Symptom-based Subtypes Research Articles

Stability of symptom-based subtypes in Sjogren’s disease

ObjectivesThe Newcastle Sjogren’s Stratification Tool (NSST) stratifies Sjogren’s disease patients into four subtypes. Understanding the stability of the subtypes is vital if symptom-based stratification is to be more broadly adopted....

OSA Symptom Subtypes and Hypoxic Burden Independently Predict Distinct Cardiovascular Outcomes

Study ObjectivesStudies on obstructive sleep apnea (OSA) have identified clinically relevant symptom-based subtypes and novel OSA-specific nocturnal hypoxic measures. Both traits are individually associated with cardiovascular outcomes, but evidence about their independent or shared effects is unknown. This study investigated the simultaneous contributions of OSA symptom subtypes and hypoxic burden (HB) on incident cardiovascular outcomes.MethodsSleep Heart Health Study participants with high-quality oxygen saturation, apnea-hypopnea index (AHI), and symptom data were included. Participants with OSA (AHI≥5 events/hour) were grouped into symptom subtypes. HB was calculated from respiratory event-related hypoxia. Cox proportional hazards models assessed whether symptom subtypes and/or HB were independently associated with cardiovascular mortality and major adverse cardiovascular events (MACE).Results4396 participants free of cardiovascular disease were analyzed, with median follow-up >11 years. Higher HB was associated with worse cardiovascular mortality (HR [95% CI]: 1.63 [1.13,2.35]; p=0.009) independently of symptom subtypes. Compared to those without OSA, the excessively sleepy OSA subtype had higher risk of incident MACE (1.62 [1.23,2.15]; p<0.001), independently of HB. Among participants with moderate-severe OSA (AHI ≥15 events/hour), excessively sleepy participants had higher risk of cardiovascular endpoints compared to other subtypes, but HB was not associated with cardiovascular mortality or MACE risk.ConclusionOSA symptom subtypes and HB are independently associated with MACE and cardiovascular mortality, respectively. Thus, both are important for understanding OSA-related cardiovascular risk. Future studies using clinical samples including OSA therapy information that incorporate symptom subtypes and novel biomarkers, such as HB, could improve predictive models for cardiovascular disease risk.

The novel subtype of major depressive disorder characterized by somatic symptoms is associated with poor treatment efficacy and prognosis: A data-driven cluster analysis of a prospective cohort in China

BackgroundThere is not yet a valid and evidence-based system to classify patients with MDD into more homogeneous subtypes based on their clinical features. This study aims to identify symptom-based subtypes of MDD and investigate whether the treatment outcomes of those subtypes would be different. MethodThe cohort was established at 12 densely populated cities of China. A total of 1487 patients were enrolled. All participants were 18–65 years old and diagnosed with MDD. Participants were followed up at baseline, weeks 4, 8, and 12, and months 4 and 6. K-means algorithm was used to cluster patients with MDD according to clinical symptoms. The network analysis was adopted to characterize and compare the symptom patterns in the clusters. We also examined the associations between the clusters and the clinical outcomes. ResultsThe optimal number of the clusters was determined to be 2. Each cluster's maximum Jaccard Co-efficient was calculated to be >0.5 (cluster1 = 0.53, cluster 2 = 0.67). The symptom “depressed mood” and some other affective symptoms were the most prominent in cluster 1. Somatic symptoms, such as weight loss and general somatic symptoms, had the greatest expected influence in cluster 2. Compared with the response rates of the patients in the “somatic cluster”, those of the patients in the “affective cluster” were significantly higher (P < 0.05). ConclusionsPatients with MDD might be classified into two symptom-based subtypes featured with affective symptoms or somatic symptoms. The treatment efficacy and prognosis of the subtype featured with somatic symptoms may be worse.

