Depression Cohort Research Articles

BRAIN AGE ESTIMATION IN LATE-LIFE DEPRESSION: ASSOCIATION WITH COGNITIVE PERFORMANCE AND DISABILITY

Introduction Mental health disorders are associated with several biological markers of accelerated aging. Recent advances in machine learning can provide an estimation of brain age that may differ from actual, chronological age in the setting of neuropsychiatric disease and accelerated aging. We examined whether depressed elders exhibited a calculated brain age that was older than expected when compared with chronological age, and if so whether that difference was related to cognitive performance and disability Methods 154 elders (118 depressed, 36 never-depressed) enrolled in three studies with common entry criteria, undergoing structural brain MRI, a cognitive battery assessing episodic memory, executive function, processing speed, and working memory, and assessment of disability using the WHODAS 2.0. A machine-learning model estimated brain age based on MRI data, which was compared to chronological age to yield a brain-age gap (BAG). (BAG; relative difference between calculated age and chronological age). Analyses examined whether BAG was greater in depressed elders and whether it was associated with cognitive performance and disability. We also examined the depressed cohort alone to test for interactive effects between BAG and depression severity on function. Results After adjustment for covariates, late-life depression was associated with a higher brain-age gap (Wald χ2=8.84, p=0.0029), or a calculated age greater than chronological age. Across all subjects, a higher brain-age gap was associated with poorer episodic memory performance (Wald χ2=4.10, p=0.0430). Among depressed adults, higher BAG was associated with slower processing speed (Wald χ2=4.43, p=0.0354.) We also observed an interaction between BAG and depression severity, where increasing depression severity in context of higher BAG resulted in poorer performance in domains of executive function (Wald χ2=5.89, p=0.0152) and working memory (Wald χ2=4.47, p=0.0346.) Across all subjects, a higher BAG was also associated with greater disability (Wald χ2=6.00, p=0.0143). Conclusions Late-life depression is associated with a higher BAG, indicating brains appear older than expected by chronological age alone. Higher BAGs have cognitive and functional implications and may moderate the effect of depression severity on cognitive performance. This research was funded by: NIH grants R01MH102246, R21MH099218

Defining major depressive disorder cohorts using the EHR: Multiple phenotypes based on ICD-9 codes and medication orders

BackgroundMajor Depressive Disorder (MDD) is one of the most common mental illnesses and a leading cause of disability worldwide. Electronic Health Records (EHR) allow researchers to conduct unprecedented large-scale observational studies investigating MDD, its disease development and its interaction with other health outcomes. While there exist methods to classify patients as clear cases or controls, given specific data requirements, there are presently no simple, generalizable, and validated methods to classify an entire patient population into varying groups of depression likelihood and severity. MethodsWe have tested a simple, pragmatic electronic phenotype algorithm that classifies patients into one of five mutually exclusive, ordinal groups, varying in depression phenotype. Using data from an integrated health system on 278,026 patients from a 10-year study period we have tested the convergent validity of these constructs using measures of external validation, including patterns of psychiatric prescriptions, symptom severity, indicators of suicidality, comorbidity, mortality, health care utilization, and polygenic risk scores for MDD. ResultsWe found consistent patterns of increasing morbidity and/or adverse outcomes across the five groups, providing evidence for convergent validity. LimitationsThe study population is from a single rural integrated health system which is predominantly white, possibly limiting its generalizability. ConclusionOur study provides initial evidence that a simple algorithm, generalizable to most EHR data sets, provides categories with meaningful face and convergent validity that can be used for stratification of an entire patient population.

Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes

Insulin-resistance (IR) is one of the most important precursors of type 2 diabetes (T2D). Recent evidence suggests an association of depression with the onset of T2D. Accumulating evidence shows that depression and T2D share common biological origins, and DNA methylation examination might reveal the link between lifestyle, disease risk, and potential therapeutic targets for T2D. Here we hypothesize that integrative mining of IR and depression cohort data will facilitate predictive biomarkers identification for T2D. We utilized a newly proposed method to extract gene-level information from probe level data on genome-wide DNA methylation array. We identified a set of genes associated with IR and depression in clinical cohorts. By overlapping the IR-related nutraceutical-gene network with depression networks, we identified a common subnetwork centered with Vitamin D Receptor (VDR) gene. Preliminary clinical validation of gene methylation set in a small cohort of T2D patients and controls was established using the Sequenome matrix-assisted laser desorption ionization-time flight mass spectrometry. A set of sites in the promoter regions of VDR showed a significant difference between T2D patients and controls. Using a logistic regression model, the optimal prediction performance of these sites was AUC = 0.902，and an odds ratio = 19.76. Thus, monitoring the methylation status of specific VDR promoter region might help stratify the high-risk individuals who could potentially benefit from vitamin D dietary supplementation. Our results highlight the link between IR and depression, and the DNA methylation analysis might facilitate the search for their shared mechanisms in the etiology of T2D.

Bi-directional association between depression and HF: An electronic health records-based cohort study.

Objective:To determine whether a bi-directional relationship exists between depression and HF within a single population of individuals receiving primary care services, using longitudinal electronic health records (EHRs).Methods:This retrospective cohort study utilized EHRs for adults who received primary care services within a large healthcare system in 2006. Validated EHR-based algorithms identified 10,649 people with depression (depression cohort) and 5,911 people with HF (HF cohort) between January 1, 2006 and December 31, 2018. Each person with depression or HF was matched 1:1 with an unaffected referent on age, sex, and outpatient service use. Each cohort (with their matched referents) was followed up electronically to identify newly diagnosed HF (in the depression cohort) and depression (in the HF cohort) that occurred after the index diagnosis of depression or HF, respectively. The risks of these outcomes were compared (vs. referents) using marginal Cox proportional hazard models adjusted for 16 comorbid chronic conditions.Results:2,024 occurrences of newly diagnosed HF were observed in the depression cohort and 944 occurrences of newly diagnosed depression were observed in the HF cohort over approximately 4–6 years of follow-up. People with depression had significantly increased risk for developing newly diagnosed HF (HR 2.08, 95% CI 1.89–2.28) and people with HF had a significantly increased risk of newly diagnosed depression (HR 1.34, 95% CI 1.17–1.54) after adjusting for all 16 comorbid chronic conditions.Conclusion:These results provide evidence of a bi-directional relationship between depression and HF independently of age, sex, and multimorbidity from chronic illnesses.

Economic Burden of Depression and Associated Resource Use in Manitoba, Canada.

To characterize the health-care utilization and economic burden associated with depression in Manitoba, Canada. Patient-level data were retrieved from the Manitoba Centre for Health Policy administrative, clinical, and laboratory databases for the study period of January 1, 1996, through December 31, 2016. Patients were assigned to the depression cohort based on diagnoses recorded in hospitalizations and outpatient physician claims, as well as antidepressant prescription drug claims. A comparison cohort of nondepressed subjects, matched with replacement for age, gender, place of residence (urban vs. rural), and index date, was created. Demographics, comorbidities, intentional self-harm, mortality, health-care utilization, prescription drug utilization, and costs of health-care utilization and social services were compared between depressed patients and matched nondepressed patients, and incidence rate ratios and hazard ratios were reported. There were 190,065 patients in the depression cohort and 378,177 patients in the nondepression cohort. Comorbidities were 43% more prevalent among depressed patients. Intentional self-harm, all-cause mortality, and suicide mortality were higher among patients with depression than the nondepression cohort. Health-care utilization-including hospitalizations, physician visits, physician-provided psychotherapy, and prescription drugs-was higher in the depression than the nondepression cohort. Mean health-care utilization costs were 3.5 times higher among depressed patients than nondepressed patients ($10,064 and $2,832, respectively). Similarly, mean social services costs were 3 times higher ($1,522 and $510, respectively). Overall, depression adds a total average cost of $8,244 (SD = $40,542) per person per year. Depression contributes significantly to health burden and per patient costs in Manitoba, Canada. Extrapolation of the results to the entire Canadian health-care system projects an excess of $12 billion annually in health system spending.

Depression increases the risk of rotator cuff tear and rotator cuff repair surgery: A nationwide population-based study.

