Personalized Medicine in Psychiatry最新文献

Trichotillomania (TTM) is an underdiagnosed and distressing condition that necessitates an effective medication; however, there is currently no established first-line pharmacological treatment. TTM is characterized by compulsive hair pulling, leading to noticeable hair loss and significant distress. We present the first documented case of using gabapentin as a treatment for trichotillomania. Our patient, who has chronic depression and anxiety, developed TTM following a traumatic brain injury to the right temporal region. Multiple pharmacotherapies over five years, including various selective serotonin reuptake inhibitors (SSRIs), buspirone, N-acetylcysteine, and valproate, produced minimal benefit. When gabapentin was added to the ongoing treatment with citalopram and valproate, the patient reported cessation of hair-pulling behavior and hair growth by the next visit, eight weeks later. This improvement was sustained for an additional fourteen weeks. However, the therapeutic effects deteriorated within two weeks after the patient individually gabapentin. Gabapentin’s potential as an effective agent for TTM deserves further investigation.

Background

Repetitive transcranial magnetic stimulation (rTMS) therapy could be improved by more accurate and earlier prediction of response. Latent class mixture (LCMM) and non-linear mixed effects (NLME) modeling have been applied to model the trajectories of antidepressant response (or non-response) to TMS, but it is not known whether such models are useful in predicting clinically meaningful change in symptom severity, i.e. categorical (non)response as opposed to continuous scores.

Methods

We compared LCMM and NLME approaches to model the antidepressant response to TMS in a naturalistic sample of 238 patients receiving rTMS for treatment resistant depression, across multiple coils and protocols. We then compared the predictive power of those models.

Results

LCMM trajectories were influenced largely by baseline symptom severity, but baseline symptoms provided little predictive power for later antidepressant response. Rather, the optimal LCMM model was a nonlinear two-class model that accounted for baseline symptoms. This model accurately predicted patient response at 4 weeks of treatment (AUC=0.70, 95 % CI=[0.52–0.87]), but not before. NLME offered slightly improved predictive performance at 4 weeks of treatment (AUC=0.76, 95 % CI=[0.58–0.94], but likewise, not before.

Conclusions

In showing the predictive validity of these approaches to model response trajectories to rTMS, we provided preliminary evidence that trajectory modeling could be used to guide future treatment decisions.

Background and objectives

We examined measurement invariance of the Screen for Child Anxiety Related Emotional Disorders (SCARED) across ethnicity (Hispanic vs. non-Hispanic White), age (8–12 vs. 13–18 years-old), and sex-at-birth (male vs. female) groups.

Design/methods

Using a sample of 975 youth with depression (M_age = 15.5) from the Texas Youth Depression and Suicide Research Network (TX-YDSRN), confirmatory factor analysis (CFA) and multi-group-CFA (MG-CFA) were employed to assess the factor structure of the SCARED across demographic groups.

Results

With the entire sample, a five-factor model demonstrated adequate fit. Evidence of measurement invariance across ethnicity, age, and sex groups was provided via MG-CFAs, which indicated no appreciable deterioration in model fit as varying levels of constraints (configural, metric, and scalar) were implemented. Factor loadings exceeded 0.5 within groups in MG-CFA models, suggesting consistent psychometric performance across groups. Mean group comparisons indicated females endorsed greater anxiety across subscales, younger children endorsed higher levels of separation anxiety, older children endorsed greater generalized anxiety, and scores were mostly equivalent across ethnicity groupings.

Conclusion

While marginal model fit qualifies conclusions, our findings concerning measurement invariance of the SCARED across various demographic groups provide further support for the use of this measure in diverse contexts.

This case report presents the unique story of a married couple, Mr. A and Mrs. B, who both suffered from severe obsessive–compulsive disorder (OCD) as well as mild to moderate depression, and underwent superolateral medial forebrain bundle deep brain stimulation (slMFB DBS) together. Mr. A struggled with fear of making mistakes and ritualistic behaviors, while Mrs. B experienced magical thinking and order obsessions when they met each other during one of their psychiatric hospital stays. After hospitalization, they quickly became a couple and decided to start a life together, culminating in marriage a few years later. Despite various treatments, the couple’s conditions remained a formidable challenge, leading them to ultimately opt for DBS together. DBS has emerged as a promising intervention for severe, treatment-resistant OCD cases, yet optimal target regions remain debated. The slMFB has recently garnered attention as a potential target due to its connectivity with reward pathways and involvement in OCD. Following surgery and postoperative management, both patients experienced substantial improvements in OCD symptoms, with reductions in intrusive thoughts and compulsive behaviors. Additionally, their depressive symptoms notably decreased. Around 15 months after the surgeries, the couple welcomed their first child. Long-term follow-up revealed sustained improvements, allowing them to actively engage in familial and professional endeavors. Mr. A successfully completed training and secured full-time employment, while Mrs. B resumed work and household responsibilities. Their experiences underscore the efficacy of slMFB DBS in alleviating OCD symptoms and associated depression, enhancing overall quality of life.

