Identification of 6 dermatomyositis subgroups using principal component analysis-based cluster analysis.
ABSTRACT: OBJECTIVE:Dermatomyositis (DM) is a heterogeneous disease with a wide range of clinical manifestations. The aim of the present study was to identify the clinical subtypes of DM by applying cluster analysis. METHODS:We retrospectively reviewed the medical records of 720 DM patients and selected 21 variables for analysis, including clinical characteristics, laboratory findings, and comorbidities. Principal component analysis (PCA) was first conducted to transform the 21 variables into independent principal components. Patient classification was then performed using cluster analysis based on the PCA-transformed data. The relationships among the clinical variables were also assessed. RESULTS:We transformed the 21 clinical variables into nine independent principal components by PCA and identified six distinct subgroups. Cluster A was composed of two sub-clusters of patients with classical DM and classical DM with minimal organ involvement. Cluster B patients were older and had malignancies. Cluster C was characterized by interstitial lung disease (ILD), skin ulcers, and minimal muscle involvement. Cluster D included patients with prominent lung, muscle, and skin involvement. Cluster E contained DM patients with other connective tissue diseases. Cluster F included all patients with myocarditis and prominent myositis and ILD. We found significant differences in treatment across the six clusters, with clusters E, C and D being more likely to receive aggressive immunosuppressive therapy. CONCLUSION:We applied cluster analysis to a large group of DM patients and identified 6 clinical subgroups, underscoring the need for better phenotypic characterization to help develop individualized treatments and improve prognosis.
Project description:Heterogeneity in chronic migraine (CM) presents significant challenge for diagnosis, management, and clinical trials. To explore naturally occurring clusters of CM, we utilized data reduction methods on migraine-related clinical dataset. Hierarchical agglomerative clustering and principal component analyses (PCA) were conducted to identify natural clusters in 100 CM patients using 14 migraine-related clinical variables. Three major clusters were identified. Cluster I (29 patients) - the severely impacted patient featured highest levels of depression and migraine-related disability. Cluster II (28 patients) - the minimally impacted patient exhibited highest levels of self-efficacy and exercise. Cluster III (43 patients) - the moderately impacted patient showed features ranging between Cluster I and II. The first 5 principal components (PC) of the PCA explained 65% of variability. The first PC (eigenvalue 4.2) showed one major pattern of clinical features positively loaded by migraine-related disability, depression, poor sleep quality, somatic symptoms, post-traumatic stress disorder, being overweight and negatively loaded by pain self-efficacy and exercise levels. CM patients can be classified into three naturally-occurring clusters. Patients with high self-efficacy and exercise levels had lower migraine-related disability, depression, sleep quality, and somatic symptoms. These results may ultimately inform different management strategies.
Project description:BACKGROUND:The current interstitial lung disease (ILD) classification has overlapping clinical presentations and outcomes. Cluster analysis modeling is a valuable tool in identifying distinct clinical phenotypes in heterogeneous diseases. However, this approach has yet to be implemented in ILD. METHODS:Using cluster analysis, novel ILD phenotypes were identified among subjects from a longitudinal ILD cohort, and outcomes were stratified according to phenotypic clusters compared with subgroups according to current American Thoracic Society/European Respiratory Society ILD classification criteria. RESULTS:Among subjects with complete data for baseline variables (N = 770), four clusters were identified. Cluster 1 (ie, younger white obese female subjects) had the highest baseline FVC and diffusion capacity of the lung for carbon monoxide (Dlco). Cluster 2 (ie, younger African-American female subjects with elevated antinuclear antibody titers) had the lowest baseline FVC. Cluster 3 (ie, elderly white male smokers with coexistent emphysema) had intermediate FVC and Dlco. Cluster 4 (ie, elderly white male smokers with severe honeycombing) had the lowest baseline Dlco. Compared with classification according to ILD subgroup, stratification according to phenotypic clusters was associated with significant differences in monthly FVC decline (Cluster 4, -0.30% vs Cluster 2, 0.01%; P < .0001). Stratification by using clusters also independently predicted progression-free survival (P < .001) and transplant-free survival (P < .001). CONCLUSIONS:Among adults with diverse chronic ILDs, cluster analysis using baseline characteristics identified four distinct clinical phenotypes that might better predict meaningful clinical outcomes than current ILD diagnostic criteria.
