Early academic achievement in children with isolated clefts: a population-based study in England

OBJECTIVES: We used national data to study differences in academic achievement between 5-year-old children with an isolated oral cleft and the general population. We also assessed differences by cleft type. METHODS: Children born in England with an oral cleft were identified in a national cleft registry. Their records were linked to databases of hospital admissions (to identify additional anomalies) and educational outcomes. Z-scores (signed number of SD actual score is above national average) were calculated to make outcome scores comparable across school years and across six assessed areas (personal development, communication and language, maths, knowledge of world, physical development andcreative development). RESULTS: 2802 children without additional anomalies, 5 years old between 2006 and 2012, were included. Academic achievement was significantly below national average for all six assessed areas with z-scores ranging from -0.24 (95% CI -0.32 to -0.16) for knowledge of world to -0.31 (-0.38 to -0.23) for personal development. Differences were small with only a cleft lip but considerably larger with clefts involving the palate. 29.4% of children were documented as having special education needs (national rate 9.7%), which varied according to cleft type from 13.2% with cleft lip to 47.6% with bilateral cleft lip and palate. CONCLUSIONS: Compared with national average, 5-year-old children with an isolated oral cleft, especially those involving the palate, have significantly poorer academic achievement across all areas of learning. These outcomes reflect results of modern surgical techniques and multidisciplinary approach. Children with a cleft may benefit from extra academic support when starting school

Early academic achievement in children with isolated clefts: a population-based study in England.

OBJECTIVES: We used national data to study differences in academic achievement between 5-year-old children with an isolated oral cleft and the general population. We also assessed differences by cleft type. METHODS: Children born in England with an oral cleft were identified in a national cleft registry. Their records were linked to databases of hospital admissions (to identify additional anomalies) and educational outcomes. Z-scores (signed number of SD actual score is above national average) were calculated to make outcome scores comparable across school years and across six assessed areas (personal development, communication and language, maths, knowledge of world, physical development andcreative development). RESULTS: 2802 children without additional anomalies, 5 years old between 2006 and 2012, were included. Academic achievement was significantly below national average for all six assessed areas with z-scores ranging from -0.24 (95% CI -0.32 to -0.16) for knowledge of world to -0.31 (-0.38 to -0.23) for personal development. Differences were small with only a cleft lip but considerably larger with clefts involving the palate. 29.4% of children were documented as having special education needs (national rate 9.7%), which varied according to cleft type from 13.2% with cleft lip to 47.6% with bilateral cleft lip and palate. CONCLUSIONS: Compared with national average, 5-year-old children with an isolated oral cleft, especially those involving the palate, have significantly poorer academic achievement across all areas of learning. These outcomes reflect results of modern surgical techniques and multidisciplinary approach. Children with a cleft may benefit from extra academic support when starting school

A whole genome screen for association with multiple sclerosis in portuguese patients

Multiple sclerosis (MS) is common in Europe affecting up to 1:500 people. In an effort to identify genes influencing susceptibility to the disease, we have performed a population-based whole genome screen for association. In this study, 6000 microsatellite markers were typed in separately pooled DNA samples from MS patients (n = 188) and matched controls (n = 188). Interpretable data was obtained from 4661 of these markers. Refining analysis of the most promising markers identified 10 showing potential evidence for association.SERONO (Portugal).Fundação para a Ciência e a Tecnologia (FCT) - grant FRH/BD/9111/2002.British Council/ICCTI.Wellcome Trust, Multiple Sclerosis Societies of the United States and Great Britain, Multiple Sclerosis International Federation - GAMES project - grant 057097

Linking consented cohort and routinely collected health data to enhance investigations into childhood obesity, asthma, infections, immunisations, and injuries

Background In longitudinal health research, combining the richness of cohort data to the extensiveness of routine data opens up new possibilities, providing information not available from one data source alone. In this study, we set out to extend information from a longitudinal birth cohort study by linking to the cohort child’s routine primary and secondary health care data. The resulting linked datasets will be used to examine health outcomes and patterns of health service utilisation for a set of common childhood health problems. We describe the experiences and challenges of acquiring and linking electronic health records for participants in a national longitudinal study, the UK Millennium Cohort Study (MCS). Method Written parental consent to link routine health data to survey responses of the MCS cohort member, mother and her partner was obtained for 90.7% of respondents when interviews took place at age seven years in the MCS. Probabilistic and deterministic linkage was used to link MCS cohort members to multiple routinely-collected health data sources in Wales and Scotland. Results Overall linkage rates for the consented population using country-specific health service data sources were 97.6% for Scotland and 99.9% for Wales. Linkage rates between different health data sources ranged from 65.3% to 99.6%. Issues relating to acquisition and linkage of data sources are discussed. Conclusions Linking longitudinal cohort participants with routine data sources is becoming increasingly popular in population data research. Our results suggest that this is a valid method to enhance information held in both sources of data

