Pub Date : 2026-03-23DOI: 10.1038/s41591-026-04312-x
Tomer Segev, Daniel Barak, Liron Zahavi, Anastasia Godneva, Michal Rein, David Krongauz, Dorit Samocha-Bonet, Hagai Rossman, Adina Weinberger, Eran Segal
Diet is a major environmental factor influencing the human gut microbiome. However, the effects of specific foods and dietary patterns on microbial composition, diversity and function is not fully understood, limiting progress toward personalized dietary strategies. Here, leveraging 10,068 participants from the Human Phenotype Project with app-based diet logs and shotgun metagenomics, we predicted diet–microbiome associations at species-level resolution. Diet significantly predicted microbial diversity (richness r = 0.26, Shannon Index r = 0.24), the relative abundance of 669 of 724 species tested (92.4%, false discovery rate <0.05), and 313 of 320 pathways (97.8%, false discovery rate <0.05). Feature attribution identified distinct food–microbe links, including coffee with Lawsonibacter asaccharolyticus (r = 0.43), yogurt with Streptococcus thermophilus (r = 0.42) and milk with Bifidobacterium species (r = 0.31–0.36). In parallel, broader dietary patterns, especially the degree of food processing, emerged as predictors of microbial diversity and composition. We also show that diet–microbiome associations persist over four years, with 82.5% of species exhibiting significant longitudinal tracking between predicted and observed abundances. Finally, we developed an exploratory analysis for simulating personalized dietary interventions with predicted microbiome shift effects that are associated with improvements in cardiometabolic health. Our findings demonstrate that diet is strongly associated with microbiome composition, diversity and function, and highlight its potential for guiding personalized interventions.
{"title":"Diet–microbiome associations in 10,068 individuals from the Human Phenotype Project to guide personalized nutrition","authors":"Tomer Segev, Daniel Barak, Liron Zahavi, Anastasia Godneva, Michal Rein, David Krongauz, Dorit Samocha-Bonet, Hagai Rossman, Adina Weinberger, Eran Segal","doi":"10.1038/s41591-026-04312-x","DOIUrl":"https://doi.org/10.1038/s41591-026-04312-x","url":null,"abstract":"Diet is a major environmental factor influencing the human gut microbiome. However, the effects of specific foods and dietary patterns on microbial composition, diversity and function is not fully understood, limiting progress toward personalized dietary strategies. Here, leveraging 10,068 participants from the Human Phenotype Project with app-based diet logs and shotgun metagenomics, we predicted diet–microbiome associations at species-level resolution. Diet significantly predicted microbial diversity (richness r = 0.26, Shannon Index r = 0.24), the relative abundance of 669 of 724 species tested (92.4%, false discovery rate <0.05), and 313 of 320 pathways (97.8%, false discovery rate <0.05). Feature attribution identified distinct food–microbe links, including coffee with Lawsonibacter asaccharolyticus (r = 0.43), yogurt with Streptococcus thermophilus (r = 0.42) and milk with Bifidobacterium species (r = 0.31–0.36). In parallel, broader dietary patterns, especially the degree of food processing, emerged as predictors of microbial diversity and composition. We also show that diet–microbiome associations persist over four years, with 82.5% of species exhibiting significant longitudinal tracking between predicted and observed abundances. Finally, we developed an exploratory analysis for simulating personalized dietary interventions with predicted microbiome shift effects that are associated with improvements in cardiometabolic health. Our findings demonstrate that diet is strongly associated with microbiome composition, diversity and function, and highlight its potential for guiding personalized interventions.","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"62 1","pages":""},"PeriodicalIF":82.9,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147496781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-23DOI: 10.1038/s41591-026-04309-6
Daniel E Coral,Jennifer L Sargent,Julia Carrasco-Zanini,Luis M Coral,Aaron J Deutsch,Miriam S Udler,Giuseppe N Giordano,Guillaume Pare,Ewan R Pearson,Maarten van Smeden,Paul W Franks
Precision medicine for complex diseases uses individual-level characteristics to improve prediction of risk, therapeutic response and prognosis. Many precision medicine studies leverage existing data types and analytic methods to reveal new insights; however, beyond oncology, there has been limited success in translating precision medicine research for complex diseases into clinical practice. Thus, there is a need to identify areas for improvement, particularly in translation-oriented analytical methods and study designs. In this perspective article, we outline five fundamental tenets to enhance the efficient clinical translation of precision medicine research. These tenets focus on addressing (1) heterogeneity in risk, response and prognosis; (2) signal robustness; (3) structured statistical benchmarking against key performance indicators; (4) precision trial designs; and (5) risks and benefits to individuals and society. Our intention is to promote clinically meaningful, reproducible, scalable and equitable health outcomes through precision medicine, beyond those possible through contemporary approaches.
