Definition Of Phenotype Research Articles

Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank

Depression is assessed in various ways in research, with large population studies often relying on minimal phenotyping. Genetic results suggest clinical diagnoses and self-report measures of depression show some core similarities, but also important differences. It is not yet clear how neuroimaging associations depend on levels of phenotyping. We studied 39,300 UK Biobank imaging participants (20,701 female; aged 44.6 to 82.3 years, M = 64.1, SD = 7.5) with structural neuroimaging and lifetime depression data. Past depression phenotypes included a single-item self-report measure, an intermediate measure of ‘probable’ lifetime depression, derived from multiple questionnaire items relevant to a history of depression, and a retrospective clinical diagnosis according to DSM-IV criteria. We tested (i) associations between brain structural measures and each depression phenotype, and (ii) effects of phenotype on these associations. Depression-brain structure associations were small (β < 0.1) for all phenotypes, but still significant after FDR correction for many regional metrics. Lifetime depression was consistently associated with reduced white matter integrity across phenotypes. Cortical thickness showed negative associations with Self-reported Depression in particular. Phenotype effects were small across most metrics, but significant for cortical thickness in most regions. We report consistent effects of lifetime depression in brain structural measures, including reduced integrity of thalamic radiations and association fibres. We also observed significant differences in associations with cortical thickness across depression phenotypes. Although these results did not relate to level of phenotyping as expected, effects of phenotype definition are still an important consideration for future depression research.

Genetics in psychiatry: Methods, clinical applications and future perspectives.

Psychiatric disorders and related traits have a demonstrated genetic component, with heritability estimated by twin studies generally between 80% and 40%. Their pathogenesis is complex and multi-determined: environmental factors interact with a polygenic architecture, making difficult the development of models able to stratify patients or predict mental health outcomes. Despite this difficult challenge, relevant progress has been made in the field of psychiatric genetics in recent years. This review aims to present the main current methods in psychiatric genetics, their output, limitations, clinical applications, and possible future developments. Genome-wide association studies (GWASs) performed in increasingly large samples have led to the identification of replicated genetic loci associated with the risk of major psychiatric disorders, including schizophrenia and mood disorders. Statistical and biological approaches have been developed to improve our understanding of the etiopathogenetic mechanisms behind genome-wide significant associations, as well as for estimating the cumulative effect of risk variants at the individual level and the genetic overlap between different disorders, as pleiotropy is the rule rather than the exception. Clinical applications are available in the pharmacogenetics field. The main issues that remain to be addressed include improving ethnic diversity in genetic studies and the optimization of statistical power through methodological improvements, such as the definition of dimensional phenotypes with specific biological correlates and the integration of different types of omics data.

Expanded COVID-19 phenotype definitions reveal distinct patterns of genetic association and protective effects.

Multiple COVID-19 genome-wide association studies (GWASs) have identified reproducible genetic associations indicating that there is a genetic component to susceptibility and severity risk. To complement these studies, we collected deep coronavirus disease 2019 (COVID-19) phenotype data from a survey of 736,723 AncestryDNA research participants. With these data, we defined eight phenotypes related to COVID-19 outcomes: four phenotypes that align with previously studied COVID-19 definitions and four 'expanded' phenotypes that focus on susceptibility given exposure, mild clinical manifestations and an aggregate score of symptom severity. We performed a replication analysis of 12 previously reported COVID-19 genetic associations with all eight phenotypes in a trans-ancestry meta-analysis of AncestryDNA research participants. In this analysis, we show distinct patterns of association at the 12 loci with the eight outcomes that we assessed. We also performed a genome-wide discovery analysis of all eight phenotypes, which did not yield new genome-wide significant loci but did suggest that three of the four 'expanded' COVID-19 phenotypes have enhanced power to capture protective genetic associations relative to the previously studied phenotypes. Thus, we conclude that continued large-scale ascertainment of deep COVID-19 phenotype data would likely represent a boon for COVID-19 therapeutic target identification.

Chronic Lung Allograft Dysfunction: More Than Meets the Eye?

