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While the concept of big data has emerged over the past decade as a hot topic in nearly all areas of scientific inquiry, it has rarely been discussed in the context of autism research. In this commentary we describe aspects of big data that are relevant to autism research and methodological issues such as confounding and data error that can hamper scientific investigation. Although big data studies can have transformative impact, bigger is not always better, and big data require the same methodological considerations and interdisciplinary collaboration as "small data" to extract useful scientific insight. Lay Summary: This commentary explains how big data can be used in autism research and the challenges that come with it, like confounding factors and data errors. Eventhough big data can have a big impact, it is not always better. Big data needs to be handled carefully and with collaboration from different fields to get the most out of it. [ABSTRACT FROM AUTHOR]

Food allergies are frequently reported to co‐occur with autism spectrum disorder (ASD), but the prevalence of this co‐occurrence remains uncertain. In the present study, we examined parent‐reported prevalence of co‐occurring food allergy and ASD in a nationally representative sample of US children ages 2–17 in the National Health Interview Survey, study years 2011–2015. All analyses used survey weights to account for the complex sampling design. In the analytic sample of 53,365 children ages 2–17, there were 905 children with parent‐reported ASD (prevalence of 1.7%) and 2,977 children with parent‐reported food allergy (prevalence of 5.6%). Parent‐reported food allergies were nearly 2.5 times more common in children with ASD (prevalence of 13.1%) than in children without ASD (5.4%). These results indicate that food allergies commonly co‐occur with ASD, which may have etiological implications. Autism Research 2019, 12: 802–805. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. Lay Summary: Food allergies are frequently reported to occur with autism spectrum disorder (ASD), but the prevalence of this co‐occurrence remains uncertain. In the present study, we examined parent‐reported prevalence of co‐occurring food allergy and ASD in a nationally representative sample of United States children. In the sample of 53,365 children ages 2–17, 1.7% of children were reported to have ASD, and 5.6% were reported to have food allergies. Parent‐reported food allergies were nearly 2.5 times more common in children with ASD (13.1%) than in children without ASD (5.4%). [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with lifelong impacts. Genetic and environmental factors contribute to ASD etiology, which remains incompletely understood. Research on ASD epidemiology has made significant advances in the past decade. Current prevalence is estimated to be at least 1.5% in developed countries, with recent increases primarily among those without comorbid intellectual disability. Genetic studies have identified a number of rare de novo mutations and gained footing in the areas of polygenic risk, epigenetics, and gene-by-environment interaction. Epidemiologic investigations focused on nongenetic factors have established advanced parental age and preterm birth as ASD risk factors, indicated that prenatal exposure to air pollution and short interpregnancy interval are potential risk factors, and suggested the need for further exploration of certain prenatal nutrients, metabolic conditions, and exposure to endocrine-disrupting chemicals. We discuss future challenges and goals for ASD epidemiology as well as public health implications. [ABSTRACT FROM AUTHOR]

Animal models indicate that maternal infection during pregnancy can result in behavioral abnormalities and neuropathologies in offspring. We examined the association between maternal inpatient diagnosis with infection during pregnancy and risk of ASD in a Swedish nationwide register-based birth cohort born 1984–2007 with follow-up through 2011. In total, the sample consisted of 2,371,403 persons with 24,414 ASD cases. Infection during pregnancy was defined from ICD codes. In the sample, 903 mothers of ASD cases (3.7%) had an inpatient diagnosis of infection during pregnancy. Logistic regression models adjusted for a number of covariates yielded odds ratios indicating approximately a 30% increase in ASD risk associated with any inpatient diagnosis of infection. Timing of infection did not appear to influence risk in the total Swedish population, since elevated risk of ASD was associated with infection in all trimesters. In a subsample analysis, infections were associated with greater risk of ASD with intellectual disability than for ASD without intellectual disability. The present study adds to the growing body of evidence, encompassing both animal and human studies, that supports possible immune-mediated mechanisms underlying the etiology of ASD. [ABSTRACT FROM AUTHOR]