{"title":"Five tenets for advancing evidence-based precision medicine.","authors":"Daniel E Coral,Jennifer L Sargent,Julia Carrasco-Zanini,Luis M Coral,Aaron J Deutsch,Miriam S Udler,Giuseppe N Giordano,Guillaume Pare,Ewan R Pearson,Maarten van Smeden,Paul W Franks","doi":"10.1038/s41591-026-04309-6","DOIUrl":"https://doi.org/10.1038/s41591-026-04309-6","url":null,"abstract":"Precision medicine for complex diseases uses individual-level characteristics to improve prediction of risk, therapeutic response and prognosis. Many precision medicine studies leverage existing data types and analytic methods to reveal new insights; however, beyond oncology, there has been limited success in translating precision medicine research for complex diseases into clinical practice. Thus, there is a need to identify areas for improvement, particularly in translation-oriented analytical methods and study designs. In this perspective article, we outline five fundamental tenets to enhance the efficient clinical translation of precision medicine research. These tenets focus on addressing (1) heterogeneity in risk, response and prognosis; (2) signal robustness; (3) structured statistical benchmarking against key performance indicators; (4) precision trial designs; and (5) risks and benefits to individuals and society. Our intention is to promote clinically meaningful, reproducible, scalable and equitable health outcomes through precision medicine, beyond those possible through contemporary approaches.","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"28 1","pages":""},"PeriodicalIF":82.9,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147502438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-23DOI: 10.1038/s41591-026-04292-y
Richard W. Lee, Arjun Nair, Haval Balata, Charlotte Graham, Craig Parylo, Jessica Abell, Michael Woodall, Michael Lawrie, Sally Mouland, Kate Brain, Michelle Clark, Philip Crosbie, Anand Devaraj, Jesme Fox, Martin Grange, Sam M. Janes, Peter Johnson, Anne Mackie, Neal Navani, Samantha L. Quaife, Amelia Randle, Janette Rawlinson, Robert C. Rintoul, Liz Rochelle, Peter Sasieni, Matthew E. J. Callister, David R. Baldwin, on behalf of UK Lung Cancer Screening Research Consortium
Lung cancer screening with low-dose computed tomography has been proven to reduce lung-cancer-specific and all-cause mortality. The UK launched the NHS England Targeted Lung Health Check Programme in 2019, which has now become the national Lung Cancer Screening Programme, with full coverage expected by 2030. Here we present the progress and outcomes of the program. People aged 55–74 were offered low-dose computed tomography of the thorax if they had ever smoked and if risk thresholds, as determined by multivariable models, were met. Delivery of the program is through regionally federated clinical infrastructure and leadership, with national strategic, clinical and economic frameworks. The program has invited over two million people, with 7,193 lung cancers diagnosed—63.1% at tumor, node, metastasis stage 1 and 12.6% stage 2—to March 2025. This has increased the early-stage proportion of lung cancer in England over 5 years, particularly in socioeconomically deprived regions. The NHS England Programme exemplifies how large-scale implementation can be achieved at speed through centralized protocols and effective project management. The program has demonstrated feasibility and scalability in reaching high-risk and underserved populations, but needs to further address inequalities in participation. These findings support adoption of lung cancer screening across the UK and globally, and offer practical tools for international adaptation.