Project description:Interstitial lung disease (ILD) is the principal cause of death in polymyositis/dermatomyositis (PM/DM). Here we investigated prognostic factors for death and serious infection in PM/DM-ILD using the multicenter database.We retrospectively reviewed baseline demographic, clinical and laboratory findings, treatment regimens and outcomes in patients with PM/DM-ILD. The distribution of ILD lesions was evaluated in four divided lung zones of high-resolution computed tomography images.Of 116 patients with PM/DM-ILD, 14 died within 6 months from the diagnosis. As independent risk factors for early death, extended ILD lesions in upper lung fields (odds ratio (OR) 8.01, p?=?0.016) and hypocapnia (OR 6.85, p?=?0.038) were identified. Serious infection was found in 38 patients, including 11 patients who died of respiratory or multiple infections. The independent risk factors were high serum KL-6 (OR 3.68, p?=?0.027), high initial dose of prednisolone (PSL) (OR 4.18, p?=?0.013), and combination immunosuppressive therapies (OR 5.51, p?<?0.001).The present study shows the progression of ILD at baseline is the most critical for survival and that infection, especially respiratory infection, is an additive prognostic factor under the potent immunosuppressive treatment.
Project description:BACKGROUND:To explore the clinical patterns of patients with IgG4-related disease (IgG4-RD) based on laboratory tests and the number of organs involved. METHODS:Twenty-two baseline variables were obtained from 154 patients with IgG4-RD. Based on principal component analysis (PCA), patients with IgG4-RD were classified into different subgroups using cluster analysis. Additionally, IgG4-RD composite score (IgG4-RD CS) as a comprehensive score was calculated for each patient by principal component evaluation. Multiple linear regression was used to establish the "IgG4-RD CS" prediction model for the comprehensive assessment of IgG4-RD. To evaluate the value of the IgG4-RD CS in the assessment of disease severity, patients in different IgG4-RD CS groups and in different IgG4-RD responder index (RI) groups were compared. RESULTS:PCA indicated that the 22 baseline variables of IgG4-RD patients mainly consisted of inflammation, high serum IgG4, multi-organ involvement, and allergy-related phenotypes. Cluster analysis classified patients into three groups: cluster 1, inflammation and immunoglobulin-dominant group; cluster 2, internal organs-dominant group; and cluster 3, inflammation and immunoglobulin-low with superficial organs-dominant group. Moreover, there were significant differences in serum and clinical characteristics among subgroups based on the CS and RI scores. IgG4-RD CS had a similar ability to assess disease severity as RI. The "IgG4-RD CS" prediction model was established using four independent variables including lymphocyte count, eosinophil count, IgG levels, and the total number of involved organs. CONCLUSION:Our study indicated that newly diagnosed IgG4-RD patients could be divided into three subgroups. We also showed that the IgG4-RD CS had the potential to be complementary to the RI score, which can help assess disease severity.
Project description:The global increase in Diabetes Mellitus (DM) has led to an increase in DM-Chronic Kidney Disease (DM-CKD). In this cross-sectional observational study we aimed to define phenotypes for patients with DM-CKD that in future may be used to individualise treatment We report 4 DM-CKD phenotypes in 220 patients recruited from Imperial College NHS Trust clinics from 2004-2012. A robust principal component analysis (PCA) was used to statistically determine clusters with phenotypically different patients. 163 patients with complete data sets were analysed: 77 with CKD and 86 with DM-CKD. Four different clusters were identified. Phenotypes 1 and 2 are entirely composed of patients with DM-CKD and phenotypes 3 and 4 are predominantly CKD (non-DM-CKD). Phenotype 1 depicts a cardiovascular phenotype; phenotype 2: microvascular complications with advanced DM-CKD; phenotype 3: advanced CKD with less anaemia, lower weight and HbA1c; phenotype 4: hypercholesteraemic, younger, less severe CKD. We are the first group to describe different phenotypes in DM-CKD using a PCA approach. Identification of phenotypic groups illustrates the differences and similarities that occur under the umbrella term of DM-CKD providing an opportunity to study phenotypes within these groups thereby facilitating development of precision/personalised targeted medicine.
