Publication Search List

HTTP 200 OK
  Allow: GET, HEAD, OPTIONS
  Content-Type: application/json
  Vary: Accept
  
  {
    "count": 127182,
    "next": "https://api-test.medunigraz.at/v1/research/search/publication/?format=api&limit=20&offset=127100",
    "previous": "https://api-test.medunigraz.at/v1/research/search/publication/?format=api&limit=20&offset=127060",
    "results": [
        {
            "text": "\n176391\nAuthor Correction: Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing.\n\nKunkle, BW\n\nGrenier-Boley, B\n\nSims, R\n\nBis, JC\n\nDamotte, V\n\nNaj, AC\n\nBoland, A\n\nVronskaya, M\n\nvan der Lee, SJ\n\nAmlie-Wolf, A\n\nBellenguez, C\n\nFrizatti, A\n\nChouraki, V\n\nMartin, ER\n\nSleegers, K\n\nBadarinarayan, N\n\nJakobsdottir, J\n\nHamilton-Nelson, KL\n\nMoreno-Grau, S\n\nOlaso, R\n\nRaybould, R\n\nChen, Y\n\nKuzma, AB\n\nHiltunen, M\n\nMorgan, T\n\nAhmad, S\n\nVardarajan, BN\n\nEpelbaum, J\n\nHoffmann, P\n\nBoada, M\n\nBeecham, GW\n\nGarnier, JG\n\nHarold, D\n\nFitzpatrick, AL\n\nValladares, O\n\nMoutet, ML\n\nGerrish, A\n\nSmith, AV\n\nQu, L\n\nBacq, D\n\nDenning, N\n\nJian, X\n\nZhao, Y\n\nDel Zompo, M\n\nFox, NC\n\nChoi, SH\n\nMateo, I\n\nHughes, JT\n\nAdams, HH\n\nMalamon, J\n\nSanchez-Garcia, F\n\nPatel, Y\n\nBrody, JA\n\nDombroski, BA\n\nNaranjo, MCD\n\nDaniilidou, M\n\nEiriksdottir, G\n\nMukherjee, S\n\nWallon, D\n\nUphill, J\n\nAspelund, T\n\nCantwell, LB\n\nGarzia, F\n\nGalimberti, D\n\nHofer, E\n\nButkiewicz, M\n\nFin, B\n\nScarpini, E\n\nSarnowski, C\n\nBush, WS\n\nMeslage, S\n\nKornhuber, J\n\nWhite, CC\n\nSong, Y\n\nBarber, RC\n\nEngelborghs, S\n\nSordon, S\n\nVoijnovic, D\n\nAdams, PM\n\nVandenberghe, R\n\nMayhaus, M\n\nCupples, LA\n\nAlbert, MS\n\nDe Deyn, PP\n\nGu, W\n\nHimali, JJ\n\nBeekly, D\n\nSquassina, A\n\nHartmann, AM\n\nOrellana, A\n\nBlacker, D\n\nRodriguez-Rodriguez, E\n\nLovestone, S\n\nGarcia, ME\n\nDoody, RS\n\nMunoz-Fernadez, C\n\nSussams, R\n\nLin, H\n\nFairchild, TJ\n\nBenito, YA\n\nHolmes, C\n\nKaramujić-Čomić, H\n\nFrosch, MP\n\nThonberg, H\n\nMaier, W\n\nRoshchupkin, G\n\nGhetti, B\n\nGiedraitis, V\n\nKawalia, A\n\nLi, S\n\nHuebinger, RM\n\nKilander, L\n\nMoebus, S\n\nHernández, I\n\nKamboh, MI\n\nBrundin, R\n\nTurton, J\n\nYang, Q\n\nKatz, MJ\n\nConcari, L\n\nLord, J\n\nBeiser, AS\n\nKeene, CD\n\nHelisalmi, S\n\nKloszewska, I\n\nKukull, WA\n\nKoivisto, AM\n\nLynch, A\n\nTarraga, L\n\nLarson, EB\n\nHaapasalo, A\n\nLawlor, B\n\nMosley, TH\n\nLipton, RB\n\nSolfrizzi, V\n\nGill, M\n\nLongstreth, WT\n\nMontine, TJ\n\nFrisardi, V\n\nDiez-Fairen, M\n\nRivadeneira, F\n\nPetersen, RC\n\nDeramecourt, V\n\nAlvarez, I\n\nSalani, F\n\nCiaramella, A\n\nBoerwinkle, E\n\nReiman, EM\n\nFievet, N\n\nRotter, JI\n\nReisch, JS\n\nHanon, O\n\nCupidi, C\n\nUitterlinden, AGA\n\nRoyall, DR\n\nDufouil, C\n\nMaletta, RG\n\nde Rojas, I\n\nSano, M\n\nBrice, A\n\nCecchetti, R\n\nGeorge-Hyslop, PS\n\nRitchie, K\n\nTsolaki, M\n\nTsuang, DW\n\nDubois, B\n\nCraig, D\n\nWu, CK\n\nSoininen, H\n\nAvramidou, D\n\nAlbin, RL\n\nFratiglioni, L\n\nGermanou, A\n\nApostolova, LG\n\nKeller, L\n\nKoutroumani, M\n\nArnold, SE\n\nPanza, F\n\nGkatzima, O\n\nAsthana, S\n\nHannequin, D\n\nWhitehead, P\n\nAtwood, CS\n\nCaffarra, P\n\nHampel, H\n\nQuintela, I\n\nCarracedo, Á\n\nLannfelt, L\n\nRubinsztein, DC\n\nBarnes, LL\n\nPasquier, F\n\nFrölich, L\n\nBarral, S\n\nMcGuinness, B\n\nBeach, TG\n\nJohnston, JA\n\nBecker, JT\n\nPassmore, P\n\nBigio, EH\n\nSchott, JM\n\nBird, TD\n\nWarren, JD\n\nBoeve, BF\n\nLupton, MK\n\nBowen, JD\n\nProitsi, P\n\nBoxer, A\n\nPowell, JF\n\nBurke, JR\n\nKauwe, JSK\n\nBurns, JM\n\nMancuso, M\n\nBuxbaum, JD\n\nBonuccelli, U\n\nCairns, NJ\n\nMcQuillin, A\n\nCao, C\n\nLivingston, G\n\nCarlson, CS\n\nBass, NJ\n\nCarlsson, CM\n\nHardy, J\n\nCarney, RM\n\nBras, J\n\nCarrasquillo, MM\n\nGuerreiro, R\n\nAllen, M\n\nChui, HC\n\nFisher, E\n\nMasullo, C\n\nCrocco, EA\n\nDeCarli, C\n\nBisceglio, G\n\nDick, M\n\nMa, L\n\nDuara, R\n\nGraff-Radford, NR\n\nEvans, DA\n\nHodges, A\n\nFaber, KM\n\nScherer, M\n\nFallon, KB\n\nRiemenschneider, M\n\nFardo, DW\n\nHeun, R\n\nFarlow, MR\n\nKölsch, H\n\nFerris, S\n\nLeber, M\n\nForoud, TM\n\nHeuser, I\n\nGalasko, DR\n\nGiegling, I\n\nGearing, M\n\nHüll, M\n\nGeschwind, DH\n\nGilbert, JR\n\nMorris, J\n\nGreen, RC\n\nMayo, K\n\nGrowdon, JH\n\nFeulner, T\n\nHamilton, RL\n\nHarrell, LE\n\nDrichel, D\n\nHonig, LS\n\nCushion, TD\n\nHuentelman, MJ\n\nHollingworth, P\n\nHulette, CM\n\nHyman, BT\n\nMarshall, R\n\nJarvik, GP\n\nMeggy, A\n\nAbner, E\n\nMenzies, GE\n\nJin, LW\n\nLeonenko, G\n\nReal, LM\n\nJun, GR\n\nBaldwin, CT\n\nGr ...\n\nBeiträge in Fachzeitschriften\nISI:000484010800018\n31417202.0\n10.1038/s41588-019-0495-7\nPMC7265117\nAn amendment to this paper has been published and can be accessed via a link at the top of the paper.\n\nHofer, Edith\n\n\n"
        },
        {
            "text": "\n121218\nIntegration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function.\n\nChasman, DI\n\nFuchsberger, C\n\nPattaro, C\n\nTeumer, A\n\nBöger, CA\n\nEndlich, K\n\nOlden, M\n\nChen, MH\n\nTin, A\n\nTaliun, D\n\nLi, M\n\nGao, X\n\nGorski, M\n\nYang, Q\n\nHundertmark, C\n\nFoster, MC\n\nO'Seaghdha, CM\n\nGlazer, N\n\nIsaacs, A\n\nLiu, CT\n\nSmith, AV\n\nO'Connell, JR\n\nStruchalin, M\n\nTanaka, T\n\nLi, G\n\nJohnson, AD\n\nGierman, HJ\n\nFeitosa, MF\n\nHwang, SJ\n\nAtkinson, EJ\n\nLohman, K\n\nCornelis, MC\n\nJohansson, A\n\nTönjes, A\n\nDehghan, A\n\nLambert, JC\n\nHolliday, EG\n\nSorice, R\n\nKutalik, Z\n\nLehtimäki, T\n\nEsko, T\n\nDeshmukh, H\n\nUlivi, S\n\nChu, AY\n\nMurgia, F\n\nTrompet, S\n\nImboden, M\n\nCoassin, S\n\nPistis, G\n\nCARDIoGRAM Consortium\n\nICBP Consortium\n\nCARe Consortium\n\nWTCCC2\n\nHarris, TB\n\nLauner, LJ\n\nAspelund, T\n\nEiriksdottir, G\n\nMitchell, BD\n\nBoerwinkle, E\n\nSchmidt, H\n\nCavalieri, M\n\nRao, M\n\nHu, F\n\nDemirkan, A\n\nOostra, BA\n\nde Andrade, M\n\nTurner, ST\n\nDing, J\n\nAndrews, JS\n\nFreedman, BI\n\nGiulianini, F\n\nKoenig, W\n\nIllig, T\n\nMeisinger, C\n\nGieger, C\n\nZgaga, L\n\nZemunik, T\n\nBoban, M\n\nMinelli, C\n\nWheeler, HE\n\nIgl, W\n\nZaboli, G\n\nWild, SH\n\nWright, AF\n\nCampbell, H\n\nEllinghaus, D\n\nNöthlings, U\n\nJacobs, G\n\nBiffar, R\n\nErnst, F\n\nHomuth, G\n\nKroemer, HK\n\nNauck, M\n\nStracke, S\n\nVölker, U\n\nVölzke, H\n\nKovacs, P\n\nStumvoll, M\n\nMägi, R\n\nHofman, A\n\nUitterlinden, AG\n\nRivadeneira, F\n\nAulchenko, YS\n\nPolasek, O\n\nHastie, N\n\nVitart, V\n\nHelmer, C\n\nWang, JJ\n\nStengel, B\n\nRuggiero, D\n\nBergmann, S\n\nKähönen, M\n\nViikari, J\n\nNikopensius, T\n\nProvince, M\n\nKetkar, S\n\nColhoun, H\n\nDoney, A\n\nRobino, A\n\nKrämer, BK\n\nPortas, L\n\nFord, I\n\nBuckley, BM\n\nAdam, M\n\nThun, GA\n\nPaulweber, B\n\nHaun, M\n\nSala, C\n\nMitchell, P\n\nCiullo, M\n\nKim, SK\n\nVollenweider, P\n\nRaitakari, O\n\nMetspalu, A\n\nPalmer, C\n\nGasparini, P\n\nPirastu, M\n\nJukema, JW\n\nProbst-Hensch, NM\n\nKronenberg, F\n\nToniolo, D\n\nGudnason, V\n\nShuldiner, AR\n\nCoresh, J\n\nSchmidt, R\n\nFerrucci, L\n\nSiscovick, DS\n\nvan Duijn, CM\n\nBorecki, IB\n\nKardia, SL\n\nLiu, Y\n\nCurhan, GC\n\nRudan, I\n\nGyllensten, U\n\nWilson, JF\n\nFranke, A\n\nPramstaller, PP\n\nRettig, R\n\nProkopenko, I\n\nWitteman, J\n\nHayward, C\n\nRidker, PM\n\nParsa, A\n\nBochud, M\n\nHeid, IM\n\nKao, WH\n\nFox, CS\n\nKöttgen, A\n\nBeiträge in Fachzeitschriften\nISI:000311965600009\n22962313.0\n10.1093/hmg/dds369\nPMC3607468\nIn conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10(-9)) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10(-4)-2.2 × 10(-7). Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.\n\nCavalieri, Margherita\n\nSchmidt, Helena\n\nSchmidt, Reinhold\n\n\n"
        },
        {
            "text": "\n161255\nErratum to: Scaling up strategies of the chronic respiratory disease programme of the European Innovation Partnership on Active and Healthy Ageing (Action Plan B3: Area 5).\n\nBousquet, J\n\nFarrell, J\n\nCrooks, G\n\nHellings, P\n\nBel, EH\n\nBewick, M\n\nChavannes, NH\n\nde Sousa, JC\n\nCruz, AA\n\nHaahtela, T\n\nJoos, G\n\nKhaltaev, N\n\nMalva, J\n\nMuraro, A\n\nNogues, M\n\nPalkonen, S\n\nPedersen, S\n\nRobalo-Cordeiro, C\n\nSamolinski, B\n\nStrandberg, T\n\nValiulis, A\n\nYorgancioglu, A\n\nZuberbier, T\n\nBedbrook, A\n\nAberer, W\n\nAdachi, M\n\nAgusti, A\n\nAkdis, CA\n\nAkdis, M\n\nAnkri, J\n\nAlonso, A\n\nAnnesi-Maesano, I\n\nAnsotegui, IJ\n\nAnto, JM\n\nArnavielhe, S\n\nArshad, H\n\nBai, C\n\nBaiardini, I\n\nBachert, C\n\nBaigenzhin, AK\n\nBarbara, C\n\nBateman, ED\n\nBeghé, B\n\nKheder, AB\n\nBennoor, KS\n\nBenson, M\n\nBergmann, KC\n\nBieber, T\n\nBindslev-Jensen, C\n\nBjermer, L\n\nBlain, H\n\nBlasi, F\n\nBoner, AL\n\nBonini, M\n\nBonini, S\n\nBosnic-Anticevitch, S\n\nBoulet, LP\n\nBourret, R\n\nBousquet, PJ\n\nBraido, F\n\nBriggs, AH\n\nBrightling, CE\n\nBrozek, J\n\nBuhl, R\n\nBurney, PG\n\nBush, A\n\nCaballero-Fonseca, F\n\nCaimmi, D\n\nCalderon, MA\n\nCalverley, PM\n\nCamargos, PAM\n\nCanonica, GW\n\nCamuzat, T\n\nCarlsen, KH\n\nCarr, W\n\nCarriazo, A\n\nCasale, T\n\nCepeda Sarabia, AM\n\nChatzi, L\n\nChen, YZ\n\nChiron, R\n\nChkhartishvili, E\n\nChuchalin, AG\n\nChung, KF\n\nCiprandi, G\n\nCirule, I\n\nCox, L\n\nCosta, DJ\n\nCustovic, A\n\nDahl, R\n\nDahlen, SE\n\nDarsow, U\n\nDe Carlo, G\n\nDe Blay, F\n\nDedeu, T\n\nDeleanu, D\n\nDe Manuel Keenoy, E\n\nDemoly, P\n\nDenburg, JA\n\nDevillier, P\n\nDidier, A\n\nDinh-Xuan, AT\n\nDjukanovic, R\n\nDokic, D\n\nDouagui, H\n\nDray, G\n\nDubakiene, R\n\nDurham, SR\n\nDykewicz, MS\n\nEl-Gamal, Y\n\nEmuzyte, R\n\nFabbri, LM\n\nFletcher, M\n\nFiocchi, A\n\nFink Wagner, A\n\nFonseca, J\n\nFokkens, WJ\n\nForastiere, F\n\nFrith, P\n\nGaga, M\n\nGamkrelidze, A\n\nGarces, J\n\nGarcia-Aymerich, J\n\nGemicioğlu, B\n\nGereda, JE\n\nGonzález Diaz, S\n\nGotua, M\n\nGrisle, I\n\nGrouse, L\n\nGutter, Z\n\nGuzmán, MA\n\nHeaney, LG\n\nHellquist-Dahl, B\n\nHenderson, D\n\nHendry, A\n\nHeinrich, J\n\nHeve, D\n\nHorak, F\n\nHourihane, JOB\n\nHowarth, P\n\nHumbert, M\n\nHyland, ME\n\nIllario, M\n\nIvancevich, JC\n\nJardim, JR\n\nJares, EJ\n\nJeandel, C\n\nJenkins, C\n\nJohnston, SL\n\nJonquet, O\n\nJulge, K\n\nJung, KS\n\nJust, J\n\nKaidashev, I\n\nKhaitov, MR\n\nKalayci, O\n\nKalyoncu, AF\n\nKeil, T\n\nKeith, PK\n\nKlimek, L\n\nKoffi N'Goran, B\n\nKolek, V\n\nKoppelman, GH\n\nKowalski, ML\n\nKull, I\n\nKuna, P\n\nKvedariene, V\n\nLambrecht, B\n\nLau, S\n\nLarenas-Linnemann, D\n\nLaune, D\n\nLe, LTT\n\nLieberman, P\n\nLipworth, B\n\nLi, J\n\nLodrup Carlsen, K\n\nLouis, R\n\nMacNee, W\n\nMagard, Y\n\nMagnan, A\n\nMahboub, B\n\nMair, A\n\nMajer, I\n\nMakela, MJ\n\nManning, P\n\nMara, S\n\nMarshall, GD\n\nMasjedi, MR\n\nMatignon, P\n\nMaurer, M\n\nMavale-Manuel, S\n\nMelén, E\n\nMelo-Gomes, E\n\nMeltzer, EO\n\nMenzies-Gow, A\n\nMerk, H\n\nMichel, JP\n\nMiculinic, N\n\nMihaltan, F\n\nMilenkovic, B\n\nMohammad, GMY\n\nMolimard, M\n\nMomas, I\n\nMontilla-Santana, A\n\nMorais-Almeida, M\n\nMorgan, M\n\nMösges, R\n\nMullol, J\n\nNafti, S\n\nNamazova-Baranova, L\n\nNaclerio, R\n\nNeou, A\n\nNeffen, H\n\nNekam, K\n\nNiggemann, B\n\nNinot, G\n\nNyembue, TD\n\nO'Hehir, RE\n\nOhta, K\n\nOkamoto, Y\n\nOkubo, K\n\nOuedraogo, S\n\nPaggiaro, P\n\nPali-Schöll, I\n\nPanzner, P\n\nPapadopoulos, N\n\nPapi, A\n\nPark, HS\n\nPassalacqua, G\n\nPavord, I\n\nPawankar, R\n\nPengelly, R\n\nPfaar, O\n\nPicard, R\n\nPigearias, B\n\nPin, I\n\nPlavec, D\n\nPoethig, D\n\nPohl, W\n\nPopov, TA\n\nPortejoie, F\n\nPotter, P\n\nPostma, D\n\nPrice, D\n\nRabe, KF\n\nRaciborski, F\n\nRadier Pontal, F\n\nRepka-Ramirez, S\n\nReitamo, S\n\nRennard, S\n\nRodenas, F\n\nRoberts, J\n\nRoca, J\n\nRodriguez Mañas, L\n\nRolland, C\n\nRoman Rodriguez, M\n\nRomano, A\n\nRosado-Pinto, J\n\nRosario, N\n\nRosenwasser, L\n\nRottem, M\n\nRyan, D\n\nSanchez-Borges, M\n\nScadding, GK\n\nSchunemann, HJ\n\nSerrano, E\n\nSchmid-Grendelmeier, P\n\nSchulz, H\n\nSheikh, A\n\nShields, M\n\nSiafakas, N\n\nSibille, Y\n\nSimilowski, T\n\nSimons, FER\n\nSisul, JC\n\nSkrindo, I\n\nSm ...\n\nBeiträge in Fachzeitschriften\nISI:000396073300001\n28239450.0\n10.1186/s13601-016-0135-6\nPMC5319069\n[This corrects the article DOI: 10.1186/s13601-016-0116-9.].\n\nAberer, Werner\n\n\n"