{"title":"Implementation of the NHS England Lung Cancer Screening Programme over 5 years","authors":"Richard W. Lee, Arjun Nair, Haval Balata, Charlotte Graham, Craig Parylo, Jessica Abell, Michael Woodall, Michael Lawrie, Sally Mouland, Kate Brain, Michelle Clark, Philip Crosbie, Anand Devaraj, Jesme Fox, Martin Grange, Sam M. Janes, Peter Johnson, Anne Mackie, Neal Navani, Samantha L. Quaife, Amelia Randle, Janette Rawlinson, Robert C. Rintoul, Liz Rochelle, Peter Sasieni, Matthew E. J. Callister, David R. Baldwin, on behalf of UK Lung Cancer Screening Research Consortium","doi":"10.1038/s41591-026-04292-y","DOIUrl":"https://doi.org/10.1038/s41591-026-04292-y","url":null,"abstract":"Lung cancer screening with low-dose computed tomography has been proven to reduce lung-cancer-specific and all-cause mortality. The UK launched the NHS England Targeted Lung Health Check Programme in 2019, which has now become the national Lung Cancer Screening Programme, with full coverage expected by 2030. Here we present the progress and outcomes of the program. People aged 55–74 were offered low-dose computed tomography of the thorax if they had ever smoked and if risk thresholds, as determined by multivariable models, were met. Delivery of the program is through regionally federated clinical infrastructure and leadership, with national strategic, clinical and economic frameworks. The program has invited over two million people, with 7,193 lung cancers diagnosed—63.1% at tumor, node, metastasis stage 1 and 12.6% stage 2—to March 2025. This has increased the early-stage proportion of lung cancer in England over 5 years, particularly in socioeconomically deprived regions. The NHS England Programme exemplifies how large-scale implementation can be achieved at speed through centralized protocols and effective project management. The program has demonstrated feasibility and scalability in reaching high-risk and underserved populations, but needs to further address inequalities in participation. These findings support adoption of lung cancer screening across the UK and globally, and offer practical tools for international adaptation.","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"48 1","pages":""},"PeriodicalIF":82.9,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147496786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-20DOI: 10.1038/s41591-026-04247-3
Yuan Gao,Yasbanoo Moayedi,Farid Foroutan,Bhavish Verma,Ben Kim,Enza De Luca,Margaret Brum,Darshan H Brahmbhatt,Joe Duhamel,Anne Simard,Chris McIntosh,Heather J Ross
Heart failure (HF) involves cycles of remission and exacerbation, which are poorly characterized by static disease measures. Consumer wearables have an understudied potential for daily monitoring of HF symptoms. Here we report results from an observational cohort of free-living patients over a median of 94.5 d with HF in the Ted Rogers Understanding Exacerbations of HF (TRUE-HF) study. The study measured the ability of Apple Watch data to predict peak oxygen uptake (pVO2) as measured using in-clinic cardiopulmonary exercise testing (CPET). A deep learning model was trained with data from 154 patients (46 women, 108 men) and validated on a held-out set of 63 patients (24 women, 39 men) for determining wearable-derived daily pVO2, which correlated strongly with CPET-measured pVO2 (Pearson's correlation = 0.85). Each 10% drop in wearable-derived daily pVO2 was associated with a 3.62-fold increased hazard ratio (HR) for unplanned healthcare events (95% confidence interval (CI), 1.37-9.55; P < 0.01), which occurred at a median of 7.4 d after the first 10% drop in wearable-derived pVO2. These findings were externally validated in an independent external cohort from the All of Us Research Program using a crossplatform model that accounted for the reduced-sensor capacities available in this external cohort. Using this reduced-sensor variant of the model, drops in wearable-derived daily pVO2 were associated with unplanned healthcare utilization (HR 1.32, 95% CI 1.03-1.69; P = 0.03), which occurred at a median of 21 d after the first 10% drop in wearable-derived pVO2. These results indicate that wearable-derived daily pVO2 provides earlier and improved risk discrimination compared with existing wearable fitness estimates and established clinical markers and offers a scalable and generalizable approach for longitudinal HF research and monitoring.
