Major depressive disorder (MDD) is the leading cause of disability globally, with moderate heritability and well-established socio-environmental risk factors. Genetic studies have been mostly restricted to European settings, with polygenic scores (PGS) demonstrating low portability across diverse global populations.

This study examines genetic architecture, polygenic prediction, and socio-environmental correlates of MDD in a family-based sample of 10 032 individuals from Nepal with array genotyping data. We used genome-based restricted maximum likelihood to estimate heritability, applied S-LDXR to estimate the cross-ancestry genetic correlation between Nepalese and European samples, and modeled PGS trained on a GWAS meta-analysis of European and East Asian ancestry samples.

We estimated the narrow-sense heritability of lifetime MDD in Nepal to be 0.26 (95% CI 0.18–0.34, p = 8.5 × 10−6). Our analysis was underpowered to estimate the cross-ancestry genetic correlation (rg = 0.26, 95% CI −0.29 to 0.81). MDD risk was associated with higher age (beta = 0.071, 95% CI 0.06–0.08), female sex (beta = 0.160, 95% CI 0.15–0.17), and childhood exposure to potentially traumatic events (beta = 0.050, 95% CI 0.03–0.07), while neither the depression PGS (beta = 0.004, 95% CI −0.004 to 0.01) or its interaction with childhood trauma (beta = 0.007, 95% CI −0.01 to 0.03) were strongly associated with MDD.

Estimates of lifetime MDD heritability in this Nepalese sample were similar to previous European ancestry samples, but PGS trained on European data did not predict MDD in this sample. This may be due to differences in ancestry-linked causal variants, differences in depression phenotyping between the training and target data, or setting-specific environmental factors that modulate genetic effects. Additional research among under-represented global populations will ensure equitable translation of genomic findings.

Majority of international guidelines for bipolar disorders are based on evidences from clinical trials. In contrast, the Korean Medication Algorithm Project for Bipolar Disorder (KMAP-BP) was developed to adopt an expert-consensus paradigm which was more practical and specific to the atmosphere in Korea.

In this study, preferred medication strategies for acute mania over six consecutively published KMAP-BP (2002, 2006, 2010, 2014, 2018, and 2022) were investigated.

A written survey using a nine-point scale was asked to Korean experts about the appropriateness of various treatment strategies and treatment agents. A written survey asked about the appropriateness of various treatment strategies and treatment agents commonly used by clinicians as the first-line.

The most preferred option for the initial treatment of mania was a combination of a mood stabilizer (MS) and an atypical antipsychotic (AAP) in every edition. Preference for combined treatment for euphoric mania increased, peaked in KMAP-BP 2010, and declined slightly. Either MS or AAP monotherapy was also considered a first-line strategy for mania, but not for all types of episodes, including mixed/psychotic mania. Among MSs, lithium and valproate are almost equally preferred except in the mixed subtype where valproate is the most recommended MS. The preference of valproate showed reverse U-shaped curve. This preference change of valproate may indicate the concern about teratotoxicity in women. Quetiapine, aripiprazole, and olanzapine were the preferred AAP for acute mania since 2014. This change might depend on the recent evidences and safety profile. In cases of unsatisfactory response to initial medications, switching or adding another first-line agent was recommended. The most notable changes over time included the increasing preference for AAPs.

The Korean experts have been increasingly convinced of the effectiveness of a combination therapy for acute mania. There have been evident preference changes: increased for AAP and decreased for carbamazepine.

None Declared

Population-wide restrictions during the COVID-19 pandemic may create barriers to mental health diagnosis. This study aims to examine changes in the number of incident cases and the incidence rates of mental health diagnoses during the COVID-19 pandemic.

By using electronic health records from France, Germany, Italy, South Korea and the UK and claims data from the US, this study conducted interrupted time-series analyses to compare the monthly incident cases and the incidence of depressive disorders, anxiety disorders, alcohol misuse or dependence, substance misuse or dependence, bipolar disorders, personality disorders and psychoses diagnoses before (January 2017 to February 2020) and after (April 2020 to the latest available date of each database [up to November 2021]) the introduction of COVID-related restrictions.