Purpose Meconium is a biomarker matrix that can be used to assess cumulative exposures in epidemiologic studies of prenatal risk factors. Depending on when meconium is collected, different exposure windows during pregnancy can be measured. However, little guidance exists regarding the extent to which timing of meconium collection will influence resulting effect estimates. Methods We performed a simulation study of prenatal tobacco smoke exposure (assessed from meconium nicotine) and birth weight. We discuss four typical meconium collection methods capturing different exposure windows and assess the biases induced by these methods. Results In simulations assuming that exposure to tobacco smoke only during late gestation was of etiologic relevance to birth weight, use of a meconium collection method that captured exposure windows other than late gestation resulted in biased estimates of the true nicotine–birth weight association. Conclusions Using meconium collection methods that do not reflect an exposure window of etiologic relevance can lead to biased results and erroneous conclusions regarding the nature of prenatal exposure–outcome associations. Understanding how prenatal exposure patterns vary across the pregnancy and exposure windows of etiologic relevance is essential in determining when and how to collect meconium for use in biomarker studies of prenatal exposure. [ABSTRACT FROM AUTHOR]

A growing body of literature suggests that exposure to infections, particularly maternal infections, during pregnancy confers risk for later development of psychotic disorder. Though brain development proceeds throughout childhood and adolescence, the influence of infections during these ages on subsequent psychosis risk is insufficiently examined. The aim of this study was to investigate the potential association between infections during childhood and nonaffective psychoses in a large population-based birth cohort with follow up long enough to include peak incidence of nonaffective psychosis. We included all individuals born in Sweden between 1973 and 1985, (N = 1172879), with follow up on first time inpatient care with nonaffective psychosis from age 14 years until 2006, (N = 4638). Following adjustment for differences in sex, socioeconomic status, family history of psychosis, and hospital admissions involving noninfectious, nonpsychiatric care, we observed a small but statistically significant association between hospital admissions for infections, in general, throughout childhood (0–13 years) and a later diagnosis of nonaffective psychosis, hazard ratio (HR) = 1.10 (95% CI 1.03–1.18), and this association seemed to be driven by bacterial infection, HR = 1.23 (95% CI 1.08–1.40). Bacterial infections and central nervous system infections during preadolescence (10–13 years) conferred the strongest risk, HR 1.57 (95% CI 1.21–2.05) and HR 1.96 (95% CI 1.05–3.62), respectively. Although preadolescence appeared to be a vulnerable age period, and bacterial infection the most severe in relation to psychosis development, the present findings can also indicate an increased susceptibility to hospital admission for infections among children who will later develop nonaffective psychosis due to social or familial/genetic factors. [ABSTRACT FROM PUBLISHER]

The article presents a population based case-control study of the offspring at a risk of autism spectrum disorder, particularly autism without intellectual disability whose mothers used antidepressants during pregnancy. Conditional logistic regression analysis displaying the relation between maternal depression, antidepressant use during pregnancy, and autism spectrum disorder in offspring (with and without intellectual disability) is also presented.

Background Attention-deficit/hyperactivity disorder (ADHD) is the most common childhood neurodevelopmental disorder, and boys are two to three times more likely to develop ADHD. Maternal polycystic ovary syndrome (PCOS), a common metabolic disorder associated with excess circulating androgens, has been associated with increased risk for autism spectrum disorder in the offspring. In this study, we aimed to investigate whether maternal PCOS increases the risk for ADHD in the offspring. Methods We conducted a matched case-control study using health and population data registers for all children born in Sweden from 1984 to 2008. Maternal PCOS was defined by ICD-coded register diagnosis. The outcome of ADHD was defined as an ICD-coded register diagnosis of ADHD and/or registered prescription of medications to treat ADHD. A total of 58,912 ADHD cases (68.8% male) were identified and matched to 499,998 unaffected controls by sex and birth month and year. Results Maternal PCOS increased the odds of offspring ADHD by 42% after adjustment for confounders (odds ratio [OR], 1.42; 95% confidence interval [CI], 1.26–1.58). Exclusion of ADHD cases with comorbid autism spectrum disorder attenuated but did not explain the relationship (OR, 1.34; 95% CI, 1.18–1.52). The risk was somewhat elevated for ADHD with comorbid autism spectrum disorder (OR, 1.76; 95% CI, 1.37–2.26). The risk for ADHD was higher among obese mothers with PCOS (OR, 1.68; 95% CI, 1.31–2.17) and was highest among obese mothers with PCOS and other features of metabolic syndrome (OR, 2.59; 95% CI, 1.02–6.58). Conclusions This study provides evidence that maternal PCOS may subtly influence the neurodevelopment of the offspring, resulting in increased risk for neurodevelopmental disorders such as ADHD. [ABSTRACT FROM AUTHOR]