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Background: SURECAN (SUrvivors' Rehabilitation Evaluation after CANcer) is a multi-phase study developing and evaluating an Acceptance and Commitment Therapy (ACT) intervention integrated with exercise and work when highly valued (thus we called the intervention ACT+), for people who have completed treatment for cancer but who have low quality of life. We developed a training programme for therapists working in different psychological services to be delivered over 2-3 days. Our aim was to evaluate the extent to which the training could improve therapists' knowledge and confidence to deliver ACT+ to cancer patients in a trial setting.Methods: Three interactive workshops were delivered to 29 therapists from three clinical settings in London and in Sheffield. A mixed-methods approach was used. Questionnaires were designed to assess knowledge and confidence in using ACT+ with people who have low quality of life after cancer treatment. They were self-administered immediately prior to and after each workshop. Open text-based questions were used to elicit feedback about the workshops alongside a satisfaction scale. Semi-structured interviews were conducted with a purposive sample of therapists (n = 12) to explore their views about the training more deeply, and how it might be optimised.Results: Quantitative analysis showed that knowledge of ACT, as well as confidence in using the ACT+ intervention in this setting increased significantly after training (28.6 and 33.5% increase in the median score respectively). Qualitative analysis indicated that most therapists were satisfied with the content and structure of the programme, valued the rich resources provided and enjoyed the practice-based approach. Potential barriers/facilitators to participation in the trial and to the successful implementation of ACT+ were identified. For some therapists, delivering a manualised intervention, as well as supporting exercise- and work-related goals as non-specialists was seen as challenging. At the same time, therapists valued the opportunity to be involved in research, whilst training in a new therapy model.Conclusions: Training can effectively improve the knowledge and confidence of therapists from different clinical backgrounds to deliver a modified ACT intervention to cancer patients in a trial setting. [ABSTRACT FROM AUTHOR]

Background: Approximately one third of cancer survivors in the United Kingdom face ongoing and debilitating psychological and physical symptoms related to poor quality of life. Very little is known about current post-cancer treatment services.Methods: Oncology healthcare professionals (HCPs) were invited to take part in a survey, which gathered both quantitative and free text data about the content and delivery of cancer aftercare and patient needs. Analysis involved descriptive statistics and content analysis.Results: There were 163 complete responses from 278 survey participants; 70% of NHS acute trusts provided data. HCPs views on patient post-cancer treatment needs were most frequently: fear of recurrence (95%), fatigue (94%), changes in physical capabilities (89%), anxiety (89%) and depression (88%). A median number of 2 aftercare sessions were provided (interquartile range: 1,4) lasting between 30 and 60 min. Usually these were provided face-to-face and intermittently by a HCP. However, sessions did not necessarily address the issues HCPs asserted as important. Themes from free-text responses highlighted inconsistencies in care, uncertain funding for services and omission of some evidence based approaches.Conclusion: Provision of post-cancer treatment follow-up care is neither universal nor consistent in the NHS, nor does it address needs HCPs identified as most important. [ABSTRACT FROM AUTHOR]

Background: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. Methods: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. Results: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ² = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ² = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. Conclusions: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity. [ABSTRACT FROM AUTHOR]

Background: Migraine is a common disorder that often coexists with depression. While a functional polymorphism in methyleneterahydrofolate reductase gene (MTHFR C677T) has been implicated in depression; the evidence to support an association of MTHFR with migraine has been inconclusive. We aim to investigate the effect of this variant on propensity for migraine and to perform a systematic review and meta-analysis of studies of MTHFR and migraine to date. Methods: Individuals with migraine (n = 447) were selected from the Depression Case Control (DeCC) study to investigate the association between migraine and MTHFR C677T single nucleotide polymorphism (SNP) rs1801133 using an additive model compared to non-migraineurs adjusting for depression status. A meta-analysis was performed and included 15 studies of MTHFR and migraine. Results: MTHFR C677T polymorphism was associated with migraine with aura (MA) (OR 1.31, 95% CI 1.01-1.70, p = 0.039) that remained significant after adjusting for age, sex and depression status. A meta-analysis of 15 casecontrol studies showed that T allele homozygosity is significantly associated with MA (OR = 1.42; 95% CI, 1.10-1.82) and total migraine (OR = 1.37; 95% CI, 1.07-1.76), but not migraine without aura (OR = 1.16; 95% CI, 0.36-3.76). In studies of non-Caucasian population, the TT genotype was associated with total migraine (OR= 3.46; 95% CI, 1.22- 9.82), whereas in studies of Caucasians this variant was associated with MA only (OR = 1.28; 95% CI, 1.002-1.63). Conclusions: MTHFR C677T is associated with MA in individuals selected for depression study. A meta-analysis of 15 studies supports this association and demonstrated effects across ethnic groups. [ABSTRACT FROM AUTHOR]

Background: We report an attempt to extend the previously successful approach of combining SNP (single nucleotide polymorphism) microarrays and DNA pooling (SNP-MaP) employing high-density microarrays. Whereas earlier studies employed a range of Affymetrix SNP microarrays comprising from 10 K to 500 K SNPs, this most recent investigation used the 6.0 chip which displays 906,600 SNP probes and 946,000 probes for the interrogation of CNVs (copy number variations). The genotyping assay using the Affymetrix SNP 6.0 array is highly demanding on sample quality due to the small feature size, low redundancy, and lack of mismatch probes. Findings: In the first study published so far using this microarray on pooled DNA, we found that pooled cheek swab DNA could not accurately predict real allele frequencies of the samples that comprised the pools. In contrast, the allele frequency estimates using blood DNA pools were reasonable, although inferior compared to those obtained with previously employed Affymetrix microarrays. However, it might be possible to improve performance by developing improved analysis methods. Conclusions: Despite the decreasing costs of genome-wide individual genotyping, the pooling approach may have applications in very large-scale case-control association studies. In such cases, our study suggests that highquality DNA preparations and lower density platforms should be preferred. [ABSTRACT FROM AUTHOR]

Background: The Depression Network Study (DeNt) is a multicentre study designed to identify genes and/or loci linked to and/or associated with susceptibility to unipolar depression in Caucasian families. This study presents the method and socio-demographic details of the first 470 affected sibling pairs recruited from 8 different sites in Europe and the United States of America. Methods: Probands fulfilling either the Diagnostic and Statistical Manual 4th edition (DSM-IV) or the International Classification of Diseases 10th edition (ICD-10) criteria for recurrent unipolar depression of moderate or severe degree and who had at least one similarly affected sibling were eligible for the study. Detailed clinical and psychological assessments were undertaken on all subjects including an interview using the Schedules for Clinical Assessment in Neuropsychiatry. Blood samples were collected from all participants to extract DNA for linkage analysis. Results: The different sites used different recruitment strategies depending on local health care organisation but despite this there was remarkable similarity across sites for the subjects recruited. Although the Bonn site had significantly older subjects both for age of onset and age at interview, for the sample as a whole, subjects were interviewed in their mid-40s and had experienced the onset of their recurrent depression in their 20s. Preliminary genome screening was able to include 929 out of the 944 subjects (98.4%) typed at 932 autosomal and 544 X chromosome markers Conclusions: This paper describes the methodology and the characteristics of the subjects from the 414 families included in the first wave of genotyping from the multi-site DeNT study. Ultimately the study aims to collect affected sibling pairs from approximately 1200 families. [ABSTRACT FROM AUTHOR]

Background: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD.Methods: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity.Results: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P < 0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P < 0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results.Conclusions: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity. [ABSTRACT FROM AUTHOR]