心力衰竭（HF）涉及缓解和恶化的周期，这是静态疾病测量的差特征。消费者可穿戴设备在日常监测心衰症状方面的潜力尚未得到充分研究。在这里，我们报告了泰德·罗杰斯了解HF恶化（TRUE-HF）研究中，一组中位时间超过94.5 d的自由生活HF患者的观察性队列结果。该研究测量了Apple Watch数据预测临床心肺运动测试（CPET）测量的峰值摄氧量（pVO2）的能力。使用154名患者（46名女性，108名男性）的数据训练深度学习模型，并在63名患者（24名女性，39名男性）的固定组上进行验证，以确定可穿戴设备衍生的每日pVO2，其与cpet测量的pVO2密切相关（Pearson’s correlation = 0.85）。可穿戴设备衍生的每日pVO2每下降10%，意外医疗事件的风险比（HR）增加3.62倍(95%置信区间（CI）， 1.37-9.55；P < 0.01)，这发生在可穿戴设备衍生的pVO2首次下降10%后的7.4 d中位数。这些发现在一个独立的外部队列中进行了外部验证，该外部队列使用了一个跨平台模型，该模型考虑了外部队列中可用的传感器容量的减少。使用这种减少传感器的模型变体，可穿戴设备每日pVO2的下降与计划外医疗保健利用相关（HR 1.32, 95% CI 1.03-1.69; P = 0.03），发生在可穿戴设备pVO2第一次下降10%后的中位数21天。这些结果表明，与现有的可穿戴健身评估和已建立的临床标志物相比，可穿戴设备衍生的每日pVO2提供了更早和更好的风险识别，并为纵向HF研究和监测提供了一种可扩展和可推广的方法。
{"title":"Remote monitoring of heart failure exacerbations using a smartwatch.","authors":"Yuan Gao,Yasbanoo Moayedi,Farid Foroutan,Bhavish Verma,Ben Kim,Enza De Luca,Margaret Brum,Darshan H Brahmbhatt,Joe Duhamel,Anne Simard,Chris McIntosh,Heather J Ross","doi":"10.1038/s41591-026-04247-3","DOIUrl":"https://doi.org/10.1038/s41591-026-04247-3","url":null,"abstract":"Heart failure (HF) involves cycles of remission and exacerbation, which are poorly characterized by static disease measures. Consumer wearables have an understudied potential for daily monitoring of HF symptoms. Here we report results from an observational cohort of free-living patients over a median of 94.5 d with HF in the Ted Rogers Understanding Exacerbations of HF (TRUE-HF) study. The study measured the ability of Apple Watch data to predict peak oxygen uptake (pVO2) as measured using in-clinic cardiopulmonary exercise testing (CPET). A deep learning model was trained with data from 154 patients (46 women, 108 men) and validated on a held-out set of 63 patients (24 women, 39 men) for determining wearable-derived daily pVO2, which correlated strongly with CPET-measured pVO2 (Pearson's correlation = 0.85). Each 10% drop in wearable-derived daily pVO2 was associated with a 3.62-fold increased hazard ratio (HR) for unplanned healthcare events (95% confidence interval (CI), 1.37-9.55; P < 0.01), which occurred at a median of 7.4 d after the first 10% drop in wearable-derived pVO2. These findings were externally validated in an independent external cohort from the All of Us Research Program using a crossplatform model that accounted for the reduced-sensor capacities available in this external cohort. Using this reduced-sensor variant of the model, drops in wearable-derived daily pVO2 were associated with unplanned healthcare utilization (HR 1.32, 95% CI 1.03-1.69; P = 0.03), which occurred at a median of 21 d after the first 10% drop in wearable-derived pVO2. These results indicate that wearable-derived daily pVO2 provides earlier and improved risk discrimination compared with existing wearable fitness estimates and established clinical markers and offers a scalable and generalizable approach for longitudinal HF research and monitoring.","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"1 1","pages":"924-933"},"PeriodicalIF":82.9,"publicationDate":"2026-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147489862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-20DOI: 10.1038/s41591-026-04280-2
Jeffrey van Putten,Petur Snaebjornsson,Linda J W Bosch,Roelof Koster,Paul Roepman,Joseph Usset,Mirjam C Boelens,Tom van Wezel,Efraim H Rosenberg,Serena Marchetti,Marieke Vollebergh,Doenja M J Lambregts,Lizet E van der Kolk,Edwin Cuppen,Hilde H Nienhuis,Kim Monkhorst
Molecular testing is essential in precision oncology. Whole-genome sequencing (WGS) provides a tumor-agnostic solution for detecting an increasingly complex range of DNA-based biomarkers. Here we present real-world data from 888 patients to demonstrate the clinical utility of routine, paired tumor-normal WGS diagnostics for solid cancers in a comprehensive cancer center. WGS succeeded in 89% of cases with a median turnaround time of 6 working days. Potentially actionable biomarkers were identified in 73% of patients, including biomarkers for reimbursed (27%) and experimental (63%) therapies. Within 1 year, 40% and 19% of patients, respectively, started biomarker-informed treatment, which was associated with a 31% longer median overall survival (+96 days) compared with patients not receiving such therapy. Among patients without prior systemic therapy, biomarker-informed treatment yielded significantly longer overall survival (median not reached) than non-biomarker-informed therapy (427 days) or no systemic therapy (214 days). In cancers of unknown primary (n = 123), WGS contributed to diagnostic solution or detected biomarker-driven reimbursed treatment options in 67%, with 68% starting tumor-type-specific therapy. Clinically relevant pathogenic germline variants were identified in 6.5% of patients. Overall, WGS-based diagnostics had clinical consequences for 41% of tested patients, providing a versatile tool for routine clinical practice in solid oncology.
