Evaluation of Frequency of CMV Replication and Disease Complications Reveals New Cellular Defects and a Time Dependent Pattern in CVID Patients.

PURPOSE: Common Variable Immunodeficiency (CVID) is characterized by hypogammaglobulinemia and failure of specific antibody production due to B-cell defects. However, studies have documented various T-cell abnormalities, potentially linked to viral complications. The frequency of Cytomegalovirus (CMV) replication in CVID cohorts is poorly studied. To address this gap in knowledge, we set up an observational study with the objectives of identifying CVID patients with active viraemia (CMV, Epstein-Barr virus (EBV)), evaluating potential correlations with immunophenotypic characteristics, clinical outcome, and the dynamic progression of clinical phenotypes over time. METHODS: 31 CVID patients were retrospectively analysed according to viraemia, clinical and immunologic characteristics. 21 patients with non CVID humoral immunodeficiency were also evaluated as control. RESULTS: Active viral replication of CMV and/or EBV was observed in 25% of all patients. CMV replication was detected only in CVID patients (16%). CVID patients with active viral replication showed reduced HLA-DR+ NK counts when compared with CMV-DNA negative CVID patients. Viraemic patients had lower counts of LIN-DNAMbright and LIN-CD16+ inflammatory lymphoid precursors which correlated with NK-cell subsets. Analysis of the dynamic progression of CVID clinical phenotypes over time, showed that the initial infectious phenotype progressed to complicated phenotypes with time. All CMV viraemic patients had complicated disease. CONCLUSION: Taken together, an impaired production of inflammatory precursors and NK activation is present in CVID patients with active viraemia. Since "Complicated" CVID occurs as a function of disease duration, there is need for an accurate evaluation of this aspect to improve classification and clinical management of CVID patients.

Clinical and genetic evaluation of hereditary myopathies in an adult Saudi cohort.

BACKGROUND: Diagnosis of hereditary myopathy is often challenging owing to overlapping clinical phenotypes and muscle histopathological findings. This retrospective study aimed to identify the phenotypic and genotypic spectra of hereditary myopathies at a tertiary hospital in Riyadh, Saudi Arabia. METHODS: We reviewed the medical records of patients with hereditary myopathy who were evaluated between January 2018 and December 2022. RESULTS: Eighty-seven patients (78 families) were included, two-thirds were men with a mean age of 35 (SD 14.2) years. Limb-girdle muscular dystrophy (LGMD) was the most prevalent clinical diagnosis (25 cases; 29%), of whom, a genetic diagnosis was achieved in 15 of 22 patients tested (68%). In genetically confirmed LGMD, the most prevalent disorders were dysferlinopathy (27%) followed by fukutin-related protein (FKRP) - related limb girdle muscular dystrophy (20%), sarcoglycanopathy (20%), lamin A/C related myopathy (13%), and calpain-3 myopathy (13%). In 26 patients with pathogenic/likely pathogenic variants, the genetic testing method was whole exome sequencing (WES) (42%), Next generation sequencing (NGS) (31%), and targeted single gene analysis (27%). The sensitivity of each genetic testing method was as follows: 100% for targeted single-gene analysis, 100% for targeted analysis of D4Z4 repeat array units, 88% for myotonic dystrophy protein kinase (DMPK) repeat expansion analysis, 42% for NGS-neuromuscular panel, and 46% for WES. CONCLUSION: The prevalent types of hereditary myopathies were consistent with those reported locally and internationally. This study highlights the diagnostic yield of various molecular genetic tests for the diagnosis of hereditary myopathy in an adult cohort and the need for improved access to advanced molecular testing in cases suspected to have facioscapulohumeral muscular dystrophy (FSHD) or mitochondrial myopathies.

Phenotypes of cough in children: A latent class analysis.