A total of 629,712,954 individuals were enrolled across nine databases. Following the introduction of restrictions, an immediate decline was observed in the number of incident cases of all mental health diagnoses in the US (rate ratios (RRs) ranged from 0.005 to 0.677) and in the incidence of all conditions in France, Germany, Italy and the US (RRs ranged from 0.002 to 0.422). In the UK, significant reductions were only observed in common mental illnesses. The number of incident cases and the incidence began to return to or exceed pre-pandemic levels in most countries from mid-2020 through 2021.

Healthcare providers should be prepared to deliver service adaptations to mitigate burdens directly or indirectly caused by delays in the diagnosis and treatment of mental health conditions.

Blood-based biomarkers represent a scalable and accessible approach for the detection and monitoring of Alzheimer’s disease (AD). Plasma phosphorylated tau (p-tau) and neurofilament light (NfL) are validated biomarkers for the detection of tau and neurodegenerative brain changes in AD, respectively. There is now emphasis to expand beyond these markers to detect and provide insight into the pathophysiological processes of AD. To this end, a reactive astrocytic marker, namely plasma glial fibrillary acidic protein (GFAP), has been of interest. Yet, little is known about the relationship between plasma GFAP and AD. Here, we examined the association between plasma GFAP, diagnostic status, and neuropsychological test performance. Diagnostic accuracy of plasma GFAP was compared with plasma measures of p-tau181 and NfL.

This sample included 567 participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC) Longitudinal Clinical Core Registry, including individuals with normal cognition (n=234), mild cognitive impairment (MCI) (n=180), and AD dementia (n=153). The sample included all participants who had a blood draw. Participants completed a comprehensive neuropsychological battery (sample sizes across tests varied due to missingness). Diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using the Simoa platform. Binary logistic regression analyses tested the association between GFAP levels and diagnostic status (i.e., cognitively impaired due to AD versus unimpaired), controlling for age, sex, race, education, and APOE e4 status. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate diagnostic groups compared with plasma p-tau181 and NfL. Linear regression models tested the association between plasma GFAP and neuropsychological test performance, accounting for the above covariates.

The mean (SD) age of the sample was 74.34 (7.54), 319 (56.3%) were female, 75 (13.2%) were Black, and 223 (39.3%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having cognitive impairment (GFAP z-score transformed: OR=2.233, 95% CI [1.609, 3.099], p<0.001; non-z-transformed: OR=1.004, 95% CI [1.002, 1.006], p<0.001). ROC analyses, comprising of GFAP and the above covariates, showed plasma GFAP discriminated the cognitively impaired from unimpaired (AUC=0.75) and was similar, but slightly superior, to plasma p-tau181 (AUC=0.74) and plasma NfL (AUC=0.74). A joint panel of the plasma markers had greatest discrimination accuracy (AUC=0.76). Linear regression analyses showed that higher GFAP levels were associated with worse performance on neuropsychological tests assessing global cognition, attention, executive functioning, episodic memory, and language abilities (ps<0.001) as well as higher CDR Sum of Boxes (p<0.001).

Higher plasma GFAP levels differentiated participants with cognitive impairment from those with normal cognition and were associated with worse performance on all neuropsychological tests assessed. GFAP had similar accuracy in detecting those with cognitive impairment compared with p-tau181 and NfL, however, a panel of all three biomarkers was optimal. These results support the utility of plasma GFAP in AD detection and suggest the pathological processes it represents might play an integral role in the pathogenesis of AD.

Blood-based biomarkers offer a more feasible alternative to Alzheimer’s disease (AD) detection, management, and study of disease mechanisms than current in vivo measures. Given their novelty, these plasma biomarkers must be assessed against postmortem neuropathological outcomes for validation. Research has shown utility in plasma markers of the proposed AT(N) framework, however recent studies have stressed the importance of expanding this framework to include other pathways. There is promising data supporting the usefulness of plasma glial fibrillary acidic protein (GFAP) in AD, but GFAP-to-autopsy studies are limited. Here, we tested the association between plasma GFAP and AD-related neuropathological outcomes in participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC).

