A review of genetic variant databases and machine learning tools for predicting the pathogenicity of breast cancer.

Studies continue to uncover contributing risk factors for breast cancer (BC) development including genetic variants. Advances in machine learning and big data generated from genetic sequencing can now be used for predicting BC pathogenicity. However, it is unclear which tool developed for pathogenicity prediction is most suited for predicting the impact and pathogenicity of variant effects. A significant challenge is to determine the most suitable data source for each tool since different tools can yield different prediction results with different data inputs. To this end, this work reviews genetic variant databases and tools used specifically for the prediction of BC pathogenicity. We provide a description of existing genetic variants databases and, where appropriate, the diseases for which they have been established. Through example, we illustrate how they can be used for prediction of BC pathogenicity and discuss their associated advantages and disadvantages. We conclude that the tools that are specialized by training on multiple diverse datasets from different databases for the same disease have enhanced accuracy and specificity and are thereby more helpful to the clinicians in predicting and diagnosing BC as early as possible.

SEMA3: A free smartphone platform for daily life surveys.

Traditionally, behavioral, social, and health science researchers have relied on global/retrospective survey methods administered cross-sectionally (i.e., on a single occasion) or longitudinally (i.e., on several occasions separated by weeks, months, or years). More recently, social and health scientists have added daily life survey methods (also known as intensive longitudinal methods or ambulatory assessment) to their toolkit. These methods (e.g., daily diaries, experience sampling, ecological momentary assessment) involve dense repeated assessments in everyday settings. To facilitate research using daily life survey methods, we present SEMA3 ( http://www.SEMA3.com ), a platform for designing and administering intensive longitudinal daily life surveys via Android and iOS smartphones. SEMA3 fills an important gap by providing researchers with a free, intuitive, and flexible platform with basic and advanced functionality. In this article, we describe SEMA3's development history and system architecture, provide an overview of how to design a study using SEMA3 and outline its key features, and discuss the platform's limitations and propose directions for future development of SEMA3.

Addressing methodological issues in a study of impulsivity and vulnerability for transition to alcohol use disorder.

BACKGROUND: Heightened behavioral impulsivity has been advocated as a preexisting risk factor for the development of alcohol use disorder (AUD). Nonetheless, studies investigating impulsivity in adolescent/young adult at-risk drinkers-who are at increased risk of developing AUD-report mixed findings. This may be due to methodological limitations related to definitions of at-risk drinking, the retrospective assessment of alcohol intake, and/or the relatively modest sample size of some studies. METHODS: Healthy individuals (N = 814, Mage  = 22.50) completed online surveys and a measure of choice impulsivity. Of these, a number of participants also undertook an online measure of response inhibition (n = 627, Mage  = 22.66), and a further subgroup submitted real-time alcohol consumption information for a period of 21 days using an app (n = 543, Mage  = 22.96). Differences in behavioral impulsivity were assessed as a function of various at-risk alcohol intake categories. Hierarchical multiple regression was employed to determine whether impulsivity predicted alcohol use in the form of a continuous index comprising variables related to intake and consequences of use. RESULTS: Significantly greater impulsivity was not evident in heavy, standard binge, high binge, harmful, or hazardous alcohol drinkers as compared to controls, regardless of the criteria employed to categorize these at-risk drinkers. Neither choice impulsivity nor reduced response inhibition significantly predicted the alcohol use index. CONCLUSIONS: While results could be attributed to the online nature of this research, it is possible that more sensitive measures of behavioral impulsivity are required when assessing nondependent drinkers.

Changes in pancreatic exocrine function in young at-risk children followed to islet autoimmunity and type 1 diabetes in the ENDIA study.

