Communications medicine最新文献

{"title":"Robustly measuring multimorbidity using disparate linked datasets.","authors":"Regina Prigge, Kelly J Fleetwood, Caroline A Jackson, Stewart W Mercer, Paul At Kelly, Cathie Sudlow, John D Norrie, Daniel R Morales, Daniel J Smith, Bruce Guthrie","doi":"10.1038/s43856-025-00995-4","DOIUrl":"10.1038/s43856-025-00995-4","url":null,"abstract":"<p><strong>Background: </strong>Measurement of multimorbidity, the co-occurrence of two or more conditions in the same individual, is highly variable which limits the consistency and reproducibility of research.</p><p><strong>Methods: </strong>Using data from 172,563 UK Biobank (UKB) participants and a cross-sectional approach, we examined how choice of data source affected estimated prevalence of 80 individual long-term conditions (LTCs) and multimorbidity. We developed code-list-based algorithms to determine the prevalence of 80 LTCs in (1) primary care records, (2) UKB baseline assessment, (3) hospital/cancer registry records, and (4) all three data sources together.</p><p><strong>Results: </strong>Using records from all three data sources, 146,811 (85.1%) participants have at least one and 109,609 (63.5%) have at least two LTCs at baseline. A median of 4.7% (IQR 1.0-16.6) of participants with a condition are identified by all three data sources. Agreement is highest for endocrine, nutritional and metabolic disorders, with a median of 32.9% (IQR 20.5-34.1) of individuals with a condition identified by all three data sources. Agreement is lowest for diseases of the genitourinary system and mental and behavioural disorders where perfect agreement varies from zero to 4.9% and zero to 12.3% across conditions, respectively. The low agreement between data sources is accompanied by high proportions of individuals with a condition identified only in primary care data (i.e. not in either of the other two sources), with a median of 59.3% (IQR 47.4-75.9) for diseases of the genitourinary system and 66.9% (IQR 42.8-79.2) for mental and behavioural disorders.</p><p><strong>Conclusions: </strong>Our study highlights the impact of the choice of which data source is used in research on individual LTCs and multimorbidity, and the importance of clearly justifying choices made.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"283"},"PeriodicalIF":5.4,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12238475/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144593075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated multi-omics of feces, plasma and urine can describe and differentiate pediatric active Crohn's Disease from remission.","authors":"Nienke Koopman, Yorrick Jaspers, Pim T van Leeuwen, Konstantinos Chronas, Andrew Y F Li Yim, Kay Diederen, Anje A Te Velde, Winfried Roseboom, Angelika Kindermann, Marc A Benninga, Gertjan Kramer, Wouter J de Jonge, Stanley Brul, Evgeni Levin, Stephan Kemp, Jurgen Seppen","doi":"10.1038/s43856-025-00984-7","DOIUrl":"10.1038/s43856-025-00984-7","url":null,"abstract":"<p><strong>Background: </strong>This study aimed to obtain a holistic view of remission in pediatric Crohn's Disease (CD) by integrating six omics datasets from three anatomical compartments.</p><p><strong>Methods: </strong>Patients with fecal calprotectin below 250 mg/kg were considered in remission (n = 27), above 250 mg/kg as having active disease (n = 31). Proteome and microbiomes (fungi and bacteria) were analyzed in feces. Metabolomes in feces, urine, and plasma. Datasets were integrated into a multi-omics model.</p><p><strong>Results: </strong>The use of individual datasets shows multiple differences between remission and active disease. Integration yielded a good model (AUC of 0.8) predicting remission. The most important features in this model are fecal bacteria (40%), fecal metabolites (22%), fecal proteins (16%), plasma metabolites (12%), fecal fungi (6%), and urine metabolites (4%). The interactome reveals Ruminococcaceae and Faecalibacterium as key players, with a correlation between antifungal urine hydroxyphenyllactic acid and fecal fungi. Pathway analysis shows an association of purine metabolism with remission, independent of thiopurine use. Changes in purine metabolism are confirmed in a pediatric CD public dataset.</p><p><strong>Conclusion: </strong>The pathways and correlations identified as playing a role in remission may remain undetectable if individual omics datasets or single anatomical compartments are used, highlighting the need for a holistic approach that integrates multiple datasets from multiple anatomical compartments.