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921 citation(s) found for "Qi, Jun".

Clinical utility of age-matched z-score maps from a large normative pediatric [18F]-FDG PET database for localizing epileptogenic abnormalities: illustrative cases
Lim, Seokbeen , Min, Paul H., Dizdar, Nur, Diaz, Miguel D., Guérin, J. , Silvera, Michelle, Wong-Kisiel, Lily C. , Salehinejad, Hojjat , Bilgin, Gokce Belge , Bilgin, Cem , Brinkmann, Benjamin H. , Britton, Jeffrey W. , Johnson, Derek R., Messina, Steven, Kemp, Bradley J. , Kendi, A. Tuba, Zhang, Jun, Lowe, Val J. , MD, Miller, Lim, Seokbeen

No container title available | September 24, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-11143642/v1 Get It

Abstract Introduction Quantitative interpretation of pediatric brain [ 18 F]-FDG PET is limited by the lack of age-matched normative reference databases, despite substantial developmental variation in cerebral glucose metabolism. This study aimed to construct a large-scale normative pediatric [ 18 F]-FDG PET database and develop an age-specific z-score mapping framework for quantitative evaluation of pediatric epilepsy. Method Pediatric brain PET data were retrospectively derived from clinically acquired whole-body or dedicated [ 18 F]-FDG PET examinations in participants 0–19 years of age without neurologic disease or visible brain abnormalities. A total of 417 PET scans from 341 participants were stratified into five developmental age groups: infancy, early childhood, middle childhood/school age, adolescence, and late adolescence. SUVR maps were generated using whole-brain atlas and brainstem reference regions. Voxel-wise t-test analyses were performed to characterize age- and sex-related metabolic differences. Age-specific voxel-wise mean and standard deviation maps were generated from the normative cohort and used to calculate age-matched hypometabolic z-score maps in 14 pediatric patients with epilepsy. The resulting abnormalities were qualitatively evaluated for concordance with epileptogenic findings identified on clinical MRI and/or PET by expert image review. Results Voxel-wise analyses demonstrated prominent age-dependent SUVR differences, particularly between infancy and older age groups. With whole-brain atlas normalization, older children showed progressively higher relative SUVR in cortical and cerebellar gray matter regions, whereas infancy showed relatively higher SUVR in the occipital cortex, white matter, thalamus, and brainstem. Brainstem normalization produced distinct developmental patterns, emphasizing higher white matter SUVR in infancy and broader gray matter differences in older groups. Sex-related differences were limited and regionally specific. Whole-brain atlas normalization showed lower variability than brainstem normalization and was selected for z-score mapping. In representative epilepsy cases, age-matched z-score maps identified focal or regional hypometabolism corresponding to malformations of cortical development, focal cortical dysplasia, mesial temporal sclerosis, nonlesional MRI cases, remote insult, tumor-related abnormalities, and Sturge-Weber syndrome. Discussion A large-scale normative pediatric [18F]-FDG PET database can support developmentally appropriate quantitative interpretation of pediatric brain PET. Age-matched z-score mapping may complement visual assessment by highlighting abnormal cerebral glucose metabolism in pediatric epilepsy, although findings should be interpreted with MRI, EEG, seizure semiology, and other presurgical data.
Differential associations of individual- and neighborhood-level socioeconomic status with mortality in dementia: Findings from the Mayo Clinic Study of Aging
Lin, Jie , Vassilaki, Maria , Sauver, Jennifer St., Petersen, Ronald C., Wi, Chung Il, Juhn, Young J., Sham, Yuk , Sohn, Sunghwan , St Sauver, Jennifer, Sham, Yuk , Sauver, Jennifer L. St. , Petersen, Ronald C. , Wi, Chung‐Il , Juhn, Young J. , Chen, Jun

Journal of Alzheimer’s Disease | September 3, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1177/13872877261482043 | PMID 42690834 Get It

Background Alzheimer's disease (AD) and related dementias are leading causes of death worldwide. While socioeconomic status (SES) is a critical determinant, its impact on mortality after diagnosis remains understudied. Objective To investigate the roles of neighborhood-level and individual-level SES in predicting mortality risk among older adults with incident dementia. Methods We analyzed data from 924 participants with incident dementia from the Mayo Clinic Study of Aging (N = 6909), a cohort with clinical follow-up visits every 15 months. We assessed mortality risk using Cox's time-varying survival regression, adjusting for time-fixed and time-varying covariates. Primary predictors were neighborhood-level SES (Area Deprivation Index [ADI]) and individual-level SES (housing-based SES index [HOUSES], education, and occupation). We also applied a random survival forest model to assess the predictive contribution of SES indicators and identify influential predictors. Results 857 participants (92.7%) died, with a median time from dementia diagnosis to death of 29 months (IQR: 12–54). Lower SES measured by HOUSES was associated with increased mortality risk (HR 1.28, 95% CI 1.07–1.52). Conversely, ADI, education, and occupation were not associated with mortality. Male sex, older age, congestive heart failure and diabetes were associated with higher mortality risk. In predictive analysis, HOUSES ranked among the top 10 contributors to mortality risk. Conclusions Among older adults with dementia, lower HOUSES was associated with higher mortality risk beyond neighborhood-level deprivation, education, and occupation. Integrating this housing-based individual-level SES measure into dementia care planning may help identify patients with greater socioeconomic vulnerability and inform mortality risk stratification.
Enterochromaffin cells as a cellular integration hub for cooperative microbial signaling to modulate gut serotonin and motility
Xiao, Yang , Till, Lisa , Gupta, Yash, Mercado‐Perez, Arnaldo , Bhagwate, Aditya V., Bellampalli, Shreya S. , Stark, Alejandro , Sekhon, Prabhjot K., Singh, Vaidhvi , Tienter, Dennis, Thompson, Michael A. , Kossick, Kimberlee , Krueger, Eugene W., Kalari, Krishna R., Hawkins, Kaitlyn R., Edwards, Brian S. , Alcaino, Constanza, Guo, Chun‐Jun , Druliner, Brooke R., Ördög, Tamás , Farrugia, Gianrico , Kashyap, Purna , Louwies, Tijs, Mars, Ruben A T, Mercado-Perez, Arnaldo, Bellampalli, Shreya S , Stark Quiroz, Alejandro , Liu, Rongfang , Thompson, Michael A , Kossick, Kimberlee , Lee, Jeong-Heon , van der Es, Daan , Willett, Julia L E , Wongkrasant, Preedajit , Prakash, Y S , Ordog, Tamas , Farrugia, Gianrico , Beyder, Arthur , Smith-Edwards, Kristen M , Kashyap, Purna C , Louwies, Tijs , Mars, Ruben A. , Gupta, Yash , Bhagwate, Aditya , Sekhon, Prabhjot Kaur , Heitman, Laura H. , Krueger, Eugene W. , Lee, Jeong‐Heon , Alcaino, Constanza , Willett, Julia L. E. , Wongkrasant, Preedajit , Prakash, Y. S. , Druliner, Brooke R. , Beyder, Arthur

Proceedings of the National Academy of Sciences | August 24, 2026 | Volume: 123 | Issue: 35 | Pages: No page available

