Disease Subgroups Research Articles

Muscle Strength and Cardiovascular Health in MASLD: A Prospective Study

Background and Objectives: The pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD) remains incompletely understood. However, recent studies highlight the interactions between muscle, liver, and adipose tissue. This study aimed to explore the relationships between clinical indicators of MASLD and sarcopenia, cardiorespiratory fitness, fatigue, and mood. Materials and Methods: The study involved 60 participants, including 28 healthy controls and 32 with MASLD, categorized into two disease subgroups: 15 with MASL and 17 with metabolic dysfunction-associated steatohepatitis (MASH). Participants completed an incremental speed shuttle walk test to evaluate cardiorespiratory fitness, a hand-held dynamometer assessment for appendicular muscle strength, and the timed up and go test for physical performance. Physical activity level, fatigue, quality of life, and emotional state were assessed using questionnaires. The test results were compared between groups and with disease characteristics. Results: MASL and MASH groups showed reduced cardiorespiratory fitness (p < 0.001). The knee extensors were significantly weaker in both MASL and MASH groups (p < 0.001 and p = 0.001, respectively). The MASH group reported higher levels of depression and negative health perception (p = 0.006 and p = 0.03, respectively). Muscle strength in patients with MASLD showed a significant negative association with depression (OR = −0.384, 95% CI: −3.10 to −0.74, p = 0.003), intrahepatic triglyceride content (OR = −0.287, 95% CI: −1.31 to −0.11, p = 0.023), and LDL (OR = −0.286, 95% CI: −0.02 to −0.33, p = 0.03). In contrast, a positive association was observed between VO2 and muscle strength (OR = 0.531, 95% CI 1.27 to 3.47, p < 0.001). Conclusions: This study suggests that muscle strength is linked to key metabolic parameters, such as hepatic fat, LDL levels, and aerobic capacity, that may contribute to the development and progression of MASLD. Interventions aimed at preserving or enhancing muscle strength in MASLD patients may be essential for preventing liver damage and improving metabolic health.

Chronic Rhinosinusitis with Nasal Polyps and Biologics: A Call for Better Data Standardisation and Presentation in Clinical Studies.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is often severe, debilitating and difficult to treat. Recent randomised control trials (RCTs) of biologics that target key inflammatory pathways have demonstrated clinical efficacy in treating CRSwNP. Such RCTs must facilitate meta-analysis. Here we report the need for urgent improvement in double-blind randomised controlled trials of biologics in CRSwNP, having previously undertaken a systematic review and meta-analysis of such studies. The RCTs included in that systematic review did not conform to a standard study design. Patient selection criteria was not consistent in studies with several heterogeneous disease subgroups of CRSwNP patients present in each study. Different durations of treatment and variable outcome measures also made the comparative assessment of efficacy between different biologics difficult. Data presentation to allow extraction for meta-analysis was not always clear, such that on occasion selected data sets or even an entire RCT had to be excluded from further evaluation. As such, the high heterogeneity between studies made the overall interpretation of the findings difficult. We make an urgent call to design and conduct future RCTS of biologics in CRSwNP in a more standardised manner, and to present data in a clear way that is easily extractable. This will facilitate more inclusive and thus robust evaluation and interpretation via meta-analysis, which will in turn enable clearer insight into which CRSwNP patient subgroups might benefit from specific biologics and thus achieve better clinical outcomes.

Salivary features of periodontitis and gingivitis in type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is associated with cellular abnormalities, tissue and organ dysfunctions, and periodontitis. This investigation examined the relationship between the oral microbiome and salivary biomarkers in T2DM patients with or without periodontitis. This cohort (35–80 years) included systemically healthy non-periodontitis (NP; n = 31), T2DM without periodontitis (DWoP; n = 32) and T2DM with periodontitis (DWP; n = 29). The oral microbiome [Operational Taxonomic Units (OTUs)] (16 s rRNA sequencing) and targeted host salivary biomarkers (immunoassays) were assessed. We identified 47 OTUs that were significantly different in abundance between NP samples and any disease subset or between disease subgroups. The most unique microbiome patterns were observed in the DWP group. Differences in genera/species abundance were also observed when T2DM patients were stratified by extent of periodontal inflammation and disease (i.e., generalized versus localized gingivitis/periodontitis). Salivary biomarkers showed significant elevations in MMP-8, MMP-9, resistin, IL-1β, IL-6, IFNα, and BAFF (THFSR13b) comparing generalized to localized periodontitis. Salivary analytes showed significant positive correlations with specific microbiome members, predominantly in DWP patients. Odds ratio analyses reinforced that a panel of biologic markers (IL-6, MMP-8) and bacteria (e.g., Bacteroidetes, Fusobacteria, Spirochaetes) discriminated the severity and extent of periodontal disease in this diabetic population.