INTRODUCTION: Distinguishing phenotypes among children with cough helps understand underlying causes. Using a statistical data-driven approach, we aimed to identify and validate cough phenotypes based on measurable traits, physician diagnoses, and prognosis. METHODS: We used data from the Swiss Paediatric Airway Cohort and included 531 children aged 5-16 years seen in outpatient clinics since 2017. We included children with any parent-reported cough (i.e. cough without a cold, cough at night, cough more than other children, or cough longer than 4 weeks) without current wheeze. We applied latent class analysis to identify phenotypes using nine symptoms and characteristics and selected the best model using the Akaike information criterion. We assigned children to the most likely phenotype and compared the resulting groups for parental atopy history, comorbidities, spirometry, fractional exhaled nitric oxide (FeNO), skin prick tests and specific IgE, physician diagnoses, and 1-year prognosis. RESULTS: We identified four cough phenotypes: non-specific cough (26%); non-allergic infectious and night cough with snoring and otitis (4%); chronic allergic dry night cough with snoring (9%); and allergic non-infectious cough with rhino-conjunctivitis (61%). Children with the allergic phenotype often had family or personal history of atopy and asthma diagnosis. FeNO was highest for the allergic phenotype [median 17.9 parts per billion (ppb)] and lowest for the non-allergic infectious phenotype [median 7.0 parts per billion (ppb)]. Positive allergy test results differed across phenotypes (p < .001) and were most common among the allergic (70%) and least common among the non-specific cough (31%) phenotypes. Subsequent wheeze was more common among the allergic than the non-specific phenotype. CONCLUSION: We identified four clinically relevant cough phenotypes with different prognoses. Although we excluded children with current wheeze, most children with cough belonged to allergy-related phenotypes.

Study of the gut microbiome in Egyptian patients with Parkinson's Disease.

BACKGROUND: Recently, an important relationship between Parkinson's disease and the gut microbiota, through the brain-gut axis interactions, has been established. Previous studies have declared that alterations in the gut microbiota have a great impact on the pathogenesis and clinical picture of Parkinson's disease (PD). The present study aimed to identify the gut microbiome that is likely related to Parkinson's disease as well as their possible relation to clinical phenotypes. METHODS: Thirty patients with Parkinson's disease, who presented to the Parkinson's disease Neurology Clinic of Alexandria University Hospital were enrolled in our study. A cross-matching control group of 35 healthy subjects of similar age and sex were included. Stool specimens were taken from each. Quantitative SYBR Green Real-Time PCR was done for the identification and quantitation of selected bacterial phyla, genera and/or species. RESULTS: There was a significant increase in Bacteroides and a significant decrease of Firmicutes and Firmicutes / Bacteroidetes ratio and Bifidobacteria in PD patients. Although Prevotella was decreased among PD patients relative to the healthy control, the difference was not statistically significant. Comparing the PD clinical phenotypes with the control group, the Mixed phenotype had significantly higher Bacteroides, Tremors predominant had lower Firmicutes and Firmicutes / Bacteroidetes ratio, and both tremors and postural instability and gait disability (PIGD) phenotypes had lower Bifidobacteria. However, there was no statistically significant difference between these phenotypes. Furthermore, when comparing tremors and non-tremors predominant phenotypes; Lactobacilli showed a significant decrease in non-tremors predominant phenotypes. CONCLUSIONS: The current study showed evidence of changes in the gut microbiome of Parkinson's disease patients compared to the healthy controls. These observations may highlight the importance of the identification of microbiome and specific bacterial changes that can be targeted for the treatment of Parkinson's disease.

Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis.

BACKGROUND: Identification of clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment. However, previous attempts did not take into account temporal dynamics with high granularity. By including the dimension of time, we aim to gain further insights into the heterogeneity of COVID-19. METHODS: We used granular data from 3202 adult COVID patients in the Dutch Data Warehouse that were admitted to one of 25 Dutch ICUs between February 2020 and March 2021. Parameters including demographics, clinical observations, medications, laboratory values, vital signs, and data from life support devices were selected. Twenty-one datasets were created that each covered 24 h of ICU data for each day of ICU treatment. Clinical phenotypes in each dataset were identified by performing cluster analyses. Both evolution of the clinical phenotypes over time and patient allocation to these clusters over time were tracked. RESULTS: The final patient cohort consisted of 2438 COVID-19 patients with a ICU mortality outcome. Forty-one parameters were chosen for cluster analysis. On admission, both a mild and a severe clinical phenotype were found. After day 4, the severe phenotype split into an intermediate and a severe phenotype for 11 consecutive days. Heterogeneity between phenotypes appears to be driven by inflammation and dead space ventilation. During the 21-day period, only 8.2% and 4.6% of patients in the initial mild and severe clusters remained assigned to the same phenotype respectively. The clinical phenotype half-life was between 5 and 6 days for the mild and severe phenotypes, and about 3 days for the medium severe phenotype. CONCLUSIONS: Patients typically do not remain in the same cluster throughout intensive care treatment. This may have important implications for prognostic or predictive enrichment. Prominent dissimilarities between clinical phenotypes are predominantly driven by inflammation and dead space ventilation.