0437 Obstructive Sleep Apnea Symptom Subtypes and Hypoxic Burden Independently Predict Distinct Cardiovascular Outcomes

Abstract Introduction Studies on heterogeneity of obstructive sleep apnea (OSA) have identified clinically relevant symptom-based subtypes and novel OSA-specific nocturnal hypoxemia measures. Evidence suggests that moderate-severe OSA patients with the excessively sleepy subtype have increased risk of incident major adverse cardiovascular events (MACE; composite of coronary heart disease, heart failure, stroke, or cardiovascular mortality) and that OSA-specific hypoxic burden (HB) is associated with increased risk of cardiovascular disease (CVD) mortality. However, no study has comprehensively examined their combined impact. This study provides a systematic assessment of the individual and combined contribution of these factors on incident CVD risk, addressing an important gap in evidence. Methods Participants from the Sleep Heart Health Study with high-quality oxygen saturation, OSA severity quantified by apnea-hypopnea index (AHI), and symptom data were included. Latent class analysis on 14 symptoms was used to classify participants with moderate-severe OSA (AHI≥15) into subtypes. HB was calculated from respiratory event-related hypoxia and sleep time. Cox proportional hazards models were used to assess the relative contributions of OSA symptom subtypes and HB (natural log transformed) on risk for CVD mortality and MACE, adjusted for demographic and CVD risk factors. Analyses were performed in both CVD-free participants and all participants (adjusted for CVD at baseline). Results A total of 5,027 participants were analyzed, with median follow-up of 11.6 years (CVD mortality) and 11.3 years (MACE). HB was independently associated with CVD mortality in all participants (HR[95% CI] = 1.44 [1.06-1.97]; p=0.021) and CVD-free participants (1.62 [1.12-2.35]; p=0.010) controlling for symptom subtype. Conversely, symptom subtypes were independently associated with MACE incidence among CVD-free participants, controlling for HB, with the excessively sleepy participants having nearly two-fold higher risk (HR[95% CI] = 1.98 [1.26-3.10]; p=0.003) compared to those without OSA. Conclusion OSA symptom subtypes and HB are independently associated with distinct CVD-related endpoints. Higher HB was associated with cardiovascular mortality, controlling for symptom subtype. The excessively sleepy subtype was at higher risk of new MACE, controlling for HB. Thus, both factors are important for understanding OSA-related CVD risk. Support (if any) AHA (20CDA35310360), NIH (P01HL094307, U01HL53916, U01HL53931, U01HL53934, U01HL53937, U01HL53938, U01HL53940, U01HL53941, U01HL64360 R24 HL114473, 75N92019R002).

Biotypes of major depressive disorder identified by a multiview clustering framework

BackgroundThe advances in resting-state functional magnetic resonance imaging techniques motivate parsing heterogeneity in major depressive disorder (MDD) through neurophysiological subtypes (i.e., biotypes). Based on graph theories, researchers have observed the functional organization of the human brain as a complex system with modular structures and have found wide-spread but variable MDD-related abnormality regarding the modules. The evidence implies the possibility of identifying biotypes using high-dimensional functional connectivity (FC) data in ways that suit the potentially multifaceted biotypes taxonomy. MethodsWe proposed a multiview biotype discovery framework that involves theory-driven feature subspace partition (i.e., “view”) and independent subspace clustering. Six views were defined using intra- and intermodule FC regarding three MDD focal modules (i.e., the sensory-motor system, default mode network, and subcortical network). For robust biotypes, the framework was applied to a large multisite sample (805 MDD participants and 738 healthy controls). ResultsTwo biotypes were stably obtained in each view, respectively characterized by significantly increased and decreased FC compared to healthy controls. These view-specific biotypes promoted the diagnosis of MDD and showed different symptom profiles. By integrating the view-specific biotypes into biotype profiles, a broad spectrum in the neural heterogeneity of MDD and its separation from symptom-based subtypes was further revealed. LimitationsThe power of clinical effects is limited and the cross-sectional nature cannot predict the treatment effects of the biotypes. ConclusionsOur findings not only contribute to the understanding of heterogeneity in MDD, but also provide a novel subtyping framework that could transcend current diagnostic boundaries and data modality.