BackgroundChronic inflammation is known to be associated with both rotator cuff tears (RCTs) and depression. However, no epidemiological studies with a longitudinal follow-up have been performed to prove this association. We aimed to investigate whether depressed patients had an elevated risk of RCT and subsequent repair surgery compared with those without depression.MethodsThis retrospective cohort study comprised of patients diagnosed with depression between 2000 and 2010 (depression cohort) and patients without depression (non-depression cohort, 1:2 age and sex matched). The risk of RCT and rotator cuff repair surgery were determined during a 13-year follow-up (2000–2013) between these two cohorts.ResultsThis study included 26,868 patients with depression and 53,736 patients without depression. The incidence of RCT was 648 and 438 per 100,000 person-years in the depression and non-depression cohorts, respectively. The adjusted hazard ratio (HR) was 1.46 (95% confidence interval [CI], 1.36–1.57) for depressed patients. The incidence of rotator cuff repair surgery was 28 and 18 per 100,000 person-years in the depression and non-depression cohorts, respectively. Depressed patients also had a significantly increased risk of subsequent rotator cuff repair surgery (adjusted HR = 1.46; 95% CI, 1.04–2.06).ConclusionThe present study showed that depression was associated with an increased risk of rotator cuff tear and rotator cuff repair surgery.

Illness perceptions in difficult-to-treat asthma compared with a depressed psychosis cohort

Illness perceptions in difficult-to-treat asthma compared with a depressed psychosis cohort

Differences in Incidence and Risks of Suicide Attempt and Suicidal Drug Overdose between Patients with Epilepsy with and without Comorbid Depression.

Objective: To determine the differences in the incidences and risks of suicide attempt (SA) and suicidal drug overdose (SDO) between patients with epilepsy with and without comorbid depression by using data from Taiwan’s National Health Insurance Research Database. Methods: We analyzed data of patients (≥20 years) who had received epilepsy diagnoses between 2000 and 2012; the diagnosis date of epilepsy was defined as the index date. The epilepsy patients were divided into the cohorts, with and without comorbid depression, and compared against a cohort from the non-affected population. We calculated adjusted hazard ratios and the corresponding 95% confidence intervals for SA and SDO in the three cohorts after adjustment for age, sex, and comorbidities. Results: The incidences of SA and SDO in the cohort with epilepsy and depression were 42.9 and 97.4 per 10,000 person-years, respectively. The epilepsy with depression cohort had 21.3 times of SA risk; and 22.9 times of SDO risk than did the comparison cohort had a 6.03-fold increased risk of SA and a 2.56-fold increased risk of SDO than did the epilepsy patients without depression. Moreover, patients’ age <65 years, and female sex would further increase the risk of SA in patients with epilepsy and comorbid depression. Conclusion: Risks of SA and SDO in patients with epilepsy are proportionally increased when depression is coexisted. Our findings provide crucial information for clinicians and the government for suicide prevention and to question whether prescribing a large number of medications to patients with epilepsy and depression is safe.

The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls

BackgroundMood disorders (including major depressive disorder and bipolar disorder) affect 10% to 20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction. MethodsTo clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424). ResultsSeventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment—the relationship is positive in bipolar disorder but negative in major depressive disorder. ConclusionsThe mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.

Prevalence of Metabolic Syndrome and Associated Factors in a Cohort of Individuals With Treatment-Resistant Depression: Results From the FACE-DR Study.

The aim of this study was to estimate the prevalence of metabolic syndrome (MetS) and its components in a cohort of French patients with treatment-resistant depression (TRD) and to determine correlations with sociodemographic, clinical, and treatment-related factors. From 2012 to 2018, 205 patients who met DSM-IV criteria for major depressive episode with moderate-to-severe symptoms (Montgomery-Asberg Depression Rating Scale score ≥ 20), and at least Stage II resistance according to Thase and Rush criteria were enrolled in the FondaMental Advanced Centers of Expertise in Resistant Depression (FACE-DR) cohort. Data on sociodemographic and clinical characteristics, lifestyle information, and treatment and comorbidities were collected, and a blood sample was drawn. MetS was defined according to the criteria of the International Diabetes Federation. Overall, 38% of individuals with TRD met criteria for MetS. The frequency of MetS was significantly higher in men than in women only for patients aged 40 years or older (46.3% vs 35.2%, P = .0427). Moreover, whereas the management for diabetes was good, less than one-third of the patients with high blood pressure or dyslipidemia were treated for these conditions. Multivariate analysis showed that individuals with abnormal plasma c-reactive protein levels had a 3-fold increased risk (95% CI, 1.5-5.2) of having MetS, independent of other potential confounders. The prevalence of MetS is higher in patients with TRD than in those with other psychiatric disorders and characterized by a considerable undertreatment of some components of MetS in this population. Diagnosis and treatment of the components of MetS should be systematically performed to prevent the occurrence of cardiovascular diseases in patients with TRD. These findings highlight the need for integrated care, with more interaction and coordination between psychiatrists and primary care providers.