Project description:BACKGROUND:Dermatomyositis (DM) with rapidly progressive interstitial lung disease (DM RP-ILD) is a life-threatening condition. Serum cytokine levels are potentially suitable biomarkers for DM RP-ILD. However, the relationships among cytokine levels, lung imaging findings, and lung pathology have not been investigated. The aim of the present retrospective study was to determine the association between hypercytokinemia and lung inflammation in patients with DM RP-ILD. METHODS:The study subjects were nine patients with life-threatening DM RP-ILD and severe hypoxemia (partial arterial oxygen pressure (PaO2)/fraction of inspired oxygen (FiO2) ratio???200) before receiving intensive care management, who were admitted to our hospital between 2006 and 2015. The controls included 10 patients with DM without RP-ILD and 19 healthy subjects. We assessed the association between serum cytokine levels and computed tomography (CT) scores of the lung (ground glass opacity-score, G-score; fibrosis-score, F-score). Lung, hilar lymph nodes, and spleen from two autopsies were examined by hematoxylin-eosin (H&E) staining and immunostaining. RESULTS:Serum interferon (IFN)-?, interleukin (IL)-1? and IL-12 levels were significantly higher in patients with DM RP-ILD than in the other two groups, whereas serum IL-6 levels were elevated in the two patient groups but not in the healthy subjects. Serum levels of IL-2, IL-4, IL-8, IL-10, IFN-?, and TNF (tumor necrosis factor)-? were not characteristically elevated in the DM RP-ILD group. Serum IFN-? levels correlated with G-scores in patients with DM RP-ILD, while IL-1? was negatively correlation with F-scores. Immunohistochemical staining showed infiltration of numerous IFN-?-positive histiocytes in the lung and hilar lymph nodes; but not in the spleen. Serum IL-6 levels did not correlate with the CT scores. Numerous IL-6-positive plasma cells were found in hilar lymph nodes, but not in the lungs or spleen. CONCLUSIONS:Our results suggest strong IFN-?-related immune reaction in the lungs and hilar lymph nodes of patients with life-threatening DM RP-ILD, and potential IFN-? involvement in the pathogenesis of DM, specifically in the pulmonary lesions of RP-ILD.
Project description:OBJECTIVES:Interstitial lung disease (ILD) is an extramuscular manifestation that results in increased morbidity and mortality from polymyositis (PM) and dermatomyositis (DM). The aim of this study was to systematically evaluate risk factors associated with the development of ILD in PM/DM. METHODS:Observational studies were identified from searching PubMed, Medline, Embase, and the Cochrane Library. Pooled odds ratios (ORs) or standardized mean differences (SMDs) and corresponding 95% confidence intervals (CIs) were obtained for the relationships between risk factors and ILD in PM/DM using either fixed- or random-effects models, whichever were appropriate. Heterogeneity tests, sensitivity analyses, and publication bias assessments were also performed. RESULTS:Twenty-three studies were selected for a meta-analysis that included 834 patients and 1245 control subjects. Risk factors that may have increased the risk of developing ILD in PM/DM patients included older age at diagnosis (SMD, 0.35; 95% CI, 0.18-0.52; P < 0.0001), arthritis/arthralgia (OR, 3.17; 95% CI, 1.99-5.04; P < 0.00001), fever (OR, 2.31; 95% CI, 1.42-3.76; P = 0.0007), presence of anti-Jo-1 antibodies (OR, 3.34; 95% CI, 2.16-5.16; P < 0.00001), elevated erythrocyte sedimentation rate (ESR; SMD, 0.48; 95% CI, 0.32-0.64; P < 0.00001), presence of anti-MDA5 antibodies (OR, 18.26; 95% CI, 9.66-34.51; P < 0.00001), and elevated C-reactive protein level (CRP; OR, 3.50; 95% CI, 1.48-8.28; P = 0.004). Meanwhile, malignancy (OR, 0.36; 95% CI, 0.18-0.72; P = 0.004) reduced the risk of developing ILD in PM/DM patients. CONCLUSION:Our meta-analysis results suggest that the association between PM/DM and ILD may be due to such risk factors as older age at diagnosis, arthritis/arthralgia, fever, presence of anti-Jo-1 antibodies, elevated ESR, presence of anti-MDA5 antibodies, and elevated CRP level, while malignancy was associated with a reduced risk of developing ILD. Thus, these variables may be used to guide screening processes for ILD in patients with PM/DM.