Sexual function in Chinese women with different clinical phenotypes of polycystic ovary syndrome.

Objective: To investigate sexual function stratified according to four clinical phenotypes of polycystic ovary syndrome (PCOS) and its association with clinical and quality of life parameters, and to compare these with healthy controls in Chinese women with PCOS. Methods: A cross-sectional study was designed in 1000 PCOS women and 500 control women aged 18-45 years. PCOS women were grouped into four clinical phenotypes according to the Rotterdam Criteria. FSFI (Female Sexual Function Index), SF-12 (the 12-item short form health survey) and clinical and hormonal characteristics likely to affect sexual function were determined. Results: 809 PCOS women and 385 control women with complete parameters were evaluated after screening. Phenotype A had a lower total FSFI mean score (23.14 ± 3.22) compared with phenotype D and control group (p < 0.05). The control group had the highest total FSFI mean score (24.98 ± 3.78). For the percentage at risk of sexual dysfunction, phenotype A (87.5%) and phenotype B (82.46%) had a higher risk of female sexual dysfunction (FSD) than that in phenotype C (75.34%), phenotype D (70.56%) and control group (61.30%) (p < 0.05). SF-12 mental domain scores were significantly lower in phenotypes A and B compared with phenotypes C and control group (p < 0.05). Infertility treatment, bioavailable testosterone, psychological factors, age and waist circumference presented negative correlation with female sexual function. Conclusions: The risk of FSD in PCOS women seemed to be associated with PCOS clinical phenotypes. The classical PCOS phenotype with oligo-ovulation and hyperandrogenism had a higher risk of sexual dysfunction.

Clinical Symptoms Influencing Parkinson's Patients' Quality of Life in Latvia: A Single-Center Cohort Study.

Background and Objectives: Parkinson's disease (PD) is a chronic, progressive illness with a profound impact on health-related quality of life, and it is crucial to know what factors influence the quality of life throughout the course of the disease. This study aimed to evaluate PD patients' motor and non-motor symptoms to compare symptom severity between PD clinical phenotypes and to assess the impact of disease symptoms on quality of life in a cohort of Latvian patients. Materials and Methods: We evaluated 43 patients with Parkinson's disease. Fourteen patients had tremor dominant (TD) PD, twenty-five patients had postural instability/gait difficulty (PIGD), and four patients had a mixed phenotype. Results: The patients' mean age was 65.21 years, and the disease's mean duration was 7 years. The most common non-motor symptoms were fatigue (95.3%), sleep disturbance (83.7%), daytime sleepiness (83.7%), and pain and other sensations (81.4%). PIGD patients had a higher prevalence of depressed mood, daytime sleepiness, constipation, lightheadedness on standing, cognitive impairment, and severe gastrointestinal and urinary disturbances (as assessed using the SCOPA-AUT domains) compared with TD patients. A high prevalence of fatigue was assessed in both disease subtypes. Health-related quality of life significantly statistically correlated with MDS-UPDRS parts III and IV (r = 0.704), the Hoehn and Yahr scale (r = 0.723), as well as the SCOPA-AUT scale's gastrointestinal (r = 0.639), cardiovascular (r = 0.586), thermoregulatory (r = 0.566) and pupillomotor domains (r = 0.597). Conclusions: The severity of motor symptoms, as well as non-motor symptoms, such as fatigue, apathy, sleep problems and daytime sleepiness, pain, and disturbances in gastrointestinal and cardiovascular function, negatively affect PD patients' health-related quality of life. Thermoregulatory and pupillomotor symptoms also significantly affect PD patients' well-being.

