The importance of social activity to risk of major depression in older adults.

BACKGROUND: Several social determinants of health (SDoH) have been associated with the onset of major depressive disorder (MDD). However, prior studies largely focused on individual SDoH and thus less is known about the relative importance (RI) of SDoH variables, especially in older adults. Given that risk factors for MDD may differ across the lifespan, we aimed to identify the SDoH that was most strongly related to newly diagnosed MDD in a cohort of older adults. METHODS: We used self-reported health-related survey data from 41 174 older adults (50-89 years, median age = 67 years) who participated in the Mayo Clinic Biobank, and linked ICD codes for MDD in the participants' electronic health records. Participants with a history of clinically documented or self-reported MDD prior to survey completion were excluded from analysis (N = 10 938, 27%). We used Cox proportional hazards models with a gradient boosting machine approach to quantify the RI of 30 pre-selected SDoH variables on the risk of future MDD diagnosis. RESULTS: Following biobank enrollment, 2073 older participants were diagnosed with MDD during the follow-up period (median duration = 6.7 years). The most influential SDoH was perceived level of social activity (RI = 0.17). Lower level of social activity was associated with a higher risk of MDD [hazard ratio = 2.27 (95% CI 2.00-2.50) for highest v. lowest level]. CONCLUSION: Across a range of SDoH variables, perceived level of social activity is most strongly related to MDD in older adults. Monitoring changes in the level of social activity may help identify older adults at an increased risk of MDD.

Alterations in resting-state functional activity and connectivity for major depressive disorder appetite and weight disturbance phenotypes.

BACKGROUND: Major depressive disorder (MDD) is often accompanied by changes in appetite and weight. Prior task-based functional magnetic resonance imaging (fMRI) findings suggest these MDD phenotypes are associated with altered reward and interoceptive processing. METHODS: Using resting-state fMRI data, we compared the fractional amplitude of low-frequency fluctuations (fALFF) and seed-based connectivity (SBC) among hyperphagic (n = 77), hypophagic (n = 66), and euphagic (n = 42) MDD groups and a healthy comparison group (n = 38). We examined fALFF and SBC in a mask restricted to reward [nucleus accumbens (NAcc), putamen, caudate, ventral pallidum, and orbitofrontal cortex (OFC)] and interoceptive (anterior insula and hypothalamus) regions and also performed exploratory whole-brain analyses. SBC analyses included as seeds the NAcc and also regions demonstrating group differences in fALFF (i.e. right lateral OFC and right anterior insula). All analyses used threshold-free cluster enhancement. RESULTS: Mask-restricted analyses revealed stronger fALFF in the right lateral OFC, and weaker fALFF in the right anterior insula, for hyperphagic MDD v. healthy comparison. We also found weaker SBC between the right lateral OFC and left anterior insula for hyperphagic MDD v. healthy comparison. Whole-brain analyses revealed weaker fALFF in the right anterior insula, and stronger SBC between the right lateral OFC and left precentral gyrus, for hyperphagic MDD v. healthy comparison. Findings were no longer significant after controlling for body mass index, which was higher for hyperphagic MDD. CONCLUSIONS: Our results suggest hyperphagic MDD may be associated with altered activity in and connectivity between interoceptive and reward regions.

The effects of the pandemic on mental health in persons with and without a psychiatric history.

