Diffusion Tensor Imaging Detects Early Cerebral Cortex Abnormalities in Neuronal Architecture Induced by Bilateral Neonatal Enucleation: An Experimental Model in the Ferret

Diffusion tensor imaging (DTI) is a technique that non-invasively provides quantitative measures of water translational diffusion, including fractional anisotropy (FA), that are sensitive to the shape and orientation of cellular elements, such as axons, dendrites and cell somas. For several neurodevelopmental disorders, histopathological investigations have identified abnormalities in the architecture of pyramidal neurons at early stages of cerebral cortex development. To assess the potential capability of DTI to detect neuromorphological abnormalities within the developing cerebral cortex, we compare changes in cortical FA with changes in neuronal architecture and connectivity induced by bilateral enucleation at postnatal day 7 (BEP7) in ferrets. We show here that the visual callosal pattern in BEP7 ferrets is more irregular and occupies a significantly greater cortical area compared to controls at adulthood. To determine whether development of the cerebral cortex is altered in BEP7 ferrets in a manner detectable by DTI, cortical FA was compared in control and BEP7 animals on postnatal day 31. Visual cortex, but not rostrally adjacent non-visual cortex, exhibits higher FA than control animals, consistent with BEP7 animals possessing axonal and dendritic arbors of reduced complexity than age-matched controls. Subsequent to DTI, Golgi-staining and analysis methods were used to identify regions, restricted to visual areas, in which the orientation distribution of neuronal processes is significantly more concentrated than in control ferrets. Together, these findings suggest that DTI can be of utility for detecting abnormalities associated with neurodevelopmental disorders at early stages of cerebral cortical development, and that the neonatally enucleated ferret is a useful animal model system for systematically assessing the potential of this new diagnostic strategy

Predicting persistent depressive symptoms in older adults : a machine learning approach to personalised mental healthcare

Background Depression causes significant physical and psychosocial morbidity. Predicting persistence of depressive symptoms could permit targeted prevention, and lessen the burden of depression. Machine learning is a rapidly expanding field, and such approaches offer powerful predictive abilities. We investigated the utility of a machine learning approach to predict the persistence of depressive symptoms in older adults. Method Baseline demographic and psychometric data from 284 patients were used to predict the likelihood of older adults having persistent depressive symptoms after 12 months, using a machine learning approach (‘extreme gradient boosting’). Predictive performance was compared to a conventional statistical approach (logistic regression). Data were drawn from the ‘treatment-as-usual’ arm of the CASPER (CollAborative care and active surveillance for Screen-Positive EldeRs with subthreshold depression) trial. Results Predictive performance was superior using machine learning compared to logistic regression (mean AUC 0.72 vs. 0.67, p < 0.0001). Using machine learning, an average of 89% of those predicted to have PHQ-9 scores above threshold at 12 months, actually did, compared to 78% using logistic regression. However, mean negative predictive values were somewhat lower for the machine learning approach (45% vs. 35%). Limitations A relatively small sample size potentially limited the predictive power of the algorithm. In addition, PHQ-9 scores were used as an indicator of persistent depressive symptoms, and whilst well validated, a clinical interview would have been preferable. Conclusions : Overall, our findings support the potential application of machine learning in personalised mental healthcare. Keywords DepressionMachine learningOld age psychiatr

Mapping Primary Gyrogenesis During Fetal Development in Primate Brains: High-Resolution in Utero Structural MRI of Fetal Brain Development in Pregnant Baboons

The global and regional changes in the fetal cerebral cortex in primates were mapped during primary gyrification (PG; weeks 17–25 of 26 weeks total gestation). Studying pregnant baboons using high-resolution MRI in utero, measurements included cerebral volume, cortical surface area, gyrification index and length and depth of 10 primary cortical sulci. Seven normally developing fetuses were imaged in two animals longitudinally and sequentially. We compared these results to those on PG that from the ferret studies and analyzed them in the context of our recent studies of phylogenetics of cerebral gyrification. We observed that in both primates and non-primates, the cerebrum undergoes a very rapid transformation into the gyrencephalic state, subsequently accompanied by an accelerated growth in brain volume and cortical surface area. However, PG trends in baboons exhibited some critical differences from those observed in ferrets. For example, in baboons, the growth along the long (length) axis of cortical sulci was unrelated to the growth along the short (depth) axis and far outpaced it. Additionally, the correlation between the rate of growth along the short sulcal axis and heritability of sulcal depth was negative and approached significance (r = −0.60; p < 0.10), while the same trend for long axis was positive and not significant (p = 0.3; p = 0.40). These findings, in an animal that shares a highly orchestrated pattern of PG with humans, suggest that ontogenic processes that influence changes in sulcal length and depth are diverse and possibly driven by different factors in primates than in non-primates