        },
        {
            "text": "\n124287\nGenome-wide association analyses identify 18 new loci associated with serum urate concentrations.\n\nKöttgen, A\n\nAlbrecht, E\n\nTeumer, A\n\nVitart, V\n\nKrumsiek, J\n\nHundertmark, C\n\nPistis, G\n\nRuggiero, D\n\nOeaghdha, CM\n\nHaller, T\n\nYang, Q\n\nTanaka, T\n\nJohnson, AD\n\nKutalik, Z\n\nSmith, AV\n\nShi, J\n\nStruchalin, M\n\nMiddelberg, RP\n\nBrown, MJ\n\nGaffo, AL\n\nPirastu, N\n\nLi, G\n\nHayward, C\n\nZemunik, T\n\nHuffman, J\n\nYengo, L\n\nZhao, JH\n\nDemirkan, A\n\nFeitosa, MF\n\nLiu, X\n\nMalerba, G\n\nLopez, LM\n\nvan der Harst, P\n\nLi, X\n\nKleber, ME\n\nHicks, AA\n\nNolte, IM\n\nJohansson, A\n\nMurgia, F\n\nWild, SH\n\nBakker, SJ\n\nPeden, JF\n\nDehghan, A\n\nSteri, M\n\nTenesa, A\n\nLagou, V\n\nSalo, P\n\nMangino, M\n\nRose, LM\n\nLehtimäki, T\n\nWoodward, OM\n\nOkada, Y\n\nTin, A\n\nMüller, C\n\nOldmeadow, C\n\nPutku, M\n\nCzamara, D\n\nKraft, P\n\nFrogheri, L\n\nThun, GA\n\nGrotevendt, A\n\nGislason, GK\n\nHarris, TB\n\nLauner, LJ\n\nMcArdle, P\n\nShuldiner, AR\n\nBoerwinkle, E\n\nCoresh, J\n\nSchmidt, H\n\nSchallert, M\n\nMartin, NG\n\nMontgomery, GW\n\nKubo, M\n\nNakamura, Y\n\nTanaka, T\n\nMunroe, PB\n\nSamani, NJ\n\nJacobs, DR\n\nLiu, K\n\nD'Adamo, P\n\nUlivi, S\n\nRotter, JI\n\nPsaty, BM\n\nVollenweider, P\n\nWaeber, G\n\nCampbell, S\n\nDevuyst, O\n\nNavarro, P\n\nKolcic, I\n\nHastie, N\n\nBalkau, B\n\nFroguel, P\n\nEsko, T\n\nSalumets, A\n\nKhaw, KT\n\nLangenberg, C\n\nWareham, NJ\n\nIsaacs, A\n\nKraja, A\n\nZhang, Q\n\nWild, PS\n\nScott, RJ\n\nHolliday, EG\n\nOrg, E\n\nViigimaa, M\n\nBandinelli, S\n\nMetter, JE\n\nLupo, A\n\nTrabetti, E\n\nSorice, R\n\nDöring, A\n\nLattka, E\n\nStrauch, K\n\nTheis, F\n\nWaldenberger, M\n\nWichmann, HE\n\nDavies, G\n\nGow, AJ\n\nBruinenberg, M\n\nLifeLines Cohort Study\n\nStolk, RP\n\nKooner, JS\n\nZhang, W\n\nWinkelmann, BR\n\nBoehm, BO\n\nLucae, S\n\nPenninx, BW\n\nSmit, JH\n\nCurhan, G\n\nMudgal, P\n\nPlenge, RM\n\nPortas, L\n\nPersico, I\n\nKirin, M\n\nWilson, JF\n\nLeach, IM\n\nvan Gilst, WH\n\nGoel, A\n\nOngen, H\n\nHofman, A\n\nRivadeneira, F\n\nUitterlinden, AG\n\nImboden, M\n\nvon Eckardstein, A\n\nCucca, F\n\nNagaraja, R\n\nPiras, MG\n\nNauck, M\n\nSchurmann, C\n\nBudde, K\n\nErnst, F\n\nFarrington, SM\n\nTheodoratou, E\n\nProkopenko, I\n\nStumvoll, M\n\nJula, A\n\nPerola, M\n\nSalomaa, V\n\nShin, SY\n\nSpector, TD\n\nSala, C\n\nRidker, PM\n\nKähönen, M\n\nViikari, J\n\nHengstenberg, C\n\nNelson, CP\n\nCARDIoGRAM Consortium\n\nDIAGRAM Consortium\n\nICBP Consortium MAGIC Consortium\n\nMeschia, JF\n\nNalls, MA\n\nSharma, P\n\nSingleton, AB\n\nKamatani, N\n\nZeller, T\n\nBurnier, M\n\nAttia, J\n\nLaan, M\n\nKlopp, N\n\nHillege, HL\n\nKloiber, S\n\nChoi, H Pirastu, M Tore, S Probst-Hensch, NM Völzke, H\n\nGudnason, V\n\nParsa, A\n\nSchmidt, R\n\nWhitfield, JB\n\nFornage, M\n\nGasparini, P\n\nSiscovick, DS\n\nPolasek, O\n\nCampbell, H\n\nRudan, I\n\nBouatia-Naji, N\n\nMetspalu, A\n\nLoos, RJ\n\nvan Duijn, CM\n\nBorecki, IB\n\nFerrucci, L\n\nGambaro, G\n\nDeary, IJ\n\nWolffenbuttel, BH\n\nChambers, JC\n\nMärz, W\n\nPramstaller, PP\n\nSnieder, H\n\nGyllensten, U\n\nWright, AF\n\nNavis, G\n\nWatkins, H\n\nWitteman, JCM\n\nSanna, S\n\nSchipf, S\n\nDunlop, MG\n\nTönjes, A\n\nRipatti, S\n\nSoranzo, N\n\nToniolo, D\n\nChasman, DI\n\nRaitakari, O\n\nKao, WHL\n\nCiullo, M\n\nFox, CS\n\nCaulfield, M\n\nBochud, M\n\nGieger, C\n\nBeiträge in Fachzeitschriften\nISI:000314333000009\n23263486.0\n10.1038/ng.2500\nPMC3663712\nElevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140, 00 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.\n\nMärz, Winfried\n\nSchmidt, Helena\n\nSchmidt, Reinhold\n\n\n"
        },
        {
            "text": "\n138208\nMesenchymal stem/stromal cells in post-menopausal endometrium.\n\nUlrich, D\n\nTan, KS\n\nDeane, J\n\nSchwab, K\n\nCheong, A\n\nRosamilia, A\n\nGargett, CE\n\nBeiträge in Fachzeitschriften\nISI:000343417900010\n24964924.0\n10.1093/humrep/deu159\nNone\nDoes post-menopausal endometrium contain mesenchymal stem/stromal cells (MSC) that have adult stem cell properties and can be prospectively isolated from a biopsy?\n                Perivascular W5C5(+) cells isolated from post-menopausal endometrial biopsies displayed characteristic MSC properties of clonogenicity, multipotency and surface phenotype irrespective of whether the women were or were not pre-treated with estrogen to regenerate the endometrium.\n                Recently MSCs have been identified in human premenopausal endometrium, and can be prospectively isolated using a single marker, W5C5/SUSD2.\n                Endometrial tissue of both the functional and basal layers, from 17 premenopausal (pre-MP) women, 19 post-menopausal (post-MP) women without hormonal treatment and 15 post-menopausal women on estrogen replacement therapy (post-MP+ E2), was collected through a prospective phase IV clinical trial over 2 years.\n                Post-menopausal women <65 years of age were treated with or without E2 for 6-8 weeks prior to tissue collection. Serum E2 levels were determined by estradiol immunoenzymatic assay. Endometrial tissue was obtained from women by biopsy (curettage) just prior to the hysterectomy. The effect of E2 on endometrial thickness and glandular and luminal epithelial height was determined using image analysis. Endometrial tissue was dissociated into single cell suspensions and MSC properties were examined in freshly isolated and short-term cultured, magnetic bead-purified W5C5(+) cells. MSC properties were assessed using clonogenicity, serial cloning, mesodermal differentiation in adipogenic, chondrogenic, osteogenic and myogenic induction culture media, and surface phenotype analysis by flow cytometry. Estrogen receptor α expression in W5C5(+) cells was examined using dual colour immunofluorescence. Vascularity was analysed using CD34 and alpha smooth muscle actin immunostaining and subsequent image analysis.\n                A small population of stromal cells with MSC properties was purified with the W5C5 antibody from post-menopausal endometrium, whether atrophic from low circulating estrogen or regenerated from systemic estrogen treatment, similar to premenopausal endometrium. The MSC derived from post-menopausal endometrium treated with or without E2 fulfilled the minimum MSC criteria: clonogenicity, surface phenotype (CD29(+), CD44(+), CD73(+), CD105(+), CD140b(+), CD146(+)) and multipotency. The post-menopausal endometrial MSCs also showed comparable properties to premenopausal eMSC with respect to self-renewal in vitro and W5C5 expression. The W5C5(+) cells were located perivascularly as expected and did not express estrogen receptor α.\n                The properties of the MSC derived from post-menopausal endometrium were evaluated in vitro and their in vivo tissue reconstitution capacity has not been established as it has for premenopausal endometrial MSC.\n                The endometrium is an accessible source of MSC obtainable with minimum morbidity that could be used for future clinical applications as a cell-based therapy. This study shows that menopausal women can access their endometrial MSC by a simple biopsy for use in autologous therapies, particularly if their endometrium has been regenerated by short-term E2 treatment, provided they have an intact uterus and are not contraindicated for short-term E2 treatment. Endometrial MSC in post-menopausal women possess key MSC properties and are a promising source of MSC independent of a woman's age.\n                This study was supported by the National Health and Medical Research Council (NHMRC) of Australia grant (1021126) (C.E.G., A.R.) and Senior Research Fellowship (1042298) (C.E.G.), Australian Gynaecological Endoscopic Society grant (A.R.) , Monash International Postgraduate Research Scholarship (DU), Australian Stem Cell Centre, South East Melbourne Alliance for Regenerative Therapies and Australian Stem Cell Centre top up scholarships (DU) and Victorian Government's Operational Infrastructure Support Program. Competing interests: AR receives Preceptorship fees from AMS, advisory board fees and sponsored study from Astellas, and conducts investigator led studies sponsored by AMS and Boston Scientific for other projects.\n                CTNRN12610000563066.\n                © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.\n\nGold ehem Ulrich, Daniela\n\n\n"
        },
        {
