A systematic comparison of FOSL1, FOSL2 and BATF-mediated transcriptional regulation during early human Th17 differentiation.

Th17 cells are essential for protection against extracellular pathogens, but their aberrant activity can cause autoimmunity. Molecular mechanisms that dictate Th17 cell-differentiation have been extensively studied using mouse models. However, species-specific differences underscore the need to validate these findings in human. Here, we characterized the human-specific roles of three AP-1 transcription factors, FOSL1, FOSL2 and BATF, during early stages of Th17 differentiation. Our results demonstrate that FOSL1 and FOSL2 co-repress Th17 fate-specification, whereas BATF promotes the Th17 lineage. Strikingly, FOSL1 was found to play different roles in human and mouse. Genome-wide binding analysis indicated that FOSL1, FOSL2 and BATF share occupancy over regulatory regions of genes involved in Th17 lineage commitment. These AP-1 factors also share their protein interacting partners, which suggests mechanisms for their functional interplay. Our study further reveals that the genomic binding sites of FOSL1, FOSL2 and BATF harbour hundreds of autoimmune disease-linked SNPs. We show that many of these SNPs alter the ability of these transcription factors to bind DNA. Our findings thus provide critical insights into AP-1-mediated regulation of human Th17-fate and associated pathologies.

A multi-modality and multi-dyad approach to measuring flexibility in psychotherapy.

INTRODUCTION: Flexibility, the ability of an individual to adapt to environmental changes in ways that facilitate goal attainment, has been proposed as a potential mechanism underlying psychopathology and psychotherapy. In psychotherapy, most findings are based on self-report measures that have important limitations. We propose a multimodal, multi-dyad approach based on a nonlinear dynamical systems framework to capture the complexity of this concept. METHOD: A new research paradigm was designed to explore the validity of the proposed conceptual model. The paradigm includes a psychotherapy-like social interaction, during which body movement and facial expressiveness data were collected. We analyzed the data using Hankel Alternative View of Koopmann analysis to reconstruct attractors of the observed behaviors and compare them. RESULTS: The patterns of behavior in the two cases differ, and differences in the reconstructed attractors correspond with differences in self-report measures and behavior in the interactions. CONCLUSIONS: The case studies show that information provided by a single modality is not enough to provide the full picture, and multiple modalities are needed. These observations can serve as an initial support for our claims that a multi-modal and multi-dyad approach to flexibility can address some of the issues of measurement in the field.

Targeted serum proteomics of longitudinal samples from newly diagnosed youth with type 1 diabetes distinguishes markers of disease and C-peptide trajectory.

AIMS/HYPOTHESIS: There is a growing need for markers that could help indicate the decline in beta cell function and recognise the need and efficacy of intervention in type 1 diabetes. Measurements of suitably selected serum markers could potentially provide a non-invasive and easily applicable solution to this challenge. Accordingly, we evaluated a broad panel of proteins previously associated with type 1 diabetes in serum from newly diagnosed individuals during the first year from diagnosis. To uncover associations with beta cell function, comparisons were made between these targeted proteomics measurements and changes in fasting C-peptide levels. To further distinguish proteins linked with the disease status, comparisons were made with measurements of the protein targets in age- and sex-matched autoantibody-negative unaffected family members (UFMs). METHODS: Selected reaction monitoring (SRM) mass spectrometry analyses of serum, targeting 85 type 1 diabetes-associated proteins, were made. Sera from individuals diagnosed under 18 years (n=86) were drawn within 6 weeks of diagnosis and at 3, 6 and 12 months afterwards (288 samples in total). The SRM data were compared with fasting C-peptide/glucose data, which was interpreted as a measure of beta cell function. The protein data were further compared with cross-sectional SRM measurements from UFMs (n=194). RESULTS: Eleven proteins had statistically significant associations with fasting C-peptide/glucose. Of these, apolipoprotein L1 and glutathione peroxidase 3 (GPX3) displayed the strongest positive and inverse associations, respectively. Changes in GPX3 levels during the first year after diagnosis indicated future fasting C-peptide/glucose levels. In addition, differences in the levels of 13 proteins were observed between the individuals with type 1 diabetes and the matched UFMs. These included GPX3, transthyretin, prothrombin, apolipoprotein C1 and members of the IGF family. CONCLUSIONS/INTERPRETATION: The association of several targeted proteins with fasting C-peptide/glucose levels in the first year after diagnosis suggests their connection with the underlying changes accompanying alterations in beta cell function in type 1 diabetes. Moreover, the direction of change in GPX3 during the first year was indicative of subsequent fasting C-peptide/glucose levels, and supports further investigation of this and other serum protein measurements in future studies of beta cell function in type 1 diabetes.