BACKGROUNDS: We aimed to monitor pancreatic exocrine function longitudinally in relation to the development of islet autoimmunity (IA) and type 1 diabetes (T1D) in at-risk children with a first-degree relative with T1D, who were followed prospectively in the Environmental Determinants of Islet Autoimmunity (ENDIA) study. METHODS: Fecal elastase-1 (FE-1) concentration was measured longitudinally in 85 ENDIA children from median age 1.0 (IQR 0.7,1.3) year. Twenty-eight of 85 children (progressors) developed persistent islet autoantibodies at median age of 1.5 (IQR 1.1,2.5) years, of whom 11 went on to develop clinical diabetes. The other 57 islet autoantibody-negative children (non-progressors) followed similarly were age and gender-matched with the progressors. An adjusted linear mixed model compared FE-1 concentrations in progressors and non-progressors. RESULTS: Baseline FE-1 did not differ between progressors and non-progressors, or by HLA DR type or proband status. FE-1 decreased over time in progressors in comparison to non-progressors (Wald statistic 5.46, P = .02); in some progressors the fall in FE-1 preceded the onset of IA. CONCLUSIONS: Pancreatic exocrine function decreases in the majority of young at-risk children who progress to IA and T1D.

Higher frequency of vertebrate-infecting viruses in the gut of infants born to mothers with type 1 diabetes.

BACKGROUND: Microbial exposures in utero and early life shape the infant microbiome, which can profoundly impact on health. Compared to the bacterial microbiome, very little is known about the virome. We set out to characterize longitudinal changes in the gut virome of healthy infants born to mothers with or without type 1 diabetes using comprehensive virome capture sequencing. METHODS: Healthy infants were selected from Environmental Determinants of Islet Autoimmunity (ENDIA), a prospective cohort of Australian children with a first-degree relative with type 1 diabetes, followed from pregnancy. Fecal specimens were collected three-monthly in the first year of life. RESULTS: Among 25 infants (44% born to mothers with type 1 diabetes) at least one virus was detected in 65% (65/100) of samples and 96% (24/25) of infants during the first year of life. In total, 26 genera of viruses were identified and >150 viruses were differentially abundant between the gut of infants with a mother with type 1 diabetes vs without. Positivity for any virus was associated with maternal type 1 diabetes and older infant age. Enterovirus was associated with older infant age and maternal smoking. CONCLUSIONS: We demonstrate a distinct gut virome profile in infants of mothers with type 1 diabetes, which may influence health outcomes later in life. Higher prevalence and greater number of viruses observed compared to previous studies suggests significant underrepresentation in existing virome datasets, arising most likely from less sensitive techniques used in data acquisition.

Predictors of Adverse Alcohol Use Consequences Among Tertiary Students.

BACKGROUND: The alcohol consumption patterns of young adults are of concern. Critically, tertiary students consume greater quantities of alcohol, are at increased risk of injury/harm, and have higher rates of alcohol use disorders as compared to their nonuniversity enrolled peers. The Brief Young Adult Alcohol Consequences Questionnaire (BYAACQ) is one of several tools utilized to explore adverse alcohol-related outcomes among tertiary students. Alcohol intake behavior, assessed via retrospective summary measures, has been linked to BYAACQ score. It is unclear, however, how drinking assessed in real time, in conjunction with variables such as age of drinking onset, might predict severity of adverse alcohol consequences as captured by the BYAACQ. METHODS: The psychometric properties of the BYAACQ were explored using a large Australian sample of tertiary students (N = 893). A subsample (n = 504) provided alcohol intake information in real time (21 days; event and notification contingent) via a smartphone app (CNLab-A) plus details related to age of drinking onset, drug use, parental alcohol/drug use, and anxiety/depression symptomology. RESULTS: Average BYAACQ score was 7.53 (SD = 5.37). Classical and item response theory analyses revealed inconsistencies related to dimensionality, progressive item severity, and male/female differential item functioning. Current drinking-namely, frequency of intake and quantity per drinking occasion-plus age of drinking onset predicted BYAACQ score after controlling for age, other drug use, and depression symptomology. CONCLUSIONS: The BYAACQ is a sound tool for use with Australian samples. Information related to current drinking, age of drinking onset, and drug use is useful for predicting severity of alcohol use consequences. These markers might enable tertiary institutions to better target students who could benefit from prevention/intervention programs.

