Phenotypes are the foundation for clinical and genetic studies of disease risk and outcomes. The growth of biobanks linked to electronic medical record (EMR) data has both facilitated and increased the demand for efficient, accurate, and robust approaches for phenotyping millions of patients. Challenges to phenotyping using EMR data include variation in the accuracy of codes, as well as the high level of manual input required to identify features for the algorithm and to obtain gold standard labels. To address these challenges, we developed PheCAP, a high-throughput semisupervised phenotyping pipeline. PheCAP begins with data from the EMR, including structured data and information extracted from the narrative notes using natural language processing (NLP). The standardized steps integrate automated procedures reducing the level of manual input, and machine learning approaches for algorithm training. PheCAP itself can be executed in 1-2 days if all data are available; however, the timing is largely dependent on the chart review stage which typically requires at least 2 weeks. The final products of PheCAP include a phenotype algorithm, the probability of the phenotype for all patients, and a phenotype classification (yes or no).

ObjectivesTo examine the feasibility and potential benefits of early peer support to improve the health and quality of life of individuals with early inflammatory arthritis (EIA).DesignFeasibility study using the 2008 Medical Research Council framework as a theoretical basis. A literature review, environmental scan, and interviews with patients, families and healthcare providers guided the development of peer mentor training sessions and a peer-to-peer mentoring programme. Peer mentors were trained and paired with a mentee to receive (face-to-face or telephone) support over 12 weeks.SettingTwo academic teaching hospitals in Toronto, Ontario, Canada.ParticipantsNine pairs consisting of one peer mentor and one mentee were matched based on factors such as age and work status.Primary outcome measureMentee outcomes of disease modifying antirheumatic drugs (DMARDs)/biological treatment use, self-efficacy, self-management, health-related quality of life, anxiety, coping efficacy, social support and disease activity were measured using validated tools. Descriptive statistics and effect sizes were calculated to determine clinically important (>0.3) changes. Peer mentor self-efficacy was assessed using a self-efficacy scale. Interviews conducted with participants examined acceptability and feasibility of procedures and outcome measures, as well as perspectives on the value of peer support for individuals with EIA. Themes were identified through constant comparison.ResultsMentees experienced improvements in the overall arthritis impact on life, coping efficacy and social support (effect size >0.3). Mentees also perceived emotional, informational, appraisal and instrumental support. Mentors also reported benefits and learnt from mentees’ fortitude and self-management skills. The training was well received by mentors. Their self-efficacy increased significantly after training completion. Participants’ experience of peer support was informed by the unique relationship with their peer. All participants were unequivocal about the need for peer support for individuals with EIA.ConclusionsThe intervention was well received. Training, peer support programme and outcome measures were demonstrated to be feasible with modifications. Early peer support may augment current rheumatological care.Trial registration numberNCT01054963, NCT01054131.

Objective: To investigate the effect of acupuncture on Parkinson's disease (PD) patients with tremor and its potential neuromechanism by functional magnetic resonance imaging (fMRI).Methods: Forty-one PD patients with tremor were randomly assigned to true acupuncture group (TAG, n = 14), sham acupuncture group (SAG, n = 14) and waiting group (WG, n = 13). All patients received levodopa for 12 weeks. Patients in TAG were acupunctured on DU20, GB20, and the Chorea-Tremor Controlled Zone, and patients in SAG accepted sham acupuncture, while patients in WG received no acupuncture treatment until 12 weeks after the course was ended. The UPDRS II and III subscales, and fMRI scans of the patients' brains were obtained before and after the treatment course. UPDRS II and III scores were analyzed by SPSS, while the degree centrality (DC), regional homogeneity (ReHo) and amplitude low-frequency fluctuation (ALFF) were determined by REST.Results: Acupuncture improved the UPDRS II and III scores in PD patients with tremor without placebo effect, only in tremor score. Acupuncture had specific effects on the cerebrocerebellar pathways as shown by the decreased DC and ReHo and increased ALFF values, and nonspecific effects on the spinocerebellar pathways as shown by the increased ReHo and ALFF values (P < 0.05, AlphaSim corrected). Increased ReHo values were observed within the thalamus and motor cortex of the PD patients (P < 0.05, AlphaSim corrected). In addition, the default mode network (DMN), visual areas and insula were activated by the acupuncture with increased DC, ReHo and/or ALFF, while the prefrontal cortex (PFC) presented a significant decrease in ReHo and ALFF values after acupuncture (P < 0.05, AlphaSim corrected).Conclusions: The cerebellum, thalamus and motor cortex, which are connected to the cerebello-thalamo-cortical (CTC) circuit, were modulated by the acupuncture stimulation to alleviate the PD tremor. The regulation of neural activity within the cognitive brain regions (the DMN, visual areas, insula and PFC) together with CTC circuit may contributes to enhancing movement and improving patients' daily life activities.