Project description:BACKGROUND: "Posterior shift" of the neuropathological changes of Alzheimer's disease (AD) produces a syndrome (posterior cortical atrophy) (PCA) dominated by high-level visual deficits. OBJECTIVE: To explore in patients with AD-type pathology whether a data-driven analysis (cluster analysis) based on neuropsychological findings resulted in the emergence of different subgroups of patients; in particular to find out whether it was possible to identify patients with visuospatial deficits consistent with the hypothesis that PCA is a "dorsal stream" syndrome or, rather, whether there were subgroups of patients with different types of impairment within the high-level visual domain. METHODS: 23 PCA and 16 DAT patients were studied. By a principal component analysis performed on a wide range of neuropsychological tasks, 15 variables were obtained that loaded onto five main factors (memory, language, perceptual, visuospatial, and calculation) which entered a hierarchical cluster analysis. RESULTS: Four clusters of cognitive impairment emerged: visuospatial/perceptual, memory, perceptual/calculation, and language. Only in the first cluster a visuospatial deficit clearly emerged. conclusions: AD pathology produces not only variants dominated by memory (DAT) and, to a lesser extent, visuospatial deficit (PCA), but also other distinct syndromic subtypes with disorders in visual perception and language which reflect a different vulnerability of specific functional networks.
Project description:Single nucleotide polymorphisms (SNPs) in TNFSF4 and ANKRD55 genes have been shown to be associated with several autoimmune diseases, although whether these genes are susceptibility genes for dermatomyositis/polymyositis (DM/PM) has, to date, not been reported. This study aimed to investigate the potential associations of these SNPs with DM/PM in a Chinese Han population. Five SNPs in TNFSF4 (rs2205960, rs844644, and rs844648) and ANKRD55 (rs6859219, rs7731626) genes were genotyped using the SequenomMassArray system in 2297 Chinese individuals. In total, 1017 DM/PM patients and 1280 gender-matched healthy controls were genotyped. No significant associations were observed in DM/PM patients for the five SNPs analyzed. The association between SNPs and interstitial lung disease (ILD) was also investigated. Both DM-ILD (Pc = 0.030, OR = 0.65, 95% CI: 0.47-0.88) and DM/PM-ILD (Pc = 0.015, OR = 0.67, 95% CI: 0.51-0.87) exhibited a significant association with the rs7731626-A allele. Rs7731626-A was less frequently found in DM-ILD and DM/PM-ILD patients compared with healthy controls. This is the first study to demonstrate a positive association between ANKRD55 polymorphism and DM-ILD and DM/PM-ILD. A decreased frequency of rs7731626-A in DM-ILD and DM/PM-ILD patients suggests that the A variant may be protective against DM/PM-ILD.
Project description:Data-driven methods such as hierarchical clustering (HC) and principal component analysis (PCA) have been used to identify asthma subtypes, with inconsistent results.To develop a framework for the discovery of stable and clinically meaningful asthma subtypes.We performed HC in a rich data set from 613 asthmatic children, using 45 clinical variables (Model 1), and after PCA dimensionality reduction (Model 2). Clinical experts then identified a set of asthma features/domains which informed clusters in the two analyses. In Model 3, we reclustered the data using these features to ascertain whether this improved the discovery process.Cluster stability was poor in Models 1 and 2. Clinical experts highlighted four asthma features/domains which differentiated the clusters in two models: age of onset, allergic sensitization, severity, and recent exacerbations. In Model 3 (HC using these four features), cluster stability improved substantially. The cluster assignment changed, providing more clinically interpretable results. In a 5-cluster model, we labelled the clusters as: "Difficult asthma" (n = 132); "Early-onset mild atopic" (n = 210); "Early-onset mild non-atopic: (n = 153); "Late-onset" (n = 105); and "Exacerbation-prone asthma" (n = 13). Multinomial regression demonstrated that lung function was significantly diminished among children with "Difficult asthma"; blood eosinophilia was a significant feature of "Difficult," "Early-onset mild atopic," and "Late-onset asthma." Children with moderate-to-severe asthma were present in each cluster.An integrative approach of blending the data with clinical expert domain knowledge identified four features, which may be informative for ascertaining asthma endotypes. These findings suggest that variables which are key determinants of asthma presence, severity, or control may not be the most informative for determining asthma subtypes. Our results indicate that exacerbation-prone asthma may be a separate asthma endotype and that severe asthma is not a single entity, but an extreme end of the spectrum of several different asthma endotypes.