTIVE: To estimate risks of major congenital anomaly (MCA) among children of mothers prescribed antidepressants during early pregnancy or diagnosed with depression but without antidepressant prescriptions. DESIGN: Population-based cohort study. SETTING: Linked UK maternal–child primary care records. POPULATION: A total of 349 127 singletons liveborn between 1990 and 2009. METHODS: Odds ratios adjusted for maternal sociodemographics and comorbidities (aORs) were calculated for MCAs, comparing women with first-trimester selective serotonin reuptake inhibitors (SSRIs) or tricyclic antidepressants (TCAs) and women with diagnosed but unmedicated depression, or women without diagnosed depression. MAIN OUTCOME MEASURES: Fourteen system-specific MCA groups classified according to the European Surveillance of Congenital Anomalies and five specific heart anomaly groups. RESULTS: Absolute risks of MCA were 2.7% (95% confidence interval, 95% CI, 2.6–2.8%) in children of mothers without diagnosed depression, 2.8% (95% CI 2.5–3.2%) in children of mothers with unmedicated depression, and 2.7% (95% CI 2.2–3.2%) and 3.1% (95% CI 2.2–4.1%) in children of mothers with SSRIs or TCAs, respectively. Compared with women without depression, MCA overall was not associated with unmedicated depression (aOR 1.07, 95% CI 0.96–1.18), SSRIs (aOR 1.01, 95% CI 0.88–1.17), or TCAs (aOR 1.09, 95% CI 0.87–1.38). Paroxetine was associated with increased heart anomalies (absolute risk 1.4% in the exposed group compared with 0.8% in women without depression; aOR 1.78, 95% CI 1.09–2.88), which decreased marginally when compared with women with diagnosed but unmedicated depression (aOR 1.67, 95% CI 1.00–2.80). CONCLUSIONS: Overall MCA risk did not increase with maternal depression or with antidepressant prescriptions. Paroxetine was associated with increases of heart anomalies, although this could represent a chance finding from a large number of comparisons undertaken

Nicotine replacement therapy in pregnancy and major congenital anomalies in offspring

BACKGROUND AND OBJECTIVES: Nicotine replacement therapy (NRT) is now being used as a smoking cessation aid during pregnancy, although little is known about fetal safety. We assessed the relationship between early pregnancy exposure to NRT or smoking with major congenital anomalies (MCA) in offspring. METHODS: We studied 192 498 children born in the United Kingdom between 2001 and 2012 with linked mother–child primary care records. The absolute risks of MCAs in the NRT group (women prescribed NRT during the first trimester or 1 month before conception [and therefore likely consumed during the first trimester]) and odds ratios (ORs) and 99% confidence intervals (CIs) were compared with those of women who smoked during pregnancy and with a control group (women who neither smoked nor were prescribed NRT); logistic regression models adjusted for maternal morbidities that increase MCA risk were used for analysis. RESULTS: MCA prevalence was 288 per 10 000 live births (5535 children with ≥1 MCA). Maternal morbidities were most common in the NRT group (35%) followed by smokers (27%) and the control group (20%). Compared with the control group, adjusted ORs for MCAs in the NRT group and smokers were 1.12 (99% CI: 0.84–1.48) and 1.05 (99% CI: 0.89–1.23), respectively. The OR comparing the NRT group directly with smokers was 1.07 (99% CI: 0.78–1.47). There were no statistically significant associations between maternal NRT and system-specific anomalies except for respiratory anomalies (OR: 4.65 [99% CI: 1.76–12.25]; absolute risk difference: 3 per 1000 births), which was based on 10 exposed cases. CONCLUSIONS: For most system-specific MCAs, we found no statistically significant increased risks associated with maternal NRT prescribed during pregnancy, except for respiratory anomalies. Although this study is the largest published to date, NRT use in pregnancy remains rare; thus, the statistical power was limited. Higher morbidities in those women prescribed NRT may also be an explanatory factor. Nevertheless, absolute MCA risks were similar between women who smoked and those prescribed NRT during pregnancy

Early life incidence of gastrointestinal and respiratory infections in children with gastroschisis: a cohort study

