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Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals.

ABSTRACT: 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 (n_DM = 178,691, n_noDM = 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.

SUBMITTER: Winkler TW

PROVIDER: S-EPMC9192715 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals.

Winkler Thomas W TW Rasheed Humaira H Teumer Alexander A Gorski Mathias M Rowan Bryce X BX Stanzick Kira J KJ Thomas Laurent F LF Tin Adrienne A Hoppmann Anselm A Chu Audrey Y AY Tayo Bamidele B Thio Chris H L CHL Cusi Daniele D Chai Jin-Fang JF Sieber Karsten B KB Horn Katrin K Li Man M Scholz Markus M Cocca Massimiliano M Wuttke Matthias M van der Most Peter J PJ Yang Qiong Q Ghasemi Sahar S Nutile Teresa T Li Yong Y Pontali Giulia G Günther Felix F Dehghan Abbas A Correa Adolfo A Parsa Afshin A Feresin Agnese A de Vries Aiko P J APJ Zonderman Alan B AB Smith Albert V AV Oldehinkel Albertine J AJ De Grandi Alessandro A Rosenkranz Alexander R AR Franke Andre A Teren Andrej A Metspalu Andres A Hicks Andrew A AA Morris Andrew P AP Tönjes Anke A Morgan Anna A Podgornaia Anna I AI Peters Annette A Körner Antje A Mahajan Anubha A Campbell Archie A Freedman Barry I BI Spedicati Beatrice B Ponte Belen B Schöttker Ben B Brumpton Ben B Banas Bernhard B Krämer Bernhard K BK Jung Bettina B Åsvold Bjørn Olav BO Smith Blair H BH Ning Boting B Penninx Brenda W J H BWJH Vanderwerff Brett R BR Psaty Bruce M BM Kammerer Candace M CM Langefeld Carl D CD Hayward Caroline C Spracklen Cassandra N CN Robinson-Cohen Cassianne C Hartman Catharina A CA Lindgren Cecilia M CM Wang Chaolong C Sabanayagam Charumathi C Heng Chew-Kiat CK Lanzani Chiara C Khor Chiea-Chuen CC Cheng Ching-Yu CY Fuchsberger Christian C Gieger Christian C Shaffer Christian M CM Schulz Christina-Alexandra CA Willer Cristen J CJ Chasman Daniel I DI Gudbjartsson Daniel F DF Ruggiero Daniela D Toniolo Daniela D Czamara Darina D Porteous David J DJ Waterworth Dawn M DM Mascalzoni Deborah D Mook-Kanamori Dennis O DO Reilly Dermot F DF Daw E Warwick EW Hofer Edith E Boerwinkle Eric E Salvi Erika E Bottinger Erwin P EP Tai E-Shyong ES Catamo Eulalia E Rizzi Federica F Guo Feng F Rivadeneira Fernando F Guilianini Franco F Sveinbjornsson Gardar G Ehret Georg G Waeber Gerard G Biino Ginevra G Girotto Giorgia G Pistis Giorgio G Nadkarni Girish N GN Delgado Graciela E GE Montgomery Grant W GW Snieder Harold H Campbell Harry H White Harvey D HD Gao He H Stringham Heather M HM Schmidt Helena H Li Hengtong H Brenner Hermann H Holm Hilma H Kirsten Holgen H Kramer Holly H Rudan Igor I Nolte Ilja M IM Tzoulaki Ioanna I Olafsson Isleifur I Martins Jade J Cook James P JP Wilson James F JF Halbritter Jan J Felix Janine F JF Divers Jasmin J Kooner Jaspal S JS Lee Jeannette Jen-Mai JJ O'Connell Jeffrey J Rotter Jerome I JI Liu Jianjun J Xu Jie J Thiery Joachim J Ärnlöv Johan J Kuusisto Johanna J Jakobsdottir Johanna J Tremblay Johanne J Chambers John C JC Whitfield John B JB Gaziano John M JM Marten Jonathan J Coresh Josef J Jonas Jost B JB Mychaleckyj Josyf C JC Christensen Kaare K Eckardt Kai-Uwe KU Mohlke Karen L KL Endlich Karlhans K Dittrich Katalin K Ryan Kathleen A KA Rice Kenneth M KM Taylor Kent D KD Ho Kevin K Nikus Kjell K Matsuda Koichi K Strauch Konstantin K Miliku Kozeta K Hveem Kristian K Lind Lars L Wallentin Lars L Yerges-Armstrong Laura M LM Raffield Laura M LM Phillips Lawrence S LS Launer Lenore J LJ Lyytikäinen Leo-Pekka LP Lange Leslie A LA Citterio Lorena L Klaric Lucija L Ikram M Arfan MA Ising Marcus M Kleber Marcus E ME Francescatto Margherita M Concas Maria Pina MP Ciullo Marina M Piratsu Mario M Orho-Melander Marju M Laakso Markku M Loeffler Markus M Perola Markus M de Borst Martin H MH Gögele Martin M Bianca Martina La M Lukas Mary Ann MA Feitosa Mary F MF Biggs Mary L ML Wojczynski Mary K MK Kavousi Maryam M Kanai Masahiro M Akiyama Masato M Yasuda Masayuki M Nauck Matthias M Waldenberger Melanie M Chee Miao-Li ML Chee Miao-Ling ML Boehnke Michael M Preuss Michael H MH Stumvoll Michael M Province Michael A MA Evans Michele K MK O'Donoghue Michelle L ML Kubo Michiaki M Kähönen Mika M Kastarinen Mika M Nalls Mike A MA Kuokkanen Mikko M Ghanbari Mohsen M Bochud Murielle M Josyula Navya Shilpa NS Martin Nicholas G NG Tan Nicholas Y Q NYQ Palmer Nicholette D ND Pirastu Nicola N Schupf Nicole N Verweij Niek N Hutri-Kähönen Nina N Mononen Nina N Bansal Nisha N Devuyst Olivier O Melander Olle O Raitakari Olli T OT Polasek Ozren O Manunta Paolo P Gasparini Paolo P Mishra Pashupati P PP Sulem Patrick P Magnusson Patrik K E PKE Elliott Paul P Ridker Paul M PM Hamet Pavel P Svensson Per O PO Joshi Peter K PK Kovacs Peter P Pramstaller Peter P PP Rossing Peter P Vollenweider Peter P van der Harst Pim P Dorajoo Rajkumar R Sim Ralene Z H RZH Burkhardt Ralph R Tao Ran R Noordam Raymond R Mägi Reedik R Schmidt Reinhold R de Mutsert Renée R Rueedi Rico R van Dam Rob M RM Carroll Robert J RJ Gansevoort Ron T RT Loos Ruth J F RJF Felicita Sala Cinzia SC Sedaghat Sanaz S Padmanabhan Sandosh S Freitag-Wolf Sandra S Pendergrass Sarah A SA Graham Sarah E SE Gordon Scott D SD Hwang Shih-Jen SJ Kerr Shona M SM Vaccargiu Simona S Patil Snehal B SB Hallan Stein S Bakker Stephan J L SJL Lim Su-Chi SC Lucae Susanne S Vogelezang Suzanne S Bergmann Sven S Corre Tanguy T Ahluwalia Tarunveer S TS Lehtimäki Terho T Boutin Thibaud S TS Meitinger Thomas T Wong Tien-Yin TY Bergler Tobias T Rabelink Ton J TJ Esko Tõnu T Haller Toomas T Thorsteinsdottir Unnur U Völker Uwe U Foo Valencia Hui Xian VHX Salomaa Veikko V Vitart Veronique V Giedraitis Vilmantas V Gudnason Vilmundur V Jaddoe Vincent W V VWV Huang Wei W Zhang Weihua W Wei Wen Bin WB Kiess Wieland W März Winfried W Koenig Wolfgang W Lieb Wolfgang W Gao Xin X Sim Xueling X Wang Ya Xing YX Friedlander Yechiel Y Tham Yih-Chung YC Kamatani Yoichiro Y Okada Yukinori Y Milaneschi Yuri Y Yu Zhi Z Stark Klaus J KJ Stefansson Kari K Böger Carsten A CA Hung Adriana M AM Kronenberg Florian F Köttgen Anna A Pattaro Cristian C Heid Iris M IM