TCR-L: an analysis tool for evaluating the association between the T-cell receptor repertoire and clinical phenotypes.

BACKGROUND: T cell receptors (TCRs) play critical roles in adaptive immune responses, and recent advances in genome technology have made it possible to examine the T cell receptor (TCR) repertoire at the individual sequence level. The analysis of the TCR repertoire with respect to clinical phenotypes can yield novel insights into the etiology and progression of immune-mediated diseases. However, methods for association analysis of the TCR repertoire have not been well developed. METHODS: We introduce an analysis tool, TCR-L, for evaluating the association between the TCR repertoire and disease outcomes. Our approach is developed under a mixed effect modeling, where the fixed effect represents features that can be explicitly extracted from TCR sequences while the random effect represents features that are hidden in TCR sequences and are difficult to be extracted. Statistical tests are developed to examine the two types of effects independently, and then the p values are combined. RESULTS: Simulation studies demonstrate that (1) the proposed approach can control the type I error well; and (2) the power of the proposed approach is greater than approaches that consider fixed effect only or random effect only. The analysis of real data from a skin cutaneous melanoma study identifies an association between the TCR repertoire and the short/long-term survival of patients. CONCLUSION: The TCR-L can accommodate features that can be extracted as well as features that are hidden in TCR sequences. TCR-L provides a powerful approach for identifying association between TCR repertoire and disease outcomes.

GBAP1 polymorphisms (rs140081212, rs1057941 and rs2990220) contribute to reduced risk of gastric cancer.

Aim: This study was designed to evaluate the contribution of GBAP1 variants to gastric cancer (GC) risk in a Chinese Han population. Methods: The genotypes of GBAP1 polymorphisms were detected using the Agena MassARRAY platform. Logistic regression analysis was used to calculate odds ratios (ORs) and 95% CIs. Results: GBAP1 rs140081212 (OR = 0.51, p = 4.50 × 10-07), rs1057941 (OR = 0.48, p = 1.19 × 10-08) and rs2990220 (OR = 0.46, p = 7.34 × 10-09) contribute to reduced GC risk, especially gastric adenocarcinoma. Interestingly, the contribution of GBAP1 variants to GC susceptibility was associated with age, sex, BMI, smoking and drinking. Conclusion: This research suggested that GBAP1 polymorphisms might provide a protective effect against GC occurrence in a Chinese Han population.

Clinical spectrum of COVID-19 and risk factors associated with severity in Spanish children.

We aimed to identify the spectrum of disease in children with COVID-19, and the risk factors for admission in paediatric intensive care units (PICUs). We conducted a multicentre, prospective study of children with SARS-CoV-2 infection in 76 Spanish hospitals. We included children with COVID-19 or multi-inflammatory syndrome (MIS-C) younger than 18 years old, attended during the first year of the pandemic. We enrolled 1200 children. A total of 666 (55.5%) were hospitalised, and 123 (18.4%) required admission to PICU. Most frequent major clinical syndromes in the cohort were mild syndrome (including upper respiratory tract infection and flu-like syndrome, skin or mucosae problems and asymptomatic), 44.8%; bronchopulmonary syndrome (including pneumonia, bronchitis and asthma flare), 18.5%; fever without a source, 16.2%; MIS-C, 10.6%; and gastrointestinal syndrome, 10%. In hospitalised children, the proportions were 28.5%, 25.7%, 16.5%, 19.1% and 10.2%, respectively. Risk factors associated with PICU admission were age in months (OR: 1.007; 95% CI 1.004 to 1.01), MIS-C (OR: 14.4, 95% CI 8.9 to 23.8), chronic cardiac disease (OR: 4.8, 95% CI 1.8 to 13), asthma or recurrent wheezing (OR: 2.5, 95% CI 1.2 to 5.2) and after excluding MIS-C patients, moderate/severe liver disease (OR: 8.6, 95% CI 1.6 to 47.6). However, asthmatic children were admitted into the PICU due to MIS-C or pneumonia, not due to asthma flare.Conclusion: Hospitalised children with COVID-19 usually present as one of five major clinical phenotypes of decreasing severity. Risk factors for PICU include MIS-C, elevation of inflammation biomarkers, asthma, moderate or severe liver disease and cardiac disease. What is Known: • All studies suggest that children are less susceptible to serious SARS-CoV-2 infection when compared to adults. Most studies describe symptoms at presentation. However, it remains unclear how these symptoms group together into clinically identifiable syndromes and the severity associated with them. What is New: • We have gathered the primary diagnoses into five major syndromes of decreasing severity: MIS-C, bronchopulmonary syndrome, gastrointestinal syndrome, fever without a source and mild syndrome. Classification of the children in one of the syndromes is unique and helps to assess the risk of critical illness and to define the spectrum of the disease instead of just describing symptoms and signs.

