Cognitive, Disability, and Treatment Outcome Implications of Symptom-Based Phenotyping in Late-Life Depression.

OBJECTIVE: Late-life depression is associated with substantial heterogeneity in clinical presentation, disability, and response to antidepressant treatment. We examined whether self-report of severity of common symptoms, including anhedonia, apathy, rumination, worry, insomnia, and fatigue were associated with differences in presentation and response to treatment. We also examined whether these symptoms improved during treatment with escitalopram. DESIGN: Eighty-nine older adults completed baseline assessments, neuropsychological testing and providing self-reported symptom and disability scales. They then entered an 8-week, placebo-controlled randomized trial of escitalopram, and self-report scales were repeated at the trial's end. Raw symptom scale scores were combined into three standardized symptom phenotypes and models examined how symptom phenotype severity was associated with baseline measures and depression improvement over the trial. RESULTS: While rumination/worry appeared independent, severity of apathy/anhedonia and fatigue/insomnia were associated with one another and with greater self-reported disability. Greater fatigue/insomnia was also associated with slower processing speed, while rumination/worry was associated with poorer episodic memory. No symptom phenotype severity score predicted a poorer overall response to escitalopram. In secondary analyses, escitalopram did not improve most phenotypic symptoms more than placebo, aside for greater reductions in worry and total rumination severity. CONCLUSION: Deeper symptom phenotype characterization may highlight differences in the clinical presentation of late-life depression. However, when compared to placebo, escitalopram did not improve many of the symptoms assessed. Further work is needed to determine whether symptom phenotypes inform longer-term course of illness, and which treatments may best benefit specific symptoms.

Influences of resting-state intrinsic functional brain connectivity on the antidepressant treatment response in late-life depression.

BACKGROUND: Late-life depression (LLD) is characterized by differences in resting state functional connectivity within and between intrinsic functional networks. This study examined whether clinical improvement to antidepressant medications is associated with pre-randomization functional connectivity in intrinsic brain networks. METHODS: Participants were 95 elders aged 60 years or older with major depressive disorder. After clinical assessments and baseline MRI, participants were randomized to escitalopram or placebo with a two-to-one allocation for 8 weeks. Non-remitting participants subsequently entered an 8-week trial of open-label bupropion. The main clinical outcome was depression severity measured by MADRS. Resting state functional connectivity was measured between a priori key seeds in the default mode (DMN), cognitive control, and limbic networks. RESULTS: In primary analyses of blinded data, lower post-treatment MADRS score was associated with higher resting connectivity between: (a) posterior cingulate cortex (PCC) and left medial prefrontal cortex; (b) PCC and subgenual anterior cingulate cortex (ACC); (c) right medial PFC and subgenual ACC; (d) right orbitofrontal cortex and left hippocampus. Lower post-treatment MADRS was further associated with lower connectivity between: (e) the right orbitofrontal cortex and left amygdala; and (f) left dorsolateral PFC and left dorsal ACC. Secondary analyses associated mood improvement on escitalopram with anterior DMN hub connectivity. Exploratory analyses of the bupropion open-label trial associated improvement with subgenual ACC, frontal, and amygdala connectivity. CONCLUSIONS: Response to antidepressants in LLD is related to connectivity in the DMN, cognitive control and limbic networks. Future work should focus on clinical markers of network connectivity informing prognosis. REGISTRATION: ClinicalTrials.gov NCT02332291.

Cognitive phenotypes in late-life depression.