Eosinophil and Mast Cell Counts in the Stomach and Duodenum of Patients with Functional Dyspepsia without a Helicobacter pylori infection.

Symptom-based subtyping of functional dyspepsia (FD) is used to segregate patients into groups with homogenous pathophysiological mechanisms. This study examined whether subtyping could reflect the duodenal and gastric microinflammation in FD patients. Twenty-one FD patients without Helicobacter pylori infection were recruited. An endoscopic biopsy was performed in the duodenum 2nd portion, stomach antrum, and body. The eosinophil and mast cell counts per high-power field (×40) were investigated by H&E and c-kit staining, respectively. The degree of inflammatory cell infiltration, atrophy, and intestinal metaplasia was also determined by H&E staining in the stomach. The baseline characteristics and eosinophil and mast cell infiltrations were compared among the three groups (epigastric pain syndrome, postprandial distress syndrome, and overlap). According to the symptom assessment, seven subjects were classified into the epigastric pain syndrome group, 10 into the postprandial syndrome group, and four into the overlap group. The baseline variables were similar in the three groups. Eosinophil infiltration was more prominent in the duodenum than in the stomach. In contrast, mast cell infiltration was similar in the duodenum and stomach. The eosinophil counts in the duodenum were similar in the three groups. The eosinophil counts in the stomach and mast cell counts in the duodenum and stomach were also similar in the three groups. Duodenal eosinophil infiltration was prominent in FD patients, but the eosinophil counts were similar regardless of the symptom-based subtypes of FD. Hence, the current symptom-based subtyping of FD does not reflect duodenal eosinophil and mast cell infiltration.

0717 Obstructive Sleep Apnea Symptom Subtype Transitions over Five Years are Associated with Increased Cardiovascular Disease Incidence Risk

Abstract Introduction Efforts to characterize clinical heterogeneity of obstructive sleep apnea (OSA) resulted in the identification and replication of symptom-based subtypes. Individuals with moderate-severe OSA that are excessively sleepy are at increased risk of cardiovascular disease (CVD). There is limited evidence about whether OSA patients that worsen their symptom presentation over time are at increased cardiovascular burden. This study aimed to assess the association between five-year transitions among OSA symptom subtypes and incidence of CVD in a community-based cohort. Methods Participants of the Sleep Heart Health Study with complete baseline and 5-year follow-up data on symptom presentation, polysomnographic data and CVD outcomes were included (N=2,643). We used latent transition analysis on 14 symptom items to determine symptom subtype transitions in participants diagnosed with OSA (apnea-hypopnea index [AHI]≥5) across both visits. The primary outcome was incidence of CVD, defined as first occurrence of a composite of coronary heart disease, heart failure or stroke after the follow-up visit (median CV follow-up: 6.7 years). Cox proportional hazards models were used to assess the association between symptom subtype transitions and CVD incidence, adjusted by relevant demographic and cardiovascular risk factors. Results Four OSA symptom subtypes were identified at baseline and follow-up visits: minimally symptomatic, disturbed sleep, moderately sleepy and excessively sleepy. When compared to participants without OSA at baseline and follow-up visits, those with OSA that transitioned from moderately sleepy to excessively sleepy had increased CVD incidence risk (HR=2.09; 95%CI=1.27-3.45; p=0.004), independent of other CV risk factors. Increased CVD incidence risk was also observed in participants who transitioned from moderately sleepy to excessively sleepy when compared to those that remained moderately sleepy (HR=2.02; 95%CI=1.20-3.40; p=0.008) and in participants who transitioned from disturbed sleep to excessively sleepy when compared to those that remained with disturbed sleep (HR=3.25; 95%CI=1.03-10.23; p=0.044). Conclusion Five-year transitions across OSA symptom subtypes are associated with increased CVD incidence risk when adjusted by other relevant cardiovascular risk factors. Participants that transitioned from moderately sleepy or from disturbed sleep to excessively sleepy were at higher CVD risk. Results of this study might inform the role of symptom progression on CVD risk in OSA. Support (If Any) American Heart Association (20CDA35310360), National Institutes of Health (U01HL53916, U01HL53931, U01HL53934, U01HL53937, U01HL53938, U01HL53940, U01HL53941, U01HL64360 R24 HL114473, 75N92019R002).

