HIC1 interacts with FOXP3 multi protein complex: Novel pleiotropic mechanisms to regulate human regulatory T cell differentiation and function

Transcriptional repressor, hypermethylated in cancer 1 (HIC1) participates in a range of important biological processes, such as tumor repression, immune suppression, embryonic development and epigenetic gene regulation. Further to these, we previously demonstrated that HIC1 provides a significant contribution to the function and development of regulatory T (Treg) cells. However, the mechanism by which it regulates these processes was not apparent. To address this question, we used affinity-purification mass spectrometry to characterize the HIC1 interactome in human Treg cells. Altogether 61 high-confidence interactors were identified, including IKZF3, which is a key transcription factor in the development of Treg cells. The biological processes associated with these interacting proteins include protein transport, mRNA processing, non-coding (ncRNA) transcription and RNA metabolism. The results revealed that HIC1 is part of a FOXP3-RUNX1-CBFB protein complex that regulates Treg signature genes thus improving our understanding of HIC1 function during early Treg cell differentiation.

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.

Serum APOC1 levels are decreased in young autoantibody positive children who rapidly progress to type 1 diabetes

Better understanding of the early events in the development of type 1 diabetes is needed to improve prediction and monitoring of the disease progression during the substantially heterogeneous presymptomatic period of the beta cell damaging process. To address this concern, we used mass spectrometry-based proteomics to analyse longitudinal pre-onset plasma sample series from children positive for multiple islet autoantibodies who had rapidly progressed to type 1 diabetes before 4 years of age (n = 10) and compared these with similar measurements from matched children who were either positive for a single autoantibody (n = 10) or autoantibody negative (n = 10). Following statistical analysis of the longitudinal data, targeted serum proteomics was used to verify 11 proteins putatively associated with the disease development in a similar yet independent and larger cohort of children who progressed to the disease within 5 years of age (n = 31) and matched autoantibody negative children (n = 31). These data reiterated extensive age-related trends for protein levels in young children. Further, these analyses demonstrated that the serum levels of two peptides unique for apolipoprotein C1 (APOC1) were decreased after the appearance of the first islet autoantibody and remained relatively less abundant in children who progressed to type 1 diabetes, in comparison to autoantibody negative children.

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.

Engagement and Utilization of a Complete Remote Digital Care Program for Musculoskeletal Pain Management in Urban and Rural Areas Across the United States: Longitudinal Cohort Study

BACKGROUND

Musculoskeletal (MSK) conditions are the number one cause of disability worldwide. Digital care programs (DCPs) for MSK pain management have arisen as alternative care delivery models to circumvent challenges in accessibility of conventional therapy. Despite the potential of DCPs to reduce inequities in accessing care, the outcomes of such interventions in rural and urban populations have yet to be studied.

OBJECTIVE

The aim of this study was to assess the impact of urban or rural residency on engagement and clinical outcomes after a multimodal DCP for MSK pain.

METHODS

This study consists of an ad hoc analysis of a decentralized single-arm investigation into engagement and clinical-related outcomes after a multimodal DCP in patients with MSK conditions. Patients were coded according to their zip codes to a specific rural-urban commuting area code and grouped into rural and urban cohorts. Changes in their engagement and clinical outcomes from baseline to program end were assessed. Latent growth curve analysis was performed to estimate change trajectories adjusting for the following covariates: age, gender, BMI, employment status, and pain acuity. Outcomes included engagement, self-reported pain, and the results of the Generalized Anxiety Disorder 7-item, Patient Health Questionnaire 9-item, and Work Productivity and Activity Impairment scales. A minimum clinically important difference (MCID) of 30% was considered for pain.

RESULTS

Patients with urban and rural residency across the United States participated in the program (n=9992). A 73.8% (7378/9992) completion rate was observed. Both groups reported high satisfaction scores and similar engagement with exercise sessions, with rural residents showing higher engagement with educational content (P<.001) and higher program completion rates (P=.02). All groups showed a significant improvement in all clinical outcomes, including pain, mental health, and work productivity, without statistically significant intergroup differences. The percentage of patients meeting the MCID was similar in both groups (urban: 67.1%, rural: 68.3%; P=.30).

CONCLUSIONS

This study advocates for the utility of a DCP in improving access to MSK care in urban and rural areas alike, showcasing its potential to promote health equity. High engagement, satisfaction, and completion rates were noted in both groups, as well as significant improvements in clinical outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04092946; https://clinicaltrials.gov/ct2/show/NCT04092946.

DAILY ACTIVITY DIVERSITY AND DAILY WORKING MEMORY IN COMMUNITY-DWELLING OLDER ADULTS

Research has shown that diverse activity engagement has positive effects on cognitive functioning in older age. However, it is unknown whether the positive effect holds within persons across days and across people. We examined daily within-person association between activity diversity and working memory in older age and effects of potential moderators therein. We examined 16-day smartphone-based ambulatory assessment data from 150 older adults (aged 65+). Participants reported their present activities and completed working memory tasks seven times per day. Within persons, higher daily activity diversity was positively associated with higher daily working memory. Moreover, the prior day’s activity diversity led to that day’s higher working memory, but not vice versa. We did not find any moderating effects of age, education, or fluid and crystallized intelligence. Our results strengthen the evidence on the beneficial effect of activity diversity on cognitive performance. Results are discussed in the context of cognitive reserve theory.

