Clinical and imaging outcomes of different phenotypes of axial spondyloarthritis: 5-year analysis of the DESIR cohort

OBJECTIVES

To compare the long-term outcomes of three phenotypes of axial SpA (axSpA).

METHODS

Patients with a clinical diagnosis of axSpA from the DESIR cohort were grouped into three phenotypes at baseline: 'Pure axSpA' ('Axial'), 'axSpA with peripheral signs' ('IBP+Peripheral') and 'axSpA at risk' ('At risk') by latent class analysis. Clinical and imaging data were collected up to 5 years. Clinical outcomes, measured in each visit, included disability (BASFI) and quality of life (QoL; SF36). Imaging outcomes included inflammatory and structural lesions on MRI and radiographs of spine and SIJ. The association between phenotype membership at baseline and each outcome was tested in multivariable GEE models.

RESULTS

In total, 576 patients with axSpA were included. 'At risk' patients had worse disability and QoL than 'Axial' patients over time. For instance, 'At risk' patients had on average 0.4 more points in BASFI over time than 'Axial' patients [β (95 % CI): 0.4 (0.2; 0.7)]. This difference was mostly noted in female patients who were HLA-B27 positive. In addition, the difference between the 'At risk' and 'Axial' phenotypes was higher in patients receiving bDMARDs than in those not (β=0.6 vs 0.5), since BASFI improved more in 'Axial' (∆BASFI: -1.3) than in 'At risk' (∆BASFI: -0.9) treated patients. There were no differences in disability and QoL between 'Axial' and 'IBP+Peripheral' patients. Imaging outcomes were worse in the 'Axial' phenotype than in the others over time.

CONCLUSION

Patients with 'axSpA at risk' show worse self-reported outcomes over time and are less likely to benefit from anti-inflammatory treatment than those with a classical axSpA phenotype.

Machine learning clustering of adult spinal deformity patients identifies four prognostic phenotypes: a multicenter prospective cohort analysis with single surgeon external validation

BACKGROUND CONTEXT

Among adult spinal deformity (ASD) patients, heterogeneity in patient pathology, surgical expectations, baseline impairments, and frailty complicates comparisons in clinical outcomes and research. This study aims to qualitatively segment ASD patients using machine learning-based clustering on a large, multicenter, prospectively gathered ASD cohort.

PURPOSE

To qualitatively segment adult spinal deformity patients using machine learning-based clustering on a large, multicenter, prospectively gathered cohort.

STUDY DESIGN/SETTING

Machine learning algorithm using patients from a prospective multicenter study and a validation cohort from a retrospective single center, single surgeon cohort with complete 2-year follow up.

PATIENT SAMPLE

About 805 ASD patients; 563 patients from a prospective multicenter study and 242 from a single center to be used as a validation cohort.

OUTCOME MEASURES

To validate and extend the Ames-ISSG/ESSG classification using machine learning-based clustering analysis on a large, complex, multicenter, prospectively gathered ASD cohort.

METHODS

We analyzed a training cohort of 563 ASD patients from a prospective multicenter study and a validation cohort of 242 ASD patients from a retrospective single center/surgeon cohort with complete two-year patient-reported outcomes (PROs) and clinical/radiographic follow-up. Using k-means clustering, a machine learning algorithm, we clustered patients based on baseline PROs, Edmonton frailty, age, surgical history, and overall health. Baseline differences in clusters identified using the training cohort were assessed using Chi-Squared and ANOVA with pairwise comparisons. To evaluate the classification system's ability to discern postoperative trajectories, a second machine learning algorithm assigned the single-center/surgeon patients to the same 4 clusters, and we compared the clusters' two-year PROs and clinical outcomes.

RESULTS

K-means clustering revealed four distinct phenotypes from the multicenter training cohort based on age, frailty, and mental health: Old/Frail/Content (OFC, 27.7%), Old/Frail/Distressed (OFD, 33.2%), Old/Resilient/Content (ORC, 27.2%), and Young/Resilient/Content (YRC, 11.9%). OFC and OFD clusters had the highest frailty scores (OFC: 3.76, OFD: 4.72) and a higher proportion of patients with prior thoracolumbar fusion (OFC: 47.4%, OFD: 49.2%). ORC and YRC clusters exhibited lower frailty scores and fewest patients with prior thoracolumbar procedures (ORC: 2.10, 36.6%; YRC: 0.84, 19.4%). OFC had 69.9% of patients with global sagittal deformity and the highest T1PA (29.0), while YRC had 70.2% exhibiting coronal deformity, the highest mean coronal Cobb Angle (54.0), and the lowest T1PA (11.9). OFD and ORC had similar alignment phenotypes with intermediate values for Coronal Cobb Angle (OFD: 33.7; ORC: 40.0) and T1PA (OFD: 24.9; ORC: 24.6) between OFC (worst sagittal alignment) and YRC (worst coronal alignment). In the single surgeon validation cohort, the OFC cluster experienced the greatest increase in SRS Function scores (1.34 points, 95%CI 1.01-1.67) compared to OFD (0.5 points, 95%CI 0.245-0.755), ORC (0.7 points, 95%CI 0.415-0.985), and YRC (0.24 points, 95%CI -0.024-0.504) clusters. OFD cluster patients improved the least over 2 years. Multivariable Cox regression analysis demonstrated that the OFD cohort had significantly worse reoperation outcomes compared to other clusters (HR: 3.303, 95%CI: 1.085-8.390).

CONCLUSION

Machine-learning clustering found four different ASD patient qualitative phenotypes, defined by their age, frailty, physical functioning, and mental health upon presentation, which primarily determines their ability to improve their PROs following surgery. This reaffirms that these qualitative measures must be assessed in addition to the radiographic variables when counseling ASD patients regarding their expected surgical outcomes.

Experts' Opinion on diagnosis and management of Severe Asthma, an Indian/Low and middle-income countries (LMIC) Perspective

Objective In this document, 9 Indian experts have evaluated the factors specific to LMICs when it came to Severe Asthma (SA) diagnosis, evaluation, biologic selection, non-biologic treatment options and follow-up.Data Sources A search was performed using 50 keywords., focusing on the Indian/LMICs perspective, in PubMed, Cochrane Library, and Google Scholar. The key areas of the search were focused on diagnosis, phenoendotyping, non-biological therapies, selecting a biologic, assessment of treatment response and management of exacerbation.Study Selections The initial search revealed 1826 articles, from these case reports, observational studies, cohort studies, non-English language papers etc were excluded and we short-listed 20 articles for each area. 5 relevant papers were selected by the experts for review.Results In LMICs SA patients may be referred to the specialist for evaluation a little late for Phenoendotyping of SA. While biologic therapy is now a standard of care, pulmonologists in LMICs may not have access to all the investigations to phenoendotype SA patients like Fractional exhaled nitric oxide (FeNO), Skin prick test (SPT) etc., but phenotyping of SA patients can also be done with simple blood investigations, eosinophil count and serum immunoglobulin E (IgE). Choosing a biologic in the overlapping phenotype of SA and ACO patients is also a challenge in the LMICs.Conclusion Given the limitations of LMIC, it is important to select the right patient and explain the potential benefits of biological therapy. Non-biologic add-on therapies can be attempted in a resource-limited setting where biological therapy is not available/feasible for patients.

Identification of sleep phenotypes in COPD using machine learning-based cluster analysis

BACKGROUND

Disturbed sleep in patients with COPD impact quality of life and predict adverse outcomes.

RESEARCH QUESTION

To identify distinct phenotypic clusters of patients with COPD using objective sleep parameters and evaluate the associations between clusters and all-cause mortality to inform risk stratification.

STUDY DESIGN AND METHODS

A longitudinal observational cohort study using nationwide Veterans Health Administration data of patients with COPD investigated for sleep disorders. Sleep parameters were extracted from polysomnography physician interpretation using a validated natural language processing algorithm. We performed cluster analysis using an unsupervised machine learning algorithm (K-means) and examined the association between clusters and mortality using Cox regression analysis, adjusted for potential confounders, and visualized with Kaplan-Meier estimates.

RESULTS

Among 9992 patients with COPD and a clinically indicated baseline polysomnogram, we identified five distinct clusters based on age, comorbidity burden and sleep parameters. Overall mortality increased from 9.4 % to 42 % and short-term mortality (<5.3 years) ranged from 3.4 % to 24.3 % in Cluster 1 to 5. In Cluster 1 younger age, in 5 high comorbidity burden and in the other three clusters, total sleep time and sleep efficiency had significant associations with mortality.

INTERPRETATION

We identified five distinct clinical clusters and highlighted the significant association between total sleep time and sleep efficiency on mortality. The identified clusters highlight the importance of objective sleep parameters in determining mortality risk and phenotypic characterization in this population.

Towards personalized medicine for the treatment of equine asthma

Although horses with asthma share similar clinical signs, the heterogeneity of the disease in terms of severity, triggering factors, inflammatory profile, and pathological features has hindered our ability to define biologically distinct subgroups. The recognition of phenotypes and endotypes could enable the development of precision medicine, including personalized, targeted therapy, to benefit affected horses. While in its infancy in horses, this review outlines the phenotypes of equine asthma and discusses how knowledge gained from targeted therapy in human medicine can be applied to evaluate the potential opportunities for personalized medicine in equine asthma and to suggest avenues for research to advance this emerging field.

Long-term characterization of cognitive phenotypes in children with seizures over 36 months

RATIONALE

Children with new-onset epilepsies often exhibit co-morbidities including cognitive dysfunction, which adversely affects academic performance. Application of unsupervised machine learning techniques has demonstrated the presence of discrete cognitive phenotypes at or near the time of diagnosis, but there is limited knowledge of their longitudinal trajectories. Here we investigate longitudinally the presence and progression of cognitive phenotypes and academic status in youth with new-onset seizures as sibling controls.

METHODS

282 subjects (6-16 years) were recruited within 6 weeks of their first recognized seizure along with 167 unaffected siblings. Each child underwent a comprehensive neuropsychological assessment at baseline, 18 and 36 months later. Factor analysis of the neuropsychological tests revealed four underlying domains - language, processing speed, executive function, and verbal memory. Latent trajectory analysis of the mean factor scores over 36 months identified clusters with prototypical cognitive trajectories.

