Body mass index interacts with a genetic-risk score for depression increasing the risk of the disease in high-susceptibility individuals.

Depression is strongly associated with obesity among other chronic physical diseases. The latest mega- and meta-analysis of genome-wide association studies have identified multiple risk loci robustly associated with depression. In this study, we aimed to investigate whether a genetic-risk score (GRS) combining multiple depression risk single nucleotide polymorphisms (SNPs) might have utility in the prediction of this disorder in individuals with obesity. A total of 30 depression-associated SNPs were included in a GRS to predict the risk of depression in a large case-control sample from the Spanish PredictD-CCRT study, a national multicentre, randomized controlled trial, which included 104 cases of depression and 1546 controls. An unweighted GRS was calculated as a summation of the number of risk alleles for depression and incorporated into several logistic regression models with depression status as the main outcome. Constructed models were trained and evaluated in the whole recruited sample. Non-genetic-risk factors were combined with the GRS in several ways across the five predictive models in order to improve predictive ability. An enrichment functional analysis was finally conducted with the aim of providing a general understanding of the biological pathways mapped by analyzed SNPs. We found that an unweighted GRS based on 30 risk loci was significantly associated with a higher risk of depression. Although the GRS itself explained a small amount of variance of depression, we found a significant improvement in the prediction of depression after including some non-genetic-risk factors into the models. The highest predictive ability for depression was achieved when the model included an interaction term between the GRS and the body mass index (BMI), apart from the inclusion of classical demographic information as marginal terms (AUC = 0.71, 95% CI = [0.65, 0.76]). Functional analyses on the 30 SNPs composing the GRS revealed an over-representation of the mapped genes in signaling pathways involved in processes such as extracellular remodeling, proinflammatory regulatory mechanisms, and circadian rhythm alterations. Although the GRS on its own explained a small amount of variance of depression, a significant novel feature of this study is that including non-genetic-risk factors such as BMI together with a GRS came close to the conventional threshold for clinical utility used in ROC analysis and improves the prediction of depression. In this study, the highest predictive ability was achieved by the model combining the GRS and the BMI under an interaction term. Particularly, BMI was identified as a trigger-like risk factor for depression acting in a concerted way with the GRS component. This is an interesting finding since it suggests the existence of a risk overlap between both diseases, and the need for individual depression genetics-risk evaluation in subjects with obesity. This research has therefore potential clinical implications and set the basis for future research directions in exploring the link between depression and obesity-associated disorders. While it is likely that future genome-wide studies with large samples will detect novel genetic variants associated with depression, it seems clear that a combination of genetics and non-genetic information (such is the case of obesity status and other depression comorbidities) will still be needed for the optimization prediction of depression in high-susceptibility individuals.

Use of a personalised depression intervention in primary care to prevent anxiety: a secondary study of a cluster randomised trial.

BACKGROUND: In the predictD-intervention, GPs used a personalised biopsychosocial programme to prevent depression. This reduced the incidence of major depression by 21.0%, although the results were not statistically significant. AIM: To determine whether the predictD-intervention is effective at preventing anxiety in primary care patients without depression or anxiety. DESIGN AND SETTING: Secondary study of a cluster randomised trial with practices randomly assigned to either the predictD-intervention or usual care. This study was conducted in seven Spanish cities from October 2010 to July 2012. METHOD: In each city, 10 practices and two GPs per practice, as well as four to six patients every recruiting day, were randomly selected until there were 26-27 eligible patients for each GP. The endpoint was cumulative incidence of anxiety as measured by the PRIME-MD screening tool over 18 months. RESULTS: A total of 3326 patients without depression and 140 GPs from 70 practices consented and were eligible to participate; 328 of these patients were removed because they had an anxiety syndrome at baseline. Of the 2998 valid patients, 2597 (86.6%) were evaluated at the end of the study. At 18 months, 10.4% (95% CI = 8.7% to 12.1%) of the patients in the predictD-intervention group developed anxiety compared with 13.1% (95% CI = 11.4% to 14.8%) in the usual-care group (absolute difference = -2.7% [95% CI = -5.1% to -0.3%]; P = 0.029). CONCLUSION: A personalised intervention delivered by GPs for the prevention of depression provided a modest but statistically significant reduction in the incidence of anxiety.