Depression and work productivity: insights from a longitudinal cohort study on digital care programs for Musculoskeletal conditions

BACKGROUND

Comorbidity between musculoskeletal (MSK) pain and depression is highly common and associated with greater symptom burden and greater loss of work productivity. 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

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

The present study is an ad-hoc analysis of an interventional, single-arm, cohort study of individuals with MSK pain undergoing a DCP. Three subgroups with different baseline depression severity levels were created based on the Patient Health Questionnaire (PHQ-9): cluster 1 (<5: minimal depression); cluster 2 (5-10: mild depression) and cluster 3 (≥10: moderate depression). The mean change between baseline and end-of-program (8-12 weeks) on depression, anxiety, fear-avoidance beliefs, work productivity and activity impairment and adherence was assessed across subgroups. Outcome changes were analyzed by latent growth curve analysis.

RESULTS

From a total of 7785 eligible participants, 6137 (78.8%) were included in Cluster 1, 1158 (14.9%) in cluster 2 and 490 (6.3%) in cluster 3. Significant improvements in depression and anxiety scores were observed in clusters 2 and 3 but not cluster 1, with average end-of-the program scores in clusters 2 and 3 below the initially defined cluster thresholds (5 and 10 for clusters 2 and 3, 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.

CLINICALTRIAL

ClinicalTrials.gov NCT04092946; https://clinicaltrials.gov/ct2/show/NCT04092946.

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.

Modeling Latent Topics in Social Media using Dynamic Exploratory Graph Analysis: The Case of the Right-wing and Left-wing Trolls in the 2016 US Elections

The past few years were marked by increased online offensive strategies perpetrated by state and non-state actors to promote their political agenda, sow discord, and question the legitimacy of democratic institutions in the US and Western Europe. In 2016, the US congress identified a list of Russian state-sponsored Twitter accounts that were used to try to divide voters on a wide range of issues. Previous research used latent Dirichlet allocation (LDA) to estimate latent topics in data extracted from these accounts. However, LDA has characteristics that may limit the effectiveness of its use on data from social media: The number of latent topics must be specified by the user, interpretability of the topics can be difficult to achieve, and it does not model short-term temporal dynamics. In the current paper, we propose a new method to estimate latent topics in texts from social media termed Dynamic Exploratory Graph Analysis (DynEGA). In a Monte Carlo simulation, we compared the ability of DynEGA and LDA to estimate the number of simulated latent topics. The results show that DynEGA is substantially more accurate than several different LDA algorithms when estimating the number of simulated topics. In an applied example, we performed DynEGA on a large dataset with Twitter posts from state-sponsored right- and left-wing trolls during the 2016 US presidential election. DynEGA revealed topics that were pertinent to several consequential events in the election cycle, demonstrating the coordinated effort of trolls capitalizing on current events in the USA. This example demonstrates the potential power of our approach for revealing temporally relevant information from qualitative text 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.

Momentary Working Memory and Momentary Activities in Healthy Older Adults: The Mediating Role of Affective States

Research has shown cognitive ability in older age is associated with activity engagement, but little is known about what psychological mechanisms are linking the two constructs. This study investigates an emotional pathway, in which affective states mediate the temporal associations between momentary working memory and momentary activities in older age. We examined data from 153 healthy older adults aged 65 to 91 who completed a smartphone-based ambulatory assessment survey seven times a day over 15 days. In each assessment point, participants reported their momentary activities (e.g., social activities, mentally stimulating activities) and affective states (i.e., positive affect, negative affect) and took a working memory task. Initial results suggest that during an approximate time period of six hours (i.e., across three assessment points), working memory performance influences subsequent likelihood of social activity engagement. Moreover, positive affect mediates this temporal association. Results will be discussed in the context of cognitive aging research.

Day-to-Day Mobility, Affect, and Stress Couplings in Swiss Older Adults

The Mobility, Activity, and Social Interactions Study (MOASIS) is part of a global effort to more closely examine indicators of functional ability in relation to person characteristics and life contexts as proposed by the WHO’s healthy aging definition. In MOASIS, sensor-based and self-reported mobility and activity indicators were used to capture functional ability in 153 community-dwelling older adults aged 65-91 over 30 days. The present study examines daily time out-of-home and place diversity and its within-person associations with positive and negative affect and stress. Initial between-person analyses indicate that mobility is only weakly related to indicators of physical and mental health. We propose that the health- and well-being implications of mobility more strongly play out in daily life and at the within-person level, and will examine general health, cognitive ability, and marital status as intrinsic capacity moderators accounting for some of the expected interindividual heterogeneity.

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.

Interactome Networks of FOSL1 and FOSL2 in Human Th17 Cells

Dysregulated function of Th17 cells has implications in immunodeficiencies and autoimmune disorders. Th17 cell differentiation is orchestrated by a complex network of transcription factors, including several members of the activator protein (AP-1) family. Among the latter, FOSL1 and FOSL2 modulate the effector functions of Th17 cells. However, the molecular mechanisms underlying these effects are unclear, owing to the poorly characterized protein interaction networks of FOSL factors. Here, we establish the first interactomes of FOSL1 and FOSL2 in human Th17 cells, using affinity purification-mass spectrometry analysis. In addition to the known JUN proteins, we identified several novel binding partners of FOSL1 and FOSL2. Gene ontology analysis found a significant fraction of these interactors to be associated with RNA-binding activity, which suggests new mechanistic links. Intriguingly, 29 proteins were found to share interactions with FOSL1 and FOSL2, and these included key regulators of Th17 fate. We further validated the binding partners identified in this study by using parallel reaction monitoring targeted mass spectrometry and other methods. Our study provides key insights into the interaction-based signaling mechanisms of FOSL proteins that potentially govern Th17 cell differentiation and associated pathologies.

