73 research outputs found
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Translational Epidemiology In Psychiatry: Linking Population To Clinical And Basic Sciences
Translational research generally refers to the application of knowledge generated by advances in basic sciences research translated into new approaches for diagnosis, prevention, and treatment of disease. This direction is called bench-to-bedside. Psychiatry has similarly emphasized the basic sciences as the starting point of translational research. This article introduces the term translational epidemiology for psychiatry research as a bidirectional concept in which the knowledge generated from the bedside or the population can also be translated to the benches of laboratory science. Epidemiologic studies are primarily observational but can generate representative samples, novel designs, and hypotheses that can be translated into more tractable experimental approaches in the clinical and basic sciences. This bedside-to-bench concept has not been explicated in psychiatry, although there are an increasing number of examples in the research literature. This article describes selected epidemiologic designs, providing examples and opportunities for translational research from community surveys and prospective, birth cohort, and family-based designs. Rapid developments in informatics, emphases on large sample collection for genetic and biomarker studies, and interest in personalized medicineāwhich requires information on relative and absolute risk factorsāmake this topic timely. The approach described has implications for providing fresh metaphors to communicate complex issues in interdisciplinary collaborations and for training in epidemiology and other sciences in psychiatry.
Translational research generally refers to the application of knowledge generated by advances in basic sciences research translated into new approaches for prevention, diagnosis, and treatment of disease, followed by the introduction of innovations into clinical practice and health policy. This direction is called bench-to-bedside. Translational research has received increasing priority in recent years, by means of the National Institutes of Health's Road Map Plan, newly launched scientific journals (eg, http:// www.sciencetranslationalmedicine.org), new career programs, and the Clinical and Translational Science Award program. This emphasis is not just within the United States: the British Medical Research Council in 2007 established new translational medicine centers, one of which is devoted to translational epidemiology, and translational research has served as a centerpiece of the European Commission health budget.
Psychiatry has similarly emphasized the basic sciences as the starting point of translational research. Wang et al, in an explicit application of translation research to psychiatry, applied the Institute of Medicine's recommendations for translational research to schizophrenia and other psychotic disorders. They describe the application of 2 translational blocks. The first block, called T1, translates discoveries from the basic sciences into new diagnostic and preventive interventions, including early identification of high-risk individuals and new methods for testing interventions. In the second block, called T2, resulting clinical developments are received in clinical practice in comparative effectiveness studies, bridging the gap between diagnosis and actual treatment, providing health education, and changing prescribing practices. Within this bench-to-bedside framework, Wang et al argue, clinical epidemiology has played an important role in the design of clinical trials, prevention, health education, and service delivery.
The purpose of this article is to expand the term translational epidemiology into psychiatric research as a bidirectional concept in which the bedside, ie, the population, can also be translated into the benches of laboratory science. This approach uses epidemiologic designs and findings to facilitate or to partner with basic science research. We will apply this concept of translational epidemiology to psychiatry and demonstrate that the representative samples, novel designs, and hypotheses offered by epidemiology can be translated into more tractable experimental approaches in the clinical and basic sciences. Because the validity, interpretation, and generalizability of findings vary by design, we provide a brief overview of core epidemiologic designs and provide illustrations of translational applications with each design. The discussion of design is not intended as a substitute for an exhaustive review of epidemiologic design, for which we direct the reader to one of many excellent textbooks. We also do not intend to appropriate bedside-to-bench as a novel direction. There are a number of classic examples in medicine, such as the epidemiologic observation of the relationship between smoking and lung cancer, which led to animal studies demonstrating the carcinogenic effect of nicotine and other cigarette toxins.