<h3>Purpose</h3> Currently, chronic lung allograft dysfunction (CLAD) is defined as the presence of an irreversible or partly reversible (to ≤ 80% of baseline) decline in FEV1 compared with baseline FEV1 values, persistent for at least 3 months. In established CLAD, total lung capacity (TLC) and chest computed tomography (CT) are required to determine the CLAD phenotype, as this has therapeutic and prognostic significance. Current CLAD phenotypes comprise bronchiolitis obliterans syndrome (BOS), restrictive allograft syndrome (RAS), Mixed, or Undefined (in patients who do not fit in either of the other phenotypes). However, some patients may present with persistent (> 3 months) chest CT abnormalities suggestive for chronic lung allograft injury/remodelling, without clear spirometric evidence of physiologic lung allograft impairment. <h3>Methods</h3> We report a series of 7 lung transplant recipients demonstrating chronic radiological abnormalities comparable to that seen in CLAD (RAS/mixed), after exclusion of other underlying causes for the observed radiological abnormalities, yet without (significant) pulmonary function decline. <h3>Results</h3> All patients had clear, persistent (> 3 months) radiological signs of chronic lung allograft injury/remodelling, however, not qualifying for formal CLAD diagnosis (i.e. FEV1 decline ≥ 20% from baseline), but instead looming in the potential CLAD area (FEV1 decline ≥ 10% from baseline) or even presenting with normal spirometry on regular pulmonary function testing. <h3>Conclusion</h3> A subgroup of lung transplant recipients may atypically present with chronic parenchymal/interstitial (‘RAS-like') abnormalities on chest CT, without qualifying for the phenotypic definition of CLAD, according to current consensus. This warrants further reflection on the role of spirometry for detection of interstitial lung disease after lung transplantation, the potential need for regular chest CT during post-transplant follow-up, and accuracy of the current CLAD definition regarding physical lung allograft characteristics.

Metabolic Phenotypes-The Game Changer in Quality of Life of Obese Patients?

Background: The present study aimed to investigate the association of obesity phenotypes and quality of life (QoL) scales and their relationship with fat mass (FM) parameters. Methods: This study categorized 104 subjects into 4 obesity phenotypes based on BMI and metabolic syndrome status: metabolically healthy obese (MHO), metabolically unhealthy obese (MUO), metabolically healthy non-obese (MHNO), and metabolically unhealthy non-obese (MUNO). Body composition was measured by dual-energy X-ray absorptiometry (DEXA) and metabolic profile was characterized by blood samples. All subjects completed the SF-36 item Short Form Health Survey Questionnaire. Results: Comparing the four obesity phenotypes, significant results were reported for Bodily Pain between MHNO/MUNO (p = 0.034), for Vitality between MHO/MUO (p = 0.024), and for Mental Component Score between MHO/MUO (p = 0.026) and MUO/MUNO (p = 0.003). A more thorough inside-groups analysis yielded a positive and moderate to high correlation between FM parameters and QoL scales in MHO and MHNO, while a negative and weak to moderate correlation was observed in MUO and MUNO. Conclusion: This study reported an inverse U-shaped relationship between FM and QoL in obesity phenotypes, suggesting that metabolic status is a key factor involved in modulating QoL and therefore challenging the idea of obesity as a main driver of low QoL. We recommend the inclusion of FM percentage in the definition of obesity phenotypes in future research, to better evaluate QoL of obesity phenotypes.

Risk Factors Associated With Mortality and Neurologic Disability After Intracerebral Hemorrhage in a Racially and Ethnically Diverse Cohort