Depressive symptoms and the development and progression of physical multimorbidity in a national cohort of Australian women.

Multiple chronic physical conditions (physical multimorbidity) are common in people with depression. This study investigated the association between elevated depressive symptoms and the development and progression of physical multimorbidity in middle-aged women. A total of 7,407 women aged 45-50 years were followed up from 1996 to 2016. These women were free from diagnosed depression or chronic physical conditions at baseline. Data on depressive symptoms and chronic physical conditions were updated every 3 years, with depressive symptoms assessed using the Center for Epidemiological Studies-Depression scale. A 1-to-1 matched cohort analysis was conducted to compare the cumulative incidence and odds of physical multimorbidity between women with (depressed cohort) and women without (nondepressed cohort) elevated depressive symptoms, adjusted for sociodemographic and health behavioral factors. Over 20 years of follow-up, 3,199 women (43.2%) reported elevated depressive symptoms. Of these, 2,035 (63.6%) developed physical multimorbidity. After the onset of elevated depressive symptoms, women had a more than 4-fold increase in cumulative incidence of multimorbidity. Compared with the nondepressed cohort, the odds of the depressed cohort developing multimorbidity before the onset of depressive symptoms was 1.81 (95% confidence interval = 1.49, 2.20). After the onset of depressive symptoms, the odds ratio was 2.38 (95% confidence interval = 2.20, 2.57). Elevated depressive symptoms were common in women's midlife. Women with elevated depressive symptoms had increased odds of physical multimorbidity both before and after the onset of depressive symptoms. These findings support the emerging integrated management and prevention of mental and physical multimorbidity. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices.

BackgroundWith a wide range of use cases in both research and clinical domains, collecting continuous mobile health (mHealth) streaming data from multiple sources in a secure, highly scalable, and extensible platform is of high interest to the open source mHealth community. The European Union Innovative Medicines Initiative Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) program is an exemplary project with the requirements to support the collection of high-resolution data at scale; as such, the Remote Assessment of Disease and Relapse (RADAR)-base platform is designed to meet these needs and additionally facilitate a new generation of mHealth projects in this nascent field.ObjectiveWide-bandwidth networks, smartphone penetrance, and wearable sensors offer new possibilities for collecting near-real-time high-resolution datasets from large numbers of participants. The aim of this study was to build a platform that would cater for large-scale data collection for remote monitoring initiatives. Key criteria are around scalability, extensibility, security, and privacy.MethodsRADAR-base is developed as a modular application; the backend is built on a backbone of the highly successful Confluent/Apache Kafka framework for streaming data. To facilitate scaling and ease of deployment, we use Docker containers to package the components of the platform. RADAR-base provides 2 main mobile apps for data collection, a Passive App and an Active App. Other third-Party Apps and sensors are easily integrated into the platform. Management user interfaces to support data collection and enrolment are also provided.ResultsGeneral principles of the platform components and design of RADAR-base are presented here, with examples of the types of data currently being collected from devices used in RADAR-CNS projects: Multiple Sclerosis, Epilepsy, and Depression cohorts.ConclusionsRADAR-base is a fully functional, remote data collection platform built around Confluent/Apache Kafka and provides off-the-shelf components for projects interested in collecting mHealth datasets at scale.

