Psychological Medicine最新文献

Background: Epidemiological data offer conflicting views of the natural course of binge-eating disorder (BED), with large retrospective studies suggesting a protracted course and small prospective studies suggesting a briefer duration. We thus examined changes in BED diagnostic status in a prospective, community-based study that was larger and more representative with respect to sex, age of onset, and body mass index (BMI) than prior multi-year prospective studies.

Methods: Probands and relatives with current DSM-IV BED (n = 156) from a family study of BED ('baseline') were selected for follow-up at 2.5 and 5 years. Probands were required to have BMI > 25 (women) or >27 (men). Diagnostic interviews and questionnaires were administered at all timepoints.

Results: Of participants with follow-up data (n = 137), 78.1% were female, and 11.7% and 88.3% reported identifying as Black and White, respectively. At baseline, their mean age was 47.2 years, and mean BMI was 36.1. At 2.5 (and 5) years, 61.3% (45.7%), 23.4% (32.6%), and 15.3% (21.7%) of assessed participants exhibited full, sub-threshold, and no BED, respectively. No participants displayed anorexia or bulimia nervosa at follow-up timepoints. Median time to remission (i.e. no BED) exceeded 60 months, and median time to relapse (i.e. sub-threshold or full BED) after remission was 30 months. Two classes of machine learning methods did not consistently outperform random guessing at predicting time to remission from baseline demographic and clinical variables.

Conclusions: Among community-based adults with higher BMI, BED improves with time, but full remission often takes many years, and relapse is common.

Background: DSM-5 differentiates avoidant/restrictive food intake disorder (ARFID) from other eating disorders (EDs) by a lack of overvaluation of body weight/shape driving restrictive eating. However, clinical observations and research demonstrate ARFID and shape/weight motivations sometimes co-occur. To inform classification, we: (1) derived profiles underlying restriction motivation and examined their validity and (2) described diagnostic characterizations of individuals in each profile to explore whether findings support current diagnostic schemes. We expected, consistent with DSM-5, that profiles would comprise individuals endorsing solely ARFID or restraint (i.e. trying to eat less to control shape/weight) motivations.

Methods: We applied latent profile analysis to 202 treatment-seeking individuals (ages 10-79 years [M = 26, s.d. = 14], 76% female) with ARFID or a non-ARFID ED, using the Nine-Item ARFID Screen (Picky, Appetite, and Fear subscales) and the Eating Disorder Examination-Questionnaire Restraint subscale as indicators.

Results: A 5-profile solution emerged: Restraint/ARFID-Mixed (n = 24; 8% [n = 2] with ARFID diagnosis); ARFID-2 (with Picky/Appetite; n = 56; 82% ARFID); ARFID-3 (with Picky/Appetite/Fear; n = 40; 68% ARFID); Restraint (n = 45; 11% ARFID); and Non-Endorsers (n = 37; 2% ARFID). Two profiles comprised individuals endorsing solely ARFID motivations (ARFID-2, ARFID-3) and one comprising solely restraint motivations (Restraint), consistent with DSM-5. However, Restraint/ARFID-Mixed (92% non-ARFID ED diagnoses, comprising 18% of those with non-ARFID ED diagnoses in the full sample) endorsed ARFID and restraint motivations.

Conclusions: The heterogeneous profiles identified suggest ARFID and restraint motivations for dietary restriction may overlap somewhat and that individuals with non-ARFID EDs can also endorse high ARFID symptoms. Future research should clarify diagnostic boundaries between ARFID and non-ARFID EDs.

Background: Psychiatric disorders and type 2 diabetes mellitus (T2DM) are heritable, polygenic, and often comorbid conditions, yet knowledge about their potential shared familial risk is lacking. We used family designs and T2DM polygenic risk score (T2DM-PRS) to investigate the genetic associations between psychiatric disorders and T2DM.

Methods: We linked 659 906 individuals born in Denmark 1990-2000 to their parents, grandparents, and aunts/uncles using population-based registers. We compared rates of T2DM in relatives of children with and without a diagnosis of any or one of 11 specific psychiatric disorders, including neuropsychiatric and neurodevelopmental disorders, using Cox regression. In a genotyped sample (iPSYCH2015) of individuals born 1981-2008 (n = 134 403), we used logistic regression to estimate associations between a T2DM-PRS and these psychiatric disorders.