This sample included 45 participants from the BU ADRC who had a plasma sample within 5 years of death and donated their brain for neuropathological examination. Most recent plasma samples were analyzed using the Simoa platform. Neuropathological examinations followed the National Alzheimer’s Coordinating Center procedures and diagnostic criteria. The NIA-Reagan Institute criteria were used for the neuropathological diagnosis of AD. Measures of GFAP were log-transformed. Binary logistic regression analyses tested the association between GFAP and autopsy-confirmed AD status, as well as with semi-quantitative ratings of regional atrophy (none/mild versus moderate/severe) using binary logistic regression. Ordinal logistic regression analyses tested the association between plasma GFAP and Braak stage and CERAD neuritic plaque score. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate autopsy-confirmed AD status. All analyses controlled for sex, age at death, years between last blood draw and death, and APOE e4 status.

Of the 45 brain donors, 29 (64.4%) had autopsy-confirmed AD. The mean (SD) age of the sample at the time of blood draw was 80.76 (8.58) and there were 2.80 (1.16) years between the last blood draw and death. The sample included 20 (44.4%) females, 41 (91.1%) were White, and 20 (44.4%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having autopsy-confirmed AD (OR=14.12, 95% CI [2.00, 99.88], p=0.008). ROC analysis showed plasma GFAP accurately discriminated those with and without autopsy-confirmed AD on its own (AUC=0.75) and strengthened as the above covariates were added to the model (AUC=0.81). Increases in GFAP levels corresponded to increases in Braak stage (OR=2.39, 95% CI [0.71-4.07], p=0.005), but not CERAD ratings (OR=1.24, 95% CI [0.004, 2.49], p=0.051). Higher GFAP levels were associated with greater temporal lobe atrophy (OR=10.27, 95% CI [1.53,69.15], p=0.017), but this was not observed with any other regions.

The current results show that antemortem plasma GFAP is associated with non-specific AD neuropathological changes at autopsy. Plasma GFAP could be a useful and practical biomarker for assisting in the detection of AD-related changes, as well as for study of disease mechanisms.

Anterior temporal lobectomy is a common surgical approach for medication-resistant temporal lobe epilepsy (TLE). Prior studies have shown inconsistent findings regarding the utility of presurgical intracarotid sodium amobarbital testing (IAT; also known as Wada test) and neuroimaging in predicting postoperative seizure control. In the present study, we evaluated the predictive utility of IAT, as well as structural magnetic resonance imaging (MRI) and positron emission tomography (PET), on long-term (3-years) seizure outcome following surgery for TLE.

Patients consisted of 107 adults (mean age=38.6, SD=12.2; mean education=13.3 years, SD=2.0; female=47.7%; White=100%) with TLE (mean epilepsy duration =23.0 years, SD=15.7; left TLE surgery=50.5%). We examined whether demographic, clinical (side of resection, resection type [selective vs. non-selective], hemisphere of language dominance, epilepsy duration), and presurgical studies (normal vs. abnormal MRI, normal vs. abnormal PET, correctly lateralizing vs. incorrectly lateralizing IAT) were associated with absolute (cross-sectional) seizure outcome (i.e., freedom vs. recurrence) with a series of chi-squared and t-tests. Additionally, we determined whether presurgical evaluations predicted time to seizure recurrence (longitudinal outcome) over a three-year period with univariate Cox regression models, and we compared survival curves with Mantel-Cox (log rank) tests.

Demographic and clinical variables (including type [selective vs. whole lobectomy] and side of resection) were not associated with seizure outcome. No associations were found among the presurgical variables. Presurgical MRI was not associated with cross-sectional (OR=1.5, p=.557, 95% CI=0.4-5.7) or longitudinal (HR=1.2, p=.641, 95% CI=0.4-3.9) seizure outcome. Normal PET scan (OR= 4.8, p=.045, 95% CI=1.0-24.3) and IAT incorrectly lateralizing to seizure focus (OR=3.9, p=.018, 95% CI=1.2-12.9) were associated with higher odds of seizure recurrence. Furthermore, normal PET scan (HR=3.6, p=.028, 95% CI =1.0-13.5) and incorrectly lateralized IAT (HR= 2.8, p=.012, 95% CI=1.2-7.0) were presurgical predictors of earlier seizure recurrence within three years of TLE surgery. Log rank tests indicated that survival functions were significantly different between patients with normal vs. abnormal PET and incorrectly vs. correctly lateralizing IAT such that these had seizure relapse five and seven months earlier on average (respectively).

