ObjectiveWe aimed to assess psychiatric morbidities of patients with head and neck cancer (HNC) in a prospective study at pretreatment, and 3 and 6 months after treatment, and to compare their health-related quality of life (HRQL) between those with and without depressive disorders (depression).Materials and methodsPatients with newly diagnosed HNC from a tertiary hospital were recruited into the study. They were assessed for psychiatric morbidities using the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, fourth edition. Their HRQL was simultaneously evaluated using the quality of life questionnaire of the European Organisation for Research and Treatment of Cancer with a specific module for head and neck cancer; and depressed and nondepressed HNC patients were compared by using the generalized mixed-effect model for repeated measurements.ResultsA total of 106 patients were recruited into this study. High rates of anxiety were found at pretreatment, but steadily declined over time (from 27.3% to 6.4%, and later 3.3%). A skew pattern of depression was observed, with prevalence rates from 8.5% at pretreatment to 24.5% and 14% at 3 and 6 months, respectively, after treatment. We found that loss of sense (P=0.001), loss of speech (P<0.001), low libido (P=0.001), dry mouth (P<0.001), and weight loss (P=0.001) were related to depression over time. The depressed patients had a higher consumption of painkillers (P=0.001) and nutrition supplements (P<0.001). The results showed that depression was predicted by sticky saliva (P<0.001) and trouble with social contact (P<0.001) at 3 months, and trouble with social eating (P<0.001) at 6 months.ConclusionPatients with HNC experienced different changes in anxiety and depression in the first 6 months of treatment. Dysfunction in salivation, problems with eating, and problems with social contacts were major risk factors for depression.

BackgroundObesity has been shown to be associated with depression and it has been suggested that higher body mass index (BMI) increases the risk of depression and other common mental disorders. However, the causal relationship remains unclear and Mendelian randomisation, a form of instrumental variable analysis, has recently been employed to attempt to resolve this issue.AimsTo investigate whether higher BMI increases the risk of major depression.MethodTwo instrumental variable analyses were conducted to test the causal relationship between obesity and major depression in RADIANT, a large case-control study of major depression. We used a single nucleotide polymorphism (SNP) in FTO and a genetic risk score (GRS) based on 32 SNPs with well-established associations with BMI.ResultsLinear regression analysis, as expected, showed that individuals carrying more risk alleles of FTO or having higher score of GRS had a higher BMI. Probit regression suggested that higher BMI is associated with increased risk of major depression. However, our two instrumental variable analyses did not support a causal relationship between higher BMI and major depression (FTO genotype: coefficient –0.03, 95% CI –0.18 to 0.13, P = 0.73; GRS: coefficient –0.02, 95% CI –0.11 to 0.07, P = 0.62).ConclusionsOur instrumental variable analyses did not support a causal relationship between higher BMI and major depression. The positive associations of higher BMI with major depression in probit regression analyses might be explained by reverse causality and/or residual confounding.

BackgroundObesity 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.MethodsLinear 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.ResultsIn 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.ConclusionsA 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-015-0334-3) contains supplementary material, which is available to authorized users.

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Circadian misalignment plays an important role in disease processes and can affect disease severity, treatment outcomes, and even survivorship. In this study, we aim to investigate whether expression and daily oscillation patterns of core circadian clock genes were disturbed in patients with obstructive sleep apnea/hypopnea (OSA) syndrome. We performed real-time quantitative reverse transcriptase-polymerase chain reactions to examine the expression of the nine core circadian clock genes in leukocytes of peripheral blood collected at 12 AM, 6 AM, 12 PM, and 6 PM from 133 patients with OSA and 11 normal controls. Daily expression patterns of the nine circadian clock genes were observed in normal controls, but three of these genes (BMAL1, CLOCK, CRY2) were disrupted in patients with OSA. The expressions of eight circadian clock genes (except PER1) at midnight were significantly downregulated in patients with severe OSA. Binary logistic regression analysis selected CRY1 and PER3 as independent factors for severe OSA and showed that the combined expressions of CRY1 and PER3 enhanced the capability of predicting severe OSA (Odds ratio, 5.800; 95% CI, 1.978 to 17.004; p = 0.001). Our results show that combined expressions of CRY1 and PER3 at midnight could be a potential predictor for severe OSA.

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