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Individuals with autism spectrum disorder (ASD), in addition to the core features of the disease, experience a higher burden of co-occurring medical conditions. This study sought to describe the frequency and distribution of comorbidit conditions in individuals with ASD, and systematically evaluate the possibility that pre- and postnatal exposures (e.g., preterm birth, hypoxia at birth, traumatic brain injury, and fetal alcohol syndrome) associated with ASD may also be linked with distinct comorbidities. We used the SPARK study database, launched by the Simons Foundation Autism Research Initiative (SFARI). Comorbidities considered in the study included neurological, cognitive, psychiatric, and physical conditions. The study sample consisted of 42,569 individuals with ASD and their 11,389 non-ASD siblings (full and half siblings). Majority (74%) of individuals with ASD had at least one comorbidity, and had a greater average number of comorbidities than their non-ASD siblings. Preterm birth and hypoxia at birth were the most common peri-natal exposures in the sample. In logistic regression models adjusted for covariates, these exposures were associated with several distinct comorbidities in ASD cases, including attention and behavior problems, psychiatric and neurological disorders, and growth conditions. A similar pattern of association was also observed in non-ASD siblings. Our findings underscore that individuals with ASD experience a greater burden of comorbidities, which could be partly attributable to the higher rates of perinatal exposures compared to their non-ASD siblings. Study findings, if replicated in other samples, can inform the etiology of comorbidity in ASD.

Background Postpartum depression (PPD) can result in negative personal and child developmental outcomes. Only a few large population‐based studies of PPD have used clinical diagnoses of depression and no study has examined how a maternal depression history interacts with known risk factors. The objective of this study was to examine the impact of a depression history on PPD and pre‐ and perinatal risk factors. Methods A nationwide prospective cohort study of all women with live singleton births in Sweden from 1997 through 2008 was conducted. Relative risk (RR) of clinical depression within the first year postpartum and two‐sided 95% confidence intervals were estimated. Results The RR of PPD in women with a history of depression was estimated at 21.03 (confidence interval: 19.72–22.42), compared to those without. Among all women, PPD risk increased with advanced age (1.25 (1.13–1.37)) and gestational diabetes (1.70 (1.36–2.13)). Among women with a history of depression, pregestational diabetes (1.49 (1.01–2.21)) and mild preterm delivery also increased risk (1.20 (1.06–1.36)). Among women with no depression history, young age (2.14 (1.79–2.57)), undergoing instrument‐assisted (1.23 (1.09–1.38)) or cesarean (1.64(1.07–2.50)) delivery, and moderate preterm delivery increased risk (1.36 (1.05–1.75)). Rates of PPD decreased considerably after the first postpartum month (RR = 0.27). Conclusion In the largest population‐based study to date, the risk of PPD was more than 20 times higher for women with a depression history, compared to women without. Gestational diabetes was independently associated with a modestly increased PPD risk. Maternal depression history also had a modifying effect on pre‐ and perinatal PPD risk factors.

The COVID-19 pandemic and mitigation measures are likely to have a marked effect on mental health. It is important to use longitudinal data to improve inferences. To quantify the prevalence of depression, anxiety and mental well-being before and during the COVID-19 pandemic. Also, to identify groups at risk of depression and/or anxiety during the pandemic. Data were from the Avon Longitudinal Study of Parents and Children (ALSPAC) index generation (n = 2850, mean age 28 years) and parent generation (n = 3720, mean age 59 years), and Generation Scotland (n = 4233, mean age 59 years). Depression was measured with the Short Mood and Feelings Questionnaire in ALSPAC and the Patient Health Questionnaire-9 in Generation Scotland. Anxiety and mental well-being were measured with the Generalised Anxiety Disorder Assessment-7 and the Short Warwick Edinburgh Mental Wellbeing Scale. Depression during the pandemic was similar to pre-pandemic levels in the ALSPAC index generation, but those experiencing anxiety had almost doubled, at 24% (95% CI 23-26%) compared with a pre-pandemic level of 13% (95% CI 12-14%). In both studies, anxiety and depression during the pandemic was greater in younger members, women, those with pre-existing mental/physical health conditions and individuals in socioeconomic adversity, even when controlling for pre-pandemic anxiety and depression. These results provide evidence for increased anxiety in young people that is coincident with the pandemic. Specific groups are at elevated risk of depression and anxiety during the COVID-19 pandemic. This is important for planning current mental health provisions and for long-term impact beyond this pandemic.

