A risk calculator to predict adult attention-deficit/hyperactivity disorder: generation and external validation in three birth cohorts and one clinical sample.

AIM: Few personalised medicine investigations have been conducted for mental health. We aimed to generate and validate a risk tool that predicts adult attention-deficit/hyperactivity disorder (ADHD). METHODS: Using logistic regression models, we generated a risk tool in a representative population cohort (ALSPAC - UK, 5113 participants, followed from birth to age 17) using childhood clinical and sociodemographic data with internal validation. Predictors included sex, socioeconomic status, single-parent family, ADHD symptoms, comorbid disruptive disorders, childhood maltreatment, ADHD symptoms, depressive symptoms, mother's depression and intelligence quotient. The outcome was defined as a categorical diagnosis of ADHD in young adulthood without requiring age at onset criteria. We also tested Machine Learning approaches for developing the risk models: Random Forest, Stochastic Gradient Boosting and Artificial Neural Network. The risk tool was externally validated in the E-Risk cohort (UK, 2040 participants, birth to age 18), the 1993 Pelotas Birth Cohort (Brazil, 3911 participants, birth to age 18) and the MTA clinical sample (USA, 476 children with ADHD and 241 controls followed for 16 years from a minimum of 8 and a maximum of 26 years old). RESULTS: The overall prevalence of adult ADHD ranged from 8.1 to 12% in the population-based samples, and was 28.6% in the clinical sample. The internal performance of the model in the generating sample was good, with an area under the curve (AUC) for predicting adult ADHD of 0.82 (95% confidence interval (CI) 0.79-0.83). Calibration plots showed good agreement between predicted and observed event frequencies from 0 to 60% probability. In the UK birth cohort test sample, the AUC was 0.75 (95% CI 0.71-0.78). In the Brazilian birth cohort test sample, the AUC was significantly lower -0.57 (95% CI 0.54-0.60). In the clinical trial test sample, the AUC was 0.76 (95% CI 0.73-0.80). The risk model did not predict adult anxiety or major depressive disorder. Machine Learning approaches did not outperform logistic regression models. An open-source and free risk calculator was generated for clinical use and is available online at https://ufrgs.br/prodah/adhd-calculator/. CONCLUSIONS: The risk tool based on childhood characteristics specifically predicts adult ADHD in European and North-American population-based and clinical samples with comparable discrimination to commonly used clinical tools in internal medicine and higher than most previous attempts for mental and neurological disorders. However, its use in middle-income settings requires caution.

The role of allelic variation in estrogen receptor genes and major depression in the Nurses Health Study.

PURPOSE: The role of exogenous and endogenous sex hormones in the etiology of depression remains elusive, in part because sex hormone variation is often correlated with behaviors, life stage changes, and other factors that may influence depression. Estrogen receptor alpha (ESR1) and beta (ESR2) are known to regulate gene expression and estrogen response in areas of the brain associated with major depression and are unlikely to be correlated with exogenous factors that may influence depression. METHODS: We examined whether functional polymorphisms in these genes are associated with lifetime major depression and chronic major depression among a sample of women from the Nurses' Health Study II (N = 2527). DSM-IV depressive disorder symptoms were assessed by structured interview in 2007. Genotyping was performed on DNA extracted from blood using Taq-man. RESULTS: Women with the AA alleles of ESR2 RS4986938 had the higher prevalence of lifetime major depression than women with other allele frequencies (36.7 % for those with AA versus 28.5 % with GA and 29.1 % with GG, p = 0.02) and chronic major depression (14.7 % for those with AA versus 9.3 % with GA and 9.1 % with GG, p = 0.01). History of post-menopausal hormone (PMH) use modified the association of ESR1 polymorphism RS2234693 with any lifetime depression; specifically, those with the TT allele had the highest risk of lifetime depression among PMH users, and the lowest risk of depression among non-PMH users (p value for interaction = 0.02). Further, carriers of the AA alleles in ESR1 polymorphism RS9340799 had increased prevalence of lifetime major depression only among lifetime PMH users (p = 0.007). CONCLUSIONS: Our findings support the hypothesis that estrogen receptor polymorphisms influence risk for major depression; the role of estrogen receptors and other sex steroid-related genetic factors may provide unique insights into etiology.

Childhood maltreatment, juvenile disorders and adult post-traumatic stress disorder: a prospective investigation.