Biochemical Diagnosis of Chromaffin Cell Tumors in Patients at High and Low Risk of Disease: Plasma versus Urinary Free or Deconjugated O-Methylated Catecholamine Metabolites.

BACKGROUND: Measurements of plasma or urinary metanephrines are recommended for diagnosis of pheochromocytoma and paraganglioma (PPGL). What test offers optimal diagnostic accuracy for patients at high and low risk of disease, whether urinary free metanephrines offer advantages over deconjugated metanephrines, and what advantages are offered by including methoxytyramine in panels all remain unclear. METHODS: A population of 2056 patients with suspected PPGLs underwent prospective screening for disease using mass spectrometric-based measurements of plasma free, urinary deconjugated, and urinary free metanephrines and methoxytyramine. PPGLs were confirmed in 236 patients and were excluded in others on follow-up evaluation. RESULTS: Measurements of plasma free metabolites offered higher (P < 0.01) diagnostic sensitivity (97.9%) than urinary free (93.4%) and deconjugated (92.9%) metabolites at identical specificities for plasma and urinary free metabolites (94.2%) but at a lower (P < 0.005) specificity for deconjugated metabolites (92.1%). The addition of methoxytyramine offered little value for urinary panels but provided higher (P < 0.005) diagnostic performance for plasma measurements than either urinary panel according to areas under ROC curves (0.991 vs 0.972 and 0.964). Diagnostic performance of urinary and plasma tests was similar for patients at low risk of disease, whereas plasma measurements were superior to both urinary panels for high-risk patients. CONCLUSIONS: Diagnosis of PPGLs using plasma or urinary free metabolites provides advantages of fewer false-positive results compared with commonly measured deconjugated metabolites. The plasma panel offers better diagnostic performance than either urinary panel for patients at high risk of disease and, with appropriate preanalytics, provides the test of choice. Measurements of methoxytyramine in urine show limited diagnostic utility compared with plasma.

Investigating reproducibility and tracking provenance - A genomic workflow case study.

BACKGROUND: Computational bioinformatics workflows are extensively used to analyse genomics data, with different approaches available to support implementation and execution of these workflows. Reproducibility is one of the core principles for any scientific workflow and remains a challenge, which is not fully addressed. This is due to incomplete understanding of reproducibility requirements and assumptions of workflow definition approaches. Provenance information should be tracked and used to capture all these requirements supporting reusability of existing workflows. RESULTS: We have implemented a complex but widely deployed bioinformatics workflow using three representative approaches to workflow definition and execution. Through implementation, we identified assumptions implicit in these approaches that ultimately produce insufficient documentation of workflow requirements resulting in failed execution of the workflow. This study proposes a set of recommendations that aims to mitigate these assumptions and guides the scientific community to accomplish reproducible science, hence addressing reproducibility crisis. CONCLUSIONS: Reproducing, adapting or even repeating a bioinformatics workflow in any environment requires substantial technical knowledge of the workflow execution environment, resolving analysis assumptions and rigorous compliance with reproducibility requirements. Towards these goals, we propose conclusive recommendations that along with an explicit declaration of workflow specification would result in enhanced reproducibility of computational genomic analyses.

Monogenic diabetes syndromes: Locus-specific databases for Alström, Wolfram, and Thiamine-responsive megaloblastic anemia.