Communications biology 20220613 1

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 (n<sub>DM</sub> = 178,691, n<sub>noDM</sub> = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional nov ...[more]

PMID: 35697829

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Project description:BackgroundClinical studies have indicated a comorbidity between sepsis and kidney diseases. Individuals with specific mutations that predispose them to kidney conditions are also at an elevated risk for developing sepsis, and vice versa. This suggests a potential shared genetic etiology that has not been fully elucidated.MethodsSummary statistics data on exposure and outcomes were obtained from genome-wide association meta-analysis studies. We utilized these data to assess genetic correlations, employing a pleiotropy analysis method under the composite null hypothesis to identify pleiotropic loci. After mapping the loci to their corresponding genes, we conducted pathway analysis using Generalized Gene-Set Analysis of GWAS Data (MAGMA). Additionally, we utilized MAGMA gene-test and eQTL information (whole blood tissue) for further determination of gene involvement. Further investigation involved stratified LD score regression, using diverse immune cell data, to study the enrichment of SNP heritability in kidney-related diseases and sepsis. Furthermore, we employed Mendelian Randomization (MR) analysis to investigate the causality between kidney diseases and sepsis.ResultsIn our genetic correlation analysis, we identified significant correlations among BUN, creatinine, UACR, serum urate, kidney stones, and sepsis. The PLACO analysis method identified 24 pleiotropic loci, pinpointing a total of 28 nearby genes. MAGMA gene-set enrichment analysis revealed a total of 50 pathways, and tissue-specific analysis indicated significant enrichment of five pairs of pleiotropic results in kidney tissue. MAGMA gene test and eQTL information (whole blood tissue) identified 33 and 76 pleiotropic genes, respectively. Notably, genes PPP2R3A for BUN, VAMP8 for UACR, DOCK7 for creatinine, and HIBADH for kidney stones were identified as shared risk genes by all three methods. In a series of immune cell-type-specific enrichment analyses of pleiotropy, we identified a total of 37 immune cells. However, MR analysis did not reveal any causal relationships among them.ConclusionsThis study lays the groundwork for shared etiological factors between kidney and sepsis. The confirmed pleiotropic loci, shared pathogenic genes, and enriched pathways and immune cells have enhanced our understanding of the multifaceted relationships among these diseases. This provides insights for early disease intervention and effective treatment, paving the way for further research in this field.