Is the Epworth Sleepiness Scale Sufficient to Identify the Excessively Sleepy Subtype of OSA?

Excessive daytime sleepiness (EDS), a prevalent clinical feature in OSA, is associated with adverse consequences.1 The Epworth Sleepiness Scale (ESS) is the most widely used instrument to characterize subjective EDS in OSA.2 Patients with an ESS score of >10 are typically categorized as having EDS.2 However, clustering analyses of a broader range of clinical symptoms have identified unique and reproducible symptom-based subtypes of moderate-to-severe OSA that is characterized by disturbed sleep, different degrees of excessive sleepiness, or minimal symptoms.

The Usefulness of Symptom-based Subtypes of Functional Dyspepsia for Predicting Underlying Pathophysiologic Mechanisms and Choosing Appropriate Therapeutic Agents.

Functional dyspepsia (FD) is considered to be a heterogeneous disorder with different pathophysiological mechanisms or pathogenetic factors. In addition to traditional mechanisms, novel concepts regarding pathophysiologic mechanisms of FD have been proposed. Candidates of therapeutic agents based on novel concepts have also been suggested. FD is a symptom complex and currently diagnosed by symptom-based Rome criteria. In the Rome criteria, symptom-based subtypes of FD including postprandial distress syndrome and epigastric pain syndrome are recommended to be used, based on the assumption that each subtype is more homogenous in terms of underlying pathophysiologic mechanisms than FD as a whole. In this review, the usefulness of symptom-based subtypes of FD for predicting underlying pathophysiologic mechanisms and choosing appropriate therapeutic agents was evaluated. Although several classic pathophysiologic mechanisms are suggested to be associated with individual dyspeptic symptoms, symptom-based subtypes of FD are not specific for a certain pathogenetic factor or pathophysiologic mechanism, and may be frequently associated with multiple pathophysiologic abnormalities. Novel concepts on the pathophysiology of FD show complex interactions between pathophysiologic mechanisms and pathogenetic factors, and prediction of underlying mechanisms of individual patients simply by the symptom pattern or symptom-based subtypes may not be accurate in a considerable proportion of cases. Therefore, subtyping by the Rome criteria appears to have limited value to guide therapeutic strategy, suggesting that the addition of objective parameters or subclassification reflecting physiologic or pathologic tests may be necessary for the targeted therapeutic approaches, particularly when therapeutic agents targeting novel mechanisms are available.

Dissecting diagnostic heterogeneity in depression by integrating neuroimaging and genetics.

Depression is a heterogeneous and etiologically complex psychiatric syndrome, not a unitary disease entity, encompassing a broad spectrum of psychopathology arising from distinct pathophysiological mechanisms. Motivated by a need to advance our understanding of these mechanisms and develop new treatment strategies, there is a renewed interest in investigating the neurobiological basis of heterogeneity in depression and rethinking our approach to diagnosis for research purposes. Large-scale genome-wide association studies have now identified multiple genetic risk variants implicating excitatory neurotransmission and synapse function and underscoring a highly polygenic inheritance pattern that may be another important contributor to heterogeneity in depression. Here, we review various sources of phenotypic heterogeneity and approaches to defining and studying depression subtypes, including symptom-based subtypes and biology-based approaches to decomposing the depression syndrome. We review "dimensional," "categorical," and "hybrid" approaches to parsing phenotypic heterogeneity in depression and defining subtypes using functional neuroimaging. Next, we review recent progress in neuroimaging genetics (correlating neuroimaging patterns of brain function with genetic data) and its potential utility for generating testable hypotheses concerning molecular and circuit-level mechanisms. We discuss how genetic variants and transcriptomic profiles may confer risk for depression by modulating brain structure and function. We conclude by highlighting several promising areas for future research into the neurobiological underpinnings of heterogeneity, including efforts to understand sexually dimorphic mechanisms, the longitudinal dynamics of depressive episodes, and strategies for developing personalized treatments and facilitating clinical decision-making.