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.

Protein interactome of the Cancerous Inhibitor of protein phosphatase 2A (CIP2A) in Th17 cells

Cancerous inhibitor of protein phosphatase 2A (CIP2A) is involved in immune response, cancer progression, and Alzheimer's disease. However, an understanding of the mechanistic basis of its function in this wide spectrum of physiological and pathological processes is limited due to its poorly characterized interaction networks. Here we present the first systematic characterization of the CIP2A interactome by affinity-purification mass spectrometry combined with validation by selected reaction monitoring targeted mass spectrometry (SRM-MS) analysis in T helper (Th) 17 (Th17) cells. In addition to the known regulatory subunits of protein phosphatase 2A (PP2A), the catalytic subunits of protein PP2A were found to be interacting with CIP2A. Furthermore, the regulatory (PPP1R18, and PPP1R12A) and catalytic (PPP1CA) subunits of phosphatase PP1 were identified among the top novel CIP2A interactors. Evaluation of the ontologies associated with the proteins in this interactome revealed that they were linked with RNA metabolic processing and splicing, protein traffic, cytoskeleton regulation and ubiquitin-mediated protein degradation processes. Taken together, this network of protein-protein interactions will be important for understanding and further exploring the biological processes and mechanisms regulated by CIP2A both in physiological and pathological conditions.

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The first characterisation of the CIP2A interactome in Th17 ​cells.

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Key interactions validated by targeted SRM-MS proteomics, western blot and confocal microscopy.

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Pathway analysis of the interactome revealed interrelationships with proteins across a broad range of cellular processes.

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The study identifies for the first time the interaction of phosphatase PP1 with CIP2A.

Nonconscious nonverbal synchrony and patient and physician affect and rapport in cancer treatment discussions with black and white patients

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Background: Clinical communication is poorer with Black patients than with White patients, but most studies are limited to verbal communication. Nonverbal synchrony, the nonconscious coordination of movement between individuals, has been shown to reflect relationship quality. We investigated nonverbal synchrony’s association with patient and physician affect and rapport in cancer treatment discussions, and if those associations differed by patient race. Methods: We used motion detection software to measure overall synchrony and synchrony based on who is leading in the interaction (similar to leading in dancing) in video recordings of 68 Black patients and 163 White patients discussing treatment with their physicians. Naïve observers rated the interaction for six constructs: patient and physician positive and negative affect and patient-physician positive and negative rapport. We examined associations between patient race, nonverbal synchrony and the six constructs. Results: In interactions with Black patients, overall synchrony was positively associated with patients’ positive affect and positive patient-physician rapport and negatively associated with patients’ negative affect and negative patient-physician rapport. When the physician was leading, synchrony was positively associated with patients’ positive affect and positive patient-physician rapport and negatively associated with patients’ negative affect and negative patient-physician rapport. When the patient was leading, synchrony was positively associated with patients’ and physicians’ positive affect and positive patient-physician rapport, and negatively associated with patients’ negative affect and negative patient-physician rapport. In interactions with White patients, overall synchrony was positively associated with patient positive affect; when the physician was leading, synchrony was negatively associated with patient negative affect. Conclusions: This is the first study to use a dynamic, jointly-determined measure in patient-physician communication. Synchrony was related to patient and physician affect and rapport in interactions with Black patients, but only patient affect in interactions with White patients, suggesting nonverbal synchrony is particularly important in interactions with Black patients. Next, we will investigate associations with patient outcomes, such as satisfaction. Findings could contribute to physician training to enhance coordination and outcomes in oncology interactions.

Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology

OBJECTIVE

One of the promises of the experience sampling methodology (ESM) is that a statistical analysis of an individual's emotions, cognitions and behaviors in everyday-life could be used to identify relevant treatment targets. A requisite for clinical implementation is that outcomes of such person-specific time-series analyses are not wholly contingent on the researcher performing them.

METHODS

To evaluate this, we crowdsourced the analysis of one individual patient's ESM data to 12 prominent research teams, asking them what symptom(s) they would advise the treating clinician to target in subsequent treatment.

RESULTS

Variation was evident at different stages of the analysis, from preprocessing steps (e.g., variable selection, clustering, handling of missing data) to the type of statistics and rationale for selecting targets. Most teams did include a type of vector autoregressive model, examining relations between symptoms over time. Although most teams were confident their selected targets would provide useful information to the clinician, not one recommendation was similar: both the number (0-16) and nature of selected targets varied widely.

CONCLUSION

This study makes transparent that the selection of treatment targets based on personalized models using ESM data is currently highly conditional on subjective analytical choices and highlights key conceptual and methodological issues that need to be addressed in moving towards clinical implementation.