Project description:Background Gut microbiota has been reported to play an important role in diabetic kidney disease (DKD), however, the alterations of gut bacteria have not been determined. Methods Studies comparing the differences of gut microbiome between patients with DKD and non-DKD individuals using high-throughput sequencing technology, were systematically searched and reviewed. Outcomes were set as gut bacterial diversity, microbial composition, and correlation with clinical parameters of DKD. Qualitative data were summarized and compared through a funnel R script, and quantitative data were estimated by meta-analysis. Results A total of 15 studies and 1640 participants were included, the comparisons were conducted between DKD, diabetes mellitus (DM), non-diabetic kidney disease (NDKD), and healthy controls. There were no significant differences of α-diversity between DKD and DM, and between DKD and NDKD, however, significant lower microbial richness was found in DKD compared to healthy controls. Different bacterial compositions were found between DKD and non-DKD subjects. The phylum Actinobacteria were found to be enriched in DKD compared to healthy controls. At the genus level, we found the enrichment of Hungatella, Bilophila, and Escherichia in DKD compared to DM, patients with DKD showed lower abundances of Faecalibacterium compared to those with NDKD. The genera Butyricicoccus, Faecalibacterium, and Lachnospira were depleted in DKD compared to healthy controls, whereas Hungatella, Escherichia, and lactobacillus were significantly enriched. The genus Ruminococcus torques group was demonstrated to be inversely correlated with estimated glomerular filtration rate of DKD. Conclusions Gut bacterial alterations was demonstrated in DKD, characterized by the enrichment of the genera Hungatella and Escherichia, and the depletion of butyrate-producing bacteria, which might be associated with the occurrence and development of DKD. Further studies are still needed to validate these findings, due to substantial heterogeneity. Systematic review registration https://www.crd.york.ac.uk/prospero/, identifier CRD42022340870.

Project description:ObjectiveReported rates of hypoglycemia in patients with type 2 diabetes mellitus are lower with glimepiride as compared to glyburide. The aim of this study was to determine whether physiologic differences in counterregulatory neuroendocrine and metabolic mechanisms during hypoglycemia provide a basis for the observed clinical differences between glimepiride and glyburide.Research design and methodsNon-diabetic volunteers (age 38±2years, BMI 26±1kg/m(2)) were studied in a single-blind fashion during separate 2day randomized protocols consisting of 2h hyperinsulinemic (9pmol/kg/min) euglycemic (4.9±0.1mmol) and hypoglycemic (2.9±0.1mmol/L) clamps. Individuals received biologically equivalent doses of glimepiride (4mg) or glyburide (10mg) 1h prior to each glucose clamp (n=11) as well as a control group of placebo studies. Glucose kinetics were calculated using D-Glucose-6-6d2.ResultsInsulin and C-peptide levels were increased (p<0.05) during euglycemia in both sulfonylurea groups as compared to placebo. However, despite equivalent hypoglycemia, insulin and C-peptide levels were higher (p<0.05) only after glyburide. Glucagon responses and endogenous glucose production (EGP) were decreased (p<0.05) during hypoglycemia following glyburide administration as compared to glimepiride. Glyburide reduced (p<0.05) norepinephrine responses during euglycemic clamps. In addition combined epinephrine and norepinephrine responses during hypoglycemia were reduced (p<0.05) following glyburide as compared to placebo. Leptin levels fell by a greater amount (p<0.05) during hypoglycemia with both sulfonylureas as compared to placebo.ConclusionsIn summary, glimepiride and glyburide can both similarly increase insulin and C-peptide levels during hyperinsulinemic euglycemia. However, during moderate hyperinsulinemic hypoglycemia (2.9mmol/L) glyburide resulted in increased C-peptide and insulin, but blunted glucagon, sympathetic nervous system and EGP responses. We conclude that glyburide can acutely reduce key neuroendocrine and metabolic counterregulatory defenses during hypoglycemia in healthy individuals.

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Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals.

Publications

Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals.

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