{"title":"Real-world clinical utility of tumor whole-genome sequencing in solid cancers.","authors":"Jeffrey van Putten,Petur Snaebjornsson,Linda J W Bosch,Roelof Koster,Paul Roepman,Joseph Usset,Mirjam C Boelens,Tom van Wezel,Efraim H Rosenberg,Serena Marchetti,Marieke Vollebergh,Doenja M J Lambregts,Lizet E van der Kolk,Edwin Cuppen,Hilde H Nienhuis,Kim Monkhorst","doi":"10.1038/s41591-026-04280-2","DOIUrl":"https://doi.org/10.1038/s41591-026-04280-2","url":null,"abstract":"Molecular testing is essential in precision oncology. Whole-genome sequencing (WGS) provides a tumor-agnostic solution for detecting an increasingly complex range of DNA-based biomarkers. Here we present real-world data from 888 patients to demonstrate the clinical utility of routine, paired tumor-normal WGS diagnostics for solid cancers in a comprehensive cancer center. WGS succeeded in 89% of cases with a median turnaround time of 6 working days. Potentially actionable biomarkers were identified in 73% of patients, including biomarkers for reimbursed (27%) and experimental (63%) therapies. Within 1 year, 40% and 19% of patients, respectively, started biomarker-informed treatment, which was associated with a 31% longer median overall survival (+96 days) compared with patients not receiving such therapy. Among patients without prior systemic therapy, biomarker-informed treatment yielded significantly longer overall survival (median not reached) than non-biomarker-informed therapy (427 days) or no systemic therapy (214 days). In cancers of unknown primary (n = 123), WGS contributed to diagnostic solution or detected biomarker-driven reimbursed treatment options in 67%, with 68% starting tumor-type-specific therapy. Clinically relevant pathogenic germline variants were identified in 6.5% of patients. Overall, WGS-based diagnostics had clinical consequences for 41% of tested patients, providing a versatile tool for routine clinical practice in solid oncology.","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"85 1","pages":""},"PeriodicalIF":82.9,"publicationDate":"2026-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147489863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-19DOI: 10.1038/s41591-026-04336-3
{"title":"A biomarker of Alzheimer's disease could be a useful diagnostic tool for other amyloidoses.","authors":"","doi":"10.1038/s41591-026-04336-3","DOIUrl":"https://doi.org/10.1038/s41591-026-04336-3","url":null,"abstract":"","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"12 1","pages":""},"PeriodicalIF":82.9,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147483425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-19DOI: 10.1038/s41591-026-04294-w
Thiago Cerqueira-Silva,Viviane Sampaio Boaventura,Enny S Paixão,Mauro Sanchez,Clémence Leyrat,Otavio Ranzani,Mauricio L Barreto,Julia M Pescarini
Tuberculosis (TB) remains a major societal burden, yet data on long-term mortality following TB diagnosis and treatment are limited. We conducted a nationwide Brazilian cohort study using linked data (2004-2018) to quantify long-term mortality (up to 14 years) following TB. We matched: (i) individuals diagnosed with TB or (ii) individuals who had completed TB treatment to TB-free individuals. We used competing risk methods to analyze natural causes (that is, defined as deaths excluding TB, HIV and external causes) and cause-specific mortality. In the diagnosed cohort (185,921 pairs), the risk of 14-year natural cause mortality was significantly higher (risk ratio (RR) = 2.16, 95% confidence interval = 1.96-2.37); RRs were significantly elevated for deaths due to cancer, cardiovascular, endocrine, respiratory and external causes. The treated cohort (111,871 pairs) presented elevated natural cause mortality risk (RR = 1.77,1.55-2.03), with similarly increased RRs across specific causes. We showed that TB survivors, even after treatment, faced a significantly elevated, prolonged risk of death from various causes up to 14 years later. This finding highlights the need for long-term monitoring to reduce the burden of TB.