            "text": "\n147104\nAdjuvant denosumab in breast cancer (ABCSG-18): a multicentre, randomised, double-blind, placebo-controlled trial.\n\nGnant, M\n\nPfeiler, G\n\nDubsky, PC\n\nHubalek, M\n\nGreil, R\n\nJakesz, R\n\nWette, V\n\nBalic, M\n\nHaslbauer, F\n\nMelbinger, E\n\nBjelic-Radisic, V\n\nArtner-Matuschek, S\n\nFitzal, F\n\nMarth, C\n\nSevelda, P\n\nMlineritsch, B\n\nSteger, GG\n\nManfreda, D\n\nExner, R\n\nEgle, D\n\nBergh, J\n\nKainberger, F\n\nTalbot, S\n\nWarner, D\n\nFesl, C\n\nSinger, CF\n\nAustrian Breast and Colorectal Cancer Study Group\n\nBeiträge in Fachzeitschriften\nISI:000358761700023\n26040499.0\n10.1016/S0140-6736(15)60995-3\nNone\nAdjuvant endocrine therapy compromises bone health in patients with breast cancer, causing osteopenia, osteoporosis, and fractures. Antiresorptive treatments such as bisphosphonates prevent and counteract these side-effects. In this trial, we aimed to investigate the effects of the anti-RANK ligand antibody denosumab in postmenopausal, aromatase inhibitor-treated patients with early-stage hormone receptor-positive breast cancer.\n                In this prospective, double-blind, placebo-controlled, phase 3 trial, postmenopausal patients with early hormone receptor-positive breast cancer receiving treatment with aromatase inhibitors were randomly assigned in a 1:1 ratio to receive either denosumab 60 mg or placebo administered subcutaneously every 6 months in 58 trial centres in Austria and Sweden. Patients were assigned by an interactive voice response system. The randomisation schedule used a randomly permuted block design with block sizes 2 and 4, stratified by type of hospital regarding Hologic device for DXA scans, previous aromatase inhibitor use, and baseline bone mineral density. Patients, treating physicians, investigators, data managers, and all study personnel were masked to treatment allocation. The primary endpoint was time from randomisation to first clinical fracture, analysed by intention to treat. As an additional sensitivity analysis, we also analysed the primary endpoint on the per-protocol population. Patients were treated until the prespecified number of 247 first clinical fractures was reached. This trial is ongoing (patients are in follow-up) and is registered with the European Clinical Trials Database, number 2005-005275-15, and with ClinicalTrials.gov, number NCT00556374.\n                Between Dec 18, 2006, and July 22, 2013, 3425 eligible patients were enrolled into the trial, of whom 3420 were randomly assigned to receive denosumab 60 mg (n=1711) or placebo (n=1709) subcutaneously every 6 months. Compared with the placebo group, patients in the denosumab group had a significantly delayed time to first clinical fracture (hazard ratio [HR] 0·50 [95% CI 0·39-0·65], p<0·0001). The overall lower number of fractures in the denosumab group (92) than in the placebo group (176) was similar in all patient subgroups, including in patients with a bone mineral density T-score of -1 or higher at baseline (n=1872, HR 0·44 [95% CI 0·31-0·64], p<0·0001) and in those with a bone mineral density T-score of less than -1 already at baseline (n=1548, HR 0·57 [95% CI 0·40-0·82], p=0·002). The patient incidence of adverse events in the safety analysis set (all patients who received at least one dose of study drug) did not differ between the denosumab group (1366 events, 80%) and the placebo group (1334 events, 79%), nor did the numbers of serious adverse events (521 vs 511 [30% in each group]). The main adverse events were arthralgia and other aromatase-inhibitor related symptoms; no additional toxicity from the study drug was reported. Despite proactive adjudication of every potential osteonecrosis of the jaw by an international expert panel, no cases of osteonecrosis of the jaw were reported. 93 patients (3% of the full analysis set) died during the study, of which one death (in the denosumab group) was thought to be related to the study drug.\n                Adjuvant denosumab 60 mg twice per year reduces the risk of clinical fractures in postmenopausal women with breast cancer receiving aromatase inhibitors, and can be administered without added toxicity. Since a main side-effect of adjuvant breast cancer treatment can be substantially reduced by the addition of denosumab, this treatment should be considered for clinical practice.\n                Amgen.\n                Copyright © 2015 Elsevier Ltd. All rights reserved.\n\nBalic, Marija\n\nBjelic-Radisic, Vesna\n\nHofmann, Guenter\n\n\n"
        },
        {
            "text": "\n186709\nAnti-interleukin-21 antibody and liraglutide for the preservation of β-cell function in adults with recent-onset type 1 diabetes: a randomised, double-blind, placebo-controlled, phase 2 trial.\n\nvon Herrath, M\n\nBain, SC\n\nBode, B\n\nClausen, JO\n\nCoppieters, K\n\nGaysina, L\n\nGumprecht, J\n\nHansen, TK\n\nMathieu, C\n\nMorales, C\n\nMosenzon, O\n\nSegel, S\n\nTsoukas, G\n\nPieber, TR\n\nAnti-IL-21–liraglutide Study Group investigators and contributors\n\nBeiträge in Fachzeitschriften\nISI:000629809800012\n33662334.0\n10.1016/S2213-8587(21)00019-X\nNone\nType 1 diabetes is characterised by progressive loss of functional β-cell mass, necessitating insulin treatment. We aimed to investigate the hypothesis that combining anti-interleukin (IL)-21 antibody (for low-grade and transient immunomodulation) with liraglutide (to improve β-cell function) could enable β-cell survival with a reduced risk of complications compared with traditional immunomodulation.\n                This randomised, parallel-group, placebo-controlled, double-dummy, double-blind, phase 2 trial was done at 94 sites (university hospitals and medical centres) in 17 countries. Eligible participants were adults aged 18-45 years with recently diagnosed type 1 diabetes and residual β-cell function. Individuals with unstable type 1 diabetes (defined by an episode of severe diabetic ketoacidosis within 2 weeks of enrolment) or active or latent chronic infections were excluded. Participants were randomly assigned (1:1:1:1), with stratification by baseline stimulated peak C-peptide concentration (mixed-meal tolerance test [MMTT]), to the combination of anti-IL-21 and liraglutide, anti-IL-21 alone, liraglutide alone, or placebo, all as an adjunct to insulin. Investigators, participants, and funder personnel were masked throughout the treatment period. The primary outcome was the change in MMTT-stimulated C-peptide concentration at week 54 (end of treatment) relative to baseline, measured via the area under the concentration-time curve (AUC) over a 4 h period for the full analysis set (intention-to-treat population consisting of all participants who were randomly assigned). After treatment cessation, participants were followed up for an additional 26-week off-treatment observation period. This trial is registered with ClinicalTrials.gov, NCT02443155.\n                Between Nov 10, 2015, and Feb 27, 2019, 553 adults were assessed for eligibility, of whom 308 were randomly assigned to receive either anti-IL-21 plus liraglutide, anti-IL-21, liraglutide, or placebo (77 assigned to each group). Compared with placebo (ratio to baseline 0·61, 39% decrease), the decrease in MMTT-stimulated C-peptide concentration from baseline to week 54 was significantly smaller with combination treatment (0·90, 10% decrease; estimated treatment ratio 1·48, 95% CI 1·16-1·89; p=0·0017), but not with anti-IL-21 alone (1·23, 0·97-1·57; p=0·093) or liraglutide alone (1·12, 0·87-1·42; p=0·38). Despite greater insulin use in the placebo group, the decrease in HbA1c (a key secondary outcome) at week 54 was greater with all active treatments (-0·50 percentage points) than with placebo (-0·10 percentage points), although the differences versus placebo were not significant. The effects diminished upon treatment cessation. Changes in immune cell subsets across groups were transient and mild (<10% change over time). The most frequently reported adverse events included gastrointestinal disorders, in keeping with the known side-effect profile of liraglutide. The rate of hypoglycaemic events did not differ significantly between active treatment groups and placebo, with an exception of a lower rate in the liraglutide group than in the placebo group during the treatment period. No events of diabetic ketoacidosis were observed. One participant died while on liraglutide (considered unlikely to be related to trial treatment) in connection with three reported adverse events (hypoglycaemic coma, pneumonia, and brain oedema).\n                The combination of anti-IL-21 and liraglutide could preserve β-cell function in recently diagnosed type 1 diabetes. The efficacy of this combination appears to be similar to that seen in trials of other disease-modifying interventions in type 1 diabetes, but with a seemingly better safety profile. Efficacy and safety should be further evaluated in a phase 3 trial programme.\n                Novo Nordisk.\n                Copyright © 2021 Elsevier Ltd. All rights reserved.\n\nPieber, Thomas\n\n\n"
        },
        {
            "text": "\n161377\nAccuracy in Diagnosis of Celiac Disease Without Biopsies in Clinical Practice.\n\nWerkstetter, KJ\n\nKorponay-Szabó, IR\n\nPopp, A\n\nVillanacci, V\n\nSalemme, M\n\nHeilig, G\n\nLillevang, ST\n\nMearin, ML\n\nRibes-Koninckx, C\n\nThomas, A\n\nTroncone, R\n\nFilipiak, B\n\nMäki, M\n\nGyimesi, J\n\nNajafi, M\n\nDolinšek, J\n\nDydensborg Sander, S\n\nAuricchio, R\n\nPapadopoulou, A\n\nVécsei, A\n\nSzitanyi, P\n\nDonat, E\n\nNenna, R\n\nAlliet, P\n\nPenagini, F\n\nGarnier-Lengliné, H\n\nCastillejo, G\n\nKurppa, K\n\nShamir, R\n\nHauer, AC\n\nSmets, F\n\nCorujeira, S\n\nvan Winckel, M\n\nBuderus, S\n\nChong, S\n\nHusby, S\n\nKoletzko, S\n\nProCeDE study group\n\nBeiträge in Fachzeitschriften\nISI:000411835200022\n28624578.0\n10.1053/j.gastro.2017.06.002\nNone\nThe guidelines of the European Society of Pediatric Gastroenterology, Hepatology, and Nutrition allow for diagnosis of celiac disease without biopsies in children with symptoms and levels of immunoglobulin A against tissue-transglutaminase (TGA-IgA) 10-fold or more the upper limit of normal (ULN), confirmed by detection of endomysium antibodies (EMA) and positivity for HLA-DQ2/DQ8. We performed a large, international prospective study to validate this approach.\n                We collected data from consecutive pediatric patients (18 years or younger) on a gluten-containing diet who tested positive for TGA-IgA from November 2011 through May 2014, seen at 33 pediatric gastroenterology units in 21 countries. Local centers recorded symptoms; measurements of total IgA, TGA, and EMA; and histopathology findings from duodenal biopsies. Children were considered to have malabsorption if they had chronic diarrhea, weight loss (or insufficient gain), growth failure, or anemia. We directly compared central findings from 16 antibody tests (8 for TGA-IgA, 1 for TGA-IgG, 6 for IgG against deamidated gliadin peptides, and 1 for EMA, from 5 different manufacturers), 2 HLA-DQ2/DQ8 tests from 2 manufacturers, and histopathology findings from the reference pathologist. Final diagnoses were based on local and central results. If all local and central results were concordant for celiac disease, cases were classified as proven celiac disease. Patients with only a low level of TGA-IgA (threefold or less the ULN) but no other results indicating celiac disease were classified as no celiac disease. Central histo-morphometry analyses were performed on all other biopsies and cases were carefully reviewed in a blinded manner. Inconclusive cases were regarded as not having celiac disease for calculation of diagnostic accuracy. The primary aim was to determine whether the nonbiopsy approach identifies children with celiac disease with a positive predictive value (PPV) above 99% in clinical practice. Secondary aims included comparing performance of different serological tests and to determine whether the suggested criteria can be simplified.