10.1073/pnas.2533336123 | PMID 42636369 Get It

The intestinal epithelium is exposed to diverse combinations of microbiota-derived compounds; however, the mechanisms by which the host integrates these signals remain poorly defined. Studying two highly abundant microbial metabolites, we identified the purine metabolite hypoxanthine as an effector metabolite that directly drives signaling and the short-chain fatty acid butyrate as a regulatory metabolite that conditions host responsiveness. Specifically, hypoxanthine activates the adenosine A1 receptor–TRPC4 axis in enterochromaffin (EC) cells, triggering calcium influx and serotonin release resulting in accelerated gastrointestinal transit locally and increased platelet activation systemically. In contrast, butyrate epigenetically upregulates specific G protein–coupled receptors and ion channels to enhance response to hypoxanthine and the neurotransmitters norepinephrine and dopamine. These findings define a cooperative signaling framework and highlight the role of EC cells as a distinct epithelial signaling hub that senses and integrates microbial metabolite signals to drive physiological responses. Our findings provide a mechanistic foundation for therapeutic strategies that leverage combinatorial microbial signaling.
Epidemiologic Study of Transfusion-Related Alpha-Gal Syndrome
Kaufman, Richard M., Hoen, Anne G., Khan, Jenna, Knudson, C. Michael, Romero, Andres E. Mindiola, Mo, Allison , Takanashi, Minoko , Collaborative, UPTICK Study Group; for the Biomedical Excellence for Safer Transfusion (BEST), Cardigan, Rebecca, Stanworth, Simon J., Commins, Scott P. , Scherer, Emily A., Davenport, Robertson D., Afraz, Sajjad, Andrews, Jennifer , Casey, John, Sullivan, Jensyn Cone , Cousins, Clara C. , Giorgi, Valeria De , Delaney, Meghan, DelBaugh, Regina M. , Gilstad, Colleen W. , Gofton, Alexander , Hill, Kate, Hogan, Keenan , Humbrecht, Catherine , Ikeda, Kazuhiko, Javanbakht, Ayda, Juskewitch, Justin E, Wojtowicz, Monique M. Menzies, Miller, Maureen J., Mills, Georgia, Nelson, Anna C. , Pauly, Marie C., Poisson, Jessica , Raval, Jay S., Samy, Nikitha, Sato, Tomohiko, Takeda, Yoshinori , Thibodeaux, Suzanne R. , Nunen, Sheryl van, Virk, Mrigender S., West-Mitchell, Kamille, Yamanouchi, Jun, Yoshihara, Satoshi, Zheng, X. Long, Ziman, Alyssa, Cone Sullivan, Jensyn , Kaufman, Richard Max , Hoen, Anne Gatewood , Knudson, Charles Michael , Metcalf, Ryan A. , Schäfer, Richard , Dunbar, Nancy M. , Cardigan, Rebecca A. , Stanworth, Simon J., Scherer, Emily A. , Cervinski, Mark A , Arai, Yasuyuki , Brugnara, Carlo , Allen, Elizabeth S. , Aurich, Konstanze , Casey, John , Cohn, Claudia S. , Crowe, Elizabeth P , Delaney, Meghan , Hendrickson, Jeanne E. , Hill, Kate, Ikeda, Kazuhiko , Jacquot, Cyril , Javanbakht, Ayda , Juskewitch, Justin E. , Lu, Wen , Wojtowicz, Monique Menzies , Miller, Maureen J. , Nelson, Anna , Pagano, Monica B. , Pauly, Marie-Christin , Saifee, Nabiha H , Sato, Tomohiko, Takeda, Yoshinori, Tiberghien, Pierre , Nunen, Sheryl van, Virk, Mrigender , Wood, Erica M , Yoshihara, Satoshi , Zheng, X. Long, Ziman, Alyssa

JAMA Internal Medicine | August 24, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1001/jamainternmed.2026.3983 | PMID 42636004 Get It

Importance Recent case reports suggest that B antigen–containing blood products may be associated with anaphylactic transfusion reactions in recipients with preformed immunoglobulin E to galactose- α -1,3-galactose (alpha-gal). Objective To test the association of local alpha-gal syndrome (AGS) prevalence and allergic transfusion reaction (ATR) in patients with blood type O. Design, Setting, and Participants In this international, multicenter, retrospective cohort study at academic medical centers, sites were assigned to AGS high- or low-prevalence clusters based on the known geographic distribution of AGS. Data were collected on platelet or plasma transfusions and ATRs during 2020 to 2024. Consecutive patients receiving platelet or plasma transfusions were included. Exposures Patients with blood type O who received B or AB units and patients with blood type O who received O units (reference group) in AGS high- and low-prevalence clusters were compared. Main Outcomes and Measures Before data collection, the hypothesis was that if transfusion-related alpha-gal syndrome (TRAGS) is a true clinical entity, excess ATRs to group B or AB units would be detected in AGS high-prevalence regions exclusively. The main measure was the overall risk ratio (RR) for ATRs to B or AB plasma or platelets in AGS high- vs low-prevalence clusters. Results In total, 558 823 platelet and plasma transfusions at 40 sites in 5 countries were analyzed, of which ATRs occurred in 1744 transfusions (0.3%). In the US AGS high-prevalence cluster (9 sites), significantly more ATRs of any severity occurred among patients with blood type O who received B or AB units vs patients with blood type O who received O units (overall RR, 3.93; 95% CI, 2.96-5.21; P < .001). In contrast, in the primary analysis of the AGS low-prevalence cluster (15 sites), excess ATRs to B or AB units were not detected. In subgroup analyses among patients with blood type O receiving B units, the RR for moderate to severe ATRs was 9.14 (95% CI, 5.39-15.52; P < .001) in the AGS high-prevalence cluster vs 2.15 (95% CI, 1.34-3.47; P = .002) in the AGS low-prevalence cluster. Outside the US, a signal consistent with TRAGS was not detected. Conclusions and Relevance This cohort study provides provocative epidemiologic evidence that TRAGS may be a unique manifestation of AGS and a previously unrecognized risk associated with transfusion. In AGS high-prevalence regions, blood collectors and hospital transfusion services should consider approaches to preventing severe ATRs from B or AB plasma or platelet units.
Evaluating longitudinal toxicity and adverse event in cetuximab-treated metastatic colorectal cancer: a pooled analysis from 1,302 patients in ARCAD database
Yin, Jun , Lopes, Guilherme S. , So, Jane, Olswold, Curt L., Cutsem, Eric Van, Bokemeyer, Carsten, Adams, Richard, Grothey, Axel, Yoshino, Takayuki, Gramont, Aimery de , Shi, Qian, Tournigand, Christophe , Zalcberg, John, Shi, Qian , Shi, Qian , Francis, Katherine E. , Lopes, Guilherme S, So, Jane , Cutsem, Eric Van , Bokemeyer, Carsten , Adams, Richard , Chibaudel, Benoist , Grothey, Axel , Yoshino, Takayuki , Sjoquist, Katrin Marie , Zalcberg, John

JNCI: Journal of the National Cancer Institute | August 20, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1093/jnci/djag287 | PMID 42636265 Get It