RESULTS

Three unique phenotypic groups with distinct cognitive trajectories over the 36-month period were identified: Resilient, Average, and Impaired phenotypes. The Resilient phenotype exhibited the highest neuropsychological factor scores and academic performance that were all similar to controls; while the Impaired phenotype showed the polar opposite with the worst performances across all test metrics. These findings remained significant and stable over 36 months. Multivariate logistic regression indicated that age of onset, EEG, neurological examination, and sociodemographic disadvantage were associated with phenotype classification.

CONCLUSIONS

This study demonstrates the presence of diverse latent cognitive trajectory phenotypes over 36 months in youth with new-onset seizures that are associated with a stable neuropsychological and academic performance longitudinally.

Clinical, Genotypic, and Imaging Characterization of the Spectrum of ABCA4 Retinopathies

PURPOSE

To investigate the clinical and genotypic differences in the spectrum of ABCA4-associated retinopathies (ABCA4Rs).

DESIGN

Observational, cross sectional case series.

PARTICIPANTS

Sixty-six patients (132 eyes) carrying biallelic ABCA4 variants.

METHODS

Patients underwent visual acuity measurement and multimodal imaging. Clinical records were reviewed for age at onset, presenting symptoms, genetic variants, and electroretinogram (ERG). Each eye was assigned to a phenotype based on age at onset, imaging and ERG: cone dystrophy-bull's-eye maculopathy (CD-BEM, 40 eyes), cone-rod dystrophy (CRD, 12 eyes), Stargardt disease (SD, 28 eyes), late-onset SD (LO-SD, 38 eyes), and fundus flavimaculatus (14 eyes). Images were analyzed for: peripapillary sparing, retinal pigment epithelium (RPE) atrophy (definitely decreased autofluorescence, DDAF), flecks patterns using autofluorescence; type of atrophy according to Classification of Atrophy Meeting reports, macular and choroidal thickness on OCT; and choriocapillaris flow deficits on OCT angiography.

MAIN OUTCOME MEASURES

Primary outcome was to report the demographic, genotypic, and imaging characteristics of the different ABCA4R phenotypes. Secondary objectives included the assessment of imaging biomarkers as outcome measures for clinical trials.

RESULTS

Age at onset was lower in CRD (12 ± 8 years) and higher in patients with LO-SD (59 ± 9 years) (all P < 0.01). Central vision loss was a common presenting symptom in CD-BEM and SD, whereas patients with LO-SD primarily complained of difficult dark adaptation. Missense variants were more frequent in CD-BEM, and splice site in CRD and LO-SD (P < 0.05). Peripapillary sparing was absent in 3 eyes with LO-SD (8%). Cone dystrophy-bull's-eye maculopathy eyes typically had complete outer retinal atrophy alterations (98%), whereas CRD and SD eyes showed both complete outer retinal atrophy and complete RPE and outer retinal atrophy (cRORA) (71%-100%). Patients with LO-SD had larger areas of DDAF (100% cRORA) and of choriocapillaris flow deficits (all P < 0.01). Repeatability of DDAF measurements was low for some phenotypes (CD-BEM and CRD) and atrophic areas <7.5 mm2. Resorbed flecks were significantly associated with CRD and LO-SD (P < 0.01).

CONCLUSIONS

This research provides a thorough evaluation of the spectrum of ABCA4R. Our findings suggest that certain phenotypes show preferential photoreceptor degeneration (e.g., CD-BEM), whereas others have substantial RPE and choriocapillaris alterations (e.g., LO-SD). We recommend that clinical trial end points take into consideration these imaging features to improve the interpretation of their results.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Identifying and understanding cognitive profiles in multiple sclerosis: a role for visuospatial memory functioning

BACKGROUND

The heterogeneous nature of cognitive impairment in people with multiple sclerosis (PwMS) hampers understanding of the underlying mechanisms and developing patient-tailored interventions. We aim to identify and classify cognitive profiles in PwMS, comparing these to cognitive status (preserved versus impaired).

METHODS

We included 1213 PwMS (72% female, age 45.4 ± 10.7 years, 83% relapsing-remitting MS). Cognitive test scores were converted to Z-scores compared to healthy controls for the functions: attention, inhibition, information processing speed (IPS), verbal fluency and verbal/visuospatial memory. Concerning cognitive status, impaired cognition (CI) was defined as performing at Z ≤ - 1.5 SD on ≥ 2 functions. Cognitive profiles were constructed using latent profile analysis on all cognitive functions. Cognitive profiles or status was classified using gradient boosting decision trees, providing the importance of each feature (demographics, clinical, cognitive and psychological functioning) for the overall classification.

RESULTS

Six profiles were identified, showing variations in overall performance and specific deficits (attention, inhibition, IPS, verbal fluency, verbal memory and visuospatial memory). Across the profiles, IPS was the most impaired function (%CI most preserved profile, Profile 1 = 22.4%; %CI most impaired profile, Profile 6 = 76.6%). Cognitive impairment varied from 11.8% in Profile 1 to 95.3% in Profile 6. Of all cognitive functions, visuospatial memory was most important in classifying profiles and IPS the least (area under the curve (AUC) = 0.910). For cognitive status, IPS was the most important classifier (AUC = 0.997).

CONCLUSIONS

This study demonstrated that cognitive heterogeneity in MS reflects a continuum of cognitive severity, distinguishable by distinct cognitive profiles, primarily explained by variations in visuospatial memory functioning.

Molecular portrait of chronic joint diseases: Defining endotypes toward personalized medicine

Joint diseases affect hundreds of millions of people worldwide, and their prevalence is constantly increasing. To date, despite recent advances in the development of therapeutic options for most rheumatic conditions, a significant proportion of patients still lack efficient disease management, considerably impacting their quality of life. Through the spectrum of rheumatoid arthritis (RA), psoriatic arthritis (PsA), and osteoarthritis (OA) as quintessential and common rheumatic diseases, this review first provides an overview of their epidemiological and clinical features before exploring how the better definition of clinical phenotypes has helped their clinical management. It then discusses the recent progress in understanding the diversity of endotypes underlying disease phenotypes. Finally, this review highlights the current challenges of implementing molecular endotypes towards the personalized management of RA, PsA and OA patients in the future.

Hand osteoarthritis phenotypes based on a biopsychosocial approach, and their associations with cross-sectional and longitudinal pain

OBJECTIVE

Hand osteoarthritis (OA) pain is characterized as heterogeneous and multifactorial. Differences in pain may be explained by underlying phenotypes, which have not been previously explored DESIGN: Latent class analysis determined classes of participants with hand OA from the Nor-Hand study baseline examination (2016-17) based on a biopsychosocial framework. Outcomes were hand and overall bodily pain intensity (Numeric Rating Scale, 0-10) at baseline and follow-up (2019-21), The relations of the classes to pain outcomes at baseline, follow-up, and change over time were analysed in separate models by linear regression, using the overall healthiest class as reference.

RESULTS

Five classes differing in radiographic hand OA burden and OA burden in the lower extremities by ultrasound, demographic factors, psychosocial burden and pain sensitization was identified. Persons with the least severe OA but higher burden of biopsychosocial factors reported the most hand pain (beta 3.65, 95% CI 2.53, 4.75). Pain was less pronounced in persons with the most severe hand OA but low burden of biopsychosocial factors (beta 1.03, 95% CI 0.41, 1.65). Results were similar for overall bodily pain and at follow-up. Changes in pain were small, but the association between a separate class defined by higher levels of biopsychosocial burden and pain changes was significant.

CONCLUSION

The five hand OA phenotypes were associated with pain at baseline and 3.5 years later. The phenotype with the least OA severity, but higher burden of biopsychosocial factors reported more pain than the phenotype with the most severe OA, reflecting the symptom-structure discordance of the hand OA pain experience.

Personalized anti-reflux surgery: connecting GERD phenotypes in 690 patients to outcomes

BACKGROUND

Anti-reflux operations are effective treatments for GERD. Despite standardized surgical techniques, variability in post-operative outcomes persists. Most patients with GERD possess one or more characteristics that augment their disease and may affect post-operative outcomes-a GERD "phenotype". We sought to define these phenotypes and to compare their post-operative outcomes.

METHODS

We performed a retrospective review of a prospective gastroesophageal database at our institution, selecting all patients who underwent an anti-reflux procedure for GERD. Patients were grouped into different phenotypes based on the presence of four characteristics known to play a role in GERD: hiatal or paraesophageal hernia (PEH), hypotensive LES, esophageal dysmotility, delayed gastric emptying (DGE), and obesity. Patient-reported outcomes (GERD-HRQL, dysphagia, and reflux symptom index (RSI) scores) were compared across phenotypes using the Wilcoxon rank-sum test.

RESULTS

690 patients underwent an anti-reflux procedure between 2008 and 2022. Most patients underwent a Nissen fundoplication (302, 54%), followed by a Toupet or Dor fundoplication (205, 37%). Twelve distinct phenotypes emerged. Non-obese patients with normal esophageal motility, normotensive LES, no DGE, with a PEH represented the most common phenotype (134, 24%). The phenotype with the best post-operative GERD-HRQL scores at one year was defined by obesity, hypotensive LES, and PEH, while the phenotype with the worst scores was defined by obesity, ineffective motility, and PEH (1.5 ± 2.4 vs 9.8 ± 11.4, p = 0.010). There was no statistically significant difference in GERD-HRQL, dysphagia, or RSI scores between phenotypes after five years.

CONCLUSIONS

We have identified distinct phenotypes based on common GERD-associated patient characteristics. With further study these phenotypes may aid surgeons in prognosticating outcomes to individual patients considering an anti-reflux procedure.

Clinical phenotypes of comorbidities in end-stage knee osteoarthritis: a cluster analysis

OBJECTIVES

Comorbidities, as components of these heterogeneous features, often coexist with knee osteoarthritis, and are particularly prevalent in end-stage knee osteoarthritis. Here, we attempted to identify the different clinical phenotypes of comorbidities in patients with end-stage knee osteoarthritis by cluster analysis.

