ALSPAC is an ongoing population-based, observational study designed to investigate how genetic/environmental characteristics might influence the health/development of children and their parents. It has evolved to facilitate the measurement of many outcomes in the parental cohort. Pregnant women resident in Bristol, UK with expected dates of delivery between April 1991-December 1992 were eligible. 14,541 pregnancies were originally enrolled. Partners of the pregnant women were initially invited to take part by the women with formal enrolment of individuals since 2010. Data has been collected from 12,113 partners, with 3,807 formally enrolled. Data collected to date: 21 questionnaires, clinical follow up in 2012 (mean age: 53 years) and a family-based clinical follow-up currently ongoing (mean age: 63 years). Questionnaires asked about a wide range of environmental measures, physical/mental health and other phenotypic details including six questionnaires throughout the COVID-19 pandemic. Clinical measures include anthropometrics, blood pressure, body composition, cardiovascular health and a fasting blood sample. DNA has been extracted with genome-wide data available on >3,000 partners and exomes on ~1500 trios. The data contributes to one of the most deeply phenotyped birth cohorts in the world, providing trios of data and multi-generational information, and is fully accessible through a managed access process.

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.

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 Euro Registers 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.

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based cohort study which recruited pregnant women in 1990-1992 and has followed these women, their partners (Generation 0; G0) and their offspring (Generation 1; G1) ever since. The study reacted rapidly to the coronavirus disease 2019 (COVID-19) pandemic, deploying three online questionnaires in March, May and October 2020. Home-based antibody tests accompanied the third questionnaire. In addition, linkage to Public Health England (PHE) Pillar I and II testing results has been obtained for all participants who have consented or for whom we have NHS Confidentiality approval group permitted Section 251 access. For the purposes of ongoing study, we have identified likely cases of COVID-19 from available data. To determine likely cases, we have developed a hierarchy depending on the source of the data: self-report, antibody test result and Pillar I and II linkage and a combination thereof; providing more certainty in the case status. This data note describes how we have ascertained case status in ALSPAC. The subsequent case variable will be made available through our COVID release files alongside testing data from PHE.

ALSPAC is an ongoing population-based, observational study designed to investigate how genetic/environmental characteristics might influence the health/development of children and their parents. It has evolved to facilitate the measurement of many outcomes in the parental cohort. Pregnant women resident in Bristol, UK with expected dates of delivery between April 1991-December 1992 were eligible. 14,541 pregnancies were originally enrolled. Partners of the pregnant women were initially invited to take part by the women with formal enrolment of individuals since 2010. Data has been collected from 12,113 partners, with 3,807 formally enrolled. Data collected to date: 21 questionnaires, clinical follow up in 2012 (mean age: 53 years) and a family-based clinical follow-up currently ongoing (mean age: 63 years). Questionnaires have asked about a wide range of environmental measures, physical/mental health and other phenotypic details at regular timepoints up to 2005, once in 2012 and regularly again since 2018, including six questionnaires completed during the COVID-19 pandemic. Clinical measures include anthropometrics, blood pressure, body composition, cardiovascular health and a fasting blood sample. DNA has been extracted with genome-wide data available on >3,000 partners and exomes on ~1500 trios. The data contributes to one of the most deeply phenotyped birth cohorts in the world, providing trios of data, allowing comparison between parents and offering multi-generational information, and is fully accessible through a managed access process.