Intracerebral hemorrhage (ICH) is the most severe subtype of stroke. Its mortality rate is high, and most survivors experience significant disability. To assess primary patient risk factors associated with mortality and neurologic disability 3 months after ICH in a large, racially and ethnically balanced cohort. This cohort study included participants from the Ethnic/Racial Variations of Intracerebral Hemorrhage (ERICH) study, which prospectively recruited 1000 non-Hispanic White, 1000 non-Hispanic Black, and 1000 Hispanic patients with spontaneous ICH to study the epidemiological characteristics and genomics associated with ICH. Participants included those with uniform data collection and phenotype definitions, centralized neuroimaging review, and telephone follow-up at 3 months. Analyses were completed in November 2021. Patient demographic and clinical characteristics as well as hospital event and imaging variables were examined, with characteristics meeting P < .20 considered candidates for a multivariate model. Elements included in the ICH score were specifically analyzed. Individual characteristics were screened for association with 3-month outcome of neurologic disability or mortality, as assessed by a modified Rankin Scale (mRS) score of 4 or greater vs 3 or less under a logistic regression model. A total of 25 characteristics were tested in the final model, which minimized the Akaike information criterion. Analyses were repeated removing individuals who had withdrawal of care. A total of 2568 patients (mean [SD] age, 62.4 [14.7] years; 1069 [41.6%] women and 1499 [58.4%] men) had a 3-month outcome determination available, including death. The final logistic model had a significantly higher area under the receiver operating characteristics curve (C = 0.88) compared with ICH score alone (C = 0.76; P < .001). Among characteristics associated with neurologic disability and mortality were larger log ICH volume (OR, 2.74; 95% CI, 2.36-3.19; P < .001), older age (OR per 1-year increase, 1.04; 95% CI, 1.02-1.05; P < .001), pre-ICH mRS score (OR, 1.62; 95% CI, 1.41-1.87; P < .001), lobar location (OR, 0.22; 95% CI, 0.16-0.30; P < .001), and presence of infection (OR, 1.85; 95% CI, 1.42-2.41; P < .001). The findings of this cohort study validate ICH score elements and suggest additional baseline and interim patient characteristics were associated with variation in 3-month outcome.

Concept Libraries for Repeatable and Reusable Research: Qualitative Study Exploring the Needs of Users.

BackgroundBig data research in the field of health sciences is hindered by a lack of agreement on how to identify and define different conditions and their medications. This means that researchers and health professionals often have different phenotype definitions for the same condition. This lack of agreement makes it difficult to compare different study findings and hinders the ability to conduct repeatable and reusable research.ObjectiveThis study aims to examine the requirements of various users, such as researchers, clinicians, machine learning experts, and managers, in the development of a data portal for phenotypes (a concept library).MethodsThis was a qualitative study using interviews and focus group discussion. One-to-one interviews were conducted with researchers, clinicians, machine learning experts, and senior research managers in health data science (N=6) to explore their specific needs in the development of a concept library. In addition, a focus group discussion with researchers (N=14) working with the Secured Anonymized Information Linkage databank, a national eHealth data linkage infrastructure, was held to perform a SWOT (strengths, weaknesses, opportunities, and threats) analysis for the phenotyping system and the proposed concept library. The interviews and focus group discussion were transcribed verbatim, and 2 thematic analyses were performed.ResultsMost of the participants thought that the prototype concept library would be a very helpful resource for conducting repeatable research, but they specified that many requirements are needed before its development. Although all the participants stated that they were aware of some existing concept libraries, most of them expressed negative perceptions about them. The participants mentioned several facilitators that would stimulate them to share their work and reuse the work of others, and they pointed out several barriers that could inhibit them from sharing their work and reusing the work of others. The participants suggested some developments that they would like to see to improve reproducible research output using routine data.ConclusionsThe study indicated that most interviewees valued a concept library for phenotypes. However, only half of the participants felt that they would contribute by providing definitions for the concept library, and they reported many barriers regarding sharing their work on a publicly accessible platform. Analysis of interviews and the focus group discussion revealed that different stakeholders have different requirements, facilitators, barriers, and concerns about a prototype concept library.

A multicenter evaluation of computable phenotyping approaches for SARS-CoV-2 infection and COVID-19 hospitalizations

Diagnosis codes are used to study SARS-CoV2 infections and COVID-19 hospitalizations in administrative and electronic health record (EHR) data. Using EHR data (April 2020–March 2021) at the Yale-New Haven Health System and the three hospital systems of the Mayo Clinic, computable phenotype definitions based on ICD-10 diagnosis of COVID-19 (U07.1) were evaluated against positive SARS-CoV-2 PCR or antigen tests. We included 69,423 patients at Yale and 75,748 at Mayo Clinic with either a diagnosis code or a positive SARS-CoV-2 test. The precision and recall of a COVID-19 diagnosis for a positive test were 68.8% and 83.3%, respectively, at Yale, with higher precision (95%) and lower recall (63.5%) at Mayo Clinic, varying between 59.2% in Rochester to 97.3% in Arizona. For hospitalizations with a principal COVID-19 diagnosis, 94.8% at Yale and 80.5% at Mayo Clinic had an associated positive laboratory test, with secondary diagnosis of COVID-19 identifying additional patients. These patients had a twofold higher inhospital mortality than based on principal diagnosis. Standardization of coding practices is needed before the use of diagnosis codes in clinical research and epidemiological surveillance of COVID-19.