Novel Prehospital Phenotypes and Outcomes in Adult-Patients with Acute Disease.

An early identification of prehospital phenotypes may allow health care workers to speed up and improve patients' treatment. To determine emergency phenotypes by exclusively using prehospital clinical data, a multicenter, prospective, and observational ambulance-based study was conducted with a cohort of 3,853 adult patients treated consecutively and transferred with high priority from the scene to the hospital emergency department. Cluster analysis determined three clusters with highly different outcome scores and pathological characteristics. The first cluster presented a 30-day mortality after the index event of 45.9%. The second cluster presented a mortality of 26.3%, while mortality of the third cluster was 5.1%. This study supports the detection of three phenotypes with different risk stages and with different clinical, therapeutic, and prognostic considerations. This evidence could allow adapting treatment to each phenotype thereby helping in the decision-making process.

[A cross-sectional study on the clinical phenotypes of rheumatoid arthritis].

OBJECTIVE: To explore the characteristics and clinical phenotypes of rheumatoid arthritis (RA) and provide the basis for further understanding, interventions and outcomes of this disease. METHODS: RA patients attended at Peking University People's Hospital from 2018 to 2021 were enrolled in the study. Data collection included demographic data, the sites and numbers of joints involved, extra-articular manifestations (EAM), comorbidities and laboratory variables. Statistical and bioinformatical analysis was performed to establish clinical subtypes by clustering analysis based on the type of joint involved, EAM involvement and other autoimmune diseases overlapped. The characteristics of each subtype were analyzed. RESULTS: A total of 411 patients with RA were enrolled. The mean age was (48.84±15.17) years, and 346 (84.2%) were females. The patients were classified into 4 subtypes: small joint subtype (74, 18.0%), total joint subtype (154, 37.5%), systemic subtype (100, 24.3%), and overlapping subtype (83, 20.2%). The small joint subtype had no medium or large joint involvement, and 35.1% had systemic involvement. The erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) levels and platelet count (PLT) were lower than those in other subtypes, and the rates of positive rheumatoid factors (RF-IgA and RF-IgG) were significantly higher in the small joint subtype. The total joint subtype had both large and small joint involvement but no systemic involvement. The rate of morning stiffness and positive antinuclear antibodies (ANA) in this subtype were lower than those in other subtypes. In the systemic subtype, interstitial lung disease and secondary Sjögren syndrome were the most common systemic involvements, with prominent levels of disease activity score 28-joint count (DAS28-ESR and DAS28-CRP). The overlapping subtype was commonly combined with Hashimoto's thyroiditis or primary Sjögren syndrome. Female in the overlapping subtype was more common than in other subtypes. This subtype was characterized by hyperglobulinemia, hypocomplementemia and high rate of positive ANA, especially spotting type. CONCLUSION: Based on the clinical features, RA patients could be classified into 4 subtypes: small joint subtype, total joint subtype, systemic subtype, and overlapping subtype. Each subtype had its own clinical characteristics. They help for further understanding and a more individualized treatment strategy of RA.

Impact of clinical phenotypes on management and outcomes in European atrial fibrillation patients: a report from the ESC-EHRA EURObservational Research Programme in AF (EORP-AF) General Long-Term Registry.