Nonconscious nonverbal synchrony and patient and physician affect and rapport in cancer treatment discussions with black and white patients

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Background: Clinical communication is poorer with Black patients than with White patients, but most studies are limited to verbal communication. Nonverbal synchrony, the subtle, nonconscious coordination of movement between individuals, has been shown to reflect relationship quality. We investigated nonverbal synchrony’s association with patient and physician affect and rapport in cancer treatment discussions, and if those associations differed by patient race. Methods: We used motion detection software to measure overall synchrony and synchrony based on who is leading in the interaction (similar to leading in dancing) in video recordings of 68 Black patients and 163 White patients discussing treatment with their non-Black physicians. Additionally, naïve observers rated the interaction for six constructs: patient and physician positive and negative affect and patient-physician positive and negative rapport. We examined associations between nonverbal synchrony and the six constructs. Results: In interactions with Black patients, overall synchrony was positively associated with patients’ positive affect and positive patient-physician rapport and negatively associated with patients’ negative affect and negative patient-physician rapport. When the physician was leading, synchrony was positively associated with patients’ positive affect and positive patient-physician rapport and negatively associated with patients’ negative affect and negative patient-physician rapport. When the patient was leading, synchrony was positively associated with patients’ and physicians’ positive affect and positive patient-physician rapport, and negatively associated with patients’ negative affect and negative patient-physician rapport. In interactions with White patients, overall synchrony was positively associated with patient positive affect; when the physician was leading, synchrony was negatively associated with patient negative affect. Conclusions: This is the first study to use an innovative measure of dynamic communication in patient-physician cancer treatment discussions. Nonverbal synchrony was related to patient and physician affect and rapport in interactions with Black patients, but only patient affect in interactions with White patients, suggesting nonverbal synchrony is particularly important in interactions with Black patients. Next steps include investigating associations with patient outcomes (e.g., satisfaction). Findings could contribute to physician training.

CIP2A Constrains Th17 Differentiation by Modulating STAT3 Signaling

Cancerous Inhibitor of Protein Phosphatase 2A (CIP2A) is an oncogene and a potential cancer therapy target protein. Accordingly, a better understanding of the physiological function of CIP2A, especially in the context of immune cells, is a prerequisite for its exploitation in cancer therapy. Here, we report that CIP2A negatively regulates interleukin (IL)-17 production by Th17 cells in human and mouse. Interestingly, concomitant with increased IL-17 production, CIP2A-deficient Th17 cells had increased strength and duration of STAT3 phosphorylation. We analyzed the interactome of phosphorylated STAT3 in CIP2A-deficient and CIP2A-sufficient Th17 cells and indicated together with genome-wide gene expression profiling, a role of Acylglycerol Kinase (AGK) in the regulation of Th17 differentiation by CIP2A. We demonstrated that CIP2A regulates the strength of the interaction between AGK and STAT3, and thereby modulates STAT3 phosphorylation and expression of IL-17 in Th17 cells.

Historical Change in the Moral Foundations of Political Persuasion

How have attempts at political persuasion changed over time? Using nine corpora dating back through 1789, containing over 7 million words of speech (1,666 documents in total), covering three different countries, plus the entire Google nGram corpus, we find that language relating to togetherness permanently crowded out language relating to duties and obligations in the persuasive speeches of politicians during the early 20th century. This shift is temporally predicted by a rise in Western nationalism and the mass movement of people from more rural to more urban areas and is unexplained by changes in language, private political speech, or nonmoral persuasion. We theorize that the emergence of the modern state in the 1920s had psychopolitical consequences for the ways that people understood and communicated their relationships with their government, which was then reflected in the levers of persuasion chosen by political elites.

QUANTIFYING SENSITIVE DEPENDENCE OF INITIAL CONDITION USING STRUCTURAL EQUATION MODELING

Human systems display sensitive dependence of initial condition. That is, even though two individuals may be similar in most regards, small differences between these individuals may have far reaching consequences later in life. In dynamical systems analysis, this sort of behavior is quantified with maximum Lyapunov exponents. These exponents quantify the degree to which small differences in initial condition between two systems affect trajectories of these systems later in time. Current methods for estimating maximum Lyapunov exponents are sensitive to noise and this sensitivity leads to estimation errors when researchers attempt to estimate these exponents on data obtained from human participants. Additionally, most current methods only allow for maximum Lyapunov exponent estimation using univariate time series. In this presentation, we present a method for using structural equation modeling for estimating latent maximum Lyapunov exponents from noisy multivariate time series and discuss applications of this method for analyzing human generated data.

Early childhood infections and the use of antibiotics and antipyretic-analgesics in Finland, Estonia and Russian Karelia

AIM

Infections in early childhood are common reasons to seek medical attention. This study compares the prevalence of infections, and the use of antibiotics and antipyretic-analgesics, in children from Finland, Estonia and Russian Karelia.

METHODS

Children with a genetically increased risk for type 1 diabetes (N = 797) were observed from birth up to 3 years of age. Illnesses and medications were reported by parents continuously. All reported infections, antibiotics and antipyretic-analgesics were compared between Finland and Estonia, and to a lesser extent with Russian Karelia, due to poor study compliance.

RESULTS

Compared with Estonians, Finns reported more infections during the first and second years of life. During the follow-up, Finnish children had 10 infections while Estonians only had 8 (p < 0.001). Finns also used more antibiotics and antipyretic-analgesics in each year during the follow-up. Russian Karelians reported the lowest frequency of infections and the most infrequent use of antibiotics and antipyretic-analgesics in the first two years of life.