BACKGROUND: Prospective studies are needed to assess the influence of pre-pandemic risk factors on mental health outcomes following the COVID-19 pandemic. From direct interviews prior to (T1), and then in the same individuals after the pandemic onset (T2), we assessed the influence of personal psychiatric history on changes in symptoms and wellbeing. METHODS: Two hundred and four (19-69 years/117 female) individuals from a multigenerational family study were followed clinically up to T1. Psychiatric symptom changes (T1-to-T2), their association with lifetime psychiatric history (no, only-past, and recent psychiatric history), and pandemic-specific worries were investigated. RESULTS: At T2 relative to T1, participants with recent psychopathology (in the last 2 years) had significantly fewer depressive (mean, M = 41.7 v. 47.6) and traumatic symptoms (M = 6.6 v. 8.1, p < 0.001), while those with no and only-past psychiatric history had decreased wellbeing (M = 22.6 v. 25.0, p < 0.01). Three pandemic-related worry factors were identified: Illness/death, Financial, and Social isolation. Individuals with recent psychiatric history had greater Illness/death and Financial worries than the no/only-past groups, but these worries were unrelated to depression at T2. Among individuals with no/only-past history, Illness/death worries predicted increased T2 depression [B = 0.6(0.3), p < 0.05]. CONCLUSIONS: As recent psychiatric history was not associated with increased depression or anxiety during the pandemic, new groups of previously unaffected persons might contribute to the increased pandemic-related depression and anxiety rates reported. These individuals likely represent incident cases that are first detected in primary care and other non-specialty clinical settings. Such settings may be useful for monitoring future illness among newly at-risk individuals.

The genetic contribution to the comorbidity of depression and anxiety: a multi-site electronic health records study of almost 178 000 people.

BACKGROUND: Depression and anxiety are common and highly comorbid, and their comorbidity is associated with poorer outcomes posing clinical and public health concerns. We evaluated the polygenic contribution to comorbid depression and anxiety, and to each in isolation. METHODS: Diagnostic codes were extracted from electronic health records for four biobanks [N = 177 865 including 138 632 European (77.9%), 25 612 African (14.4%), and 13 621 Hispanic (7.7%) ancestry participants]. The outcome was a four-level variable representing the depression/anxiety diagnosis group: neither, depression-only, anxiety-only, and comorbid. Multinomial regression was used to test for association of depression and anxiety polygenic risk scores (PRSs) with the outcome while adjusting for principal components of ancestry. RESULTS: In total, 132 960 patients had neither diagnosis (74.8%), 16 092 depression-only (9.0%), 13 098 anxiety-only (7.4%), and 16 584 comorbid (9.3%). In the European meta-analysis across biobanks, both PRSs were higher in each diagnosis group compared to controls. Notably, depression-PRS (OR 1.20 per s.d. increase in PRS; 95% CI 1.18-1.23) and anxiety-PRS (OR 1.07; 95% CI 1.05-1.09) had the largest effect when the comorbid group was compared with controls. Furthermore, the depression-PRS was significantly higher in the comorbid group than the depression-only group (OR 1.09; 95% CI 1.06-1.12) and the anxiety-only group (OR 1.15; 95% CI 1.11-1.19) and was significantly higher in the depression-only group than the anxiety-only group (OR 1.06; 95% CI 1.02-1.09), showing a genetic risk gradient across the conditions and the comorbidity. CONCLUSIONS: This study suggests that depression and anxiety have partially independent genetic liabilities and the genetic vulnerabilities to depression and anxiety make distinct contributions to comorbid depression and anxiety.

Inhibition Predicts the Course of Depression and Anxiety Symptoms Among Adolescents: The Moderating Role of Familial Risk.

ABSTRACT: Numerous theoretical models suggest that inhibition difficulties-the inability to moderate automatic responses-contribute to the onset and/or maintenance of internalizing symptoms. Inhibition deficits and internalizing disorders run in families and share overlapping genetic risk factors, suggesting that inhibition deficits may be particularly prognostic of internalizing symptoms in those with high familial risk. This study tested this hypothesis in a longitudinal sample during the transition from adolescence to early adulthood. As hypothesized, prospective associations between inhibition and anxiety and depressive symptoms 8 years later were moderated by familial risk for depression. Specifically, poorer inhibition prospectively predicted greater anxiety and depressive symptoms in those at high (but not low) familial risk for major depressive disorder. These findings provide preliminary support for impaired inhibition as an indicator of risk for later internalizing symptoms in those at high familial risk.

Structural brain measures linked to clinical phenotypes in major depression replicate across clinical centres.