Genetic and environmental factors contribute to the etiologies of autism spectrum disorder (ASD), but evidence of specific environmental exposures and susceptibility windows is limited. Here we study monozygotic and dizygotic twins discordant for ASD to test whether fetal and postnatal metal dysregulation increases ASD risk. Using validated tooth-matrix biomarkers, we estimate pre- and post-natal exposure profiles of essential and toxic elements. Significant divergences are apparent in metal uptake between ASD cases and their control siblings, but only during discrete developmental periods. Cases have reduced uptake of essential elements manganese and zinc, and higher uptake of the neurotoxin lead. Manganese and lead are also correlated with ASD severity and autistic traits. Our study suggests that metal toxicant uptake and essential element deficiency during specific developmental windows increases ASD risk and severity, supporting the hypothesis of systemic elemental dysregulation in ASD. Independent replication in population-based studies is needed to extend these findings. The contribution of metal exposure to the etiology of ASD is unclear. Here the authors tested whether elemental dysregulation contributes to ASD risk by analysing tooth metal biomarkers from ASD discordant twins, and found significant differences in metal uptake between ASD cases and their control twin siblings, but only during certain developmental periods.

Hoarding disorder is typified by persistent difficulties discarding possessions, resulting in significant clutter that obstructs the individual's living environment and produces considerable functional impairment. The prevalence of hoarding disorder, as defined in DSM-5, is currently unknown. To provide a prevalence estimate specific to DSM-5 hoarding disorder and to delineate the demographic, behavioural and health features that characterise individuals with the disorder. We conducted a two-wave epidemiological study of 1698 adult individuals, originally recruited via the South East London Community Health (SELCoH) study. Participants screening positively for hoarding difficulties in wave 1, and who agreed to be re-contacted for wave 2 (n = 99), underwent in-home psychiatric interviews and completed a battery of self-report questionnaires. Current DSM-5 diagnoses were made via consensus diagnostic procedure. In total, 19 individuals met DSM-5 criteria for hoarding disorder at the time of interview, corresponding to a weighted prevalence of 1.5% (95% CI 0.7-2.2). Those with hoarding disorder were older and more often unmarried (67%). Members of this group were also more likely to be impaired by a current physical health condition (52.6%) or comorbid mental disorder (58%), and to claim benefits as a result of these issues (47.4%). Individuals with hoarding disorder were also more likely to report lifetime use of mental health services, although access in the past year was less frequent. With a lower-bound prevalence of approximately 1.5%, hoarding disorder presents as a condition that affects people of both genders and is associated with substantial adversity.

A knowledge gap exists about the risk of cancer in individuals with intellectual disability (ID). The primary aim of this study was to estimate the cancer risk among individuals with ID compared to individuals without ID. We conducted a population-based cohort study of all children live-born in Sweden between 1974 and 2013 and whose mothers were born in a Nordic country. All individuals were followed from birth until cancer diagnosis, emigration, death, or 31 December 2016 (up to age 43 years), whichever came first. Incident cancers were identified from the Swedish Cancer Register. We fitted Cox regression models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) as measures of cancer risk in relation to ID after adjusting for several potential confounders. We analyzed ID by severity, as well as idiopathic ID and syndromic ID separately. We performed a sibling comparison to investigate familial confounding. The study cohort included a total of 3,531,305 individuals, including 27,956 (0.8%) individuals diagnosed with ID. Compared with the reference group (individuals without ID and without a full sibling with ID), individuals with ID were in general more likely to be male. The median follow-up time was 8.9 and 23.0 years for individuals with ID and individuals without ID, respectively. A total of 188 cancer cases were identified among individuals with ID (incidence rate [IR], 62 per 1,000 person-years), and 24,960 among individuals in the reference group (IR, 31 per 1,000 person-years). A statistically significantly increased risk was observed for any cancer (HR 1.57, 95% CI 1.35-1.82; P < 0.001), as well as for several cancer types, including cancers of the esophagus (HR 28.4, 95% CI 6.2-130.6; P < 0.001), stomach (HR 6.1, 95% CI 1.5-24.9; P = 0.013), small intestine (HR 12.0, 95% CI 2.9-50.1; P < 0.001), colon (HR 2.0, 95% CI 1.0-4.1; P = 0.045), pancreas (HR 6.0, 95% CI 1.5-24.8; P = 0.013), uterus (HR 11.7, 95% CI 1.5-90.7; P = 0.019), kidney (HR 4.4, 95% CI 2.0-9.8; P < 0.001), central nervous system (HR 2.7, 95% CI 2.0-3.7; P < 0.001), and other or unspecified sites (HR 4.8, 95% CI 1.8-12.9; P = 0.002), as well as acute lymphoid leukemia (HR 2.4, 95% CI 1.3-4.4; P = 0.003) and acute myeloid leukemia (HR 3.0, 95% CI 1.4-6.4; P = 0.004). Cancer risk was not modified by ID severity or sex but was higher for syndromic ID. The sibling comparison showed little support for familial confounding. The main study limitations were the limited statistical power for the analyses of specific cancer types, and the potential for underestimation of the studied associations (e.g., due to potential underdetection or delayed diagnosis of cancer among individuals with ID). In this study, we found that individuals with ID showed an increased risk of any cancer, as well as of several specific cancer types. These findings suggest that extended surveillance and early intervention for cancer among individuals with ID are warranted.

