[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119257-en":3,"doc-seo-119257-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119257,7971461740886,"Theodore","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","Circulating miRNAs and Machine Learning for Lateralizing Primary Aldosteronism - Research article summary","Distinguishing unilateral from bilateral primary aldosteronism is essential because treatment strategies differ, yet adrenal venous sampling is invasive and can be difficult to interpret. This study evaluates whether circulating microRNAs (miRNAs) combined with machine learning can identify laterality. Plasma profiling was performed on samples collected during adrenal venous sampling, followed by bioinformatics and miRNA validation using RT-qPCR. A neural-network approach supported feature selection and comparison, and deep learning performed classification across a validation cohort.","Zurich Open Repository and Archive  \nUniversity of Zurich  \nUniversity Library Strickhofstrasse 39  \nCH-8057 Zurich [www.zora.uzh.ch](www.zora.uzh.ch)  \nYear: 2024  \nCirculating miRNAs and Machine Learning for Lateralizing Primary Aldosteronism  \nVékony, Bálint ; Nyirő, Gábor ; Herold, Zoltan ; Fekete, János ; Ceccato, Filippo ; Gruber, Sven ; Kürzinger, Lydia; Parasiliti-Caprino, Mirko ; Bioletto, Fabio ; Szücs, Nikolette ; Doros, Attila ; Szeredás, Bálint Kende ; Syed Mohammed Nazri, Siti Khadijah ; Fell, Vanessa ; Bassiony, Mohamed ; Dank, Magdolna ; Azizan, Elena Aisha ;  \nBancos, Irina ; Beuschlein, Felix ; Igaz, Peter  \nDOI: [https://doi.org/10.1161/HYPERTENSIONAHA.124.23418](https://doi.org/10.1161/HYPERTENSIONAHA.124.23418)  \nPosted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: [https://doi.org/10.5167/uzh-267257](https://doi.org/10.5167/uzh-267257)  \nJournal Article Published Version  \nThe following work is licensed under a Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4 .0) License.  \nOriginally published at:  \nVékony, Bálint; Nyirő, Gábor; Herold, Zoltan; Fekete, János; Ceccato, Filippo; Gruber, Sven; Kürzinger, Lydia; Parasiliti-Caprino, Mirko; Bioletto, Fabio; Szücs, Nikolette; Doros, Attila; Szeredás, Bálint Kende; Syed Mohammed Nazri, Siti Khadijah; Fell, Vanessa; Bassiony, Mohamed; Dank, Magdolna; Azizan, Elena Aisha; Bancos, Irina; Beuschlein, Felix; Igaz, Peter (2024) . Circulating miRNAs and Machine Learning for Lateralizing Primary Aldosteronism. Hypertension, 81(12):2479-2488 .  \nDOI: [https://doi.org/10.1161/HYPERTENSIONAHA.124.23418](https://doi.org/10.1161/HYPERTENSIONAHA.124.23418)  \nDownloaded from [http://ahajournals.org by on January 6](http://ahajournals.org by on January 6), 2025  \nHypertension  \nORIGINAL ARTICLE  \n| Circulating miRNAs and Machine Learning for Lateralizing Primary Aldosteronism\u003Cbr>Bálint Vékony, Gábor Nyirő, Zoltan Herold, János Fekete, Filippo Ceccato, Sven Gruber, Lydia Kürzinger, Mirko Parasiliti-Caprino, Fabio Bioletto, Nikolette Szücs, Attila Doros, Bálint Kende Szeredás,\u003Cbr>Siti Khadijah Syed Mohammed Nazri, Vanessa Fell, Mohamed Bassiony, Magdolna Dank, Elena Aisha Azizan, Irina Bancos, Felix Beuschlein, Peter Igaz\u003Cbr>BACKGROUND: Distinguishing between unilateral and bilateral primary aldosteronism, a major cause of secondary hypertension, is crucial due to different treatment approaches. While adrenal venous sampling is the gold standard, its invasiveness, limited availability, and often dif cult interpretation pose challenges. This study explores the utility of circulating microRNAs (miRNAs) and machine learning in distinguishing between unilateral and bilateral forms of primary aldosteronism.\u003Cbr>METHODS: MiRNA pro ling was conducted on plasma samples from 18 patients with primary aldosteronism taken during adrenal venous sampling on an Illumina MiSeq platform. Bioinformatics and machine learning identi ed 9 miRNAs for validation by reverse transcription real-time quantitative polymerase chain reaction. Validation was performed on a cohort consisting of 108 patients with known subdifferentiation. A 30-patient subset of the validation cohort involved both adrenal venous sampling and peripheral, the rest only peripheral samples. A neural network model was used for feature selection and comparison between adrenal venous sampling and peripheral samples, while a deep-learning model was used forclassi cation.\u003Cbr>RESULTS: Our model identi ed 10 miRNA combinations achieving >85% accuracy in distinguishing unilateral primary aldosteronism and bilateral adrenal hyperplasia on a 30-sample subset, while also con rming the suitability of peripheral samples for analysis. The best model, involving 6 miRNAs, achieved an area under curve of 87.1% . Deep learning resulted in 100% accuracy on the subset and 90.9% sensitivity and 81.8% speci city on all 108 samples, with an area under curve of 86. 7% .\u003Cbr>CONCLUSIONS: Mac","cbCaihXfxARJ4lpL","https://ap.wps.com/l/cbCaihXfxARJ4lpL","pdf",723731,1,11,"English","en",105,"# Background\n## Methods\n## Results\n## Conclusions\n# Key concepts","[{\"question\":\"Why is laterality determination in primary aldosteronism clinically important?\",\"answer\":\"Unilateral and bilateral primary aldosteronism require different treatment approaches. Accurate lateralization therefore guides appropriate therapy and improves patient management.\"},{\"question\":\"How were circulating miRNAs measured and validated?\",\"answer\":\"Plasma miRNA profiling was conducted on samples collected during adrenal venous sampling, using an Illumina MiSeq platform. Nine miRNAs were selected for validation by RT-qPCR.\"},{\"question\":\"What performance did the machine learning models achieve?\",\"answer\":\"The best model using six miRNAs achieved an AUC of 87.1% in a 30-sample subset. Deep learning reached 100% accuracy on the subset and, across 108 samples, showed 90.9% sensitivity and 81.8% specificity with an AUC of 86.7%.\"}]","Circulating miRNAs and Machine Learning for Lateralizing Primary Aldosteronism - Research article summary | PDF",1785723359,28,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"circulating-mirnas-and-machine-learning-for-lateralizing-primary-aldosteronism-research-article-summary","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/circulating-mirnas-and-machine-learning-for-lateralizing-primary-aldosteronism-research-article-summary/119257/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04","2026-08-03",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Why is laterality determination in primary aldosteronism clinically important?","Question",{"text":76,"@type":77},"Unilateral and bilateral primary aldosteronism require different treatment approaches. Accurate lateralization therefore guides appropriate therapy and improves patient management.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How were circulating miRNAs measured and validated?",{"text":81,"@type":77},"Plasma miRNA profiling was conducted on samples collected during adrenal venous sampling, using an Illumina MiSeq platform. Nine miRNAs were selected for validation by RT-qPCR.",{"name":83,"@type":74,"acceptedAnswer":84},"What performance did the machine learning models achieve?",{"text":85,"@type":77},"The best model using six miRNAs achieved an AUC of 87.1% in a 30-sample subset. Deep learning reached 100% accuracy on the subset and, across 108 samples, showed 90.9% sensitivity and 81.8% specificity with an AUC of 86.7%.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]