Abnormalities in brain structural measures, such as cortical thickness and subcortical volumes, are observed in patients with major depressive disorder (MDD) who also often show heterogeneous clinical features. This study seeks to identify the multivariate associations between structural phenotypes and specific clinical symptoms, a novel area of investigation. T1-weighted magnetic resonance imaging measures were obtained using 3 T scanners for 178 unmedicated depressed patients at four academic medical centres. Cortical thickness and subcortical volumes were determined for the depressed patients and patients' clinical presentation was characterized by 213 item-level clinical measures, which were grouped into several large, homogeneous categories by K-means clustering. The multivariate correlations between structural and cluster-level clinical-feature measures were examined using canonical correlation analysis (CCA) and confirmed with both 5-fold and leave-one-site-out cross-validation. Four broad types of clinical measures were detected based on clustering: an anxious misery composite (composed of item-level depression, anxiety, anhedonia, neuroticism and suicidality scores); positive personality traits (extraversion, openness, agreeableness and conscientiousness); reported history of physical/emotional trauma; and a reported history of sexual abuse. Responses on the item-level anxious misery measures were negatively associated with cortical thickness/subcortical volumes in the limbic system and frontal lobe; reported childhood history of physical/emotional trauma and sexual abuse measures were negatively correlated with entorhinal thickness and left hippocampal volume, respectively. In contrast, the positive traits measures were positively associated with hippocampal and amygdala volumes and cortical thickness of the highly-connected precuneus and cingulate cortex. Our findings suggest that structural brain measures may reflect neurobiological mechanisms underlying MDD features.

Childhood trauma history is linked to abnormal brain connectivity in major depression.

Patients with major depressive disorder (MDD) present with heterogeneous symptom profiles, while neurobiological mechanisms are still largely unknown. Brain network studies consistently report disruptions of resting-state networks (RSNs) in patients with MDD, including hypoconnectivity in the frontoparietal network (FPN), hyperconnectivity in the default mode network (DMN), and increased connection between the DMN and FPN. Using a large, multisite fMRI dataset (n = 189 patients with MDD, n = 39 controls), we investigated network connectivity differences within and between RSNs in patients with MDD and healthy controls. We found that MDD could be characterized by a network model with the following abnormalities relative to controls: (i) lower within-network connectivity in three task-positive RSNs [FPN, dorsal attention network (DAN), and cingulo-opercular network (CON)], (ii) higher within-network connectivity in two intrinsic networks [DMN and salience network (SAN)], and (iii) higher within-network connectivity in two sensory networks [sensorimotor network (SMN) and visual network (VIS)]. Furthermore, we found significant alterations in connectivity between a number of these networks. Among patients with MDD, a history of childhood trauma and current symptoms quantified by clinical assessments were associated with a multivariate pattern of seven different within- and between-network connectivities involving the DAN, FPN, CON, subcortical regions, ventral attention network (VAN), auditory network (AUD), VIS, and SMN. Overall, our study showed that traumatic childhood experiences and dimensional symptoms are linked to abnormal network architecture in MDD. Our results suggest that RSN connectivity may explain underlying neurobiological mechanisms of MDD symptoms and has the potential to serve as an effective diagnostic biomarker.

Intra-session test-retest reliability of functional connectivity in infants.