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"281"},"PeriodicalIF":5.4,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12238252/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144593073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cancer Research Funding in Africa.","authors":"Oluwasegun Afolaranmi, Elise M Garton, Olaoluwa Ezekiel Dada, Sehar Salim Virani, Abdul R Shour, Adedayo A Onitilo, Syed Nabeel Zafar","doi":"10.1038/s43856-025-00992-7","DOIUrl":"10.1038/s43856-025-00992-7","url":null,"abstract":"<p><strong>Background: </strong>Africa is projected to witness the steepest rise in cancer incidence and mortality in the coming decades. Therefore, it is critical to understand the current landscape of cancer research funding to identify key gaps and inform decision-making.</p><p><strong>Methods: </strong>We conducted a retrospective study of funded cancer research projects involving at least one African country over the 20 years between January 2004 and December 2023. Data was collected from four publicly available databases, namely the International Cancer Research Partnership (ICRP), National Institutes of Health World Research Portfolio Online Reporting Tools (WoRLD RePORT), ClinicalTrials.gov (CTG), and International Clinical Trials Registry Platform (ICTRP). We retrieved data on country, year of funding, cancer types, study types, and funding sources. Furthermore, we used incidence, mortality, and prevalence data to compare the level of funded projects to the burden of disease.</p><p><strong>Results: </strong>A total of 3047 unique funded projects/grants were reported from all 4 databases, with a consistent rise in the number of funded projects throughout the study period. Egypt and South Africa had the most funded cancer research projects, and 9 (16%) countries had no reported studies. Breast, lung, and cervical cancers received the highest funding allocation. We found that several cancers, notably cervical, prostate, and liver, are relatively underfunded compared to their disease burden. 70% of projects reported in ICRP/WoRLD RePORT were funded by the U.S. NIH. Notably, 40% of studies in CTG/ICTRP reported local funding, with Egypt accounting for 94% of these locally financed studies.</p><p><strong>Conclusions: </strong>This study provides a comprehensive overview of the current state of cancer research funding in Africa, highlighting notable gaps and critical insights to guide data-driven decision-making.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"278"},"PeriodicalIF":5.4,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12234859/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144585759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A whole blood assay for antibody dependent phagocytosis of Plasmodium falciparum infected erythrocytes.","authors":"Dilini Rathnayake, Wina Hasang, Alexander Macpherson, HongHua Ding, Laurens Manning, Moses Laman, Maria Ome-Kaius, Holger W Unger, Feiko Ter Kuile, Mwayi Madanitsa, Bruce Wines, P Mark Hogarth, Elizabeth H Aitken, Stephen J Rogerson","doi":"10.1038/s43856-025-00989-2","DOIUrl":"10.1038/s43856-025-00989-2","url":null,"abstract":"<p><strong>Background: </strong>Antibodies are used to protect against Plasmodium falciparum malaria. One antibody target, the variant surface antigens, is expressed on infected erythrocytes (IEs). Antibodies to these antigens can either block IE sequestration in the tissues, facilitate natural killer cell-mediated killing, or opsonise IEs for phagocytic clearance by neutrophils and monocytes.</p><p><strong>Methods: </strong>We developed a high-throughput assay to measure antibody-dependent neutrophil phagocytosis (ADNP) and antibody-dependent cellular phagocytosis (ADCP, by blood monocytes) in the same sample of fresh whole blood.</p><p><strong>Results: </strong>Here we show that immune plasma mediates ADNP and ADCP in a concentration-dependent manner. Uptake is greater in the presence of complement proteins and is largely dependent on the expression of P. falciparum Erythrocyte Membrane Protein 1 located on the IE surface. Plasma from pregnant Papua New Guinean women with and without placental malaria shows that ADNP and ADCP are associated with protection from placental malaria. ADNP, but not ADCP, using IEs expressing IT4VAR19 (a PfEMP1 variant that binds to endothelial protein C receptor through a DC8 domain cassette) is higher at hospital presentation in children with uncomplicated malaria than in severe malaria. In pregnant women, ADNP and ADCP in whole blood are strongly correlated with one another (Spearman's rho = 0.90), but not with ADNP or ADCP using purified neutrophils and monocytes in the absence of complement proteins.</p><p><strong>Conclusions: </strong>The whole blood assay is a powerful new tool to assess functional antibodies that may protect against P. falciparum malaria. It allows simultaneous measurement of phagocytosis of opsonised IEs by monocytes and neutrophils.