Insights From Dimensional Phenotypic Definitions of Posttraumatic Stress Disorder and Trauma in Genome-wide Association Studies

Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure InformationBiological PsychiatryVol. 91Issue 7PreviewPosttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Full-Text PDF Open Access

EP291: Disease characterization in sodium-potassium ATPases by reverse genetics in humans

Most genetic disorders are discovered via forward genetics: a shared phenotype is recognized in a group of patients, allowing causative gene(s) to be determined. This can lead to excessively narrow definitions of disease phenotypes due to selection bias, as patients with symptoms outside the “classic” presentation are less likely to be diagnosed. We hypothesized that reverse human genetics, ie, studying variants in a gene without phenotype-based recruitment, could more accurately characterize new diseases. We established the first such approach for ATP1A1, the ubiquitously expressed housekeeping isoform of sodium-potassium ATPase. ATP1A1-associated disease is an emerging entity with several reports of heterozygous variants in individuals with differing neurological phenotypes: peripheral neuropathy, childhood epilepsy-renal hypomagnesemia, or spastic paraplegia. Gain-of-function ion leakage has been proposed as a mechanism for the more severe phenotype in the patients with epilepsy, versus loss-of-function in patients with neuropathy. However, only 14 families in total have been reported with possible ATP1A1 pathogenic variants and the true spectrum of disease remains unknown. Through genotype-based recruitment combined with detailed functional characterization of variants, we broadened the phenotypic spectrum to include incomplete penetrance and identified distinct molecular categories of ATP1A1 variants. We collected variants identified on next-generation sequencing of both clinical and research samples. We recruited patients with heterozygous ATP1A1 variants of uncertain significance found on testing for any indication. In addition, we filtered rare variants found in 7,000 “healthy” volunteers in a population genome sequencing study and prioritized 2 for study based on predicted functional impact. We re-contacted one individual from this cohort for targeted phenotyping at the NIH Clinical Center under an IRB-approved study protocol (ClinicalTrials.gov identifier NCT00369421). We developed a comprehensive panel of 3 assays measuring the ability of ATP1A1 to support survival in transfected cells and its total enzymatic activity and turnover rate per molecule in Xenopus oocytes. In the latter experimental system, we directly measured enzyme activity as steady-state electrical currents in two-electrode voltage clamp. Using sodium transient current measurements, we quantified sodium ion substrate binding by ATP1A1 as well as the number of ATP1A1 molecules reaching the cell surface. We identified 7 rare missense variants with significant impacts on enzyme function, as well as 1 nonsense variant predicted to lead to nonsense-mediated decay. Of 9 missense variants identified in clinically ascertained people, 6 had functional impact and 3 did not. Phenotypes of patients with functionally significant ATP1A1 variants included not only neurological deficits but also previously unreported features such as hypothyroidism (two patients), skin changes, and unusual facial features. Of the 2 variants selected from the population sequencing cohort, 1 was a missense variant with clear loss-of-function impact in multiple assays yet was present in an adult without neurological symptoms. This individual declined research phenotyping. The other was a nonsense variant identified in an asymptomatic adult. This individual underwent detailed phenotyping including nerve conduction/electromyography and was confirmed not to have subclinical neuropathy, magnesium wasting, or spasticity. Molecular characterization of the variants revealed three general patterns of impact on enzyme function. First, some variants decreased protein abundance at the cell membrane with a corresponding loss of enzyme function. Second, other variants resulted in ATP1A1 that reached the cell membrane but had decreased enzyme activity with or without ion leak currents. Third, some variants changed enzyme properties by reducing the voltage dependence of its activity, possibly suggesting gain-of-function at negative voltages. Genotype-based collection of variants for functional characterization was an effective strategy to study the spectrum of ultra-rare ATP1A1 disease. We identified 8 putative pathogenic variants, expanding the total known pool of such variants by more than half. Connecting functional impacts of variants to the phenotypes of the individuals carrying them revealed incomplete penetrance into adulthood in two individuals as well as possible non-neurological disease features for further study. Detailed molecular characterization allowed us to propose distinct classes of variants based on their effects on enzyme function, which could form the basis for future genotype-phenotype correlation.