International students are susceptible to several mental health disorders, including anxiety and depression amid the COVID-19 pandemic due to the implementation of epidemic control measures such as lockdown, quarantine, etc. The study aimed to investigate the depression and anxiety status as well as influencing factors of international students in Hunan, China during the COVID-19 outbreak lockdown. An online cross-sectional survey was conducted between May and June 2020. A snowball sampling technique was used to recruit participants. Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) were used to assess depression and anxiety status, respectively. 450 participants completed the online survey. The overall prevalence of depression and anxiety was 28.7 % and 36.9 %, respectively. Multivariate logistic regression analyses showed that having suspected symptoms of COVID-19 (aOR = 3.54, 95 %CI = 1.30–9.64) and having family members or friends infected with COVID-19 (aOR = 1.51, 95 %CI = 1.31–3.84) were positively associated with depression. Being single was positively associated with anxiety (aOR = 3.10, 95 %CI = 1.46–6.57). Also, obtaining news or updates about the COVID-19 daily (aOR = 1.76, 95 %CI = 1.13–3.75), and using electronic devices for 5–6 h every day (aOR = 2.21, 95 %CI = 1.17–4.17) showed a positive association with anxiety. Furthermore, having a high coping strategy was negatively associated with anxiety (aOR = 0.33, 95 %CI = 0.12–0.92). Although implementing lockdown was an excellent measure, it resulted in a high prevalence of depression and anxiety symptoms. The findings support previous studies that reported an increased in depression and anxiety status due to the COVID-19 pandemic. Therefore, mental health education and psychological support should be provided to this population during the pandemic or future epidemic diseases.

The Narrative Crisis Model of Suicide (NCM) is a dynamic multi-stage model that incorporates well-documented long- and short-term risk factors to conceptualize individuals’ progression to suicidal behavior. Comprising chronic long-term suicide vulnerabilities, subacute mental state of Suicidal Narrative, and acute Suicide Crisis Syndrome, the NCM emerged out of the urgent need to better understand, assess, and treat mental processes resulting in suicide with the ultimate goal of creating a comprehensive framework for suicide prevention. This paper conducts the first peer-reviewed critical review of the NCM. In the first section, we provide a comprehensive presentation of the NCM with emphasis on its innovative approach to address common pitfalls in clinical conceptualizations and assessment of suicidal mental states and suicide risk. Second, we present a narrative review of the empirical support for each NCM component and the emerging evidence for the whole model. Last, we compare the NCM to alternative models of suicide in order to highlight their shared features as well as the NCM’s unique contribution to risk assessment and prevention. By clarifying the tenets of the NCM, its emerging empirical support, and its relationships to the other models of suicide in the extant literature, this critical review paper sets the stage for future studies on the model.

The Narrative Crisis Model of Suicide (NCM) is an iterative, dynamic, diathesis-stress model that conceptualizes individuals’ progression to suicidal behavior through the incorporation of four distinct and successive stages. The NCM strives to reflect a paradigm change in the prevention of suicide: rather than assessing individuals’ suicide risk and categorizing them along different risk levels based on their self-reported suicidal ideation at a given time, the NCM proposes to assess psychological vulnerabilities and processes characteristic of critical milestones in the progression from chronic factors to acute suicidal mental states. As a comprehensive model, the NCM provides an empirically grounded conceptual framework for intervention at each stage of the psychological progression towards suicidal action. In this article, we propose stage-specific treatment modalities, moving progressively from acute to chronic risk. Such treatments would first target the acute Suicide Crisis Syndrome (Stage 4), the subacute suicidal narrative (Stage 3), deficits in stress management (Stage 2), and finally long-term risk factors/trait vulnerabilities (Stage 1). Although future research is needed to establish the optimal combination and sequence of empirically-supported interventions, the NCM may be a useful framework to guide innovations in clinical intervention and research.