We developed a variant database for diabetes syndrome genes, using the Leiden Open Variation Database platform, containing observed phenotypes matched to the genetic variations. We populated it with 628 published disease-associated variants (December 2016) for: WFS1 (n = 309), CISD2 (n = 3), ALMS1 (n = 268), and SLC19A2 (n = 48) for Wolfram type 1, Wolfram type 2, Alström, and Thiamine-responsive megaloblastic anemia syndromes, respectively; and included 23 previously unpublished novel germline variants in WFS1 and 17 variants in ALMS1. We then investigated genotype-phenotype relations for the WFS1 gene. The presence of biallelic loss-of-function variants predicted Wolfram syndrome defined by insulin-dependent diabetes and optic atrophy, with a sensitivity of 79% (95% CI 75%-83%) and specificity of 92% (83%-97%). The presence of minor loss-of-function variants in WFS1 predicted isolated diabetes, isolated deafness, or isolated congenital cataracts without development of the full syndrome (sensitivity 100% [93%-100%]; specificity 78% [73%-82%]). The ability to provide a prognostic prediction based on genotype will lead to improvements in patient care and counseling. The development of the database as a repository for monogenic diabetes gene variants will allow prognostic predictions for other diabetes syndromes as next-generation sequencing expands the repertoire of genotypes and phenotypes. The database is publicly available online at https://lovd.euro-wabb.org.

The Australasian Diabetes Data Network: first national audit of children and adolescents with type 1 diabetes.

OBJECTIVES: To assess glycaemic control, anthropometry and insulin regimens in a national sample of Australian children and adolescents with type 1 diabetes. DESIGN: Cross-sectional analysis of de-identified, prospectively collected data from the Australasian Diabetes Data Network (ADDN) registry. SETTING: Five paediatric diabetes centres in New South Wales, Queensland, South Australia, Victoria and Western Australia. PARTICIPANTS: Children and adolescents (aged 18 years or under) with type 1 diabetes of at least 12 months' duration for whom data were added to the ADDN registry during 2015. MAIN OUTCOME MEASURES: Glycaemic control was assessed by measuring haemoglobin A1c (HbA1c) levels. Body mass index standard deviation scores (BMI-SDS) were calculated according to the CDC-2000 reference; overweight and obesity were defined by International Obesity Task Force guidelines. Insulin regimens were classified as twice-daily injections (BD), multiple daily injections (MDI; at least three injection times per day), or continuous subcutaneous insulin infusion (CSII). RESULTS: The mean age of the 3279 participants was 12.8 years (SD, 3.7), mean diabetes duration was 5.7 years (SD, 3.7), and mean HbA1c level 67 mmol/mol (SD, 15); only 27% achieved the national HbA1c target of less than 58 mmol/mol. The mean HbA1c level was lower in children under 6 (63 mmol/mol) than in adolescents (14-18 years; 69 mmol/mol). Mean BMI-SDS for all participants was 0.6 (SD, 0.9); 33% of the participants were overweight or obese. 44% were treated with CSII, 38% with MDI, 18% with BD. CONCLUSIONS: Most Australian children and adolescents with type 1 diabetes are not meeting the recognised HbA1c target. The prevalence of overweight and obesity is high. There is an urgent need to identify barriers to achieving optimal glycaemic control in this population.

SMPD1 Mutation Update: Database and Comprehensive Analysis of Published and Novel Variants.

Niemann-Pick Types A and B (NPA/B) diseases are autosomal recessive lysosomal storage disorders caused by the deficient activity of acid sphingomyelinase (ASM) because of the mutations in the SMPD1 gene. Here, we provide a comprehensive updated review of already reported and newly identified SMPD1 variants. Among them, 185 have been found in NPA/B patients. Disease-causing variants are equally distributed along the SMPD1 gene; most of them are missense (65.4%) or frameshift (19%) mutations. The most frequently reported mutation worldwide is the p.R610del, clearly associated with an attenuated NP disease type B phenotype. The available information about the impact of 52 SMPD1 variants on ASM mRNA and/or enzymatic activity has been collected and whenever possible, phenotype/genotype correlations were established. In addition, we created a locus-specific database easily accessible at http://www.inpdr.org/genes that catalogs the 417 SMPD1 variants reported to date and provides data on their in silico predicted effects on ASM protein function or mRNA splicing. The information reviewed in this article, providing new insights into the genotype/phenotype correlation, is extremely valuable to facilitate diagnosis and genetic counseling of families affected by NPA/B.

Biochemical diagnosis of phaeochromocytoma using plasma-free normetanephrine, metanephrine and methoxytyramine: importance of supine sampling under fasting conditions.