BACKGROUND: Epidemiological studies in atrial fibrillation (AF) illustrate that clinical complexity increase the risk of major adverse outcomes. We aimed to describe European AF patients' clinical phenotypes and analyse the differential clinical course. METHODS: We performed a hierarchical cluster analysis based on Ward's Method and Squared Euclidean Distance using 22 clinical binary variables, identifying the optimal number of clusters. We investigated differences in clinical management, use of healthcare resources and outcomes in a cohort of European AF patients from a Europe-wide observational registry. RESULTS: A total of 9363 were available for this analysis. We identified three clusters: Cluster 1 (n = 3634; 38.8%) characterized by older patients and prevalent non-cardiac comorbidities; Cluster 2 (n = 2774; 29.6%) characterized by younger patients with low prevalence of comorbidities; Cluster 3 (n = 2955;31.6%) characterized by patients' prevalent cardiovascular risk factors/comorbidities. Over a mean follow-up of 22.5 months, Cluster 3 had the highest rate of cardiovascular events, all-cause death, and the composite outcome (combining the previous two) compared to Cluster 1 and Cluster 2 (all P < .001). An adjusted Cox regression showed that compared to Cluster 2, Cluster 3 (hazard ratio (HR) 2.87, 95% confidence interval (CI) 2.27-3.62; HR 3.42, 95%CI 2.72-4.31; HR 2.79, 95%CI 2.32-3.35), and Cluster 1 (HR 1.88, 95%CI 1.48-2.38; HR 2.50, 95%CI 1.98-3.15; HR 2.09, 95%CI 1.74-2.51) reported a higher risk for the three outcomes respectively. CONCLUSIONS: In European AF patients, three main clusters were identified, differentiated by differential presence of comorbidities. Both non-cardiac and cardiac comorbidities clusters were found to be associated with an increased risk of major adverse outcomes.

The susceptibility of attaining and maintaining DMARD-free remission in different (rheumatoid) arthritis phenotypes.

OBJECTIVES: To compare (sustained) DMARD-free remission rates((S)DFR), defined as respectively ≥6 months and >1 year, after 2 and 5 years between three clinical arthritis phenotypes; undifferentiated arthritis(UA), autoantibody-negative(RA-) and positive rheumatoid arthritis(RA+). METHODS: All UA(n = 130), RA-(n = 176) and RA + (n = 331) patients from the tREACH trial, a stratified single-blinded trial with a treat-to-target approach, were used. (S)DFR comparisons between phenotypes after 2 and 5 years were performed with Logistic regression. Medication use and early and late flares(DAS ≥ 2.4), respectively defined as < 12 and >12 months after reaching DFR, were also compared. Cox proportional hazard models were used to evaluate potential predictors for (S)DFR. RESULTS: Within 2 and 5 years less DFR was seen in RA + (17.2-25.7%), followed by RA-(28.4-42.1%) and UA patients(43.1-58.5%). This also applied for SDFR within 2 and 5 years (respectively 7.6% and 21.4%; 20.5% and 38.1%; and 35.4% and 55.4%). A flare during tapering was seen in 22.7% of patients. Of the patients in DFR 7.5% had an early flare and 3.4% a late flare. Also more treatment intensifications occurred in RA+ compared with RA- and UA. We found that higher baseline DAS, ACPA positivity, BMI and smoking were negatively associated with (S)DFR, while clinical phenotype(reference RA+), short symptom duration(<6 months) and remission within 6 months were positively associated. CONCLUSIONS: (Long-term) clinical outcomes differ between undifferentiated arthritis, autoantibody-negative and positive rheumatoid arthritis(RA). These data reconfirm that RA can be subdivided into aforementioned clinical phenotypes and that treatment might be stratified upon these phenotypes, although validation is needed. TRIAL REGISTRATION: ISRCTN, https://www.isrctn.com/, ISRCTN26791028.

The impact of different (rheumatoid) arthritis phenotypes on patients' lives.