Clozapine and rapamycin reverse behavioral abnormalities in an animal model of autoimmune schizophrenia.

Autoantibody-associated psychosis represents a distinct disease subgroup of patients with schizophrenia with a suspected autoimmune origin. Although preliminary studies have suggested adjunctive drug treatment strategies targeting the immune system, further validation of these findings is warranted. Autoantibodies against SFT2D2 have been identified in patients with schizophrenia. ApoE-/- mice immunized with SFT2D2-peptides can be used as a model for testing immunotherapy in this subgroup of patients. We used the atypical antipsychotic drug clozapine and immunosuppressant rapamycin to test their effects in this mouse model. The mice were evaluated for cognitive and schizophrenia-like behaviors. Following behavioral testing, brain samples were collected for analyzing specific pathological changes and dendritic spine formation. Clozapine and rapamycin reversed impaired pre-pulse inhibition, motor impairment, and improved cognitive ability in ApoE -/- mice exposed to anti-SFT2D2 immunoglobulin G. Immunohistochemical assays revealed that both clozapine and rapamycin significantly reduced activated microglial infiltration and restored neuronal dendritic spine density. Our study results suggested that clozapine and rapamycin possess therapeutic benefits for managing autoimmune psychosis and provide mechanistic insights into immunotherapies involving immunosuppressive agents.

Randomized Trial of Pulsatile and Nonpulsatile Flow in Cyanotic and Acyanotic Congenital Heart Surgery.

The study objective was to determine the impact of cardiopulmonary bypass perfusion modalities on cerebral hemodynamics and clinical outcomes in congenital cardiac surgery patients stratified by acyanotic versus cyanotic heart disease. A total of 159 pediatric (age <18 years) cardiac surgery patients were prospectively randomized to pulsatile or nonpulsatile cardiopulmonary bypass and stratified by type of congenital heart disease: acyanotic versus cyanotic. Intraoperative cerebral gaseous microemboli counts and middle cerebral artery pulsatility index were assessed. Organ injury was quantified by Pediatric Logistic Organ Dysfunction-2 (PELOD-2) score at 24, 48, and 72 h postoperatively. Additional outcomes included Pediatric Risk of Mortality-3 score, vasoactive-inotropic score, duration of mechanical ventilation, intensive care and hospital length of stay, and 180-day mortality. Heterogenous variance linear models (ie, ANOVA and mixed models) and χ2 tests were used to compare groups for continuous and categorical variables, respectively. Within congenital heart disease subgroups, patients randomized to nonpulsatile versus pulsatile bypass had similar preoperative and operative characteristics. While the intraoperative pulsatility index was higher in the pulsatile subset of both acyanotic and cyanotic groups (P < .05), regional cerebral oxygen saturation, mean arterial pressure, and gaseous microemboli counts were similar. Postoperative PELOD-2 scores decreased at similar rates in the acyanotic and cyanotic subgroups regardless of the perfusion modality utilized. There were also no significant between-group differences in the additional postoperative outcomes by perfusion modality in either acyanotic or cyanotic groups. Despite patients undergoing pulsatile cardiopulmonary bypass experiencing a more physiologic pulsatility index in both acyanotic and cyanotic groups, no significant differences in cerebral hemodynamics or clinical outcomes were appreciated.

Alpha-synuclein seed amplification assay longitudinal outcomes in Lewy body disease spectrum.