Presurgical normal PET scan and incorrectly lateralizing IAT were associated with increased risk of post-surgical seizure recurrence and shorter time-to-seizure relapse.

Excessive and persistent fear of clusters of holes, also known as trypophobia, has been suggested to reflect cortical hyperexcitability and may be associated with mental health risks. No study, however, has yet examined these associations in representative epidemiological samples.

To examine the prevalence of trypophobia in a population-representative youth sample, its association with mental health and functioning, and its interaction with external stress.

A total of 2065 young people were consecutively recruited from a household-based epidemiological youth mental health study in Hong Kong. Trypophobia, symptoms of anxiety, depression and stress, and exposure to personal stressors were assessed. Logistic regression was used to assess the relationships between trypophobia and mental health. Potential additive and interaction effects of trypophobia and high stress exposure on mental health were also tested.

The prevalence of trypophobia was 17.6%. Trypophobia was significantly associated with severe symptoms of anxiety (odds ratio (OR) = 1.83, 95% CI = 1.32–2.53), depression (OR = 1.78, 95% CI = 1.24–2.56) and stress (OR = 1.68, 95% CI = 1.11–2.53), even when accounting for sociodemographic factors, personal and family psychiatric history, resilience and stress exposure. Dose–response relationships were observed, and trypophobia significantly potentiated the effects of stress exposure on symptom outcomes, particularly for depressive symptoms. Those with trypophobia also showed significantly poorer functioning across domains and poorer health-related quality of life.

Screening for trypophobia in young people may facilitate early risk detection and intervention, particularly among those with recent stress exposure. Nevertheless, the generally small effect sizes suggest that other factors have more prominent roles in determining recent mental health outcomes in population-based samples; these should be explored in future work.

Clinical trials provide the “gold standard” evidence for advancing the practice of medicine, even as they evolve to integrate real-world data sources. Modern clinical trials are increasingly incorporating real-world data sources – data not intended for research and often collected in free-living contexts. We refer to trials that incorporate real-world data sources as real-world trials. Such trials may have the potential to enhance the generalizability of findings, facilitate pragmatic study designs, and evaluate real-world effectiveness. However, key differences in the design, conduct, and implementation of real-world vs traditional trials have ramifications in data management that can threaten their desired rigor.

Three examples of real-world trials that leverage different types of data sources – wearables, medical devices, and electronic health records are described. Key insights applicable to all three trials in their relationship to Data and Safety Monitoring Boards (DSMBs) are derived.

Insight and recommendations are given on four topic areas: A. Charge of the DSMB; B. Composition of the DSMB; C. Pre-launch Activities; and D. Post-launch Activities. We recommend stronger and additional focus on data integrity.

Clinical trials can benefit from incorporating real-world data sources, potentially increasing the generalizability of findings and overall trial scale and efficiency. The data, however, present a level of informatic complexity that relies heavily on a robust data science infrastructure. The nature of monitoring the data and safety must evolve to adapt to new trial scenarios to protect the rigor of clinical trials.

Autism spectrum disorders (ASD) and psychotic disorders have historically considered to be related conditions with a long history of diagnostic confusion. Although DSM-III distinguishes ASD and Schizophrenia Spectrum Disorders as distinct clinical entities, they continue to share overlaps in their clinical symptom presentations leading to diagnostic challenges that may consequentially result in delayed treatment. Prompt diagnosis is crucial in the context of psychosis, where early intervention impacts recovery.

To present the diagnostic challenges encountered in distinguishing ASD from Psychosis.

We present a case report demonstrating the challenges of distinguishing ASD from Psychosis.

This is a case of a gentleman who initially presented to psychiatric services at 18 years old for conflicts with his mother related to his inflexibility to change. Further psychological evaluation revealed that he had a history of restricted social interaction with his peers, difficulties in non-verbal communications and identifying emotional states, stereotyped interests and obsessions that isolated him from his peers. He was diagnosed with ASD.

In subsequent presentations, there were symptoms of excessive preoccupation of his facial appearance, excessive concern over contracting HIV, obsessions with arranging objects in a particular order and avoiding words starting with the letter “S” out of fears of blasphemy. While these symptoms had qualities of cognitive inflexibility, they could not fully be explained by ASD. Additional diagnoses of Body Dysmorphic Disorder, Borderline Personality Disorder, Obsessive Compulsive Personality Disorder and At-Risk Mental State were considered.