OBJECTIVE: To document the influences of blood sampling under supine fasting versus seated nonfasting conditions on diagnosis of phaeochromocytomas and paragangliomas (PPGL) using plasma concentrations of normetanephrine, metanephrine and methoxytyramine. DESIGN AND METHODS: Biochemical testing for PPGL was performed on 762 patients at six centres, two of which complied with requirements for supine sampling after an overnight fast and four of which did not. Phaeochromocytomas and paragangliomas were found in 129 patients (67 noncompliant, 62 compliant) and not in 633 patients (195 noncompliant, 438 compliant). RESULTS: Plasma concentrations of normetanephrine and methoxytyramine did not differ between compliant and noncompliant sampling conditions in patients with PPGL but were 49-51% higher in patients without PPGL sampled under noncompliant compared with compliant conditions. The 97·5 percentiles of distributions were also higher under noncompliant compared with compliant conditions for normetanephrine (1·29 vs 0·79 nmol/l), metanephrine (0·49 vs 0·41 nmol/l) and methoxytyramine (0·42 vs 0·18 nmol/l). Use of upper cut-offs established from seated nonfasting sampling conditions resulted in substantially decreased diagnostic sensitivity (98% vs 85%). In contrast, use of upper cut-offs established from supine fasting conditions resulted in decreased diagnostic specificity for testing under noncompliant compared with compliant conditions (71% vs 95%). CONCLUSIONS: High diagnostic sensitivity of plasma normetanephrine, metanephrine and methoxytyramine for the detection of PPGL can only be guaranteed using upper cut-offs of reference intervals established with blood sampling under supine fasting conditions. With such cut-offs, sampling under seated nonfasting conditions can lead to a 5·7-fold increase in false-positive results necessitating repeat sampling under supine fasting conditions.

Deaths by suicide and their relationship with general and psychiatric hospital discharge: 30-year record linkage study.

BACKGROUND: Studies have rarely explored suicides completed following discharge from both general and psychiatric hospital settings. Such research might identify additional opportunities for intervention. AIMS: To identify and summarise Scottish psychiatric and general hospital records for individuals who have died by suicide. METHOD: A linked data study of deaths by suicide, aged ≥15 years from 1981 to 2010. RESULTS: This study reports on a UK data-set of individuals who died by suicide (n = 16 411), of whom 66% (n = 10 907) had linkable previous hospital records. Those who died by suicide were 3.1 times more frequently last discharged from general than from psychiatric hospitals; 24% of deaths occurred within 3 months of hospital discharge (58% of these from a general hospital). Only 14% of those discharged from a general hospital had a recorded psychiatric diagnosis at last visit; an additional 19% were found to have a previous lifetime psychiatric diagnosis. Median time between last discharge and death was fourfold greater in those without a psychiatric history. Diagnoses also revealed that less than half of those last discharged from general hospital had had a main diagnosis of 'injury or poisoning'. CONCLUSIONS: Suicide prevention activity, including a better psychiatric evaluation of patients within general hospital settings deserves more attention. Improved information flow between secondary and primary care could be facilitated by exploiting electronic records of previous psychiatric diagnoses.

Environmental Determinants of Islet Autoimmunity (ENDIA) longitudinal prospective pregnancy to childhood cohort study of Australian children at risk of type 1 diabetes: parental demographics and birth information.