This approach does not contradict the literature on bench-to-bedside translation; rather, it is complementary and iterative. The use of epidemiology in bedside-to-bench translational research in psychiatry has not been fully explicated, even though a number of studies appearing in the psychiatric literature have indirectly used epidemiologic designs. It is useful to make this idea explicit because epidemiology can provide hypotheses, designs, and samples for basic research, and the failure to avail oneself of these resources can lead to lost opportunities. Furthermore, different epidemiologic designs answer different questions, and inappropriate designs or inferences, particularly generalization of findings across designs, can confound results
Prenatal smoking exposure and neuropsychiatric comorbidity of ADHD: a finnish nationwide population-based cohort study
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Risks For Major Depression: Searching For Stable Traits
In this issue of Biological Psychiatry, Scifo et al. follow a reasonable clinical and epidemiologic classification to separate biological traits and states. They base their hypothesis on existing strong findings that patients often have lifelong recurring episodes of major depression of increasing severity, shorter remission periods, and reduced therapeutic response. Based on these observations, they reason that patients with differing clinical courses (single episodes, single episodes in remission, recurrent episodes, recurrent episodes in remission, and control subjects) should show differing biological traits and states.
Applying mass spectrometryābased proteomics to postmortem tissue, they tested 3630 proteins within the subgenual anterior cingulate cortex, a region previously implicated in the modulation of negative mood and found to be responsive to deep brain stimulation in patients with treatment-refractory depression. They identified 98 proteins whose expression was associated with major depressive disorder (MDD). Much to their surprise, they found weak evidence of proteomic differences as a function of depressive state. Instead, they found persistent effects of MDD independent of episode or remission, demographic characteristics, or other clinical measures of severity. They concluded that these proteomic differences did not predict state differences, but may have predicted traits. These depression effects were detected in a host of proteomic measures that certainly will guide numerous other investigations
Brain Derived Neurotrophic Factor Moderates Associations Between Maternal Smoking During Pregnancy And Offspring Behavioral Disorders
Maternal smoking during pregnancy is associated with a number of adverse offspring outcomes. In the present study, based on 209 offspring from a 3-generation family study of depression, we show that the effects of prenatal exposure on offspring externalizing psychopathology (conduct, substance use disorder) is more pronounced in the presence of lower-expressing brain derived neurotrophic factor (BDNF) gene variants. BDNF plays an important role in the development and survival of neural circuits. Individuals with low-expressing variants who are further exposed to prenatal tobacco smoke may be most vulnerable to a spectrum of behavioral disorders that depend on these circuits
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Effects of Serotonin Transporter Gene Variation on Impulsivity Mediated by Default Mode Network: A Family Study of Depression
Serotonergic neurotransmission, potentially through effects on the brainās default mode network (DMN), may regulate aspects of attention including impulse control. Indeed, genetic variants of the serotonin transporter (5-HTT) have been implicated in impulsivity and related psychopathology. Yet it remains unclear the mechanism by which the 5-HTT genetic variants contribute to individual variability in impulse control. Here, we tested whether DMN connectivity mediates an association between the 5-HTT genetic variants and impulsivity. Participants (N = 92) were from a family cohort study of depression in which we have previously shown a broad distribution of 5-HTT variants. We genotyped for 5-HTTLPR and rs25531 (stratified by transcriptional efficiency: 8 low/low, 53 low/high, and 31 high/high), estimated DMN structural connectivity using diffusion probabilistic tractography, and assessed behavioral measures of impulsivity (from 12 low/low, 48 low/high, and 31 high/high) using the Continuous Performance Task. We found that low transcriptional efficiency genotypes were associated with decreased connection strength between the posterior DMN and the superior frontal gyrus (SFG). Path modeling demonstrated that decreased DMNāSFG connectivity mediated the association between low-efficiency genotypes and increased impulsivity. Taken together, this study suggests a gene-brain-behavior pathway that perhaps underlies the role of the serotonergic neuromodulation in impulse control
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Temporal Stability Of Posterior EEG Alpha Over Twelve Years
Objective: We previously identiļ¬ed posterior EEG alpha as a potential biomarker for antidepressant treatment response. To meet the deļ¬nition of a trait biomarker or endophenotype, it should be independent of the course of depression. Accordingly, this report evaluated the temporal stability of posterior EEG alpha at rest. Methods: Resting EEG was recorded from 70 participants (29 male; 46 adults), during testing sessions separated by 12 Ā± 1.1 years. EEG alpha was identiļ¬ed, separated and quantiļ¬ed using reference-free methods that combine current source density (CSD) with principal components analysis (PCA). Measures of overall (eyes closed-plus-open) and net (eyes closed-minus-open) posterior alpha amplitude and asymmetry were compared across testing sessions. Results: Overall alpha was stable for the full sample (Spearman-Brown [rSB] = .834, Pearsonās r = .718), and showed excellent reliability for adults (rSB = .918; r = 0.848). Net alpha showed acceptable reliability for adults (rSB = .750; r = .600). Hemispheric asymmetries (right-minus-left hemisphere) of posterior overall alpha showed signiļ¬cant correlations, but revealed acceptable reliability only for adults (rSB = .728; r = .573). Findings were highly comparable between 29 male and 41 female participants. Conclusions: Overall posterior EEG alpha amplitude is reliable over long time intervals in adults. Signiļ¬cance: The temporal stability of posterior EEG alpha oscillations at rest over long time intervals is indicative of an individual trait. Ć 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved
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Offspring Of Depressed Parents: 30 Years Later
Objective:
While the increased risk of psychopathology in the biological offspring of depressed parents has been widely replicated, the long-term outcome through their full age of risk is less known. The authors present a 30-year follow-up of biological offspring (mean age=47 years) of depressed (high-risk) and nondepressed (low-risk) parents.