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"277"},"PeriodicalIF":5.4,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12234751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144585758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The association between the gut microbiome and 24-h blood pressure measurements in the SCAPIS study.","authors":"Yi-Ting Lin, Sergi Sayols-Baixeras, Gabriel Baldanzi, Koen F Dekkers, Ulf Hammar, Diem Nguyen, Nynne Nielsen, Aron C Eklund, Georgios Varotsis, Jacob B Holm, H Bjørn Nielsen, Lars Lind, Göran Bergström, J Gustav Smith, Gunnar Engström, Johan Ärnlöv, Johan Sundström, Marju Orho-Melander, Tove Fall","doi":"10.1038/s43856-025-00980-x","DOIUrl":"10.1038/s43856-025-00980-x","url":null,"abstract":"<p><strong>Background: </strong>There is mounting evidence supporting the role of the microbiota in hypertension from experimental studies and population-based studies. We aimed to investigate the relationship between specific characteristics of the gut microbiome and 24-h ambulatory blood pressure measurements.</p><p><strong>Methods: </strong>The association of gut microbial species and microbial functions, determined by shotgun metagenomic sequencing of fecal samples, with 24-h ambulatory blood pressure measurements in 3695 participants and office blood pressure was assessed in multivariable-adjusted models in 2770 participants without antihypertensive medication from the Swedish CArdioPulmonary bioImage Study.</p><p><strong>Results: </strong>Gut microbiome alpha diversity was negatively associated with diastolic blood pressure variability. Additionally, four microbial species were associated with at least one of the 24-h blood pressure traits. Streptococcus sp001556435 was associated with higher systolic blood pressure, Intestinimonas massiliensis and Dysosmobacter sp001916835 with lower systolic blood pressure, Dysosmobacter sp001916835 with lower diastolic blood pressure, and ER4 sp900317525 with lower systolic blood pressure variability. Moreover, office blood pressure data from a subsample without ambulatory blood pressure measurements replicated the association of Intestinimonas massiliensis with systolic blood pressure and Dysosmobacter sp001916835 with diastolic blood pressure. Species associated with 24-h blood pressure were linked to a similar pattern of metabolites.</p><p><strong>Conclusions: </strong>In this large cross-sectional analysis, gut microbiome alpha diversity negatively associates with diastolic blood pressure variability, and four gut microbial species associate with 24-h blood pressure traits.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"276"},"PeriodicalIF":5.4,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12234806/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144585760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Selective identification of polyploid hepatocellular carcinomas with poor prognosis by artificial intelligence-based pathological image recognition.","authors":"Takanori Matsuura, Masatoshi Abe, Yoshiyuki Harada, Masahiro Kido, Hajime Nagahara, Yuzo Kodama, Yoshihide Ueda, Eiji Hara, Hirohiko Niioka, Tomonori Matsumoto","doi":"10.1038/s43856-025-00967-8","DOIUrl":"10.1038/s43856-025-00967-8","url":null,"abstract":"<p><strong>Background: </strong>Polyploidy is frequently observed in cancer cells and is closely associated with chromosomal instability, which can lead to cancer progression. Polyploid cancers are more aggressive than diploid cancers, and polyploidy has been shown to be a prognostic marker for hepatocellular carcinoma (HCC). However, polyploidy is challenging to diagnose. Currently, no clinically implementable methods are available for diagnosing polyploidy in cancer.</p><p><strong>Methods: </strong>We established a method for assessing polyploidization in HCC using deep-learning-based artificial intelligence image recognition models to assess hematoxylin and eosin-stained pathological images. Using 44 HCCs whose ploidy status had been determined by chromosome fluorescence in situ hybridization, we evaluated the ability of our constructed deep learning models to detect HCC ploidy. We then tested the models on an independent group of 169 liver cancers and applied them to a publicly available dataset.</p><p><strong>Results: </strong>Here we show that our constructed models effectively assess HCC ploidy in a separate cohort and identify a subset with poor prognosis based on the ploidy determinations for 169 HCCs. Our pipeline also identifies HCCs with poor prognosis in the external dataset, with a more significant difference than that for ploidy inferences by genomic analysis. By exploiting the high processing capacity of artificial intelligence, new aspects of polyploid HCC, such as the high prevalence of scirrhous structures, are identified.</p><p><strong>Conclusions: </strong>Our findings suggest that ploidy assessment using artificial intelligence-based pathological image recognition can serve as a novel diagnostic tool for personalized medicine.