Resting functional MRI studies of the infant brain are increasingly becoming an important tool in developmental neuroscience. Whereas the test-retest reliability of functional connectivity (FC) measures derived from resting fMRI data have been characterized in the adult and child brain, similar assessments have not been conducted in infants. In this study, we examined the intra-session test-retest reliability of FC measures from 119 infant brain MRI scans from four neurodevelopmental studies. We investigated edge-level and subject-level reliability within one MRI session (between and within runs) measured by the Intraclass correlation coefficient (ICC). First, using an atlas-based approach, we examined whole-brain connectivity as well as connectivity within two common resting fMRI networks - the default mode network (DMN) and the sensorimotor network (SMN). Second, we examined the influence of run duration, study site, and scanning manufacturer (e.g., Philips and General Electric) on ICCs. Lastly, we tested spatial similarity using the Jaccard Index from networks derived from independent component analysis (ICA). Consistent with resting fMRI studies from adults, our findings indicated poor edge-level reliability (ICC = 0.14-0.18), but moderate-to-good subject-level intra-session reliability for whole-brain, DMN, and SMN connectivity (ICC = 0.40-0.78). We also found significant effects of run duration, site, and scanning manufacturer on reliability estimates. Some ICA-derived networks showed strong spatial reproducibility (e.g., DMN, SMN, and Visual Network), and were labelled based on their spatial similarity to analogous networks measured in adults. These networks were reproducibly found across different study sites. However, other ICA-networks (e.g. Executive Control Network) did not show strong spatial reproducibility, suggesting that the reliability and/or maturational course of functional connectivity may vary by network. In sum, our findings suggest that developmental scientists may be on safe ground examining the functional organization of some major neural networks (e.g. DMN and SMN), but judicious interpretation of functional connectivity is essential to its ongoing success.

Major depression, temperament, and social support as psychosocial mechanisms of the intergenerational transmission of parenting styles.

In this three-generation longitudinal study of familial depression, we investigated the continuity of parenting styles, and major depressive disorder (MDD), temperament, and social support during childrearing as potential mechanisms. Each generation independently completed the Parental Bonding Instrument (PBI), measuring individuals' experiences of care and overprotection received from parents during childhood. MDD was assessed prospectively, up to 38 years, using the semi-structured Schedule for Affective Disorders and Schizophrenia (SADS). Social support and temperament were assessed using the Social Adjustment Scale - Self-Report (SAS-SR) and Dimensions of Temperament Scales - Revised, respectively. We first assessed transmission of parenting styles in the generation 1 to generation 2 cycle (G1→G2), including 133 G1 and their 229 G2 children (367 pairs), and found continuity of both care and overprotection. G1 MDD accounted for the association between G1→G2 experiences of care, and G1 social support and temperament moderated the transmission of overprotection. The findings were largely similar when examining these psychosocial mechanisms in 111 G2 and their spouses (G2+S) and their 136 children (G3) (a total of 223 pairs). Finally, in a subsample of families with three successive generations (G1→G2→G3), G2 experiences of overprotection accounted for the association between G1→G3 experiences of overprotection. The results of this study highlight the roles of MDD, temperament, and social support in the intergenerational continuity of parenting, which should be considered in interventions to "break the cycle" of poor parenting practices across generations.

Allele-specific expression reveals interactions between genetic variation and environment.

Identifying interactions between genetics and the environment (GxE) remains challenging. We have developed EAGLE, a hierarchical Bayesian model for identifying GxE interactions based on associations between environmental variables and allele-specific expression. Combining whole-blood RNA-seq with extensive environmental annotations collected from 922 human individuals, we identified 35 GxE interactions, compared with only four using standard GxE interaction testing. EAGLE provides new opportunities for researchers to identify GxE interactions using functional genomic data.

Trajectories of childhood anxiety disorders in two generations at high risk.