\n                Of 803 children recruited for the study, 96 were excluded due to incomplete data, low level of IgA, or poor-quality biopsies. In the remaining 707 children (65.1% girls; median age, 6.2 years), 645 were diagnosed with celiac disease, 46 were found not to have celiac disease, and 16 had inconclusive results. Findings from local laboratories of TGA-IgA 10-fold or more the ULN, a positive result from the test for EMA, and any symptom identified children with celiac disease (n = 399) with a PPV of 99.75 (95% confidence interval [CI], 98.61-99.99); the PPV was 100.00 (95% CI, 98.68-100.00) when only malabsorption symptoms were used instead of any symptom (n = 278). Inclusion of HLA analyses did not increase accuracy. Findings from central laboratories differed greatly for patients with lower levels of antibodies, but when levels of TGA-IgA were 10-fold or more the ULN, PPVs ranged from 99.63 (95% CI, 98.67-99.96) to 100.00 (95% CI, 99.23-100.00).\n                Children can be accurately diagnosed with celiac disease without biopsy analysis. Diagnosis based on level of TGA-IgA 10-fold or more the ULN, a positive result from the EMA tests in a second blood sample, and the presence of at least 1 symptom could avoid risks and costs of endoscopy for more than half the children with celiac disease worldwide. HLA analysis is not required for accurate diagnosis. Clinical Trial Registration no: DRKS00003555.\n                Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.\n\nHauer, Almuthe\n\n\n"
        },
        {
            "text": "\n119282\nLarge-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci.\n\nSaxena, R\n\nElbers, CC\n\nGuo, Y\n\nPeter, I\n\nGaunt, TR\n\nMega, JL\n\nLanktree, MB\n\nTare, A\n\nCastillo, BA\n\nLi, YR\n\nJohnson, T\n\nBruinenberg, M\n\nGilbert-Diamond, D\n\nRajagopalan, R\n\nVoight, BF\n\nBalasubramanyam, A\n\nBarnard, J\n\nBauer, F\n\nBaumert, J\n\nBhangale, T\n\nBöhm, BO\n\nBraund, PS\n\nBurton, PR\n\nChandrupatla, HR\n\nClarke, R\n\nCooper-DeHoff, RM\n\nCrook, ED\n\nDavey-Smith, G\n\nDay, IN\n\nde Boer, A\n\nde Groot, MC\n\nDrenos, F\n\nFerguson, J\n\nFox, CS\n\nFurlong, CE\n\nGibson, Q\n\nGieger, C\n\nGilhuijs-Pederson, LA\n\nGlessner, JT\n\nGoel, A\n\nGong, Y\n\nGrant, SF\n\nGrobbee, DE\n\nHastie, C\n\nHumphries, SE\n\nKim, CE\n\nKivimaki, M\n\nKleber, M\n\nMeisinger, C\n\nKumari, M\n\nLangaee, TY\n\nLawlor, DA\n\nLi, M\n\nLobmeyer, MT\n\nMaitland-van der Zee, AH\n\nMeijs, MF\n\nMolony, CM\n\nMorrow, DA\n\nMurugesan, G\n\nMusani, SK\n\nNelson, CP\n\nNewhouse, SJ\n\nO'Connell, JR\n\nPadmanabhan, S\n\nPalmen, J\n\nPatel, SR\n\nPepine, CJ\n\nPettinger, M\n\nPrice, TS\n\nRafelt, S\n\nRanchalis, J\n\nRasheed, A\n\nRosenthal, E\n\nRuczinski, I\n\nShah, S\n\nShen, H\n\nSilbernagel, G\n\nSmith, EN\n\nSpijkerman, AW\n\nStanton, A\n\nSteffes, MW\n\nThorand, B\n\nTrip, M\n\nvan der Harst, P\n\nvan der A, DL\n\nvan Iperen, EP\n\nvan Setten, J\n\nvan Vliet-Ostaptchouk, JV\n\nVerweij, N\n\nWolffenbuttel, BH\n\nYoung, T\n\nZafarmand, MH\n\nZmuda, JM\n\nLook AHEAD Research Group\n\nDIAGRAM consortium\n\nBoehnke, M\n\nAltshuler, D\n\nMcCarthy, M\n\nKao, WH\n\nPankow, JS\n\nCappola, TP\n\nSever, P\n\nPoulter, N\n\nCaulfield, M\n\nDominiczak, A\n\nShields, DC\n\nBhatt, DL\n\nBhatt, D\n\nZhang, L\n\nCurtis, SP\n\nDanesh, J\n\nCasas, JP\n\nvan der Schouw, YT\n\nOnland-Moret, NC\n\nDoevendans, PA\n\nDorn, GW\n\nFarrall, M\n\nFitzGerald, GA\n\nHamsten, A\n\nHegele, R\n\nHingorani, AD\n\nHofker, MH\n\nHuggins, GS\n\nIllig, T\n\nJarvik, GP\n\nJohnson, JA\n\nKlungel, OH\n\nKnowler, WC\n\nKoenig, W\n\nMärz, W\n\nMeigs, JB\n\nMelander, O\n\nMunroe, PB\n\nMitchell, BD\n\nBielinski, SJ\n\nRader, DJ\n\nReilly, MP\n\nRich, SS\n\nRotter, JI\n\nSaleheen, D\n\nSamani, NJ\n\nSchadt, EE\n\nShuldiner, AR\n\nSilverstein, R\n\nKottke-Marchant, K\n\nTalmud, PJ\n\nWatkins, H\n\nAsselbergs, FW\n\nAsselbergs, F\n\nde Bakker, PI\n\nMcCaffery, J\n\nWijmenga, C\n\nSabatine, MS\n\nWilson, JG\n\nReiner, A\n\nBowden, DW\n\nHakonarson, H\n\nSiscovick, DS\n\nKeating, BJ\n\nBeiträge in Fachzeitschriften\nISI:000301762800007\n22325160.0\n10.1016/j.ajhg.2011.12.022\nPMC3309185\nTo identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom ∼50, 00 SNP genotyping array (the ITMAT-Broad-CARe array) with ∼2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17, 18 cases and 70, 98 controls. First, meta-analysis of 25 studies comprising 14, 73 cases and 57, 89 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8, 30 cases and 38, 87 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 × 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p < 2.4 × 10(-6)). Second, meta-analyses of 1, 86 cases and 7, 95 controls from eight African-American studies identified study-wide-significant (p = 2.4 × 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 × 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 × 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups.\n                Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.\n\nMärz, Winfried\n\nSilbernagel, Günther\n\n\n"
        },
        {
            "text": "\n187062\nDevelopment of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies.\n\nBest, JG\n\nAmbler, G\n\nWilson, D\n\nLee, KJ\n\nLim, JS\n\nShiozawa, M\n\nKoga, M\n\nLi, L\n\nLovelock, C\n\nChabriat, H\n\nHennerici, M\n\nWong, YK\n\nMak, HKF\n\nPrats-Sanchez, L\n\nMartínez-Domeño, A\n\nInamura, S\n\nYoshifuji, K\n\nArsava, EM\n\nHorstmann, S\n\nPurrucker, J\n\nLam, BYK\n\nWong, A\n\nKim, YD\n\nSong, TJ\n\nLemmens, R\n\nEppinger, S\n\nGattringer, T\n\nUysal, E\n\nTanriverdi, Z\n\nBornstein, NM\n\nBen Assayag, E\n\nHallevi, H\n\nMolad, J\n\nNishihara, M\n\nTanaka, J\n\nCoutts, SB\n\nPolymeris, A\n\nWagner, B\n\nSeiffge, DJ\n\nLyrer, P\n\nAlgra, A\n\nKappelle, LJ\n\nAl-Shahi Salman, R\n\nJäger, HR\n\nLip, GYH\n\nFischer, U\n\nEl-Koussy, M\n\nMas, JL\n\nLegrand, L\n\nKarayiannis, C\n\nPhan, T\n\nGunkel, S\n\nChrist, N\n\nAbrigo, J\n\nLeung, T\n\nChu, W\n\nChappell, F\n\nMakin, S\n\nHayden, D\n\nWilliams, DJ\n\nMess, WH\n\nNederkoorn, PJ\n\nBarbato, C\n\nBrowning, S\n\nWiegertjes, K\n\nTuladhar, AM\n\nMaaijwee, N\n\nGuevarra, AC\n\nYatawara, C\n\nMendyk, AM\n\nDelmaire, C\n\nKöhler, S\n\nvan Oostenbrugge, R\n\nZhou, Y\n\nXu, C\n\nHilal, S\n\nGyanwali, B\n\nChen, C\n\nLou, M\n\nStaals, J\n\nBordet, R\n\nKandiah, N\n\nde Leeuw, FE\n\nSimister, R\n\nHendrikse, J\n\nKelly, PJ\n\nWardlaw, J\n\nSoo, Y\n\nFluri, F\n\nSrikanth, V\n\nCalvet, D\n\nJung, S\n\nKwa, VIH\n\nEngelter, ST\n\nPeters, N\n\nSmith, EE\n\nHara, H\n\nYakushiji, Y\n\nOrken, DN\n\nFazekas, F\n\nThijs, V\n\nHeo, JH\n\nMok, V\n\nVeltkamp, R\n\nAy, H\n\nImaizumi, T\n\nGomez-Anson, B\n\nLau, KK\n\nJouvent, E\n\nRothwell, PM\n\nToyoda, K\n\nBae, HJ\n\nMarti-Fabregas, J\n\nWerring, DJ\n\nMicrobleeds International Collaborative Network\n\nBeiträge in Fachzeitschriften\nISI:000630325700020\n33743239.0\n10.1016/S1474-4422(21)00024-7\nNone\nBalancing the risks of recurrent ischaemic stroke and intracranial haemorrhage is important for patients treated with antithrombotic therapy after ischaemic stroke or transient ischaemic attack. However, existing predictive models offer insufficient performance, particularly for assessing the risk of intracranial haemorrhage. We aimed to develop new risk scores incorporating clinical variables and cerebral microbleeds, an MRI biomarker of intracranial haemorrhage and ischaemic stroke risk.\n                We did a pooled analysis of individual-patient data from the Microbleeds International Collaborative Network (MICON), which includes 38 hospital-based prospective cohort studies from 18 countries. All studies recruited participants with previous ischaemic stroke or transient ischaemic attack, acquired baseline MRI allowing quantification of cerebral microbleeds, and followed-up participants for ischaemic stroke and intracranial haemorrhage. Participants not taking antithrombotic drugs were excluded. We developed Cox regression models to predict the 5-year risks of intracranial haemorrhage and ischaemic stroke, selecting candidate predictors on biological relevance and simplifying models using backward elimination. We derived integer risk scores for clinical use. We assessed model performance in internal validation, adjusted for optimism using bootstrapping. The study is registered on PROSPERO, CRD42016036602.\n                The included studies recruited participants between Aug 28, 2001, and Feb 4, 2018. 15 766 participants had follow-up for intracranial haemorrhage, and 15 784 for ischaemic stroke. Over a median follow-up of 2 years, 184 intracranial haemorrhages and 1048 ischaemic strokes were reported. The risk models we developed included cerebral microbleed burden and simple clinical variables. Optimism-adjusted c indices were 0·73 (95% CI 0·69-0·77) with a calibration slope of 0·94 (0·81-1·06) for the intracranial haemorrhage model and 0·63 (0·62-0·65) with a calibration slope of 0·97 (0·87-1·07) for the ischaemic stroke model. There was good agreement between predicted and observed risk for both models.\n                The MICON risk scores, incorporating clinical variables and cerebral microbleeds, offer predictive value for the long-term risks of intracranial haemorrhage and ischaemic stroke in patients prescribed antithrombotic therapy for secondary stroke prevention; external validation is warranted.\n                British Heart Foundation and Stroke Association.\n                Copyright © 2021 Elsevier Ltd. All rights reserved.\n\nEppinger, Sebastian\n\nFazekas, Franz\n\nGattringer, Thomas\n\n\n"
        },
        {