CONCLUSION

Infections and the use of antibiotics and antipyretic-analgesics in early childhood were most frequent in Finland, where socio-economic conditions are the most developed and microbial encounters are sparse. This may reflect on the hygiene hypothesis, a less effective immune system that allows normally harmless microbes to attack and cause clinical infections.

Comparing nonconscious nonverbal synchrony in racially concordant and racially discordant oncology interactions

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Background: Communication in racially discordant (Black patient, non-Black physician) oncology interactions, which constitute about 80% of Black patients’ interactions, is generally poorer than in racially concordant interactions, and likely contributes to treatment disparities. However, the nonverbal behaviors that contribute to this problem are largely unknown. We examined nonverbal synchrony, or the nonconscious coordination of movement, which can reflect relationship quality. We hypothesized that racially discordant interactions will have lower levels of nonverbal synchrony. Methods: Data include video recordings of 68 Black patients and 163 White patients discussing treatment with their non-Black oncologists. Recordings were submitted to motion detection software to measure nonverbal synchrony. This software measures global synchrony (all correlated motion), peak synchrony (all positively correlated motion), who is leading the interaction (similar to who is leading in ballroom dancing), and how much synchrony occurs based on who is leading the interaction. Using multi-level models, we investigated whether nonverbal synchrony differed in racially concordant and racially discordant dyads. Results: Findings showed greater levels of global synchrony (p < .05) and greater peak synchrony (p < .05) in racially discordant interactions compared to racially concordant interactions. Global synchrony was the same in racially concordant interactions regardless of who was leading, but greater global synchrony occurred in racially discordant interactions when the patient was leading (p < .05). Conclusions: This is the first study to use a dynamic jointly determined measure of behavior to assess oncology interactions. Contrary to our hypothesis, nonverbal synchrony was greater in racially discordant interactions than in racially concordant interactions. Patients are driving more of the synchrony in racially discordant interactions. This may suggest that patients in racially discordant interactions adapt to their physicians to bridge racial differences. Findings could contribute to physician training to enhance coordination and outcomes in oncology interactions.

Abstract 3356: Working together to put kids first: Outreach strategies driving collaborative research, data sharing and cross-disease analysis to accelerate discoveries in pediatric cancer and structural birth defects

The Gabriella Miller Kids First Pediatric Research Program launched the Kids First Pediatric Data Resource Center (DRC) in 2017 as a collaborative, pediatric research effort with the goal of understanding the genetic causes of and links between childhood cancer and structural birth defects. The DRC is charged with developing data-driven platforms that integrate large amounts of genomic and clinical data, empowering the collaborative discovery, engagement, and necessary partnerships that are crucial for progress in our biological understanding of diseases, enabling rapid translation to personalized treatments for patients and accelerating discovery of genetic causes and shared biologic pathways within and across these conditions. The DRC is comprised of 3 cores including the Data Resource Portal Core, Data Coordination Core and the Administrative & Outreach Core (AOC). The AOC brings together researchers, physicians, and patient and foundation advocates to support collaborative research and data sharing to accelerate discoveries. The AOC specific aims are to employ outreach strategies including print, web, social media, in-person presentations, conferences, videos, webinars, e-newsletters, surveys, communication strategies, and reports to support accelerated discoveries. The AOC is committed to learning from the childhood cancer and birth defect communities. By capturing, synthesizing, and prioritizing unmet needs for development of the Kids First DRC portal, website, and materials, the AOC engages with researchers, clinicians, foundations, and patient advocates in the childhood cancer and structural birth defect communities. In its first year, the AOC partnered with 32 foundations to launch the Kids First DRC Portal and support data sharing throughout the research community. Key findings during the first six months of requirements gathering revealed the following unmet needs: a) Increase understanding of the disease types, research projects, and the investigators that are a part of the Kids First community b) Highlight the need for cross-disease analyses including structural birth defects and childhood cancers and c) Promote education on the data sharing, agreements, data availability and accessibility. The AOC, gathered pertinent user requirements, conducted educational activities, and engaged prospective users of the researcher community resulting in over 200 users and 22,000 portal views since launch and will continue to use feedback from the research community to further inform the development of the Kids First DRC tools and materials to meet the goals of the program.

Citation Format: Tatiana S. Patton, Robert Moulder, Erin Alexander, Donna Vito, Jonathan Waller, Colleen Gaynor, Sarah Thomas, Bailey Farrow, Joseph Yamada, Kim Cullion, Danyelle Winchester, Angela Waanders, Allison Heath, Pichai Raman, Adam Resnick, Jena Lilly. Working together to put kids first: Outreach strategies driving collaborative research, data sharing and cross-disease analysis to accelerate discoveries in pediatric cancer and structural birth defects [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3356.