Family physicians' views on participating in prevention of major depression. The predictD-EVAL qualitative study.

BACKGROUND: The predictD intervention, a multicomponent intervention delivered by family physicians (FPs), reduced the incidence of major depression by 21% versus the control group and was cost-effective. A qualitative methodology was proposed to identify the mechanisms of action of these complex interventions. PURPOSE: To seek the opinions of these FPs on the potential successful components of the predictD intervention for the primary prevention of depression in primary care and to identify areas for improvement. METHOD: Qualitative study with FPs who delivered the predictD intervention at 35 urban primary care centres in seven Spanish cities. Face-to-face semi-structured interviews adopting a phenomenological approach. The data was triangulated by three investigators using thematic analysis and respondent validation was carried out. RESULTS: Sixty-seven FPs were interviewed and they indicated strategies used to perform the predictD intervention, including specific communication skills such as empathy and the activation of patient resources. They perceived barriers such as lack of time and facilitators such as prior acquaintance with patients. FPs recognized the positive consequences of the intervention for FPs, patients and the doctor-patient relationship. They also identified strategies for future versions and implementations of the predictD intervention. CONCLUSIONS: The FPs who carried out the predictD intervention identified factors potentially associated with successful prevention using this program and others that could be improved. Their opinions about the predictD intervention will enable development of a more effective and acceptable version and its implementation in different primary health care settings.

Prevención de los trastornos de la salud mental en atención primaria. Actualización PAPPS 2018 / No disponible

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A personalized intervention to prevent depression in primary care: cost-effectiveness study nested into a clustered randomized trial.

BACKGROUND: Depression is viewed as a major and increasing public health issue, as it causes high distress in the people experiencing it and considerable financial costs to society. Efforts are being made to reduce this burden by preventing depression. A critical component of this strategy is the ability to assess the individual level and profile of risk for the development of major depression. This paper presents the cost-effectiveness of a personalized intervention based on the risk of developing depression carried out in primary care, compared with usual care. METHODS: Cost-effectiveness analyses are nested within a multicentre, clustered, randomized controlled trial of a personalized intervention to prevent depression. The study was carried out in 70 primary care centres from seven cities in Spain. Two general practitioners (GPs) were randomly sampled from those prepared to participate in each centre (i.e. 140 GPs), and 3326 participants consented and were eligible to participate. The intervention included the GP communicating to the patient his/her individual risk for depression and personal risk factors and the construction by both GPs and patients of a psychosocial programme tailored to prevent depression. In addition, GPs carried out measures to activate and empower the patients, who also received a leaflet about preventing depression. GPs were trained in a 10- to 15-h workshop. Costs were measured from a societal and National Health care perspective. Qualityadjustedlife years were assessed using the EuroQOL five dimensions questionnaire. The time horizon was 18 months. RESULTS: With a willingness-to-pay threshold of €10,000 (£8568) the probability of cost-effectiveness oscillated from 83% (societal perspective) to 89% (health perspective). If the threshold was increased to €30,000 (£25,704), the probability of being considered cost-effective was 94% (societal perspective) and 96%, respectively (health perspective). The sensitivity analysis confirmed these results. CONCLUSIONS: Compared with usual care, an intervention based on personal predictors of risk of depression implemented by GPs is a cost-effective strategy to prevent depression. This type of personalized intervention in primary care should be further developed and evaluated. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01151982. Registered on June 29, 2010.

Predicting the onset of hazardous alcohol drinking in primary care: development and validation of a simple risk algorithm.