METHODS

A total of 421 inpatients diagnosed with end-stage knee osteoarthritis who underwent inpatient surgery were included in this cross-sectional study. 23 demographic, comorbidity, inflammatory immune and evaluation scale variables were collected. Systematic clustering after factor analysis and separate two-step cluster analysis were performed for individual comorbidity variables and all variables, respectively, to objectively identify the different clinical phenotypes of the study patients.

RESULTS

Four clusters were finally identified. Cluster 1 had the largest proportion of obese patients (93.8%) and hypertension was common (71.2%). Almost all patients in cluster 2 were depressed (95.8%) and anxiety disorders (94.7%). Cluster 3 combined patients with isolated end-stage knee osteoarthritis and a few comorbidities. Cluster 4 had the highest proportion of patients with rheumatoid arthritis (58.8%).

CONCLUSIONS

Patients with end-stage knee osteoarthritis may be classified into four different clinical phenotypes: "isolated end-stage knee osteoarthritis"; "obesity + hypertension"; "depression + anxiety"; and "rheumatoid arthritis", which may help guide individualized patient care and treatment strategies.

The biochemical pattern defines MASLD phenotypes linked to distinct histology and prognosis

BACKGROUND

MASLD can manifest as hepatocellular damage, which can result in mild elevation of aminotransferases. However, in some patients, MASLD presents with cholestatic pattern.

OBJECTIVE

To assess the impact of the biochemical pattern on the natural course of MASLD, including liver damage in histology, the accuracy of non-invasive tests(NITs), and prognosis.

METHODS

Multicenter study enrolling 2156 patients with biopsy-proven MASLD, who were classified based on their[ALT/ULN)]/[(ALP/ULN)] levels at the time of biopsy: (a) hepatocellular pattern(H), > 5; (b) mixed pattern(M),2-5; (c) cholestatic pattern(C), < 2.

OUTCOMES

(a) histological evaluation of the single components of NAS, MASH, and fibrosis; (b) NITs and transient elastography assessing advanced fibrosis; (c) prognosis determined by the appearance of decompensated cirrhosis and death.

RESULTS

Out of the 2156 patients, 22.9% exhibited the H-pattern, whilst 31.7% exhibited the C-pattern. Severe steatosis, ballooning, lobular inflammation, and MASH (56.4% H vs. 41.9% M vs. 31.9% C) were more common in H-pattern (p = 0.0001),whilst C-pattern was linked to cirrhosis (5.8% H vs. 5.6% M vs. 10.9% C; p = 0.0001). FIB-4(0.74(95% CI 0.69-0.79) vs. 0.83 (95% CI 0.80-0.85); p = 0.005) and Hepamet Fibrosis Score(0.77 (95% CI 0.69-0.85) vs. 0.84 (95% CI 0.80-0.87); p = 0.044)exhibited lower AUROCs in the H-pattern. The C-pattern[HR 2.37 (95% CI 1.12-5.02); p = 0.024], along with age, diabetes, and cirrhosis were independently associated with mortality. Most patients maintained their initial biochemical pattern during the second evaluation.

CONCLUSIONS

The H-pattern exhibited greater necro-inflammation in the histology than the C-pattern, whereas the latter showed more cirrhosis. The accuracy of NITs in detecting fibrosis was decreased in H-pattern. The occurrence of decompensated events and mortality was predominant in C-pattern. Therefore, identifying MASLD phenotypes based on the biochemical presentation could be relevant for clinical practice.

Phenotypes of Metabolic Dysfunction-Associated Steatotic Liver Disease-Associated Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) typically develops as a consequence of liver cirrhosis, but HCC epidemiology has evolved drastically in recent years. Metabolic dysfunction-associated steatotic liver disease (MASLD), including metabolic dysfunction-associated steatohepatitis, has emerged as the most common chronic liver disease worldwide and a leading cause of HCC. A substantial proportion of MASLD-associated HCC (MASLD-HCC) also can develop in patients without cirrhosis. The specific pathways that trigger carcinogenesis in this context are not elucidated completely, and recommendations for HCC surveillance in MASLD patients are challenging. In the era of precision medicine, it is critical to understand the processes that define the profiles of patients at increased risk of HCC in the MASLD setting, including cardiometabolic risk factors and the molecular targets that could be tackled effectively. Ideally, defining categories that encompass key pathophysiological features, associated with tailored diagnostic and treatment strategies, should facilitate the identification of specific MASLD-HCC phenotypes. In this review, we discuss MASLD-HCC, including its epidemiology and health care burden, the mechanistic data promoting MASLD, metabolic dysfunction-associated steatohepatitis, and MASLD-HCC. Its natural history, prognosis, and treatment are addressed specifically, as the role of metabolic phenotypes of MASLD-HCC as a potential strategy for risk stratification. The challenges in identifying high-risk patients and screening strategies also are discussed, as well as the potential approaches for MASLD-HCC prevention and treatment.

Phenotypes in antiphospholipid syndrome: A hierarchical cluster analysis based on two independent databases

BACKGROUND

Antiphospholipid syndrome (APS) is a rare autoimmune disease characterized by thromboses at various sites and obstetric events associated with the persistent presence of antiphospholipid antibodies. The identification of clinical phenotypes in APS patients is a clinical need. In this study, we aimed to determine the clinical phenotypes of APS patients through an unsupervised analysis of two well-characterized cohorts of APS patients.

PATIENTS AND METHODS

APS phenotypes were defined by an ascending hierarchical cluster analysis to identify preferential associations between 18 types of organ involvement and clinical characteristics. This analysis was performed on an initial multi-center cohort of 1000 patients, with validation in a replication cohort of 435 patients.

RESULTS

The hierarchical analysis identified three APS phenotypes in both the initial and replication cohorts: an obstetric phenotype (n = 259 and n = 74 patients, respectively), a venous thrombosis phenotype, accounting for the largest number of patients (n = 461 and n = 297 patients, respectively), and a skin-central nervous system-heart phenotype (n = 280 and n = 64 patients, respectively). The clinical characteristics of the patients differed significantly between the three phenotypes, but there was no difference in antiphospholipid antibody profile between the groups.

CONCLUSIONS

We identified three phenotypes of APS defined based on preferential associations of organ involvements and differences in presentation. These observations may help clinicians to detect organ involvement and to manage treatment.

Chinese guideline for the diagnosis and treatment of drug-induced liver injury: an update

Drug-induced liver injury (DILI) is an important adverse drug reaction that can lead to acute liver failure or even death in severe cases. Currently, the diagnosis of DILI still follows the strategy of exclusion. Therefore, a detailed history taking and a thorough and careful exclusion of other potential causes of liver injury is the key to correct diagnosis. This guideline was developed based on evidence-based medicine provided by the latest research advances and aims to provide professional guidance to clinicians on how to identify suspected DILI timely and standardize the diagnosis and management in clinical practice. Based on the clinical settings in China, the guideline also specifically focused on DILI in chronic liver disease, drug-induced viral hepatitis reactivation, common causing agents of DILI (herbal and dietary supplements, anti-tuberculosis drugs, and antineoplastic drugs), and signal of DILI in clinical trials and its assessment.

Phenotypic Spectrum of Progressive Supranuclear Palsy: Clinical Study and Apolipoprotein E Effect

OBJECTIVE

Progressive supranuclear palsy (PSP) is a rare neurodegenerative disorder encompassing several phenotypes with various motor and cognitive deficits. We aimed to study motor and cognitive characteristics across PSP phenotypes and to assess the influence of apolipoprotein E (APOE) gene variants on PSP phenotypic expression.

METHODS

In this 20-year cross-sectional study, we retrospectively reviewed the charts of all patients classified as PSP patients and recategorized them according to phenotype using the Movement Disorder Society criteria (2017). Phenotypes were divided into three subgroups, Richardson's syndrome (PSP-RS), PSP-cortical (PSP with predominant frontal presentation [PSP-F] + PSP with predominant speech/language disorder [PSP-SL] + PSP with predominant corticobasal syndrome [PSP-CBS]) and PSP-subcortical (PSP with predominant parkinsonism [PSP-P] + PSP with progressive gait freezing [PSP-PGF] + PSP with predominant postural instability [PSP-PI] + PSP with predominant ocular motor dysfunction [PSP-OM] + PSP with cerebellar ataxia [PSP-C] + PSP with primary lateral sclerosis [PSP-PLS]), based on clinical presentation during the first 3 years after symptom onset, which defines the early disease stage. Clinical and neuropsychological assessment data were collected. Genotyping of APOE was performed using restriction fragment length polymorphism polymerase chain reaction and verified by Sanger sequencing.

RESULTS

We included 112 PSP patients comprising 10 phenotypes classified into 48 PSP-RS, 34 PSP-cortical (PSP-CBS, 17.6%; PSP-F, 9.4%; PSP-SL, 8.2%) and 30 PSP-subcortical (PSP-P, 11.6%; PSP-PI, 8%; PSP-OM, 2.7%; PSP-PGF, 1.8%; PSP-C, 1.8%; PSP-PLS, 0.9%) subgroups. PSP-RS patients were older at disease onset (p = 0.009) and had more akinetic-rigid and levodopa-resistant parkinsonism (p = 0.006), while PSP-cortical patients had more tremors and asymmetric and/or levodopa-responsive parkinsonism (p = 0.025). Cognitive domains were significantly less altered in the PSP-subcortical subgroup. Overall, PSP-APOEε4 carriers developed parkinsonism earlier (p = 0.038), had earlier oculomotor dysfunction (p = 0.052) and had more altered cognitive profiles. The APOEε4 allele was also associated with a younger age of parkinsonism onset in the PSP-RS phenotype group (p = 0.026).

CONCLUSION

This study demonstrated the wide phenotypic spectrum of PSP among Tunisians. Disease onset and akinetic-rigid and levodopa-resistant parkinsonism were the hallmarks of the PSP-RS phenotype, while milder cognitive impairment was characteristic of the PSP-subcortical subgroup. The APOEε4 allele was associated with earlier parkinsonism and oculomotor dysfunction and seemed to play a role in defining a more altered cognitive profile in PSP patients.