Classifying atopic dermatitis: a systematic review of phenotypes and associated characteristics.

Atopic dermatitis is a heterogeneous disease, accompanied by a wide variation in disease presentation and the potential to identify many phenotypes that may be relevant for prognosis and treatment. We aimed to systematically review previously reported phenotypes of atopic dermatitis and any characteristics associated with them. Ovid EMBASE, Ovid MEDLINE and Web of Science were searched from inception till 12 February 2021 for studies attempting to classify atopic dermatitis. Primary outcomes are atopic dermatitis phenotypes and characteristics associated with them in subsequent analyses. A secondary outcome is the methodological approach used to derive them. In total, 8511 records were found. By focussing only on certain clinical phenotypes, 186 studies were eligible for inclusion. The majority of studies were hospital‐based (59%, 109/186) and cross‐sectional (76%, 141/186). The number of included patients ranged from seven to 526 808. Data‐driven approaches to identify phenotypes were only used in a minority of studies (7%, 13/186). Ninety‐one studies (49%) investigated a phenotype based on disease severity. A phenotype based on disease trajectory, morphology and eczema herpeticum was investigated in 56 (30%), 22 (12%) and 11 (6%) studies respectively. Thirty‐six studies (19%) investigated morphological characteristics in other phenotypes. Investigated associated characteristics differed between studies. In conclusion, we present an overview of phenotype definitions used in literature for severity, trajectory, morphology and eczema herpeticum, including associated characteristics. There is a lack of uniform and consistent use of atopic dermatitis phenotypes across studies.

Systematic Heritability and Heritability Enrichment Analysis for Diabetes Complications in UK Biobank and ACCORD Studies.

Diabetes-related complications reflect longstanding damage to small and large vessels throughout the body. In addition to the duration of diabetes and poor glycemic control, genetic factors are important contributors to the variability in the development of vascular complications. Early heritability studies found strong familial clustering of both macrovascular and microvascular complications. However, they were limited by small sample sizes and large phenotypic heterogeneity, leading to less accurate estimates. We take advantage of two independent studies-UK Biobank and the Action to Control Cardiovascular Risk in Diabetes trial-to survey the single nucleotide polymorphism heritability for diabetes microvascular (diabetic kidney disease and diabetic retinopathy) and macrovascular (cardiovascular events) complications. Heritability for diabetic kidney disease was estimated at 29%. The heritability estimate for microalbuminuria ranged from 24 to 60% and was 41% for macroalbuminuria. Heritability estimates of diabetic retinopathy ranged from 6 to 33%, depending on the phenotype definition. More severe diabetes retinopathy possessed higher genetic contributions. We show, for the first time, that rare variants account for much of the heritability of diabetic retinopathy. This study suggests that a large portion of the genetic risk of diabetes complications is yet to be discovered and emphasizes the need for additional genetic studies of diabetes complications.

The Applications of Single-Cell RNA Sequencing in Atherosclerotic Disease.

Atherosclerosis still is the primary cause of death worldwide. Our characterization of the atherosclerotic lesion is mainly rooted in definitions based on pathological descriptions. We often speak in absolutes regarding plaque phenotypes: vulnerable vs. stable plaques or plaque rupture vs. plaque erosion. By focusing on these concepts, we may have oversimplified the atherosclerotic disease and its mechanisms. The widely used definitions of pathology-based plaque phenotypes can be fine-tuned with observations made with various -omics techniques. Recent advancements in single-cell transcriptomics provide the opportunity to characterize the cellular composition of the atherosclerotic plaque. This additional layer of information facilitates the in-depth characterization of the atherosclerotic plaque. In this review, we discuss the impact that single-cell transcriptomics may exert on our current understanding of atherosclerosis.