Objectives: Survival in infants with gastroschisis is increasing although little is known about early childhood morbidity. In the context of a hypothesised link between the gastrointestinal (GI) tract and immune function, this study explores rates of GI and respiratory infections in children with gastroschisis. Methods: We conducted a population-based retrospective cohort study using data from the Health Improvement Network (THIN), a large database of UK primary care medical records. We identified children born from 1990 to 2013, and extracted follow-up data to their fifth birthday. We calculate incidence rates (IR) of GI and respiratory tract infections, overall and stratified by age, sex, socioeconomic status and gestational age at birth, and compared these between children with and without gastroschisis by calculating adjusted incidence rate ratios (aIRR). Results: Children with gastroschisis had a 65% higher IR of GI infection compared to children without (aIRR 1.65, 95% CI 1.37-1.99, p<0.001). Children with gastroschisis had a 27% higher IR of all respiratory tract infections (aIRR 1.27, 95% CI 1.12-1.44, p<0.001) and more than 2-fold increase in lower respiratory tract infections compared to children without the condition (aIRR 2.15, 95% CI 1.69-2.74, p<0.001). Conclusions: Children born with gastroschisis have a significantly higher incidence of GI and respiratory tract infections compared to children without gastroschisis. This association requires further investigations but could be related to the neonatal care they receive such as delayed eneteral feeding or frequent antibiotic courses altering the gut microbiome and developing immune system

Early childhood respiratory morbidity and antibiotic use in ex-preterm infants: A primary care population-based cohort study

Background Globally, bronchopulmonary dysplasia (BPD) continues to increase in preterm infants. Recent studies exploring subsequent early childhood respiratory morbidity have been small or focused on hospital admissions.Primary aim Examine early childhood rates of primary care consultations for respiratory tract infections (RTI), lower respiratory tract infections (LRTI), wheeze and antibiotic prescriptions (Abx Px) in ex-preterm and term children. Secondary aim: examine differences between preterm infants discharged home with or without oxygen.Methods Retrospective cohort study using linked electronic primary care and hospital databases of children born between 1997 and 2014. We included 253 677 eligible children, with 1666 born preterm [less than] 32 weeks' gestation, followed up from primary care registration to age 5 years. Adjusted incidence rate ratios (aIRR) were calculated.Results Ex-preterm infants had higher rates of morbidity across all respiratory outcomes. After adjusting for confounders, aIRRs for RTI (1.37, 95% CI 1.33–1.42), LRTI (2.79, 95% CI 2.59–3.01), wheeze (3.05, 95% CI 2.64–3.52) and Abx Px (1.49, 95% CI 1.44–1.55) were higher for ex-preterm infants. Ex-preterm infants discharged home on oxygen had significantly greater morbidity across all respiratory diagnoses and Abx Px compared to those without home oxygen. The highest rates of respiratory morbidity were observed in children from the most deprived socioeconomic groups.Conclusion Ex-preterm infants, particularly those with BPD requiring home oxygen, have significant respiratory morbidity and antibiotic prescriptions in early childhood. With the increasing prevalence of BPD, further research should focus on strategies to reduce the burden of respiratory morbidity in these high-risk infants after hospital discharge

Maternal depression, antidepressant prescriptions, and congenital anomaly risk in offspring: a population-based cohort study

OBJECTIVE: To estimate risks of major congenital anomaly (MCA) among children of mothers prescribed antidepressants during early pregnancy or diagnosed with depression but without antidepressant prescriptions. DESIGN: Population-based cohort study. SETTING: Linked UK maternal–child primary care records. POPULATION: A total of 349 127 singletons liveborn between 1990 and 2009. METHODS: Odds ratios adjusted for maternal sociodemographics and comorbidities (aORs) were calculated for MCAs, comparing women with first-trimester selective serotonin reuptake inhibitors (SSRIs) or tricyclic antidepressants (TCAs) and women with diagnosed but unmedicated depression, or women without diagnosed depression. MAIN OUTCOME MEASURES: Fourteen system-specific MCA groups classified according to the European Surveillance of Congenital Anomalies and five specific heart anomaly groups. RESULTS: Absolute risks of MCA were 2.7% (95% confidence interval, 95% CI, 2.6–2.8%) in children of mothers without diagnosed depression, 2.8% (95% CI 2.5–3.2%) in children of mothers with unmedicated depression, and 2.7% (95% CI 2.2–3.2%) and 3.1% (95% CI 2.2–4.1%) in children of mothers with SSRIs or TCAs, respectively. Compared with women without depression, MCA overall was not associated with unmedicated depression (aOR 1.07, 95% CI 0.96–1.18), SSRIs (aOR 1.01, 95% CI 0.88–1.17), or TCAs (aOR 1.09, 95% CI 0.87–1.38). Paroxetine was associated with increased heart anomalies (absolute risk 1.4% in the exposed group compared with 0.8% in women without depression; aOR 1.78, 95% CI 1.09–2.88), which decreased marginally when compared with women with diagnosed but unmedicated depression (aOR 1.67, 95% CI 1.00–2.80). CONCLUSIONS: Overall MCA risk did not increase with maternal depression or with antidepressant prescriptions. Paroxetine was associated with increases of heart anomalies, although this could represent a chance finding from a large number of comparisons undertaken