Abstract Purpose Traditional adverse event (AE) reporting in oncology trials focuses on the single worst CTCAE grade, which may underrepresent chronic or recurrent toxicity burden. We applied a longitudinal toxicity framework to compare toxicity profiles of chemotherapy with or without cetuximab in metastatic colorectal cancer. Patients and Methods We pooled two randomized first-line trials in the ARCAD database. AEs examined were diarrhea, rash, hand-foot syndrome (HFS), fatigue, anorexia, and mucositis. Outcomes included grade ≥3 AE, time to first occurrence of maximum grade, early onset (≤6 weeks), and AEL, a normalized measure of cumulative toxicity burden over treatment. Analyses were adjusted for chemotherapy backbone, ECOG performance status, sex, primary tumor location, dose reduction, and treatment duration. Results Compared with Chemotherapy alone (n = 564), Chemotherapy plus cetuximab (n = 738) was associated with higher grade ≥3 rash (21% vs 0.5%; adjusted odds ratio [OR] 49.89, 95% CI 15.8–157.4), higher rash AEL (0.257 vs 0.069; adjusted mean difference 0.22, 95% CI 0.21–0.23), and more frequent early-onset maximum rash (67% vs 34%; adjusted OR 4.28, 95% CI 2.72–6.74). Rash AEL remained higher with cetuximab within maximum-grade strata. HFS showed higher grade ≥3 risk and overall AEL with cetuximab, but no within-grade AEL difference, indicating higher overall HFS burden reflected grade distribution rather than within-grade chronicity. No consistent differences were observed for other AEs. Conclusions Incorporating onset timing and AEL distinguished persistent toxicity burden from isolated peak events. This framework may support comparative tolerability assessment when chronic toxicity burden is central to decision-making.
Inter‐software variability of Centiloid quantification in amyloid PET: A head‐to‐head comparison of five software platforms
Zhang, Jun , MD, Miller, Dizdar, Nur, Johnson, Matthew P. , Bilgin, Cem, Kemp, Bradley J. , Durski, Jolanta M. , Lowe, Val, Johnson, Derek R., Burkett, Brian J. , Schwarz, Christopher G. , Bilgin, Cem , Lowe, Val J.

Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring | August 13, 2026 | Volume: 18 | Issue: 3 | Pages: No page available

10.1002/dad2.70443 | PMID 42597411 Get It

Abstract INTRODUCTION Centiloid (CL) scaling standardizes amyloid positron emission tomography (PET) quantification across tracers and platforms; however, variability across software implementations may affect diagnostic classification. This study evaluated inter‐software variability and diagnostic performance across five platforms using identical 1 8 F‐florbetapir datasets. METHODS Retrospectively, 192 patients undergoing 1 8 F‐florbetapir PET/computed tomography (CT) and magnetic resonance imaging (MRI) were analyzed. CL values were generated using four US Food and Drug Administration (FDA) ‐cleared platforms and an in‐house Centiloid standard pipeline. Agreement was assessed using intraclass correlation coefficient, with bias and limits of agreement evaluated by linear modeling and Bland–Altman analysis. Diagnostic performance was assessed using receiver operating characteristic (ROC) analysis and classification against visual interpretation. RESULTS Agreement was excellent (intraclass correlation coefficient [ICC] 0.969; 95%CI 0.961–0.975). Some platforms produced systematically higher CL values versus others slightly lower. LoA reached ± 30 CL. Diagnostic accuracy was high (area under the curve [AUC]: 0.949–0.975), with sensitivity 0.923–0.968 and specificity 0.667–0.806. DISCUSSION Despite excellent agreement, systematic differences persist and may affect classification near thresholds, supporting consistent use of a single processing pipeline.
Clinical Functional Assignment of TPMT and NUDT15 Alleles by the Clinical Pharmacogenetics Implementation Consortium Pharmacogene Curation Expert Panel
Tibben, Bailey M. , Maillard, Maud , Pratt, Victoria M. , Moyer, Ann M. , Figueroa, Debbie M. , Gaedigk, Andrea , Stocco, Gabriele , Schwab, Matthias , Caudle, Kelly E. , Whirl-Carrillo, Michelle , Gaedigk, Andrea , Stocco, Gabriele , Schwab, Matthias , Caudle, Kelly E , Yang, Jun J.J. , Maillard, Maud , Figueroa, Debbie M , Whirl‐Carrillo, Michelle

Clinical Pharmacology & Therapeutics | August 6, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1002/cpt.70433 | PMID 42560154 Get It