Evidence from neuropathological cohorts indicates that a CSF α-synuclein (α-syn) seed amplification assay (SAA) may provide quantitative kinetic parameters correlating with α-syn pathology burden in patients with Lewy body disease (LBD). Studies are needed to assess their longitudinal trend during the pre-symptomatic and clinical disease phases and their correlation with measures of disease progression. We aimed to assess the baseline α-syn CSF SAA kinetic parameters, their longitudinal variations and associations with clinical outcomes in a cohort of longitudinally repeatedly sampled Lewy Body disease patients, including clinically unimpaired (asymptomatic LBD) and neurologically impaired individuals. Participants from the prospective BioFINDER-1 study with longitudinal CSF collections (n=718) were screened by α-syn SAA. CSF samples were tested in four replicates blinded to clinical diagnoses. The number of positive replicates (Nrep), the time needed by the fluorescence signal to reach the threshold (Lag) and the highest intensity of the fluorescent signal (Imax). were analysed at baseline (time of first positive SAA) in all participants and longitudinally in those with at least two α-syn positive CSF samples available. One hundred ninety-six individuals (whole cohort) showing α-syn seeding activity were included. Of those, 170 participants tested positive by SAA in all available samples, while 26 converted from a negative to a positive test result during follow-up (LBD-converters), suggesting an early LBD stage. At baseline, LBD-converters showed lower Nrep (p=0.001) and a longer Lag (p=0.001) than subjects displaying α-syn seeding activity from the first available sample. Nrep increased longitudinally in the whole cohort (β=0.09, 95% confidence interval (95%CI) 0.06-0.12, p<0.001), in asymptomatic LBD (β=0.15, 95%CI 0.09-0.21, p<0.001) and Parkinson's disease individuals without dementia (β=0.07, 95%CI 0.02-0.12, p=0.01). The Lag decreased longitudinally in asymptomatic LBD (β=-0.24, 95%CI -0.42 - -0.06, p=0.008). Baseline Nrep predicted the subsequent appearance of dementia in the whole cohort (Hazard ratio (HR) 1.57, 95%CI 1.19-2.07, p=0.001) and the Parkinson's disease subgroup (HR 1.83, 95%CI 1.17-2.85, p=0.008). The difference between the Lag at each sampling and that at baseline was negatively associated with the appearance of dementia in the whole cohort (HR 0.76, 95%CI 0.59-0.99, p=0.04) and Parkinson's disease subgroup (HR 0.69, 95%CI 0.50-0.95, p=0.02). α-syn SAA parameters Nrep and Lag showed associations with the LBD stage and the development of dementia. Furthermore, their longitudinal variation is coherent with pathology progression over time. These data support the use of SAA kinetic parameters to monitor disease progression and therapeutic response.

Important Guide for Natural Compounds Inclusion in Precision Medicine

Precision medicine describes the definition of disease at a higher resolution by genomic and other technologies to enable more precise targeting of disease subgroups with new therapies. Preventative or therapeutic interventions can be developed with the knowledge of how a compound acts safely in the body to target receptors and produce the desirable effect. With the completion of the Human Genome Project in 2003 and the rapid increase in sequencing and bioinformatics tools, obtaining information about a person's genome is becoming more accessible. To make use of genetic information in precision or personalised medicine, it is important to examine the roles of natural remedies in the individualization of treatment - to use as the right drug, at the correct dose, for the right person, at the right time. Integrating biomarkers, especially within clinical workflows, plays a crucial role in implementing precision medicine. Though the horizon in precision medicine looks promising, one major issue resides in the precise mapping into clearly defined medical conditions associated with biomarker identification and precedence ranking. This communication is met to provide guidelines that could improve biomarker discovery and enhance the participation and integration of novel natural compounds in the processes of implementing precision or personalized medicine.

Sublingual varices as predictor of factors associated with cardiovascular diseases: A systematic review with meta-analysis.

