Major depressive disorder (MDD) is a prevalent and disabling condition. Approximately 30-50% of patients do not respond to first-line medication or psychotherapy. Therefore, several studies have investigated the predictive potential of pretreatment severity rating or neuroimaging features to guide clinical approaches that can speed optimal treatment selection.

To evaluate the performance of 1) severity ratings (scores of Hamilton Depression/Anxiety Scale, illness duration, and sleep quality, etc.) and demographic characteristic and 2) brain magnetic resonance imaging (MRI) features in predicting treatment outcomes for MDD. Second, to assess performance variations among varied modalities and interventions in MRI studies.

We searched studies in PubMed, Embase, Web of Science, and Science Direct databases before March 22, 2023. We extracted a confusion matrix for prediction in each study. Separate meta-analyses were performed for clinical and MRI studies. The logarithm of diagnostic odds ratio [log(DOR)], sensitivity, and specificity were conducted using Reitsma’s random effect model. The area under curve (AUC) of summary receiver operating characteristic (SROC) curve was calculated.

Subgroup analyses were conducted in MRI studies based on modalities: resting-state functional MRI (rsfMRI), task-based fMRI (tbfMRI), and structural MRI (sMRI), and interventions: antidepressant (including selective serotonin reuptake inhibitors [SSRI]) and electroconvulsive therapy (ECT). Meta-regression was conducted 1) between clinical and MRI studies and 2) among modality or intervention subgroups in MRI studies.

We included ten studies used clinical features covering 6494 patients, yielded a log(DOR) of 1.42, AUC of 0.71, sensitivity of 0.61, and specificity of 0.74. In terms of MRI, 44 studies with 2623 patients were included, revealing an overall log(DOR) of 2.53. The AUC, sensitivity, and specificity were 0.89, 0.78, and 0.75.

Studies using MRI features had a higher sensitivity (0.89 vs. 0.61) in predicting treatment outcomes than clinical features (P < 0.001). RsfMRI had higher specificity (0.79 vs. 0.69) than tbfMRI subgroup (P = 0.01). No significant differences were found between sMRI and other modalities, nor between antidepressants (SSRIs and others) and ECT. Antidepressant studies primarily identified predictive imaging features in limbic and default mode networks, while ECT mainly focused on limbic network.

Our findings suggest a robust promise for pretreatment brain MRI features in predicting treatment outcomes in MDD, offering higher accuracy than clinical studies. While tasks in tbfMRI studies differed, those studies overall had less predictive utility than rsfMRI data. For MRI studies, overlapping but distinct network level measures predicted outcomes for antidepressants and ECT.

None Declared

Obsessive-compulsive disorder (OCD) is a common psychiatric disorder. It is considered that dysregulation of cytokine levels is related to the pathophysiological mechanism of OCD. However, the results of previous studies on cytokine levels in OCD are inconsistent.

To perform a meta-analysis assessing cytokine levels in peripheral blood of OCD patients.

We searched in PubMed, Web of Science, and Embase from inception to March 31, 2023 for eligible studies. We conducted multivariate meta-analysis in combined proinflammatory cytokines (interleukin-6 [IL-6], IL-1β, IL-2, tumor necrosis factor-α [TNF-α], and interferon-γ [IFN-γ]) and combined anti-inflammatory cytokines (IL-10 and IL-4) respectively, and calculated the same meta-analysis in each cytokine. We also performed sensitivity analysis and publication bias tests, as well as subgroup analysis (i.e. different age groups, varied cytokine measurement methods, medication treated or naïve, and presence of psychiatric comorbidities) and meta-regression analysis (variables including patients’ sex ratio, age, age at symptom onset, illness duration, scores of Y-BOCS, family history of psychiatric disorders, and BMI).

17 original studies (13, 13, 10, 5, 4, 3, 2 studies for IL-6, TNF-α, IL-1β, IL-10, IL-2, IL-4, and IFN-γ, respectively), 573 patients (mean age, 25.2; 50.3% female) and 498 healthy controls (HC; mean age, 25.3; 51.4% female) were included. The results showed that the levels of combined pro- or anti-inflammatory cytokines and each signle cytokine were not significantly different between OCD patients and HC (all P>0.05), with significant heterogeneities in all analyses (I2 from 79.1% to 91.7%). We did not find between-group differences in cytokine levels in all subgroup analyses. Meta-regression analysis suggested that age at onset (P=0.0003) and family history (P=0.0062) might be the source of heterogeneity in TNF-α level. Sensitivity analysis confirmed that all results were stable, except for IL-4 where different cytokine measurement methods may be the contributing factor. Egger test did not find publication bias.