A psychiatric admission was necessitated at 21 years old, when he presented with a 2-year history of repetitive banging of furniture in the middle of the night to communicate his frustrations towards his parents for their perceived acts of blasphemy. He also began to isolate himself, fearing that his parents would be able to look into his soul and reveal his sins. This paranoia towards his parents worsened to the point of urinating and defecating in his room to avoid his parents. His school performance declined as well.

A unifying diagnosis of psychosis was made. His previous diagnosis of ASD was challenged as a misdiagnosis, with the impression that he likely had attenuated psychotic symptoms in his adolescent years, disguised as autistic traits. The diagnosis of psychosis was confirmed when the patient’s symptoms were observed to respond to antipsychotic treatment.

This case report illustrates the challenges in distinguishing ASD from psychosis. A prior diagnosis of ASD may result in diagnostic overshadowing and subsequent delays in diagnosing psychosis. Further research in diagnostic tools would be helpful for diagnostic precision, thereby enabling prompt treatment for better recovery outcomes.

None Declared

Despite emerging evidence suggesting the efficacy of psilocybin in the treatment of mood disorders such as depression, the exact mechanisms by which psilocybin is able to elicit these antidepressant effects remains unknown.

As the use of psilocybin as a treatment modality for depression has garnered increasing interest, this study aims to summarize the existing evidence of the mechanism of action with which psilocybin alleviates depressive symptoms, focusing specifically on the neurobiological effects of psilocybin in human subjects.

Four databases (Ovid MEDLINE, EMBASE, psychINFO, and Web of Science) were searched using a combination of MeSH terms and free text keywords in September 2021. The original search included both human and animal studies and must have included testing of the mechanism of action of psilocybin. Only antidepressant effects were considered, with no other mood disorders or psychiatric diagnoses included. Two independent researchers screened at every stage of the review, with a third researcher resolving any conflicts. Though a full systematic review outlining the current literature on the complete mechanisms of action of psilocybin on depression was conducted, this abstract will focus specifically on the nine papers that included human subjects, disregarding the five animal models. PROSPERO registration number: 282710.

After removing duplicates, the search identified 2193 papers and forty-nine were selected for full text review. Out of nine papers outlining the mechanisms of action of psilocybin use in human subjects, three papers investigated psilocybin’s effect on serotonin or glutamate receptor activity, two found an increase in synaptogenesis in regions such as the medial frontal cortex and hippocampus. Four found variation in blood flow to the amygdala, two found altered blood flow to the prefrontal cortex, and one found a reduction in delta power during sleep. Four papers found changes in functional connectivity or neurotransmission, most commonly in the hippocampus or prefrontal cortex.

Overall, the exact mechanism of psilocybin’s potential antidepressant effect remains unclear. Multiple pathways may be involved, including alterations in serotonin and glutamate receptor activity, as well as shifts in amygdala activity, neurogenesis, and functional connectivity in various brain regions. The relative lack of studies, and the variety of neurobiological modalities and endpoints used challenged the consolidation of data into consensus findings. Further studies are needed to better characterize psilocybin’s mechanism of action and to better understand the clinical effects of the use of psilocybin in the treatment of depression.

None Declared

Childhood adversities (CAs) predict heightened risks of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) among people exposed to adult traumatic events. Identifying which CAs put individuals at greatest risk for these adverse posttraumatic neuropsychiatric sequelae (APNS) is important for targeting prevention interventions.

Data came from n = 999 patients ages 18–75 presenting to 29 U.S. emergency departments after a motor vehicle collision (MVC) and followed for 3 months, the amount of time traditionally used to define chronic PTSD, in the Advancing Understanding of Recovery After Trauma (AURORA) study. Six CA types were self-reported at baseline: physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect and bullying. Both dichotomous measures of ever experiencing each CA type and numeric measures of exposure frequency were included in the analysis. Risk ratios (RRs) of these CA measures as well as complex interactions among these measures were examined as predictors of APNS 3 months post-MVC. APNS was defined as meeting self-reported criteria for either PTSD based on the PTSD Checklist for DSM-5 and/or MDE based on the PROMIS Depression Short-Form 8b. We controlled for pre-MVC lifetime histories of PTSD and MDE. We also examined mediating effects through peritraumatic symptoms assessed in the emergency department and PTSD and MDE assessed in 2-week and 8-week follow-up surveys. Analyses were carried out with robust Poisson regression models.