Leveraging deep phenotyping from health check-up cohort with 10,000 Korean individuals for phenome-wide association study of 136 traits

The expanding use of the phenome-wide association study (PheWAS) faces challenges in the context of using International Classification of Diseases billing codes for phenotype definition, imbalanced study population ethnicity, and constrained application of the results in research. We performed a PheWAS utilizing 136 deep phenotypes corroborated by comprehensive health check-ups in a Korean population, along with trans-ethnic comparisons through using the UK Biobank and Biobank Japan Project. Meta-analysis with Korean and Japanese population was done. The PheWAS associated 65 phenotypes with 14,101 significant variants (P < 4.92 × 10–10). Network analysis, visualization of cross-phenotype mapping, and causal inference mapping with Mendelian randomization were conducted. Among phenotype pairs from the genotype-driven cross-phenotype associations, we evaluated penetrance in correlation analysis using a clinical database. We focused on the application of PheWAS in order to make it robust and to aid the derivation of biological meaning post-PheWAS. This comprehensive analysis of PheWAS results based on a health check-up database will provide researchers and clinicians with a panoramic overview of the networks among multiple phenotypes and genetic variants, laying groundwork for the practical application of precision medicine.

Relationship Between Dental Caries and Erosive Tooth Wear in Adolescents

BackgroundOur aim was to investigate the relationship between caries experience and erosive tooth wear of adolescents.MethodsWe compared the Decayed, Missing, and Filled Teeth (dmft/DMFT) data of 795 adolescents to their erosive tooth wear scores using diet as a covariate and determined if dental caries and erosive tooth wear scores are associated using linear regression analysis. Diet data and oral hygiene habits were collected using self-reported surveys and erosive tooth wear scores were previously collected. We also compared patients' genotypes and phenotypes and looked for an association between erosive tooth wear experience and different single nucleotide polymorphisms (SNPs). A Bonferroni correction was implemented to correct multiple comparisons. Two-group comparisons were made depending on the phenotype definitions implemented, and both chi-square and linear regression analyses were used to test association between genetic variants and caries definitions. All covariates were included in each model.ResultsFor four SNPs (rs17159702, rs10246939, rs1800972, and rs1676303), there was an association between a spike in caries experience of DMFT 4 or more between two time points and increased frequency of fruit juice intake. A fifth SNP rs2860216 was shown to be a protective factor toward a spike in caries when coupled with more frequently eating yogurt. We did not find significant associations between our dental caries phenotypes or our demographic data and erosive tooth wear status in our linear regression.ConclusionsDental caries and erosive tooth wear are two diseases that differ in mechanism and heritability.

VARYING PATTERNS OF PROGRESSION ARE OBSERVED IN KELLGREN‐LAWRENCE 2 AND 3 KNEES FULFILLING DIFFERENT DEFINITIONS OF A CARTILAGE‐MENISCUS PHENOTYPE IN THE FOUNDATION FOR NATIONAL INSTITUTES OF HEALTH OSTEOARTHRITIS BIOMARKERS CONSORTIUM STUDY (FNIH)