BACKGROUND: The course of anxiety disorders during childhood is heterogeneous. In two generations at high or low risk, we described the course of childhood anxiety disorders and evaluated whether parent or grandparent major depressive disorder (MDD) predicted a persistent anxiety course. METHODS: We utilized a multigenerational study (1982-2015), following children (second generation, G2) and grandchildren (third generation, G3) of generation 1 (G1) with either moderate/severe MDD or no psychiatric illness. Psychiatric diagnoses were based on diagnostic interviews. Using group-based trajectory models, we identified clusters of children with similar anxiety disorder trajectories (age 0-17). RESULTS: We identified three primary trajectories in G2 (N = 275) and G3 (N = 118) cohorts: "no/low anxiety disorder" during childhood (G2 = 66%; G3 = 53%), "nonpersistent" with anxiety during part of childhood (G2 = 16%; G3 = 21%), and "persistent" (G2 = 18%; G3 = 25%). Childhood mood disorders and substance use disorders tended to be more prevalent in children in the persistent anxiety trajectory. In G2 children, parent MDD was associated with an increased likelihood of being in the persistent (84%) or nonpersistent trajectory (82%) versus no/low anxiety trajectory (62%). In G3 children, grandparent MDD, but not parent, was associated with an increased likelihood of being in the persistent (83%) versus nonpersistent (48%) and no/low anxiety (51%) trajectories. CONCLUSION: Anxiety trajectories move beyond what is captured under binary, single time-point measures. Parent or grandparent history of moderate/severe MDD may offer value in predicting child anxiety disorder course, which could help clinicians and caregivers identify children needing increased attention and screening for other psychiatric conditions.

Interpersonal Psychotherapy: History and Future.

This review details the history of the development of interpersonal psychotherapy (IPT), beginning at Yale University when Dr. Gerald Klerman led a maintenance study of the treatment of depression. The trial aimed to mimic clinical practice and, therefore, included psychotherapy. This review describes the first IPT clinical trial, subsequent trials, and numerous IPT adaptations for different age groups, formats (group, telephone, computer), disorders, and educational levels of mental health trainees. As of 2017, at least 133 clinical trials of IPT had been carried out worldwide. This review also describes challenges associated with training clinicians to deliver evidence-based psychotherapy. It concludes with a discussion of future directions for IPT, which include expanding training to community health workers and testing IPT in low- and middle-income countries.

Impact of the X Chromosome and sex on regulatory variation.

The X Chromosome, with its unique mode of inheritance, contributes to differences between the sexes at a molecular level, including sex-specific gene expression and sex-specific impact of genetic variation. Improving our understanding of these differences offers to elucidate the molecular mechanisms underlying sex-specific traits and diseases. However, to date, most studies have either ignored the X Chromosome or had insufficient power to test for the sex-specific impact of genetic variation. By analyzing whole blood transcriptomes of 922 individuals, we have conducted the first large-scale, genome-wide analysis of the impact of both sex and genetic variation on patterns of gene expression, including comparison between the X Chromosome and autosomes. We identified a depletion of expression quantitative trait loci (eQTL) on the X Chromosome, especially among genes under high selective constraint. In contrast, we discovered an enrichment of sex-specific regulatory variants on the X Chromosome. To resolve the molecular mechanisms underlying such effects, we generated chromatin accessibility data through ATAC-sequencing to connect sex-specific chromatin accessibility to sex-specific patterns of expression and regulatory variation. As sex-specific regulatory variants discovered in our study can inform sex differences in heritable disease prevalence, we integrated our data with genome-wide association study data for multiple immune traits identifying several traits with significant sex biases in genetic susceptibilities. Together, our study provides genome-wide insight into how genetic variation, the X Chromosome, and sex shape human gene regulation and disease.

Multidimensional understanding of religiosity/spirituality: relationship to major depression and familial risk.

BACKGROUND: Previous research has shown prospectively that religiosity/spirituality protects against depression, but these findings are commonly critiqued on two grounds, namely: (1) apparent religiosity/spirituality reflects merely an original absence of depression or elevated mood and (2) religiosity/spirituality too often is measured as a global construct. The current study investigates the relationship between depression and religiosity/spirituality by examining its multidimensional structural integrity. METHOD: Confirmatory factor analyses with a previously observed cross-cultural factor structure of religiosity/spirituality variables were conducted on an independent sample, diagnostic and familial risk subgroups from this sample, and a subsample of the original cross-cultural sample. Linear regressions onto a previous diagnosis of major depressive disorder (MDD) 5 years prior to assess the potential attenuating impact of a previous depression was explored. RESULTS: Across familial risk groups and clinical subgroups, each of the previously validated religiosity/spirituality domains was confirmed, namely: religious/spiritual commitment, contemplative practice, sense of interconnectedness, the experience of love, and altruistic engagement. Previous MDD diagnosis was associated with a lower religious/spiritual commitment among high-risk individuals, higher contemplation among low-risk individuals, and lower importance of religion or spirituality regardless of risk group. CONCLUSIONS: Structural integrity was found across familial risk groups and diagnostic history for a multidimensional structure of religiosity/spirituality. Differential associations between a previous diagnosis of MDD and level of religiosity/spirituality across domains suggest a complex and interactive relation between depression, familial risk, and religiosity/spirituality. Accounting for an empirically valid, multidimensional understanding of religiosity/spirituality may advance research on mechanisms underlying the relationship between religiosity/spirituality and mental health.