Effect of collaborative depression treatment on risk for diabetes: A 9-year follow-up of the IMPACT randomized controlled trial

Considerable epidemiologic evidence and plausible biobehavioral mechanisms suggest that depression is an independent risk factor for diabetes. Moreover, reducing the elevated diabetes risk of depressed individuals is imperative given that both conditions are leading causes of death and disability. However, because no prior study has examined clinical diabetes outcomes among depressed patients at risk for diabetes, the question of whether depression treatment prevents or delays diabetes onset remains unanswered. Accordingly, we examined the effect of a 12-month collaborative care program for late-life depression on 9-year diabetes incidence among depressed, older adults initially free of diabetes. Participants were 119 primary care patients [M (SD) age: 67.2 (6.9) years, 41% African American] with a depressive disorder but without diabetes enrolled at the Indiana sites of the Improving Mood-Promoting Access to Collaborative Treatment (IMPACT) trial. Incident diabetes cases were defined as diabetes diagnoses, positive laboratory values, or diabetes medication prescription, and were identified using electronic medical record and Medicare/Medicaid data. Surprisingly, the rate of incident diabetes in the collaborative care group was 37% (22/59) versus 28% (17/60) in the usual care group. Even though the collaborative care group exhibited greater reductions in depressive symptom severity (p = .024), unadjusted (HR = 1.29, 95% CI: 0.69-2.43, p = .428) and adjusted (HR = 1.18, 95% CI: 0.61-2.29, p = .616) Cox proportional hazards models indicated that the risk of incident diabetes did not differ between the treatment groups. Our novel preliminary findings raise the possibility that depression treatment alone may be insufficient to reduce the excess diabetes risk of depressed, older adults

The interpretation of low mood and worry by high users of secondary care with medically unexplained symptoms

DA - 20111021 IS - 1471-2296 (Electronic) IS - 1471-2296 (Linking) LA - eng PT - Journal Article SB - IMPeer reviewedPublisher PD

The effects of implementing a point-of-care electronic template to prompt routine anxiety and depression screening in patients consulting for osteoarthritis (the Primary Care Osteoarthritis Trial): A cluster randomised trial in primary care

Background This study aimed to evaluate whether prompting general practitioners (GPs) to routinely assess and manage anxiety and depression in patients consulting with osteoarthritis (OA) improves pain outcomes. Methods and findings We conducted a cluster randomised controlled trial involving 45 English general practices. In intervention practices, patients aged ≥45 y consulting with OA received point-of-care anxiety and depression screening by the GP, prompted by an automated electronic template comprising five questions (a two-item Patient Health Questionnaire–2 for depression, a two-item Generalized Anxiety Disorder–2 questionnaire for anxiety, and a question about current pain intensity [0–10 numerical rating scale]). The template signposted GPs to follow National Institute for Health and Care Excellence clinical guidelines for anxiety, depression, and OA and was supported by a brief training package. The template in control practices prompted GPs to ask the pain intensity question only. The primary outcome was patient-reported current pain intensity post-consultation and at 3-, 6-, and 12-mo follow-up. Secondary outcomes included pain-related disability, anxiety, depression, and general health. During the trial period, 7,279 patients aged ≥45 y consulted with a relevant OA-related code, and 4,240 patients were deemed potentially eligible by participating GPs. Templates were completed for 2,042 patients (1,339 [31.6%] in the control arm and 703 [23.1%] in the intervention arm). Of these 2,042 patients, 1,412 returned questionnaires (501 [71.3%] from 20 intervention practices, 911 [68.0%] from 24 control practices). Follow-up rates were similar in both arms, totalling 1,093 (77.4%) at 3 mo, 1,064 (75.4%) at 6 mo, and 1,017 (72.0%) at 12 mo. For the primary endpoint, multilevel modelling yielded significantly higher average pain intensity across follow-up to 12 mo in the intervention group than the control group (adjusted mean difference 0.31; 95% CI 0.04, 0.59). Secondary outcomes were consistent with the primary outcome measure in reflecting better outcomes as a whole for the control group than the intervention group. Anxiety and depression scores did not reduce following the intervention. The main limitations of this study are two potential sources of bias: an imbalance in cluster size (mean practice size 7,397 [intervention] versus 5,850 [control]) and a difference in the proportion of patients for whom the GP deactivated the template (33.6% [intervention] versus 27.8% [control]). Conclusions In this study, we observed no beneficial effect on pain outcomes of prompting GPs to routinely screen for and manage comorbid anxiety and depression in patients presenting with symptoms due to OA, with those in the intervention group reporting statistically significantly higher average pain scores over the four follow-up time points than those in the control group. Trial registration ISRCTN registry ISRCTN4072198