Method:
One hundred forty-seven offspring of moderately to severely depressed or nondepressed parents selected from the same community were followed for up to 30 years. Diagnostic assessments were conducted blind to parentsā clinical status. Final diagnoses were made by a blinded M.D. or Ph.D. evaluator.
Results:
The risk for major depression was approximately three times as high in the high-risk offspring. The period of highest risk for first onset was between ages 15 and 25 in both groups. Prepubertal onsets were uncommon, but high-risk offspring had over 10-fold increased risk. The early onset of major depression seen in the offspring of depressed parents was not offset by later first onsets in the low-risk group as they matured. The increased rates of major depression in the high-risk group were largely accounted for by the early onsets, but later recurrences in the high-risk group were significantly increased. The high-risk offspring continue to have overall poorer functioning and receive more treatment for emotional problems. There was increased mortality in the high-risk group (5.5% compared with 2.5%) due to unnatural causes, with a nearly 8-year difference in the mean age at death (38.8 years compared with 46.5 years).
Conclusions:
The offspring of depressed parents remain at high risk for depression, morbidity, and mortality that persists into their middle years. While adolescence is the major period of onset for major depression in both risk groups, it is the offspring with family history who go on to have recurrences and a poor outcome as they mature. In the era of personalized medicine, until a more biologically based understanding of individual risk is found, a simple family history assessment of major depression as part of clinical care can be a predictor of individuals at long-term risk
Associations Between Brain Structure and Connectivity in Infants and Exposure to Selective Serotonin Reuptake Inhibitors During Pregnancy
Importance Selective serotonin reuptake inhibitor (SSRI) use among pregnant women is increasing, yet the association between prenatal SSRI exposure and fetal neurodevelopment is poorly understood. Animal studies show that perinatal SSRI exposure alters limbic circuitry and produces anxiety and depressive-like behaviors after adolescence, but literature on prenatal SSRI exposure in humans is limited and mixed.
Objective To examine associations between prenatal SSRI exposure and brain development using structural and diffusion magnetic resonance imaging (MRI).
Design, Setting, and Participants A cohort study conducted at Columbia University Medical Center and New York State Psychiatric Institute included 98 infants: 16 with in utero SSRI exposure, 21 with in utero untreated maternal depression exposure, and 61 healthy controls. Data were collected between January 6, 2011, and October 25, 2016.
Exposures Selective serotonin reuptake inhibitors and untreated maternal depression.
Main Outcomes and Measures Gray matter volume estimates using structural MRI with voxel-based morphometry and white matter structural connectivity (connectome) using diffusion MRI with probabilistic tractography.