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"270"},"PeriodicalIF":5.4,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12229707/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144562143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epidemiology and future trend predictions of ischemic stroke based on the global burden of disease study 1990-2021.","authors":"Jiayu Liu, Aoxi Xu, Zhifeng Zhao, Bin Ren, Zhao Gao, Dandong Fang, Bo Hei, Junzhao Sun, Xiangyang Bao, Lin Ma, Xiaoque Zheng, Yuxin Wang, Hecheng Ren, Guan Wang, Li Zhu, Jianning Zhang","doi":"10.1038/s43856-025-00939-y","DOIUrl":"10.1038/s43856-025-00939-y","url":null,"abstract":"<p><strong>Background: </strong>Visualizing the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 and predicting future disease burdens at global, regional, and national levels can help health policymakers develop evidence-based ischemic stroke (IS) prevention and cure strategies.</p><p><strong>Methods: </strong>We stratify epidemiological parameters by sex, age, the World Bank's classification of economies, and sociodemographic index (SDI) levels. We use frontier analysis to assess whether the burden of ischemic stroke (IS) in each country aligns with its level of economic development. We apply the Autoregressive Integrated Moving Average (ARIMA) model and the Bayesian age-period-cohort (BAPC) model to predict the burden of IS over the next 15 years.</p><p><strong>Results: </strong>Here we show that IS accounts for 69.9 million prevalent cases, 7.8 million incident cases, 3.6 million deaths, and 70.4 million DALYs in 2021. In men, the global DALY rate of IS increases up to age 90-94 years and then decreases; however, for women, the rate increases up to the oldest age group (≥95 years). Regionally, we find that the association between the SDI and the age-standardized DALY rate of IS starts relatively flat, with a small peak up to a sociodemographic index of about 0.7, and then declines rapidly. Factors contributing most to the DALY rates for IS are high systolic blood pressure, high LDL cholesterol, and air pollution.</p><p><strong>Conclusions: </strong>The disease burden of IS in medium-high SDI countries is still high, which means we could not meet the Sustainable Development Goal targets by 2030. Countries should formulate prevention and control measures suitable for their national conditions based on risk factors.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"273"},"PeriodicalIF":5.4,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12229500/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144562142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clustering analysis of multi-site electronic health records reveals distinct subphenotypes in stage-1 acute kidney injury.","authors":"Deyi Li, Ho Yin Chan, Alan S L Yu, John A Kellum, Dana Y Fuhrman, Elizabeth A Chrischilles, Lindsay G Cowell, Sravani Chandaka, Jacob Kean, Kathleen M McTigue, Abu Saleh Mohammad Mosa, Bradley Taylor, Lemuel R Waitman, Mahanaz Syed, Yong Hu, Mei Liu","doi":"10.1038/s43856-025-00993-6","DOIUrl":"10.1038/s43856-025-00993-6","url":null,"abstract":"<p><strong>Background: </strong>Acute Kidney Injury (AKI) can adversely affect multiple organ systems, including the heart, brain, and immune system. Stage 1 AKI (AKI-1), although mild in clinical presentation, constitutes a substantial subset of AKI patients with heterogeneous outcomes, warranting further investigation into its subphenotypes.</p><p><strong>Methods: </strong>We performed clustering analysis on seven-day serum creatinine (SCr) trajectories preceding AKI-1 onset in 53,565 AKI-1 patients (aged 18-89 years; 55.57% male) across eight academic hospitals. Each AKI-1 patient was matched to a non-AKI counterpart to evaluate how different AKI-1 subphenotypes influence clinical indicators and outcomes.</p><p><strong>Results: </strong>Three distinct AKI-1 subphenotypes are identified. Patients in Subphenotype C (n = 5,378; 10.0%) exhibit a higher proportion of abnormal values across clinical indicators compared to those in Subphenotypes A (n = 27,049; 50.5%) and B (n = 21,138; 39.5%). Subphenotype C is associated with significantly higher odds ratios (ORs) for in-hospital, 30-day, and one-year all-cause mortality relative to Subphenotypes A and B. Conversely, Subphenotype B exhibits a higher susceptibility to developing chronic kidney disease (CKD) within one year after discharge following AKI-1, compared to both Subphenotypes A and C, after adjustment for baseline SCr levels. All AKI-1 subphenotypes are associated with significantly elevated risks of all-cause mortality and the need for dialysis or renal replacement therapy (RRT) compared to their respective non-AKI counterparts.</p><p><strong>Conclusions: </strong>This study reveals substantial heterogeneity in clinical indicators and outcomes within AKI-1. Future research focusing on these subphenotypes may pave the way for more personalized and targeted interventions for patients with AKI-1.