Comparing nonverbal synchrony in racially concordant and racially discordant oncology interactions

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Background: Communication in racially discordant (Black patient, non-Black physician) oncology interactions, which constitute about 80% of Black patients’ interactions, is generally poorer than in racially concordant interactions, and likely contributes to treatment disparities. However, the nonverbal behaviors that contribute to this problem are largely unknown. We examined nonverbal synchrony, or the nonconscious coordination of movement, which can reflect relationship quality. We hypothesized that racially discordant interactions will have lower levels of nonverbal synchrony. Methods: Data include video recordings of 68 Black patients and 163 White patients discussing treatment with their non-Black oncologists. Recordings were submitted to motion detection software to measure nonverbal synchrony. This software measures global synchrony (all correlated motion), peak synchrony (all positively correlated motion), who is leading the interaction (similar to who is leading in ballroom dancing), and how much synchrony occurs based on who is leading the interaction. Using multi-level models, we investigated whether nonverbal synchrony differed in racially concordant and racially discordant dyads. Results: Findings showed greater levels of global synchrony (p < .05) and greater peak synchrony (p < .05) in racially discordant interactions compared to racially concordant interactions. Global synchrony was the same in racially concordant interactions regardless of who was leading, but greater global synchrony occurred in racially discordant interactions when the patient was leading (p < .05). Conclusions: This is the first study to use a dynamic jointly determined measure of behavior to assess oncology interactions. Contrary to our hypothesis, nonverbal synchrony was greater in racially discordant interactions than in racially concordant interactions. It appears patients are driving more of the synchrony in racially discordant interactions. This may suggest that patients in racially discordant interactions adapt to their physicians to bridge racial differences. Findings could contribute to physician training to enhance coordination and outcomes in oncology interactions.

Quantitative Proteomics Reveals the Dynamic Protein Landscape during Initiation of Human Th17 Cell Polarization

Th17 cells contribute to the pathogenesis of inflammatory and autoimmune diseases and cancer. To reveal the Th17 cell-specific proteomic signature regulating Th17 cell differentiation and function in humans, we used a label-free mass spectrometry-based approach. Furthermore, a comprehensive analysis of the proteome and transcriptome of cells during human Th17 differentiation revealed a high degree of overlap between the datasets. However, when compared with corresponding published mouse data, we found very limited overlap between the proteins differentially regulated in response to Th17 differentiation. Validations were made for a panel of selected proteins with known and unknown functions. Finally, using RNA interference, we showed that SATB1 negatively regulates human Th17 cell differentiation. Overall, the current study illustrates a comprehensive picture of the global protein landscape during early human Th17 cell differentiation. Poor overlap with mouse data underlines the importance of human studies for translational research.

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Quantitative proteomics analysis of early human Th17 cell polarization

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The proteome and transcriptome highly correlate during early Th17 polarization

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Poor overlap of proteome profiles of human and mouse during early Th17 polarization

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The results underline the importance of human studies for translational research

Nonverbal synchrony as a behavioural marker of patient and physician race-related attitudes and a predictor of outcomes in oncology interactions: protocol for a secondary analysis of video-recorded cancer treatment discussions

INTRODUCTION

Racial disparities in cancer treatment contribute to racial disparities in mortality rates. The quality of patient-physician communication during clinical interactions with black patients and non-black physicians (racially discordant) is poorer than communication quality with white patients (racially concordant). Patient and physician race-related attitudes affect the quality of this communication. These attitudes are likely expressed through subtle non-verbal behaviours, but prior research has not examined these behaviours. Nonverbal synchrony, the coordination of physical movement, reflects the preinteraction attitudes of participants in interactions and predicts their postinteraction perceptions of and affect towards one another. In this study, peer reviewed and funded by the National Institute of Minority Health and Health Disparities (R21MD011766), we will investigate non-verbal synchrony in racially concordant and discordant interactions to better understand racial disparities in clinical communication.

METHODS AND ANALYSIS

This secondary analysis includes racially concordant (n=163) and racially discordant (n=68) video-recorded oncology interactions, patient and oncologist self-reported race-related attitudes, perceptions of the interaction and observer ratings of physician patient-centred communication and patient and physician affect and rapport. In aim 1, we will assess and compare non-verbal synchrony between physicians and patients in racially concordant and discordant interactions. In aim 2, we will determine the influence of non-verbal synchrony on patient and physician affect and communication. In aim 3, we will examine possible causes (ie, race-related attitudes) and consequences (ie, negative perceptions) of non-verbal synchrony in racially discordant interactions. In aim 4, we will develop and test a mediational model linking physician and patient race-related attitudes to non-verbal synchrony and, in turn, interaction outcomes.

ETHICS AND DISSEMINATION

The parent and current studies were approved by the Wayne State University Institutional Review Board. Since only archival data will be used, ethical or safety risks are low. We will disseminate our findings to relevant conferences and journals.

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.

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.

T helper 17 (Th17) cells and induced regulatory T (iTreg) cells are two subsets of T helper cells differentiated from naïve cells that play important roles in autoimmune diseases, immune homeostasis, and tumor immunity. The differentiation process is achieved by changes in numerous proteins, including transcription regulators, enzymes, membrane receptors, and cytokines, which are critical in lineage commitment. To profile protein expression changes in Th17 and iTreg cells, we polarized murine naïve CD4+ T (Thp) cells in vitro to Th17 and iTreg cells and performed quantitative proteomic analysis of these 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. The present study serves as a valuable resource that may prove useful in developing treatment of autoimmune diseases and cancer.