Our study showed no difference in cytokine levels between OCD patients and HC, but age at onset and family history may affect TNF-α level. Confounding factors such as age at onset, family history, and cytokine measurement methods should be controlled in future studies to further explore the immune mechanism of OCD.

None Declared

There’s large heterogeneity present in major depressive disorder (MDD) and controversial evidence on alterations of brain functional connectivity (FC), making it hard to elucidate the neurobiological basis of MDD. Subtyping is one promising solution to characterize this heterogeneity.

To identify neurophysiological subtypes of MDD based on FC derived from resting-state functional magnetic resonance imaging using large multisite data and investigate the differences in genetic mechanisms and neurotransmitter basis of FC alterations, and the differences of FC-related cognition between each subtype.

Consensus clustering of FC patterns was applied to a population of 829 MDD patients from REST-Meta-MDD database after data cleaning and image quality control. Gene transcriptomic data derived from Allen Human Brain Atlas and neurotransmitter receptor/transporter density data acquired by using neuromap toolbox were used to characterize the molecular mechanism underlying each FC-based subtype by identifying the gene set and neurotransmitters/transporters showing high spatial similarity with the profiles of FC alterations between each subtype and 770 healthy controls. The FC-related cognition in each subtype was also selected by lasso regression.

Two stable neurophysiological MDD subtypes were found and labeled as hypoconnectivity (n=527) and hyperconnectivity (n=299) characterized by the FC differences in each subtype relative to controls, respectively. The two subtypes did not differ in age, sex, and scores of Hamilton Depression/Anxiety Scale.

The genes related to FC alterations were enriched in ion transmembrane transport, synaptic transmission/organization, axon development, and regulation of neurotransmitter level for both subtypes, but specifically enriched in glial cell differentiation for hypoconnectivity subtype, while enriched in regulation of presynaptic membrane and regulation of neuron differentiation for hyperconnectivity subtype.

FC alterations were associated with the density of 5-HT2a receptor in both subtypes. For hyperconnectivity subtype, FC alterations were also correlated with the density of norepinephrine transporter, glutamate receptor, GABA receptor, 5-HT1b receptor, and cannabinoid receptor.

Both subtypes showed correlations between FC and categorization, motor inhibition, and localization. The FC in hypoconnectivity subtype correlated with response inhibition, selective attention, face recognition, sleep, empathy, expertise, uncertainty, and anticipation, while that was related to inference, speech perception, and reward anticipation in hyperconnectivity subtype.

Our findings suggested the presence of two neuroimaging subtypes of MDD characterized by hypo or hyper-connectivity. The two subtypes had both shared and distinct genetic mechanisms, neurotransmitter receptor/transporter profiles, and cognition types.

None Declared

Leveraging the National COVID-19 Cohort Collaborative (N3C), a nationally sampled electronic health records repository, we explored associations between individual-level social determinants of health (SDoH) and COVID-19-related hospitalizations among racialized minority people with human immunodeficiency virus (HIV) (PWH), who have been historically adversely affected by SDoH.

We retrospectively studied PWH and people without HIV (PWoH) using N3C data from January 2020 to November 2023. We evaluated SDoH variables across three domains in the Healthy People 2030 framework: (1) healthcare access, (2) economic stability, and (3) social cohesion with our primary outcome, COVID-19-related hospitalization. We conducted hierarchically nested additive and adjusted mixed-effects logistic regression models, stratifying by HIV status and race/ethnicity groups, accounting for age, sex, comorbidities, and data partners.

Our analytic sample included 280,441 individuals from 24 data partner sites, where 3,291 (1.17%) were PWH, with racialized minority PWH having higher proportions of adverse SDoH exposures than racialized minority PWoH. COVID-19-related hospitalizations occurred in 11.23% of all individuals (9.17% among PWH, 11.26% among PWoH). In our initial additive modeling, we observed that all three SDoH domains were significantly associated with hospitalizations, even with progressive adjustments (adjusted odds ratios [aOR] range 1.36–1.97). Subsequently, our HIV-stratified analyses indicated economic instability was associated with hospitalization in both PWH and PWoH (aOR range 1.35–1.48). Lastly, our fully adjusted, race/ethnicity-stratified analysis, indicated access to healthcare issues was associated with hospitalization across various racialized groups (aOR range 1.36–2.00).

Our study underscores the importance of assessing individual-level SDoH variables to unravel the complex interplay of these factors for racialized minority groups.

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.

The locus coeruleus (LC) innervates the cerebrovasculature and plays a crucial role in optimal regulation of cerebral blood flow. However, no human studies to date have examined links between these systems with widely available neuroimaging methods. We quantified associations between LC structural integrity and regional cortical perfusion and probed whether varying levels of plasma Alzheimer’s disease (AD) biomarkers (Aß42/40 ratio and ptau181) moderated these relationships.