Fear Avoidance Beliefs in Upper-Extremity Musculoskeletal Pain Conditions: Secondary Analysis of a Prospective Clinical Study on Digital Care Programs.

BACKGROUND: Fear-avoidance beliefs (FAB) have been associated with poorer prognosis and decreased adherence to exercise-based treatments in musculoskeletal (MSK) pain. However, the impact of high FAB on adherence and outcomes in upper extremity MSK (UEMSK) pain is poorly explored, particularly through exercise-based digital care programs (DCP). OBJECTIVE: Assess the adherence levels, clinical outcomes and satisfaction in patients with UEMSK pain and elevated FAB after a fully remote multimodal DCP. Associations between FABQ-PA and clinical outcomes were conducted. METHODS: Secondary analysis of an ongoing clinical trial. Participants with UEMSK pain (shoulder, elbow, and wrist/hand) and elevated FAB-physical activity (FABQ-PA ≥ 15) were included. Adherence (completion rate, sessions/week, total exercise time) and mean change in clinical outcomes-disability (QuickDASH), numerical pain score, FABQ-PA, anxiety (GAD-7), and depression (PHQ-9)-between baseline and end-of-program were assessed. Associations between FABQ-PA and clinical outcomes were conducted. RESULTS: 520 participants were included, with mean baseline FABQ-PA of 18.02 (SD 2.77). Patients performed on average 29.3 exercise sessions (2.8 sessions/week), totalizing 338.2 exercise minutes. Mean satisfaction was 8.5/10 (SD 1.7). Significant improvements were observed in all clinical outcomes. Higher baseline FAB were associated with higher baseline disability (P < .001), and smaller improvements in disability (P < .001) and pain (P = .001). Higher engagement was associated with greater improvements in FABQ-PA (P = .043) and pain (P = 0.009). CONCLUSIONS: This study provides evidence of the potential benefits of a structured and multimodal home-based DCP in the management of UEMSK pain conditions in patients with elevated FAB in a real-world context.

The Mediating Role of Affective States in Short-Term Effects of Activity Engagement on Working Memory in Older Age.

INTRODUCTION: It has been shown that activity engagement is associated with cognitive ability in older age, but mechanisms behind the associations have rarely been examined. Following a recent study which showed short-term effects of activity engagement on working memory performance appearing 6 h later, this study examined the mediating role of affective states in this process. METHODS: For 7 times per day over 2 weeks, 150 Swiss older adults (aged 65-91 years) reported their present (sociocognitive/passive leisure) activities and affective states (high-arousal positive, low-arousal positive, high-arousal negative, and low-arousal negative) and completed an ambulatory working memory task on a smartphone. RESULTS: Multilevel vector autoregression models showed that passive leisure activities were associated with worse working memory performance 6 h later. Passive leisure activities were negatively associated with concurrent high-arousal positive affect (and high-arousal negative affect); high-arousal positive affect was negatively associated with working memory performance 6 h later. A Sobel test showed a significant mediation effect of high-arousal positive affect linking the time-lagged relationship between passive leisure activities and working memory. Additionally, sociocognitive activities were associated with better working memory performance 6 h later. Sociocognitive activities were associated with concurrent higher high- and low-arousal positive affect, which, however, were not associated with working memory performance 6 h later. Thus, a mediation related to sociocognitive activities was not found. DISCUSSION: Passive leisure activities could influence working memory performance through high-arousal positive affect within a timeframe of several hours. Results are discussed in relation to an emotional, and possibly a neuroendocrine, pathway explaining the time-lagged effects of affective states on working memory performance.

Comparing Digital to Conventional Physical Therapy for Chronic Shoulder Pain: Randomized Controlled Trial.