{"title":"Long-term risk of death after tuberculosis diagnosis and treatment.","authors":"Thiago Cerqueira-Silva,Viviane Sampaio Boaventura,Enny S Paixão,Mauro Sanchez,Clémence Leyrat,Otavio Ranzani,Mauricio L Barreto,Julia M Pescarini","doi":"10.1038/s41591-026-04294-w","DOIUrl":"https://doi.org/10.1038/s41591-026-04294-w","url":null,"abstract":"Tuberculosis (TB) remains a major societal burden, yet data on long-term mortality following TB diagnosis and treatment are limited. We conducted a nationwide Brazilian cohort study using linked data (2004-2018) to quantify long-term mortality (up to 14 years) following TB. We matched: (i) individuals diagnosed with TB or (ii) individuals who had completed TB treatment to TB-free individuals. We used competing risk methods to analyze natural causes (that is, defined as deaths excluding TB, HIV and external causes) and cause-specific mortality. In the diagnosed cohort (185,921 pairs), the risk of 14-year natural cause mortality was significantly higher (risk ratio (RR) = 2.16, 95% confidence interval = 1.96-2.37); RRs were significantly elevated for deaths due to cancer, cardiovascular, endocrine, respiratory and external causes. The treated cohort (111,871 pairs) presented elevated natural cause mortality risk (RR = 1.77,1.55-2.03), with similarly increased RRs across specific causes. We showed that TB survivors, even after treatment, faced a significantly elevated, prolonged risk of death from various causes up to 14 years later. This finding highlights the need for long-term monitoring to reduce the burden of TB.","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"9 1","pages":""},"PeriodicalIF":82.9,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147483428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marked socioeconomic divides and unequal advances in renewable energy transition across Europe have raised concerns about widening inequalities in air pollution exposure and related health risks. Here we analyzed 88.8 million deaths across 653 contiguous regions in 31 European countries, encompassing the entire urban and rural population of 521 million people from 2003 to 2019, to investigate how socioeconomic conditions and renewable energy adoption relate to regional disparities in acute air pollution-related mortality risks and their trends over time. Regions with higher gross domestic product per capita, lower poverty rates and longer life expectancy-primarily in Western and Northern Europe-showed lower and declining risks in air pollution-related mortality compared to other regions in Europe. We assessed renewable energy transition as both an upstream driver and an effect modifier of the relationship between air pollution and mortality. As an upstream driver, greater renewable energy adoption was associated with 15-54% lower air pollutant levels and, consequently, 12-53% fewer attributable deaths. As an effect modifier, high renewable adoption was significantly associated with lower and declining mortality risks. Taken together, our findings show that differences in socioeconomic conditions and energy transition are associated with widening disparities in air pollution-related health risks across Europe.