An extended association screen in multiple sclerosis using 202 microsatellite markers targeting apoptosis-related genes does not reveal new predisposing factors

Apoptosis, the programmed death of cells, plays a distinct role in the etiopathogenesis of Multiple sclerosis (MS), a common disease of the central nervous system with complex genetic background. Yet, it is not clear whether the impact of apoptosis is due to altered apoptotic behaviour caused by variations of apoptosis-related genes. Instead, apoptosis in MS may also represent a secondary response to cellular stress during acute inflammation in the central nervous system. Here, we screened 202 apoptosis-related genes for association by genotyping 202 microsatellite markers in initially 160 MS patients and 160 controls, both divided in 4 sets of pooled DNA samples, respectively. When applying Bonferroni correction, no significant differences in allele frequencies were detected between MS patients and controls. Nevertheless, we chose 7 markers for retyping in individual DNA samples, thereby eliminating 6 markers from the list of candidates. The remaining candidate, the ERBB3 gene microsatellite, was genotyped in additional 245 MS patients and controls. No association of the ERBB3 marker with the disease was detected in these additional cohorts. In consequence, we did not find further evidence for apoptosis-related genes as predisposition factors in MS

An Arabidopsis Example of Association Mapping in Structured Samples

A potentially serious disadvantage of association mapping is the fact that marker-trait associations may arise from confounding population structure as well as from linkage to causative polymorphisms. Using genome-wide marker data, we have previously demonstrated that the problem can be severe in a global sample of 95 Arabidopsis thaliana accessions, and that established methods for controlling for population structure are generally insufficient. Here, we use the same sample together with a number of flowering-related phenotypes and data-perturbation simulations to evaluate a wider range of methods for controlling for population structure. We find that, in terms of reducing the false-positive rate while maintaining statistical power, a recently introduced mixed-model approach that takes genome-wide differences in relatedness into account via estimated pairwise kinship coefficients generally performs best. By combining the association results with results from linkage mapping in F2 crosses, we identify one previously known true positive and several promising new associations, but also demonstrate the existence of both false positives and false negatives. Our results illustrate the potential of genome-wide association scans as a tool for dissecting the genetics of natural variation, while at the same time highlighting the pitfalls. The importance of study design is clear; our study is severely under-powered both in terms of sample size and marker density. Our results also provide a striking demonstration of confounding by population structure. While statistical methods can be used to ameliorate this problem, they cannot always be effective and are certainly not a substitute for independent evidence, such as that obtained via crosses or transgenic experiments. Ultimately, association mapping is a powerful tool for identifying a list of candidates that is short enough to permit further genetic study

Using consented health record linkage in a longitudinal cohort study

ABSTRACT Objectives The aim of this project is to address important issues relevant to children’s health This will be done by enhancing information collected in the longitudinal, UK-wide Millennium Cohort Study (MCS) by linking participating children to their routine health records. These issues include: health service implications of early life onset of obesity and overweight; timeliness of immunisations; association of infections with asthma and allergic disorders in childhood; and burden of disease due to childhood injuries. Approach The MCS comprises information on the social, economic and health-related circumstances of children surveyed at ages 9 months, 3, 5, 7, 11 and 14 years. At the age 7 interview, 12517 (89.1%) of the 14043 adults with parental responsibility consented for information from their child’s routine heath records to be released to the MCS (a). Routine health records have been requested for Wales, England and Scotland to be linked to MCS responses within the Secure Anonymised Information Linkage Databank at Swansea University. Data will be analysed using weights for non-response, non-consent and non-linkage and the linkage reported according to the RECORD guidelines (b). Results To date, all 1881 MCS children with valid consent who live or have lived in Wales have been linked by assigning an Anonymous Linking Field (ALF) to each individual which can be mapped across multiple datasets without risk of identification (c). Of these children, 1365 (72.3%) had experienced at least one hospital admission by the age of 14 years. Risk of admission by each of the survey ages for boys and girls separately will be calculated adjusting for non-response at different sweeps. These children have also been linked to their immunisation records (n = 1872), Emergency Department attendances (n = 1276), and available GP records (n = 1151) to enable analyses in fulfilment of the project objectives. Conclusions Routine health records are a potentially valuable enhancement to longitudinal studies, allowing evaluation of questions of relevance to public health and health services, and the completeness and consistency of records from these different sources to be addressed. References a. Shepherd, P. (2013) Consent to linkage to child health data ISBN 978-1-906929-59-6 b. Benchimol, E.I. et al (2015) DOI: 10.1371/journal.pmed.1001885 c. Ford, D.V. et al (2009) DOI: 10.1186/1472-6963-9-15