Commentary: Studies of prenatal antidepressant exposures: what can you recommend? A reflection on Sujan et al. (2019).

The review by Sujan et al. asks a question of clinical and public health importance: are antidepressant medications safe to use during pregnancy from the perspective of their potential effects on the infant and growing child? They provide a thorough review of the animal and human literature to date, focusing primarily on offspring neurodevelopmental outcomes (autism spectrum disorder, ASD, and attention deficit hyperactivity disorder, ADHD). They conclude, based on their review, that antidepressant exposure in pregnancy does not substantially increase the risk of these outcomes, and that women should therefore be reassured about the safety of these medications when used in pregnancy. While their review should be of interest to clinicians and researchers, we would advocate a more conservative approach. Even if associations with ASD and ADHD are equivocal, there is still evidence that SSRI exposure may be associated with outcomes occurring at other developmental timepoints. Clinical recommendations should be based on a fuller picture of potential risks and benefits to both the mother and the fetus, in the context of the mother's underlying depression. In this commentary, we also suggest some approaches that future observational studies may adopt to help strengthen the interpretability of findings.

Harmonization of cortical thickness measurements across scanners and sites.

With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as "scanner effects", can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements across a total of 11 scanners. We propose a set of tools for visualizing and identifying scanner effects that are generalizable to other modalities. We then propose to use ComBat, a technique adopted from the genomics literature and recently applied to diffusion tensor imaging data, to combine and harmonize cortical thickness values across scanners. We show that ComBat removes unwanted sources of scan variability while simultaneously increasing the power and reproducibility of subsequent statistical analyses. We also show that ComBat is useful for combining imaging data with the goal of studying life-span trajectories in the brain.

Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder.

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.

Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data.

Acquiring resting-state functional magnetic resonance imaging (fMRI) datasets at multiple MRI scanners and clinical sites can improve statistical power and generalizability of results. However, multi-site neuroimaging studies have reported considerable nonbiological variability in fMRI measurements due to different scanner manufacturers and acquisition protocols. These undesirable sources of variability may limit power to detect effects of interest and may even result in erroneous findings. Until now, there has not been an approach that removes unwanted site effects. In this study, using a relatively large multi-site (4 sites) fMRI dataset, we investigated the impact of site effects on functional connectivity and network measures estimated by widely used connectivity metrics and brain parcellations. The protocols and image acquisition of the dataset used in this study had been homogenized using identical MRI phantom acquisitions from each of the neuroimaging sites; however, intersite acquisition effects were not completely eliminated. Indeed, in this study, we found that the magnitude of site effects depended on the choice of connectivity metric and brain atlas. Therefore, to further remove site effects, we applied ComBat, a harmonization technique previously shown to eliminate site effects in multi-site diffusion tensor imaging (DTI) and cortical thickness studies. In the current work, ComBat successfully removed site effects identified in connectivity and network measures and increased the power to detect age associations when using optimal combinations of connectivity metrics and brain atlases. Our proposed ComBat harmonization approach for fMRI-derived connectivity measures facilitates reliable and efficient analysis of retrospective and prospective multi-site fMRI neuroimaging studies.