            "text": "\n124116\nLarge-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.\n\nAsselbergs, FW\n\nGuo, Y\n\nvan Iperen, EP\n\nSivapalaratnam, S\n\nTragante, V\n\nLanktree, MB\n\nLange, LA\n\nAlmoguera, B\n\nAppelman, YE\n\nBarnard, J\n\nBaumert, J\n\nBeitelshees, AL\n\nBhangale, TR\n\nChen, YD\n\nGaunt, TR\n\nGong, Y\n\nHopewell, JC\n\nJohnson, T\n\nKleber, ME\n\nLangaee, TY\n\nLi, M\n\nLi, YR\n\nLiu, K\n\nMcDonough, CW\n\nMeijs, MF\n\nMiddelberg, RP\n\nMusunuru, K\n\nNelson, CP\n\nO'Connell, JR\n\nPadmanabhan, S\n\nPankow, JS\n\nPankratz, N\n\nRafelt, S\n\nRajagopalan, R\n\nRomaine, SP\n\nSchork, NJ\n\nShaffer, J\n\nShen, H\n\nSmith, EN\n\nTischfield, SE\n\nvan der Most, PJ\n\nvan Vliet-Ostaptchouk, JV\n\nVerweij, N\n\nVolcik, KA\n\nZhang, L\n\nBailey, KR\n\nBailey, KM\n\nBauer, F\n\nBoer, JM\n\nBraund, PS\n\nBurt, A\n\nBurton, PR\n\nBuxbaum, SG\n\nChen, W\n\nCooper-Dehoff, RM\n\nCupples, LA\n\ndeJong, JS\n\nDelles, C\n\nDuggan, D\n\nFornage, M\n\nFurlong, CE\n\nGlazer, N\n\nGums, JG\n\nHastie, C\n\nHolmes, MV\n\nIllig, T\n\nKirkland, SA\n\nKivimaki, M\n\nKlein, R\n\nKlein, BE\n\nKooperberg, C\n\nKottke-Marchant, K\n\nKumari, M\n\nLaCroix, AZ\n\nMallela, L\n\nMurugesan, G\n\nOrdovas, J\n\nOuwehand, WH\n\nPost, WS\n\nSaxena, R\n\nScharnagl, H\n\nSchreiner, PJ\n\nShah, T\n\nShields, DC\n\nShimbo, D\n\nSrinivasan, SR\n\nStolk, RP\n\nSwerdlow, DI\n\nTaylor, HA\n\nTopol, EJ\n\nToskala, E\n\nvan Pelt, JL\n\nvan Setten, J\n\nYusuf, S\n\nWhittaker, JC\n\nZwinderman, AH\n\nLifeLines Cohort Study\n\nAnand, SS\n\nBalmforth, AJ\n\nBerenson, GS\n\nBezzina, CR\n\nBoehm, BO\n\nBoerwinkle, E\n\nCasas, JP\n\nCaulfield, MJ\n\nClarke, R\n\nConnell, JM\n\nCruickshanks, KJ\n\nDavidson, KW\n\nDay, IN\n\nde Bakker, PI\n\nDoevendans, PA\n\nDominiczak, AF\n\nHall, AS\n\nHartman, CA\n\nHengstenberg, C\n\nHillege, HL\n\nHofker, MH\n\nHumphries, SE\n\nJarvik, GP\n\nJohnson, JA\n\nKaess, BM\n\nKathiresan, S\n\nKoenig, W\n\nLawlor, DA\n\nMärz, W\n\nMelander, O\n\nMitchell, BD\n\nMontgomery, GW\n\nMunroe, PB\n\nMurray, SS\n\nNewhouse, SJ\n\nOnland-Moret, NC\n\nPoulter, N\n\nPsaty, B\n\nRedline, S\n\nRich, SS\n\nRotter, JI\n\nSchunkert, H\n\nSever, P\n\nShuldiner, AR\n\nSilverstein, RL\n\nStanton, A\n\nThorand, B\n\nTrip, MD\n\nTsai, MY\n\nvan der Harst, P\n\nvan der Schoot, E\n\nvan der Schouw, YT\n\nVerschuren, WM\n\nWatkins, H\n\nWilde, AA\n\nWolffenbuttel, BH\n\nWhitfield, JB\n\nHovingh, GK\n\nBallantyne, CM\n\nWijmenga, C\n\nReilly, MP\n\nMartin, NG\n\nWilson, JG\n\nRader, DJ\n\nSamani, NJ\n\nReiner, AP\n\nHegele, RA\n\nKastelein, JJ\n\nHingorani, AD\n\nTalmud, PJ\n\nHakonarson, H\n\nElbers, CC\n\nKeating, BJ\n\nDrenos, F\n\nBeiträge in Fachzeitschriften\nISI:000311011400005\n23063622.0\n10.1016/j.ajhg.2012.08.032\nPMC3487124\nGenome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66, 40 individuals of European ancestry was based on the custom ∼50, 00 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2, 00 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24, 36 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.\n\nMärz, Winfried\n\nScharnagl, Hubert\n\n\n"
        },
        {
            "text": "\n140356\nPrevalence and Risk of Down Syndrome in Monozygotic and Dizygotic Multiple Pregnancies in Europe: Implications for Prenatal Screening EDITORIAL COMMENT\n\nBoyle, B\n\nMorris, JK\n\nMcConkey, R\n\nGarne, E\n\nLoane, M\n\nAddor, MC\n\nGatt, M\n\nHaeusler, M\n\nLatos-Bielensk, A\n\nLelong, N\n\nMcDonnell, R\n\nMullaney, C\n\nO'Mahony, M\n\nDolk, H\n\nBeiträge in Fachzeitschriften\nISI:000344453200008\nNone\n10.1097/01.ogx.0000456350.77840.b1\nNone\nDuring the past 20 years, the prevalence of Down syndrome (DS) has increased with the increase in mean maternal age. The prevalence of multiple births has also increased because of older maternal age and use of assisted reproductive technologies. This study was designed to determine the maternal age-specific prevalence of DS in monozygotic and dizygotic pregnancies, assess risk relative to singleton pregnancies, as well as compare prenatal diagnosis and pregnancy outcomes for DS fetuses in multiple and singleton pregnancies. The database of the European Surveillance of Congenital Anomalies includes live-born congenital anomaly cases, stillborn cases and fetal deaths after 20 weeks' gestation, as well as prenatally diagnosed cases resulting in termination of pregnancy for fetal anomaly. The study population consisted of 14, 27, 05 pregnancies between 1990 and 2009, of which 2.89% were multiple gestations. Individual fetuses/babies with DS from multiple and singleton pregnancies were considered cases. Twin pairs with both twins having DS were concordant pairs. Relative risk (RR) with the 95% confidence interval (CI) was used to estimate the prevalence of cases with DS among multiple births relative to that among singleton births. From 1990 to 1999, the total corrected prevalence of DS cases from multiple pregnancies as opposed to singleton pregnancies per 10, 00 births was 0.40 (95% CI, 0.36-0.45), rising to 0.47 (95% CI, 0.42-0.53) in 2000 to 2009 (P > 0.05). Overall (1990-2009), the prevalence of DS cases per 10, 00 multiple births was 15.1 (95% CI, 14.6-15.9); and per 10, 00 singleton births, 20.1 (95% CI, 19.9-20.3). The prevalence of DS cases per 10, 00 multiple births rose with age of 44 years or younger, after which it was considerably lower. The adjusted RR of DS for babies from multiple births relative to singleton births was 0.58 (95% CI, 0.53-0.62). Of 19, 97 babies born to mothers older than 44 years, 2043 (10.5%) were from multiple births. Only 1 fetus from a multiple pregnancy was a DS case, a prevalence of 4.48 (95% CI, 0.67-35.1) per 10, 00 multiple births, compared with 562 singleton DS cases, a prevalence of 327 (95% CI, 301-356) per 10, 00 singleton births (RR, 0.015; 95% CI, 0.002-0.107). In 8.7% (n = 54) of affected pairs, the twins were concordant for DS, 51 same-sex twin pairs and 3 unlike-sex twin pairs. The maternal age-adjusted RR of a monozygotic pregnancy being affected was 0.34 (95% CI, 0.25-0.44) compared with singleton pregnancies. No affected monozygotic twin pregnancies occurred in the group older than 44 years. For dizygotic pregnancies, the maternal age-adjusted RR of at least 1 twin being affected was 1.34 (95% CI, 1.23-1.46) compared with singleton pregnancies. For age older than 44 years, the RR was 0.04 (95% CI, 0.01-0.27). The proportion of DS cases prenatally diagnosed was lower for multiple than for singleton pregnancies at all maternal ages, for an overall maternal age-adjusted odds ratio (OR) of 0.62 (95% CI, 0.50-0.78). The overall proportion of termination of pregnancy for fetal anomaly cases from multiple pregnancies was lower than singletons at every maternal age, giving an overall maternal age-adjusted OR of 0.52 (95% CI, 0.41-0.65). Down syndrome cases from multiple births were not more likely to be stillbirths/fetal deaths than from singleton births; the maternal age-adjusted OR was 1.03 (95% CI, 0.59-1.78). Individual fetuses from twin pregnancies are at lower risk for DS than those from singleton pregnancies. The estimates of the lower maternal age-specific DS risk in twin pregnancies, combined with the clinician's knowledge of zygosity/chorionicity and maternal age at ovulation for women having assisted reproductive technologies, should allow more accurate risk estimates for genetic counseling and prenatal screening.\n\n\n"
        },
        {
            "text": "\n128814\nCommon variants at 12q15 and 12q24 are associated with infant head circumference.\n\nTaal, HR\n\nSt Pourcain, B\n\nThiering, E\n\nDas, S\n\nMook-Kanamori, DO\n\nWarrington, NM\n\nKaakinen, M\n\nKreiner-Møller, E\n\nBradfield, JP\n\nFreathy, RM\n\nGeller, F\n\nGuxens, M\n\nCousminer, DL\n\nKerkhof, M\n\nTimpson, NJ\n\nIkram, MA\n\nBeilin, LJ\n\nBønnelykke, K\n\nBuxton, JL\n\nCharoen, P\n\nChawes, BL\n\nEriksson, J\n\nEvans, DM\n\nHofman, A\n\nKemp, JP\n\nKim, CE\n\nKlopp, N\n\nLahti, J\n\nLye, SJ\n\nMcMahon, G\n\nMentch, FD\n\nMüller-Nurasyid, M\n\nO'Reilly, PF\n\nProkopenko, I\n\nRivadeneira, F\n\nSteegers, EA\n\nSunyer, J\n\nTiesler, C\n\nYaghootkar, H\n\nCohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) Consortium\n\nIkram, MA\n\nFornage, M\n\nSmith, AV\n\nSeshadri, S\n\nSchmidt, R\n\nDebette, S\n\nVrooman, HA\n\nSigurdsson, S\n\nRopele, S\n\nCoker, LH\n\nLongstreth, WT\n\nNiessen, WJ\n\nDestefano, AL\n\nBeiser, A\n\nZijdenbos, AP\n\nStruchalin, M\n\nJack, CR\n\nNalls, MA\n\nAu, R\n\nHofman, A\n\nGudnason, H\n\nvan der Lugt, A\n\nHarris, TB\n\nMeeks, WM\n\nVernooij, MW\n\nvan Buchem, MA\n\nCatellier, D\n\nGudnason, V\n\nWindham, BG\n\nWolf, PA\n\nvan Duijn, CM\n\nMosley, TH\n\nSchmidt, H\n\nLauner, LJ\n\nBreteler, MM\n\nDecarli, C\n\nBreteler, MM\n\nDebette, S\n\nFornage, M\n\nGudnason, V\n\nLauner, LJ\n\nvan der Lugt, A\n\nMosley, TH\n\nSeshadri, S\n\nSmith, AV\n\nVernooij, MW\n\nEarly Genetics & Lifecourse Epidemiology (EAGLE) Consortium\n\nAng, W\n\nvan Beijsterveldt, T\n\nBergen, N\n\nBenke, K\n\nBerry, D\n\nBradfield, JP\n\nCharoen, P\n\nCoin, L\n\nCousminer, DL\n\nDas, S\n\nElliott, P\n\nEvans, DM\n\nFrayling, T\n\nFreathy, RM\n\nGaillard, R\n\nGroen-Blokhuis, M\n\nGuxens, M\n\nHadley, D\n\nHottenga, JJ\n\nHuikari, V\n\nHypponen, E\n\nKaakinen, M\n\nKowgier, M\n\nLawlor, DA\n\nLewin, A\n\nLindgren, C\n\nMarsh, J\n\nMiddeldorp, C\n\nMillwood, I\n\nMook-Kanamori, DO\n\nNivard, M\n\nO'Reilly, PF\n\nPalmer, LJ\n\nProkopenko, I\n\nRodriguez, A\n\nSebert, S\n\nSovio, U\n\nSt Pourcain, B\n\nStandl, M\n\nStrachan, DP\n\nSunyer, J\n\nTaal, HR\n\nThiering, E\n\nTiesler, C\n\nUitterlinden, AG\n\nValcárcel, B\n\nWarrington, NM\n\nWhite, S\n\nWillemsen, G\n\nYaghootkar, H\n\nBoomsma, DI\n\nEstivill, X\n\nGrant, SF\n\nHakonarson, H\n\nHattersley, AT\n\nHeinrich, J\n\nJaddoe, VW\n\nJarvelin, MR\n\nMcCarthy, MI\n\nPennell, CE\n\nPower, C\n\nTimpson, NJ\n\nWiden, E\n\nBlakemore, AI\n\nChiavacci, RM\n\nFeenstra, B\n\nFernandez-Banet, J\n\nGrant, SF\n\nHartikainen, AL\n\nvan der Heijden, AJ\n\nIñiguez, C\n\nLathrop, M\n\nMcArdle, WL\n\nMølgaard, A\n\nNewnham, JP\n\nPalmer, LJ\n\nPalotie, A\n\nPouta, A\n\nRing, SM\n\nSovio, U\n\nStandl, M\n\nUitterlinden, AG\n\nWichmann, HE\n\nVissing, NH\n\nDecarli, C\n\nvan Duijn, CM\n\nMcCarthy, MI\n\nKoppelman, GH\n\nEstivill, X\n\nHattersley, AT\n\nMelbye, M\n\nBisgaard, H\n\nPennell, CE\n\nWiden, E\n\nHakonarson, H\n\nSmith, GD\n\nHeinrich, J\n\nJarvelin, MR\n\nJaddoe, VW\n\nEarly Growth Genetics (EGG) Consortium\n\nAdair, LS\n\nAng, W\n\nAtalay, M\n\nvan Beijsterveldt, T\n\nBergen, N\n\nBenke, K\n\nBerry, D\n\nBradfield, JP\n\nCharoen, P\n\nCoin, L\n\nCousminer, DL\n\nDas, S\n\nDavis, OS\n\nElliott, P\n\nEvans, DM\n\nFeenstra, B\n\nFlexeder, C\n\nFrayling, T\n\nFreathy, RM\n\nGaillard, R\n\nGeller, F\n\nGroen-Blokhuis, M\n\nGoh, LK\n\nGuxens, M\n\nHaworth, CM\n\nHadley, D\n\nHedebrand, J\n\nHinney, A\n\nHirschhorn, JN\n\nHolloway, JW\n\nHolst, C\n\nHottenga, JJ\n\nHorikoshi, M\n\nHuikari, V\n\nHypponen, E\n\nIñiguez, C\n\nKaakinen, M\n\nKilpeläinen, TO\n\nKirin, M\n\nKowgier, M\n\nLakka, HM\n\nLange, LA\n\nLawlor, DA\n\nLehtimäki, T\n\nLewin, A\n\nLindgren, C\n\nLindi, V\n\nMaggi, R\n\nMarsh, J\n\nMiddeldorp, C\n\nMillwood, I\n\nMook-Kanamori, DO\n\nMurray, JC\n\nNivard, M\n\nNohr, EA\n\nNtalla, I\n\nOken, E\n\nO'Reilly, PF\n\nPalmer, LJ\n\nPanoutsopoulou, K\n\nPararajasingham, J\n\nProkopenko, I\n\nRodriguez, A\n\nSalem, RM\n\nSebert, S\n\nSiitonen, N\n\nSovio, U\n\nSt Pourcain, B\n\nStrachan, DP\n\nSunyer, J\n\nTaal, HR\n\nTeo, YY\n\nThiering, E\n\nTiesler, C\n\nUitterlinden, AG\n\nValcárcel, B\n\nWarrington, NM\n\nWhite, S\n\nWillemsen, G\n\nYaghootkar, H\n\nZeggini, E\n\nBoomsma, DI\n\nCooper, C\n\nEstivill, X\n\nGillman, M\n\nGrant, SF\n\nHakonarson, H\n\nHattersley, AT\n\nHeinrich, J\n\nHocher, B\n\nJaddoe, VW\n\nJarvelin, MR\n\nLakka, TA\n\nMcCarthy, MI\n\nMelbye, M\n\nMohlke, KL\n\nDedoussis, GV\n\nOng, KK\n\nPearson, ER\n\nPennell, CE\n\nPrice, TS\n\nPower, C\n\nRaitakari, OT\n\nSaw, SM\n\nScherag, A\n\nSimell, O\n\nTimpson, NJ\n\nWiden, E\n\nWilson, JF\n\nBeiträge in Fachzeitschriften\nISI:000319563900025\nNone\n10.1038/ng0613-713a\nNone\nNone\n\nRopele, Stefan\n\nSchmidt, Reinhold\n\n\n"