BACKGROUND: Little is known about the risk of progressing to hazardous alcohol use in abstinent or low-risk drinkers. AIM: To develop and validate a simple brief risk algorithm for the onset of hazardous alcohol drinking (HAD) over 12 months for use in primary care. DESIGN AND SETTING: Prospective cohort study in 32 health centres from six Spanish provinces, with evaluations at baseline, 6 months, and 12 months. METHOD: Forty-one risk factors were measured and multilevel logistic regression and inverse probability weighting were used to build the risk algorithm. The outcome was new occurrence of HAD during the study, as measured by the AUDIT. RESULTS: From the lists of 174 GPs, 3954 adult abstinent or low-risk drinkers were recruited. The 'predictAL-10' risk algorithm included just nine variables (10 questions): province, sex, age, cigarette consumption, perception of financial strain, having ever received treatment for an alcohol problem, childhood sexual abuse, AUDIT-C, and interaction AUDIT-C*Age. The c-index was 0.886 (95% CI = 0.854 to 0.918). The optimal cutoff had a sensitivity of 0.83 and specificity of 0.80. Excluding childhood sexual abuse from the model (the 'predictAL-9'), the c-index was 0.880 (95% CI = 0.847 to 0.913), sensitivity 0.79, and specificity 0.81. There was no statistically significant difference between the c-indexes of predictAL-10 and predictAL-9. CONCLUSION: The predictAL-10/9 is a simple and internally valid risk algorithm to predict the onset of hazardous alcohol drinking over 12 months in primary care attendees; it is a brief tool that is potentially useful for primary prevention of hazardous alcohol drinking.

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Suicidality in primary care patients who present with sadness and anhedonia: a prospective European study.

BACKGROUND: Sadness and anhedonia (loss of interest in activities) are central symptoms of major depression. However, not all people with these symptoms meet diagnostic criteria for major depression. We aimed to assess the importance of suicidality in the outcomes for primary care patients who present with sadness and anhedonia. METHOD: Cohort study of 2,599 unselected primary care attenders in six European countries followed up at 6 and 12 months. RESULTS: 1) In patients with sadness and/or anhedonia who were not depressed at entry to the study, suicide plans (OR = 3.05; 95 % CI = 1.50-6.24; p = 0.0022) and suicide attempts (OR = 9.08; 95 % CI = 2.57-32.03; p = 0.0006) were significant predictors of developing new onset depression at 6 or 12 months. 2) In patients with sadness and/or anhedonia who met CIDI criteria for major depression at entry, suicidal ideation (OR = 2.93; 95 % CI = 1.70-5.07; p = 0.0001), suicide plans (OR = 3.70; 95 % CI = 2.08-6.57; p < 0.0001), and suicide attempts (OR = 3.33; 95 % CI = 1.47-7.54; p = 0.0040) were significant predictors of persistent depression at 6 or 12 months. CONCLUSIONS: Three questions on suicidality could help primary care professionals to assess such patients more closely without necessarily establishing whether they meet criteria for major depression.

Intervention to Prevent Major Depression in Primary Care: A Cluster Randomized Trial.

BACKGROUND: Not enough is known about universal prevention of depression in adults. OBJECTIVE: To evaluate the effectiveness of an intervention to prevent major depression. DESIGN: Multicenter, cluster randomized trial with sites randomly assigned to usual care or an intervention. (ClinicalTrials.gov: NCT01151982). SETTING: 10 primary care centers in each of 7 cities in Spain. PARTICIPANTS: Two primary care physicians (PCPs) and 5236 nondepressed adult patients were randomly sampled from each center; 3326 patients consented and were eligible to participate. INTERVENTION: For each patient, PCPs communicated individual risk for depression and personal predictors of risk and developed a psychosocial program tailored to prevent depression. MEASUREMENTS: New cases of major depression, assessed every 6 months for 18 months. RESULTS: At 18 months, 7.39% of patients in the intervention group (95% CI, 5.85% to 8.95%) developed major depression compared with 9.40% in the control (usual care) group (CI, 7.89% to 10.92%) (absolute difference, -2.01 percentage points [CI, -4.18 to 0.16 percentage points]; P = 0.070). Depression incidence was lower in the intervention centers in 5 cities and similar between intervention and control centers in 2 cities. LIMITATION: Potential self-selection bias due to nonconsenting patients. CONCLUSION: Compared with usual care, an intervention based on personal predictors of risk for depression implemented by PCPs provided a modest but nonsignificant reduction in the incidence of major depression. Additional study of this approach may be warranted. PRIMARY FUNDING SOURCE: Institute of Health Carlos III.