BACKGROUND: Chronic shoulder pain (CSP) is a common condition with various etiologies, including rotator cuff disorders, adhesive capsulitis, shoulder instability, and shoulder arthritis. It is associated with substantial disability and psychological distress, resulting in poor productivity and quality of life. Physical therapy constitutes the mainstay treatment for CSP, but several barriers exist in accessing care. In recent years, telerehabilitation has gained momentum as a potential solution to overcome such barriers. It has shown numerous benefits, including improving access and convenience, promoting patient adherence, and reducing costs. However, to date, no previous randomized controlled trial has compared fully remote digital physical therapy to in-person rehabilitation for nonoperative CSP. OBJECTIVE: The aim of this study is to compare clinical outcomes between digital physical therapy and conventional in-person physical therapy in patients with CSP. METHODS: We conducted a single-center, parallel-group, randomized controlled trial involving 82 patients with CSP referred for outpatient physical therapy. Participants were randomized into digital or conventional physical therapy (8-week interventions). The digital intervention consisted of home exercise, education, and cognitive behavioral therapy (CBT), using a device with movement digitalization for biofeedback and asynchronous physical therapist monitoring through a cloud-based portal. The conventional group received in-person physical therapy, including exercises, manual therapy, education, and CBT. The primary outcome was the change (baseline to 8 weeks) in function and symptoms using the short-form of Disabilities of the Arm, Shoulder, and Hand questionnaire. Secondary outcome measures included self-reported pain, surgery intent, analgesic intake, mental health, engagement, and satisfaction. All questionnaires were delivered electronically. RESULTS: A total of 90 participants were randomized into digital or conventional physical therapy, with 82 receiving the allocated intervention. Both groups experienced significant improvements in function measured by the short-form of the Disabilities of the Arm, Shoulder, and Hand questionnaire, with no differences between groups (-1.8, 95% CI -13.5 to 9.8; P=.75). For secondary outcomes, no differences were observed in surgery intent, analgesic intake, and mental health or worst pain. Higher reductions were observed in average and least pain in the conventional group, which, given the small effect sizes (least pain 0.15 and average pain 0.16), are unlikely to be clinically meaningful. High adherence and satisfaction were observed in both groups, with no adverse events. CONCLUSIONS: This study shows that fully remote digital programs can be viable care delivery models for CSP given their scalability and effectiveness, assessed through comparison with high-dosage in-person rehabilitation. TRIAL REGISTRATION: ClinicalTrials.gov (NCT04636528); https://clinicaltrials.gov/study/NCT04636528.

Extracting Nonlinear Dynamics from Psychological and Behavioral Time Series Through HAVOK Analysis.

Analytical methods derived from nonlinear dynamical systems, complexity, and chaos theories offer researchers a framework for in-depth analysis of time series data. However, relatively few studies involving time series data obtained from psychological and behavioral research employ such methods. This paucity of application is due to a lack of general analysis frameworks for modeling time series data with strong nonlinear components. In this article, we describe the potential of Hankel alternative view of Koopman (HAVOK) analysis for solving this issue. HAVOK analysis is a unified framework for nonlinear dynamical systems analysis of time series data. By utilizing HAVOK analysis, researchers may model nonlinear time series data in a linear framework while simultaneously reconstructing attractor manifolds and obtaining a secondary time series representing the amount of nonlinear forcing occurring in a system at any given time. We begin by showing the mathematical underpinnings of HAVOK analysis and then show example applications of HAVOK analysis for modeling time series data derived from real psychological and behavioral studies.

Stability and spread: A novel method for quantifying transitions within multivariate binary time series data.