Neurovegetative symptom subtypes in young people with major depressive disorder and their structural brain correlates

Depression is a leading cause of burden of disease among young people. Current treatments are not uniformly effective, in part due to the heterogeneous nature of major depressive disorder (MDD). Refining MDD into more homogeneous subtypes is an important step towards identifying underlying pathophysiological mechanisms and improving treatment of young people. In adults, symptom-based subtypes of depression identified using data-driven methods mainly differed in patterns of neurovegetative symptoms (sleep and appetite/weight). These subtypes have been associated with differential biological mechanisms, including immuno-metabolic markers, genetics and brain alterations (mainly in the ventral striatum, medial orbitofrontal cortex, insular cortex, anterior cingulate cortex amygdala and hippocampus). K-means clustering was applied to individual depressive symptoms from the Quick Inventory of Depressive Symptoms (QIDS) in 275 young people (15–25 years old) with MDD to identify symptom-based subtypes, and in 244 young people from an independent dataset (a subsample of the STAR*D dataset). Cortical surface area and thickness and subcortical volume were compared between the subtypes and 100 healthy controls using structural MRI. Three subtypes were identified in the discovery dataset and replicated in the independent dataset; severe depression with increased appetite, severe depression with decreased appetite and severe insomnia, and moderate depression. The severe increased appetite subtype showed lower surface area in the anterior insula compared to both healthy controls. Our findings in young people replicate the previously identified symptom-based depression subtypes in adults. The structural alterations of the anterior insular cortex add to the existing evidence of different pathophysiological mechanisms involved in this subtype.

Predictability of temperaments and negative experiences on higher-order symptom-based subtypes of depression

BackgroundThe identification of subtypes of depression based on higher-order symptoms of emotional, thought, and behavioral dysfunction will broaden understanding of the heterogeneity in depression. Furthermore, exploring the ability of temperaments and negative experiences to predict each subtype is an effective way of facilitating treatment decisions. MethodsParticipants were 417 patients diagnosed with depressive disorder at the psychiatry department of a major medical hospital in Seoul, Korea. A latent profile analysis was performed based on three higher-order scales of the MMPI-2-RF: Emotional/Internalizing Dysfunction, Thought Dysfunction, and Behavioral/Externalizing Dysfunction. Four temperament dimensions were assessed by the Temperament and Character Inventory-Revised-Short, and negative experiences including recent negative life events, number of lifetime traumatic events, and severity of maltreatment, were used as covariates in a multinomial regression analysis. ResultsFour classes were obtained from the latent profile analysis: a “severe mood class” (39.8%), a “moderate mood class” (37.4%), a “mild mood class” (11.3%), and a “severe mood/thought class” (11.5%). Among temperament dimensions, high harm avoidance and low persistence significantly predicted more severe mood classes. Low reward dependence, number of lifetime traumatic events, and severity of maltreatment in negative experiences were significant predictors of the severe mood/thought class. LimitationsThis study could not explain the more detailed heterogeneity within depression because of over-inclusiveness of the higher-order scales. ConclusionsThis study identified three latent classes that differed in emotional severity and one other class with thought problems. The distinct dimensions of temperament and different types of negative experiences predicted the identified subtypes.

