Mental health resilience in the adolescent offspring of parents with depression:a prospective longitudinal study

Background Young people whose parents have depression have a greatly increased risk of developing a psychiatric disorder, but poor outcomes are not inevitable. Identification of the contributors to mental health resilience in young people at high familial risk is an internationally recognised priority. Our objectives were to identify protective factors that predict sustained good mental health in adolescents with a parent with depression and to test whether these contribute beyond what is explained by parent illness severity. Methods The Early Prediction of Adolescent Depression study (EPAD) is a prospective longitudinal study of offspring of parents with recurrent depression. Parents with recurrent major depressive disorder, co-parents, and offspring (aged 9–17 years at baseline) were assessed three times over 4 years in a community setting. Offspring outcomes were operationalised as absence of mental health disorder, subthreshold symptoms, or suicidality on all three study occasions (sustained good mental health); and better than expected mental health (mood and behavioural symptoms at follow-up lower than predicted given severity of parental depression). Family, social, cognitive, and health behaviour predictor variables were assessed using interview and questionnaire measures. Findings Between February and June, 2007, we screened 337 families at baseline, of which 331 were eligible. Of these, 262 completed the three assessments and were included in the data for sustained mental health. Adolescent mental health problems were common, but 53 (20%) of the 262 adolescents showed sustained good mental health. Index parent positive expressed emotion (odds ratio 1·91 [95% CI 1·31–2·79]; p=0·001), co-parent support (1·90 [1·38–2·62]; p<0·0001), good-quality social relationships (2·07 [1·35–3·18]; p=0·001), self-efficacy (1·49 [1·05–2·11]; p=0·03), and frequent exercise (2·96 [1·26–6·92]; p=0·01) were associated with sustained good mental health. Analyses accounting for parent depression severity were consistent, but frequent exercise only predicted better than expected mood-related mental health (β=–0·22; p=0·0004) not behavioural mental health, whereas index parents' expression of positive emotions predicted better than expected behavioural mental health (β=–0·16; p=0·01) not mood-related mental health. Multiple protective factors were required for offspring to be free of mental health problems (zero or one protective factor, 4% sustained good mental health; two protective factors, 10%; three protective factors, 13%, four protective factors, 38%; five protective factors, 48%). Interpretation Adolescent mental health problems are common, but not inevitable, even when parental depression is severe and recurrent. These findings suggest that prevention programmes will need to enhance multiple protective factors across different domains of functioning

The health informatics cohort enhancement project (HICE): using routinely collected primary care data to identify people with a lifetime diagnosis of psychotic disorder

Background: We have previously demonstrated that routinely collected primary care data can be used to identify potential participants for trials in depression [1]. Here we demonstrate how patients with psychotic disorders can be identified from primary care records for potential inclusion in a cohort study. We discuss the strengths and limitations of this approach; assess its potential value and report challenges encountered. Methods: We designed an algorithm with which we searched for patients with a lifetime diagnosis of psychotic disorders within the Secure Anonymised Information Linkage (SAIL) database of routinely collected health data. The algorithm was validated against the "gold standard" of a well established operational criteria checklist for psychotic and affective illness (OPCRIT). Case notes of 100 patients from a community mental health team (CMHT) in Swansea were studied of whom 80 had matched GP records. Results: The algorithm had favourable test characteristics, with a very good ability to detect patients with psychotic disorders (sensitivity > 0.7) and an excellent ability not to falsely identify patients with psychotic disorders (specificity > 0.9). Conclusions: With certain limitations our algorithm can be used to search the general practice data and reliably identify patients with psychotic disorders. This may be useful in identifying candidates for potential inclusion in cohort studies

'Sifting the significance from the data' - the impact of high-throughput genomic technologies on human genetics and health care.

This report is of a round-table discussion held in Cardiff in September 2009 for Cesagen, a research centre within the Genomics Network of the UK's Economic and Social Research Council. The meeting was arranged to explore ideas as to the likely future course of human genomics. The achievements of genomics research were reviewed, and the likely constraints on the pace of future progress were explored. New knowledge is transforming biology and our understanding of evolution and human disease. The difficulties we face now concern the interpretation rather than the generation of new sequence data. Our understanding of gene-environment interaction is held back by our current primitive tools for measuring environmental factors, and in addition, there may be fundamental constraints on what can be known about these complex interactions.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Opportunities to engage in positive activities during the COVID-19 pandemic: Perspectives of individuals with mood disorders