We present a novel method for quantifying transitions within multivariate binary time series data, using a sliding series of transition matrices, to derive metrics of stability and spread. We define stability as the trace of a transition matrix divided by the sum of all observed elements within that matrix. We define spread as the number of all non-zero cells in a transition matrix divided by the number of all possible cells in that matrix. We developed this method to allow investigation into high-dimensional, sparse data matrices for which existing binary time series methods are not designed. Results from 1728 simulations varying six parameters suggest that unique information is captured by both metrics, and that stability and spread values have a moderate inverse association. Further, simulations suggest that this method can be reliably applied to time series with as few as nine observations per person, where at least five consecutive observations construct each overlapping transition matrix, and at least four time series variables compose each transition matrix. A pre-registered application of this method using 4 weeks of ecological momentary assessment data (N = 110) showed that stability and spread in the use of 20 emotion regulation strategies predict next timepoint affect after accounting for affect and anxiety's auto-regressive and cross-lagged effects. Stability, but not spread, also predicted next timepoint anxiety. This method shows promise for meaningfully quantifying two unique aspects of switching behavior in multivariate binary time series data.

Nonverbal Synchrony: An Indicator of Clinical Communication Quality in Racially-Concordant and Racially-Discordant Oncology Interactions.

OBJECTIVES: The aim of this cross-sectional study was to apply a novel software to measure and compare levels of nonverbal synchrony, as a potential indicator of communication quality, in video recordings of racially-concordant and racially-discordant oncology interactions. Predictions include that the levels of nonverbal synchrony will be greater during racially-concordant interactions than racially-discordant interactions, and that levels of nonverbal synchrony will be associated with traditional measures of communication quality in both racially-concordant and racially-discordant interactions. DESIGN: This is a secondary observational analysis of video-recorded oncology treatment discussions collected from 2 previous studies. SETTING: Two National Cancer Institute-designated Comprehensive Cancer Centers and another large urban cancer center. PARTICIPANTS: Participants from Study 1 include 161 White patients with cancer and 11 White medical oncologists. Participants from Study 2 include 66 Black/African-American patients with cancer and 17 non-Black medical oncologists. In both studies inclusion criteria for patients was a recent cancer diagnosis; in Study 2 inclusion criteria was identifying as Black/African American. MAIN OUTCOME MEASURES: Nonverbal synchrony and communication quality. RESULTS: Greater levels of nonverbal synchrony were observed in racially-discordant interactions than in racially-concordant interactions. Levels of nonverbal synchrony were associated with indicators of communication quality, and these associations were more consistently found in racially-discordant interactions. CONCLUSION: This study advances clinical communication and disparities research by successfully applying a novel approach capturing the unconscious nature of communication, and revealing differences in communication in racially-discordant and racially-concordant oncology interactions. This study highlights the need for further exploration of nonverbal aspects relevant to patient-physician interactions.

Impacts of Digital Care Programs for Musculoskeletal Conditions on Depression and Work Productivity: Longitudinal Cohort Study.

BACKGROUND: Comorbidity between musculoskeletal (MSK) pain and depression is highly common, and is associated with a greater symptom burden and greater loss of work productivity than either condition alone. Multimodal care programs tackling both physical and mental health components may maximize productivity recovery and return to work. Digital delivery of such programs can facilitate access, ensure continuity of care, and enhance patient engagement. OBJECTIVE: The aim of this study was to assess the impact of a completely remote multimodal digital care program (DCP) for MSK pain on mental health and work-related outcomes stratified by baseline depression levels. METHODS: Ad hoc analysis of an interventional, single-arm, cohort study of individuals with MSK pain undergoing a DCP was performed. Three subgroups with different baseline depression severity levels were established based on responses to the Patient Health Questionnaire (PHQ-9): cluster 1 (score<5: minimal depression), cluster 2 (scores 5-10: mild depression), and cluster 3 (score≥10: moderate depression). The mean changes in depression, anxiety, fear-avoidance beliefs, work productivity, and activity impairment and adherence between baseline and end of program (8-12 weeks) were assessed across subgroups by latent growth curve analysis. RESULTS: From a total of 7785 eligible participants, 6137 (78.83%) were included in cluster 1, 1158 (14.87%) in cluster 2, and 490 (6.29%) in cluster 3. Significant improvements in depression and anxiety scores were observed in clusters 2 and 3 but not in cluster 1, with average end-of-the program scores in clusters 2 and 3 below the initially defined cluster thresholds (score of 5 and 10, respectively). All clusters reported significant improvements in productivity impairment scores (mean changes from -16.82, 95% CI -20.32 to -13.42 in cluster 1 to -20.10, 95% CI -32.64 to -7.57 in cluster 3). Higher adherence was associated with higher improvements in depression in clusters 2 and 3, and with greater recovery in activities of daily living in cluster 3. Overall patient satisfaction was 8.59/10.0 (SD 1.74). CONCLUSIONS: A multimodal DCP was able to promote improvements in productivity impairment scores comparable to those previously reported in the literature, even in participants with comorbid depression and anxiety. These results reinforce the need to follow a biopsychosocial framework to optimize outcomes in patients with MSK pain. TRIAL REGISTRATION: ClinicalTrials.gov NCT04092946; https://clinicaltrials.gov/ct2/show/NCT04092946.