INTRODUCTION: The Environmental Determinants of Islet Autoimmunity (ENDIA) Study is an ongoing Australian prospective cohort study investigating how modifiable prenatal and early-life exposures drive the development of islet autoimmunity and type 1 diabetes (T1D) in children. In this profile, we describe the cohort's parental demographics, maternal and neonatal outcomes and human leukocyte antigen (HLA) genotypes. RESEARCH DESIGN AND METHODS: Inclusion criteria were an unborn child, or infant aged less than 6 months, with a first-degree relative (FDR) with T1D. The primary outcome was persistent islet autoimmunity, with children followed until a T1D diagnosis or 10 years of age. Demographic data were collected at enrollment. Lifestyle, clinical and anthropometric data were collected at each visit during pregnancy and clinical pregnancy and birth data were verified against medical case notes. Data were compared between mothers with and without T1D. HLA genotyping was performed on the ENDIA child and all available FDRs. RESULTS: The final cohort comprised 1473 infants born to 1214 gestational mothers across 1453 pregnancies, with 80% enrolled during pregnancy. The distribution of familial T1D probands was 62% maternal, 28% paternal and 11% sibling. The frequency of high-risk HLA genotypes was highest in T1D probands, followed by ENDIA infants, and lowest among unaffected family members. Mothers with T1D had higher rates of pregnancy complications and perinatal intervention, and larger babies of shorter gestation. Parent demographics were comparable to the Australian population for age, parity and obesity. A greater percentage of ENDIA parents were Australian born, lived in a major city and had higher socioeconomic advantage and education. CONCLUSIONS: This comprehensive profile provides the context for understanding ENDIA's scope, methodology, unique strengths and limitations. Now fully recruited, ENDIA will provide unique insights into the roles of early-life factors in the development of islet autoimmunity and T1D in the Australian environment. TRIAL REGISTRATION NUMBER: ACTRN12613000794707.

EURO-WABB: an EU rare diseases registry for Wolfram syndrome, Alström syndrome and Bardet-Biedl syndrome.

BACKGROUND: Wolfram, Alström and Bardet-Biedl (WABB) syndromes are rare diseases with overlapping features of multiple sensory and metabolic impairments, including diabetes mellitus, which have caused diagnostic confusion. There are as yet no specific treatments available, little or no access to well characterized cohorts of patients, and limited information on the natural history of the diseases. We aim to establish a Europe-wide registry for these diseases to inform patient care and research. METHODS: EURO-WABB is an international multicenter large-scale observational study capturing longitudinal clinical and outcome data for patients with WABB diagnoses. Three hundred participants will be recruited over 3 years from different sites throughout Europe. Comprehensive clinical, genetic and patient experience data will be collated into an anonymized disease registry. Data collection will be web-based, and forms part of the project's Virtual Research and Information Environment (VRIE). Participants who haven't undergone genetic diagnostic testing for their condition will be able to do so via the project. CONCLUSIONS: The registry data will be used to increase the understanding of the natural history of WABB diseases, to serve as an evidence base for clinical management, and to aid the identification of opportunities for intervention to stop or delay the progress of the disease. The detailed clinical characterisation will allow inclusion of patients into studies of novel treatment interventions, including targeted interventions in small scale open label studies; and enrolment into multi-national clinical trials. The registry will also support wider access to genetic testing, and encourage international collaborations for patient benefit.

A GDPR-Compliant Dynamic Consent Mobile Application for the Australasian Type-1 Diabetes Data Network.

Australia has a high prevalence of diabetes, with approximately 1.2 million Australians diagnosed with the disease. In 2012, the Australasian Diabetes Data Network (ADDN) was established with funding from the Juvenile Diabetes Research Foundation (JDRF). ADDN is a national diabetes registry which captures longitudinal information about patients with type-1 diabetes (T1D). Currently, the ADDN data are directly contributed from 42 paediatric and 17 adult diabetes centres across Australia and New Zealand, i.e., where the data are pre-existing in hospital systems and not manually entered into ADDN. The historical data in ADDN have been de-identified, and patients are initially afforded the opportunity to opt-out of being involved in the registry; however, moving forward, there is an increased demand from the clinical research community to utilise fully identifying data. This raises additional demands on the registry in terms of security, privacy, and the nature of patient consent. General Data Protection Regulation (GDPR) is an increasingly important mechanism allowing individuals to have the right to know about their health data and what those data are being used for. This paper presents a mobile application being designed to support the ADDN data collection and usage processes and aligning them with GDPR. The app utilises Dynamic Consent-an informed specific consent model, which allows participants to view and modify their research-driven consent decisions through an interactive interface. It focuses specifically on supporting dynamic opt-in consent to both the registry and to associated sub-projects requesting access to and use of the patient data for research purposes.

