Background: Clinicians are less likely to prescribe guideline-recommended treatments to people with multimorbidity than to people with a single condition. Doubts as to the applicability of clinical trials of drug treatments (the gold standard for evidence-based medicine) when people have co-existing diseases (comorbidity) may underlie this apparent reluctance. Therefore, for a range of index conditions, we measured the comorbidity among participants in clinical trials of novel drug therapies and compared this to the comorbidity among patients in the community. Methods: Data from industry-sponsored phase 3/4 multicentre trials of novel drug therapies for chronic medical conditions were identified from two repositories: Clinical Study Data Request and the Yale University Open Data Access project. We identified 116 trials (n = 122,969 participants) for 22 index conditions. Community patients were identified from a nationally representative sample of 2.3 million patients in Wales, UK. Twenty-one comorbidities were identified from medication use based on pre-specified definitions. We assessed the prevalence of each comorbidity and the total number of comorbidities (level of multimorbidity), for each trial and in community patients. Results: In the trials, the commonest comorbidities in order of declining prevalence were chronic pain, cardiovascular disease, arthritis, affective disorders, acid-related disorders, asthma/COPD and diabetes. These conditions were also common in community-based patients. Mean comorbidity count for trial participants was approximately half that seen in community-based patients. Nonetheless, a substantial proportion of trial participants had a high degree of multimorbidity. For example, in asthma and psoriasis trials, 10–15% of participants had ≥ 3 conditions overall, while in osteoporosis and chronic obstructive pulmonary disease trials 40–60% of participants had ≥ 3 conditions overall. Conclusions: Comorbidity and multimorbidity are less common in trials than in community populations with the same index condition. Comorbidity and multimorbidity are, nevertheless, common in trials. This suggests that standard, industry-funded clinical trials are an underused resource for investigating treatment effects in people with comorbidity and multimorbidity.

Summary: The health of carers and others close to the patient will often be relevant to economic evaluation, but it is very rarely considered in practice. This may reflect a lack of understanding of how the spillover effect of illness can be appropriately quantified. In this study we used three different approaches to quantify health spillovers resulting from meningitis. We conducted a survey of 1218 family networks affected by meningitis and used regression modelling to estimate spillover effects. The findings show that meningitis had long‐term effects on family members' health, particularly affecting the likelihood of family members reporting anxiety and depression. These effects extended beyond a single close family member. These findings suggest that vaccinating against meningitis will bring significant health benefits not just to those that might have contracted the illness but also to their family networks. In methodological terms, different approaches for quantifying health spillovers provided broadly consistent results. The choice of method will be influenced by the ease of collecting primary data from family members in intervention contexts. © 2015 The Authors.Health Economicspublished by John Wiley & Sons Ltd.

Background The Norwegian Mother, Father, and Child Cohort Study (MoBa) is a population-based pregnancy cohort, which includes approximately 114,500 children, 95,200 mothers, and 75,200 fathers. Genotyping of MoBa has been conducted through multiple research projects, spanning several years; using varying selection criteria, genotyping arrays, and genotyping centres. MoBa contains numerous interrelated families, which necessitated the implementation of a family-based quality control (QC) pipeline that verifies and accounts for diverse types of relatedness. Methods The MoBaPsychGen pipeline, comprising pre-imputation QC, phasing, imputation, and post-imputation QC, was developed based on current best-practice protocols and implemented to account for the complex structure of the MoBa genotype data. The pipeline includes QC on both single nucleotide polymorphism (SNP) and individual level. Phasing and imputation were performed using the publicly available Haplotype Reference Consortium release 1.1 panel as a reference. Information from the Medical Birth Registry of Norway and MoBa questionnaires were used to identify biological sex, year of birth, reported parent-offspring (PO) relationships, and multiple births (only available in the offspring generation). Results In total, 207,569 unique individuals (90% of the unique individuals included in the study) and 6,981,748 SNPs passed the MoBaPsychGen pipeline. The relatedness checks performed throughout the pipeline allowed identification of within-generation and across-generation first-degree, second-degree, and third-degree relatives. The individuals passing post-imputation QC comprised 64,471 families ranging in size from singletons to 84 unique individuals (singletons are included as families as other family members may not have been genotyped, imputed, or passed post-imputation QC). The relationships identified include 287 monozygotic twin pairs, 22,884 full siblings, 117,004 PO pairs, 23,299 second-degree relative pairs, and 10,828 third-degree relative pairs. Discussion MoBa contains a highly complex relatedness structure, with a variety of family structures including singletons, PO duos, full (mother, father, child) PO trios, nuclear families, blended families, and extended families. The availability of robustly quality-controlled genetic data for such a large cohort with a unique extended family structure will allow many novel research questions to be addressed. Furthermore, the MoBaPsychGen pipeline has potential utility in similar cohorts.