Background Despite cross-sectional population and clinical studies finding individuals with existing mood disorders being adversely impacted by the COVID-19 pandemic, longitudinal studies have not shown a worsening of psychiatric symptoms. In response to these findings, we explored opportunities to engage in positive activities during the pandemic from the perspectives of individuals with mood disorders. Methods A bespoke survey, containing closed and open questions, was sent to participants with mood disorders who were part of the UK Bipolar Disorder Research Network (BDRN). Questions related to experiences of positive impacts of the pandemic, levels of engagement in positive activities and coping strategies. Results Response rate was 46.4 % (N = 1688). 61.9 % reported positive life changes during the pandemic, with slower pace of life reported most frequently (52.8 %). 47.3 % reported no adverse impact of the pandemic on implementing their usual coping strategies. Activities that respondents most commonly reported the same or greater level of engagement in compared to before the pandemic were avoiding known mood triggers (82.3 %), relaxation techniques (78.8 %) and the ability to maintain set routines (69.4 %). Limitations Responder bias may be present and experiences during the pandemic are likely to differ among other clinical and research mood disorders cohorts. Conclusions Our findings may help to explain why longitudinal studies have not found a worsening of mental health symptoms during the COVID-19 pandemic. Identifying potential facilitators to maintaining mental health have wider applicability, and may help to inform future evidence-based psychoeducation and self-management programmes for mood disorders

The Bipolar Affective Disorder Dimension Scale (BADDS) – a dimensional scale for rating lifetime psychopathology in Bipolar spectrum disorders

BACKGROUND: Current operational diagnostic systems have substantial limitations for lifetime diagnostic classification of bipolar spectrum disorders. Issues include: (1) It is difficult to operationalize the integration of diverse episodes of psychopathology, (2) Hierarchies lead to loss of information, (3) Boundaries between diagnostic categories are often arbitrary, (4) Boundaries between categories usually require a major element of subjective interpretation, (5) Available diagnostic categories are relatively unhelpful in distinguishing severity, (6) "Not Otherwise Specified (NOS)" categories are highly heterogeneous, (7) Subclinical cases are not accommodated usefully within the current diagnostic categories. This latter limitation is particularly pertinent in the context of the increasing evidence for the existence of a broader bipolar spectrum than has been acknowledged within existing classifications. METHOD: We have developed a numerical rating system, the Bipolar Affective Disorder Dimension Scale, BADDS, that can be used as an adjunct to conventional best-estimate lifetime diagnostic procedures. The scale definitions were informed by (a) the current concepts of mood syndrome recognized within DSMIV and ICD10, (b) the literature regarding severity of episodes, and (c) our own clinical experience. We undertook an iterative process in which we initially agreed scale definitions, piloted their use on sets of cases and made modifications to improve utility and reliability. RESULTS: BADDS has four dimensions, each rated as an integer on a 0 – 100 scale, that measure four key domains of lifetime psychopathology: Mania (M), Depression (D), Psychosis (P) and Incongruence (I). In our experience it is easy to learn, straightforward to use, has excellent inter-rater reliability and retains the key information required to make diagnoses according to DSMIV and ICD10. CONCLUSIONS: Use of BADDS as an adjunct to conventional categorical diagnosis provides a richer description of lifetime psychopathology that (a) can accommodate sub-clinical features, (b) discriminate between illness severity amongst individuals within a single conventional diagnostic category, and (c) demonstrate the similarity between the illness experience of individuals who have been classified into different disease categories but whose illnesses both fall near the boundaries between the two categories. BADDS may be useful for researchers and clinicians who are interested in description and classification of lifetime psychopathology of individuals with disorders lying on the bipolar spectrum

Heaviness, health and happiness: a cross-sectional study of 163 066 UK Biobank participants

&lt;b&gt;Background&lt;/b&gt;&lt;p&gt;&lt;/p&gt; Obesity is known to increase the risk of many diseases and reduce overall quality of life. This study examines the relationship with self-reported health (SRH) and happiness.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Methods&lt;/b&gt; &lt;p&gt;&lt;/p&gt;We conducted a cross-sectional study of the 163 066 UK Biobank participants who completed the happiness rating. The association between adiposity and SRH and happiness was examined using logistic regression. SRH was defined as good (excellent, good), or poor (fair, poor). Self-reported happiness was defined as happy (extremely, very, moderately) or unhappy (moderately, very, extremely). &lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt; &lt;p&gt;&lt;/p&gt;Poor health was reported by 44 457 (27.3%) participants. The adjusted ORs for poor health were 3.86, 2.92, 2.60 and 6.41 for the highest, compared with lowest, deciles of Body Mass Index, waist circumference, waist to hip ratio and body fat percent, respectively. The associations were stronger in men (p&lt;0.001). Overall, 7511 (4.6%) participants felt unhappy, and only class III obese participants were more likely to feel unhappy (adjusted OR 1.33, 95% CI 1.15 to 1.53, p&lt;0.001) but the associations differed by sex (p&lt;0.001). Among women, there was a significant association between unhappiness and all levels of obesity. By contrast, only class III obese men had significantly increased risk and overweight and class I obese men were less likely to be unhappy. &lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions&lt;/b&gt;&lt;p&gt;&lt;/p&gt;Obesity impacts adversely on happiness as well as health, but the association with unhappiness disappeared after adjustment for self-reported health, indicating this may be mediated by health. Compared with obese men, obese women are less likely to report poor health, but more likely to feel unhappy. &lt;p&gt;&lt;/p&gt