The Clinical Pharmacogenetics Implementation Consortium (CPIC) TPMT/NUDT15 Pharmacogene Curation Expert Panel (PCEP) conducted a comprehensive review of clinical, laboratory, and computational evidence to determine the clinical function assignments for TPMT and NUDT15 star alleles. These genes are critical for the metabolism of thiopurines, which are widely used in the treatment of cancer and autoimmune disorders. Standardized allele function assignment is essential for predicting metabolizer phenotypes and pharmacogenetics‐guided thiopurine dosing. The work presented here includes the first designation of decreased function alleles for both TPMT and NUDT15 , reflecting new clinical data that demonstrate partial loss of enzymatic activity and reduced dose tolerance. The panel also reclassified several alleles previously assigned uncertain or unknown function. The functional assignments were informed by a standardized framework incorporating clinical data, such as thiopurine tolerance and toxicity, as well as in vitro protein activity, ex vivo enzymatic measurements, and in silico variant effect prediction tools. These updates enhance the precision of genotype‐to‐phenotype mapping and support more personalized thiopurine therapy across diverse patient populations.
Global Burden of Elevated LDL-C
Collaborators, GBD 2023 LDL Cholesterol, Razo, Christian, DeCleene, Nicole K., Johnson, Catherine O., Stark, Benjamin, LeGrand, Kate, Aalruz, Hasan, Abaraogu, Ukachukwu O., Abdelnabi, Mahmoud, Abd-Elsalam, Sherief, Abdelwahab, Siddig Ibrahim, Abdollahi, Arash, Abdrabou, Mostafa M., Abdul‐Rahman, Toufik , Getahun, Habtamu Abebe, Abiodun, Olumide, Abohashem, Shady, Abonie, Ulric Sena , Abourashed, Nagah M , Abramov, Dmitry, Abrar, Mohammed Mehdi, Farha, Rana Kamal Abu, Abubakar, Bilyaminu, Aburuz, Salahdein, Abushanab, Dina, Adams, Lisa C., Adamu, Nuhu Lawan Lawan, Adegbile, Oluwatobi E , Adegoke, Nurudeen A., Adekola, Saheed Ayodeji, Adeleke, Olumide Thomas , Adesina, Miracle Ayomikun, Afoakwah, Clifford, Afolabi, Aanuoluwapo Adeyimika, Afrashteh, Fatemeh , Afrifa-Yamoah, Ebenezer, Agyemang‐Duah, Williams , Ahmad, Suhaib, Ahmed, Asma , Ahmed, Gasha Salih, Ahmed, Luai A., Ahmed, Mehrunnisha Sharif, Ahmed, Meqdad Saleh , Ahmed, M. , Ahmed, Mushood, Ahmed, Syed Anees, Ahmed, Zohra, Aiyer, Aishwarya, Ajami, Marjan, Akalanka, Kasuni H.M. , Akhtar, Muhammad Nadeem, Akrami, Ashley E, Akyea, Ralph Kwame, Hasan, Syed Mahfuz Al , Zoubi, Mohammad Ahmmad Mahmoud Al, Alahdab, Fares , Al-Ahmad, Mohammad M. , Alajajian, Stephen , Alajlani, Muaaz , Alalwan, Tariq A., Al-Amri, Issa Sulaiman, Alanzi, Turki M., Alarifi, Abdullah, Al-Azzam, Sayer, Albashtawy, Mohammed, Al-Dewik, Nader, Algahtani, Fahad D., Algammal, Abdelazeem M, Alhalaiqa, Fadwa Naji, Ali, Mohammad Daud , Ali, Mohammed Usman, Ali, Rafat, Ali, Syed Shujait, AL-Iede, Montaha, Alipour, Morteza, Al-Jabi, Samah W., Alkhatib, Mayson H. , Allawi, Raad Hatim , Allemailem, Khaled S. , (6837737), Mohammed Z. Allouh, Almahmeed, Wael, Al-Marwani, Sabah , Almazan, Joseph Uy, Alnaeem, Mohmmad Minwer, Alotaibi, Haifa F. F., Alqahtani, Saleh A, Alqudah, Mohammad , Alqudimat, Mohammad R, Al-Qudimat, Ahmad Rajeh, Alrimawi, Intima , Alrousan, Sahel Majed, Alshahrani, Najim Z., Altaany, Zaid, Altaf, Awais, Althobiani, Malik A., Altwalbeh, Diala, Al-Worafi, Yaser Mohammed, Aly, Hany, Alzoubi, Karem H., Al-Zubairi, Adel S., Amafah, Joy, Mohammadi, Masoud Aman, Amini, Saeed, Amini-Salehi, Ehsan, Ananda, Roshan A., Ancuceanu, Robert, Anil, Abhishek, Anjana, Prapti, Anuoluwa, Boluwatife Stephen, Anvari, Saeid, Anwar, Sumadi Lukman, Anyasodor, Anayochukwu Edward , Appati, Walter, Arafa, Elshaimaa A , Aravkin, Aleksandr Y. , Areda, Demelash, Aregawi, Brhane Berhe, Torre, Jorge Arias de la, Arruda, Gustavo Aires , Asghari-Jafarabadi, Mohammad , Ashraf, Saad , Asare, Bernard Yeboah‐Asiamah , Atac, Omer, Athari, Seyyed Shamsadin, Atorkey, Prince , Aurangzeb, Khursheed, Awan, Usman Ayub , Awol, Kemal Lemnuro Lemnuro, Ayala, Camila Ospina , Ayli, Berrak Itir, Azad, A.K.M., Azzam, Ahmed Y., Babiker, Rasha, Badar, Muhammad, Badran, Alaa Aboelnour, Baghlaf, Khlood K., Balabekova, Marina, Balakrishnan, Senthilkumar , Baltatu, Ovidiu Constantin , Banach, Maciej, Bashir, Muhammad Irfan , Bashir, Shahid, Bashiri, Azadeh, Bastan, Mohammad-Mahdi, Bayat, Mahdis , Behera, Surama Manjari , Belayneh, Melesse, Bello, Abdulrahman Babatunde , Belo, Luís, Bhaskar, Sonu, Bizzozero-Peroni, Bruno, Bogale, Sitotaw Kerie, Bolourinejad, Paria , Bonny, Aimé , Carvajal, Alejandro Botero, Bouaoud, Souad, Britton, Gabrielle, Bustanji, Yasser, Butt, Zahid A., Cao, Yu, Catapano, Alberico L., Cegolon, Luca, Cembranel, Francieli , Chadwick, Joshua , Chau, Lam Duc, Chaudhary, Anis Ahmad, Chen, An-Tian, Chen, Hana, Chen, Haowei , Cheng, Haojin, Cheung, Ka Ching , Chew, Nicholas WS, Chi, Gerald, Cho, William C. S., Chong, Bryan, Chopra, Deepti, Chopra, Shivani , Cicero, Arrigo Francesco Giuseppe, Criqui, Michael H., Cruz-Martins, Natalia, Dahabiyeh, Lina, Khatri, Bishal Dahal , Dalakoti, Mayank, D’Amico, Emanuele, Damtie, Endalamaw Tesfa, Dandona, Lalit , Dandona, Rakhi, D’Anna, Lucio , Danpanichkul, Pojsakorn, Dardas, Latefa Ali , Das, Sayan Kumar, Davletov, Dimash, Dergaa, Ismail, Derseh, Hunegnaw Almaw , Desale, Aragaw Tesfaw, Devanbu, Vinoth Gnana Chellaiyan, Devegowda, Devananda, Dewan, Syed Masudur Rahman, Dhali, Arkadeep , Dhungel, Bibha, Silva, Diana Dias da, Didehvar, Kimia, Ding, Xueting, Do, Thanh Chi, Do, Thao Huynh Phuong, Dohare, Sushil, Dong, Dachuan, D’Oria, Mario, Dorostkar, Fariba, Doshi, Ojas Prakashbhai, Dresse, Menayit Tamrat , Du, Mi, Ebraheim, Lamiaa Labieb Mahmoud, Edeh, Cynthia , Eftekhari, Behrad, Sedeh, Ashkan Eighaei , Ekholuenetale, Michael , Arab, Rabie Adel El , Eldaboush, Ahmed, El-Dahiyat, Faris , Elhoumed, Mohamed, Elmeligy, Omar Abdelsadek Abdou, Elmonem, Mohamed A., Elmoselhi, Adel B., Elnaem, Mohamed Hassan , Eltahawy, Abdelgawad Salah, Etaee, Farshid, Fakhradiyev, Ildar , Fakorede, Sodiq, Farasani, Abdullah , Fareed, Mohammad , Farhana, Aisha, Faris, MoezAlIslam Ezzat Mahmoud, Farsi, Farima , Fatima, Zareen, Fazylov, Timur, Fekadu, Ginenus , Ferreira, Nuno, Fischer, Florian, Fonzo, Marco , Gadanya, Muktar A., Galali, Yaseen, Ganesh, Balasubramanian , Gangachannaiah, Shivaprakash, Gao, Dingwei, Garcia-Azorin, David, Garg, Paarth, Gautam, Rupesh K., Gaye, Bamba , Gebresilassie, Mizan Habtemichael, Gete, Kalab Yigermal , Ghadirian, Fataneh, Ghaffari, Kazem , Ghamkhar, Arin, Gharaibeh, Lobna, Ghasemi, Mohammadreza, Ghimire, Sailaja, Gil, Artyom Urievich, Gilani, Syed Abdullah , Gohari, Kimiya, Gohil, Megha Nishith , Golechha, Mahaveer, Goleij, Pouya , Golmohammadi, Melika , Goyal, Aman, Grada, Ayman, Grover, Ashna , Gu, Long, Gufue, Zenawi Hagos , Guo, Zheng, Gupta, Sapna , Gurgoglione, Filippo Luca, Haghtalab, Arian, Nam, Nguyen Hai, Hailu, Kirubel Tesfaye , Halder, Pritam, Hamdy, Nadia M., Hamidi, Hossein , Hamidi, Samer, Hamoudi, Rifat, Harsini, Sara, Hasnain, Md Saquib , Hassan, Ikrama, Hassan, Nageeb, Hassan, Treska S , Ahmed, Omed Hassan , Hebert, Jeffrey J., Helmy, Yosra A. , Hiraike, Yuta, Holla, Ramesh, Hoseinzadeh, Mehdi, Hostiuc, Mihaela , Hostiuc, Sorin, Hotwani, Priya, Hu, Yifei, Huang, Junjie, Huang, Yu-Song, Hushmandi, Kiavash, Hussein, Dursa, Hussein, Mohammed Asif , Ibrahim, Ismail A., Ibrayeva, Anel, Ikiroma, Adalia , Ikram, Jibran, Ilic, Irena M., Imam, Mohammad Tarique , Imani, Masoud, Imodoye, Sikiru Opeyemi, Imoh, Lucius Chidiebere , Ionescu, Andreea Iuliana, Ionescu, Radu Tudor, Iqhrammullah, Muhammad, Ishaqui, Azfar Athar, Islek, Duygu , ISMAIL, NAHLAH ELKUDSSIAH, Ismoldayev, Yerlan, Iwagami, Masao , Iyer, Mahalaxmi, Izquierdo-Condoy, Juan S.S., Jafari-Khounigh, Ali , Jahanshahi, Ali, Jahrami, Haitham , Jakovljevic, Mihajlo, Jamal, Armaan, Jamali, Navid, Jamaluddin, Jazlan , Jamshidi, Masoud, Jansen, Robin , Jarrahi, Esmaeil , Javaid, Syed Sarmad , Jawaid, Talha, JEBASINGH, FELIX, Jemal, Mohammed, Ji, Zixiang , Jibat, Nathan T., Jin, Wenyi , Jokar, Mohammad, Joseph, Nitin, Raj, Jesu Vijay Sheldon Joseph Michael, Joshi, Krupal, Joshua, Charity Ehimwenma, Jung, Sang-Hyuk, K, Vaishali, Kadir, Dler Hussein , Kahe, Farima, Kalani, Rizwan, Kalra, Sanjay, Kamenova, Saltanat, Kamorudeen, Ramat T., Kamyshnyi, Oleksandr, Kansal, Subham, Kantar, Rami S., Kar, Debasish , Karakasis, Paschalis, Karimi, Aliasghar, Behnagh, Arman Karimi , Karun, Sadanand , Kazemian, Sina, Kesse-Guyot, Emmanuelle, Khaleel, Anas, Khalid, Nauman, Khalid, Sidra, Khalil, Anees Ahmed , Khan, Ajmal, Khan, Md Abdullah Saeed, Khan, Moien AB, Khan, Muhammad Hamza , Khan, Serab, Khan, Sumaiya, Khan, Yusuf S. , Kheirallah, Khalid A, Khoshvaght, Samira, Khosravi, Sepehr, Kim, Hye Jun, Kim, Kwanghyun, Kisa, Adnan, Kishore, Ladli, Kokkorakis, Michail, Kondybayeva, Aida, Krishan, Kewal, Kua, Chong-Han, Kuddus, Mohammed, Kulimbet, Mukhtar , Kulkarni, Vishnutheertha, Kumar, Dewesh , Kumar, Nitesh, Kumar, Sanjay Kirshan, Kunutsor, Setor K., Kurpad, Krishna Prasad , Kusuma, Dian, Lahariya, Chandrakant, Lai, Daphne Teck Ching , Lai, Hanpeng , Lajunen, Timo, Lakanova, Balzhan, Lallukka, Tea, Larsson, Anders O., Le, Duc Tin , Le, Thao T. , Le, Thoa, Le, Trang Thi Bich , Ledda, Caterina, Lee, Hayeon, Lee, Sang-woong, Lee, Sergey Vadimovich, Lee, Seung Won, Leivaditis, Vasileios, Lema, Gebretsadik Kiros , Lemma, Dawit Alemu, Lenjisa, Jimma, Lewis, Mitchelle Shilpa , Li, Chengfeng , Li, Xingang , Li, Yongze, Lim, Lee-Ling, Lindholm, Daniel , Liu, Haipeng , Liu, Xianliang, Liu, Xuefeng, Liu, Yubo, Livingstone, Katherine M., Llanaj, Erand , Lokunarangoda, Niroshan Chandrajith, López-Gil, José Francisco, Lui, Pauline Po Yee, Luo, Peng, Lv, Lei, Lytvyak, Ellina, Ma, Kevin Sheng-Kai, Mabrok, Mahmoud, Machoy-Rakoczy, Monika , Madinehzad, Seyed Ataollah , Maffia, Pasquale, Gomez, Javier A. Magaña, Mahmood, Nozad Hussein, Malik, Md. Zubbair, Malta, Deborah Carvalho, MAMAND, DOSTE RASHID, Maniya, Muhammad Talha, Mansoor, Farheen, Mansourian, Marjan, Manzoor, Shaista, Marghani, Basma Hamed, Martinez-Piedra, Ramon, Martini, Santi, Martorell, Miquel, März, Winfried, Marzouk, Sammer, Masi, Stefano, Masrouri, Soroush , Maude, Richard J. , Mavrovounis, Georgios, McPhail, Steven M., Mendoza, Walter, Menezes, Ritesh G., Mengistie, Emiru Ayalew, Menon, Tara P., Mestrovic, Tomislav, Mettananda, Chamila