Sublingual varicose veins are variations of normality that appear more prominent during aging. The systematic review aim to investigate sublingual varicose veins frequency in patients exposed to systemic and environmental exposed factors linked to cardiovascular diseases. This systematic review was based on the PECO strategy, and the PubMed, Web of Science, Scopus, Embase and Grey Literature library were searched for publications examining the association between sublingual varicose veins and systemic and environmental exposed factors linked to cardiovascular diseases, such as hypertension, diabetes, smoking, and leg varices. A meta-analysis was conducted using random-effects models. This review included 11 studies with a total of 2,272 patients with sublingual varicosity and systemic exposed factors linked to cardiovascular diseases. The quality assessment was improved by Newcastle and Ottawa Scales (NOS). Consistent results were observed across all systemic and environmental exposed factors linked to cardiovascular diseases subgroups. We found association between sublingual varicose veins and hypertension [p = 0.0002; 95%IC2.90 [1.66-5.06]; I2 91%); diabetics (p = 0.009; 95%IC 3.19 [1.34 - 7.62]; I2 84%); tobacco abuse (p = 0.002; 95%IC 1.97 [1.29 - 3.01]; I2 82%) and leg varicosity (p = 0.03; 95%IC 2.63 [1.08 - 6.44]; I2 95%). Seven articles received score 7, indicating good quality and four articles received moderate quality. Patients exposed to exposed factors that affect blood vessels showed a higher prevalence of sublingual varicose veins. These findings emphasize the importance of recognizing oral signs underlying systemic diseases. PROSPERO CRD42023397166.

Health care utilization and cost differences across cognitively‐defined Alzheimer’s disease subgroups

Health care utilization and cost differences across cognitively‐defined Alzheimer’s disease subgroups

Impact of the peak period of coronavirus disease 2019 on 28‐day mortality, emergency department visits and length of hospital stay of emergency admissions: A single center retrospective observational study in Hong Kong

AbstractBackgroundDuring the fifth wave of COVID‐19, accident and emergency departments in Hong Kong experienced significant overcrowding yet there was limited evidence available regarding emergency services and patients' clinical outcomes. The aim of this study was to compare the 28‐day mortality, emergency department (ED) visits, and length of stay (LOS) between the peak period of COVID‐19 and a control period in 2019.MethodThis was a retrospective case‐control study comparing the peak period of COVID‐19 (7 Feb 2022 to 23 Apr 2022) with a control period (7 Feb 2019 to 23 Apr 2019). Patients' characteristics, ED visits, diagnoses, mortality, and LOS were compared.Results35,429 patients were included. The 28‐day in‐hospital mortality was significantly higher in the peak period of COVID‐19 with a risk ratio of 3.91 (95% CI: 3.38–4.53). There was a 36% reduction in ED visits during the peak period of COVID‐19 while there was a 53.7% increase in critical cases at triage. The average LOS of emergency admissions increased from 3.8 days (Median = 2.0; IQR = 1.0–3.0) in the control period to 5.1 days (Median = 2.0; IQR = 1.0–6.0) in the peak period of COVID‐19 especially in the subgroups of chronic kidney disease, influenza and pneumonia, diabetes, and mental disorders.ConclusionIncreased risk of all‐cause 28‐day in‐hospital deaths was observed during the peak period of COVID‐19 along with a reduction in overall ED visits and lengthened LOS.

Exploring the Role of Long Non-Coding RNAs in Predicting Outcomes for Hepatitis B Patients.

Hepatitis B is a significant public health issue worldwide. Long noncoding RNAs (lncRNAs) are pivotal in biological mechanisms. The involvement of lncRNAs in hepatitis Hepatitis B remains incompletely understood. This study sought to explore the potential of certain lncRNAs as diagnostic and prognostic markers in hepatitis B, and their ability to differentiate between clinical disease subgroups. Plasma samples from 204 individuals diagnosed with hepatitis B were meticulously examined for the presence of specific lncRNAs, focusing on those known to be associated with hepatitis B as indicated in the literature. In this study, gene expression levels of 14 lncRNAs were analyzed in three subgroups (chronic, recovered and inactive HBsAg carriers) and compared with those in the healthy control group. The downregulation of the RN7SL1 and Alpha-280 genes in all patients indicates potential diagnostic lncRNAs. ZFHX2-AS1 expression was consistently lower in all subgroups, while SRA1 showed high expression in recovered hepatitis B patients, indicating that it is a descriptive marker. DLG2-AS2 expression increased in the chronic hepatitis B but decreased in the other groups. These findings reveal the prognostic importance of lncRNAs in hepatitis B. The expression levels of ZFHX2-AS1, RN7SL1, PCAT-1, PCA3, SRA1 and Alpha-280 have been identified as crucial biomarkers for the diagnosis of hepatitis B and for distinguishing between its clinical subgroups. A strong association between hepatitis B disease and the gene expression of the DLG2-AS2, HOTTIP, HOTAIRM1, HOXA11-AS, NOS2P3, LINC02665, MEG9, and RNY5 lncRNAs has been suggested.