Insights Into Differences in Pulmonary Hemodynamics in Hispanic Patients With Pulmonary Arterial Hypertension

Background

Emerging data suggest that Hispanic patients with pulmonary arterial hypertension (PAH) exhibit improved survival rates compared to individuals of other ethnicities with similar baseline hemodynamics. However, the underlying reasons for this survival advantage remain unclear. This study focused on comparing pulmonary hemodynamics in Hispanic and non-Hispanic PAH patients and how these differences may contribute to varied clinical outcomes.

Methods

A retrospective analysis of right heart catheterization data was conducted on a treatment-naive PAH patient cohort from a single center.

Results

Over a 10-year period, a total of 226 PAH patients were identified, of which 138 (61%) were Hispanic and 88 (39%) were non-Hispanic. Hispanic patients presented with lower pulmonary artery pressures, lower pulmonary vascular resistance, and exhibited significantly higher pulmonary arterial compliance (PAc). Hispanic patients had better 5-year survival rates.

Conclusions

This study highlights the importance of exploring phenotypic differences in ethnically diverse PAH cohorts.

Precision Cardiology: Phenotype-targeted Therapies for HFmrEF and HFpEF

Heart failure with mid-range ejection fraction (HFmrEF) and preserved ejection fraction (HFpEF) represent over half of heart failure cases but lack proven effective therapies beyond sodium-glucose cotransporter 2 inhibitor and diuretics. HFmrEF and HFpEF are heterogeneous conditions requiring precision phenotyping to enable tailored therapies. This review covers concepts on precision medicine approaches for HFmrEF and HFpEF. Areas discussed include HFmrEF mechanisms, anti-inflammatory and antifibrotic treatments for obesity-related HFpEF, If inhibition for HFpEF with atrial fibrillation, and mineralocorticoid receptor antagonism for chronic kidney disease-HFpEF. Incorporating precision phenotyping and matched interventions in HFmrEF and HFpEF trials will further advance therapy compared to blanket approaches.

Current and Novel Biologic Therapies for Patients with Asthma and Nasal Polyps

A substantial portion of asthma and nasal polyps (NPs) share a common pathogenesis, which includes type 2-mediated inflammation. Distinct endotypes and phenotypes characterizing asthma and chronic rhinosinusitis have been identified. With emerging evidence describing pathophysiology, novel targets for biologic monoclonal antibody treatments have been developed. There are currently six biologic therapies approved by the US Food and Drug Administration to treat asthma, including omalizumab, mepolizumab, reslizumab, benralizumab, dupilumab, and tezepelumab, three of these-omalizumab, mepolizumab, and dupilumab-are also approved for NPs.

Acute Respiratory Distress Syndrome: Definition, Diagnosis, and Routine Management

Acute respiratory distress syndrome (ARDS) is an acute inflammatory lung injury characterized by severe hypoxemic respiratory failure, bilateral opacities on chest imaging, and low lung compliance. ARDS is a heterogeneous syndrome that is the common end point of a wide variety of predisposing conditions, with complex pathophysiology and underlying mechanisms. Routine management of ARDS is centered on lung-protective ventilation strategies such as low tidal volume ventilation and targeting low airway pressures to avoid exacerbation of lung injury, as well as a conservative fluid management strategy.

SER recommendations on treatment of refractory Behçet's syndrome

OBJECTIVE

To develop multidisciplinary recommendations based on available evidence and expert consensus for the therapeutic management of patients with refractory Behçet's syndrome (BS) (difficult to treat, severe resistant, severe relapse) to conventional treatment.

METHODS

A group of experts identified clinical research questions relevant to the objective of the document. These questions were reformulated in PICO format (patient, intervention, comparison and outcome). Systematic reviews of the evidence were conducted, the quality of the evidence was evaluated following the methodology of the international working group Grading of Recommendations Assessment, Development, and Evaluation (GRADE). After that, the multidisciplinary panel formulated the specific recommendations.

RESULTS

4 PICO questions were selected regarding the efficacy and safety of systemic pharmacological treatments in patients with BS with clinical manifestations refractory to conventional therapy related to mucocutaneous and/or articular, vascular, neurological parenchymal and gastrointestinal phenotypes. A total of 7 recommendations were made, structured by question, based on the identified evidence and expert consensus.

CONCLUSIONS

The treatment of most severe clinical manifestations of BS lacks solid scientific evidence and, besides, there are no specific recommendation documents for patients with refractory disease. With the aim of providing a response to this need, here we present the first official Recommendations of the Spanish Society of Rheumatology for the management of these patients. They are devised as a tool for assistance in clinical decision making, therapeutic homogenisation and to reduce variability in the care of these patients.

Large-scale next generation sequencing based analysis of SLCO1B1 pharmacogenetics variants in the Saudi population

BACKGROUND

SLCO1B1 plays an important role in mediating hepatic clearance of many different drugs including statins, angiotensin-converting enzyme inhibitors, chemotherapeutic agents and antibiotics. Several variants in SLCO1B1 have been shown to have a clinically significant impact, in relation to efficacy of these medications. This study provides a comprehensive overview of SLCO1B1 variation in Saudi individuals, one of the largest Arab populations in the Middle East.

METHODS

The dataset of 11,889 (9,961 exomes and 1,928 pharmacogenetic gene panel) Saudi nationals, was used to determine the presence and frequencies of SLCO1B1 variants, as described by the Clinical Pharmacogenetic Implementation Consortium (CPIC).

RESULTS

We identified 141 previously described SNPs, of which rs2306283 (50%) and rs4149056 (28%), were the most common. In addition, we observed six alleles [*15 (24.7%) followed by *20 (8.04%), *14 (5.86%), *5 (3.84%), *31 (0.21%) and *9 (0.03%)] predicted to be clinically actionable. Allele diplotype to phenotype conversion revealed 41 OATP1B1 diplotypes. We estimated the burden of rare, and novel predicted deleterious variants, resulting from 17 such alterations.

CONCLUSIONS

The data we present, from one of the largest Arab cohorts studied to date, provides the most comprehensive overview of SLCO1B1 variants, and the subsequent OATP1B1 activity of this ethnic group, which thus far remains relatively underrepresented in available international genomic databases. We believe that the presented data provides a basis for further clinical investigations and the application of personalized statin drug therapy guidance in Arabs.

Identification of a hyperinflammatory sepsis phenotype using protein biomarker and clinical data in the ProCESS randomized trial

Sepsis is a heterogeneous syndrome and phenotypes have been proposed using clinical data. Less is known about the contribution of protein biomarkers to clinical sepsis phenotypes and their importance for treatment effects in randomized trials of resuscitation. The objective is to use both clinical and biomarker data in the Protocol-Based Care for Early Septic Shock (ProCESS) randomized trial to determine sepsis phenotypes and to test for heterogeneity of treatment effect by phenotype comparing usual care to protocolized early, goal-directed therapy(EGDT). In this secondary analysis of a subset of patients with biomarker sampling in the ProCESS trial (n = 543), we identified sepsis phenotypes prior to randomization using latent class analysis of 20 clinical and biomarker variables. Logistic regression was used to test for interaction between phenotype and treatment arm for 60-day inpatient mortality. Among 543 patients with severe sepsis or septic shock in the ProCESS trial, a 2-class model best fit the data (p = 0.01). Phenotype 1 (n = 66, 12%) had increased IL-6, ICAM, and total bilirubin and decreased platelets compared to phenotype 2 (n = 477, 88%, p < 0.01 for all). Phenotype 1 had greater 60-day inpatient mortality compared to Phenotype 2 (41% vs 16%; p < 0.01). Treatment with EGDT was associated with worse 60-day inpatient mortality compared to usual care (58% vs. 23%) in Phenotype 1 only (p-value for interaction = 0.05). The 60-day inpatient mortality was similar comparing EGDT to usual care in Phenotype 2 (16% vs. 17%). We identified 2 sepsis phenotypes using latent class analysis of clinical and protein biomarker data at randomization in the ProCESS trial. Phenotype 1 had increased inflammation, organ dysfunction and worse clinical outcomes compared to phenotype 2. Response to EGDT versus usual care differed by phenotype.

Applicability of an unsupervised cluster model developed on first wave COVID-19 patients in second/third wave critically ill patients

OBJECTIVE

To validate the unsupervised cluster model (USCM) developed during the first pandemic wave in a cohort of critically ill patients from the second and third pandemic waves.

DESIGN

Observational, retrospective, multicentre study.

SETTING

Intensive Care Unit (ICU).

PATIENTS

Adult patients admitted with COVID-19 and respiratory failure during the second and third pandemic waves.

INTERVENTIONS

None.

MAIN VARIABLES OF INTEREST

Collected data included demographic and clinical characteristics, comorbidities, laboratory tests and ICU outcomes. To validate our original USCM, we assigned a phenotype to each patient of the validation cohort. The performance of the classification was determined by Silhouette coefficient (SC) and general linear modelling. In a post-hoc analysis we developed and validated a USCM specific to the validation set. The model's performance was measured using accuracy test and area under curve (AUC) ROC.

RESULTS

A total of 2330 patients (mean age 63 [53-82] years, 1643 (70.5%) male, median APACHE II score (12 [9-16]) and SOFA score (4 [3-6]) were included. The ICU mortality was 27.2%. The USCM classified patients into 3 clinical phenotypes: A (n = 1206 patients, 51.8%); B (n = 618 patients, 26.5%), and C (n = 506 patients, 21.7%). The characteristics of patients within each phenotype were significantly different from the original population. The SC was -0.007 and the inclusion of phenotype classification in a regression model did not improve the model performance (0.79 and 0.78 ROC for original and validation model). The post-hoc model performed better than the validation model (SC -0.08).

CONCLUSION

Models developed using machine learning techniques during the first pandemic wave cannot be applied with adequate performance to patients admitted in subsequent waves without prior validation.