The risk for major depression conferred by childhood maltreatment is multiplied by BDNF and SERT genetic vulnerability: a replication study.

BACKGROUND: There is limited evidence for a moderating role of both serotonin transporter (SERT) and brain-derived neurotrophic factor (BDNF) genes on the risk for major depression (MD) developing after childhood maltreatment. However, research on this topic remains inconclusive, and there is a lack of data from longitudinal studies with large and representative population samples. Our study aimed to clarify whether, in the presence of previous childhood maltreatment, individuals carrying low functional alleles for both SERT 5-HTTLPR and BDNF Val66Met polymorphisms had a higher risk for MD. METHODS: We explored 2- and 3-way gene (SERT and BDNF) × environment (childhood maltreatment) interactions in a large sample of Spanish adults who were followed up over a 3-year period and assessed in person for both DSM-IV MD and exposure to childhood maltreatment. RESULTS: Our study included 2679 participants. Those with both the 5-HTTLPR s allele and the BDNF Met allele showed the highest risk of MD if they had previously experienced emotional (z = 2.08, p = 0.037), sexual (z = 2.19, p = 0.029) or any kind of childhood abuse (z = 2.37, p = 0.018). These 3-way interactions remained significant regardless of whether the 5-HTTLPR triallelic or the 5-HTTLPR biallelic polymorphisms were included in the analyses. LIMITATIONS: Retrospective assessment of childhood maltreatment may have resulted in a moderate degree of recall bias. CONCLUSION: Our results confirm that the risk of depression conferred by childhood maltreatment is modified by variation at both SERT and BDNF genes.

Predicting the onset of anxiety syndromes at 12 months in primary care attendees. The predictA-Spain study.

BACKGROUND: There are no risk algorithms for the onset of anxiety syndromes at 12 months in primary care. We aimed to develop and validate internally a risk algorithm to predict the onset of anxiety syndromes at 12 months. METHODS: A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multilevel logistic regression and inverse probability weighting to build the risk algorithm. Our main outcome was generalized anxiety, panic and other non-specific anxiety syndromes as measured by the Primary Care Evaluation of Mental Disorders, Patient Health Questionnaire (PRIME-MD-PHQ). We recruited 3,564 adult primary care attendees without anxiety syndromes from 174 family physicians and 32 health centers in 6 Spanish provinces. RESULTS: The cumulative 12-month incidence of anxiety syndromes was 12.2%. The predictA-Spain risk algorithm included the following predictors of anxiety syndromes: province; sex (female); younger age; taking medicines for anxiety, depression or stress; worse physical and mental quality of life (SF-12); dissatisfaction with paid and unpaid work; perception of financial strain; and the interactions sex*age, sex*perception of financial strain, and age*dissatisfaction with paid work. The C-index was 0.80 (95% confidence interval=0.78-0.83) and the Hedges' g=1.17 (95% confidence interval=1.04-1.29). The Copas shrinkage factor was 0.98 and calibration plots showed an accurate goodness of fit. CONCLUSIONS: The predictA-Spain risk algorithm is valid to predict anxiety syndromes at 12 months. Although external validation is required, the predictA-Spain is available for use as a predictive tool in the prevention of anxiety syndromes in primary care.

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Patients' opinions about knowing their risk for depression and what to do about it. The predictD-qualitative study.