Preeclampsia and fetal growth restriction: does novel proteomics reveal immunological possible candidate biomarkers?

The aim of this review is to explore a possible link between immunological candidate proteins, identified through modern proteomic techniques, and preeclampsia (PE) and fetal growth restriction (FGR). Proteomics has become a promising tool in the search for disease pathways, drug targets, and biomarkers. PE and FGR are adverse pregnancy complications with supposed immunological involvement in their pathogenesis, but no circulating immunological biomarkers are currently established for diagnosis and risk stratification. Several proteomic studies have aimed to identify PE and FGR biomarkers - often with varying results across studies. However, proteomics has revealed altered expression of human leukocyte antigen-I in PE cases, which is supported in Genome-wide association study (GWAS) studies. Proteomic results support the heterogeneous nature of PE by identification of molecular subgroups - including subgroups characterized by immune-related proteins e.g. CXCL10. No specific immunological markers are found on FGR, but differences in overall plasma proteomic signature have been suggested. Proteomics certainly holds great potential. The immunological component in PE and FGR are still unclarified, but improvements in proteomic technologies may provide both definition of disease subgroups and subsequent discovery of biomarkers and targeted analysis within each subgroup.

Identification of Severe Acute Exacerbations of Chronic Obstructive Pulmonary Disease Subgroups by Machine Learning Implementation in Electronic Health Records.

Acute exacerbations of chronic obstructive pulmonary disease (AECOPDs) are heterogeneous. Machine learning (ML) has previously been used to dissect some of the heterogeneity in COPD. The widespread adoption of electronic health records (EHRs) has led to the rapid accumulation of large amounts of patient data as part of routine clinical care. However, it is unclear whether the implementation of ML in EHR-derived data has the potential to identify subgroups of AECOPD. To determine whether ML implementation using EHR data from severe AECOPDs requiring hospitalization identifies relevant subgroups. This study used 2 retrospective cohorts of patients with AECOPDs (non-COVID-19 and COVID-19) treated at Yale-New Haven Hospital. K-means clustering was used to identify patient subgroups. We identified 3 subgroups in the non-COVID cohort (n=1736). Each subgroup had distinct clinical characteristics. The reference subgroup was the largest (n=904), followed by cardio-renal (n=548) and eosinophilic (n=284). The eosinophilic subgroup had milder severity of AECOPD, including a shorter hospital stay (p<0.01). The cardio-renal subgroup had the highest mortality during (5%) and in the year after hospitalization (30%). Validation of the severe AECOPD classifier in the COVID-19 cohort recapitulated the characteristics seen in the non-COVID cohort. AECOPD subgroups in the COVID-19 cohort had different interleukin (IL)-1 beta, IL-2R, and IL-8 levels (false discovery rate ≤ 0.05). These specific leukocyte and cytokine profiles resulted in inflammatory differences between the AECOPD subgroups based on C-reactive protein levels. Incorporating ML with EHR data allows the identification of specific clinical and biological subgroups for severe AECOPD.

BIOM-44.18F-DOPA-PET THRESHOLDS FOR BOTH NEWLY DIAGNOSED AND RECURRENT ASTROCYTOMA USING PATHOLOGICAL GROUPING OF SPATIALLY CORRELATED BIOPSIES