        },
        {
            "text": "\n175528\nEfficacy and safety of oral semaglutide with flexible dose adjustment versus sitagliptin in type 2 diabetes (PIONEER 7): a multicentre, open-label, randomised, phase 3a trial.\n\nPieber, TR\n\nBode, B\n\nMertens, A\n\nCho, YM\n\nChristiansen, E\n\nHertz, CL\n\nWallenstein, SOR\n\nBuse, JB\n\nPIONEER 7 investigators\n\nBeiträge in Fachzeitschriften\nISI:000471906500013\n31189520.0\n10.1016/S2213-8587(19)30194-9\nNone\nOral semaglutide is the first oral formulation of a glucagon-like peptide-1 (GLP-1) receptor agonist developed for the treatment of type 2 diabetes. We aimed to compare the efficacy and safety of flexible dose adjustments of oral semaglutide with sitagliptin 100 mg.\n                In this 52-week, multicentre, randomised, open-label, phase 3a trial, we recruited patients with type 2 diabetes from 81 sites in ten countries. Patients were eligible if they were aged 18 years or older (19 years or older in South Korea), had type 2 diabetes (diagnosed ≥90 days before screening), HbA1c of 7·5-9·5% (58-80 mmol/mol), and were inadequately controlled on stable daily doses of one or two oral glucose-lowering drugs (for 90 days or more before screening). Participants were randomly assigned (1:1) by use of an interactive web-response system, stratified by background glucose-lowering medication at screening, to oral semaglutide with flexible dose adjustments to 3, 7, or 14 mg once daily or sitagliptin 100 mg once daily. To approximate treatment individualisation in clinical practice, oral semaglutide dose could be adjusted on the basis of prespecified HbA1c and tolerability criteria. Two efficacy-related estimands were prespecified: treatment policy (regardless of treatment discontinuation or use of rescue medication) and trial product (on treatment and without use of rescue medication) for participants randomly assigned to treatment. The primary endpoint was achievement of HbA1c of less than 7% (53 mmol/mol) at week 52 and the confirmatory secondary efficacy endpoint was change in bodyweight from baseline to week 52. Safety was assessed in all participants who received at least one dose of study drug. This trial is registered with ClinicalTrials.gov, number NCT02849080, and European Clinical Trials Database, EudraCT number 2015-005593-38, and an open-label extension is ongoing.\n                Between Sept 20, 2016, and Feb 7, 2017, of 804 patients assessed for eligibility, 504 were eligible and randomly assigned to oral semaglutide (n=253) or sitagliptin (n=251). Most participants were male (285 [57%] of 504) with a mean age of 57·4 years (SD 9·9). All participants were given at least one dose of their allocated study drug except for one participant in the sitagliptin group. From a mean baseline HbA1c of 8·3% (SD 0·6%; 67 mmol/mol [SD 6·4]), a greater proportion of participants achieved an HbA1c of less than 7% with oral semaglutide than did with sitagliptin (treatment policy estimand: 58% [134 of 230] vs 25% [60 of 238]; and trial product estimand: 63% [123 of 196] vs 28% [52 of 184]). The odds of achieving an HbA1c of less than 7% was significantly better with oral semaglutide than sitagliptin (treatment policy estimand: odds ratio [OR] 4·40, 95% CI 2·89-6·70, p<0·0001; and trial product estimand: 5·54, 3·54-8·68, p<0·0001). The odds of decreasing mean bodyweight from baseline to week 52 were higher with oral semaglutide than with sitagliptin (estimated mean change in bodyweight, treatment policy estimand: -2·6 kg [SE 0·3] vs -0·7 kg [SE 0·2], estimated treatment difference [ETD] -1·9 kg, 95% CI -2·6 to -1·2; p<0·0001; and trial product estimand: -2·9 kg [SE 0·3] vs -0·8 kg [SE 0·3], ETD -2·2 kg, -2·9 to -1·5; p<0·0001). Adverse events occurred in 197 (78%) of 253 participants in the oral semaglutide group versus 172 (69%) of 250 in the sitagliptin group, and nausea was the most common adverse event with oral semaglutide (53 [21%]). Two deaths occurred in the sitagliptin group during the trial.\n                Oral semaglutide, with flexible dose adjustment, based on efficacy and tolerability, provided superior glycaemic control and weight loss compared with sitagliptin, and with a safety profile consistent with subcutaneous GLP-1 receptor agonists.\n                Novo Nordisk A/S.\n                Copyright © 2019 Elsevier Ltd. All rights reserved.\n\nPieber, Thomas\n\n\n"
        },
        {
            "text": "\n171105\nShort-acting insulin analogues versus regular human insulin for adult, non-pregnant persons with type 2 diabetes mellitus.\n\nFullerton, B\n\nSiebenhofer, A\n\nJeitler, K\n\nHorvath, K\n\nSemlitsch, T\n\nBerghold, A\n\nGerlach, FM\n\nBeiträge in Fachzeitschriften\nISI:000455302700023\n30556900.0\n10.1002/14651858.CD013228\nNone\nThe use of short-acting insulin analogues (insulin lispro, insulin aspart, insulin glulisine) for adult, non-pregnant people with type 2 diabetes is still controversial, as reflected in many scientific debates.\n                To assess the effects of short-acting insulin analogues compared to regular human insulin in adult, non-pregnant people with type 2 diabetes mellitus.\n                For this update we searched CENTRAL, MEDLINE, Embase, the WHO ICTRP Search Portal, and ClinicalTrials.gov to 31 October 2018. We placed no restrictions on the language of publication.\n                We included all randomised controlled trials with an intervention duration of at least 24 weeks that compared short-acting insulin analogues to regular human insulin in the treatment of people with type 2 diabetes, who were not pregnant.\n                Two review authors independently extracted data and assessed the risk of bias. We assessed dichotomous outcomes by risk ratios (RR), and Peto odds ratios (POR), with 95% confidence intervals (CI). We assessed continuous outcomes by mean differences (MD) with 95% CI. We assessed trials for certainty of the evidence using the GRADE approach.\n                We identified 10 trials that fulfilled the inclusion criteria, randomising 2751 participants; 1388 participants were randomised to receive insulin analogues and 1363 participants to receive regular human insulin. The duration of the intervention ranged from 24 to 104 weeks, with a mean of about 41 weeks. The trial populations showed diversity in disease duration, and inclusion and exclusion criteria. None of the trials were blinded, so the risk of performance bias and detection bias, especially for subjective outcomes, such as hypoglycaemia, was high in nine of 10 trials from which we extracted data. Several trials showed inconsistencies in the reporting of methods and results.None of the included trials defined all-cause mortality as a primary outcome. Six trials provided Information on the number of participants who died during the trial, with five deaths out of 1272 participants (0.4%) in the insulin analogue groups and three deaths out of 1247 participants (0.2%) in the regular human insulin groups (Peto OR 1.66, 95% CI 0.41 to 6.64; P = 0.48; moderate-certainty evidence). Six trials, with 2509 participants, assessed severe hypoglycaemia differently, therefore, we could not summarise the results with a meta-analysis. Overall, the incidence of severe hypoglycaemic events was low, and none of the trials showed a clear difference between the two intervention arms (low-certainty evidence).The MD in glycosylated haemoglobin A1c (HbA1c) change was -0.03% (95% CI -0.16 to 0.09; P = 0.60; 9 trials, 2608 participants; low-certainty evidence). The 95% prediction ranged between -0.31% and 0.25%. The MD in the overall number of non-severe hypoglycaemic episodes per participant per month was 0.08 events (95% CI 0.00 to 0.16; P = 0.05; 7 trials, 2667 participants; very low-certainty evidence). The 95% prediction interval ranged between -0.03 and 0.19 events per participant per month. The results provided for nocturnal hypoglycaemic episodes were of questionable validity. Overall, there was no clear difference between the two short-acting insulin analogues and regular human insulin. Two trials assessed health-related quality of life and treatment satisfaction, but we considered the results for both outcomes to be unreliable (very low-certainty evidence).No trial was designed to investigate possible long term effects (all-cause mortality, microvascular or macrovascular complications of diabetes), especially in participants with diabetes-related complications. No trial reported on socioeconomic effects.\n                Our analysis found no clear benefits of short-acting insulin analogues over regular human insulin in people with type 2 diabetes. Overall, the certainty of the evidence was poor and results on patient-relevant outcomes, like all-cause mortality, microvascular or macrovascular complications and severe hypoglycaemic episodes were sparse. Long-term efficacy and safety data are needed to draw conclusions about the effects of short-acting insulin analogues on patient-relevant outcomes.\n\nBerghold, Andrea\n\nHorvath, Karl\n\nJeitler, Klaus\n\nSemlitsch, Thomas\n\nSiebenhofer-Kroitzsch, Andrea\n\n\n"
        },
        {