A surge in serum mucosal cytokines associated with seroconversion in children at risk for type 1 diabetes.

AIMS/INTRODUCTION: Autoantibodies to pancreatic islet antigens identify young children at high risk of type 1 diabetes. On a background of genetic susceptibility, islet autoimmunity is thought to be driven by environmental factors, of which enteric viruses are prime candidates. We sought evidence for enteric pathology in children genetically at-risk for type 1 diabetes followed from birth who had developed islet autoantibodies ("seroconverted"), by measuring mucosa-associated cytokines in their sera. MATERIALS AND METHODS: Sera were collected 3 monthly from birth from children with a first-degree type 1 diabetes relative, in the Environmental Determinants of Islet Autoimmunity (ENDIA) study. Children who seroconverted were matched for sex, age, and sample availability with seronegative children. Luminex xMap technology was used to measure serum cytokines. RESULTS: Of eight children who seroconverted, for whom serum samples were available at least 6 months before and after seroconversion, the serum concentrations of mucosa-associated cytokines IL-21, IL-22, IL-25, and IL-10, the Th17-related cytokines IL-17F and IL-23, as well as IL-33, IFN-γ, and IL-4, peaked from a low baseline in seven around the time of seroconversion and in one preceding seroconversion. These changes were not detected in eight sex- and age-matched seronegative controls, or in a separate cohort of 11 unmatched seronegative children. CONCLUSIONS: In a cohort of children at risk for type 1 diabetes followed from birth, a transient, systemic increase in mucosa-associated cytokines around the time of seroconversion lends support to the view that mucosal infection, e.g., by an enteric virus, may drive the development of islet autoimmunity.

Protocol for a nested case-control study design for omics investigations in the Environmental Determinants of Islet Autoimmunity cohort.

Background: The Environmental Determinants of Islet Autoimmunity (ENDIA) pregnancy-birth cohort investigates the developmental origins of type 1 diabetes (T1D), with recruitment between 2013 and 2019. ENDIA is the first study in the world with comprehensive data and biospecimen collection during pregnancy, at birth and through childhood from at-risk children who have a first-degree relative with T1D. Environmental exposures are thought to drive the progression to clinical T1D, with pancreatic islet autoimmunity (IA) developing in genetically susceptible individuals. The exposures and key molecular mechanisms driving this progression are unknown. Persistent IA is the primary outcome of ENDIA; defined as a positive antibody for at least one of IAA, GAD, ZnT8 or IA2 on two consecutive occasions and signifies high risk of clinical T1D.Method: A nested case-control (NCC) study design with 54 cases and 161 matched controls aims to investigate associations between persistent IA and longitudinal omics exposures in ENDIA. The NCC study will analyse samples obtained from ENDIA children who have either developed persistent IA or progressed to clinical T1D (cases) and matched control children at risk of developing persistent IA. Control children were matched on sex and age, with all four autoantibodies absent within a defined window of the case's onset date. Cases seroconverted at a median of 1.37 years (IQR 0.95, 2.56). Longitudinal omics data generated from approximately 16,000 samples of different biospecimen types, will enable evaluation of changes from pregnancy through childhood.Conclusions: This paper describes the ENDIA NCC study, omics platform design considerations and planned univariate and multivariate analyses for its longitudinal data. Methodologies for multivariate omics analysis with longitudinal data are discovery-focused and data driven. There is currently no single multivariate method tailored specifically for the longitudinal omics data that the ENDIA NCC study will generate and therefore omics analysis results will require either cross validation or independent validation.KEY MESSAGESThe ENDIA nested case-control study will utilize longitudinal omics data on approximately 16,000 samples from 190 unique children at risk of type 1 diabetes (T1D), including 54 who have developed islet autoimmunity (IA), followed during pregnancy, at birth and during early childhood, enabling the developmental origins of T1D to be explored.