Dinushi Kukulege, Metwally, Mohamed M.M., Jonasson, Junmei Miao , Mikrajab, Muhammad Agus Naufal, Minhas, Abdul Mannan Khan, Mirrakhimov, Erkin M., Mitra, Sayan , Mitra, Tridip, Modi, Dhruti, Mohamed, Mona Gamal, Ahmed, Khabab Abbasher Hussien Mohamed, Mohammad, Ameen Mosa , Mohammadi, Saeed, Mohammed, Omer, Mohan, Syam , Molla, Tewodros Shibabaw, Molokhia, Mariam, Moni, Mohammad Ali, Namin, Sara Montazeri , Morovvati, Mahdis, Heris, Reza Mosaddeghi, Motappa, Rohith, Mousavi, Seyed Ahmad , Kiasary, Seyed Mohamad Sadegh Mousavi, Yousefi, Kimia Mozahheb , Mubarik, Sumaira, Munkhsaikhan, Yanjinlkham, Musa, Sani, Mwita, Julius C., Nabipoorashrafi, SeyedAli, Nagarajan, Ahamarshan Jayaraman , Naik, Ganesh R., Naik, Hiten, Nainu, Firzan, Nartey, Yvonne , Nassar, Mahmoud, Natto, Zuhair S., Naureen, Zakira, Nawaiseh, Hala Khaled, Nayak, Biswa Prakash, Nayak, Vinod C., Nazari, Mojdeh, Ndakotsu, Andrew , Nega, Amanuel Tebabal , Nega, Mulata H., Negash, Abigia Ashenafi, Negoi, Ionut, Nguyễn, Cao Duy, Nguyen, Cuong Tat , Nguyen, Hau Thi Hien, Nguyen, Nghia Phu , Nguyen, Phat Tuan , Nguyen, Van Thanh, Niazi, Robina Khan, Nomura, Shuhei , Noreen, Mamoona , Nawsherwan, Noubiap, Jean Jacques, Nugen, Fred, Nur, Aqsha, Odediji, Saheed Adeyinka, Ogunmodede, O.S., Ojedoyin, Olusegun Olatunji , Ojo, Oluwafemi Adeleke , Okati-Aliabad, Hassan, Oliveira, Gláucia Maria Moraes, Olorukooba, Abdulhakeem Abayomi, Ong, Qi Chwen, Orru, H, Ortiz, A., Ortiz-Prado, Esteban, Osborne, Augustus, Osei, George Nkrumah , Ostrominski, John W. , Oumer, Abdu, Ouyahia, Amel, Owolabi, Mayowa O., Oyebola, Kolapo, Ozsahin, Ilker, Anand, Mahesh Padukudru, Palicz, Tamás , Panda, Sujogya Kumar , Pandi-Perumal, Seithikurippu R., Panos, Georgios D., Papadimopoulos, Ilias, Parija, Pragyan Paramita , Parikh, Romil R., Pascucci, Eleonora, Pasovic, Maja , Passera, Roberto, Patel, Mitesh, Patel, Niki Rut, Patel, Satyananda, Patil, Ashlesh, Patil, Shankargouda, Patoulias, Dimitrios, Pattnaik, Snigdha, Toroudi, Hamidreza Pazoki, Pekarcikova, Jarmila, Peprah, Prince, Pereira, Gavin, Pirera, Edoardo , Plotnikov, Evgenii, Poluru, Ramesh, Prasad, Manya, Prashant, Akila, Prates, Elton Junio Sady, Pugliese, Nicola Riccardo, Puvvula, Jagadeesh, Qi, Xiang, Qureshi, Ali, Radhakrishnan, Venkatraman, Raghav, Pankaja, Raghav, Yashpal Singh Raghav, Raghuveer, Pracheth , Rahim, Fakher , Rahim, Hawbash Mohammed-Amin, Rahimi, Sajjad, Rahman, Fryad Majeed, Rahman, M Sajjadur , Rahman, Mohammad Hifz Ur, Rahman, Mosiur, Rajendran, Judah, Rajput, Prashant, Ramasamy, Chitra, Ramasamy, Shakthi Kumaran, Rao, Asad Gul , Rao, Mithun , Rao, Sowmya J, Rasouli-Saravani, Ashkan, Rath, Shree, Rathi, Isha, Rawaf, David Laith , Rawaf, Salman, Reddy, Murali Mohan Rama Krishna, Rezaei, Mina, Rezaei, Nazila, Rezaeian, Mohsen , Rodriguez, Jefferson Antonio Buendia, Roever, Leonardo, Ross, Allen Guy Patrick, Rubeshkumar, Polani, Rwegerera, Godfrey Mutashambara , Saad, Aly M. A., Sabet, Cameron John, Sadarangani, Kabir P., Rafiei, Seyed Kiarash Sadat, Sadeghi, Ehsan, Sadeghi, Erfan, Sadeghi, Masoumeh, Sadek, Bassem, Sadek, Mustafa, Sadr, Hossein, Saeb, Mohammad Reza, Saeed, Umar, Saeedi, Maryam , Safiullah, Muhammad , Sahebkar, Amirhossein, Sajadi, S Mohammad, Saleh, Mohamed A., Salehi, Mahdi , Salimi, Sohrab, Samargandy, Saad, Samy, Abdallah M., Saravanan, Aswini , Sarfo, Jacob Owusu, Sarode, Gargi Sachin, Sarode, Sachin C., Sathian, Brijesh, Far, Mehrdad Savabi, Schlaich, Markus P., Schuermans, Art, Sejben, Anita, Semreen, Mohammad H., Senol, Yigit Can, Sessa, Francesco, Sewor, Christian , Seylani, Allen, Shahrahmani, Fatemeh, Shahwan, Moyad Jamal, Sham, Sunder, Shan, Dan, Sharifan, Amin , Sharma, Kamal, Sharma, Ravi Kumar, Sharma, Ujjawal , Shehzadi, Somia , Shetty, Mahabalesh, Shetty, Pavanchand H, Shi, Fanchao , Shi, Huizhong , Shi, Yongfeng, Shiri, Rahman , Shittu, Aminu, Shiue, Ivy, Shoaib, Ambreen, Shool, Sina, Shorofi, Seyed Afshin, Shuval, Kerem, Sia, Ching-Hui, Silva, Luís Manuel Lopes Rodrigues, Singh, Amit, Singh, Baljinder, Singh, Harmanjit, Singh, Harpreet, Singh, Lucky, Singh, Paramdeep, Singh, Siddharth , Singh, Sunil Kumar, Singh, Surjit, Singh, Vanshika , Sinha, Mukesh Kumar, Skryabin, Valentin Yurievich, Sokhal, Balamrit Singh , Sood, Prashant , Soraneh, Soroush , Sorensen, Reed J D , Srivastav, Prateek , Stanikzai, Muhammad Haroon , Starodubova, Antonina V., Stubbs, Peter, Suhag, Alisha, Sulaiman, Sahabi K., Odidi, Muritala Suleiman, Sulistiyorini, Desy , Sun, Jing , Sun, Zhong, Szarpak, Lukasz, Ty, Sree Sudha, Damavandi, Payam Tabaee, Tabatabaei, Seyyed Mohammad, Tabatabai, Shima, Tagiisuran, Balamurugan, Ali, Eman Taha Osman, Soodejani, Moslem Taheri, Taiba, Jabeen, Tajabadi, Shima, Talic, Stella, Talukder, Ashis, Adugna, Dessalegn Tamiru, Tampa, Mircea, Tan, Jianye, Tanabayeva, Dariga, Tanashat, Mohammad , Tang, Jiahao , Tantisattamo, Ekamol, Tariq, Saba, Temsah, Reem, Teramoto, Masayuki, Tesfamariam, Wegen Beyene , Tewari, Jay , Thakar, Vidhi, Thangavelu, Lakshmi, Tharwat, Ismaeel, Thiruvengadam, Muthu , Thomas, Nikhil Kenny, Ticoalu, Jansje Henny Vera, Tiwari, Krishna, Tleshev, Madi, Tonelli, Marcello, Topór-Mądry, Roman , Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Tran, An Thien, Tran, Thang Huu, Duc, Nguyen Tran Minh , Tricò, Domenico , Tse, Gary, Tseriotis, Vasilis-Spyridon, Tualeka, Abdul Rohim , Tye, Sok Cin , Ullah, Riaz, Umair, Muhammad, Umar, Lawan , Ozsahin, Dilber Uzun, Uzunçıbuk, Hande, Vaithinathan, Asokan Govindaraj , Vakili, Omid , Eynde, Jef Van den, Varghese, Joe, Vellingiri, Balachandar, Verma, Poonam, Villalobos-Daniel, Victor E., Vlassov, Vasily, Wang, Nelson, Wang, Qingzhi, Wang, Wanzhou, Wang, Wei, Wang, Yanzhong, Wang, Zhihua, Wani, Tanveer A.A., Wei, Melissa Y., Weintraub, Robert G., Wibowo, Yohanes Cakrapradipta, Wickramasinghe, Dakshitha Praneeth, Wickramasinghe, Nuwan Darshana, Witts, William Kwame , Wonde, Tewodros Eshete , Wongsin, Utoomporn , Wu, Peng, Xiao, Guangqin, Xie, Wanqing , Xu, Suowen, Xu, Wanqing, Yadav, Vikas , Yahoo, Saba, Yang, Hanwen, Yano, Yuichiro , Yao, Haiqiang , Yarahmadi, Amir, Yin, Dehui , Yismaw, Yazachew Engida, Yon, Dong Keon, Yu, Chuanhua, Yu, Elaine A., Yu, Hairui , Yu, Yong , Yuan, Quan, Zafar, Mubashir , Zaghampour, Manijeh, Zamora, Nelson, Zanghì, Aurora , Zargar, Seema , Zeariya, Mohammed G M, Zeru, Eyael M, Zhang, Beijian, Zhang, Hanyu, Zhang, Julio Min Fei, Zhang, Yunquan, Zhang, Zhichang, Zhanuzakov, Murat , Zhao, Zhongyi, Zheng, Ming‐Hua , Zhong, Anthony , Zhong, Claire Chenwen, Zhou, Hao, Zhou, Jiayan, Zhou, Xiao-Dong, Zhu, Zhengyang , Zhumagaliuly, Abzal, Zitoun, Osama A. , Zoghi, Ghazal , Zoromba, Mohamed Ali, Zumla, Alimuddin, Zyoud, Sa’ed H., Hay, Simon I., Mokdad, Ali H., Murray, Christopher J. L., Roth, Gregory A., Sun, Zhong , Hay, Simon I , Roever, Leonardo , Krishan, Kewal , Moni, Mohammad Ali , Buendía, Jefferson Antonio , Badar, Muhammad , Wickramasinghe, Nuwan Darshana , Nassar, Mahmoud , Dewan, Syed Masudur Rahman , Naik, Ganesh R. , Wang, Yanzhong , Rath, Shree , Karakasis, Paschalis , Zheng, Ming-Hua , Taiba, Jabeen , Razo, Christian , DeCleene, Nicole K., LeGrand, Kate E , Abaraogu, Ukachukwu Okoroafor , ElHafeez, Samar Abd , Abdelmasseh, Michael , Abdelnabi, Mahmoud , Abd‐Elsalam, Sherief , Elshenawy, Rasha Abdelsalam , Abdelwahab, Siddig İbrahim , Abdolizadeh, Ali , Abdollahi, Arash, Abdoun, Meriem , Abdrabou, Mostafa M. , Abdulah, Deldar Morad , Abdullahi, Auwal , Shenkut, Melese, Abiodun, Olugbenga Olusola , Abiodun, Olumide A , Abohashem, Shady , Abtahi, Dariush , Farha, Rana Kamal Abu , Abubakar, Bilyaminu , Abuhelwa, Ahmad Y. , Abukhadijah, Hana J , Aburuz, Salahdein , Adamu, Nuhu Lawan , Adane, Mesafint Molla , Addo, Isaac Yeboah , Adedokun, Kamoru Ademola , Adekola, Saheed Ayodeji, Adesina, Miracle Ayomikun , Adisu, Molalign Aligaz , Adnan, Mohd , Afoakwah, Clifford , Afolabi, Aanuoluwapo Adeyimika, Afrifa‐Yamoah, Ebenezer , Afzal, Saira , Agordoh, Percival Delali , Ahmad, Aqeel , Ahmad, Khabir , Ahmad, Sajjad , Ahmed, Gasha Salih, Ahmed, Nesredin , Ajami, Marjan , Akhtar, Muhammad Nadeem , Akindele, Mukadas Oyeniran , Akkaif, Mohammed Ahmed , Akyea, Ralph Kwame , Zoubi, Mohammad Ahmmad Mahmoud Al, Alalwan, Tariq A. , Al‐Aly, Ziyad , Al-Amri, Issa Sulaiman , Alanzi, Turki Matar Khalaf, Al-Ashwal, Fahmi Y. , Al‐Azayzih, Ahmad , Al-Azzam, Sayer , Al-Bashaireh, Ahmad M. , ALBashtawy, Mohammed , Aleidi, Shereen M. , Algahtani, Fahad D. , AlHabib, Khalid F. , Ali, Abid , Ali, Asgar , Ali, Bassam R. , Al‐Iede, Montaha , Alif, Sheikh Mohammad , Alipour, Morteza, Al‐Jabi, Samah W. , Aljunid, Syed Mohamed , Alkubati, Sameer Abdulmalik , Almagharbeh, Wesam Taher , Almahmeed, Wael , Almazan, Joseph Uy , Alniss, Hasan Yaser , Alomari, Mahmoud A. , Alotaibi, Haifa F. , Alqahtani, Saleh A. , Alqudimat, Mohammad R. , Al-Qudimat, Ahmad Rajeh , Al‐Raddadi, Rajaa , Alsbou, Mohammed , Alshahrani, Najim Zafer , Al-Shami, Ali Salman , Altaf, Awais , Althobiani, Malik A , Alwafi, Hassan , Al‐Worafi, Yaser Mohammed , Aly, Hany Z. , Al‐Zalabani, Abdulmohsen H. , Alzoubi, Abdallah , Alzoubi, Karem Hasan , Amafah, Joy, Amin, Amr , Amini, Saeed, Amini‐Salehi, Ehsan , Amusa, Ganiyu , Ang, Song Peng , Anieto, Ebuka Miracle , Anil, Abhishek , Anjana, Dr. Prapti, Anvari, Saeid, Appati, Walter , Arabloo, Jalal , Arafat, Mosab , Areda, Demelash, Arefnezhad, Reza , Torre, Jorge Arias de la, Aripov, Timur , Arockiaraj, Jesu , Asdaq, Syed Mohammed Basheeruddin , Ashraf, Syed Amir , Ashraf, Tahira , Ataç, Ömer , Athar, Mohammad , Athari, Seyyed Shamsadin , Aurangzeb, Khursheed , Awan, Sana Javaid , Awol, Kemal Lemnuro, Awotidebe, Adedapo Wasiu , Aylı, Berrak Itır , Azarboo, Alireza , Aziz, Sadat Abdulla , Azzolino, Domenico , Babu, Abraham Samuel , Babu, Giridhara R. , Badiye, Ashish , Baghlaf, Khlood K , Baig, Atif Amin , Bakhshali, Mohamad Amin , Banach, Maciej , Banik, Palash Chandra , Barqawi, Hiba Jawdat , Barrow, Amadou , Barua, Lingkan , Bashir, Shahid , Bashiri, Azadeh , Bastan, Mohammad‐Mahdi , Bayih, Mulat Tirfie , Beeraka, Narasimha Murthy , Begum, Tahmina , Behera, Priyamadhaba , Behnam, Babak , Ramírez, Diana Fernanda Bejarano , Belo, Luı́s , Berihun, Abiye Assefa , Bhattacharjee, Priyadarshini , Bhatti, Gurjit Kaur , Bhatti, Jasvinder Singh , Biswas, Atanu , Biswas, Bijit , Bizzozero‐Peroni, Bruno , Bodur, Mahmut , Bogale, Sitotaw Kerie , Bohn, Lucimére , Boloor, Archith , Carvajal, Alejandro Botero , Boudalia, Sofiane , Bugiardini, Raffaele , Busch, Felix , Bustanji, Yasser, Campos, Luciana Aparecida , Catapano, Alberico Luigi , Cegolon, Luca , Cenko, Edina , Cerin, Ester , Chakraborty, Chiranjib , Chandika, Rama Mohan , Chandrasekar, Eeshwar K , Chandrasekaran, Baskaran , Chattu, Vijay Kumar , Chaudhary, Anis Ahmad , Chaudhuri, Sirshendu , Cheema, Asad Ali Ahmed , Chichagi, Fatemeh , Ching, Patrick R , Cho, William C.S., Choi, Dong‐Woo , Chong, Bryan , Chopra, Deepti , Chopra, Hitesh , Choudhari, Sonali Gajanan , Chu, Dinh‐Toi , Chukwu, Chidozie Williams , Chung, Sheng‐Chia , Chung, S. Y. , Cicero, Arrigo F.G. , Cosma, Claudia , Criqui, Michael H. , Dadras, Omid , Dai, Xiaochen , Dai, Zhaoli , Dalakoti, Mayank , D’Amico, Emanuele , Tesfa, Endalamaw , Danpanichkul, Pojsakorn , Darcho, Samuel Demissie , Davletov, Dimash , Davletov, Kairat , Dejenie, Tadesse Asmamaw , Bo’, Cristian Del , Delgado‐Enciso, Iván , Denova‐Gutiérrez, Edgar , Dergaa, Ismail , Dervišević, Emina , Devegowda, Devananda , Dewan, Syed Masudur Rahman , Dhimal, Meghnath , Dhungel, Bibha , Do, Thanh Chi, Phuong, Thao Huynh, Doshi, Ojas Prakashbhai , Doshi, Rajkumar , Dourado, Paulo Magno Martins , Dowou, Robert Kokou , Du, Mi , Duncan, Bruce Bartholow , Durães, André Rodrigues , Ebohon, Osamudiamen , Eftekhari, Behrad , Eladl, Mohamed Ahmed , Eldaboush, Ahmed , Elgendy, Islam Y. , Elhadi, Muhammed , El‐Huneidi, Waseem , Elmonem, Mohamed A. , Elmoselhi, Adel B. , Fabin, Natalia , Fadaka, Adewale Oluwaseun , Fagbamigbe, Adeniyi Francis , Fakorede, Sodiq , Fatima, Zareen , Fayaz, Mohammad , Fazylov, 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Yuta , Holla, Ramesh , Hostiuc, Sorin , Htay, Mila Nu Nu , Huang, Junjie, Hushmandi, Kiavash , Hwang, Bing‐Fang , Ibitoye, Segun Emmanuel , Ibrahim, Khalid S. , Ibrayeva, Anel , Ikram, Jibran, Ilesanmi, Olayinka Stephen , Ilić, Irena , Ilić, Milena , Imodoye, Sikiru O. , Inbaraj, Leeberk Raja , Ionescu, Radu Tudor, Iqhrammullah, Muhammad , Irham, Lalu Muhammad , Ishaqui, Azfar Athar , Ismail, Nahlah Elkudssiah , Ismoldayev, Yerlan, Isola, Gaetano , Izquierdo‐Condoy, Juan S. , Jacob, Jaison , Jahanshahi, Ali , Jamal, Armaan , Jamali, Navid , James, Jerin , Jamshidi, Masoud , Jawaid, Talha, Jayasinghe, Yovanthi Anurangi , Jemal, Mohammed , Jeong, Seogsong , Jeswani, Bijay Mukesh , Jibat, Nathan Tolemariam , Jokar, Mohammad , Joó, Tamás , Joseph, Akaninyene Paul , Joseph, Mickaël Antoine , Joseph, Nitin , Joshi, Krupal , Jürisson, Mikk , K, Vaishali , Kakkar, Ashish Kumar , Kalani, Rizwan , Kalavani, Khalil , Kalra, Sanjay , Kamorudeen, Ramat T. , Kamyshnyi, Oleksandr , Kanaan, Saddam Fuad , Kanmodi, Kehinde Kazeem , Kantar, Rami S. , Kapoor, Neeti , Karajizadeh, Mehrdad , Karakasis, Paschalis , Karasneh, Reema A. , Kashoo, Faizan , Kashyap, Manoj Kumar , Kausar, Mohd Adnan , Kazemian, Sina , Kebede, Yabets Tesfaye , Kesse‐Guyot, Emmanuelle , Khademi, Reza , Khader, Yousef , Khajuria, Himanshu , Khaleel, Anas , Khalid, Sidra , Khalili, Anita , Khalili, Pantea , Khan, Maseer , Khan, Mohammad Idreesh , Khasbage, Sameer Uttamaro , Khatatbeh, Moawiah Mohammad , Khosla, Pavan , Khosravi, Sepehr , Kimokoti, Ruth W , Kısa, Adnan , Kishore, Ladli , Kivimäki, Mika , Kokkorakis, Michail , Kolahi, Ali‐Asghar , Kompani, Farzad , Kondybayeva, Аida , Korzh, Oleksii , Kostev, Karel , Laxminarayana, Sindhura Lakshmi Koulmane , Kua, Chong-Han , Kuddus, Mohammed , Kumar, Chandan , Kumar, G Anil , Kumar, Jogender , Kumar, Laksh , Kundu, Amartya , Kundu, Satyajit , Kunutsor, Setor K. , Kurniasari, Maria Dyah , Kytö, Ville , Lahariya, Chandrakant , Lakanova, Balzhan, Lantos, Tamás , Larebo, Yilma Markos , Lasrado, Savita , Lee�, HwaMin , Lee, Wei‐Chen , Leivaditis, Vasileios , Lenjisa, Jimma Likisa , Li, Ming‐Chieh , Li, Qiang , Li, Shaojie , Lim, Lee-Ling , Lodhi, Madeeha Shahzad , Lokunarangoda, Niroshan Chandrajith , López-Gil, José Francisco , Lorkowski, Stefan , Lucchetti, Giancarlo , Lui, Pauline Po Yee , Lv, Lei , Lytvyak, Ellina , Amin, Hawraz Ibrahim M. , Maffia, Pasquale , Magaña‐Gómez, Javier A. , Mahalleh, Mehrdad , Malik, Ahmad Azam , Malik, Tabarak , Malta, Déborah Carvalho , Mamand, Doste R. , Maniya, Muhammad Talha , Mannethodi, Kamaruddeen , Mansoor, Farheen, Mansourian, Marjan , Maqsood, Kaleem , Marateb, Hamid Reza , Marghani, Basma H. , Marino, Mirko , Martínez, Ramón , Martini, Daniela , Martini, Santi , Martorell, Miquel , März, Winfried , Marzouk, Sammer , Masi, Stefano , Mathur, Neeta , Matozinhos, Fernanda Penido , Mattiello, Rita , Mavrovounis, Georgios , McPhail, Steven , Mehto, Subhash , Meles, Hadush Negash , Menezes, Godfred Antony , 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P. , Zhong, Claire Chenwen , Zhou, Xiao-Dong, Zhumagaliuly, Abzal , Zoromba, Mohamed Ali , Zumla, Alimuddin I. , Zyoud, Ahed H. , Zyoud, Shaher H. , Mokdad, Ali H. , Murray, Christopher J. L., Roth, Gregory A.

JAMA | July 29, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1001/jama.2026.8628 | PMID 42525403 Get It

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.