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"274"},"PeriodicalIF":5.4,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12229304/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144562140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-modal analyses of proteomic measurements associated with type 2 diabetes from the Project Baseline Health Study.","authors":"Alessandra Breschi, Yuliang Wang, Sarah Short, Wilman Luk, David Erani, Pouya Kheradpour, Peter Cimermancic, Gary J Tong, Jean Philippe Martin, Manway Liu, Lulu Cao, Daniel Liu, Ranee Chatterjee, Lydia Coulter Kwee, Thomas M Snyder, Andrew Han, Katherine Drake, Charles C Kim","doi":"10.1038/s43856-025-00964-x","DOIUrl":"10.1038/s43856-025-00964-x","url":null,"abstract":"<p><strong>Background: </strong>Understanding diabetes at the molecular level can help refine diagnostic approaches and personalized treatment efforts.</p><p><strong>Methods: </strong>We generated proteomic data from plasma collected from participants enrolled in the longitudinal observational cohort study Project Baseline Health Study (PBHS) (evaluated cohort, n = 738, 27.9% of the total PBHS cohort), and integrated those data with information from their medical history and laboratory tests to determine diabetes status. We then identified biomarker proteins associated with diabetes status.</p><p><strong>Results: </strong>Here we identify 87 differentially expressed proteins in people with diabetes compared to those without diabetes, 71 of which show higher expression. This proteomic profile, integrated with clinical data into a logistic regression model, can discriminate diabetes status with over 85% balanced accuracy.</p><p><strong>Conclusions: </strong>Our approach indicates that proteomic data can enhance diabetes phenotyping, showing potential for marker-based stratification of diabetes diagnosis. These results suggest that a holistic molecular-clinical approach to diagnosis might help personalize treatments or interventions for people with diabetes.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"272"},"PeriodicalIF":5.4,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12222898/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144556043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quality of life and mental health in children with long COVID.","authors":"Lieke C E Noij, Coen R Lap, Michiel A J Luijten, Simone Hashimoto, Lorynn Teela, Kim J Oostrom, Mattijs W Alsem, Marlies A van Houten, Giske Biesbroek, Lotte Haverman, Anke H Maitland-van der Zee, Johannes B van Goudoever, Suzanne W J Terheggen-Lagro","doi":"10.1038/s43856-025-00947-y","DOIUrl":"10.1038/s43856-025-00947-y","url":null,"abstract":"<p><strong>Background: </strong>Pediatric Long COVID (PLC) is a heterogeneous condition, which can have a substantial impact on daily life of children and adolescents. This study aimed to evaluate health related quality of life (HRQoL), and mental and social health of children with PLC, in relation to children with other chronic health conditions (CHC) and from the general population (GP) during the pandemic.</p><p><strong>Methods: </strong>Dutch children (8-18 years) with PLC (n = 106, 31% male) were included between May 2021 and March 2023. Reference data was available from a CHC-cohort (n = 90, 56% male) and GP-cohort (n = 844, 47% male) during the first wave of the pandemic (April-May, 2020). Participants completed the Pediatric Quality of Life Inventory (PedsQL) 4.0 and Patient-Reported Outcomes Measurement Information System (PROMIS) instruments (Anxiety, Anger, Depressive symptoms, Sleep-Related Impairment (SRI), and Peer Relationships). Mean scores were analyzed using adjusted ANCOVA. Relative risks (RR (95% CI)) were calculated for impaired HRQoL and severe PROMIS scores.</p><p><strong>Results: </strong>Children with PLC report high proportions of impaired HRQoL (84%, RR = 3.67 (2.35-5.74)), and have significantly lower PedsQL scores than children with CHC. Children with PLC also exhibit worse PROMIS T-scores of Anxiety, Depressive Symptoms, and SRI than children from the CHC- and GP-cohorts (mean difference range 2.2-9.8 (95%CI 0.6-11.7)), and significantly higher risks of severe anxiety (17%), depressive symptoms (18%), and SRI (17%).</p><p><strong>Conclusions: </strong>PLC can severely impact HRQoL and mental and social health in children. Screening of these outcomes and individualized management of children with PLC should be a vital part of clinical care for these highly burdened patients.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"271"},"PeriodicalIF":5.4,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12222676/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144556057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}