Abstract BACKGROUND Glioma radiotherapy planning requires accurate tumor delineation. While T1- contrast-enhanced-MRI (T1-CE-MRI) is the standard, due to blood-brain-barrier breakdown dependencies, T1-CE-MRI fails to reflect the extent of glioma. Studies using amino acid PET tracers report glioma uptake up to 3cm-4cm beyond T1-CE. In this study, amino acid tracer 18F-fluoro-dihydroxyphenylalanine (18F-DOPA) uptake was correlated with histopathological features to determine tumor thresholds. METHODS Using registered 18F-DOPA-PET and T1-CE-MRI images in the Stealth Neuronavigation system targeting concordant and discordant regions, 181 stereotactic biopsy samples (newly-diagnosed=74; recurrent=107) were obtained from 59 enrolled astrocytoma patients across two prospective phase II clinical trials between 2010-2019. An experienced neuropathologist reviewed each sample with hematoxylin and eosin stain and assigned an alphanumeric score: mitotic activity (0=no tumor; 1=no mitosis; 2=few/scattered mitosis; 3=frequent mitosis) and cellular density (A=&amp;lt;25%; B=25%-50%; C=50%-75%; D=&amp;gt;75%). Samples assigned 1C-1D, 2B-2D, or 3A-3D were categorized as histopathological high-score (aggressive disease), remaining samples as low-score. Relative mean (rFDOPA_mean) tumor-to-background uptake ratios were computed for 5mm uniformly expanded volumes from each Stealth biopsy coordinate using the crescent and wedge normalization methods. Relative uptake was compared overall and separately within newly-diagnosed/recurrent disease subgroups. An optimal rFDOPA_mean threshold to delineate high- from low-score was determined using the maximal Youden index of ROC curves. RESULTS Overall, high-score samples (n=116) had higher median (IQR) rFDOPA_mean uptake than low-score samples (n=65): high-score rFDOPA:mean=1.70(1.16-2.26), low-score rFDOPA:mean=1.16(0.83-1.49), Kruskal-Wallis p&amp;lt;0.001. The uptake difference between high- vs. low-score samples was observed within newly-diagnosed and recurrent subgroups, but was only significant for newly-diagnosed (p&amp;lt;0.001). For newly-diagnosed, an rFDOPA:mean=1.49 cutoff between high- and low-score groups shows 69% accuracy, 63% sensitivity, 80% specificity (AUC=0.782). Using the wedge normalization method, rFDOPA_mean values were 0.2 higher than crescent method values. CONCLUSIONS This work presents histologically verified 18F-DOPA-PET thresholds for aggressive disease in newly-diagnosed astrocytoma patients. Separate thresholds will need to be determined for recurrent glioma patients.

Diffuse lung diseases ascribed to drugs: a nationwide observational study over 37 years using the French pharmacovigilance database.

Drug-induced interstitial lung disease (DI-ILD) is a heterogeneous subgroup of interstitial lung diseases (ILD). The number of molecules involved is increasing with time. Due to their low incidence, DI-ILDs may be detected only after a drug has been marketed, notably through Adverse Drug Reaction (ADR) reports to pharmacovigilance centres. The aim of our study was to describe drug-induced diffuse lung disease cases notified to and recorded by the French Pharmacovigilance Database (FPVD), reported clinical pictures and the potentially causal drugs. This retrospective study included cases registered in the FPVD from 1st January 1985 to 1st April 2022 which had ADR coded in MedDRA with a High Level Group Term "Lower respiratory tract disorders (excluding obstruction and infection)" involving patients aged 18 and over. We analysed 7234 cases involving 13 059 suspect medications and 1112 specific molecules. Cases were categorised as serious in 96.7% and in 13.3% death ensued. Men accounted for 54.4% of the cases. Median age was 69 [18-103] years. The most prevalent ADRs were "ILD" (51.0%), "Pulmonary oedema" (acute/non-acute) (15.6%) and "Pulmonary fibrosis" (10.5%). "Anti-cancer drugs" (31.2%) and "Cardiovascular drugs" (29.1%) were the most prominent therapeutic classes involved, with amiodarone being the most commonly reported suspected drug (10.0%), followed by methotrexate (3.1%). This study from a large nationwide dataset spanning 37 years is the largest known to date. Drug-induced diffuse lung diseases are serious with a potentially fatal outcome. Accurate diagnoses remain essential to identify it properly and discontinue the culprit drug urgently.

Dye-based chromoendoscopy detects more neoplasia than white light endoscopy in patients with primary sclerosing cholangitis and IBD.