Increased risk of prostatitis in male patients with depression

Objectives: To investigate whether male patients with depression are at an increased risk of prostatitis.Methods: We used a universal insurance claims database in Taiwan from 2000 to 2010 to identify patients with newly diagnosed depression (n = 13,019) (depression cohort) and those without depression (n = 53,026) (comparison cohort). Both cohorts were matched by age and index year of depression incidence. Hazard ratios of prostatitis were calculated by multivariable Cox proportional hazard models.Results: The incidence of prostatitis demonstrated a 2-fold increase in the depression cohort in comparison with that observed in the non-depression cohort, with an adjusted hazard ratio of 1.70 after adjustment for age, occupation, urbanisation level, potential comorbidity and medication. Furthermore, patients with depression, relative to the non-depression cohort, were 1.85-fold more likely to develop acute prostatitis, 1.76-fold more likely to develop chronic prostatitis and 1.63-fold more likely to develop unspecific prostatitis. Major associations still existed; even those stratified by age, occupation, urbanisation level and comorbidity all showed greater increased risks of prostatitis in the depression cohort than in the non-depression cohort.Conclusions: Depression can be an independent factor associated with the increased risk of prostatitis for men. The incidence of chronic prostatitis is greater than that of acute prostatitis. Close surveillance for UTI and depression treatment and lifestyle intervention should be considered for men with high risk for prostatitis. The mechanism associated with the development of prostatitis in men with depression requires further study. In addition, the mechanism of prostatitis may need comprehensive investigation.

RESULTS OF THE ADNI-DEPRESSION STUDY: Session 323

Results Of The ADNI-Depression Study. Overview: Late life depression (LLD) is one of the most common mental health disorders with which older patients are afflicted. LLD is complicated by the common co-occurrence of cognitive impairment (CI). Estimates suggest as many as 50-60% of older depressed patients may have mild cognitive deficits however the mechanisms contributing to CI are unclear. The ADNI-Depression (ADNI-D) Study is a 5-year two-site (University of California San Francisco and the University of Pittsburgh) NIMH sponsored study of late life depression. The study aims to characterize cognitive functioning patients with LLD and clarify neurobiological mechanisms contributing to cognitive impairment and accelerated cognitive decline in this patient population. The ADNI -D study partners with the Alzheimer's Disease Network Initiative (ADNI) and utilizes its core labs for data management, brain imaging, and biomarker assessments. The ADNI D study has been designed to focus on evaluating the impact of reduced cerebral blood flow, cortical atrophy, white matter disease, and amyloid deposition on cognitive impairment in LLD. The study is longitudinal; after an initial assessment subject are followed for 2 ½ years. ADNI-D is committed to rapid data sharing of the ADNI-D data. This session will present initial data from the ADNI-Depression Study baseline evaluation and will be organized into 4 topic areas. ADNI-D Methodology and Sample Characteristics (Nelson) The ADNI D sample is a well characterized sample of older adults with depression. The ADNI D methodology facilitates comparisons of this cohort of LLD participants with the larger ADNI study of non-depressed older adults with normal cognition, Mild Cognitive Impairment (MCI), and dementia in order to clarify neurobiological mechanisms contributing to cognitive impairment and accelerated cognitive decline. This session will be focused on describing the ADNI-D methodology for participant enrollment and data collection and to report ADNI D sample (n=121) characteristics for depression severity, lifetime history of depression and depression treatment, and functional impairment. Specifically, participant enrollment criteria and methods for the assessment of depression severity and lifetime history of depression and depression treatments will be summarized. Additionally, standardized methodology for collection of neuroimaging data, biomarkers, and data management will be presented. Cognitive Functioning in the ADNI Depression cohort (Morin). The clarification of types and severity of cognitive dysfunction in LLD remains a significant area of research. This session will focus on identifying the cognitive impairment rates of participants with LLD in the ADNI-D study at baseline, highlighting methodological considerations for matching subjects to ADNI participants on basis of cognitive functioning for biomarker analyses, and to assess the relationship of subjective cognitive complaints and ApoE status with objective measures cognitive performance. Association of Cortical Atrophy, White Matter Lesions, and Amyloid Accumulation with Cognition in Late Life Depression (Mackin) Cognitive impairment (CI) in LLD is often characterized by deficits of executive functioning (EF), memory, and language and LLD has been strongly linked to accelerated rates of cognitive decline in older adults. However, the causes of CI in LLD are not clear, in part due to limitations of previous work which have lacked comparisons to well characterized non-depressed older adults with CI caused by neurodegenerative diseases that are often concurrent with LLD, such as the early stages of Alzheimer's disease (AD) and cerebrovascular disease (CVD). The ADNI-D study will facilitate clarification of neurobiological mechanisms contributing to CI in LLD. This session will be focused on evaluating the impact of reduced cerebral blood flow (hypoperfusion), cortical atrophy, and amyloid deposition on CI in LLD in the context of previously documented relationships between CI and subcortical white matter abnormalities and genetic risk factors. Functional Network Level Pathophysiologic Abnormalities Associated with Late Life Depression (Tosun) Cognitive impairment, particularly in the domains of information processing speed, executive functioning, and memory, in LLD is consistent with neurobiological conceptualizations of LLD as being heavily mediated by extended neural networks comprised of the orbitofrontal, medial prefrontal, and cingulate cortices, and anatomical connections with the temporal and parietal lobes, and basal ganglia. By disturbing the normal function and dynamics of different brain networks, the pathophysiological mechanisms of LLD may generate different specific clinical symptoms. Therefore we examine the extent to which multimodal neuroimaging techniques can identify biomarkers reflecting key pathophysiologic processes in LLD and whether such biomarkers may act as predictors, moderators, and mediators of depressive symptoms. This might facilitate development of personalized treatments based on a better understanding of the pathophysiological mechanisms of late life depression.