Obsessive-compulsive disorder (OCD) is a widespread neuropsychiatric disorder with a lifetime prevalence of 2–3 %. This disorder is marked by significant obsessive distress, leading to interpersonal and occupational challenges, as well as high economic and societal burdens. As 40–60 % of patients fail to respond to standard psychological and pharmacological interventions, there is a critical need for effective alternatives. Transcranial Magnetic Stimulation (TMS), a non-invasive procedure for focal cortical neuro-modulation, received approval by the Food and Drug Administration in 2018 for the treatment of OCD. The TMS protocol includes a step of symptom provocation prior to each treatment session, which is intended to increase patients’ responsiveness to magnetic stimulation. However, the absence of a standard protocol has led to significant heterogeneity in how symptom provocation is conducted, posing challenges in comparing studies. This paper systematically reviews the literature on the theories, methods, and parameters of symptom provocation, focusing on how it is implemented in existing clinical studies. The findings reveal a substantial lack of details in most studies about the execution and parameters of symptom provocation. There is a pressing need for randomized clinical trials to determine the optimal level of obsessive distress to be induced before TMS. The insights gained will inform future protocols and guidelines, enhancing the efficiency and precision of the symptom provocation procedure.

Background

The role of testosterone in mood regulation has been studied by different authors with inconsistent results. It seems that low testosterone could be related to depressed mood in hypogonadal men; however, in women, both high and low testosterone levels have been implicated in depression. In this study, we evaluated androgen levels in depressed patients, comparing between sexes, and testing anxiety levels.

Methods

We included unmedicated women and men diagnosed with major depressive disorder, according to DSM-5 criteria. Patients with drug and alcohol abuse, hormonal medication, uncontrolled medical illness, or psychiatric disorders other than depression or anxiety were excluded. We applied the HDRS, State and Trait Anxiety Inventory (STAI), and Perceived Stress Scale (PSS) to all participants and measured cortisol, total testosterone, free testosterone, and dehydroepiandrosterone.

Results

A total of 71 participants (21 male) completed all evaluations. In the overall sample, we detected correlations between cortisol levels and STAI scores, as well as between perceived stress and cortisol. In our correlation analysis of testosterone and psychological evaluations stratified by sex, we found that in women, higher levels of free testosterone were associated with increased perceived stress, as indicated by the PSS.

Limitations

A small sample was recruited for the study. Furthermore, although validated anxiety scales were used, all data were self-reported.

Conclusions

The role of testosterone in anxiety differs between male and female depressed patients. Perceived stress could be an important measurement in women, as it was related to FT levels in this sample.

Objectives

We aimed to identify the significant genetic variations and molecular mechanisms associated with the pathogenesis of mood disorders associated with genetic variants.

Methods

Genome-wide association studies (GWAS, ID: EFO_0003761), ClueGO plug-in, and GEO database were the main approaches.

Results

Ten biomarkers that are frequently related to mood disorders were identified across all studies. In terms of mood disorders, a collection of biomarkers has been found, with specific attention given to seven fundamental genetic variations. A comprehensive analysis revealed a total of five central biomarkers that exhibited a significant association with unipolar depression, with an additional five central biomarkers that demonstrated a significant association with mixed traits. Biomarkers that have been linked to an increased vulnerability to mood disorders have been found to disrupt many cellular processes in neuronal development, including cell morphogenesis, cell projection organization, and cell adhesion. The main signaling pathways associated with biomarkers that contribute to a reduced susceptibility to mood disorders encompass the activation of neuro projection morphogenesis, O-linked glycosylation, modulation of chemical synaptic transmission, and G-protein-coupled glutamate receptor activity. hsa-miR-3937, hsa-miR-4499, and hsa-miR-7106-5p exhibited the most significant downregulation in the GSE182194 dataset. A microRNA (hsa-miR-26b-5p) and transcription factors (zinc finger proteins) were found to have a pivotal role in the elucidation of genetic variations linked to mood disorders across different datasets (EFO_0003761, GSE101521, and GSE217811).

Conclusions

Our findings provide a foundational framework for prospective therapeutic approaches aimed at addressing mood disorders, specifically focusing on the genetic variants and pathways linked to this condition.