Glucocorticoid use in acute respiratory failure from pulmonary causes and association with early changes in the systemic host immune response

BACKGROUND

Glucocorticoids are commonly used in patients with or at-risk for acute respiratory distress syndrome (ARDS), but optimal use remains unclear despite well-conducted clinical trials. We performed a secondary analysis in patients previously enrolled in the Acute Lung Injury and Biospecimen Repository at the University of Pittsburgh. The primary aim of our study was to investigate early changes in host response biomarkers in response to real-world use of glucocorticoids in patients with acute respiratory failure due to ARDS or at-risk due to a pulmonary insult. Participants had baseline plasma samples obtained on study enrollment and on follow-up 3 to 5 days later to measure markers of innate immunity (IL-6, IL-8, IL-10, TNFr1, ST2, fractalkine), epithelial injury (sRAGE), endothelial injury (angiopoietin-2), and host response to bacterial infections (procalcitonin, pentraxin-3). In our primary analyses, we investigated the effect of receiving glucocorticoids between baseline and follow-up samples on host response biomarkers measured at follow-up by doubly robust inverse probability weighting analysis. In exploratory analyses, we examined associations between glucocorticoid use and previously characterized host response subphenotypes (hyperinflammatory and hypoinflammatory).

RESULTS

67 of 148 participants (45%) received glucocorticoids between baseline and follow-up samples. Dose and type of glucocorticoids varied. Regimens that used hydrocortisone alone were most common (37%), and median daily dose was equivalent to 40 mg methylprednisolone (interquartile range: 21, 67). Participants who received glucocorticoids were more likely to be female, to be on immunosuppressive therapy at baseline, and to have higher baseline levels of ST-2, fractalkine, IL-10, pentraxin-3, sRAGE, and TNFr1. Glucocorticoid use was associated with decreases in IL-6 and increases in fractalkine. In exploratory analyses, glucocorticoid use was more frequent in participants in the hyperinflammatory subphenotype (58% vs 40%, p = 0.05), and was not associated with subphenotype classification at the follow-up time point (p = 0.16).

CONCLUSIONS

Glucocorticoid use varied in a cohort of patients with or at-risk for ARDS and was associated with early changes in the systemic host immune response.

Deciphering the comprehensive knowledgebase landscape featuring infertility with IDDB Xtra

Infertility affects ∼15% of couples globally and half of cases are related to genetic disorders. Despite growing data and unprecedented improvements in high-throughput sequencing technologies, accumulated fertility-related issues concerning genetic diagnosis and potential treatment are urgent to be solved. However, there is a lack of comprehensive platforms that characterise various infertility-related records to provide research applications for exploring infertility in-depth and genetic counselling of infertility couple. To solve this problem, we provide IDDB Xtra by further integrating phenotypic manifestations, genomic datasets, epigenetics, modulators in collaboration with numerous interactive tools into our previous infertility database, IDDB. IDDB Xtra houses manually-curated 2369 genes of human and nine model organisms, 273 chromosomal abnormalities, 884 phenotypes, 60 genomic datasets, 464 epigenetic records, 1144 modulators relevant to infertility diagnosis and treatment. Additionally, IDDB Xtra incorporated customized graphical applications for researchers and clinicians to decipher in-depth disease mechanisms from the perspectives of developmental atlas, mutation effects, and clinical manifestations. Users can browse genes across developmental stages of human and mouse, filter candidate genes, mine potential variants and retrieve infertility biomedical network in an intuitive web interface. In summary, IDDB Xtra not only captures valuable research and data, but also provides useful applications to facilitate the genetic counselling and drug discovery of infertility. IDDB Xtra is freely available at https://mdl.shsmu.edu.cn/IDDB/and http://www.allostery.net/IDDB.

The enigma of depression in corticobasal degeneration, a frequent but poorly understood co-morbidity

Depression is one of the most frequent neuropsychiatric symptoms in corticobasal degeneration (CBD), a rare, sporadic, and late-onset progressive neurodegenerative disorder of unknown etiology. It is clinically characterized by a levodopa-poorly responsible akinetic-rigid syndrome, apraxia, limb dystonia, cognitive, mood, behavioral, and language disorders. This 4-repeat (4R) tauopathy is morphologically featured by asymmetric frontoparietal atrophy, neuronal loss, and gliosis in cortex and subcortex including substantia nigra, ballooned/achromatic neurons with filamentous 4R tau aggregates in cortex and striatum, widespread thread-like structures, pathognomonic "astroglial plaques", "tufted astrocytes", and numerous "coiled bodies" (in astrocytes and oligodendroglia) in cerebral white matter. CBD is non-specific, as pathologically proven cases include several clinical phenotypes. Pubmed and Google Scholar were systematically analyzed until October 2023, with focus on the prevalence, clinical manifestation, neuroimaging data, and treatment options of depression in CBD. Its prevalence is about 30-40% which is more frequent than in most other atypical parkinsonian syndromes. Depression usually does not correlate with motor and other clinical parameters, suggesting different pathophysiological mechanisms. Asymmetric atrophy and hypometabolism of frontoparietal cortical areas are associated with disruption of fronto-subcortical circuits, nigrostriatal dopaminergic, and cholinergic deficiency. Since no specific neuroimaging, neuropathological, or biomarker studies of depression in CBD are available, its pathobiological mechanisms and pathogenesis are poorly understood. Antidepressive therapy may be useful, but is often poorly tolerated. Depression in CBD, like in other parkinsonian syndromes, may be related to multi-regional patterns of cerebral disturbances and complex pathogenic mechanisms that deserve further elucidation as a basis for early diagnosis and adequate treatment to improve the quality of life in this fatal disease.

Clinical Subtypes of Neutrophilic Asthma: A Cluster Analysis From Australasian Severe Asthma Network

BACKGROUND

Clinical heterogeneity may exist within asthma subtypes defined by inflammatory markers. However, the heterogeneity of neutrophilic asthma (NA) remains largely unexplored.

OBJECTIVE

To explore potential clusters and the stability of NA.

METHODS

Participants with NA from the Australasian Severe Asthma Network underwent a multidimensional assessment. They were then asked to participate in a 12-month longitudinal cohort study. We explored potential clusters using a hierarchical cluster analysis and validated the differential future risk of asthma exacerbations in the identified clusters. A decision tree analysis was developed to predict cluster assignments. Finally, the stability of prespecified clusters was examined within 1 month.

RESULTS

Three clusters were identified in 149 patients with NA. Cluster 1 (n = 99; 66.4%) was characterized by female-predominant nonsmokers with well-controlled NA, cluster 2 (n = 16; 10.7%) by individuals with comorbid anxiety/depressive symptoms with poorly controlled NA, and cluster 3 by older male smokers with late-onset NA. Cluster 2 had a greater proportion of participants with severe exacerbations (P = .005), hospitalization (P = .010), and unscheduled visits (P = .013) and a higher number of emergency room visits (P = .039) than that of the other two clusters. The decision tree assigned 92.6% of participants correctly. Most participants (87.5%; n = 7) in cluster 2 had a stable NA phenotype, whereas participants of clusters 1 and 3 had variable phenotypes.

CONCLUSIONS

We identified three clinical clusters of NA, in which cluster 2 represents an uncontrolled and stable NA subtype with an elevated risk of exacerbations. These findings have clinical implications for the management of NA.

A study on genotypes and phenotypes of short stature caused by epigenetic modification gene variants

Mendelian disorders of the epigenetic machinery (MDEMs) are caused by genetic mutations, a considerable fraction of which are associated with epigenetic modification. These MDEMs exhibit phenotypic overlap broadly characterized by multiorgan abnormalities. The variant detected in genes associated with epigenetic modification can lead to short stature accompanied with multiple system abnormalities. This study is aimed at presenting and summarizing the diagnostic rate, clinical, and genetic profile of MDEMs-associated short stature. Two hundred and fourteen short-stature patients with multiorgan abnormalities were enrolled. Clinical information and whole exome sequence (WES) were analyzed for these patients. WES identified 33 pathogenic/likely pathogenic variants in 19 epigenetic modulation genes (KMT2A, KMT2D, KDM6A, SETD5, KDM5C, HUWE1, UBE2A, NIPBL, SMC1A, RAD21, CREBBP, CUL4B, BPTF, ANKRD11, CHD7, SRCAP, CTCF, MECP2, UBE3A) in 33 patients (15.4%). Of note, 19 variants had never been reported previously. Furthermore, these 33 variants were associated with 16 different disorders with overlapping clinical features characterized by development delay/intelligence disability (31/33; 93.9%), small hands (14/33; 42.4%), clinodactyly of the 5th finger (14/33; 42.4%), long eyelashes (13/33; 39.4%), and hearing impairment (9/33; 27.3%). Additionally, several associated phenotypes are reported for the first time: clubbing with KMT2A variant, webbed neck with SETD5 variant, retinal detachment with CREBBP variant, sparse lateral eyebrow with HUWE1 variant, and long palpebral fissure with eversion of the lateral third of the low eyelid with SRCAP variant.Conclusions: Our study provided a new conceptual framework for further understanding short stature. Specific clinical findings may indicate that a short-stature patient may have an epigenetic modified gene variant.

Profiling migraine patients according to clinical and psychophysical characteristics: clinical validity of distinct migraine clusters

AIMS

Investigate if different clinical and psychophysical bedside tools can differentiate between district migraine phenotypes in ictal/perictal (cohort 1) and interictal (cohort 2) phases.

METHOD

This observational study included two independent samples in which patients were subgrouped into distinct clusters using standardized bedside assessment tools (headache frequency, disability, cervical active range of motion, pressure pain threshold in different areas): (A) cohort 1-ictal/perictal migraine patients were subgrouped, based on previous studies, into two clusters, i.e., Cluster-1.1 No Psychophysical Impairments (NPI) and Cluster-1.2 Increased Pain Sensitivity and Cervical Musculoskeletal Dysfunction (IPS-CMD); (B) cohort 2-interictal migraine patients were subgrouped into three clusters, i.e., Cluster-2.1 NPI, Cluster-2.2 IPS, and Cluster-2.3 IPS-CMD. Clinical characteristics (multiple questionnaires), somatosensory function (comprehensive quantitative sensory testing (QST)), and cervical musculoskeletal impairments (cervical musculoskeletal assessment) were assessed and compared across headache clusters and a group of 56 healthy controls matched for sex and age.