OBJECTIVES: To compare patient-reported outcome (PRO) domains between three arthritis phenotypes [undifferentiated arthritis (UA), autoantibody-negative RA (RA-) and autoantibody-positive RA (RA+)] at diagnosis, after 2 years and over time. METHODS: All UA (n = 130), RA- (n = 176) and RA+ (n = 331) patients from the tREACH trial, a stratified single-blinded trial with a treat-to-target approach, were used. PRO comparisons between phenotypes at baseline and after 2 years were performed with analysis of variance, while a linear mixed model compared them over time. Effect sizes were weighted against the minimal clinically important differences (MCIDs) for each PRO. RESULTS: RA- patients had a higher disease burden compared with RA+ and UA. At baseline and after 2 years, RA- patients had more functional impairment and a poorer Physical Component Summary (PCS) compared with the other phenotypes, while they only scored worse for general health and morning stiffness duration at baseline. The MCIDs were exceeded at baseline, except for functional ability between RA+ and UA, while after 2 years only the MCID of the PCS was exceeded by RA- compared with UA and RA. After 2 years the PROs of all phenotypes improved, but PROs measuring functioning were still worse compared with the general population, even when patients had low disease activity. CONCLUSION: RA- patients had the highest disease burden of all phenotypes. Although most patients have low disease activity after treatment, all clinical phenotypes still have a similar significant impact on patients' lives, which is mainly physical. Therefore it is important to assess and address PROs in daily practice because of persistent disease burden despite low disease activity. TRIAL REGISTRATION: ISRCTN26791028.

Mask-induced Koebner phenomenon and its clinical phenotypes: A multicenter, real-life study focusing on 873 dermatological consultations during COVID-19 pandemics.

During COVID-19 pandemic, wearing masks for prevention became mandatory but evidence suggest that is also detrimental for skin. Although facial dermatoses due to masks increase in both healthcare workers and general population, a pathogenetic hypothesis remains still elusive. We aimed to evaluate the prevalence of dermatological consultations due to Koebner triggered dermatoses In this prospective, multicenter, real life study carried out in Italy from March 11th to December 11th 2020 during COVID-19 pandemics, dermatological consultations (in-person and telemedicine) to study the prevalence of Koebner (KB) phenomenon due to masks were evaluated. Boyd and Nelder classification was adopted for Koebner phenomenon and Bizzozero's for KB intensity. A total of 229/873 (26.2%) dermatological consultations were KB triggered dermatoses and lesions were located in mask-covered ear area (76 [33.2%]), malar area (73 [31.8%]), perioral area (53 [23.1%]), and nose (27 [11.8%]). The first KB category grouped 142 patients (psoriasis, vitiligo, maskne, and mask rosacea), the second one 24 (warts, molluscum contagiosum, and impetigo), the third one 46 (atopic dermatitis), and the fourth one 17 (eczema). Among previously KB negative psoriatic patients that became KB positive, 9/13 (69.2%) had discontinued or modified the prescribed antipsoriatic treatment. Mask-related Koebner phenomenon is an important clinical sign to orient clinician's therapeutic protocols during COVID-19 pandemic, especially in patients with psoriasis.

The Effect of Sleep Apnea on Cardiovascular Events in Different Acute Coronary Syndrome Phenotypes.

Rationale: Obstructive sleep apnea (OSA) is associated with increased cardiovascular disease (CVD) risk. Conversely, OSA has not been shown to increase recurrent cardiovascular events in patients with acute coronary syndrome (ACS). This lack of homogeneity could suggest that the deleterious effect of OSA and its contribution to CVD could depend on specific patient profiles.Objectives: To evaluate the effect of OSA on cardiovascular risk for patients with different ACS phenotypes.Methods:Post hoc analysis of the ISAACC (Continuous Positive Airway Pressure in Patients with ACS and OSA) study, including 1,701 patients admitted for ACS (NCT01335087). To evaluate the presence of OSA (apnea-hypopnea index ≥ 15 events · h-1), all patients underwent polygraphy. Patients were followed up for a minimum period of 1 year. We performed nonsupervised clustering using latent class analysis to identify subgroups of patients on the basis of 12 clinical factors associated with cardiovascular risk. The effect of OSA on recurrent cardiovascular event risk was evaluated for each phenotype identified.Measurements and Main Results: Two phenotypes were identified: patients without previous heart disease and without previous ACS ("no-previous-CVD" phenotype; 81%) and patients with previous heart disease and previous ACS ("previous-CVD" phenotype; 19%). The median (interquartile range) at follow-up was 2.67 (3.8) years. For the no-previous-CVD phenotype, the effect of OSA showed an adjusted hazard ratio (95% confidence interval) of 1.54 (1.06-2.24; P value = 0.02), whereas for the previous-CVD phenotype, the effect of OSA showed an adjusted hazard ratio of 0.69 (0.46-1.04; P value = 0.08).Conclusions: For patients with ACS and a specific phenotype, OSA is associated with an increased risk of recurrent cardiovascular events. These patients are mainly characterized by no previous heart disease and admission for a first ACS occurrence.