Multimodal characterization of the late effects of traumatic brain injury: a methodological overview of the Late Effects of Traumatic Brain Injury Project

Epidemiological studies suggest that a single moderate-to-severe traumatic brain injury (TBI) is associated with an increased risk of neurodegenerative disease, including Alzheimer’s and Parkinson’s disease (AD and PD). Histopathological studies describe complex neurodegenerative pathologies in individuals exposed to single moderate-to-severe TBI or repetitive mild TBI, including chronic traumatic encephalopathy (CTE). However, the clinicopathological links between TBI and post-traumatic neurodegenerative diseases such as AD, PD, and CTE remain poorly understood. Here we describe the methodology of the Late Effects of TBI (LETBI) study, whose goals are to characterize chronic post-traumatic neuropathology and to identify in vivo biomarkers of post-traumatic neurodegeneration. LETBI participants undergo extensive clinical evaluation using National Institutes of Health TBI Common Data Elements, proteomic and genomic analysis, structural and functional MRI, and prospective consent for brain donation. Selected brain specimens undergo ultra-high resolution ex vivo MRI and histopathological evaluation including whole mount analysis. Co-registration of ex vivo and in vivo MRI data enables identification of ex vivo lesions that were present during life. In vivo signatures of postmortem pathology are then correlated with cognitive and behavioral data to characterize the clinical phenotype(s) associated with pathological brain lesions. We illustrate the study methods and demonstrate proof of concept for this approach by reporting results from the first LETBI participant, who despite the presence of multiple in vivo and ex vivo pathoanatomic lesions had normal cognition and was functionally independent until her mid-80s. The LETBI project represents a multidisciplinary effort to characterize post-traumatic neuropathology and identify in vivo signatures of postmortem pathology in a prospective study

Persistent frequent attenders in primary care: costs, reasons for attendance, organisation of care and potential for cognitive behavioural therapeutic intervention

<p><b>Abstract</b></p> <p>Background</p> <p>The top 3% of frequent attendance in primary care is associated with 15% of all appointments in primary care, a fivefold increase in hospital expenditure, and more mental disorder and functional somatic symptoms compared to normal attendance. Although often temporary if these rates of attendance last more than two years, they may become persistent (persistent frequent or regular attendance). However, there is no long-term study of the economic impact or clinical characteristics of regular attendance in primary care. Cognitive behaviour formulation and treatment (CBT) for regular attendance as a motivated behaviour may offer an understanding of the development, maintenance and treatment of regular attendance in the context of their health problems, cognitive processes and social context.</p> <p>Methods/design</p> <p>A case control design will compare the clinical characteristics, patterns of health care use and economic costs over the last 10 years of 100 regular attenders (≥30 appointments with general practitioner [GP] over 2 years) with 100 normal attenders (6–22 appointments with GP over 2 years), from purposefully selected primary care practices with differing organisation of care and patient demographics. Qualitative interviews with regular attending patients and practice staff will explore patient barriers, drivers and experiences of consultation, and organisation of care by practices with its challenges. Cognitive behaviour formulation analysed thematically will explore the development, maintenance and therapeutic opportunities for management in regular attenders. The feasibility, acceptability and utility of CBT for regular attendance will be examined.</p> <p>Discussion</p> <p>The health care costs, clinical needs, patient motivation for consultation and organisation of care for persistent frequent or regular attendance in primary care will be explored to develop training and policies for service providers. CBT for regular attendance will be piloted with a view to developing this approach as part of a multifaceted intervention.</p