RESULTS

Cohort 1: A total of 156 subjects were included. Cluster-1.2 (IPS-CMD) had higher headache intensity (p = 0.048), worse headache-related (p = 0.003) and neck-related disability (p = 0.005), worse quality of life (p = 0.003), and higher symptoms related to sensitization (p = 0.001) and psychological burden (p = 0.005) vs. Cluster-1.1(NPI). Furthermore, Cluster-1.2 (IPS-CMD) had (1) reduced cervical active and passive range of motion (p < 0.023), reduced functionality of deep cervical flexors (p < 0.001), and reduced values in all QST(p < 0.001) vs. controls, and (2) reduced active mobility in flexion, left/right lateral flexion (p < 0.045), and reduced values in QST (p < 0.001) vs. Cluster-1.1 (NPI). Cohort 2: A total of 154 subjects were included. Cluster-2.3 (IPS-CMD) had (1) longer disease duration (p = 0.006), higher headache frequency (p = 0.006), disability (p < 0.001), and psychological burden (p = 0.027) vs. Cluster-2.2 (IPS) and (2) higher headache-related disability (p = 0.010), neck-related disability (p = 0.009), and higher symptoms of sensitization (p = 0.018) vs. Cluster-2.1 (NPI). Cluster-2.3(IPS-CMD) had reduced cervical active and passive range of motion (p < 0.034), and reduced functionality of deep cervical flexors (p < 0.001), vs. controls, Custer-2.1 (NPI), and Cluster-2.2 (IPS). Cluster-2.2 (IPS) and 2.3 (IPS-CMD) had reduced QST values vs. controls (p < 0.001) and Cluster-2.1 (p < 0.039).

CONCLUSION

A battery of patient-related outcome measures (PROMs) and quantitative bedside tools can separate migraine clusters with different clinical characteristics, somatosensory functions, and cervical musculoskeletal impairments. This confirms the existence of distinct migraine phenotypes and emphasizes the importance of migraine phases of which the characteristics are assessed. This may have implications for responders and non-responders to anti-migraine medications.

Pain-phenotyping in osteoarthritis: Current concepts, evidence, and considerations towards a comprehensive framework for assessment and treatment

Objectives

Pain as central symptom of osteoarthritis (OA) needs to be addressed as part of successful treatment. The assessment of pain as feature of disease or outcome in clinical practice and drug development remains a challenge due to its multidimensionality and the plethora of confounders. This article aims at providing insights into our understanding of OA pain-phenotypes and suggests a framework for systematic and comprehensive assessments.

Methods

This narrative review is based on a search of current literature for various combinations of the search terms "pain-phenotype" and "knee OA" and summarizes current knowledge on OA pain-phenotypes, putting OA pain and its assessment into perspective of current research efforts.

Results

Pain is a complex phenomenon, not necessarily associated with tissue damage. Various pain-phenotypes have been described in knee OA. Among those, a phenotype with high pain levels not necessarily matching structural changes and a phenotype with low pain levels and impact are relatively consistent. Further subgroups can be differentiated based on patient reported outcome measures, assessments of comorbidities, anxiety and depression, sleep, activity and objective measures such as quantitative sensory testing.

Conclusions

The complexity of both OA as disease and pain in OA prompt the definition of a set of variables that facilitate assessments comparable across studies to maximize our understanding of pain, as central concern for the patient.

A proposed framework for advancing acute kidney injury risk stratification and diagnosis in children: a report from the 26th Acute Disease Quality Initiative (ADQI) conference

Acute kidney injury (AKI) in children is associated with increased morbidity, reduced health-related quality of life, greater resource utilization, and higher mortality. Improvements in the timeliness and precision of AKI diagnosis in children are needed. In this report, we highlight existing, novel, and on-the-horizon diagnostic and risk-stratification tools for pediatric AKI, and outline opportunities for integration into clinical practice. We also summarize pediatric-specific high-risk diagnoses and exposures for AKI, as well as the potential role of real-time risk stratification and clinical decision support to improve outcomes. Lastly, the key characteristics of important pediatric AKI phenotypes will be outlined. Throughout, we identify key knowledge gaps, which represent prioritized areas of focus for future research that will facilitate a comprehensive, timely and personalized approach to pediatric AKI diagnosis and management.

Phenotype-specific therapeutic efficacy of ilofotase alfa in patients with sepsis-associated acute kidney injury

BACKGROUND

There is no effective treatment for sepsis-associated acute kidney injury (SA-AKI). Ilofotase alfa (human recombinant alkaline phosphatase) has been shown to exert reno-protective properties, although it remains unclear which patients might be most likely to benefit. We aimed to identify a clinical phenotype associated with ilofotase alfa's therapeutic efficacy.

METHODS

Data from 570 out of 650 patients enrolled in the REVIVAL trial were used in a stepwise machine learning approach. First, clinical variables with increasing or decreasing risk ratios for ilofotase alfa treatment across quartiles for the main secondary endpoint, Major Adverse Kidney Events up to day 90 (MAKE90), were selected. Second, linear regression analysis was used to determine the therapeutic effect size. Finally, the top-15 variables were used in different clustering analyses with consensus assessment.

RESULTS

The optimal clustering model comprised two phenotypes. Phenotype 1 displayed relatively lower disease severity scores, and less pronounced renal and pulmonary dysfunction. Phenotype 2 exhibited higher severity scores and creatinine, with lower eGFR and bicarbonate levels. Compared with placebo treatment, ilofotase alfa significantly reduced MAKE90 events for phenotype 2 patients (54% vs. 68%, p = 0.013), but not for phenotype 1 patients (49% vs. 46%, p = 0.54).

CONCLUSION

We identified a clinical phenotype comprising severely ill patients with underlying kidney disease who benefitted most from ilofotase alfa treatment. This yields insight into the therapeutic potential of this novel treatment in more homogeneous patient groups and could guide patient selection in future trials, showing promise for personalized medicine in SA-AKI and other complex conditions.

[Management of cardiomyopathies : New ESC guidelines 2023]

The group of cardiomyopathies has received increasing attention over the last few years after some of the causes were identified and they could be characterized more exactly using modern imaging methods. New definitions and classification schemes were regularly provided by national and international cardiac societies. The new guidelines of the European Society of Cardiology (ESC) from 2023 on the management of cardiomyopathies are the first guidelines that comprehensively address all cardiomyopathies in one document. As these are new guidelines most of the recommendations are also new. An exception is the section on hypertrophic cardiomyopathy (HCM), which provides a targeted update of the 2014 ESC guidelines on the diagnosis and treatment of HCM. The main aim of the guidelines is to provide clear guidance for the diagnosis of cardiomyopathies, to highlight general assessment and management problems and to point out the relevant scientific evidence for the recommendations to the readership. Due to the magnitude detailed descriptions and recommendations cannot be provided for each individual cardiomyopathy phenotype; however, reference is made to the relevant literature.

Latent Class Analysis Identifies Distinctive Behavioral Subtypes in Children with Fragile X Syndrome

Fragile X syndrome (FXS) is characterized by variable neurobehavioral abnormalities, which leads to difficulties in developing and evaluating treatments and in determining accurate prognosis. We employed a pediatric cross-sectional sample (1,072 males, 338 females) from FORWARD, a clinic-based natural history study, to identify behavioral subtypes by latent class analysis. Input included co-occurring behavioral conditions, sleep and sensory problems, autistic behavior scales (SCQ, SRS-2), and the Aberrant Behavior Checklist revised for FXS (ABCFX). A 5-class solution yielded the most clinically meaningful, pharmacotherapy independent behavioral groups with distinctive SCQ, SRS-2, and ABCFX profiles, and adequate non-overlap (≥ 71%): "Mild" (31%), "Moderate without Social Impairment" (32%), "Moderate with Social Impairment" (7%), "Moderate with Disruptive Behavior" (20%), and "Severe" (9%). Our findings support FXS subtyping, for improving clinical management and therapeutic development.

Exploring different models of pain phenotypes and their association with pain worsening in people with early knee osteoarthritis: The MOST cohort study

OBJECTIVE

To determine i) pain phenotypes (PP) in people with early-stage knee osteoarthritis (EKOA); ii) the longitudinal association between the phenotypes and pain worsening at two years.

DESIGN

We studied participants with EKOA from the Multicenter Osteoarthritis Study defined as pain intensity ≤3/10, Kellgren and Lawrence grade ≤2, intermittent pain none to sometimes, and no constant pain. Two models of PP were explored. Model A included pressure pain thresholds, temporal summation, conditioned pain modulation, pain catastrophizing, sleep quality, depression, and widespread pain (WSP). In Model B, gait characteristics, quadriceps strength, comorbidities, and magnetic resonance imaging features were added to Model A. Latent Class Analysis was used to create phenotypes, and logistic regression was used to determine their association with pain worsening.

RESULTS

750 individuals (60% females), mean age [standard deviation (SD)]: 60.3 (9.4) were included in Model A and 333 individuals (60% females), mean age (SD): 59.4 (8.1) in Model B. 3-class and 4-class solutions were chosen for Model A and Model B. In Model A, the most "severe" phenotype was dominated by psychosocial factors, WSP, and measures of nervous system sensitization. Similarly in Model B, the Model A phenotype plus gait variables, quadriceps strength, and comorbidities were dominant. Surprisingly, none of the phenotypes in either model had a significant relationship with pain worsening.

CONCLUSION

Phenotypes based upon various factors thought to be important for the pain experience were identified in those with EKOA but were not significantly related to pain worsening. These phenotypes require validation with clinically relevant endpoints.

