The Avon Longitudinal Study of Parents and Children - A resource for COVID-19 research: Questionnaire data capture November 2020 - March 2021.

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 has reacted rapidly and repeatedly to the coronavirus disease 2019 (COVID-19) pandemic, deploying online questionnaires throughout the pandemic. In November/December 2020, a fourth questionnaire was deployed asking about physical and mental health, lifestyle and behaviours, employment and finances. G0 participants were offered an online questionnaire between 17 th November 2020 and 7 th February 2021, while G1 participants were offered both online and paper questionnaires between 1 st December 2020 and 19 th March 2021. Of 15,844 invitations, 8,643 (55%) participants returned the questionnaire (3,101 original mothers [mean age 58.6 years], 1,172 original fathers/partners [mean age 61.5 years] and 4,370 offspring [mean age 28.4 years]). Of these 8,643 participants, 2,012 (23%) had not returned a previous COVID-19 questionnaire, while 3,575 (41%) had returned all three previous questionnaires. In this questionnaire, 300 participants (3.5%) reported a previous positive COVID-19 test, 110 (1.3%) had been told by a doctor they likely had COVID-19, and 759 (8.8%) suspected that they had had COVID-19. Based on self-reported symptoms, between October 2020 and February 2021 359 participants (4.2%) were predicted COVID-19 cases. COVID data is being complemented with linkage to health records and Public Health England pillar testing results as they become available. Data has been released as an update to the previous COVID-19 datasets. It comprises: 1) a standard dataset containing all participant responses to both questionnaires with key sociodemographic factors; and 2) as a composite release coordinating data from the existing resource, thus enabling bespoke research across all areas supported by the study. This data note describes the fourth questionnaire and the data obtained from it.

Bias from questionnaire invitation and response in COVID-19 research: an example using ALSPAC.

Background: Longitudinal studies are crucial for identifying potential risk factors for infection with, and consequences of, COVID-19, but relationships can be biased if they are associated with invitation and response to data collection. We describe factors relating to questionnaire invitation and response in COVID-19 questionnaire data collection in a multigenerational birth cohort (the Avon Longitudinal Study of Parents and Children, ALSPAC). Methods: We analysed online questionnaires completed between the beginning of the pandemic and easing of the first UK lockdown by participants with valid email addresses who had not actively disengaged from the study. We assessed associations of pre-pandemic sociodemographic, behavioural, anthropometric and health-related factors with: i) being sent a questionnaire; ii) returning a questionnaire; and iii) item response (for specific questions). Analyses were conducted in three cohorts: the index children born in the early 1990s (now young adults; 41 variables assessed), their mothers (35 variables) and the mothers' partners (27 variables). Results: Of 14,849 young adults, 41% were sent a questionnaire, of whom 57% returned one. Item response was >95%. In this cohort, 78% of factors were associated with being sent a questionnaire, 56% with returning one, and, as an example of item response, 20% with keyworker status response. For instance, children from mothers educated to degree-level had greater odds of being sent a questionnaire (OR=5.59; 95% CI=4.87-6.41), returning one (OR=1.60; 95% CI=1.31-1.95), and responding to items (e.g., keyworker status OR=1.65; 95% CI=0.88-3.04), relative to children from mothers with fewer qualifications. Invitation and response rates and associations were similar in all cohorts. Conclusions: These results highlight the importance of considering potential biases due to non-response when using longitudinal studies in COVID-19 research and interpreting results. We recommend researchers report response rates and factors associated with invitation and response in all COVID-19 observational research studies, which can inform sensitivity analyses.

The Avon Longitudinal Study of Parents and Children - A resource for COVID-19 research: Antibody testing results, April - June 2021.

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based cohort 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 and repeatedly to the coronavirus disease 2019 (COVID-19) pandemic, deploying multiple online questionnaires and a previous home-based antibody test in October 2020. A second antibody test, in collaboration with ten other longitudinal population studies, was completed by 4,622 ALSPAC participants between April and June 2021. Of 4,241 participants with a valid spike protein antibody test result (8.2% were void), indicating antibody response to either COVID-19 vaccination or natural infection, 3,172 were positive (74.8%). Generational differences were substantial, with 2,463/2,555 G0 participants classified positive (96.4%) compared to 709/1,686 G1 participants (42.1%). Of 4,199 participants with a valid nucleocapsid antibody test result (9.2% were void), suggesting potential and recent natural infection, 493 were positive (11.7%); 248/2,526 G0 participants (9.8%) and 245/1,673 G1 participants (14.6%) tested positive, respectively. We also compare results for this round of testing to that undertaken in October 2020. Future work will combine these test results with additional sources of data to identify participants' COVID-19 infection and vaccination status. These ALSPAC COVID-19 serology data are being complemented with linkage to health records and Public Health England pillar testing results as they become available, in addition to four previous questionnaire waves and a prior antibody test. Data have been released as an update to the previous COVID-19 datasets. These comprise: 1) a standard dataset containing all participant responses to all four previous questionnaires with key sociodemographic factors; and 2) individual participant-specific release files enabling bespoke research across all areas supported by the study. This data note describes the second ALSPAC antibody test and the data obtained from it.