[...]with advances in neonatal care, the survival for very preterm babies has improved, but longer-term risks in this group have not been comprehensively investigated. ASD has a male predominance, and size at birth is known to influence ASD risk, with increased risks in children born either small or large for GA [27–29]. [...]sex and size for GA should be considered in analyses of ASD risk by GA. To adjust for differences in birth weight, sex-specific size for GA was calculated as “small for GA” (below or equal to the 10th percentile), “appropriate for GA” (between the 11th and 90th percentile), and “large for GA” (above the 90th percentile) [36]. Cohort characteristics by gestational age (weeks) in 3,526,174 live births. https://doi.org/10.1371/journal.pmed.1003207.t001 Risk of ASD The risk of ASD by GA showed a gradual increase in risk of ASD from GA week 40 to GA week 24, and a small rise between GA week 40 and 44, with statistically significantly higher risk across the range of GA compared to the reference group of infants born week 40.

Lower urinary tract symptoms (LUTS), e.g., urinary frequency, pressure, urgency, and overactive bladder syndrome, are commonly reported in children with attention-deficit/hyperactivity disorder (ADHD). Understanding the co-occurrence of these conditions has implications regarding clinical approaches, treatments, and improved quality of life. We conducted a systematic review and meta-analysis to examine the relationships between LUTS and ADHD in children. We searched for articles published between January 1990 and July 2019, in PubMed, CENTRAL, and PsycNet. Two authors independently screened all articles and extracted data. We performed random-effect meta-analyses for ADHD with pooled outcomes for LUTS. We identified 119 relevant articles in the literature and 18 articles fulfilled the inclusion criteria for the systematic review, of which, 5 articles had sufficient data for meta-analysis. Examining ADHD among individuals with LUTS, the odds ratio was 2.99 (95% CI 1.13, 7.88, p  < 0.001), compared to controls. In multiple studies, the mean overall score for LUTS, using a standardized measure, was significantly higher in patients with ADHD in comparison to controls, and the severity of ADHD was positively associated with the severity of LUTS. Younger age in children was correlated with a higher LUTS score. Different subtypes of urinary incontinence demonstrated differences in behavioral problems and psychiatric comorbidity. Sex differences in LUTS were not consistent across articles. Our results indicate clinically significant associations between ADHD and LUTS in children. Because LUTS and ADHD are common disorders in children, clinicians should be aware of these associations as they inform optimal assessment and treatment strategies.

Information on neurodevelopmental effects of antenatal exposure to antipsychotics is limited to 10 studies, all examining children up to 5 years of age or less. The paper aimed to investigate the association between in utero exposure to antipsychotics and psychiatric outcomes in children using Danish nationwide registers. In total, 9011 liveborn singletons born 1998–2015 in Denmark whose mothers took antipsychotic medication before pregnancy were identified. Children whose mothers continued to take antipsychotics during pregnancy were compared with children of mothers who discontinued antipsychotics before pregnancy. As a negative control, paternal antipsychotic use in the same window was investigated. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazards regression for the primary outcome of psychiatric disorders, as well for subcategories of psychiatric disorders. In total, 9.9% of children in the discontinuation group and 11.0% of children in the continuation group received a psychiatric disorder diagnosis during follow-up. The adjusted HR for psychiatric disorders among offspring in the continuation group compared to the discontinuation group was 1.10 (95% CI 0.93–1.30). For antipsychotic use in the fathers, the HR was 1.05 (95% CI 0.89–1.24). The study does not provide evidence of increased risk of psychiatric disorders among children of women who continue antipsychotic treatment during pregnancy. This was observed after accounting for the underlying risk conferred by maternal psychiatric disorders. This suggests women who need to continue antipsychotic medications during pregnancy can do so without adverse psychiatric outcomes for offspring.

Current approaches for early identification of individuals at high risk for autism spectrum disorder (ASD) in the general population are limited, and most ASD patients are not identified until after the age of 4. This is despite substantial evidence suggesting that early diagnosis and intervention improves developmental course and outcome. The aim of the current study was to test the ability of machine learning (ML) models applied to electronic medical records (EMRs) to predict ASD early in life, in a general population sample. We used EMR data from a single Israeli Health Maintenance Organization, including EMR information for parents of 1,397 ASD children (ICD-9/10) and 94,741 non-ASD children born between January 1st, 1997 and December 31st, 2008. Routinely available parental sociodemographic information, parental medical histories, and prescribed medications data were used to generate features to train various ML algorithms, including multivariate logistic regression, artificial neural networks, and random forest. Prediction performance was evaluated with 10-fold cross-validation by computing the area under the receiver operating characteristic curve (AUC; C-statistic), sensitivity, specificity, accuracy, false positive rate, and precision (positive predictive value [PPV]). All ML models tested had similar performance. The average performance across all models had C-statistic of 0.709, sensitivity of 29.93%, specificity of 98.18%, accuracy of 95.62%, false positive rate of 1.81%, and PPV of 43.35% for predicting ASD in this dataset. We conclude that ML algorithms combined with EMR capture early life ASD risk as well as reveal previously unknown features to be associated with ASD-risk. Such approaches may be able to enhance the ability for accurate and efficient early detection of ASD in large populations of children.