De Novo Dissecting the Three-Dimensional Facial Morphology of 2379 Han Chinese Individuals

Phenotypic diversity, especially that of facial morphology, has not been fully investigated in the Han Chinese, which is the largest ethnic group in the world. In this study, we systematically analyzed a total of 14,838 facial traits representing 15 categories with both a large-scale three-dimensional (3D) manual landmarking database and computer-aided facial segmented phenotyping in 2379 Han Chinese individuals. Our results illustrate that homogeneous and heterogeneous facial morphological traits exist among Han Chinese populations across the three geographical regions: Zhengzhou, Taizhou, and Nanning. We identified 1560 shared features from extracted phenotypes, which characterized well the basic facial morphology of the Han Chinese. In particular, heterogeneous phenotypes showing population structures corresponded to geographical subpopulations. The greatest facial variation among these geographical populations was the angle of glabella, left subalare, and right cheilion (p = 3.4 × 10-161). Interestingly, we found that Han Chinese populations could be classified into northern Han, central Han, and southern Han at the phenotypic level, and the facial morphological variation pattern of central Han Chinese was between the typical differentiation of northern and southern Han Chinese. This result was highly consistent with the results revealed by the genetic data. These findings provide new insights into the analysis of multidimensional phenotypes as well as a valuable resource for further facial phenotype-genotype association studies in Han Chinese and East Asian populations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00109-x.

Comorbid Inducible Urticaria Is Linked to Non-Autoimmune Chronic Spontaneous Urticaria: CURE Insights

BACKGROUND

Patients with chronic spontaneous urticaria (CSU) can have comorbid inducible urticaria (CIndU). How comorbid CIndU affects patients and their CSU is largely unclear.

OBJECTIVE

To compare patients with CSU with and without comorbid CIndUs for differences in demographic features, clinical characteristics, and laboratory markers.

METHODS

We analyzed 708 patients with CSU of our Urticaria Center of Reference and Excellence enrolled in CURE, the chronic urticaria registry. CURE data collected until October 2022 were used to compare patients with and without comorbid CIndU for their demographic characteristics, disease onset, activity, impact, and control, as well as concomitant allergic and autoimmune diseases and laboratory parameters associated with autoimmune CSU.

RESULTS

Of 708 patients with CSU, 247 (35%) had comorbid CIndU. Compared with patients with standalone CSU, patients with CSU with comorbid CIndU were significantly younger, had earlier disease onset, longer disease duration, higher impact on quality of life, and a higher rate of concomitant allergic diseases. Moreover, patients with CSU with comorbid CIndU less often had features linked to autoimmune CSU such as angioedema, concomitant autoimmune diseases, eosinopenia, low levels of total IgE, and low total IgE combined with elevated anti-thyroid peroxidase IgG.

CONCLUSIONS

Autoimmune CSU may be less common in patients with comorbid CIndU than without, and comorbid CIndU may point to autoallergic CSU.

Increasing Age at the Time of Diagnosis and Evolving Phenotypes of Eosinophilic Esophagitis Over 20 Years

BACKGROUND

The presentation of eosinophilic esophagitis (EoE) is heterogeneous, but trends over time are not known.

AIM

To determine whether clinical and endoscopic phenotypes at EoE diagnosis have changed over the past 2 decades.

METHODS

In this retrospective cohort study, adults and children with newly diagnosed EoE were phenotyped as follows: (1) inflammatory vs fibrostenotic vs mixed on endoscopy; (2) atopic vs non-atopic; (3) age at symptom onset; (4) age at diagnosis; (5) presence of autoimmune or connective tissue disease; and (6) responsive to steroids. The prevalence of different phenotypes was categorized by 5-year intervals. Multivariate analysis was performed to assess for changes in patient features over time.

RESULTS

Of 1187 EoE patients, age at diagnosis increased over time (from 22.0 years in 2002-2006 to 31.8 years in 2017-2021; p < 0.001) as did the frequency of dysphagia (67% to 92%; p < 0.001). Endoscopic phenotypes were increasingly mixed (26% vs 68%; p < 0.001) and an increasing proportion of patients had later onset of EoE. However, there were no significant trends for concomitant autoimmune/connective tissue disease or steroid responder phenotypes. On multivariate analysis, after accounting for age, dysphagia, and food impaction, the increase in the mixed endoscopic phenotype persisted (aOR 1.51 per each 5-year interval, 95% CI 1.31-1.73).

CONCLUSION

EoE phenotypes have changed over the past two decades, with increasing age at diagnosis and age at symptom onset. The mixed endoscopic phenotype also increased, even after controlling for age and symptomatology. Whether this reflects changes in provider recognition or disease pathophysiology is yet to be elucidated.

Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, Ca2+ imaging and electrophysiology

I review recent technological advancements in coupling single-cell transcriptomics with cellular phenotypes including morphology, calcium signaling, and electrophysiology. Single-cell RNA sequencing (scRNAseq) has revolutionized cell type classifications by capturing the transcriptional diversity of cells. A new wave of methods to integrate scRNAseq and biophysical measurements is facilitating the linkage of transcriptomic data to cellular function, which provides physiological insight into cellular states. I briefly discuss critical factors of these phenotypical characterizations such as timescales, information content, and analytical tools. Dedicated sections focus on the integration with cell morphology, calcium imaging, and electrophysiology (patch-seq), emphasizing their complementary roles. I discuss their application in elucidating cellular states, refining cell type classifications, and uncovering functional differences in cell subtypes. To illustrate the practical applications and benefits of these methods, I highlight their use in tissues with excitable cell-types such as the brain, pancreatic islets, and the retina. The potential of combining functional phenotyping with spatial transcriptomics for a detailed mapping of cell phenotypes in situ is explored. Finally, I discuss open questions and future perspectives, emphasizing the need for a shift towards broader accessibility through increased throughput.

MicroRNAs correlate with bacillary index and genes associated to cell death processes in leprosy

Mycobacterium leprae infects skin and peripheral nerves causing a broad of clinical forms. MicroRNAs (miRNAs) control immune mechanisms such as apoptosis, autophagy as well as to target genes leading to abnormal proliferation, metastasis, and invasion of cells. Herein we evaluated miRNAs expression for leprosy phenotypes in biopsies obtained from patients with and without reactions. We also correlated those miRNAs with both, bacillary index (BI) and genes involved in the micobacteria elimination process. Our results show a significant increase in the miR-125a-3p expression in paucibacillary (PB) patients vs multibacillary (MB) subjects (p = 0.007) and vs reversal reactions (RR) (p = 0.005), respectively. Likewise, there was a higher expression of miR-125a-3p in patients with erythema nodosum leprosum (ENL) vs MB without reactions (p = 0.002). Furthermore, there was a positive correlation between miR-125a-3p, miR-146b-5p and miR-132-5p expression and BI in patients with RR and ENL. These miRNAS were also correlated with genes such as ATG12 (miR-125a-3p), TNFRSF10A (miR-146b-5p), PARK2, CFLAR and STX7 (miR-132-5p). All together we underpin a role for these miRNAs in leprosy pathogenesis, implicating mechanisms such as apoptosis and autophagy in skin. The miR-125a-3p might have a distinct role associated with PB phenotype and ENL in MB patients.

Incidence of Different Characters of Neuropathic Pain in Cancer Patients Coming to Tertiary Care Centre in North India Over A Period of 1 Year - An Observational Study

Objectives

Pain is classified as nociceptive, neuropathic, or nociplastic. Neuropathic pain presents as variable phenotypes (characters) based on specific aetiology and pathophysiology. This study aimed to find out among cancer patients the incidence of different phenotypes of neuropathic pain and form specific phenotypic clusters based on the underlying neurophysiology and association of sensory profile with various organ systems - A prospective observational study.

Materials and methods

The Institutional Ethical Committee clearance (IEC code: 2020-49-MD-EXP-15) https://ctri.nic.in/Clinicaltrials/showallp.php?mid1=44886&EncHid=88651.15716&userName=CTRI/2020/09/027964 approval was obtained. After written and informed consent, patients of age group 18-80 years, registering in the pain and palliative outpatient department or radiotherapy department with complaints of pain and not taking any anti-neuropathic pain medications, were enrolled. They were assessed using Leeds assessment of neuropathic symptoms and signs (LANSS) pain score, and a score of >12 was eligible for assessment of neuropathic pain phenotypes.

Results

Out of 210 cancer patients complaining of pain, a neuropathic component with LANSS >12 was found in 73 (34.76%). The most predominant phenotypes, allodynia> tingling> pricking = burning, were found in 72.60%, 56.16%, and 43.84% of patients, respectively. Phenotypes were clustered into Nodes 1 and 2 based on clinically significant separation of phenotypes. Node 1 had neuropathic pain of spontaneous origin found predominantly in gastrointestinal tract (GIT) and genitourinary tract (GUT) cancers. Node 2 had stimulus-evoked negative and positive characters which occurred in head and neck, thoracic, and spinal metastatic cancers.

Conclusion

Careful patient assessment reveals the incidence of neuropathic pain in 34.76%; allodynia and tingling astable the most prominent phenotypes. Broadly, sensory characters were clustered into spontaneous and stimulus-evoked sensations with GIT and GUT cancers presenting with Node 1 symptoms.

Obstructive sleep apnea diagnosis and beyond using portable monitors

Obstructive sleep apnea (OSA) is a chronic sleep and breathing disorder with significant health complications, including cardiovascular disease and neurocognitive impairments. To ensure timely treatment, there is a need for a portable, accurate and rapid method of diagnosing OSA. This review examines the use of various physiological signals used in the detection of respiratory events and evaluates their effectiveness in portable monitors (PM) relative to gold standard polysomnography. The primary objective is to explore the relationship between these physiological parameters and OSA, their application in calculating the apnea hypopnea index (AHI), the standard metric for OSA diagnosis, and the derivation of non-AHI metrics that offer additional diagnostic value. It is found that increasing the number of parameters in PMs does not necessarily improve OSA detection. Several factors can cause performance variations among different PMs, even if they extract similar signals. The review also highlights the potential of PMs to be used beyond OSA diagnosis. These devices possess parameters that can be utilized to obtain endotypic and other non-AHI metrics, enabling improved characterization of the disorder and personalized treatment strategies. Advancements in PM technology, coupled with thorough evaluation and validation of these devices, have the potential to revolutionize OSA diagnosis, personalized treatment, and ultimately improve health outcomes for patients with OSA. By identifying the key factors influencing performance and exploring the application of PMs beyond OSA diagnosis, this review aims to contribute to the ongoing development and utilization of portable, efficient, and effective diagnostic tools for OSA.