Results: Among 5 235 300 relative pairs, relatives of individuals with a psychiatric disorder had an increased risk for T2DM with stronger associations for closer relatives (parents:hazard ratio = 1.38, 95% confidence interval 1.35-1.42; grandparents: 1.14, 1.13-1.15; and aunts/uncles: 1.19, 1.16-1.22). In the genetic sample, one standard deviation increase in T2DM-PRS was associated with an increased risk for any psychiatric disorder (odds ratio = 1.11, 1.08-1.14). Both familial T2DM and T2DM-PRS were significantly associated with seven of 11 psychiatric disorders, most strongly with attention-deficit/hyperactivity disorder and conduct disorder, and inversely with anorexia nervosa.

Conclusions: Our findings of familial co-aggregation and higher T2DM polygenic liability associated with psychiatric disorders point toward shared familial risk. This suggests that part of the comorbidity is explained by shared familial risks. The underlying mechanisms still remain largely unknown and the contributions of genetics and environment need further investigation.

Background: Individuals at risk for bipolar disorder (BD) have a wide range of genetic and non-genetic risk factors, like a positive family history of BD or (sub)threshold affective symptoms. Yet, it is unclear whether these individuals at risk and those diagnosed with BD share similar gray matter brain alterations.

Methods: In 410 male and female participants aged 17-35 years, we compared gray matter volume (3T MRI) between individuals at risk for BD (as assessed using the EPIbipolar scale; n = 208), patients with a DSM-IV-TR diagnosis of BD (n = 87), and healthy controls (n = 115) using voxel-based morphometry in SPM12/CAT12. We applied conjunction analyses to identify similarities in gray matter volume alterations in individuals at risk and BD patients, relative to healthy controls. We also performed exploratory whole-brain analyses to identify differences in gray matter volume among groups. ComBat was used to harmonize imaging data from seven sites.

Results: Both individuals at risk and BD patients showed larger volumes in the right putamen than healthy controls. Furthermore, individuals at risk had smaller volumes in the right inferior occipital gyrus, and BD patients had larger volumes in the left precuneus, compared to healthy controls. These findings were independent of course of illness (number of lifetime manic and depressive episodes, number of hospitalizations), comorbid diagnoses (major depressive disorder, attention-deficit hyperactivity disorder, anxiety disorder, eating disorder), familial risk, current disease severity (global functioning, remission status), and current medication intake.

Conclusions: Our findings indicate that alterations in the right putamen might constitute a vulnerability marker for BD.

Background: Cognitive control (CC) involves a top-down mechanism to flexibly respond to complex stimuli and is impaired in schizophrenia.

Methods: This study investigated the impact of increasing complexity of CC processing in 140 subjects with psychosis and 39 healthy adults, with assessments of behavioral performance, neural regions of interest and symptom severity.

Results: The lowest level of CC (Stroop task) was impaired in all patients; the intermediate level of CC (Faces task) with explicit emotional information was most impaired in patients with first episode psychosis. Patients showed activation of distinct neural CC and reward networks, but iterative learning based on the higher-order of CC during the trust game, was most impaired in chronic schizophrenia. Subjects with first episode psychosis, and patients with lower symptom load, demonstrate flexibility of the CC network to facilitate learning, which appeared compromised in the more chronic stages of schizophrenia.

Conclusion: These data suggest optimal windows for opportunities to introduce therapeutic interventions to improve CC.

Major depressive disorder (MDD) is characterized by deficient reward functions in the brain. However, existing findings on functional alterations during reward anticipation, reward processing, and learning among MDD patients are inconsistent, and it was unclear whether a common reward system implicated in multiple reward functions is altered in MDD. Here we meta-analyzed 18 past studies that compared brain reward functions between adult MDD patients (N = 477, mean age = 26.50 years, female = 59.40%) and healthy controls (N = 506, mean age = 28.11 years, females = 55.58%), and particularly examined group differences across multiple reward functions. Jack-knife sensitivity and subgroup meta-analyses were conducted to test robustness of findings across patient comorbidity, task paradigm, and reward nature. Meta-regression analyses assessed the moderating effect of patient symptom severity and anhedonia scores. We found during reward anticipation, MDD patients showed lower activities in the lateral prefrontal-thalamus circuitry. During reward processing, patients displayed reduced activities in the right striatum and prefrontal cortex, but increased activities in the left temporal cortex. During reward learning, patients showed reduced activity in the lateral prefrontal-thalamic-striatal circuitry and the right parahippocampal-occipital circuitry but higher activities in bilateral cerebellum and the left visual cortex. MDD patients showed decreased activity in the right thalamus during both reward anticipation and learning, and in the right caudate during both reward processing and learning. Larger functional changes in MDD were observed among patients with more severe symptoms and higher anhedonia levels. The thalamic-striatal circuitry functional alterations could be the key neural mechanism underlying MDD patients overarching reward function deficiencies.