Differences in Fecal Microbiomes and Metabolomes of People With vs Without Irritable Bowel Syndrome and Bile Acid Malabsorption

Irritable bowel syndrome (IBS) is a heterogeneous disorder, but diagnoses and determination of subtypes are made based on symptoms. We profiled the fecal microbiomes of patients with and without IBS to identify biomarkers of this disorder. We collected fecal and urine samples from 80 patients with IBS (Rome IV criteria; 16-70 years old) and 65 matched individuals without IBS (control individuals), along with anthropometric, medical, and dietary information. Shotgun and 16S ribosomal RNA amplicon sequencing were performed on feces, whereas urine and fecal metabolites were analyzed by gas chromatography and liquid chromatography-mass spectrometry. Co-occurrence networks were generated based on significant Spearman correlations between data. Bile acid malabsorption (BAM) was identified in patients with diarrhea by retention of radiolabeled selenium-75 homocholic acid taurine. Patients with IBS had significant differences in network connections between diet and fecal microbiomes compared with control individuals; these were accompanied by differences in fecal metabolomes. We did not find significant differences in fecal microbiota composition among patients with different IBS symptom subtypes. Fecal metabolome profiles could discriminate patients with IBS from control individuals. Urine metabolomes also differed significantly between patients with IBS and control individuals, but most discriminatory metabolites were related to diet or medications. Fecal metabolomes, but not microbiomes, could distinguish patients with IBS with vs those without BAM. Despite the heterogeneity of IBS, patients have significant differences in urine and fecal metabolomes and fecal microbiome vs control individuals, independent of symptom-based subtypes of IBS. Fecal metabolome analysis can be used to distinguish patients with IBS with vs those without BAM. These findings might be used for developing microbe-based treatments for these disorders.

Data-driven biological subtypes of depression: systematic review of biological approaches to depression subtyping.

Research into major depressive disorder (MDD) is complicated by population heterogeneity, which has motivated the search for more homogeneous subtypes through data-driven computational methods to identify patterns in data. In addition, data on biological differences could play an important role in identifying clinically useful subtypes. This systematic review aimed to summarize evidence for biological subtypes of MDD from data-driven studies. We undertook a systematic literature search of PubMed, PsycINFO, and Embase (December 2018). We included studies that identified (1) data-driven subtypes of MDD based on biological variables, or (2) data-driven subtypes based on clinical features (e.g., symptom patterns) and validated these with biological variables post-hoc. Twenty-nine publications including 24 separate analyses in 20 unique samples were identified, including a total of ~ 4000 subjects. Five out of six biochemical studies indicated that there might be depression subtypes with and without disturbed neurotransmitter levels, and one indicated there might be an inflammatory subtype. Seven symptom-based studies identified subtypes, which were mainly determined by severity and by weight gain vs. loss. Two studies compared subtypes based on medication response. These symptom-based subtypes were associated with differences in biomarker profiles and functional connectivity, but results have not sufficiently been replicated. Four out of five neuroimaging studies found evidence for groups with structural and connectivity differences, but results were inconsistent. The single genetic study found a subtype with a distinct pattern of SNPs, but this subtype has not been replicated in an independent test sample. One study combining all aforementioned types of data discovered a subtypes with different levels of functional connectivity, childhood abuse, and treatment response, but the sample size was small. Although the reviewed work provides many leads for future research, the methodological differences across studies and lack of replication preclude definitive conclusions about the existence of clinically useful and generalizable biological subtypes.

Seroreactivity to Microbial Antigens and Gut‐Homing Immune Responses in Functional Dyspepsia Patients with Postprandial Distress Syndrome