Is it a Small World After All? Investigating the Theoretical Structure of Working Memory Cross-Nationally

To our knowledge, this is one of the first studies to test different theoretical models of working memory in childhood based on a computerized assessment. We tested this across several countries: Argentina, Brazil, Canada, Italy, and uk. The present study addressed the wider macro-cultural context and how this impacts working memory. We used two economic indices (gdp and ppp) to characterize the participating countries and ranked the countries based on the Global Index of Cognitive Skills and Educational Attainment. Children between 5 and 10 years completed the same set of short-term and working memory tests. There were two main findings. First, there was a similar pattern in verbal working memory across countries, which suggests that this skill may be relatively consistent across different cultural groups. In contrast, the pattern for visuo-spatial working memory was different across countries, which may explained by cultural differences and educational rankings of the countries. The second main finding was that both a domain-general model (3-factor) and a domain-specific model (4-factor) provided a reasonably good fit with the data, there was the high relationship between the verbal and visuo-spatial working memory constructs across the countries in the latter model. Thus, it may be a more parsimonious choice to rely on a three-factor model. The data also suggest culture-similar patterns in a computerized assessment of working memory.

DNA methylation and Transcriptome Changes Associated with Cisplatin Resistance in Ovarian Cancer

High-grade serous ovarian cancer is the most common ovarian cancer type. Although the combination of surgery and platinum-taxane chemotherapy provide an effective treatment, drug resistance frequently occurs leading to poor outcome. In order to clarify the molecular mechanisms of drug resistance, the DNA methylation and transcriptomic changes, associated with the development of drug resistance in high-grade serous ovarian cancer, were examined from patient derived malignant ascites cells. In parallel with large-scale transcriptome changes, cisplatin resistance was associated with loss of hypermethylation at several CpG sites primarily localized in the intergenic regions of the genome. The transcriptome and CpG methylome changes in response to cisplatin treatment of both sensitive and resistant cells were minimal, indicating the importance of post-translational mechanisms in regulating death or survival of the cells. The response of resistant cells to high concentrations of cisplatin revealed transcriptomic changes in potential key drivers of drug resistance, such as KLF4. Among the strongest changes was also induction of IL6 in resistant cells and the expression was further increased in response to cisplatin. Also, several other components of IL6 signaling were affected, further supporting previous observations on its importance in malignant transformation and development of drug resistance in ovarian cancer.

Mass Spectrometry-Based Serum Proteomics for Biomarker Discovery and Validation

Blood protein measurements are used frequently in the clinic in the assessment of patient health. Nevertheless, there remains the need for new biomarkers with better diagnostic specificities. With the advent of improved technology for bioanalysis and the growth of biobanks including collections from specific disease risk cohorts, the plasma proteome has remained a target of proteomics research toward the characterization of disease-related biomarkers. The following protocol presents a workflow for serum/plasma proteomics including details of sample preparation both with and without immunoaffinity depletion of the most abundant plasma proteins and methodology for selected reaction monitoring mass spectrometry validation.

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.

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

BACKGROUND

Sarcoidosis is an inflammatory granulomatous disorder characterized by accumulation of T_H1-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.

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.

Label-Free Quantitation for Clinical Proteomics

Label-free quantification (LFQ) has emerged as a viable option for quantitative LC-MS/MS-based proteomic analyses for use on the scale of hundreds of samples such as are encountered in clinical analysis. Notably, sample preparation, sample loading, HPLC separations, and mass spectrometric performance must be highly reproducible for this approach to be effective. The following protocols describe the key steps in the methods related to sample preparation and analysis for LC-MS/MS-based label-free quantitation using standard data-dependent acquisition.

Serum proteomes distinguish children developing type 1 diabetes in a cohort with HLA-conferred susceptibility

We determined longitudinal serum proteomics profiles from children with HLA-conferred diabetes susceptibility to identify changes that could be detected before seroconversion and positivity for disease-associated autoantibodies. Comparisons were made between children who seroconverted and progressed to type 1 diabetes (progressors) and those who remained autoantibody negative, matched by age, sex, sample periodicity, and risk group. The samples represented the prediabetic period and ranged from the age of 3 months to 12 years. After immunoaffinity depletion of the most abundant serum proteins, isobaric tags for relative and absolute quantification were used for sample labeling. Quantitative proteomic profiles were then measured for 13 case-control pairs by high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Additionally, a label-free LC-MS/MS approach was used to analyze depleted sera from six case-control pairs. Importantly, differences in abundance of a set of proteins were consistently detected before the appearance of autoantibodies in the progressors. Based on top-scoring pairs analysis, classification of such progressors was observed with a high success rate. Overall, the data provide a reference of temporal changes in the serum proteome in healthy children and children progressing to type 1 diabetes, including new protein candidates, the levels of which change before clinical diagnosis.

Quantitative proteomics analysis of the nuclear fraction of human CD4+ cells in the early phases of IL-4-induced Th2 differentiation

We used stable isotope labeling with 4-plex iTRAQ (isobaric tags for relative and absolute quantification) reagents and LC-MS/MS to investigate proteomic changes in the nucleus of activated human CD4⁺ cells during the early stages of Th2 cell differentiation. The effects of IL-4 stimulation upon activated naïve CD4⁺ cells were measured in the nuclear fractions from 6 and 24 h in three biological replicates, each using pooled cord blood samples derived from seven or more individuals. In these analyses, in the order of 800 proteins were detected with two or more peptides and quantified in three biological replicates. In addition to consistent differences observed with the nuclear localization/expression of established human Th2 and Th1 markers, there were changes that suggested the involvement of several proteins either only recently reported or otherwise not known in this context. These included SATB1 and among the novel changes detected and validated an IL-4-induced increase in the level of YB1. This unique data set from human cord blood CD4⁺ T cells details an extensive list of protein determinations that compares with and complements previous data determined from the Jurkat cell nucleus.