Racial and Ethnic Differences in Outcomes of a 12-Week Digital Rehabilitation Program for Musculoskeletal Pain: Prospective Longitudinal Cohort Study.

BACKGROUND: Musculoskeletal (MSK) pain disproportionately affects people from different ethnic backgrounds through higher burden and less access to care. Digital care programs (DCPs) can improve access and help reduce inequities. However, the outcomes of such programs based on race and ethnicity have yet to be studied. OBJECTIVE: We aimed to assess the impact of race and ethnicity on engagement and outcomes in a multimodal DCP for MSK pain. METHODS: This was an ad hoc analysis of an ongoing decentralized single-arm investigation into engagement and clinical-related outcomes after a multimodal DCP in patients with MSK conditions. Patients were stratified by self-reported racial and ethnic group, and their engagement and outcome changes between baseline and 12 weeks were compared using latent growth curve analysis. Outcomes included program engagement (number of sessions), self-reported pain scores, likelihood of surgery, Generalized Anxiety Disorder 7-item scale, Patient Health Questionnaire 9-item, and Work Productivity and Activity Impairment. A minimum clinically important difference (MCID) of 30% was calculated for pain, and multivariable logistic regression was performed to evaluate race as an independent predictor of meeting the MCID. RESULTS: A total of 6949 patients completed the program: 65.5% (4554/6949) of them were non-Hispanic White, 10.8% (749/6949) were Black, 9.7% (673/6949) were Asian, 9.2% (636/6949) were Hispanic, and 4.8% (337/6949) were of other racial or ethnic backgrounds. The population studied was diverse and followed the proportions of the US population. All groups reported high engagement and satisfaction, with Hispanic and Black patients ranking first among satisfaction despite lower engagement. Black patients had a higher likelihood to drop out (odds ratio [OR] 1.19, 95% CI 1.01-1.40, P=.04) than non-Hispanic White patients. Hispanic and Black patients reported the highest level of pain, surgical intent, work productivity, and impairment in activities of daily living at baseline. All race groups showed a significant improvement in all outcomes, with Black and Hispanic patients reporting the greatest improvements in clinical outcomes. Hispanic patients also had the highest response rate for pain (75.8%) and a higher OR of meeting the pain MCID (OR 1.74, 95% CI 1.24-2.45, P=.001), when compared with non-Hispanic White patients, independent of age, BMI, sex, therapy type, education level, and employment status. No differences in mental health outcomes were found between race and ethnic groups. CONCLUSIONS: This study advocates for the utility of a DCP in improving access to MSK care and promoting health equity. Engagement and satisfaction rates were high in all the groups. Black and Hispanic patients had higher MSK burden at baseline and lower engagement but also reported higher improvements, with Hispanic patients presenting a higher likelihood of pain improvement.

Examining the dynamic nature of nonverbal communication between Black patients with cancer and their oncologists.