            "text": "\n160472\n10 years of denosumab treatment in postmenopausal women with osteoporosis: results from the phase 3 randomised FREEDOM trial and open-label extension.\n\nBone, HG\n\nWagman, RB\n\nBrandi, ML\n\nBrown, JP\n\nChapurlat, R\n\nCummings, SR\n\nCzerwiński, E\n\nFahrleitner-Pammer, A\n\nKendler, DL\n\nLippuner, K\n\nReginster, JY\n\nRoux, C\n\nMalouf, J\n\nBradley, MN\n\nDaizadeh, NS\n\nWang, A\n\nDakin, P\n\nPannacciulli, N\n\nDempster, DW\n\nPapapoulos, S\n\nBeiträge in Fachzeitschriften\nISI:000403672400017\n28546097.0\n10.1016/S2213-8587(17)30138-9\nNone\nLong-term safety and efficacy of osteoporosis treatment are important because of the chronic nature of the disease. We aimed to assess the long-term safety and efficacy of denosumab, which is widely used for the treatment of postmenopausal women with osteoporosis.\n                In the multicentre, randomised, double-blind, placebo-controlled, phase 3 FREEDOM trial, postmenopausal women aged 60-90 years with osteoporosis were enrolled in 214 centres in North America, Europe, Latin America, and Australasia and were randomly assigned (1:1) to receive 60 mg subcutaneous denosumab or placebo every 6 months for 3 years. All participants who completed the FREEDOM trial without discontinuing treatment or missing more than one dose of investigational product were eligible to enrol in the open-label, 7-year extension, in which all participants received denosumab. The data represent up to 10 years of denosumab exposure for women who received 3 years of denosumab in FREEDOM and continued in the extension (long-term group), and up to 7 years for women who received 3 years of placebo and transitioned to denosumab in the extension (crossover group). The primary outcome was safety monitoring, comprising assessments of adverse event incidence and serious adverse event incidence, changes in safety laboratory analytes (ie, serum chemistry and haematology), and participant incidence of denosumab antibody formation. Secondary outcomes included new vertebral, hip, and non-vertebral fractures as well as bone mineral density (BMD) at the lumbar spine, total hip, femoral neck, and one-third radius. Analyses were done according to the randomised FREEDOM treatment assignments. All participants who received at least one dose of investigational product in FREEDOM or the extension were included in the combined safety analyses. All participants who enrolled in the extension with observed data were included in the efficacy analyses. The FREEDOM trial (NCT00089791) and its extension (NCT00523341) are both registered with ClinicalTrials.gov.\n                Between Aug 3, 2004, and June 1, 2005, 7808 women were enrolled in the FREEDOM study. 5928 (76%) women were eligible for enrolment in the extension, and of these, 4550 (77%) were enrolled (2343 long-term, 2207 crossover) between Aug 7, 2007, and June 20, 2008. 2626 women (1343 long-term; 1283 crossover) completed the extension. The yearly exposure-adjusted participant incidence of adverse events for all individuals receiving denosumab decreased from 165·3 to 95·9 per 100 participant-years over the course of 10 years. Serious adverse event rates were generally stable over time, varying between 11·5 and 14·4 per 100 participant-years. One atypical femoral fracture occurred in each group during the extension. Seven cases of osteonecrosis of the jaw were reported in the long-term group and six cases in the crossover group. The yearly incidence of new vertebral fractures (ranging from 0·90% to 1·86%) and non-vertebral fractures (ranging from 0·84% to 2·55%) remained low during the extension, similar to rates observed in the denosumab group during the first three years of the FREEDOM study, and lower than rates projected for a virtual long-term placebo cohort. In the long-term group, BMD increased from FREEDOM baseline by 21·7% at the lumbar spine, 9·2% at total hip, 9·0% at femoral neck, and 2·7% at the one-third radius. In the crossover group, BMD increased from extension baseline by 16·5% at the lumbar spine, 7·4% at total hip, 7·1% at femoral neck, and 2·3% at one-third radius.\n                Denosumab treatment for up to 10 years was associated with low rates of adverse events, low fracture incidence compared with that observed during the original trial, and continued increases in BMD without plateau.\n                Amgen.\n                Copyright © 2017 Elsevier Ltd. All rights reserved.\n\nFahrleitner-Pammer, Astrid\n\n\n"
        },
        {
            "text": "\n2074\nPrevention of CNS recurrence in childhood ALL: results with reduced radiotherapy combined with CNS-directed chemotherapy in four consecutive ALL-BFM trials.\n\nSchrappe, M\n\nReiter, A\n\nHenze, G\n\nNiemeyer, C\n\nBode, U\n\nKühl, J\n\nGadner, H\n\nHavers, W\n\nPlüss, H\n\nKornhuber, B\n\nZintl, F\n\nRitter, J\n\nUrban, C\n\nNiethammer, D\n\nRiehm, H\n\nBeiträge in Fachzeitschriften\nISI:000075354500009\n9743952.0\n10.1055/s-2008-1043878\nNone\nBACKGROUND: The introduction of cranial radiotherapy (CRT) has provided efficient control of overt or subclinical meningeosis in acute lymphoblastic leukemia (ALL). Especially due to the long-term toxicity of CRT, reduction or elimination of radiotherapy appeared mandatory after cure rates of more than 70% had been achieved in ALL. The Berlin-Frankfurt-Münster (BFM) Study Group initiated several attempts in certain ALL subgroups to omit or reduce CRT while using more CNS-directed chemotherapy but without extended intrathecal treatment during maintenance therapy. This analysis summarizes the essential results that are in particular relevant because irradiation of the central nervous system (CNS) has been further reduced in the most recent trial ALL-BFM 95. PATIENTS AND METHODS: More than 4000 patients enrolled between 1981 and 1995 in one of the last four ALL-BFM trials have been analyzed to demonstrate the efficiency of intensive systemic and intrathecal chemotherapy with or without reduced CRT in the prevention of CNS relapses. RESULTS: In trial ALL-BFM81, it was shown that only in low-risk (LR) patients preventive radiotherapy can be replaced safely by intermediate dose (0.5 g/m2) methotrexate (MHD-MTX). In intermediate risk (IR) patients this attempt failed: IR pts had 8 times more CNS relapses if treated by MHD-MTX without CRT. In the subsequent trial ALL-BFM 83, all pts received MHD-MTX. IR pts were randomly treated with 12 or 18 Gy of preventive CRT which did not result in a significantly different outcome. The results from the subsequent trial ALL-BFM 86, using a more intensive consolidation with high-dose methotrexate (HD-MTX), demonstrated that the elimination of CRT in low-risk ALL, the reduced CRT of 12 Gy for IR, 18 Gy for medium (MR), and the reduced CRT with 18 Gy for high risk (HR) ALL, respectively, was justified: the incidence of relapses with CNS involvement was reduced to less than 5% (Reiter et al. 1994, Blood 84: 3122). When even less intensive preventive CRT (12 Gy for all medium and high risk patients) was used in trial ALL-BFM 90, the rate of CNS-related relapses was again below 5%. HR patients now treated with more CNS-directed chemotherapy had the lowest rate of CNS-related relapses observed so far in the BFM trials, even though CRT was also reduced to 12 Gy. Patients with T-cell ALL were shown to be protected from CNS recurrence by the combination of CRT (12 Gy) and HD-MTX more effectively than by HD-MTX in consolidation and TIT therapy during maintenance, especially if they presented with high WBC as shown in a joint AIEOP/BFM analysis (Conter et al. 1997, JCO 15: 2786). Patients with overt meningeosis which are characterized by a high leukemic cell load at diagnosis had a rate of recurrences that was comparable to that of patients with high WBC but no CNS disease. CONCLUSION: Low-risk ALL patients can be efficiently prevented from CNS relapse by intensive systemic and intrathecal chemotherapy without CRT. Patients with intermediate or medium risk ALL, including T-cell ALL, did not suffer from more CNS or systemic relapses when CRT was reduced to only 12 Gy. Patients with inadequate response to therapy are at particularly high risk for relapse with CNS involvement. Therefore, more CNS-directed systemic and intrathecal chemotherapy was applied in trial ALL-BFM 90, combined with only 12 Gy cranial irradiation, and improved the control of CNS recurrence. It seems likely that larger subsets of B-precursor ALL can be protected from CNS-related relapse by intensive chemotherapy without extended IT treatment and without CRT. This is being investigated in the ongoing trial ALL-BFM 95.\n\nUrban, Ernst-Christian\n\n\n"
        },
        {
            "text": "\n1626\nMediation by bradykinin of rat paw oedema induced by collagenase from Clostridium histolyticum.\n\nLegat, FJ\n\nGriesbacher, T\n\nLembeck, F\n\nBeiträge in Fachzeitschriften\nISI:A1994NN63600020\n7915609.0\n10.1111/j.1476-5381.1994.tb13094.x\nPMC1910340\n1. Collagenases are thought to play a major role in the pathology of gas gangrene caused by Clostridium histolyticum, because they can destroy the connective tissue barriers. We investigated possible mediators involved in the oedema formation and plasma protein extravasation which follow the injection of a collagenase (EC 3.4.24.3) from Clostridium histolyticum into one hind paw of anaesthetized rats. 2. The magnitude of the oedema following a subplantar injection was dependent on the dose of collagenase (30, 100 and 300 micrograms) injected. It reached its maximum within 30 min and remained unchanged for at least 5 h. Plasma protein extravasation into the paw was most pronounced within 20 min of the injection. Heat-inactivated collagenase was ineffective. 3. The B2 bradykinin (BK) antagonist icatibant (D-Arg-[Hyp3-Thi5-D-Tic7- Oic8] bradykinin, formerly named Hoe-140) reduced oedema formation in a dose-dependent manner with a maximal reduction of around 65% at a dose of 100 nmol kg-1 (s.c.). A significant effect could already be observed at a dose of 10 nmol kg-1. The duration of the effect of icatibant (100 nmol kg-1) was found to be at least 3 h. These results demonstrate the high potency and long duration of action of icatibant. Pretreatment of rats with the bradykinin B1 antagonist, des-Arg9-[Leu8]-BK did not affect collagenase-induced paw oedema. Thus, the observed collagenase-induced effects are mainly mediated by BK through activation of B2 receptors. 