Background and study aims Patients with primary sclerosing cholangitis and inflammatory bowel disease (IBD) have a high risk of colorectal cancer. There is no agreement on the best technique for surveillance for colorectal neoplasia. We aimed to assess whether chromoendoscopy and/or high-definition endoscopy is associated with increased detection of neoplasia in patients with primary sclerosing cholangitis undergoing surveillance compared with when they were not used. Patients and methods This was a single-center, retrospective, observational study designed to analyze differences in the detection of neoplasia (adenomatous and serrated) among patients with primary sclerosing cholangitis and IBD who underwent annual surveillance between 2010 and 2020. Multilevel logistic regression was used to adjust for confounders. Results Ninety-one patients were identified, resulting in 359 colonoscopies with 360 person-years of follow up. Over the study period, 22 of 91 patients (24%) had at least one neoplastic lesion identified; however, the mean neoplastic lesion rate was 0.87 (54/63) for the primary sclerosing cholangitis-ulcerative colitis subgroup compared with 0.24 (4/17) for the primary sclerosing cholangitis-Crohn's disease subgroup. Chromoendoscopy was associated with a significantly higher detection rate for neoplasia (odds ratio [OR] 5.58, 95% confidence interval [CI] 2.08-14.9, P =0.001), and this association remained after adjusting for confounders, including high-definition endoscopy. High-definition endoscopes had a higher rate of neoplasia detection, but the significance was lost after adjustment for confounders, including chromoendoscopy (OR 1.93, 95% CI 0.69-5.40, P =0.21). Conclusions Chromoendoscopy is associated with a higher detection rate for neoplasia in patients with primary sclerosing cholangitis and IBD even with high-definition colonoscopes.

High-throughput phenotype-to-genotype testing of meningococcal carriage and disease isolates detects genetic determinants of disease-relevant phenotypic traits.

Genome-wide association studies (GWAS) with binary or single phenotype data have successfully identified disease-associated genotypes and determinants of antimicrobial resistance. We describe a novel phenotype-to-genotype approach for a major bacterial pathogen that involves simultaneously testing for associations among multiple disease-related phenotypes and linkages between phenotypic variation and genetic determinants. High-throughput assays quantified variation among 163 Neisseria meningitidis serogroup W ST-11 clonal complex isolates for 11 phenotypic traits. A comparison of carriage and two disease subgroups detected significant differences between groups for eight phenotypic traits. Candidate genotypic testing indicated that indels in csw, a capsular biosynthesis gene, were associated with reduced survival in antibody-depleted heat-inactivated serum. GWAS testing detected 341 significant genetic variants (3 single-nucleotide polymorphisms and 338 unitigs) across all traits except serum bactericidal antibody-depleted assays. Growth traits were associated with variants of capsular biosynthesis genes, carbonic anhydrase, and an iron-uptake system while adhesion-linked variation was in pilC2, marR, and mutS. Multiple phase variation states or combinatorial phasotypes were associated with significant differences in multiple phenotypes. Controlling for group effects through regression and recursive random forest approaches detected group-independent effects for nalP with biofilm formation and fetA with a growth trait. Through random forest testing, nine phenotypes were weakly predictive of MenW:cc11 sub-lineage, original or 2013, for disease isolates while three characteristics separated carriage and disease isolates with >80% accuracy. This study demonstrates the power of combining high-throughput phenotypic testing of pathogenically relevant isolate collections with genomics for identifying genetic determinants of specific disease-relevant phenotypes and the pathobiology of microbial pathogens.IMPORTANCENext-generation sequencing technologies have led to the creation of extensive microbial genome sequence databases for several bacterial pathogens. Mining of these databases is now imperative for unlocking the maximum benefits of these resources. We describe a high-throughput methodology for detecting associations between phenotypic variation in multiple disease-relevant traits and a range of genetic determinants for Neisseria meningitidis, a major causative agent of meningitis and septicemia. Phenotypic variation in 11 disease-related traits was determined for 163 isolates of the hypervirulent ST-11 lineage and linked to specific single-nucleotide polymorphisms, short sequence variants, and phase variation states. Application of machine learning algorithms to our data outputs identified combinatorial phenotypic traits and genetic variants predictive of a disease association. This approach overcomes the limitations of generic meta-data, such as disease versus carriage, and provides an avenue to explore the multi-faceted nature of bacterial disease, carriage, and transmissibility traits.