Background: Migration is a well-established risk factor for psychotic disorders, and migrant language has been proposed as a novel factor that may improve our understanding of this relationship. Our objective was to explore the association between indicators of linguistic distance and the risk of psychotic disorders among first-generation migrant groups.

Methods: Using linked health administrative data, we constructed a retrospective cohort of first-generation migrants to Ontario over a 20-year period (1992-2011). Linguistic distance of the first language was categorized using several approaches, including language family classifications, estimated acquisition time, syntax-based distance scores, and lexical-based distance scores. Incident cases of non-affective psychotic disorder were identified over a 5- to 25-year period. We used Poisson regression to estimate incidence rate ratios (IRR) for each language variable, after adjustment for knowledge of English at arrival and other factors.

Results: Our cohort included 1 863 803 first-generation migrants. Migrants whose first language was in a different language family than English had higher rates of psychotic disorders (IRR = 1.08, 95% CI 1.01-1.16), relative to those whose first language was English. Similarly, migrants in the highest quintile of linguistic distance based on lexical similarity had an elevated risk of psychotic disorder (IRR = 1.15, 95% CI 1.06-1.24). Adjustment for knowledge of English at arrival had minimal effect on observed estimates.

Conclusion: We found some evidence that linguistic factors that impair comprehension may play a role in the excess risk of psychosis among migrant groups; however, the magnitude of effect is small and unlikely to fully explain the elevated rates of psychotic disorder across migrant groups.

Background: Machine learning could predict binge behavior and help develop treatments for bulimia nervosa (BN) and alcohol use disorder (AUD). Therefore, this study evaluates person-specific and pooled prediction models for binge eating (BE), alcohol use, and binge drinking (BD) in daily life, and identifies the most important predictors.

Methods: A total of 120 patients (BN: 50; AUD: 51; BN/AUD: 19) participated in an experience sampling study, where over a period of 12 months they reported on their eating and drinking behaviors as well as on several other emotional, behavioral, and contextual factors in daily life. The study had a burst-measurement design, where assessments occurred eight times a day on Thursdays, Fridays, and Saturdays in seven bursts of three weeks. Afterwards, person-specific and pooled models were fit with elastic net regularized regression and evaluated with cross-validation. From these models, the variables with the 10% highest estimates were identified.

Results: The person-specific models had a median AUC of 0.61, 0.80, and 0.85 for BE, alcohol use, and BD respectively, while the pooled models had a median AUC of 0.70, 0.90, and 0.93. The most important predictors across the behaviors were craving and time of day. However, predictors concerning social context and affect differed among BE, alcohol use, and BD.

Conclusions: Pooled models outperformed person-specific models and the models for alcohol use and BD outperformed those for BE. Future studies should explore how the performance of these models can be improved and how they can be used to deliver interventions in daily life.

Background: Cognitive behavioral therapy (CBT) is an effective treatment for patients with social anxiety disorder (SAD) or major depressive disorder (MDD), yet there is variability in clinical improvement. Though prior research suggests pre-treatment engagement of brain regions supporting cognitive reappraisal (e.g. dorsolateral prefrontal cortex [dlPFC]) foretells CBT response in SAD, it remains unknown if this extends to MDD or is specific to CBT. The current study examined associations between pre-treatment neural activity during reappraisal and clinical improvement in patients with SAD or MDD following a trial of CBT or supportive therapy (ST), a common-factors comparator arm.

Methods: Participants were 75 treatment-seeking patients with SAD (n = 34) or MDD (n = 41) randomized to CBT (n = 40) or ST (n = 35). Before randomization, patients completed a cognitive reappraisal task during functional magnetic resonance imaging. Additionally, patients completed clinician-administered symptom measures and a self-report cognitive reappraisal measure before treatment and every 2 weeks throughout treatment.

Results: Results indicated that pre-treatment neural activity during reappraisal differentially predicted CBT and ST response. Specifically, greater trajectories of symptom improvement throughout treatment were associated with less ventrolateral prefrontal cortex (vlPFC) activity for CBT patients, but more vlPFC activity for ST patients. Also, less baseline dlPFC activity corresponded with greater trajectories of self-reported reappraisal improvement, regardless of treatment arm.

Conclusions: If replicated, findings suggest individual differences in brain response during reappraisal may be transdiagnostically associated with treatment-dependent improvement in symptom severity, but improvement in subjective reappraisal following psychotherapy, more broadly.