Imaging plays an important role in defining structural disease severity and potential suitability of patients recruited to disease-modifying osteoarthritis drug (DMOAD) trials. Three main structural phenotypes in knee OA have been proposed based on MRI, i.e., inflammation, cartilage-meniscus and subchondral bone. The cartilage-meniscus phenotype has received particular attention as such knees are likely to benefit most from pharmacological intervention. However, cartilage damage that is too severe may be of negative impact. To describe frequencies for different thresholds regarding an MRI-defined cartilage-meniscus phenotype and to report phenotypic progression in Kellgren-Lawrence (KL) 2 and 3 knees over 48 months. The study sample was selected as a nested case-control study with knees showing either 1) radiographic and pain progression (“composite” case), 2) radiographic progression only, 3) pain progression only, and 4) no progression. MRI was performed on 3T systems. MRIs were read according to the MOAKS scoring system. Three different phenotypes were defined according to the maximum severity of medial cartilage damage: ‘D1’: ≤ 2.2, ‘D2’ ≤ 2.1 and ‘D3’ ≤ 2.0. The odds of being a composite case for those with vs. without each phenotype definition was determined using logistic regression. 485 knees were included. For KL2 knees 191(64%) knees fulfilled D1 criteria, 183 (62%) D2 and 167 (56%) D3. For KL3 these numbers were 164 (87%), 103 (55%) and 77 (41%). Odds for being a composite case were 2.52 (95% CI 1.40,4.54) for D1, 1.93 (95% CI 1.11,3.35) for D2 and 1.92 (95% CI 1.13,3.28) for KL2 knees. For KL3 knees odds were 0.32 (95% CI 0.13,0.78) for D1, 0.56 (95% CI 0.31,1.01) for D2 and 0.49 (95% CI 0.26,0.91) for D3. Details for the medial compartment are presented in Table 1 . Increased odds for progression are seen for KL2 knees and all definitions, while a seemingly protective effect is seen for KL3 knees. The latter is explained by the fact that KL3 knees stratified as suggested will have comparably mild cartilage damage at screening. Scientific and financial support for the Foundation for the National Institutes of Health (FNIH) Osteoarthritis (OA) Biomarkers Consortium and for this study has been made possible through grants as well as direct and indirect in-kind contributions from AbbVie, Amgen Inc., the Arthritis Foundation, Bioiberica SA, DePuy Mitek, Inc., Flexion Therapeutics, Inc., GlaxoSmithKline, Merck Serono, Rottapharm | Madaus, Sanofi, Stryker, and the Pivotal Osteoarthritis Initiative Magnetic Resonance Imaging Analyses (POMA) Study (NIH/National Heart, Lung, and Blood Institute grant HHSN- 2682010000). The Osteoarthritis Initiative (OAI) is a public–private partnership between the NIH (contracts N01-AR-2-2258, N01-AR-2- 2259, N01-AR-2-2260, N01-AR-2-2261, and N01-AR-2-2262) and private funding partners (Merck Research Laboratories, Novartis Pharmaceuticals, GlaxoSmithKline, and Pfizer, Inc.) and is conducted by the OAI Study Investigators. Private sector funding for the Biomarkers Consortium and the OAI is managed by the FNIH. AG has received consultancies, speaking fees, and/or honoraria from Pfizer, Novartis, AstraZeneca, Merck Serono, and TissuGene and is President and shareholder of Boston Imaging Core Lab (BICL), LLC a company providing image assessment services. FWR is Chief Medical Officer and shareholder of BICL, LLC. and has received consultancies, speaking fees, and/or honoraria from Calibr –California Institute of Biomedical Research and Grünenthal, GmbH. DJH is funded by an NHMRC Practitioner Fellowship and received a grant from the FNIH OA Biomarkers Consortium. He reports consulting fees from Merck Serono, TLCBio, Pfizer and Lilly CORRESPONDENCE ADDRESS: frank.roemer@uk-erlangen.de .

Pediatric high-grade gliomas and the WHO CNS Tumor Classification-Perspectives of pediatric neuro-oncologists and neuropathologists in light of recent updates.

BackgroundThe WHO Classification of Tumors of the Central Nervous System has undergone major restructuring. Molecularly defined diagnostic criteria were introduced in 2016 (revised 4th edition) and expanded in 2021 (5th edition) to incorporate further essential diagnostic molecular parameters. We investigated potential differences between specialists in perception of these molecularly defined subtypes for pediatric high-grade gliomas (pedHGG).MethodsWe designed a 22-question survey studying the impact of the revised 4th edition of the WHO classification on pedHGG. Data were collected and statistically analyzed to examine the spectrum of viewpoints and possible differences between neuro-oncologists and neuropathologists.Results465 participants from 53 countries were included; 187 pediatric neuro-oncologists (40%), 160 neuropathologists (34%), and 118 additional experts (26%). Neuro-oncologists reported issues with the introduction of molecularly defined tumor types, as well as the abolishment or renaming of established tumor entities, while neuropathologists did not to the same extent. Both groups indicated less relevant or insufficient diagnostic definitions were available in 2016. Reported issues were classified and assessed in the 2021 WHO classification and a substantial improvement was perceived. However, issues of high clinical relevance remain to be addressed, including the definition of clinical phenotypes for diffuse intrinsic pontine glioma and gliomatosis cerebri.ConclusionsWithin the WHO classification of pediatric brain tumors, such as pedHGG, rapid changes in molecular characterization have been introduced. This study highlights the ongoing need for cross talk between pathologist and oncologist to advance the classification of pedHGG subtypes and ensure biological relevance and clinical impact.

Sex Differences in Frailty Incidence in Greek Community-Dwelling Older People: The HELIAD Study.