Most participants (90.9%) reported at least rarely having experienced some CA. Ever experiencing each CA other than emotional neglect was univariably associated with 3-month APNS (RRs = 1.31–1.60). Each CA frequency was also univariably associated with 3-month APNS (RRs = 1.65–2.45). In multivariable models, joint associations of CAs with 3-month APNS were additive, with frequency of emotional abuse (RR = 2.03; 95% CI = 1.43–2.87) and bullying (RR = 1.44; 95% CI = 0.99–2.10) being the strongest predictors. Control variable analyses found that these associations were largely explained by pre-MVC histories of PTSD and MDE.

Although individuals who experience frequent emotional abuse and bullying in childhood have a heightened risk of experiencing APNS after an adult MVC, these associations are largely mediated by prior histories of PTSD and MDE.

Binge eating disorder (BED) is a pernicious psychiatric disorder which is linked with broad medical and psychiatric morbidity, and obesity. While BED may be characterized by altered cortical morphometry, no evidence to date examined possible sex-differences in regional gray matter characteristics among those with BED. This is especially important to consider in children, where BED symptoms often emerge coincident with rapid gray matter maturation.

Pre-adolescent, 9–10-year old boys (N = 38) and girls (N = 33) with BED were extracted from the 3.0 baseline (Year 0) release of the Adolescent Brain Cognitive Development Study. We investigated sex differences in gray matter density (GMD) via voxel-based morphometry. Control sex differences were also assessed in age and body mass index and developmentally matched control children (boys N = 36; girls N = 38). Among children with BED, we additionally assessed the association between dorsolateral prefrontal (dlPFC) GMD and parent-reported behavioral approach and inhibition tendencies.

Girls with BED uniquely demonstrate diffuse clusters of greater GMD (p < 0.05, Threshold Free Cluster Enhancement corrected) in the (i) left dlPFC (p = 0.003), (ii) bilateral dmPFC (p = 0.004), (iii) bilateral primary motor and somatosensory cortex (p = 0.0003) and (iv) bilateral precuneus (p = 0.007). Brain-behavioral associations suggest a unique negative correlation between GMD in the left dlPFC and behavioral approach tendencies among girls with BED.

Early-onset BED may be characterized by regional sex differences in terms of its underlying gray matter morphometry.

Adolescents with major depressive disorder (MDD) often show reduced prefrontal functional connectivity with the subcortical regions than healthy controls (HC) (Tang et al., 2018). However, relatively little is known about longitudinal effects of antidepressant (AD) treatment on resting state functional connectivity (RSFC) in the prefrontal cortex (PFC).

This study aimed to investigate abnormal PFC RSFC in MDD adolescents compared to HC and longitudinal effects of AD on PFC RSFC.

This study included 59 adolescents with MDD and 43 HC. MDD adolescents were treated with escitalopram in an 8 week, open-label trial. The treatment outcome was assessed by Children’s Depression Rating Scale (CDRS-R) and patients showing at least a 40% improvement in CDRS-R scores from baseline to week 8 were defined as “responders”. Functional and T1 images collected before and after treatment were processed using AFNI and Freesurfer. Our seed was the lateral PFC (LPFC, BA46). T-tests and repeated measures ANCOVAs, controlling for age and IQ, were conducted to examine abnormal PFC RSFC and longitudinal effects of AD on LPFC RSFC.

Relative to HC, MDD showed increased LPFC RSFC with the posterior middle temporal gyrus (pMTG) and superior frontal cortex (SFG) involved in attentional networks. Responders showed greater changes in LPFC RSFC with the MTG and SFG after AD treatment compared to non-responders and HC (Figure 1).

Our finding suggests that reduced LPFC RSFC with the pMTG and SFG reflecting decreased attentional network connectivity may serve as a biomarker to predict AD treatment outcome in adolescents with MDD.

No significant relationships.