Chronic endometritis incidence in infertile women with and without polycystic ovary syndrome: a propensity score matched study

BACKGROUND

Polycystic ovary syndrome (PCOS) is known to be associated with chronic low-grade inflammation and endometrial dysfunction. Chronic endometritis (CE) is a type of local inflammation that can contribute to endometrial dysfunction in infertile women. Some clinicians recommend screening for CE in women at high risk, such as those with endometrial polyps. However, it is still uncertain whether there is a relationship between PCOS and CE, as well as whether women with PCOS require enhanced screening for CE. This study was to assess the incidence of CE among infertile women with PCOS by hysteroscopy combined with histopathology CD138 immunohistochemical staining of endometrium.

METHODS

A total of 205 patients in the PCOS group and 4021 patients in the non-PCOS group from July 2017 to August 2022 were included in this retrospective study. After nearest-neighbor 1:4 propensity score matching (PSM), 189 PCOS patients were matched with 697 non-PCOS patients. Basic information was recorded. The CE incidence was compared. The risk factors affecting CE incidence were also analyzed.

RESULTS

No significantly higher CE incidence in infertile women with PCOS were found either in total analysis or after PSM (P = 0.969; P = 0.697; respectively). Similar results were discovered in the subgroup of Body Mass Index (BMI) (P = 0.301; P = 0.671; P = 0.427; respectively) as well as the four PCOS phenotypes (P = 0.157). Intriguingly, the incidence of CE increased as BMI increased in the PCOS group, even though no significant differences were found (P = 0.263). Multivariate logistic regression showed that age, infertility duration, infertility type, PCOS, and obesity were not the independent risk factors affecting CE incidence.

CONCLUSION

The incidence of CE in PCOS patients did not significantly increase compared to non-PCOS patients. Similarly, no significant differences in the incidence of CE were observed among different PCOS phenotypes. The current evidence does not substantiate the need for widespread CE screening among PCOS women, potentially mitigating the undue financial and emotional strain associated with such screenings.

Association of insulin resistance with polycystic ovary syndrome phenotypes and patients' characteristics: a cross-sectional study in Iran

BACKGROUND

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women. This disorder affects 6-15% of women of childbearing age worldwide. It is diagnosed with hyperandrogenism, polycystic ovaries, and chronic anovulation with insulin resistance. This study aimed to assess the prevalence of insulin resistance (IR) in 4 phenotypes of PCOS, and its relationship with demographic, clinical, and paraclinical individual characteristics in a sample of Iranian PCOS patients.

METHODS

This particular cross-sectional investigation involved 160 female participants, aged between 18 and 45 years, who were receiving care at gynecology clinics in Urmia, northwestern Iran. All the participants had been diagnosed with PCOS and were categorized into one of four phenotypes. All the participants underwent clinical evaluations, paraclinical assessments, and ultrasound scans. IR was defined as HOMA-IR > 2.5. The statistical significance level was 0.05.

RESULTS

Among the 160 participants, the prevalences of the 4 phenotypes were: A: 83 (51.9%), B: 37 (23.1%), C: 21 (13.1%), and D: 19 (11.9%). IR was detected in 119 participants (74.4%); its rate was significantly different between the 4 phenotypes (p-value: 0.008) as A: 62 (74.7%), B: 34 (91.9%), C: 12 (57.1%), D: 11 (57.9%). Linear and logistic regression analyses were performed to control confounding factors. In linear regression, PCOS phenotype, classic phenotype (A&B), economic status, and Hb levels were significantly related to HOMA-IR; in logistic regression Hb levels, exercise, economic status, and PCOS phenotypes were significantly associated with insulin resistance.

CONCLUSIONS

The most prevalent PCOS phenotype in this study was A. PCOS phenotypes were significantly related to insulin resistance and HOMA-IR, with the highest levels of insulin resistance and HOMA-IR observed in phenotype B. Determining the phenotype of PCOS may be helpful for better management of PCOS and its associated complications. However, further investigations are recommended in this regard.

Acute heart failure: mechanisms and pre-clinical models-a Scientific Statement of the ESC Working Group on Myocardial Function

While chronic heart failure (CHF) treatment has considerably improved patient prognosis and survival, the therapeutic management of acute heart failure (AHF) has remained virtually unchanged in the last decades. This is partly due to the scarcity of pre-clinical models for the pathophysiological assessment and, consequently, the limited knowledge of molecular mechanisms involved in the different AHF phenotypes. This scientific statement outlines the different trajectories from acute to CHF originating from the interaction between aetiology, genetic and environmental factors, and comorbidities. Furthermore, we discuss the potential molecular targets capable of unveiling new therapeutic perspectives to improve the outcome of the acute phase and counteracting the evolution towards CHF.

Is metabolic-healthy obesity associated with risk of dementia? An age-stratified analysis of the Whitehall II cohort study

BACKGROUND

Metabolically healthy obesity is hypothesized to be a benign condition but whether this is the case for dementia remains debated. We examined the role of age at assessment of metabolic-obesity phenotypes in associations with incident dementia.

METHODS

Obesity (body mass index ≥ 30 kg/m2) and poor metabolic health (≥ 2 of elevated serum triglycerides, low HDL-C, elevated blood pressure, and elevated serum fasting glucose) were used to define four metabolic-obesity phenotypes (metabolically healthy (MHNO) and unhealthy non-obesity (MUNO), metabolically healthy (MHO) and unhealthy obesity (MUO)) at < 60, 60 to < 70, and ≥ 70 years using 6 waves of data from the Whitehall II study and their associations with incident dementia was examined using Cox regression.

RESULTS

Analyses with exposures measured < 60, 60 to < 70, and ≥ 70 years involved 410 (5.8%), 379 (5.6%), and 262 (7.4%) incident dementia cases over a median follow-up of 20.8, 10.3, and 4.2 years respectively. In analyses of individual components, obesity before 60 years (HR 1.41, 95% CI: [1.08, 1.85]) but not at older ages was associated with dementia; unhealthy metabolic status when present < 60 years (HR 1.33, 95% CI: [1.08, 1.62]) and 60 to < 70 years (HR 1.32, 95% CI: [1.07, 1.62]) was associated with dementia. Compared to the metabolically healthy non-obesity group, the risk of dementia was higher in those with metabolically healthy obesity before 60 years (1.69; 95% CI: [1.16, 2.45]); this was not the case when metabolic-obesity phenotype was present at 60 to < 70 years or ≥ 70 years. Analyses at older ages were on smaller numbers due to death and drop-out but inverse probability weighting to account for missing data yielded similar results.

CONCLUSIONS

Individuals with metabolically healthy obesity before age 60 had a higher risk of incident dementia over a 27-year follow-up; the excess risk dissipates when metabolic health and obesity are measured after 70 years.

Application of the International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) to frontal lobe epilepsy using multicenter data

RATIONALE

The International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) was recently introduced as a consensus-based, empirically-driven taxonomy of cognitive disorders in epilepsy and has been effectively applied to patients with temporal lobe epilepsy (TLE). The purpose of this study was to apply the IC-CoDE to patients with frontal lobe epilepsy (FLE) using national multicenter data.

METHODS

Neuropsychological data of 455 patients with FLE aged 16 years or older were available across four US-based sites. First, we examined test-specific impairment rates across sites using two impairment thresholds (1.0 and 1.5 standard deviations below the normative mean). Following the proposed IC-CoDE guidelines, patterns of domain impairment were determined based on commonly used tests within five cognitive domains (language, memory, executive functioning, attention/processing speed, and visuospatial ability) to construct phenotypes. Impairment rates and distributions across phenotypes were then compared with those found in patients with TLE for which the IC-CoDE classification was initially validated.

RESULTS

The highest rates of impairment were found among tests of naming, verbal fluency, speeded sequencing and set-shifting, and complex figure copy. The following IC-CoDE phenotype distributions were observed using the two different threshold cutoffs: 23-40% cognitively intact, 24-29% single domain impairment, 13-20% bi-domain impairment, and 18-33% generalized impairment. Language was the most common single domain impairment (68% for both thresholds) followed by attention and processing speed (15-18%). Overall, patients with FLE reported higher rates of cognitive impairment compared with patients with TLE.

CONCLUSIONS

These results demonstrate the applicability of the IC-CoDE to epilepsy syndromes outside of TLE. Findings indicated generally stable and reproducible phenotypes across multiple epilepsy centers in the U.S. with diverse sample characteristics and varied neuropsychological test batteries. Findings also highlight opportunities for further refinement of the IC-CoDE guidelines as the application expands.

Structural phenotypes of knee osteoarthritis: potential clinical and research relevance

A joint contains many different tissues that can exhibit pathological changes, providing many potential targets for treatment. Researchers are increasingly suggesting that osteoarthritis (OA) comprises several phenotypes or subpopulations. Consequently, a treatment for OA that targets only one pathophysiologic abnormality is unlikely to be similarly efficacious in preventing or delaying the progression of all the different phenotypes of structural OA. Five structural phenotypes have been proposed, namely the inflammatory, meniscus-cartilage, subchondral bone, and atrophic and hypertrophic phenotypes. The inflammatory phenotype is characterized by marked synovitis and/or joint effusion, while the meniscus-cartilage phenotype exhibits severe meniscal and cartilage damage. Large bone marrow lesions characterize the subchondral bone phenotype. The hypertrophic and atrophic OA phenotype are defined based on the presence large osteophytes or absence of any osteophytes, respectively, in the presence of concomitant cartilage damage. Limitations of the concept of structural phenotyping are that they are not mutually exclusive and that more than one phenotype may be present. It must be acknowledged that a wide range of views exist on how best to operationalize the concept of structural OA phenotypes and that the concept of structural phenotypic characterization is still in its infancy. Structural phenotypic stratification, however, may result in more targeted trial populations with successful outcomes and practitioners need to be aware of the heterogeneity of the disease to personalize their treatment recommendations for an individual patient. Radiologists should be able to define a joint at risk for progression based on the predominant phenotype present at different disease stages.