Diabetes and Genetics: A Relationship Between Genetic Risk Alleles, Clinical Phenotypes and Therapeutic Approaches.

Unveiling human genome through successful completion of Human Genome Project and International HapMap Projects with the advent of state of art technologies has shed light on diseases associated genetic determinants. Identification of mutational landscapes such as copy number variation, single nucleotide polymorphisms or variants in different genes and loci have revealed not only genetic risk factors responsible for diseases but also region(s) playing protective roles. Diabetes is a global health concern with two major types - type 1 diabetes (T1D) and type 2 diabetes (T2D). Great progress in understanding the underlying genetic predisposition to T1D and T2D have been made by candidate gene studies, genetic linkage studies, genome wide association studies with substantial number of samples. Genetic information has importance in predicting clinical outcomes. In this review, we focus on recent advancement regarding candidate gene(s) associated with these two traits along with their clinical parameters as well as therapeutic approaches perceived. Understanding genetic architecture of these disease traits relating clinical phenotypes would certainly facilitate population stratification in diagnosing and treating T1D/T2D considering the doses and toxicity of specific drugs.

Phenotyping of IgG4-related diseases based on affected organ pattern: A multicenter cohort study using cluster analysis.

OBJECTIVES: Immunoglobulin G4-related disease (IgG4-RD) is a systemic, multiorgan disease of unknown etiology. We aimed to classify IgG4-RD by a combination pattern of affected organs and identify the clinical features, including the comorbidities of each subgroup. METHODS: Patients diagnosed with IgG4-RD between April 1996 and June 2018 were enrolled from three institutes. Hierarchical cluster analysis was performed using six frequently affected organs (lacrimal gland and/or orbit, salivary gland, lung, pancreas, kidney, and retroperitone and/or aorta). Clinical features, such as comorbidities and outcomes, were compared between clusters. RESULTS: In total, 108 patients enrolled in this cohort could be stratified into five distinct subgroups: group 1, lung dominant group; group 2, retroperitoneal fibrosis and/or aortitis dominant group; group 3, salivary glands limited group; group 4, Mikulicz's disease dominant group; and group 5, autoimmune pancreatitis with systemic involvement group. There were significant between-group differences in sex (male dominant in group 1, 2, and 5), history of asthma and allergies on the respiratory tract (most frequent in group 5), and malignancy (most frequent in group 5). CONCLUSION: IgG4-RD can be classified into subgroups according to the pattern of affected organs. Group 5 may have frequent complications with allergies and malignancies.

Chronic obstructive pulmonary disease: diagnosis and treatment of stable phase of disease; personalized treatment approach using phenotype features of the disease Summary of the 2020-2021 Czech Pneumological and Phthiseological Society position paper.

Chronic obstructive pulmonary disease (COPD) is a heterogenous condition affecting hundreds of millions of people worldwide. COPD is a major health problem associated with significant morbidity and mortality. In this review, the authors present the current concept of care for patients with COPD in the Czech Republic, along with a summary of treatment recommendations formulated by the expert group of the Czech Pneumological and Phthisiological Society. A more detailed version of the position paper was published in 2020. The aim of this work was to transform the most recent scientific knowledge into the context of daily practice in the Czech Republic. Our concept of care for patients with COPD uses a complex approach with special emphasis on individual phenotypic features of the disease. Maximal effort has been put into individualization of treatment according to the presence of certain clinical phenotypes/treatable traits with respect to current scientific knowledge.