The Avon Longitudinal Study of Parents and Children - A resource for COVID-19 research: Generation 2 questionnaire data capture May-July 2020.

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based cohort study which recruited pregnant women in 1990-1992 from the Bristol area (UK). ALSPAC has followed these women, their partners (Generation 0; G0) and their offspring (Generation 1; G1) ever since. From 2012, ALSPAC has identified G1 participants who were pregnant (or their partner was) or had become parents, and enrolled them, their partners, and children in the ALSPAC-Generation 2 (ALSPAC-G2) study, providing a unique multi-generational cohort. At present, approximately 1,100 G2 children (excluding those in utero) from 810 G1 participants have been enrolled. In response to the COVID-19 pandemic, ALSPAC rapidly deployed two online questionnaires; one during the initial lockdown phase in 2020 (9 th April-15 th May), and another when national lockdown restrictions were eased (26 th May-5 th July). As part of this second questionnaire, G1 parents completed a questionnaire about each of their G2 children. This covered: parental reports of children's feelings and behaviour since lockdown, school attendance, contact patterns, and health. A total of 289 G1 participants completed this questionnaire on behalf of 411 G2 children. This COVID-19 G2 questionnaire data can be combined with pre-pandemic ALSPAC-G2 data, plus ALSPAC-G1 and -G0 data, to understand how children's health and behaviour has been affected by the pandemic and its management. Data from this questionnaire will be complemented with linkage to health records and results of biological testing as they become available. Prospective studies are necessary to understand the impact of this pandemic on children's health and development, yet few relevant studies exist; this resource will aid these efforts. Data has been released as: 1) a freely-available dataset containing participant responses with key sociodemographic variables; and 2) an ALSPAC-held dataset which can be combined with existing ALSPAC data, enabling bespoke research across all areas supported by the study.

The Avon Longitudinal Study of Parents and Children - A resource for COVID-19 research: Questionnaire data capture April-May 2020.

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based cohort study which recruited pregnant women in 1990-1992. The resource provides an informative and efficient setting for collecting data on the current coronavirus 2019 (COVID-19) pandemic. In early March 2020, a questionnaire was developed in collaboration with other longitudinal population studies to ensure cross-cohort comparability. It targeted retrospective and current COVID-19 infection information (exposure assessment, symptom tracking and reported clinical outcomes) and the impact of both disease and mitigating measures implemented to manage the COVID-19 crisis more broadly. Data were collected on symptoms of COVID-19 and seasonal flu, travel prior to the pandemic, mental health and social, behavioural and lifestyle factors. The online questionnaire was deployed across parent (G0) and offspring (G1) generations between 9 th April and 15 th May 2020. 6807 participants completed the questionnaire (2706 original mothers, 1014 original fathers/partners, 2973 offspring (mean age ~28 years) and 114 offspring partners). Eight (0.01%) participants (4 G0 and 4 G1) reported a positive test for COVID-19, 77 (1.13%; 28 G0 and 49 G1) reported that they had been told by a doctor they likely had COVID-19 and 865 (12.7%; 426 G0 and 439 G1) suspected that they have had COVID-19.  Using algorithmically defined cases, we estimate that the predicted proportion of COVID-19 cases ranged from 1.03% - 4.19% depending on timing during the period of reporting (October 2019-March 2020). Data from this first questionnaire will be complemented with at least two more follow-up questionnaires, linkage to health records and results of biological testing as they become available. Data has been released as: 1) a standard dataset containing all participant responses with key sociodemographic factors and 2) as a composite release coordinating data from the existing resource, thus enabling bespoke research across all areas supported by the study.

Correction to: Is population structure in the genetic biobank era irrelevant, a challenge, or an opportunity?