OBJECTIVE: To identify cognitive phenotypes in late-life depression (LLD) and describe relationships with sociodemographic and clinical characteristics. DESIGN: Observational cohort study. SETTING: Baseline data from participants recruited via clinical referrals and community advertisements who enrolled in two separate studies. PARTICIPANTS: Non-demented adults with LLD (n = 120; mean age = 66.73 ± 5.35 years) and non-depressed elders (n = 56; mean age = 67.95 ± 6.34 years). MEASUREMENTS: All completed a neuropsychological battery, and individual cognitive test scores were standardized across the entire sample without correcting for demographics. Five empirically derived cognitive domain composites were created, and cluster analytic approaches (hierarchical, k-means) were independently conducted to classify cognitive patterns in the depressed cohort only. Baseline sociodemographic and clinical characteristics were then compared across groups. RESULTS: A three-cluster solution best reflected the data, including "High Normal" (n = 47), "Reduced Normal" (n = 35), and "Low Executive Function" (n = 37) groups. The "High Normal" group was younger, more educated, predominantly Caucasian, and had fewer vascular risk factors and higher Mini-Mental Status Examination compared to "Low Executive Function" group. No differences were observed on other sociodemographic or clinical characteristics. Exploration of the "High Normal" group found two subgroups that only differed in attention/working memory performance and length of the current depressive episode. CONCLUSIONS: Three cognitive phenotypes in LLD were identified that slightly differed in sociodemographic and disease-specific variables, but not in the quality of specific symptoms reported. Future work on these cognitive phenotypes will examine relationships to treatment response, vulnerability to cognitive decline, and neuroimaging markers to help disentangle the heterogeneity seen in this patient population.

Structural MRI-Based Measures of Accelerated Brain Aging do not Moderate the Acute Antidepressant Response in Late-Life Depression.

OBJECTIVE: Late-life depression (LLD) is characterized by accelerated biological aging. Accelerated brain aging, estimated from structural magnetic resonance imaging (sMRI) data by a machine learning algorithm, is associated with LLD diagnosis, poorer cognitive performance, and disability. We hypothesized that accelerated brain aging moderates the antidepressant response. DESIGN AND INTERVENTIONS: Following MRI, participants entered an 8-week randomized, controlled trial of escitalopram. Nonremitting participants then entered an open-label 8-week trial of bupropion. PARTICIPANTS: Ninety-five individuals with LLD. MEASUREMENTS: A machine learning algorithm estimated each participant's brain age from sMRI data. This was used to calculate the brain-age gap (BAG), or how estimated age differed from chronological age. Secondary sMRI measures of aging pathology included white matter hyperintensity (WMH) volumes and hippocampal volumes. Mixed models examined the relationship between sMRI measures and change in depression severity. Initial analyses tested for a moderating effect of MRI measures on change in depression severity with escitalopram. Subsequent analyses tested for the effect of MRI measures on change in depression severity over time across trials. RESULTS: In the blinded initial phase, BAG was not significantly associated with a differential response to escitalopram over time. BAG was also not associated with a change in depression severity over time across both arms in the blinded phase or in the subsequent open-label bupropion phase. We similarly did not observe effects of WMH volume or hippocampal volume on change in depression severity over time. CONCLUSION: sMRI markers of accelerated brain aging were not associated with treatment response in this sequential antidepressant trial.

Relationship Between Ethical Attitudes and the Dark Triad: Differences Among College Majors.

This study examined the relationship between the Dark Triad (narcissism, Machiavellianism, and psychopathy), ethical attitudes, college major, and social desirability. Researchers investigated if business and psychology majors differed on the Dark Triad and ethical attitudes. In addition, social desirability was hypothesized to moderate the relationship between the Dark Triad and ethical attitudes. In total, 383 upper division business and psychology students from a large public university were surveyed online. Results showed a significant negative correlation between the Dark Triad and ethical attitudes. Business majors have significantly higher levels of psychopathy and lower levels of ethical attitudes compared to psychology majors, and social desirability moderates the relationship between psychopathy and ethical attitudes. Given the deleterious nature of the Dark Triad, and the negative impact of unethical behavior in the workplace, the findings underscore the need for future research that further examines differences between majors on these variables.

Differences in late adolescent psychopathology among youth with histories of co-occurring abuse and neglect experiences.