64 dementia-free community-dwelling older adults (ages 55-87) recruited across two studies underwent structural and functional neuroimaging on the same MRI scanner. 3D-pCASL MRI measured regional cerebral blood flow in limbic and frontal cortical regions, while T1-FSE MRI quantified rostral LC-MRI contrast, a well-established proxy measure of LC structural integrity. A subset of participants underwent fasting blood draw to measure plasma AD biomarker concentrations (Aß42/40 ratio and ptau181). Multiple linear regression models examined associations between perfusion and LC integrity, with rostral LC-MRI contrast as predictor, regional CBF as outcome, and age and study as covariates. Moderation analyses included additional terms for plasma AD biomarker concentration and plasma x LC interaction.

Greater rostral LC-MRI contrast was linked to lower regional perfusion in limbic regions, such as the amygdala (ß = -0.25, p = 0.049) and entorhinal cortex (ß = -0.20, p = 0.042), but was linked to higher regional perfusion in frontal cortical regions, such as the lateral (ß = 0.28, p = 0.003) and medial (ß = 0.24, p = 0.05) orbitofrontal (OFC) cortices. Plasma amyloid levels moderated the relationship between rostral LC and amygdala CBF (Aß42/40 ratio x rostral LC interaction term ß = -0.31, p = 0.021), such that as plasma Aß42/40 ratio decreased (i.e., greater pathology), the strength of the negative relationship between rostral LC integrity and amygdala perfusion decreased. Plasma ptau181levels moderated the relationship between rostral LC and entorhinal CBF (ptau181 x rostral LC interaction term ß = 0.64, p = 0.001), such that as ptau181 increased (i.e., greater pathology), the strength of the negative relationship between rostral LC integrity and entorhinal perfusion decreased. For frontal cortical regions, ptau181 levels moderated the relationship between rostral LC and lateral OFC perfusion (ptau181 x rostral LC interaction term ß = -0.54, p = .004), as well as between rostral LC and medial OFC perfusion (ptau181 x rostral LC interaction term ß = -0.53, p = .005), such that as ptau181 increased (i.e., greater pathology), the strength of the positive relationship between rostral LC integrity and frontal perfusion decreased.

LC integrity is linked to regional cortical perfusion in non-demented older adults, and these relationships are moderated by plasma AD biomarker concentrations. Variable directionality of the associations between the LC and frontal versus limbic perfusion, as well as the differential moderating effects of plasma AD biomarkers, may signify a compensatory mechanism and a shifting pattern of hyperemia in the presence of aggregating AD pathology. Linking LC integrity and cerebrovascular regulation may represent an important understudied pathway of dementia risk and may help to bridge competing theories of dementia progression in preclinical AD studies.

Blood pressure variability (BPV), independent of traditionally targeted average blood pressure levels, is an emerging vascular risk factor for stroke, cerebrovascular disease, and dementia, possibly through links with vascular-endothelial injury. Recent evidence suggests visit-to-visit (e.g., over months, years) BPV is associated with cerebrovascular disease severity, but less is known about relationships with short-term (e.g., < 24 hours) fluctuations in blood pressure. Additionally, it is unclear how BPV may be related to angiogenic growth factors that play a role in cerebral arterial health.

We investigated relationships between short-term BPV, white matter hyperintensities on MRI, and levels of plasma vascular endothelial growth factor (VEGF) in a sample of community-dwelling older adults (n = 57, ages 55-88) without history of dementia or stroke. Blood pressure was collected continuously during a 5-minute resting period. BPV was calculated as variability independent of mean, a commonly used index of BPV uncorrelated with average blood pressure levels. Participants underwent T2-FLAIR MRI to determine severity of white matter lesion burden. Severity of lesions was classified as Fazekas scores (0-3). Participants also underwent venipuncture to determine levels of plasma VEGF. Ordinal logistic regression examined the association between BPV and Fazekas scores. Multiple linear regression explored relationships between BPV and VEGF. Models controlled for age, sex, and average blood pressure.

Elevated BPV was related to greater white matter lesion burden (i.e., Fazekas score) (systolic: OR = 1.17 [95% CI 1.01, 1.37]; p = .04; diastolic: OR = 2.47 [95% CI 1.09, 5.90]; p = .03) and increased levels of plasma VEGF (systolic: ß = .39 [95% CI .11, .67]; adjusted R2 = .16; p = .007; diastolic: ß = .48 [95% CI .18, .78]; adjusted R2 = .18; p = .003).

Findings suggest short-term BPV may be related to cerebrovascular disease burden and angiogenic growth factors relevant to cerebral arterial health, independent of average blood pressure. Understanding the role of BPV in cerebrovascular disease and vascular-endothelial health may help elucidate the increased risk for stroke and dementia associated with elevated BPV.