Abstract TP153: Cognitive Profile in Patients With Hemodynamic Failure Due to Severe Carotid Stenosis

Background: Severe carotid stenosis can reduce cognition due to hypoperfusion. Published cognitive profiles for vascular disease are variable, however, precluding identification of hemodynamic failure as a specific cause. We investigated the relationship among carotid stenosis, hemodynamic failure, and cognition by characterizing cognition in patients with severe carotid stenosis, with and without hemodynamic failure. Methods: Sixty-one patients (18 with TIA, none with stroke) with ≥80% carotid stenosis were drawn from two study cohorts, RECON and BFC 1 . Hemodynamic status was assessed using oxygen extraction fraction by positron emission tomography (RECON) or mean flow velocity by transcranial Doppler (BFC) and dichotomized into normal (n=30) vs impaired (n=31). Cognition was assessed with 16 tests. Sixteen linear regressions, one for each cognitive test, were performed to assess the influence of hemodynamic failure on test scores, adjusting for side of occlusion, depression, age, gender, education, and study cohort. Multiple comparisons were adjusted using false discovery rate (FDR) correction. Results: Hemodynamic failure was a significant independent predictor for Rey Complex Figure Test-Copy (RCFT-C, p=0.007), RCFT-Delayed Recall (RCFT-D, p=0.003), and Trail Making Test-B (TMT-B, p=0.006) and remained so after FDR correction. The other tests were not predicted by hemodynamic status. Conclusions: Tests of mental flexibility, visuospatial skill, and organization were sensitive to hemodynamic failure in patients with severe carotid stenosis. A larger sample is required to validate this cognitive profile in such patients. Cognitive assessment with RCFT-C, RCFT-D, and TMT-B may detect the effects of hemodynamic failure specific to large vessel disease, having research and treatment utility. 1 NINDS NS048212 (Randomized Evaluation of Carotid Occlusion and Neurocognition -RECON), R01NS076277 (Blood Flow and Cognition - BFC)

Correlation between the microRNA-874-Sirtuin2-p53/nuclear factor-kappa B signaling pathway and depressive symptoms: a prospective multicenter study