BACKGROUND: We examine prospectively the influence of two separate but potentially inter-related factors in the etiology of post-traumatic stress disorder (PTSD): childhood maltreatment as conferring a susceptibility to the PTSD response to adult trauma and juvenile disorders as precursors of adult PTSD. METHOD: The Dunedin Multidisciplinary Health and Development Study (DMHDS) is a birth cohort (n = 1037) from the general population of New Zealand's South Island, with multiple assessments up to age 38 years. DSM-IV PTSD was assessed among participants exposed to trauma at ages 26-38. Complete data were available on 928 participants. RESULTS: Severe maltreatment in the first decade of life, experienced by 8.5% of the sample, was associated significantly with the risk of PTSD among those exposed to adult trauma [odds ratio (OR) 2.64, 95% confidence interval (CI) 1.16-6.01], compared to no maltreatment. Moderate maltreatment, experienced by 27.2%, was not associated significantly with that risk (OR 1.55, 95% CI 0.85-2.85). However, the two estimates did not differ significantly from one another. Juvenile disorders (ages 11-15), experienced by 35% of the sample, independent of childhood maltreatment, were associated significantly with the risk of PTSD response to adult trauma (OR 2.35, 95% CI 1.32-4.18). CONCLUSIONS: Severe maltreatment is associated with risk of PTSD response to adult trauma, compared to no maltreatment, and juvenile disorders, independent of earlier maltreatment, are associated with that risk. The role of moderate maltreatment remains unresolved. Larger longitudinal studies are needed to assess the impact of moderate maltreatment, experienced by the majority of adult trauma victims with a history of maltreatment.

Neuropsychological performance and family history in children at age 7 who develop adult schizophrenia or bipolar psychosis in the New England Family Studies.

BACKGROUND: Persons developing schizophrenia (SCZ) manifest various pre-morbid neuropsychological deficits, studied most often by measures of IQ. Far less is known about pre-morbid neuropsychological functioning in individuals who later develop bipolar psychoses (BP). We evaluated the specificity and impact of family history (FH) of psychosis on pre-morbid neuropsychological functioning. METHOD: We conducted a nested case-control study investigating the associations of neuropsychological data collected systematically at age 7 years for 99 adults with psychotic diagnoses (including 45 SCZ and 35 BP) and 101 controls, drawn from the New England cohort of the Collaborative Perinatal Project (CPP). A mixed-model approach evaluated full-scale IQ, four neuropsychological factors derived from principal components analysis (PCA), and the profile of 10 intelligence and achievement tests, controlling for maternal education, race and intra-familial correlation. We used a deviant responder approach (<10th percentile) to calculate rates of impairment. RESULTS: There was a significant linear trend, with the SCZ group performing worst. The profile of childhood deficits for persons with SCZ did not differ significantly from BP. Neuropsychological impairment was identified in 42.2% of SCZ, 22.9% of BP and 7% of controls. The presence of psychosis in first-degree relatives (FH+) significantly increased the severity of childhood impairment for SCZ but not for BP. CONCLUSIONS: Pre-morbid neuropsychological deficits are found in a substantial proportion of children who later develop SCZ, especially in the SCZ FH+ subgroup, but less so in BP, suggesting especially impaired neurodevelopment underlying cognition in pre-SCZ children. Future work should assess genetic and environmental factors that explain this FH effect.

Measuring quality of care for rheumatic diseases using an electronic medical record.

OBJECTIVES: The objective of this study was twofold: (1) to determine how best to measure adherence with time-dependent quality indicators (QIs) related to laboratory monitoring, and (2) to assess the accuracy and efficiency of gathering QI adherence information from an electronic medical record (EMR). METHODS: A random sample of 100 patients were selected who had at least three visits with the diagnosis of rheumatoid arthritis (RA) at Brigham and Women's Hospital Arthritis Center in 2005. Using the EMR, it was determined whether patients had been prescribed a disease-modifying antirheumatic drug (DMARD) (QI #1) and if patients starting therapy received appropriate baseline laboratory testing (QI #2). For patients consistently prescribed a DMARD, adherence with follow-up testing (QI #3) was calculated using three different methods, the Calendar, Interval and Rolling Interval METHOD: . RESULTS: It was found that 97% of patients were prescribed a DMARD (QI #1) and baseline tests were completed in 50% of patients (QI #2). For follow-up testing (QI #3), mean adherence was 60% for the Calendar Method, 35% for the Interval Method, and 48% for the Rolling Interval Method. Using the Rolling Interval Method, adherence rates were similar across drug and laboratory testing type. CONCLUSIONS: Results for adherence with laboratory testing QIs for DMARD use differed depending on how the QIs were measured, suggesting that care must be taken in clearly defining methods. While EMRs will provide important opportunities for measuring adherence with QIs, they also present challenges that must be examined before widespread adoption of these data collection methods.