Future directions in myelodysplastic syndromes/neoplasms and acute myeloid leukaemia classification: from blast counts to biology.

Myelodysplastic syndromes/neoplasms (MDS) and acute myeloid leukaemia (AML) are neoplastic haematopoietic cell proliferations that are diagnosed and classified based on a combination of morphological, clinical and genetic features. Specifically, the percentage of myeloblasts in the blood and bone marrow is a key feature that has historically separated MDS from AML and, together with several other morphological parameters, defines distinct disease entities within MDS. Both MDS and AML have recurrent genetic abnormalities that are increasingly influencing their definitions and subclassification. For example, in 2022, two new MDS entities were recognised based on the presence of SF3B1 mutation or bi-allelic TP53 abnormalities. Genomic information is more objective and reproducible than morphological analyses, which are subject to interobserver variability and arbitrary numeric cut-offs. Nevertheless, the integration of genomic data with traditional morphological features in myeloid neoplasm classification has proved challenging by virtue of its sheer complexity; gene expression and methylation profiling also can provide information regarding disease pathogenesis, adding to the complexity. New machine-learning technologies have the potential to effectively integrate multiple diagnostic modalities and improve on historical classification systems. Going forward, the application of machine learning and advanced statistical methods to large patient cohorts can refine future classifications by advancing unbiased and robust previously unrecognised disease subgroups. Future classifications will probably incorporate these newer technologies and higher-level analyses that emphasise genomic disease entities over traditional morphologically defined entities, thus promoting more accurate diagnosis and patient risk stratification.

Investigation of Long-Term CD4+ T Cell Receptor Repertoire Changes Following SARS-CoV-2 Infection in Patients with Different Severities of Disease.

The difference in the immune response to severe acute respiratory syndrome coro-navirus 2 (SARS-CoV-2) in patients with mild versus severe disease remains poorly understood. Recent scientific advances have recognised the vital role of both B cells and T cells; however, many questions remain unanswered, particularly for T cell responses. T cells are essential for helping the generation of SARS-CoV-2 antibody responses but have also been recognised in their own right as a major factor influencing COVID-19 disease outcomes. The examination of T cell receptor (TCR) family differences over a 12-month period in patients with varying COVID-19 disease severity is crucial for understanding T cell responses to SARS-CoV-2. We applied a machine learning approach to analyse TCR vb family responses in COVID-19 patients (n = 151) across multiple timepoints and disease severities alongside SARS-CoV-2 infection-naïve (healthy control) individ-uals (n = 62). Blood samples from hospital in-patients with moderate, severe, or critical disease could be classified with an accuracy of 94%. Furthermore, we identified significant variances in TCR vb family specificities between disease and control subgroups. Our findings suggest advantageous and disadvantageous TCR repertoire patterns in relation to disease severity. Following validation in larger cohorts, our methodology may be useful in detecting protective immunity and the assessment of long-term outcomes, particularly as we begin to unravel the immunological mechanisms leading to post-COVID complications.

Proteolysis Targeting Chimera Agents (PROTACs): New Hope for Overcoming the Resistance Mechanisms in Oncogene-Addicted Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) remains a disease with a poor prognosis despite the advances in therapies. NSCLC with actionable oncogenic alterations represent a subgroup of diseases for which tyrosine kinase inhibitors (TKIs) have shown relevant and robust impact on prognosis, both in early and advanced stages. While the introduction of powerful TKIs increases the ratio of potentially curable patients, the disease does develop resistance over time through either secondary mutations or bypass activating tracks. Therefore, new treatment strategies are being developed to either overcome this inevitable resistance or to prevent it, and proteolysis targeting chimera agents (PROTACs) are among them. They consist of two linked molecules that bind to a target protein and an E3 ubiquitin ligase that causes ubiquitination and degradation of proteins of interest. In this paper, we review the rationale for PROTAC therapy and the current development of PROTACs for oncogene-addicted lung cancer. Moreover, we critically analyze the strengths and limitations of this promising technique that may help pave the way for future perspectives.