Results The sample included 98 mother (31 [32%] white, 26 [27%] Hispanic/Latina, 26 [27%] black/African American, 15 [15%] other) and infant (46 [47%] boys, 52 [53%] girls) dyads. Mean (SD) age of the infants at the time of the scan was 3.43 (1.50) weeks. Voxel-based morphometry showed significant gray matter volume expansion in the right amygdala (Cohen dā=ā0.65; 95% CI, 0.06-1.23) and right insula (Cohen dā=ā0.86; 95% CI, 0.26-1.14) in SSRI-exposed infants compared with both healthy controls and infants exposed to untreated maternal depression (Pā<ā.05; whole-brain correction). In connectome-level analysis of white matter structural connectivity, the SSRI group showed a significant increase in connectivity between the right amygdala and the right insula with a large effect size (Cohen dā=ā0.99; 95% CI, 0.40-1.57) compared with healthy controls and untreated depression (Pā<ā.05; whole connectome correction).
Conclusions and Relevance Our findings suggest that prenatal SSRI exposure has an association with fetal brain development, particularly in brain regions critical to emotional processing. The study highlights the need for further research on the potential long-term behavioral and psychological outcomes of these neurodevelopmental changes
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Adult Outcomes Of Childhood Disruptive Disorders In Offspring Of Depressed And Healthy Parents
Background: Longitudinal studies of children with disruptive disorders (DDs) have shown high rates of antisocial personality disorder (ASPD) and substance use in adulthood, but few have examined the contribution of parental disorders. We examine child-/adulthood outcomes of DDs in offspring, whose biological parents did not have a history of ASPD, bipolar disorder, or substance use disorders. Method: Offspring (N = 267) of parents with or without major depression (MDD), but no ASPD or bipolar disorders were followed longitudinally over 33 years, and associations between DDs and psychiatric and functional outcomes were tested. Results: Eighty-nine (33%) offspring had a DD. Those with, compared to without DDs, had higher rates of MDD (adjusted odds ratio, AOR = 3.42, p < 0.0001), bipolar disorder (AOR = 3.10, p = 0.03), and substance use disorders (AOR = 5.69, p < 0.0001) by age 18, as well as poorer school performance and global functioning. DDs continued to predict MDD and substance use outcomes in adulthood, even after accounting for presence of the corresponding disorder in childhood (MDD: hazards ratio, HR = 3.25, p < 0.0001; SUD, HR = 2.52, p < 0.0001). Associations were similar among the offspring of parents with and without major depression. DDs did not predict adulthood ASPD in either group. Limitations: Associations are largely accounted for by conduct disorder (CD), as there were few offspring with ADHD, and oppositional defiant disorder (ODD) was not diagnosed at the time this study began. Conclusion: If there is no familial risk for ASPD, bipolar disorder or substance use, childhood DDs do not lead to ASPD in adulthood; however, the children still have poorer prognosis into midlife. Early treatment of children with DD, particularly CD, while carefully considering familial risk for these disorders, may help mitigate later adversity
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Remission Of Maternal Depression And Child Symptoms Among Single Mothers: A Star*d-child Report
Objective: Offspring of depressed parents are at increased risk for depressive and other disorders. We recently found that when depressed mothers reached full remission over 3 months of treatment, a significant improvement in the childrenās disorders occurred. Since only a third of the mothers remitted, factors related to maternal remission rates, and thereby child outcomes, were important. This report examined the relationship of the presence of a father in the household to maternal depression remission and child outcomes.
Method: Maternal depression was measured using the 17-item Hamilton Rating Scale for Depression (HRSD17); social functioning was assessed using the Social Adjustment Scale-Self Report (SAS-SR). Children (age 7ā17) were assessed independently, blind to maternal outcome, using the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS-PL) and the Child Global Assessment Scale (C-GAS).
Results: Single mothers (n = 50), as compared to those in two-parent households (n = 61), were more likely to discontinue treatment (31% vs. 16%, P = 0.04), and less likely to remit if they remained in treatment (20% vs. 43%, P = 0.013). These differences remained significant after adjusting for socioeconomic status and potential confounders, but were partially explained by the motherās pre-treatment social functioning. The reduction in child diagnoses following maternal remission was greater in two-parent than in single-parent households, although a formal test of interaction between the odds ratios was not significant.
Conclusion: Single depressed mothers are more likely to drop out of treatment, and less likely to reach remission if they stay in treatment. This high-risk group requires vigorous treatment approaches
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