Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals
Yang Q; Felix JF; O'Connell J; Sveinbjornsson G; Schulz CA; Lieb W; Guilianini F; Ghasemi S; Wilson JF; Preuss MH; Palmer ND; Willer CJ; Hartman CA; Kramer BK; Foo VHX; Bansal N; Hung AM; Thorsteinsdottir U; Parsa A; Yu Z; Pirastu N; Gordon SD; Verweij N; Porteous DJ; Rice KM; Stefansson K; Magnusson PKE; Kuusisto J; Hveem K; Chai JF; Stringham HM; Waeber G; Campbell A; Phillips LS; Tin A; Heng CK; Franke A; Spedicati B; Gunther F; Huang W; Christensen K; Mishra PP; Langefeld CD; Morris AP; Okada Y; Burkhardt R; Ning B; Ciullo M; Schottker B; Schmidt R; Tao R; Pontali G; Ehret G; Friedlander Y; Nikus K; Girotto G; Tayo B; Giedraitis V; Stanzick KJ; Jakobsdottir J; Holm H; Gao H; Oldehinkel AJ; Vanderwerff BR; Orho-Melander M; Mychaleckyj JC; Kronenberg F; Loos RJF; Wallentin L; Citterio L; Lucae S; Rasheed H; Wang CL; Vaccargiu S; Bottinger EP; Salomaa V; Kahonen M; Scholz M; Waldenberger M; Bochud M; Freitag-Wolf S; Morgan A; Milaneschi Y; Tham YC; Kooner JS; O'Donoghue ML; Haller T; Stark KJ; Kovacs P; Daw EW; Korner A; Kerr SM; Salvi E; Sedaghat S; Melander O; Miliku K; Zonderman AB; Svensson PO; Polasek O; Kammerer CM; Rabelink TJ; Rudan I; Marz W; Rivadeneira F; Kastarinen M; Teumer A; Kramer H; Gaziano JM; de Vries APJ; Tan NYQ; Lim SC; Kirsten H; Feresin A; Noordam R; Thio CHL; Rossing P; Spracklen CN; Cook JP; Montgomery GW; Brumpton B; Gasparini P; Magi R; Patil SB; Lanzani C; Raitakari OT; Hamet P; Metspalu A; Smith AV; Waterworth DM; Manunta P; Reilly DF; Jung B; Martins J; Rizzi F; Nolte IM; Rowan BX; Vogelezang S; Graham SE; Heid IM; Pramstaller PP; Jaddoe VWV; Penninx BWJH; Gorski M; Coresh J; Feitosa MF; Koenig W; Boehnke M; Kuokkanen M; Banas B; Marten J; Rotter JI; Ikram MA; Lehtimaki T; Lyytikainen LP; Strauch K; Boutin TS; Gudbjartsson DF; Campbell H; Sim RZH; Wang YX; Tremblay J; Podgornaia AI; Catamo E; Lee JJM; Vitart V; Nalls MA; Xu J; Pistis G; Volker U; Peters A; Shaffer CM; Arnlov J; Delgado GE; Ryan KA; Mook-Kanamori DO; Rueedi R; Correa A; Divers J; van der Most PJ; Cocca M; Tai ES; Bergmann S; Martin NG; Hallan S; Launer LJ; Josyula NS; Lukas MA; Mononen N; Horn K; van der Harst P; Stumvoll M; Perola M; Chambers JC; Carroll RJ; Francescatto M; Raffield LM; Hayward C; Chee ML; Khor CC; Ahluwalia TS; Gansevoort RT; Snieder H; Brenner H; Biggs ML; Halbritter J; Hwang SJ; Padmanabhan S; Tonjes A; Chu AY; Cheng CY; Pattaro C; Thomas LF; Klaric L; Endlich K; Nutile T; Meitinger T; Taylor KD; De Grandi A; Laakso M; White HD; Bakker SJL; Kottgen A; Eckardt KU; Yerges-Armstrong LM; Sieber KB; Wei WB; Schmidt H; La Bianca M; Kanai M; Yasuda M; Ising M; Dehghan A; Kavousi M; Hutri-Kahonen N; Lindgren CM; Loeffler M; Hoppmann A; Dittrich K; Wuttke M; Jonas JB; Gieger C; Rosenkranz AR; Matsuda K; Guo F; Winkler TW; Mascalzoni D; Mahajan A; Kamatani Y; Dorajoo R; Gao X; Boerwinkle E; Joshi PK; Sabanayagam C; Evans MK; Psaty BM; Cusi D; Hofer E; Ruggiero D; Li Y; Sim XL; Boger CA; Toniolo D; Freedman BI; Piratsu M; Smith BH; Concas MP; Nadkarni GN; Robinson-Cohen C; Hicks AA; Felicita SC; Mohlke KL; Elliott P; Bergler T; Kleber ME; Gudnason V; Biino G; Liu JJ; Fuchsberger C; Esko T; Zhang WH; Kubo M; Asvold BO; Schupf N; Vollenweider P; Thiery J; Wong TY; van Dam RM; Ponte B; Ghanbari M; Wojczynski MK; Li HT; Whitfield JB; Ridker PM; Tzoulaki I; Teren A; Nauck M; Li M; Ho K; Lind L; Kiess W; de Borst MH; Akiyama M; Gogele M; Olafsson I; Chasman DI; Corre T; Province MA; Sulem P; Czamara D; Lange LA; de Mutsert R; Pendergrass SA; Devuyst O
https://urn.fi/URN:NBN:fi-fe2022091258482
Tiivistelmä
A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease.Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM.
Kokoelmat
- Rinnakkaistallenteet [19206]