ISSN 1662-4009 (online)

ey0018.8-7 | Important for Clinical Practice | ESPEYB18

8.7. Targeted metabolomics as a tool in discriminating endocrine from primary hypertension

Z Erlic , P Reel , S Reel , L Amar , A Pecori , CK Larsen , M Tetti , C Pamporaki , C Prehn , J Adamski , A Prejbisz , F Ceccato , C Scaroni , M Kroiss , MC Dennedy , J Deinum , K Langton , P Mulatero , M Reincke , L Lenzini , AP Gimenez-Roqueplo , G Assie , A Blanchard , MC Zennaro , E Jefferson , F Beuschlein

J Clin Endocrinol Metab. 2021 Mar 25;106(4):1111–1128.https://pubmed.ncbi.nlm.nih.gov/33382876/In this multicentre patient cohort study, the authors investigated the use of targeted metabolomics to discriminate primary hypertension (PHT) from endocrine forms of hypertension (EHT). They identified 16 metabolites that help to discriminate between PHT and EHT.Arteri...

ey0019.15-4 | Diabetes | ESPEYB19

15.4. Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

A Wesolowska-Andersen , CA Brorsson , R Bizzotto , A Mari , A Tura , R Koivula , A Mahajan , A Vinuela , JF Tajes , S Sharma , M Haid , C Prehn , A Artati , MG Hong , PB Musholt , A Kurbasic , F De Masi , K Tsirigos , HK Pedersen , V Gudmundsdottir , CE Thomas , K Banasik , C Jennison , A Jones , G Kennedy , J Bell , L Thomas , G Frost , H Thomsen , K Allin , TH Hansen , H Vestergaard , T Hansen , F Rutters , P Elders , L t'Hart , A Bonnefond , M Canouil , S Brage , T Kokkola , A Heggie , D McEvoy , A Hattersley , T McDonald , H Teare , M Ridderstrale , M Walker , I Forgie , GN Giordano , P Froguel , I Pavo , H Ruetten , O Pedersen , E Dermitzakis , PW Franks , JM Schwenk , J Adamski , E Pearson , MI McCarthy , S Brunak , Consortium ID

Cell Rep Med. 2022;3(1):100477. doi: 10.1016/j.xcrm.2021.100477. PubMed ID: 35106505Brief summary: To explore clinical heterogeneity, this study analyzed baseline visit data on 726 adults with newly diagnosed Type 2 diabetes (T2D) adults and identified in 4 distinct profiles (clusters of phenotypes), which predicted differences in subsequent disease progression and anti-diabetic treatments...