BACKGROUND: Knowledge about the impacts of child abuse and neglect (CAN) experiences on late adolescent psychopathology has been limited by a failure to consider the frequent co-occurrence of CAN types and potential unique impacts of specific combinations. OBJECTIVE: Using person-centered analyses, we aimed to identify unobserved groups of youth with similar patterns of lifetime CAN experiences before age 16 and differences in psychopathology symptom counts between groups two years later. PARTICIPANTS AND SETTING: Participants were 919 adolescent-caregiver dyads (56% female; 56% Black, 7% Latina/o, 13% mixed/other). METHODS: Prospective, multi-informant data, including child protective services records and caregiver and youth reports were collected, and youth completed a diagnostic interview at age 18. RESULTS: Latent Class Analyses classified adolescents into four distinct groups based on patterns of physical neglect, supervisory neglect, and physical, sexual, and psychological abuse: "Low-Risk" (37%), "Neglect" (19%), "Abuse" (11%), and "Multi-type CAN" (33%). The Multi-type CAN class had significantly more major depressive, generalized anxiety, and nicotine use symptoms than the Low-Risk class, and more post-traumatic stress, antisocial personality, and illicit substance use symptoms, than Low-Risk and Neglect classes. The Abuse class had significantly more generalized anxiety and attention deficit/hyperactivity symptoms than the Low-Risk class, and more major depressive, antisocial personality, and illicit substance use symptoms, than Low-Risk and Neglect classes. The Neglect class did not have elevated psychopathology symptoms. CONCLUSION: Findings highlight important differences in the associations between lifetime CAN experience patterns and psychopathology. Researchers should explore mechanisms underlying psychopathology that are impacted by different CAN experience patterns.

Examining the Factor Structure and Measurement Invariance of the Trauma Symptom Checklist for Children in a Diverse Sample of Trauma-Exposed Adolescents.

The Trauma Symptom Checklist for Children (TSCC) is a widely used youth assessment of broad, transdiagnostic symptomatology following trauma. However, its factor structure has not been thoroughly tested in diverse samples. Youth (N = 738) exposed to interpersonal violence, including physical and sexual abuse, completed the TSCC. Confirmatory factor analysis was used to test one-, six-, and eight-factor models of the TSCC clinical scales, based on previous literature and the TSCC manual. We examined measurement invariance across boys and girls and Black and non-Black participants, as well as convergent and discriminant validity. An eight-factor structure, consisting of posttraumatic stress, anxiety, depression, anger, overt dissociation, fantasy dissociation, sexual preoccupation, and sexual distress, demonstrated the best fit, with two items removed. Invariance tests supported configural and metric (but not scalar) invariance. This research highlights the need for further testing before differences between gender and racial groups can be accurately compared.

Preliminary Evidence That Cortical Amyloid Burden Predicts Poor Response to Antidepressant Medication Treatment in Cognitively Intact Individuals With Late-Life Depression.

OBJECTIVE: Amyloid accumulation, the pathological hallmark of Alzheimer's disease, may predispose some older adults to depression and cognitive decline. Deposition of amyloid also occurs prior to the development of cognitive decline. It is unclear whether amyloid influences antidepressant outcomes in cognitively intact depressed elders. DESIGN: A pharmacoimaging trial utilizing florbetapir (18F) PET scanning followed by 2 sequential 8-week antidepressant medication trials. PARTICIPANTS: Twenty-seven depressed elders who were cognitively intact on screening. MEASUREMENTS AND INTERVENTIONS: After screening, diagnostic testing, assessment of depression severity and neuropsychological assessment, participants completed florbetapir (18F) PET scanning. They were then randomized to receive escitalopram or placebo for 8 weeks in a double-blinded two-to-one allocation rate. Individuals who did not respond to initial treatment transitioned to a second open-label trial of bupropion for another 8 weeks. RESULTS: Compared with 22 amyloid-negative participants, 5 amyloid-positive participants exhibited significantly less change in depression severity and a lower likelihood of remission. In the initial blinded trial, 4 of 5 amyloid-positive participants were nonremitters (80%), while only 18% (4 of 22) of amyloid-negative participants did not remit (p = 0.017; Fisher's Exact test). In separate models adjusting for key covariates, both positive amyloid status (t = 3.07, 21 df, p = 0.003) and higher cortical amyloid binding by standard uptake value ratio (t = 2.62, 21 df, p = 0.010) were associated with less improvement in depression severity. Similar findings were observed when examining change in depression status across both antidepressant trials. CONCLUSIONS: In this preliminary study, amyloid status predicted poor antidepressant response to sequential antidepressant treatment. Alternative treatment approaches may be needed for amyloid-positive depressed elders.