Whole genome linkage scan of recurrent depressive disorder from the depression network study

Genome-wide linkage analysis was carried out in a sample of 497 sib pairs concordant for recurrent major depressive disorder (MDD). There was suggestive evidence for linkage on chromosome 1p36 where the LOD score for female-female pairs exceeded 3 (but reduced to 2.73 when corrected for multiple testing). The region includes a gene, MTHFR, that in previous studies has been associated with depressive symptoms. Two other regions, on chromosomes 12q23.3-q24.11 and 13q31.1-q31.3, showed evidence for linkage with a nominal P<0.01. The 12q peak overlaps with a region previously implicated by linkage studies of unipolar and bipolar disorders and contains a gene, DAO, that has been associated with both bipolar disorder and schizophrenia. The 13q peak lies within a region previously linked strongly to panic disorder. A fourth modest peak with an LOD of greater than 1 on chromosome 15q lies within a region that showed genome-wide significant evidence of a recurrent depression locus in a previous sib-pair study. Both the 12q and the 15q findings remained significant at genome-wide level when the data from the present study and the previous reports were combine

Dissecting the shared genetic architecture of suicide attempt, psychiatric disorders and known risk factors

Background Suicide is a leading cause of death worldwide, and non-fatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium. The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via mtCOJO, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with non-psychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders

Rare copy number variants: a point of rarity in genetic risk for bipolar disorder and schizophrenia

Context: Recent studies suggest that copy number variation in the human genome is extensive and may play an important role in susceptibility to disease, including neuropsychiatric disorders such as schizophrenia and autism. The possible involvement of copy number variants (CNVs) in bipolar disorder has received little attention to date. Objectives: To determine whether large (>100 000 base pairs) and rare (found in <1% of the population) CNVs are associated with susceptibility to bipolar disorder and to compare with findings in schizophrenia. Design: A genome-wide survey of large, rare CNVs in a case-control sample using a high-density microarray. Setting: The Wellcome Trust Case Control Consortium. Participants: There were 1697 cases of bipolar disorder and 2806 nonpsychiatric controls. All participants were white UK residents. Main Outcome Measures: Overall load of CNVs and presence of rare CNVs. Results: The burden of CNVs in bipolar disorder was not increased compared with controls and was significantly less than in schizophrenia cases. The CNVs previously implicated in the etiology of schizophrenia were not more common in cases with bipolar disorder. Conclusions: Schizophrenia and bipolar disorder differ with respect to CNV burden in general and association with specific CNVs in particular. Our data are consistent with the possibility that possession of large, rare deletions may modify the phenotype in those at risk of psychosis: those possessing such events are more likely to be diagnosed as having schizophrenia, and those without them are more likely to be diagnosed as having bipolar disorder

Gender differences in the association between adiposity and probable major depression: a cross-sectional study of 140,564 UK Biobank participants

&lt;b&gt;Background&lt;/b&gt;&lt;p&gt;&lt;/p&gt; Previous studies on the association between adiposity and mood disorder have produced contradictory results, and few have used measurements other than body mass index (BMI). We examined the association between probable major depression and several measurements of adiposity: BMI, waist circumference (WC), waist-hip-ratio (WHR), and body fat percentage (BF%).&lt;p&gt;&lt;/p&gt; &lt;b&gt;Methods&lt;/b&gt;&lt;p&gt;&lt;/p&gt; We conducted a cross-sectional study using baseline data on the sub-group of UK Biobank participants who were assessed for mood disorder. Multivariate logistic regression models were used, adjusting for potential confounders including: demographic and life-style factors, comorbidity and psychotropic medication.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt;&lt;p&gt;&lt;/p&gt; Of the 140,564 eligible participants, evidence of probable major depression was reported by 30,145 (21.5%). The fully adjusted odds ratios (OR) for obese participants were 1.16 (95% confidence interval (CI) 1.12, 1.20) using BMI, 1.15 (95% CI 1.11, 1.19) using WC, 1.09 (95% CI 1.05, 1.13) using WHR and 1.18 (95% CI 1.12, 1.25) using BF% (all p &#60;0.001). There was a significant interaction between adiposity and gender (p = 0.001). Overweight women were at increased risk of depression with a dose response relationship across the overweight (25.0-29.9 kg/m2), obese I (30.0-34.9 kg/m2), II (35.0-39.9 kg/m2) and III (≥40.0 kg/m2) categories; fully adjusted ORs 1.14, 1.20, 1.29 and 1.48, respectively (all p &#60; 0.001). In contrast, only obese III men had significantly increased risk of depression (OR 1.29, 95% CI 1.08, 1.54, p = 0.006).&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusion&lt;/b&gt;&lt;p&gt;&lt;/p&gt; Adiposity was associated with probable major depression, irrespective of the measurement used. The association was stronger in women than men. Physicians managing overweight and obese women should be alert to this increased risk