BACKGROUND: Although communication quality is associated with patient outcomes, racial disparities in communication exist, disproportionately burdening Black patients. However, most communication research focuses on verbal behaviors in predominantly White patient populations. We used a newly developed and theory-guided network analysis that examines the dynamic interplay and behavioral convergence and divergence between Black patients with cancer and their oncologists during cancer treatment discussions. METHODS: We applied a nonverbal behavioral coding system to thin slices of video recordings of Black patients and their oncologists discussing treatment. We then estimated 3 networks: 1) a temporal network to determine whether a nonverbal behavior predicts another nonverbal behavior at the next time point in an interaction, and how much each nonverbal behavior influences other nonverbal behaviors and is influenced by other nonverbal behaviors; 2) a contemporaneous network to determine whether a nonverbal behavior co-occurs with other nonverbal behaviors at the same time point in an interaction; and 3) a between-dyads network to examine the covariation between nonverbal behaviors across all dyads. RESULTS: Black patients (n = 74) and their non-Black physicians (n = 15) showed a mix of convergence and divergence in their nonverbal behaviors at the same points in time, from one time point to the next, and across dyads. Across analyses, convergence was most likely to occur when physicians matched their behaviors to their patients; especially with smiling, gaze, leaning, and laughter behaviors. CONCLUSION: Our findings reveal patterns of modifiable behaviors that can potentially inform interventions to reduce disparities in clinical communication and, in turn, treatment and mortality disparities.

Quantitative proteomic characterization and comparison of T helper 17 and induced regulatory T cells.

The transcriptional network and protein regulators that govern T helper 17 (Th17) cell differentiation have been studied extensively using advanced genomic approaches. For a better understanding of these biological processes, we have moved a step forward, from gene- to protein-level characterization of Th17 cells. Mass spectrometry-based label-free quantitative (LFQ) proteomics analysis were made of in vitro differentiated murine Th17 and induced regulatory T (iTreg) cells. More than 4,000 proteins, covering almost all subcellular compartments, were detected. Quantitative comparison of the protein expression profiles resulted in the identification of proteins specifically expressed in the Th17 and iTreg cells. Importantly, our combined analysis of proteome and gene expression data revealed protein expression changes that were not associated with changes at the transcriptional level. Our dataset provides a valuable resource, with new insights into the proteomic characteristics of Th17 and iTreg cells, which may prove useful in developing treatment of autoimmune diseases and developing tumor immunotherapy.

Entropy Fit Indices: New Fit Measures for Assessing the Structure and Dimensionality of Multiple Latent Variables.

The accurate identification of the content and number of latent factors underlying multivariate data is an important endeavor in many areas of Psychology and related fields. Recently, a new dimensionality assessment technique based on network psychometrics was proposed (Exploratory Graph Analysis, EGA), but a measure to check the fit of the dimensionality structure to the data estimated via EGA is still lacking. Although traditional factor-analytic fit measures are widespread, recent research has identified limitations for their effectiveness in categorical variables. Here, we propose three new fit measures (termed entropy fit indices) that combines information theory, quantum information theory and structural analysis: Entropy Fit Index (EFI), EFI with Von Neumman Entropy (EFI.vn) and Total EFI.vn (TEFI.vn). The first can be estimated in complete datasets using Shannon entropy, while EFI.vn and TEFI.vn can be estimated in correlation matrices using quantum information metrics. We show, through several simulations, that TEFI.vn, EFI.vn and EFI are as accurate or more accurate than traditional fit measures when identifying the number of simulated latent factors. However, in conditions where more factors are extracted than the number of factors simulated, only TEFI.vn presents a very high accuracy. In addition, we provide an applied example that demonstrates how the new fit measures can be used with a real-world dataset, using exploratory graph analysis.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling.

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

Pulmonary sarcoidosis is associated with exosomal vitamin D-binding protein and inflammatory molecules.

BACKGROUND: Sarcoidosis is an inflammatory granulomatous disorder characterized by accumulation of TH1-type CD4+ T cells and immune effector cells within affected organs, most frequently the lungs. Exosomes are extracellular vesicles conveying intercellular communication with possible diagnostic and therapeutic applications. OBJECTIVES: We aimed to provide an understanding of the proinflammatory role of bronchoalveolar lavage fluid (BALF) exosomes in patients with sarcoidosis and to find candidates for disease biomarkers. METHODS: We performed a mass spectrometric proteomics characterization of BALF exosomes from 15 patients with sarcoidosis and 5 healthy control subjects and verified the most interesting results with flow cytometry, ELISA, and Western blot analyses in an additional 39 patients and 22 control subjects. RESULTS: More than 690 proteins were identified in the BALF exosomes, several of which displayed significant upregulation in patients, including inflammation-associated proteins, such as leukotriene A4 hydrolase. Most of the complement-activating factors were upregulated, whereas the complement regulator CD55 was seen less in patients compared with healthy control subjects. In addition, for the first time, we detected vitamin D-binding protein in BALF exosomes, which was more abundant in patients. To evaluate exosome-associated vitamin D-binding protein as a biomarker for sarcoidosis, we investigated plasma exosomes from 23 patients and 11 healthy control subjects and found significantly higher expression in patients. CONCLUSION: Together, these data contribute to understanding the role of exosomes in lung disease and provide suggestions for highly warranted sarcoidosis biomarkers. Furthermore, the validation of an exosome-associated biomarker in the blood of patients provides novel, and less invasive, opportunities for disease diagnosis.