Background and objective: Impaired hippocampal neurogenesis and local inflammatory responses are considered to be important mechanisms underlying depression. Sirtuin2 can inhibit cellular oxidative stress by regulating p53/nuclear factor-κB expression, prevent high-glucose-induced vascular endothelial cell damage, and interfere with neuroinflammation and blood-brain barrier destruction. Endogenous small RNAs or microRNAs (miRs) can be involved in the development and plasticity of the nervous system, which has been associated with depression. Our preliminary studies discovered that the 3′-untranslated region of Sirtuin2 messenger RNA (mRNA) is rich in miR-874 binding sites, suggesting that miR-874 may act as an upstream regulatory molecule for Sirtuin2. Therefore, we aim to explore the association between miR-874 and depressive symptoms through clinical trials. Participants and methods: This study will be conducted as a multicenter, prospective, clinical trial, at the Department of Rehabilitation at Tangdu Hospital of the Air Force Military Medical University and at the Department of Psychosomatic Medicine at Xijing Hospital of the Air Force Military Medical University, located in Xi’an, Shaanxi Province, China. A total of 50 patients with depression and 50 healthy controls will be recruited from these two locations. All patients with depression will be newly diagnosed, characterized by experiencing their first attack, and with no history of antidepressant administration. Moreover, no drug interventions will be utilized in this trial, for either the depressed or healthy cohorts. The trial protocol was approved by the Medical Ethics Committee of Tangdu Hospital of the Fourth Military Military Medical University in Xi’an, Shaanxi Province, China on June 1, 2018 (approval No. K201806-03). Protocol version is 1.0. All participants or their legal representatives will sign informed consent forms prior to the initiation of the trial. Patient recruitment began on October 31, 2018, and is expected to end on February 28, 2021. All data analysis was completed on August 1, 2021, and the trial will be completed on September 1, 2021. Outcome measures: Primary outcome measures include the expression levels miR-874 and Sirtuin2 mRNA in the blood. The secondary outcome measures include the levels of inflammatory factors, including interleukin-1β, interleukin-6, and tumor necrosis factor α, in the blood, the Hamilton Depression Rating Scale score, the Hamilton Anxiety Rating Scale score, the Global Assessment Function score, and the incidence of overall adverse events. We will also analyze the association between miR-874 expression levels and depression. Discussion: Determining whether any association exists between the miR-874-Sirtuin2-p53/nuclear factor-κB signaling pathway and depressive symptoms will assist in the exploration of the pathogenesis of depression and may provide novel therapeutic targets for the treatment of depression. Trial registration: This study was registered with the Chinese Clinical Trial Registry on October 17, 2018 (registration number: ChiCTR1800018933).

M65 - EXOME SEQUENCING OF MULTIPLEX PEDIGREES WITH EARLY ONSET, RECURRENT MAJOR DEPRESSIVE DISORDER

Background Major Depressive Disorder (MDD) is a common, often impairing disorder that ranks as the second leading cause of disability worldwide. More effective treatments are urgently needed, but few novel treatments have been developed over the last several decades, in large part due to our limited understanding of the pathophysiology of MDD. A long history of family and twin studies has shown consistent evidence for significant heritability in MDD and recent large scale GWAS analyses have begun to identify strongly associated common variants. However, few studies have so far focused on rare more penetrant variants, which may provide more interpretable insights into MDD related biology. Methods We selected 25 multiplex families from the Genetics of Early Onset Depression cohort, hypothesizing that pedigrees with at least three family members with childhood-onset depression, would be enriched for highly penetrant rare variants. We have completed exome sequencing in 3 affected members from these 25 highly multiplex families to average depth of 50X. Alignment and genotyping was performed employing standard pipelines using BWA-mem and GATK. Given prior evidence that ultra-rare variation may be most likely associated with greater penetrance, we focused our analyses on singly-segregating variants, defined as variants that fully segregated in a single family and were absent in all other pedigrees. Annotation was performed with ANNOVAR. Selected variants were confirmed with sanger sequencing. Results Each of the 25 multiplex families had an average of 4,092 segregating variants of which 412 were rare (defined as minor allele frequency Discussion Our study represents one of the first family based exome sequencing studies of major depression using an early onset, multiplex sample. We have found a number of highly damaging segregating variants that may be associated with MDD. Additional ongoing analyses, including pathway enrichment and replication, will also be presented.

Association of Depression and Cervical Spondylosis: A Nationwide Retrospective Propensity Score-Matched Cohort Study.