Accounting for Population Stratification in Practice: A Comparison of the Main Strategies Dedicated to Genome-Wide Association Studies

Genome-Wide Association Studies are powerful tools to detect genetic variants associated with diseases. Their results have, however, been questioned, in part because of the bias induced by population stratification. This is a consequence of systematic differences in allele frequencies due to the difference in sample ancestries that can lead to both false positive or false negative findings. Many strategies are available to account for stratification but their performances differ, for instance according to the type of population structure, the disease susceptibility locus minor allele frequency, the degree of sampling imbalanced, or the sample size. We focus on the type of population structure and propose a comparison of the most commonly used methods to deal with stratification that are the Genomic Control, Principal Component based methods such as implemented in Eigenstrat, adjusted Regressions and Meta-Analyses strategies. Our assessment of the methods is based on a large simulation study, involving several scenarios corresponding to many types of population structures. We focused on both false positive rate and power to determine which methods perform the best. Our analysis showed that if there is no population structure, none of the tests led to a bias nor decreased the power except for the Meta-Analyses. When the population is stratified, adjusted Logistic Regressions and Eigenstrat are the best solutions to account for stratification even though only the Logistic Regressions are able to constantly maintain correct false positive rates. This study provides more details about these methods. Their advantages and limitations in different stratification scenarios are highlighted in order to propose practical guidelines to account for population stratification in Genome-Wide Association Studies

Is Replication the Gold Standard for Validating Genome-Wide Association Findings?

With the advent of genome-wide association (GWA) studies, researchers are hoping that reliable genetic association of common human complex diseases/traits can be detected. Currently, there is an increasing enthusiasm about GWA and a number of GWA studies have been published. In the field a common practice is that replication should be used as the gold standard to validate an association finding. In this article, based on empirical and theoretical data, we emphasize that replication of GWA findings can be quite difficult, and should not always be expected, even when true variants are identified. The probability of replication becomes smaller with the increasing number of independent GWA studies if the power of individual replication studies is less than 100% (which is usually the case), and even a finding that is replicated may not necessarily be true. We argue that the field may have unreasonably high expectations on success of replication. We also wish to raise the question whether it is sufficient or necessary to treat replication as the ultimate and gold standard for defining true variants. We finally discuss the usefulness of integrating evidence from multiple levels/sources such as genetic epidemiological studies (at the DNA level), gene expression studies (at the RNA level), proteomics (at the protein level), and follow-up molecular and cellular studies for eventual validation and illumination of the functional relevance of the genes uncovered

A Latent Variable Partial Least Squares Path Modeling Approach to Regional Association and Polygenic Effect with Applications to a Human Obesity Study

Genetic association studies are now routinely used to identify single nucleotide polymorphisms (SNPs) linked with human diseases or traits through single SNP-single trait tests. Here we introduced partial least squares path modeling (PLSPM) for association between single or multiple SNPs and a latent trait that can involve single or multiple correlated measurement(s). Furthermore, the framework naturally provides estimators of polygenic effect by appropriately weighting trait-attributing alleles. We conducted computer simulations to assess the performance via multiple SNPs and human obesity-related traits as measured by body mass index (BMI), waist and hip circumferences. Our results showed that the associate statistics had type I error rates close to nominal level and were powerful for a range of effect and sample sizes. When applied to 12 candidate regions in data (N = 2,417) from the European Prospective Investigation of Cancer (EPIC)-Norfolk study, a region in FTO was found to have stronger association (rs7204609∼rs9939881 at the first intron P = 4.29×10−7) than single SNP analysis (all with P>10−4) and a latent quantitative phenotype was obtained using a subset sample of EPIC-Norfolk (N = 12,559). We believe our method is appropriate for assessment of regional association and polygenic effect on a single or multiple traits