4. Pretreatment of adult rats with capsaicin (125 mg kg-1, s.c.) three weeks before the collagenase injection caused a significant attenuation of the paw oedema and of plasma extravasation but was significantly less effective than icatibant (100 nmol kg-1, s.c.). The non-peptide substance P antagonist, P-96, 45 (l0 micromol kg-1, i.v.) significantly reduced collagenase-induced oedema formation to a degree comparable with that seen after capsaicin pretreatment. The inhibition by the substance P antagonist was significantly smaller than that seen after icatibant. The inhibitory effect of icatibant in capsaicin pretreated rats, or of icatibant together with CP-96, 45 in untreated rats, was not greater than that oficatibant alone in rats treated with the vehicle for either capsaicin or CP-96, 45. CP-96, 44(10 micromol kg-1, i.v.), the inactive enantiomer of CP-96, 45, did not affect collagenase-induced paw oedema. In capsaicin-pretreated rats, CP-96, 45 (10 micromol kg-1, i.v.) did not reduce collagenase-induced paw oedema.The subplantar injection of bradykinin (30 nmol) induced a paw oedema comparable with that induced by collagenase (100 microg). CP-96, 45 (10 micromol kg-1, i.v.), but not CP-96, 44 (1O micromol kg-1, i.v.), ignificantly reduced the bradykinin-induced paw oedema. These findings indicate that collagenase leads to the release of bradykinin; bradykinin then stimulates afferent C-fibre terminals and causes the release of substance P and probably also neurokinin A, which augment the oedema-inducing effect of bradykinin.5. Indomethacin or mepyramine plus cimetidine failed to inhibit collagenase-induced paw oedema.Thus, prostaglandins and histamine do not seem to be involved in collagenase-induced paw oedema.6. After subplantar injection of collagenase, the sensitivity scores in a modified formalin-test rapidly increased during the first 10 min. This increase was abolished by pretreatment with icatibant(100 nmol kg-1, s.c.) indicating that the stimulation of nociceptive afferent neurones following injection of collagenase is due to the action of released kinins.7. In conclusion, bradykinin appears to be the main mediator of inflammation induced by a collagenase from Clostridium histolyticum. As well as having direct relevance to a known pathological condition, ollagenase-induced paw oedema could prove to be a useful model in inflammation research and in the investigation of bradykinin antagonists. The present results might provide an experimental basis for clinical investigations of the effects of icatibant in infectious diseases where the release of collagenases from bacteria causes rapid spreading of inflammation.\n\nGriesbacher, Thomas\n\nLegat, Franz\n\n\n"
        },
        {
            "text": "\n178415\nNew hemodynamic definition of pulmonary hypertension A critical appraisal of the German Pediatric Pulmonary Vascular Disease Network of the German Society of Pediatric Cardiology\n\nApitz, C\n\nAbdul-Khaliq, H\n\nAlbini, S\n\nBeerbaum, P\n\nDubowy, KO\n\nGorenflo, M\n\nHager, A\n\nHansmann, G\n\nHilgendorff, A\n\nHumpl, T\n\nKaestner, M\n\nKoestenberger, M\n\nKozlik-Feldmann, R\n\nLatus, H\n\nMichel-Behnke, I\n\nMiera, O\n\nQuandt, D\n\nSallmon, H\n\nSchranz, D\n\nSchulze-Neick, I\n\nStiller, B\n\nWarnecke, G\n\nPattathu, J\n\nLammers, AE\n\nBeiträge in Fachzeitschriften\nISI:000493356600001\nNone\n10.1007/s00112-019-00792-z\nNone\nPulmonary hypertension (PH) is a pathological elevation of pulmonary pressure and is associated with a heterogeneous spectrum of diseases affecting the pulmonary vasculature. The most common etiologies in children are idiopathic pulmonary arterial hypertension (IPAH), hereditary pulmonary arterial hypertension (HPAH) and PH associated with congenital heart disease (PH-CHD). According to international guidelines, PH used to be defined as elevation of the mean pulmonary arterial pressure (mPAP) >= 25mmHg at rest. In children, particularly with congenital heart disease and a shunt lesion, pulmonary vascular resistance (PVR, indexed to body surface area, PVRi) has been used for years as an adjunct diagnostic criterion to distinguish high-flow PH from pulmonary hypertensive vascular disease (PHVD) with an increase in PVR. A PVRi >= 3 WU center dot m(2)BSA suggests the presence of PHVD, which has a precapillary component (if a normal or reduced cardiac output is present). At the latest World Symposium on Pulmonary Hypertension (WSPH) in 2018 in Nice a new definition of PH has been introduced with a lower cut-off value for a normal mPAP from 24 to 20 mmHg. This is motivated by register studies in adult PH patients in whom a higher mortality has been shown with these lower mPAP levels. Although not uniformly welcomed by all pediatric cardiologists, this new definition (mPAP >20mmHg) has been accepted by the Pediatric Task Force of the WSPH to establish a uniform language and facilitate transition to adult services. The authors would like to emphasize, that there are no published pediatric data demonstrating, that a mild elevation of the mPAP of 21-24mmHg (according to the new definition) has a similar impact in children and leads to adverse outcomes and increased mortality. Hence no change in treatment strategies can be derived on the basis of the new definition to date. Randomized controlled studies in children with PH are sparse, evidence-based pediatric therapeutic strategies are lacking and experience is mostly adopted from adult guidelines. All available studies testing safety and efficacy of medical treatment in PAH have been performed mainly in adult patients, with inclusion criteria according to the former definition of mPAP >= 25mmHg. From the authors' point of view, the indication for using advanced treatment on the basis of the new definition (mPAP >20mmHg) is debatable. In most children and adolescents with PH advanced medical treatment is still only warranted if mPAP exceeds >= 25mmHg. Indications for treatment are often a patient-tailored decision, depending on PH etiology and other driving factors. For individual (symptomatic) patients with only mild elevation of the mPAP (21-24mmHg) and increase of PVRi >= 3 WU center dot m(2)BSA, targeted therapy may be indicated. Because of the complexity and heterogeneity of PH in childhood and adolescence, children should be referred to pediatric cardiology centers with PH expertise. Independent of clinical severity at presentation, the decision for the indication for PAH-specific therapy should be addressed by experienced PH specialists and children should be linked to PH clinics. Conclusion. Counselling patients and parents on the implications of the new PH definition (mPAP >20mmHg) is paramount. To date there are no therapeutic consequences, even though a child may fulfil contemporary criteria according to the new definition with mPAP of 21-24mmHg. Summary. The definition of PH has changed in 2018 (WSPH, Nice) to mPAP >20mmHg. Because of lacking evidence this change of definition does not necessarily result in any changes to currently applied pharmaceutical strategies in children.\n\nKoestenberger, Martin\n\n\n"
        },
        {
            "text": "\n144305\nA novel Alzheimer disease locus located near the gene encoding tau protein.\n\nJun, G\n\nIbrahim-Verbaas, CA\n\nVronskaya, M\n\nLambert, JC\n\nChung, J\n\nNaj, AC\n\nKunkle, BW\n\nWang, LS\n\nBis, JC\n\nBellenguez, C\n\nHarold, D\n\nLunetta, KL\n\nDestefano, AL\n\nGrenier-Boley, B\n\nSims, R\n\nBeecham, GW\n\nSmith, AV\n\nChouraki, V\n\nHamilton-Nelson, KL\n\nIkram, MA\n\nFievet, N\n\nDenning, N\n\nMartin, ER\n\nSchmidt, H\n\nKamatani, Y\n\nDunstan, ML\n\nValladares, O\n\nLaza, AR\n\nZelenika, D\n\nRamirez, A\n\nForoud, TM\n\nChoi, SH\n\nBoland, A\n\nBecker, T\n\nKukull, WA\n\nvan der Lee, SJ\n\nPasquier, F\n\nCruchaga, C\n\nBeekly, D\n\nFitzpatrick, AL\n\nHanon, O\n\nGill, M\n\nBarber, R\n\nGudnason, V\n\nCampion, D\n\nLove, S\n\nBennett, DA\n\nAmin, N\n\nBerr, C\n\nTsolaki, M\n\nBuxbaum, JD\n\nLopez, OL\n\nDeramecourt, V\n\nFox, NC\n\nCantwell, LB\n\nTárraga, L\n\nDufouil, C\n\nHardy, J\n\nCrane, PK\n\nEiriksdottir, G\n\nHannequin, D\n\nClarke, R\n\nEvans, D\n\nMosley, TH\n\nLetenneur, L\n\nBrayne, C\n\nMaier, W\n\nDe Jager, P\n\nEmilsson, V\n\nDartigues, JF\n\nHampel, H\n\nKamboh, MI\n\nde Bruijn, RF\n\nTzourio, C\n\nPastor, P\n\nLarson, EB\n\nRotter, JI\n\nO'Donovan, MC\n\nMontine, TJ\n\nNalls, MA\n\nMead, S\n\nReiman, EM\n\nJonsson, PV\n\nHolmes, C\n\nSt George-Hyslop, PH\n\nBoada, M\n\nPassmore, P\n\nWendland, JR\n\nSchmidt, R\n\nMorgan, K\n\nWinslow, AR\n\nPowell, JF\n\nCarasquillo, M\n\nYounkin, SG\n\nJakobsdóttir, J\n\nKauwe, JS\n\nWilhelmsen, KC\n\nRujescu, D\n\nNöthen, MM\n\nHofman, A\n\nJones, L\n\nIGAP Consortium\n\nHaines, JL\n\nPsaty, BM\n\nVan Broeckhoven, C\n\nHolmans, P\n\nLauner, LJ\n\nMayeux, R\n\nLathrop, M\n\nGoate, AM\n\nEscott-Price, V\n\nSeshadri, S\n\nPericak-Vance, MA\n\nAmouyel, P\n\nWilliams, J\n\nvan Duijn, CM\n\nSchellenberg, GD\n\nFarrer, LA\n\nBeiträge in Fachzeitschriften\nISI:000367096900014\n25778476.0\n10.1038/mp.2015.23\nPMC4573764\nAPOE ɛ4, the most significant genetic risk factor for Alzheimer disease (AD), may mask effects of other loci. We re-analyzed genome-wide association study (GWAS) data from the International Genomics of Alzheimer's Project (IGAP) Consortium in APOE ɛ4+ (10 352 cases and 9207 controls) and APOE ɛ4- (7184 cases and 26 968 controls) subgroups as well as in the total sample testing for interaction between a single-nucleotide polymorphism (SNP) and APOE ɛ4 status. Suggestive associations (P<1 × 10(-4)) in stage 1 were evaluated in an independent sample (stage 2) containing 4203 subjects (APOE ɛ4+: 1250 cases and 536 controls; APOE ɛ4-: 718 cases and 1699 controls). Among APOE ɛ4- subjects, novel genome-wide significant (GWS) association was observed with 17 SNPs (all between KANSL1 and LRRC37A on chromosome 17 near MAPT) in a meta-analysis of the stage 1 and stage 2 data sets (best SNP, rs2732703, P=5·8 × 10(-9)). Conditional analysis revealed that rs2732703 accounted for association signals in the entire 100-kilobase region that includes MAPT. Except for previously identified AD loci showing stronger association in APOE ɛ4+ subjects (CR1 and CLU) or APOE ɛ4- subjects (MS4A6A/MS4A4A/MS4A6E), no other SNPs were significantly associated with AD in a specific APOE genotype subgroup. In addition, the finding in the stage 1 sample that AD risk is significantly influenced by the interaction of APOE with rs1595014 in TMEM106B (P=1·6 × 10(-7)) is noteworthy, because TMEM106B variants have previously been associated with risk of frontotemporal dementia. Expression quantitative trait locus analysis revealed that rs113986870, one of the GWS SNPs near rs2732703, is significantly associated with four KANSL1 probes that target transcription of the first translated exon and an untranslated exon in hippocampus (P ⩽ 1.3 × 10(-8)), frontal cortex (P ⩽ 1.3 × 10(-9)) and temporal cortex (P⩽1.2 × 10(-11)). Rs113986870 is also strongly associated with a MAPT probe that targets transcription of alternatively spliced exon 3 in frontal cortex (P=9.2 × 10(-6)) and temporal cortex (P=2.6 × 10(-6)). Our APOE-stratified GWAS is the first to show GWS association for AD with SNPs in the chromosome 17q21.31 region. Replication of this finding in independent samples is needed to verify that SNPs in this region have significantly stronger effects on AD risk in persons lacking APOE ɛ4 compared with persons carrying this allele, and if this is found to hold, further examination of this region and studies aimed at deciphering the mechanism(s) are warranted.\n\nSchmidt, Helena\n\nSchmidt, Reinhold\n\n\n"
        }
    ]
}