The progress and potential of proteomic biomarkers for type 1 diabetes in children.

INTRODUCTION: Although it is possible to identify the genetic risk for type 1 diabetes (T1D), it is not possible to predict who will develop the disease. New biomarkers are needed that would help understand the mechanisms of disease onset and when to administer targeted therapies and interventions. Areas covered: An overview is presented of international study efforts towards understanding the cause of T1D, including the collection of several extensive temporal sample series that follow the development of T1D in at risk children. The results of the proteomics analysis of these materials are presented, which have included bodily fluids, such as serum or plasma and urine, as well as tissue samples from the pancreas. Expert commentary: Promising recent reports have indicated detection of early proteomic changes in the serum of patients prior to diagnosis, potentially providing new measures for risk assessment. Similarly, there has been evidence that post-translational modification (PTM) may result in the recognition of islet cell proteins as autoantigens; modified proteins could thus be used as targets for immunomodulation to overcome the threat of the autoimmune response.

Early signs of disease in type 1 diabetes.

As a severe chronic disease with long-term complications, type 1 diabetes (T1D) is a burden to the patients and their families as well as a challenge to the health care system. T1D is a heterogeneous disease with a variety of etiologies and a wide range in the rate of progression to the disease. In order to prevent and treat T1D it would be important to identify measures that could be used to predict and monitor disease progression, as well as to further understand the molecular mechanisms involved. During the past 20 yr since its initiation, the Finnish Diabetes Prediction and Prevention Project (DIPP) has collected longitudinal biological samples from children with a human leukocyte antigen gene-conferred risk of T1D. This large sample collection has provided detailed sample series that enable studies to map the progression from health to disease, as well as the healthy maturation of risk-matched children. The DIPP samples have been used in a large body of research to elucidate the factors involved in the development of T1D. Interestingly, results from recent studies exploiting omics platforms have revealed that signs of the disease process can be detected very early on, even prior to appearance of the first T1D-associated antibodies, which are currently considered the earliest indications of the emerging disease. Identification and validation of multi-modal molecular markers will we hope provide a means to subgroup the heterogeneous group of T1D patients and enable prediction, diagnosis, and monitoring of T1D. Discovery of such markers is important in the design and testing of prevention and therapies for T1D.

Activity Diversity and Well-Being in Daily Life: Evidence for Heterogeneity Between Older Adults.

OBJECTIVES: Although higher activity diversity is associated with higher well-being at the between-person level, it is unknown whether a day with higher activity diversity is related to higher well-being within persons. Within 24 hr per day, there are a limited number of activities on which individuals could spend their time and energy. Personal resources could influence the expenditure of energy and thus the experience with daily activities. This study examined daily associations between activity diversity and well-being and whether age and self-related health moderated the associations. METHODS: For seven times per day over 2 weeks, 129 retired older adults (Mage = 73.9 years, SDage = 5.6) reported their present activity engagement and positive and negative affect. Daily activity diversity was operationalized as the number of different activity types reported per day. Daily positive and negative affect were assessed as the average of a range of high- and low-arousal affective states. Self-rated health was assessed with an item from the 12-Item Short-Form Health Survey at baseline. RESULTS: Multilevel models showed that daily activity diversity was unrelated, on average, to daily positive or negative affect at the between- and within-person levels. Daily activity diversity was associated with lower daily positive affect in participants with lower self-rated health, but the Johnson-Neyman regions of significance were outside of the range of observed data. DISCUSSION: Divergent patterns were observed in the within-person associations between activity diversity and well-being across participants. Results are discussed in the context of time use and well-being in older age.