Glioblastoma (GBM) is one of the most prevalent malignant brain tumors with poor prognosis. Increasing evidence has revealed that infiltrating immune cells and other stromal components in the tumor microenvironment (TME) are associated with prognosis of GBM. The aim of the present study was to identify immune cells and immune-related genes extracted from TME in GBM. RNA-sequencing and clinical data of GBM were downloaded from The Cancer Genome Atlas (TCGA). Four survival-related immune cells were identified via Kaplan-Meier survival analysis and immune-related differentially expressed genes (DEGs) screened. Functional enrichment and proteinprotein interaction (PPI) networks for the genes were constructed. In addition, we identified 24 hub genes and the expressions of 6 of the genes were significantly associated with prognosis of GBM. Finally, the genes were validated in single-cell sequencing studies of GBM, and the immune cells validated in an independent GBM cohort from the Chinese Glioma Genome Atlas (CGGA). Overall, 24 immune-related genes infiltrating the tumor microenvironment were identified in the present study, which could serve as novel biomarkers and immune therapeutic targets.

Objective To determine the association between novel lifestyle factors on risk of rheumatoid arthritis-associated interstitial lung disease (RA-ILD), define the threshold at which smoking increases RA-ILD risk, and calculate the degree to which known lifestyle and clinical factors predict RA-ILD. Methods This nested case-control study matched incident RA-ILD cases to RA non-ILD controls on age, sex, RA duration, rheumatoid factor, and time from exposure assessment to RA-ILD. Exposures included education, body mass index (BMI), smoking, anti-cyclic citrullinated peptide, race, joint erosions, rheumatoid nodules, C-reactive protein (CRP), disease activity score, functional status, disease-modifying anti-rheumatic drug use, and glucocorticoid use. Odds ratios (OR) for each exposure on risk of RA-ILD were obtained from logistic regression models. Area under the curve (AUC) was calculated based all lifestyle and clinical exposures. Results We identified 84 incident RA-ILD cases and 233 matched controls. After adjustment, obesity, high-positive CRP (≥10 mg/L), and poor functional status (MDHAQ ≥1) were associated with increased risk of RA-ILD (OR 2.42, 95% confidence interval [CI] 1.11-5.24 vs. normal BMI; OR 2.61, 95% CI 1.21-5.64 vs. CRP <3mg/L; OR 3.10, 95% CI 1.32-7.26 vs. MDHAQ <0.2). Smoking 30 pack-years or more was strongly associated with risk of RA-ILD compared to nonsmokers (OR 6.06, 95% CI 2.72-13.5). Together, lifestyle and clinical risk factors for RA-ILD had an AUC of 0.79 (95% CI 0.73-0.85). Conclusion Obesity, CRP, functional status, and extensive smoking may be novel risk factors for RA-ILD, useful for RA-ILD risk assessment and prevention. The overall ability to predict RA-ILD remains modest.

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Objective The objective of this study was to compare the performance of an RA algorithm developed and trained in 2010 utilizing natural language processing and machine learning, using updated data containing ICD10, new RA treatments, and a new electronic medical records (EMR) system. Methods We extracted data from subjects with ≥1 RA International Classification of Diseases (ICD) codes from the EMR of two large academic centres to create a data mart. Gold standard RA cases were identified from reviewing a random 200 subjects from the data mart, and a random 100 subjects who only have RA ICD10 codes. We compared the performance of the following algorithms using the original 2010 data with updated data: (i) a published 2010 RA algorithm; (ii) updated algorithm, incorporating ICD10 RA codes and new DMARDs; and (iii) published algorithm using ICD codes only, ICD RA code ≥3. Results The gold standard RA cases had mean age 65.5 years, 78.7% female, 74.1% RF or antibodies to cyclic citrullinated peptide (anti-CCP) positive. The positive predictive value (PPV) for ≥3 RA ICD was 54%, compared with 56% in 2010. At a specificity of 95%, the PPV of the 2010 algorithm and the updated version were both 91%, compared with 94% (95% CI: 91, 96%) in 2010. In subjects with ICD10 data only, the PPV for the updated 2010 RA algorithm was 93%. Conclusion The 2010 RA algorithm validated with the updated data with similar performance characteristics as the 2010 data. While the 2010 algorithm continued to perform better than the rule-based approach, the PPV of the latter also remained stable over time.