BACKGROUND: The predictD study developed and validated a risk algorithm for predicting the onset of major depression in primary care. We aimed to explore the opinion of patients about knowing their risk for depression and the values and criteria upon which these opinions are based. METHODS: A maximum variation sample of patients was taken, stratified by city, age, gender, immigrant status, socio-economic status and lifetime depression. The study participants were 52 patients belonging to 13 urban health centres in seven different cities around Spain. Seven Focus Groups (FGs) were given held with primary care patients, one for each of the seven participating cities. RESULTS: The results showed that patients generally welcomed knowing their risk for depression. Furthermore, in light of available evidence several patients proposed potential changes in their lifestyles to prevent depression. Patients generally preferred to ask their General Practitioners (GPs) for advice, though mental health specialists were also mentioned. They suggested that GPs undertake interventions tailored to each patient, from a "patient-centred" approach, with certain communication skills, and giving advice to help patients cope with the knowledge that they are at risk of becoming depressed. CONCLUSIONS: Patients are pleased to be informed about their risk for depression. We detected certain beliefs, attitudes, values, expectations and behaviour among the patients that were potentially useful for future primary prevention programmes on depression.

Psychometric properties of the List of Threatening Experiences--LTE and its association with psychosocial factors and mental disorders according to different scoring methods.

BACKGROUND: The List of Threatening Experiences (LTE) questionnaire is frequently used to assess stressful events; however, studies of its psychometric properties are scarce. We examined the LTE's reliability, factorial structure, construct validity and explored the association between LTE scores and psychosocial variables and mental disorders. METHOD: This study involved interviewing 5442 primary care attendees from Spain. Associations between four different methods of quantifying LTE scores, psychosocial factors, major depression (CIDI), anxiety disorders (PRIME-MD), alcohol misuse and dependence (AUDIT) were measured. RESULTS: The LTE showed high test-retest reliability (Kappa range=0.61-0.87) and low internal consistency (α=0.44). Tetrachoric factorial analysis yielded four factors (spousal and relational problems; employment and financial problems; personal problems; illness and bereavement in close persons). Logistic multilevel regression found a strong association between greater social support and a lower occurrence of stressful events (OR range=0.36-0.79). The association between religious-spiritual beliefs and the LTE, was weaker. The association between mental disorders and LTE scores was greater for depression (OR range=1.64-2.57) than anxiety (OR range=1.35-1.97), though the highest ORs were obtained with alcohol dependence (OR range=2.86-4.80). The ordinal score (ordinal regression) was more sensitive to detect the strength of association with mental disorders. LIMITATIONS: We are unable to distinguish the direction of the association between stressful events, psychosocial factors and mental disorders, due to our cross-sectional design of the study. CONCLUSIONS: The LTE is a valid and reliable measure of stress in mental health, and the strength of association with mental disorders depends on the method of quantifying LTE scores.

Preventing the onset of major depression based on the level and profile of risk of primary care attendees: protocol of a cluster randomised trial (the predictD-CCRT study).

BACKGROUND: The 'predictD algorithm' provides an estimate of the level and profile of risk of the onset of major depression in primary care attendees. This gives us the opportunity to develop interventions to prevent depression in a personalized way. We aim to evaluate the effectiveness, cost-effectiveness and cost-utility of a new intervention, personalized and implemented by family physicians (FPs), to prevent the onset of episodes of major depression. METHODS/DESIGN: This is a multicenter randomized controlled trial (RCT), with cluster assignment by health center and two parallel arms. Two interventions will be applied by FPs, usual care versus the new intervention predictD-CCRT. The latter has four components: a training workshop for FPs; communicating the level and profile of risk of depression; building up a tailored bio-psycho-family-social intervention by FPs to prevent depression; offering a booklet to prevent depression; and activating and empowering patients. We will recruit a systematic random sample of 3286 non-depressed adult patients (1643 in each trial arm), nested in 140 FPs and 70 health centers from 7 Spanish cities. All patients will be evaluated at baseline, 6, 12 and 18 months. The level and profile of risk of depression will be communicated to patients by the FPs in the intervention practices at baseline, 6 and 12 months. Our primary outcome will be the cumulative incidence of major depression (measured by CIDI each 6 months) over 18 months of follow-up. Secondary outcomes will be health-related quality of life (SF-12 and EuroQol), and measurements of cost-effectiveness and cost-utility. The inferences will be made at patient level. We shall undertake an intention-to-treat effectiveness analysis and will handle missing data using multiple imputations. We will perform multi-level logistic regressions and will adjust for the probability of the onset of major depression at 12 months measured at baseline as well as for unbalanced variables if appropriate. The economic evaluation will be approached from two perspectives, societal and health system. DISCUSSION: To our knowledge, this will be the first RCT of universal primary prevention for depression in adults and the first to test a personalized intervention implemented by FPs. We discuss possible biases as well as other limitations. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01151982.