Little is known about the etiology of developmental change and continuity in educational achievement. Here, we study achievement from primary school to the end of compulsory education for 6000 twin pairs in the UK-representative Twins Early Development Study sample. Results showed that educational achievement is highly heritable across school years and across subjects studied at school (twin heritability ~60%; SNP heritability ~30%); achievement is highly stable (phenotypic correlations ~0.70 from ages 7 to 16). Twin analyses, applying simplex and common pathway models, showed that genetic factors accounted for most of this stability (70%), even after controlling for intelligence (60%). Shared environmental factors also contributed to the stability, while change was mostly accounted for by individual-specific environmental factors. Polygenic scores, derived from a genome-wide association analysis of adult years of education, also showed stable effects on school achievement. We conclude that the remarkable stability of achievement is largely driven genetically even after accounting for intelligence.

Maternal prenatal depression is a known risk factor for early-life psychopathology among offspring; however, potential risk transmission mechanisms need to be distinguished. We aimed to test the relative importance of passive genetic transmission, direct exposure, and indirect exposure in the association between maternal prenatal depressive symptoms and early-life internalising and externalising psychopathology in offspring. We used structural equation modelling of phenotypic data and genetically informative relationships from the families of participants in the Norwegian Mother and Child Birth Cohort Study (MoBa). The analytic subsample of MoBa used in the current study comprises 22 195 mothers and 35 299 children. We used mothers' self-reported depressive symptoms during pregnancy, as captured by the Symptom Checklist, and their reports of symptoms of psychopathology in their offspring during the first few years of life (measured at 18, 36, and 60 months using the Child Behavior Checklist). Maternal prenatal depressive symptoms were found to be associated with early-life psychopathology primarily via intergenerationally shared genetic factors, which explained 41% (95% CI 36-46) of variance in children's internalising problems and 37% (30-44) of variance in children's externalising problems. For internalising problems, phenotypic transmission also contributed significantly, accounting for 14% (95% CI 5-19) of the association, but this contribution was found to be explained by exposure to concurrent maternal depressive symptoms, rather than by direct exposure in utero. Associations between maternal prenatal depressive symptoms and offspring behavioural outcomes in early childhood are likely to be at least partially explained by shared genes. This genetic confounding should be considered when attempting to quantify risks posed by in-utero exposure to maternal depressive symptoms. UK Economic and Social Research Council, Norwegian Research Council, Norwegian Ministries of Health and Care Services, and Education & Research, Wellcome Trust, Royal Society, and National Institute for Health Research.

Emotional and behavioural problems in childhood and adolescence can be chronic and are predictive of future psychiatric problems. Understanding what factors drive the development and maintenance of these problems is therefore crucial. Longitudinal behavioural genetic studies using twin, sibling or adoption data can be used to explore the developmental aetiology of stability and change in childhood and adolescent psychopathology. We present a systematic review of longitudinal, behavioural genetic analyses of emotional and behavioural problems between ages 0 to 18 years. We identified 58 studies, of which 19 examined emotional problems, 30 examined behavioural problems, and 9 examined both. In the majority of studies, stability in emotional and behavioural problems was primarily genetically influenced. Stable environmental factors were also widely found, although these typically played a smaller role. Both genetic and environmental factors were involved in change across development. We discuss the findings in the context of the wider developmental literature and make recommendations for future research.