Objective: Depression is a psychiatric disorder associated with poorer health outcomes. Inappropriate mechanical stress and aging are factors associated with developing cervical spondylosis. The connection between cervical spondylosis and depression is not developed. Methods: From the health insurance claims data of Taiwan, we identified 34,166 persons newly diagnosed with depression in 2000–2010 and 34,166 persons without the disorder frequency matched by sex, age and diagnosis year. Both cohorts were followed up to the end of 2013 to estimate incident cervical spondylosis. We further examined the risk of cervical spondylosis in depressed people taking antidepressants. Results: The incidence of cervical spondylosis was 1.8-fold greater in the depression cohort than in comparison cohort (9.46 vs. 5.36 per 1000 person-years), with an adjusted hazard ratio (aHR) of 1.79 (95% confidence interval (CI) = 1.66–1.92). The incidence of cervical spondylosis increased in patients who had taken medications of serotonin-specific reuptake inhibitors (SSRIs) or of non-SSRIs than in those without these medicines (9.13 or 11.5 vs. 6.54 per 1000 person-years, respectively). Conclusions: Patients with depression are at an increased risk of developing cervical spondylosis. Additional efforts in reducing the risk of cervical spondylosis might be required in depressed individuals undergoing anti-depressive therapy.

Exploring comorbid depression and physical health trajectories: A case-based computational modelling approach.

While comorbid depression/physical health is a major clinical concern, the conventional methods of medicine make it difficult to model the complexities of this relationship. Such challenges include cataloguing multiple trends, developing multiple complex aetiological explanations, and modelling the collective large-scale dynamics of these trends. Using a case-based complexity approach, this study engaged in a richly described case study to demonstrate the utility of computational modelling for primary care research. N=259 people were subsampled from the Diamond database, one of the largest primary care depression cohort studies worldwide. A global measure of depressive symptoms (PHQ-9) and physical health (PCS-12) were assessed at 3, 6, 9, and 12months and then annually for a total of 7years. Eleven trajectories and 2 large-scale collective dynamics were identified, revealing that while depression is comorbid with poor physical health, chronic illness is often low dynamic and not always linked to depression. Also, some of the cases in the unhealthy and oscillator trends remain ill without much chance of improvement. Finally, childhood abuse, partner violence, and negative life events are greater amongst unhealthy trends. Computational modelling offers a major advance for health researchers to account for the diversity of primary care patients and for developing better prognostic models for team-based interdisciplinary care.

Supported Internet-Delivered Cognitive Behavior Treatment for Adults with Severe Depressive Symptoms: A Secondary Analysis.

BackgroundDepression is a highly prevalent mental health issue that exacts significant economic, societal, personal, and interpersonal costs. Innovative internet-delivered interventions have been designed to increase accessibility to and cost-effectiveness of treatments. These treatments have mainly targeted mild to moderate levels of depression. The increased risk associated with severe depression, particularly of suicidal ideation often results in this population being excluded from research studies. As a result, the effectiveness of internet-delivered cognitive behavioral therapy (iCBT) in more severely depressed cohorts is less researched.ObjectiveThe aim of this study is to examine the effect of iCBT on symptoms of severe depression, comorbid symptoms of anxiety, and levels of work and social functioning.MethodsRetrospective consent was provided by participants with elevated scores (>28 severe depression symptoms) on the Beck Depression Inventory (BDI-II) who accessed an iCBT intervention (Space from Depression) with support for up to 8 weeks. Data were collected at baseline, posttreatment, and 3-month follow-up on the primary outcome (BDI-II), and secondary outcomes (the Generalized Anxiety Disorder-7 and the Work and Social Adjustment Scale).ResultsA significant change was observed on all measures between pre- and postmeasurement and maintained at 3-month follow-up. Clinical improvement was observed for participants on the BDI-II from pre- to postmeasurement, and suicidal ideation also reduced from pre- to postmeasurement.ConclusionsUsers of Space from Depression with symptoms of severe depression were found to have decreased symptoms of depression and anxiety and increased levels of work and social functioning. The intervention also demonstrated its potential to decrease suicidal ideation. Further investigation is required to determine why some individuals improve, and others do not. iCBT may have the potential to be used as an adjunct treatment for severe depression symptoms, but participants may require further treatment if they receive iCBT as a standalone intervention. Although promising, further research incorporating control groups is needed to support the utility of Space from Depression for use in or as an adjunct to treatment for severe depression.