Psychosocial and sociodemographic predictors of attrition in a longitudinal study of major depression in primary care: the predictD-Spain study.

BACKGROUND: Few data exist on the psychosocial factors associated with attrition in longitudinal surveys. This study was undertaken to determine psychosocial and sociodemographic predictors of attrition from a longitudinal study of the onset and persistence of episodes of major depression in primary care. METHODS: A systematic random sample of general practice attendees was recruited in seven Spanish provinces between October 2005 and February 2006. Major depression was diagnosed using the Composite International Diagnostic Interview and a set of 39 individual and environmental risk factors for depression were assessed at baseline and after 6 and 12 months of follow-up. Data were analysed using multilevel logistic regression. RESULTS: 7777 primary care attendees aged 18-75 years were selected, of whom 1251 (16.1%) were excluded. Of the remaining 6526, 1084 (16.6%) refused to participate. Thus, 5442 patients (attending 231 family physicians in 41 health centres) were interviewed at baseline, of whom 3804 (70%) and 3567 (66%) remained at 6 and 12 months of follow-up, respectively. The province and sociodemographic factors were stronger predictors of attrition than psychosocial factors. Depression and anxiety had no effect but other psychosocial factors affected attrition. There were different profiles for the patients lost at 12 months when predictors measured at baseline versus 6 months were included. CONCLUSIONS: These findings suggest that several psychosocial factors might be considered factors of attrition in primary care cohorts and confirm that baseline characteristics are insufficient for analysing non-response in longitudinal studies, indicating that different retention strategies should be applied for patients interviewed at 6 and 12 months.

Predicting the onset and persistence of episodes of depression in primary health care. The predictD-Spain study: methodology.

BACKGROUND: The effects of putative risk factors on the onset and/or persistence of depression remain unclear. We aim to develop comprehensive models to predict the onset and persistence of episodes of depression in primary care. Here we explain the general methodology of the predictD-Spain study and evaluate the reliability of the questionnaires used. METHODS: This is a prospective cohort study. A systematic random sample of general practice attendees aged 18 to 75 has been recruited in seven Spanish provinces. Depression is being measured with the CIDI at baseline, and at 6, 12, 24 and 36 months. A set of individual, environmental, genetic, professional and organizational risk factors are to be assessed at each follow-up point. In a separate reliability study, a proportional random sample of 401 participants completed the test-retest (251 researcher-administered and 150 self-administered) between October 2005 and February 2006. We have also checked 118,398 items for data entry from a random sample of 480 patients stratified by province. RESULTS: All items and questionnaires had good test-retest reliability for both methods of administration, except for the use of recreational drugs over the previous six months. Cronbach's alphas were good and their factorial analyses coherent for the three scales evaluated (social support from family and friends, dissatisfaction with paid work, and dissatisfaction with unpaid work). There were 191 (0.16%) data entry errors. CONCLUSION: The items and questionnaires were reliable and data quality control was excellent. When we eventually obtain our risk index for the onset and persistence of depression, we will be able to determine the individual risk of each patient evaluated in primary health care.