Functional dyspepsia (FD) is characterised by recurrent upper gastrointestinal symptoms with no explainable structural changes seen at endoscopy. FD can be classed by two symptom‐based subtypes: postprandial distress syndrome (PDS) and epigastric pain syndrome (EPS). Although FD is associated with an altered microbiome, the nature and consequence of the host‐microbiota interactions and how they relate to FD symptom subtypes is not well understood. We have previously identified an increase in the abundance of Streptococcus spp. in the duodenal microbiota of FD patients compared to controls (Zhong et al. 2017 Gut). We hypothesised that the microbiota of FD patients influenced immune homeostasis and aimed to investigate whether specific species provoked immune responses in patients with FD.New isolates of Streptococcus and Corynebacterium spp. found to be abundant in the duodenal microbiota of FD patients were selected for further analysis. Whole cell lysates from cultures of these bacteria were separated by polyacrylamide gel electrophoresis and transferred to a PVDF membrane for immunoblotting. Immunoblots were probed with plasma from FD patients or non‐FD controls. Density gradient separation was used to isolate peripheral blood mononuclear cells from blood. Cells were then stained with fluorophore conjugated markers for CD3, CD4, integrins α4 &amp; β7 before analysis by flow cytometry to examine changes in proportions of gut‐homing associated lymphocytes (α4+β7+).For lysate isolated from a Streptococcus spp. strain, seroreactive IgG antibody bands were observed at approximately 70kDa in 9 out of 10 FD patients. This band was absent in all but 2 of the control cohort (total n=8). A further band was observed around 30kDa in 9 FD patients (total n=10) that was only present in 3 controls (total n=8). 8 of the 10 patients reported PDS symptoms, of which all demonstrated seroreactivity at 70kDa, and 7 of the total 8 demonstrated a further band at approximately 30kDa. Cross‐reactivity was also observed with a different strain of the same Streptococcus spp. An increase in the proportion of peripheral α4+β7+ T cells (p&lt;0.05) was seen in PDS patients (n=4) but not in EPS (n=3) or EPS/PDS overlap (n=3) patients.Our data suggest an adaptive immune response against duodenal Streptococcus spp. in PDS but not EPS patients. In addition, PDS patients had significantly higher proportions of circulating gut‐homing T cells. These data suggest that PDS is the result of altered microbiota‐immune interactions. With further work, this finding may become a diagnostic indicator of PDS, and provide further insight into the mechanisms that drive FD.Support or Funding InformationNational Health and Medical Research Council Project Grant.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Depressive symptom composites associated with cortisol stress reactivity in adolescents

BackgroundAltered hypothalamic-pituitary-adrenal (HPA) function is common in youth with major depressive disorder (MDD) but variability in the strength and direction of HPA alterations has prompted a search for symptom-based subtypes with unique neuroendocrine signatures. This study investigated the extent to which depressive symptom composites were differentially associated with cortisol responses to psychosocial stress. MethodsThis study examined salivary cortisol responses to the Trier Social Stress Test (TSST) in 145 adolescents who varied in their risk for MDD: 38 had current MDD; 35 were healthy but at high risk for MDD based on having one or both parents with unipolar MDD; and 72 were healthy youth with no personal or family history of a psychiatric disorder. Multilevel models examined within-person change in cortisol levels during a 2-h resting phase prior to the TSST and both linear and quadratic changes in cortisol levels following the TSST. ResultsAnticipatory cortisol reactivity was lower in MDD youth compared to low-risk youth, and in youth with higher compared to lower depressive symptom severity. Whereas affective symptoms were associated with increased anticipatory cortisol reactivity and more rapid recovery to the TSST, neurovegetative symptoms were associated with decreased anticipatory cortisol reactivity and slower recovery. LimitationsThe cross-sectional design does not permit inferences regarding temporal relations between cortisol responses and depressive symptom composites. ConclusionsThe present findings suggest that heterogeneity among studies examining HPA reactivity in depressed youth may be driven, in part, by differences in depressive symptom composites across samples.

6.100 DEPRESSIVE SYMPTOM PROFILES ASSOCIATED WITH CORTISOL STRESS REACTIVITY IN ADOLESCENTS

Altered hypothalamic-pituitary-adrenal (HPA) function is common in youth with MDD, but variability in the strength and direction of HPA alterations has prompted a search for symptom-based subtypes with unique neuroendocrine signatures. The purpose of this study was to investigate whether depressive symptom profiles were associated differentially with cortisol responses to psychosocial stress.

Social disinhibition is a heritable subphenotype of tics in Tourette syndrome.