{"title":"Socioeconomic and energy transition disparities in air pollution-related mortality across Europe.","authors":"Zhao-Yue Chen,Hicham Achebak,Wenzhong Huang,Blanca Paniello-Castillo,Hervé Petetin,Raúl Fernando Méndez Turrubiates,Carlos Pérez García-Pando,Joan Ballester","doi":"10.1038/s41591-026-04293-x","DOIUrl":"https://doi.org/10.1038/s41591-026-04293-x","url":null,"abstract":"Marked socioeconomic divides and unequal advances in renewable energy transition across Europe have raised concerns about widening inequalities in air pollution exposure and related health risks. Here we analyzed 88.8 million deaths across 653 contiguous regions in 31 European countries, encompassing the entire urban and rural population of 521 million people from 2003 to 2019, to investigate how socioeconomic conditions and renewable energy adoption relate to regional disparities in acute air pollution-related mortality risks and their trends over time. Regions with higher gross domestic product per capita, lower poverty rates and longer life expectancy-primarily in Western and Northern Europe-showed lower and declining risks in air pollution-related mortality compared to other regions in Europe. We assessed renewable energy transition as both an upstream driver and an effect modifier of the relationship between air pollution and mortality. As an upstream driver, greater renewable energy adoption was associated with 15-54% lower air pollutant levels and, consequently, 12-53% fewer attributable deaths. As an effect modifier, high renewable adoption was significantly associated with lower and declining mortality risks. Taken together, our findings show that differences in socioeconomic conditions and energy transition are associated with widening disparities in air pollution-related health risks across Europe.","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"20 1","pages":""},"PeriodicalIF":82.9,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147483427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-19DOI: 10.1038/s41591-026-04274-0
Yunwen Xu,Natalie Daya Malek,Alexander R Chang,Justin B Echouffo-Tcheugui,Elizabeth Selvin,Morgan E Grams,Michael Fang,Jung-Im Shin
There is substantial interest in the use of glucagon-like peptide-1 receptor agonists (GLP-1RAs) in type 1 diabetes, but data on the long-term clinical outcomes are lacking. Using national electronic health record data from 174,678 patients with type 1 diabetes, we conducted a sequential target trial emulation from January 2013 to March 2024. After propensity score weighting, GLP-1RA initiation was associated with significantly lower risks of major adverse cardiovascular events (5-year risk: 4.3% versus 5.0%; risk difference: -0.7% (95% confidence interval (CI): -1.2% to -0.2%); hazard ratio (HR): 0.85 (0.77-0.95)) and end-stage kidney disease (5-year risk: 1.6% versus 1.9%; risk difference: -0.3% (-0.6% to 0%); HR: 0.81 (0.69-0.95)). No increased risks of hospitalization for diabetic ketoacidosis or severe hypoglycemia were observed. These findings suggest that GLP-1RAs may be beneficial against major adverse cardiorenal events in patients with type 1 diabetes, without compromising safety.
{"title":"Glucagon-like peptide-1 receptor agonists for major cardiovascular and kidney outcomes in type 1 diabetes.","authors":"Yunwen Xu,Natalie Daya Malek,Alexander R Chang,Justin B Echouffo-Tcheugui,Elizabeth Selvin,Morgan E Grams,Michael Fang,Jung-Im Shin","doi":"10.1038/s41591-026-04274-0","DOIUrl":"https://doi.org/10.1038/s41591-026-04274-0","url":null,"abstract":"There is substantial interest in the use of glucagon-like peptide-1 receptor agonists (GLP-1RAs) in type 1 diabetes, but data on the long-term clinical outcomes are lacking. Using national electronic health record data from 174,678 patients with type 1 diabetes, we conducted a sequential target trial emulation from January 2013 to March 2024. After propensity score weighting, GLP-1RA initiation was associated with significantly lower risks of major adverse cardiovascular events (5-year risk: 4.3% versus 5.0%; risk difference: -0.7% (95% confidence interval (CI): -1.2% to -0.2%); hazard ratio (HR): 0.85 (0.77-0.95)) and end-stage kidney disease (5-year risk: 1.6% versus 1.9%; risk difference: -0.3% (-0.6% to 0%); HR: 0.81 (0.69-0.95)). No increased risks of hospitalization for diabetic ketoacidosis or severe hypoglycemia were observed. These findings suggest that GLP-1RAs may be beneficial against major adverse cardiorenal events in patients with type 1 diabetes, without compromising safety.","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"12 1","pages":""},"PeriodicalIF":82.9,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147483430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：