178 research outputs found

    A single, one-off measure of depression and anxiety predicts future symptoms, higher healthcare costs, and lower quality of life in coronary heart disease patients: Analysis from a multi-wave, primary care cohort study

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    To determine whether a one-off, baseline measure of depression and anxiety in a primary care, coronary heart disease (CHD) population predicts ongoing symptoms, costs, and quality of life across a 3-year follow-up.Longitudinal cohort study.16 General Practice surgeries across South-East London.803 adults (70% male, mean age 71 years) contributing up to 7 follow-up points.Ongoing reporting of symptoms, health care costs, and quality of life.At baseline, 27% of the sample screened positive for symptoms of depression and anxiety, as measured by the Hospital Anxiety and Depression Scale (HADS). The probability of scoring above the cut-off throughout the follow-up was 71.5% (p<0.001) for those screening positive at baseline, and for those screening negative, the probability of scoring below the cut-off throughout the follow-up was 97.6% (p<0.001). Total health care costs were 39% higher during follow-up for those screening positive (p<0.05). Quality of life as measured by the SF-12 was lower on the mental component during follow-up for those screening positive (-0.75, CI -1.53 to 0.03, p = 0.059), and significantly lower on the physical component (-4.99, CI -6.23 to -.376, p<0.001).A one-off measure for depression and anxiety symptoms in CHD predicts future symptoms, costs, and quality of life over the subsequent three-years. These findings suggest symptoms of depression and anxiety in CHD persist throughout long periods and are detrimental to a patient's quality of life, whilst incurring higher health care costs for primary and secondary care services. Screening for these symptoms at the primary care level is important to identify and manage patients at risk of the negative effects of this comorbidity. Implementation of screening, and possible collaborative care strategies and interventions that help mitigate this risk should be the ongoing focus of researchers and policy-makers

    A polygenic resilience score moderates the genetic risk for schizophrenia.

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    Based on the discovery by the Resilience Project (Chen R. et al. Nat Biotechnol 34:531–538, 2016) of rare variants that confer resistance to Mendelian disease, and protective alleles for some complex diseases, we posited the existence of genetic variants that promote resilience to highly heritable polygenic disorders1,0 such as schizophrenia. Resilience has been traditionally viewed as a psychological construct, although our use of the term resilience refers to a different construct that directly relates to the Resilience Project, namely: heritable variation that promotes resistance to disease by reducing the penetrance of risk loci, wherein resilience and risk loci operate orthogonal to one another. In this study, we established a procedure to identify unaffected individuals with relatively high polygenic risk for schizophrenia, and contrasted them with risk-matched schizophrenia cases to generate the first known “polygenic resilience score” that represents the additive contributions to SZ resistance by variants that are distinct from risk loci. The resilience score was derived from data compiled by the Psychiatric Genomics Consortium, and replicated in three independent samples. This work establishes a generalizable framework for finding resilience variants for any complex, heritable disorder

    Transcriptome of iPSC-derived neuronal cells reveals a module of co-expressed genes consistently associated with autism spectrum disorder

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    Evaluation of expression profile in autism spectrum disorder (ASD) patients is an important approach to understand possible similar functional consequences that may underlie disease pathophysiology regardless of its genetic heterogeneity. Induced pluripotent stem cell (iPSC)-derived neuronal models have been useful to explore this question, but larger cohorts and different ASD endophenotypes still need to be investigated. Moreover, whether changes seen in this in vitro model reflect previous findings in ASD postmortem brains and how consistent they are across the studies remain underexplored questions. We examined the transcriptome of iPSC-derived neuronal cells from a normocephalic ASD cohort composed mostly of high-functioning individuals and from non-ASD individuals. ASD patients presented expression dysregulation of a module of co-expressed genes involved in protein synthesis in neuronal progenitor cells (NPC), and a module of genes related to synapse/neurotransmission and a module related to translation in neurons. Proteomic analysis in NPC revealed potential molecular links between the modules dysregulated in NPC and in neurons. Remarkably, the comparison of our results to a series of transcriptome studies revealed that the module related to synapse has been consistently found as upregulated in iPSC-derived neurons-which has an expression profile more closely related to fetal brain-while downregulated in postmortem brain tissue, indicating a reliable association of this network to the disease and suggesting that its dysregulation might occur in different directions across development in ASD individuals. Therefore, the expression pattern of this network might be used as biomarker for ASD and should be experimentally explored as a therapeutic target