Identification of novel Stat6 regulated proteins in IL-4-treated mouse lymphocytes

Interleukin 4 (IL-4) has an indispensable role in the differentiation of naive T helper (Th) cells toward the Th2 phenotype and induction of B cells to produce the IgE class of Igs. By regulating these two cell types, IL-4 has a pre-eminent role in regulation of allergic inflammation. IL-4-mediated regulation of T and B cell functions is largely transmitted through signal transducer and activator of transcription 6 (Stat6). In this study, we have used metabolic labeling and 2-D electrophoresis to detect differences in the proteomes of IL-4 stimulated spleen mononuclear cells of Stat6-/- and wild type mice and MS/MS for protein identification. With this methodology, we identified 49 unique proteins from 21 protein spots to be differentially expressed. Interestingly, in Stat6-/- CD4(+) cells the expression of isoform 2 of core binding factor b (CBFb2) was enhanced. CBFb is a non-DNA binding cofactor for the Runx family of transcription factors, which have been implicated in regulation of Th cell differentiation. We also found cellular nucleic acid protein (CNBP) to be downregulated in Stat6-/- cells. None of the proteins identified in this study have previously been reported to be regulated via Stat6. The results highlight the importance of exploiting proteomics tools to complement the studies on Stat6 target genes identified through transcriptional profiling.

Quantitative proteomics reveals GIMAP family proteins 1 and 4 to be differentially regulated during human T helper cell differentiation

T helper (Th) cells differentiate into functionally distinct effector cell subsets of which Th1 and Th2 cells are best characterized. Besides T cell receptor signaling, IL-12-induced STAT4 and T-bet- and IL-4-induced STAT6 and GATA3 signaling pathways are the major players regulating the Th1 and Th2 differentiation process, respectively. However, there are likely to be other yet unknown factors or pathways involved. In this study we used quantitative proteomics exploiting cleavable ICAT labeling and LC-MS/MS to identify IL-4-regulated proteins from the microsomal fractions of CD4(+) cells extracted from umbilical cord blood. We were able to identify 557 proteins of which 304 were also quantified. This study resulted in the identification of the down-regulation of small GTPases GIMAP1 and GIMAP4 by IL-4 during Th2 differentiation. We also showed that both GIMAP1 and GIMAP4 genes are up-regulated by IL-12 and other Th1 differentiation-inducing cytokines in cells induced to differentiate toward Th1 lineage and down-regulated by IL-4 in cells induced to Th2. Our results indicate that the GIMAP (GTPase of the immunity-associated protein) family of proteins is differentially regulated during Th cell differentiation.

Quality classification of tandem mass spectrometry data

Peptide identification by tandem mass spectrometry is an important tool in proteomic research. Powerful identification programs exist, such as SEQUEST, ProICAT and Mascot, which can relate experimental spectra to the theoretical ones derived from protein databases, thus removing much of the manual input needed in the identification process. However, the time-consuming validation of the peptide identifications is still the bottleneck of many proteomic studies. One way to further streamline this process is to remove those spectra that are unlikely to provide a confident or valid peptide identification, and in this way to reduce the labour from the validation phase.

RESULTS

We propose a prefiltering scheme for evaluating the quality of spectra before the database search. The spectra are classified into two classes: spectra which contain valuable information for peptide identification and spectra that are not derived from peptides or contain insufficient information for interpretation. The different spectral features developed for the classification are tested on a real-life material originating from human lymphoblast samples and on a standard mixture of 9 proteins, both labelled with the ICAT-reagent. The results show that the prefiltering scheme efficiently separates the two spectra classes.

A comparative evaluation of software for the analysis of liquid chromatography-tandem mass spectrometry data from isotope coded affinity tag experiments

The options available for processing quantitative data from isotope coded affinity tag (ICAT) experiments have mostly been confined to software specific to the instrument of acquisition. However, recent developments with data format conversion have subsequently increased such processing opportunities. In the present study, data sets from ICAT experiments, analysed with liquid chromatography/tandem mass spectrometry (MS/MS), using an Applied Biosystems QSTAR Pulsar quadrupole-TOF mass spectrometer, were processed in triplicate using separate mass spectrometry software packages. The programs Pro ICAT, Spectrum Mill and SEQUEST with XPRESS were employed. Attention was paid towards the extent of common identification and agreement of quantitative results, with additional interest in the flexibility and productivity of these programs. The comparisons were made with data from the analysis of a specifically prepared test mixture, nine proteins at a range of relative concentration ratios from 0.1 to 10 (light to heavy labelled forms), as a known control, and data selected from an ICAT study involving the measurement of cytokine induced protein expression in human lymphoblasts, as an applied example. Dissimilarities were detected in peptide identification that reflected how the associated scoring parameters favoured information from the MS/MS data sets. Accordingly, there were differences in the numbers of peptides and protein identifications, although from these it was apparent that both confirmatory and complementary information was present. In the quantitative results from the three programs, no statistically significant differences were observed.