Previous frailty studies found higher prevalence of frailty in female than in male participants. This was mainly attributed to the fact that compared to men, women show increased longevity. Recent studies have reported that the observed difference between sexes applies irrespectively of the age of older people. To provide data on sex differences in incident frailty by applying both phenotypic and multi-domain frailty measures in the same population of Greek community-dwelling older people. Longitudinal study. Data were drawn from the Hellenic longitudinal Investigation of Aging and Diet (HELIAD), a population-based, multidisciplinary study designed to estimate the prevalence and incidence of dementia in the Greek population. 1104 participants aged 65 year and above were included in this longitudinal study. This incidence cohort was re-evaluated after a mean follow-up period of 3.04±0.90 years. Frailty was operationalized using 5 different definitions in the same population: the Fried Frailty Phenotype (FFP) definition, the FRAIL Scale, the Frailty Index (FI), the Tilburg Frailty Indicator (TFI) and the Groningen Frailty Index (GFI). Frailty incidence was calculated a) for the whole sample, b) separately for men and women and c) after both age and sex stratification. Age and sex stratification revealed that irrespective of age and frailty measurement, women showed higher incidence rates of frailty than men. Specifically, frailty seems to be a condition concerning women >65 years old, but when it comes to men, it is more frequent in those aged more than 75 years old. Finally, in relation to overall frailty incidence and comparing our results to previous studies, we detected a lower frailty incidence in the Greek population. Differences between the two sexes indicate that when exploring the factors that are related to frailty, studies should provide data disaggregated for men and women.

A Cross-Sectional Study on the Association between Body Mass Index and Frailty According to Sex in Elderly Patients with Disabilities from an Elderly Day-Care Center.

The association between body mass index (BMI) and frailty in elderly patients with disabilities is unclear. We aimed to investigate the association between BMI and frailty in the elderly with disabilities according to sex. This cross-sectional study included 280 elderly patients with disabilities from an elderly daycare center. BMI classification for the Asian population was used to categorize the patients into four groups: underweight, normal, overweight, and obese. Frailty score was based on the phenotypic definition of frailty and consisted of five criteria derived from the revised Japanese version of the Cardiovascular Health Study. Those who had three or more criteria were considered frail. Logistic regression models were constructed to investigate the associations between frailty and BMI in each group (males and females). In females, being underweight was significantly associated with frailty after adjusting for confounders (age and Mini-Mental State Examination score); after adding medical history as a confounder, the aforementioned association was not significant. In males, BMI was not significantly associated with frailty. The association between BMI and frailty differed according to sex among the elderly with disabilities. This finding provides important information regarding frailty risk to workers in daycare facilities.

Outcomes and Incidence of PF-ILD According to Different Definitions in a Real-World Setting.

Background: Almost one-third of fibrosing ILD (fILDs) have a clinical disease behavior similar to IPF, demonstrating a progressive phenotype (PF-ILD). However, there are no globally accepted criteria on the definition of a progressive phenotype in non-IPF fILD yet. Four different definitions have been used; however, no internationally accepted definition currently exists. Research Question: To compare the clinical and functional characteristics of progressive fILD according to the currently available definitions. Study design and methods: Cases of fILD were identified retrospectively from the database of the tertiary referral center for ILD in Heidelberg. Lung function, clinical signs of progression, and radiological changes were evaluated. Patients with fILD were considered to have progression according to each of the four available definitions: Cottin (CO), RELIEF (RE), INBUILD (IN), and UILD study. Lung function changes, expressed as mean absolute decline of FVC%, were reported every 3 months following diagnosis and analyzed in the context of each definition. Survival was also analyzed. Results: A total of 566 patients with non-IPF fILD were included in the analysis. Applying CO-, RE-, IN-, and UILD-definitions, 232 (41%), 183 (32%), 274 (48%), and 174 (31%) patients were defined as PF-ILD, respectively. RE- and UILD-criteria were the most stringent, with only 32 and 31% patients defined as progressive, while IN- was the most broad, with almost 50% of patients defined as progressive. CO- definition was in-between, classifying 41% as progressive. PF ILD patients with a UILD definition had worse prognosis. Interpretation: Depending on the definition used, the existing criteria identify different groups of patients with progressive fILD, and this may have important prognostic and therapeutic implications.