In the original article publication, there is an incorrect impression that Fig. 1 formed a formal Directed Acyclic Graph (DAG) by describing it as a causal model. However, it was not correct if interpreted in this way.

Is population structure in the genetic biobank era irrelevant, a challenge, or an opportunity?

Replicable genetic association signals have consistently been found through genome-wide association studies in recent years. The recent dramatic expansion of study sizes improves power of estimation of effect sizes, genomic prediction, causal inference, and polygenic selection, but it simultaneously increases susceptibility of these methods to bias due to subtle population structure. Standard methods using genetic principal components to correct for structure might not always be appropriate and we use a simulation study to illustrate when correction might be ineffective for avoiding biases. New methods such as trans-ethnic modeling and chromosome painting allow for a richer understanding of the relationship between traits and population structure. We illustrate the arguments using real examples (stroke and educational attainment) and provide a more nuanced understanding of population structure, which is set to be revisited as a critical aspect of future analyses in genetic epidemiology. We also make simple recommendations for how problems can be avoided in the future. Our results have particular importance for the implementation of GWAS meta-analysis, for prediction of traits, and for causal inference.

GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals.

Loci discovered by genome-wide association studies predominantly map outside protein-coding genes. The interpretation of the functional consequences of non-coding variants can be greatly enhanced by catalogs of regulatory genomic regions in cell lines and primary tissues. However, robust and readily applicable methods are still lacking by which to systematically evaluate the contribution of these regions to genetic variation implicated in diseases or quantitative traits. Here we propose a novel approach that leverages genome-wide association studies' findings with regulatory or functional annotations to classify features relevant to a phenotype of interest. Within our framework, we account for major sources of confounding not offered by current methods. We further assess enrichment of genome-wide association studies for 19 traits within Encyclopedia of DNA Elements- and Roadmap-derived regulatory regions. We characterize unique enrichment patterns for traits and annotations driving novel biological insights. The method is implemented in standalone software and an R package, to facilitate its application by the research community.

The Genetic Sphygmomanometer: an argument for routine genome-wide genotyping in the population and a new view on its use to inform clinical practice.

Initial genomewide association studies were exceptional owing to an ability to yield novel and reliable evidence for heritable contributions to complex disease and phenotype. However the top results alone were certainly not responsible for a wave of new predictive tools. Despite this, even studies small by contemporary standards were able to provide estimates of the relative contribution of all recorded genetic variants to outcome. Sparking efforts to quantify heritability, these results also provided the material for genomewide prediction. A fantastic growth in the performance of human genetic studies has only served to improve the potential of these complex, but potentially informative predictors. Prompted by these conditions and recent work, this letter explores the likely utility of these predictors, considers how clinical practice might be altered through their use, how to measure the efficacy of this and some of the potential ethical issues involved. Ultimately we suggest that for common genetic variation at least, the future should contain an acceptance of complexity in genetic architecture and the possibility of useful prediction even if only to shift the way we interact with clinical service providers.

A genome-wide association study reveals variants in ARL15 that influence adiponectin levels.

The adipocyte-derived protein adiponectin is highly heritable and inversely associated with risk of type 2 diabetes mellitus (T2D) and coronary heart disease (CHD). We meta-analyzed 3 genome-wide association studies for circulating adiponectin levels (n = 8,531) and sought validation of the lead single nucleotide polymorphisms (SNPs) in 5 additional cohorts (n = 6,202). Five SNPs were genome-wide significant in their relationship with adiponectin (P< or =5x10(-8)). We then tested whether these 5 SNPs were associated with risk of T2D and CHD using a Bonferroni-corrected threshold of P< or =0.011 to declare statistical significance for these disease associations. SNPs at the adiponectin-encoding ADIPOQ locus demonstrated the strongest associations with adiponectin levels (P-combined = 9.2x10(-19) for lead SNP, rs266717, n = 14,733). A novel variant in the ARL15 (ADP-ribosylation factor-like 15) gene was associated with lower circulating levels of adiponectin (rs4311394-G, P-combined = 2.9x10(-8), n = 14,733). This same risk allele at ARL15 was also associated with a higher risk of CHD (odds ratio [OR] = 1.12, P = 8.5x10(-6), n = 22,421) more nominally, an increased risk of T2D (OR = 1.11, P = 3.2x10(-3), n = 10,128), and several metabolic traits. Expression studies in humans indicated that ARL15 is well-expressed in skeletal muscle. These findings identify a novel protein, ARL15, which influences circulating adiponectin levels and may impact upon CHD risk.