To identify heritable symptom-based subtypes of Tourette syndrome (TS). Forty-nine motor and phonic tics were examined in 3,494 individuals (1,191 TS probands and 2,303 first-degree relatives). Item-level exploratory factor and latent class analyses (LCA) were used to identify tic-based subtypes. Heritabilities of the subtypes were estimated, and associations with clinical characteristics were examined. A 6-factor exploratory factor analysis model provided the best fit, which paralleled the somatotopic representation of the basal ganglia, distinguished simple from complex tics, and separated out socially disinhibited and compulsive tics. The 5-class LCA model best distinguished among the following groups: unaffected, simple tics, intermediate tics without social disinhibition, intermediate with social disinhibition, and high rates of all tic types. Across models, a phenotype characterized by high rates of social disinhibition emerged. This phenotype was associated with increased odds of comorbid psychiatric disorders, in particular, obsessive-compulsive disorder and attention-deficit/hyperactivity disorder, earlier age at TS onset, and increased tic severity. The heritability estimate for this phenotype based on the LCA was 0.53 (SE 0.08, p 1.7 × 10(-18)). Expanding on previous modeling approaches, a series of TS-related phenotypes, including one characterized by high rates of social disinhibition, were identified. These phenotypes were highly heritable and may reflect underlying biological networks more accurately than traditional diagnoses, thus potentially aiding future genetic, imaging, and treatment studies.

The identification of symptom-based subtypes of depression: A nationally representative cohort study

BackgroundIn recent years, researchers have used various techniques to elucidate the heterogeneity in depressive symptoms. This study seeks to resolve the extent to which variations in depression reflect qualitative differences between symptom categories and/or quantitative differences in severity. MethodsData were used from the Netherlands Mental Health Survey and Incidence Study-2, a nationally representative face-to-face survey of the adult general population. In a subsample of respondents with a lifetime key symptom of depression at baseline and who participated in the first two waves (n=1388), symptom profiles at baseline were based on symptoms reported during their worst lifetime depressive episode. Depressive symptoms and DSM-IV diagnoses were assessed with the Composite International Diagnostic Interview 3.0. Three latent variable techniques (latent class analysis, factor analysis, factor mixture modelling) were used to identify the best subtyping model. ResultsA latent class analysis, adjusted for local dependence between weight change and appetite change, described the data best and resulted in four distinct depressive subtypes: severe depression with anxiety (28.0%), moderate depression with anxiety (29.3%), moderate depression without anxiety (23.6%) and mild depression (19.0%). These classes showed corresponding clinical correlates at baseline and corresponding course and outcome indicators at follow-up (i.e., class severity was linked to lifetime mental disorders at baseline, and service use for mental health problems and current disability at follow-up). LimitationsAlthough the sample was representative of the population on most parameters, the findings are not generalisable to the most severely affected depressed patients. ConclusionsDepression could best be described in terms of both qualitative differences between symptom categories and quantitative differences in severity. In particular anxiety was a distinguishing feature within moderate depression. This study stresses the central position anxiety occupies in the concept of depression.

Symptom-Based Subtypes of Postnatal Depression

Background: Despite a long history of debate regarding subtypes of depression, there have been no attempts to examine subtypes of Postnatal Depression (PND) on the basis of symptom profiles. Method: 413 mothers admitted to a residential program for unsettled infant behaviour completed a structured clinical interview for current and lifetime depressive and anxiety disorder diagnosis, self-report symptom measures and a range of self-report questionnaires relating to known depression risk/vulnerability factors. From this larger sample, a ‘depressed’ subsample (n = 159) was selected on the basis of interview and symptom-based questionnaire data. Results: Five symptom-based factors were identified (‘cognitive features of depression’, ‘physiological features of anxiety’, ‘emotional / affective features of depression’, ‘cognitive features of anxiety’ and ‘fatigue’). Three clusters differing in terms of depressive symptom severity were identified, with the severest cluster also being characterized by elevated levels of anxiety. There were no differences between the clusters with respect to the type of symptoms reported or vulnerability / risk factors. Conclusion: This study found no evidence of qualitatively distinct symptom-based subtypes of PND, therefore adding to the growing body of evidence suggesting that depression is a uni-dimensional construct.