    Factor analysis of the Zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care

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    <p>Abstract</p> <p>Background</p> <p>The aim of this study was to examine the symptomatic dimensions of depression in a large sample of patients with major depressive disorder (MDD) in the primary care (PC) setting by means of a factor analysis of the Zung self-rating depression scale (ZSDS).</p> <p>Methods</p> <p>A factor analysis was performed, based on the polychoric correlations matrix, between ZSDS items using promax oblique rotation in 1049 PC patients with a diagnosis of MDD (DSM-IV).</p> <p>Results</p> <p>A clinical interpretable four-factor solution consisting of a <it>core depressive </it>factor (I); a <it>cognitive </it>factor (II); an <it>anxiety </it>factor (III) and a <it>somatic </it>factor (IV) was extracted. These factors accounted for 36.9% of the variance on the ZSDS. The 4-factor structure was validated and high coefficients of congruence were obtained (0.98, 0.95, 0.92 and 0.87 for factors I, II, III and IV, respectively). The model seemed to fit the data well with fit indexes within recommended ranges (GFI = 0.9330, AGFI = 0.9112 and RMR = 0.0843).</p> <p>Conclusion</p> <p>Our findings suggest that depressive symptoms in patients with MDD in the PC setting cluster into four dimensions: <it>core depressive, cognitive, anxiety </it>and <it>somatic</it>, by means of a factor analysis of the ZSDS. Further research is needed to identify possible diagnostic, therapeutic or prognostic implications of the different depressive symptomatic profiles.</p

    Depression, Rational Identity and the Educational Imperative: Concordance-Finding in Tricky Diagnostic Moments

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    It is well-documented, within most medical and much health psychology, that many individuals find diagnoses of depression confusing or even objectionable. Within a corpus of research and practical clinical guidance dominated by the social-cognitive paradigm, the explanation for resistance to a depression diagnosis (or advice pertaining to it) within specific interactions is bordering on the canonical; patients misunderstand depression itself, often as an output of an associated social stigma that distorts public knowledge. The best way to overcome corollary resistance in situ is, logically thus, taken to be a clarification of the true (clinical) nature of depression. In this paper, exploring the diagnosis of depression in UK primary care contexts, the social-cognitive position embedded in contemporary medical reasoning around this matter is critically addressed. It is firstly highlighted how, even in a great deal of extant public health research, the link between an individual holding “correct” medical knowledge and being actively compliant with it is far from inevitable. Secondly, and with respect to concerns around direct communication in clinical contexts, a body of research emergent of Discursive Psychology and Conversation Analysis is explored so as to shed light on how non-cognitive concerns (not least those around the local interactional management of a patient’s social identity) that can inform the manner in which ostensibly “tricky” medical talk plays-out in practice, especially in cases where a mental illness is at stake. Finally, observations are drawn together in a formal Discursive Psychological analysis of a small but highly illustrative sample of three cases where a depression diagnosis is initially questioned or disputed by a patient in primary care but, following further in-consultation activity, concordance with the diagnosis is ultimately reached—a specific issue hitherto unaddressed in either DP or CA fields. These cases specifically reveal the coordinative attention of interlocutors to immediate concerns regarding how the patient might maintain a sense of being an everyday and rational witness to their own lives; indeed, the very act of challenging the diagnosis emerges as a means by which a patient can open up conversational space within the consultation to address such issues. While the veracity of the social-cognitive model is not deemed to be without foundation herein, it is concluded that attention to local interactional concerns might firstly be accorded, such that the practical social concerns and skills of practitioners and patients alike might not be overlooked in the endeavour to produce generally applicable theories
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