Ascertaining and classifying cases of congenital anomalies in the ALSPAC birth cohort

Abstract

Congenital anomalies (CAs) are structural or functional disorders that occur during intrauterine life. Longitudinal cohort studies provide unique opportunities to investigate potential causes and consequences of these disorders. In this data note, we describe how we identified cases of major CAs, with a specific focus on congenital heart diseases (CHDs), in the Avon Longitudinal Study of Parents and Children (ALSPAC). We demonstrate that combining multiple sources of data including data from antenatal, delivery, primary and secondary health records, and parent-reported information can improve case ascertainment. Our approach identified 590 participants with a CA according to the European Surveillance of Congenital Anomalies (EUROCAT) guidelines, 127 of whom had a CHD. We describe the methods that identified these cases and provide statistics on subtypes of anomalies. The data note contains details on the processes required for researchers to access these data.

Effect of Maternal Prepregnancy/Early‐Pregnancy Body Mass Index and Pregnancy Smoking and Alcohol on Congenital Heart Diseases: A Parental Negative Control Study

“…In the ALSPAC cohort, cases were obtained from a range of data sources, including health record linkage and questionnaire data up until age 25 years following European Surveillance of Congenital Anomalies guidelines. 29 In BASELINE, at 2 months, mothers were asked of any medical problems and/or referrals. If a baby had been referred to a specialist, he/she was checked by a cardiologist to see if he/she had results from an echocardiogram with exact diagnoses reported.…”

The effect of maternal BMI, smoking and alcohol on congenital heart diseases: a Mendelian randomization study

“…Many of the cohorts that we considered for inclusion had genetic data but no information on CHD (or other congenital anomalies). (ii) Linkage to electronic records should be regularly updated at least until early adulthood so that cases that are diagnosed later in life are also captured 34,35 46 . As these GWAS continue to grow, significant data sharing and collaboration will be required, which could then pave way for large-scale two-sample MR studies to explore maternal risk factors for CHDs.…”

“…We think this is possible over the coming years as running GWAS is relatively cheap, and most cohort studies increasingly have these data. The following could considerably increase the sample size for MR in this field and result in key advances in preventing CHDs: (i) Add data on CHDs through electronic record linkage to existing cohorts; this was done recently in ALSPAC nearly 30 years after the original pregnancies 34 . Many of the cohorts that we considered for inclusion had genetic data but no information on CHD (or other congenital anomalies).…”

“…Many of the cohorts that we considered for inclusion had genetic data but no information on CHD (or other congenital anomalies). (ii) Linkage to electronic records should be regularly updated at least until early adulthood so that cases that are diagnosed later in life are also captured 34,35 . (iii) Ensure new cohorts, particularly large birth/pregnancy cohorts or those with the potential to prospectively collect data during pregnancy (such as the planned UK Our Future Health (https://ourfuturehealth.org.uk/about-us/) gain consent to collect health data on CHDs (and other congenital anomalies).…”

“…In the ALSPAC cohort, cases were obtained from a range of data sources, including health record linkage and questionnaire data up until age 25 following European surveillance of congenital anomalies (EUROCAT) guidelines 34 . In BiB, cases were identified from either the Yorkshire and Humber congenital anomaly register database, which will tend to pick up most cases that were diagnosed antenatally and in the early postnatal period of life, and through linkage to primary care (up until aged 5), which will have picked up any additional cases, in particular those that might have been less severe and not identified antenatally/in early life 35 .…”